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1,153 results for “conservation data”
Stable isotope and conservative tracer data used to estimate uptake of stream water dissolved organic carbon (DOC) through a whole-stream addition of a ¹³C-DOC tracer coupled with laboratory measurements of bioavailability of the tracer and stream water DOC using lability profiling with bioreactors
We performed a whole-stream addition of a ¹³C-DOC tracer and made laboratory measurements of the biological availability of the tracer as well as stream water DOC. The study was performed in October 2002 in a 1.27 km stretch of the third-order White Clay Creek in southeastern Pennsylvania. The tracer was prepared as a cold-water leachate of ¹³C-labeled tulip poplar saplings and it was added to the stream along with sodium bromide, a conservative tracer, over a 2-h period. Stream water samples were collected at 8 downstream stations over an 8-h period, filtered, and analyzed for concentrations of bromide and DOC. DOC was measured by Pt-catalyzed, persulfate oxidation, Br- was analyzed by ion chromatography, and C isotope samples were rotary evaporated, acidified, lyophilized, combusted, and the CO₂ analyzed with an elemental analyzer interfaced with an isotope ratio mass spectrometer. Lability profiling of the ¹³C-DOC tracer and stream water DOC were performed with a series of plug-flow bioreactors of increasing empty-bed contact times with the concentration of biodegradable DOC operationally defined as the difference between the DOC concentrations in the influent and effluent waters of the bioreactors. The bioreactor measurements were performed 2 days after the whole-stream release. Data were analyzed to estimate the uptake of stream water DOC associated with labile and semi-labile fraction of biodegradable DOC. These data have been previously used in a 2008 publication in Freshwater Biology, doi:10.1111/j.1365-2427.2007.01941.x.
Throw trap and Electrofishing Data from Water Conservation Area 3B, Florida, USA, 2019-2022 for the Decompartmentalization Physical Model Project
This dataset includes densities and biomass of fishes and macroinvertebrates collected using throw traps or an airboat-mounted electrofisher in the study region of the Decompartmentalization Physical Model (DPM) located in Water Conservation Area (WCA) 3B. Some sites in this region experienced seasonal increases in water flow due to the operations of the S-152 structure. The sites sampled for this dataset were either located along a gradient of water flow (downstream the S-152) or were in a reference area that had ambient flow conditions. The purpose of this dataset was to quantify community responses of consumers groups to flowing water and how it may interact with local nutrient conditions at the site level. Hydrological, floc nutrient and periphyton volume data used in the analyses are included. This data package includes the R script that was used to run the statistical models for the manuscript titled "Discharge and nutrients interact to determine trophic structure in a wetland: evidence from a landscape-scale manipulation". The data collection for this data package is complete.
Fig. 3 in New acoustic and molecular data shed light on the poorly known Amazonian frog Adenomera simonstuarti (Leptodactylidae): implications for distribution and conservation
Fig. 3. Preserved male of nominal Adenomera simonstuarti (Angulo & Icochea, 2010) (= genetic lineage 3): call voucher INPA-H 40967 (SVL = 23.4 mm) from the upper Juruá River, in Tarauacá, Brazilian state of Acre. This specimen corresponds to a call voucher (see Fig. 5). A−B. Body in dorsal and ventral views, not to scale. C−D. Detail of the ventral surface of right foot and hand, respectively. Note the nearly solid, dark-colored stripe along the underside of the forearm. Photographs by J. Magnusson. Scale bar = 5 mm.
Data from: Australian rodents reveal conserved craniofacial evolutionary allometry across 10 million years of murid evolution
<p>Among vertebrates, placental mammals are particularly variable in the covariance between cranial shape and body size (allometry), with rodents a major exception. Australian murid rodents allow an assessment of the cause of this anomaly because they radiated on an ecologically diverse continent notably lacking other terrestrial placentals. Here we use 3D geometric morphometrics to quantify species-level and evolutionary allometries in 38 species (317 crania) from all Australian murid genera. We ask if ecological opportunity resulted in greater allometric diversity compared to other rodents, or if conserved allometry suggests intrinsic constraints and/or stabilizing selection. We also assess whether cranial shape variation follows the proposed "rule of craniofacial evolutionary allometry" (CREA), whereby larger species have relatively longer snouts and smaller braincases. To ensure we could differentiate parallel versus non-parallel species-level allometric slopes, we compared the slopes of rarefied samples across all clades. We found exceedingly conserved allometry and CREA-like patterns across the 10 million year split between <i>Mus</i> and Australian murids. This could support both intrinsic constraints and stabilizing selection hypotheses for conserved allometry. Large-bodied frugivores evolved faster than other species along the allometric trajectory, which could suggest stabilizing selection on the shape of the masticatory apparatus as body size changes.</p>
Data from: A conservation status survey of hornbills (Bucerotidae) in the Western Ghats, India
The Western Ghats biodiversity hotspot in India is threatened by habitat loss and fragmentation, which is likely to impact large-bodied, wide-ranging species with specialised requirements such as hornbills. In this survey along the Western Ghats, we surveyed for four hornbill species that occur here: Malabar Pied Hornbill Anthracoceros coronatus, and Indian Grey Hornbill Ocyceros birostris (endemic to South Asia), Malabar Grey Hornbill Ocyceros griseus (endemic to the Western Ghats), and the Great Hornbill Buceros bicornis. We visited 45 localities across five states: Maharashtra, Goa, Karnataka, Kerala, and Tamil Nadu. These included 26 wildlife sanctuaries, 5 national parks, 13 reserved forests, and one plantation landscape. Across sites, we walked 80 transect surveys totalling a length of 286.4 km. In all, 631 individual hornbills (412 detections) were recorded across 35 localities. The Malabar Grey Hornbill was most frequently detected, and widely-distributed, followed by the Great, and Malabar Pied hornbills. The Indian Grey Hornbill, more widespread across India, was seen in only two locations in this survey. Hornbill encounter was up to five times higher in moist, and wet forests as compared to dry forest types. Based on hornbill distribution and protected areas, five important hornbill conservation landscapes were identified in the Western Ghats (Amboli–Goa–Dandeli, Anamalai–Parambikulam–Vazhachal, Nilgiris– Wayanad, Someshwara–Sharavati–Mookambika, Neyyar–Peppara–KMTR, and Periyar) along with key reserved forests (Kottiyoor, New Amarambalam, Vazhachal, Nelliampathy, Goodarickal, Kulathupuzha–Palode). Hornbill densities were estimated in two of the above landscapes, and are provided as a baseline. We highlight some key considerations for hornbill research and conservation, and future needs.
Data from: Habitat selection in transformed landscapes and the role of forest remnants and shade coffee in the conservation of resident birds
1. Biodiversity conservation in transformed landscapes is becoming increasingly important. However, most assessments of the value of modified habitats rely heavily on species presence and/or abundance, masking ecological processes such as habitat selection and phenomena like ecological traps, which may render species persistence uncertain. High species richness has been documented in tropical agroforestry systems but comparisons with native habitat remnants generally lack detailed information on species demography and habitat use. 2. We generated a multi-species, multi-measure framework to evaluate the role of habitat selection in the adaptation of species to transformed landscapes, and demonstrate that its use could affect how we value the contribution different land uses make to biodiversity conservation. 3. We analyzed seven years of capture-mark-recapture and observation data for twelve species of resident birds present in native forest remnants and shade coffee plantations in a mega-diverse region. We assessed whether species behaved adaptively by evaluating the correlation between measures of habitat preference (occurrence, abundance, fidelity, inter-seasonal variance and age) and performance (body condition, muscle, primary molt, breeding and juveniles) in forest and coffee, and generated hypotheses about their role in species persistence. 4. We documented adaptive habitat selection for seven species, non-ideal selection for four, and maladaptive selection for one. While many species showed equal-preference and/or equal performance in many traits, in general we found more evidence for birds preferring and/or performing better in forest than coffee, although relationships between our indicators and population adaptation need to be studied further before our proposed framework can be applied to more species and landscapes. 5. While shade coffee can act as a biodiversity-friendly matrix providing complementary or supplementary habitat to a wide range of resident bird species, protecting remnants of native vegetation is still of paramount importance for biodiversity conservation in agricultural landscapes. 28-Aug-2019
Supporting data: Grain-dependent responses of mammalian diversity to land-use and the implications for conservation set-aside
<p>Camera trap and live trap datasets underlying the analyses in an <em>Ecological Applications </em>paper (http://onlinelibrary.wiley.com/doi/10.1890/15-1363/abstract), provided in .csv format. Each row consists of a single trap night at a given location, with species in different columns. Old-growth forest, logged forest and oil palm plantation locations have the prefixes "Old", "Log" and "Palm", respectively. Values in each cell are the number of independent captures, as defined in the paper. </p>
Survey data for "Remote Sensing & GIS Training in Ecology and Conservation"
<p>This file provides the raw data of an online survey intended at gathering information regarding remote sensing (RS) and Geographical Information Systems (GIS) for conservation in academic education. The aim was to unfold best practices as well as gaps in teaching methods of remote sensing/GIS, and to help inform how these may be adapted and improved. A total of 73 people answered the survey, which was distributed through closed mailing lists of universities and conservation groups.</p>
FIGURE 30 in Morphological and molecular data reveal the cryptic diversity among populations of Aegla paulensis (Decapoda, Anomura, Aeglidae), with descriptions of four new species and comments on dispersal routes and conservation status
FIGURE 30. Bayesian tree (TPM 2 uf + G) for Aegla species based on partial fragment of 16 S. Node numbers represent posterior probabilities (values <50 % are not shown), and divergence time in millions of years (my); * indicates the calibration points to molecular clock. The clade C proposed by Pérez-Losada et al. (2004) is highlighted in grey. The basin and sub-basin origin of the discussed species in this study are shown after the specific names.
FIGURE 24. A – L in Morphological and molecular data reveal the cryptic diversity among populations of Aegla paulensis (Decapoda, Anomura, Aeglidae), with descriptions of four new species and comments on dispersal routes and conservation status
FIGURE 24. A – L, proximal portion of fifth pereiopod showing coxa and sexual tube of long and narrow type. A – B, Aegla paulensis Schmitt, 1942 s. str., male topotype (MZUSP 34368). C – D, Aegla rosanae Campos Jr., 1998, male topotype (MZUSP 34369). E – F, Aegla vanini n. sp., male paratype (MZUSP 34372). G – H, Aegla japi n. sp., male paratype (MZUSP 34375). I – J, Aegla jaragua n. sp. male paratype (MZUSP 34378). K-L, Aegla jundiai n. sp., male paratype (MZUSP 13490). Bars: A – D, F – H, J = 200 µm; K, L = 100 µm; E, I = 500 µm.
FIGURE 8 in Morphological and molecular data reveal the cryptic diversity among populations of Aegla paulensis (Decapoda, Anomura, Aeglidae), with descriptions of four new species and comments on dispersal routes and conservation status
FIGURE 8. Types of Aegla Leach, 1820 male sexual tubes. A, long and narrow (A. lancinhas Bond-Buckup & Buckup in Santos et al., 2015, MZUSP 34403). B, short and wide (A. leptochela Bond-Buckup & Buckup, 1994, MZUSP 34491).
FIGURE 1 in Morphological and molecular data reveal the cryptic diversity among populations of Aegla paulensis (Decapoda, Anomura, Aeglidae), with descriptions of four new species and comments on dispersal routes and conservation status
FIGURE 1. Distribution of the species of Aegla in four main hydrographic basins of southern Brazil: Rio Grande, Rio Tietê (Upper Paraná system), Rio Paraíba do Sul and Ribeira de Iguape. Indications L 1 through L 7 refer to the locations mentioned under “ sampling area ” in the Material & Methods section.
Data for "Water (or the Lack Thereof), Management, and Conservation of an Endangered Desert Wetland Obligate, Lilaeopsis schaffneriana var. recurva"
<p>Raw and RData forms of data for "Water (or the Lack Thereof), Management, and Conservation of an Endangered Desert Wetland Obligate, <em>Lilaeopsis schaffneriana </em>var. <em>recurva". </em>Consists of six Excel files, with names corresponding to the type of data.</p> <ol> <li>field_ecology_data.xlsx </li> <li>experiment_randomization.xlsx </li> <li>experiment_entered_data.xlsx </li> <li>resilience_days_to_critical.xlsx </li> <li>resilience_experiment_data.xlsx </li> <li>resilience_leaf_density_data.xlsx </li> </ol> <p>Four RData files of the loaded Excel data, and one text file to explain the coding of the drought experiment data.</p>
Data from: Area of habitat maps and validated occurrences for neotropical birds of conservation concern
<p>Understanding species distributions is essential for advancing bird conservation, especially in the rapidly changing landscapes of the Neotropics, where habitat loss and degradation are accelerating. Area of Habitat (AOH) maps offer valuable spatial tools for illustrating species distributions by highlighting potentially suitable habitats within their geographic range. In this study, we generated AOH maps for 713 neotropical bird species of conservation concern, which includes species listed as globally or nationally threatened, endemic, or with restricted ranges. Using primary biodiversity data and a structured geospatial workflow, we refined approximately 2.5 million occurrence records through a flagging process and validated 50,743 records manually.<strong> </strong>This unparalleled effort led to the creation of high-quality AOH maps, along with altitude-corrected Extent of Occurrence (EOO-DEM) and Inverse Distance Weighted (IDW) range maps. Our AOH maps significantly improved species distribution predictions for 82% of species, over EOO-DEM maps. The validated occurrences and AOH maps produced in this study have wide-ranging applications, providing a valuable basis for the development of new species distribution models and for evaluating species’ natural history, extinction risk, and habitat threats. They also support the identification of priority areas for strategic conservation investments. Importantly, these maps played a key role in systematic conservation planning analyses for the Conserva Aves initiative, which is facilitating the creation of more than 80 new protected areas across Latin America, safeguarding 2 million hectares and improving the management of an additional 2 million hectares (<a href="https://conserva-aves.org/">https://conserva-aves.org/</a>).</p>
Supporting data sets for "Evolutionary analyses of IDRs reveal widespread signals of conservation"
<p>S1: Disorder and order regions of alignments computed from AUCPreD scores which passed the 30 residue minimum length and phylogenetic diversity filters. The "ppids" column indicates the sequences in each alignment which were not excluded due these and other filtering criteria. See the main text methods for more details.<br><br>S2: Substitution model parameters fit to meta-alignments derived from disorder and order filtered regions.<br><br>S3: Features of segments in all regions.<br><br>S4: Contrasts and root estimates of disorder scores in filtered regions computed with Felsenstein's contrasts algorithm.<br><br>S5: Contrasts and root estimates of features in filtered regions computed with Felsenstein's contrasts algorithm.<br><br>S6: Estimated BM and OU model parameters of simulated data.<br><br>S7: Estimated BM and OU model parameters of features in filtered regions computed with maximum likelihood.</p><p> </p>
Data and code for publication: Advancing Maternal Transfer of Organic Pollutants across Reptiles for Conservation and Risk Assessment Purposes
<p>Dataset and r code to prepare the dataset, in support of the publication:</p> <p>"Advancing maternal transfer of organic pollutants across reptiles for conservation and risk assessment purposes"</p> <p>Munoz, C.C., Charles, S., Vermeiren, P. (2024) Environmental Science and Technology, https://doi.org/10.1021/acs.est.4c04668</p> <p>contact email: munozc.cynthia@gmail.com</p>
Data for "Future global mangrove losses and the key role of protected areas in their conservation"
<p>Content (spatial resolution, data info)</p> <ol> <li>Mangrove table input to the machine learning model (1 table)</li> <li>Results of mangrove cumulative loss proportion under SSP1 and SPP5 scenarios (1km, 1 ZIP)</li> <li>All processing R codes can be accessed: https://github.com/2pangp/Mangrove-TidalFlat_Distribution</li> </ol>
Supplementary data for: Chromosome-scale genome assemblies of aphids reveal extensively rearranged autosomes and long-term conservation of the X chromosome
<p><strong><em>Myzus persicae </em>clone O v2 frozen release</strong></p> <p>Genome assembly: Myzus_persicae_O_v2.0.scaffolds.fa.gz</p> <p>BRAKER2 gene models: Myzus_persicae_O_v2.0.scaffolds.braker2.gff3</p> <p>List of gene models containing internal stop codons (removed from the protein and cds fasta files): Myzus_persicae_O_v2.0.scaffolds.braker2.bad_genes.lst</p> <p>BRAKER2 protein sequences: Myzus_persicae_O_v2.0.scaffolds.braker2.gff3.filtered.aa.fa</p> <p>BRAKER2 protein sequences (longest transcript per gene only): Myzus_persicae_O_v2.0.scaffolds.braker2.gff3.filtered.aa.LTPG.fa</p> <p>BRAKER2 coding sequences: Myzus_persicae_O_v2.0.scaffolds.braker2.gff3.filtered.cds.fa</p> <p>BRAKER2 coding sequences (longest transcript per gene only): Myzus_persicae_O_v2.0.scaffolds.braker2.gff3.filtered.cds.LTPG.fa</p> <p><em>De novo </em>repeat library (ReapeatModeler merged with repbase insecta): Myzus_persicae_O_v2.0_repeat_lib.repeatmodeler_merged_repbase_insecta.fa</p> <p>RepeatMasker transposable element annotation using the <em>M. persicae de novo</em> repeat library: Myzus_persicae_O_v2.0.scaffolds.repeatmodeler_merged_repbase_insecta.repeatmasker.gff.out</p> <p>RepeatMasker transposable element annotation using the <em>M. persicae</em> <em>de novo r</em>epeat library (gff format): Myzus_persicae_O_v2.0.scaffolds.repeatmodeler_merged_repbase_insecta.repeatmasker.gff</p> <p><strong><em>Acyrthosiphon pisum</em> clone JIC1 v1 frozen release</strong></p> <p>Genome assembly: Acyrthosiphon_pisum_JIC1_v1.0.scaffolds.fa.gz</p> <p>BRAKER2 gene models: Acyrthosiphon_pisum_JIC1_v1.0.scaffolds.braker2.gff</p> <p>List of gene models containing internal stop codons (removed from the protein and cds fasta files): Acyrthosiphon_pisum_JIC1_v1.0.scaffolds.braker2.bad_genes.lst</p> <p>BRAKER2 protein sequences: Acyrthosiphon_pisum_JIC1_v1.0.scaffolds.braker2.gff.filtered.aa.fa</p> <p>BRAKER2 protein sequences (longest transcript per gene only): Acyrthosiphon_pisum_JIC1_v1.0.scaffolds.braker2.gff.filtered.aa.LTPG.fa</p> <p>BRAKER2 coding sequences: Acyrthosiphon_pisum_JIC1_v1.0.scaffolds.braker2.gff.filtered.cds.fa</p> <p>BRAKER2 coding sequences (longest transcript per gene only): Acyrthosiphon_pisum_JIC1_v1.0.scaffolds.braker2.gff.filtered.cds.LTPG.fa</p> <p><em>De novo </em>repeat library (ReapeatModeler merged with repbase insecta): Acyrthosiphon_pisum_JIC1_repeat_lib.repeatmodeler_merged_repbase_insecta.fa</p> <p>RepeatMasker transposable element annotation using the <em>A. pisum</em> <em>de novo</em> repeat library: Acyrthosiphon_pisum_JIC1_v1.0.scaffolds.repeatmodeler_merged_repbase_insecta.repeatmasker.out</p> <p>RepeatMasker transposable element annotation using the <em>A. pisum de novo</em> repeat library (gff format): Acyrthosiphon_pisum_JIC1_v1.0.scaffolds.repeatmodeler_merged_repbase_insecta.repeatmasker.gff</p> <p><strong><em>Rhodnius prolixus</em> DNA zoo chromosome-scale genome assembly annotation</strong></p> <p><em>R. prolixus </em>chromosome-scale genome assembly was obtained here: <a href="https://www.dnazoo.org/assemblies/Rhodnius_prolixus">https://www.dnazoo.org/assemblies/Rhodnius_prolixus</a>.</p> <p>Genome assembly: Rhodnius_prolixus-3.0.3_HiC.fasta</p> <p>BRAKER2 gene models: Rhodnius_prolixus-3.0.3_HiC.braker2.gff</p> <p>BRAKER2 protein sequences: Rhodnius_prolixus-3.0.3_HiC.braker2.gff.aa.fa</p> <p>BRAKER2 protein sequences (longest transcript per gene only): Rhodnius_prolixus-3.0.3_HiC.braker2.gff.aa.LTPG.fa</p> <p>BRAKER2 coding sequences: Rhodnius_prolixus-3.0.3_HiC.braker2.gff.cds.fa</p> <p><strong><em>Triatoma rubrofasciata</em> chromosome-scale genome assembly annotation</strong></p> <p><em>T. rubrofasciata </em>chromosome-scale genome assembly was obtained here: <a href="http://dx.doi.org/10.5524/100614">http://dx.doi.org/10.5524/100614</a></p> <p>Genome assembly: zhuichun_assembly.fasta</p> <p>BRAKER2 gene models: zhuichun_assembly.braker2.gff</p> <p>BRAKER2 protein sequences: zhuichun_assembly.braker2.gff.aa.fa</p> <p>BRAKER2 protein sequences (longest transcript per gene only): zhuichun_assembly.braker2.gff.aa.LTPG.fa</p> <p>BRAKER2 coding sequences: zhuichun_assembly.braker2.gff.cds.fa</p> <p><strong>Hemiptera orthogroups and species tree</strong></p> <p>OrthoFinder was used to cluster proteomes of 14 Hemiptera into orthogroups for phylogenomic analysis. All proteomes were reduced to the longest transcript per gene. See here for full details:</p> <p>Species included, taxon IDs and data source:</p> <p>Mcer = Myzus cerasi v1.1 (<a href="https://bipaa.genouest.org/sp/myzus_cerasi/">https://bipaa.genouest.org/sp/myzus_cerasi/</a>)</p> <p>MperO = Myzus persicae clone O v2 (This study)</p> <p>Dnox = Diuraphis noxia Thorpe et. al. gene predictions (<a href="https://bipaa.genouest.org/sp/diuraphis_noxia/">https://bipaa.genouest.org/sp/diuraphis_noxia/</a>)</p> <p>Apis = Acyrthosiphon pisum JIC1 v1 (This study)</p> <p>Pnig = Pentalonia nigronervosa (This study)</p> <p>Rmai = Rhopalosiphum maidis v0.1 (<a href="http://gigadb.org/dataset/100572">http://gigadb.org/dataset/100572</a>)</p> <p>Rpad = Rhopalosiphum padi v1.0 (<a href="https://bipaa.genouest.org/sp/rhopalosiphum_padi/">https://bipaa.genouest.org/sp/rhopalosiphum_padi/</a>)</p> <p>Agly = Aphis glycines biotype 4 v2.1 (<a href="https://zenodo.org/record/3453468#.XnpL5JOgLRY">https://zenodo.org/record/3453468#.XnpL5JOgLRY</a>)</p> <p>BtabMEAM1 = Bemissia tabacci MEAM1 v1.2 (<a href="http://www.whiteflygenomics.org/cgi-bin/bta/index.cgi">http://www.whiteflygenomics.org/cgi-bin/bta/index.cgi</a>)</p> <p>Trub = Triatoma rubrofasciata (This study)</p> <p>Rpro = Rhodnius prolixus (This study)</p> <p>Ofas = Oncopeltus fasciatus OGS v1.0 (<a href="https://i5k.nal.usda.gov/Oncopeltus_fasciatus">https://i5k.nal.usda.gov/Oncopeltus_fasciatus</a>)</p> <p>Sfuc = Sogatella furcifera v1 (<a href="http://dx.doi.org/10.5524/100255">http://dx.doi.org/10.5524/100255</a>)</p> <p>Nlug = Nilaparvata lugens (<a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-014-0521-0#Sec42">https://genomebiology.biomedcentral.com/articles/10.1186/s13059-014-0521-0#Sec42</a>)</p> <p>Files:</p> <p>Proteomes included in the analysis: proteomes.tar.gz</p> <p>Orthogroups: Orthogroups.txt</p> <p>Gene counts per orthogroup, per species: Orthogroups.GeneCount.csv</p> <p>Single copy conserved orthogroups used for species tree: SingleCopyOrthogroups.txt</p> <p>Species tree alignment: SpeciesTreeAlignment.fa</p> <p>r8s configuration file (includes time calibrations and OrthoFinder ML species tree with branch lengths): species_tree_rooted.r8s.nex</p> <p>r8s time calibrated species tree: r8s_tree.nwk</p>
Data from: Integrated SDM database: Enhancing the relevance and utility of species distribution models in conservation management
<p><span>1. Species' ranges are changing at accelerating rates. Species distribution models (SDMs) are powerful tools that help rangers and decision-makers prepare for reintroductions, range shifts, reductions, and/or expansions by predicting habitat suitability across landscapes. Yet, range-expanding or -shifting species in particular face other challenges that traditional SDM procedures cannot quantify, due to large differences between a species' currently-occupied range and potential future range. The realism of SDMs is thus lost and not as useful for conservation management in practice. Here, we address these challenges with an extended assessment of habitat suitability through an <i>integrated SDM database (iSDMdb)</i>.</span></p> <p><span>2. The<i> iSDMdb</i> is a spatial database of predicted sites in a species' prediction range, derived from SDM results, and is a single spatial feature that contains additional, user-friendly data fields that synthesise and summarise SDM predictions and uncertainty, human impacts, restoration features, novel preferences in novel spaces, and management priorities. To illustrate its utility<i>,</i> we used the endangered New Zealand sea lion (<i>Phocarctos hookeri</i>). We consulted with wildlife rangers, decision-makers, and sea lion experts to supplement SDM predictions with additional, more realistic, and applicable information for management. </span></p> <p><span>3. Almost half the data fields included in this database resulted from engaging with these end-users during our study. The SDM found 395 predicted sites. However, the <i>iSDMdb</i>'s additional assessments showed that the actual suitability of most sites (90%) was questionable due to human impacts. >50% of sites contained unnatural barriers (fences, grazing grasslands), and 75% of sites had roads located within the species' range of inland movement. Just 5% of the predicted sites were mostly (>80%) protected.</span></p> <p><span>4. Integrating SDM results with supplemental assessments provides a way to address SDM limitations, especially for range-expanding or -shifting species. SDM products for conservation applications have been critiqued for lacking transparency and interpretation support, and ineffectively communicating uncertainty. The <i>iSDMdb</i> addresses these issues and enhances the practical relevance and utility of SDMs for stakeholders, rangers, and decision-makers. We exemplify how to build an <i>iSDMdb</i> using open-source tools, and how to make diverse, complex assessments more accessible for end-users.</span></p>
Genetic diversity of wild and cultivated Coffea canephora in northeastern DR Congo and the implications for conservation - Additional Data
<p>List of wild and cultivated <em>Coffea canephora </em>accessions from northeastern Democratic Republic of the Congo included in Vanden Abeele et al. 2021 - American Journal of Botany, and the corresponding alleles for each of the 18 microsatellite markers (0 indicates missing alleles).</p>
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.