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39 results for “coastal protection”
Data from Bieri Thesis: Evaluating Coastal Protection Benefits of Restored Oyster Reef Designs - 2022
This dataset consists of spreadsheets used in the creation of: "Elizabeth Bieri, Evaluating Coastal Protection Benefits of Restored Oyster Reef Designs. MS Thesis, University of Virginia, Charlottesville, VA. Advisors: Matthew Reidenbach & Patricia Wiberg, 2022" (https://doi.org/10.18130/2b04-wz72). Documentation on methods and types of data are given in the thesis and are not repeated here. There are two .zip files. One contains the original Excel workbooks. The other contains the data from individual sheets within the workbooks as comma-separated-value (.csv) text files. The file listing for the CSV files are: Archive: Bieri_Comma_separated_Value_Files.zip Length Date Time Name --------- ---------- ----- ---- 0 2025-12-15 12:47 Bieri_Comma_separated_Value_Files/ 1787 2025-12-15 12:41 Bieri_Comma_separated_Value_Files/elevation_crests.csv 239 2025-12-15 12:41 Bieri_Comma_separated_Value_Files/elevation_S4.csv 273 2025-12-15 12:41 Bieri_Comma_separated_Value_Files/elevation_S7.csv 652 2025-12-15 12:45 Bieri_Comma_separated_Value_Files/erosionpins_exposed.csv 476 2025-12-15 12:45 Bieri_Comma_separated_Value_Files/erosionpins_exposed_no_reef.csv 102 2025-12-15 12:46 Bieri_Comma_separated_Value_Files/erosionpins_S4.csv 97 2025-12-15 12:46 Bieri_Comma_separated_Value_Files/erosionpins_S7.csv 297 2025-12-15 12:41 Bieri_Comma_separated_Value_Files/grainsize_july.csv 290 2025-12-15 12:41 Bieri_Comma_separated_Value_Files/grainsize_oct.csv 399 2025-12-15 12:41 Bieri_Comma_separated_Value_Files/infauna_om_All.csv 509 2025-12-15 12:41 Bieri_Comma_separated_Value_Files/infauna_om_July2021.csv 507 2025-12-15 12:41 Bieri_Comma_separated_Value_Files/infauna_om_Oct2021.csv 1242 2025-12-15 12:41 Bieri_Comma_separated_Value_Files/infauna_om_Sed_OM.csv 516 2025-12-15 12:41 Bieri_Comma_separated_Value_Files/infauna_om_Sept2020.csv 913981 2025-12-15 12:41 Bieri_Comma_separated_Value_Files/jul2021waveS4.csv 715881 2025-12-15 12:41 Bieri_Comma_separated_Value_Files/jul2021waveS7.csv 5251
Data: Cutting the costs of coastal protection by integrating vegetation in flood defences.
<p>File: levee_crest_height_reduction_per_country_version_July2021.nc<br>Fields: (1) Crest height reduction m per km along the populated coastline susceptible to flooding (return period = 100 years)<br> (2) Crest height reduction cost saving per country in million USD<sub>2005</sub> PPP along the populated coastline susceptible to flooding (return period = 100 years)<br> (3) Cost savings as percentage of GDP<sub>2005</sub> along the urban populated coastline susceptible to flooding (return period = 100 years)</p> <p>File: transectdata_version_July2021.nc<br> Transectdata of vegetated transects within the study area.<br>Fields: <br>(1) rps = return period <br>(2) fid = id of the transects<br>(3) centroids = coordinates of the transects<br>(4) inun = (1) in area susceptible to flooding<br>(5) urban = (1) in urban area, (0) not in urban area<br>(6) veg_width = derived coastal vegetation belt width along the foreshore<br>(7) veg_type = derived coastal vegetation type along the foreshore (1: salt marshes, 2: mangroves)<br>(8) hsig = Offshore significant wave heights (multiple return periods) corresponding to the transects<br>(9) wave period = Offshore peak wave period (multiple return periods) corresponding to the transects<br>(10) surge = Extreme water level combination of surge and tide (m +MSL) (multiple return periods)<br>(11) veg_z0 = elevation at the start of the vegetated zone (m +MSL)<br>(12) hrms_end_noveg = root mean square wave height at the end of the foreshore (without vegetation) (multiple return periods)<br>(13) hrms_endveg = root mean square wave height at the end of the foreshore (with vegetation) (multiple return periods) <br>(14) pdens_15km = population density derived using buffer of 15 kilometre radius</p>
Assessment of current and future invasive plants in protected dune habitats of the Atlantic coastal region for the LIFE DUNIAS project (LIFE20 NAT/BE/001442)
<p>This .csv file contains the raw data from the risk screening supplementing the LIFE DUNIAS horizon scan for (invasive) alien species in protected habitats of Atlantic coastal dune ecosystems (<a href="https://doi.org/10.21436/inbor.86703335">Adriaens et al. 2022</a>). We gladly refer to the annexes and methods section in this report for more explanation about the fields and their contained values.</p> <p>The file contains the following fields:</p> <p><em>TaxonName</em>: original taxonomic name of the considered alien species</p> <p><em>WorkName</em>: taxonomic name of the considered alien species after lumping of subspecies, closely related species of a complex, functionally similar species of the same genus (see chapter 3.1)</p> <p><em>hab_xxxx</em> (1110, 1130, 1140, 1210, 1230, 1310, 1320, 1330, 2110, 2120, 2130, 2140, 21A0, 2150, 2190, 2160, 2170, 2180): susceptibility of habitat for the alien species (4-digit code refering to the Annex I habitat under the Habitats Directive) </p> <p><em>occ_XX</em> (BE, FR, IE, NL, ES, UK, DK, DE, PT, ALL): occupancy of the alien species in different countries of the Atlantic European region (as the number of 10km<sup>2</sup> squares per country). Country codes: BE = Belgium, FR = France, IE = Ireland, NL = Netherlands, ES = Spain, UK = United Kingdom, DK = Denmark, DE = Germany, PT = Portugal, ALL = total for all countries.</p> <p><em>scor_XXX_xxxx</em>: score of the assessment per criterium (INT = introduction, EST = establishment, SPR = spread, IMP = ecological impact, ALL = overall score) and per habitat group (salt = salties, sand = sandies, shru = shrubbies) conf_<em>XXX_xxxx</em>: confidence on the scores of the assessment per criterium (INT = introduction, EST = establishment, SPR = spread, IMP = ecological impact, ALL = overall score) and per habitat group (salt = salties, sand = sandies, shru = shrubbies)</p> <p><em>scor_ALL_MAX</em>: maximum ecological impact score of the alien taxon across all habitats</p>
Fig. 5 in Assessment of coastal fish assemblages before the establishment of a new marine protected area in the central Mediterranean: its role in formulating a zoning proposal Abstract
Fig. 5: Size class frequency distributions of species of recreational value (i.e. attractive for SCUBA diving) recorded along the transects at each sector and depth range.
Fig. 4 in Assessment of coastal fish assemblages before the establishment of a new marine protected area in the central Mediterranean: its role in formulating a zoning proposal Abstract
Fig. 4: Total density (mean number of individuals/125 m2 ± S.E.) of fishes recorded along the transects at each (a) sector and (b) depth range.
Fig. 2 in Assessment of coastal fish assemblages before the establishment of a new marine protected area in the central Mediterranean: its role in formulating a zoning proposal Abstract
Fig. 2: Scatter plot of the canonical analysis of principal coordinates (CAP) based on the Bray–Curtis dissimilarities on the effects of (a) habitat type (RAR=rocky-algal reef; POM=Posidonia oceanica meadow; SOB=soft bottom) and (b) depth range.
High resolution Sea Surface Wind retrieval over coastal Protected Areas by means of Sentinel-1 data
<p><br> The algorithm used, i.e. SARWIND LG-Mod ver. v4.01 (see reference below), is aimed at producing the Sea Surface Wind (SSW), i.e. Speed and Direction, from a single co-polarized (VV or HH) SAR image. We used EW (Extended Wide) and IW (Interferometric Wide) Swath Mode GRD (Ground Range, Multi-Look, Detected) HR (High Resolution) Sentinel-1 images, with pixel spacings of 40m x 40m and 10m x 10m (azimuth x range) respectively. Associated auxiliary products were obtained from ESA SNAP 5.0 release. SSW fields were provided for the two coastal Protected Areas (PAs) named Camargue and Wadden Sea.</p> <p>Each output folder of the SARWIND LG-Mod results contains useful plots and the estimated SSW field, provided in the file 'SAR_Sigma0_pp_decimationL2P2Tn_gradientOptSobel_LGMod_Results.txt' (pp = VV or HH; n = smoothing/decimation level), which is in the sub-folder 'LG-Mod_Theoretical_Results/Results_MEdegTHxx.xxx_Fisher (where xx.xxx is the final threshold applied). This txt file reports the following 19 columns:</p> <p><br> 1) LAT; 2) LON; 3) AZI; 4) RNG; [Location of the centre of the processed AOI]</p> <p>5) REF_U; 6) REF_V; 7) REF_W; 8) REF_D; [ECMWF reference wind, as U/V components and speed/direction]</p> <p>9) SAR_U; 10) SAR_V; 11) SAR_W; 12) SAR_D; [SARWIND LG-Mod wind estimates, as U/V components and speed/direction]</p> <p>Both REF_D and SAR_D are wind directions (expressed in degrees) with respect to the geographic North (0°=North, 90°=East, 180°=South, 270°=West), that the wind is blowing to.<br> Both REF_W and SAR_W are wind speeds (expressed in m/s).<br> Regarding REF_U/SAR_U and REF_V/SAR_V, note that a positive U component represents wind blowing to the East; a positive V component represents wind blowing to the North.</p> <p>13) SceneCentre_TrueHeading_FF; [Mean angle formed between the geographical South-North direction and the SAR azimuth direction (wrt the centre of the SAR Full-Frame image)]</p> <p>SceneCentre_TrueHeading_FF is a positive clockwise angle. In particular: SceneCentre_TrueHeading_FF is in ]180,360[ [deg].<br> Thus:<br> Descending Pass <-> SceneCentre_TrueHeading_FF is in ]180,270[ [deg]<br> Ascending Pass <-> SceneCentre_TrueHeading_FF is in ]270,360[ [deg]</p> <p>14) ROI_Npoints_UnUsablePointsMasked; [Number of samples used for each SARWIND LG-Mod wind estimation]</p> <p>15) MeanIncAng; 16) MeanNRCS; [Mean incident angle (expressed in degrees) and NRCS of the ROI]</p> <p>17) MeanResultantLength; 18) Alpha2_Est; [Fisher's formula parameters]</p> <p>19) MEdeg [Margin of Error, i.e. accuracy of each wind direction estimate, between 0° and 45°]</p> <p>The accuracy MEdeg is given by the semi-width of the confidence interval, with a confidence level (1-α) fixed, which is assigned to the wind direction estimate. Consequently, lower MEdeg values correspond to better estimates. And, if MEdeg == 45°, wind estimates must be discharged.</p> <p><br> Finally, note also that you can cut an entire row when [SAR_U SAR_V SAR_W SAR_D] == [NaN NaN NaN NaN] (typically, this happens for 'land pixels').</p> <p>% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %<br> % %<br> % REFERENCES: %<br> % %<br> % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %<br> % %<br> % The algorithm SARWIND LG-Mod is based on the Ph.D thesis below: %<br> % %<br> % [1] Rana, Fabio Michele (2016) "Exploitation of Satellite %<br> % Synthetic Aperture Radar Data for Geophysical Parameters Retrieval over %<br> % Land and Ocean". Unpublished Ph.D thesis. Politecnico di Bari. %<br> % %<br> % Some applications of the method are described in the following papers: %<br> % %<br> % [2] Fabio M. Rana, Maria Adamo, Guido Pasquariello, Giacomo De Carolis, %<br> % and Sandra Morelli, "LG-Mod: A Modified Local Gradient (LG) Method to %<br> % Retrieve SAR Sea Surface Wind Directions in Marine Coastal Areas," %<br> % Journal of Sensors, vol. 2016, Article ID 9565208, 7 pages, 2016. %<br> % doi:10.1155/2016/9565208. %<br> % %<br> % [3] Rana, F. M., Adamo, M., & Blanda, P. (2018, July). %<br> % LG-Mod Multi-Scale Approach for Sar Sea Surface Wind Directions %<br> % Retrieval. In IGARSS 2018-2018 IEEE International Geoscience and Remote %<br> % Sensing Symposium (pp. 3216-3219). IEEE. %<br> % %<br> % [4] Rana, F. M., Adamo, M., Lucas, R., & Blonda, P. (2019). Sea surface %<br> % wind retrieval in coastal areas by means of Sentinel-1 and numerical %<br> % weather prediction model data. Remote Sensing of Environment, 225, %<br> % 379-391. %<br> % %<br> % Suggestions and comments are always welcome. %<br> % Thanks in advance, %<br> % Fabio Michele Rana %<br> % %<br> % MOB: (+39) 3804114171 %<br> % E-MAILS: fabiomichele.rana@gmail.com; fabiomichele.rana@iia.cnr.it %<br> % %<br> % SKYPE: fabiomichelerana %<br> % %<br> % SARWIND_LG-Mod_v4.01, 2014-2019 %<br> % Author: Fabio M. Rana %<br> % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %<br> </p>
Projections of the Timing of Decreasing Coastal Flood Protection
<p>This data set contains projections of the timing of decreasing coastal flood protection (i.e., projections of the timing of frequency amplifications of estimated flood protection standards) associated with Hermans et al. (in revision), The Timing of Decreasing Coastal Flood Protection Due to Sea-Level Rise. It contains the output of extreme value analysis of high-frequency GESLA3 tide gauge observations (daily maxima, generalized Pareto distribution fits and return curves), total AR6 sea-level projections interpolated to GESLA3 tide gauge locations, and the required sea-level rise for and the timing of frequency amplifications relative to estimated coastal flood protection standards (FLOPROS) or to the historical centennial event. Results are included for both automatically selected extremes thresholds and for a constant threshold of 98.8% at all locations.</p> <p>The manuscript that this data accompanies can be found at <a href="https://www.nature.com/articles/s41558-023-01616-5">https://www.nature.com/articles/s41558-023-01616-5</a>.</p> <p>The code used to produce this data can be found at <a href="https://github.com/Timh37/TimingAFs">https://github.com/Timh37/TimingAFs</a>.</p> <p><strong>Required Acknowledgements and Citations</strong></p> <p>Users of this dataset are asked to cite:</p> <ul> <li>The manuscript that this dataset accompanies: Hermans, T.H.J., Malagón-Santos, V., Katsman, C.A. <em>et al.</em> The timing of decreasing coastal flood protection due to sea-level rise. <em>Nat. Clim. Chang.</em> <strong>13</strong>, 359–366 (2023). https://doi.org/10.1038/s41558-023-01616-5</li> <li>Garner, G. G., T.H.J. Hermans, R. E. Kopp, A. B. A. Slangen, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, B. Fox-Kemper, H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, Y. Yu, L. Hua, T. Palmer, B. Pearson, 2021. IPCC AR6 Global Mean Sea-Level Rise Projections. Version 20210809. Dataset accessed [YYYY-MM-DD] at <a href="https://doi.org/10.5281/zenodo.5914709">https://doi.org/10.5281/zenodo.5914709</a></li> <li>Tiggeloven, T., de Moel, H., Winsemius, H. C., Eilander, D., Erkens, G., Gebremedhin, E., Diaz Loaiza, A., Kuzma, S., Luo, T., Iceland, C., Bouwman, A., van Huijstee, J., Ligtvoet, W., and Ward, P. J.: Global-scale benefit–cost analysis of coastal flood adaptation to different flood risk drivers using structural measures, Nat. Hazards Earth Syst. Sci., 20, 1025–1044, <a href="https://doi.org/10.5194/nhess-20-1025-2020">https://doi.org/10.5194/nhess-20-1025-2020</a>, 2020</li> </ul> <pre><code>R.E.K. was supported by the National Science Foundation (NSF) as part of the Megalopolitan Coastal Transformation Hub (MACH) under NSF award ICER-2103754. T.H.J.H., V.M.-S. and A.B.A.S. were supported by PROTECT. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 869304, PROTECT contribution number TBD.</code></pre> <p> </p>
DynaRev - Dynamic Coastal Protection: Resilience of Dynamic Revetments Under Sea Level Rise
<p>This dataset contains processed data from the DynaRev experiments carried out in the Large Wave Flume (Grosser Wellenkanal, GWK) from 14-08-2017 to 29-09-2017 as a Transnational Access project within the EU funded project HYDRALAB+ (654110). The dataset provided under this DOI includes the post-processed data detailed in the article submitted to Scientific Data titled "High-resolution, prototype-scale laboratory measurements of nearshore wave processes and morphological evolution of a sandy beach with and without a dynamic cobble berm revetment"</p> <p>The overall aim of this project was to construct a prototype-scale beach and investigate the response of the beach to a rising sea level and storms with and without a cobble berm dynamic revetment structure (a gravel or shingle ridge placed around the wave runup limit). The response of two beach configurations was investigated under erosive wave conditions (Hs=0.8m, Tp=6.0s) and a total sea-level rise, SLR = 0.4 m:</p> <p>i) an unmodified sand beach with an initially plane slope of 1:15, and<br> ii) a natural beach profile with a dynamic revetment installed at the location of the natural berm before imposing SLR.</p> <p>SLR was imposed in 4 steps of 0.1 m with an initial water depth of 4.5 m above the flume base. Each phase ran for a total of 58 hours, after which resilience testing under storm waves and accretive conditions was undertaken for a further 12 hours in each case.</p> <p>The changing profile of the sand beach and revetment was monitored throughout the experiments using a traditional profiler and a LiDAR array. Additional hydrodynamic measurements were obtained at the location of the offshore sandbar to investigate the process of bar formation and migration with SLR.</p> <p>The model set-up, experimental program and data structure are explained in the submitted Scientific Data paper. The data files are organised as detailed in "DynaRev_Data_Structure.doc".</p> <p> </p>
Archive Documents Covering Rhode Island Coastal Flood Protection (1954-2002)
<p>This is a repository of nearly 2000 primary and secondary documents covering the politics of coastal flood protection infrastructure projects form the 1950s through the end of the 20th century. Nearly all documents are from the 1950s and 1960s. They are in the form of mostly scans and photos and were collected from public and private archives between September and November 2019.</p> <p> </p> <p>Documents include internal memos, project-related materials, and newspaper clippings from the New England District of the USACE archived at the U.S. National Archives and Records Administration facility (Waltham, Massachusetts), personal papers from Congressman John E. Fogarty, Senator John Pastore, and Governor Dennis J. Roberts archived at Providence College, over three decades of newspaper articles on microfilm from the Providence Journal and Evening Bulletin archived at both the Rhode Island Historical Society and the Providence Public Library, and additional materials associated with the Fox Point Hurricane Barrier at the Providence City Archive (all Providence, Rhode Island).</p> <p> </p> <p>A selection of documents from this repository were used to reconstruct event sequences associated with the Fox Point Hurricane Barrier in Providence Rhode Island and the proposed (but never built) Narragansett Bay Hurricane Barrier.</p> <p> </p> <p>This selection of documents is in an organized folder tree, entitled "Rasmussen2022" and is used to support the arguments in a climate change adaptation study. As of February 2022, the study is under review with the Journal of Water Resources Policy and Management, "Coastal defense megaprojects in an era of sea-level rise: politically feasible strategies or Army Corps fantasies?", by D.J. Rasmussen, Robert E. Kopp, and Michael Oppenheimer.</p>
Fig. 1 in Assessment of coastal fish assemblages before the establishment of a new marine protected area in the central Mediterranean: its role in formulating a zoning proposal Abstract
Fig. 1: Map of the study area with indication of sampling sectors around the promontory of Milazzo.
Extract of the project data from the LIFE KPI webtool. Deliverable 2.5 of the LIFE NatuReef project: Nature-based reef solution for coastal protection and marine biodiversity enhancement. LIFE22-NAT-IT-LIFE-NatuReef/101113742
<p>Key performance indicator, a quantifiable measure of performance over time for a specific objective.</p>
Data for "Are exotic saltmarsh species better than native species for coastal protection? "
<p>Full data for Figue 2~3 are saved in "Figure 2.xlsx" and "Figure 3.xlsx", and data for Figure 4a is saved in "Figure 4.xlsx".</p>
Monitoring vertebrate biodiversity of a protected coastal wetland using eDNA metabarcoding
<p>Monitoring plans using environmental DNA have the potential to offer a standardized and cost-efficient method to survey biodiversity in aquatic ecosystems. Among these ecosystems, coastal wetlands are key elements that serve as transition zones between marine and freshwater ecosystems and are today the target of many conservation and restoration efforts. In this sense, eDNA monitoring could provide a rapid and efficient tool for studying and generating baseline biodiversity information to guide coastal wetland management programs. Here we test an eDNA metabarcoding assay as a tool to characterize vertebrate biodiversity in one of the largest coastal wetlands of Chile, the Rio Cruces Wetland, a Ramsar designated site since 1981. We sampled surface water from 49 sites along the entire wetland. Our eDNA approach detected 91 genera of vertebrates including amphibians, fishes, mammals, and birds, as well as identified several cryptic, exotic, and endangered species. Our results also indicated that the spatial distribution of eDNA from different species is spatially structured despite the complex hydrodynamics inherent in this wetland due to the influence of daily tidal regimes. For amphibians and fishes, the number of taxa detected with eDNA was higher in the periphery of the wetland, and increased with proximity to the ocean, a pattern consistent with small-scale spatial sensitivity for some species and eDNA accumulation downstream for others. Birds and mammals showed somewhat more idiosyncratic distributions. Taken together our results add to the growing body of evidence showing eDNA can serve as a rapid cost-effective tool to characterize vertebrate communities in protected coastal wetlands, where visual surveys are difficult and animal collections are often prohibited. The use of multiple primer sets is also recommended as it facilitates the detection of ephemeral terrestrial organisms and resident aquatic organisms that make use of these wetlands.</p>
Fijian sea krait behavior relates to fine‐scale environmental heterogeneity in old‐growth coastal forest: The importance of integrated land–sea management for protecting amphibious animals
<p><span>Here the data for "Fijian sea krait behaviour relates to fine-scale environmental heterogeneity in old growth forest: the importance of integrated land-sea management for protecting amphibious animals" by</span><span> Lowe, C., Keppel, G., Waqa, K., Peters, S., Fisher, R.N., Scanlon, A., Osborne-Naikatini, T, and Thomas-Moko, N </span><span> is provided. This article investigates the habitat of </span>Yellow Lipped Sea Kraits, <em>Laticauda</em> <em>colubrina</em>, in the terrestrial realm on Leluvia Island, a small, topographically flat atoll in Fiji with coastal forest. The investigation uses concurrent microclimate measurements and behaviour surveys, as well as vegetation surveys, and the data collected for these analyses are provided here. Microclimates were significantly related to canopy cover, leaf litter depth, and distance from the high-water mark (HWM). Sea kraits were almost exclusively observed in coastal forest within 30 m of the HWM. Sloughing of skins only occurred within crevices of mature or dying trees. Resting <em>L</em>. <em>colubrina</em> were significantly more likely to occur at locations with higher mean diurnal temperatures, lower leaf litter depths, and shorter distances from the HWM. On Leleuvia, behaviour of <em>L</em>. <em>colubrina</em> therefore relates to environmental heterogeneity created by old-growth coastal forests, particularly canopy cover and crevices in mature and dead tree trunks. The importance of healthy coastal habitats, both terrestrial and marine, for <em>L</em>. <em>colubrina</em> suggests it could be a good flagship species for advocating integrated land-sea management. Furthermore, our study highlights the importance of coastal forests and topographically flat atolls for biodiversity conservation. Effective conservation management of amphibious species that utilise land- and seascapes is therefore likely to require a holistic approach that incorporates connectivity among ecosystems and environmental heterogeneity at all relevant scales.</p>
Fijian sea krait behavior relates to fine‐scale environmental heterogeneity in old‐growth coastal forest: The importance of integrated land–sea management for protecting amphibious animals
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Data from: Seagrass coastal protection services reduced by invasive species expansion and megaherbivore grazing
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Monitoring vertebrate biodiversity of a protected coastal wetland using eDNA metabarcoding
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Data for: Functions of coastal feeder bluff systems: Implications for prioritizing protection and restoration
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Data from: Upgrades of coastal protection infrastructure affect benthic communities
<ol> <li>Sea level rise, storm surges, aging and wear are forcing upgrades to breakwaters and seawalls to protect coastal areas from erosion and inundation. Such upgrades involve the introduction of new material which may consequently act as an ecological disturbance that can alter established marine communities and ecosystem function. Mitigating ecological impacts requires an understanding of how species assemblages are affected by such works.</li> <li>Here, we use the major upgrade of a regularly wave-overtopped breakwater as a case study to evaluate the impacts of upgrades to hard coastal protection structure on benthic rocky reef communities. An asymmetrical Before-After Control-Impact (BACI) experimental design was used to test interactive effects of the infrastructure upgrades on benthic communities.</li> <li>While benthic assemblages were not significantly different from controls prior to the upgrade, improving the defensive capacity of the breakwater significantly changed community structure. Notably, most taxonomic groups showed higher cover at the control sites than at the impacted site post-upgrade, with articulated calcareous algae (e.g. <i>Corallina officinalis</i> and <i>Amphiroa anceps</i>) showing an opposite trend.</li> <li> <i>Synthesis and applications</i>: Ecological implications and structural limitations make regular upgrading of existing infrastructure unsuitable as a long-term management strategy. More sustainable alternatives need to be considered, such as decommissioning of structures and retreat from flood-prone areas. This transition, however, will take time and requires a change of mindset and policies. Where upgrades are urgent, eco-engineering techniques can mitigate impacts to habitats and associated taxa.</li> </ol>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.