Data for: Social-ecological predictors of spotted hyena navigation through a shared landscape

Human-wildlife interactions are increasing in severity due to climate change and proliferating urbanization. Regions where human infrastructure and activity are rapidly densifying or newly appearing constitute novel environments in which wildlife must learn to coexist with people, thereby serving as ideal case studies with which to infer future human-wildlife interactions in shared landscapes. As a widely reviled and behaviorally plastic apex predator, the spotted hyena (Crocuta crocuta) is a model species for understanding how large carnivores navigate these human-caused ‘landscapes of fear’ in a changing world. Using high-resolution GPS collar data, we applied resource selection functions and step selection functions to assess spotted hyena landscape navigation and fine-scale movement decisions in relation to social-ecological features in a rapidly developing region comprising two protected areas: Lake Nakuru National Park and Soysambu Conservancy, Kenya. We then used camera trap imagery and Barrier Behavior Analysis (BaBA) to further examine hyena interactions with barriers. Our results show that environmental factors, linear infrastructure, human-carnivore conflict hotspots, and human tolerance were all important predictors for landscape-scale resource selection by hyenas, while human experience elements were less important for fine-scale hyena movement decisions. Hyena selection for these characteristics also changed seasonally and across land management types. Camera traps documented an exceptionally high number of individual spotted hyenas (234) approaching the national park fence at 16 sites during the study period, and BaBA results suggested that hyenas perceive protected area boundaries’ semi-permeable electric fences as risky but may cross them out of necessity. Our findings highlight that the ability of carnivores to flexibly respond within human-caused landscapes of fear may be expressed differently depending on context, scale, and climatic factors. These results also point to the need to incorporate societal factors into multiscale analyses of wildlife movement to effectively plan for human-wildlife coexistence.

Methods
Spotted hyena GPS data were collected from February 2019-December 2021 in Nakuru County, Kenya.

Human perception and experience raster data were derived from participatory mapped data collected in 2018-2019 from residents of 16 sub-villages in Nakuru County, Kenya (see Wilkinson et al. 2021; https://doi.org/10.3389/fcosc.2021.681769).

The "distance to roads" raster data were derived from Open Street Maps and by hand tracing roads prior to rasterization. 

The "distance to boundaries" raster data were derived from in-person mapping via driving and walking the boundaries of the study region's two protected areas: Lake Nakuru National Park and Soysambu Conservancy.

All raster data were derived at 30m spatial resolution.

受气候变化与城市化扩张影响，人类与野生动物的互动强度正不断升级。人类基础设施与活动快速密集化或新兴出现的区域，构成了野生动物必须学会与人类共存的全新环境，也因此成为推断共享景观中未来人类与野生动物互动模式的理想案例研究对象。作为一种广受诟病且行为可塑性极强的顶级捕食者，斑鬣狗（spotted hyena, *Crocuta crocuta*）是探究变化世界中大型食肉动物如何应对人类塑造的“恐惧景观”的模式物种。

本研究依托高分辨率GPS项圈数据，运用资源选择函数（resource selection functions）与步长选择函数（step selection functions），针对肯尼亚境内由纳库鲁湖国家公园与索亚姆博保护区组成的快速发展区域，分析斑鬣狗的景观导航行为与基于社会-生态特征的精细化运动决策。随后，本研究借助相机陷阱（camera trap）影像与屏障行为分析（Barrier Behavior Analysis, BaBA），进一步探究斑鬣狗与各类屏障的互动关系。

研究结果显示，环境因子、线性基础设施、食肉动物与人类冲突热点区域以及人类容忍度，均是斑鬣狗景观尺度资源选择的重要预测因子；而人类感知经验相关要素对斑鬣狗的精细化运动决策影响则相对较弱。斑鬣狗对上述特征的选择偏好还会随季节与土地管理类型的变化而改变。相机陷阱记录到，研究期间共有234只次个体斑鬣狗在16个点位靠近国家公园围栏；屏障行为分析结果显示，斑鬣狗会将保护区边界的半渗透性电网视为风险屏障，但在必要时仍会穿越。

本研究结果表明，食肉动物在人类塑造的恐惧景观中灵活应对的能力，会因场景、尺度与气候因子的不同而呈现差异。同时，本研究结果也提示，若要有效规划人类与野生动物的共存方案，需将社会因子纳入野生动物运动的多尺度分析框架中。

研究方法
斑鬣狗GPS项圈数据采集于2019年2月至2021年12月的肯尼亚纳库鲁郡。

人类感知与经验栅格数据（raster data）源自2018-2019年从肯尼亚纳库鲁郡16个次级村落居民处收集的参与式测绘数据（详见Wilkinson等人2021年研究；https://doi.org/10.3389/fcosc.2021.681769）。

“距道路距离”栅格数据源自开放街道地图（Open Street Maps），并通过人工手绘道路后完成栅格化处理。

“距边界距离”栅格数据通过实地测绘获取：研究人员驾车步行遍历研究区域内两个保护区——纳库鲁湖国家公园与索亚姆博保护区的边界线完成制图。

所有栅格数据的空间分辨率均为30米。