Summary1. Concern about the effects of habitat fragmentation has led to increasing interest in dispersal and connectivity modelling. Most modern techniques for connectivity modelling have resistance surfaces as their foundation. However, resistance surfaces for animal movement are frequently estimated without considering dispersal, despite being the principal natural mechanism by which organisms move between populations. 2. We collected Global Positioning System data over 10 years from 50 African lions Panthera leo (11 male natal dispersers, 20 adult males and 19 adult females) and used a path level analysis to parameterize demographic-specific resistance surfaces for the Kavango Zambezi Transfrontier Conservation Area (KAZA) in Southern Africa. 3. Lion path selection varied according to demographic grouping: adult females were most averse to risky landscapes such as agro-pastoral lands, towns, areas of high human density and highways. Male natal dispersers were the least-risk averse suggesting they are potentially the most prone demographic to human-lion conflict. Adults of both sexes selected bushed grassland and shrubland habitats and avoided woodland. Male natal dispersers displayed the opposite trend suggesting con-specific avoidance and/or suboptimal habitat use. 4. We used the resistance surfaces to calculate factorial least-cost path networks for each demographic-specific resistance surface and present results that show substantial differences between predicted patterns of connectivity for male natal dispersers, adult females and adult males. 5. Synthesis and applications. Resistance surfaces are widely used to create connectivity models, which are promoted for use by conservation managers. Our results suggest that the demographic category used to parameterize resistance surfaces may lead to radically different conclusions about connectivity. Failure to include dispersing individuals when parameterizing resistance surfaces intended for connectivity modelling may lead to erroneous conclusions about connectivity and potentially unsound management strategies.

Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide-ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3-month survey and adapted a Bayesian spatially explicit capture-recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture-recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km , and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and policy decisions.

Summary Demography and conservation status of many wild organisms are increasingly shaped by interactions with humans. This is particularly the case for large, wide‐ranging carnivores. Using 206 mortality records (1999–2012) of lions in Hwange National Park, Zimbabwe, we calculated mortality rates for each source of anthropogenic mortality, modelled risk of anthropogenic mortality across the landscape accounting for time lions spent in different parts of the landscape, and assessed whether subsets of the population were more at risk. Anthropogenic activities caused 88% of male and 67% of female mortalities; male mortality being dominated by trophy hunting while the sources for female mortality were more varied (bycatch snaring, retaliatory killing, hunting). Landscapes of anthropogenic mortality risk revealed that communal subsistence farming areas, characterized by high risk (due to retaliatory killing) but avoided by lions, are population sinks. Trophy hunting areas and areas within protected areas bordering communal farmland, where bushmeat snaring is prevalent, form ‘ecological traps’ (or ‘attractive sinks’). Lions avoided risky areas, suggesting they may make behavioural decisions based on perceptions of risk. Experienced adults used risky areas less and incorporated lower proportions of them in their home ranges than young individuals, suggesting that the latter may either be naïve or forced into peripheral habitats. Synthesis and applications. This paper contributes to an understanding of how large carnivore populations are affected by anthropogenic mortality across the conservation landscape. This is critical to designing focussed, appropriate and cost‐effective conservation management strategies. Agricultural areas are intuitively identified by conservationists as being risky for carnivores due to retaliatory killing, with threats largely mitigated against by improving livestock protection. However, parts of protected areas may also form less easily identified ‘attractive sinks’ for carnivores. In particular, trophy hunting areas adjacent to national parks need careful management to avoid damaging effects of overhunting. Law enforcement is needed to reduce the effects of bushmeat poaching on predators and other wildlife in protected areas. To be most effective, resource‐limited antipoaching activities should prioritize wildlife‐rich areas close to human settlement as these tend to be hot spots for bushmeat poaching.

Conservation of large carnivores, such as the African lion, requires preservation of extensive core habitat areas, linkages between them, and mitigation of human-wildlife conflict. However, there are few rigorous examples of efforts that prioritized conservation actions for all three of these critical components. We used an empirically optimized resistance surface to calculate resistant kernel and factorial least cost path predictions of population connectivity and conflict risk for lions across the Kavango-Zambezi Transfrontier Conservation Area (KAZA) and surrounding landscape. We mapped and ranked the relative importance of (1) lion dispersal areas outside National Parks, (2) corridors between the key areas, and (3) areas of highest human-lion conflict risk. Spatial prioritization of conservation actions is critical given extensive land use redesignations that are reducing the extent and increasing the fragmentation of lion populations. While our example focuses on lions in southern Africa, it provides a general approach for rigorous, empirically based comprehensive conservation planning based on spatial prioritization.