Dr. Ren is broadly interested in understanding, assessing and predicting natural processes and human-caused changes in Earth’s Ecosystems and Climate System by using an integrated systems approach with a combination of numerical models, remote sensing/GIS, and field observations and measurements. She works at multiple spatiotemporal scales ranging from plot, landscape/watershed, regional, to the global levels, and over daily, seasonal, annual, decadal, and century scales. Her research is driven by scientific questions such as: How do multiple global change drivers influence ecosystem processes and exchanges (water, carbon, nutrients) across soil-plant-atmosphere interfaces? How do human-induced changes in energy and matter movement through different biogeochemical cycles among terrestrial ecosystems affect the physical climate system and aquatic system? How can we identify and apply Climate-Smart Agricultural practices to enhance food production, soil carbon sequestration, and water/nutrients use efficiency while minimizing negative environmental effects on water quality and greenhouse gas emissions? Her research foci include:
Investigate the Single and Combination Effects of Natural and Anthropogenic Factors, including climate change/extremes (drought and flood), air pollution (tropospheric ozone), atmospheric CO2, nitrogen deposition, disturbance (fire), land cover change (e.g. crop expansion and urbanization) and land management practices (e.g., fertilizer use, irrigation, harvest, rotation, tillage, cover cropping, straw return), in the context of multiple global changes.
Assess Dynamics of Terrestrial Ecosystems(Cropland, Grassland, Forest) productivity, carbon/nitrogen storage in plant and soil; land-atmosphere exchange of water, energy and greenhouse gases (CO2, CH4, N2O); water discharge, carbon and nitrogen transport from land to ocean as influenced by those multiple global changes at broad scales (e.g., Mississippi river basin, southeastern US, North America, China, Monsoon Asia, and the globe).
Develop and Improve Land Ecosystem Model, by incorporating improved representations of physical, chemical, and biological processes, in simulating multiple global changes, fully coupled cycles of water-carbon-nitrogen-phosphorus, and human activities with an emphasis on diverse land management practices for climate change adaptation and mitigation. We aim to enhance the capability of Earth system models to simulate human activities (management practices) as an interdependent component of the Earth system.
Use, Analyze, and Synthesize Big Data derived from site-level observations/experiments to large-scale remote sensing monitoring for model parameterization, evaluation, and validation. We generate gridded datasets at multiple time and space scales as model inputs for different purposes in study regions. Through data-model fusion, we work toward developing systems-oriented thinking framework, tools and approaches to support stakeholder for the sustainable management and use of land and water resources, and facilitate the environmental policy and decision making.
