| 1. |
- Hudson, Lawrence N, et al.
(author)
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The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project
- 2017
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In: Ecology and Evolution. - : John Wiley & Sons. - 2045-7758. ; 7:1, s. 145-188
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Journal article (peer-reviewed)abstract
- The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.
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| 2. |
- Hudson, Lawrence N., et al.
(author)
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The PREDICTS database : a global database of how local terrestrial biodiversity responds to human impacts
- 2014
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In: Ecology and Evolution. - : Wiley. - 2045-7758. ; 4:24, s. 4701-4735
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Journal article (peer-reviewed)abstract
- Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - ). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
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| 3. |
- Kehoe, Laura, et al.
(author)
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Make EU trade with Brazil sustainable
- 2019
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In: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 364:6438, s. 341-
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Journal article (other academic/artistic)
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| 4. |
- Maes, Dirk, et al.
(author)
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Integrating national Red Lists for prioritising conservation actions for European butterflies
- 2019
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In: Journal of Insect Conservation. - : Springer Science and Business Media LLC. - 1366-638X .- 1572-9753. ; 23:2, s. 301-330
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Journal article (peer-reviewed)abstract
- Red Lists are very valuable tools in nature conservation at global, continental and (sub-) national scales. In an attempt to prioritise conservation actions for European butterflies, we compiled a database with species lists and Red Lists of all European countries, including the Macaronesian archipelagos (Azores, Madeira and Canary Islands). In total, we compiled national species lists for 42 countries and national Red Lists for 34 of these. The most species-rich countries in Europe are Italy, Russia and France with more than 250 species each. Endemic species are mainly found on the Macaronesian archipelagos and on the Mediterranean islands. By attributing numerical values proportionate to the threat statuses in the different national Red List categories, we calculated a mean Red List value for every country (cRLV) and a weighted Red List value for every species (wsRLV) using the square root of the country’s area as a weighting factor. Countries with the highest cRLV were industrialised (NW) European countries such as the Netherlands, Belgium, the Czech Republic and Denmark, whereas large Mediterranean countries such as Spain and Italy had the lowest cRLV. Species for which a Red List assessment was available in at least two European countries and with a relatively high wsRLV (≥ 50) are Colias myrmidone, Pseudochazara orestes, Tomares nogelii, Colias chrysotheme and Coenonympha oedippus. We compared these wsRLVs with the species statuses on the European Red List to identify possible mismatches. We discuss how this complementary method can help to prioritise butterfly conservation on the continental and/or the (sub-)national scale.
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| 5. |
- Selva, Nuria, et al.
(author)
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Roadless and Low-Traffic Areas as Conservation Targets in Europe
- 2011
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In: Environmental Management. - : Springer Science and Business Media LLC. - 0364-152X .- 1432-1009. ; 48:5, s. 865-877
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Journal article (peer-reviewed)abstract
- This paper is part of an initiative launched by the Policy Committee of the Society for Conservation Biology-Europe Section. We are indebted to our colleagues from SCB, especially P. Chylarecki, M. Dieterich, B. Livoreil, O. Nevin and A. Pullin, as well as W. Barthlott and N. Fernandez for support and insightful comments to the manuscript. O. Nevin kindly checked the English. We thank the German Federal Agency for Nature Conservation (BfN) for data facilitation. We also acknowledge funding for Eberswalde University for Sustainable Development provided by the BfN under the research project "Protected areas under climate change" (FKZ 80682270K) and by the German Federal Ministry of Education and Research under the project "Innovation Network Climate Change Adaptation Brandenburg Berlin-INKA BB". We very much appreciated the critical and constructive support provided by four anonymous reviewers.
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