Factors affecting susceptibility of farms to crop raiding by African elephants: using a predictive model to mitigate conflict

Abstract

Crop raiding by African elephants Loxodonta africana erodes local tolerance for elephants and thereby impedes conservation efforts, so solutions are urgently required. Within conflict zones, crop raiding is not distributed equally amongst farms, which may be a result of variation in local physical or geographical factors, or in farmers’ efforts to defend their fields. Understanding the efficacy of local conflict mitigation methods is important, but few quantitative evaluations exist. Using a comparative survey of raided and non-raided farms in Transmara District, Kenya, and multivariate logistic and linear regression analyses, we explored a range of factors affecting (i) the susceptibility of farms to elephant crop raiding and (ii) the amount of crop damage once elephants had entered a field. The results revealed that farms that had been habitually raided in the past were more likely to be raided during the study period, as were those that were larger and bordered by hedges or fences. Greater guarding effort increased the likelihood that elephants were detected prior to entry and decreased the likelihood of successful crop raiding, as did the use of fire and noise. However, there was an interaction between physical and human factors; larger farms used more advanced barrier methods at the expense of guarding effort. Farmers’ efforts did not appear to diminish the damage inflicted once elephants had entered a field.

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A subsequent experimental test confirmed these results; the application of enhanced early warning and guarding effort on previously raided farms reduced incidents of crop raiding by 89·6% over 2 years in comparison with a control group of farms. Synthesis and applications . These results suggest that early detection of elephants approaching fields, increased guarding effort, and the use of active deterrents could form the basis of an effective mitigation strategy regardless of location and the physical attributes of a farm. Validating the results of predictive models through participatory mitigation trials serves to demonstrate effective solutions to farmers themselves. Researchers and practitioners should be encouraged to replicate such field trials over broader spatial and temporal scales and to find means to encourage farmers to take up appropriate solutions.