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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Adaptive Cropping Systems Laboratory » Research » Research Project #428181

Research Project: Development and Application of Mechanistic Process-Driven Crop Models for Assessing Effects and Adapting Agriculture to Climate Changes

Location: Adaptive Cropping Systems Laboratory

2016 Annual Report


Objectives
Objective 1: Characterize responses of potato and soybean to the interacting effects of temperature and CO2. Objective 2: Improve mechanistic models for corn, potato, cotton and soybean to better account for growth and development responses to environment, genotype, and nutrient factors, and enable simulations of multi-year cropping rotations. Objective 3: Estimate the sensitivity of regional food production to climate change and contribute to international model intercomparison efforts.


Approach
Mechanistic models for soybean (GLYCIM), cotton (GOSSYM), corn (MAIZSIM), and potato (SPUDSIM), have been developed in previous projects by this group. The proposed research will broaden the capabilities of the corn and potato models by utilizing data from experiments carried out in unique, state-of-the-art sun-lit growth chambers and field plots. Short and long term experiments will be employed to test hypotheses and develop algorithms for plant processes to be used in the computer models. Data collected by collaborators will be used to test and evaluate the models. A simple Rye model will be developed to simulate a cover crop during the fall-winter season. A computer graphical user interface will be developed using components from the existing software program, GUICS, to allow a user to simulate long term crop rotations over multiple growing seasons. Advanced data management capabilities will be added to the interface to help with interpretation and management of input and output data. Tools for weather generation and estimation of soil hydraulic properties will be added to the interface to provide a wide range of environmental conditions for assessment. All crop models will be used within the new interface to assess the environmental and economic impacts of climate change on carbon sequestration, and nitrogen and water balances for relevant production systems.


Progress Report
Current bridging project began on January 1, 2016, so most progress is on-going at the time of this writing. Technology transfer and international cooperators continue from 8042-61660-008-00D. A potato experiment was initiated in May 2016, to investigate interactive effects of atmospheric carbon dioxide concentration and air temperature on two widely grown potato genotypes. This study will provide important data to evaluate genotype x environment components in the SPUDSIM potato model. Experimental data will also inform the scientific community regarding the genotypic differences with respect to climate change response. This focuses primarily on Objective 1 and 2 to a lesser extent. A corn experiment was initiated in June 2016, in indoor growth chambers. The goal was to assess differences in leaf expansion due to air temperature and changes in vapor pressure. The data will be useful for testing the MAIZSIM model and will provide needed data regarding the effect humidity levels may have on corn growth. This focuses primarily on Objective 2 and 1 to a lesser extent. Computer scripts and other programs were developed, and are currently being tested, to facilitate input of field data experiments into the format needed to conduct simulations with MAIZSIM and SPUDSIM models. We have developed the conceptual approach for this interface and successfully tested the implementation of the initial methods. This work will form the basis of developing and improved interface from which simulations exploring genetic, environment, and management components can be tested. Addresses Objective 2. Geospatial simulations involving corn, potato, and wheat production at the sub-county level in the north-eastern seaboard states were conducted. The simulations include comparisons of crop yields (and corn silage) when grown under historical climate conditions as well as two different mid-century climate change scenarios. The results indicate the potential vulnerabilities and strengths of the region’s agricultural system to a changing climate and address Objective 3. A manuscript was submitted for peer-review on corn and potato responses. We are leading the AgMIP potato model inter-comparison and the AgMIP maize leaf expansion pilots. As part of the potato initiative, we coordinated model simulation runs and experimental datasets from over twenty-four international collaborators. Results of the model-intercomparisons were analyzed, including sensitivity to climate change at different potato production locations around the world. A manuscript was submitted for peer-review. Similar efforts are taking place with the maize leaf expansion project. These tasks directly address Objective 3.


Accomplishments
1. Climate change effect on crop yields in the East Coast seaboard. Projected climate change impacts on agricultural vary by crop and location. Understanding these impacts at a sub-regional scale is important to develop adaptation strategies. ARS researchers in Beltsville, Maryland, have an on-going research project used SPUDSIM and MAIZSIM models with soil, management, and climate data to simulate how tuber yields and corn silage might be impacted by a changing climate at the sub-county level in the northeastern seaboard region. The results showed a potential 50% reduction in potato yield and 19% loss in corn silage if no adaptation measures were implemented. These impacts were comparatively larger in northern states than southern states in large part due to warming temperature and dryer, less humid air in the climate predictions. The results provide an initial assessment of climate impacts on two important crops and can be used by scientists and policy planners to explore adaptation mechanisms, including a more optimal distribution of the current production system under future climates.

2. Darker soybean leaf colors can help minimize severity of nutrient deficiencies. The greenness of soybean leaves plays an important role in maintaining high growth rates when exposed to phosphorus (P) deficiency. High amounts of solar radiation may be damaging to plant photosynthesis. Leaf compounds called chlorophylls and carotenoids may help minimize this damage when present in the plant in certain ratios. Results from an experiment conducted in the SPAR facility in Beltsville, Maryland, showed that that carotenoids help protect soybean leaves under different levels of P deficiency and CO2 concentration. This finding underscores the significance of quantifying leaf carotenoids in order to understand the underlying mechanisms of photoprotection in a given environment. Results are useful to the researchers interested in improving photosynthetic capacity in crops under stress conditions.


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