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Characterizing spatial uncertainty when integrating social data in conservation planning

Citation

Lechner, AM and Raymond, CM and Adams, VM and Polyakov, M and Gordon, A and Rhodes, JR and Mills, M and Stein, A and Ives, CD and Lefroy, EC, Characterizing spatial uncertainty when integrating social data in conservation planning, Conservation Biology, 28, (6) pp. 1497-1511. ISSN 0888-8892 (2014) [Refereed Article]

Copyright Statement

2014 Society for Conservation Biology

DOI: doi:10.1111/cobi.12409

Abstract

Recent conservation planning studies have presented approaches for integrating spatially referenced social (SRS) data with a view to improving the feasibility of conservation action. We reviewed the growing conservation literature on SRS data, focusing on elicited or stated preferences derived through social survey methods such as choice experiments and public participation geographic information systems. Elicited SRS data includes the spatial distribution of willingness to sell, willingness to pay, willingness to act, and assessments of social and cultural values. We developed a typology for assessing elicited SRS data uncertainty which describes how social survey uncertainty propagates when projected spatially and the importance of accounting for spatial uncertainty such as scale effects and data quality. These uncertainties will propagate when elicited SRS data is integrated with biophysical data for conservation planning andmay have important consequences for assessing the feasibility of conservation actions. To explore this issue further, we conducted a systematic review of the elicited SRS data literature. We found that social survey uncertainty was commonly tested for, but that these uncertainties were ignored when projected spatially. Based on these results we developed a framework which will help researchers and practitioners estimate social survey uncertainty and use these quantitative estimates to systematically address uncertainty within an analysis. This is important when using SRS data in conservation applications because decisions need to be made irrespective of data quality and well characterized uncertainty can be incorporated into decision theoretic approaches.

Item Details

Item Type:Refereed Article
Keywords:conservation opportunity, conservation planning, elicited values, public participation GIS, social research, spatial data quality, spatial uncertainty, systematic conservation assessment
Research Division:Environmental Sciences
Research Group:Environmental Science and Management
Research Field:Conservation and Biodiversity
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Environmental Sciences
Author:Lechner, AM (Dr Alex Lechner)
Author:Raymond, CM (Dr Chris Raymond)
Author:Lefroy, EC (Professor Ted Lefroy)
ID Code:98570
Year Published:2014
Web of Science® Times Cited:14
Deposited By:Geography and Environmental Studies
Deposited On:2015-02-19
Last Modified:2017-10-31
Downloads:0

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