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Characterizing spatial uncertainty when integrating social data in conservation planning.

A M Lechner1, C M Raymond, V M Adams

  • 1The Centre for Environment, University of Tasmania, Private Bag 141, Hobart, TAS, 7001, Australia.

Conservation Biology : the Journal of the Society for Conservation Biology
|November 11, 2014
PubMed
Summary
This summary is machine-generated.

Integrating social and economic data (SRS) into conservation planning is crucial. This study highlights how social survey uncertainty is often ignored spatially, impacting conservation feasibility. A new framework helps manage this uncertainty for better decision-making.

Keywords:
SIG de participación públicacalidad de datos espacialesconservation opportunityconservation planningelicited valuesevaluación de la conservación sistemáticaincertidumbre espacialinvestigación socialoportunidad de conservaciónplaneación de la conservaciónpublic participation GISsocial researchspatial data qualityspatial uncertaintysystematic conservation assessmentvalores obtenidos

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Area of Science:

  • Conservation Science
  • Spatial Planning
  • Social Science Research

Background:

  • Conservation planning increasingly incorporates spatially referenced social (SRS) data to enhance action feasibility.
  • Elicited SRS data, including willingness to pay/sell and social values, are derived from social surveys.
  • Integrating SRS data with biophysical data for conservation planning faces challenges due to uncertainty propagation.

Purpose of the Study:

  • To review the literature on elicited SRS data and its integration into conservation planning.
  • To develop a typology for assessing uncertainty in elicited SRS data.
  • To create a framework for estimating and addressing social survey uncertainty in spatial conservation planning.

Main Methods:

  • Systematic literature review of elicited SRS data in conservation planning.
  • Development of a typology for assessing spatial propagation of social survey uncertainty.
  • Analysis of how scale effects and data quality influence spatial uncertainty.

Main Results:

  • Social survey uncertainty is frequently assessed but often ignored during spatial projection.
  • Uncertainty in elicited SRS data can significantly impact the assessment of conservation action feasibility.
  • A framework was developed to quantify and systematically address social survey uncertainty in conservation analyses.

Conclusions:

  • Accounting for spatial uncertainty in elicited SRS data is critical for robust conservation planning.
  • The developed framework enables researchers and practitioners to better manage uncertainty in SRS data.
  • Incorporating well-characterized uncertainty into decision-theoretic approaches improves conservation decision-making.