A new study calls for improvements in the way scientists predict the impact of climate change on plants and wildlife.
A study recently published in the journal Science assessed the current methods for predicting the impacts of climate change on wildlife and plants. The researchers found that current projections are based on broad statistical correlations and fail to produce meaningful data that will inform effective decision-making and policy development.
Some of the factors not adequately accounted for include species’ reproductive success, survival, competition, mobility, and ability to adapt and evolve.
For example, some species of frog are able to move along miles of terrain and remain in a habitable environment but other species may only be capable of moving a few metres over generations.
Without these kinds of considerations, the extent of the effects of climate change on wildlife cannot be well understood.
However, a new sophisticated computer software called RangeShifter, developed by Professor Justin Travis, Dr. Greta Bocedi and Dr. Steve Palmer from the University of Aberdeen, aims to fill in some of these blanks and support conservation efforts around the world.
Developing approaches for providing more accurate forecasts is essential for global conservation efforts.
Professor Travis said:
The Intergovernmental Panel on Climate Change has overseen vast improvements in climate change forecasting by adopting more advanced tools and applying detailed information that is gathered, coordinated and shared on a global scale, and this is the approach that we require for making more realistic forecasts of ecological responses to climate change.
The researchers advocate the establishment of “Centers for Ecological Forecasting,” pointing out that having more models to compare with existing ones would help scientists predict how climate change affects wildlife and plants. The key constituents of these centers would be ecological modelers, computer programmers, and teams of field ecologists and evolutionary biologists, all working together to better understand the state of the natural world.
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