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.

中文翻译：

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生态陷阱中的农作物入侵者：基于个体的最佳觅食模型可量化替代农作物的影响。

作物抢劫是人类与野生生物冲突的日益严重的根源，它使人类感到反感，并可能导致对野生生物的更多杀害。对农作物的吸引力会触发生态陷阱，在这种生态陷阱中，动物偏爱其适应能力相对较低的区域。食物可以用来将动物带离有问题的地区，但很少有人考虑的替代方法是用较差的替代品代替高质量的食物。在任何情况下，管理人员通常都无法预料此类干预将对动物对空间的利用产生多大影响。最佳觅食理论预测，优化饮食的觅食者应根据其相对获利能力（即可消化的能量/处理时间）选择食物，这是一种可以指导管理行动的理论预测。因此，我们开发了基于个人的模型（IBM），该模型在最佳觅食框架下通过经验规则模拟运动。我们的目标是量化耕种替代作物以减少作物突袭的影响规模，以及相关的人为导致的死亡率，从而驱动能源陷阱，平原野牛的生态陷阱（野牛野牛野牛）。结果表明，利润较低的农作物的种植面积几乎增加了两倍（从一种管理方案中的保护区域外的野牛范围占24.3％到另一种管理方案中的70.3％），仅使作物突袭强度进一步降低了25％ （从第一种情况下的减少40％到第二种情况下的减少65％）。这表明，与忽略粮食分配空间格局的广泛行动相比，在景观中进行局部干预可能对减轻农作物袭击的影响更大。但是，在第一种情况下，当干预在空间上很宽泛时，没有获得明显减少的模拟野牛数量的减少，而在第二种情况下，只有少量减少。我们以最佳觅食为基础的基于个体的动物运动方法表明，将景观配置与死亡率联系起来可以帮助管理人员预测处理食物的有效性，以使动物远离有问题的地区。然而，解除人类狩猎驱动的生态陷阱似乎是一项更具挑战性的工作。