Yamashita Thomas J, Livingston Trinity D, Ryer Kevin W, Young John H, Kline Richard J
School of Earth, Environmental, and Marine Sciences University of Texas Rio Grande Valley Port Isabel TX USA.
Caesar Kleberg Wildlife Research Institute Texas A&M University -Kingsville Kingsville TX USA.
Ecol Evol. 2021 Sep 1;11(19):13305-13320. doi: 10.1002/ece3.8053. eCollection 2021 Oct.
Collisions with vehicles can be a major threat to wildlife populations, so wildlife mitigation structures, including exclusionary fencing and wildlife crossings, are often constructed. To assess mitigation structure effectiveness, it is useful to compare wildlife road mortalities (WRMs) before, during, and after mitigation structure construction; however, differences in survey methodologies may make comparisons of counts impractical. Location-based cluster analyses provide a means to assess how WRM spatial patterns have changed over time. We collected WRM data between 2015 and 2019 on State Highway 100 in Texas, USA. Five wildlife crossings and exclusionary fencing were installed in this area between September 2016 and May 2018 for the endangered ocelot () and other similarly sized mammals. Roads intersecting State Highway 100 were mitigated by gates, wildlife guards, and wing walls. However, these structures may have provided wildlife access to the highway. We combined local hot spot analysis and time series analysis to assess how WRM cluster intensity changed after mitigation structure construction at fine spatial and temporal scales and generalized linear regression to assess how gaps in fencing and land cover were related to WRM cluster intensity in the before, during, and after construction periods. Overall, WRMs/survey day decreased after mitigation structure construction and most hot spots occurred where there were more fence gaps, and, while cluster intensity increased in a few locations, these were not at fence gaps. Cluster intensity of WRMs increased when nearer to fence gaps in naturally vegetated areas, especially forested areas, and decreased nearer to fence gaps in areas with less natural vegetation. We recommend that if fence gaps are necessary in forested areas, less permeable mitigation structures, such as gates, should be used. Local hot spot analysis, coupled with time series and regression techniques, can effectively assess how WRM clustering changes over time.
与车辆的碰撞可能对野生动物种群构成重大威胁，因此通常会建造野生动物缓解设施，包括隔离围栏和野生动物通道。为了评估缓解设施的有效性，比较缓解设施建设前、建设期间和建设后的野生动物道路死亡数量（WRMs）是很有用的；然而，调查方法的差异可能使数量比较不切实际。基于位置的聚类分析提供了一种评估WRM空间模式随时间如何变化的方法。我们于2015年至2019年在美国得克萨斯州100号州际公路上收集了WRM数据。2016年9月至2018年5月期间，在该地区安装了五个野生动物通道和隔离围栏，以保护濒危豹猫（）和其他体型相近的哺乳动物。与100号州际公路相交的道路通过大门、野生动物防护装置和翼墙进行了缓解处理。然而，这些设施可能为野生动物提供了进入高速公路的通道。我们结合局部热点分析和时间序列分析，在精细的空间和时间尺度上评估缓解设施建设后WRM聚类强度的变化，并使用广义线性回归来评估围栏缺口和土地覆盖与建设前、建设期间和建设后时期WRM聚类强度之间的关系。总体而言，缓解设施建设后WRMs/调查日减少，大多数热点出现在围栏缺口较多的地方，虽然在一些地点聚类强度增加了，但这些地点并非在围栏缺口处。在自然植被覆盖区域，尤其是森林区域，靠近围栏缺口时WRMs的聚类强度增加，而在自然植被较少的区域，靠近围栏缺口时聚类强度降低。我们建议，如果在森林区域需要设置围栏缺口，应使用渗透性较小的缓解设施，如大门。局部热点分析与时间序列和回归技术相结合，可以有效地评估WRM聚类随时间的变化。
