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Resistance of termite mounds to variation in long-term fire regimes across semi-arid African savannas

Cite this dataset

Hockridge, Evan; Singh, Jenia; Boucher, Peter; Davies, Andrew (2022). Resistance of termite mounds to variation in long-term fire regimes across semi-arid African savannas [Dataset]. Dryad.


1. Fire regimes are expected to change with climate change, resulting in a crucial need to understand the specific ways in which variable fire regimes impact important contributors to ecosystem functioning, such as mound-building termites. Termite mounds and fire are both important agents of savanna ecosystem heterogeneity and functioning, but there is little understanding of how they interact across savanna types. 2. We used very high-resolution LiDAR remote sensing to measure the size, density, and distribution of termite mounds across approximately 1,300 ha of experimental burn plots in four South African savanna landscapes representing a wide range of fire treatments differing in seasonality and frequency of burning. 3. In nutrient-poor granitic savannas, fire had no impact on termite mound size, densities, and spatial distributions. In nutrient-rich basaltic savannas with high mammalian herbivore abundance and intermediate rainfall, very frequent fires caused a decrease in termite mound size, whereas in arid nutrient-rich basaltic savannas, fires that occurred at intermediate frequencies and in transitional seasons (i.e., late dry season and late wet season) decreased the degree of spatial overdispersal exhibited by mounds. 4. Overall, our results suggest that termite mounds are resistant to variation in fire seasonality and frequency, likely indicating that ecosystem services provided by mound-building termites will be unaffected by changing fire regimes. However, consideration of changes to termite mound size and distribution could be necessary for land managers in specific savanna types, such as nutrient-rich soils with high mammalian herbivore abundance.


The dataset consists of shape files of termite mounds and experimental burn plots manually deliniated from drone-based LiDAR and RGB remote sensing data at 10cm resolution. The plot level data is also provided in a csv document format.

Usage notes

Any GIS software, open source or proporietary.


Harvard University