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Efficacy of beehive fences as barriers to African elephants: a case study in Tanzania

Published online by Cambridge University Press:  21 May 2018

Ciska P.J. Scheijen
Affiliation:
Department of Wildlife Management, Van Hall Larenstein University of Applied Sciences, Leeuwarden, The Netherlands
Shane A. Richards
Affiliation:
School of Natural Sciences, University of Tasmania, Sandy Bay, Australia
Josephine Smit
Affiliation:
Department of Psychology, University of Stirling, Stirling, UK
Trevor Jones
Affiliation:
Southern Tanzania Elephant Program, Iringa, Tanzania
Katarzyna Nowak*
Affiliation:
Zoology & Entomology, University of the Free State, Qwaqwa Campus, Phuthaditjhaba, 9866, South Africa
*
(Corresponding author) E-mail knowak02@gmail.com
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Abstract

Non-lethal mitigation of crop use by elephants Loxodonta africana is an increasingly important part of protected area management across Africa and Asia. Recently, beehive fences have been suggested as a potential mitigation strategy. We tested the effectiveness of this method in a farming community adjacent to Udzungwa Mountains National Park in southern Tanzania. Over a 5.5-year period (2010–2016) a beehive fence was introduced and subsequently extended along the Park boundary. The probability that one or more farms experienced crop loss from elephants on a given day was reduced in the presence of the fence and was reduced further as the fence was extended. The number of hives occupied by bees along the fence was the best predictor of elephants’ visits to farms. Farms closest to the fence experienced a greater likelihood of damage, particularly during the initial period when the fence was shorter. The number of farms affected by elephants declined when the fence was extended. There was a higher probability of damage on farms that were closer to the Park boundary and further from a road. Our mixed results suggest that the shape, length and location of fences need to be carefully planned because changes in a farm's long-term susceptibility to elephant damage vary between individual farms; fences need to be long enough to be effective and ensure that decreasing crop loss frequency is not outweighed by an increasing number of farms damaged per visit.

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Copyright © Fauna & Flora International 2018 
Figure 0

Fig. 1 Study area with the two focal villages Mang'ula A and Mang'ula B along the eastern boundary of Udzungwa Mountains National Park. All 120 farms included in our analysis are shown, as is the main road, elephant routes, and the short and long beehive fences. Map data are from Google imagery (2017).

Figure 1

Table 1 Beehive fence construction costs, expressed per beehive. The length occupied by a beehive and poles is 3 m, and each beehive is connected to 7 m of wire.

Figure 2

Fig. 2 (a) The number of hives occupied by bees when the hive fence was short and long. (b) The number of farms damaged during an elephant visit over time separated according to three fencing conditions: the beehive fence is absent, the presence of a short beehive fence, and the presence of a long beehive fence. Days when a visit was not observed (i.e. zero farms were damaged) are not presented, for clarity. See Figs 1 and 3 for the placement of the short and long fences.

Figure 3

Table 2 Akaike Information Criterion (AIC) analysis examining temporal trends in the daily probability that elephants Loxodonta africana visit farms. Three pairs of logistic models were fit to the daily data on the presence/absence of a visit by elephants. We considered a smooth long-term trend (T), the presence of a beehive fence (F), and the number of hives occupied by bees (H). These models were paired with a seasonal effect (S). FS describes the effect of adding the short beehive fence, FL is the effect of extending the short fence to a long fence, ϕ is fractional time of year when raids are most likely, K is the number of estimated parameters, LL is the maximum log-likelihood and * indicates that the model is selected using the suggested rules outlined in Richards (2008).

Figure 4

Fig. 3 Changes in the ranking of farm susceptibility to damage during an elephant visit for the three phases of the study: no beehive fence, short beehive fence, and long beehive fence.

Figure 5

Table 3 Akaike Information Criterion (AIC) analysis examining farm traits that influence susceptibility to damage during a visit by elephants. Fits for 16 binomial regression models with a random farm effect are presented. Up to four predictor variables without interaction effects were considered: farm size (S), distance to National Park (P), distance to beehive fence (F) and distance to nearest road (R). Predictor variables were z-transformed so the regression coefficients (βx) describe relative effect sizes. σ is the standard deviation of the random effect term. K is the number of estimated parameters, LL is the maximum log-likelihood and * indicates that the model is selected using the suggested rules outlined in Richards (2008).