Protected areas fall far short of securing the space needed to sustain biodiversity and ecosystem function at a global scale and in the face of climate change. The prospects of conserving biodiversity in working landscapes help buffer the insularization effects of protected areas and hold great potential for biodiversity conservation on a landscape scale but depend on finding adequate space and a meaningful place in the lives of rural land users. Using a case study in southern Kenya, we show that the conservation of large open landscapes, biodiversity and the coexistence between wildlife and livestock can be achieved indirectly by reinforcing pastoral practices that depend on open space, mobility, social networks and institutional arrangements governing common‐pool resources. Pastoral practices and wildlife both depend on large multiscale interactions within interlinked social and ecological systems, which are threatened by land fragmentation, alienation and degradation. We show that large open spaces can be maintained by using a conservation approach starting from within community aspirations that emphasize the links between livelihoods, productivity, efficiency and resilience in pastoral economies and the secondary benefits of wildlife enterprises. Scaling up from an ecosystem to multi‐scale approach benefits pastoral communities by building resilience and new economic opportunities. In the process, the expanded scale conserves regional biodiversity and large free‐ranging herbivore and carnivore populations underpinning ecosystem function and the nationally important tourism industry centered on the Kenya–Tanzania boundary. The ‘inside‐out’ approach to the conservation of wildlife and biodiversity is place‐based, draws on local knowledge and informal governance arrangements and avoids the stigma of wildlife conservation driven by outside agencies. The human‐centered approach reinforces land health and spatial connectivity and encourages multi‐level and distributed governance arrangements embedded in large regional and national jurisdictions.

In savannas, mapping grazing resources and indicators of land degradation is important for assessing ecosystem conditions and informing grazing and land management decisions. We investigated the effects of classifiers and used time series imagery—images acquired within and across seasons—on the accuracy of plant species maps. The study site was a grazed savanna in southern Kenya. We used Sentinel-2 multi-spectral imagery due to its high spatial (10–20 m) and temporal (five days) resolution with support vector machine (SVM) and random forest (RF) classifiers. The species mapped were important for grazing livestock and wildlife (three grass species), indicators of land degradation (one tree genus and one invasive shrub), and a fig tree species. The results show that increasing the number of images, including dry season imagery, results in improved classification accuracy regardless of the classifier (average increase in overall accuracy (OA) = 0.1632). SVM consistently outperformed RF, and the most accurate model and was SVM with a radial kernel using imagery from both wet and dry seasons (OA = 0.8217). Maps showed that seasonal grazing areas provide functionally different grazing opportunities and have different vegetation characteristics that are critical to a landscape’s ability to support large populations of both livestock and wildlife. This study highlights the potential of multi-spectral satellite imagery for species-level mapping of savannas.

Conservation in eastern and southern Africa has historically centered on megafauna and protected areas (PAs), yet, in the face of rapid change, biodiversity outside of PAs is under threat. With policy changes underway in Kenya, we have performed an analysis that (a) quantifies how inclusive the current PA network is of the country's vertebrate diversity, and (b) identifies wildlife policy areas that need reform to achieve conservation targets. We found that species richness of mammals, birds, and amphibians is highest in areas of intermediate human pressures, whereas Kenya's current wildlife conservation policy focuses on land use (LU) types with the least human pressure. Percentage of range overlap for amphibians, mammals, and birds were all highest in rangelands followed by agricultural (cultivated) areas and then national PAs. Out of 1,535 terrestrial vertebrate species, 80 had no range overlap with national PAs. The current wildlife PA network adequately covers only 16% of amphibians, 45% of birds, and 41% of mammals. In addition, we used a biodiversity importance score which demonstrated the importance of rangelands and agricultural areas for biodiversity conservation. Finally, we observed that the distribution of current PAs, and the focus of Kenya's wildlife policy in general, is in areas of lowest human pressure, often with the highest large mammal densities. However, other biodiversity indicators ‐ such as bird and plant species richness ‐ show that areas under human‐dominated LU currently support substantial biodiversity. Overall, our analysis demonstrates that formal PAs and wildlife policy presently cover only a small fraction of national biodiversity, which resides mainly in human‐dominated landscapes that are undergoing rapid change. These findings echo global calls for a landscape‐based approach to conservation policy and practice that promotes the coexistence of people and wildlife within social‐ecological systems.

Human activity affecting the welfare of wild vertebrates, widely accepted to be sentient, and therefore deserving of moral concern, is widespread. A variety of motives lead to the killing of individual wild animals. These include to provide food, to protect stock and other human interests, and also for sport. The acceptability of such killing is widely believed to vary with the motive and method. Individual vertebrates are also killed by conservationists. Whether securing conservation goals is an adequate reason for such killing has recently been challenged. Conventional conservation practice has tended to prioritise ecological collectives, such as populations and species, when their interests conflict with those of individuals. Supporters of the ‘Compassionate Conservation’ movement argue both that conservationists have neglected animal welfare when such conflicts arise and that no killing for conservation is justified. We counter that conservationists increasingly seek to adhere to high standards of welfare, and that the extreme position advocated by some supporters of ‘Compassionate Conservation’, rooted in virtue ethics, would, if widely accepted, lead to considerable negative effects for conservation. Conservation practice cannot afford to neglect consequences. Moreover, the do-no-harm maxim does not always lead to better outcomes for animal welfare.

Aim: Species‐specific conservation strategies are frequently formulated based on species distribution maps, which are challenging to produce, especially at large spatial scales. Our aim was to use a novel empirical approach to predict the national distribution for all six large carnivore species found in Kenya to guide conservation and management decisions by identifying knowledge and conservation gaps.Location: Kenya.Methods: We collected data on carnivore presence and absence through questionnaire and sightings‐based surveys and analysed the combined data set using single‐season false‐positive occupancy models, which account for imperfect detections and false positives. To predict potential distributions and inform conservation strategies, we used the occupancy outputs to make predictions for unsampled areas and create occupancy‐based distribution maps where ψ > 0.50, to (1) quantify differences with IUCN Red List range maps, (2) quantify overlap with wildlife areas and (3) identify areas of high carnivore richness.Results: Large carnivore occupancy was associated with land conversion, habitat and prey availability. Our results suggest that all six species are widely distributed across Kenya and reveal substantial differences to distribution maps compiled by the IUCN Red List. More specifically, our occupancy‐based distribution maps predict much larger distribution for African wild dog (5.09X), lion (4.77X) and leopard (1.46X), similar distribution for cheetah, and smaller distribution for spotted hyaena (0.84X) and striped hyaena (0.65X). For all large carnivores, the vast majority (~80%) of their predicted distribution falls outside wildlife areas and northern Kenya is predicted to have the highest large carnivore richness.Main conclusions: Our results are encouraging as large carnivores may be widely distributed across Kenya, in some cases potentially more so than previously acknowledged. However, much of this range lies outside wildlife areas and represent areas of concern both for conservation and human livelihoods illustrating the challenges of conserving large carnivores across their range.