Fine-scale habitat heterogeneity influences browsing damage by elephant and giraffe

Effects of large mammalian herbivores on woody vegetation tend to
be heterogeneous in space and time, but the factors that drive such
heterogeneity are poorly understood. We examined the influence of
fine-scale habitat heterogeneity on the distribution and browsing effects
of two of the largest African terrestrial mammals, the elephant and
giraffe. We conducted this study within a 120-ha (500 x 2400 m) ForestGEO
long-term vegetation monitoring plot located at Mpala Research Center,
Kenya. The plot traverses three distinct topographic habitats (‘plateau’,
‘steep slopes’, and ‘valley’) with contrasting elevation, slope, soil
properties, and vegetation composition. To quantify browsing damage, we
focused on Acacia mellifera, a palatable tree species that occurs across
the three habitat categories. Overall tree density, species richness, and
diversity was highest on the steep slopes and lowest on the plateau. Acacia
mellifera trees were tallest and had the lowest number of stems per tree on
the steep slopes. Both elephant and giraffe avoided the steep slopes and
their activity was higher during the wet season than during the dry season.
Browsing damage on Acacia mellifera was lowest on the steep slopes.
Elephant browsing damage was highest in the valley whereas giraffe browsing
damage was highest on the plateau. Our findings suggest that fine-scale
habitat heterogeneity is an important factor in predicting the distribution
of large herbivores and their effects on vegetation and may interact with
other drivers such as edaphic variations to influence local variation in
vegetation structure and composition.
Methods
Camera trap data was collected over a period of one year. Frequency of detection reffers to the number of indepedent photographic events. Working days reffers to the number of days that individual camera traps are known to have been working (there are occasions when come camera traps would fail). Presence is culculated by dividing the frequency of detection with the number of workiking days. This dataset is used to generate figure 4 and figure 6. 

The browsing data is obtained by indepedently scoring elephant and giraffe browsing damage in both wet and dry season. The scores are based on the proportion of canopy removed by the two browsers. This dataset is used to generate figure 5 and 6.