Forest edges influence more than half of the world’s forests and contribute to worldwide declines in biodiversity and ecosystem functions. However, predicting these declines is challenging in heterogeneous fragmented landscapes. Here we assembled a global dataset on species responses to fragmentation and developed a statistical approach for quantifying edge impacts in heterogeneous landscapes to quantify edge-determined changes in abundance of 1,673 vertebrate species. We show that the abundances of 85% of species are affected, either positively or negatively, by forest edges. Species that live in the centre of the forest (forest core), that were more likely to be listed as threatened by the International Union for Conservation of Nature (IUCN), reached peak abundances only 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.

Abstract:  The growing demand for biofuels is promoting the expansion of a number of agricultural commodities, including oil palm (Elaeis guineensis). Oil‐palm plantations cover over 13 million ha, primarily in Southeast Asia, where they have directly or indirectly replaced tropical rainforest. We explored the impact of the spread of oil‐palm plantations on greenhouse gas emission and biodiversity. We assessed changes in carbon stocks with changing land use and compared this with the amount of fossil‐fuel carbon emission avoided through its replacement by biofuel carbon. We estimated it would take between 75 and 93 years for the carbon emissions saved through use of biofuel to compensate for the carbon lost through forest conversion, depending on how the forest was cleared. If the original habitat was peatland, carbon balance would take more than 600 years. Conversely, planting oil palms on degraded grassland would lead to a net removal of carbon within 10 years. These estimates have associated uncertainty, but their magnitude and relative proportions seem credible. We carried out a meta‐analysis of published faunal studies that compared forest with oil palm. We found that plantations supported species‐poor communities containing few forest species. Because no published data on flora were available, we present results from our sampling of plants in oil palm and forest plots in Indonesia. Although the species richness of pteridophytes was higher in plantations, they held few forest species. Trees, lianas, epiphytic orchids, and indigenous palms were wholly absent from oil‐palm plantations. The majority of individual plants and animals in oil‐palm plantations belonged to a small number of generalist species of low conservation concern. As countries strive to meet obligations to reduce carbon emissions under one international agreement (Kyoto Protocol), they may not only fail to meet their obligations under another (Convention on Biological Diversity) but may actually hasten global climate change. Reducing deforestation is likely to represent a more effective climate‐change mitigation strategy than converting forest for biofuel production, and it may help nations meet their international commitments to reduce biodiversity loss.

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.