A study led by the Center for Ecological Research and Forest Applications (CREAF) determines that the forests with the highest risk of dying due to drought are located in the mediterranean basinthe south of Australiaand the northwest of the Amazon and of USA. An international team with participation of the Autonomous University of Barcelona (UAB) has published in the magazine ‘Nature Ecology and Evolution’ a new method to characterize which forests in the world are most vulnerable to water deficiency. The system includes physiological data on the strategies of thousands of species to overcome the lack of water, evolutionary and phylogenetic data on how adaptation to drought has evolved, and soil and climate data for each biome in the world.
The most important innovation of this new method is that evaluates the forest as an entire ecosystema set of organisms that respond differently to external conditions, allowing predicting the impacts of climate change on a much larger scale in forests around the world. Thus, the physiological data by species determine that many Mediterranean trees are very well adapted to drought, but the model indicates that these forests have a very high risk of suffering death from drought.
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This is because the method allows you to expand the field of view to determine that the area also contains species very sensitive to drought, episodes that lately have been more recurring and longer. Certain trees have mechanisms to withstand the lack of water because they store it and need little to live, but some are not adapted to drought conditionswhich makes them very vulnerable.
Physiological data like this are key to understanding which forests are most at risk of suffering from water failure and dying from drought, but they have limitations that now included within the new model provide very useful information at a more general level. Thus, the study presents for the first time a global characterization of forest mortality riskalthough it is still necessary to advance more in the system to guarantee good predictions, according to the researchers.