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A regional assessment of baseline (1980–2010) and future (2015–2085) yields of dryland wheat-based cropping systems in the US Inland Pacific Northwest (IPNW) was conducted. The computer simulation-based assessment was done using CropSyst, a cropping systems simulation model, and projected daily weather data downscaled to a 4 × 4 km grid using 12 general circulation models (GCMs) for two atmospheric CO2 representative concentration pathways (RCP 4.5 and RCP 8.5). The study region was divided into 3 agro-ecological zones (AEZs): continuous cropping (CC), continuous cropping-fallow transition (CCF), and crop-fallow (CF), with the following typical rotations assigned to the zones: winter wheat (WW) – summer fallow (SF) (CF zone), WW – spring wheat (SW) – SF (CCF zone), and WW – SW – spring pea (CC zone). By the 2070s (2065–2085), precipitation in the IPNW is projected to increase by about 8 and 12% compared to the baseline period under RCP 4.5 and 8.5, respectively. Mean temperature during the WW growing season will increase about 1.5 and 2.3 °C under RCP 4.5 and 8.5, respectively, but will not change noticeably during the SW growing season due to the adaptive early planting used in this study. Concurrently, atmospheric CO2 concentration will increase from today's average of ~ 400 ppm to 532 ppm to 801 ppm by 2085 depending on future emissions of greenhouse gases. Soil water-crop growth interactions, which show large variation across the region, will modulate crop responses to these changing conditions, with our results showing an overall increase in yield across the IPNW. By the 2070s, the mean ratio of future to baseline WW yield will range from 1.29 to 1.35 under RCP 4.5 and from 1.41 to 1.64 under RCP 8.5 depending on the AEZ. The mean yield ratio for SW across AEZs will range from 1.38 to 1.53 under RCP 4.5 and 1.54 to 1.91 under RCP 8.5. Given substantial climatic heterogeneity in the region, these gains will not be distributed equally across the region or within AEZs, and overall they will not be shared equally by all growers.

Despite its potential to mitigate many environmental impacts of agriculture, organic farming does contribute to greenhouse gas (GHG) emissions. A full accounting and understanding of the GHG emissions associated with specific activities, materials, and energy used in organic operations are needed to support decision-making for GHG mitigation. A small-scale organic vegetable farm in Washington State, USA, was used as a case study to determine the carbon footprint (CF) and GHG hotspots. A partial life cycle assessment was conducted to identify primary and secondary GHG fluxes associated with activities and materials used in production of potatoes, cauliflower, dry bush beans, winter squash, summer squash, chard, peppers, and onions grown in a crop rotation. The CF associated with each crop ranged from a low of 1.68 t CO2-eq ha− 1 yr− 1 for chard to a high of 2.67 t CO2-eq ha− 1 yr− 1 for cauliflower. Cauliflower had the highest CF per ha followed by potatoes and pepper. Across the farm as a whole, the major CF hotspots were fuel use for both on-farm and off-farm operations (38%), fertilization (18%), soil emission (12%), and irrigation (11%). Simulation of a switch to biodiesel instead of petroleum gasoline and diesel resulted in a 32% reduction in the total farm CF. By identifying the CF hotspots of a whole farm and individual crops, particular inputs and activities can be targeted for modification in order to effectively reduce the farm's CF.

Integrated environmental and economic assessment studies are required to support tillage reduction decisions. In this paper, carbon sequestration and nitrous oxide emissions from winter wheat-based cropping systems were evaluated in eastern Washington, USA, using computer simulation. System boundaries were expanded to consider fertilizer production and use of machinery in a standard life cycle assessment (LCA) study. Variations in rainfall, tillage intensity and crop rotation were considered. Potential earnings from carbon credits obtained by converting to reduced and no-till management were evaluated and compared with the corresponding changes in farm budgets. No-till increased the average soil carbon sequestration by 0.5, 0.3, 0.2 Mg-C ha−1 yr−1 (30-year average) in high, middle and low rainfall zones, respectively. On-farm N2O emissions contributed 60–70% of the total CO2-equivalent emissions (CO2e ha−1 yr−1) in high and middle rainfall scenarios and 30–40% in low rainfall scenarios. Production of fertilizers contributed 13 ± 3% of total emissions. Emissions from fuel consumption varied across sites due to differences in machinery use with different topography, tillage, soils and number of fallow years. Reduced tillage systems are more profitable in the moderate and high rainfall zones with 2011 crop price and input cost assumptions but they are less profitable in the drier rainfall zone. Even a more inclusive accounting with LCA that includes credits for reductions in N2O emissions, fuel usage and fertilizer production was insufficient to compensate for the lower returns. With the net market price assumption of 2.48 $ CO2e−1 ha−1 yr−1, the CO2e credits for reducing tillage ranged from 0.27 to 1.63 $ CO2e−1 ha−1 yr−1 across the region.

Metadata only record In the Sahel region of West Africa, the traditional organization of the population and the grazing land avoided overexploitation of pastures. Since independence in the 1960s, grazing lands have been opened to all without specific guidance, and the vulnerability of the pastures to degradation has increased. Rotational grazing is postulated as a possible solution to provide higher pasture productivity, higher animal loads per unit land, and perhaps improved soil carbon storage. The objective of this study was to conduct a simulation-based assessment of the impact of rotational grazing management on pasture biomass production, grazing efficiency, animal grazing requirement satisfaction, and soil carbon storage in the Madiama Commune, Mali. The results showed that grazing intensity is the primary factor influencing the productivity of annual pastures and their capacity to provide for animal grazing requirements. Rotating the animals in paddocks is a positive practice for pasture protection that showed advantage as the grazing pressure increased. Increasing the size of the reserve biomass not available for grazing, which triggers the decision of taking the animals off the field, provided better pasture protection but reduced animal grazing requirements satisfaction. In terms of soil carbon storage, all management scenarios led to reduction of soil carbon at the end of the 50-year simulation periods, ranging between 4% and 5% of the initial storage. The differences in reduction as a function of grazing intensity were of no practical significance in these soils with very low organic matter content, mostly resistant to decomposition. SysCoor-2 (Farm/Enterprise)

The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to 'take stock' and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of 'relevance' and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socioeconomic variability and change. (C) 2001 Elsevier Science Ltd. All rights reserved.

The need for tools to evaluate cropping systems and their impact on production and the environment is increasing. Field experiments, which are usually site specific, require considerable resources and time to test hypotheses or management options. Computer models for cropping systems simulation are an alternative, but they require calibration and validation before applications can be developed for a given region. The ability of CropSyst, a cropping systems simulation model, to simulate spring and winter wheat yields and evapotranspiration in a wheat-fallow region of eastern Washington for different tillage and residue management practices was evaluated. Validation of the model was accomplished by (a) providing initial conditions prior to planting for each cropping season of a 6-year wheat-fallow rotation and (b) providing initial conditions at the beginning of the rotation without reinitializing the model in later years. The statistical structure (mean and SD) of simulations and field data were similar. The root mean square errors fluctuated from 7 to 14% of the observed mean for grain yield and from 5 to 9% for evapotranspiration, depending on the type of evaluation, and was 17% for soil moisture profile in the case of continuous 6-year rotation simulation without reinitialization. The Wilmott index of agreement fluctuated from 0.92 to 0.97 (an index of 1.0 indicating perfect agreement), with all values but one equal or better than 0.94. Similar water production functions were obtained from simulation and field data. Based on this validation, Crop'Syst appears promising as a tool to analyze the effectiveness of management practices for water conservation in a wheat-fallow cropping region.

CropSyst, a cropping system simulation model, was evaluated for its ability to simulate growth, yield, and water and nitrogen use of two wheat cultivars (Cham 1 and Hourani). These cultivars were grown under different water (rainfed, 60% and 100% of crop water requirements) and nitrogen (without and with 100 kg N/ha) regimes in a Mediterranean type of environment at the Tel Hadya Research Station of ICARDA. Data from three contrasting growing seasons (1989/90 to 1991/1992) were used in these simulations. Soil characteristics, initial conditions of available moisture, N and organic matter, and daily weather data were input to CropSyst. Crop input parameters were mostly selected from the model documentation or determined from the experimental data. A few cultivar-specific parameters were adjusted within a narrow range of typical fluctuation by model calibration. Results showed that CropSyst was generally able to simulate evapotranspiration, crop N content, green leaf area, aboveground biomass, and grain yield as observed in the field experiments. Overall, the magnitude of the root mean square errors was about 10% of the observed means with two exceptions (25% and 32%). Index of agreement between predicted and observed values fluctuated from 0.90 to 0.98 (a value of 1.0 indicating excellent agreement), with most values equal or better than 0.95.

In agriculture, water and nitrogen are two critical resources for growing a crop. However, their management cannot be analyzed independently of weather, soil characteristics, field hydrology, crop characteristics, crop rotation, and management factors. This paper describes the water, nitrogen, and crop growth components of CropSyst, a comprehensive cropping systems simulation model, and provides preliminary verification of these components. The water budget of the model properly describes crop water use. Predicted nitrogen contents throughout the soil profile did not exactly match the measured values from leaching experiments, but they did follow the general trends of the data. The agreement between simulated and observed biomass and yield of corn, winter wheat and spring wheat grown in two locations with a total of 77 data points was good as shown by several statistical indicators. Based on this preliminary validation, CropSyst appears promising as a tool to analyze management practices for water and nitrogen. Additional validation of model components, including a wide range of crops and conditions, should be conducted in the future.

That atmospheric CO2 concentration is increasing is well established, and it is generally well accepted that this increase will have beneficial effects on plant productivity. What remains most uncertain is the nature and magnitude of the climatic changes that will occur as a result of the increase of carbon dioxide and other radiatively active trace gases. Thus, it is difficult to predict the combined impact of increasing atmospheric carbon dioxide on agricultural productivity. A comprehensive cropping system simulation model, EPIC, was used in a sensitivity analysis of crop growth response to the combined effects of CO2 concentration increase and CO2-induced climate change. Maize, soybean and wheat cropping systems in the midwestern USA were studied.

The potential impact of the global rise in atmospheric CO2 concentration and associated climatic change on agricultural productivity needs assessment. The complexity of climate-crop production interactions makes computer simulation a natural approach for such assessment. EPIC, a comprehensive mathematical cropping system model, was modified to account for the effects of change in CO2 concentration and vapor pressure deficit on the radiation-use efficiency, leaf resistance and transpiration of crops. Details of these modifications are presented in this paper. A companion paper describes an application of the modified model (this issue).