Illegal wildlife trade in Mesoamerica 709
TABLE 1 Knowledge resource nomination worksheet (Okoli & Pawlowski, 2004) showing institutional and geographical representation of experts throughout the horizon scan.
Geographical representation1 Total
Stage 1—Selecting experts Experts identified Experts emailed
Experts to interview
Stage 2—Expert elicitation Interviews
Stage 3—First ranking Online surveys
Stage 4—Online focus group Additional specialists participated
Stage 5—Second ranking Online surveys
Institutional representation2 PA CR NI HN SV GT BZ MX All UNI NGO IGO GVT LAW PRI
80 11 10 6 10 10 10 6 4 13 6 19 9 32 11 3 56 17
8 5 4 5 6 7 5 3 13 4 15 8 19 4 2 0 1 0 4 1 1
16 12
4 1 0 1 0 4 1 1 2 1 0 1 0 3 1 1
4 1 4 1 3 1
8 3 7 3 6 2
11 1 11 2 1 0 1 0 3 1 1 2 1 6 1 2 0 1
1UN/LOCODE Codes: PA, Panama; CR, Costa Rica; NI, Nicaragua; HN, Honduras; SV, El Salvador; GT, Guatemala; BZ, Belize; MX, Mexico. Some experts represented more than one country, but were not double counted. Experts with knowledge of IWT across Mesoamerica, but not based in the region are
recorded under ‘All’. 2UNI, academia; NGO, non-governmental organizations; IGO, intergovernmental organization; GVT, government; LAW, law enforcement; PRI, private. Some experts represented more than one institution, but were not double counted.
scanning as a rapid scoping process can help identify conserva- tion needs and priorities, especially in data-poor contexts, such as in Mesoamerica. In the absence of sufficient data and resources at the required scale and resolution, expert- driven horizon scanning can provide geo-specific and alter- native sources of evidence (Adams et al., 2016). This can act as a first step to help governments, civil society organiza- tions and donors prioritize resources for conservation ac- tion, by better understanding threats to biodiversity. Here we aimed to use horizon scanning to identify emer-
ging trends in threats to wildlife species and opportunities to address illegal wildlife trade inMesoamerica.We explored patterns and trends in poaching, trafficking and consumer demand for products derived from protected fauna and flora. To minimize potential cognitive biases,we adapted ele- ments of the horizon scanning process of Sutherland et al. (2011) with the structured IDEA protocol that Investigates, Discusses, Estimates and Aggregates predictionsmade by ex- perts (Burgman, 2015; Hemming et al., 2017). Given the geo- graphical spread of experts to be consulted, we trialled a re- mote method of group facilitation using an online platform in real time.We conducted this study tomeet a research need identified by theWildlife Conservation Society on the emer- ging threats toMesoamerican species.
Study area
The Mesoamerican region is defined as an economic zone (OECD, 2006) and contains the Mesoamerican Biological Corridor (Gamboa, 2019). It comprises seven Central American countries (Panama, Costa Rica, Nicaragua,
Honduras, El Salvador, Guatemala and Belize) and the nine southern-most states of Mexico (Campeche, Chia- pas, Guerrero, Oaxaca, Puebla, Quintana Roo, Tabasco, Veracruz and Yucatan). Historically, the region has been exploited by North American, Spanish and British enter- prises for its strategic location and natural resources. Of the 6,500 native species assessed in Mesoamerica, .1,500 are threatened or near threatened with extinction (IUCN, 2018), including flagship species such as the jaguar Pan- thera onca, quetzals (birds in the family Trogonidae) and marine turtles.
Methods
Stage 1: selecting experts We used a knowledge resource nomination worksheet (Okoli & Pawlowski, 2004) to document a variety of institutions with exposure to illegal wildlife trade across Mesoamerica, which provided a clear structure to sample experts pur- posively. We conducted our search of potential institutions and experts online in English and Spanish, and included information on experts’ backgrounds and experience. We created a list of experts who had knowledge of illegal wildlife trade in one or more Mesoamerican countries and access to wider (often unpublished) data from their respective institu- tions (White, 2009). We contacted these experts by e-mail, using persuasive writing techniques to improve response rates (Grant, 2013).We used snowball sampling during initial e-mail contact and telephone interviews to recruit additional experts. Eleven experts took part in the full horizon scanning
Oryx, 2021, 55(5), 708–716 © The Author(s), 2020. Published by Cambridge University Press on behalf of Fauna & Flora International doi:10.1017/S0030605319001133
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7 3 0 1
0 1 0 1
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