The observation that species may be positively or negatively associated with each other is at least as old as the debate surrounding the nature of community structure which began in the early 1900's with Gleason and Clements. Since then investigating species co-occurrence patterns has taken a central role in understanding the causes and consequences of evolution, history, coexistence mechanisms, competition, and environment for community structure and assembly. This is because co-occurrence among species is a measurable metric in community datasets that, in the context of phylogeny, geography, traits, and environment, can sometimes indicate the degree of competition, displacement, and phylogenetic repulsion as weighed against biotic and environmental effects promoting correlated species distributions. Historically, a multitude of different co-occurrence metrics have been developed and most have depended on data randomization procedures to produce null distributions for significance testing. Here we improve upon and present an R implementation of a recently published model that is metric-free, distribution-free, and randomization-free. The R package, cooccur, is highly accessible, easily integrates into common analyses, and handles large datasets with high performance. In the article we develop the package's functionality and demonstrate aspects of co-occurrence analysis using three sample datasets.

SummaryForest edges influence more than half the world’s forests and contribute to worldwide declines in biodiversity and ecosystem functions. However, predicting these declines is challenging in heterogeneous fragmented landscapes. We assembled an unmatched global dataset on species responses to fragmentation and developed a new statistical approach for quantifying edge impacts in heterogeneous landscapes to quantify edge-determined changes in abundance of 1673 vertebrate species. We show that 85% of species’ abundances are affected, either positively or negatively, by forest edges. Forest core species, which were more likely to be listed as threatened by the IUCN, only reached peak abundances at sites farther than 200-400 m from sharp high-contrast forest edges. Smaller-bodied amphibians, larger reptiles and medium-sized non-volant mammals experienced a larger reduction in suitable habitat than other forest core species. Our results highlight the pervasive ability of forest edges to restructure ecological communities on a global scale.

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.

Grassland ecosystems cover vast areas of the Earth's surface and provide many ecosystem services including carbon (C) storage, biodiversity preservation and the production of livestock forage. Predicting the future delivery of these services is difficult, because widespread changes in atmospheric CO 2 concentration, climate and nitrogen (N) inputs are expected. We compiled published data from global change driver manipulation experiments and combined these with climate data to assess grassland biomass responses to CO 2 and N enrichment across a range of climates. CO 2 and N enrichment generally increased aboveground biomass (AGB) but effects of CO 2 enrichment were weaker than those of N. The response to N was also dependent on the amount of N added and rainfall, with a greater response in high precipitation regions. No relationship between response to CO 2 and climate was detected within our dataset, thus suggesting that other site characteristics, e.g. soils and plant community composition, are more important regulators of grassland responses to CO 2 . A statistical model of AGB response to N was used in conjunction with projected N deposition data to estimate changes to future biomass stocks. This highlighted several potential hotspots (e.g. in some regions of China and India) of grassland AGB gain. Possible benefits for C sequestration and forage production in these regions may be offset by declines in plant biodiversity caused by these biomass gains, thus necessitating careful management if ecosystem service delivery is to be maximized. An approach such as ours, in which meta-analysis is combined with global scale model outputs to make large-scale predictions, may complement the results of dynamic global vegetation models, thus allowing us to form better predictions of biosphere responses to environmental change.

The accurate sampling of communities is vital to any investigation of ecological processes and biodiversity. Dung beetles have emerged as a widely used focal taxon in environmental studies and can be sampled quickly and inexpensively using baited pitfalls. Although there is now a wealth of available data on dung beetle communities from around the world, there is a lack of standardisation between sampling protocols for accurately sampling dung beetle communities. In particular, bait choice is often led by the idiosyncrasies of the researcher, logistic problems and the dung sources available, which leads to difficulties for inter-study comparisons. In general, human dung is the preferred choice, however, it is often in short supply, which can severely limit sampling effort. By contrast, pigs may produce up to 20 times the volume. We tested the ability of human and pig dung to attract a primary forest dung beetle assemblage, as well as three mixes of the two baits in different proportions. Analyses focussed on the comparability of sampling with pig or human-pig dung mixes with studies that have sampled using human dung. There were no significant differences between richness and abundance sampled by each bait. The assemblages sampled were remarkably consistent across baits, and ordination analyses showed that the assemblages sampled by mixed dung baits were not significantly different from that captured by pure human dung, with the assemblages sampled by 10% and 90% pig mixes structurally most similar to assemblages sampled by human dung. We suggest that a 10:90 human:pig ratio, or similar, is an ideal compromise between sampling efficiency, inter-study comparability and the availability of large quantities of bait for sampling Amazonian dung beetles. Assessing the comparability of assemblage samples collected using different baits represents an important step to facilitating large-scale meta-analyses of dung beetle assemblages collected using non-standard methodology.