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

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

Using multiple survey methods to detect terrestrial reptiles and mammals: What are the most successful and cost-efficient combinations?

The selection of methods for wildlife surveys is a decision that will influence the accuracy and comprehensiveness of survey outcomes. The choice of methods is commonly based on the species of interest, yet is often limited by the project budget. Although several studies have investigated the effectiveness of various survey techniques for detecting terrestrial mammal and reptile species, none have provided a quantitative analysis of the costs associated with different methods. We compare the detection success and cost efficiency of cage traps, Elliott traps, pit- fall traps, hair funnels, direct observation, and scat detection/ analysis for detecting the occurrence of terrestrial reptile and small mammal species in urban bushland remnants of Brisbane City, Queensland, Australia. Cage traps and Elliott traps coupled with hair funnels were the most cost-effective methods for detecting the highest number of ground-dwelling mammal species. Pit-fall traps and direct observations were the most cost- effective methods for maximising the number of reptile species identified. All methods made a contribution to overall detection success by detecting at least one species not detected by any other method. This suggests that a combination of at least two complementary methods will provide the most successful and cost- efficient detection of reptile and mammal species in urban forest remnants. Future studies should explicitly test these findings and examine efficient trapping combinations across different habitat types and for other fauna groups

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