Greg McLean

An overview of APSIM, a model designed for farming systems simulation

The Agricultural Production Systems Simulator (APSIM) is a modular modelling framework that has been developed by the Agricultural Production Systems Research Unit in Australia. APSIM was developed to simulate biophysical process in farming systems, in particular where there is interest in the economic and ecological outcomes of management practice in the face of climatic risk. The paper outlines APSIMs structure and provides details of the concepts behind the different plant, soil and management modules. These modules include a diverse range of crops, pastures and trees, soil processes including water balance, N and P transformations, soil pH, erosion and a full range of management controls. Reports of APSIM testing in a diverse range of systems and environments are summarised. An example of model performance in a long-term cropping systems trial is provided. APSIM has been used in a broad range of applications, including support for on-farm decision making, farming systems design for production or resource management objectives, assessment of the value of seasonal climate forecasting, analysis of supply chain issues in agribusiness activities, development of waste management guidelines, risk assessment for government policy making and as a guide to research and education activity. An extensive citation list for these model testing and application studies is provided.

Development of a generic crop model template in the cropping system model APSIM

The Agricultural Production Systems slMulator, APSIM, is a cropping system modelling environment that simulates the dynamics of soil-plant-management interactions within a single crop or a cropping system. Adaptation of previously developed crop models has resulted in multiple crop modules in APSIM, which have low scientific transparency and code efficiency. A generic crop model template (GCROP) has been developed to capture unifying physiological principles across crops (plant types) and to provide modular and efficient code for crop modelling. It comprises a standard crop interface to the APSIM engine, a generic crop model structure, a crop process library, and well-structured crop parameter files. The process library contains the major science underpinning the crop models and incorporates generic routines based on physiological principles for growth and development processes that are common across crops. It allows APSIM to simulate different crops using the same set of computer code. The generic model structure and parameter files provide an easy way to test, modify, exchange and compare modelling approaches at process level without necessitating changes in the code. The standard interface generalises the model inputs and outputs, and utilises a standard protocol to communicate with other APSIM modules through the APSIM engine. The crop template serves as a convenient means to test new insights and compare approaches to component modelling, while maintaining a focus on predictive capability. This paper describes and discusses the scientific basis, the design, implementation and future development of the crop template in APSIM. On this basis, we argue that the combination of good software engineering with sound crop science can enhance the rate of advance in crop modelling. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.

Adapting APSIM to model the physiology and genetics of complex adaptive traits in field crops

Progress in molecular plant breeding is limited by the ability to predict plant phenotype based on its genotype, especially for complex adaptive traits. Suitably constructed crop growth and development models have the potential to bridge this predictability gap. A generic cereal crop growth and development model is outlined here. It is designed to exhibit reliable predictive skill at the crop level while also introducing sufficient physiological rigour for complex phenotypic responses to become emergent properties of the model dynamics. The approach quantifies capture and use of radiation, water, and nitrogen within a framework that predicts the realized growth of major organs based on their potential and whether the supply of carbohydrate and nitrogen can satisfy that potential. The model builds on existing approaches within the APSIM software platform. Experiments on diverse genotypes of sorghum that underpin the development and testing of the adapted crop model are detailed. Genotypes differing in height were found to differ in biomass partitioning among organs and a tall hybrid had significantly increased radiation use efficiency: a novel finding in sorghum. Introducing these genetic effects associated with plant height into the model generated emergent simulated phenotypic differences in green leaf area retention during grain filling via effects associated with nitrogen dynamics. The relevance to plant breeding of this capability in complex trait dissection and simulation is discussed.

Simulating the Yield Impacts of Organ-Level Quantitative Trait Loci Associated With Drought Response in Maize: A “Gene-to-Phenotype” Modeling Approach

Under drought, substantial genotype–environment (G × E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this “gene-to-phenotype” gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G × E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such “leafy” genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G × E interactions for complex traits such as drought tolerance.

The shifting influence of drought and heat stress for crops in northeast Australia

Characterization of drought environment types (ETs) has proven useful for breeding crops for drought-prone regions. Here, we consider how changes in climate and atmospheric carbon dioxide (CO2 ) concentrations will affect drought ET frequencies in sorghum and wheat systems of northeast Australia. We also modify APSIM (the Agricultural Production Systems Simulator) to incorporate extreme heat effects on grain number and weight, and then evaluate changes in the occurrence of heat-induced yield losses of more than 10%, as well as the co-occurrence of drought and heat. More than six million simulations spanning representative locations, soil types, management systems, and 33 climate projections led to three key findings. First, the projected frequency of drought decreased slightly for most climate projections for both sorghum and wheat, but for different reasons. In sorghum, warming exacerbated drought stresses by raising the atmospheric vapor pressure deficit and reducing transpiration efficiency (TE), but an increase in TE due to elevated CO2 more than offset these effects. In wheat, warming reduced drought stress during spring by hastening development through winter and reducing exposure to terminal drought. Elevated CO2 increased TE but also raised radiation-use efficiency and overall growth rates and water use, thereby offsetting much of the drought reduction from warming. Second, adding explicit effects of heat on grain number and grain size often switched projected yield impacts from positive to negative. Finally, although average yield losses associated with drought will remain generally higher than that for heat stress for the next half century, the relative importance of heat is steadily growing. This trend, as well as the likely high degree of genetic variability in heat tolerance, suggests that more emphasis on heat tolerance is warranted in breeding programs. At the same time, work on drought tolerance should continue with an emphasis on drought that co-occurs with extreme heat.

Simulation Supplements Field Studies to Determine No-Till Dryland Corn Population Recommendations for Semiarid Western Nebraska

tem of wheat–summer crop–fallow increased the efficient use of precipitation by reducing the frequency of In a 2-yr multiple-site field study conducted in western Nebraska summer fallow and using more water for crop transpiraduring 1999 and 2000, optimum dryland corn (Zea mays L.) population varied from less than 1.7 to more than 5.6 plants m 2, depending tion (Farahani et al., 1998). In addition to increased largely on available water resources. The objective of this study was precipitation use efficiency and grain yield, more intento use a modeling approach to investigate corn population recommensified dryland cropping systems increase potentially acdations for a wide range of seasonal variation. A corn growth simulative surface soil organic C and N (Peterson et al., 1998), tion model (APSIM-maize) was coupled to long-term sequences of effectively control winter annual grass weeds in winter historical climatic data from western Nebraska to provide probabilistic wheat (Daugovish et al., 1999), and increase net return estimates of dryland yield for a range of corn populations. Simulated and reduce financial risk (Dhuyvetter et al., 1996). populations ranged from 2 to 5 plants m 2. Simulations began with Growers in the semiarid regions of western Nebraska one of three levels of available soil water at planting, either 80, 160, have had limited experience with dryland corn. Before or 240 mm in the surface 1.5 m of a loam soil. Gross margins were 1997, fewer than 3800 ha of dryland corn were planted maximized at 3 plants m 2 when starting available water was 160 or 240 mm, and the expected probability of a financial loss at this populaeach year in the western crop-reporting district. As more tion was reduced from about 10% at 160 mm to 0% at 240 mm. When growers diversified and intensified their rotations, land starting available water was 80 mm, average gross margins were less planted to corn grew to more than 28 700 ha in 1999 than

Modelling the effects of row configuration on sorghum yield reliability in north-eastern Australia

15 ha 1, and risk of financial loss exceeded 40%. Median yields (NASS, 2000). Growers were getting conflicting populawere greatest when starting available soil water was 240 mm. However, tion recommendations and requested assistance from perhaps the greater benefit of additional soil water at planting was the University of Nebraska. reduction in the risk of making a financial loss. Dryland corn growers Determining population response of corn is a recurin western Nebraska are advised to use a population of 3 plants m 2 rent area of study, with modern hybrids having greater as a base recommendation. tolerance of high plant density than older hybrids (Tollenaar, 1991). In one southwest Kansas study, dryland corn performed best when no-till–planted in early to W is the most limiting resource for dryland mid-May at plant populations not exceeding 4.45 plants crop growth in the semiarid areas of the U.S. m 2 (Norwood and Currie, 1996). A more recent study Great Plains (Smika, 1970). Summer fallow, the practice from this same region achieved maximum yield and of controlling all plant growth during the noncrop seawater use efficiency with a late May planting, combined son, is commonly used to stabilize winter wheat (Tritiwith later-maturing hybrids and plant populations up to cum aestivum L.) production in this region of high envi6.0 plants m 2 (Norwood, 2001). However, in northwest ronmental variability. Wheat–fallow is the predominate Kansas, no yield differences were found for corn populacropping system in the Great Plains, but water storage tions of 2.1, 2.47, and 3.71 plants m 2 (Havlin and Lamm, efficiency during fallow is frequently less than 25% with 1988). In a summary of research results from locations conventional tillage (McGee et al., 1997). The advent across the USA and Canada, corn grain yields leveled of reducedand no-till systems has generally enhanced off but did not decrease above the optimum plant poputhe ability to capture and retain precipitation in the soil lation, except in those fields with yield levels below 7500 during noncrop periods of the cropping cycle, making kg ha 1 (Paszkiewicz and Butzen, 2001). it more feasible to reduce the frequency of fallow and Blumenthal et al. (2003) advised dryland corn growers intensify cropping systems relative to wheat–fallow (Peto use a plant population of 2.7 plants m 2, based on terson et al., 1996). 2 yr of field research conducted at four locations each In the Great Plains, annual precipitation is concenyear. Unfortunately, summer precipitation was very diftrated during the warm season from April to September. ferent between the 2 yr of the study, and often the Hence, inclusion of a summer crop, e.g., corn or grain treatment resulting in the greatest yield in 1 yr provided sorghum [Sorghum bicolor (L.) Moench], in a 3-yr systhe least yield in the other year. The standard analysisof-variance approach used in that study did not allow D.J. Lyon and J.M. Blumenthal, Panhandle Res. and Ext. Cent, 4502 for a satisfactory assessment of the production risks Ave. I, Scottsbluff, NE 69361; and G.L. Hammer and G.B. McLean, Agric. Prod. Syst. Res. Unit, QDPI, PO Box 102, Toowoomba, QLD, associated with the various population treatments. Australia 4350. Journal Ser. no. 13756 of the Univ. of Nebraska Agric. Crop modeling has been a developing component of Res. Div. Received 11 July 2002. *Corresponding author (DLYON1@ agronomic research for more than 30 yr (Sinclair and unl.edu). Seligman, 1996). Crop models have been successfully used to analyze management practice in regions where Published in Agron. J. 95:884–891 (2003).

Modelling the effect of plant water use traits on yield and stay-green expression in sorghum

In recent years, many sorghum producers in the more marginal (<600mm annual rainfall) cropping areas of Queensland and northern New South Wales have used skip row configurations in an attempt to improve yield reliability and reduce sorghum production risk. This paper describes modi. cations made to the APSIM sorghum module to account for the difference in water usage and light interception between alternative crop planting configurations, and then demonstrates how this new model can be used to quantify the long-term benefits of skip sorghum production. Detailed measurements of light interception and water extraction from sorghum crops grown in solid, single and double skip row configurations were collected from on-farm experiments in southern Qld and northern NSW. These measurements underpinned changes to the APSIM-Sorghum model so that it accounted for the elliptical water uptake pattern below the crop row and the reduced total light interception associated with skip row configurations. Long-term simulation runs using long-term weather files for locations near the experimental sites were used to determine the value of skip row sorghum production as a means of maintaining yield reliability. These simulations showed a trade-off between long-term average production (profitability) and annual yield reliability ( risk of failure this year). Over the long term, the production of sorghum in a solid configuration produced a higher average yield compared with sorghum produced in a skip configuration. This difference in average yield is a result of the solid configuration having a higher yield potential compared with the skip configurations. Skip configurations limit the yield potential as a safeguard against crop failure. To achieve the higher average yield in the solid configuration the producer suffers some total failures. Skip configurations reduce the chance of total failure by capping the yield potential, which in turn reduces the long-term average yield. The decision on what row configuration to use should be made tactically and requires consideration of the starting soil water, the soils plant-available water capacity (PAWC), and the farm familys current attitude to risk.

Robust features of future climate change impacts on sorghum yields in West Africa

Post-rainy sorghum (Sorghum bicolor (L.) Moench) production underpins the livelihood of millions in the semiarid tropics, where the crop is affected by drought. Drought scenarios have been classified and quantified using crop simulation. In this report, variation in traits that hypothetically contribute to drought adaptation (plant growth dynamics, canopy and root water conducting capacity, drought stress responses) were virtually introgressed into the most common post-rainy sorghum genotype, and the influence of these traits on plant growth, development, and grain and stover yield were simulated across different scenarios. Limited transpiration rates under high vapour pressure deficit had the highest positive effect on production, especially combined with enhanced water extraction capacity at the root level. Variability in leaf development (smaller canopy size, later plant vigour or increased leaf appearance rate) also increased grain yield under severe drought, although it caused a stover yield trade-off under milder stress. Although the leaf development response to soil drying varied, this trait had only a modest benefit on crop production across all stress scenarios. Closer dissection of the model outputs showed that under water limitation, grain yield was largely determined by the amount of water availability after anthesis, and this relationship became closer with stress severity. All traits investigated increased water availability after anthesis and caused a delay in leaf senescence and led to a stay-green phenotype. In conclusion, we showed that breeding success remained highly probabilistic; maximum resilience and economic benefits depended on drought frequency. Maximum potential could be explored by specific combinations of traits.

Crop design for specific adaptation in variable dryland production environments

West Africa is highly vulnerable to climate hazards and better quantification and understanding of the impact of climate change on crop yields are urgently needed. Here we provide an assessment of near-term climate change impacts on sorghum yields in West Africa and account for uncertainties both in future climate scenarios and in crop models. Towards this goal, we use simulations of nine bias-corrected CMIP5 climate models and two crop models (SARRA-H and APSIM) to evaluate the robustness of projected crop yield impacts in this area. In broad agreement with the full CMIP5 ensemble, our subset of bias-corrected climate models projects a mean warming of +2.8 °C in the decades of 2031–2060 compared to a baseline of 1961–1990 and a robust change in rainfall in West Africa with less rain in the Western part of the Sahel (Senegal, South-West Mali) and more rain in Central Sahel (Burkina Faso, South-West Niger). Projected rainfall deficits are concentrated in early monsoon season in the Western part of the Sahel while positive rainfall changes are found in late monsoon season all over the Sahel, suggesting a shift in the seasonality of the monsoon. In response to such climate change, but without accounting for direct crop responses to CO2, mean crop yield decreases by about 16–20% and year-to-year variability increases in the Western part of the Sahel, while the eastern domain sees much milder impacts. Such differences in climate and impacts projections between the Western and Eastern parts of the Sahel are highly consistent across the climate and crop models used in this study. We investigate the robustness of impacts for different choices of cultivars, nutrient treatments, and crop responses to CO2. Adverse impacts on mean yield and yield variability are lowest for modern cultivars, as their short and nearly fixed growth cycle appears to be more resilient to the seasonality shift of the monsoon, thus suggesting shorter season varieties could be considered a potential adaptation to ongoing climate changes. Easing nitrogen stress via increasing fertilizer inputs would increase absolute yields, but also make the crops more responsive to climate stresses, thus enhancing the negative impacts of climate change in a relative sense. Finally, CO2 fertilization would significantly offset the negative climate impacts on sorghum yields by about 10%, with drier regions experiencing the largest benefits, though the net impacts of climate change remain negative even after accounting for CO2.