When you walk through a forest, you are surrounded by carbon. Every branch and every leaf, every inch of trunk and every tendril of unseen root contains carbon pulled from the atmosphere through photosynthesis. And as long as it stays stored away inside that forest, it’s not contributing to the rising concentrations of carbon dioxide that cause climate change. So it’s only natural that we might want to use forests’ carbon-storage superpower as a potential climate solution in addition to reducing human greenhouse gas emissions.
But climate change itself might compromise how permanently forests are able to store carbon and keep it out of the air, according to a new study led by University of Utah researchers. A study of how different regions and tree species will respond to climate change finds a wide range of estimates of how much carbon forests in different regions might gain or lose as the climate warms. Importantly, the researchers found, the regions most at risk to lose forest carbon through fire, climate stress or insect damage are those regions where many forest carbon offset projects have been set up.
“This tells us there’s a really urgent need to update these carbon offsets protocols and policies with the best available science of climate risks to U.S. forests,” said William Anderegg, study senior author and director of the U’s Wilkes Center for Climate Science and Policy.
The study is published in Nature Geoscience. Find an interactive tool showing carbon storage potential in forests in the U.S. here.
A Multi-Perspective Modeling Approach
For this study, the researchers were interested in forecasting changes in the amount of aboveground carbon storage in forests of different regions in the United States. Aboveground carbon refers to any living parts of a tree that are above ground, including wood and leaves or needles.
Scientists can look at the future of forests under climate change in a few different ways. They can look at historical and future projections of climate, or look at datasets from long-term forest plots. They can also use machine learning to identify which climate niches tree species most prefer. Or they …
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