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FIGURE 4 in A morphological, phylogenetic and phylogeographic reappraisal of the land crabs Gecarcinus quadratus De Saussure, 1853, and G. lateralis Fréminville in Guérin 1832 (Decapoda: Gecarcinidae). Are they different species?
FIGURE 4. Maximum clade credibility tree based on Bayesian inference (BI) for Gecarcinus, Johngarthia and the outgroup, Cardisoma guanhumi, using the concatenated matrix of the 16S and COI genes. Probability values at the nodes refer to support values for BI and maximum likelihood (ML). In the assigned key for Mexican specimens, the last letter indicates the sex of the organism: male (M), female (H) or juvenile (JU), followed by the individual number. The organisms highlighted in red in the Atlantic Clade correspond to specimens from Costa Rica and Panama. See the locality list in table 1.
FIGURE 1 in A morphological, phylogenetic and phylogeographic reappraisal of the land crabs Gecarcinus quadratus De Saussure, 1853, and G. lateralis Fréminville in Guérin 1832 (Decapoda: Gecarcinidae). Are they different species?
FIGURE 1. Dorsal view of: A) Gecarcinus lateralis from Río Prieto, Veracruz (CNCR 33942) and B) G. quadratus from Barra de Boca del Cielo, Chiapas (CNCR 34630).
FIGURE 6 in A morphological, phylogenetic and phylogeographic reappraisal of the land crabs Gecarcinus quadratus De Saussure, 1853, and G. lateralis Fréminville in Guérin 1832 (Decapoda: Gecarcinidae). Are they different species?
FIGURE 6. Median-joining network for Gecarcinus quadratus based on the alignment of the mitochondrial gene COI. Each middle line indicates one mutational step between haplotypes. Circles represent different haplotypes and their diameters the frequency of each.
FIGURE 3 in A morphological, phylogenetic and phylogeographic reappraisal of the land crabs Gecarcinus quadratus De Saussure, 1853, and G. lateralis Fréminville in Guérin 1832 (Decapoda: Gecarcinidae). Are they different species?
FIGURE 3. Left male first gonopod (G1): Cephalic view, A) G. lateralis from Río Prieto, Veracruz (CNCR 33942); B) G. quadratus from Boca del Cielo, Chiapas (CNCR 34630). Lateral view, C) G. quadratus from Boca del Cielo, Chiapas (CNCR 34630). Ventral surface, D) G. lateralis female from Barra de Sontecomapan, Veracruz (CNCR 33943); E) G. quadratus female from Playa Higuera Blanca, Nayarit (CNCR 34012); F) G. ruricola male from Cuba (MNHN-IU-2017-8392). Frontal view, G) G. ruricola from Cuba (MNHN-IU-2017-8392) (G. ruricola photos modified from Guinot et al., 2018).
FIGURE 5 in A morphological, phylogenetic and phylogeographic reappraisal of the land crabs Gecarcinus quadratus De Saussure, 1853, and G. lateralis Fréminville in Guérin 1832 (Decapoda: Gecarcinidae). Are they different species?
FIGURE 5. Maximum likelihood tree (ML) for Gecarcinus, Johngarthia and the outgroup, Cardisoma guanhumi, using the 16S gene. Probability values at the nodes represent support values for likelihood (ML). In the assigned key for Mexican specimens, the last letter indicates whether the organism is male (M), female (H) or juvenile (JU) followed by the individual number. The organisms highlighted in red in the Atlantic Clade correspond to specimens from Costa Rica and Panama. See the locality list in table 1.
Data from: Cryogenic land surface processes shape vegetation biomass patterns in northern European tundra
<p>Tundra ecosystems have experienced changes in vegetation composition, distribution, and productivity over the past century due to climate warming. However, the increase in above-ground biomass (AGB) may be constrained by cryogenic land surface processes (LSP) that cause topsoil disturbance and variable microsite conditions. These effects have remained unaccounted for in tundra biomass models, although they can impact multiple opposing feedbacks between the biosphere and atmosphere, ecosystem functioning and biodiversity. Here, by using field-quantified data from northern Europe, remote sensing, and machine learning, we show that LSP substantially constrain AGB in tundra. The three surveyed LSP (cryoturbation, solifluction and nivation) collectively reduced AGB by an average of 123.0 g m<sup>-2 </sup>(-30.0%). This effect was significant over landscape positions and was especially pronounced in snowbed environments, where the mean reduction in AGB was 57.3%. Our results imply that LSP are pivotal in shaping future patterns of tundra biomass, as long as cryogenic ground activity is retained by climate warming.</p> <p>These are the key data and codes related from Aalto et al., (2021).</p> <p> </p>
A boreal forest model benchmarking dataset for North America: a case study with the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC)
<p>A boreal forest model benchmarking dataset for North America by harmonizing eddy covariance and supporting measurements from black spruce (Picea mariana)-dominated mature forest stands.</p> <p>Dataset glossary and users’ instructions are documented in ‘README.md’. </p>
Influence of land use changes on landscape connectivity for North China leopard (Panthera pardus japonensis)
<p><span>North China leopard (<em>Panthera pardus japonensis</em></span><span>), is the most wid</span><span>espread subspecies of leopard and one of the rare and endangered species in China. It is currently confined to several isolated natural reserves, and little is known about its habitat network connectivity with land use changes. This study was conducted to assess the impacts of land use changes on landscape connectivity for North China leopards in the Great Taihang Region. Circuit theory-based connectivity models and least-cost path analyses were used to delineate pathways suitable for species movement, and evaluate the impacts of land use changes on landscape connectivity. The results revealed that there were 37 least-cost paths in 1990 and 38 in 2020. The area of forest land increased from 57142.74 km<sup>2</sup> to 74836.64 km<sup>2</sup>, with the percentage increasing from 26.61% to 34.85%. In general, the increase of forest land area promoted landscape connectivity for North China leopards at broad spatial scales. The improvement of landscape connectivity was not always consistent with the land use changes, and there was a slightly decreasing trend in connectivity in some key movement barrier areas </span><span>with high-intensity of human activities</span><span>. Improving landscape connectivity at broad spatial scales is as important as protecting the habitats (natural reserves) where the species lives. Our study can serve as an example of exploring the relationships between land use changes and landscape connectivity for species conservation at broad spatial scales with limited movement pattern data. This information is proved to be critical for enhancing landscape connectivity for the conservation concerns of North China leopard and planning of natural reserves network.</span></p>
Climate-ecosystem modelling made easy: the Land Sites Platform - simulation results
<p>Model data to reproduce the experiments and figures presented in "Climate-ecosystem modelling made easy: the Land Sites Platform" (Keetz & Lieungh et al., accepted; publication details to be added).</p> <p>The repository includes model input data for the BOR1 site, and model output for two cases (simulations) executed for that site. Case "bor1-1000y-allpfts" was run with default settings, whereas case "bor1-1000y-grasspfts" was run with C3 grass and Arctic C3 grass as the only plant functional types.<br> Concatenated versions of the model output (made by combining monthly history files) for each case are stored in the top folder as NetCDF files (.nc). The full case folders, including monthly output under /archive/lnd/hist, are stored under "cases/" as zipped directories.<br> The "data/" folder contains model input data for the site, and is identical for the two cases.</p> <p>Jupyter notebooks to analyse the data and create the plots in Figure 4 of the article are stored under "notebooks/technical_paper_results/" in the NorESM-LSP GitHub repository, which is accessible in the same version as the submitted manuscript here: 10.5281/zenodo.7310652</p> <p>Description: Model data to reproduce the experiments and figures presented in "Climate-ecosystem modelling made easy: the Land Sites Platform".<br> Coverage: Geographical coordinates 9.07876, 61.0355. Forcing data from the closest 0.5-degree model grid cell.<br> Format: NetCDF (.nc), zipped directories (.zip), shell scripts (.sh), XML files (.xml), text files (.txt), and others<br> Language: English<br> Relation: 10.5281/zenodo.7310652, <br> Source: GSWP3 for input data (Dirmeyer, P. A., Gao, X., Zhao, M., Guo, Z., Oki, T. and Hanasaki, N. (2006) GSWP-2: Multimodel Analysis and Implications for Our Perception of the Land Surface. Bulletin of the American Meteorological Society, 87(10), 1381–98.)</p>
A 10 m land mask for the Nuup Kangerlua, Kobbefjord, and Ameralik fjord systems in southwest Greenland
<p>This dataset consists of a 10 m land mask of the Nuup Kangerlua, Kobbefjord, and Ameralik fjord systems in southwest Greenland. The land mask is based on two Sentinel-2 MSI images of the area (tiles WDS and WES) that were acquired at high tide on 30 July 2017. Land was masked by applying a threshold of 0.1 Wm<sup>-2</sup> to the short-wave infrared (SWIR) band at 1614 nm. Mountain lakes and shaded coastal regions were masked using the TanDEM-X digital elevation model. Some inland waters were masked manually. </p> <p>Land and water were assigned values of 0 and 1, respectively, and are provided in geotiff format projected to UTM Zone 22 (WGS 84).</p> <p>The boundaries of the mask area extend from 63.90°N, 51.999°W in the southwest to 64.01°N, 51.302°W in the northeast.</p>
Fig. 3 in Further And Further East: Steppe Land Snail, Xerolenta Obvia (Gastropoda, Geomitridae), Expands Its Range In Ukraine
Fig. 3. Shells of X. obvia with an atypically dark colored upper part from Western Ukraine: A — Sosulivka, Ternopil Region; B — Romaniv, Lviv Region; C — Lviv. Scale bars 5 mm.
Fig. 1 in Further And Further East: Steppe Land Snail, Xerolenta Obvia (Gastropoda, Geomitridae), Expands Its Range In Ukraine
Fig. 1. Xeropicta derbentina (A, B) and Xerolenta obvia (C–E) from the Slovianskyi Kurort Regional Landscape Park, Donetsk Region: 1 — stylophores, 2 — swollen basal part of stylophore. Scale bars 5 mm for A–D, 1 mm for E.
Deep Geo Stat WP3 Land Use Change Detection Dataset
<p>This dataset is created as part of work package WP3 of the Deep Geo Stat project, as part of the ESS topic B5674-2020-GEOS (project 101033951: 2020-NL-GEOS-DEEP-GEO-STAT). The objective was to research whether a Siamese Convolutional Neural Network (SCNN) could be used to automatically detect changes in land use.</p> <p>At Statistics Netherlands, every few years, the so-called "Bestand Bodemgebruik" (BBG) is created, which is a file containing information about the land use of the Netherlands for a given year. The country is split up into many polygons, whereby each polygon is labelled with the most common type of land use for that specific area. Creating the BBG is a time-consuming process and the assumption is that it can be speed up if we can automatically detect the changes in land use. During the research, SCCNs were created to decide the changes in land use for three classes. The SCCN models were then applied to the whole of The Netherlands. The results were then converted to GIS files.</p> <p>This dataset contains the GIS files for the classes 34 (building sites), 51 (other agricultural), and 60 (forest). These files can be loaded in QGIS, for example. Each polygon contains the prediction as it rolls out of the model to which we add the label (0: changed, 1: unchanged). Predictions are made on polygons that belonged to the specific class in 2017 and the new label is the prediction for 2018 and 2020.</p>
Vulnerability of estuarine systems in the contiguous United States to water quality change under future climate and land-use
<p>Changes in climate and land-use and land-cover (LULC) are expected to influence surface water runoff and nutrient characteristics of estuarine watersheds, but the extent to which estuaries are vulnerable to altered nutrient loading under future conditions is poorly understood. The present work aims to address this gap through the development of a new vulnerability assessment framework that accounts for (1) estuarine exposure to projected changes in total nitrogen (TN) and total phosphorus (TP) loads as a function of LULC and climate change under several scenarios to altered nutrient loads, (2) sensitivity (i.e., how responsive estuaries are to altered nutrient loads), and (3) adaptive capacity (i.e., how the socio-ecological system can use existing resources to reduce the impacts associated with increased exposure). The framework was applied to 112 estuaries and their contributing watersheds across the contiguous U.S., specifically to look at regional variability in estuarine vulnerability to nutrient loading. Study findings revealed that the largest increases in estuarine nutrient loads are expected in the North and South Atlantic regions and eastern Gulf of Mexico, while the lowest increase is expected in the North and South Pacific regions and the western Gulf of Mexico. However, the North Atlantic and the South Pacific had the highest adaptive capacity, which could potentially counteract the effects of LULC and climate change on nutrient loads. Our findings illustrate the benefits of integrating natural and socio-ecological factors to identify opportunities to develop adaptation plans and policies to mitigate ecological degradation in vitally important estuaries. A<a href="https://lisemontefiore.shinyapps.io/estuarine_vulnerability/"> web-based application</a> has been developed to visualize and download the data.</p>
Data for "Global Riverine Export of Dissolved Lignin Constrained by Hydrology, Geomorphology and Land-Cover"
<p>Dataset for the "Global Riverine Export of Dissolved Lignin Constrained by Hydrology, Geomorphology and Land-Cover". Dataset 01 includes site locations, basin area, dissolved organic carbon (DOC), dissolved lignin concentration and relevant references. Dataset 03 includes mean/discharge-weighted DOC, mean/discharge-weighted dissolved lignin concentrations. Dataset 03 includes geomorphological, climatic, hydrological and land-cover data for the 25 rivers. Dataset 04 includes the reconstructed yield of dissolved lignin and basin area of the 79 rivers.</p>
Concordant and opposing effects of climate and land-use change on avian assemblages in California's most transformed landscapes
<p>Climate and land-use change could exhibit concordant effects that favor or disfavor the same species, which would amplify their impacts, or species may respond to each threat in a divergent manner, causing opposing effects that moderate their impacts in isolation. We used early 20th-century surveys of birds conducted by Joseph Grinnell paired with modern resurveys and land-use change reconstructed from historic maps to examine avian change in Los Angeles and California's Central Valley (and their surrounding foothills). Occupancy and species richness declined greatly in Los Angeles from urbanization, strong warming (+1.8°C) and drying (-77.2 mm), but remained stable in the Central Valley, despite large-scale agricultural development, average warming (+0.9°C), and increased precipitation (+11.2 mm). While climate was the main driver of species distributions a century ago, the combined impacts of land-use and climate change drove temporal changes in occupancy, with similar numbers of species experiencing concordant and opposing effects.</p>
Data for: Combining environmental niche models, multi-grain analyses, and species traits identifies pervasive effects of land use on butterfly biodiversity across Italy
<p><span>Understanding how species respond to human activities is paramount to ecology and conservation science, one outstanding question being how large-scale patterns in land use affect biodiversity. To facilitate answering this question, we propose a novel analytical framework that combines Environmental Niche Models, multi-grain analyses, and species traits. We illustrate the framework capitalizing on the most extensive dataset compiled to date for the butterflies of Italy (106,514 observations for 288 species), assessing how agriculture and urbanization have affected biodiversity of these taxa from landscape to regional scales (3–48 km grains) across the country while accounting for its steep climatic gradients.</span></p> <p><span>Multiple lines of evidence suggest pervasive and scale-dependent effects of land use on butterflies in Italy. While land use explained patterns in species richness primarily at grains ≤ 12 km, idiosyncratic responses in species highlighted "winners" and "losers" across human-dominated regions. Detrimental effects of agriculture and urbanization emerged from landscape (3-km grain) to regional (48-km grain) scales, disproportionally affecting small butterflies and butterflies with a short flight curve. Human activities have therefore reorganized the biogeography of Italian butterflies, filtering out species with poor dispersal capacity and narrow niche breadth not only from local assemblages but also from regional species pools. </span></p> <p><span>These results suggest that global conservation efforts neglecting large-scale patterns in land use risk falling short of their goals, even for taxa typically assumed to persist in small natural areas (e.g., invertebrates). Our study also confirms that consideration of spatial scales will be crucial to implementing effective conservation actions in the Post-2020 Global Biodiversity Framework. In this context, applications of the proposed analytical framework have broad potential to identify which mechanisms underlie biodiversity change at different spatial scales. </span></p> <p><span><em>Funding statement: </em>FR is supported by the PROBAE project "Protect butterflies across Europe through climate refugia" funded by the European Commission through Horizon 2020, Marie Skłodowska-Curie Actions (MSCA) individual fellowship, reintegration panel (Grant agreement ID: 101024579). Open Access Funding provided by Universita degli Studi di Torino within the CRUI-CARE Agreement.</span></p>
CS3 Land-based IMTA abalone South Africa - Socio economic analysis
<p>Data set builds on dataset and bio-economic modelling "CS3 Land-based abalone IMTA - bioeconomic model South Africa 2022" (available in the AquaVitae community in Zenodo) by considering the integrated inclusion of sea cucumbers in abalone farming. It considers three different impacts of including sea cucumbers and compares the socio-economic effects in these with a baseline scenario of abalone farming without sea cucumbers.</p>
Data from: Time series of bird abundances, land cover and temperature from standardized breeding bird monitoring schemes (line transects and point count routes) from Norway, Sweden and Finland, for 1975-2016
<p><span>These data on bird species abundance and environmental variables were used in testing and comparing two different species distribution model validation methods that are applied to models which are used to predict the effects of climate change on species' distributions. The aim of the study was to investigate whether different validation methods give different results of the model's predictive performance and to demonstrate that validation methods based on measuring and validating a "static" pattern in distribution can assess model performance over-optimistically compared to methods based on measuring and validating a "change" in the distribution, which can assess the predictive performance more critically. </span></p>
Data for: The effect of land-use change on soil C, N, P, and their stoichiometries: A global synthesis
<p><strong><em>Data description</em></strong></p> <p>This dataset includes detailed information about five different types of land use change reported in “The effect of land-use change on soil C, N, P, and their stoichiometries: A global synthesis (Agriculture, Ecosystems and Environment; <a href="https://doi.org/10.1016/j.agee.2023.108402)">https://doi.org/10.1016/j.agee.2023.108402)</a>”. </p> <p> </p> <p>Lists of five different types of land use change</p> <p>1) conversion of primary forest to cropland</p> <p>2) conversion of primary forest to grassland</p> <p>3) conversion of cropland to forest</p> <p>4) conversion of grassland to forest</p> <p>5) conversion of grassland to cropland</p> <p> </p> <p>Lists of detailed information</p> <ul> <li>Land use change (pre-LUC, post-LUC)</li> <li>Country, Location, Geographic position (Longitude, Latitude) </li> <li>Altitude (m)</li> <li>Climate zone</li> <li>Weather [rainfall (mm yr<sup>-1</sup>) and temperature (°C)]</li> <li>Reported time of change (years)</li> <li>Vegetation type (pre-LUC, post-LUC)</li> <li>Fertilizer (pre-LUC, post-LUC: type, application; change)</li> <li>Soil sampling depth (cm)</li> <li>Soil type [units, pre-LUC, post-LUC, change rate (%)]</li> <li>Soil pH, bulk density, CEC [units, pre-LUC, post-LUC, change rate (%)]</li> <li>Soil organic carbon [units, pre-LUC, post-LUC, change rate (%)]</li> <li>Soil total nitrogen [units, pre-LUC, post-LUC, change rate (%)]</li> <li>Soil total phosphorus [units, pre-LUC, post-LUC, change rate (%)]</li> <li>Soil C:N [units, pre-LUC, post-LUC, change rate (%)]</li> <li>Soil C:P [units, pre-LUC, post-LUC, change rate (%)]</li> <li>Soil N:P [units, pre-LUC, post-LUC, change rate (%)]</li> <li>Reference</li> </ul> <p> </p> <p><em><strong>Data collection method</strong></em></p> <p>We analyzed five different types of LUC: 1) conversion of primary forest to cropland, 2) conversion of primary forest to grassland, 3) conversion of cropland to forest, 4) conversion of grassland to forest, and 5) conversion of grassland to cropland.</p> <p>We classified primary forest as forest that had not previously been cleared and used for other land uses. The conversion of cropland or grassland to forest includes naturally generated and intentionally planted forest. Cropland is land used for growing agricultural crops and may include short pasture phases, and grassland is land used continuously for grazing purposes, but may include occasional and repeated pasture-renewal phases.</p> <p>While we tried to make categorical distinctions between these land-use types, land uses are often more fluid in practice, which may not always have been stated in the publications underlying our data compilation.</p> <p>When a paper reported both contents and stocks, we used the stock-based measure. We used reported stocks if the original work had already been corrected to equivalent soil mass (Ellert and Bettany, 1995) or if corrected stocks had been reported in previous reviews or meta-analyses (Don et al., 2011; Poeplau et al., 2011; Guo and Gifford, 2002). Where bulk-density correction had not been applied, we tried to make those corrections to estimate changes to equivalent soil mass if studies provided sufficient information on soil bulk density and depth, using the method of Zhang et al. (2004). If that was not possible, we used the reported SOC, TN, or TP contents.</p> <p> </p> <p><em><strong>Acknowledgements</strong></em></p> <p>We thank scientists who measured, analyzed, and published the data compiled for this study. We are especially grateful to Drs. Axel Don, Christopher Poeplau, Lex Bouwman, and Gaihe Yang, who provided their global meta-data through personal communication. D.-G.K. acknowledges support from the IAEA CRP D15020. M.U.F.K and L.L.L. were supported by the Strategic Science Investment Fund (SSIF) of New Zealand’s Ministry of Business, Innovation and Employment.</p>
ScienceDex guides
Understand access before you commit
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.