Elephants respond to resource trade-offs in an aseasonal system through daily and annual variability in resource selection

Abstract

Animals and humans regularly make trade-offs between competing objectives. In Addo Elephant National Park (AENP), elephants (Loxodonta africana) trade off selection of resources, while managers balance tourist desires with conservation of elephants and rare plants. Elephant resource selection has been examined in seasonal savannas, but is understudied in aseasonal systems like AENP. Understanding elephant selection may suggest ways to minimise management trade-offs. We evaluated how elephants select vegetation productivity, distance to water, slope and terrain ruggedness across time in AENP and used this information to suggest management strategies that balance the needs of tourists and biodiversity. Resource selection functions with time-interacted covariates were developed for female elephants, using three data sets of daily movement to capture circadian and annual patterns of resource use. Results were predicted in areas of AENP currently unavailable to elephants to explore potential effects of future elephant access. Elephants displayed dynamic resource selection at daily and annual scales to meet competing requirements for resources. In summer, selection patterns generally conformed to those seen in savannas, but these relationships became weaker or reversed in winter. At daily scales, resource selection in the morning differed from that of midday and afternoon, likely reflecting trade-offs between acquiring sufficient forage and water. Dynamic selection strategies exist even in an aseasonal system, with both daily and annual patterns. This reinforces the importance of considering changing resource availability and trade-offs in studies of animal selection.

Conservation implications: Guiding tourism based on knowledge of elephant habitat selection may improve viewing success without requiring increased elephant numbers. If AENP managers expand elephant habitat to reduce density, our model predicts where elephant use may concentrate and where botanical reserves may be needed to protect rare plants from elephant impacts.