Proposed Research
- To develop a robust SEM (species environmental matching) to best capture the observed agricultural and invasive plant species distribution using the conditions from CEP (climate-ecosystem predictive).
- To make projections for the potential niche distributions of alternative crops adaptable to the likely range of climate changes in the future using CEP.
- To project the geographic distribution and abundance of U.S. agricultural weeds and invasive plant species by integrating newly-developed SEM and future soil and bioclimatic conditions simulated by CEP.
Research Plan
- Reproduce the observed climate and crop production.
Historical simulations of the U.S. climate and major crops' yield for the recent past will be conducted by CEP at 30-km grid spacing as specified with the realistic finer-scale mosaic land cover/use distribution and driven by the available observational reanalyses and fully-coupled general circulation model (GCM) simulations. The result will serve as the basis for CEP model validation and bias identification and, more importantly, provide a unique high-resolution, physically-consistent and most-complete database as the best proxy of the actual soil and bioclimatic variables representing the present availability of the primary resources of light, heat, water and nutrients that are fundamental to the plant survival and reproduction.
- Develop a robust SEM to best capture the observed agricultural and invasive plant species distribution.
The SEM is an optimally-weighted composite of several most-advanced niche models that will be trained by the unique CEP database of soil and bioclimatic variables from Task 1 to reproduce the observed U.S. agricultural and invasive plant species distributions. The weights of individual niche models will be developed for the composite SEM to most realistically simulate the observed species geographic distributions. The optimization will also incorporate into each niche model the effect of localized characteristics (e.g., soil productivity) on the species' environmental envelopes as a proportional spatial scaling.
- Project the potential niche distributions of alternative crops under the likely range of future climate changes.
For major existing and alternative crops, CEP simulations in parallel to Task 1 are conducted for the 2050s as driven by a representative range of climate projections from two different GCMs under two IPCC SRES emissions scenarios. Each crop will be initially planted everywhere in the U.S. and the CEP simulation will determine its survival locations and final yields in response to the new climate. Those crops that survive and produce reasonable yields will be considered as being able to adapt to the future climate at the designated niche locations. Some existing crops may not survive or fail to produce minimum yields, and hence will be regarded as extinct or diminishing species.
- Project the agricultural weed and invasive plant species distribution and abundance in response to the future climate changes.
The CEP simulations of the future soil and bioclimatic conditions resulted from Task 3 will be used as the input for the SEM developed from Task 2 to project the geographic distribution and abundance of U.S. agricultural weeds and invasive plant species for the 2050s. For each adaptable existing or alternative crop, the accompaning weeds will be first identified from the existing database and then screened by the SEM to determine the locations where they survive under the new environment. The distribution of other invasive plant species will be projected by similar SEM simulations.
Project Personnel
- Dr. Wei Gao, Director of USDA UV-B Monitoring Research Program and Center of Remote Sensing and Modeling for Agriculture Sustainability. Dr. Gao will be the lead PI and direct the overall project. Dr. Gao, an expert in remote sensing, will lead the GIS data mining for model development and validation.
- Dr. XinZhong Liang, Illinois State Water Survey, University of Illinois, Urbana-Champaign. Dr. Liang, an expert in regional and global climate modeling and the principal CEP developer, will lead the dynamic regional climate/ecosystem modeling and will co-lead, with Dr. Stohlgren, the statistical species niche modeling.
- Dr. Thomas Stohlgren, USGS/NREL, Colorado State University, Fort Collins, Colorado. Dr. Stohlgren, an expert on invasive species, will lead the SEM modeling.