Characterizing spatial uncertainty when integrating social data in conservation planning

Lechner, A, Raymond, C, Adams, V, Polyakov, M, Gordon, A, Rhodes, J, Mills, M, Stein, A, Ives, C and Lefroy, E 2014, 'Characterizing spatial uncertainty when integrating social data in conservation planning', Conservation Biology, vol. 28, no. 6, pp. 1497-1511.


Document type: Journal Article
Collection: Journal Articles

Title Characterizing spatial uncertainty when integrating social data in conservation planning
Author(s) Lechner, A
Raymond, C
Adams, V
Polyakov, M
Gordon, A
Rhodes, J
Mills, M
Stein, A
Ives, C
Lefroy, E
Year 2014
Journal name Conservation Biology
Volume number 28
Issue number 6
Start page 1497
End page 1511
Total pages 15
Publisher Wiley-Blackwell Publishing, Inc
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 and may 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.
Subject Conservation and Biodiversity
Environmental Management
Geospatial Information Systems
Keyword(s) Conservation opportunity
Conservation planning
Elicited values
Public participation GIS
Social research
Spatial data quality
Spatial uncertainty
Systematic conservation assessment
DOI - identifier 10.1111/cobi.12409
Copyright notice © 2014 Society for Conservation Biology
ISSN 0888-8892
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