Scientific Data (Jun 2022)

Voluntary consensus based geospatial data standards for the global illegal trade in wild fauna and flora

  • Meredith L. Gore,
  • Lee R. Schwartz,
  • Kofi Amponsah-Mensah,
  • Emily Barbee,
  • Susan Canney,
  • Maria Carbo-Penche,
  • Drew Cronin,
  • Rowan Hilend,
  • Melinda Laituri,
  • David Luna,
  • Faith Maina,
  • Christian Mey,
  • Kathleena Mumford,
  • Robinson Mugo,
  • Redempta Nduguta,
  • Christopher Nyce,
  • John McEvoy,
  • William McShea,
  • Angelo Mandimbihasina,
  • Nick Salafsky,
  • David Smetana,
  • Alexander Tait,
  • Tim Wittig,
  • Dawn Wright,
  • Leah Wanambwa Naess

DOI
https://doi.org/10.1038/s41597-022-01371-w
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 8

Abstract

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Abstract We have more data about wildlife trafficking than ever before, but it remains underutilized for decision-making. Central to effective wildlife trafficking interventions is collection, aggregation, and analysis of data across a range of source, transit, and destination geographies. Many data are geospatial, but these data cannot be effectively accessed or aggregated without appropriate geospatial data standards. Our goal was to create geospatial data standards to help advance efforts to combat wildlife trafficking. We achieved our goal using voluntary, participatory, and engagement-based workshops with diverse and multisectoral stakeholders, online portals, and electronic communication with more than 100 participants on three continents. The standards support data-to-decision efforts in the field, for example indictments of key figures within wildlife trafficking, and disruption of their networks. Geospatial data standards help enable broader utilization of wildlife trafficking data across disciplines and sectors, accelerate aggregation and analysis of data across space and time, advance evidence-based decision making, and reduce wildlife trafficking.