Robust policy decisions regarding the protection and management of terrestrial mammals require knowledge of where species are and in what numbers. The last comprehensive review, presenting absolute estimates at a national scale, was published nearly 20 years ago and was largely based on expert opinion. We investigated and propose a systematic data driven approach combing publically available occurrence data with published density estimates to predict species distribution maps and derive total abundance figures for all terrestrial mammals inhabiting Britain. Our findings suggest that the methodology has potential; generally producing plausible predictions consistent with existing information. However, inconsistencies in the availability and recording of data impact the certainty of this output limiting its current application for policy. Restrictions on access and use of occurrence data at a local level produces “data deserts” for which models cannot compensate. This leads to gaps in spatial distribution of species and consequently underestimates abundance. For many species the limited number of geo-referenced densities hampered the extrapolation from habitat suitability to absolute abundance. Even for well-studied species, further density estimates are required. Many density estimates used were pre-1995 and therefore the derived abundance should not be considered a current estimate. To maximise a systematic approach in the future we make the following recommendations: To mitigate the attitudes of a minority of local data providers occurrence records must be submitted to national surveys such as the Mammal Society’s Mammal Tracker.Studies are required to estimate density for common species and in areas of low or no abundance.To ensure such studies can be collated and used efficiently we propose a standardised approach reporting density estimates based on the 1km resolution British National Grid, or habitat representative of the 1km square, with digital maps to accompany publications.

Consumption of globally traded agricultural commodities like soy and palm oil is one of the primary causes of deforestation and biodiversity loss in some of the world’s most species-rich ecosystems. However, the complexity of global supply chains has confounded efforts to reduce impacts. Companies and governments with sustainability commitments struggle to understand their own sourcing patterns, while the activities of more unscrupulous actors are conveniently masked by the opacity of global trade. We combine state-of-the-art material flow, economic trade, and biodiversity impact models to produce an innovative approach for understanding the impacts of trade on biodiversity loss and the roles of remote markets and actors. We do this for the production of soy in the Brazilian Cerrado, home to more than 5% of the world´s species. Distinct sourcing patterns of consumer countries and trading companies result in substantially different impacts on endemic species. Connections between individual buyers and specific hot spots explain the disproportionate impacts of some actors on endemic species and individual threatened species, such as the particular impact of European Union consumers on the recent habitat losses for the iconic giant anteater (Myrmecophaga tridactyla). In making these linkages explicit, our approach enables commodity buyers and investors to target their efforts much more closely to improve the sustainability of their supply chains in their sourcing regions while also transforming our ability to monitor the impact of such commitments over time.

Globally, considerable carbon (C) is stored in soils, particularly in peatlands. These stores play a potentially significant role in atmospheric C-cycle feedbacks, and thus need to be accounted for in global models. However, present global soil models do not accurately represent peat C-stocks and -dynamics; thus, their climate-soil C feedback predictions are questionable. A major shortcoming of current models that are based on the decomposition of soil C pools is the lack of representation of long-term (non-equilibrium) soil organic carbon (SOC) accumulation, as peat cohorts, with cohort age information. Whereas C-pool models are commonly 'spun up' to equilibrium over several hundred years using an average climate, in nature, soils actually evolve over many thousands of years with associated changes in litter amounts and quality, which affect SOC accumulation, and hence peat formation. Secondly, peat soils have a unique hydrology, and changes in the water table depth (WTD) of peat are important in regulating SOC turnover, yet current non-cohort C pool models fail to include such dynamic hydrological processes. We have developed an improved peat agecohort model called MILLENNIA, with a variable WTD driving C-dynamics during Holocene peat accumulation, allowing validation with peat age data and the testing of a realistic WTD-driven peat SOC stock response to climate-change scenarios. Model C-dynamics showed particular sensitivity to water table dynamics through precipitation and runoff, as well as to litter quality and decomposition rates. We show that predicted SOC accumulation and peat ages compare well with observations from a UK peatland site, which is currently (on average) a weak net C source with strong climate sensitivity.

Sub-Saharan African human populations rely heavily on wild-harvested medicinal plants for their health. The trade in herbal medicine provides an income for many West African people, but little is known about the effects of commercial extraction on wild plant populations. Detailed distribution maps are lacking for even the most commonly traded species. Here we combine quantitative market surveys in Ghana and Benin with species distribution models (SDMs) to assess potential species' vulnerability to overharvesting and to prioritize areas for sustainable extraction studies. We provide the first detailed distribution maps for 12 commercially extracted medicinal plants in West Africa. We suggest an IUCN threat status for four forest species that were not previously assessed (Sphenocentrum jollyanum, Okoubaka aubrevillei, Entada gigas and Piper guineense), which have narrow distributions in West Africa and are extensively commercialized. As SDMs estimate the extent of suitable abiotic habitat conditions rather than population size per se, their output is of limited use to assess vulnerability for overharvesting of widely distributed species. Examples of such species are Khaya senegalensis and Securidaca longipedunculata, two trees that were reported by market vendors as becoming increasingly scarce in the wild. Field surveys should start in predicted suitable habitats closest to urban areas and main roads, as commercial extraction likely occurs at the shortest cost distance to the markets. Our study provides an example of applying SDMs to conservation assessments aiming to safeguard provisioning ecosystems.

In 2007, the current outbreak of African swine fever (ASF), which severely affects wild boar populations and pigs, reached the Caucasus region. Since then, the virus has spread into eastern Europe and some places in central and western Europe (such as Belgium) through wild boar, domestic pigs, and human activities. The virus has raised serious concerns in countries with large pork industries, which may suffer economic losses due to trade restrictions. To control the outbreak, national authorities have taken drastic but likely ineffective measures that disregard the science of wildlife management. Poland, for example, has massively increased culling of wild boar to minimize ASF spread and the risk of transmission to domestic pigs, despite opposition by experts. The policy does not include population monitoring that could evaluate its effectiveness. It also does not limit wild boar access to agricultural crops and game feed, which is a key driver of population growth. Meanwhile, Denmark is building a 70-km border fence to exclude cross-border migration of wild boar. The fence will disrupt wildlife habitats, but it will not stop the virus from spreading through the transportation of live pigs, wild boar, or pig-and wild boar-derived tissues and products or through the movement of other objects carrying the virus, such as human clothing. Factors that govern wild boar abundance and virus spread are not bound by national borders. Instead of haphazard policies, we urge governments to agree on a coordinated response that adheres to the principles of modern wildlife management. Adaptive wildlife management strategies consider the human dimension and prevent unsound reactive management. Improved wildlife population monitoring and analysis are the best ways to determine which approaches to wildlife management are successful ecologically, economically, and socially. Sustainable management will depend on local circumstances and national wildlife management regulations, but science-based strategies can be implemented at the continental scale. Legislators across Europe should consult scientists and wildlife and animal health agencies before making decisions about wildlife policy. European countries should coordinate population monitoring and management. Shared responsibility for wildlife management among countries will enable funding for research that can critically evaluate its success. The ASF crisis can serve as a chance to develop a science-based wildlife policy for Europe.