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Abstract: Understanding the confounding impacts of climatic and varietal changes on crop phenology is of importance to help make appropriate adaptation measures and target future directions for crop breeding. This paper investigated the changes in winter wheat phenology and analysed the impact of climatic, varietal and sowing date changes on crop phenology during the last three decades by combining field data with modeling. The APSIM crop model was used to quantify the changes in wheat phenology in terms of vernalization and photoperiod sensitivity as well as the changes in thermal time of pre- and post-flowering stage among wheat varieties at six sites in the North China Plain (NCP). The results showed that APSIM model could capture the phenological changes of winter wheat caused by interannual climatic change. There was a large spatial difference in the response pattern of wheat phenology to climatic and varietal changes across NCP. At most sites the increase in temperature shortened the growth duration of winter wheat mainly by shortening the growth period from sowing to jointing. The delayed sowing of winter wheat further shortened the growth period from sowing to jointing at two northern sites (Tianjin and Huimin). Continuous adoption of new wheat varieties shortened the growth period from sowing to jointing at Huimin, Xinxiang and Zhumadian, from jointing to flowering at Tianjin, but helped increase the length of growth period from jointing to flowering at Huimin, Tangyin and Xinxiang and post-flowering growth period at all the sites except for Tangyin. The findings of the study suggest that past cultivar changes in wheat in the NCP have been varied geographically. [Copyright &y& Elsevier]

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]

Abstract: In the North China Plain (NCP), while irrigation using groundwater has maintained a high-level crop productivity of the wheat–maize double cropping systems, it has resulted in rapid depletion of groundwater table. For more efficient and sustainable utilization of the limited water resources, improved understanding of how crop productivity and water balance components respond to climate variations and irrigation is essential. This paper investigates such responses using a modelling approach. The farming systems model APSIM (Agricultural Production Systems Simulator) was first calibrated and validated using 3 years of experimental data. The validated model was then applied to simulate crop yield and field water balance of the wheat–maize rotation in the NCP. Simulated dryland crop yield ranged from 0 to 4.5tha−1 for wheat and 0 to 5.0tha−1 for maize. Increasing irrigation amount led to increased crop yield, but irrigation required to obtain maximum water productivity (WP) was much less than that required to obtain maximum crop yield. To meet crop water demand, a wide range of irrigation water supply would be needed due to the inter-annual climate variations. The range was simulated to be 140–420mm for wheat, and 0–170mm for maize. Such levels of irrigation applications could potentially lead to about 1.5myear−1 decline in groundwater table when other sources of groundwater recharge were not considered. To achieve maximum WP, one, two and three irrigations (i.e., 70, 150 and 200mmseason−1) were recommended for wheat in wet, medium and dry seasons, respectively. For maize, one irrigation and two irrigations (i.e., 60 and 110mmseason−1) were recommended in medium and dry seasons, while no irrigation was needed in wet season. [Copyright &y& Elsevier]