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

Geospatial data has supported design, implementation, and evaluation of interventions in diverse areas including public health, humanitarian relief, human rights documentation, and law enforcement11,12,13,14. We know from prior experience with these and other sectors that successful geospatial data standards need to be useful (i.e., identified by end users as important), usable (i.e., in a format with proper documentation/ metadata that allows for data to be properly ingested in any platform or system being used to manage information), and used (i.e., finds itself to an end user that can apply the knowledge to whatever sector in which they are operating). Geospatial information allows sectors working on IWT from a variety of disciplines to contextualize spatial relationships of crimes. Geospatial information can aid understanding about the spatial mobility of crime(s), offenders, and defenders; and be used to identify crime patterns, such as spatial-temporal clusters of activity. Law enforcement authorities can use such information to allocate resources for interdiction, conservation workers can more effectively target areas of concern for threatened populations, and researchers can more accurately describe wildlife trafficking supply chains and their dynamics. Geospatial information that captures movement along the entire supply chain—in both physical and virtual environments—can aid in determining the optimal location for interdiction activities, justice-oriented interventions, and allocating resources to regions where they are most likely to have an impact. Recording the location of activities surrounding the interdiction of wildlife trafficking can help enable multi-scale analysis of gaps in enforcement efforts and evaluation of wildlife protection and monitoring systems. Outputs could be integrated with other data analysis efforts and inform mechanisms for promoting communication, translation, privacy, and mediation across the knowledge-action boundary. Agencies and others can employ enterprise-specific privacy protection measures when sharing; enabling effective data collection in the first place is the paramount task. Pendleton et al.8. acknowledged the failure to move data from producers to users can lead to “data waste,” or lost opportunities to inform science and decision-making as well as result in costly replication of data collection efforts1. The data standards and dictionary presented here incorporate multiple data purviews and thus help converge scientific disciplines for decision-making, such as conservation, law enforcement and criminal justice, and supply chain sectors (Table 2). These sectors are not the only ones with relevance to IWT, but they were repeatedly mentioned by participants during the derivation of standards. Geospatial data in different formats (e.g., point, line, polygon) and at different scales can build understanding about, for example, wildlife species and populations of interest, targets of harm, and market prices. Organizations, agencies, researchers, and other sectors are expected to add additional fields and attributes depending on their mission and operational strategy, including for example, market characteristics, police reports and/or statistics, and location where sentencing occurs, but a foundational minimum enables cross-functional and cross-organizational compatibility and support.

Table 2 An example from United States District Court Southern District of New York, Sealed Indictment 19 CRIM 338 (United States of America v. Moazu Kromah, Amara Cherif, Mansur Surur, Abdi Ahmed).

Geospatial data standards are important for combating IWT because the crime is intimately linked across space and time: knowledge about crime patterns and trends is required for crime prevention and response, including non-law enforcement-oriented response. Problem definition and solutions are fundamentally conceptualized in terms of location-based information: source (i.e., where does the killing and/or taking of wildlife take place?), transit (i.e., where, and how the wildlife and wildlife products are being moved along/through to market?), and destination (i.e., where are the wildlife consumers and where is wildlife marketed?). Geospatial data standards are a first step in integrating data that can be better linked to, for example, existing apps for mobile data collection or visualizations mapped results. The utility of tracking data across space and time is exemplified by research detailing illegal elephant ivory sampled from commercial markets and seized by authorities in airports9,15. The ability to apply a common set of geospatial information to link illegal wildlife products removed from various stages of the illicit supply chain back to the source location has enabled identification of crime hotspots, development of criminal profiles, indictments of alleged offenders, prosecutions in court, and indictments and convictions of kingpins (e.g., Table 1).

Standards in this data dictionary portend broad utility in support of investments to combat IWT, especially if standards can be mainstreamed. Substantial investments to combat IWT include capacity building activities, allocation of new financial and personnel resources, scientific discovery, regulatory changes, and public engagement activities. Monitoring these investments empowers stakeholders combating wildlife trafficking to evaluate progress and make evidence-based adjustments. How and whether use of standards and the relationship of data to confidentiality and access concerns is up to the community of practitioners, scientists, law enforcement authorities, and policymakers. The strength of geospatial data standards crimes not only from its content and structure but from the process by which it was created, in this case participatory, multisectoral, consensus-based, iterative, and interdisciplinary16. Local community stakeholders and expert practitioners were continuously engaged. There is intrinsic value in dissolving dataset boundaries that artificially constrict the necessary flow of information. For example, standardized geospatial data can foster transboundary engagement across geographies, institutions, and disciplines. As data availability increases the initial standard goal of interoperability may be broadened; the dictionary is publicly accessible online and any group can adapt it to their needs. The demonstrated value of geospatial data standards from other contexts (e.g., covid-1917, environmental models18 suggests the combating wildlife trafficking standards presented herein could support a similar positive impact, if the standards were adopted by as broad a range of stakeholders as possible. These could include, for example, non-governmental organizations with field operations (e.g., Chengeta Wildlife), inter-governmental organizations coordinating across geopolitical regions (e.g., Lusaka Agreement Task Force), and law enforcement authorities (e.g., Michigan Department of Natural Resources Office of Law Enforcement).