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Comparison of the accuracy of various land use/land cover datasets in Tianjin
<p>Accuracy comparison of LULC datasets in Tianjin. The dataset consists of interpretation results and five datasets in four time periods of 2010, 2015, 2017 and 2020.</p>
Characterization of Irreversible Land Subsidence in the Yazd-Ardakan Plain, Iran from 2003 to 2020 InSAR Time Series
<p>This repository contains the data used in <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022258">Mirzadeh et al., 2021</a>. It includes two InSAR time-series datasets from Envisat and Sentinel-1 satellite in both ascending and descending orbits, acquired over Yazd-Ardakan Plain, Iran, as well as, the population density information and weather data for this study area.</p> <p>Dataset 1: Envisat ascending track 99 and descending track 20</p> <ul> <li>Date: 06 Sep 2004 - 12 Jul 2010 (17 ascending acquisitions) + 26 Mar 2003 - 23 Oct 2010 (23 descending acquisitions)</li> <li>Processor: ISCE/stripmapStack + MintPy</li> <li>Displacement time-series (in HDF-EOS5 format): timeseries_LODcor_ERA5_ramp_demErr.h5</li> <li>Mean LOS Velocity (in HDF-EOS5 format): velocity.h5</li> <li>Mask Temporal Coherence (in HDF-EOS5 format): maskTempCoh.h5</li> <li>Geometry (in HDF-EOS5 format): geometryRadar.h5</li> </ul> <p>Dataset 2: Sentinel-1 ascending track 130 and descending track 64</p> <ul> <li>Date: 14 Oct 2014 - 28 Mar 2020 (129 ascending acquisitions) + 10 Oct 2014 - 24 Mar 2020 (119 descending acquisitions)</li> <li>Processor: ISCE/topsStack + MintPy</li> <li>Displacement time-series (in HDF-EOS5 format): timeseries_ERA5_ramp_demErr.h5</li> <li>Mean LOS Velocity (in HDF-EOS5 format): velocity.h5</li> <li>Mask Temporal Coherence (in HDF-EOS5 format): maskTempCoh.h5</li> <li>Geometry (in HDF-EOS5 format): geometryRadar.h5</li> </ul> <p>The time series and Mean LOS Velocity (MVL) products can be georeferenced and resampled using the makTempCoh and geometryRadar products, and the MintPy commands/functions.</p>
Data supplement for: Agreement of analytical and simulation-based estimates of the required land depth in climate models
<p>Many current-generation climate models have land components that are too shallow. Under climate change conditions, the long-term warming trend at the surface propagates deeper into the ground than the commonly used 3-10m. Shallow models alter the terrestrial heat storage and distribution of temperatures in the subsurface, influencing the simulated land-atmosphere interactions. Previous studies focusing on annual timescales suggest that deeper models are required to match subsurface-temperature observations and the classic analytical heat conduction solution. However, for a systematic investigation of land-model deepening in the frame of anthropogenic climate change, the classic analytical solution is inaccurate because it does not mimic the timescale and amplitude of the simulated warming trend. This study intends to bridge the gap between analytical and simulation-based estimates of the subsurface thermodynamic state by adapting the classic analytical framework to mimic long-term anthropogenic warming. The analysis shows that a land-model depth of at least 170m is recommended for a proper simulation of the post-1850 ground climate, which differs up to 30% from the estimate of the classic approach. Compared to previous studies, this provides an accurate estimate of the required land model depth for long-term climate-change simulations and indicates the relative bias in insufficiently deep land models.</p>
Projected impacts of climate and land use changes on the habitat of Atlantic Forest plants in Brazil
<p>Aim:<b> </b>To provide novel evidence on the average impact of climate and land use changes on habitat suitability for tropical plants and to test previous conclusions on the relative importance of these two drivers in shaping future availability of habitat for tropical plant species.</p> <p>Location<b>: </b>Brazil's Atlantic Forest domain.</p> <p>Time period: Plant occurrences recorded between 1960 and 2014. Baseline climate from 1960-2000 and land use from 2015. Projected scenarios of climate for 2041-2060 and land use for 2050.</p> <p>Major taxa studied: Angiosperms.</p> <p>Results: Our results suggest that climate change alone will, surprisingly, have only a modest negative impact on the mean habitat suitability, decreasing it by 2% (median = -5% to -7%, variation associated with scenarios). Land use change alone had a more consistent negative impact on habitat suitability, causing mean and median reductions of 4% to 6%. When the effects of climate and land use are combined, the mean habitat suitability was reduced by 4% (median = -9% to -11%).</p> <p>Main conclusions: The combined impacts of climate and land use changes were substantial, although smaller than expected. Habitat suitability decreased for most species, but it increased substantially for some species, suggesting that the distribution of impacts across species is markedly right skewed. The impacts were typically detrimental to small-ranged species and neutral or beneficial to widespread species. Land use change rather than climate change will likely cause more losses to the habitat of Atlantic Forest plant species within the next several decades.</p>
Distinct Roles of Land Cover in Regulating Spatial Variabilities of Temperature Responses to Radiative Effects of Aerosols and Clouds
<p>Dataset of drawing figures in work 'Distinct Roles of Land Cover in Regulating Spatial Variabilities of Temperature Responses to Radiative Effects of Aerosols and Clouds'.</p> <p>Dataset File List </p> <p>1. Present_Day_Variables.nc : global spatial distributions of radiative forcing, climate sensitivity and temperature response </p> <p>2. Regional_Variables.xlsx : regional data of radiative forcing, climate sensitivity and temperature response</p> <p>3. Aerosol_Burdens.nc : monthly aerosol burdens (atmospheric column concentration) of ten simulation cases </p> <p>4. Aerosol_Burdens_README.txt : dimensional descriptions of Aerosol_Burdens.nc</p> <p>5. Monthly_Radiation.nc : monthly radiation variables of PD simulation for testing model performance</p> <p>6. Monthly_Radiation_README.txt : dimensional descriptions of Monthly_Radiation.nc</p> <p> </p>
Figure 33 in Descriptions of New Species of the Diverse and Endemic Land Snail Amplirhagada Iredale, 1933 from Rainforest Patches across the Kimberley, Western Australia (Pulmonata: Camaenidae)
Figure 33. Penial anatomy of Amplirhagada
Data from: Predicting range shifts of pikas (Mammalia, Ochotonidae) in China under scenarios incorporating land-use change, climate change, and dispersal limitations
<p><span>Two of the most important forces affecting biodiversity are land-use change (LUC) and global climate change (GCC). Previous studies have modeled their impacts on species separately and together, but few have done so for multiple species with dispersal limitations incorporated into the models.</span></p> <p><span>We integrate species distribution models plus a dispersal model to predict LUC and GCC impacts on the ranges of five species of pikas in the Qinghai-Tibet Plateau region of China. Pikas are sensitive to land-use and climate change, and have limited dispersal abilities.</span></p> <p><span>The predicted impacts of LUC and GCC on pikas vary between species as well as between LUC and GCC projections. Incorporation of dispersal limitations appreciably restricts the amount of colonized habitat. For all five species, the amount of habitat abandoned or colonized when LUC and GCC are modeled together is less than the sum of LUC and GCC modeled separately. Three of the five species experience a net increase in occupied habitat by 2080 relative to their current ranges under all modeled projections. However, relative to a "Dispersal Only" baseline scenario that assumes no environmental change but continued range expansion into suitable, unoccupied habitat, all five species suffer a net loss of occupied habitat by 2080 under some or all projections.</span></p> <p><span>Predictions of future distributions of species based solely on LUC or GCC, as well as predictions assuming additive impacts, can be misleading. Inclusion of dispersal limitations in models markedly alters predicted future distributions of species. The use of a "Dispersal Only" scenario provides a different and perhaps more accurate way to gauge net impacts to species. Future work should consider incorporating all these parameters to better predict the impacts of LUC and GCC on biodiversity.</span></p>
Dataset of the paper titled Geological characteristics and high scientific interest targets of the Zhurong landing region on Mars
<p>This dataset contains the original data and crater counting data of the paper titled Geological characteristics and high scientific interest targets of the Zhurong landing region on Mars.</p>
Fig. 3 in Discovery of an overlooked Helicarionid land snail (Helicarionidae: Durgellinae) from northeastern Thailand, with description of a new genus and new species, and note on radula morphology and genital system
Fig. 3. Aenigmatoconcha clivicola, new species, holotype (NHMSU-0013).
FIGURE 10 in A second endemic land mammal for the Hawaiian Islands: a new genus and species of fossil bat (Chiroptera: Vespertilionidae)
FIGURE 10. Skeleton of Synemporion keana in situ on the floor near the lower end of Māhiehie Cave.
Fig. 5 in Gomphos elkema (Glires, Mammalia) from the Erlian Basin: Evidence for the Early Tertiary Bumbanian Land Mammal Age in Nei-Mongol, China
Fig. 5. Lower teeth of Gomphos elkema. A–C. Occlusal, lingual, and labial views of right m1–m3
Fig. 6 in Gomphos elkema (Glires, Mammalia) from the Erlian Basin: Evidence for the Early Tertiary Bumbanian Land Mammal Age in Nei-Mongol, China
Fig. 6. Lower teeth of Gomphos elkema. A–B. Occlusal views of left and right m1–m3, respectively
Fig. 1 in Gomphos elkema (Glires, Mammalia) from the Erlian Basin: Evidence for the Early Tertiary Bumbanian Land Mammal Age in Nei-Mongol, China
Fig. 1. Locality map of the Erlian Basin (after Meng et al., 1998).
R scripts for the practical exercises with QGIS in the book "Land Use Cover Datasets and Validation Tools"
<p>This dataset includes a series of R scripts required to carry out some of the practical exercises in the book “Land Use Cover Datasets and Validation Tools”, available in open access.</p> <p>The scripts have been designed within the context of the R Processing Provider, a plugin that integrates the R processing environment into QGIS. For all the information about how to use these scripts in QGIS, please refer to Chapter 1 of the book referred to above.</p> <p>The dataset includes 15 different scripts, which can implement the calculation of different metrics in QGIS:</p> <ul> <li>Change statistics such as absolute change, relative change and annual rate of change (Change_Statistics.rsx)</li> <li>Areal and spatial agreement metrics, either overall (Overall Areal Inconsistency.rsx, Overall Spatial Agreement.rsx, Overall Spatial Inconsistency.rsx) or per category (Individual Areal Inconsistency.rsx, Individual Spatial Agreement.rsx)</li> <li>The four components of change (gross gains, gross losses, net change and swap) proposed by Pontius Jr. (2004) (LUCCBudget.rsx)</li> <li>The intensity analysis proposed by Aldwaik and Pontius (2012) (Intensity_analysis.rsx)</li> <li>The Flow matrix proposed by Runfola and Pontius (2013) (Stable_change_flow_matrix.rsx, Flow_matrix_graf.rsx)</li> <li>Pearson and Spearman correlations (Correlation.rsx)</li> <li>The Receiver Operating Characteristic (ROC) (ROCAnalysis.rsx)</li> <li>The Goodness of Fit (GOF) calculated using the MapCurves method proposed by Hargrove et al. (2006) (MapCurves_raster.rsx, MapCurves_vector.rsx)</li> <li>The spatial distribution of overall, user and producer’s accuracies, obtained through Geographical Weighted Regression methods (Local accuracy assessment statistics.rsx).</li> </ul> <p>Descriptions of all these methods can be found in different chapters of the aforementioned book.</p> <p>The dataset also includes a readme file listing all the scripts provided, detailing their authors and the references on which their methods are based.</p>
Data for the practical exercises in the book "Land Use Cover Datasets and Validation Tools"
<p>This dataset contains all the data that is required to carry out the practical exercises in the book “Land Use Cover Datasets and Validation Tools”, available in open access.</p> <p>The dataset includes data for three different case studies: The Asturias Central Area (Spain), the Ariège Valley (France) and Marqués de Comillas (Mexico). For the Asturias Central Area and the Ariège Valley, the dataset includes Land Use Cover (LUC) maps for several years of reference as well as data (simulation outputs, model drivers) for different modelling exercises. For Marqués de Comillas, the dataset includes a LUC map and a set of reference points used to validate it.</p> <p>The dataset includes a readme file listing all the files it contains and auxiliary files describing the data. For further information on the study area and the files used in the practical exercises, users are referred to Chapter 1 of the book.</p>
Figure 6 in A mass recruitment event in the land crab Gecarcinus ruricola (Linnaeus, 1758) (Brachyura: Grapsoidea: Gecarcinidae), and a description of the megalop
Figure 6. Gecarcinus ruricola (Linnaeus, 1758); megalop; A, second maxilliped; B, third maxilliped.
Figure 5 in A mass recruitment event in the land crab Gecarcinus ruricola (Linnaeus, 1758) (Brachyura: Grapsoidea: Gecarcinidae), and a description of the megalop
Figure 5. Gecarcinus ruricola (Linnaeus, 1758); megalop; A, maxilla; B, first maxilliped.
European soil seed bank communities across a climate and land-cover gradient
<p>This is the data set used for the publication <em>Buffering effects of soil seed banks on plant community composition in response to land use and climate</em>, published in the journal<em> Global Ecology and Biogeography</em>.</p> <p><strong>Aim</strong>. Climate and land use are key determinants of biodiversity, with past and ongoing changes posing serious threats to global ecosystems. Unlike most other organism groups, plant species can possess dormant life-history stages such as soil seed banks, which may help plant communities to resist or at least postpone the detrimental impact of global changes. This study investigates the potential for soil seed banks to achieve this.</p> <p><strong>Location</strong>. Europe</p> <p><strong>Time</strong> <strong>period</strong>. 1978 – 2014</p> <p><strong>Major taxa studied</strong>. Flowering plants</p> <p><strong>Methods</strong>. Using a space-for-time/warming approach, we study plant species richness and composition in the herb layer and the soil seed bank in 2796 community plots from 54 datasets in managed grasslands, forests and intermediate, successional habitats across a climate gradient.</p> <p><strong>Results</strong>. Soil seed banks held more species than the herb layer, being compositionally similar across habitats. Species richness was lower in forests and successional habitats compared to grasslands, with annual temperature range more important than mean annual temperature for determining richness. Climate and land use effects were generally less pronounced when plant community richness included seed bank species richness, while there was no clear effect of land use and climate on compositional similarity between the seed bank and the herb layer.</p> <p><strong>Main conclusions</strong>. High seed bank diversity and compositional similarity between the herb layer and seed bank plant communities may provide a potentially important functional buffer against the impact of ongoing environmental changes on plant communities. This capacity could, however, be threatened by climate warming. Dormant life-history stages can therefore be important sources of diversity in changing environments, potentially underpinning already observed time-lags in plant community responses to global change. However, as soil seed banks themselves appear, albeit less, vulnerable to the same changes, their potential to buffer change can only be temporary, and major community shifts may still be expected.</p>
Relationship of insect biomass and richness with land use along a climate gradient
<p>This dataset contains data from a field study conducted in 2019 and described in the paper "Relationship of insect biomass and richness with land use along a climate gradient" by Uhler et al.</p> <p>In this study, arthropod communities were collected by Malaisetraps along a land use and climate gradient and identified by Metabarcoding. Malaise traps are versatile passive net-traps, capable of catching a large spectrum of insect taxa and are very effective when the aim is to get a representative snapshot of the local insect community. Overall, 179 Malaise traps were set up in 2019 along a gradient of increasing land use intensity, ranging from forests, to meadows, to arable fields, and settlements. The analyzed sites were spatially distributed over 400km and covered an elevational gradient of 1000m.</p> <p>Generalized additive models were fitted to test for the effects of local and landscape-level land-use categories on insect biomass and species richness.</p> <p>We found the largest difference in biomass between semi-natural and urban environments (−42%), whereas differences in total richness (−29%) and the richness of threatened species (−56%) were largest from semi-natural to agricultural environments. These results point to urbanization and agriculture as major drivers of decline. We also found that richness and biomass increase monotonously with increasing temperature, independent of habitat. The contrasting patterns of insect biomass and richness question the use of these indicators as mutual surrogates. Our study provides support for the implementation of more comprehensive measures aimed at habitat restoration in order to halt insect declines.</p>
Europe and China Refined Land cover (ECRLC)
<p>Europe and China Refined Land cover (ECRLC) is a 30-m Landsat-based landcover database spanning 3 epochs(2000, 2010, and 2020) for Paris Region (Europe), Aarhus (Europe), Velika Gorica (Europe), Beijing (China), Shanghai (China), and Ningbo (China).</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.