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.

Habitat loss and degradation, driven largely by agricultural expansion and intensification, present the greatest immediate threat to biodiversity. Tropical forests harbour among the highest levels of terrestrial species diversity and are likely to experience rapid land-use change in the coming decades. Synthetic analyses of observed responses of species are useful for quantifying how land use affects biodiversity and for predicting outcomes under land-use scenarios. Previous applications of this approach have typically focused on individual taxonomic groups, analysing the average response of the whole community to changes in land use. Here, we incorporate quantitative remotely sensed data about habitats in, to our knowledge, the first worldwide synthetic analysis of how individual species in four major taxonomic groups—invertebrates, ‘herptiles’ (reptiles and amphibians), mammals and birds—respond to multiple human pressures in tropical and sub-tropical forests. We show significant independent impacts of land use, human vegetation offtake, forest cover and human population density on both occurrence and abundance of species, highlighting the value of analysing multiple explanatory variables simultaneously. Responses differ among the four groups considered, and—within birds and mammals—between habitat specialists and habitat generalists and between narrow-ranged and wide-ranged species.

BackgroundRandomised Control Trials (RCTs) are used in impact evaluation in a range of fields. However, despite calls for their greater use in environmental management, their use to evaluate landscape scale interventions remains rare. Payments for Ecosystem Services (PES) incentivise land users to manage land to provide environmental benefits. We present the first RCT evaluation of a PES program aiming to improve water quality. Watershared is a program which incentivises landowners to avoid deforestation and exclude cattle from riparian forests. Using this unusual landscape-scale experiment we explore the efficacy of Watershared at improving water quality, and draw lessons for future RCT evaluations of landscape-scale environmental management interventions.MethodsOne hundred and twenty-nine communities in the Bolivian Andes were randomly allocated to treatment (offered Watershared agreements) or control (not offered agreements) following baseline data collection (including Escherichia coli contamination in most communities) in 2010. We collected end-line data in 2015. Using our end-line data, we explored the extent to which variables associated with the intervention (e.g. cattle exclusion, absence of faeces) predict water quality locally. We then investigated the efficacy of the intervention at improving water quality at the landscape scale using the RCT. This analysis was done in two ways; for the subset of communities for which we have both baseline and end-line data from identical locations we used difference-in-differences (matching on baseline water quality), for all sites we compared control and treatment at end-line controlling for selected predictors of water quality.ResultsThe presence of cattle faeces in water adversely affected water quality suggesting excluding cattle has a positive impact on water quality locally. However, both the matched difference-in-differences analysis and the comparison between treatment and control communities at end-line suggested Watershared was not effective at reducing E. coli contamination at the landscape scale. Uptake of Watershared agreements was very low and the most important land from a water quality perspective (land around water intakes) was seldom enrolled.DiscussionAlthough excluding cattle may have a positive local impact on water quality, higher uptake and better targeting would be required to achieve a significant impact on the quality of water consumed in the communities. Although RCTs potentially have an important role to play in building the evidence base for approaches such as PES, they are far from straightforward to implement. In this case, the randomised trial was not central to concluding that Watershared had not produced a landscape scale impact. We suggest that this RCT provides valuable lessons for future use of randomised experiments to evaluate landscape-scale environmental management interventions.

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