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  • 2019-2023
  • Research data
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  • English
  • Aurora Universities Network
  • European Marine Science

  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Moran, Peter A.; Bosse, Mirte; Marien, Janine; Halfwerk, Wouter;

    Urbanisation is rapidly altering ecosystems, leading to profound biodiversity loss. To mitigate these effects, we need a better understanding of how urbanisation impacts dispersal and reproduction. Two contrasting population demographic models have been proposed that predict that urbanisation either promotes (facilitation model) or constrains (fragmentation model) gene flow and genetic diversity. Which of these models prevails likely depends on the strength of selection on specific phenotypic traits that influence dispersal, survival, or reproduction. Here, we a priori examined the genomic impact of urbanisation on the Neotropical túngara frog (Engystomops pustulosus), a species known to adapt its reproductive traits to urban selective pressures. Using whole-genome resequencing for multiple urban and forest populations we examined genomic diversity, population connectivity and demographic history. Contrary to both the fragmentation and facilitation models, urban populations did not exhibit substantial changes in genomic diversity or differentiation compared to forest populations, and genomic variation was best explained by geographic distance rather than environmental factors. Adopting an a posteriori approach, we additionally found both urban and forest populations to have undergone population declines. The timing of these declines appears to coincide with extensive human activity around the Panama Canal during the last few centuries rather than recent urbanisation. Our study highlights the long-lasting legacy of past anthropogenic disturbances in the genome and the importance of considering the historical context in urban evolution studies as anthropogenic effects may be extensive and impact non-urban areas on both recent and older timescales.  # Genomic footprints of (pre) colonialism: population declines in urban and forest túngara frogs coincident with historical human activity ## Description of the data and file structure The metadata file encompasses sampling location, corresponding population code (pop), and environmental data for forest (F) and urban (U) sites. The collection of light (in Lux), noise (in dB SPL, fast, max, A-weighted) and canopy cover data (percentage canopy cover estimated from pictures) was previously described and published in Halfwerk et al., 2019. The level of urbanisation (Urban_score) was calculated based on the type of landscape-cover for each sampling location using ‘Urbanisation Score’ software (Lipovits et al., 2015; Seress et al., 2014). This program accesses satellite images via GoogleMaps and applies a semi-automated approach to quantify the relative abundance of vegetation and impervious surfaces within a 1 km2 area around each sampling location. These values were then combined using principal component analysis (PCA) and an urbanisation score retained (PC1) for each location. ## Sharing/Access information Related data: Whole genome resequencing data used in this study is available from the European Nucleotide Archive (ENA) (PRJEB60348). ## Code/Software Main bash scripts for running software and R code used for analyses. Additional custom scripts are available from the corresponding authors upon request. Full Methods description provided in manuscript: Moran et al., 2023 Genomic data: Whole genome resequencing data used in this study is available from the European Nucleotide Archive (ENA) (PRJEB60348). Environmental data: The collection of light (in Lux), noise (in dB SPL, fast, max, A-weighted) and canopy cover data (percentage canopy cover estimated from pictures) data was previously described and published in Halfwerk et al., 2019. The level of urbanisation (Urban_score) was calculated based on the type of landscape-cover for each sampling location using ‘Urbanisation Score’ software (Lipovits et al., 2015; Seress et al., 2014). This program accesses satellite images via GoogleMaps and applies a semi-automated approach to quantify the relative abundance of vegetation and impervious surfaces within a 1 km2 area around each sampling location. These values were then combined using principal component analysis (PCA) and an urbanisation score retained (PC1) for each location.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DRYAD; ZENODOarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    DRYAD; ZENODO
    Dataset . 2023
    License: CC 0
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DRYAD; ZENODOarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      DRYAD; ZENODO
      Dataset . 2023
      License: CC 0
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: de la Vega-Leinert, Anne Cristina; Kaufmann, Julia; Reinwardt, Nadine; Wermes, Maike; +1 Authors

    {"references": ["ABPmer. 2023. OMReg \u2013 A database of completed coastal habitat creation schemes and other adaptation projects. https://www.omreg.net/ - last access: 01 June 2023.", "de la Vega-Leinert AC, Stoll-Kleemann S, Wegener E. 2018. Managed realignment (MR) along the Eastern German Baltic Sea: a catalyst for conflict or for a coastal zone management consensus. J. Coast Res. 34 (3): 586\u2013601. https://doi.org/10.2112/JCOASTRES-D-15-00217.1.", "de la Vega-Leinert AC, Stoll-Kleemann S. 2015. Identifying gaps between science, policy and societal perspectives on coastal land use: the case of managed realignment in Dar\u00df \u2013 Zingst region, Mecklenburg Western Pomerania, Eastern German Baltic coast. Greifswalder Geographische Arbeiten Bd. 51. Institut f\u00fcr Geographie und Geologie der Ernst-Moritz-Arndt Universit\u00e4t Greifswald: 41-67. https://geo.uni-greifswald.de/institut/schriftenreihen/greifswalder-geographische-arbeiten/ - last accessed: 01 June 2023.", "Esteves LS. 2014. Managed Realignment: A Viable Long-Term Coastal Management Strategy? Springer: Dordrecht.", "Nordstrom KL, Lampe R, Jackson NL. 2007. Increasing the dynamism of coastal landforms by modifying shore protection methods: Examples from the eastern German Baltic Sea Coast. Environmental Conservation, 34(3), 205\u2013214. https://doi.org/10.1017/S037689290700416X", "Rupp-Armstrong S, Nicholls R. 2007. Coastal and estuarine retreat: A comparison of the application of managed realignment in England and Germany. Journal of Coastal Research, 23(6), 1418\u20131430. doi: https://doi.org/10.2112/04-0426.1", "S\u00e1nchez-Arcilla A, C\u00e1ceres I, Le Roux X, Hinkel J, Schuerch M, Nicholls RJ, Otero M, Staneva J, de Vries M, Pernice U, Briere C, Caiola N, Gracia V, Ib\u00e1\u00f1ez C, Torresan S. 2022. Barriers and enablers for upscaling coastal restoration. Nature-Based Solutions 2, 100032. https://doi.org/10.1016/j.nbsj.2022.100032", "Schoonees T, Gij\u00f3n Manche\u00f1o A, Scheres B, Bouma TJ, Silva R, Schlurmann T, Sch\u00fcttrumpf H. 2019. Hard Structures for Coastal Protection, Towards Greener Designs. Estuaries and Coasts. https://doi.org/10.1007/s12237-019-00551-z", "Schuerch M, Mossman HL, Moore HE, Christie E, Kiesel J. 2022. Managed realignment as a solution to mitigate coastal flood risks \u2013 optimizing success through knowledge co-production. Nat. Hazards Earth Syst. Sci., 22, 2879\u20132890. https://doi.org/10.5194/nhess-22-2879-2022", "van den Hoven K, Kroeze C, van Loon-Steensma JM. 2022. Characteristics of realigned dikes in coastal Europe: Overview and opportunities for nature-based flood protection. Ocean and Coastal Management 222, 106116. https://doi.org/10.1016/j.ocecoaman.2022.106116", "Weisner E, Schernewski G. 2013. Adaptation to climate change: A combined coastal protection and re-alignment measure in a southern Baltic tourism region. Journal of Coastal Research 65 (10065): 1963-1968. https://doi.org/10.2112/SI65-332.1", "Wulf S. 2021. Deichr\u00fcckverlegungen an der deutschen Ostseek\u00fcste - Erfahrungen aus bestehenden Projekten. Natur und Landschaft 3 (2021): 121-128. doi: 10.17433/3.2021.50153887.121-128"]} Within the ECAS-Baltic project,1 we investigated coastal ecological restoration projects on the German Baltic Coast in the State of Mecklenburg- Western Pomerania. The restoration of near natural coastal hydrological regimes, flood plains and habitats, often involving coastal maanged retreat, is currently being performed for a number of conservation purposes (e.g., climate mitigation, habitat protection and restoration) and contribute to a more resilient coast. The articulation of these closely related goals is an interesting avenue for regional planing and coastal zone management, especially where planed measures are polemic and social acceptance fraught with obstacles. Our goals are: to produce a comprehensive and systematic inventory of coastal restoration projects involving (plans for) MR, to describe the projects identified with a focus on decision-making, planing and implementation, to determine factors that facilitate / hinder their successful implementation, and to reflect on MR potential for coastal zone management and regional planning. We developed a methodology to formalize rich, locally situated empirical data from practitioners to draw lessons learnt from past experiences and identify generic strategies towards resilient coastal land management. We currently have identified 68 projects for the coast of the State of Mecklenburg – Western Pomerania, for which we have collected a range of information. We are in the process of verifying our dataset through iterative expert consultation. Work on our inventory is ongoing and data will be updated until the end of the ECAS-Baltic Project (end of October 2023). Our dataset is currently embargoed, until publications have been approved. After which, the dataset will be made public on this platform.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    ZENODO
    Dataset . 2023
    Data sources: Datacite
    ZENODO
    Dataset . 2023
    Data sources: ZENODO
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      ZENODO
      Dataset . 2023
      Data sources: Datacite
      ZENODO
      Dataset . 2023
      Data sources: ZENODO
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    Authors: Karstensen, Johannes; Krahmann, Gerd;

    Seabird 911plus systems equipped with dual temperature-conductivity-oxygen sensors were employed. All systems had a 24-bottle water sampling rosette with 10 l Niskin bottles. Water sampling, processing, and calibration followed GO-SHIP recommendations (Swift, 2010; McTaggart et al., 2010; Uchida et al., 2010) and included the recommended steps Data Conversion, Sensor Time-Alignment, Creation of Bottle Files, Outlier Removal, Pressure Sensor Filtering, Conductivity Cell Thermal Mass Correction, Ship Roll Correction and Deck Offset Correction by Loop Editing, as well as Derivation of Calculated Properties. After these steps, conductivity and oxygen readings were calibrated against values determined with salinometry and Winkler titration , respectively. Finally, the downcast data was averaged over 1 dbar wide intervals. An independent upcast calibration was used to obtain calibrated CTDO values coincident with the discrete water samples. PO-GLOBAL-SVN = 689 used on 10-Jun-2020 15:15:01Matlab = 9.4.0.813654 (R2018a)Release = 3nc_uncertainty_p = 2.000000nc_uncertainty_t = 0.002000nc_uncertainty_s = 0.003000nc_uncertainty_o = 1.000000

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    PANGAEA
    Dataset . 2023
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      PANGAEA
      Dataset . 2023
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Servetto, Natalia; Ruiz, Micaela Belen; Martinez, Mariano; Harms, Lars; +6 Authors

    Southern Ocean organisms are thought to be particularly vulnerable to ocean acidification, as they inhabit cold waters where calcite-aragonite saturation states are naturally low. It is also generally assumed that calcifying animals would be more affected by ocean acidification than non-calcifying ones. In this context, we aimed to study the impacts of reduced pH on the ascidia Cnemidocarpa verrucosa sp. A. Here, we used gene expression profiling and enzymatic activity to study the responses of that Antarctic benthic species to ocean acidification. We sampled Cnemidocarpa verrucosa sp. A. by scuba diving at approximately 15 m depth at Carlini station, Potter Cove, King George Island, Antarctica. Superoxide dismutase (SOD) activity was measured in the ascidia, samples (approximately 70 mg of brachial basket) were homogenized in 20 mM Tris-HCl, 1 mM EDTA, pH 7.6, with a ratio 1:4 w/v. Homogenates were centrifuged at 14,000 x g for 3 min at 4°C and the supernatant was used to measure SOD activity at 20°C following Livingstone et al. (1992) protocol. Supernatant was mixed with the measurement buffer (43 mM K₂HPO₄, 43 mM KH₂PO₄, 0.1 mM EDTA, pH 7.68), 5 mM Xanthina (Sigma X-0626), 100 µM Citocromo-C (Sigma C-2037), 0.3 mU/µl XOD (Xanthin-Oxidasa, Sigma X-4875) in 2 M (NH₄)2SO₄. The measurement was made in a photometer at 20°C, 550 nm wavelength, for 3 minutes, every 10 seconds. For the calculations, the total protein content of the samples was measured using the method of Bradford (1976). Superoxide dismutase activity was expressed in activity in the extract (mU) / amount of protein (mg). All measurements were made in triplicate.

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    PANGAEA
    Dataset . 2023
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      PANGAEA
      Dataset . 2023
      Data sources: B2FIND
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    Authors: Droste, Elise Sayana; Bakker, Dorothee C E; Hoppema, Mario; Ossebaar, Sharyn; +4 Authors

    Discrete seawater samples for the determination of dissolved inorganic carbon (DIC) and total alkalinity (TA) were collected from CTD stations during RV POLARSTERN expedition PS117, between 15 December 2018 and 7 February 2019. Seawater samples were collected from stations that used the AWI-operated CTD, as well as the Ultra-Clean-CTD, operated by NIOZ. DIC and TA were measured using coulometric titration and potentiometric titration, respectively, on a VINDTA 3C system. Nutrients were measured with UV-Vis spectrophotometry and a continuous gas-segmented flow auto-analyser. Data for station 41 have previously been published on Pangaea and are excluded from this dataset (https://doi.org/10.1594/PANGAEA.946363). Bottle data (including nutrients) from the AWI CTD and Ultra-Clean-CTD stations have already been published and are stored on Pangaea under https://doi.org/10.1594/PANGAEA.910673 and https://doi.org/10.1594/PANGAEA.940209, respectively. Data quality flags follow the WOCE quality code definitions for water sample measurements. Details on sample collection and analysis methods for DIC and TA can be found in Droste et al. (2022).

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    PANGAEA
    Dataset . 2023
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      PANGAEA
      Dataset . 2023
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Authors: Wilcox, Paul S; Spötl, Christoph; Honkonen, Jessica; Edwards, R Lawrence;

    The dataset includes speleothem oxygen isotopes used to reconstruct climate in southeastern Alaska during the past ~13.5 ka. In total, four speleothems were used in this reconstruction. Speleothems EC-17-7-A and EC-16-5-F were collected in July 2022 and May 2016, respectively, from El Capitan Cave (56.170 N, -133.320 E; 80 m.a.s.l). Speleothem WB-21-5-A was collected in Wishbone Cave (55.774 N, -133.191 E; 420 m.a.s.l.) and speleothem WA-21-6-A was collected in Walkabout Cave (55.776° N, 133.195° W; 350 m.a.s.l.) in May and June 2022, respectfully. The data collection was completed between 2016 and 2022. stable isotopes were measured on a ThermoFisher Delta V isotope ratio mass spectrometer.

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    PANGAEA
    Dataset . 2023
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2023
      Data sources: B2FIND
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: El-Hokayem, Léonard; De Vita, Pantaleone; Usman, Muhammad; Link, Andreas; +1 Authors

    Groundwater dependent vegetation (GDV) is essential for maintaining ecosystem functions and services, providing critical habitat and sustaining human livelihoods. A novel multicriteria framework helps to identify areas where potential groundwater dependent vegetation (pGDV) occurs in the Mediterranean biome. Globally-available datasets targeting 1) groundwater vegetation interaction; 2) soil water holding capacity; 3) topographical landscape wetness potential; 4) land use land cover and 5) hydraulic conductivity of rocks are combined in a weighted, easy-to-use index, composed of eleven thematic layers. Input layers for the index calculation are available in the data collection: 1) pre-processed (rasterised and clipped to the Mediterranean) and 2) harmonised and reclassified. All input data was extracted globally. Either, directly from the respective studies or through the data catalogue in the Google Earth Engine. All datasets were acquired and processed in 2022 and 2023. Time series data for potential inflow dependency and Normalized Difference Vegetation Index (NDVI) were extracted for the period 2003-2021. Finally, the mean value was calculated over this period. All other data sets, however, mark a fixed point in time. Ground truth vegetation data was used to calculate layer weightings with a Random Forest. 10 m * 10 m vegetation plots were collected in July and August 2021 and 2022 in southern Italy (Campania region) inside the 'Cilento, Vallo di Diano and Alburni National Park'. 236 vegetation plots are available, containing general information on the vegetation (habitat, species number, stratification), mean indicator values, plant life forms, leaf anatomy as well as a calculated ecohydrological potential for the presence of GDV. The potential was calculated based on the coverage of phreatophyte species and the moisture value of non-phreatophyte species. The final pGDV maps including different weightings of the eleven thematic layers are compiled at a resolution of 500 m in WGS1984 (EPSG 4326). Finally, five pGDV classes (very low to very high potential) were derived and the share of high pGDV was calculated for level 8 HydroBASINS in the Mediterranean. Results support prioritisation of areas for essential regional high-resolution identification of GDV, to ensure sustainable groundwater management and in turn protect GDV as local biodiversity hotspots.

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    PANGAEA
    Dataset . 2023
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2023
      Data sources: B2FIND
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    Authors: van der Does, Michèlle; Lamy, Frank; Krätschmer, Stephan; Stuut, Jan-Berend W; +3 Authors

    We present the characteristics of the lithogenic components of seafloor surface sediments covering the entire South Atlantic Ocean (from the equator to Antarctica). These samples were collected by multiple seagoing expeditions between 1988 and 2005. By using end-member modelling on the multi-modal grain-size distributions, we decomposed the lithogenic fraction into a fine- and coarse-grained dust component, current-sorted sediments and IRD. By multiplying these specific components with 230Th-normalized lithogenic fluxes, we obtained specific fluxes for these four fractions. This allows us to study dust deposition over the remote open ocean more specifically.

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    PANGAEA
    Dataset . 2023
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2023
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    Authors: Lüskow, Florian; Sigurdsson, Gudjon Mar; Svavarsson, Jörundur; Gislason, Astthor;

    Scyphozoan jellyfish in Icelandic waters have received limited attention, despite apparent recent increases in jellyfish blooms and considerable regional oceanographic and climatic changes. We studied the species composition, abundance, phenology, and growth of scyphomedusae around the island and explored changes in distribution, species composition, and seasonality by comparing our findings with reports from the 1930s. Scyphomedusae were collected with a Bongo net (60 cm ring diameter, 250 cm net length, and 500 µm mesh size) in the top 10 m of the water column in five regions (fjords between 64 and 66°N) around Iceland in the spring, summer, and autumn of 2008. Between 4 and 36 tows were performed per sampling region. This dataset includes umbrella diameter, dry and wet mass, as well as abundance data of two species: Aurelia aurita and Cyanea capillata.

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    PANGAEA
    Dataset . 2023
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2023
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    Authors: Servetto, Natalia; Ruiz, Micaela Belen; Martinez, Mariano; Harms, Lars; +6 Authors

    Southern Ocean organisms are thought to be particularly vulnerable to ocean acidification, as they inhabit cold waters where calcite-aragonite saturation states are naturally low. It is also generally assumed that calcifying animals would be more affected by ocean acidification than non-calcifying ones. In this context, we aimed to study the impacts of reduced pH on the ascidia Cnemidocarpa verrucosa sp. A. Here, we used gene expression profiling and enzymatic activity to study the responses of that Antarctic benthic species to ocean acidification. We sampled Cnemidocarpa verrucosa sp. A. by scuba diving at approximately 15 m depth at Carlini station, Potter Cove, King George Island, Antarctica. Caspases 3/7 activity as indicators of apoptosis intensity was measured using the Caspase-Glow 3/7 Assay kit (Promega, USA) following the manufacturer's instructions. Samples were homogenized (16-33 mg) in lysis buffer consisting in 25 mM HEPES, 5 mM MgCl₂·6H₂O, 1 mM EGTA, 1 μg/mL pepstatin, 1 μg/mL leupectin, and 1 μg/mL aprotinin at a ratio 1:100 (Rivera-Ingraham et al., 2013) using a Precellys homogenizer (2 cycles at 5,500 x g at 4°C for 20 s). Homogenates were centrifuged at 13,000 x g at 4°C for 15 min and the supernatant was used to measure luminescence using Tristar LB941 plate reader (Berthold Technologies GmbH & Co. KG, Bad Wildbad, Germany). The total protein content of the samples was measured using the method of Bradford (1976). Caspase/Apoptotic activity was expressed as relative light units (RLU) per μg of protein × 104.

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    PANGAEA
    Dataset . 2023
    Data sources: B2FIND
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      Dataset . 2023
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Moran, Peter A.; Bosse, Mirte; Marien, Janine; Halfwerk, Wouter;

    Urbanisation is rapidly altering ecosystems, leading to profound biodiversity loss. To mitigate these effects, we need a better understanding of how urbanisation impacts dispersal and reproduction. Two contrasting population demographic models have been proposed that predict that urbanisation either promotes (facilitation model) or constrains (fragmentation model) gene flow and genetic diversity. Which of these models prevails likely depends on the strength of selection on specific phenotypic traits that influence dispersal, survival, or reproduction. Here, we a priori examined the genomic impact of urbanisation on the Neotropical túngara frog (Engystomops pustulosus), a species known to adapt its reproductive traits to urban selective pressures. Using whole-genome resequencing for multiple urban and forest populations we examined genomic diversity, population connectivity and demographic history. Contrary to both the fragmentation and facilitation models, urban populations did not exhibit substantial changes in genomic diversity or differentiation compared to forest populations, and genomic variation was best explained by geographic distance rather than environmental factors. Adopting an a posteriori approach, we additionally found both urban and forest populations to have undergone population declines. The timing of these declines appears to coincide with extensive human activity around the Panama Canal during the last few centuries rather than recent urbanisation. Our study highlights the long-lasting legacy of past anthropogenic disturbances in the genome and the importance of considering the historical context in urban evolution studies as anthropogenic effects may be extensive and impact non-urban areas on both recent and older timescales.  # Genomic footprints of (pre) colonialism: population declines in urban and forest túngara frogs coincident with historical human activity ## Description of the data and file structure The metadata file encompasses sampling location, corresponding population code (pop), and environmental data for forest (F) and urban (U) sites. The collection of light (in Lux), noise (in dB SPL, fast, max, A-weighted) and canopy cover data (percentage canopy cover estimated from pictures) was previously described and published in Halfwerk et al., 2019. The level of urbanisation (Urban_score) was calculated based on the type of landscape-cover for each sampling location using ‘Urbanisation Score’ software (Lipovits et al., 2015; Seress et al., 2014). This program accesses satellite images via GoogleMaps and applies a semi-automated approach to quantify the relative abundance of vegetation and impervious surfaces within a 1 km2 area around each sampling location. These values were then combined using principal component analysis (PCA) and an urbanisation score retained (PC1) for each location. ## Sharing/Access information Related data: Whole genome resequencing data used in this study is available from the European Nucleotide Archive (ENA) (PRJEB60348). ## Code/Software Main bash scripts for running software and R code used for analyses. Additional custom scripts are available from the corresponding authors upon request. Full Methods description provided in manuscript: Moran et al., 2023 Genomic data: Whole genome resequencing data used in this study is available from the European Nucleotide Archive (ENA) (PRJEB60348). Environmental data: The collection of light (in Lux), noise (in dB SPL, fast, max, A-weighted) and canopy cover data (percentage canopy cover estimated from pictures) data was previously described and published in Halfwerk et al., 2019. The level of urbanisation (Urban_score) was calculated based on the type of landscape-cover for each sampling location using ‘Urbanisation Score’ software (Lipovits et al., 2015; Seress et al., 2014). This program accesses satellite images via GoogleMaps and applies a semi-automated approach to quantify the relative abundance of vegetation and impervious surfaces within a 1 km2 area around each sampling location. These values were then combined using principal component analysis (PCA) and an urbanisation score retained (PC1) for each location.

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    DRYAD; ZENODO
    Dataset . 2023
    License: CC 0
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      DRYAD; ZENODO
      Dataset . 2023
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: de la Vega-Leinert, Anne Cristina; Kaufmann, Julia; Reinwardt, Nadine; Wermes, Maike; +1 Authors

    {"references": ["ABPmer. 2023. OMReg \u2013 A database of completed coastal habitat creation schemes and other adaptation projects. https://www.omreg.net/ - last access: 01 June 2023.", "de la Vega-Leinert AC, Stoll-Kleemann S, Wegener E. 2018. Managed realignment (MR) along the Eastern German Baltic Sea: a catalyst for conflict or for a coastal zone management consensus. J. Coast Res. 34 (3): 586\u2013601. https://doi.org/10.2112/JCOASTRES-D-15-00217.1.", "de la Vega-Leinert AC, Stoll-Kleemann S. 2015. Identifying gaps between science, policy and societal perspectives on coastal land use: the case of managed realignment in Dar\u00df \u2013 Zingst region, Mecklenburg Western Pomerania, Eastern German Baltic coast. Greifswalder Geographische Arbeiten Bd. 51. Institut f\u00fcr Geographie und Geologie der Ernst-Moritz-Arndt Universit\u00e4t Greifswald: 41-67. https://geo.uni-greifswald.de/institut/schriftenreihen/greifswalder-geographische-arbeiten/ - last accessed: 01 June 2023.", "Esteves LS. 2014. Managed Realignment: A Viable Long-Term Coastal Management Strategy? Springer: Dordrecht.", "Nordstrom KL, Lampe R, Jackson NL. 2007. Increasing the dynamism of coastal landforms by modifying shore protection methods: Examples from the eastern German Baltic Sea Coast. Environmental Conservation, 34(3), 205\u2013214. https://doi.org/10.1017/S037689290700416X", "Rupp-Armstrong S, Nicholls R. 2007. Coastal and estuarine retreat: A comparison of the application of managed realignment in England and Germany. Journal of Coastal Research, 23(6), 1418\u20131430. doi: https://doi.org/10.2112/04-0426.1", "S\u00e1nchez-Arcilla A, C\u00e1ceres I, Le Roux X, Hinkel J, Schuerch M, Nicholls RJ, Otero M, Staneva J, de Vries M, Pernice U, Briere C, Caiola N, Gracia V, Ib\u00e1\u00f1ez C, Torresan S. 2022. Barriers and enablers for upscaling coastal restoration. Nature-Based Solutions 2, 100032. https://doi.org/10.1016/j.nbsj.2022.100032", "Schoonees T, Gij\u00f3n Manche\u00f1o A, Scheres B, Bouma TJ, Silva R, Schlurmann T, Sch\u00fcttrumpf H. 2019. Hard Structures for Coastal Protection, Towards Greener Designs. Estuaries and Coasts. https://doi.org/10.1007/s12237-019-00551-z", "Schuerch M, Mossman HL, Moore HE, Christie E, Kiesel J. 2022. Managed realignment as a solution to mitigate coastal flood risks \u2013 optimizing success through knowledge co-production. Nat. Hazards Earth Syst. Sci., 22, 2879\u20132890. https://doi.org/10.5194/nhess-22-2879-2022", "van den Hoven K, Kroeze C, van Loon-Steensma JM. 2022. Characteristics of realigned dikes in coastal Europe: Overview and opportunities for nature-based flood protection. Ocean and Coastal Management 222, 106116. https://doi.org/10.1016/j.ocecoaman.2022.106116", "Weisner E, Schernewski G. 2013. Adaptation to climate change: A combined coastal protection and re-alignment measure in a southern Baltic tourism region. Journal of Coastal Research 65 (10065): 1963-1968. https://doi.org/10.2112/SI65-332.1", "Wulf S. 2021. Deichr\u00fcckverlegungen an der deutschen Ostseek\u00fcste - Erfahrungen aus bestehenden Projekten. Natur und Landschaft 3 (2021): 121-128. doi: 10.17433/3.2021.50153887.121-128"]} Within the ECAS-Baltic project,1 we investigated coastal ecological restoration projects on the German Baltic Coast in the State of Mecklenburg- Western Pomerania. The restoration of near natural coastal hydrological regimes, flood plains and habitats, often involving coastal maanged retreat, is currently being performed for a number of conservation purposes (e.g., climate mitigation, habitat protection and restoration) and contribute to a more resilient coast. The articulation of these closely related goals is an interesting avenue for regional planing and coastal zone management, especially where planed measures are polemic and social acceptance fraught with obstacles. Our goals are: to produce a comprehensive and systematic inventory of coastal restoration projects involving (plans for) MR, to describe the projects identified with a focus on decision-making, planing and implementation, to determine factors that facilitate / hinder their successful implementation, and to reflect on MR potential for coastal zone management and regional planning. We developed a methodology to formalize rich, locally situated empirical data from practitioners to draw lessons learnt from past experiences and identify generic strategies towards resilient coastal land management. We currently have identified 68 projects for the coast of the State of Mecklenburg – Western Pomerania, for which we have collected a range of information. We are in the process of verifying our dataset through iterative expert consultation. Work on our inventory is ongoing and data will be updated until the end of the ECAS-Baltic Project (end of October 2023). Our dataset is currently embargoed, until publications have been approved. After which, the dataset will be made public on this platform.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    ZENODO
    Dataset . 2023
    Data sources: Datacite
    ZENODO
    Dataset . 2023
    Data sources: ZENODO
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      ZENODO
      Dataset . 2023
      Data sources: Datacite
      ZENODO
      Dataset . 2023
      Data sources: ZENODO
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    Authors: Karstensen, Johannes; Krahmann, Gerd;

    Seabird 911plus systems equipped with dual temperature-conductivity-oxygen sensors were employed. All systems had a 24-bottle water sampling rosette with 10 l Niskin bottles. Water sampling, processing, and calibration followed GO-SHIP recommendations (Swift, 2010; McTaggart et al., 2010; Uchida et al., 2010) and included the recommended steps Data Conversion, Sensor Time-Alignment, Creation of Bottle Files, Outlier Removal, Pressure Sensor Filtering, Conductivity Cell Thermal Mass Correction, Ship Roll Correction and Deck Offset Correction by Loop Editing, as well as Derivation of Calculated Properties. After these steps, conductivity and oxygen readings were calibrated against values determined with salinometry and Winkler titration , respectively. Finally, the downcast data was averaged over 1 dbar wide intervals. An independent upcast calibration was used to obtain calibrated CTDO values coincident with the discrete water samples. PO-GLOBAL-SVN = 689 used on 10-Jun-2020 15:15:01Matlab = 9.4.0.813654 (R2018a)Release = 3nc_uncertainty_p = 2.000000nc_uncertainty_t = 0.002000nc_uncertainty_s = 0.003000nc_uncertainty_o = 1.000000

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    PANGAEA
    Dataset . 2023
    Data sources: B2FIND
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      PANGAEA
      Dataset . 2023
      Data sources: B2FIND
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    Authors: Servetto, Natalia; Ruiz, Micaela Belen; Martinez, Mariano; Harms, Lars; +6 Authors

    Southern Ocean organisms are thought to be particularly vulnerable to ocean acidification, as they inhabit cold waters where calcite-aragonite saturation states are naturally low. It is also generally assumed that calcifying animals would be more affected by ocean acidification than non-calcifying ones. In this context, we aimed to study the impacts of reduced pH on the ascidia Cnemidocarpa verrucosa sp. A. Here, we used gene expression profiling and enzymatic activity to study the responses of that Antarctic benthic species to ocean acidification. We sampled Cnemidocarpa verrucosa sp. A. by scuba diving at approximately 15 m depth at Carlini station, Potter Cove, King George Island, Antarctica. Superoxide dismutase (SOD) activity was measured in the ascidia, samples (approximately 70 mg of brachial basket) were homogenized in 20 mM Tris-HCl, 1 mM EDTA, pH 7.6, with a ratio 1:4 w/v. Homogenates were centrifuged at 14,000 x g for 3 min at 4°C and the supernatant was used to measure SOD activity at 20°C following Livingstone et al. (1992) protocol. Supernatant was mixed with the measurement buffer (43 mM K₂HPO₄, 43 mM KH₂PO₄, 0.1 mM EDTA, pH 7.68), 5 mM Xanthina (Sigma X-0626), 100 µM Citocromo-C (Sigma C-2037), 0.3 mU/µl XOD (Xanthin-Oxidasa, Sigma X-4875) in 2 M (NH₄)2SO₄. The measurement was made in a photometer at 20°C, 550 nm wavelength, for 3 minutes, every 10 seconds. For the calculations, the total protein content of the samples was measured using the method of Bradford (1976). Superoxide dismutase activity was expressed in activity in the extract (mU) / amount of protein (mg). All measurements were made in triplicate.

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    PANGAEA
    Dataset . 2023
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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