Remarkably little is still understood about how the leopard (Panthera pardus) is faring in much of its remaining African range, despite the species’ importance for ecosystem function and generating funding for conservation via tourism. In this study, we address this knowledge gap in southern Tanzania’s Selous-Nyerere ecosystem, one of the largest intact wilderness areas on the continent, by estimating leopard population density via spatially explicit capture-recapture (SECR) modelling of data from seven camera trap surveys.

Population density was highest in Nyerere National Park’s Matambwe sector (8.08 ± SE 1.54 adult and subadult leopards per 100 km²), followed by Selous Game Reserve’s Miguruwe sector (7.38 ± 1.26 per 100 km²); Nyerere NP’s Msolwa sector (6.05 ± 0.78 per 100 km²); Selous GR’s Liwale sector (5.93 ± 0.88 per 100 km²), western Kingupira sector (5.58 ± 0.87 per 100 km²), and eastern Kingupira sector (5.22 ± 0.71 per 100 km²); and Nyerere NP’s Kalulu sector (3.80 ± 0.64 per 100 km²).

Together, our surveys covered an important component of extant leopard range in Tanzania, and our findings highlight the importance of the Selous-Nyerere ecosystem as a leopard stronghold. The estimates include the highest leopard densities yet documented in miombo woodland, which represents nearly one fifth of the species’ remaining African range.

Unlike lion, leopard population density was highly correlated with relative abundance of preferred prey. Although limited by a small number of data points, this suggests that the two species may not be uniformly affected by anthropogenic threats. Threats to leopard in Selous-Nyerere include accelerating habitat conversion in boundary areas and bushmeat poaching, which impacts leopard indirectly by suppressing prey populations and directly via accidental snaring.

Practical implication: Placed in the context of range-wide leopard monitoring, this study highlights the need to address persistent knowledge gaps on the species’ continental status and prioritise sites for monitoring based on their potential to inform evidence-based conservation management.