Thirty-year elephant population trends across 93 South African reserves and the implications for conservation management

Abstract

While ivory poaching has driven elephant declines across much of Africa, South Africa's populations have expanded steadily, sparking debate over ecological impacts and population control. Yet these debates have lacked a harmonized, long-term national evidence base. To address this gap, we analyzed 30-year (1991–2021) population trends and current densities across 93 South African elephant populations. Owing to numerous translocations and sustained growth within reserves (mean 5.4 ± 7.9% p.a.), South Africa's national elephant population increased from ~8900 individuals across five reserves in 1991 (95% confidence interval: 5942–11,886) to ~39,400 across 93 reserves in 2021 (28,624–50,494). Most elephants (73%) occurred in Kruger National Park, while most populations (70%) occurred on private reserves/properties. Three findings carry direct management implications. First, most populations remain on a growth trajectory: over the past decade, 42% increased steadily (1%–5% p.a.) and 30% rapidly (>5% p.a.), with the largest 25 (>100 individuals) growing fastest. Second, despite this growth, most reserves support small, low-density populations: in 2021, 63% (n = 59) had <50 elephants and 70% (n = 65) had <0.5 elephants/km². Third, only 12 populations exceeded 1 elephant/km², and these were predominantly clustered in the Greater Kruger region; they were also large (median 620 individuals) and fast growing (median 3.9% p.a.). Overall, South Africa's elephant recovery represents a conservation success. A few high-density populations may be approaching ecological thresholds and pose management challenges due to their large size, whereas for most populations high densities are not yet a concern and may even underdeliver positive megaherbivore functions. Further work is needed to clarify the context-specific influence of elephant density, fire, rainfall, and other drivers on ecological impact. Our study highlights the policy value of a single, standardized national dataset that integrates counts and uncertainty to support evidence-based, spatially differentiated management of this increasingly complex national meta-population.