Department of Environmental Conservation, University of Massachusetts at Amherst, 210 Holdsworth Hall, MA, 01003-9285 USA; Biodiversity Research Institute, 276 Canco Road, Portland, ME, 04103, USA.
Department of Environmental Conservation, University of Massachusetts at Amherst, 210 Holdsworth Hall, MA, 01003-9285 USA.
J Environ Manage. 2019 Apr 1;235:77-83. doi: 10.1016/j.jenvman.2019.01.022. Epub 2019 Jan 21.
Governments and developers are pursuing offshore wind energy to address climate change, but multiple wind farms may cumulatively affect wildlife populations. Assessments of cumulative effects must first calculate the cumulative exposure of a wildlife population to a hazard and then estimate how the exposure will affect the population. Our research responds to the first need by developing a model designed to assess how different wind farm siting scenarios cumulatively expose wildlife. The model assesses cumulative exposure by identifying all locations where development could occur, placing wind farms within this suitability layer, and then overlaying wind engineering and biological data sets. The first model output is a graphical representation of how offshore wind farm siting decisions affect wildlife cumulative exposure. The second output is an index that ranks which offshore wind farm siting decisions will have the greatest influence on wildlife cumulative exposure. Together these outputs provide stakeholders with valuable information that could be used to guide siting and management decisions.
政府和开发商正在寻求开发海上风能以应对气候变化，但多个风电场可能会累积影响野生动物种群。累积效应评估必须首先计算野生动物种群对危险的累积暴露程度，然后估计暴露程度将如何影响种群。我们的研究通过开发一种旨在评估不同风电场选址方案如何累积暴露野生动物的模型来满足这一需求。该模型通过确定所有可能发生开发的地点、在适宜性图层中放置风电场，然后覆盖风工程和生物数据集来评估累积暴露。第一个模型输出是一个图形表示，展示了海上风电场选址决策如何影响野生动物的累积暴露。第二个输出是一个指数，对哪些海上风电场选址决策将对野生动物的累积暴露产生最大影响进行排名。这些输出共同为利益相关者提供了有价值的信息，可用于指导选址和管理决策。
