Literature DB >> 30677658

Assessing the cumulative exposure of wildlife to offshore wind energy development.

M Wing Goodale1, Anita Milman2.   

Abstract

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.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Keywords:  Adverse effects; Cumulative effects; Exposure; Mitigation; Offshore wind farm; Wildlife

Mesh:

Year:  2019        PMID: 30677658     DOI: 10.1016/j.jenvman.2019.01.022

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  1 in total

1.  Multi-use of the sea: A wide array of opportunities from site-specific cases across Europe.

Authors:  Martina Bocci; Stephen Joseph Sangiuliano; Alessandro Sarretta; Joseph Onwona Ansong; Bruce Buchanan; Andronikos Kafas; Mario Caña-Varona; Vincent Onyango; Eva Papaioannou; Emiliano Ramieri; Angela Schultz-Zehden; Maximilian Felix Schupp; Vassiliki Vassilopoulou; Marta Vergílio
Journal:  PLoS One       Date:  2019-04-11       Impact factor: 3.240

  1 in total

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