Holistic Systems Approaches
- Transdisciplinary, deeply based on mechanistic understanding
- System view: earth system science, to study agroecosystem dynamics
- Carbon cycle science as an example
Scientists at ASC use a holistic and integrated systems approach to study the agroecosystem and build solutions towards sustainable agrifood systems. We aim to deepen our mechanistic understanding of the complex biophysical and biogeochemical processes in the agroecosystem through interdisciplinary studies. We use a systems approach to study the agroecosystem dynamics, especially the coupled carbon-water-nutrient dynamics. Comprehensive observations of different components in the agroecosystem, systems modeling, and model-data integration improve our systems-level understanding of the agroecosystem. We also use a system approach to integrate social, economic, policy aspects together to generate real-world solutions, for farming communities and policymakers.
Cross-Scale Remote Sensing
Ground Sensors
Spatially-distributed and temporally-continuous ground data are prerequisite for understanding agroecosystems as well as interpreting remote sensing data. To meet this requirement, we have built and developed Fluospec2 solar-induced fluorescence and hyperspectral observation system, CropEYEs crop growth monitoring system, and FieldRover observation system.
Airborne Hyperspectral Imaging
A high-fidelity full-optical-range airborne hyperspectral system with a high-performance data processing pipeline collects and produces high-quality, high spatial and spectral resolution visible, near-infrared, and shortwave infrared surface reflectance for agroecosystem monitoring.
Satellite Sensing
Integration of multi-source and multi-modal spaceborne remote sensing data, such as multispectral, hyperspectral, solar-induced fluorescence, thermal infrared, microwave, LiDAR and gravity, to comprehensively understand energy-carbon-water-nutrient dynamics in agroecosystems.
Agroecosystem Modeling
Advanced Ecosystem Models: ecosys, CLM5
Ecosystem models are process-based models that simulate the dynamics of biophysical and biogeochemical processes in the ecosystem. The ecosystem models used at the ASC center include: (1) ecosys, an advanced ecosystem model with full representation of soil C-N-P cycles; and (2) CLM, the land component of U.S. flagship earth system model CESM.
Model-Data Fusion
Both observations and process-based modeling have their strengths and weaknesses. Systematic model-data fusion (MDF) is the most promising way for accurately quantifying agroecosystem outcomes through combining advantages from both observation and process-based modeling. Advanced techniques such as artificial intelligence and graphics processing unit (GPU) computing are fostering MDF to be scalable, accurate, and efficient.
Environmental Flux Measurements
EC Towers
An eddy covariance tower, also known as a flux tower, is a scientific instrument to measure the exchange of carbon dioxide, water vapor, and energy between the atmosphere and land surface at a high temporal resolution. The tower relies on the eddy covariance method, which involves measuring the fluctuations in wind speed, temperature, and gas concentration to calculate the flux of gasses and energy.
Chambers
Soil chambers are experimental apparatus to study soil processes by measuring the fluxes of gasses (such as carbon dioxide, methane, and nitrous oxide) between soil surface and the atmosphere. The chamber is usually placed over the soil, creating a sealed environment in which gas concentrations can be measured over time to determine the rate of gas exchange between the soil and the atmosphere.
N2O EC towers
An eddy covariance tower to measure the nitrous oxide exchange between ecosystems and the atmosphere.