RESEARCHES

The overarching questions motivating our research

  • How do vegetation, microbial communities, and human disturbance respond and adapt to climate and environmental change at different spatiotemporal scales?
  • How do these environmental responses and adaptations, in turn, shape land surface energy balance, hydrological cycle, carbon and nutrient biogeochemical cycling?
  • How do ecosystem-climate-human interactions affect ecosystem goods and services (e.g., agricultural production, bioenergy feedstock, carbon sequestration, and water quality and quantity) and their climate resilience? 

Our methodology: Multi-scale data-mechanism-model approach

Discover mechanisms behind the multi-scale and multi-discipline data.

Develop scaling solutions and parameterization approaches to integrate multi-scale data.

Advance numerical solutions to incorporate identified mechanisms into the ESMs.

Research areas

Small Bugs, Big Roles: Linking ecosystem genomics to Earth system modeling for improving the prediction of microbially-mediated soil biogeochemical cycles in the ESMs.

Soil microbial communities catalyze the essential cycles of carbon (C), nitrogen (N), and phosphorus (P) in ecosystems. However, our limited understanding of the composition, function, and structure of soil microbial communities still impedes our ability to model microbially-mediated soil biogeochemical cycles in ESMs. This deficiency contributes substantially to the uncertainty in predicting climate-carbon feedback and global nutrient cycling. The advance in omics technology now can inform “who exists in the soils?”, “what do they do?” and “How do they respond to environmental change?”. However, it remains unclear how massive omics datasets can be used to predict ecosystem functions of the microbial community on a global scale. 

Our team aims to fill this gap by developing computational approaches and parameterization schemes for developing omics-informed microbial functional prediction in ESMs. 

  • We have provided the concept of “Enzyme functional Classes” to effectively represent the complexity and overcome functional redundancies of omics data. 
  • We have developed an upscaling solution to scale omics-informed microbial information from gene to ecosystem for modeling ecosystem functions. 
  • We have produced the first omics-informed soil biogeochemical model, CoMEND. The model can utilize omics data to represent functional diversity and environmental acclimation of soil microbial communities and predict their effects on soil C, N, and P cycling. 
  • We are now expanding our study to a global scale to develop omics-informed microbial functional prediction in ESMs.

Related project:

Diverse Plants, Distinctive Impacts: Linking diverse plant function-environmental feedback to Earth system modeling for improving parameterization of vegetative regulation on the water cycle, energy balance, carbon, and nutrient cycles in ESMs.

Plants are diverse in functional traits, such as physiology, architecture, phenology, nutrient uptakes, and their adaptation to climate change. Thus, they play distinct roles in regulating water, energy, carbon, and nutrient interactions between the atmosphere and terrestrial ecosystem. To date, our ability to understand and represent diverse plant functional traits, especially their feedback on climate change in ESMs, is still inadequate. This deficiency brings uncertainty in assessing the climate resilience of our ecosystem and the effect of land use and land cover change, such as the expansion of cropland and bioenergy feedstock production and deforestation, on atmosphere-terrestrial ecosystem interaction.

Our team aims to fill these gaps by developing the computational approach and parameterization schemes for representing diverse functional traits of plants and their environmental feedback in ESMs.

  • We specialize in parameterizing the dynamic growth scheme for diverse plants (e.g., row crops, bioenergy crops, grass, and forest). Our parameterization scheme can model the growth dynamics of vegetative architecture, phenology, carbon and nutrient allocation, and their environmental acclimation. It can also differentiate these key plant traits between different plant functional types.
  • We specialize in integrating multi-scale observations to parameterize dryland vegetation feedback to changing hydroclimate and its impact on the dryland water cycle, energy balance, carbon, and nutrient cycles.
  • We are integrating biophysical modeling with the biochemical modeling of photosynthesis for advancing gross primary productivity (GPP) prediction in ESMs.

Related project:

  • UA TRIF: Assessing Resilience of Arizona Grassland to Changes in the North American Monsoon: Fewer, Larger Rainfall Events with Longer-Duration Drought Intervals (PI 2021)
  • EDO: Addressing substantial unknowns in the understanding and model representation of the response of drylands to hydroclimate variability and extremes (Co-PI 2021-2022)
  • DOE Oak Ridge National Lab collaboration: Integrating biophysical modeling with the biochemical modeling of photosynthesis for advancing gross primary productivity (GPP) prediction in ESMs.

Human-centric Practices, Climate-smart Ecosystem Management: Developing model assessment tools to identify climate-smart ecosystem management. 

Climate change (e.g., warming, drought, and increased extreme weather) significantly impacts ecosystem services, such as agriculture productivity and bioenergy feedstock, water quantity and quality, and greenhouse gas (GHG) emissions, which also affect regional climate. The nature and characteristics of the interaction between climate change and these ecosystem services evolve with human activities through land conversion, crop and bioenergy variety selection, soil health management, and agricultural practices. Humans can practice activities in a “Climate-smart” way that can intensify the climate resilience of the ecosystem and, meanwhile, also reduce the negative impact on regional climate. 

We aim to transform ESM to an integrated assessment tool for evaluating the impacts of human activities on ecosystem service and identifying “Climate-smart” ecosystem management.

  • We specialize in integrated assessing climate-smart ecosystem management that can maintain sustainable agricultural yields, promote net ecosystem productivity (NEP), and mitigate GHG emissions and negative impacts on water quantity and quality.
  • We specialize in developing climate-smart soil health assessment tools and improving the prediction of soil moisture prediction for ecosystem management.

Related project: