The PREDICTS database: A global database of how local terrestrial biodiversity responds to human impacts

© 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. 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 - www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015. The collation of biodiversity datasets with broad taxonomic and biogeographic extents is necessary to understand historical declines and to project - and hopefully avert - future declines. We describe a newly collated database of more than 1.6 million biodiversity measurements 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 of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

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

Response to: 'To DAPSA or not to DAPSA? That is not the question' by Schoels et al.

We thank the authors for the interest in our paper and are grateful for the opportunity to respond to the points raised1. We agree that there is a clear distinction between composite measures of psoriatic arthritis such as DAPSA and composite measures of psoriatic disease such as MDA/VLDA and PASDAS. As the Vienna group rightly point out, these measures differ in terms of the components included, but not due to disagreement within the outcome measure community as suggested in the letter. The choice of components for each composite measure was decided using different methodology in the development of each one, thus resulting in different measures. We believe that this variation in scores is one reason for the need to compare such scores in different populations to establish the optimal measure or measures for PsA. Indeed when the DAPSA was originally suggested, it was because the same components used in the DAREA were identified in a principal component analysis (PCA) in PsA. Interestingly in this analysis, the variables tested were taken from the OMERACT PsA domains and therefore DAPSA was not, a priori, designed specifically to be a unidimensional composite measure. The fourth component identified in the PCA was the PASI highlighting the importance of skin in PsA despite the fact that patients had a low baseline mean PASI of only 3.3. Whilst PASI was not included in the DAPSA as the eigenvalue was 0.949 and therefore just under the threshold of 12, it is interesting to imagine how the results may have differed if it were developed in a group with slightly more active skin disease