Data for: Developing a Global Indicator for Aichi Target 1 by Merging Online Data Sources to Measure Biodiversity Awareness and Engagement
Contributors: Matthew Cooper, Siyu Qin, Anna Hausmann, Enrico Di Minin, Ricardo Correia, Aaron Schwartz
... This is the data used to calculate an indicator for Aichi Biodiversity Target 1
Data for: Habitat selection in a dynamic seasonal environment: vegetation composition drives the choice of the breeding habitat for the community of passerines in floodplain grasslands
Contributors: Yoan Fourcade, Aurélien G. Besnard, Jean Secondi, Guillaume Berdin, Stéphanie Hennique, Édouard Beslot, Gilles Mourgaud
... All data used in the manuscript in 3 sheets: - Sites - Vegetation structure and composition - BIrds sampling
Contributors: Stuart Butchart, Hannah Wheatley, Stephen Lowe, James Westrip, Andy Symes, Rob Martin
... Estimates of the probability of extinction for bird taxa, based on quantitative estimates of the timing and reliability of records, the timing and adequacy of surveys, and the timing, intensity and extent of threats.
Top results from Data Repository sources. Show only results like these.
Contributors: Yik Hei Sung, Jonathan Fong
Contributors: Olivia Rhoades, Steve Lonhart, John Stachowicz
Contributors: Julia Put, Lenore Fahrig, Greg Mitchell
... Abstract Studies that have compared biodiversity at organic and conventional farms have generally found that there are more species in greater abundances at organic farms. One widespread problem with previous studies is that most do not control for differences in field structure and landscape composition at organic and conventional farms. Thus, the effects observed may be due to factors other than organic farming practices. We solved this problem by selecting matched organic-conventional pairs of soybean fields such that in each pair the soybean fields were similar in size, hedgerow length, and surrounding landscape composition within 1 km, 2 km and 3 km of the fields. At each of our 16 field pairs (32 sites), we measured relative difference in bat species richness and abundance using acoustic bat recorders, and bat prey availability using black-light traps. We predicted that organic soybean fields would have greater bat species richness, bat abundance and bat prey abundance than conventional soybean fields due to the prohibition of synthetic pesticides and longer more diverse crop rotations in organic fields, both of which should benefit bat insect prey. We found that organic soybean fields had higher bat species richness, bat abundance and bat prey abundance than conventional fields, after controlling for the effect of differences in soybean height between conventional and organic fields. Our results suggest that the management practices used at organic farms benefit bats at least in part through their greater bat prey availability.
Contributors: Kerry Griffis-Kyle, Krista Mougey, Joseph Drake, Sharmistha Swain, Matthew VanLandeghem
... Qualitative vulnerability calculations for 25 desert amphibian and reptile species using NatureServe's Climate Change Vulnerability Index version 3.0. Analyses are done across 4 spatial scales and three climate scenarios. We used four types of spatial data, including point data, minimum convex polygons based on the point data, range data clipped to the desert region, and range data clipped to the contiguous United States. We used climate data from the Coupled Model Intercomparison Project (CMIP) 5 for Representative Concentration Pathways (RCP) 2.6, 6.0, and 8.5. Each file is a species x spatial data x climate data model.
Data for: Population declines, genetic bottlenecks and potential hybridization in sea snakes on Australia’s Timor Sea reefs.
Contributors: Vimoksalehi Lukoschek
Data for: Species richness, geographic distribution, pressures, and threats to bats in the Caatinga drylands of Brazil
Contributors: Enrico Bernard, Mariana Delgado-Jaramillo, Ulremberg Silva
... APPENDIX A1 – Spatial distribution of 8,849 records used for modelling bat species distribution in Brazil. See Methodology for the description of data sources and treatments. APPENDIX A2 – Bioclimatic variables used to generate bat species distribution models in Brazil´s Caatinga. Variables available at the WorldClim database (http://www.worldclim.org). APPENDIX A3 – Number of localities for which there were records of bat species in Brazil´s Caatinga and the respective number of environmental variables and replicates used to run the species distribution models in MaxEnt. APPENDIX A4 – Human Footprint Index for the Caatinga region, in northeastern Brazil. See WCS & SCIESIN (2005) for details on how the index is calculated. Full protected areas (FPA) are in black. APPENDIX A5 – List of bat species recorded in Brazil´s Caatinga. APPENDIX A6 – Distribution modelling of threatened bat species in Brazil´s Caatinga. Seven bat species are officially threatened in Brazil (ICMBio, 2014) and four of them have known records in the Caatinga: Furipterus horrens, Lonchorhina aurita, Natalus macrourus, and Xeronycteris vieirai. Two others (Glyphonycteris behnii and Lonchophylla dekeyseri) are expected to occur based on environmental suitability models, but with no records so far. Full protected areas (FPA) are in black.
Contributors: Thomas Couvreur, Lauren M. Gardiner, Ariane Cosiaux, Steven Bachman, Fred W. Stauffer, Bonaventure Sonké, William Baker
... The dataset includes a total of 4 238 georeferenced occurrence records: 4 096 of which were extracted from RAINBIO (Dauby et al., 2016) and the others from literature, field work observations and the database of Malagasy palms (Mijoro Rakotoarinivo pers. comm.). The dates of these occurrences records range from the years 1837 to 2016.