Roger Nelson

CropSyst, a cropping systems simulation model

CropSyst is a multi-year, multi-crop, daily time step cropping systems simulation model developed to serve as an analytical tool to study the effect of climate, soils, and management on cropping systems productivity and the environment. CropSyst simulates the soil water and nitrogen budgets, crop growth and development, crop yield, residue production and decomposition, soil erosion by water, and salinity. The development of CropSyst started in the early 1990s, evolving to a suite of programs including a cropping systems simulator (CropSyst), a weather generator (ClimGen), GIS-CropSyst cooperator program (ArcCS), a watershed model (CropSyst Watershed), and several miscellaneous utility programs. CropSyst and associated programs can be downloaded free of charge over the Internet. One key feature of CropSyst is the implementation of a generic crop simulator that enables the simulation of both yearly and multi-year crops and crop rotations via a single set of parameters. Simulations can last a fraction of a year to hundreds of years. The model has been evaluated in many world locations by comparing model estimates to data collected in field experiments. CropSyst has been applied to perform risk and economic analyses of scenarios involving different cropping systems, management options, and soil and climatic conditions. An extensive list of references related to model development, evaluation, and application is provided.

CropSyst model evolution

Motivated by global and regional challenges in food production and a broader consideration of ecosystem services, there has been a substantial increase in the demand for integrated agricultural systems models and spatially-distributed applications that can be used for regional and global assessments and as decision support tools. This demand marks a shift from earlier emphasis in single-crop point simulations and poses a significant challenge as cropping systems models need to improve and increase their capabilities to address multiple scales in a cohesive scientific manner and using updated computing platforms. In this article we discuss how the cropping systems model CropSyst has evolved to meet these new demands and provide some concepts for the future. Climate change and environmental concerns are driving the development of crop models.The cropping systems model CropSyst has evolved in response to new research needs.Our vision is to provide Internet-based open access to a library of CropSyst modules.Global communities of crop, climate, and economic modelers are emerging.

BioEarth: Envisioning and developing a new regional earth system model to inform natural and agricultural resource management

As managers of agricultural and natural resources are confronted with uncertainties in global change impacts, the complexities associated with the interconnected cycling of nitrogen, carbon, and water present daunting management challenges. Existing models provide detailed information on specific sub-systems (e.g., land, air, water, and economics). An increasing awareness of the unintended consequences of management decisions resulting from interconnectedness of these sub-systems, however, necessitates coupled regional earth system models (EaSMs). Decision makers’ needs and priorities can be integrated into the model design and development processes to enhance decision-making relevance and “usability” of EaSMs. BioEarth is a research initiative currently under development with a focus on the U.S. Pacific Northwest region that explores the coupling of multiple stand-alone EaSMs to generate usable information for resource decision-making. Direct engagement between model developers and non-academic stakeholders involved in resource and environmental management decisions throughout the model development process is a critical component of this effort. BioEarth utilizes a bottom-up approach for its land surface model that preserves fine spatial-scale sensitivities and lateral hydrologic connectivity, which makes it unique among many regional EaSMs. This paper describes the BioEarth initiative and highlights opportunities and challenges associated with coupling multiple stand-alone models to generate usable information for agricultural and natural resource decision-making.

Carbon storage and nitrous oxide emissions of cropping systems in eastern Washington: A simulation study

Conservation tillage is an agricultural strategy to mitigate atmospheric greenhouse gas (GHG) emissions. In eastern Washington, we evaluated the long-term effects of conventional tillage (CT), reduced tillage (RT) and no-tillage (NT) on soil organic carbon (SOC) storage and nitrous oxide (N2O) emissions at three dryland and one irrigated location using the cropping systems simulation model CropSyst. Conversion of CT to NT produced the largest relative increase in SOC storage (ΔSOC, average yearly change relative to CT) in the top 30 cm (11.8 in) of soil where ΔSOC ranged from 0.29 to 0.53 Mg CO2e ha−1 y−1 (CO2e is carbon dioxide [CO2] equivalent of SOC; 0.13 to 0.24 tn CO2e ac−1 yr−1). The ΔSOC were less with lower annual precipitation, greater fallow frequency, and when changing from CT to RT. Overall, ΔSOC decreased from the first to the third decade after conversion from CT to NT or RT. Simulations of ΔSOC for the conversion of CT to NT based on a 0 to 15 cm (0 to 5.9 in) soil depth were greater than the ΔSOC based on a 0 to 30 cm depth, primarily due to differences among tillage regimes in the depth-distribution of carbon (C) inputs and the resultant SOC distribution with depth. Soil erosion rates under CT in the study region are high, posing deleterious effects on soil quality, productivity, and aquatic systems. However, an analysis that includes deposition, burial, and sedimentation on terrestrial and aquatic systems of eroded SOC indicates that the substantial erosion reduction obtained with RT and NT may result only in minor additional SOC oxidation as compared to CT. Simulated N2O emissions, expressed as CO2 equivalent, were not very different under CT, RT, and NT. However, N2O emissions were sufficiently high to offset gains in SOC from the conversion of CT to RT or NT. Thus, reducing tillage intensity can result in net C storage, but mitigation of GHG is limited unless it is coupled with nitrogen (N) fertilizer management to also reduce N2O emission.

Harmonization and translation of crop modeling data to ensure interoperability

The Agricultural Model Intercomparison and Improvement Project (AgMIP) seeks to improve the capability of ecophysiological and economic models to describe the potential impacts of climate change on agricultural systems. AgMIP protocols emphasize the use of multiple models; consequently, data harmonization is essential. This interoperability was achieved by establishing a data exchange mechanism with variables defined in accordance with international standards; implementing a flexibly structured data schema to store experimental data; and designing a method to fill gaps in model-required input data. Researchers and modelers are able to use these tools to run an ensemble of?models on a single, harmonized dataset. This allows them to compare models directly, leading ultimately to model improvements. An important outcome is the development of a platform that facilitates researcher collaboration from many organizations, across many countries. This would have been very difficult to achieve without the AgMIP data interoperability standards described in this paper. Heterogeneous data can be harmonized and translated to multiple model formats.The ICASA data standards provide an extensible data structure and ontology.JSON structures provide a flexible, efficient means of handling heterogeneous data.DOME functions enable a consistent means of providing missing or inadequate data.Data provenance is maintained from data sources through simulated model outputs.

Evaluating opportunities for an increased role of winter crops as adaptation to climate change in dryland cropping systems of the U.S. Inland Pacific Northwest

The long-term sustainability of wheat-based dryland cropping systems in the Inland Pacific Northwest (IPNW) of the United States depends on how these systems adapt to climate change. Climate models project warming with slight increases in winter precipitation but drier summers for the IPNW. These conditions combined with elevated atmospheric CO2, which promote crop growth and improve transpiration-use efficiency, may be beneficial for cropping systems in the IPNW and may provide regional opportunities for agricultural diversification and intensification. Crop modeling simulation under future climatic conditions showed increased wheat productivity for the IPNW for most of the century. Water use by winter wheat was projected to decrease significantly in higher and intermediate precipitation zones and increase slightly in drier locations, but with winter crops utilizing significantly more water overall than spring crops. Crop diversification with inclusion of winter crops other than wheat is a possibility depending on agronomic and economic considerations, while substitution of winter for spring crops appeared feasible only in high precipitation areas. Increased weed pressure, higher pest populations, expanded ranges of biotic stressors, and agronomic, plant breeding, economic, technology, and other factors will influence what production systems eventually prevail under future climatic conditions in the region.

Projected Dryland Cropping System Shifts in the Pacific Northwest in Response to Climate Change

Agriculture in the dryland region of the Inland Pacific Northwest (IPNW, including northern Idaho, eastern Washington and northern Oregon) is typically characterized based on annual rainfall and associated distribution of cropping systems that have evolved in response to biophysical and socio-economic factors. Three agro-ecological classes (AEC) have been proposed for the region: a) crop/fallow (CF), b) annual crop/fallow transition (CCF), and c) continuous cropping (CC). AECs attempt to associate land use into relatively homogeneous areas that result in common production systems. Although there is an interest in sustainable intensification of cropping systems (e.g., reduction of fallow), the question remains whether climate change will preclude intensification or shift the borders of existing AECs toward greater fallow utilization. A simulation study was conducted to address this question, with the aim of classifying 4x4 km pixels throughout the region into one of the three AECs for baseline (1979-2010) and future periods (2030s, 2015-2045; 2050s, 2035-2065; 2070s, 2055-2085). Baseline data were derived from traditional rotations and historical climate records. Data for future projections were derived from atmospheric CO2 concentration considering daily weather downloaded from 12 global circulation models and 2 representative concentration pathways (RCP 4.5 and 8.5). Due to the direct effect of atmospheric CO2 on photosynthesis and stomatal conductance, the transpiration use efficiency of crops (TUE; g above-ground biomass kg water-1) showed an increasing trend, with winter wheat TUE changing from 4.76 in the historical period to 6.17 and 7.08 g kg-1 in 2070s, depending on AEC. Compared to the baseline, total grain yield by the 2070s in the region was projected to increase in the range of 18% to 48% (RCP 4.5) and 30% to 65% (RCP 8.5), depending on AEC. As a consequence of these changes, compared to the historical baseline period, the future fraction of the area classified as CF decreased from 50% to 39-36%, CC increased from 16% to 24-28%, and CCF decreased slightly (~1%), with the greater change projected for the RCP 8.5 scenario.

Assessment of Climate Change and Atmospheric CO2 Impact on Winter Wheat in the Pacific Northwest Using a Multimodel Ensemble

Simulations of crop yields under climate change are subject to uncertainties whose quantification is important for effective use of projected results for adaptation and mitigation strategies. In the US Pacific Northwest (PNW), studies based on single crop models and weather projections downscaled from a few general circulation models (GCM) have indicated mostly beneficial effects of climate change on winter wheat production for most of the 21st century. In this study we evaluated the uncertainty in the projection of winter wheat yields at 7 sites in the PNW using five crop growth simulation models (CropSyst, APSIM, DSSAT, STICS and EPIC) and daily weather data downscaled from 14 GCMs for 2 representative concentration pathways (RCP) of atmospheric CO2 (RCP4.5 and 8.5). All crop models were calibrated for high, medium, and low precipitation dryland sites and one irrigated site using 1979–2010 as the baseline period. All five models were run from years 2000 to 2100 to evaluate the effect of future conditions (precipitation, temperature and atmospheric CO2) on winter wheat grain yield. Simulations of future climatic conditions and impacts were organized into three 31-year periods centered around the years 2030, 2050 and 2070. All models predicted a decrease of the growing season length and crop transpiration, and increase in transpiration-use efficiency, biomass production, and yields, but with substantial variation that increased from the 2030s to 2070s. Most of the uncertainty (up to 85%) associated with predictions of yield was due to variation among the crop models. Maximum uncertainty due to GCMs was 15% which was less than the maximum uncertainty associated with the interaction between the crop model effect and GCM effect (25%). Large uncertainty associated with the interaction between crop models and GCMs indicated that the effect of GCM on yield varied among the 5 models. The mean of the ensemble of all crop models and GCMs provided a robust indication of positive effects of future environmental conditions on winter wheat yield during this century at all sites studied, with greater beneficial effect under water stressed conditions than under well-watered conditions, and under RCP8.5 than RCP4.5.

Development of a web application for estimating carbon footprints of organic farms

Abstract Organic farmers often use complex management practices to foster a positive impact on the environment. Many tools exist to aid in estimating environmental services but few are able to properly handle the complexities of organic agriculture. We developed an online tool called OFoot to estimate the carbon footprint of organic farms located in the Pacific Northwest and to help evaluate the potential for environmental benefits. OFoot utilizes a cradle-to-gate carbon calculator and a biophysical, process-based, cropping and field management model. We present the software architecture of the tool, model descriptions, and a case study which simulates several scenarios of organic potato production. The scenario simulating potato production with organic fertilizers and a leguminous winter cover crop sequestered soil carbon. The other scenarios, either lacking fertilizer or cover crops, lost soil carbon. The usefulness of the tool as an aid to management decisions is demonstrated.