Search

Abstract: Long-term soil carbon (C) dynamics in agro-ecosystems is controlled by interactions of climate, soil and agronomic management. A modeling approach is a useful tool to understand the interactions, especially over long climatic sequences. In this paper, we examine the performance of the Agricultural Production Systems sIMulator (APSIM) to predict the long-term soil C dynamics under various agricultural practices at four semi-arid sites across the wheat-belt of eastern Australia. We further assessed the underlying factors that regulate soil C dynamics in the top 30cm of soil through scenario analysis using the validated model. The results show that APSIM is able to predict aboveground biomass production and soil C dynamics at the study sites. Scenario analyses indicate that nitrogen (N) fertilization combined with residue retention (SR) has the potential to significantly slow or reverse the loss of C from agricultural soils. Optimal N fertilization (Nopt) and 100% SR, increased soil C by 13%, 46% and 45% at Warra, Wagga Wagga and Tarelee, respectively. Continuous lucerne pasture was the most efficient strategy to accumulate soil C, resulting in increases of 49%, 57% and 50% at Warra, Wagga Wagga and Tarlee, respectively. In contrast, soil C decreases regardless of agricultural practices as a result of cultivation of natural soils at the Brigalow site. Soil C input, proportional to the amount of retained residue, is a significant predictor of soil C change. At each site, water and nitrogen availability and their interaction, explain more than 59% of the variation in soil C. Across the four sites, mean air temperature has significant (P <0.05) effects on soil C change. There was greater soil C loss at sites with higher temperature. Our simulations suggest that detailed information on agricultural practices, land use history and local environmental conditions must be explicitly specified to be able to make plausible predictions of the soil C balance in agro-ecosystems at different agro-ecological scales. [Copyright &y& Elsevier]

Context: Investigating agronomic responses of dryland maize (Zea mays L.) systems under global change could provide important insights in designing climate-resilient cropping systems. Aims and methods: In this study, we integrated Agricultural Production Systems sIMulator (APSIM) with Representative Concentration Pathways 8.5 and 20 Global Climate Models to systematically: (1) calibrate and validate APSIM using large-field study conducted in East-Central Texas; (2) evaluate the impacts of climate change on maize productivity and risks; and (3) investigate the variations in growth stage lengths. Key results: Results indicated that APSIM simulated grain yield, biomass production, precipitation productivity (PP; kg ha−1 mm−1) and developmental stage transition agreed well with observation (NRMSE < 14.9%). Changes in temperature and precipitation shortened growing seasons and affected available water, resulting in widely varied yield and PP. Mean grain yield changed from −34.8 to +19.7%, mean PP were improved 9.2–36.5%. The grain production could be maintained at least the standard of 75% of historical in most cases, but with greater risks for achieving higher threshold (50% of baseline). Finally, simulations indicated shortened days (4–13 days) for reaching key developmental stages for maize. Conclusions and implications: The results advocate adoptions of management practice that incorporating early sowing, irrigations at sowing/VT stages, and selections of late-maturing cultivars for better sustainability and higher productivity. Global change greatly challenge the maize (Zea mays L.) systems, and crop modelling could provide comprehensive assessment on the impacts of climate change. We investigated the effects of projected future climate on maize yield, climate risks and growth stage transitions in the East-Central Texas (ECT), indicating that yield could maintain historical level in most cases with shorten seasons and higher risk. Extending maize growing season, choosing soil with low-sand level and supplement of irrigation in ECT have greater impact in moderating risk. [ABSTRACT FROM AUTHOR]

The potential impacts of climate change on wheat were assessed for Kulmsa area in central highlands of Ethiopia using the Agricultural Production Systems sIMulator (APSIM)—wheat model. The objectives were to (i) evaluate the performance of wheat under increased temperatures with or without changes in rainfall and carbon dioxide (CO2) levels and (ii) assess the response of different wheat cultivars to projected future climates under improved management practices (optimal nitrogen rate, planting date, and density) (IMPs). The model was first calibrated and used to identify ranges of IMPs. Then, the model was used to (i) conduct sensitivity analysis of wheat in response to assumed elevated temperature (T), with and without change in rainfall and CO2 level, and to (ii) evaluate average effect of future worst-case climate change scenarios as predicted by an ensemble of three global climate models (GCM) under highest Representative Concentration Pathways (RCP8.5) for three future time frames, NF (2010–2039), MC (2040–2069), and EC (2070–2099). The simulation was evaluated for three wheat cultivars ("early", "medium", and "late") relative to their corresponding baseline values under the selected IMPs. The baseline climate was represented by the long-term (1980–2009) dataset and CO2 of 360 μmol/mol. Results showed that increased temperature above 4 °C alone had strong negative impacts on yields under the IMPs when CO2 staying constant at the baseline level. In contrast, climate change simulations with GCM projections under IMPs and elevated CO2 effect showed that wheat yield remained unchanged (− 0.4 to + 9%) for all three genotypes. This suggests that the IMPs and elevated CO2 were able to reduce the negative effect of elevated T on wheat yield as T stress did not go beyond optimal T range for wheat. Overall, climate change may not reduce wheat production in the climate of the location of study in the near future, midcentury, or end century. [ABSTRACT FROM AUTHOR]

This study assessed the growth of wheat under climate change conditions (increases in CO2 and temperature) in southwestern Iran. Future climate data were projected using long‐term climate data for radiation and minimum and maximum temperatures for the baseline period 1980–2010. The future climate scenarios made use of delta changes from the Coupled Model Intercomparison Project Phase 5 (CMIP5) in the R package of the Agricultural Model Intercomparison and Improvement Project for 2040–2070. After generating the weather data, the Agricultural Production System Simulator wheat model was applied to assess the potential impact of climate change on wheat yield and the relative growth rate, crop growth rate, total dry weight and leaf area index. Averaged across all locations, an increase of 1.6 and 2.3°C in annual temperature was projected under representative concentration pathway 4.5 (RCP4.5) and RCP8.5, respectively. The decrease in the average length of the growing season was 7.5 and 9.3% under RCP4.5 and RCP8.5, respectively, in the mid‐21st century with respect to baseline. The mean cumulative radiation will decrease by 11.6 and 14.3% averaged across all sites for RCP4.5 and RCP8.5, respectively. Grain yield will decrease at all sites for both RCPs. The greatest decrease in wheat yield was projected for Izeh under RCP4.5 and RCP8.5 (7.9 and 9.3%, respectively) for 2040–2070 relative to baseline. A greater grain yield at baseline than for the RCP8.5 and RCP4.5 scenarios was closely related to higher leaf area index, relative growth rate and crop growth rate values during the reproductive phase. Thus, these parameters can be defined as indicators of crop yield. [ABSTRACT FROM AUTHOR]