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The age profile of populations fundamentally affects their conservation status. Yet, age is frequently difficult to assess in wild animals. Here, we assessed the use of DNA methylation of homologous genes to establish the age structure of a rare and elusive wild mammal: the Bechstein's bat (Myotis bechsteinii). We collected 62 wing punches from individuals whose ages were known as a result of a long-term banding study. DNA methylation was measured at seven CpG sites from three genes, which have previously shown age-associated changes in humans and laboratory mice. All CpG sites from the tested genes showed a significant relationship between DNA methylation and age, both individually and in combination (multiple linear regression R2 = 0.58, p

Overexploitation is one of the main pressures driving wildlife closer to extinction, yet broad-scale data to evaluate species’ declines are limited. Using African pangolins (Family: Pholidota) as a case study, we demonstrate that collating local-scale data can provide crucial information on regional trends in exploitation of threatened species to inform conservation actions and policy. We estimate that 0.4-2.7 million pangolins are hunted annually in Central African forests. The number of pangolins hunted has increased by ∼150% and the proportion of pangolins of all vertebrates hunted increased from 0.04% to 1.83% over the past four decades. However, there were no trends in pangolins observed at markets, suggesting use of alternative supply chains. We found evidence that the price of giant (Smutsia gigantea) and arboreal (Phataginus sp.) pangolins in urban markets has increased, mirroring trends in Asian pangolins. Efforts and resources are needed to increase law enforcement and population monitoring, and investigate linkages between subsistence hunting and illegal wildlife trade. Overexploitation is one of the main pressures driving wildlife closer to extinction, yet broad-scale data to evaluate species’ declines are limited. Using African pangolins (Family: Pholidota) as a case study, we demonstrate that collating local-scale data can provide crucial information on regional trends in exploitation of threatened species to inform conservation actions and policy. We estimate that 0.4-2.7 million pangolins are hunted annually in Central African forests. The number of pangolins hunted has increased by ∼150% and the proportion of pangolins of all vertebrates hunted increased from 0.04% to 1.83% over the past four decades. However, there were no trends in pangolins observed at markets, suggesting use of alternative supply chains. We found evidence that the price of giant (Smutsia gigantea) and arboreal (Phataginus sp.) pangolins in urban markets has increased, mirroring trends in Asian pangolins. Efforts and resources are needed to increase law enforcement and population monitoring, and investigate linkages between subsistence hunting and illegal wildlife trade.

Currently, human society is predominantly powered by fossil fuels—coal, oil and natural gas—yet also ultimately depends on goods and services provided by biodiversity. Fossil fuel extraction impacts biodiversity indirectly through climate change and by increasing accessibility, and directly through habitat loss and pollution. In contrast to the indirect effects, quantification of the direct impacts has been relatively neglected. To address this, we analyse the potential threat to > 37,000 species and > 200,000 protected areas globally from the locations of present and future fossil fuel extraction in marine and terrestrial environments. Sites that are currently exploited have higher species richness and endemism than unexploited sites, whereas known future hydrocarbon activities will predominantly move into less biodiverse locations. We identify 181 ‘high‐risk’ locations where oil or gas extraction suitability coincides with biodiversity importance, making conflicts between extraction and conservation probable. In total, protected areas are located on US$3‐15 trillion of unexploited hydrocarbon reserves, posing challenges and potentially opportunities for protected area management and sustainable financing.

Remotely sensed data - available at medium to high resolution across global spatial and temporal scales - are a valuable resource for ecologists. In particular, products from NASA's MODerate-resolution Imaging Spectroradiometer (MODIS), providing twice-daily global coverage, have been widely used for ecological applications. We present MODISTools, an R package designed to improve the accessing, downloading, and processing of remotely sensed MODIS data. MODISTools automates the process of data downloading and processing from any number of locations, time periods, and MODIS products. This automation reduces the risk of human error, and the researcher effort required compared to manual per-location downloads. The package will be particularly useful for ecological studies that include multiple sites, such as meta-analyses, observation networks, and globally distributed experiments. We give examples of the simple, reproducible workflow that MODISTools provides and of the checks that are carried out in the process. The end product is in a format that is amenable to statistical modeling. We analyzed the relationship between species richness across multiple higher taxa observed at 526 sites in temperate forests and vegetation indices, measures of aboveground net primary productivity. We downloaded MODIS derived vegetation index time series for each location where the species richness had been sampled, and summarized the data into three measures: maximum time-series value, temporal mean, and temporal variability. On average, species richness covaried positively with our vegetation index measures. Different higher taxa show different positive relationships with vegetation indices. Models had high R (2) values, suggesting higher taxon identity and a gradient of vegetation index together explain most of the variation in species richness in our data. MODISTools can be used on Windows, Mac, and Linux platforms, and is available from CRAN and GitHub (https://github.com/seantuck12/MODISTools).