Illegal wildlife trafficking poses a significant threat to many species, especially ones that are already endangered or declining. Yet conservationists have struggled to find more effective ways to combat it. Now, in a study published today in Proceedings of the National Academy of Sciences, researchers introduce new methods for identifying the most important countries in the illegal wildlife trade network and deciding which ones to target when attempting to break it down.
The key to combating the trade of any given species, the researchers concluded, is to first identify where the trafficking of the animals is taking place and which countries are the most crucial to holding up those networks.
Lead author Nikkita Patel, a researcher from the University of Pennsylvania School of Veterinary Medicine, and her colleagues used a database called HealthMap Wildlife Trade to figure out where trafficked animals are coming from, where they’re going and who the middlemen are. The database pinpoints illegal wildlife seizures around the world by culling official reports and media stories from the web. “I’m really pleased that [the paper] shows the potential of using data to help us inform our understanding,” says Sarah Olson, associate director of wildlife epidemiology with the Wildlife Conservation Society, who was not affiliated with the study. “I think this approach really gives us a current global snapshot based on the best available data.”
Patel and her colleagues decided to focus their paper on elephants, rhinos and tigers because these were the three animals that popped up most frequently in the database. (They also all happen to be endangered or declining.) Using the information from the database, the researchers were able to construct webs for each animal showing the countries that are involved in the trafficking and which ones trade with each other. They were able to use these webs to identify some of the key players in the trade of each animal — which countries had the highest number of imports, exports or connections to other countries.
But the most important information, according to Patel, is which countries are the most critical in keeping a network going as well as which governments would be the most effective in stopping the trafficking through programs such as educational campaigns.
The researchers experimented with removing different sets of countries from each of the webs to see how doing so would affect the network. Eventually, they were able to pinpoint a set of six countries in each animal’s network that would cause the maximum amount of disruption if taken out. In other words, for each network they identified “which six would cause the most isolated nodes with the remainder of the network that was left,” Patel says. For example, they found that the six nodes capable of best disrupting the rhino network are China, Mozambique, South Africa, Thailand, the United Kingdom and Vietnam.
It’s important to note that these countries are not always the ones with the highest number of imports or exports of a given species. Rather, these are the players that are the most crucial in keeping a trafficking network going — an important distinction for policymakers to consider when targeting their conservation efforts.
Additionally, the researchers conducted analyses to see which countries would have the farthest reach, or the greatest number of connections, if they were to introduce educational campaigns about the wildlife trade, another method used to combat illegal trafficking. Again, they identified a set of six for each network.
While some countries came up noticeably more than others — China, for example, was a top importer and key node for both fragmenting networks and disseminating information for all three animals — Patel cautions that the paper is not meant to encourage finger pointing. Rather than casting blame when such a key player is identified, researchers should take it as an opportunity to explore the cultural, social and economic drivers behind its role in the trade in order to better effect change, she says. And while the paper acknowledges that focusing on transnational trafficking tends to yield “culprit” countries, the authors add that “there are forces at play exploiting wildlife in each country that are not so black and white. Thus, understanding the cultural and economic backdrop within these countries could improve our ability to devise better interventions.”
And the data on the connections between involved countries can be valuable to conservationists looking for new ways to break down trafficking networks, says Olson, with the Wildlife Conservation Society. Understanding which countries are most critical to holding the network together, as well as which countries can spread educational message the farthest, can help policymakers direct their resources to the most important areas.
“You’re going to war against the wildlife trade and you need to have a good [idea] of where the players are and where are the nodes,” she says. “Moving forward, we can track how these nodes change in time, we can improve the data we put into it and we can monitor the impact of different interventions.”
Improving these kinds of interventions can also have public health benefits, in addition to supporting conservation work around the world. All kinds of diseases are spread through the illegal wildlife trade, Patel says. For example, she says, SARS (severe acute respiratory syndrome) has been known to spread through wildlife markets in China. Cutting down on the wildlife trade can help stop diseases from moving around the world, but simply knowing where and how animals are being shipped around the world can also help public health experts track the spread of disease.
In the future, the methods used in this study could be applied to other species — the pangolin is one highly trafficked animal that comes to mind, says Olson. And keeping a close eye on HealthMap data, for any species, can help conservationists and law enforcement officers stay abreast of how trade routes may shift over time.
The paper is among the first studies to take a scientific, analytical approach to understanding the illegal wildlife trade, says Patel, so it’s a good introduction to future data-based efforts toward examining trafficking networks. “There isn’t a lot of analytical work around the wildlife trade, and so I look forward to advancing the science around the illegal wildlife trade,” Patel says.