Abstract Human-wildlife conflict has serious conservation consequences, both for populations of wildlife and for the people who live alongside them. Connectivity analyses can incorporate species-specific landscape resistance, and therefore have the potential to be used to understand where wildlife moves and causes conflict with people. We used circuit theory to develop connectivity models for the African savanna elephant in northwestern Botswana based on step-selection functions of movement data for 15 elephants and tested whether areas of high connectivity were correlated with occurrences of crop raiding. We used government records and field assessments of crop-raiding incidents between 2010 and 2016 to quantify conflict, which we predicted would correlate with landscape connectivity. The step-selection model revealed that linear boundaries such as rivers, fences, and dune crests were barriers to movement that impacted connectivity, while high vegetation index values and distance from villages were strong positive predictors of movement. Connectivity values were positively and significantly correlated with frequency of conflict incidents (p

中文翻译：

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使用景观连通性来预测人类与野生动物的冲突

摘要 人与野生动物冲突对野生动物种群和与它们生活在一起的人们都具有严重的保护后果。连通性分析可以结合特定物种的景观阻力，因此有可能用于了解野生动物的移动位置并与人类发生冲突。我们使用电路理论为博茨瓦纳西北部的非洲稀树草原大象开发了基于 15 头大象运动数据的步进选择函数的连通性模型，并测试了高连通性区域是否与作物袭击事件相关。我们使用政府记录和 2010 年至 2016 年间作物袭击事件的实地评估来量化冲突，我们预测这将与景观连通性相关。阶梯选择模型显示，河流、围栏和沙丘顶等线性边界是影响连通性的运动障碍，而高植被指数值和与村庄的距离是运动的强阳性预测因子。连通性值与冲突事件的频率呈显着正相关（p