Characterizing Spatial Uncertainty when Integrating Social Data in Conservation Planning

A Lechner, C Raymond, Vanessa Adams, M Polyakov, A Gordon, Jonathon Rhodes, M Mills, A Stein, C Ives, E Lefroy

    Research output: Contribution to journalArticleResearchpeer-review

    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.
    Original languageEnglish
    Pages (from-to)1497-1511
    Number of pages15
    JournalConservation Biology
    Volume28
    Issue number6
    DOIs
    Publication statusPublished - 2014

    Fingerprint

    conservation planning
    uncertainty
    planning
    data quality
    cultural values
    survey method
    scale effect
    willingness to pay
    social benefit
    typology
    systematic review
    geographic information systems
    spatial distribution
    researchers
    social survey

    Cite this

    Lechner, A., Raymond, C., Adams, V., Polyakov, M., Gordon, A., Rhodes, J., ... Lefroy, E. (2014). Characterizing Spatial Uncertainty when Integrating Social Data in Conservation Planning. Conservation Biology, 28(6), 1497-1511. https://doi.org/10.1111/cobi.12409
    Lechner, A ; Raymond, C ; Adams, Vanessa ; Polyakov, M ; Gordon, A ; Rhodes, Jonathon ; Mills, M ; Stein, A ; Ives, C ; Lefroy, E. / Characterizing Spatial Uncertainty when Integrating Social Data in Conservation Planning. In: Conservation Biology. 2014 ; Vol. 28, No. 6. pp. 1497-1511.
    @article{1859fadd6f69489492978fc358490ddb,
    title = "Characterizing Spatial Uncertainty when Integrating Social Data in Conservation Planning",
    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.",
    keywords = "assessment method, conservation planning, data set, decision analysis, GIS, participatory approach, typology, uncertainty analysis, willingness to pay, consumer, environmental protection, organization and management, spatial analysis, uncertainty, Conservation of Natural Resources, Consumer Participation, Planning Techniques, Spatial Analysis, Uncertainty",
    author = "A Lechner and C Raymond and Vanessa Adams and M Polyakov and A Gordon and Jonathon Rhodes and M Mills and A Stein and C Ives and E Lefroy",
    year = "2014",
    doi = "10.1111/cobi.12409",
    language = "English",
    volume = "28",
    pages = "1497--1511",
    journal = "Conservation Biology",
    issn = "0888-8892",
    publisher = "Blackwell Publishing Inc.",
    number = "6",

    }

    Lechner, A, Raymond, C, Adams, V, Polyakov, M, Gordon, A, Rhodes, J, Mills, M, Stein, A, Ives, C & Lefroy, E 2014, 'Characterizing Spatial Uncertainty when Integrating Social Data in Conservation Planning', Conservation Biology, vol. 28, no. 6, pp. 1497-1511. https://doi.org/10.1111/cobi.12409

    Characterizing Spatial Uncertainty when Integrating Social Data in Conservation Planning. / Lechner, A; Raymond, C; Adams, Vanessa; Polyakov, M; Gordon, A; Rhodes, Jonathon; Mills, M; Stein, A; Ives, C; Lefroy, E.

    In: Conservation Biology, Vol. 28, No. 6, 2014, p. 1497-1511.

    Research output: Contribution to journalArticleResearchpeer-review

    TY - JOUR

    T1 - Characterizing Spatial Uncertainty when Integrating Social Data in Conservation Planning

    AU - Lechner, A

    AU - Raymond, C

    AU - Adams, Vanessa

    AU - Polyakov, M

    AU - Gordon, A

    AU - Rhodes, Jonathon

    AU - Mills, M

    AU - Stein, A

    AU - Ives, C

    AU - Lefroy, E

    PY - 2014

    Y1 - 2014

    N2 - 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.

    AB - 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.

    KW - assessment method

    KW - conservation planning

    KW - data set

    KW - decision analysis

    KW - GIS

    KW - participatory approach

    KW - typology

    KW - uncertainty analysis

    KW - willingness to pay

    KW - consumer

    KW - environmental protection

    KW - organization and management

    KW - spatial analysis

    KW - uncertainty

    KW - Conservation of Natural Resources

    KW - Consumer Participation

    KW - Planning Techniques

    KW - Spatial Analysis

    KW - Uncertainty

    U2 - 10.1111/cobi.12409

    DO - 10.1111/cobi.12409

    M3 - Article

    VL - 28

    SP - 1497

    EP - 1511

    JO - Conservation Biology

    JF - Conservation Biology

    SN - 0888-8892

    IS - 6

    ER -

    Lechner A, Raymond C, Adams V, Polyakov M, Gordon A, Rhodes J et al. Characterizing Spatial Uncertainty when Integrating Social Data in Conservation Planning. Conservation Biology. 2014;28(6):1497-1511. https://doi.org/10.1111/cobi.12409