Understanding the determinants of ranging patterns in species susceptible to habitat fragmentation is fundamental for assessing their long‐term adaptability to an increasingly human‐dominated landscape. The aim of this study was to determine and compare the influence of ground‐based food availability, remotely sensed plant productivity, and indigenous forest use on the ranging patterns of the endangered samango monkey (Cercopithecus albogularis schwarzi). We collected monthly ranging data on two habituated samango monkey groups, from February 2012 to December 2016, from our field site in the Soutpansberg Mountains, South Africa. We used linear mixed models to explore how food availability, plant productivity, and indigenous forest use influenced monthly ranging patterns, while controlling for group size, number of sample days and day length. We found that as more areas of high plant productivity (derived from remotely sensed EVI) were incorporated into the ranging area, both total and core monthly ranging areas decreased. In addition, both total ranging area and mean monthly daily path length decreased as more indigenous forest was incorporated into the ranging area. However, we found no effect of either ground‐based food availability or remotely sensed plant productivity on ranging patterns. Our findings demonstrate the behavioral flexibility in samango monkey ranging, as samangos can utilize matrix habitat during periods of low productivity but are ultimately dependent on access to indigenous forest patches. In addition, we highlight the potential of using remotely sensed areas of high plant productivity to predict ranging patterns in a small ranging, forest‐dwelling guenon, over ground‐based estimates of food availability.

中文翻译：

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南非Soutpansberg山区的粮食供应，植物生产力和原始森林利用对濒临灭绝的芒果猴（Cercopithecus albogularis schwarzi）的放牧行为的影响。

了解易受生境破碎化影响的物种的分布格局的决定因素，对于评估其对日益由人类主导的景观的长期适应性至关重要。这项研究的目的是确定和比较地面粮食供应，遥感植物生产力和土著森林使用对濒临灭绝的芒果猴（Cercopithecus albogularis schwarzi）。从2012年2月到2016年12月，我们从南非Soutpansberg山脉的野外站点收集了两个习惯化的samango猴子组的月度测距数据。我们使用线性混合模型来探索食物供应量，植物生产力和本地森林使用量如何影响月度分布模式，同时控制群体大小，采样天数和天长。我们发现，随着越来越多的植物高产区（源自遥感EVI）被纳入测距区域，总测距和核心月测距区域均下降。此外，随着更多的本地森林被纳入测距区域，总的测距区域和平均每月日路径长度均减少。但是，我们发现地面粮食供应量或遥感植物生产力对测距模式均无影响。我们的研究结果证明了在芒果猴测距中的行为灵活性，因为芒果在生产力低下的时期可以利用基质栖息地，但最终取决于获得本地森林斑块的机会。此外，我们强调了使用遥感的高植物生产力地区来预测地面上对粮食供应量的估计，这是在小范围的森林居住的古农中预测测距模式的潜力。