We use a combination of laboratory and field measurements, and multi-scale modeling to further understanding of how microbial metabolism shapes carbon, nitrogen, and phosphorus biogeochemistry within terrestrial and aquatic ecosystems.
Mountainous watersheds
Nitrogen cycling within a mountainous watershed: Snowmelt dominated mountainous watersheds are characterized by substantial heterogeneity that determine hydrological flow paths and water residence times through distinct catchment subsystems. Despite advances in understanding the spatial and temporal drivers of biogeochemical cycling within snowmelt-dominated ecosystems, knowledge gaps remain. This project is attempting to develop an improved understanding of how these systems cycle nitrogen, which is a major limiting element within the East River (CO) catchment. We’re using a combination of field and lab measurements and watershed-scale modeling to identify hot spots and hot moments of nitrogen cycling, and to quantify the input, transformation, and export of different organic and inorganic nitrogen species around the catchment across different seasons.
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High-Latitude ecosystems
Ecosystem response to disturbance: Climate warming is occurring fastest at high-latitudes. Understanding, the impact of chronic climate change, and related increase in wildfire occurrence, is critical for understanding future carbon-climate feedbacks. Specific questions we are addressing include,
1. How does the carbon-cycle response to climate-perturbation differ from short-term warming experiments relative to long-term climate change? See here for more information on this study.
2. What are the long-term ramifications of abrupt wildfire disturbance against the backdrop of ongoing climate change across a centennial timescale?
3. What role does the belowground microbial community play in enabling the recovery of the aboveground community?
We address these questions using a well-tested, mechanistic model (ecosys, eg., Grant et al., 2017), which simulates the interdependent physical, hydrological, and biological processes that govern ecosystem responses to perturbation. This model also includes a mechanistic treatment of carbon, water, nitrogen, and phosphorus dynamics within soils, microbes (bacterial, archaea, and fungi), and plants. This work is mainly funded by DOE’s Next Generation Ecosystem Experiment located in Alaska (NGEE-Arctic).
Microbial trait-based models: Microbes play critical roles in biogeochemical cycling, but their diversity and metabolic flexibility are poorly captured by most models. Furthermore, the traits underpinning microbial response to environmental fluctuations are still the subject of debate. Here we identified a number of traits that determine microbial fitness over a range of environmental conditions and evaluate community emergence and nitrous oxide production.
1. How does the carbon-cycle response to climate-perturbation differ from short-term warming experiments relative to long-term climate change? See here for more information on this study.
2. What are the long-term ramifications of abrupt wildfire disturbance against the backdrop of ongoing climate change across a centennial timescale?
3. What role does the belowground microbial community play in enabling the recovery of the aboveground community?
We address these questions using a well-tested, mechanistic model (ecosys, eg., Grant et al., 2017), which simulates the interdependent physical, hydrological, and biological processes that govern ecosystem responses to perturbation. This model also includes a mechanistic treatment of carbon, water, nitrogen, and phosphorus dynamics within soils, microbes (bacterial, archaea, and fungi), and plants. This work is mainly funded by DOE’s Next Generation Ecosystem Experiment located in Alaska (NGEE-Arctic).
Microbial trait-based models: Microbes play critical roles in biogeochemical cycling, but their diversity and metabolic flexibility are poorly captured by most models. Furthermore, the traits underpinning microbial response to environmental fluctuations are still the subject of debate. Here we identified a number of traits that determine microbial fitness over a range of environmental conditions and evaluate community emergence and nitrous oxide production.
Soil carbon stocks over short-term 'step' manipulation simulations, and long-term chronic climate change simulations (Bouskill et al., 2020).
Trait-based approaches to Microbial Ecology.
Drought impacts on tropical forest soils.
This experiment examines the response of individual isolates and microbial communities from semi-arid and humid, tropical forest soils to reoccurring drought. This is a multi scale experiment, aimed at identifying and quantifying the traits and trade-offs of different microorganisms expressing a metabolic response to drought perturbation. This experiment is conducted at the scale of the individual microbe, and simple communities through a microfluidics-based platform, within intact soil cores within laboratory soil mesocosms, and by leveraging a throughfall exclusion experiment across a precipitation gradient in Panama. This study aims to further understanding of how microbial metabolism and community composition feeds back on the formation of soil organic matter and its in situ stability through sorption onto mineral surfaces.
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This work is supported by the DOE Early Career
Award program, and individual grants from the Joint Genome Institute, and the Advanced Light Source at Berkeley National Lab. Dwivedi et al., 2019 |
Microbial trait-based models.
The array of microbial diversity and functional redundancy necessitates approaches to reduce this complexity for representation within models. We use conceptual abstractions of soil microbial and algal physiology to better understand community dynamics, community interactions, and feedbacks to biogeochemical rates.
Examples of this work can be found here, here, and here!
Examples of this work can be found here, here, and here!
