However, studies from Beringia (in the high Arctic) suggest that significant levels of parasite interchange occur during intermittent periods of climatic warming when host species from the arctic regions of different continents disperse across the poles and provide new host opportunities for their parasites (Hoberg and Adams, 1992).
If the range size of avian species, orders, and families increases with distance from the equator (Fig. 4.4), might we see a similar effect with the range size of parasites? If so, then this will have caused us to further underestimate the diversity of parasites in the tropics, because the area sampled by tropical parasite taxonomists is tiny. Similarly, do the nested patterns of geographical diversity for the hosts reflect pulses of radiation and speciation between the tropics and temperate zones after past periods of climate change, and would we see similar radiations of diversity if we traced the phylogenies and geographical distributions of avian parasites at different taxonomic levels? Surveys suggest that the diversity of human parasites is significantly higher in the tropics (Low, 1990; Guernier et al., 2004), but as we saw above, this is less clearly the case for fish parasites. If similar latitudinal patterns occur in avian orders and genera, and if parasites are responsible for driving significant components of sexual selection that lead to host speciation, then we might expect complex patterns of geographical variation in parasite diversity at the taxonomic level of host order and family. Unfortunately, the parasite data with which to test these hypotheses are unavailable.
We have used the geographic distribution database for birds described above to evaluate potential impacts of projected environmental change on each of the major continents (Jetz et al., 2007). The Millennium Ecosystem Assessment (MEA) used four quantitative scenarios to examine how land cover would change across the land surface of the Earth over the next 50 and 100 years (Alcamo et al., 2005; Carpenter et al., 2005). The scenarios were driven by quantitative climate models derived from the Intergovernmental Panel on Climate Change (IPCC) and projections of human population growth, wealth, and other socioeconomic parameters across regions (Image_Team, 2001). In these projections, rates of land conversion would be driven either by climate change or by the need for new agriculture land. The four MEA scenarios were defined by whether or not governments take a proactive or reactive response to environmental management, and by whether the world’s nations become more unified and interactive or they become more protectionist and isolated (Cork et al., 2005). Jetz et al. (2007) used the output from the scenarios to examine the