750 M. Montero‐Botey et al.
TABLE 1 Estimation of selection indexes based on the occurrence of elephant Loxodonta africana damage to 18 crop types, ordered from high to low preference.
Crop type
Sweet potatoes Bananas Peanuts Onions
Pumpkins Maize Beans Millet
Sugarcane
Cashew nuts Cassava Rice Peas
Sesame
Sunflowers Tomatoes Soy
Tobacco
Expected proportion (πi)
0.02220922 0.02188360 0.00207072 0.01181172 0.00446930 0.27985307 0.01260981 0.02263380 0.02225466 0.00383083 0.11140652 0.31450241 0.11748521 0.02951533 0.01915413 0.00223465 0.00159618 0.00047885
1Ranges from 0 to 1. 2For definition of grouping, see text.
Observed proportion (oi)
0.11817851 0.09264034 0.00743397 0.04011231 0.01470785 0.39495978 0.01384830 0.02368537 0.02244379 0.00382022 0.10961458 0.12121233 0.03371344 0.00315168 0.00047753 0.00000000 0.00000000 0.00000000
Selection index (wi)
5.32114671 4.23332294 3.59003242 3.39597662 3.29086305 1.41131125 1.09821667 1.04645985 1.00849872 0.99723123 0.98391526 0.38540986 0.28695903 0.10678119 0.02493078 0.00000000 0.00000000 0.00000000
Standardized index (Bi)1
0.19576674 0.15574535 0.13207848 0.12493910 0.12107194 0.05192261 0.04040375 0.03849960 0.03710300 0.03668847 0.03619857 0.01417936 0.01055732 0.00392852 0.00091721 0.00000000 0.00000000 0.00000000
Selection order
1 2 3 4 5 6 7 8 9
10 11 12 13 14 15
16-17-18 16-17-18 16-17-18
Preference group2
High High High High High High
Medium Medium Medium Medium Medium Low Low Low Low Low Low Low
when 0.75,wi,1.25, and high preference when wi$1.25. Additionally, we calculated Manly’s standardized selection ratio (Bi), for relative comparisons, which ranges from 0 to 1 (Manly et al., 2002), as: Bi = wi/j
To analyse the factors influencing crop damage in each n=1 wi.
farm we used beta regression models (Cribari-Neto & Zeileis, 2010). We first built a beta regression mixed model to include the possible spatial correlation structure of data (villages) in the model using the package glmmTMB for R 3.5.1 (R Core Team, 2016). Proportion of crop area da- maged by elephants in each farm was the response variable. Fixed effects (predictors) were (1) Euclidean distance from the sampled farm to the nearest water supply, (2) relative abundance of highly preferred crops (area covered by preferred crops divided by the total area of each farm), and (3) the existence or not of an investor in the Wildlife Management Area of each sampled village. As village had no significant effect in the model, we built a simpler model without the random structure, using the betareg package (Cribari-Neto & Zeileis, 2010)in R. The beta regression model was fitted with a logit link function (that with the highest pseudo R2) to obtain the predicted (fitted) values. We used model averaging to summarize all competing mod- els. We first fitted the maximal model, containing all the predictors.We then compared all possible models by using Akaike information criterion (AIC)weights. Formodel com- parison we used the dredge function in the MuMIn package in R. Finally, we obtained the importance of each predictor (from 0 to 1) using the model.avg function of MuMIn.
Results
Crops were grouped into three categories according to their selection index by elephants (Table 1), with significant differences in crop preference across the 18 crop types (χ2
17 = 3276.8;P,0.0001). Sweet potatoes, bananas, pea-
nuts, onions and pumpkins were the most preferred crops (wi$3; Table 1). Maize was the most preferred crop of the crops most cultivated in the area (Table 1). The mean per cent area damaged in each farm was 25.74 ± SE 2.94%(range 2.5–100%). In the southern part of the
Corridor, where elephant populations are smaller, the mean per cent area damaged per farmwas 13.06 ± SE 2.86%, where- as in the northern part it was 30.13 ± SE 3.64%. Model averaging revealed that the relative abundance of preferred food was by far the most important variable explaining crop damage on each farm (relative importance of 1), fol- lowed by the presence of investors (relative importance of 0.41; Tables 2 & 3). Distance to water supply had little im- portance (relative importance of 0.29; Tables 2 & 3). Thus, damage by elephants was positively associated with relative abundance of preferred food and negatively associated with distance towater supply (Fig. 2), although only relative abun- dance of preferred food had a significant effect on crop dam- age by elephants (Table 2). Farms with .70%of their land covered by preferred crops had high elephant damage, with an area damaged.50%(Fig. 2a). A reduction in the cultiva- tion of preferred crops from 75 to 25%of
the farmland resulted in a 64% decrease in elephant crop damage. On Oryx, 2021, 55(5), 747–754 © The Author(s), 2020. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S0030605319000978
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92 |
Page 93 |
Page 94 |
Page 95 |
Page 96 |
Page 97 |
Page 98 |
Page 99 |
Page 100 |
Page 101 |
Page 102 |
Page 103 |
Page 104 |
Page 105 |
Page 106 |
Page 107 |
Page 108 |
Page 109 |
Page 110 |
Page 111 |
Page 112 |
Page 113 |
Page 114 |
Page 115 |
Page 116 |
Page 117 |
Page 118 |
Page 119 |
Page 120 |
Page 121 |
Page 122 |
Page 123 |
Page 124 |
Page 125 |
Page 126 |
Page 127 |
Page 128 |
Page 129 |
Page 130 |
Page 131 |
Page 132 |
Page 133 |
Page 134 |
Page 135 |
Page 136 |
Page 137 |
Page 138 |
Page 139 |
Page 140 |
Page 141 |
Page 142 |
Page 143 |
Page 144 |
Page 145 |
Page 146 |
Page 147 |
Page 148 |
Page 149 |
Page 150 |
Page 151 |
Page 152 |
Page 153 |
Page 154 |
Page 155 |
Page 156 |
Page 157 |
Page 158 |
Page 159 |
Page 160 |
Page 161 |
Page 162 |
Page 163 |
Page 164
