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https://openalex.org/W2163196794
https://figshare.com/articles/journal_contribution/Supplementary_Figure_1_from_Cetuximab-Activated_Natural_Killer_and_Dendritic_Cells_Collaborate_to_Trigger_Tumor_Antigen_Specific_T-cell_Immunity_in_Head_and_Neck_Cancer_Patients/22454904/1/files/39906024.pdf
unk
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Cetuximab-Activated Natural Killer and Dendritic Cells Collaborate to Trigger Tumor Antigen–Specific T-cell Immunity in Head and Neck Cancer Patients
Clinical cancer research
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31
Day 0 Day 14 Day 7 + + + + + + + + + + + + + - - + + + + - - - - - -
https://openalex.org/W2784295131
https://www.matec-conferences.org/10.1051/matecconf/201814502004/pdf
English
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Tensile behavior of humid aged advanced composites for helicopter external fuel tank development
MATEC web of conferences
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© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/). Tensile behavior of humid aged advanced composites for helicopter external fuel tank development Mihaela Condruz1*, Alexa...
https://openalex.org/W3172459663
https://wrap.warwick.ac.uk/157454/1/WRAP-grey-white-matter-volume-changes-preterm-birth-Wolke-2021.pdf
English
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Grey and white matter volume changes after preterm birth: A meta-analytic approach
medRxiv (Cold Spring Harbor Laboratory)
2,021
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9,016
  10 Department of Psychiatry, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany Citation: Schmitz-Koep, B.; Haller, B.; Coupé, P.; Menegaux, A.; Gaser, C.; Zimmer, C.; Wolke, D.; Bartmann, P.; Sorg, C.; Hedderich, D.M. Grey and White Matter Volume Changes af...
https://openalex.org/W4389524588
https://aclanthology.org/2023.findings-emnlp.816.pdf
English
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Dimensions of Online Conflict: Towards Modeling Agonism
null
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Abstract Not all conflicts are equal, and the confusion over the political and social value of conflict partly stems from its diverse nature. Conflict exists on a sliding scale ranging from antagonistic conflict be- tween enemies (which is often silencing, undemo- cratic, and hateful because it is focused on delegit- i...
https://openalex.org/W3111837814
http://umu.diva-portal.org/smash/get/diva2:1525853/FULLTEXT03
English
null
Argumentation-Based Health Information Systems: A Design Methodology
IEEE intelligent systems
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Argumentation-Based Health Information Systems: A Design Methodology Helena Lindgren, Timotheus Kampik , Esteban Guerrero Rosero , Madeleine Blusi , and Juan Carlos Nieve Umea  University, 90187 Umea , Sweden In this article, we present a design methodology for argumentation-based health information systems. With a f...
https://openalex.org/W2291357105
https://europepmc.org/articles/pmc4766945?pdf=render
English
null
ERICA: prevalence of healthy eating habits among Brazilian adolescents
Revista de saúde pública/Revista de Saúde Pública
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Correspondence: Laura Augusta Barufaldi Edifício Premium Térreo, sala 15 SAF Sul, Trecho 02 Lotes 05/06 Bloco “F” Torre 1 70070-600 Brasília, DF, Brasil E-mail: laurabarufaldi@yahoo.com.br http://www.rsp.fsp.usp.br/ Supplement ERICA Original Article Supplement ERICA Original Article Rev Saúde Pública 2016;50...
https://openalex.org/W2410783462
https://europepmc.org/articles/pmc4926619?pdf=render
English
null
Barcoding Chrysomelidae: a resource for taxonomy and biodiversity conservation in the Mediterranean Region
ZooKeys
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5,202
http://zoobank.org/4D7CCA18-26C4-47B0-9239-42C5F75E5F42 Citation: Magoga G, Sassi D, Daccordi M, Leonardi C, Mirzaei M, Regalin R, Lozzia G, Montagna M (2016) Barcoding Chrysomelidae: a resource for taxonomy and biodiversity conservation in the Mediterranean Region. In: Jolivet P, Santiago-Blay J, Schmitt M (Eds) Rese...
https://openalex.org/W2087711953
https://europepmc.org/articles/pmc3621509?pdf=render
English
null
Cultural background modulates how we look at other persons’ gaze
International journal of behavioral development
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Introduction can we study the effect of postnatal environment on the develop- ment of face gaze in humans? One of the most promising ways is a cross-cultural comparison, because different cultural norms would systematically modulate how the people in each culture would learn to process and interact with others in face-...
https://openalex.org/W3162709001
https://www.frontiersin.org/articles/10.3389/fpsyg.2021.652673/pdf
English
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Perception of Nigerian Dùndún Talking Drum Performances as Speech-Like vs. Music-Like: The Role of Familiarity and Acoustic Cues
Frontiers in psychology
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ORIGINAL RESEARCH published: 20 May 2021 doi: 10.3389/fpsyg.2021.652673 ORIGINAL RESEARCH published: 20 May 2021 doi: 10.3389/fpsyg.2021.652673 ORIGINAL RESEARCH published: 20 May 2021 doi: 10.3389/fpsyg.2021.652673 Perception of Nigerian Dùndún Talking Drum Performances as Speech-Like vs. Music-Like: The Role of Famil...
https://openalex.org/W2966115183
https://www.biorxiv.org/content/biorxiv/early/2019/04/11/606590.full.pdf
English
null
Knockout of Babesia bovis rad51 ortholog and its complementation by expression from the BbACc3 artificial chromosome platform
PloS one
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. CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted April 11, 2019. ; https://doi.org/10.1101/606590 doi: bioR...
https://openalex.org/W2125691952
https://pure.mpg.de/pubman/item/item_2151777_8/component/file_2152104/2151777.pdf
English
null
Directional properties of polar paramagnetic molecules subject to congruent electric, magnetic and optical fields
New journal of physics
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This content has been downloaded from IOPscience. Please scroll down to see the full text. Download details: IP Address: 141.14.132.32 This content was downloaded on 11/05/2015 at 08:13 Please note that terms and conditions apply. Directional properties of polar paramagnetic molecules subject to congruent electric and ...
https://openalex.org/W2803448435
http://old.scielo.br/pdf/urbe/v10n3/2175-3369-urbe-2175-3369010003AO01.pdf
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Financeirização da moradia e segregação socioespacial: Minha Casa, Minha Vida em São José dos Campos, Taubaté e Jacareí/SP
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Financeirização da moradia e segregação socioespacial: Minha Casa, Minha Vida em São José dos Campos, Taubaté e Jacareí/SP Housing financing and socio-spatial segregation: “Minha Casa Minha Vida” in São José dos Campos, Taubaté and Jacareí/SP Daniela das Neves Alvarenga[a], Paulo Romano Reschilian[a] [a] Universidad...
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https://europepmc.org/articles/pmc6599201?pdf=render
English
null
Building a DNA barcode library for the freshwater fishes of Bangladesh
Scientific reports
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Md. Mizanur Rahman1, Michael Norén2, Abdur Rob Mollah1 & Sven O. Kullander We sequenced the standard DNA barcode gene fragment in 694 newly collected specimens, representing 243 species level Operational Barcode Units (OBUs) of freshwater fishes from Bangladesh. We produced coi sequences for 149 out of the 237 species...
https://openalex.org/W2286515682
http://tao.cgu.org.tw/index.php/articles/archive/geophysics/item/download/2794_1814b6237bd201af30408480c4fa872b
English
null
Traveltime Analysis of VSP Seismograms in a Horizontal Transversely Isotropic Medium: A Physical Modeling Result
Terrestrial, atmospheric and oceanic sciences/Terrestrial, atmospheric, and oceanic sciences
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TAO, Vol. 12, No. 4, 685-693, December 2001 TAO, Vol. 12, No. 4, 685-693, December 2001 1 Institute of Applied Geophysics, Institute of Seismology, National Chung Cheng University, Min-hsiung Chia-yi, Taiwan, ROG 2Department of Applied Physics, National Chiayi University, Min-hsiung, Chia-yi, Taiwan, ROG *Correspondi...
https://openalex.org/W2070752776
https://www.biodiversitylibrary.org/partpdf/72470
English
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On the Existence of Rudimentary Antlers in the Okapi
Proceedings of the Zoological Society of London
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public-domain
3,134
* For explanation of the Plates, see p. 134. 26 PROF E RAY LA 26 PROF E RAY LA eb. 5, 126 RAY LANKESTER ON 3. On the Hxistence of Rudimentary Antlers in the Okapi. By E. Ray Lanxester, M.A., D.Sc., LL.D., F.B.S., F.Z.8., Director of the British Museum (Natural His- tory). | | (Plates VI. & VII...
W282090071.txt
http://www.bioinformation.net/010/97320630010555.pdf
en
Erratum in Jayapalan & Natarajan, The role of CDK5 and GSK3B kinases in hyperphosphorylation of microtubule associated protein tau (MAPT) in Alzheimer’s disease
Bioinformation
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120
open access www.bioinformation.net Erratum Volume 10(8) Erratum: A numerical error in methodology section under Sequence retrieval and modeling side heading Bioinformation - 2013 Dec 9(20): 1023-1030 The role of CDK5 and GSK3B kinases in hyperphosphorylation of microtubule associated protein tau (MAPT) in Alzheimer...
W2798665765.txt
https://link.springer.com/content/pdf/10.1007/JHEP11(2018)094.pdf
en
Unitarity of the box diagram
˜The œJournal of high energy physics/˜The œjournal of high energy physics
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Published for SISSA by Springer Received: September 26, 2018 Accepted: November 8, 2018 Published: November 14, 2018 Roji Piusa and Ashoke Senb a Perimeter Institute for Theoretical Physics, Waterloo, ON N2L 2Y5, Canada b Harish-Chandra Research Institute, HBNI, Chhatnag Road, Jhusi, Allahabad 211019, India E-mail...
https://openalex.org/W2962950012
https://link.springer.com/content/pdf/10.1007%2FJHEP03%282018%29079.pdf
English
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Chiral algebras in Landau-Ginzburg models
˜The œJournal of high energy physics/˜The œjournal of high energy physics
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Published for SISSA by Springer Published for SISSA by Springer Published for SISSA by Springer Received: January 22, 2018 Accepted: March 2, 2018 Published: March 13, 2018 Received: January 22, 2018 Accepted: March 2, 2018 Published: March 13, 2018 Received: January 22, 2018 Accepted: March 2, 2018 Published: March 13...
https://openalex.org/W2083606760
https://researchonline.lshtm.ac.uk/id/eprint/7839/1/1475-2875-7-6.pdf
English
null
Feasibility and acceptability of artemisinin-based combination therapy for the home management of malaria in four African sites
Malaria journal
2,008
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7,396
Received: 22 October 2007 Accepted: 8 January 2008 Received: 22 October 2007 Accepted: 8 January 2008 Published: 8 January 2008 Malaria Journal 2008, 7:6 doi:10.1186/1475-2875-7-6 Malaria Journal 2008, 7:6 doi:10.1186/1475-2875-7-6 This article is available from: http://www.malariajournal.com/content/7/1/6 © 2008 Ajayi...
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https://bmcpublichealth.biomedcentral.com/counter/pdf/10.1186/s12889-015-1670-0
English
null
Malaria policies versus practices, a reality check from Kinshasa, the capital of the Democratic Republic of Congo
BMC public health
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* Correspondence: mavoko@yahoo.com 1Département de Médecine Tropicale, Université de Kinshasa, B.P. 747, Kin XI, Kinshasa, République Démocratique du Congo 2International Health Unit, Department of Epidemiology, University of Antwerp, Campus Drie Eiken, Universiteitsplein 1, 2610 Kinshasa, République Démocratique du Co...
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https://repository.ubn.ru.nl/bitstream/handle/2066/227649/1/227649.pdf
English
null
Key role for lipids in cognitive symptoms of schizophrenia
Translational psychiatry
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2020, Article / Letter to editor (Translational Psychiatry, 10, 1, (2020), pp. 1-12, article 399) Doi link to publisher: https://doi.org/10.1038/s41398-020-01084-x Version of the following full text: Publisher’s version Downloaded from: https://hdl.handle.net/2066/227649 Download date: 2024-10-24 Version of the followi...
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https://www.investigacionesgeograficas.com/article/view/18723/pdf, https://rua.ua.es/dspace/bitstream/10045/119750/6/Investigaciones_Geograficas_77_12.pdf
es
Susceptibilidad de afección por enjambres de medusas (Pelagia noctiluca) en las playas del litoral occidental de la provincia de Málaga
Investigaciones geográficas/Investigaciones geográficas
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Investigaciones Geográficas Instituto Interuniversitario de Geografía Universidad de Alicante Nº 77, enero-junio de 2022, pp. 239-258. ISSN: 0213 - 4691. eISSN: 1989 - 9890. DOI: 10.14198/INGEO.18723 Cita bibliográfica: de la Fuente Roselló, A., Sortino Barrionuevo, J.F., Reyes Corredera, S. J., & Perles Roselló, M.J...
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The use of scenarios in climate policy planning: an assessment of actors’ experiences and lessons learned in Finland
Climate policy
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Climate Policy ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/tcpo20 Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=tcpo20 Kalle Aro, Jyrki Aakkula, Ville Lauttamäki, Vilja Varho, Pim Martens & Pasi Rikkonen To cite t...
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https://www.nature.com/articles/srep46576.pdf
English
null
Neurodevelopmental Changes in Excitatory Synaptic Structure and Function in the Cerebral Cortex of Sanfilippo Syndrome IIIA Mice
Scientific reports
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10,255
Neurodevelopmental Changes in Excitatory Synaptic Structure and Function in the Cerebral Cortex of Sanfilippo Syndrome IIIA Mice Chrissa A. Dwyer1, Samantha L. Scudder2, Ying Lin1, Lara E. Dozier2, Dustin Phan1, Nicola J Allen3 Gentry N Patrick2 & Jeffrey D Esko1 received: 06 December 2016 accepted: 17 March 2017 P...
https://openalex.org/W2749666098
https://link.springer.com/content/pdf/10.1007%2Fs11406-017-9866-4.pdf
English
null
Analytic Pragmatism and Universal LX Vocabulary
Philosophia
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1 Department of Philosophy, The Ohio State University, Columbus, OH, USA 2 Department of Philosophy; Arché Philosophical Research Centre; Centre for Exoplanet Science, University of Saint Andrews, St Andrews, Fife, UK Philosophia (2017) 45:1803–1827 DOI 10.1007/s11406-017-9866-4 Analytic Pragmatism and Universal LX Voc...
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https://europepmc.org/articles/pmc3929584?pdf=render
English
null
The Novel Long Noncoding RNA linc00467 Promotes Cell Survival but Is Down-Regulated by N-Myc
PloS one
2,014
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8,950
Abstract Competing Interests: The authors have declared that no competing interests exist. Funding: The authors were supported by National Health and Medical Research Council Australia and Cancer Council New South Wa recipient of an ARC Future Fellowship. The funders had no role in study design, data collection and ana...
https://openalex.org/W2182324063
https://www.ssoar.info/ssoar/bitstream/document/57327/1/ssoar-ilshs-2015-50-abedi_et_al-The_effect_of_emotional_intelligence.pdf
English
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The Effect of Emotional Intelligence Group Training on Human and Social Capital in Isfahan University of Technology
International letters of social and humanistic sciences
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www.ssoar.info www.ssoar.info The effect of emotional intelligence group training on human and social capital in Isfahan University of technology Abedi, Mohammad Reza; Nilforoushan, Parisa; Charsoughi, Batoul Tadayon Veröffentlichungsversion / Published Version Zeitschriftenartikel / journal article Empfohlene Zitierun...
https://openalex.org/W2904861441
https://europepmc.org/articles/pmc6496756?pdf=render
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Zerumbone, a cyclic sesquiterpene, exerts antimitotic activity in HeLa cells through tubulin binding and exhibits synergistic activity with vinblastine and paclitaxel
Cell proliferation
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O R I G I N A L A R T I C L E O R I G I N A L A R T I C L E Funding information g This work is partly supported by the grant from the DST/SERB, Government of India (SR/SO/BB‐0013/2010), to Dr Rathinasamy K and partly by TEQIP‐II, NIT Calicut, for the Student Project to SMA (Ref. NITC/TEQIP‐ II/R&D/2014). Results:...
https://openalex.org/W2578351455
https://hrcak.srce.hr/file/254552
Latin
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Wood Waste Turned Into Value Added Products: Thermal Plasticization by Benzylation Process
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ner, Köse, Yürümez, Ümit Yalçın, Akgül: Wood Waste Turned Into Value Added Products ner, Köse, Yürümez, Ümit Yalçın, Akgül: Wood Waste Turned Into Value Added Products Birol Üner1, Gökhan Köse1, Yeşim Yürümez1, Ömer Ümit Yalçın2, Mehmet Akgül3 1 Autori su izvanredni profesor, dodiplomski student i doktorand Sveučilišta...
https://openalex.org/W2891902755
https://revistas.pucsp.br/index.php/ReCaPe/article/download/37285/26434
Portuguese
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Gamificação e gestão de pessoas: um estudo de caso sobre treinamento e ambiente de diversidade cultural
Revista de Carreiras e Pessoas
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cc-by
6,494
RESUMO Este artigo tem como objetivo discutir a aplicação de gamificação na gestão de pessoas, mais especificamente no treinamento e desenvolvimento de competências de colaboradores de diferentes níveis culturais dentro de uma grande organização. Para tal estudo, iremos trabalhar, principalmente, com as teorias de ...
https://openalex.org/W4312735321
https://www.scielo.br/j/pp/a/PLSPZxNytNQvQkZsL3Dywmx/?lang=en&format=pdf
English
null
Theorizations about the child's Play and Movent: implications for the pedagogical practice of Physical Education in Early Childhood Education and other problematizations
Pro-Posições
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cc-by
10,098
2 References correction and bibliographic normalization services: Vera Lúcia Fator Gouvêa Bonilha - verah.bonilha@gmail.com 3 English version: Viviane Ramos - vivianeramos@gmail.com 1 Responsible editor: Carmen Lúcia Soares - https://orcid.org/0000-0002-4347-1924 (ii) Universidade Federal do Espírito Santo – UFES, Ce...
https://openalex.org/W2486036269
https://europepmc.org/articles/pmc4974648?pdf=render
English
null
Small angle x-ray scattering with edge-illumination
Scientific reports
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6,787
Small angle x-ray scattering with edge-illumination Peter Modregger1, Tiziana P. Cremona2, Charaf Benarafa3, Johannes C. Schittny2, Alessandro Olivo1 & Marco Endrizzi1 received: 14 April 2016 accepted: 11 July 2016 Published: 05 August 2016 Sensitivity to sub-pixel sample features has been demonstrated as a valuable ...
https://openalex.org/W4322501456
https://arthritis-research.biomedcentral.com/counter/pdf/10.1186/s13075-023-03001-1
English
null
TGF-β is elevated in hyperuricemic individuals and mediates urate-induced hyperinflammatory phenotype in human mononuclear cells
Arthritis research & therapy
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8,572
Arthritis Research & Therapy Arthritis Research & Therapy Klück et al. Arthritis Research & Therapy (2023) 25:30 https://doi.org/10.1186/s13075-023-03001-1 Open Access Abstract Background  Soluble urate leads to a pro-inflammatory phenotype in human monocytes characterized by increased production of IL-1β ...
https://openalex.org/W2124593363
https://europepmc.org/articles/pmc4999641?pdf=render
English
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Extensive Mucocutaneous Verruca Vulgaris in a Nonimmunocompromised Patient
Jaypee's international journal of clinical pediatric dentistry
2,011
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1,736
IJCPD CASE REPORT  10.5005/jp-journals-10005-1084 Extensive Mucocutaneous Verruca Vulgaris in a Nonimmunocompromised Patient 1Vela D Desai, 2Rajeev Sharma, 3Durgesh N Bailoor 1Vela D Desai, 2Rajeev Sharma, 3Durgesh N Bailoor 1Professor and Head, Department of Oral Medicine and Radiology, Jaipur Dental College, Jaipur...
https://openalex.org/W2980238500
https://repositum.tuwien.at/bitstream/20.500.12708/20132/1/Schultis-2019-Energies-vor.pdf
English
null
Behaviour of Distribution Grids with the Highest PV Share Using the Volt/Var Control Chain Strategy
Energies
2,019
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18,772
Received: 30 August 2019; Accepted: 10 October 2019; Published: 12 October 2019 Received: 30 August 2019; Accepted: 10 October 2019; Published: 12 October 2019 Abstract: The large-scale integration of rooftop PVs stalls due to the voltage limit violations they provoke, the uncontrolled reactive power flow in the superor...
https://openalex.org/W2145363311
https://digital.library.adelaide.edu.au/dspace/bitstream/2440/59375/1/hdl_59375.pdf
English
null
Reference genes for normalising gene expression data in collagenase-induced rat intracerebral haemorrhage
BMC molecular biology
2,010
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8,721
PUBLISHED VERSION Cook, Naomi Louise; Kleinig, Timothy John; Van Den Heuvel, Corinna; Vink, Robert Reference genes for normalising gene expression data in collagenase-induced rat intracerebral haemorrhage BMC Molecular Biology, 2010; 11:7 Cook, Naomi Louise; Kleinig, Timothy John; Van Den Heuvel, Corinna; Vink, Ro...
https://openalex.org/W2919913683
https://discovery.ucl.ac.uk/10068358/1/s40425-019-0508-1.pdf
English
null
Avelumab (anti–PD-L1) as first-line switch-maintenance or second-line therapy in patients with advanced gastric or gastroesophageal junction cancer: phase 1b results from the JAVELIN Solid Tumor trial
Journal for immunotherapy of cancer
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RESEARCH ARTICLE Open Access Chung et al. Journal for ImmunoTherapy of Cancer (2019) 7:30 https://doi.org/10.1186/s40425-019-0508-1 Chung et al. Journal for ImmunoTherapy of Cancer (2019) 7:30 https://doi.org/10.1186/s40425-019-0508-1 (2019) 7:30 Chung et al. Journal for ImmunoTherapy of Cancer ...
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https://www.frontiersin.org/articles/10.3389/fendo.2018.00753/pdf
English
null
Metformin-Induced Mitochondrial Complex I Inhibition: Facts, Uncertainties, and Consequences
Frontiers in endocrinology
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8,055
Metformin-Induced Mitochondrial Complex I Inhibition: Facts, Uncertainties, and Consequences INSERM, LBFA, Université Grenoble Alpes, Grenoble, France Metformin is the most widely prescribed drug to treat patients with type II diabetes, for whom retrospective studies suggest that metformin may have anticancer propertie...
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https://www.biorxiv.org/content/biorxiv/early/2019/07/20/708719.full.pdf
English
null
Plasma-derived HIV Nef+ exosomes persist in ACTG384 study participants despite successful virological suppression
bioRxiv (Cold Spring Harbor Laboratory)
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. CC-BY 4.0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted July 20, 2019. ; https://doi.org/10.1101/708719 doi: bioRx...
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https://www.cdc.gov/pcd/issues/2015/pdf/15_0290.pdf
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null
Consumption of Alcoholic Beverages and Liquor Consumption by Michigan High School Students, 2011
Preventing chronic disease
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public-domain
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Katherine R. Gonzales, MPH; Thomas W. Largo, MPH; Corinne Miller, PhD, DDS; Dafna Kanny, PhD; Robert D. Brewer, MD, MSPH Katherine R. Gonzales, MPH; Thomas W. Largo, MPH; Corinne Miller, PhD, DDS; Dafna Kanny, PhD; Robert D. Brewer, MD, MSPH Katherine R. Gonzales, MPH; Thomas W. Largo, MPH; Corinne Miller, PhD, DDS; Da...
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https://bmcpublichealth.biomedcentral.com/counter/pdf/10.1186/s12889-020-09558-9
English
null
Propensity for COVID-19 severe epidemic among the populations of the neighborhoods of Fortaleza, Brazil, in 2020
BMC public health
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cc-by
5,729
Open Access Propensity for COVID-19 severe epidemic among the populations of the neighborhoods of Fortaleza, Brazil, in 2020 Jose Ueleres Braga1,2* , Alberto Novaes Ramos Jr3,4, Anderson Fuentes Ferreira4, Victor Macêdo Lacerda5, Renan Monteiro Carioca Freire5 and Bruno Vieira Bertoncini6,7 Abstract Background: The sta...
https://openalex.org/W2904013152
https://jhiphalexu.journals.ekb.eg/article_19913_8e65a695adb6e8ffcd23e74a55fd75ad.pdf
English
null
Evaluation of Leading Safety Performance of Primary School Buildings in Alexandria, Egypt: Cross-Sectional Study
Journal of High Institute of Public Health
2,018
cc-by-sa
5,869
Evaluation of Leading Safety Performance of Primary School Buildings in Alexandria, Egypt: Cross- Sectional Study Gehan R. Zaki1 ¥, Kholoud Y. Tayel2, Mayada M. Reda3, 4, Aleya H. Mahmoud3, Engy I. Labib 1 Department of Occupational Health and Air Pollution, High Institute of Public Health, Alexandria University, Egy...
https://openalex.org/W4320073862
https://www.gp-mgimo.ru/jour/article/download/7/7
English
null
Russia’s Sovereignty and Emergence of Pragmatic Polycentrism
Upravlenie i politika
2,022
cc-by
16,687
2022, Vol. 1, No. 1 Received: February 15, 2022 / Accepted: March 10, 2022 Political Science / Country in Focus 2022, Vol. 1, No. 1 Received: February 15, 2022 / Accepted: March 10, 2022 Political Science / Country in Focus 2022, Vol. 1, No. 1 Received: February 15, 2022 / Accepted: March 10, 2022 Political Science / C...
https://openalex.org/W2810630497
https://cyberleninka.ru/article/n/microbiological-oropharyngeal-patterns-in-patients-with-different-phenotypes-of-chronic-obstructive-pulmonary-disease/pdf
English
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Microbiological Oropharyngeal Patterns in Patients with Different Phenotypes of Chronic Obstructive Pulmonary Disease
Sovremennye tehnologii v medicine
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cc-by
5,726
Microbiological Oropharyngeal Patterns in Patients with Different Phenotypes of Chronic Obstructive Pulmonary Disease DOI: 10.17691/stm2018.10.2.11 Received April 27, 2017 DOI: 10.17691/stm2018.10.2.11 Received April 27, 2017 M.A. Karnaushkina, MD, PhD, Associate Professor, Department of Hospital Therapy No.21; M...
https://openalex.org/W3003401706
https://europepmc.org/articles/pmc7072309?pdf=render
English
null
How Quickly Do Proteins Fold and Unfold, and What Structural Parameters Correlate with These Values?
Biomolecules
2,020
cc-by
12,319
Received: 27 December 2019; Accepted: 26 January 2020; Published: 29 January 2020 Abstract: The correlations between the logarithm of the unfolding rate of 108 proteins and their structural parameters were calculated. We showed that there is a good correlation between the logarithm of folding and unfolding rates (0.79)...
https://openalex.org/W2581537342
https://www.frontiersin.org/articles/10.3389/fnhum.2017.00390/pdf
English
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When null hypothesis significance testing is unsuitable for research: a reassessment
bioRxiv (Cold Spring Harbor Laboratory)
2,016
cc-by
21,862
Edited by: Satrajit S. Ghosh, Massachusetts Institute of Technology, United States Edited by: Satrajit S. Ghosh, Massachusetts Institute of Technology, United States Reviewed by: Bertrand Thirion, Institut National de Recherche en Informatique et en Automatique (INRIA), France Cyril R. Pernet, University of Edinburgh, ...
https://openalex.org/W2460871468
https://europepmc.org/articles/pmc4991230?pdf=render
English
null
Video observations of treatment administration to children on antiretroviral therapy in rural KwaZulu-Natal
AIDS care
2,016
cc-by
5,802
AIDS CARE, 2016 VOL. 28, NO. S2, 34–41 http://dx.doi.org/10.1080/09540121.2016.1176674 AIDS CARE, 2016 VOL. 28, NO. S2, 34–41 http://dx.doi.org/10.1080/09540121.2016.1176674 AIDS CARE, 2016 VOL. 28, NO. S2, 34–41 http://dx.doi.org/10.1080/09540121.2016.1176674 AIDS CARE, 2016 VOL. 28, NO. S2, 34–41 http://dx.doi.org/10...
https://openalex.org/W4280581650
https://orca.cardiff.ac.uk/id/eprint/152778/4/netn_a_00279.pdf
English
null
Increased structural connectivity in high schizotypy
bioRxiv (Cold Spring Harbor Laboratory)
2,022
cc-by
11,733
a n o p e n a c c e s s j o u r n a l Corresponding Author: Eirini Messaritaki messaritakie2@cardiff.ac.uk Handling Editor: Alex Fornito Copyright: © 2022 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license The MIT Press Keywords: Schizophrenia, Sch...
https://openalex.org/W4292748779
https://backend.orbit.dtu.dk/ws/files/289959238/JGR_Atmospheres_2022_Skeie_The_Temporal_Relationship_Between_Terrestrial_Gamma_Ray_Flashes_and_Associated_Optical.pdf
English
null
The Temporal Relationship Between Terrestrial Gamma‐Ray Flashes and Associated Optical Pulses From Lightning
Journal of geophysical research. Atmospheres
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cc-by
12,295
Citation (APA): Skeie, C. A., Østgaard, N., Mezentsev, A., Bjørge‐Engeland, I., Marisaldi, M., Lehtinen, N., Reglero, V., & Neubert, T. (2022). The temporal relationship between Terrestrial Gamma‐ray flashes and associated optical pulses from lightning. Journal of Geophysical Research: Atmospheres, 127(17), Article e20...
https://openalex.org/W2071568738
https://zenodo.org/records/2012261/files/article.pdf
Dutch
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Het phytopathologisch laboratorium willie commelin scholten van 1895 TOT 1906
Tijdschrift over planteziekten/Tijdschrift over plantenziekten
1,906
public-domain
9,652
28 -- 28 -- HET PHITOPATHOLOGISCH LABORATORIUIII WILLIE COiilHELIH SCHOLTEli VAH 1895 TOF 1906, Met ingang van Januari 1906 vrangde ik ontslag als Directeur van her phytopathologizch laboratorium Willie Commelin Schelten te Amsterdam, om op to fxeden als Directeur van een Instituut veer phytopat.hologie, 't wclk d...
https://openalex.org/W2585119302
https://cronfa.swan.ac.uk/Record/cronfa36103/Download/0036103-17102017100114.pdf
English
null
Bioremediation efficacy—comparison of nutrient removal from an anaerobic digest waste-based medium by an algal consortium before and after cryopreservation
Journal of applied phycology
2,017
cc-by
9,413
Cronfa - Swansea University Open Access Repository This is an author produced version of a paper published in: Journal of Applied Phycology Cronfa URL for this paper: http://cronfa.swan.ac.uk/Record/cronfa36103 p Silkina, A., Nelson, G., Bayliss, C., Pooley, C. & Day, J. (2017). Bioremediation efficacy—comparison of ...
https://openalex.org/W4361812727
https://figshare.com/articles/journal_contribution/Supplementary_Figure_from_Upfront_Biology-Guided_Therapy_in_Diffuse_Intrinsic_Pontine_Glioma_Therapeutic_Molecular_and_Biomarker_Outcomes_from_PNOC003/22486337/1/files/39937916.pdf
English
null
Supplementary Figure from Upfront Biology-Guided Therapy in Diffuse Intrinsic Pontine Glioma: Therapeutic, Molecular, and Biomarker Outcomes from PNOC003
null
2,023
cc-by
988
A p = 9.6e-1 0.00 0.25 0.50 0.75 1.00 0 10 20 30 40 50 Time Overall Survival CBTN (H3K27-altered DMG) PNOC003 (H3K27-altered DIPG) 22 11 4 1 1 1 28 19 4 0 0 0 PNOC003 CBTN 0 10 20 30 40 50 Time Number at risk PNOC003+CBTN A p = 9.6e-1 0.00 0.25 0.50 0.75 1.00 0 10 20 30 40 50 Time Overall Survival CBTN (H3K27-altered D...
W4367300121.txt
https://www.frontiersin.org/articles/10.3389/fimmu.2023.1161145/pdf?isPublishedV2=False
en
Inactivated ostreid herpesvirus-1 induces an innate immune response in the Pacific oyster, Crassostrea gigas, hemocytes
Frontiers in immunology
2,023
cc-by
7,713
Brief Research Report 28 April 2023 DOI 10.3389/fimmu.2023.1161145 TYPE PUBLISHED OPEN ACCESS EDITED BY Daniela Melillo, National Research Council (CNR), Italy REVIEWED BY Alejandro Romero, Spanish National Research Council (CSIC), Spain Junfa Yuan, Huazhong Agricultural University, China *CORRESPONDENCE Lizenn De...
https://openalex.org/W4393047257
https://ateroskleroz.elpub.ru/jour/article/download/1026/919
Russian
null
Assessment of the association of the rs12329760 polymorphism of the <i>TMPRSS2</i> gene with acute coronary syndrome in patients with new coronavirus infection
Ateroskleroz
2,024
cc-by
5,297
Оценка ассоциации полиморфизма rs12329760 гена TMPRSS2 с острым коронарным синдромом у пациентов, перенесших новую коронавирусную инфекцию В.А. Козик1, Л.А. Шпагина1, И.С. Шпагин1, С.В. Максимова1, 2, Н.Г. Ложкина3, В.Н. Максимов1, 2 1 Новосибирский государственный медицинский университет Министерства здравоохранен...
https://openalex.org/W2894688931
https://revistas.ucm.es/index.php/CIYC/article/download/60692/4564456547542
es
"Teoría e historia de la propaganda" (2017), Adrián Huici Módenes, Madrid, Editorial Síntesis, 2017, pp. 278.
Cuadernos de información y comunicación
2,018
cc-by
1,786
RESEÑAS CIC. Cuadernos de Información y Comunicación ISSN: 1135-7791 http://dx.doi.org/10.5209/CIYC.60692 Teoría e historia de la propaganda (2017), Adrián Huici Módenes, Madrid, Editorial Síntesis, 2017, pp. 278. Adrián Huici Módenes es profesor titular en la Facultad de Comunicación de la Universidad de Sevilla. D...
https://openalex.org/W4311505148
https://www.frontiersin.org/articles/10.3389/fragi.2022.1063760/pdf
English
null
Living alone reduces the decline of calf circumference among Chinese older adults: A 4-year longitudinal study
Frontiers in aging
2,022
cc-by
5,880
TYPE Original Research PUBLISHED 15 December 2022 DOI 10.3389/fragi.2022.1063760 TYPE Original Research PUBLISHED 15 December 2022 DOI 10.3389/fragi.2022.1063760 TYPE Original Research PUBLISHED 15 December 2022 DOI 10.3389/fragi.2022.1063760 OPEN ACCESS OPEN ACCESS EDITED BY Alan Bruno Silva Vasconcelos, University Ce...
https://openalex.org/W4315864599
https://www.mdpi.com/2075-4450/14/1/80/pdf?version=1673680064
English
null
Presence of Spodoptera frugiperda Multiple Nucleopolyhedrovirus (SfMNPV) Occlusion Bodies in Maize Field Soils of Mesoamerica
Insects
2,023
cc-by
11,387
Presence of Spodoptera frugiperda Multiple Nucleopolyhedrovirus (SfMNPV) Occlusion Bodies in Maize Field Soils of Mesoamerica Trevor Williams 1,* , Guadalupe del Carmen Melo-Molina 2, Jaime A. Jiménez-Fernández 2, Holger Weissenberger 3, Juan S. Gómez-Díaz 1, Laura Navarro-de-la-Fuente 1 and Andrew R. R 1 Instituto de ...
https://openalex.org/W3174449198
https://zenodo.org/record/7092294/files/45%2025262.pdf
English
null
Unsupervised feature selection with least-squares quadratic mutual information
Indonesian journal of electrical engineering and computer science
2,021
cc-by
6,625
Corresponding Author: Janya Sainui Division of Computational Science, Faculty of Science Prince of Songkla University Songkhla, Thailand Email: janya.s@psu.ac.th Indonesian Journal of Electrical Engineering and Computer Science Vol. 22, No. 3, June 2021, pp. 1619∼1628 ISSN: 2502-4752, DOI: 10.11591/ijeecs.v22i3.pp1619-...
https://openalex.org/W4392892860
https://www.qeios.com/read/O0X1UB/pdf
English
null
Review of: "Ancient Houses in Ben Tre City: A Multifaceted Approach to Preserve Artistic Architectural Heritage and Boost Local Tourism"
null
2,024
cc-by
311
Qeios, CC-BY 4.0 · Review, March 17, 2024 Review of: "Ancient Houses in Ben Tre City: A Multifaceted Approach to Preserve Artistic Architectural Heritage and Boost Local Tourism" Rute Matos1 Rute Matos1 Rute Matos1 1 Universidade de Evora 1 Universidade de Evora 1 Universidade de Evora Potential competing interests...
https://openalex.org/W4225727893
https://bmjopen.bmj.com/content/bmjopen/12/1/e053327.full.pdf
English
null
Adoption and continued use of mobile contact tracing technology: multilevel explanations from a three-wave panel survey and linked data
BMJ open
2,022
cc-by
6,938
Strengths and limitations of this study Objective  To identify the key individual-­level (demographics, attitudes, mobility) and contextual (COVID-­19 case numbers, tiers of mobility restrictions, urban districts) determinants of adopting the NHS COVID-­19 contact tracing app and continued use overtime. Design and ...
https://openalex.org/W2093810977
https://figshare.com/articles/journal_contribution/PDC_Mediated_Tandem_Oxidative_8211_Wittig_Olefination/1009039/1/files/1476662.pdf
English
null
PDC-Mediated Tandem Oxidative–Wittig Olefination
Synthetic communications
2,014
cc-by
2,583
2. General Procedure To a magnetically stired suspension of pyridinium dichromate (1.85 mmol), Wittig reagent (1.85 mmol) in anhyd CH2Cl2 (10 mL), alcohol (1.85 mmol) in anhyd CH2Cl2 (10 mL) was added in one portion. The reaction mixture was stirred at r.t. for 24h. Et2O (30 mL) was added to the reaction mixture and...
https://openalex.org/W4299631625
https://hal.science/hal-01602210/document
English
null
Classifying simulated wheat yield responses to changes in temperature and precipitation across a european transect
HAL (Le Centre pour la Communication Scientifique Directe)
2,016
cc-by-sa
1,239
International Crop Modelling Symposium 15-17 March 2016, Berlin 15-17 March 2016, Berlin Introduction A wide variety of dynamic crop growth simulation models have been developed over the past few decades that can differ greatly in their treatment of key processes and hence in their response to environmental conditi...
https://openalex.org/W2171243607
https://europepmc.org/articles/pmc4635008?pdf=render
English
null
Interactions Increase Forager Availability and Activity in Harvester Ants
PloS one
2,015
cc-by
10,083
RESEARCH ARTICLE Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Funding: Field work for EP in 2012 was funded by a Stanford UAR Student Small Grant, and fi...
W4225157612.txt
https://journals.wlb-stuttgart.de/ojs/index.php/zwlg/article/download/1938/2010
de
Rezension von: Schmidt, Ernst, Heimatgeschichtliches Lesebuch
Zeitschrift für württembergische Landesgeschichte
2,022
cc-by
1,016
Städte und Orte 555 Linke, Juden, „Zigeuner“, Zwangsarbeiter, Homosexuelle und andere so genannte „Volksschädlinge“ geprägt; Folterungen und willkürliche Exekutionen in großer Zahl waren an der Tagesordnung. Betroffene haben ihn beschrieben als „fauchenden Zwerg und zappelnden Sadisten mit kreischender Stimme“. Bei ...
https://openalex.org/W2989903755
http://www.scielo.br/pdf/pat/v49/1983-4063-pat-49-e55628.pdf
English
null
Behavioral aspects of Helicoverpa armigera in the cotton vegetative phase1
Pesquisa Agropecuária Tropical
2,019
cc-by
5,786
RESUMO Aspectos comportamentais de Helicoverpa armigera na fase vegetativa do algodoeiro Helicoverpa armigera (Hübner) is part of an important complex of insects-pests that attack the cotton crop. This study aimed to identify the preferential plant parts for the oviposition of moths, as well as the movement and fee...
https://openalex.org/W2582221738
https://repub.eur.nl/pub/97988/journal.pntd.0005310.pdf
English
null
Diagnosing Polyparasitism in a High-Prevalence Setting in Beira, Mozambique: Detection of Intestinal Parasites in Fecal Samples by Microscopy and Real-Time PCR
PLoS neglected tropical diseases
2,017
cc-by
11,926
RESEARCH ARTICLE Background Many different intestinal parasite species can co-occur in the same population. However, classic diagnostic tools can only frame a particular group of intestinal parasite species. Hence, one or two tests do not suffice to provide a complete picture of infecting parasite spe- cies in a given ...
https://openalex.org/W2121310997
https://www.scielo.br/j/rbh/a/5t8SPLNx6sxhLRNNyXQfSkr/?lang=pt&format=pdf
Portuguese
null
As cidades da juventude em Fortaleza
Revista brasileira de história
2,007
cc-by
12,926
ABSTRACT A cidade de Fortaleza é apresentada a partir da experiência juvenil, de suas organizações, de seus deslocamentos e de suas formas específicas de apropria- ção da cidade.Desta observação delineio a idéia de Experiência Musical e de Des- locamentos Geo-Estéticos na cidade. As organizações e experiências juvenis ...
W1986052297.txt
https://www.frontiersin.org/articles/10.3389/fnins.2014.00186/pdf
en
Pairmate-dependent pup retrieval as parental behavior in male mice
Frontiers in neuroscience
2,014
cc-by
8,092
ORIGINAL RESEARCH ARTICLE published: 11 July 2014 doi: 10.3389/fnins.2014.00186 Pairmate-dependent pup retrieval as parental behavior in male mice Mingkun Liang 1,2 , Jing Zhong 1,2 , Hong-Xiang Liu 1 , Olga Lopatina 1 , Ryusuke Nakada 2 , Agnes-Mikiko Yamauchi 2 and Haruhiro Higashida 1* 1 2 Department of Basic Rese...
https://openalex.org/W3016593255
https://www.journals.vu.lt/slavistica-vilnensis/article/download/16834/15961
Russian
null
Immigration Discourse and the Prospects of Russian Language in Lithuania
Slavistica Vilnensis
2,019
cc-by
6,918
Received: 24/11/2019. Accepted: 15/12/2019 Copyright © 2019 Алла Борисовна Лихачева. Published by Vilnius University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the...
https://openalex.org/W4244562454
https://scielosp.org/article/ssm/content/raw/?resource_ssm_path=/media/assets/csp/v29n7/05.pdf
Portuguese
null
Qualidade de vida dos indivíduos expostos ao césio-137, em Goiânia, Goiás, Brasil
Cadernos de Saúde Pública
2,013
cc-by
6,641
1 Programa de Pós-graduação Ciências da Saúde, Universidade Federal de Goiás, Goiânia, Brasil. 2 Instituto de Patologia Tropical e Saúde Pública, Universidade Federal de Goiás, Goiânia, Brasil. 3 Faculdade de Medicina, Universidade Federal de Goiás, Goiânia, Brasil. 4 Faculdade de Farmácia, Universidade Federa...
https://openalex.org/W2028130894
https://curis.ku.dk/ws/files/127547653/Control_region_sequences_indicate_that_multiple_externae_represent_multiple_infections_by_Sacculina_carcini.pdf
English
null
Control region sequences indicate that multiple externae represent multiple infections by Sacculina carcini (Cirripedia: Rhizocephala)
Ecology and evolution
2,014
cc-by
6,410
university of copenhagen university of copenhagen Control region sequences indicate that multiple externae represent multiple infections by Sacculina carcini (Cirripedia: Rhizocephala) university of copenhagen Control region sequences indicate that multiple externae represent multiple infections by Sacculina carcini (...
https://openalex.org/W4321458814
https://www.frontiersin.org/articles/10.3389/fgene.2023.1137017/pdf
English
null
Regulatory mechanisms of microRNAs in endocrine disorders and their therapeutic potential
Frontiers in genetics
2,023
cc-by
12,865
Abbreviations: miRNA, microRNA; DM, Diabetes mellitus; T1D, Type 1 diabetes; T2D, Type 2 diabetes; Treg Regulatory T cells AITDs, Autoimmune thyroid disorders; GD, Graves’ disease; HT, Hashimoto’s thyroiditis; BMD, Bone mineral density; MSC, Mesenchymal stem cells; APA, Aggressive pituitary adenoma; CAB, Cabergoline. K...
https://openalex.org/W3037036092
https://journals.iucr.org/e/issues/2020/07/00/wm5569/wm5569.pdf
English
null
Selective synthesis and crystal structures of manganese(I) complexes with a bi- or tridentate terpyridine ligand
Acta crystallographica. Section E, Crystallographic communications
2,020
cc-by
7,688
research communications Selective synthesis and crystal structures of manganese(I) complexes with a bi- or tridentate terpyridine ligand Selective synthesis and crystal structures of manganese(I) complexes with a bi- or tridentate terpyridine ligand ISSN 2056-9890 Kosei Wadayama,a Tsugiko Takaseb and Dai Oyamab* aGradu...
https://openalex.org/W4312964994
https://revistas.ucm.es/index.php/ANHA/article/download/83058/4564456561480
es
Memoria oral del pueblo Mapuche en la reforma agraria y la dictadura. Aplicación del archivo en el proyecto Dungun, instalación sonora interactiva
Anales de historia del arte
2,022
cc-by
10,668
FORO Anales de Historia del Arte ISSN: 0214-6452 https://dx.doi.org/10.5209/anha.83058 Memoria oral del pueblo Mapuche en la reforma agraria y la dictadura. Aplicación del archivo en el proyecto Dungun, instalación sonora interactiva Luis Urquieta Robles1 Recibido: 1 de febrero de 2022 / Aceptado: 6 de junio de 2022...
https://openalex.org/W4280605643
https://repositorioinstitucional.ceu.es/bitstream/10637/14376/1/News_Pou_CCAC_2022.pdf
English
null
News coverage of the Church dealing with the pandemic: Spanish and Italian newspapers
Church, communication and culture
2,022
cc-by
11,678
Church, Communication and Culture Church, Communication and Culture ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/rchu20 ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/rchu20 Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action...
https://openalex.org/W4304807314
https://www.aging-us.com/article/204334/pdf
English
null
Palmitic acid inhibits vascular smooth muscle cell switch to synthetic phenotype via upregulation of miR-22 expression
Aging
2,022
cc-by
7,293
ABSTRACT Synthetic phenotype switch of vascular smooth muscle cells (VSMCs) has been shown to play key roles in vascular diseases. Mounting evidence has shown that fatty acid metabolism is highly associated with vascular diseases. However, how fatty acids regulate VSMC phenotype is poorly understood. Hence, the effec...
https://openalex.org/W4229988195
https://zenodo.org/records/2231079/files/article.pdf
English
null
A Note-Book on Experimental Mathematics. C. Godfrey and G. M. Bell. (Arnold.)
˜The œmathematical gazette/Mathematical gazette
1,906
public-domain
2,585
Review Source: The Mathematical Gazette, Vol. 3, No. 56 (Mar., 1906), pp. 297-298 Published by: Mathematical Association Stable URL: http://www.jstor.org/stable/3603481 Accessed: 02-12-2015 05:46 UTC Review Review Source: The Mathematical Gazette, Vol. 3, No. 56 (Mar., 1906), pp. 297-298 Published by: ...
https://openalex.org/W4231506190
http://e-journal.metrouniv.ac.id/index.php/istinbath/article/download/951/783
Indonesian
null
FAKTOR PENGHAMBAT DALAM PENEGAKAN QANUN JINAYAT DI ACEH
null
2,019
cc-by-sa
8,010
Abstrak Tulisan ini membuktikan bahwa pelaksanaan Qanun Aceh No. 14 Tahun 2003 tentang khalwat di Kota Subulussalam belum sepenuhnya berjalan dengan baik. Banyak kendala yang dihadapi baik dari pelaksananya (pemerintah) maupun masyarakat sebagai objek hukum penerapan syariat Islam itu sendiri. Faktor hukum yang meru...
https://openalex.org/W2031764972
https://europepmc.org/articles/pmc2805710?pdf=render
English
null
Microphthalmia in Texel Sheep Is Associated with a Missense Mutation in the Paired-Like Homeodomain 3 (PITX3) Gene
PloS one
2,010
cc-by
8,280
Abstract The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. Competing Interests: The authors have declared that no competing interests exist. * E-mail: Cord.Droege...
https://openalex.org/W2108456140
https://link.springer.com/content/pdf/10.1186%2F2052-336X-12-87.pdf
English
null
Optimizing photo-Fenton like process for the removal of diesel fuel from the aqueous phase
Journal of environmental health science & engineering
2,014
cc-by
5,275
Abstract Background: In recent years, pollution of soil and groundwater caused by fuel leakage from old underground storage tanks, oil extraction process, refineries, fuel distribution terminals, improper disposal and also spills during transferring has been reported. Diesel fuel has created many problems for water res...
https://openalex.org/W2464335014
https://zenodo.org/records/56298/files/NB_article_7113.pdf
English
null
Biological control of weeds in the 22 Pacific island countries and territories: current status and future prospects
NeoBiota
2,016
cc-by
10,824
Abstract Biological control of introduced weeds in the 22 Pacific island countries and territories (PICTs) began in 1911, with the lantana seed-feeding fly introduced into Fiji and New Caledonia from Hawaii. To date, a to­ tal of 62 agents have been deliberately introduced into the PICTs to control 21 weed species in ...
https://openalex.org/W2944092791
https://europepmc.org/articles/pmc6572060?pdf=render
English
null
Prevalence and Risk Factors for Positive Nasal Methicillin-Resistant Staphylococcus aureus Carriage among Orthopedic Patients in Korea
Journal of clinical medicine
2,019
cc-by
6,607
Received: 14 April 2019; Accepted: 7 May 2019; Published: 8 May 2019 Abstract: Methicillin-resistant Staphylococcus aureus (MRSA) causes purulent skin and soft tissue infections as well as other life-threatening diseases. Recent guidelines recommend screening for MRSA at the time of admission. However, few studies have...
https://openalex.org/W4293661304
https://journal2.unusa.ac.id/index.php/MTPHJ/article/download/3187/1749
Indonesian
null
The Relationship between Snack Consumption Patterns and Nutritional Status in Adolescents in Malang City Indonesia
Medical technology and public health journal
2,022
cc-by-sa
2,785
ABSTRACT Background : The consumption of snacks is often done between meals. About 20% of the daily intake of adolescents comes from snacks. Snacks contribute ‘empty’ energy but provide an excess intake of substances that are not beneficial to the teenager’s body. Objectives; this study aims to determine the pattern...
https://openalex.org/W2951066048
https://europepmc.org/articles/pmc6572740?pdf=render
English
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Public health application of predictive modeling: an example from farm vehicle crashes
Injury epidemiology.
2,019
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8,629
© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original au...
https://openalex.org/W832180393
https://journals.agh.edu.pl/geotour/article/download/687/512
English
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Middle Jurassic black shales (Skrzypny Shale Formation) – palaeoenvironmental significance of one of the oldest deposits of the Pieniny Klippen Belt.
Geotourism/Geoturystyka
2,008
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5,450
Środkowojurajskie czarne łupki (formacja łupków ze Skrzypnego) – znaczenie paleośrodowiskowe jednych z najstarszych osadów pienińskiego pasa skałkowego Katarzyna Górniak1, Krzysztof Bahranowski1, Adam Gaweł1, Leszek Marynowski2 & Tadeusz Szydłak1 1 AGH University of Science and Technology, Department of Mineralogy, ...
https://openalex.org/W3042632995
https://revistas.ucm.es/index.php/ANQE/article/download/66701/4564456554017
es
Traducción comentada de un acta notarial de celebración de matrimonio civil del español al árabe
Anaquel de estudios árabes
2,020
cc-by
14,414
ARTÍCULOS Anaquel de Estudios Árabes ISSN: 1130-3964 https://dx.doi.org/10.5209/anqe.66701 Traducción comentada de un acta notarial de celebración de matrimonio civil del español al árabe Beatriz Soto Aranda1; Rabab Kabbour2 Recibido: 2 de diciembre de 2019 / Aceptado: 29 de febrero de 2020 Resumen. Las actas notar...
https://openalex.org/W2920243230
https://europepmc.org/articles/pmc6473468?pdf=render
English
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Role of Nitrate Reductase in NO Production in Photosynthetic Eukaryotes
Plants
2,019
cc-by
9,306
Received: 16 January 2019; Accepted: 8 February 2019; Published: 6 March 2019 Abstract: Nitric oxide is a gaseous secondary messenger that is critical for proper cell signaling and plant survival when exposed to stress. Nitric oxide (NO) synthesis in plants, under standard phototrophic oxygenic conditions, has long bee...
https://openalex.org/W4212939849
https://discovery.ucl.ac.uk/10144625/1/s13023-022-02191-2.pdf
English
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Challenges and improvement needs in the care of patients with central diabetes insipidus
Orphanet journal of rare diseases
2,022
cc-by
10,727
Abstract Central diabetes insipidus (CDI) is a rare condition, with significant impact on patient health and well-being. It is a chronic condition which usually requires meticulous long-term care. It can affect both children and adults. There is limited literature considering the needs and challenges inherent in prov...
W4394815528.txt
https://www.emerald.com/insight/content/doi/10.1108/IJDI-12-2023-0287/full/pdf?title=efficiency-of-brics-countries-in-sustainable-development-a-comparative-data-envelopment-analysis
en
Efficiency of BRICS countries in sustainable development: a comparative data envelopment analysis
International journal of development issues
2,024
cc-by
8,611
The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/1446-8956.htm Efficiency of BRICS countries in sustainable development: a comparative data envelopment analysis Isabella Melissa Gebert Iscte-Instituto Universitário de Lisboa, Lisbon, Portugal, an...
https://openalex.org/W4313417200
https://sensors.myu-group.co.jp/sm_pdf/SM3144.pdf
English
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Deep-learning-based Automatic Detection and Classification of Traffic Signs Using Images Collected by Mobile Mapping Systems
Sensors and materials
2,022
cc-by
4,563
*Corresponding author: e-mail: kemyoung@nsu.ac.kr https://doi.org/10.18494/SAM3956 Keywords: high-definition maps, traffic sign, mask R-CNN, Inception-v3, autonomous driving Keywords: high-definition maps, traffic sign, mask R-CNN, Inception-v3, autonomous driving As interest in autonomous driving has increased in re...
https://openalex.org/W4313589007
https://www.researchsquare.com/article/rs-2178907/latest.pdf
English
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Study on the mechanical properties of clayey slip zone soil considering montmorillonite content
Research Square (Research Square)
2,023
cc-by
7,680
Research Article Keywords: cohesive slipband soils, expansion characteristics, hydrophilic minerals, montmorillonite, shear strength parameters Posted Date: January 4th, 2023 DOI: https://doi.org/10.21203/rs.3.rs-2178907/v1 License:   This work is licensed under a Creative Commons Attribution 4.0 International Licens...
https://openalex.org/W2152263162
https://europepmc.org/articles/pmc3201606?pdf=render
English
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Vertebral cryptococcosis in an immunocompetent patient - a case report
˜The œPan African medical journal
2,011
cc-by
1,351
Abstract We report an unusual case of 70 years old, immunocompetent woman who was diagnosed with vertebral cryptococcosis. The diagnosis was made on the basis of radiological and histological findings. The outcome was favorable under antifungal treatment. &Corresponding author: Ammouri Wafa, Department of Internal med...
https://openalex.org/W4391329061
https://egusphere.copernicus.org/preprints/2023/egusphere-2023-3000/egusphere-2023-3000.pdf
English
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Comment on egusphere-2023-3000
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34,210
ERROR: type should be string, got "https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0.\nl\n.\n0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 Impact of Hurricane Irma on Coral Reef Sediment Redistribution at \n5 \nLooe Key Reef, Florida, USA \nKimberly K. Yates1, Zachery Fehr2, Selena Johnson1, David Zawada1 \n1U.S. Geological Survey, St. Petersburg, FL, 33701, United States \n2Cherokee Nation System Solutions, Tulsa, OK, 74166, United States, Contractor to the U.S. Geological Survey \nCorrespondence to: Kimberly K. Yates (kyates@usgs.gov) \n10 Rates of elevation \nchange during this post-storm period were one to two orders of magnitude greater than decadal and multi-decadal rates of \nchange in the same location, and changes showed erosion of approximately 50% of sediment deposited during the storm event \nas seafloor sediment distribution began to re-equilibrate to non-storm sea state conditions. Our results suggest higher resolution \n30 \nelevation-change data collected over seasonal and annual time periods could enhance characterization and understanding of \nshort-term and long-term rates and processes of seafloor change and help guide post-storm recovery and restoration of benthic \nhabitats in topographically complex coral reef systems. Abstract. Understanding event-driven sediment transport in coral reef environments is essential to assessing impacts to reef \nspecies, habitats, restoration, and mitigation, yet there remains a global knowledge gap due to limited quantitative studies. Hurricane Irma made landfall in the Lower Florida Keys with sustained 209 km h-1 winds and greater than 8 m waves on 10 \nSeptember 2017, directly impacting the Florida Reef Tract (FRT), and providing an opportunity to perform a unique comprehensive, quantitative assessment of its impact on coral reef structure and sediment redistribution. We used lidar and \n15 \nmultibeam derived digital elevation models (DEMs) collected before and after the passing of Hurricane Irma over a 15.98 km2 \narea along the Lower FRT including Looe Key Reef to quantify changes in seafloor elevation, volume, and structure due to \nstorm impacts. Elevation change was calculated at over 4-million point-locations across 10 habitat types within this study area \nfor two time periods using data collected from 1) approximately one year before the passing of Irma and three to six months 15 comprehensive, quantitative assessment of its impact on coral reef structure and sediment redistribution. We used lidar and \n15 \nmultibeam derived digital elevation models (DEMs) collected before and after the passing of Hurricane Irma over a 15.98 km2 \narea along the Lower FRT including Looe Key Reef to quantify changes in seafloor elevation, volume, and structure due to \nstorm impacts. Elevation change was calculated at over 4-million point-locations across 10 habitat types within this study area \nfor two time periods using data collected from 1) approximately one year before the passing of Irma and three to six months following the storm’s impact, and 2) from three to six months after, and up to 16.5 months after, the storm. Impact of Hurricane Irma on Coral Reef Sediment Redistribution at \n5 \nLooe Key Reef, Florida, USA \nKimberly K. Yates1, Zachery Fehr2, Selena Johnson1, David Zawada1 \n1U.S. Geological Survey, St. Petersburg, FL, 33701, United States \n2Cherokee Nation System Solutions, Tulsa, OK, 74166, United States, Contractor to the U.S. Geological Survey \nCorrespondence to: Kimberly K. Yates (kyates@usgs.gov) \n10 Impact of Hurricane Irma on Coral Reef Sediment Redistribution at \n5 \nLooe Key Reef, Florida, USA \nKimberly K. Yates1, Zachery Fehr2, Selena Johnson1, David Zawada1 \n1U.S. Geological Survey, St. Petersburg, FL, 33701, United States \n2Cherokee Nation System Solutions, Tulsa, OK, 74166, United States, Contractor to the U.S. Geological Survey \nCorrespondence to: Kimberly K. Yates (kyates@usgs.gov) \n10 rly K. Yates1, Zachery Fehr2, Selena Johnson1, David Zawada1 Abstract. Understanding event-driven sediment transport in coral reef environments is essential to assessing impacts to reef \nspecies, habitats, restoration, and mitigation, yet there remains a global knowledge gap due to limited quantitative studies. Hurricane Irma made landfall in the Lower Florida Keys with sustained 209 km h-1 winds and greater than 8 m waves on 10 \nSeptember 2017, directly impacting the Florida Reef Tract (FRT), and providing an opportunity to perform a unique \ncomprehensive, quantitative assessment of its impact on coral reef structure and sediment redistribution. We used lidar and \n15 \nmultibeam derived digital elevation models (DEMs) collected before and after the passing of Hurricane Irma over a 15.98 km2 \narea along the Lower FRT including Looe Key Reef to quantify changes in seafloor elevation, volume, and structure due to \nstorm impacts. Elevation change was calculated at over 4-million point-locations across 10 habitat types within this study area \nfor two time periods using data collected from 1) approximately one year before the passing of Irma and three to six months \nfollowing the storm’s impact, and 2) from three to six months after, and up to 16.5 months after, the storm. Elevation-change \n20 \ndata were then used to generate Triangulated Irregular Network (TIN) models in ArcMap to calculate changes in seafloor \nvolume during each time-period. Our results indicate that Hurricane Irma was primarily a depositional event that increased \nmean seafloor elevation and volume at this study site by 0.34 m and up to 5.4 Mm3, respectively. Sediment was transported \nprimarily west-southwest (WSW) and downslope modifying geomorphic seafloor features including the migration of sand \nwaves and rubble fields, formation of scour marks in shallow seagrass habitat, and burial of seagrass and coral-dominated \n25 \nhabitat. Approximately 16.5 months after Hurricane Irma (during a 13-month period between 2017 and 2019), net erosion was \nobserved across all habitats with mean elevation-change of -0.15 m and net volume change up to -2.46 Mm3. https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 1 Introduction Coral coverage \nhas been reported at less than 7% along the Florida Keys Reef Tract and less than 3% along the northern FRT in recent years \n50 \n(Jackson et al., 2014; Walton et al, 2018; Knowlton, 2020); and many of Florida’s reefs are in a net erosional state (Yates et \nal., 2017; Morris et al, 2022). Additionally, seagrass has been decreasing in coverage since early Thalassia testudinum die-\noffs in 1987 and more contemporary die-offs in 2015 following storm events and water quality variations (Hall et al., 2016). al., 2009; Gorstein et al., 2016, Towle et al., 2020). Benthic communities of the Florida Reef Tract (FRT) have been degrading \n40 \nfor the past several decades. Coral coverage has declined across the Caribbean and Florida reefs by more than 50% since the \n1970’s due to coral disease and bleaching (Porter et al., 2001; Patterson et al., 2002; Williams and Miller, 2012; Joyner et al., \n2015; Walker et al., 2018), pollution and overfishing (Littler et al., 1986; Lapointe & Clark, 1992; and Hughes 1994), and \nmass-mortality of macroalgal grazers (e.g., Lessios et al. 1983). Progression of climate change has increased thermal stress, al., 2009; Gorstein et al., 2016, Towle et al., 2020). Benthic communities of the Florida Reef Tract (FRT) have been degrading \n40 \nfor the past several decades. Coral coverage has declined across the Caribbean and Florida reefs by more than 50% since the \n1970’s due to coral disease and bleaching (Porter et al., 2001; Patterson et al., 2002; Williams and Miller, 2012; Joyner et al., \n2015; Walker et al., 2018), pollution and overfishing (Littler et al., 1986; Lapointe & Clark, 1992; and Hughes 1994), and \nmass-mortality of macroalgal grazers (e.g., Lessios et al. 1983). Progression of climate change has increased thermal stress, coral bleaching and disease, ocean acidification, and corallivory (predation of corals) (Wilkinson 1996; Mumby et al., 2006; \n45 \nBrandt and McManus, 2009; Soto et al., 2011; Kuffner et al., 2015; Randall and van Woesik, 2015; Muehllehner et al., 2016; \nHughes et al., 2017; Rice et al., 2019). These multiple stressors and increased storm occurrences have caused a shift from \nstony-coral-dominated reefs to macroalgae and octocoral dominated reefs (Bohsnack 1983; Hughs, 1994; Knowlton, 1992; \nMiller et al., 2002; Norstrom et al., 2009; Bruno et al., 2009; Ruzicka et al., 2013 and Jackson et al., 2014). Impact of Hurricane Irma on Coral Reef Sediment Redistribution at \n5 \nLooe Key Reef, Florida, USA \nKimberly K. Yates1, Zachery Fehr2, Selena Johnson1, David Zawada1 \n1U.S. Geological Survey, St. Petersburg, FL, 33701, United States \n2Cherokee Nation System Solutions, Tulsa, OK, 74166, United States, Contractor to the U.S. Geological Survey \nCorrespondence to: Kimberly K. Yates (kyates@usgs.gov) \n10 Elevation-change \n20 \ndata were then used to generate Triangulated Irregular Network (TIN) models in ArcMap to calculate changes in seafloor \nvolume during each time-period. Our results indicate that Hurricane Irma was primarily a depositional event that increased \nmean seafloor elevation and volume at this study site by 0.34 m and up to 5.4 Mm3, respectively. Sediment was transported \nprimarily west-southwest (WSW) and downslope modifying geomorphic seafloor features including the migration of sand following the storm’s impact, and 2) from three to six months after, and up to 16.5 months after, the storm. Elevation-change \n20 \ndata were then used to generate Triangulated Irregular Network (TIN) models in ArcMap to calculate changes in seafloor \nvolume during each time-period. Our results indicate that Hurricane Irma was primarily a depositional event that increased \nmean seafloor elevation and volume at this study site by 0.34 m and up to 5.4 Mm3, respectively. Sediment was transported \nprimarily west-southwest (WSW) and downslope modifying geomorphic seafloor features including the migration of sand waves and rubble fields, formation of scour marks in shallow seagrass habitat, and burial of seagrass and coral-dominated \n25 \nhabitat. Approximately 16.5 months after Hurricane Irma (during a 13-month period between 2017 and 2019), net erosion was \nobserved across all habitats with mean elevation-change of -0.15 m and net volume change up to -2.46 Mm3. Rates of elevation \nchange during this post-storm period were one to two orders of magnitude greater than decadal and multi-decadal rates of \nchange in the same location, and changes showed erosion of approximately 50% of sediment deposited during the storm event as seafloor sediment distribution began to re-equilibrate to non-storm sea state conditions. Our results suggest higher resolution \n30 \nelevation-change data collected over seasonal and annual time periods could enhance characterization and understanding of \nshort-term and long-term rates and processes of seafloor change and help guide post-storm recovery and restoration of benthic \nhabitats in topographically complex coral reef systems. as seafloor sediment distribution began to re-equilibrate to non-storm sea state conditions. Our results suggest higher resolution \n30 \nelevation-change data collected over seasonal and annual time periods could enhance characterization and understanding of \nshort-term and long-term rates and processes of seafloor change and help guide post-storm recovery and restoration of benthic \nhabitats in topographically complex coral reef systems. 1 1 Introduction Coral reefs provide a variety of services to coastal communities including protection from coastal hazards such as storms, \n35 \nwaves, and erosion (Ferrario et al., 2014; Storlazzi et al., 2021); socioeconomic benefits such as fisheries, recreation, and \ntourism (Moberg and Folk, 1999; Hall et al. 2020); and they support numerous habitats and diverse marine species (Knowlton, \n2020). Socioeconomic benefits of Florida reefs have an estimated value of over 8 billion dollars a year, supporting 39,000 \nSouth Florida jobs and 70,400 total jobs, with at least 2.9 billion dollars contributing directly to the local economy (Krediet et Coral reefs provide a variety of services to coastal communities including protection from coastal hazards such as storms, \n35 \nwaves, and erosion (Ferrario et al., 2014; Storlazzi et al., 2021); socioeconomic benefits such as fisheries, recreation, and \ntourism (Moberg and Folk, 1999; Hall et al. 2020); and they support numerous habitats and diverse marine species (Knowlton, \n2020). Socioeconomic benefits of Florida reefs have an estimated value of over 8 billion dollars a year, supporting 39,000 \nSouth Florida jobs and 70,400 total jobs, with at least 2.9 billion dollars contributing directly to the local economy (Krediet et \nal., 2009; Gorstein et al., 2016, Towle et al., 2020). Benthic communities of the Florida Reef Tract (FRT) have been degrading \n40 \nfor the past several decades. Coral coverage has declined across the Caribbean and Florida reefs by more than 50% since the \n1970’s due to coral disease and bleaching (Porter et al., 2001; Patterson et al., 2002; Williams and Miller, 2012; Joyner et al., \n2015; Walker et al., 2018), pollution and overfishing (Littler et al., 1986; Lapointe & Clark, 1992; and Hughes 1994), and \nmass-mortality of macroalgal grazers (e.g., Lessios et al. 1983). Progression of climate change has increased thermal stress, \ncoral bleaching and disease, ocean acidification, and corallivory (predation of corals) (Wilkinson 1996; Mumby et al., 2006; \n45 \nBrandt and McManus, 2009; Soto et al., 2011; Kuffner et al., 2015; Randall and van Woesik, 2015; Muehllehner et al., 2016; \nHughes et al., 2017; Rice et al., 2019). These multiple stressors and increased storm occurrences have caused a shift from \nstony-coral-dominated reefs to macroalgae and octocoral dominated reefs (Bohsnack 1983; Hughs, 1994; Knowlton, 1992; \nMiller et al., 2002; Norstrom et al., 2009; Bruno et al., 2009; Ruzicka et al., 2013 and Jackson et al., 2014). 1 Introduction Coral coverage has been reported at less than 7% along the Florida Keys Reef Tract and less than 3% along the northern FRT in recent years \n50 \n(Jackson et al., 2014; Walton et al, 2018; Knowlton, 2020); and many of Florida’s reefs are in a net erosional state (Yates et \nal., 2017; Morris et al, 2022). Additionally, seagrass has been decreasing in coverage since early Thalassia testudinum die-\noffs in 1987 and more contemporary die-offs in 2015 following storm events and water quality variations (Hall et al., 2016). Multi-decadal seafloor elevation-change analyses along the FRT indicate that degradation of coral reefs and surrounding \n55 \nseafloor habitats has led to substantial erosion and loss of elevation from the 1930’s to 2002 and increased water depths to \nlevels not expected until near the year 2100 (Yates et al., 2017). Projected socioeconomic impacts due to continued FRT coral \nreef degradation and loss of seafloor elevation estimate increases of flooding risk from storms and coastal inundation to more \nthan 7,300 people and $823.6 million (2010 U.S. dollars, USD) in direct and indirect damage to housing, buildings, and Multi-decadal seafloor elevation-change analyses along the FRT indicate that degradation of coral reefs and surrounding \n55 \nseafloor habitats has led to substantial erosion and loss of elevation from the 1930’s to 2002 and increased water depths to \nlevels not expected until near the year 2100 (Yates et al., 2017). Projected socioeconomic impacts due to continued FRT coral \nreef degradation and loss of seafloor elevation estimate increases of flooding risk from storms and coastal inundation to more \nthan 7,300 people and $823.6 million (2010 U.S. dollars, USD) in direct and indirect damage to housing, buildings, and businesses, annually (Storlazzi et al., 2021). Storm frequency and strength are projected to increase as sea-surface temperatures \n60 \nand atmospheric energy increase due to climate change and global warming (Elsner et al., 2008, Bhatia et al., 2019; Knutson \net al., 2020). While advances have been made in understanding long-term change in seafloor elevation and structure and its \npotential socioeconomic consequences, understanding the effects of event-driven changes to seafloor geomorphology due to \nstorms remains a major knowledge gap. businesses, annually (Storlazzi et al., 2021). Storm frequency and strength are projected to increase as sea-surface temperatures \n60 \nand atmospheric energy increase due to climate change and global warming (Elsner et al., 2008, Bhatia et al., 2019; Knutson \net al., 2020). https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 Major tropical storms persistently impact the state of Florida with historical hurricane impacts estimated to have caused more \nthan $450 billion dollars of damage across the state from the early 1900’s to 2007 (Malmstadt et al., 2009). The Middle to \nLower Florida Keys (from Islamorada to Key West) has been impacted by 15 major hurricane landfall events (Category 3 \nthrough 5) and numerous tropical storm and Category 1 and 2 hurricanes from the early 1900’s to 2022 (NOAA, 2022a). Hurricane Irma made landfall at Cudjoe Key in the Lower Florida Keys after passing directly over Looe Key Reef on 10 \n70 \nSeptember 2017 as a category 4 hurricane with maximum wind speeds of 213 km h-1 (115 kts) (Cangialosi et al., 2021) and \nsignificant wave heights of approximately 14 m a few kilometers offshore of the Florida Keys (Xian et al., 2018, Fig. 1a, b). Satellite imagery showed extensive sediment plumes throughout South Florida and the FRT caused by sediment resuspension \nand transport during the storm (Fig. 1c, d). The storm damaged up to 75% of buildings near its landfall point and caused Hurricane Irma made landfall at Cudjoe Key in the Lower Florida Keys after passing directly over Looe Key Reef on 10 \n70 \nSeptember 2017 as a category 4 hurricane with maximum wind speeds of 213 km h-1 (115 kts) (Cangialosi et al., 2021) and \nsignificant wave heights of approximately 14 m a few kilometers offshore of the Florida Keys (Xian et al., 2018, Fig. 1a, b). Satellite imagery showed extensive sediment plumes throughout South Florida and the FRT caused by sediment resuspension \nand transport during the storm (Fig. 1c, d). The storm damaged up to 75% of buildings near its landfall point and caused \napproximately 50 billion USD of wind and water damage across the state of Florida (Xian et al., 2018; Cangialosi et al., 2021; \n75 \nNOAA, 2022b). Prior to Hurricane Irma, the most recent, direct impact to Looe Key Reef from a tropical storm was in 2008 \nduring Tropical Storm Fay (NOAA, 2022a). Diver\nbased surveys of coral reefs at 57 locations along the FRT by the National Oceanic and Atmospheric Administration showed \n80 \nhighest levels of damage in the Middle to Lower Keys including dislodged and fractured corals, clogged and damaged sponges, \nheavy sedimentation, burial of corals, displaced rubble and sand, reef erosion, fractured substrate, and marine debris; 14% of \nsites showed severe impact, 33% showed moderate impact, and 53% showed minimal impact (Viehman et al., 2018). Looe \nKey Reef, located near the hurricane landfall location, showed more than 26% prevalence of hurricane-impacted corals (Florida based surveys of coral reefs at 57 locations along the FRT by the National Oceanic and Atmospheric Administration showed \n80 \nhighest levels of damage in the Middle to Lower Keys including dislodged and fractured corals, clogged and damaged sponges, \nheavy sedimentation, burial of corals, displaced rubble and sand, reef erosion, fractured substrate, and marine debris; 14% of \nsites showed severe impact, 33% showed moderate impact, and 53% showed minimal impact (Viehman et al., 2018). Looe \nKey Reef, located near the hurricane landfall location, showed more than 26% prevalence of hurricane-impacted corals (Florida Resilience Program, 2017). Similar surveys along the northern FRT from Key Biscayne north showed from approximately 5% \n85 \nto 17% of 62 sites with impacts to corals including dislodged and buried colonies, and at least one site with slabs of hardbottom \n2 to 5 m in size fractured and displaced several meters (Walker, 2018). Analyses of long-term monitoring-transect data at 40 \nsites throughout the Florida Keys National Marine Sanctuary (FKNMS) showed instantaneous losses in seagrass and \ncalcareous green macroalgae density after the storm passed, particularly in the Lower Florida Keys near where Hurricane Irma Resilience Program, 2017). Similar surveys along the northern FRT from Key Biscayne north showed from approximately 5% \n85 \nto 17% of 62 sites with impacts to corals including dislodged and buried colonies, and at least one site with slabs of hardbottom \n2 to 5 m in size fractured and displaced several meters (Walker, 2018). Analyses of long-term monitoring-transect data at 40 \nsites throughout the Florida Keys National Marine Sanctuary (FKNMS) showed instantaneous losses in seagrass and \ncalcareous green macroalgae density after the storm passed, particularly in the Lower Florida Keys near where Hurricane Irma made landfall (Wilson et al., 2020). 1 Introduction While advances have been made in understanding long-term change in seafloor elevation and structure and its \npotential socioeconomic consequences, understanding the effects of event-driven changes to seafloor geomorphology due to \nstorms remains a major knowledge gap. 65 2 2 Hurricane Irma made landfall at Cudjoe Key in the Lower Florida Keys after passing directly over Looe Key Reef on 10 \n70 \nSeptember 2017 as a category 4 hurricane with maximum wind speeds of 213 km h-1 (115 kts) (Cangialosi et al., 2021) and \nsignificant wave heights of approximately 14 m a few kilometers offshore of the Florida Keys (Xian et al., 2018, Fig. 1a, b). Satellite imagery showed extensive sediment plumes throughout South Florida and the FRT caused by sediment resuspension \nand transport during the storm (Fig. 1c, d). The storm damaged up to 75% of buildings near its landfall point and caused \napproximately 50 billion USD of wind and water damage across the state of Florida (Xian et al., 2018; Cangialosi et al., 2021; \n75 approximately 50 billion USD of wind and water damage across the state of Florida (Xian et al., 2018; Cangialosi et al., 2021; \n75 \nNOAA, 2022b). Prior to Hurricane Irma, the most recent, direct impact to Looe Key Reef from a tropical storm was in 2008 \nduring Tropical Storm Fay (NOAA, 2022a). Numerous rapid assessments of seafloor habitats were conducted along the FRT in the weeks following Hurricane Irma. Diver-\nbased surveys of coral reefs at 57 locations along the FRT by the National Oceanic and Atmospheric Administration showed \n80 \nhighest levels of damage in the Middle to Lower Keys including dislodged and fractured corals, clogged and damaged sponges, \nheavy sedimentation, burial of corals, displaced rubble and sand, reef erosion, fractured substrate, and marine debris; 14% of \nsites showed severe impact, 33% showed moderate impact, and 53% showed minimal impact (Viehman et al., 2018). Looe \nKey Reef, located near the hurricane landfall location, showed more than 26% prevalence of hurricane-impacted corals (Florida \nResilience Program, 2017). Similar surveys along the northern FRT from Key Biscayne north showed from approximately 5% \n85 \nto 17% of 62 sites with impacts to corals including dislodged and buried colonies, and at least one site with slabs of hardbottom \n2 to 5 m in size fractured and displaced several meters (Walker, 2018). Analyses of long-term monitoring-transect data at 40 \nsites throughout the Florida Keys National Marine Sanctuary (FKNMS) showed instantaneous losses in seagrass and \ncalcareous green macroalgae density after the storm passed, particularly in the Lower Florida Keys near where Hurricane Irma \nmade landfall (Wilson et al., 2020). Additionally, several locations showed moderate burial of seagrass with up to 5 to 10 cm \n90 \nof sand, while other locations showed heavy erosion or moderate seagrass canopy thinning (Wilson et al., 2020). Reef Visual \nCensus (RVC) surveys including structure from motion (SfM) habitat photogrammetry at sites in the Lower Florida Keys from \nFebruary 2017 to December 2018 showed a 30% decrease in macroalgae at the Looe Key Sanctuary Preservation Area (SPA) \nand a 30% increase at the Looe Key Special Use Area (SPU) post Irma; while both Looe Key locations showed a 10% decrease \nin live coral cover and a 20% increase in octocoral cover (Simmons et al., 2022). Comparison of restored (outplant) coral \n95 \nsurvival rates at two fore reef and two patch reef sites near Tavernier Key in the Upper Florida Keys showed approximately \n85% outplant survival at all locations prior to the passage of Hurricane Irma; however, no outplants survived at the fore reef \nsites and only 51% of outplants survived at the patch reef sites post-Irma, the difference likely due to protection of the patch \nreefs from dissipation of wave energy by the reef crest (Lohr et al., 2020). Examination of Diadema antillarum sea urchins (a Numerous rapid assessments of seafloor habitats were conducted along the FRT in the weeks following Hurricane Irma. Diver-\nbased surveys of coral reefs at 57 locations along the FRT by the National Oceanic and Atmospheric Administration showed \n80 \nhighest levels of damage in the Middle to Lower Keys including dislodged and fractured corals, clogged and damaged sponges, \nheavy sedimentation, burial of corals, displaced rubble and sand, reef erosion, fractured substrate, and marine debris; 14% of \nsites showed severe impact, 33% showed moderate impact, and 53% showed minimal impact (Viehman et al., 2018). Looe \nKey Reef, located near the hurricane landfall location, showed more than 26% prevalence of hurricane-impacted corals (Florida Numerous rapid assessments of seafloor habitats were conducted along the FRT in the weeks following Hurricane Irma. Additionally, several locations showed moderate burial of seagrass with up to 5 to 10 cm \n90 \nof sand, while other locations showed heavy erosion or moderate seagrass canopy thinning (Wilson et al., 2020). Reef Visual \nCensus (RVC) surveys including structure from motion (SfM) habitat photogrammetry at sites in the Lower Florida Keys from \nFebruary 2017 to December 2018 showed a 30% decrease in macroalgae at the Looe Key Sanctuary Preservation Area (SPA) \nand a 30% increase at the Looe Key Special Use Area (SPU) post Irma; while both Looe Key locations showed a 10% decrease in live coral cover and a 20% increase in octocoral cover (Simmons et al., 2022). Comparison of restored (outplant) coral \n95 \nsurvival rates at two fore reef and two patch reef sites near Tavernier Key in the Upper Florida Keys showed approximately \n85% outplant survival at all locations prior to the passage of Hurricane Irma; however, no outplants survived at the fore reef \nsites and only 51% of outplants survived at the patch reef sites post-Irma, the difference likely due to protection of the patch \nreefs from dissipation of wave energy by the reef crest (Lohr et al., 2020). Examination of Diadema antillarum sea urchins (a 3 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 100 re 1. Location of the Florida Keys Reef Tract, Hurricane Irma trackline and impact. (a) NOAA, National Weather Service WSR-\nradar image (decibels, DBZ) from south Florida on 10 September 2017 at 5:22 am Eastern Daylight Time (EDT) showing approach of\nicane Irma (inset black line = hurricane trackline). (b) Significant wave height (m) from the U.S. Geological Survey (USGS) Coupled\nan, Atmosphere, Wave, Sediment Transport (COAWST) model on 10 September 2017 at 5:00 am EDT (Warner et al., 2010, image\nit: Patricia Dalyander, USGS). (c) Satellite imagery from 30 August 2017, 11 days prior to landfall of Hurricane Irma in the Florida\ns (NASA, 2023, EOSDIS Worldview Imagery). (d) Satellite imagery from 13 September 2017, 3 days after Hurricane Irma landfall in\nFlorida Keys showing extensive resuspended sediment plume (NASA, 2023, EOSDIS Worldview Imagery). Red boxes show the location\nooe Key Reef relative to other reefs along the reef tract Figure 1. Location of the Florida Keys Reef Tract, Hurricane Irma trackline and impact. https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 key reef grazer) density, size structure, and coral reef community structure before and 2.5 months after Irma at 10 locations in \n110 \nthe Middle and Upper Florida Keys showed a significant decrease in D. antillarum density with increased sedimentation, \nsuggesting sediment transport caused mortality through abrasion and burial (Kobelt et al. 2019). key reef grazer) density, size structure, and coral reef community structure before and 2.5 months after Irma at 10 locations in \n110 \nthe Middle and Upper Florida Keys showed a significant decrease in D. antillarum density with increased sedimentation, \nsuggesting sediment transport caused mortality through abrasion and burial (Kobelt et al. 2019). While observational data from several locations indicate seafloor sediments were transporte While observational data from several locations indicate seafloor sediments were transported and likely caused damage to \nbenthic habitats, the direct impact of Hurricane Irma or other tropical storms on seafloor elevation and geomorphologic \n115 \nstructures has not previously been quantified along the FRT. In this study, we used high-resolution light-detection-and-ranging \n(lidar) and multibeam bathymetry data collected before and after the passage of Hurricane Irma to quantify seafloor elevation \nand volume change of benthic habitats and geomorphological structures resulting from the storm’s impact and post-storm re-\nequilibration of seafloor sediments at more than 4-million point-locations at the Looe Key Reef system in the Lower FRT. benthic habitats, the direct impact of Hurricane Irma or other tropical storms on seafloor elevation and geomorphologic \n115 \nstructures has not previously been quantified along the FRT. In this study, we used high-resolution light-detection-and-ranging \n(lidar) and multibeam bathymetry data collected before and after the passage of Hurricane Irma to quantify seafloor elevation \nand volume change of benthic habitats and geomorphological structures resulting from the storm’s impact and post-storm re-\nequilibration of seafloor sediments at more than 4-million point-locations at the Looe Key Reef system in the Lower FRT. 2.1 Looe Key Reef Study Site The FRT is the only living coral barrier reef in the continental United States, and it spans more than 580 km along the east \ncoast of Florida from St. Lucie Inlet to the Dry Tortugas, with total reef area of approximately 1,179 km2 (Finkl and Andrews, \n2008; Jackson et al., 2014; Florida Department of Environmental Protection, 2022). Water depth along the FRT is up to approximately 20 m with discontinuous spur and groove formations and patch reefs separated by tidal passes, and it is \n125 \ncharacterized by both coral-dominated and non-coral dominated seafloor habitat as characterized and mapped by the Florida \nFish and Wildlife Conservation Commission-Fish and Wildlife Research Institute (FWC, 2015). Much of the FRT is protected \nby the FKNMS, Biscayne National Park, and Dry Tortugas National Park, and includes several sanctuary preservation areas \n(SPAs) and special use areas (SPUs) within FKNMS, including the Looe Key SPA and SPU, that together protect over 6000 approximately 20 m with discontinuous spur and groove formations and patch reefs separated by tidal passes, and it is \n125 \ncharacterized by both coral-dominated and non-coral dominated seafloor habitat as characterized and mapped by the Florida \nFish and Wildlife Conservation Commission-Fish and Wildlife Research Institute (FWC, 2015). Much of the FRT is protected \nby the FKNMS, Biscayne National Park, and Dry Tortugas National Park, and includes several sanctuary preservation areas \n(SPAs) and special use areas (SPUs) within FKNMS, including the Looe Key SPA and SPU, that together protect over 6000 marine species (Keller and Donahue, 2006). Looe Key Reef is a barrier bank reef located approximately 10 km offshore in the \n130 \nLower Florida Keys, south of Cudjoe Key, and it is characterized by a prominent, shallow reef crest with two extensive coral \nrubble fields, a fore reef with a spur-and-groove formation, a forereef terrace and deep reef zone, and a back reef area with \nseagrass communities, patch reefs, and individual coral heads (Fig. 2a-d). Seagrass beds and sandflats with intermittent patch \nreefs extend shoreward from Looe Key Reef proper to Hawk Channel, approximately 2 km to the north. Looe Key SPA, marine species (Keller and Donahue, 2006). (a) NOAA, National Weather Service WSR-\n88D radar image (decibels, DBZ) from south Florida on 10 September 2017 at 5:22 am Eastern Daylight Time (EDT) showing approach of \nHurricane Irma (inset black line = hurricane trackline). (b) Significant wave height (m) from the U.S. Geological Survey (USGS) Coupled \nOcean, Atmosphere, Wave, Sediment Transport (COAWST) model on 10 September 2017 at 5:00 am EDT (Warner et al., 2010, image \ncredit: Patricia Dalyander, USGS). (c) Satellite imagery from 30 August 2017, 11 days prior to landfall of Hurricane Irma in the Florida \nKeys (NASA, 2023, EOSDIS Worldview Imagery). (d) Satellite imagery from 13 September 2017, 3 days after Hurricane Irma landfall in \nthe Florida Keys showing extensive resuspended sediment plume (NASA, 2023, EOSDIS Worldview Imagery). Red boxes show the location \nof Looe Key Reef relative to other reefs along the reef tract. 105 4 2.1 Looe Key Reef Study Site Looe Key Reef is a barrier bank reef located approximately 10 km offshore in the \n130 \nLower Florida Keys, south of Cudjoe Key, and it is characterized by a prominent, shallow reef crest with two extensive coral \nrubble fields, a fore reef with a spur-and-groove formation, a forereef terrace and deep reef zone, and a back reef area with \nseagrass communities, patch reefs, and individual coral heads (Fig. 2a-d). Seagrass beds and sandflats with intermittent patch \nreefs extend shoreward from Looe Key Reef proper to Hawk Channel, approximately 2 km to the north. Looe Key SPA, located at approximately 24° 32' N, 81° 24' W, is just over 18 km2 and surrounds LKR proper which is less than 1.7 km2. Looe \n135 \nKey Reef contains a coral nursery and several restoration sites for coral outplants; it is one of seven FKNMS iconic reefs, and \nthe focus of a major collaborative habitat restoration effort known as Mission: Iconic reefs (NOAA Fisheries, 2022). located at approximately 24° 32' N, 81° 24' W, is just over 18 km2 and surrounds LKR proper which is less than 1.7 km2. Looe \n135 \nKey Reef contains a coral nursery and several restoration sites for coral outplants; it is one of seven FKNMS iconic reefs, and \nthe focus of a major collaborative habitat restoration effort known as Mission: Iconic reefs (NOAA Fisheries, 2022). 5\nThe northeastern eyewall of Hurricane Irma passed directly over LKR with the storm’s center passing approximately 9 km \nwest of LKR. However, the storm was approximately 684 km in diameter and covered the entire FRT and much of South \n140 \nFlorida. The National Weather Service’s technical summary of the storm reported tropical storm force winds more than 640 The northeastern eyewall of Hurricane Irma passed directly over LKR with the storm’s center passing approximately 9 km 5\nwest of LKR. However, the storm was approximately 684 km in diameter and covered the entire FRT and much of South \n140 \nFlorida. The National Weather Service’s technical summary of the storm reported tropical storm force winds more than 640 5\nwest of LKR. However, the storm was approximately 684 km in diameter and covered the entire FRT and much of South \n140 \nFlorida. The National Weather Service’s technical summary of the storm reported tropical storm force winds more than 640 5 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 km away from the storm’s center, and hurricane force winds more than 125 km from the storm’s center (NWS, 2022b). Gale \nforce winds (sustained winds above 63 km h-1) were detected by the evening of 9 September 2017 at the National Oceanic and \nAtmospheric Administration - National Ocean Service (NOAA-NOS), Tides and Currents Station at Vaca Key (number \n8723970), 35 km to the northeast of LKR; maximum sustained winds of 213 km h-1 were reported as the storm made landfall, 155 and latent gale force winds were detected after the storm passed on the evening of 10 September 2017 (NOAA-NOS, 2023). 155 \nThe average wind direction for this period was 67.01 degrees indicating winds moved from ENE toward WSW. Wind speeds \nfell sharply below gale force after the storm, shifting north eastward. Wind conditions were relatively quiescent from July \n2016 through January 2019 (except during Hurricane Irma) with wind speeds occasionally ranging up to approximately 56 km \nh-1 during winter storms (NOAA-NOS, 2023). and latent gale force winds were detected after the storm passed on the evening of 10 September 2017 (NOAA-NOS, 2023). 155 \nThe average wind direction for this period was 67.01 degrees indicating winds moved from ENE toward WSW. Wind speeds \nfell sharply below gale force after the storm, shifting north eastward. Wind conditions were relatively quiescent from July \n2016 through January 2019 (except during Hurricane Irma) with wind speeds occasionally ranging up to approximately 56 km \nh-1 during winter storms (NOAA-NOS, 2023). https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 gure 2. Looe Key Reef location, bathymetry, and seafloor habitats. (a) Location of the Florida Keys along the southern coast of Florida, \nckline of Hurricane Irma and the location of its landfall (red box). (b) Proximity of Hurricane Irma’s trackline to the Looe Key Reef study \ne (purple box), location of landfall at Cudjoe Key, and location of Vaca Key where the nearest NOAA-NOS (2023) Tides and Currents \ntion was located. (c) 2016 lidar bathymetric map of the Looe Key Reef study site showing location of Florida Keys National Marine \nnctuary Special Preservation Area (SPA), Special Use Area (SPU), and geomorphic features of focused investigation for this study. (d) \nbitat distribution at the Looe Key Study site from Florida Fish and Wildlife Conservation Commission-Fish and Wildlife Research \ntitute (2015). Figure 2. Looe Key Reef location, bathymetry, and seafloor habitats. (a) Location of the Florida Keys along the southern coast of Florida, \ntrackline of Hurricane Irma and the location of its landfall (red box). (b) Proximity of Hurricane Irma’s trackline to the Looe Key Reef study \nsite (purple box), location of landfall at Cudjoe Key, and location of Vaca Key where the nearest NOAA-NOS (2023) Tides and Currents \n145 \nstation was located. (c) 2016 lidar bathymetric map of the Looe Key Reef study site showing location of Florida Keys National Marine \nSanctuary Special Preservation Area (SPA), Special Use Area (SPU), and geomorphic features of focused investigation for this study. (d) \nHabitat distribution at the Looe Key Study site from Florida Fish and Wildlife Conservation Commission-Fish and Wildlife Research \nInstitute (2015). 150 150 6 The 2016 lidar DEM refers to data that were collected on 23 July 2016 (13.5 months before the passage of Hurricane Irma) by \nthe NOAA Office for Coastal Management, National Geodetic Survey, Topobathy Lidar Dem Block 1 dataset (Office for \nCoastal Management, 2017). The 2017 multibeam DEM refers to multibeam bathymetry data collected by the U.S. Geological \nSurvey in December 2017, and February–March 2018 at Looe Key Reef (between three and six months after the passage of \nHurricane Irma), specifically to examine impacts from the storm (Fredericks et al., 2019). The 2019 lidar DEM refers to data \n170 \ncollected January 8–31, 2019 by NOAA NGS Topobathy Lidar DEM Hurricane Irma: Miami to Marquesas Keys, FL dataset \n(National Geodetic Survey, 2022). The Florida Fish and Wildlife Conservation Commission (FWC) Unified Florida Reef Tract \n(UFRT) Map version 2.0, Level 2 habitat categories (FWC, 2015) were used to delineate geographic boundaries for 10 habitat 2.2 Elevation and Habitat Data \n160 Three Digital Elevation Models (DEMs) derived from lidar or multibeam bathymetric surveys were used for seafloor elevation- \nand volume-change analyses and are referenced in this study as 2016 lidar, 2017 multibeam, and 2019 lidar (Table 1). Table 1: Elevation datasets used in this analysis; collection dates are specific to the geographic extent of this study. Digital Elevation Model \nSource \nCollection Dates \nHorizontal Resolution/ \nVertical RMSE \n(meters/meters) \n2016 NOAA NGS Topobathy \nLidar DEM:Florida Keys \nOuter Reef Block 01 \nOffice for \nCoastal \nManagement, \n2017 \n23 July 2016 \n \n1.0/0.15 \nMultibeam bathymetry data \ncollected in December 2017, \nFebruary and March 2018 at \nLooe Key, the Florida Keys \nFredericks et al, \n2019 \nLeg 1: 12 December 2017 – 16 December 2017 \nLeg 2: 2 February 2018 – 9 February 2018 \nLeg 3: 9 March 2018 –11 March 2018 \n \n1.0/0.14 \n2018-2019 NOAA NGS \nTopobathy Lidar Hurricane \nIrma: Miami to Marquesas \nKeys, FL \nNational \nGeodetic Survey, \n2022 \n8 January 2019– 31 January 2019 \n \n1.0/0.11 \nRMSE = root mean square error. 165 165 The 2016 lidar DEM refers to data that were collected on 23 July 2016 (13.5 months before the passage of Hurricane Irma) by \nthe NOAA Office for Coastal Management, National Geodetic Survey, Topobathy Lidar Dem Block 1 dataset (Office for \nCoastal Management, 2017). The 2017 multibeam DEM refers to multibeam bathymetry data collected by the U.S. Geological \nSurvey in December 2017, and February–March 2018 at Looe Key Reef (between three and six months after the passage of \nHurricane Irma), specifically to examine impacts from the storm (Fredericks et al., 2019). The 2019 lidar DEM refers to data \n170 \ncollected January 8–31, 2019 by NOAA NGS Topobathy Lidar DEM Hurricane Irma: Miami to Marquesas Keys, FL dataset \n(National Geodetic Survey, 2022). The Florida Fish and Wildlife Conservation Commission (FWC) Unified Florida Reef Tract \n(UFRT) Map version 2.0, Level 2 habitat categories (FWC, 2015) were used to delineate geographic boundaries for 10 habitat The 2016 lidar DEM refers to data that were collected on 23 July 2016 (13.5 months before the passage of Hurricane Irma) by \nthe NOAA Office for Coastal Management, National Geodetic Survey, Topobathy Lidar Dem Block 1 dataset (Office for \nCoastal Management, 2017). The 2017 multibeam DEM refers to multibeam bathymetry data collected by the U.S. https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 types within the LKR study site (Fig. 2d). Habitat labelled as ‘not classified’ was indistinguishable during mapping due to \nturbidity, cloud cover, water depth, or other interferences with obtaining an optical signature of the seafloor (Zitello et al., \n175 \n2009). turbidity, cloud cover, water depth, or other interferences with obtaining an optical signature of the seafloor (Zitello et al., \n175 \n2009). turbidity, cloud cover, water depth, or other interferences with obtaining an optical signature of the seafloor (Zitello et al., \n175 \n2009). 2.2 Elevation and Habitat Data \n160 Geological \nSurvey in December 2017, and February–March 2018 at Looe Key Reef (between three and six months after the passage of Hurricane Irma), specifically to examine impacts from the storm (Fredericks et al., 2019). The 2019 lidar DEM refers to data \n170 \ncollected January 8–31, 2019 by NOAA NGS Topobathy Lidar DEM Hurricane Irma: Miami to Marquesas Keys, FL dataset \n(National Geodetic Survey, 2022). The Florida Fish and Wildlife Conservation Commission (FWC) Unified Florida Reef Tract \n(UFRT) Map version 2.0, Level 2 habitat categories (FWC, 2015) were used to delineate geographic boundaries for 10 habitat Hurricane Irma), specifically to examine impacts from the storm (Fredericks et al., 2019). The 2019 lidar DEM refers to data \n170 \ncollected January 8–31, 2019 by NOAA NGS Topobathy Lidar DEM Hurricane Irma: Miami to Marquesas Keys, FL dataset \n(National Geodetic Survey, 2022). The Florida Fish and Wildlife Conservation Commission (FWC) Unified Florida Reef Tract \n(UFRT) Map version 2.0, Level 2 habitat categories (FWC, 2015) were used to delineate geographic boundaries for 10 habitat 7 7 2.3 Elevation- and Volume-Change Analyses A 2-m XY grid was created in Global Mapper and clipped to the same footprint. Elevation values were then extracted \nfrom each of the three DEMs at the center points of co-aligned 2-m grid boxes. Elevation change between time periods was \ncalculated for each of 4,007,961 paired elevation values (e.g., 2017 elevation – 2016 elevation, and 2019 elevation – 2017 extent of each DEM was then clipped to the areal extent of the common overlapping footprint prior to elevation change analysis \n185 \nusing the ‘Clip’ tool in ArcMap. The following steps were performed in Global Mapper 22.1 due to file size limitations in \nArcMap. A 2-m XY grid was created in Global Mapper and clipped to the same footprint. Elevation values were then extracted \nfrom each of the three DEMs at the center points of co-aligned 2-m grid boxes. Elevation change between time periods was \ncalculated for each of 4,007,961 paired elevation values (e.g., 2017 elevation – 2016 elevation, and 2019 elevation – 2017 elevation). Elevation-change (XYZ) point maps were generated as shapefiles for each time-period of change for the total study \n190 \nsite; positive values indicate an increase in elevation and negative values indicate a decrease in elevation. Data are available \nfrom Fehr et al. (2021). Vertical uncertainty of elevation change analyses were estimated using methods of Yates et al. 2017 \nand the reported vertical accuracy of the lidar and multibeam data sets (typically reported as the 95% root-mean-square error, \nRMSE, Table 1) to calculate a composite RMSE (RMSETotal) for each elevation change analysis (Fig. 3b). The RMSE of lidar and multibeam data sets used for elevation-change analyses in our study ranged from 0.11 to 0.15 m (Table 1). These values \n195 \nare consistent with RMSEs determined in performance evaluations of lidar sensors that ranged from 0.08 to 0.52 m (Fernandez-\nDiaz et al., 2014; Legleiter et al., 2016; Kinzel et al., 2013; Tonina et al., 2019; Yoshida et al., 2022). Composite RMSE values \nfor elevation-change analyses based on comparison of lidar to multibeam DEMs ranged from 0.19 to 0.21m in our study. These \nvalues are consistent with RMSEs determined in performance evaluations of lidar sensors against multibeam echosounders and multibeam data sets used for elevation-change analyses in our study ranged from 0.11 to 0.15 m (Table 1). 2.3 Elevation- and Volume-Change Analyses The RMSE of lidar \nand multibeam data sets used for elevation-change analyses in our study ranged from 0.11 to 0.15 m (Table 1). These values \n195 \nare consistent with RMSEs determined in performance evaluations of lidar sensors that ranged from 0.08 to 0.52 m (Fernandez-\nDiaz et al., 2014; Legleiter et al., 2016; Kinzel et al., 2013; Tonina et al., 2019; Yoshida et al., 2022). Composite RMSE values \nfor elevation-change analyses based on comparison of lidar to multibeam DEMs ranged from 0.19 to 0.21m in our study. These \nvalues are consistent with RMSEs determined in performance evaluations of lidar sensors against multibeam echosounders \nthat ranged from 0.02 to 0.23 m (Awadallah et al., 2023). The FWC UFRT habitat map was clipped to the intersect footprint \n200 \nfor each elevation-change analysis using ArcMap 10.7. Each total-study-site elevation-change data set was then clipped to \nindividual habitat polygons to create individual elevation-change shapefiles for each habitat type. of the three 1-m resolution digital elevation models (DEMs) in ArcMap 10.7 and were used to create a common footprint \n180 \npolygon shapefile for the total LKR study site encompassing the overlapping area among the three datasets. The original (full \nareal extent, or unclipped) 2016–2017 elevation-change data set was 19.71 km2 and included 4,934,364 data points. The \noverlapping areal extent for the 2016, 2017, and 2019 DEMs was 15.98 km2 and excluded areas where water depths were too \nshallow for boat access to collect multibeam data in 2017 and areas of coarse interpolation within the 2017 DEM. The areal of the three 1-m resolution digital elevation models (DEMs) in ArcMap 10.7 and were used to create a common footprint \n180 \npolygon shapefile for the total LKR study site encompassing the overlapping area among the three datasets. The original (full \nareal extent, or unclipped) 2016–2017 elevation-change data set was 19.71 km2 and included 4,934,364 data points. The \noverlapping areal extent for the 2016, 2017, and 2019 DEMs was 15.98 km2 and excluded areas where water depths were too \nshallow for boat access to collect multibeam data in 2017 and areas of coarse interpolation within the 2017 DEM. The areal 180 extent of each DEM was then clipped to the areal extent of the common overlapping footprint prior to elevation change analysis \n185 \nusing the ‘Clip’ tool in ArcMap. The following steps were performed in Global Mapper 22.1 due to file size limitations in \nArcMap. 2.3 Elevation- and Volume-Change Analyses Seafloor elevation- and volume-change analyses were conducted using the methods of Yates et al. techniques of Murphy et al. (2022) (Fig. 3a). Briefly, individual geographic footprint areas (poly Seafloor elevation- and volume-change analyses were conducted using the methods of Yates et al. (2017) and 2-m grid spacing \ntechniques of Murphy et al. (2022) (Fig. 3a). Briefly, individual geographic footprint areas (polygons) were created for each Seafloor elevation- and volume-change analyses were conducted using the methods of Yates et al. (2017) and 2-m grid spacing \ntechniques of Murphy et al. (2022) (Fig. 3a). Briefly, individual geographic footprint areas (polygons) were created for each \nof the three 1-m resolution digital elevation models (DEMs) in ArcMap 10.7 and were used to create a common footprint \n180 \npolygon shapefile for the total LKR study site encompassing the overlapping area among the three datasets. The original (full \nareal extent, or unclipped) 2016–2017 elevation-change data set was 19.71 km2 and included 4,934,364 data points. The \noverlapping areal extent for the 2016, 2017, and 2019 DEMs was 15.98 km2 and excluded areas where water depths were too \nshallow for boat access to collect multibeam data in 2017 and areas of coarse interpolation within the 2017 DEM. The areal \nextent of each DEM was then clipped to the areal extent of the common overlapping footprint prior to elevation change analysis \n185 \nusing the ‘Clip’ tool in ArcMap. The following steps were performed in Global Mapper 22.1 due to file size limitations in \nArcMap. A 2-m XY grid was created in Global Mapper and clipped to the same footprint. Elevation values were then extracted \nfrom each of the three DEMs at the center points of co-aligned 2-m grid boxes. Elevation change between time periods was \ncalculated for each of 4,007,961 paired elevation values (e.g., 2017 elevation – 2016 elevation, and 2019 elevation – 2017 \nelevation). Elevation-change (XYZ) point maps were generated as shapefiles for each time-period of change for the total study \n190 \nsite; positive values indicate an increase in elevation and negative values indicate a decrease in elevation. Data are available \nfrom Fehr et al. (2021). Vertical uncertainty of elevation change analyses were estimated using methods of Yates et al. 2017 \nand the reported vertical accuracy of the lidar and multibeam data sets (typically reported as the 95% root-mean-square error, \nRMSE, Table 1) to calculate a composite RMSE (RMSETotal) for each elevation change analysis (Fig. 3b). 2.3 Elevation- and Volume-Change Analyses These values \n195 \nare consistent with RMSEs determined in performance evaluations of lidar sensors that ranged from 0.08 to 0.52 m (Fernandez-\nDiaz et al., 2014; Legleiter et al., 2016; Kinzel et al., 2013; Tonina et al., 2019; Yoshida et al., 2022). Composite RMSE values \nfor elevation-change analyses based on comparison of lidar to multibeam DEMs ranged from 0.19 to 0.21m in our study. These \nvalues are consistent with RMSEs determined in performance evaluations of lidar sensors against multibeam echosounders that ranged from 0.02 to 0.23 m (Awadallah et al., 2023). The FWC UFRT habitat map was clipped to the intersect footprint \n200 \nfor each elevation-change analysis using ArcMap 10.7. Each total-study-site elevation-change data set was then clipped to \nindividual habitat polygons to create individual elevation-change shapefiles for each habitat type. that ranged from 0.02 to 0.23 m (Awadallah et al., 2023). The FWC UFRT habitat map was clipped to the intersect footprint \n200 \nfor each elevation-change analysis using ArcMap 10.7. Each total-study-site elevation-change data set was then clipped to \nindividual habitat polygons to create individual elevation-change shapefiles for each habitat type. Elevation-change data from each time-period were then used to generate TIN (Triangulated Irregular Network) surface mode Elevation-change data from each time-period were then used to generate TIN (Triangulated Irregular Network) surface models \nin ArcMap for calculation of volume change. TIN models were clipped to the original overall study site intersect footprint to \n205 \nremove interpolation across areas where no data were collected. Lower bound (conservative) volume-change was calculated Elevation-change data from each time-period were then used to generate TIN (Triangulated Irregular Network) surface models in ArcMap for calculation of volume change. TIN models were clipped to the original overall study site intersect footprint to \n205 \nremove interpolation across areas where no data were collected. Lower bound (conservative) volume-change was calculated in ArcMap for calculation of volume change. TIN models were clipped to the original overall study site intersect footprint to \n205 \nremove interpolation across areas where no data were collected. Lower bound (conservative) volume-change was calculated 8 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 𝑅𝑀𝑆𝐸𝑡𝑜𝑡𝑎𝑙= √(𝑅𝑀𝑆𝐸𝑆𝑜𝑢𝑟𝑐𝑒 𝐷𝑎𝑡𝑎𝑠𝑒𝑡 1\n2\n+ 𝑅𝑀𝑆𝐸𝑆𝑜𝑢𝑟𝑐𝑒 𝐷𝑎𝑡𝑎𝑠𝑒𝑡 2\n2\n) 𝑅𝑀𝑆𝐸𝑡𝑜𝑡𝑎𝑙= √(𝑅𝑀𝑆𝐸𝑆𝑜𝑢𝑟𝑐𝑒 𝐷𝑎𝑡𝑎𝑠𝑒𝑡 1\n2\n+ 𝑅𝑀𝑆𝐸𝑆𝑜𝑢𝑟𝑐𝑒 𝐷𝑎𝑡𝑎𝑠𝑒𝑡 2\n2\n) \nation and volume change methods. 2.3 Elevation- and Volume-Change Analyses (a) Flowchart outlining generalized geoprocessing steps in ArcMap and Global \nh 3), and in the Seafloor Elevation Change Analysis Tool (SECAT, step 4) for seafloor elevation and volume change \ns et al. (2017), Murphy et al. (2022), and Zieg and Zawada (2021). (b) Composite RMSE (RMSETotal) for each \nis (2016 to 2017 and 2017 to 2019) calculated using reported RMSE for lidar and multibeam source data and methods \nBlack boxes indicate source data files. Blue boxes indicate steps using geoprocessing tools from ArcMap or Global \ndicate data analysis conducted using SECAT. 𝑅𝑀𝑆𝐸𝑡𝑜𝑡𝑎𝑙= √(𝑅𝑀𝑆𝐸𝑆𝑜𝑢𝑟𝑐𝑒 𝐷𝑎𝑡𝑎𝑠𝑒𝑡 1\n2\n+ 𝑅𝑀𝑆𝐸𝑆𝑜𝑢𝑟𝑐𝑒 𝐷𝑎𝑡𝑎𝑠𝑒𝑡 2\n2\n) \nand volume change methods. (a) Flowchart outlining generalized geoprocessin\nnd in the Seafloor Elevation Change Analysis Tool (SECAT, step 4) for seafloor\nl. (2017), Murphy et al. (2022), and Zieg and Zawada (2021). (b) Composite\n6 to 2017 and 2017 to 2019) calculated using reported RMSE for lidar and multib\nboxes indicate source data files. Blue boxes indicate steps using geoprocessing \ndata analysis conducted using SECAT. 𝑅𝑀𝑆𝐸𝑡𝑜𝑡𝑎𝑙= √(𝑅𝑀𝑆𝐸𝑆𝑜𝑢𝑟𝑐𝑒 𝐷𝑎𝑡𝑎𝑠𝑒𝑡 1\n2\n+ 𝑅𝑀𝑆𝐸𝑆𝑜𝑢𝑟𝑐𝑒 𝐷𝑎𝑡𝑎𝑠𝑒𝑡 2\n2\n) 𝑅𝑀𝑆𝐸𝑡𝑜𝑡𝑎𝑙= √(𝑅𝑀𝑆𝐸𝑆𝑜𝑢\n2 𝑅𝑀𝑆𝐸𝑡𝑜𝑡𝑎𝑙= √(𝑅𝑀𝑆𝐸𝑆𝑜𝑢𝑟𝑐𝑒 𝐷𝑎𝑡𝑎𝑠𝑒𝑡 1\n2\n+ 𝑅𝑀𝑆𝐸𝑆𝑜𝑢𝑟𝑐𝑒 𝐷𝑎𝑡𝑎𝑠𝑒𝑡 2\n2\n) Figure 3. Seafloor elevation and volume change methods. (a) Flowchart outlining generalized geop\n0 Figure 3. Seafloor elevation and volume change methods. (a) Flowchart outlining generalized geoprocessing steps in ArcMap and Global \nMapper (steps 1 through 3), and in the Seafloor Elevation Change Analysis Tool (SECAT, step 4) for seafloor elevation and volume change \n210 \nanalyses based on Yates et al. (2017), Murphy et al. (2022), and Zieg and Zawada (2021). (b) Composite RMSE (RMSETotal) for each \nelevation change analysis (2016 to 2017 and 2017 to 2019) calculated using reported RMSE for lidar and multibeam source data and methods \nof Yates et al. (2017). Black boxes indicate source data files. Blue boxes indicate steps using geoprocessing tools from ArcMap or Global \nMapper. Green boxes indicate data analysis conducted using SECAT. Figure 3. Seafloor elevation and volume change methods. (a) Flowchart outlining generalized geoprocessing steps in ArcMap and Global \nMapper (steps 1 through 3), and in the Seafloor Elevation Change Analysis Tool (SECAT, step 4) for seafloor elevation and volume change \n210 \nanalyses based on Yates et al. (2017), Murphy et al. (2022), and Zieg and Zawada (2021). 2.4 Geomorphic Feature Analyses Sub-areas or geomorphic features of high-magnitude elevation change (greater than approximately ±0.5 m) were delineated \non each total-study-site elevation-change point map by manually drawing polygons in ArcMap 10.7 and creating elevation-\nchange shapefiles for each sub-area. Each sub-area was clipped to individual habitat polygons to create individual shapefiles \n230 \nfor each habitat type within a given sub-area. Elevation- volume-change statistics were computed for each geomorphic feature \nof interest, and each habitat within sub-areas of interest using SECAT and methods described in section 2.3. Sub-areas or geomorphic features of high-magnitude elevation change (greater than approximately ±0.5 m) were delineated \non each total-study-site elevation-change point map by manually drawing polygons in ArcMap 10.7 and creating elevation-\nchange shapefiles for each sub-area. Each sub-area was clipped to individual habitat polygons to create individual shapefiles \n230 \nfor each habitat type within a given sub area Elevation volume change statistics were computed for each geomorphic feature Sub-areas or geomorphic features of high-magnitude elevation change (greater than approximately ±0.5 m) were delineated \non each total-study-site elevation-change point map by manually drawing polygons in ArcMap 10.7 and creating elevation- on each total study site elevation change point map by manually drawing polygons in ArcMap 10.7 and creating elevation\nchange shapefiles for each sub-area. Each sub-area was clipped to individual habitat polygons to create individual shapefiles \n230 \nfor each habitat type within a given sub-area. Elevation- volume-change statistics were computed for each geomorphic feature \nof interest, and each habitat within sub-areas of interest using SECAT and methods described in section 2.3. We examined elevation and elevation-change along four 200 to 300 m transects across exam We examined elevation and elevation-change along four 200 to 300 m transects across examples of high-elevation change \ngeomorphic features. Elevation profiles for 2016, 2017, and 2019 were created for each feature of interest by extracting \n235 \nelevation values from each DEM along transect lines across the areas of greatest elevation change for each feature using \nArcMap. Points were selected using the Select Feature by Line tool in ArcMap, and the selected features were then exported \nas a new shapefile. Positions and types of geomorphic features of interest were verified through in-situ observation by SCUBA \ndivers using methods of Fehr and Yates (2020) at 30 diver reconnaissance sites throughout the total study site. https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 based on areal volume above and below surface plane heights corresponding to plus and minus the RMSETotal of the elevation \nchange analysis (RMSETotal = 21 cm for 2016 to 2017, and 19 cm for 2017 to 2019 change analyses). Upper bound volume \nchanges were calculated based on area volume above and below a plane height of 0 m. The attribute values stored within the \nelevation-change and TIN surface shapefiles were then used to compute elevation and volume change statistics for the total LKR study site and each habitat type using the Seafloor Elevation Change Analysis Tool (SECAT) custom Python script of \n220 \nZieg and Zawada (2021). Pearson correlation and linear regression analyses were performed using Microsoft Excel Version \n2302 (build 16.0.16130.20690) to assess relationships between mean habitat water depth, elevation change, and area-\nnormalized volume change for each habitat type including: 1) 2016 mean water depth (estimated from mean elevation) and \nmean elevation change; 2) 2016 mean water depth and area-normalized volume change; 3) 2017 mean water depth and mean LKR study site and each habitat type using the Seafloor Elevation Change Analysis Tool (SECAT) custom Python script of \n220 \nZieg and Zawada (2021). Pearson correlation and linear regression analyses were performed using Microsoft Excel Version \n2302 (build 16.0.16130.20690) to assess relationships between mean habitat water depth, elevation change, and area-\nnormalized volume change for each habitat type including: 1) 2016 mean water depth (estimated from mean elevation) and \nmean elevation change; 2) 2016 mean water depth and area-normalized volume change; 3) 2017 mean water depth and mean elevation change; 4) 2017 mean water depth and area-normalized volume change; and 5) 2017 to 2019 mean elevation change \n225 \nand 2016 to 2017 mean elevation. 2.3 Elevation- and Volume-Change Analyses (b) Composite RMSE (RMSETotal) for each \nelevation change analysis (2016 to 2017 and 2017 to 2019) calculated using reported RMSE for lidar and multibeam source data and methods \nof Yates et al. (2017). Black boxes indicate source data files. Blue boxes indicate steps using geoprocessing tools from ArcMap or Global \nMapper. Green boxes indicate data analysis conducted using SECAT. 215 9 3.1 Elevation and Volume Change Analyses Elevation-change results for 4,007,961 point-locations at LKR between 2016–2017 (approximately 13.5 months before and 3 \nto 6 months after Hurricane Irma) and between 2017–2019 (from approximately 3 to 16.5 months after Hurricane Irma) are \nshown in Fig. 4a and b, respectively. Mean elevation-change for the total LKR study site from 2016–2017 was 0.34 m ± 0.21; \nand all ten habitat types (Fig. 4c) showed increases in mean elevation (accretion) ranging from 0.20 m to 0.54 m (Table 2). 245 \nLargest mean elevation changes were associated with ‘aggregate reef’ (mean 2016 elevation -13.41 m) and ‘not classified’ 10 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 Table 2. Elevation change data by habitat type associated with each period and geomorphic feature subarea. Habitat type \nTotal points \nArea Mean elevation (m) \nMean elevation change (m) (SD) \n(no.) \n(km2) \n2016 \n2017 \n2019 \n2016 to 2017 2017 to 2019 \nOverall Looe Key Study Site \n Total Study Site \n4007961 \n15.98 \n-8.87 \n-8.53 \n-8.69 \n0.34 (0.21) \n-0.15 (0.11) \n Aggregate Reef \n76647 \n0.30 \n-13.41 -12.91 \n-13.16 \n0.51 (0.20) \n-0.25 (0.20) \n Colonized Pavement \n750 \n0.0028 \n-10.65 -10.33 \n-10.44 \n0.32 (0.12) \n-0.11 (0.08) \n Individual or Aggregate Patch Reef \n54414 \n0.22 \n-8.66 \n-8.33 \n-8.51 \n0.34 (0.15) \n-0.19 (0.10) \n Not Classified \n6932 \n0.026 \n-15.84 -15.30 \n-15.55 \n0.54 (0.25) \n-0.25 (0.17) \n Pavement \n645001 \n2.57 \n-10.00 \n-9.62 \n-9.79 \n0.37 (0.16) \n-0.16 (0.11) \n Reef Rubble \n80987 \n0.32 \n-6.19 \n-5.99 \n-6.17 \n0.20 (0.36) \n-0.18 (0.12) \n Seagrass Continuous \n402458 \n1.60 \n-7.69 \n-7.42 \n-7.54 \n0.27 (0.18) \n-0.12 (0.09) \n Seagrass Discontinuous \n1067504 \n4.26 \n-7.24 \n-6.96 \n-7.10 \n0.28 (0.21) \n-0.14 (0.10) \n Spur and Groove \n184875 \n0.74 \n-9.82 \n-9.45 \n-9.65 \n0.37 (0.25) \n-0.19 (0.19) \n Unconsolidated Sediment \n1488416 \n5.94 \n-9.63 \n-9.26 \n-9.42 \n0.37 (0.21) \n-0.16 (0.09) \nSand Wave \n Total Accretion Area \n15336 \n0.060 \n-6.32 \n-5.53 \n-5.68 \n0.79 (0.45) \n-0.15 (0.12) \n Seagrass Discontinuous \n7345 \n0.029 \n-5.98 \n-5.08 \n-5.23 \n0.90 (0.49) \n-0.15 (0.13) \n Unconsolidated Sediment \n7991 \n0.031 \n-6.63 \n-5.95 \n-6.09 \n0.68 (0.37) \n-0.14 (0.10) \n Total Erosion Area \n11265 \n0.043 \n-5.40 \n-5.75 \n-5.90 \n-0.36 (0.28) \n-0.15 (0.06) \n Seagrass Discontinuous \n580 \n0.002 \n-5.72 \n-5.87 \n-6.02 \n-0.15 (0.15) \n-0.15 (0.08) \n Unconsolidated Sediment \n10685 \n0.041 \n-5.38 \n-5.74 \n-5.90 \n-0.37 (0.29) \n-0.15 (0.05) \nScour Marks \n Scour Mark 1 \n202 \n0.00071 \n-7.03 \n-7.51 \n-7.41 \n-0.49 (0.26) \n0.10 (0.12) \n Seagrass Discontinuous \n197 \n0.00071 \n-7.02 \n-7.51 \n-7.41 \n-0.49 (0.26) \n0.11 (0.12) \n Unconsolidated Sediment \n5 <0.00001 \n-7.34 \n-7.47 \n-7.52 \n-0.12 (0.03) \n-0.05 (0.02) \n Scour Mark 2 \n388 \n0.0014 \n-5.41 \n-5.91 \n-5.71 \n-0.50 (0.27) \n0.20 (0.20) \n Seagrass Continuous \n338 \n0.00124 \n-5.41 \n-5.94 \n-5.70 \n-0.53 (0.27) \n0.24 (0.18) \n Unconsolidated Sediment \n50 \n0.00016 \n-5.42 \n-5.67 \n-5.72 \n-0.26 (0.16) \n-0.05 (0.13) \n Scour Mark 3 \n518 \n0.00188 \n-5.64 \n-6.14 \n-6.02 \n-0.50 (0.29) \n0.12 (0.19) \n Seagrass Continuous \n518 \n0.00188 \n-5.64 \n-6.14 \n-6.02 \n-0.50 (0.29) \n0.12 (0.19) \n Scour Mark 4 \n417 \n0.00152 \n-5.20 \n-5.74 \n-5.63 \n-0.54 (0.28) \n0.12 (0.21) \n Seagrass Continuous \n411 \n0.00151 \n-5.19 \n-5.74 \n-5.62 \n-0.55 (0.27) \n0.12 (0.21) \n Unconsolidated Sediment \n6 \n0.00001 \n-5.69 \n-5.74 \n-5.84 \n-0.06 (0.05) \n-0.10 (0.05) \nReef Rubble Field \n Total Accretion Area \n7216 \n0.028 \n-4.22 \n-3.32 \n-3.57 \n0.89 (0.45) \n-0.24 (0.30) \n Reef Rubble \n3102 \n0.012 \n-3.71 \n-2.84 \n-3.05 \n0.87 (0.44) \n-0.21 (0.36) \n Seagrass Discontinuous \n3489 \n0.014 \n-4.66 \n-3.67 \n-3.97 \n0.99 (0.42) \n-0.30 (0.24) \n Unconsolidated Sediment \n628 \n0.00237 \n-4.25 \n-3.82 \n-3.91 \n0.43 (0.26) \n-0.10 (0.12) \n Total Erosion Area \n6043 \n0.023 \n-3.00 \n-3.64 \n-3.74 \n-0.63 (0.48) \n-0.10 (0.19) \n Reef Rubble \n3409 \n0.013 \n-2.61 \n-3.39 \n-3.44 \n-0.77 (0.50) \n-0.06 (0.20) \n Seagrass Discontinuous \n1941 \n0.00708 \n-3.51 \n-4.05 \n-4.22 \n-0.54 (0.43) \n-0.17 (0.15) \n Unconsolidated Sediment \n694 \n0.00248 \n-3.50 \n-3.70 \n-3.82 \n-0.20 (0.15) \n-0.12 (0.13) \nSand Lobe \n Total Area \n67389 \n0.266 \n-12.41 -11.90 \n-12.10 \n0.51 (0.29) -0.20 (0.09) \n Unconsolidated Sediment \n67389 \n0.266 \n-12.41 -11.90 \n-12.10 \n0.51 (0.29) -0.20 (0.09) \n *58 data points fell on borders between habitats and were counted twice during habitat analysis. https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 Figure 4. Elevation-change results for 4,007,961 point-locations at Looe Key Reef. Elevation change between (a) 2016 \nmonths before and 3 to 6 months after Hurricane Irma) and (b) between 2017 to 2019 (from approximately 3 to 16.5 months af\nrma), and (c) corresponding seafloor habitats (FWC, 2015). The Hurricane Irma best track data in the panel b’s inset is fro\nNHC Irma Storm Track resource page (NHC, 2018, see also Figure 2b). Boundaries for the Looe Key Sanctuary Protection Ar\npecial Protection Unit (SPU) are shown as pink polygons. Geomorphic features of interest are indicated with black polygons\nreas indicate locations where water depth was too shallow for collection of multibeam bathymetric data. Figure 4. Elevation-change results for 4,007,961 point-locations at Looe Key Reef. Elevation change between (a) 2016 to 2017 (13.5 \nmonths before and 3 to 6 months after Hurricane Irma) and (b) between 2017 to 2019 (from approximately 3 to 16.5 months after Hurricane \nIrma), and (c) corresponding seafloor habitats (FWC, 2015). The Hurricane Irma best track data in the panel b’s inset is from the NOAA \n250 \nNHC Irma Storm Track resource page (NHC, 2018, see also Figure 2b). Boundaries for the Looe Key Sanctuary Protection Area (SPA) and \nSpecial Protection Unit (SPU) are shown as pink polygons. Geomorphic features of interest are indicated with black polygons. Gaps in map \nareas indicate locations where water depth was too shallow for collection of multibeam bathymetric data. 255 11 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 habitat types showed increases in net volume (accretion) with upper bound ranges from 0.001 to 2.19 Mm3 (Table 3). Largest \nnet volume changes were associated with habitats covering the largest areal extent of the study area including ‘pavement,’ \n‘discontinuous seagrass,’ and ‘unconsolidated sediment.’ Pearson correlation analysis also indicated a very strong positive \ncorrelation (r(8) = 0.99, p = 0.000) and linear relationship (r2 = 0.92, Fig. 5b)) between 2016 mean habitat water depth and habitat types showed increases in net volume (accretion) with upper bound ranges from 0.001 to 2.19 Mm3 (Table 3). Largest \nnet volume changes were associated with habitats covering the largest areal extent of the study area including ‘pavement,’ \n‘discontinuous seagrass,’ and ‘unconsolidated sediment.’ Pearson correlation analysis also indicated a very strong positive \ncorrelation (r(8) = 0.99, p = 0.000) and linear relationship (r2 = 0.92, Fig. 5b)) between 2016 mean habitat water depth and \narea-normalized volume change; area-normalized volume gains increased significantly with increasing water depth. Largest \n270 \narea-normalized volume changes of 0.51 mM3 and 0.54 mM3 were observed for ‘aggregate reef’ and ‘not classified’ habitats, \nrespectively; and smallest changes of 0.20 to 0.27 mM3 were observed for ‘reef rubble’ and ‘continuous seagrass’ habitats \n(Table 3), consistent with mean elevation changes for those habitats. Mean elevation-change values of the 2016–2017 elevation \nchange data set that was clipped to an area of 15.98 km2 and used for this analysis were within ±0.01 m, and area-normalized \nvolumes were within ±0.016 Mm3 km-2, of values calculated in the original 19.71 km2 published data set (unclipped) for the \n275 \noverall study site and all habitats (Yates et al., 2019). area-normalized volume change; area-normalized volume gains increased significantly with increasing water depth. Largest \n270 \narea-normalized volume changes of 0.51 mM3 and 0.54 mM3 were observed for ‘aggregate reef’ and ‘not classified’ habitats, \nrespectively; and smallest changes of 0.20 to 0.27 mM3 were observed for ‘reef rubble’ and ‘continuous seagrass’ habitats \n(Table 3), consistent with mean elevation changes for those habitats. SD = standard deviation. Elevation change data by habitat type associated with each period and geomorphic feature subarea. elevation -6.19 m) and ‘seagrass continuous’ (mean 2016 elevation -7.69 m) habitats (Table 2). Only 4% of all data points \n260 \nshowed losses in elevation (erosion) ranging from -0.01 m to -0.44 m, while 96% of all data points showed gains in elevation \nranging from 0.31 m to 0.55 m across all habitats. Pearson correlation analysis showed a very strong positive correlation (r(8) \n= 0.96, p = 0.000) and linear relationship (r2 = 0.92, Fig. 5a) between 2016 mean habitat water depth (estimated from mean \nelevation) and mean elevation change; mean elevation gains increased significantly with increasing water depth (i.e., \ndecreasing seafloor elevation). Net volume change was up to 5.36 mM3 over the total 15.98 km2 Looe Key study site; and all \n265 260 12 5c) between estimated to -0.25 m (Fig. 4b, Table 2). Largest mean elevation changes were associated with ‘aggregate reef’ and ‘not classified’ habitat \n280 \ntypes, and smallest changes were associated with ‘colonized pavement’ and ‘continuous seagrass’ habitats (Table 2). Only 5% \nof all data points showed gains in elevation with mean accretion ranging from 0.04 m to 0.19 m, while 95% of all data points \nshowed losses in elevation with mean erosion ranging from -0.13 m to -0.27 m across all habitat types. Pearson correlation \nanalysis indicated a moderate correlation (r(8) = -0.67, p = 0.035) and linear relationship (r2 = 0.45, Fig. 5c) between estimated 2017 mean habitat water depth and mean elevation change; mean elevation loss generally increased with increasing water \n285 \ndepth. Net volume change was up to -2.46 mM3 over the total 15.98 km2 Looe Key study site and area-normalized volume \nchange was -0.15 Mm3km-2. Losses in net volume up to -0.931 Mm3 (erosion) were observed across all habitat types (Table \n4). 2017 mean habitat water depth and mean elevation change; mean elevation loss generally increased with increasing water \n285 \ndepth. Net volume change was up to -2.46 mM3 over the total 15.98 km2 Looe Key study site and area-normalized volume \nchange was -0.15 Mm3km-2. Losses in net volume up to -0.931 Mm3 (erosion) were observed across all habitat types (Table \n4). Largest net volume changes were associated with habitats covering the largest areal extent of the study area including \n290 \n‘pavement,’ ‘discontinuous seagrass,’ and ‘unconsolidated sediment.’ Pearson correlation analysis indicated a moderate \ncorrelation (r(8) = -0.67, p = 0.035) and linear relationship (r2 = 0.45, Fig. 5d) between 2017 mean habitat water depth and \narea-normalized volume change; area-normalized volume losses generally increased with increasing water depth. Largest area-\nnormalized volume changes were observed for ‘aggregate reef’ and ‘not classified’ habitats, -0.254 and -0.247 Mm3 km-2, Largest net volume changes were associated with habitats covering the largest areal extent of the study area including \n290 \n‘pavement,’ ‘discontinuous seagrass,’ and ‘unconsolidated sediment.’ Pearson correlation analysis indicated a moderate \ncorrelation (r(8) = -0.67, p = 0.035) and linear relationship (r2 = 0.45, Fig. 5d) between 2017 mean habitat water depth and \narea-normalized volume change; area-normalized volume losses generally increased with increasing water depth. Mean elevation-change values of the 2016–2017 elevation \nchange data set that was clipped to an area of 15.98 km2 and used for this analysis were within ±0.01 m, and area-normalized area-normalized volume change; area-normalized volume gains increased significantly with increasing water depth. Largest \n270 \narea-normalized volume changes of 0.51 mM3 and 0.54 mM3 were observed for ‘aggregate reef’ and ‘not classified’ habitats, \nrespectively; and smallest changes of 0.20 to 0.27 mM3 were observed for ‘reef rubble’ and ‘continuous seagrass’ habitats \n(Table 3), consistent with mean elevation changes for those habitats. Mean elevation-change values of the 2016–2017 elevation \nchange data set that was clipped to an area of 15.98 km2 and used for this analysis were within ±0.01 m, and area-normalized \nvolumes were within ±0.016 Mm3 km-2, of values calculated in the original 19.71 km2 published data set (unclipped) for the \n275 \noverall study site and all habitats (Yates et al 2019) Mean elevation-change during a 13-month time-period between December 2017 to June 2019 (up to approximately 16.5 \nmonths after Hurricane Irma) was -0.15 ± 0.11 m, and all habitat types showed losses in mean elevation ranging from -0.11 m )\n,\nyp\ng g\nto -0.25 m (Fig. 4b, Table 2). Largest mean elevation changes were associated with ‘aggregate reef’ and ‘not classified’ habitat \n280 \ntypes, and smallest changes were associated with ‘colonized pavement’ and ‘continuous seagrass’ habitats (Table 2). Only 5% \nof all data points showed gains in elevation with mean accretion ranging from 0.04 m to 0.19 m, while 95% of all data points \nshowed losses in elevation with mean erosion ranging from -0.13 m to -0.27 m across all habitat types. Pearson correlation \nanalysis indicated a moderate correlation (r(8) = -0.67, p = 0.035) and linear relationship (r2 = 0.45, Fig. 5c) between estimated to -0.25 m (Fig. 4b, Table 2). Largest mean elevation changes were associated with ‘aggregate reef’ and ‘not classified’ habitat \n280 \ntypes, and smallest changes were associated with ‘colonized pavement’ and ‘continuous seagrass’ habitats (Table 2). Only 5% \nof all data points showed gains in elevation with mean accretion ranging from 0.04 m to 0.19 m, while 95% of all data points \nshowed losses in elevation with mean erosion ranging from -0.13 m to -0.27 m across all habitat types. Pearson correlation \nanalysis indicated a moderate correlation (r(8) = -0.67, p = 0.035) and linear relationship (r2 = 0.45, Fig. Largest area-\nnormalized volume changes were observed for ‘aggregate reef’ and ‘not classified’ habitats, -0.254 and -0.247 Mm3 km-2, Largest net volume changes were associated with habitats covering the largest areal extent of the study area including \n290 \n‘pavement,’ ‘discontinuous seagrass,’ and ‘unconsolidated sediment.’ Pearson correlation analysis indicated a moderate \ncorrelation (r(8) = -0.67, p = 0.035) and linear relationship (r2 = 0.45, Fig. 5d) between 2017 mean habitat water depth and \narea-normalized volume change; area-normalized volume losses generally increased with increasing water depth. Largest area-\nnormalized volume changes were observed for ‘aggregate reef’ and ‘not classified’ habitats, -0.254 and -0.247 Mm3 km-2, respectively; smallest changes were observed for ‘colonized pavement’ and ‘continuous seagrass’ habitats, -0.112 to -0.118 \n295 \nMm3 km-2 respectively (Table 4), consistent with mean elevation changes for those habitats. Pearson correlation analysis \nindicated a strong negative correlation (r(8) = -0.74, p = 0.014) and linear relationship (r2 = 0.55, Fig. 5e) between 2017 to \n2019 mean habitat elevation change and 2016 to 2017 mean habitat elevation change; mean elevation losses during 2017 to \n2019 were significantly greater in habitats with larger mean elevation gains during 2016 to 2017. Mean elevation change (loss) respectively; smallest changes were observed for ‘colonized pavement’ and ‘continuous seagrass’ habitats, -0.112 to -0.118 \n295 \nMm3 km-2 respectively (Table 4), consistent with mean elevation changes for those habitats. Pearson correlation analysis \nindicated a strong negative correlation (r(8) = -0.74, p = 0.014) and linear relationship (r2 = 0.55, Fig. 5e) between 2017 to \n2019 mean habitat elevation change and 2016 to 2017 mean habitat elevation change; mean elevation losses during 2017 to \n2019 were significantly greater in habitats with larger mean elevation gains during 2016 to 2017. Mean elevation change (loss) 13 during 2017 to 2019 was 35 to 55% of the mean elevation change (gain) during 2016 to 2017 for all habitats except for reef \n00 \nrubble which was 92% and had the shallowest mean depth (6.0 m) of all habitats. https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 Table 3. Compiled volume change data by habitat type for all study areas during the 2016 to 2017 study period (storm period). Habitat Type \nHabitat Area \n(km2) \nGross erosion \n(Mm3) \nGross accretion \n(Mm3) \nNet volume change \n(Mm3 study-area-1) \nArea-normalized volume \nchange (Mm3 km-2) \nLower \nUpper \nLower Upper \n Lower \nUpper \nLower \nUpper \nOverall Looe Key Study Site \n Total Study Site \n15.98 \n0.053 \n0.134 \n2.456 \n5.490 \n2.403 \n5.356 \n0.150 \n0.335 \n Aggregate Reef \n0.30 \n0 \n0 \n0.090 \n0.154 \n0.090 \n0.154 \n0.296 \n0.505 \n Colonized Pavement \n0.0028 \n0 \n0 \n0 \n0.001 \n0 \n0.001 \n0.124 \n0.323 \n Individual or Aggregate Patch Reef \n0.22 \n0 \n0 \n0.029 \n0.073 \n0.029 \n0.072 \n0.136 \n0.336 \n Not Classified \n0.026 \n0 \n0 \n0.009 \n0.014 \n0.009 \n0.014 \n0.337 \n0.540 \n Pavement \n2.57 \n0 \n0.003 \n0.445 \n0.962 \n0.445 \n0.959 \n0.173 \n0.373 \n Reef Rubble \n0.32 \n0.013 \n0.021 \n0.033 \n0.085 \n0.020 \n0.064 \n0.062 \n0.199 \n Seagrass Continuous \n1.60 \n0.008 \n0.021 \n0.152 \n0.449 \n0.144 \n0.428 \n0.090 \n0.267 \n Seagrass Discontinuous \n4.26 \n0.015 \n0.045 \n0.477 \n1.250 \n0.462 \n1.205 \n0.109 \n0.283 \n Spur and Groove \n0.74 \n0.003 \n0.007 \n0.136 \n0.278 \n0.133 \n0.271 \n0.181 \n0.367 \n Unconsolidated Sediment \n5.94 \n0.013 \n0.037 \n1.083 \n2.226 \n1.070 \n2.189 \n0.180 \n0.369 \nSand Wave \n Total Accretion Area \n0.060 \n0 \n0 \n0.036 \n0.048 \n0.036 \n0.048 \n0.598 \n0.800 \n Seagrass Discontinuous \n0.029 \n0 \n0 \n0.020 \n0.026 \n0.020 \n0.026 \n0.709 \n0.914 \n Unconsolidated Sediment \n0.031 \n0 \n0 \n0.015 \n0.021 \n0.015 \n0.021 \n0.494 \n0.694 \n Total Erosion Area \n0.043 \n0.009 \n0.016 \n0 \n0 \n-0.009 \n-0.016 \n-0.198 \n-0.370 \n Seagrass Discontinuous \n0.002 \n<0.001 \n<0.001 \n0 \n0 \n<-0.001 \n<-0.001 \n-0.045 \n-0.162 \n Unconsolidated Sediment \n0.041 \n0.008 \n0.016 \n0 \n0 \n-0.008 \n-0.016 \n-0.205 \n-0.380 \nScour Marks \n Scour Mark 1 \n0.00071 \n0.0002 \n0.0004 \n0 \n0 \n-0.0002 \n-0.0004 \n-0.3083 \n-0.5114 \n Seagrass Discontinuous \n0.00071 \n0.0002 \n0.0004 \n0 \n0 \n-0.0002 \n-0.0004 \n-0.3118 \n-0.5154 \n Unconsolidated Sediment \n<0.00001 \n0 \n0 \n0 \n0 \n0 <-0.0001 \n-0.0001 \n-0.1479 \n Scour Mark 2 \n0.0014 \n0.0005 \n0.0007 \n0 \n0 \n-0.0005 \n-0.0007 \n-0.3255 \n-0.5271 \n Seagrass Continuous \n0.00124 \n0.0004 \n0.0007 \n0 \n0 \n-0.0004 \n-0.0007 \n-0.3558 \n-0.5595 \n Unconsolidated Sediment \n0.00016 \n0 <-0.0001 \n0 \n0 \n0 <-0.0001 \n-0.0943 \n-0.2790 \n Scour Mark 3 \n0.00188 \n0.0006 \n0.0010 \n0 \n0 \n-0.0006 \n-0.0010 \n-0.3247 \n-0.5232 \n Seagrass Continuous \n0.00188 \n0.0006 \n0.0010 \n0 \n0 \n-0.0006 \n-0.0010 \n-0.3247 \n-0.5232 \n Scour Mark 4 \n0.00152 \n0.0006 \n0.0009 \n0 \n0 \n-0.0006 \n-0.0009 \n-0.3631 \n-0.5661 \n Seagrass Continuous \n0.00151 \n0.0006 \n0.0009 \n0 \n0 \n-0.0006 \n-0.0009 \n-0.3658 \n-0.5697 \n Unconsolidated Sediment \n0.00001 \n0 <-0.0001 \n0 \n0 \n0 <-0.0001 \n0.0000 \n-0.0748 \nReef Rubble Field \n Total Accretion Area \n0.028 \n0 \n0 \n0.020 \n0.025 \n0.020 \n0.025 \n0.707 \n0.914 \n Reef Rubble \n0.012 \n0 \n0 \n0.008 \n0.011 \n0.008 \n0.011 \n0.690 \n0.897 \n Seagrass Discontinuous \n0.014 \n0 \n0 \n0.011 \n0.014 \n0.011 \n0.014 \n0.802 \n1.011 \n Unconsolidated Sediment \n0.002 \n0 \n0 \n0.001 \n0.001 \n0.001 \n0.001 \n0.252 \n0.446 \n Total Erosion Area \n0.023 \n0.011 \n0.015 \n0 \n0 \n-0.011 \n-0.015 \n-0.464 \n-0.661 \n Reef Rubble \n0.013 \n0.008 \n0.010 \n0 \n0 \n-0.008 \n-0.010 \n-0.584 \n-0.788 \n Seagrass Discontinuous \n0.007 \n0.003 \n0.004 \n0 \n0 \n-0.003 \n-0.004 \n-0.382 \n-0.577 \n Unconsolidated Sediment \n0.002 \n0.000 \n0.001 \n0 \n0 \n0.000 \n-0.001 \n-0.064 \n-0.221 \nSand Lobe \n Total Area \n0.27 \n0 \n0.002 \n0.089 \n0.139 \n0.089 \n0.137 \n0.332 \n0.513 \n Unconsolidated Sediment \n0.27 \n0 \n0.002 \n0.089 \n0.139 \n0.089 \n0.137 \n0.332 \n0.513 \n‘Upper’ and ‘lower’ headings refer to the upper and lower bounds of volume change based on total RMSE root mean square error). https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 during 2017 to 2019 was 35 to 55% of the mean elevation change (gain) during 2016 to 2017 for all habitats except for reef \n300 \nrubble which was 92% and had the shallowest mean depth (6.0 m) of all habitats. during 2017 to 2019 was 35 to 55% of the mean elevation change (gain) during 2016 to 2017 for all habitats except for reef \n300 \nrubble which was 92% and had the shallowest mean depth (6.0 m) of all habitats. during 2017 to 2019 was 35 to 55% of the mean elevation change (gain) during 2016 to 2017 for all habitats except for reef \n300 \nrubble which was 92% and had the shallowest mean depth (6.0 m) of all habitats. (a) \n \n(b) \n \n(c) \n \n(d) \n \n (e) \n \nFigure 5. Linear relationships between elevation change, volume change, and water depth. Linear relationships and coeffici\ndetermination between (a) mean elevation change, (b) mean area-normalized volume change, and estimated 2016 mean water de\nseafloor habitats of the Looe Key study site between 2016 to 2017. Linear relationships and coefficients of determination between (c\n5 \nelevation change, (d) mean area-normalized volume change, and estimated 2017 mean water depth for seafloor habitats of the Loo\nstudy site between 2017 to 2019 (a, b). Linear relationship between 2017 to 2019 mean elevation change and 2016 to 2017 mean ele\nchange (e). (a) (b) (a) (d) (c) (d) (c) (e) (e) Figure 5. Linear relationships between elevation change, volume change, and water depth. Linear relationships and coefficients of \ndetermination between (a) mean elevation change, (b) mean area-normalized volume change, and estimated 2016 mean water depth for \nseafloor habitats of the Looe Key study site between 2016 to 2017. Linear relationships and coefficients of determination between (c) mean \nelevation change, (d) mean area-normalized volume change, and estimated 2017 mean water depth for seafloor habitats of the Looe Key \nstudy site between 2017 to 2019 (a, b). Linear relationship between 2017 to 2019 mean elevation change and 2016 to 2017 mean elevation \nchange (e). 14 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 Table 4. Compiled volume change data by habitat type for all study areas during the 2017 to 2019 study period (post-storm re-\nequilibration period). Table 4. Compiled volume change data by habitat type for all study areas during the 2017 to 2019 study period (post-storm re-\nequilibration period). 4. Compiled volume change data by habitat type for all study areas during the 2017 to 2019 study \nbration period). hange data by habitat type for all study areas during the 2017 to 2019 study period (post-storm re- 320 Lower bounds use tota\nRMSE as a plane height in calculating volume. Table 3. Compiled volume change data by habitat type for all study areas during the 2016 to 2017 study period (storm period). 310 Table 3. Compiled volume change data by habitat type for all study areas during the 2016 to 2017 stud e change data by habitat type for all study areas during the 2016 to 2017 study period (storm period). 315 15 Habitat Type \nHabitat Area \n(km2) \nGross erosion \n(Mm3) \nGross accretion \n(Mm3) \nNet volume change \n(Mm3 study-area-1) \nArea-normalized volume \nchange (Mm3 km-2) \nLower \nUpper \nLower Upper \n Lower \nUpper \nLower \nUpper \nOverall Looe Key Study Site \n Total Study Site \n15.98 \n0.316 \n2.502 \n0.005 \n0.041 \n-0.311 \n-2.461 \n-0.019 \n-0.154 \n Aggregate Reef \n0.30 \n0.028 \n0.078 \n0 <0.001 \n-0.028 \n-0.077 \n-0.093 \n-0.254 \n Colonized Pavement \n0.0028 \n<0.001 \n<0.001 \n0 \n0 \n<-0.001 \n<-0.001 \n-0.004 \n-0.112 \n Individual or Aggregate Patch Reef \n0.22 \n0.006 \n0.040 \n0 \n0 \n-0.006 \n-0.040 \n-0.028 \n-0.186 \n Not Classified \n0.026 \n0.002 \n0.007 \n0 <0.001 \n-0.002 \n-0.006 \n-0.083 \n-0.247 \n Pavement \n2.57 \n0.059 \n0.424 \n0 \n0.004 \n-0.059 \n-0.420 \n-0.023 \n-0.163 \n Reef Rubble \n0.32 \n0.010 \n0.061 \n0.001 \n0.002 \n-0.009 \n-0.059 \n-0.029 \n-0.182 \n Seagrass Continuous \n1.60 \n0.012 \n0.197 \n0.001 \n0.008 \n-0.011 \n-0.189 \n-0.007 \n-0.118 \n Seagrass Discontinuous \n4.26 \n0.064 \n0.612 \n0.001 \n0.015 \n-0.063 \n-0.597 \n-0.015 \n-0.140 \n Spur and Groove \n0.74 \n0.032 \n0.145 \n0.001 \n0.003 \n-0.031 \n-0.141 \n-0.042 \n-0.192 \n Unconsolidated Sediment \n5.94 \n0.102 \n0.938 \n0.000 \n0.007 \n-0.102 \n-0.931 \n-0.017 \n-0.157 \nSand Wave \n Total Accretion Area \n0.060 \n0.0015 \n0.0093 \n0 0.0005 \n-0.0015 \n-0.0088 \n-0.0245 \n-0.1479 \n Seagrass Discontinuous \n0.029 \n0.0010 \n0.0048 \n0 0.0003 \n-0.0010 \n-0.0044 \n-0.0336 \n-0.1544 \n Unconsolidated Sediment \n0.031 \n0.0005 \n0.0045 \n0 0.0001 \n-0.0005 \n-0.0044 \n-0.0159 \n-0.1419 \n Total Erosion Area \n0.043 \n0.0003 \n0.0066 \n0 \n0 \n-0.0003 \n-0.0066 \n-0.0074 \n-0.1529 \n Seagrass Discontinuous \n0.002 \n<0.0001 \n0.0003 \n0 \n0 \n<-0.0001 \n-0.0003 \n-0.0158 \n-0.1521 \n Unconsolidated Sediment \n0.041 \n0.0003 \n0.0063 \n0 \n0 \n-0.0003 \n-0.0063 \n-0.0070 \n-0.1529 \nScour Marks \n Scour Mark 1 \n0.00071 \n0.0000 \n0.0000 \n<0.0001 0.0001 \n<0.0001 \n0.0001 \n0.0171 \n0.1201 \n Seagrass Discontinuous \n0.00071 \n0.0000 \n0.0000 \n<0.0001 0.0001 \n<0.0001 \n0.0001 \n0.0173 \n0.1219 \n Unconsolidated Sediment \n<0.00001 \n0.0000 \n<0.0001 \n0.0000 0.0000 \n0.0000 <-0.0001 \n0.0000 \n-0.0447 \n Scour Mark 2 \n0.0014 \n0 \n0 \n0.0001 0.0003 \n0.0001 \n0.0003 \n0.0880 \n0.2226 \n Seagrass Continuous \n0.00124 \n0 \n0 \n0.0001 0.0003 \n0.0001 \n0.0003 \n0.0996 \n0.2550 \n Unconsolidated Sediment \n0.00016 \n<0.0001 \n<0.0001 \n0 \n0 \n<-0.0001 <-0.0001 \n-0.0009 \n-0.0254 \n Scour Mark 3 \n0.00188 \n0 \n0 \n0.0001 0.0003 \n0.0001 \n0.0003 \n0.0524 \n0.1380 \n Seagrass Continuous \n0.00188 \n0 \n0 \n0.0001 0.0003 \n0.0001 \n0.0003 \n0.0524 \n0.1380 \n Scour Mark 4 \n0.00152 \n0 \n0 \n0.0001 0.0002 \n0.0001 \n0.0002 \n0.0615 \n0.1334 \n Seagrass Continuous \n0.00151 \n0 \n0 \n0.0001 0.0002 \n0.0001 \n0.0002 \n0.0620 \n0.1351 \n Unconsolidated Sediment \n0.00001 \n0.0000 \n<0.0001 \n0.0000 0.0000 \n0.0000 <-0.0001 \n0.0000 \n-0.1029 \nReef Rubble Field \n Total Accretion Area \n0.028 \n0.0040 \n0.0080 \n0.0010 0.0010 \n-0.0040 \n-0.0070 \n-0.1310 \n-0.2480 \n Reef Rubble \n0.012 \n0.0020 \n0.0040 \n0 0.0010 \n-0.0010 \n-0.0030 \n-0.1260 \n-0.2180 \n Seagrass Discontinuous \n0.014 \n0.0020 \n0.0040 \n0 \n0 \n-0.0020 \n-0.0040 \n-0.1560 \n-0.3020 \n Unconsolidated Sediment \n0.002 \n<0.0001 \n<0.0001 \n0 \n0 \n<-0.0001 <-0.0001 \n-0.0070 \n-0.0910 \n Total Erosion Area \n0.023 \n0.0005 \n0.0031 \n0.0003 0.0008 \n-0.0002 \n-0.0023 \n-0.0084 \n-0.1026 \n Reef Rubble \n0.013 \n0.0001 \n0.0015 \n0.0003 0.0007 \n0.0002 \n-0.0008 \n0.0113 \n-0.0612 \n Seagrass Discontinuous \n0.007 \n0.0003 \n0.0013 \n0 0.0001 \n-0.0003 \n-0.0012 \n-0.0429 \n-0.1741 \n Unconsolidated Sediment \n0.002 \n<0.0001 \n0.0003 \n0 \n0 \n<-0.0001 \n-0.0003 \n-0.0152 \n-0.1188 \nSand Lobe \n Total Area \n0.27 \n0.010 \n0.055 \n0 <0.001 \n-0.010 \n-0.054 \n-0.038 \n-0.204 \n Unconsolidated Sediment \n0.27 \n0.010 \n0.055 \n0 <0.001 \n-0.010 \n-0.054 \n-0.038 \n-0.204 \n‘Upper’ and ‘lower’ headings refer to the upper and lower bounds of volume change based on total RMSE (root mean square error). https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 Several scour features developed in ‘discontinuous seagrass’ and ‘unconsolidated sediment’ habitats of the Looe Key back \nreef, indicated by areas of erosion that appear as pits. Rubble fields within and near the Looe Key SPA area were displaced, \nas indicated by adjacent areas of accretion and erosion. Substantial deposition of sediments occurred along a sand lobe at the \nbase of the Looe Key Reef ‘spur and groove’ habitat. 330 330 3.2.1 Sand Wave Total net volume change for the accretion area of the feature was 0.048 Mm3 and area-normalized \nvolume change was 0.800 Mm3 km-2 (Table 3). Mean elevation-change and area-normalized volume change was greatest within the discontinuous seagrass habitat (0.90 m and 0.914 Mm3 km-2, respectively), approximately 2.7 times greater than \n345 \nmean elevation change and area-normalized volume change for the overall Looe Key study site. It accounted for 55% of total \nnet volume gain, indicating burial of seagrass habitat during migration of the sand wave. Net volume change of the erosion \narea was approximately -0.016 Mm3 and area-normalized volume change -0.37 Mm3 km-2 with 98% of net volume change \nassociated with erosion of unconsolidated sediment habitat (Table 3). within the discontinuous seagrass habitat (0.90 m and 0.914 Mm3 km-2, respectively), approximately 2.7 times greater than \n345 \nmean elevation change and area-normalized volume change for the overall Looe Key study site. It accounted for 55% of total \nnet volume gain, indicating burial of seagrass habitat during migration of the sand wave. Net volume change of the erosion \narea was approximately -0.016 Mm3 and area-normalized volume change -0.37 Mm3 km-2 with 98% of net volume change \nassociated with erosion of unconsolidated sediment habitat (Table 3). 350 \nBetween 2017 and 2019, the sand wave (accretion area) showed mean elevation and net volume change of approximately -\n0.15 m and approximately -0.009 Mm3, respectively (Table 2, 4 and Fig. 6b). Similar mean elevation change values were \nobserved for discontinuous seagrass and unconsolidated sediment habitats associated with the feature, and net volume change \nfor each habitat was approximately 50% of the total net volume change (Table 4). Area-normalized volume change was similar 350 \nBetween 2017 and 2019, the sand wave (accretion area) showed mean elevation and net volume change of approximately -\n0.15 m and approximately -0.009 Mm3, respectively (Table 2, 4 and Fig. 6b). Similar mean elevation change values were \nobserved for discontinuous seagrass and unconsolidated sediment habitats associated with the feature, and net volume change \nfor each habitat was approximately 50% of the total net volume change (Table 4). Area-normalized volume change was similar 350 \nBetween 2017 and 2019, the sand wave (accretion area) showed mean elevation and net volume change of approximately -\n0.15 m and approximately -0.009 Mm3, respectively (Table 2, 4 and Fig. 6b). 3.2 Geomorphic Feature Analyses Large-scale geomorphic features that were 10s to 100s of m2 in areal extent and showed extensive erosion and/or accretion \nwith elevation-changes greater than 0.5 m were observed between 2016 and 2017 (Fig. 6 and 7). Examples of these features \n325 \nincluded migration of a sand wave in the back reef area of Looe Key reef indicated by adjacent areas of erosion and accretion. 16 3.2.1 Sand Wave An accretion of 0.060 km2 included \napproximately 50% discontinuous seagrass and 50% unconsolidated sediment habitat. of approximately 5.6 m. Transect elevation profiles showed the location of this feature in 2016, westward migration of \n335 \napproximately 78 m (crest to crest) in 2017, and minor erosion in 2019 (Fig. 7a). An accretion of 0.060 km2 included \napproximately 50% discontinuous seagrass and 50% unconsolidated sediment habitat. of approximately 5.6 m. Transect elevation profiles showed the location of this feature in 2016, westward migration of \n335 \napproximately 78 m (crest to crest) in 2017, and minor erosion in 2019 (Fig. 7a). An accretion of 0.060 km2 included \napproximately 50% discontinuous seagrass and 50% unconsolidated sediment habitat. Between 2016 and 2017, mean elevation change of the accretion area (2017 location of the sand wave) was 0.79 m (Table 2) \nwith a maximum elevation gain at the crest of 1.84m. An adjacent area of erosion was approximately 630 x 122 m in length \n340 \nand width (0.043 km2) and included approximately 5% discontinuous seagrass and 95% unconsolidated sediment. Mean \nelevation-change of the erosion area was -0.36 m (Table 2) with a maximum elevation loss of -1.23 m near the 2016 location \nof the sand wave crest. Total net volume change for the accretion area of the feature was 0.048 Mm3 and area-normalized \nvolume change was 0.800 Mm3 km-2 (Table 3). Mean elevation-change and area-normalized volume change was greatest g\nwith a maximum elevation gain at the crest of 1.84m. An adjacent area of erosion was approximately 630 x 122 m in length \n340 \nand width (0.043 km2) and included approximately 5% discontinuous seagrass and 95% unconsolidated sediment. Mean \nelevation-change of the erosion area was -0.36 m (Table 2) with a maximum elevation loss of -1.23 m near the 2016 location \nof the sand wave crest. Total net volume change for the accretion area of the feature was 0.048 Mm3 and area-normalized \nvolume change was 0.800 Mm3 km-2 (Table 3). Mean elevation-change and area-normalized volume change was greatest with a maximum elevation gain at the crest of 1.84m. An adjacent area of erosion was approximately 630 x 122 m in length \n340 \nand width (0.043 km2) and included approximately 5% discontinuous seagrass and 95% unconsolidated sediment. Mean \nelevation-change of the erosion area was -0.36 m (Table 2) with a maximum elevation loss of -1.23 m near the 2016 location \nof the sand wave crest. 3.2.1 Sand Wave Migration of a sand wave was observed in the back reef area of Looe Key Reef between 2016 and 2017, with minor erosion \nof this feature occurring between 2017 and 2019 (Fig. 6a, b, and c). The sand wave was approximately 733 m long and 104 m \nwide at its widest point in 2017, 2 m in height from the crest to base on the deepest (western) edge, with average water depth \nof approximately 5.6 m. Transect elevation profiles showed the location of this feature in 2016, westward migration of \n335 \napproximately 78 m (crest to crest) in 2017, and minor erosion in 2019 (Fig. 7a). An accretion of 0.060 km2 included \napproximately 50% discontinuous seagrass and 50% unconsolidated sediment habitat. Migration of a sand wave was observed in the back reef area of Looe Key Reef between 2016 and 2017, with minor erosion \nof this feature occurring between 2017 and 2019 (Fig. 6a, b, and c). The sand wave was approximately 733 m long and 104 m \nwide at its widest point in 2017, 2 m in height from the crest to base on the deepest (western) edge, with average water depth \nof approximately 5.6 m. Transect elevation profiles showed the location of this feature in 2016, westward migration of \n335 \ni\nl\n78\n(\n) i\n2017\nd\ni\ni\ni\n2019 (Fi\n7 ) A\ni\nf 0 060 k\n2 i\nl d d Migration of a sand wave was observed in the back reef area of Looe Key Reef between 2016 and 2017, with minor erosion \nof this feature occurring between 2017 and 2019 (Fig. 6a, b, and c). The sand wave was approximately 733 m long and 104 m \nwide at its widest point in 2017, 2 m in height from the crest to base on the deepest (western) edge, with average water depth of this feature occurring between 2017 and 2019 (Fig. 6a, b, and c). The sand wave was approximately 733 m long and 104 m \nwide at its widest point in 2017, 2 m in height from the crest to base on the deepest (western) edge, with average water depth \nof approximately 5.6 m. Transect elevation profiles showed the location of this feature in 2016, westward migration of \n335 \napproximately 78 m (crest to crest) in 2017, and minor erosion in 2019 (Fig. 7a). 3.2.1 Sand Wave Similar mean elevation change values were \nobserved for discontinuous seagrass and unconsolidated sediment habitats associated with the feature, and net volume change \nfor each habitat was approximately 50% of the total net volume change (Table 4). Area-normalized volume change was similar for the total area of the sand wave and the sub-areas within it, including discontinuous seagrass and unconsolidated sediment \n355 \nhabitats, ranging from approximately -0.148 to -0.154 Mm3/km2. The adjacent erosion area (original 2016 location of the sand \nwave) also showed a mean elevation change of -0.15 m with similar values for the associated discontinuous seagrass and \nunconsolidated sediment habitats. Net volume change of the erosion area was approximately -0.007 Mm3 with approximately for the total area of the sand wave and the sub-areas within it, including discontinuous seagrass and unconsolidated sediment \n355 \nhabitats, ranging from approximately -0.148 to -0.154 Mm3/km2. The adjacent erosion area (original 2016 location of the sand \nwave) also showed a mean elevation change of -0.15 m with similar values for the associated discontinuous seagrass and \nunconsolidated sediment habitats. Net volume change of the erosion area was approximately -0.007 Mm3 with approximately 17 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 95% of this loss associated with unconsolidated sediment (Table 4). Area-normalized volume change was also consistent \nacross the total erosion feature area, discontinuous seagrass, and unconsolidated sediment habitats at -0.15 Mm3 km-2. 360 95% of this loss associated with unconsolidated sediment (Table 4). Area-normalized volume change was also consistent \nacross the total erosion feature area, discontinuous seagrass, and unconsolidated sediment habitats at -0.15 Mm3 km-2. 360 360 Figure 6. Elevation change data and transect positions for each geomorphic feature subarea. Geomorphic features included a s\nwave (a, b, c), scour marks (d, e, f), western rubble field (g, h, i), and sand lobe subareas (j, k, l). These feature locations and correspond\nhabitat are also shown in Fig. 4. Elevation-change from 2016 to 2017 (a, d, g, j), 2017 to 2019 (b, e, h, k), and corresponding reconnaissa\n5 \nimagery (c, f, i, l) Transect positions are indicated by black lines and lowercase letters in the elevation change panels (see also Fig. 7). Sc\nmarks in panels d and e are labelled SM1 through 4. Photo credit: Mitch Lemon, Cherokee Nations System Solutions for U.S. Geolog\nSurvey. Figure 6. Elevation change data and transect positions for each geomorphic feature subarea. Geomorphic features included a sand \nwave (a, b, c), scour marks (d, e, f), western rubble field (g, h, i), and sand lobe subareas (j, k, l). These feature locations and corresponding \nhabitat are also shown in Fig. 4. Elevation-change from 2016 to 2017 (a, d, g, j), 2017 to 2019 (b, e, h, k), and corresponding reconnaissance \n365 \nimagery (c, f, i, l) Transect positions are indicated by black lines and lowercase letters in the elevation change panels (see also Fig. 7). Scour \nmarks in panels d and e are labelled SM1 through 4. Photo credit: Mitch Lemon, Cherokee Nations System Solutions for U.S. Geological \nSurvey. 18 Figure 7. Elevation transects across geomorphic features in 2016, 2017, and 2019. Geomorphic features included a sand wave (a, e\nscour marks (b, f), western reef rubble field (c, g), and a sand lobe (d, h). Lowercase letters indicate direction of transects as shown in Figur\n6. Vertical red lines indicate areas of erosion and vertical blue lines indicate areas of accretion between (a-d) 2016 and 2017 (before an\nafter Hurricane Irma) and between (e-f) 2017 and 2019. SM = scour mark. Figure 7. Elevation transects across geomorphic features in 2016, 2017, and 2019. Geomorphic features included a sand wave (a, e), \n370 \nscour marks (b, f), western reef rubble field (c, g), and a sand lobe (d, h). Lowercase letters indicate direction of transects as shown in Figure \n6. Vertical red lines indicate areas of erosion and vertical blue lines indicate areas of accretion between (a-d) 2016 and 2017 (before and \nafter Hurricane Irma) and between (e-f) 2017 and 2019. SM = scour mark. 3.2.2 Scour Marks \n375 Development of scour marks was observed in seagrass and unconsolidated sediment habitats in the back reef area of Looe Key \nReef between 2016 and 2017 (Fig. 6d, e, and f). These features ranged from approximately 30 to 60 m in length and width \nwith average depths of approximately 5.7 to 7.5 m in 2017. Visual validation of select scour features indicated they developed 19 mean elevation change of 0.10 m and a net volume change of less than 0.001 Mm3 (Tables 2 and 4). Area-normalized volume \n390 \nchange was approximately 0.12 Mm3 km-2. Scour mark 2 was 1,400 m2 with 88% of the area consisting of continuous seagrass \nand 12% unconsolidated sediment. Between 2016 and 2017, mean elevation change was -0.50 m (Table 2) with maximum \nobserved change of -1.28 m. Net volume change was less than -0.001 Mm3 and area-normalized volume change was \napproximately -0.53 Mm3 km-2 (Table 3). Ninety-four percent of net volume change was associated with continuous seagrass mean elevation change of 0.10 m and a net volume change of less than 0.001 Mm3 (Tables 2 and 4). Area-normalized volume \n390 \nchange was approximately 0.12 Mm3 km-2. Scour mark 2 was 1,400 m2 with 88% of the area consisting of continuous seagrass \nand 12% unconsolidated sediment. Between 2016 and 2017, mean elevation change was -0.50 m (Table 2) with maximum \nobserved change of -1.28 m. Net volume change was less than -0.001 Mm3 and area-normalized volume change was \napproximately -0.53 Mm3 km-2 (Table 3). Ninety-four percent of net volume change was associated with continuous seagrass habitat, which also had the highest area-normalized volume change of -0.56 Mm3 km-2. Between 2017 and 2019, this feature \n395 \nshowed accretion with mean elevation change of 0.20 m and net volume change of 0.0003 Mm3 (Tables 2 and 4). Continuous \nseagrass showed an increase in mean elevation (0.24 m) and net volume (0.0003 Mm3) while unconsolidated sediment showed \na decrease in mean elevation (-0.05 m) and net volume (less than -0.0001 Mm3). Area-normalized volume change across the \nentire scour mark was approximately 0.22 Mm3 km-2. Scour mark 3 was 1,882 m2 with 100% of the area consisting of habitat, which also had the highest area-normalized volume change of -0.56 Mm3 km-2. Between 2017 and 2019, this feature \n395 \nshowed accretion with mean elevation change of 0.20 m and net volume change of 0.0003 Mm3 (Tables 2 and 4). Continuous \nseagrass showed an increase in mean elevation (0.24 m) and net volume (0.0003 Mm3) while unconsolidated sediment showed \na decrease in mean elevation (-0.05 m) and net volume (less than -0.0001 Mm3). Area-normalized volume change across the \nentire scour mark was approximately 0.22 Mm3 km-2. Scour mark 3 was 1,882 m2 with 100% of the area consisting of continuous seagrass. https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 between 2016 and 2017 at the edges of seagrass beds where small (approximately 0.5 m) ledges marked the transition between \nthe slightly higher elevation of seagrass beds and lower elevation of adjacent unconsolidated sediment (Fig. 6f). Transect \n380 \nanalyses showed considerable erosion of the western boundaries of seagrass beds, development of pit-like features up to \napproximately 20 m in diameter and 1 m deep, transport of sediment westward, and burial of seagrass between scour features \n(Fig. 7b). Scour marks showed some infilling between 2017 and 2019. Validation imagery showed exposed rhizomatous \ngrowth at the western edges of seagrass beds (Fig. 8). 380 385 \nElevation- and volume-change analyses were performed on four examples of these features (Fig. 6d and e). Scour mark 1 was \n714 m2 with 99% of the area consisting of discontinuous seagrass. Between 2016 and 2017, mean elevation change was -0.49 \nm (Table 2) with a maximum observed change of -1.09 m. Net volume change was less than -0.001 Mm3, and area-normalized \nvolume change was approximately -0.51 Mm3 km-2 (Table 3). Between 2017 and 2019, this feature showed accretion with 385 \nElevation- and volume-change analyses were performed on four examples of these features (Fig. 6d and e). Scour mark 1 was \n714 m2 with 99% of the area consisting of discontinuous seagrass. Between 2016 and 2017, mean elevation change was -0.49 \nm (Table 2) with a maximum observed change of -1.09 m. Net volume change was less than -0.001 Mm3, and area-normalized \nvolume change was approximately -0.51 Mm3 km-2 (Table 3). Between 2017 and 2019, this feature showed accretion with Elevation- and volume-change analyses were performed on four examples of these features (Fig. 6d and e). Scour mark 1 was \n714 m2 with 99% of the area consisting of discontinuous seagrass. Between 2016 and 2017, mean elevation change was -0.49 \nm (Table 2) with a maximum observed change of -1.09 m. Net volume change was less than -0.001 Mm3, and area-normalized \nvolume change was approximately -0.51 Mm3 km-2 (Table 3). Between 2017 and 2019, this feature showed accretion with \nmean elevation change of 0.10 m and a net volume change of less than 0.001 Mm3 (Tables 2 and 4). Area-normalized volume \n390 \nchange was approximately 0.12 Mm3 km-2. Scour mark 2 was 1,400 m2 with 88% of the area consisting of continuous seagrass \nand 12% unconsolidated sediment. Between 2016 and 2017, mean elevation change was -0.50 m (Table 2) with maximum \nobserved change of -1.28 m. Net volume change was less than -0.001 Mm3 and area-normalized volume change was \napproximately -0.53 Mm3 km-2 (Table 3). Ninety-four percent of net volume change was associated with continuous seagrass \nhabitat, which also had the highest area-normalized volume change of -0.56 Mm3 km-2. Between 2017 and 2019, this feature \n395 \nshowed accretion with mean elevation change of 0.20 m and net volume change of 0.0003 Mm3 (Tables 2 and 4). Continuous \nseagrass showed an increase in mean elevation (0.24 m) and net volume (0.0003 Mm3) while unconsolidated sediment showed \na decrease in mean elevation (-0.05 m) and net volume (less than -0.0001 Mm3). Area-normalized volume change across the \nentire scour mark was approximately 0.22 Mm3 km-2. Scour mark 3 was 1,882 m2 with 100% of the area consisting of \ncontinuous seagrass. Between 2016 and 2017, mean elevation change was -0.50 m with a maximum observed change of -1.25 \n400 \nm (Table 2). Net volume change was -0.001 Mm3 and area-normalized volume change was approximately -0.52 Mm3 km-2 \n(Table 3). Between 2017 to 2019, this feature showed accretion with mean elevation change of 0.12 m and net volume change \nof 0.0003 Mm3 (Tables 2 and 4). Area-normalized volume change was approximately 0.14 Mm3 km-2. Scour mark 4 was 1,520 \nm2 with 99% of area consisting of continuous seagrass and 1% unconsolidated sediment. Between 2016 and 2017, mean \nelevation change was -0.54 m with a maximum observed change of -1.29 m (Table 2). Net volume change was -0.0009 Mm3 \n405 \nand area-normalized volume change was approximately -0.57 Mm3 km-2 (Table 3). Ninety-nine percent of net volume change \nwas associated with continuous seagrass habitat which also had the highest area-normalized volume change of -0.57 Mm3 km-\n2. Between 2017 to 2019, this feature showed accretion with mean elevation change of 0.12 m and net volume change of -\n0.0002 Mm3 (Tables 2 and 4). Area-normalized volume change was approximately 0.13 Mm3 km-2. More than 99% of net \nvolume change was associated with continuous seagrass habitat which also had the highest area-normalized volume change of \n410 \napproximately 0.14 Mm3 km-2. High erosion was noted between 2016 and 201\non the sand flat (western) side of the habitat transition and minimal accretion was noted on the seagrass bed (eastern) side of the habit Figure 8. Cardinal orientation imagery (a, b, d, and e represent north, west, east, and south, respectively) and elevation change (c) \nat a scour mark location used to validate benthic features observed in elevation change data. East and west arrows show the boundaries \n415 \nbetween seagrass beds and sand flats in the elevation change data (c) and imagery (b and d). High erosion was noted between 2016 and 2017 \non the sand flat (western) side of the habitat transition and minimal accretion was noted on the seagrass bed (eastern) side of the habitat \ntransition. Photo credit: Mitch Lemon, Cherokee Nations System Solutions for U.S. Geological Survey. 415 Between 2016 and 2017, mean elevation change was -0.50 m with a maximum observed change of -1.25 \n400 \nm (Table 2). Net volume change was -0.001 Mm3 and area-normalized volume change was approximately -0.52 Mm3 km-2 \n(Table 3). Between 2017 to 2019, this feature showed accretion with mean elevation change of 0.12 m and net volume change \nof 0.0003 Mm3 (Tables 2 and 4). Area-normalized volume change was approximately 0.14 Mm3 km-2. Scour mark 4 was 1,520 \nm2 with 99% of area consisting of continuous seagrass and 1% unconsolidated sediment. Between 2016 and 2017, mean elevation change was -0.54 m with a maximum observed change of -1.29 m (Table 2). Net volume change was -0.0009 Mm3 \n405 \nand area-normalized volume change was approximately -0.57 Mm3 km-2 (Table 3). Ninety-nine percent of net volume change \nwas associated with continuous seagrass habitat which also had the highest area-normalized volume change of -0.57 Mm3 km-\n2. Between 2017 to 2019, this feature showed accretion with mean elevation change of 0.12 m and net volume change of -\n0.0002 Mm3 (Tables 2 and 4). Area-normalized volume change was approximately 0.13 Mm3 km-2. More than 99% of net volume change was associated with continuous seagrass habitat which also had the highest area-normalized volume change of \n410 \napproximately 0.14 Mm3 km-2. 20 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 Figure 8. Cardinal orientation imagery (a, b, d, and e represent north, west, east, and south, respectively) and elevation change (c) \nat a scour mark location used to validate benthic features observed in elevation change data. East and west arrows show the boundaries \n415 \nbetween seagrass beds and sand flats in the elevation change data (c) and imagery (b and d). High erosion was noted between 2016 and 2017 \non the sand flat (western) side of the habitat transition and minimal accretion was noted on the seagrass bed (eastern) side of the habitat \ntransition. Photo credit: Mitch Lemon, Cherokee Nations System Solutions for U.S. Geological Survey. Figure 8. Cardinal orientation imagery (a, b, d, and e represent north, west, east, and south, respectively) and elevation change (\nat a scour mark location used to validate benthic features observed in elevation change data. East and west arrows show the boundarie\n415 \nbetween seagrass beds and sand flats in the elevation change data (c) and imagery (b and d). The adjacent erosion \n440 \narea (original 2016 location of the rubble field) showed a mean elevation change of -0.10 m (Table 2) with a maximum \nelevation loss of -0.52 m. Total net volume change was approximately -0.002 Mm3 and area-normalized volume change was \n-0.103 Mm3 km-2 with 53% of net volume change associated with discontinuous seagrass (Table 4). Highest mean elevation \nand area-normalized volume changes were also associated with discontinuous seagrass. Mean elevation and volume losses \ngenerally decreased with increasing mean habitat depth in the erosion area (Tables 2 and 4). 445 loss in mean elevation and area-normalized volume change and accounted for 59% of net volume change. The adjacent erosion \n440 \narea (original 2016 location of the rubble field) showed a mean elevation change of -0.10 m (Table 2) with a maximum \nelevation loss of -0.52 m. Total net volume change was approximately -0.002 Mm3 and area-normalized volume change was \n-0.103 Mm3 km-2 with 53% of net volume change associated with discontinuous seagrass (Table 4). Highest mean elevation \nand area-normalized volume changes were also associated with discontinuous seagrass. Mean elevation and volume losses \ngenerally decreased with increasing mean habitat depth in the erosion area (Tables 2 and 4). 445 3.2.3 Rubble Fields \n420 Migration of reef rubble fields was observed in areas north and northeast of Looe Key Reef between 2016 and 2017. The \nlargest of these features was approximately 418 m long and x 122 m wide at its widest point in 2017, 3 m in height from the \ncrest to base on the deepest (western) edge, with average water depth of approximately 3.3 m (Fig 6g, h, and i). Transect \nelevation profiles showed the location of this feature in 2016, westward migration of approximately 80 m (crest to crest) in Migration of reef rubble fields was observed in areas north and northeast of Looe Key Reef between 2016 and 2017. The \nlargest of these features was approximately 418 m long and x 122 m wide at its widest point in 2017, 3 m in height from the \ncrest to base on the deepest (western) edge, with average water depth of approximately 3.3 m (Fig 6g, h, and i). Transect \nelevation profiles showed the location of this feature in 2016, westward migration of approximately 80 m (crest to crest) in 2017, and minor eastward migration of 8 m (crest to crest) in 2019 (Fig. 7c). The accretion area of this feature covered an area \n425 \nof about 0.03 km2 including approximately 43% reef rubble, 49% discontinuous seagrass, and 9% unconsolidated sediment. Between 2016 and 2017, mean elevation change of the accretion area (2017 location of the rubble field) was 0.89 m (Table 2) \nwith a maximum elevation gain of 2.21 m. Total net volume change was 0.025 Mm3 and area-normalized volume change was 21 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 0.914 Mm3 km-2 with discontinuous seagrass accounting for 54% of net volume change indicating burial of seagrass during \nmigration of the rubble field (Table 3). Highest mean elevation and area-normalized volume changes were also associated with \n430 \ndiscontinuous seagrass habitat. An area of erosion (0.023 km2) was observed in 2017 at the original 2016 location of the rubble \nfield that was approximately 428 m long and x 78 m wide including 58% reef rubble, 31% discontinuous seagrass, and 11% \nunconsolidated sediment. Mean elevation-change of the erosion area between 2016 and 2017 was -0.63 m (Table 2) with a \nmaximum elevation loss of -2.11 m. Total net volume change was approximately -0.015 Mm3 and area-normalized volume \nchange was -0.661 Mm3 km-2 with 69% of net volume change associated with reef rubble (Table 3). Highest mean elevation \n435 \nand area-normalized volume changes were also associated with reef rubble. 0.914 Mm3 km-2 with discontinuous seagrass accounting for 54% of net volume change indicating burial of seagrass during \nmigration of the rubble field (Table 3). Highest mean elevation and area-normalized volume changes were also associated with \n430 \ndiscontinuous seagrass habitat. An area of erosion (0.023 km2) was observed in 2017 at the original 2016 location of the rubble \nfield that was approximately 428 m long and x 78 m wide including 58% reef rubble, 31% discontinuous seagrass, and 11% \nunconsolidated sediment. Mean elevation-change of the erosion area between 2016 and 2017 was -0.63 m (Table 2) with a \nmaximum elevation loss of -2.11 m. Total net volume change was approximately -0.015 Mm3 and area-normalized volume change was -0.661 Mm3 km-2 with 69% of net volume change associated with reef rubble (Table 3). Highest mean elevation \n435 \nand area-normalized volume changes were also associated with reef rubble. Between 2017 and 2019, the rubble field (accretion area) showed mean elevation change of -0.24 m, net volume change of -\n0.007 Mm3, and area-normalized volume change of -0.248 Mm3 km-2 (Tables 2 and 4). Discontinuous seagrass showed greatest 0.007 Mm3, and area-normalized volume change of -0.248 Mm3 km-2 (Tables 2 and 4). Discontinuous seagrass showed greatest \nloss in mean elevation and area-normalized volume change and accounted for 59% of net volume change. 3.2.4 Sand Lobe Substantial accretion was observed along a sand lobe located near the base of the fore-reef slope of Looe Key Reef between \n2016 and 2017 (Fig. 6j, k, and l). This feature was approximately 1,383 m long and 344 m wide (approximately 0.27 km2) at \nthe widest point with an average water depth of approximately 11.9 m in 2017 and included only unconsolidated sediment \nhabitat. Between 2016 and 2017, mean elevation change was 0.51 m (Table 2) with maximum gains in elevation up to 1.5 m \n450 \nalong the southern (seaward) downslope section of this feature and maximum elevation losses of -0.58 m along the northern \nlandward section, nearest to the base of the of the fore-reef slope (Fig. 7d). Total net volume change was 0.14 Mm3 and area-\nnormalized volume change was 0.51 Mm3 km-2 (Table 3). Between 2017and 2019, mean elevation change was -0.20 m with \nmaximum elevation losses up to -1.12 m (Table 2, Fig. 7d). Only 852 of 67,389 elevation points analysed for this feature \nshowed gains in elevation after 2017, averaging 0.05 m. Transect elevation profiles showed relatively consistent losses in \n455 \nelevation (erosion) across the sand lobe north to south (landward to seaward) during this time-period. Total net volume change \nwas -0.05 Mm3 and area-normalized volume change was -0.20 Mm3 km-2 (Table 4). Substantial accretion was observed along a sand lobe located near the base of the fore-reef slope of Looe Key Reef between \n2016 and 2017 (Fig. 6j, k, and l). This feature was approximately 1,383 m long and 344 m wide (approximately 0.27 km2) at \nthe widest point with an average water depth of approximately 11.9 m in 2017 and included only unconsolidated sediment (\ng\nj, ,\n)\npp\ny ,\ng\n( pp\ny\n)\nthe widest point with an average water depth of approximately 11.9 m in 2017 and included only unconsolidated sediment \nhabitat. Between 2016 and 2017, mean elevation change was 0.51 m (Table 2) with maximum gains in elevation up to 1.5 m \n450 \nalong the southern (seaward) downslope section of this feature and maximum elevation losses of -0.58 m along the northern \nlandward section, nearest to the base of the of the fore-reef slope (Fig. 7d). Total net volume change was 0.14 Mm3 and area-\nnormalized volume change was 0.51 Mm3 km-2 (Table 3). https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 3.2.4 Sand Lobe Between 2017and 2019, mean elevation change was -0.20 m with \nmaximum elevation losses up to -1.12 m (Table 2, Fig. 7d). Only 852 of 67,389 elevation points analysed for this feature \nshowed gains in elevation after 2017, averaging 0.05 m. Transect elevation profiles showed relatively consistent losses in \n455 \nelevation (erosion) across the sand lobe north to south (landward to seaward) during this time-period. Total net volume change \nwas -0.05 Mm3 and area-normalized volume change was -0.20 Mm3 km-2 (Table 4). habitat. Between 2016 and 2017, mean elevation change was 0.51 m (Table 2) with maximum gains in elevation up to 1.5 m \n450 \nalong the southern (seaward) downslope section of this feature and maximum elevation losses of -0.58 m along the northern \nlandward section, nearest to the base of the of the fore-reef slope (Fig. 7d). Total net volume change was 0.14 Mm3 and area-\nnormalized volume change was 0.51 Mm3 km-2 (Table 3). Between 2017and 2019, mean elevation change was -0.20 m with \nmaximum elevation losses up to -1.12 m (Table 2, Fig. 7d). Only 852 of 67,389 elevation points analysed for this feature showed gains in elevation after 2017, averaging 0.05 m. Transect elevation profiles showed relatively consistent losses in\n455 \nelevation (erosion) across the sand lobe north to south (landward to seaward) during this time-period. Total net volume change\nwas -0.05 Mm3 and area-normalized volume change was -0.20 Mm3 km-2 (Table 4). 22 4 Discussion Our 2016 to 2017 elevation change results showed general movement of sediment \nand migration of major geomorphic features from ENE to WSW in shallow areas (ranging from approximately 2 to 5.5 m \nwater depth in 2016) of the reef proper and back reef area, consistent with the direction of sustained, high magnitude winds \nduring the passing of Hurricane Irma (Fig. 4; Fig. 6a, d, and g). For example, large sand waves and rubble fields (approximately \n475 \n0.02 to 0.06 km2 in area) migrated westward approximately 80 m (Fig. 6a and g) causing burial of seagrass habitat. Scour \nmarks developed due to erosion of the western edges of seagrass beds and westward transport of sediment, causing burial of \nadjacent seagrass beds between scour marks (Fig. 6d). Numerical modelling of the impact of hurricane-induced wave-current \ninteractions on the transport of material along the FRT during Hurricane Irma showed that wave radiation stress primarily \naffected particle transport trajectories during the passage of the hurricane (Dobbelaere et al., 2022). Additionally, wave energy \n480 \ndissipation occurred through depth-induced wave breaking and bottom dissipation at the shelf break and over the coral reefs. Furthermore, after the passage of the hurricane, suspended particles were transported northeastward by the Florida Current \n(Fig. 1d) and were advected (via Stokes drift) from the outer shelf to inshore for approximately 2 days (Dobbelaere et al., storm and, therefore, included any persistent change that occurred during quiescent sea state conditions before and after the \n465 \npassing of Irma. However, observations during several rapid reef assessments after the storm indicated broad-scale sediment \ndeposition as a direct result of Hurricane Irma (Viehman et al., 2018; Walker, 2018; Wilson et al., 2020; Kobelt et al. 2019), \nwhich corroborates our findings of increased mean elevation and sediment accretion resulting from this storm event. Furthermore, wind conditions were relatively quiescent from the 2016 lidar acquisition date up to the passing of Hurricane storm and, therefore, included any persistent change that occurred during quiescent sea state conditions before and after the \n465 \npassing of Irma. However, observations during several rapid reef assessments after the storm indicated broad-scale sediment \ndeposition as a direct result of Hurricane Irma (Viehman et al., 2018; Walker, 2018; Wilson et al., 2020; Kobelt et al. 2019), \nwhich corroborates our findings of increased mean elevation and sediment accretion resulting from this storm event. 4 Discussion Furthermore, wind conditions were relatively quiescent from the 2016 lidar acquisition date up to the passing of Hurricane Irma and after the storm, and historical aerial imagery of LKR from 2014 and 18 March 2017 (3 years and 6 months prior to \n470 \nHurricane Irma, respectively, Fig. 9) show that patterns of major sedimentary features were mostly static (Finkl and Vollmer, \n2017) in the few years prior to the storm. Our 2016 to 2017 elevation change results showed general movement of sediment \nand migration of major geomorphic features from ENE to WSW in shallow areas (ranging from approximately 2 to 5.5 m \nwater depth in 2016) of the reef proper and back reef area, consistent with the direction of sustained, high magnitude winds Irma and after the storm, and historical aerial imagery of LKR from 2014 and 18 March 2017 (3 years and 6 months prior to \n470 \nHurricane Irma, respectively, Fig. 9) show that patterns of major sedimentary features were mostly static (Finkl and Vollmer, \n2017) in the few years prior to the storm. Our 2016 to 2017 elevation change results showed general movement of sediment \nand migration of major geomorphic features from ENE to WSW in shallow areas (ranging from approximately 2 to 5.5 m \nwater depth in 2016) of the reef proper and back reef area, consistent with the direction of sustained, high magnitude winds Irma and after the storm, and historical aerial imagery of LKR from 2014 and 18 March 2017 (3 years and 6 months prior to \n470 \nHurricane Irma, respectively, Fig. 9) show that patterns of major sedimentary features were mostly static (Finkl and Vollmer, \n2017) in the few years prior to the storm. Our 2016 to 2017 elevation change results showed general movement of sediment \nand migration of major geomorphic features from ENE to WSW in shallow areas (ranging from approximately 2 to 5.5 m \nwater depth in 2016) of the reef proper and back reef area, consistent with the direction of sustained, high magnitude winds during the passing of Hurricane Irma (Fig. 4; Fig. 6a, d, and g). For example, large sand waves and rubble fields (approximately \n475 \n0.02 to 0.06 km2 in area) migrated westward approximately 80 m (Fig. 6a and g) causing burial of seagrass habitat. 4 Discussion There are few comprehensive assessments of the effects of major hurricanes on seafloor elevation and geomorphology on coral \nreefs; and no quantitative studies of reef-scale seafloor elevation change resulting from tropical storm impacts have previously \n460 \nbeen conducted in the Florida Keys. Our results showed Hurricane Irma was primarily a depositional event that increased mean \nseafloor elevation and volume over a 15.98 km2 section of Looe Key Reef by 0.34 m (annualized elevation-change rate of up \nto 247 mm yr-1) and up to 5.4 Mm3, respectively, with area-normalized volume change of approximately 0.34 Mm3km-2. Our \nobservations were based on elevation measurements collected 13.5 months before the storm and three to six months after the There are few comprehensive assessments of the effects of major hurricanes on seafloor elevation and geomorphology on coral \nreefs; and no quantitative studies of reef-scale seafloor elevation change resulting from tropical storm impacts have previously \n460 \nbeen conducted in the Florida Keys. Our results showed Hurricane Irma was primarily a depositional event that increased mean \nseafloor elevation and volume over a 15.98 km2 section of Looe Key Reef by 0.34 m (annualized elevation-change rate of up \nto 247 mm yr-1) and up to 5.4 Mm3, respectively, with area-normalized volume change of approximately 0.34 Mm3km-2. Our \nobservations were based on elevation measurements collected 13.5 months before the storm and three to six months after the \nstorm and, therefore, included any persistent change that occurred during quiescent sea state conditions before and after the \n465 \npassing of Irma. However, observations during several rapid reef assessments after the storm indicated broad-scale sediment \ndeposition as a direct result of Hurricane Irma (Viehman et al., 2018; Walker, 2018; Wilson et al., 2020; Kobelt et al. 2019), \nwhich corroborates our findings of increased mean elevation and sediment accretion resulting from this storm event. Furthermore, wind conditions were relatively quiescent from the 2016 lidar acquisition date up to the passing of Hurricane \nIrma and after the storm, and historical aerial imagery of LKR from 2014 and 18 March 2017 (3 years and 6 months prior to \n470 \nHurricane Irma, respectively, Fig. 9) show that patterns of major sedimentary features were mostly static (Finkl and Vollmer, \n2017) in the few years prior to the storm. 4 Discussion Scour \nmarks developed due to erosion of the western edges of seagrass beds and westward transport of sediment, causing burial of \nadjacent seagrass beds between scour marks (Fig. 6d). Numerical modelling of the impact of hurricane-induced wave-current \ninteractions on the transport of material along the FRT during Hurricane Irma showed that wave radiation stress primarily during the passing of Hurricane Irma (Fig. 4; Fig. 6a, d, and g). For example, large sand waves and rubble fields (approximately \n475 \n0.02 to 0.06 km2 in area) migrated westward approximately 80 m (Fig. 6a and g) causing burial of seagrass habitat. Scour \nmarks developed due to erosion of the western edges of seagrass beds and westward transport of sediment, causing burial of \nadjacent seagrass beds between scour marks (Fig. 6d). Numerical modelling of the impact of hurricane-induced wave-current \ninteractions on the transport of material along the FRT during Hurricane Irma showed that wave radiation stress primarily affected particle transport trajectories during the passage of the hurricane (Dobbelaere et al., 2022). Additionally, wave energy \n480 \ndissipation occurred through depth-induced wave breaking and bottom dissipation at the shelf break and over the coral reefs. Furthermore, after the passage of the hurricane, suspended particles were transported northeastward by the Florida Current \n(Fig. 1d) and were advected (via Stokes drift) from the outer shelf to inshore for approximately 2 days (Dobbelaere et al., \n2022). affected particle transport trajectories during the passage of the hurricane (Dobbelaere et al., 2022). Additionally, wave energy \n480 \ndissipation occurred through depth-induced wave breaking and bottom dissipation at the shelf break and over the coral reefs. Furthermore, after the passage of the hurricane, suspended particles were transported northeastward by the Florida Current \n(Fig. 1d) and were advected (via Stokes drift) from the outer shelf to inshore for approximately 2 days (Dobbelaere et al., \n2022). 485 \nSimilar geomorphic seafloor changes have been documented for other category 4 hurricanes in the Florida Keys based on \nphotographic air and ground surveys, maps, sediment cores, and bottom markers. 4 Discussion In 1967, Hurricane Donna approached from \nthe southeast and passed over the central islands of the Florida Keys in September 1960 with sustained winds of 226 km h-1 \n(category 4) and with breaking waves and storm currents causing broken coral rubble up to a meter in diameter, shoreward 485 \nSimilar geomorphic seafloor changes have been documented for other category 4 hurricanes in the Florida Keys based on \nphotographic air and ground surveys, maps, sediment cores, and bottom markers. In 1967, Hurricane Donna approached from \nthe southeast and passed over the central islands of the Florida Keys in September 1960 with sustained winds of 226 km h-1 \n(category 4) and with breaking waves and storm currents causing broken coral rubble up to a meter in diameter, shoreward \ntransport of gravel to boulder sized rubble and sand approximately 60 to 150 m shoreward, and burial of seagrass with 15 cm \n490 485 \nSimilar geomorphic seafloor changes have been documented for other category 4 hurricanes in the Florida Keys based on \nphotographic air and ground surveys, maps, sediment cores, and bottom markers. In 1967, Hurricane Donna approached from \nthe southeast and passed over the central islands of the Florida Keys in September 1960 with sustained winds of 226 km h-1 \n(category 4) and with breaking waves and storm currents causing broken coral rubble up to a meter in diameter, shoreward \ntransport of gravel to boulder sized rubble and sand approximately 60 to 150 m shoreward, and burial of seagrass with 15 cm \n490 transport of gravel to boulder sized rubble and sand approximately 60 to 150 m shoreward, and burial of seagrass with 15 cm \n490 23 Figure 9. Historical satellite and aerial imagery of Looe Key Reef. Imagery from (a) 17 December 2014, before Hurricane Irma; (b) 18\nMarch 2017, before Hurricane Irma; (c) 30 December 2017, 3 months after Hurricane Irma; (d) 2019, 16.5 months after Hurricane Irma; \n2023. Panel d source: 2019 NOAA National Geodetic Survey via NOAA Digital Coast, downloaded 11 September 2023, \nhttps://www.fisheries.noaa.gov/inport/item/63292. and (e) from 1975 (Lidz et al., 2016). Panels a, b, and c source: Maxar 2023 via © Google Earth Pro 7.3.6.9345, downloaded 11 Septembe Figure 9. Historical satellite and aerial imagery of Looe Key Reef. 4 Discussion Imagery from (a) 17 December 2014, before Hurricane Irma; (b) 18 \nMarch 2017, before Hurricane Irma; (c) 30 December 2017, 3 months after Hurricane Irma; (d) 2019, 16.5 months after Hurricane Irma; \n2023. Panel d source: 2019 NOAA National Geodetic Survey via NOAA Digital Coast, downloaded 11 September 2023, \nhttps://www.fisheries.noaa.gov/inport/item/63292. 495 \nand (e) from 1975 (Lidz et al., 2016). Panels a, b, and c source: Maxar 2023 via © Google Earth Pro 7.3.6.9345, downloaded 11 September of sediment (Ball et al., 1967). Hurricane Betsy approached from the west and passed over the Florida Keys approximately 25 \nkm north of Hurricane Donna’s landfall in September 1965 with sustained winds of up to 226 km h-1. While both storms had \n500 \nsimilar destructive effects to corals on the outer reefs, Hurricane Betsy produced less rubble, showed an overall effect of \nerosion and recycling of sediment in the environment, and caused sediment plumes from the mainland to the edge of the Gulf km north of Hurricane Donna’s landfall in September 1965 with sustained winds of up to 226 km h-1. While both storms had \n500 \nsimilar destructive effects to corals on the outer reefs, Hurricane Betsy produced less rubble, showed an overall effect of \nerosion and recycling of sediment in the environment, and caused sediment plumes from the mainland to the edge of the Gulf 24 Fourqurean and Rutten (2004) showed that seagrass recovery was slowest at sites that were \neroded; losses by mechanical thinning and burial with only a few centimeters of sediment recovered quickly; and seagrass \nburied with 10s of centimeters of sediment hadn’t recovered by three years after the storm. Results from these studies show \n515 \nthe variability in storm impacts due complex interactions among factors such as location, fetch, wind speed, duration, storm \nhistory, and water depth (Fourqurean and Rutten, 2004), and demonstrate the value of comprehensive, quantitative post storm \nassessments of geological and ecological impacts. with maximum sustained winds of only 145 km h-1. However, data from 30 seagrass monitoring transects showed a 3% decline \n510 \nin density of Thalassia testudinum and 19% decline in density of Syringodium filiforme seagrasses, with complete loss of \nseagrass beds at 3 monitoring stations, burial of one station with 50cm of sediment, substantial erosion at two stations \n(Fourqurean and Rutten, 2004). Fourqurean and Rutten (2004) showed that seagrass recovery was slowest at sites that were \neroded; losses by mechanical thinning and burial with only a few centimeters of sediment recovered quickly; and seagrass with maximum sustained winds of only 145 km h-1. However, data from 30 seagrass monitoring transects showed a 3% decline \n510 \nin density of Thalassia testudinum and 19% decline in density of Syringodium filiforme seagrasses, with complete loss of \nseagrass beds at 3 monitoring stations, burial of one station with 50cm of sediment, substantial erosion at two stations \n(Fourqurean and Rutten, 2004). Fourqurean and Rutten (2004) showed that seagrass recovery was slowest at sites that were \neroded; losses by mechanical thinning and burial with only a few centimeters of sediment recovered quickly; and seagrass buried with 10s of centimeters of sediment hadn’t recovered by three years after the storm. Results from these studies show \n515 \nthe variability in storm impacts due complex interactions among factors such as location, fetch, wind speed, duration, storm \nhistory, and water depth (Fourqurean and Rutten, 2004), and demonstrate the value of comprehensive, quantitative post storm \nassessments of geological and ecological impacts. buried with 10s of centimeters of sediment hadn’t recovered by three years after the storm. Results from these studies show \n515 \nthe variability in storm impacts due complex interactions among factors such as location, fetch, wind speed, duration, storm \nhistory, and water depth (Fourqurean and Rutten, 2004), and demonstrate the value of comprehensive, quantitative post storm \nassessments of geological and ecological impacts. 520 \nA previous analysis of seafloor elevation change at LKR during the decade prior to Hurricane Irma (from 2004–2016, during \nwhich only one minor tropical storm impacted this location in 2008) indicated an increase in mean elevation of 0.39 m \n(annualized elevation-change rate of 32.5 mm yr-1), net volume gain of up to 6.4 Mm3 and area-normalized volume change of \n0.39 Mm3 km-2, with accretion observed across all habitat types and some WSW movement of sand waves (Yates et al., 2019). 520 \nA previous analysis of seafloor elevation change at LKR during the decade prior to Hurricane Irma (from 2004–2016, during \nwhich only one minor tropical storm impacted this location in 2008) indicated an increase in mean elevation of 0.39 m \n(annualized elevation-change rate of 32.5 mm yr-1), net volume gain of up to 6.4 Mm3 and area-normalized volume change of \n0.39 Mm3 km-2, with accretion observed across all habitat types and some WSW movement of sand waves (Yates et al., 2019). 520 \nA previous analysis of seafloor elevation change at LKR during the decade prior to Hurricane Irma (from 2004–2016, during \nwhich only one minor tropical storm impacted this location in 2008) indicated an increase in mean elevation of 0.39 m \n(annualized elevation-change rate of 32.5 mm yr-1), net volume gain of up to 6.4 Mm3 and area-normalized volume change of \n0.39 Mm3 km-2, with accretion observed across all habitat types and some WSW movement of sand waves (Yates et al., 2019). Our results showed that sediment deposited during the approximately 16.5 to 19.5-month time-period including impacts from \n525 \nHurricane Irma caused changes in seafloor elevation and volume across all habitat types similar in magnitude to net changes \nobserved over the past decade and at accumulation rates one order of magnitude greater. Previous studies on several coral reefs \naround St. Croix, U.S. https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 Stream for several days after the Hurricane passed (Perkins and Enos, 1968). Perkins and Enos (1968) noted the difference in \nwind directions for the two storms caused different effects, and that it is difficult to extrapolate quantitative sedimentation rates \nfrom the sedimentary record of one hurricane and frequency of recorded hurricanes. Hurricane Andrew made landfall along \n505 \nthe southeast coast of Florida just south of Miami also with sustained winds of 226 km h-1 with maximum wave heights of less \nthan 2 m. Branching corals were broken, massive coral heads were toppled, seafans and sponges were ripped loose, and shallow \nreefs sustained the most damage (Orr and Ogden, 1992); however, there was little damage to seagrass beds immediately \nseaward of coastal mangroves (Tilmant et al., 1994). Hurricane Georges was a category 2 storm that passed over Key West Stream for several days after the Hurricane passed (Perkins and Enos, 1968). Perkins and Enos (1968) noted the difference in \nwind directions for the two storms caused different effects, and that it is difficult to extrapolate quantitative sedimentation rates \nfrom the sedimentary record of one hurricane and frequency of recorded hurricanes. Hurricane Andrew made landfall along \n505 \nthe southeast coast of Florida just south of Miami also with sustained winds of 226 km h-1 with maximum wave heights of less \nthan 2 m. Branching corals were broken, massive coral heads were toppled, seafans and sponges were ripped loose, and shallow \nreefs sustained the most damage (Orr and Ogden, 1992); however, there was little damage to seagrass beds immediately \nseaward of coastal mangroves (Tilmant et al., 1994). Hurricane Georges was a category 2 storm that passed over Key West \nwith maximum sustained winds of only 145 km h-1. However, data from 30 seagrass monitoring transects showed a 3% decline \n510 \nin density of Thalassia testudinum and 19% decline in density of Syringodium filiforme seagrasses, with complete loss of \nseagrass beds at 3 monitoring stations, burial of one station with 50cm of sediment, substantial erosion at two stations \n(Fourqurean and Rutten, 2004). https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0.\nl\n.\n0 Virgin Islands showed that physical transport of sediment is primarily due to wave-induced oscillatory \nand unidirectional currents, and that storms can increase sediment transport by an order of magnitude higher than during non- Our results showed that sediment deposited during the approximately 16.5 to 19.5-month time-period including impacts from \n525 \nHurricane Irma caused changes in seafloor elevation and volume across all habitat types similar in magnitude to net changes \nobserved over the past decade and at accumulation rates one order of magnitude greater. Previous studies on several coral reefs \naround St. Croix, U.S. Virgin Islands showed that physical transport of sediment is primarily due to wave-induced oscillatory \nand unidirectional currents, and that storms can increase sediment transport by an order of magnitude higher than during non- storm conditions (Hubbard et al., 1981; Hubbard, 1986). Measurements from 15 locations around St. Croix showed sediment \n530 \ntransport rates ranging from 0.009 to 0.3 Mm3 km-2yr-1 during non-storm conditions, and 0.09 to 1.5 Mm3 km-2yr-1 during storm \nconditions (Hubbard et al., 1981; Yates et al., 2017). Sediment trap studies along the southwest coast of Puerto Rico showed \nmedian sediment accumulation rates increased by an order of magnitude (from approximately 6 to 68 mg m-2 d-1) after the \npassage of Hurricane Maria in September of 2017 (a category 4 storm) and a large October 2017 storm that caused resuspension storm conditions (Hubbard et al., 1981; Hubbard, 1986). Measurements from 15 locations around St. Croix showed sediment \n530 \ntransport rates ranging from 0.009 to 0.3 Mm3 km-2yr-1 during non-storm conditions, and 0.09 to 1.5 Mm3 km-2yr-1 during storm \nconditions (Hubbard et al., 1981; Yates et al., 2017). Sediment trap studies along the southwest coast of Puerto Rico showed \nmedian sediment accumulation rates increased by an order of magnitude (from approximately 6 to 68 mg m-2 d-1) after the \npassage of Hurricane Maria in September of 2017 (a category 4 storm) and a large October 2017 storm that caused resuspension 25 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 which is considered heavy sedimentation and has been associated with fewer coral species, less live coral, lower coral growth \nrates, reduced coral recruitment and calcification rates, and slower rates of reef accretion (Rogers, 1990). Mean elevation- and area-normalized volume-change from 2016–2017 for habitats examined in our study increased \nsignificantly with water depth suggesting that, in addition to broad-scale sediment deposition across the study site, sediment \n540 \nwas also transported from shallower to deeper habitats (Fig. 5a and b). Notably, greatest increases in elevation (accretion) were \nassociated with habitats in water depths exceeding 11 m including aggregate reef, a sand lobe consisting of unconsolidated \nsediment, and ‘not classified’ habitat located seaward and near the base of the reef’s spur-and-groove formation, suggesting \nsome movement of sediment offshore and downslope (Fig. 4a, Table 2). Additionally, erosion was observed in the shallower, upslope grooves of the spur-and-groove formation, and accretion was observed in the deeper, downslope areas of the grooves \n545 \nfrom 2016 to 2017 further suggesting downslope, offshore movement of sediments (Fig. 10). The sand lobe at the base of the \nspur and groove formation also showed upslope erosion and considerable downslope (seaward) accretion, further suggesting \noffshore transport of sediments (Fig. 7d). Our observations are consistent with previous bathymetric change analyses \nconducted along the northern FRT from 2001 to 2008 (approximately 3 years before Hurricane Ivan and 3 years after Hurricane Katrina) that showed movement of up to 1.8 Mm3 of sediment between these time periods and transport of sediment from the \n550 \ninner shelf to offshore and beyond the shelf edge through gaps in the barrier reef and diabathic (cross-shore) channels during \nhigh-energy events or when the back reef overfills with sand (Finkl, 2004; Finkl and Vollmer, 2017). These observations are \nalso consistent with results of Yates et al. (2017) that show a multi-decadal trend along the FRT of reef sediment transport \ndown the fore-reef-slope and export offshore. Field observations of currents, waves, and reef sediment grain-size analyses Katrina) that showed movement of up to 1.8 Mm3 of sediment between these time periods and transport of sediment from the \n550 \ninner shelf to offshore and beyond the shelf edge through gaps in the barrier reef and diabathic (cross-shore) channels during \nhigh-energy events or when the back reef overfills with sand (Finkl, 2004; Finkl and Vollmer, 2017). These observations are \nalso consistent with results of Yates et al. (2017) that show a multi-decadal trend along the FRT of reef sediment transport \ndown the fore-reef-slope and export offshore. Field observations of currents, waves, and reef sediment grain-size analyses Katrina) that showed movement of up to 1.8 Mm3 of sediment between these time periods and transport of sediment from the \n550 \ninner shelf to offshore and beyond the shelf edge through gaps in the barrier reef and diabathic (cross-shore) channels during \nhigh-energy events or when the back reef overfills with sand (Finkl, 2004; Finkl and Vollmer, 2017). These observations are \nalso consistent with results of Yates et al. (2017) that show a multi-decadal trend along the FRT of reef sediment transport \ndown the fore-reef-slope and export offshore. Field observations of currents, waves, and reef sediment grain-size analyses coupled with integrated ocean-atmosphere-wave-sediment transport modelling during a one-year study at Crocker reef in the \n555 \nUpper Florida Keys showed that sediment mobility was primarily driven by wave stress exceeding critical shear stress; current \nstress alone only exceeded the critical shear stress for sediment mobility 5% of the time usually due to Florida Current eddies \n(Torres-Garcia et al., 2018). Torres-Garcia (2018) showed that nonbreaking wave stress (characteristic of quiescent sea states) \nmobilizes sand approximately 23 to 59% of the time; and fine-grained material is winnowed from the shallow areas of the reef and deposited to the flanks and offshore, particularly to the southwest. Furthermore, the critical stress threshold of gravel-sized \n560 \nmaterial was exceeded only 1 to 13% of the time, particularly during near-field tropical storm conditions (similar to Hurricane \nWilma, a category 3 hurricane) that cause breaking waves, mobilize and transport gravel material, and can cause physical reef \ndegradation (Torres-Garcia et al., 2018). https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 570 \n \nFigure 10. Elevation-change along Looe Key Reef spur and groove formation. (a) Upslope to downslope transects along Looe Key\nReef spur and groove formation (green lines); image source: 2019 NOAA National Geodetic Survey via NOAA Digital Coast, downlo\n11 September 2023, https://www.fisheries.noaa.gov/inport/item/63292 with structure from motion overlay image of Hatcher et al. (202\nAreas of erosion (red circles) and accretion (blue circles) along transect 1 between (b) 2016 and 2017, and between (c) 2017 and 2019. 575 \nAreas of erosion (red circles) and accretion (blue circles) along transect 2 between (d) 2016 and 2017, and between (e) 2017 and 2019. Elevation profiles from 2016, 2017, and 2019 for (f) transect 1 and (g) transect 2. Vertical red lines indicate net erosion and vertical blu\nlines indicate net accretion between 2016 and 2017. 570 Figure 10. Elevation-change along Looe Key Reef spur and groove formation. (a) Upslope to downslope transects along Looe Key \nReef spur and groove formation (green lines); image source: 2019 NOAA National Geodetic Survey via NOAA Digital Coast, downloaded \n11 September 2023, https://www.fisheries.noaa.gov/inport/item/63292 with structure from motion overlay image of Hatcher et al. (2022). Areas of erosion (red circles) and accretion (blue circles) along transect 1 between (b) 2016 and 2017, and between (c) 2017 and 2019. 575 \nAreas of erosion (red circles) and accretion (blue circles) along transect 2 between (d) 2016 and 2017, and between (e) 2017 and 2019. Elevation profiles from 2016, 2017, and 2019 for (f) transect 1 and (g) transect 2. Vertical red lines indicate net erosion and vertical blue \nlines indicate net accretion between 2016 and 2017. Figure 10. Elevation-change along Looe Key Reef spur and groove formation. (a) Upslope to downslope transects along Looe Key \nReef spur and groove formation (green lines); image source: 2019 NOAA National Geodetic Survey via NOAA Digital Coast, downloaded \n11 September 2023, https://www.fisheries.noaa.gov/inport/item/63292 with structure from motion overlay image of Hatcher et al. (2022). Areas of erosion (red circles) and accretion (blue circles) along transect 1 between (b) 2016 and 2017, and between (c) 2017 and 2019. 575 \nAreas of erosion (red circles) and accretion (blue circles) along transect 2 between (d) 2016 and 2017, and between (e) 2017 and 2019. Elevation profiles from 2016, 2017, and 2019 for (f) transect 1 and (g) transect 2. Southwest counter currents due to the formation of Florida Current eddies (Lee and \nWilliams, 1999) and WSW movement of sand wave features over a decadal time-period (Yates et al., 2019b) have also been and deposited to the flanks and offshore, particularly to the southwest. Furthermore, the critical stress threshold of gravel-sized \n560 \nmaterial was exceeded only 1 to 13% of the time, particularly during near-field tropical storm conditions (similar to Hurricane \nWilma, a category 3 hurricane) that cause breaking waves, mobilize and transport gravel material, and can cause physical reef \ndegradation (Torres-Garcia et al., 2018). Southwest counter currents due to the formation of Florida Current eddies (Lee and \nWilliams, 1999) and WSW movement of sand wave features over a decadal time-period (Yates et al., 2019b) have also been observed near LKR. Results from these previous studies suggest that some sediment transport observed in our study could be \n565 \ndue to persistent transport of sand during quiescent sea state conditions; however, the large volume of material transported \n(including gravel-sized and larger reef rubble) during the short time-period of our study from 2016 to 2017 was likely due \nprimarily to storm conditions caused by Hurricane Irma. observed near LKR. Results from these previous studies suggest that some sediment transport observed in our study could be \n565 \ndue to persistent transport of sand during quiescent sea state conditions; however, the large volume of material transported \n(including gravel-sized and larger reef rubble) during the short time-period of our study from 2016 to 2017 was likely due \nprimarily to storm conditions caused by Hurricane Irma. observed near LKR. Results from these previous studies suggest that some sediment transport observed in our study could be \n565 \ndue to persistent transport of sand during quiescent sea state conditions; however, the large volume of material transported \n(including gravel-sized and larger reef rubble) during the short time-period of our study from 2016 to 2017 was likely due \nprimarily to storm conditions caused by Hurricane Irma. 26 Vertical red lines indicate net erosion and vertical blue \nlines indicate net accretion between 2016 and 2017. 580 27 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 Approximately 16.5 months after Hurricane Irma (during a 13-month period between 2017 and 2019), net erosion was observed \nacross all habitats with mean elevation-change of -0.15 (annualized elevation change-rate of -139 mm yr-1), net volume change \nup to -2.46 Mm3, and area-normalized volume change of -0.15 Mm3km-2. Newly deposited carbonate sediments typically have \nporosities of 40 to 70% (Choquette and Pray, 1970) at shallow sediment depths of a few hundreds of meters (Schmoker and Halley, 1982). Porosity of carbonate sands on the FRT and in Hawk Channel ranges from 60 to 72% in the upper 22 cm of \n585 \ndeposited sediment (Walter et al. 2007). Schmoker and Halley (1982) showed that there is little or no sediment porosity loss \nat near-surface sediment depths. Application of their exponential function for porosity versus depth of sediment (porosity (%) \n= 41.73e-z/2498, where z = depth below sediment surface) indicates that the decrease in porosity of deposited carbonate sediments \nat 2 m below the sediment-surface is only 0.03%. Carbonate sands have settling velocities ranging from 0.025 to 0.364 m s-1 Halley, 1982). Porosity of carbonate sands on the FRT and in Hawk Channel ranges from 60 to 72% in the upper 22 cm of \n585 \ndeposited sediment (Walter et al. 2007). Schmoker and Halley (1982) showed that there is little or no sediment porosity loss \nat near-surface sediment depths. Application of their exponential function for porosity versus depth of sediment (porosity (%) \n= 41.73e-z/2498, where z = depth below sediment surface) indicates that the decrease in porosity of deposited carbonate sediments \nat 2 m below the sediment-surface is only 0.03%. Carbonate sands have settling velocities ranging from 0.025 to 0.364 m s-1 585 (Riazi et al., 2020). Satellite imagery shows the sediment plume caused by resuspension of sediment during Hurricane Irma \n590 \ncleared within approximately 5 days of the storm’s passing (NASA, 2023). Therefore, it is likely that resuspended sediment \nsettled quickly (within days) when storm conditions subsided; and it is unlikely that the decrease in elevation observed between \n2017 and 2019 was caused by compaction of sediment after the storm. This suggests that approximately 50% of sediment \ndeposited between 2016 and 2017 was eroded by 2019 due to physical transport away from the study site. The sand wave and (Riazi et al., 2020). Satellite imagery shows the sediment plume caused by resuspension of sediment during Hurricane Irma \n590 \ncleared within approximately 5 days of the storm’s passing (NASA, 2023). Therefore, it is likely that resuspended sediment \nsettled quickly (within days) when storm conditions subsided; and it is unlikely that the decrease in elevation observed between \n2017 and 2019 was caused by compaction of sediment after the storm. This suggests that approximately 50% of sediment \ndeposited between 2016 and 2017 was eroded by 2019 due to physical transport away from the study site. The sand wave and reef rubble field showed continued erosion between 2017 to 2019 with some evidence for migration of the crest of the rubble \n595 \nfield back toward its original 2016 position indicated in the elevation profile (Fig. 6 and 7). Shallow areas between the scour \nmarks showed erosion, while the scour mark pits showed infilling (Fig. 6 and 7). Spurs of the spur-and-groove formation \nprimarily showed erosion, while shallow (landward) sections of grooves showed some accretion, likely due to transport of \nsediments from spurs to grooves and downslope from the shallow reef (Fig. 10). Deeper (seaward) areas of grooves and the reef rubble field showed continued erosion between 2017 to 2019 with some evidence for migration of the crest of the rubble \n595 \nfield back toward its original 2016 position indicated in the elevation profile (Fig. 6 and 7). Shallow areas between the scour \nmarks showed erosion, while the scour mark pits showed infilling (Fig. 6 and 7). Spurs of the spur-and-groove formation \nprimarily showed erosion, while shallow (landward) sections of grooves showed some accretion, likely due to transport of \nsediments from spurs to grooves and downslope from the shallow reef (Fig. 10). Deeper (seaward) areas of grooves and the reef rubble field showed continued erosion between 2017 to 2019 with some evidence for migration of the crest of the rubble \n595 \nfield back toward its original 2016 position indicated in the elevation profile (Fig. 6 and 7). Shallow areas between the scour \nmarks showed erosion, while the scour mark pits showed infilling (Fig. 6 and 7). Spurs of the spur-and-groove formation \nprimarily showed erosion, while shallow (landward) sections of grooves showed some accretion, likely due to transport of \nsediments from spurs to grooves and downslope from the shallow reef (Fig. 10). Deeper (seaward) areas of grooves and the sand lobe located at the base of the spur and groove formation showed erosion (Fig. 4 and 6k) suggesting continued downslope, \n600 \noffshore transport of sediments. Historical aerial and satellite imagery from before and after the passing of Hurricane Irma \ncorroborates our elevation-change observations (Fig. 9). Imagery from 2014 and March 2017 shows that major geomorphic \nfeatures of Looe Key proper such as distribution of seagrass beds and the size and position of the sand lobe and rubble fields \nwere relatively static between these time periods leading up to Hurricane Irma (Fig. 9a and b). Imagery from December 2017, sand lobe located at the base of the spur and groove formation showed erosion (Fig. 4 and 6k) suggesting continued downslope, \n600 \noffshore transport of sediments. Historical aerial and satellite imagery from before and after the passing of Hurricane Irma \ncorroborates our elevation-change observations (Fig. 9). Imagery from 2014 and March 2017 shows that major geomorphic \nfeatures of Looe Key proper such as distribution of seagrass beds and the size and position of the sand lobe and rubble fields \nwere relatively static between these time periods leading up to Hurricane Irma (Fig. 9a and b). Imagery from December 2017, 3 months after Hurricane Irma passed, shows broad scale sediment deposition and burial of seagrass beds in the shallow areas \n605 \nof the reef proper, erosion and exposure of deeper, downslope spur-and-groove formation and downslope deposition on the \nsand lobe (Fig. 9c). Imagery from 2019 shows re-exposure of some shallow seagrass beds and deep spur-and-groove formation \nas sediments were eroded (Fig. 9d). Historical areal imagery from 1975 (Fig. 9e, Lidz et al., 2016) shows a distribution of \nseagrass, presence of rubble fields, and patterns of sediment along the sand lobe similar to 2014 and 2017 imagery (before 3 months after Hurricane Irma passed, shows broad scale sediment deposition and burial of seagrass beds in the shallow areas \n605 \nof the reef proper, erosion and exposure of deeper, downslope spur-and-groove formation and downslope deposition on the \nsand lobe (Fig. 9c). Imagery from 2019 shows re-exposure of some shallow seagrass beds and deep spur-and-groove formation \nas sediments were eroded (Fig. 9d). Historical areal imagery from 1975 (Fig. 9e, Lidz et al., 2016) shows a distribution of \nseagrass, presence of rubble fields, and patterns of sediment along the sand lobe similar to 2014 and 2017 imagery (before 3 months after Hurricane Irma passed, shows broad scale sediment deposition and burial of seagrass beds in the shallow areas \n605 \nof the reef proper, erosion and exposure of deeper, downslope spur-and-groove formation and downslope deposition on the \nsand lobe (Fig. 9c). Imagery from 2019 shows re-exposure of some shallow seagrass beds and deep spur-and-groove formation \nas sediments were eroded (Fig. 9d). Historical areal imagery from 1975 (Fig. 9e, Lidz et al., 2016) shows a distribution of \nseagrass, presence of rubble fields, and patterns of sediment along the sand lobe similar to 2014 and 2017 imagery (before Hurricane Irma) indicating these features have persisted over the past several decades despite repeated impact from tropical \n610 \nand seasonal storms. Lidz et al. (2016) suggested the formation of rubble fields in the shallow back reef area is mainly due to \nhistorical passage of hurricanes and winter storms, and our elevation change results suggest that these structures continue to \nmigrate in response to storm conditions. Lidz et al. (2016) also suggested that transport of sediment during hurricanes was Hurricane Irma) indicating these features have persisted over the past several decades despite repeated impact from tropical \n610 \nand seasonal storms. Lidz et al. (2016) suggested the formation of rubble fields in the shallow back reef area is mainly due to \nhistorical passage of hurricanes and winter storms, and our elevation change results suggest that these structures continue to \nmigrate in response to storm conditions. Lidz et al. (2016) also suggested that transport of sediment during hurricanes was Hurricane Irma) indicating these features have persisted over the past several decades despite repeated impact from tropical \n610 \nand seasonal storms. Lidz et al. (2016) suggested the formation of rubble fields in the shallow back reef area is mainly due to \nhistorical passage of hurricanes and winter storms, and our elevation change results suggest that these structures continue to \nmigrate in response to storm conditions. Lidz et al. (2016) also suggested that transport of sediment during hurricanes was 28 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 primarily to the north; however, our observations showed primary sediment movement during Hurricane Irma was WSW and \ndownslope from shallow to deep habitats with apparent seaward movement of the sand lobe after the storm passed. 615 615 elevation-change rate of -1.4 mm yr-1 between 1934 and 2004 (Yates et al., 2017). Furthermore, six of nine habitats at LKR \n620 \nshowed elevation loss over those periods, with greatest losses associated with shallow habitats, and mean elevation and \nvolume gains in deep-water habitats including at the base of the spur-and-groove habitat, indicating transport of reef \nsediments down the fore-reef-slope and export offshore (Yates et al., 2017). Our observed rate of mean elevation loss \nbetween 2017 and 2019 (-139 mm yr-1) was two orders of magnitude higher than the multi-decadal rates of Yates et al. (2017). Additionally, elevation loss (erosion) showed a moderate correlation with water depth, and mean elevation losses \n625 \nduring 2017 to 2019 were significantly greater in habitats with larger mean elevation gains during 2016 to 2017, suggesting \nthat sediment distribution was re-equilibrating or stabilizing to quiescent sea-state conditions up to 16.5 months after the \nstorm. The annualized mean rate of elevation-change for LKR from the 2.5-year period between July 2016 to January 2019 examined \nin our study, including sediment accretion from Hurricane Irma and the post-storm erosion and re-equilibration, was \n630 \napproximately 72 mm yr-1, which is almost double the rate of accretion observed in the previous decade of 32.5 mm yr-1 (Yates \net al. 2019b). Numerous field reconnaissance observations immediately after the passing of Hurricane Irma indicated \nbroadscale sediment deposition across the FRT due to the storm (e.g., Viehman et al., 2018; Walker, 2018; Wilson et al., 2020; \nKobelt et al. 2019). Our 2016 to 2019 elevation-change rate is consistent with annualized mean elevation-change rates from The annualized mean rate of elevation-change for LKR from the 2.5-year period between July 2016 to January 2019 examined \nin our study, including sediment accretion from Hurricane Irma and the post-storm erosion and re-equilibration, was \n630 \napproximately 72 mm yr-1, which is almost double the rate of accretion observed in the previous decade of 32.5 mm yr-1 (Yates \net al. 2019b). 5 Conclusion High-resolution lidar and multibeam bathymetric data were used to quantify seafloor elevation and volume change within the \nLooe Key Reef system of the Florida Keys Reef Tract over a 2.5-year period from 2016–2019 and to examine impacts from \ncategory-4 Hurricane Irma and post-storm re-equilibration of seafloor sediments. Analysis of seafloor elevation and volume \nchange over a 16.5-month period from July 2016 to December 2017 showed Hurricane Irma caused broadscale deposition of \n655 \nsediments across all benthic habitats of this reef system and burial of seagrass and coral dominated habitat. Rates of net \nelevation change were one order of magnitude greater during this short-term period that included storm impacts from Hurricane \nIrma than for the previous decade (Yates et al., 2019). Major seafloor geomorphic features such as sand waves and rubble \nfields migrated 10s of meters to the WSW in response to predominant wind conditions during the passing of Hurricane Irma, \nand sediment accretion was significantly greater in deep habitats than shallow habitats, suggesting downslope and offshore \n660 \ntransport of seafloor sediment. High-resolution lidar and multibeam bathymetric data were used to quantify seafloor elevation and volume change within the \nLooe Key Reef system of the Florida Keys Reef Tract over a 2.5-year period from 2016–2019 and to examine impacts from \ncategory-4 Hurricane Irma and post-storm re-equilibration of seafloor sediments. Analysis of seafloor elevation and volume change over a 16.5-month period from July 2016 to December 2017 showed Hurricane Irma caused broadscale deposition of \n655 \nsediments across all benthic habitats of this reef system and burial of seagrass and coral dominated habitat. Rates of net \nelevation change were one order of magnitude greater during this short-term period that included storm impacts from Hurricane \nIrma than for the previous decade (Yates et al., 2019). Major seafloor geomorphic features such as sand waves and rubble \nfields migrated 10s of meters to the WSW in response to predominant wind conditions during the passing of Hurricane Irma, \nand sediment accretion was significantly greater in deep habitats than shallow habitats, suggesting downslope and offshore \n660 \ntransport of seafloor sediment. 655 Loss of mean elevation and volume in all habitats in the period following the storm (from December 2017 to January 2019) \nindicated that 35% to 50% of sediment deposited during the storm had eroded by approximately 16.5 months after the storm \nand that erosion rates were two orders of magnitude greater than historical, multi-decadal rates of erosion. https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 Table 5. Annualized mean elevation-change rates (mm yr-1) for event-driven to multi-decadal time periods at the Florida Keys \nReef Tract. Annualized mean elevation change rate (mm yr-1) \nLocation \nEvent-drivena \n2016 to 2017 \nPost-stormb \n2017 to 2019 \nShort-termc \n2016 to 2019 \nDecadal \n2004 to 2016 \nMulti-decadal \n1930s to 2000s \nLooe Key Reef \n247 \n-139 \n72 \n32.5d \n-4.5e \nLower Florida Reef Tract \n(south of Big Pine) \nna \nna \n84f \nna \nna \nFlorida Reef Tract (Miami to \nKey West) \nna \nna \n76f \nna \nna \nUpper Florida Reef Tract \n(Elliott Key to Tavernier Key) \nna \nna \nna \nna \n-1.4e \na = calculated assuming a total time-period of 16.5 months (13.5 month pre- to 3 months post-storm); b = total time period 13.5 months (3 to 16.5 months \npost-storm); c = total time-period approximately 30 months (13.5 months pre- to 16.5 months post-storm); d = using data from Yates et al., 2019; e = using \ndata from Yates et al., 2017; f = using data from Fehr et al., 2021; na = no data available. 0 Table 5. Annualized mean elevation-change rates (mm yr-1) for event-driven to multi-decadal time periods at the Florida Keys \nReef Tract Table 5. Annualized mean elevation-change rates (mm yr-1) for event-driven to multi-decadal time per\nReef Tract. elevation-change rates (mm yr-1) for event-driven to multi-decadal time periods at the Florida Keys a = calculated assuming a total time-period of 16.5 months (13.5 month pre- to 3 months post-storm); b = total time period 13.5 months (3 to 16.5 months \npost-storm); c = total time-period approximately 30 months (13.5 months pre- to 16.5 months post-storm); d = using data from Yates et al., 2019; e = using \ndata from Yates et al., 2017; f = using data from Fehr et al., 2021; na = no data available. 650 Numerous field reconnaissance observations immediately after the passing of Hurricane Irma indicated \nbroadscale sediment deposition across the FRT due to the storm (e.g., Viehman et al., 2018; Walker, 2018; Wilson et al., 2020; \nKobelt et al. 2019). Our 2016 to 2019 elevation-change rate is consistent with annualized mean elevation-change rates from 2016 to 2019 for the Lower FRT from approximately Big Pine Key to Key West of 84 mm yr-1, and for the FRT from Miami \n635 \nto Key West of 76 mm yr-1 (Fehr et al., 2021), further suggesting that sediment distribution may have still been undergoing \npost-storm re-equilibration at our study site and along the broader FRT (Table 5). Collection and analysis of additional elevation-change data sets over shorter time-periods (e.g., seasonal to annual) could Collection and analysis of additional elevation-change data sets over shorter time-periods (e.g., seasonal to annual) could \nimprove characterization of post-storm elevation-change rates and duration of post-storm sediment re-equilibration periods \n640 \nrelative to persistent seasonal, interannual, decadal, and multi-decadal time periods. Our results also suggest that caution should \nbe used in selection of DEMs for use in elevation change and projection modelling to minimize bias that could result from \nselecting elevation surfaces that reflect periods of rapid elevation change due to storm impacts and periods of post-storm re-\nequilibration. improve characterization of post-storm elevation-change rates and duration of post-storm sediment re-equilibration periods \n640 \nrelative to persistent seasonal, interannual, decadal, and multi-decadal time periods. Our results also suggest that caution should \nbe used in selection of DEMs for use in elevation change and projection modelling to minimize bias that could result from \nselecting elevation surfaces that reflect periods of rapid elevation change due to storm impacts and periods of post-storm re-\nequilibration. 645 29 5 Conclusion Sediment erosion \n665 \nafter the storm (2017–2019) was moderately correlated with depth and was significantly greater in habitats that showed greater \naccumulation during the period including Hurricane Irma from 2016–2017, suggesting a period of rapid sediment re-\nequilibration after the storm. Historical satellite and aerial imagery show that major geomorphic features at this location \nincluding rubble fields, sand waves, and a sand lobe at the base of the spur-and-groove formation have persisted over the past several decades despite impacts from storms. However, our elevation-change results indicate these features are highly \n670 \nephemeral, migrating rapidly during storms, re-equilibrating to non-storm sea state conditions between storms, and periodically \nburying seafloor habitat such as seagrass. Such features and the area surrounding them likely represent localized areas of long- \nand short-term seafloor instability that could be less suitable for restoration of slow growing benthic species. Our observed several decades despite impacts from storms. However, our elevation-change results indicate these features are highly \n670 \nephemeral, migrating rapidly during storms, re-equilibrating to non-storm sea state conditions between storms, and periodically \nburying seafloor habitat such as seagrass. Such features and the area surrounding them likely represent localized areas of long- \nand short-term seafloor instability that could be less suitable for restoration of slow growing benthic species. Our observed 30 Data availability Elevation-change and multibeam bathymetric data are publicly available in U.S. Geological Survey Data Releases at \nhttps://doi.org/10.5066/P9CHC95D, \nhttps://doi.org/10.5066/P937LNZF, \nhttps://doi.org/10.5066/P9NXNX61, \nhttps://doi.org/10.5066/P9JTOOMB and https://doi.org/10.5066/P9P2V7L0. Lidar topobathymetric data are publicly available \n690 \nfrom \nthe \nNOAA \nOffice \nfor \nCoastal \nManagement \nat \nhttps://www.fisheries.noaa.gov/inport/item/63018 \nand \nhttps://www.fisheries.noaa.gov/inport/item/48373. Seafloor habitat data are publicly available from the Florida Fish and \nWildlife \nConservation \nCommission, \nFish \nand \nWildlife \nResearch \nInstitute \nat \nhttp://ocean.floridamarine.org/IntegratedReefMap/UnifiedReefTract.htm. p\ng\ng\np\n \n695 \nAuthor contribution \nKY and DZ conceptualized the research, data acquisition approach, and methodology for analysis of seafloor elevation data. KY, ZF, and DZ performed formal analysis of data. DZ developed the SECAT software for statistical analysis of elevation- \nand volume-change data. KY and ZF developed data interpretations and prepared the original manuscript draft with \ncontributions from SJ and DZ. All authors contributed to preparation of the final, published manuscript. 700 \n \nCompeting interests 695 \nAuthor contribution \nKY and DZ conceptualized the research, data acquisition approach, and methodology for analysis of seafloor elevation data. KY, ZF, and DZ performed formal analysis of data. DZ developed the SECAT software for statistical analysis of elevation- \nand volume-change data. KY and ZF developed data interpretations and prepared the original manuscript draft with \ncontributions from SJ and DZ. All authors contributed to preparation of the final, published manuscript. 700 Code availability Python script for the Seafloor Elevation Change Analysis Tool (SECAT), intended to be applied in ArcMap or ArcGIS Pro, is \npublicly \navailable \nas \na \nU. S. Geological \nSurvey \nsoftware \nrelease, \ndoi: \n10.5066/P9D5UUZ0, \nhttps://www.usgs.gov/software/seafloor-elevation-change-analysis-tool. Python script for the Seafloor Elevation Change Analysis Tool (SECAT), intended to be applied in ArcMap or ArcGIS Pro, is \npublicly \navailable \nas \na \nU. S. Geological \nSurvey \nsoftware \nrelease, \ndoi: \n10.5066/P9D5UUZ0, \nhttps://www.usgs.gov/software/seafloor-elevation-change-analysis-tool. https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 rates of elevation change in the 16-month period after Hurricane Irma were one to two orders of magnitude greater than during \nthe past decade or multi-decadal period (Yates et al., 2017; 2019b) indicating seafloor sediments across all habitats may have \n675 \nstill been re-equilibrating to non-storm sea state conditions up January 2019. Higher resolution elevation-change data collected \nover seasonal and annual time periods could improve characterization and understanding of short-term (event-driven, seasonal, \ninterannual) and long-term (decadal to multi-decadal) rates and processes of seafloor change and help guide benthic habitat \npost-storm recovery and restoration efforts in topographically complex coral reef systems. https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 https://doi.org/10.5194/egusphere-2023-3000\nPreprint. Discussion started: 22 December 2023\nPub ic domain CC\n1.0. l\n. 0 Acknowledgement Funding for this study was provided by the U.S. Geological Survey, Coastal and Marine Hazards and Resources Program and \n710 \nby 2018 Hurricane and Wildfire Supplemental Funding provided to the U.S. Geological Survey from the Additional \nSupplemental Appropriations for Disaster Relief Requirements Act of 2018 (P.L. 115-123). We would like to thank J.J. Fredericks, B.J. Reynolds, and A.S. Farmer for collection of the multibeam bathymetry data and J.J. Fredericks for \ndevelopment of the associated multibeam digital elevation model. We also thank J. Zieg for assistance with development of Funding for this study was provided by the U.S. Geological Survey, Coastal and Marine Hazards and Resources Program and \n710 \nby 2018 Hurricane and Wildfire Supplemental Funding provided to the U.S. Geological Survey from the Additional \nSupplemental Appropriations for Disaster Relief Requirements Act of 2018 (P.L. 115-123). We would like to thank J.J. Fredericks, B.J. Reynolds, and A.S. Farmer for collection of the multibeam bathymetry data and J.J. Fredericks for \ndevelopment of the associated multibeam digital elevation model. We also thank J. Zieg for assistance with development of the SECAT software and K. Murphy for assistance with development of methods for sub-sampling large-scale digital elevation \n715 \nmodels. We greatly appreciate reviews of the original draft manuscript and constructive comments from L. Toth and G. Hatcher. Competing interests The authors declare that they have no conflict of interest. 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G., and Arsenault, S.R.: Seafloor elevation change from 2016 to 2017 at Looe Key, Florida Keys—\nImpacts from Hurricane Irma (ver. 2.0, November 2020), U.S. Geological Survey data release, USGS [data set], \nhttps://doi.org/10.5066/P937LNZF, 2019a. 5 Yoshida, K., Kajikawa, Y., Nishiyama, S., Islam, M.T., Adachi, S., and Sakai, K.: Three-dimensional numerical modelling \n1050 \nof floods in river corridor with complex vegetation quantified using airborne LiDAR imagery, J. Hydraul. Res., 1–21, \nhttps://www.tandfonline.com/doi/full/10.1080/00221686.2022.2106596, 2022. Zieg, J. A. and Zawada, D. G.: Seafloor Elevation Change Analysis Tool, U. S. Geological Survey software release, USGS \n[code], doi: 10.5066/P9D5UUZ0, 2021. 1055 Zitello, A. G., Bauer, L. J., Battista, T. A., Mueller, P. W., Kendall, M. S., and Monaco, M. E.: Shallow-water benthic \nhabitats of St. John, U.S. Virgin Islands, NOAA technical memorandum NOS NCCOS, 96, 53 pp. 42 42"
https://openalex.org/W4388751076
http://journals.uqs-ye.info/index.php/uqs/article/download/22/18
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شبهات حول حجية اللغة في التفسير
Maǧallaẗ ǧāmiʿaẗ al-Qurʾān al-karīm wa-al-ʿulūm al-islāmiyyaẗ
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 òÌÜÛa @ À @ ÐnÛa pb @ Þìy @ òîvy @a @@@@@@@ bèj’  òÌÜÛa @ À @ ÐnÛa pb @ Þìy @ òîvy @a @@@@@@@ bèj’ ﺩ ﺍﳋﺎﻣﺲ ﺍﻟﻌﺪﺩ ﺣﻮﻟﻴﺔ •ﺣ ﻀﻰ ﺍﻟﻠﻐﺔ،)(١ ﻑ ﺍﻟﺒﻴﺎﻥ ﺇﱃ ﻡﺎﻜﺣﻷﺍ «. ﺎﻥ ﻋﻨﻪ ﻋﻠﻴﻪ ﺍﻟﻘﺮﺁﻥ ﲟﻘﺘﻀ ﻢﻬﻨ . ﻲﻫﻭ : ، ﻓﻘﺪ ﺃﺿﺎﻑ ﻮﻝ ﻋﻠﻰ ﺑﻴﺎﻥ ﺎ ﻓﻴﻪ ﺑﻴﺎ ﻭﺭﺩ ﺯﺍﻮﺟ ﲑﺴﻔﺗ ﺔ ﻘﻘﶈﺍﻭ ﲔ ﻨﻣ n ﻞﺤﻨﻟﺍ ٤٤ : ﻚ) .(٢ ﻪ : »ﻪﻧﺇ ﻮﻤﳏ ﻪﻨﻋ  ﺎﻤﻴﻓ ...
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https://europepmc.org/articles/pmc4474600?pdf=render
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Changes in Extremely Hot Summers over the Global Land Area under Various Warming Targets
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Changes in Extremely Hot Summers over the Global Land Area under Various Warming Targets Lei Wang, Jianbin Huang*, Yong Luo, Yao Yao, Zongci Zhao Lei Wang, Jianbin Huang*, Yong Luo, Yao Yao, Zongci Zhao Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, and Joint Center for...
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PLOS BIOLOGY PLOS BIOLOGY PLOS BIOLOGY RESEARCH ARTICLE OPEN ACCESS Citation: Zhong Q, Roumeliotis TI, Kozik Z, Cepeda-Molero M, Ferna´ndez LA´, Shenoy AR, et al. (2020) Clustering of Tir during enteropathogenic E. coli infection triggers calcium influx–dependent pyroptosis in intestinal epithelial cells. PLoS Biol 18(...
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Notes ON THE SUPERSTITIONS OF MENSTRUATION.
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