That title might well apply to the problem, dominating the news and presidential debates these days, of illegal immigration into the US. But it appears that the phenomenon applies more broadly, biologically speaking.
Invasion by non-native species is a big and growing problem worldwide, especially in globally connected nations (think zebra mussel, or dutch elm disease). Now China, which is rapidly heading for status as the largest economy on earth, is reaping its share of this dubious distinction. Indeed the 11 most serious invasive species in China are costing its economy almost 7 billion US dollars a year. Part of this of course comes from the increased trade and international travel that has accompanied its breakneck development in the last three decades.
But a new analysis by Lin et al in PLoS One of the rapidly developing Chinese colossus finds that the prevalence of invasive species is surprisingly well predicted by a combination of economic development and climatic factors, which together explain roughly 70% of geographic variation in invasions within the country. Interestingly, within-country economic factors proved to be equally or more important in determining the occurrence of invasive species than climate. International travel and trade, which are widely believed to be the big factors driving invasion, turned out be less significant predictors.
The rapid increase in introduced invasive species in China since the 1970s coincided with a sharp upturn in economic growth (GDP, see Figure 1). Moreover, the aliens were found primarily in the more economically developed provinces of southern and coastal eastern China. Using Principal Factor Analysis, the authors found by that about half the variation in invasion prevalence could be attritbuted to economic factors, primarily residential construction and GDP, but also human population density, industry, freight and passenger traffic, investment in capital construction, and length of transportation routes. Another large chunk of the variance was attributed to climatic variation, specifically mean annual and mean winter temperatures, and precipitation. A possible alternative explanation for the results, that more intense scientific study in developed areas had identified more invasive species there, was tested statistically and discounted
The authors summarize the biological mechanisms for the phenomenon thus:
“Biological invasion is a battle between the ability of the alien species to dominate its new environment and the resistance of the local community. Climatic conditions determine the potential geographic range where the alien species could establish its populations. Increase in economic development enhances international trade and travel that transport alien species to new areas. Economic development also brings about road and building constructions that in turn modifies natural habitats, enhances the spread of invasive species, intensifies the loss of resistance from the local communities to the invasions, thus accelerating biological invasions. Biology, meteorology and economy are the three legs of the tripod that constitutes the basis for understanding and predicting biological invasions.”
They also note that the great majority of previous academic research on biological invasions has focused on the biological traits of species and the recipient communities that might favor invasion. The message here is that these ecological factors operate under the influence of massive human impacts, which in China (and likely elsewhere as well), dominate the process of invasion.
What are the practical implications? First, the authors note that the single strongest predictor of invasion in this study was residential construction. They suggest that more ecologically informed city planning needs to be implemented now, as well as policies to minimize future habitat dislocation from deforestation. Other recommendations include beefing up supervision, inspection, and quarantine procedures for both import/export and inter-province freight transportation.
Original source (free access):