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How Much is Enough? Improving Participatory Mapping Using Area Rarefaction Curves

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  • Jennifer C. Selgrath

    (Hopkins Marine Station, Stanford University; Pacific Grove, CA 93950, USA
    Project Seahorse, Institute for the Oceans and Fisheries, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada)

  • Sarah E. Gergel

    (Forest and Conservation Sciences, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada)

Abstract

Participatory mapping is a valuable approach for documenting the influence of human activities on species, ecosystems, and ecosystem services, as well as the variability of human activities over space and time. This method is particularly valuable in data-poor systems; however, there has never been a systematic approach for identifying the total number of respondents necessary to map the entire spatial extent of a particular human activity. Here, we develop a new technique for identifying sufficient respondent sample sizes for participatory mapping by adapting species rarefaction curves. With a case study from a heavily fished marine ecosystem in the central Philippines, we analyze participatory maps depicting locations of individuals’ fishing grounds across six decades. Within a specified area, we assessed how different sample sizes (i.e. small vs. large numbers of respondents) would influence the estimated extent of fishing for a specified area. The estimated extent of fishing demonstrated asymptotic behavior as after interviewing a sufficiently large number of individuals, additional respondents did not increase the estimated extent. We determined that 120 fishers were necessary to capture 90% of the maximum spatial extent of fishing within our study area from 1990 to 2010, equivalent to 1.1% of male fishers in the region. However, a higher number of elder fishers need to be interviewed to accurately map fishing extent in 1960 to 1980. Participatory maps can provide context for current ecosystem conditions and can support guidelines for management and conservation. Their utility is strengthened by better consideration of the impacts of respondent sample sizes and how this can vary over time for historical assessments.

Suggested Citation

  • Jennifer C. Selgrath & Sarah E. Gergel, 2019. "How Much is Enough? Improving Participatory Mapping Using Area Rarefaction Curves," Land, MDPI, vol. 8(11), pages 1-14, November.
    • Handle: RePEc:gam:jlands:v:8:y:2019:i:11:p:166-:d:284010
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    References listed on IDEAS

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    4. Richards, Daniel R. & Tunçer, Bige, 2018. "Using image recognition to automate assessment of cultural ecosystem services from social media photographs," Ecosystem Services, Elsevier, vol. 31(PC), pages 318-325.
    5. Gonzalez, Rhodora M., 2002. "Joint learning with GIS: multi-actor resource management," Agricultural Systems, Elsevier, vol. 73(1), pages 99-111, July.
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