5bf972a8-c9a3-4721-8089-552dfe3ff124 English ISO/IEC 8859-1 (also known as Latin 1) dataset dataset NERC EDS Environmental Information Data Centre Lancaster Environment Centre, Library Avenue, Bailrigg Lancaster LA1 4AP UK info@eidc.ac.uk https://eidc.ac.uk/ EIDC website The Environmental Information Data Centre (EIDC) is the UK's national data centre for terrestrial and freshwater sciences. information pointOfContact 2025-11-13T16:20:04 UK GEMINI 2.3 WGS 84 / Pseudo-Mercator Projected national-level climate change impacts on terrestrial mammals and birds, and projected global transboundary range shifts by 2070 2021-01-22 publication https://catalogue.ceh.ac.uk/id/5bf972a8-c9a3-4721-8089-552dfe3ff124 10.5285/5bf972a8-c9a3-4721-8089-552dfe3ff124 doi: Titley, M.A., Willis, S.G. (2021). Projected national-level climate change impacts on terrestrial mammals and birds, and projected global transboundary range shifts by 2070. NERC Environmental Information Data Centre 10.5285/5bf972a8-c9a3-4721-8089-552dfe3ff124 This dataset is derived from modelled changes to the distributions of >12,700 terrestrial mammal and bird species under four different climate scenarios, projected to 2070. It contains national-level projections of species richness change under each climate scenario, based on species' modelled climatic niches, as well as projected range shifts in relation to political borders globally. Full details about this dataset can be found at https://doi.org/10.5285/5bf972a8-c9a3-4721-8089-552dfe3ff124 Titley, M.A. Durham University mark.a.titley@durham.ac.uk https://orcid.org/0000-0002-4170-0535 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Willis, S.G. Durham University s.g.willis@durham.ac.uk https://orcid.org/0000-0002-8656-5808 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Titley, M. Durham University mark.a.titley@durham.ac.uk pointOfContact NERC EDS Environmental Information Data Centre info@eidc.ac.uk custodian NERC Environmental Information Data Centre info@eidc.ac.uk publisher Durham University library.resources@durham.ac.uk owner Environmental Monitoring Facilities theme GEMET - INSPIRE themes, version 1.0 2008-06-01 publication biodiversity climate change GEMET - Concepts, version 4.1.3 2019-01-28 creation Biodiversity Climate and climate change species distribution models political borders otherRestrictions no limitations otherRestrictions This resource is available under the terms of the Open Government Licence otherRestrictions If you reuse this data, you should cite: Titley, M.A., Willis, S.G. (2021). Projected national-level climate change impacts on terrestrial mammals and birds, and projected global transboundary range shifts by 2070. NERC Environmental Information Data Centre https://doi.org/10.5285/5bf972a8-c9a3-4721-8089-552dfe3ff124 textTable 1 English utf8 biota 2018-01-01 2070-12-31 -180 180 -90 90 Comma-separated values (CSV) NERC EDS Environmental Information Data Centre info@eidc.ac.uk distributor https://data-package.ceh.ac.uk/data/5bf972a8-c9a3-4721-8089-552dfe3ff124 Download the data Download a copy of this data download https://data-package.ceh.ac.uk/sd/5bf972a8-c9a3-4721-8089-552dfe3ff124.zip Supporting information Supporting information available to assist in re-use of this dataset information dataset dataset Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 Data were generated using ensemble Species Distribution Models, trained on five climatic predictor variables and projected using future climate data from three general circulation models. Species distributions were modelled at a half-degree resolution. We followed best-practice guidelines for creating the models, and validated the projections using ten-fold cross validation with present climate data. These methods have been peer-reviewed and are widely used. Data were checked for errors before publication. See supporting documentation for more information.