Terrestrial mammals are experiencing a massive collapse in their population sizes and geographical ranges around the world, but many of the drivers, patterns and consequences of this decline remain poorly understood. Here we provide an analysis showing that bushmeat hunting for mostly food and medicinal products is driving a global crisis whereby 301 terrestrial mammal species are threatened with extinction. Nearly all of these threatened species occur in developing countries where major coexisting threats include deforestation, agricultural expansion, human encroachment and competition with livestock. The unrelenting decline of mammals suggests many vital ecological and socio-economic services that these species provide will be lost, potentially changing ecosystems irrevocably. We discuss options and current obstacles to achieving effective conservation, alongside consequences of failure to stem such anthropogenic mammalian extirpation. We propose a multi-pronged conservation strategy to help save threatened mammals from immediate extinction and avoid a collapse of food security for hundreds of millions of people.

Wild large herbivores are declining worldwide. Despite extensive use of exclosure experiments to investigate herbivore impacts, there is little consensus on the effects of wild large herbivores on ecosystem function. Of the ecosystem functions likely impacted, we reviewed the five most‐studied in exclosure experiments: ecosystem resilience/resistance to disturbance, nutrient cycling, carbon cycling, plant regeneration, and primary productivity. Experimental data on large wild herbivores' effects on ecosystem functions were predominately derived from temperate grasslands (50% grasslands, 75% temperate zones). Additionally, data were from experiments that may not be of adequate size (median size 400 m²despite excluding all experiments below 25 m²) or duration (median duration 6 years) to capture ecosystem‐scale responses to these low‐density and wide‐ranging taxa. Wild herbivore removal frequently impacted ecosystem functions; for example, net carbon uptake increased by three times in some instances. However, the magnitude and direction of effects, even within a single function, were highly variable. A focus on carbon cycling highlighted challenges in interpreting effects on a single function. While the effect of large herbivore exclusion on carbon cycling was slightly positive when its components (e.g. pools vs. fluxes of carbon) were aggregated, effects on individual components were variable and sometimes opposed. Given modern declines in large wild herbivores, it is critical to understand their effects on ecosystem function. However, this synthesis highlights strong variability in direction, magnitude, and modifiers of these effects. Some variation is likely due to disparity in what components are used to describe a given function. For example, for the carbon cycle we identified eight distinctly meaningful components, which are not easily combined yet are potentially misrepresentative of the larger cycle when considered alone. However, much of the observed difference in responses likely reflects real ecological variability across complex systems. To move towards a general predictive framework we must identify where variation in effect is due to methodological differences and where due to ecosystem context. Two critical steps forward are (a) additional quantitative synthetic analyses of large herbivores' effects on individual functions, and (b) improved, increased systematic exclosure research focusing on effects of large herbivores' exclusion on functions. A freePlain Language Summarycan be found within the Supporting Information of this article.

Infectious disease burdens vary from country to country and year to year due to ecological and economic drivers. Recently, Murray et al. (Murray CJ et al . 2012 Lancet 380 , 2197–2223. ( doi:10.1016/S0140-6736(12)61689-4 )) estimated country-level morbidity and mortality associated with a variety of factors, including infectious diseases, for the years 1990 and 2010. Unlike other databases that report disease prevalence or count outbreaks per country, Murray et al. report health impacts in per-person disability-adjusted life years (DALYs), allowing comparison across diseases with lethal and sublethal health effects. We investigated the spatial and temporal relationships between DALYs lost to infectious disease and potential demographic, economic, environmental and biotic drivers, for the 60 intermediate-sized countries where data were available and comparable. Most drivers had unique associations with each disease. For example, temperature was positively associated with some diseases and negatively associated with others, perhaps due to differences in disease agent thermal optima, transmission modes and host species identities. Biodiverse countries tended to have high disease burdens, consistent with the expectation that high diversity of potential hosts should support high disease transmission. Contrary to the dilution effect hypothesis, increases in biodiversity over time were not correlated with improvements in human health, and increases in forestation over time were actually associated with increased disease burden. Urbanization and wealth were associated with lower burdens for many diseases, a pattern that could arise from increased access to sanitation and healthcare in cities and increased investment in healthcare. The importance of urbanization and wealth helps to explain why most infectious diseases have become less burdensome over the past three decades, and points to possible levers for further progress in improving global public health. This article is part of the themed issue ‘Conservation, biodiversity and infectious disease: scientific evidence and policy implications’.

Many species of large wildlife have declined drastically worldwide. These reductions often lead to profound shifts in the ecology of entire communities and ecosystems. However, the effects of these large‐wildlife declines on other taxa likely hinge upon both underlying abiotic properties of these systems and on the types of secondary anthropogenic changes associated with wildlife loss, making impacts difficult to predict. To better understand how these important contextual factors determine the consequences of large‐wildlife declines on other animals in a community, we examined the effects of three common forms of large‐wildlife loss (removal without replacement [using fences], removal followed by replacement with domestic stock, and removal accompanied by crop agricultural use) on small‐mammal abundance, diversity, and community composition, in landscapes that varied in several abiotic attributes (rainfall, soil fertility, land‐use intensity) in central Kenya. We found that small‐mammal communities were indeed heavily impacted by all forms of large‐wildlife decline, showing, on average: (1) higher densities, (2) lower species richness per site, and (3) different species assemblages in sites from which large wildlife were removed. However, the nature and magnitude of these effects were strongly context dependent. Rainfall, type of land‐use change, and the interaction of these two factors were key predictors of both the magnitude and type of responses of small mammals. The strongest effects, particularly abundance responses, tended to be observed in low‐rainfall areas. Whereas isolated wildlife removal primarily led to increased small‐mammal abundance, wildlife removal associated with secondary uses (agriculture, domestic stock) had much more variable effects on abundance and stronger impacts on diversity and composition. Collectively, these results (1) highlight the importance of context in determining the impacts of large‐wildlife decline on small‐mammal communities, (2) emphasize the challenges in extrapolating results from controlled experimental studies to predict the effects of wildlife declines that are accompanied by secondary land‐uses, and (3) suggest that, because of the context‐dependent nature of the responses to large‐wildlife decline, large‐wildlife status alone cannot be reliably used to predict small‐mammal community changes.