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Land-use and climate change are among the greatest threats facing biodiversity, but understanding their combined effects has been hampered by modelling and data limitations, resulting in part from the very different scales at which land-use and climate processes operate. I combine two different modelling paradigms to predict the separate and combined (additive) effects of climate and land-use change on terrestrial vertebrate communities under four different scenarios. I predict that climate-change effects are likely to become a major pressure on biodiversity in the coming decades, probably matching or exceeding the effects of land-use change by 2070. The combined effects of both pressures are predicted to lead to an average cumulative loss of 37.9% of species from vertebrate communities under ‘business as usual’ (uncertainty ranging from 15.7% to 54.2%). Areas that are predicted to experience the effects of both pressures are concentrated in tropical grasslands and savannahs. The results have important implications for the conservation of biodiversity in future, and for the ability of biodiversity to support important ecosystem functions, upon which humans rely.

Climate change could increase species’ extinction risk as temperatures and precipitation begin to exceed species’ historically observed tolerances. Using long-term data for 66 bumble bee species across North America and Europe, we tested whether this mechanism altered likelihoods of bumble bee species’ extinction or colonization. Increasing frequency of hotter temperatures predicts species’ local extinction risk, chances of colonizing a new area, and changing species richness. Effects are independent of changing land uses. The method developed in this study permits spatially explicit predictions of climate change–related population extinction-colonization dynamics within species that explains observed patterns of geographical range loss and expansion across continents. Increasing frequencies of temperatures that exceed historically observed tolerances help explain widespread bumble bee species decline. This mechanism may also contribute to biodiversity loss more generally.

Several previous studies have investigated changes in insect biodiversity, with some highlighting declines and others showing turnover in species composition without net declines 1 – 5 . Although research has shown that biodiversity changes are driven primarily by land-use change and increasingly by climate change 6 , 7 , the potential for interaction between these drivers and insect biodiversity on the global scale remains unclear. Here we show that the interaction between indices of historical climate warming and intensive agricultural land use is associated with reductions of almost 50% in the abundance and 27% in the number of species within insect assemblages relative to those in less-disturbed habitats with lower rates of historical climate warming. These patterns are particularly evident in the tropical realm, whereas some positive responses of biodiversity to climate change occur in non-tropical regions in natural habitats. A high availability of nearby natural habitat often mitigates reductions in insect abundance and richness associated with agricultural land use and substantial climate warming but only in low-intensity agricultural systems. In such systems, in which high levels (75% cover) of natural habitat are available, abundance and richness were reduced by 7% and 5%, respectively, compared with reductions of 63% and 61% in places where less natural habitat is present (25% cover). Our results show that insect biodiversity will probably benefit from mitigating climate change, preserving natural habitat within landscapes and reducing the intensity of agriculture. Interaction between climate warming and intensive agricultural land use is associated with reductions in insect abundance and species richness, which can be mitigated by nearby natural habitats in low-intensity agricultural settings.

Land use change—for example, the conversion of natural habitats to agricultural or urban ecosystems—is widely recognized to influence the risk and emergence of zoonotic disease in humans 1 , 2 . However, whether such changes in risk are underpinned by predictable ecological changes remains unclear. It has been suggested that habitat disturbance might cause predictable changes in the local diversity and taxonomic composition of potential reservoir hosts, owing to systematic, trait-mediated differences in species resilience to human pressures 3 , 4 . Here we analyse 6,801 ecological assemblages and 376 host species worldwide, controlling for research effort, and show that land use has global and systematic effects on local zoonotic host communities. Known wildlife hosts of human-shared pathogens and parasites overall comprise a greater proportion of local species richness (18–72% higher) and total abundance (21–144% higher) in sites under substantial human use (secondary, agricultural and urban ecosystems) compared with nearby undisturbed habitats. The magnitude of this effect varies taxonomically and is strongest for rodent, bat and passerine bird zoonotic host species, which may be one factor that underpins the global importance of these taxa as zoonotic reservoirs. We further show that mammal species that harbour more pathogens overall (either human-shared or non-human-shared) are more likely to occur in human-managed ecosystems, suggesting that these trends may be mediated by ecological or life-history traits that influence both host status and tolerance to human disturbance 5 , 6 . Our results suggest that global changes in the mode and the intensity of land use are creating expanding hazardous interfaces between people, livestock and wildlife reservoirs of zoonotic disease. Wildlife communities in human-managed ecosystems contain proportionally more species that share human pathogens, and at a higher abundance, than undisturbed habitats, suggesting that landscape transformation creates increasing opportunities for contact between humans and potential hosts of human disease.

The global food system is a key driver of land-use and climate change which in turn drive biodiversity change. Developing sustainable food systems is therefore critical to reversing biodiversity loss. We use the multi-regional input-output model EXIOBASE to estimate the biodiversity impacts embedded within the global food system in 2011. Using models that capture regional variation in the sensitivity of biodiversity both to land use and climate change, we calculate the land-driven and greenhouse gas-driven footprints of food using two metrics of biodiversity: local species richness and rarity-weighted species richness. We show that the footprint of land area underestimates biodiversity impact in more species-rich regions and that our metric of rarity-weighted richness places a greater emphasis on biodiversity costs in Central and South America. We find that methane emissions are responsible for 70% of the overall greenhouse gas-driven biodiversity footprint and that, in several regions, emissions from a single year’s food production are associated with global biodiversity loss equivalent to 2% or more of that region’s total land-driven biodiversity loss. The measures we present are relatively simple to calculate and could be incorporated into decision-making and environmental impact assessments by governments and businesses. In this study, the biodiversity impacts of the global food system from land use and climate change are estimated using the EXIOBASE model. The findings show that emissions from a single year’s food production are associated with global biodiversity loss equivalent to 2% or more of a region’s total land-driven biodiversity loss.

Pollinating species are in decline globally, with land use an important driver. However, most of the evidence on which these claims are made is patchy, based on studies with low taxonomic and geographic representativeness. Here, we model the effect of land-use type and intensity on global pollinator biodiversity, using a local-scale database covering 303 studies, 12,170 sites, and 4502 pollinating species. Relative to a primary vegetation baseline, we show that low levels of intensity can have beneficial effects on pollinator biodiversity. Within most anthropogenic land-use types however, increasing intensity is associated with significant reductions, particularly in urban (43% richness and 62% abundance reduction compared to the least intensive urban sites), and pasture (75% abundance reduction) areas. We further show that on cropland, the strongly negative response to intensity is restricted to tropical areas, and that the direction and magnitude of response differs among taxonomic groups. Our findings confirm widespread effects of land-use intensity on pollinators, most significantly in the tropics, where land use is predicted to change rapidly. Anthropogenic losses of animal pollinators threaten ecosystem functioning. Here the authors report a global analysis showing geographically varied yet widespread declines of pollinator diversity and abundance with land use intensification, particularly in tropical biomes.

Global biodiversity is undergoing rapid declines, driven in large part by changes to land use and climate. Global models help us to understand the consequences of environmental changes for biodiversity, but tend to neglect important geographical variation in the sensitivity of biodiversity to these changes. Here we test whether biodiversity responses to climate change and land-use change differ among biomes (geographical units that have marked differences in environment and species composition). We find the strongest negative responses to both pressures in tropical biomes and in the Mediterranean. A further analysis points towards similar underlying drivers for the sensitivity to each pressure: we find both greater reductions in species richness in the types of land use most disturbed by humans and more negative predicted responses to climate change in areas of lower climatic seasonality, and in areas where a greater proportion of species are near their upper temperature limit. Within the land most modified by humans, reductions in biodiversity were particularly large in regions where humans have come to dominate the land more recently. Our results will help to improve predictions of how biodiversity is likely to change with ongoing climatic and land-use changes, pointing toward particularly large declines in the tropics where much future agricultural expansion is expected to occur. This finding could help to inform the development of the post-2020 biodiversity framework, by highlighting the under-studied regions where biodiversity losses are likely to be greatest. Analysing responses of biodiversity to changes in land use and climate across global ecoregions, the authors identify strong negative responses in both tropical and Mediterranean biomes, driven primarily by low climatic seasonality and the history of human disturbance.

The body of ecological literature, which informs much of our knowledge of the global loss of biodiversity, has been experiencing rapid growth in recent decades. The increasing difficulty of synthesising this literature manually has simultaneously resulted in a growing demand for automated text mining methods. Within the domain of deep learning, large language models (LLMs) have been the subject of considerable attention in recent years due to great leaps in progress and a wide range of potential applications; however, quantitative investigation into their potential in ecology has so far been lacking. In this work, we analyse the ability of GPT‐4 to extract information about invertebrate pests and pest controllers from s of articles on biological pest control, using a bespoke, zero‐shot prompt. Our results show that the performance of GPT‐4 is highly competitive with other state‐of‐the‐art tools used for taxonomic named entity recognition and geographic location extraction tasks. On a held‐out test set, we show that species and geographic locations are extracted with F1‐scores of 99.8% and 95.3%, respectively, and highlight that the model can effectively distinguish between ecological roles of interest such as predators, parasitoids and pests. Moreover, we demonstrate the model's ability to effectively extract and predict taxonomic information across various taxonomic ranks. However, we do report a small number of cases of fabricated information (confabulations). Due to a lack of specialised, pre‐trained ecological language models, general‐purpose LLMs may provide a promising way forward in ecology. Combined with tailored prompt engineering, such models can be employed for a wide range of text mining tasks in ecology, with the potential to greatly reduce time spent on manual screening and labelling of the literature.

Protected areas are widely considered essential for biodiversity conservation. However, few global studies have demonstrated that protection benefits a broad range of species. Here, using a new global biodiversity database with unprecedented geographic and taxonomic coverage, we compare four biodiversity measures at sites sampled in multiple land uses inside and outside protected areas. Globally, species richness is 10.6% higher and abundance 14.5% higher in samples taken inside protected areas compared with samples taken outside, but neither rarefaction-based richness nor endemicity differ significantly. Importantly, we show that the positive effects of protection are mostly attributable to differences in land use between protected and unprotected sites. Nonetheless, even within some human-dominated land uses, species richness and abundance are higher in protected sites. Our results reinforce the global importance of protected areas but suggest that protection does not consistently benefit species with small ranges or increase the variety of ecological niches. Protected areas are thought essential for biodiversity conservation, but few studies confirm that protection benefits species. Here, Gray and Hill et al . analyse a global, taxonomically broad database to show that local species richness and abundance are higher inside protected areas than outside.

Human use of the land (for agriculture and settlements) has a substantial negative effect on biodiversity globally. However, not all species are adversely affected by land use, and indeed, some benefit from the creation of novel habitat. Geographically rare species may be more negatively affected by land use than widespread species, but data limitations have so far prevented global multi-clade assessments of land-use effects on narrow-ranged and widespread species. We analyse a large, global database to show consistent differences in assemblage composition. Compared with natural habitat, assemblages in disturbed habitats have more widespread species on average, especially in urban areas and the tropics. All else being equal, this result means that human land use is homogenizing assemblage composition across space. Disturbed habitats show both reduced abundances of narrow-ranged species and increased abundances of widespread species. Our results are very important for biodiversity conservation because narrow-ranged species are typically at higher risk of extinction than widespread species. Furthermore, the shift to more widespread species may also affect ecosystem functioning by reducing both the contribution of rare species and the diversity of species' responses to environmental changes among local assemblages.