Climate scenarios are the alternative images of how the climate in the future may unfold. The Special Report Emissions Scenarios (SRES) describes four climate scenario âfamiliesâ, each with a divergent future description. Since it is difficult to project far-off future emissions and other human factors that influence climate, scientists use a range of scenarios making various assumptions about economic, social, demographic, technological, and environmental conditions to project future global warming.
Scenarios range from Low emissions (B1, B2: less pronounced future warming than A1 and A2) to High emissions (A1 and A2) in three time slices: â2020sâ (2010-2039), â2050sâ (2040-2069) and â2080sâ (2070-2099). To predict the potential distribution of invasive species under the different climate change scenarios, various modeling algorithms have been used by researchers. Here, the choice of the modeling algorithm plays a critical role in determining the accuracy of the predictions. Most algorithms require both presence and absence data sets. This is difficult to collate because while the presence data can be collected with confidence, the absence data has high inherent uncertainties. Hence, modeling methods that require presence only dataset, and can predict effectively even with limited available data have been used more commonly.
Last date updated on June, 2014