Biodiversity monitoring is critical to assess the effectiveness of management activities and policy change, particularly in the light of accelerating impacts of environmental change, and for compiling national responses to international obligations and agreements. Monitoring methods able to identify species most likely to be affected by environmental change, and pinpoint those changes with the strongest impacts, will enable managers to target efforts towards vulnerable species and significant threats. Here we take a new approach to carnivore monitoring, combining camera-trap surveys with ecological niche factor analysis to assess distribution and patterns of habitat use of mammalian carnivore assemblages across northern Tanzania. We conducted 11 surveys over 430 camera-trap stations and 11 355 trap-days. We recorded 23 out of 35 carnivore species known to occur in Tanzania and report major extensions to the known distribution of the bushy-tailed mongoose Bdeogale crassicauda, previously thought to be rare. Carnivore biodiversity tended to be higher in national parks than in game reserves and forest reserves. We explored habitat use for seven species for which we had sufficient information. All species tended to be found near rivers and southern Acacia commiphora woodlands (except one mongoose species), and avoided deciduous shrubland, favouring deciduous woodland and/or open grassland. All species tended to avoid croplands suggesting that habitat conversion to agriculture could have serious implications for carnivore distribution. Our study provides a first example where camera-trap data are combined with niche analyses to reveal patterns in habitat use and spatial distribution of otherwise elusive and poorly known species and to inform reserve design and land-use planning. Our methodology represents a potentially powerful tool that can inform national and site-based wildlife managers and policy makers as well as international agreements on conservation.

Limited mapping of migrations hampers conservation

Summary1. This study utilizes a unique data set covering over 19 000 georeferenced records of species presence collected between 1993 and 2008, to explore the distribution and habitat selectivity of an assemblage of 26 carnivore species in the Serengeti-Ngorongoro landscape in northern Tanzania. 2. Two species, the large-spotted genet and the bushy-tailed mongoose, were documented for the first time within this landscape. Ecological Niche Factor Analysis (ENFA) was used to examine habitat selectivity for 18 of the 26 carnivore species for which there is sufficient data. Eleven ecogeographical variables (EGVs), such as altitude and habitat type, were used for these analyses. 3. The ENFA demonstrated that species differed in their habitat selectivity, and supported the limited ecological information already available for these species, such as the golden jackals' preference for grassland and the leopards' preference for river valleys. 4. Two aggregate scores, marginality and tolerance, are generated by the ENFA, and describe each species' habitat selectivity in relation to the suite of EGVs. These scores were used to test the hypothesis that smaller species are expected to be more selective than larger species [Science, 1989[Science, , 243, 1145. Two predictions were tested: Marginality should decrease with body mass; and tolerance should increase with body mass. Our study provided no evidence for either prediction. 5. Our results not only support previous analyses of carnivore diet breadth, but also represent a novel approach to the investigation of habitat selection across species assemblages. Our method provides a powerful tool to explore similar questions in other systems and for other taxa.

Background Current animal tracking studies are most often based on the application of external geolocators such as GPS and radio transmitters. While these technologies provide detailed movement data, they are costly to acquire and maintain, which often restricts sample sizes. Furthermore, deploying external geolocators requires physically capturing and recapturing of animals, which poses an additional welfare concern. Natural biomarkers provide an alternative, non-invasive approach for addressing a range of geolocation questions and can, because of relatively low cost, be collected from many individuals thereby broadening the scope for population-wide inference. Methods We developed a low-cost, minimally invasive method for distinguishing between local versus non-local movements of cattle using sulfur isotope ratios (δ34S) in cattle tail hair collected in the Greater Serengeti Ecosystem, Tanzania. Results We used a Generalized Additive Model to generate a predicted δ34S isoscape across the study area. This isoscape was constructed using spatial smoothers and underpinned by the positive relationship between δ34S values and lithology. We then established a strong relationship between δ34S from recent sections of cattle tail hair and the δ34S from grasses sampled in the immediate vicinity of an individual’s location, suggesting δ34S in the hair reflects the δ34S in the environment. By combining uncertainty in estimation of the isoscape, with predictions of tail hair δ34S given an animal’s position in the isoscape we estimated the anisotropic distribution of travel distances across the Serengeti ecosystem sufficient to detect movement using sulfur stable isotopes. Conclusions While the focus of our study was on cattle, this approach can be modified to understand movements in other mobile organisms where the sulfur isoscape is sufficiently heterogeneous relative to the spatial scale of animal movements and where tracking with traditional methods is difficult.