Mobile decision-tree tool technology as a means to detect wildlife crimes and build enforcement networks

Abstract

Accurate field identification of illegally traded wildlife and wildlife products is critically important in the detection and suppression of wildlife crimes. Yet many law enforcement officers and concerned citizens lack access to resources for identifying species and products; this is particularly true for those with no formal expertise in biology, zoology or wildlife training. Emerging digital technologies such as mobile applications may provide important easy-to-use decision-tree style tools for in situ identification. With local government and civil society partners, we are piloting such tools in China and Vietnam to identify whole animals and ivory products; and in the United States developing tools that will be used at U.S. military bases in Afghanistan to identify species from wildlife products. We are coordinating these efforts to minimize redundancy and overhead; we benefit from shared backend support for a photo database and species ID keys that can be translated easily to ensure enough flexibility for targeting needs of the specific country and audience. Planned inclusion of ‘ask the expert’ and geolocation functions will increase accuracy in identification and aid monitoring and research of supply chains. For these emerging technologies to be successful, deployment must be accompanied with on-the-ground trainings to recruit and retain enforcement personnel. The establishment of a supporting network of experts and a user community will be critical for long-term implementation and evaluation of success. Preliminary response from users of a pilot app in China demonstrates high potential for employing these technologies as routine tools to help fight wildlife crimes.