By Chase Brewster, MESM '20
The International Illegal Wildlife Trade (IWT) is the second largest criminal market in the world. Over 20 billion USD worth of plants and animals are traded annually around the globe for medicine, pets, food, and fashion.[i] Apart from habitat destruction, it is the largest direct threat to species conservation.[ii]
While the IWT poses a major threat to biodiversity, efforts to control it have been unsuccessful. The technology needed to identify poached wildlife is often expensive and impractical, and international coordination and enforcement has been weak. However, the fight against this illegal market has an effective new tool.
According to research recently published in Nature, forensic technologies can be used to accurately distinguish between wild and farm raised animals – a critical resource to combat poaching. In the study, high resolution x-ray fluorescence (XRF) is proposed as a readily available, non-destructive, and cost-effective solution to the shortcomings that traditional forensics has shown when applied to wildlife crime.[iii]
Though XRF technology has been around for decades, its use in the context of wildlife poaching is a novel application. The geographic location and diets of farm raised animals verse their wild counterparts can differ significantly. These differences influence the molecular makeup of these individuals, known as an “elemental signature.” Essentially, they are what they eat. XRF technology can be used to read the elemental signature of a sample – such as the feather of a bird – to determine the diet of the sample animal and give clues to its life history. Because this type of testing can be performed on a living individual with inexpensive and compact tools, XRF will be useful for in-situ testing on wildlife disguised as legal and farm-raised.
The demand for animals on the criminal market has a catastrophic effect on wild populations and biodiversity. Poaching affects the animal during and after capture, weakens the greater ecosystem, reduces genetic diversity critical for conservation, and facilitates the spread of zoonic and agricultural diseases.[iv] In some cases, wildlife poaching is so severe that it threatens the survival of entire species. In the last century, the world’s tiger population has declined 97% due to poaching. In just the last 19 years, the global rhino population has declined by 85%.[v]
At the 1973 Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), 179 countries agreed upon strict international regulations and better global coordination in attempts to curb the IWT. Despite these efforts, corruption and fraud are widespread, and enforcement on the local level is unreliable. According to one assessment published in Conservation Biology, discrepancies in the volume of wildlife trade range from 376% to 5202% greater than that reported by Customs.[vi]
Certified breeding farms were approved under the CITES agreement to help relieve the pressure of illegal poaching on wild populations. But illegal, uncertified breeding farms were established alongside them, sourcing their animals from wild populations and acting as brokers for illegally caught wildlife. Because legally-bred and poached wildlife are undistinguishable to the naked eye, experts have called for the use of forensic tools to identify the origin of these species. Until now, those tools have either been too expensive or too inaccurate to be practical.
While high-resolution x-ray fluorescence is better known for its use in geology, the basic concept of this technology is being applied in a creative new way to identify wildlife crime. Geologists typically use XRF to analyze sediment cores, determining when and where samples originate based on the abundances of certain elements in those samples. Following the same logic, XRF can also provide insights on the diet and geographic origin of wildlife by analyzing the elemental signatures in the animal left behind by certain foods and regions. In combination with machine learning, these signatures can be used to distinguish between animals that have been living in the wild versus those raised on farms – and thus, determine if they are being traded illegally.
For the study, the effectiveness and accuracy of XRF in the context of the wildlife is tested by analyzing quill samples of the short-beaked echidna – a highly desired species in the IWT. The research team was able to correctly determine wild or captive origin for the birds 96% of the time, and the accuracy grew to 100% when multiple scans were taken.[vii] While additional testing is needed, the high accuracy of this initial study is promising for the value that XRF holds as a tool for combating poaching in the near future.
The findings of this study are a significant step in the fight against illegal wildlife trade. While the XRF tool has limitations for species with larger geographic ranges and more diverse diets, it is shown here to be non-destructive and extremely effective in certain situations. And, since hand-held XRF equipment is readily available and relatively inexpensive, the tool has considerable value in the field. In the efforts to curb the IWT - where local enforcement is critical - XRF may prove to be a breakthrough technology.
#poaching #IllegalWildlifeTrade #xrf #conservation
References
[i] Tensen, Laura. “Under What Circumstances Can Wildlife Farming Benefit Species Conservation?” Global Ecology and Conservation, vol. 6, 2016, pp. 286 – 298., doi: 10.1016/j.gecco.2016.03.007.
[ii] “Unsustainable and Illegal Wildlife Trade.” WWF, wwf.panda.org/our_work/wildlife/problems/illegal_trade/.
[iii] Brandis, Kate J., et al. “Novel Detection of Provenance in the Illegal Wildlife Trade Using Elemental Data.” Scientific Reports, vol. 8, no. 1, 2018, doi: 10.1038/s41598-018-33786-0.
[iv] Brandis, Kate J., et al. “Novel Detection of Provenance in the Illegal Wildlife Trade Using Elemental Data.” Scientific Reports, vol. 8, no. 1, 2018, doi: 10.1038/s41598-018-33786-0.
[v] Tensen, Laura. “Under What Circumstances Can Wildlife Farming Benefit Species Conservation?” Global Ecology and Conservation, vol. 6, 2016, pp. 286 – 298., doi: 10.1016/j.gecco.2016.03.007.
[vi] Blundell, Arthur G., and Michael B. Mascia. “Discrepancies in Reported Levels of International Wildlife Trade.” Conservation Biology, vol. 19, no. 6, 2005, pp. 2020 – 2025., doi: 10.1111/j.1523-1739.2005.00253.x.
[vii] Brandis, Kate J., et al. “Novel Detection of Provenance in the Illegal Wildlife Trade Using Elemental Data.” Scientific Reports, vol. 8, no. 1, 2018, doi: 10.1038/s41598-018-33786-0.