Soil fungi and trees in changing environments

Soil is a part of the natural world that is both affected by and contributing to climate change. Soil is one of the largest sources of carbon in the world. It is primarily accumulated through plants which fix the carbon from carbon dioxide in the air; soil then absorbs the carbon as plants decay. Additionally, dead leaves and animals are broken down by microbes in the soil, and carbon is accumulated. In the forest ecosystem, tree growth largely depends on the nutrients available in the soil; and the transfer of carbon through roots to the soil regulates ecosystem processes.

This nutrient-carbon exchange is made possible by mycorrhizal fungi and tree mutualism. Two groups of mycorrhizal fungi associations are typically formed in forest trees: arbuscular mycorrhizal (AM) fungi or ectomycorrhizal (ECM) fungi. With collaborators, we find that the EMF-associated trees migrate slower than the AMF-associated trees, in both contemporary and paleo forests (Lankau et al. 2015). We further examine the continental-scale distribution of tree-mycorrhizal associations in relation to soil carbon and nitrogen (Zhu et al. 2018). Our results suggest that AM and ECM trees have differential success along nitrogen fertility gradients that could lead to a self-reinforcing positive plant-soil feedback. Overall, the mycorrhizal guild could be an emerging functional trait that determines the resistance of forests to the changing environment.

Ongoing research focuses on quantifying soil fungal communities’ responses to climate change across North America. To achieve the goal, we first leverage the soil microbial data from the National Ecological Observatory Network (NEON) and build a robust and user-friendly R package, neonMicrobe, to process DNA sequences into ecologically meaningful community data (Qin et al. in press). Meanwhile, we are developing novel models of spatial community-level biodiversity to quantify soil fungal biogeography and predict their responses to climate change. This project is supported by an NSF collaborative grant with the Peay Lab at Stanford.

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