Using Species Distribution Modeling to Assess Illegal Trade Risk: A Case Study of US Imports of Endangered Mahogany (Swietenia spp.)

Abstract

Illegal logging threatens biodiversity and the global conservation of endangered species. To protect tree species from this threat, governments have enacted legislation against importing illegally sourced plant products. These laws, including the US Lacey Act Amendment of 2008, involve collecting information from importers on the scientific name and country of harvest of their plant products. For many species, a lack of consistent, comprehensive global distribution data makes validating these declarations difficult. I aimed to assist in this analysis by developing species distribution models for the American mahogany species (genus Swietenia). American mahoganies are high-value, high-demand tropical timber species restricted in international trade and known to be illegally logged and traded. I combined presence-absence species occurrence data from government forest surveys and presence-only species occurrence data from citizen science programs and herbarium collections for each Swietenia species. Both data types were modeled as dependent on climate variables, with the presence-only data also modeled as dependent on sampling bias predictors, such as distances to roads or cities. I combined the range maps generated by the models with previously compiled range country lists to create a global distribution for each species. I compared my range map predictions and the range country lists to a set of US import declarations of Swietenia species. Each declared species-country pair was classified as confirmed or unconfirmed based on the range country lists, and suitable or unsuitable based on the model output. By examining the unconfirmed, but climatically suitable, species-country pairs, I identified new range countries for Swietenia species that were poorly documented in the literature. I also found that many unconfirmed but suitable country-species pairs were from countries that did not contain Swietenia but did contain other, closely related species. Many of these species are endangered and/or regulated and produce wood that can be indistinguishable from Swietenia. These results show how species distribution modeling can expand knowledge of a species’ global range and help identify patterns of potential illegal trade. While this study focused on US imports of Swietenia, these methods could be applied to any species or regulatory framework where knowing the country of harvest is necessary.