Small-scale fires interact with herbivore feedbacks to create persistent grazing lawn environments

Fire-herbivory feedbacks strongly influence the formation of grazing lawns in savanna ecosystems. Preliminary findings suggest that small-scale (< 25 ha) fires can engineer grazing lawns by concentrating herbivores on the post-burn green flush; however, the persistence of such grazing lawns over the longer term and without repeated fire is unknown.

We used high-resolution Light Detection and Ranging (LiDAR) to investigate the long-term effects of fire manipulation on short grass structure (height, cover, volume, and spatial continuity) and grazing lawn establishment in Kruger National Park, South Africa. We analysed the effects of fire exclusion and experimental burns applied over a 7-year period (2013-2019) followed by a one-year cessation of burning at varying spatial scales during the early and late dry seasons.

Fires contributed a fourfold increase in short grass cover, regardless of fire season or size. The distribution of grass height differed significantly between fire-induced grazing lawns and recently unburnt parts of the landscape where controlled fires were excluded over the experimental period. The volume (corresponding to bulk density) of short grass on the landscape responded strongly to fires, with grass volume <20 cm in height increasing with both early and late dry season fires.

Early dry season fires caused larger and more homogeneous short grass patches. Furthermore, early dry season fires were more influential in increasing the cover of the shortest grass height class (1-5 cm).

Synthesis and applications. Our results demonstrate that fire-induced grazing lawns can persist over the longer-term, even when fires are no longer applied, leading to the creation of vertical and horizontal heterogeneity in the grass layer. Small-scale fires, therefore, represent a feasible management approach to expanding grazing lawn extent, potentially benefiting grazer coexistence and diversity.

Methods
The dataset consists of short grass vegetation metrics (height, cover, volume, patch sizes) derived from drone-based LiDAR.