Spatial analysis to inform the mitigation hierarchy. Issue 6 (9th April 2022)

• Record Type: Journal Article
• Authors: Jones, Kendall R.; von Hase, Amrei; Costa, Hugo M.; Rainey, Hugo; Sidat, Naseeba; Jobson, Benjamin; White, Thomas B.; Grantham, Hedley S.
• Is Part Of: Conservation science and practice. Volume 4:Issue 6(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-04-09
• Subjects: avoidance -- business and biodiversity -- conservation planning -- development -- impact mitigation -- industry -- mitigation hierarchy -- offsets -- spatial planning; Biodiversity conservation -- Periodicals; Biodiversity conservation; Periodicals; 333.951605
• DOI: 10.1111/csp2.12686
• Languages: English
• ISSNs: 2578-4854

Abstract

Abstract: Human activities such as urbanization, infrastructure and agriculture are driving global biodiversity declines. In an attempt to balance economic development goals with biodiversity conservation, governments and industry apply a decision‐making framework known as the mitigation hierarchy, with a goal of achieving no net loss or net gain outcomes for biodiversity. Successful application of the mitigation hierarchy requires biodiversity assessments and spatial planning to inform the design of mitigation policies, identify priority areas for biodiversity conservation and impact avoidance, assess the biodiversity impacts of developments, and identify appropriate mitigation measures including offsetting residual impacts. However, guidance on the necessary data and assessment techniques is often lacking, especially in countries where formal mitigation policies do not exist or are in their infancy. Here, we discuss and demonstrate analyses that can help answer some key questions for formulating effective mitigation policies and applying the mitigation hierarchy. We focus on data and analyses that can inform the avoidance and offset steps in particular, and demonstrate these techniques using a case study in Mozambique. While these analyses will not replace field‐based assessments for projects, they offer rapid, low‐cost approaches to support scoping and development of mitigation policy, planning and decision‐making, especially in relatively data‐poor regions.