The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (https://www.nhm.ac.uk/our-science/our-work/biodiversity/predicts.html)—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.

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 thePREDICTSproject (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems –https://www.nhm.ac.uk/our-science/our-work/biodiversity/predicts.html). We make site‐level summary data available alongside this article. The full database will be publicly available in 2015.

Estimating population densities of small mammals (< 100g) has typically been carried out by intensive livetrapping, but this technique may be stressful to animals and the effort required is considerable. Here, we used camera traps to detect small mammal presence and assessed if this provided a feasible alternative to livetrapping for density estimation. During 2010–2012, we used camera trapping in conjunction with mark–recapture livetrapping to estimate the density of northern red-backed voles (Myodes rutilus) and deer mice (Peromyscus maniculatus) in the boreal forest of Yukon, Canada. Densities for these 2 species ranged from 0.29 to 9.21 animals/ha and 0 to 5.90 animals/ha, respectively, over the course of this investigation. We determined if hit window—the length of time used to group consecutive videos together as single detections or “hits”—has an effect on the correlation between hit rate and population density. The relationship between hit rate and density was sensitive to hit window duration for Myodes with R ² values ranging from 0.45 to 0.59, with a 90-min hit window generating the highest value. This relationship was not sensitive to hit window duration for Peromyscus, with R ² values for the tested hit windows ranging from 0.81 to 0.84. Our results indicate that camera trapping may be a robust method for estimating density of small rodents in the boreal forest when the appropriate hit window duration is selected and that camera traps may be a useful tool for the study of small mammals in boreal forest habitat.

Understanding parasite diversity and distribution is essential in managing the potential impact of parasitic diseases in animals and people. Imperfect diagnostic methods, however, may conceal cryptic species. Here, we report the discovery and phylogeography of a previously unrecognized species of Trichinella in wolverine (Gulo gulo) from northwestern Canada that was indistinguishable from T. nativa using the standard multiplex PCR assay based on the expansion segment 5 (ESV) of ribosomal DNA. The novel genotype, designated as T13, was discovered when sequencing the mitochondrial genome. Phylogenetic analyses of the mitochondrial genome and of 15 concatenated single copy orthologs of nuclear DNA indicated a common ancestor for the encapsulated clade is shared by a subclade containing Trichinella spiralis and Trichinella nelsoni, and a subclade containing T13 and remaining taxa: T12 + (T2 + T6) + [(T5 + T9) + (T3 + T8)]. Of 95 individual hosts from 12 species of mammalian carnivores from northwestern Canada from which larvae were identified as T. nativa on multiplex PCR, only wolverines were infected with T13 (14 of 42 individuals). These infections were single or mixed with T. nativa and/or T6. Visual examination and motility testing confirmed that T13 is encapsulated and likely freeze-tolerant. We developed a new Polymerase Chain Reaction-Restriction Fragment Length Polymorphism which unequivocally distinguishes between T13 and T. nativa. We propose Trichinella chanchalensis n. sp. for T13, based on significant genetic divergence from other species of Trichinella and broad-based sampling of the Trichinella genome. Exploration of Alaskan and Siberian isolates may contribute to further resolution of a phylogeographically complex history for species of Trichinella across Beringia, including Trichinella chanchalensis n. sp. (T13).