Can Microbial Ecology and Mycorrhizal Functioning Inform Climate Change Models?
EMSL Project ID
51006
Abstract
Using archived samples from forest Free Air CO2 Enrichment (FACE) experiments, field measurements from the Marcell Experimental Forest (MEF) and the Spruce and Peatland Response Under Climatic and Environmental Change (SPRUCE) experiment, and the Mycorrhizal Status, Carbon and Nutrient cycling (MySCaN) model, we will identify how the microbial regulation of organic nitrogen (N) availability influences forest responses to climate change.
1. We will assess to what degree elevated CO2 increases organic N depolymerization by proteolytic and chitinolytic bacteria throughout the mineral soil profile. We will use extracellular enzyme assays, qPCR, and tag sequencing of bacterial protease and chitinase genes in archived soil samples from the Duke Forest and ORNL FACE experiments. (Note: archived samples from Rhinelander FACE are not available; Mark E. Kubiske, U.S. Forest Service, Northern Research Station, personal communication).
2. We will estimate the source and quantify the use of organic N among ectomycorrhizal taxa by combining existing stable isotope data from the Duke Forest FACE experiment, additional analyses of 13C, 14C, and 15N, and a fungal culture experiment with 15N- and 13C-labeled amino acids. For example, 14C on carbohydrate and protein fractions in fungi can partition protein sources between current-year plant photosynthate and soil organic nitrogen; in FACE sites, similar analyses can use both 14C and 13C. Both natural abundance and tracer 15N, 13C, and 14C levels can provide additional information on organic N use, the recalcitrance of the assimilated N, and the depth of N sources.
3. We will further develop and validate a new model that incorporates organic nitrogen use and mycorrhizal fungi (MySCaN). We will use existing data to: a) optimize parameter choices, b) validate or modify the relationships used to govern C and N transfer between plants and mycorrhizal fungi, and c) test whether the model predicts similar patterns to those seen in previous FACE studies. To test model performance and our interpretations of isotopic patterns, output from the model will then be used to run the NESIS model, which will predict isotopic signatures in Duke Forest and ORNL FACE studies. NESIS will be modified to include 14C fluxes. These models will be used to gain insights into: 1) the interactions among bacteria, free- living fungi, and mycorrhizal fungi, and 2) the relative importance of mycorrhizal uptake of organic N of variable recalcitrance under different climate change scenarios.
Project Details
Start Date
2019-07-02
End Date
2020-03-20
Status
Closed
Released Data Link
Team
Principal Investigator
Team Members