Factors governing selective impacts of elephant on woody vegetation
Date
2009-02-02T10:03:44Z
Authors
Chafota, Jonas
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Abstract
ABSTRACT This study investigated factors governing selective impacts of elephants on different tree species, size classes, and plant parts in different areas at different times of the year in the elephant range of northern Botswana. Differential impacts on woody vegetation by different age/sex classes of elephant were considered. Also, environmental factors fortuitously identified to have direct influence on habitat resources, spatial distribution of elephant and the manner in which they interacted with woody vegetation were studied. These environmental factors included frost, fire and drought. Plant-based and animal-based data collection methods were used. The plant-based observation method involved an assessment of woody species impacts by sampling on foot, areas indicated by fresh tracks of actively feeding elephants. The animal-based observation method involved focal animal sampling whereby the feeding activities of the closest readily visible and actively feeding elephant were recorded. Due to safety problems and impassable terrain, much of the data for this study was collected from the plant-based method. Elephant favoured the intermediate height categories, but were not narrowly selective for plant height class within these categories. In fact, they generally subsisted on commonly available shrub species and were quite narrowly selective for a few woody plant species, with only fairly minor seasonal changes in the diet of woody species included in the diet during the cool-dry and wet seasons. The favoured shrub species included Baphia massaisensis, Bauhinia petersiana, Grewia monticola and Diplorhyncus condylocarpon. No clear distinction could be made with respect to differences in impacts between cow and bull herds on the commonly utilized shrub species. However, bulls appeared to have greater impact than cows with respect to severe impacts such as snapping of trunks, digging and uprooting plants.
The major factors found to influence elephant impacts on woody vegetation were season and height class. Thus, the impacts tended to be species and size class specific and varied seasonally. Also, availability of alternative food types in a feeding patch appeared to influence acceptability of woody species by elephant during the hot-dry
season when the diet of elephant was widened to include more woody species. This study found no evidence of a relationship between acceptance and availability of woody species. Elephant impacts on woody vegetation were considered to be severe if feeding events involved snapping of tree trunks, debarking, uprooting or pushing over. Severe elephant impacts on canopy trees appeared to be caused by a ‘restriction’ in the shrub layer food. The findings of this study, although not replicated suggested a linkage of severe elephant impacts on canopy trees to episodic or occurrence of drought, frost and fire events. As elephant normally subsist on the shrub layer, severe impacts on canopy trees may be induced by non availability of this food base as a result of localised over utilization in drought years and impacts of fire and frost. The study confirmed finding of other studies that elephant showed a relative dependence on leaves and shoots; stems and bark for a given season. However, important factors highlighted by the study are that in any given season, one or two woody species dominated by being included either jointly or alternately in elephant diet. Furthermore, an interesting observation on elephant feeding habits was that for some species, they discarded leaves in the process of consuming stems.
The study indicated that the long term consequence of elephant-vegetation interaction in northern Botswana is unclear but some management and research options were suggested. These aspects could be integrated into a long term modelling framework to assist in monitoring and decision making. A useful and interactive modelling approach could be a long term rule based qualitative model development which can continually be updated to incorporate new experience and knowledge.