Nicholson Jeremy M, VAN Manen Frank T
Department of Forestry, Wildlife, and Fisheries, University of Tennessee, Knoxville, Tennessee, USAUS Geological Survey, Southern Appalachian Research Branch, University of Tennessee, Knoxville, Tennessee, USA.
Integr Zool. 2009 Jun;4(2):232-239. doi: 10.1111/j.1749-4877.2009.00159.x.
Determining impacts of anthropogenic landscape changes on wildlife populations is difficult. Besides the challenges of designing field studies to document conditions before and after landscape changes occur, assessment of population responses (e.g. changes in population density) often provide poor inference because of sampling limitations. Estimation of occupancy, however, only requires data on detection or non-detection of a species and might provide better inference. To demonstrate the utility of occupancy models, we used data from an American black bear (Ursus americanus Pallas) population in North Carolina, USA to test our research hypothesis that documented declines in site occupancy of black bears would be greater near a new four-lane highway. We used multi-season occupancy models to estimate site occupancy based on bear visitation to survey sites before and after completion of the new highway and as a function of distance to the highway. Site occupancy declined from 0.81 to 0.35 between the two study phases, but was not a function of distance to the highway. Therefore, the impact of the new highway on occupancy extended to the entire study area. Our case study demonstrates that occupancy models can provide powerful inference regarding the potential impacts of landscape changes on species occupancy. As urban areas and transportation infrastructure are rapidly expanding in developing regions of the world, the need to determine how these changes affect mammal populations and how they might be mitigated increases accordingly. Because field sampling for occupancy models only requires detection data, surveys can be conducted for extensive geographic areas, thus making these surveys particularly applicable to studies of large mammals.
确定人为景观变化对野生动物种群的影响是困难的。除了设计实地研究以记录景观变化前后状况的挑战外,由于抽样限制,对种群反应(如种群密度变化)的评估往往提供的推断不佳。然而,占有率估计仅需要关于物种被检测或未被检测的数据,可能会提供更好的推断。为了证明占有率模型的效用,我们使用了来自美国北卡罗来纳州一个美洲黑熊(Ursus americanus Pallas)种群的数据,来检验我们的研究假设,即记录到的黑熊栖息地占有率下降在一条新建的四车道高速公路附近会更大。我们使用多季节占有率模型,根据黑熊在新高速公路建成前后对调查地点的访问情况以及到高速公路的距离函数来估计栖息地占有率。在两个研究阶段之间,栖息地占有率从0.81下降到0.35,但不是到高速公路距离的函数。因此,新高速公路对占有率的影响扩展到了整个研究区域。我们的案例研究表明,占有率模型可以就景观变化对物种占有率的潜在影响提供有力的推断。随着世界发展中地区城市地区和交通基础设施的迅速扩张,确定这些变化如何影响哺乳动物种群以及如何减轻这些影响的需求相应增加。由于占有率模型的实地抽样仅需要检测数据,因此可以对广泛的地理区域进行调查,从而使这些调查特别适用于大型哺乳动物的研究。