Spatial ecology and recovery patterns of a translocated mammal community in southern Africa

Conservation translocations are an increasingly common tool to restore wildlife populations within protected areas. Along with identifying and mitigating threats, post-release monitoring allows managers to evaluate recovery effectiveness and improve success rates. Multispecies translocations present challenges in monitoring design, data processing, and analysis. Camera traps coupled with computer-vision-assisted workflows, environmental data, and spatially explicit occupancy models show promise for efficient multispecies monitoring over broad spatiotemporal scales. We applied this approach to a large translocation program in Nkhotakota Wildlife Reserve, Malawi, using a six-year camera-trap dataset to assess recovery patterns of nine large herbivore species. We fit spatial occupancy models to estimate species distributions and trends in landscape use while incorporating environmental covariates and accounting for spatial autocorrelation. African bush elephants (Loxodonta africana) and cape buffalo (Syncerus caffer) showed the strongest evidence of establishment and expansion, while common eland (Taurotragus oryx), greater kudu (Tragelaphus strepsiceros), plains zebra (Equus quagga), and impala (Aepyceros melampus) showed positive but weaker or uneven trends. Sable antelope (Hippotragus niger) showed evidence of establishment without expansion, whereas waterbuck (Kobus ellipsiprymnus) and warthog (Phacochoerus africanus) exhibited negative trends, although support for waterbuck declines was weak. Species exhibited variable and seasonally specific relationships with tree density, proximity to water, elevation, slope, and the reserve boundary, indicating that a range of environmental conditions support this mammal community. Our results demonstrate how spatial occupancy models can provide interpretable recovery indicators for multispecies translocations while highlighting how long-term monitoring can distinguish early recovery, behavioral shifts, and interannual variation from long-term population responses.