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Ecological forecasting: predicting responses of coastal species to climate changeBrian Helmuth, David Wethey, Jerry Hilbish, Sally Woodin, Venkat Lakshmi, and Helen Power University of South Carolina, Departments of Biological Sciences and Geological Sciences |
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Funded By: NASA Ecological Forecasting Program (Helmuth, P.I.) and NOAA Ecofore Program (Wethey, P.I.) |
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Background: There is now consensus among the scientific community that the Earth’s climate is changing, and that these alterations to our climate are due in large part to human activities resulting from the release of greenhouse gases. A 2004 review (published in Science) of all 928 refereed journal articles with the key words “climate change” found that not one peer-reviewed paper presented evidence that disagreed with the position that “ human activities.. are modifying the concentration of atmospheric constituents… that absorb or scatter radiant energy…” and that “most of the observed warming over the last 50 years is likely to have been due to increase in greenhouse gas concentrations” (Oreskes 2004). Reversing greenhouse gas emissions is thus of paramount importance. However, even if such reversals are realized, damage to ecosystems is still expected to occur, and in many cases is already being observed (Parmesan and Galbraith 2004). For example, over 25% of the world’s reefs have been permanently damaged due to the impacts of climate change (Hughes et al 2003). Ecological Forecasting: The field of ecological forecasting recognizes that while solutions to the causes of climate change are being sought (namely greenhouse gas emissions), some effort must concomitantly be sought to identify and mitigate the worst-hit areas affected by climate change. By explicitly identifying those target areas where global climate change is most likely to cause damage, it allows biologists and resource managers to perform a sort of “ecological triage,” effectively spending effort and resources where they are most sorely needed. For example, consider a marine parks manager who is tasked with the well-being of 5 reserves, but who has the manpower to realistically protect only one of those areas from point source pollution. Where should the manager expend his or her effort? We know from experience that pollution stress interacts with temperature stress to push species over their physiological “edge” much in the same way that a person is more susceptible to infection and disease when infected with cancer or other illness. Ideally, the manager does not want to throw money at a site mitigating pollution where, despite the managers best efforts, the animals will die due to climate change within the next few years anyways. Conversely, the money is probably not best spent at a site where animals are robust enough to withstand some insult. However, if we can identify the sites where animals are closest to their “danger zone” we can perhaps prevent them from being pushed over their limits. Consider an alternative scenario, where animals on a large section of beach are found dead on a hot sunny day, next to a large power plant. What killed them? Was it the power plant? Can we develop a technique to determine what the likelihood is that it was climate change that killed them versus something that the power plant did? The ecological forecasting approach ties-in well with the concept of “ecosystem services” (see below) which posits that the environment provides crucial services for society (such as flood protection, water filtration), and that once these services disappear, humans are often forced to replace them at significant cost. |
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| Our Research: Our project addresses the question of, how hot do animals get in nature? While seemingly simple, patterns of temperature in nature are surprisingly complex. Just as a parking lot heats far above the temperature of the surrounding air on a hot sunny day, so do the temperatures of most plants and animals. Moreover, characteristics of the animal such as its color and shape drive temperature so that two organisms sitting side by side can have very different temperatures. See for example the infrared picture of a starfish on top of a mussel. Both are exposed to identical climates, yet each has a very different temperature. We use sophisticated computer models that take inputs from satellites, weather stations, and weather buoys to make “weather predictions” of animal temperatures in coastal environments. | |||||||||||||
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We focus on these animals because they, like coral reefs, are thought to be "early warning systems" for the effects of climate change. In fact, we have already observed die-offs in several parts of the U.S., and in sites where we have predicted such events to occur. These same approaches, however, should be applicable to other ecosystems. Our target users are the resource managers of the National Estuarine Research Reserve Networks, and we are developing software tools to enable them to make predictions of the effects of climate on animals within the reserve network. Ecosystem Services: A recent analysis performed by over 1300 international scientists and summarized in the Millennium Ecosystem Assessment found that significant business opportunities arise when the environment is viewed as a capital asset. Significantly, a report entitled Ecosystems and Human Well Being: Opportunities and Challenges for Business and Industry, co-chaired by Steve Percy, former CEO of BP America, came to the following conclusions:
Literature Cited: Hughes, T. P., A. H. Baird, D. R. Bellwood, M. Card, S. R. Connolly, C. Folke, R. Grosberg, O. Hoegh-Guldberg, J. B. C. Jackson, J. Kleypas, J. M. Lough, P. Marshall, M. Nyström, S. R. Palumbi, J. M. Pandolfi, B. Rosen, and J. Roughgarden. 2003. Climate change, human impacts, and the resilience of coral reefs. Science 301:929-933. Oreskes, N. 2004. The scientific consensus on climate change. Science 306:1686. Parmesan, C., and H. Galbraith. 2004. Observed impacts of global climate change in the U.S. Pew Center on Global Climate Change. |
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