Département de Biologie and Centre d'Étude de la Forêt, Université Laval, Pavillon Alexandre-Vachon, 1045, avenue de la Médecine, bureau 2050, Québec, Quebec, G1V 0A6, Canada.
Ecol Appl. 2020 Jul;30(5):e02111. doi: 10.1002/eap.2111. Epub 2020 Apr 1.
Crop raiding is an increasing source of human-wildlife conflict that antagonizes humans and can lead to heightened killing of wildlife. Attraction to crops can trigger ecological traps, where animals prefer areas of their range that confer relatively low fitness. Food can be used to draw animals away from problematic areas, but an alternative considered less often is to replace high-quality food with poorer alternatives. In any case, managers often have no means of anticipating by how much such interventions should impact animal use of space. Optimal foraging theory predicts that foragers optimizing their diet should choose food items according to their relative profitability (i.e., digestible energy/ handling time), a theoretical prediction that can orient management actions. Accordingly, we developed an individual-based model (IBM) simulating movement through empirical rules under an optimal foraging framework. Our objective was to quantify the effect size of cultivating alternate crops to reduce crop raiding and the associated human-induced mortality driving an ecological trap for an energy maximizer, plains bison (Bison bison bison). Results showed that almost tripling the area of cultivation of crops of lower profitability (from 24.3% of the bison range outside the protected area in one management scenario to 70.3% in another) only led to a 25% additional decrease in the intensity of crop raiding (from a decrease of 40% in the first scenario to a decrease of 65% in the second). This suggests that localized interventions in the landscape are likely to have a stronger impact in mitigating crop raiding than broad actions ignoring spatial patterns in food distribution. However, we obtained no significant reduction in the number of simulated bison being harvested in the first scenario, and only a small reduction in the second, when the intervention was spatially broad. Our individual-based approach to animal movement informed by optimal foraging demonstrates that linking landscape configuration to mortality rates can help managers anticipate the effectiveness of manipulating food to keep animals away from problematic zones. Yet disarming ecological traps driven by human hunting appears to be a much more challenging undertaking.
作物掠夺是人类与野生动物冲突日益加剧的一个来源,会使人类与野生动物产生对立情绪,并可能导致野生动物被杀戮的数量增加。对作物的吸引力可能引发生态陷阱,动物会偏好其活动范围中那些相对低适应性的区域。可以用食物将动物从有问题的区域引开,但另一种较少被考虑的替代方法是用较差的食物代替高质量的食物。在任何情况下,管理者通常都无法预测这些干预措施应该对动物空间利用产生多大的影响。最优觅食理论预测,优化其饮食的觅食者应该根据食物的相对收益(即可消化能量/处理时间)来选择食物,这一理论预测可以指导管理行动。因此,我们根据最优觅食框架,使用基于个体的模型(IBM)模拟通过经验规则的运动。我们的目标是量化种植替代作物以减少作物掠夺的效应大小,以及减少与能量最大化相关的人类诱导死亡率,这种死亡率为平原野牛(Bison bison bison)带来了生态陷阱。结果表明,将低收益作物的种植面积几乎增加两倍(从一个管理方案中保护区外野牛活动范围的 24.3%增加到另一个方案中的 70.3%),只会导致作物掠夺的强度增加 25%(从第一个方案中的 40%减少到第二个方案中的 65%)。这表明,在景观中进行局部干预可能比忽视食物分布空间模式的广泛行动更能有效减轻作物掠夺。然而,当干预措施具有空间广泛性时,我们在第一个方案中没有获得被模拟的野牛数量显著减少,而在第二个方案中仅获得了少量减少。我们基于最优觅食的动物运动的个体方法表明,将景观配置与死亡率联系起来可以帮助管理者预测操纵食物以防止动物进入问题区域的效果。然而,消除由人类狩猎驱动的生态陷阱似乎是一项更具挑战性的任务。