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SCIENCE OBSERVER

Tracking the Invaders

A new study uses air travel and climate data to predict the riskiest times for invasions by nonnative species

Anna Lena Phillips

Projected traffic-scaled climatic similarity indexClick to Enlarge ImageIt’s not just ecosystems that feel the effects of invasive species. They’re an increasingly obvious threat to economies as well. A 2005 estimate from David Pimentel and his colleagues at Cornell University put the cost of annual environmental damage and losses due to invasive species at nearly $120 billion—and that was just for the United States. But with limited funds and the involvement of many parties, it can be hard to prevent the introduction of potentially harmful species into new locales, and even harder to restore ecosystems once such species have become established.

Andy Tatem, a professor of geography with the Emerging Pathogens Institute at the University of Florida, believes we need better tools for predicting when and where the risk of species invasion is high. In a paper published online in March in the journal Ecography, he demonstrates just such a tool.

“It’s really about exploring what barriers there are left in the world to the movement of invasive species,” Tatem says. “Up to a hundred years ago, sheer distance would have been the major barrier preventing species movement.”

But the worldwide airline network has changed all that. As international travelers know from strict customs warnings, the likelihood of potentially invasive organisms traveling by air to new destinations can be high. Fruit flies, beetles, moths, mollusks, nematodes, mites, mosquitoes—all have been known to hitch an airplane ride, whether it’s in a suitcase, inside a mango someone has brought home to eat or buzzing about in the flight cabin.

Another important factor is easier to miss: If the places of origin and destination have similar climates, the risk that a climatically sensitive organism will get established in a new place increases.

In a 2007 study, Tatem and epidemiologist Simon I. Hay detailed a set of indices for measurement of these factors. Tatem has now applied them to create predictions about future risk. “This is the first time more contemporary and future projections have been used,” he says. He compiled data on international air-traffic routes, passenger and freight volumes, and yearly and seasonal climatic conditions for each of 3,570 airports and a total of 44,000 flight routes. These current measurements and economic and climate-change projections allowed him to create models for each month from 2007 to 2010.

First, Tatem focused on flight routes. To determine how similar the climatic conditions are at the origin and destination of a given route, he calculated the Euclidean distance between the set of several climatic variables at each location. The climatic Euclidean distance (CED) for a given route and month incorporates data on projected air temperature, total precipitation and relative humidity. A relatively low CED indicates that the regions connected by the route have similar climates during that month; a relatively high CED suggests that the regions will have dissimilar climates. Next, the factor of air-traffic volume was added to produce the CEDt, or traffic-scaled climatic Euclidean distance, for each route.

To identify airports with higher numbers of low-CED routes, the climatic similarity index (CSI) was calculated. For a given airport, this index takes into account the number of other airports from which incoming direct flights arrive. Finally, a traffic-scaled climatic similarity index, CSIt, combines climatic distance, traffic volume and number of low-CED routes to create a relative indicator that identifies airports with high incoming traffic from a greater number of regions with similar climates—and thus higher risk.

For example, according to the indices, June 2010 will have particularly high overall risk. But that’s just “within the limits of the study,” Tatem cautions, highlighting the need for further work. “If we extrapolate to 2011 or 2012, the summertime may be the most risky.”

Stas Burgiel, policy director for the Global Invasive Species Programme, likes the study’s real-world relevance: “This type of work offers tools and analysis with direct application for decision-makers and border control staff, whereas a significant portion of the academic literature on invasive species remains two to three degrees removed from policy relevance.“

Tatem would like to take this even further. “I’d like to make it available as a free online resource and have data sets on specific species that have invaded in the past,” he says. This would allow airport authorities to figure out when their highest-risk times are and even what organisms to watch for.

Even without such a program, though, airport authorities can use inferences from the study to determine when to concentrate staff and resources for the next couple of years. “Governments need good early warning and inspection procedures—ultimately, to save them money,” says Tatem.

Speaking of money, what would he do if he had unlimited funding for this work? “I’d probably try to implement standardized data-gathering techniques at all airports, seaports and border crossings for a range of notifiable species,” he says, “so that we can get an idea of how different transport techniques, traffic levels, times of year and routes translate to numbers of exotic organisms being moved around the world.”

Such extensive study would “give us a solid quantitative base on which to build models.” Economists and ecologists can likely agree that this would be a good thing.—Anna Lena Phillips


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