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首页> 外文期刊>Environmental Management >Understanding Human-Coyote Encounters in Urban Ecosystems Using Citizen Science Data: What Do Socioeconomics Tell Us?
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Understanding Human-Coyote Encounters in Urban Ecosystems Using Citizen Science Data: What Do Socioeconomics Tell Us?

机译：使用公民科学数据了解城市生态系统中的土狼遭遇：社会经济学告诉我们什么？

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The coyote (Canis latrans) has dramatically expanded its range to include the cities and suburbs of the western US and those of the Eastern Seaboard. Highly adaptable, this newcomer's success causes conflicts with residents, necessitating research to understand the distribution of coyotes in urban landscapes. Citizen science can be a powerful approach toward this aim. However, to date, the few studies that have used publicly reported coyote sighting data have lacked an in-depth consideration of human socioeconomic variables, which we suggest are an important source of overlooked variation in data that describe the simultaneous occurrence of coyotes and humans. We explored the relative importance of socio-economic variables compared to those describing coyote habitat in predicting human-coyote encounters in highly-urbanized Mecklenburg County, North Carolina, USA using 707 public reports of coyote sightings, high-resolution land cover, US Census data, and an autologistic multi-model inference approach. Three of the four socioeconomic variables which we hypothesized would have an important influence on encounter probability, namely building density, household income, and occupation, had effects at least as large as or larger than coyote habitat variables. Our results indicate that the consideration of readily available socioeconomic variables in the analysis of citizen science data improves the prediction of species distributions by providing insight into the effects of important factors for which data are often lacking, such as resource availability for coyotes on private property and observer experience. Managers should take advantage of citizen scientists in human-dominated landscapes to monitor coyotes in order to understand their interactions with humans.
机译：土狼（Canis latrans）的业务范围已大大扩展，涵盖了美国西部和东部沿海地区的城市和郊区。适应性强，这个新人的成功导致与居民的冲突，因此有必要进行研究以了解土狼在城市景观中的分布。公民科学可以是实现这一目标的有力方法。但是，迄今为止，很少有使用公开报道的土狼目击数据的研究缺乏对人类社会经济变量的深入考虑，我们认为这是描述土狼和人类同时发生的数据被忽略变化的重要来源。我们使用707份发现土狼的公开报告，高分辨率土地覆盖，美国人口普查数据，探讨了与描述土狼栖息地的社会经济变量相比，它们在预测高度城市化的梅克伦堡县（美国北卡罗来纳州）的人土狼遭遇中的相对重要性，以及自动逻辑的多模型推理方法。我们假设的四个社会经济变量中的三个会对遭遇概率产生重要影响，即建筑密度，家庭收入和职业，其影响至少与土狼栖息地变量一样大或更大。我们的结果表明，在公民科学数据分析中考虑随时可用的社会经济变量，可以通过洞察经常缺乏数据的重要因素的影响（例如土狼对私有财产的资源可利用性）来改善物种分布的预测。观察者的经验。管理人员应利用人为主导景观中的公民科学家来监视土狼，以了解它们与人的相互作用。

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