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Understanding sources of uncertainty in climate–crop modelling is critical for informing adaptation strategies for cropping systems. An understanding of the major sources of uncertainty in yield change is needed to develop strategies to reduce the total uncertainty. Here, we simulated rain-fed wheat cropping at four representative locations in China and Australia using eight crop models, 32 global climate models (GCMs) and two climate downscaling methods, to investigate sources of uncertainty in yield response to climate change. We partitioned the total uncertainty into sources caused by GCMs, crop models, climate scenarios and the interactions between these three. Generally, the contributions to uncertainty were broadly similar in the two downscaling methods. The dominant source of uncertainty is GCMs in Australia, whereas in China it is crop models. This difference is largely due to uncertainty in GCM-projected future rainfall change across locations. Our findings highlight the site-specific sources of uncertainty, which should be one step towards understanding uncertainties for more robust climate–crop modelling. Understanding major sources of uncertainty in yield change facilitates adaptation strategies for cropping systems. Using eight crop models, 32 global climate models and two climate downscaling methods, it is shown that their relative contribution to uncertainty in climate–crop modelling depends on location.

Investigating how climate affects multiple consecutive crop growth stages is helpful to provide guidance for adopting appropriate agronomic practices. Based on the observed data from 51 agro-meteorological stations across China during 1981–2010, we qualified the spatio-temporal variability of eight consecutive phenological stages of rice [sowing (SD), emergence (ED), transplanting (TPD), tillering (TD), booting (BD), heading (HD), milk ripe (MRD), and maturity date (MD)] and the durations of three growth phases [vegetative growth phase (VGP), reproductive growth phase (RGP), and whole growth phase (WGP)]. We also explored the correlation and sensitivity of each of the growth phases to three climatic factors [i.e., mean temperature (Tmean), precipitation (PRE), and sunshine hours (SSH)]. We found that SD, ED, and TPD of single rice advanced by 0.22, 0.15, and 1.15 days 10a−1, while TD, BD, HD, MRD, and MD delayed by 0.26, 1.14, 0.66, 2.47, and 1.50 days 10a−1, respectively. For early rice, the dates of all the phenological stages advanced to different extents, except MRD. For late rice, SD, ED, BD, and MRD delayed, while dates of the other phenological stages advanced. The durations of VGP, RGP, and WGP prolonged for both single rice and early rice, but these shortened for late rice. Overall, the durations of three growth phases were negatively correlated with Tmean, but positively correlated with PRE and SSH during corresponding growth phase across rice cultivation region. Sensitivity analysis indicated that increases in temperature tended to reduce duration of single-rice and double-rice VGP. Increases in PRE tended to increase duration of late-rice RGP, and increases in SSH tended to increase duration of single-rice RGP. The results indicated that climate change during the past three decades had a negative impact on rice growth and development. However, the observed phenological changes indicated that agronomic practice with long seasonal cultivar has mitigated these adverse effects.

Global climate change results in more extreme temperature events, which poses a serious threat to wheat production in the North China Plain (NCP). Assessing the potential impact of temperature extremes on crop growth and yield is an important prerequisite for exploring crop adaptation measures to deal with changing climate. In this study, we evaluated the effects of heat and frost stress during wheat sensitive period on grain yield at four representative sites over the NCP using Agricultural Production System Simulator (APSIM)-wheat model driven by the climate projections from 20 Global Climate Models (GCMs) in the Coupled Model Inter-comparison Project phase 6 (CMIP6) during two future periods of 2031-2060 (2040S) and 2071-2100 (2080S) under societal development pathway (SSP) 245 and SSP585 scenarios. We found that extreme temperature stress had significantly negative impacts on wheat yield. However, increased rainfall and the elevated atmospheric CO

Climate change has had a considerable impact on potato production in Agro-Pastoral Ecotone (APE) in North China over the past several decades and it will continue to influence the growth of potato. Thus, understanding the impact of climate change on potato production is critical for future food security in this region. In this study, the calibrated APSIM-Potato model was used to assess the impact of future climate change on potato at Zhangbei (ZB) and Wuchuan (WC) experimental stations. The daily climate data were statistically downscaled from 32 global climate models under two Representative Concentration Pathways (RCP4.5 and RCP8.5). The results showed that potato yield under rainfed condition at ZB site respectively increased by 7.3% and 6.7% in the 2030s, 25.8% and 21.8% in the 2060s and 44.7% and 51.9% in 2090s under RCP4.5 and RCP8.5 scenarios. Potato yield under irrigated condition at WC site increased respectively by 5.5%, 10.0% and 15.1% in the 2030s, 2060s and 2090s under RCP4.5 scenario and by 5.7%, 20.9% and 41.1% under RCP8.5 scenario. Both evapotranspiration and water use efficiency increased under future climate change. Based on the statistical analysis, 70% of the variation in potato yield under rainfed condition at ZB site and 50% of it under irrigated condition at WC site were driven by future climate change. We concluded that rainfed potato yield will be enhanced more by future climate change than irrigation system. Our study filled the knowledge gap in understanding the potential effects of future climate change on potato production under different water management measures, and will be useful in developing adaptable strategies to enhance potato yield in the APE region under future climate change.

Climate warming has and will continue to exert a significantly impact on crop phenology in the past and coming decades. Combining observed data of phenology and a crop growth model provides a good approach for quantitating the effects of climate warming and crop management on crop phenology. The purpose of this study is to determine the impacts of temperature change, sowing date (SD) adjustment and cultivar shift on maize phenology in northern China during 1981–2010. Results indicated that climate warming caused anthesis date (AD) and maturity date (MD) of maize to advance by 0.2–5.5 and 0.6–11.1 d/10a, respectively. Due to climate-driven changes in maize phenology, three growth periods of maize, i.e., vegetative growth period (VGP; from sowing to anthesis), reproductive growth period (RGP; from anthesis to maturity) and whole growth period (WGP; from sowing to maturity) shortened by 0.2–5.5, 0.4–5.6 and 0.6–11.1 d/10a, respectively. With SD adjustment (i.e., SD advancement), AD and MD occurred early by 0.5–2.6 and 0.1–3.4 d/10a, respectively. SD adjustment caused duration of VGP of maize to prolong. However, duration of RGP slightly shortened by 0.1–1.3 d/10a. Furthermore, due to cultivar shift, MD of maize significantly delayed by 4.9–12.2 d/10a. Durations of VGP, RGP and WGP of maize prolonged by 0.2–4.1, 1.6–8.4 and 4.3–11.8 d/10a, respectively. In conclusion, our results indicated that cultivar shift, to some extent, could mitigate the negative impact of climate warming on maize phenology.

Multi-model ensemble climate projections in combination with crop models are increasingly used to assess the impact of future climate change on agricultural systems. In this study, we used a biophysical process-oriented CERES-Rice crop model driven by downscaled future climate data from 28 Global Climate Models (GCMs) under two emissions scenarios: representative concentration pathway (RCP) 4.5 and RCP8.5, for phase five of the Coupled Model Intercomparison Project (CMIP5) to project the effects of climate change on rice yields in three future time periods in the Northeast China Plain (NECP). The results showed that without consideration of CO2 effects, rice yield would increase by 1.3%, 1.3%, and 0.4% in the 2030s, 2060s, and 2090s, respectively, under the RCP4.5 scenario. Rice yield would change by +1.1%, −2.3%, and −10.7% in the 2030s, 2060s, and 2090s, respectively, under the RCP8.5 scenario. With consideration of CO2 effects, rice yield during the 2030s, 2060s, and 2090s would increase by 5.4%, 10.0%, and 11.6% under RCP4.5, and by 6.4%, 12.9%, and 15.6% under RCP8.5, respectively. The rice-growing season would be shortened by 2 to 5 weeks in the future. Overall, the future climate would have positive effects on rice yields in the NECP. Although uncertainties in our study on the impact of climate change on rice might arise from the choice of crop model and GCMs, the results are important for informing policy makers and developing appropriate strategies to improve rice productivity in China.

Climate change would exert significantly impact on crop yield by altering crop growth and development processes. Therefore, to ensure food security, it is necessary to assess the response and adaptation of crop phenology to the natural (mainly climate change) and artificial (including sowing date (SD) change and cultivar shift) factors. In this study, using field data from 113 agro-meteorological experiment stations across China, along with the Agricultural Production System Simulator (APSIM) oryza model, we investigated the trends of rice phenology in relation to climate change and agronomic factors (i.e., SD change and cultivar shift) from 1981 to 2010. We found that flowering date (FD) and maturity date (MD) of single-rice were delayed by 0.3 and 1.4 days 10a−1, respectively, but FD and MD of double-rice were advanced by 0.7–0.8 and 0.2–1.1 days 10a−1, respectively. Climate change advanced FD and MD of rice at representative stations except FD of late-rice, and shortened length of rice growth period. SD change of rice mainly affected duration of vegetative growth phase (VGP, from SD to FD), but had no significant impact on duration of reproductive growth phase (RGP, from FD to MD). Cultivar shift delayed FD and MD of rice at all representative stations except late-rice at Lianhua. Moreover, cultivar shift prolonged the duration of rice RGP by 0.2–2.8 days 10a−1. Overall, the results suggested that rice phenology was adapting to ongoing climate change by SD change and adoption of cultivars with longer RGP. Therefore, crop phenological characteristics should be sufficiently taken into account to develop adaptation strategies in the future.

The land cover and management changes have strong feedbacks to climate through surface biophysical and biochemical processes. Agricultural phenology dynamic exerted measurable impacts on land surface properties, biophysical process and climate feedback in particular times at local/regional scale. But the responses of climate feedback through surface biophysical process to sowing date shift in the winter wheat ecosystem have been overlooked, especially at winter dormancy period. Considering the large cultivation area, unique surface property and phenology shift of winter wheat in the North China Plain, we first validated the SiBcrop model. Then, we used it to investigate the dynamics of leaf area index (LAI) and canopy temperature (Tc) under two planting date scenarios (Early Sowing: EP; Late Sowing: LP) of winter wheat at 10 selected stations. Finally, the surface energy budget was analyzed and interpreted. The results showed that the SiBcrop with a modified crop phenology scheme better simulated the seasonal dynamic of LAI, Tc, phenology, and surface heat fluxes. Earlier sowing date had higher LAI with earlier development than later sowing date. But the response of Tc to sowing date exhibited opposite patterns during the dormancy and active growth periods: EP led to higher Tc (0.05 K) than LP in the dormancy period and lower Tc (−0.2 K) in the growth period. The highest difference (0.6 K) between EP and LP happened at the time when wheat was sown in EP but wasn't in LP. The higher LAI captured more net radiation with lower surface albedo for warming, whist surface energy partitioning exerted cooling effect. The relative contributions of albedo-radiative process and partitioning-non-radiative process determined the climate effect of sowing date shift. The spatial pattern of the climate response to sowing date was influence by precipitation and air temperature. The study highlight that the climate effects of the sowing date shift in winter dormancy period are worthy of attention.

The North China Plain (NCP) has a severe water shortage. About 70% groundwater has been exploited for irrigation. Winter wheat – summer maize and pears are typical representative cereal crops and commercial fruit trees in this area, respectively. Water budget for the typical cropland and orchard ecosystems has a significant importance for agricultural production, especially in the NCP. Therefore, evapotranspiration (ET) and water balance were studied in the annual winter wheat – summer maize rotation (cropland) and pear orchard. Latent and sensible heat fluxes were measured by eddy covariance. Annual ET for pear trees was 764 mm and for both crops was 690 mm. The difference of ET between these two ecosystems was about equal to one irrigation. Transpiration was the main loss with the mean proportion of 63% for crops and 76% for pear trees. Wheat growth period is in the dry season and requires much more irrigation than maize. Mainly transpiration (80%) occurred from April through September in the both ecosystems which was also the growing period for pear trees. The annual precipitation was 469 mm and 444 mm in the pear orchard and cropland, respectively, although 80% of it occurred from June to September. Compared with the precipitation, annual mean water deficit was 294 mm for the pear trees and 244 mm for crops. The water shortage was severe in May while surplus water presented in July and August. Energy and ET fluxes were determined by atmospheric demand and the response of plants as controlled by plant phenology and crop selection. As the water shortage situation becomes more serious in the NCP, sustainability of the agricultural ecosystems could be improved by changing crop planting patterns, specifically, increasing the area ratio of maize to pear trees.

Irrigation of the conventional double cropping system of winter wheat and summer maize has caused serious problems regarding water resources and the environment on the Beijing-Tianjin-Hebei plain (HP), China. Reducing or replacing high water consumption crops (such as winter wheat) is the most impactful way to effectively save water in the HP region. In this study, crop coefficient and vegetation remote sensing data were used to estimate evapotranspiration ( ET a ) for winter wheat and summer maize on the HP from 2009 to 2013. For early maize, ET a and yield were based on the results from the APSIM (Agricultural Production System Simulator) crop model, which had been calibrated and validated using field experimental data. The effects on groundwater conservation and grain yield were estimated at the regional scale for the conventional winter wheat (WW) and summer maize (SM) double cropping system (Y 1 M 2 ) and three alternative cropping systems: three harvests in two years system (Y 2 M 3 , 1st year: WW-SM; 2nd year: early maize), four harvests in three years system (Y 3 M 4 , 1st year: WW-SM; the next two years: early maize), as well as a continuous early maize monoculture system (Y 1 M 1 ). The results showed that: (1) Relative to Y 1 M 2 , the water savings in each alternative cropping system exceeded 50% of the groundwater overdraft on the HP. The evapotranspirations of Y 2 M 3 , Y 3 M 4 and Y 1 M 1 decreased by 14%, 19% and 29% over that of Y 1 M 2 (740 mm), respectively. The economic water use efficiencies (WUE e ) of the alternative cropping systems were 7% –16% greater than that of Y 1 M 2 . The groundwater drop by Y 1 M 2 (0.59 m year − 1 ) was higher than that by Y 2 M 3 (0.20 m year − 1 ) and Y 3 M 4 (0.07 m year − 1 ), and the drop by Y 1 M 1 was negative, indicating a groundwater rise of 0.20 m. The groundwater overdraft in Y 1 M 2 was 160 mm (3.83 billion m 3 ), and the alternative cropping systems were more sustainable, with groundwater overdrafts that were less than the recharge value of 128 mm on the HP. (2) In comparison with Y 1 M 2 , the total yield was reduced by 2.28, 3.04 and 4.56 billion kg a − 1 (or 7.7%, 10.2% and 15.3%) for Y 2 M 3 , Y 3 M 4 and Y 1 M 1 , respectively, which accounted for 2 M 3 is a preferred alternative cropping system over Y 1 M 2 in the near future because of the advantages of high WUE e , economic return, mitigated groundwater level decline and balance between wheat supply and demand on the HP. Y 1 M 1 , which had the least water use and highest WUE e and economic return, is an option for the most serious groundwater overdraft area despite a contradiction between the traditional dietary habit and complete abandonment of wheat. Y 3 M 4 is recommended as the transitional cropping system between Y 2 M 3 and Y 1 M 1 . The method in this study is applicable to relevant regional research, and the results can be of use to the government when formulating policies on cropping systems and groundwater management.

Excessive use of groundwater in irrigation (mainly for production of winter wheat) in the North China Plain (NCP) has resulted in markedly decreased groundwater levels. Alternative cropping systems may have potential to reduce groundwater use in the region. The APSIM (Agricultural Production System Simulator) farming systems model was used to simulate long-term (1981–2015) water use, net overdraft and crop yield for eight cropping systems. The wheat-maize double cropping system (WW–SM) in the study area resulted in overdrafts of 258 mm yr − 1 , about 100 mm yr − 1 more than estimated groundwater recharge. Although six of eight simulated systems reduced overdrafts below the estimated recharge value of 150 mm yr − 1 , a triple-cropping system consisting of winter wheat/summer maize followed by fallow and early maize (WW–SM/F–EM) in two years appears to be the most viable alternative. Annual grain yield under the triple cropping system was only 13% less than that under the current WW–SM double cropping system. Groundwater overdrafts under triple-cropping system were about equal to lateral recharge from the mountains, water brought in via the South-North Water Transfer (SNWT) project and water from other water-saving measures (e.g. plastic film mulching) in the region.

Our understanding of climate impacts and adaptations on crop growth and productivity can be accelerated by analyzing historical data over the past few decades. We used crop trial and climate data from 1981 to 2009 at 34 national agro-meteorological stations in the Huang-Huai-Hai Plain (HHHP) of China to investigate the impacts of climate factors during different growth stages on the growth and yields of winter wheat, accounting for the adaptations such as shifts in sowing dates, cultivars, and agronomic management. Maximum (Tmax) and minimum temperature (Tmin) during the growth period of winter wheat increased significantly, by 0.4 and 0.6 °C/decade, respectively, from 1981 to 2009, while solar radiation decreased significantly by 0.2 MJ/m2/day and precipitation did not change significantly. The trends in climate shifted wheat phenology significantly at 21 stations and affected wheat yields significantly at five stations. The impacts of Tmax and Tmin differed in different growth stages of winter wheat. Across the stations, during 1981–2009, wheat yields increased on average by 14.5% with increasing trends in Tmin over the whole growth period, which reduced frost damage, however, decreased by 3.0% with the decreasing trends in solar radiation. Trends in Tmax and precipitation had comparatively smaller impacts on wheat yields. From 1981 to 2009, climate trends were associated with a ≤ 30% (or ≤1.0% per year) wheat yield increase at 23 stations in eastern and southern parts of HHHP; however with a ≤ 30% (or ≤1.0% per year) reduction at 11 other stations, mainly in western part of HHHP. We also found that wheat reproductive growth duration increased due to shifts in cultivars and flowering date, and the duration was significantly and positively correlated with wheat yield. This study highlights the different impacts of Tmax and Tmin in different growth stages of winter wheat, as well as the importance of management (e.g. shift of sowing date) and cultivars shift in adapting to climate change in the major wheat production region.

Potato is a staple food crop in the agro-pastoral ecotone (APE) of North China. However, the potato yield is low and highly variable due to limited water and nutrient availabilities in the region. Irrigation and nitrogen (N) fertilization have been used widely to enhance potato yield but result in negative environmental impacts in the APE. This study aims to explore the optimum combinations of irrigation and N fertilization for different potato production goals by using APSIM-Potato model calibrated well by field experiments with different combinations of irrigation and N fertilizer conducted at the typical site in the APE. Long-term (1981–2010) simulation for potato yield, water use efficiency (WUE), nitrogen use efficiency (NUE), economic profits and environmental impacts were analyzed under different combinations of irrigation (IR, based on the soil water deficit, ranged from 10 (IR10) to 100 mm (IR100) with the interval of 10 mm) and N fertilization (ranged from 0 (N0) to 210 (N210) kg ha−1 with the interval of 30 kg ha−1). Combination of IR10 and N210 maximized potato yields in the whole APE, and the yield was highest in the middle APE, with the value of 35.2 t ha−1, which was 6.7% and 2.1% higher than that in the eastern and western APE. However, such water and nitrogen managements would cause annual decline of groundwater table by 1.6 m and N loss by 10.9 kg ha−1. In order to achieve the highest WUE, the irrigation amounts should be 124, 107 and 132 mm in the eastern, middle and western APE, respectively, coupled with 90 kg ha−1 N fertilizer, and the highest WUEs were 89.6 kg ha−1 mm−1, 93.1 kg ha−1 mm−1 and 84.8 kg ha−1 mm−1 in the eastern, middle and western APE. For highest FNUE, the combination should be IR10 and N30 across APE, and the highest values were 959 kg ha−1 kg−1, 1092 kg ha−1 kg−1 and 1022 kg ha−1 kg−1 in the eastern, middle and western APE. Moreover, to get the highest income, the irrigation ranged from IR50 to IR10 and the amounts of N fertilizers ranged from 30 kg ha−1 to 120 kg ha−1, and the maximum incomes were 18,250 CNY ha−1, 20,060 CNY ha−1 and 19,660 CNY ha−1 in the eastern, middle and western APE. In all, the combination that maximized the income could contain the relative higher yield, WUE, NUE and lower environmental sequence. Our study would be helpful in determining the optimal amounts of irrigation and N fertilization for different goals of potato production in the APE.

Crop production in the North China Plain (NCP) is heavily influenced by the unfolding climate change and water shortage. Groundwater overdraft for irrigation in this region has caused serious ecological and environmental problems. Cropping systems adjustment offers an effective approach for the sustainable use of groundwater. However, the assessment of the impacts of future climate change on crop production and water consumption under different cropping systems with/without straw mulching has not been reported in the NCP. In this study, we applied the well validated APSIM model to explore the implementation of five cropping systems (i.e., two maturities per year, 1Y2MS0; three maturities per two year without (with) straw mulching during the fallow period, 2Y3MS0 (2Y3MS1); and one maturity per year without (with) straw mulching during the fallow period, 1Y1MS0 (1Y1MS1)). Statistical downscaled daily climate data based on 33 global climate models (GCMs) were used to drive APSIM to simulate crop phenology, yield and water use under future climate change. We found that cropping system adjustment significantly reduced the amount of water required for irrigation, thereby decreasing groundwater overdraft to a certain extent. Straw mulching could have mitigating effect on groundwater overdraft. Multi-GCMs ensemble means show an increase in temperature, precipitation and solar radiation in the future. Under future climate change scenarios, the phenological date (e.g. flower and maturity dates) of maize and wheat were advanced due to climate warming. Our simulated results indicated that future climate change would have negative impact on maize yield across all cropping systems but have positive impact on wheat yield under most climate change scenarios. Both irrigation and groundwater overdraft reduced in the future due to decreased evapotranspiration and increased precipitation. We concluded that 2Y3MS1 would be the optimum cropping system to balance crop yield and groundwater overdraft. This knowledge can inform the development of improved regional impact assessments of the sustainability of multi-crop rotation systems.

Given climate change can potentially influence crop phenology and subsequent yield, an investigation of relevant adaptation measures could increase the understanding and mitigation of these responses in the future. In this study, field observations at 10 stations in the Huang-Huai-Hai Plain of China (HHHP) are used in combination with the Agricultural Production Systems Simulator (APSIM)–Wheat model to determine the effect of thermal time shift on the phenology and potential yield of wheat from 1981–2009. Warming climate speeds up winter wheat development and thereby decreases the duration of the wheat growth period. However, APSIM–Wheat model simulation suggests prolongation of the period from flowering to maturity (Gr) of winter wheat by 0.2–0.8 d∙10yr–1 as the number of days by which maturity advances, which is less than that by which flowering advances. Based on computed thermal time of the two critical growth phases of wheat, total thermal time from floral initiation to flowering (TT_floral_initiation) increasesd in seven out of the 10 investigated stations. Alternatively, total thermal time from the start of grainfilling to maturity (TT_start_ grain_fill) increased in all investigated stations, except Laiyang. It is thus concluded that thermal time shift during the past three decades (1981–2009) prolongs Gr by 0.2–3.0 d∙10yr–1 in the study area. This suggests that an increase in thermal time (TT) of the wheat growth period is critical for mitigating the effect of growth period reduction due to warming climatic condition. Furthermore, climate change reduces potential yield of winter wheat in 80% of the stations by 2.3–58.8 kg∙yr–1. However, thermal time shift (TTS) increases potential yield of winter wheat in most of the stations by 3.0–51.0 kg∙yr–1. It is concluded that wheat cultivars with longer growth periods and higher thermal requirements could mitigate the negative effects of warming climate on crop production in the study area.

Distinct climate changes since the end of the 1980s have led to clear responses in crop phenology in many parts of the world. This study investigated the trends in the dates of spring wheat phenology in relation to mean temperature for different growth stages. It also analyzed the impacts of climate change, cultivar shift, and sowing date adjustments on phenological events/phases of spring wheat in northern China (NC). The results showed that significant changes have occurred in spring wheat phenology in NC due to climate warming in the past 30 years. Specifically, the dates of anthesis and maturity of spring wheat advanced on average by 1.8 and 1.7 day (10 yr)−1. Moreover, while the vegetative growth period (VGP) shortened at most stations, the reproductive growth period (RGP) prolonged slightly at half of the investigated stations. As a result, the whole growth period (WGP) of spring wheat shortened at most stations. The findings from the Agricultural Production Systems Simulator (APSIM)-Wheat model simulated results for six representative stations further suggested that temperature rise generally shortened the spring wheat growth period in NC. Although the warming trend shortened the lengths of VGP, RGP, and WGP, the shift of new cultivars with high accumulated temperature requirements, to some extent, mitigated and adapted to the ongoing climate change. Furthermore, shifts in sowing date exerted significant impacts on the phenology of spring wheat. Generally, an advanced sowing date was able to lower the rise in mean temperature during the different growth stages (i.e., VGP, RGP, and WGP) of spring wheat. As a result, the lengths of the growth stages should be prolonged. Both measures (cultivar shift and sowing date adjustments) could be vital adaptation strategies of spring wheat to a warming climate, with potentially beneficial effects in terms of productivity.

Most studies do not consider the potential variation in carbon concentration among the different tree components of the same species in regional scale. This study examined the carbon concentrations of the components (i.e., foliage, branch, stem, and root) in a 10-year-old poplar species (Populus davidiana Dode) from the Desertification Combating Program of Northern China. The highest and lowest carbon concentrations were found in the stem and foliage, respectively. There was a significant difference in carbon concentrations among the different tree components. All of the observed carbon concentrations of tree components were lower than those predicted using the conversion factor of 0.5 applied to component biomass. Stem carbon made up 59.7% of the total tree biomass carbon. The power equation estimating proportion of tree biomass carbon against the independent variable of diameter at breast height explained more than 90% of the variability in allocation of carbon among tree components. Tree height, as a second independent variable is also discussed. Our results suggest that the difference in organic carbon concentration among tree components should be incorporated into accurately develop forest carbon budget. Moreover, further investigations on how the diameter at breast height equation developed in the present study performs across broader scales are required.

Climate change has already and will continue to exert a vital impact on crop yield and water use in the North China Plain (NCP). Currently, this plain is facing a dilemma between groundwater depletion and grain production demand. It is urgent to identify the impact of future climate change on crop yield and water consumption and then develop efficient adaptation strategies in the region. In this study, we used statistically downscaled daily climate data from 33 global climate models (GCMs) and two Representative Concentration Pathways (RCP4.5 and RCP8.5) for 61 stations distributed across the NCP and drove the well-validated APSIM model to simulate crop yield and water use for two future periods of 2031–2060 (2040s) and 2071–2100 (2080s). Data from all 33 GCMs show an increase in annual mean temperature and almost all the GCMs also show increases in annual mean solar radiation and annual total precipitation across the NCP. Future climate warming led to an advance in phenology for both winter wheat and summer maize, two typical crops in the NCP. However, the length of the reproductive growth period (RGP) of winter wheat was prolonged while that of summer maize was shortened under future climate scenarios across the NCP. Our simulated results show that future climate change had negative impacts on maize yield but positive impacts on wheat yield across the NCP. Mainly due to the shortening of the whole growth period, crop water consumption was largely decreased under future climate scenarios. The amount of irrigation required was also reduced mainly due to increased precipitation and decreased ET. Although future climate change would likely mitigate groundwater overdraft in most part of NCP, some areas in the northern NCP still had groundwater over-pumping in the future. Therefore, we suggest that it might be a good choice to change cropping system for reducing planting area of water-consuming crop (e.g. winter wheat) in those over-pumping areas to balance groundwater use and crop yield.

Recurring drought has caused large crop yield losses in Australia during past decades. Long-term drought forecasting is of great importance for the development of risk management strategies. Recently, large-scale climate drivers (e.g. El Nino-Southern Oscillation) have been demonstrated as useful in the application of drought forecasting. Machine learning-based models that use climate drivers as input are commonly adopted to provide drought forecasts as these models are easy to develop and require less information compared to physical-based models. However, few machine learning-based models have been developed to forecast drought conditions during growing season across all Australian cropping areas. In this study, we developed a growing season (Apr.-Nov.) meteorological drought forecasting model for each climate gauging location across the Australian wheatbelt based on multiple lagged (past) large-scale climate indices and the Random Forest (RF) algorithm. The Standardized Precipitation Index (SPI) was used as the response variable to measure the degree of meteorological drought. Results showed that the RF model could provide satisfactory drought forecasts in the eastern areas of the wheatbelt with Pearson's correlation coefficient r > 0.5 and normalized Root Mean Square Error (nRMSE)

Global food production to meet growing demand is facing serious challenges from changing climate. Efficient adaptation is an important approach for mitigating the effects of changing climate on crop production and secure food supply in the future. Maize is a critically important source of food, feed and fuel, and is highly vulnerable to warming climate. In our study, using Agricultural Production Systems sIMulator (APSIM) model, we designed different features of maize ideotypes sown at various times to maximize the yield and water use efficiency (WUE) under future climate conditions in the North China Plain (NCP). The future climate projections were sourced from one Global Climate Model (GCM) from the Coupled Model Inter-comparison Project phase 6 (CMIP6) under a high emission scenario of future societal development pathway (SSP) 585. The selected GCM projected future mean maximum (minimum) temperature during maize growing season to increase by 1.9 °C and 3.7 °C (1.5 °C and 3.2 °C) in 2040s (2031–2060) and 2080s (2071–2100) respectively, compared to the baseline (1981–2010). The mean solar radiation during maize growing season increased by 3.9% and 6.5%, and total precipitation rose by 17.3% and 21% in 2040s and 2080s, respectively. Our simulated results indicated future maize yield without adaptation decreased slightly by 2.3% in 2040s and 2.4% in 2080s, but WUE significantly increased by 11.8% and 26.6% in 2040s and 2080s, respectively. We found that delayed sowing date was able to increase maize yield and WUE under the future climate conditions. When the ideotypic cultivar and optimum sowing date were adopted, simulated yield increased by 132% and 124% in 2040s and 2080s, respectively, and WUE rose by 85% and 117%, respectively. Our simulated results indicate maize ideotypes under future climate should have a longer reproductive growing period, faster potential grain filling rate, larger maximum grain numbers and larger radiation use efficiency. Maize ideotypes based on simulated results from APSIM models could provide breeders and/or plant scientists with a road map to choose the ideal target traits for increasing maize production and adapting future climate.

Early and reliable seasonal crop yield forecasts are crucial for both farmers and decision-makers. Commonly-used methods for seasonal yield forecasting are based on process-based crop models or statistical regression-based models. Both have limitations, particularly in regard to accounting for growth stage-specific climate extremes (such as drought, heat, and frost). In this study, we firstly developed a hybrid yield forecasting approach by blending of multiple growth stage-specific indicators, i.e. APSIM (a process-based crop model)-simulated biomass, and climate extremes, NDVI (Normalized Difference Vegetation Index), and SPEI (Standardized Precipitation and Evapotranspiration Index) before forecasting dates, using a regression model (random forest or multiple linear regression). Plot-scale wheat yield (2008–2017) in the southeastern Australian wheat belt was dynamically forecasted at the end of several targeted growth stages as the growing season progressed to harvest. Results showed that the forecasting accuracy increased significantly for both systems as forecast time approached harvest time. The forecasting system based on random forest outperformed the forecasting system based on multiple linear regression at each forecasting event. Satisfactory yield forecasts occurred at one month (~35 days) prior to harvest (r = 0.85, LCCC = 0.81, MAPE = 17.6%, RMSE = 0.70 t ha−1, and ROC score = 0.90), and at two months before harvest (r = 0.62, LCCC = 0.53, MAPE = 27.1%, RMSE = 1.01 t ha−1, and ROC score = 0.88). In addition, drought events throughout the growing season were identified as the main factor causing yield losses in the wheat belt during the past decade. With the increasing availability of farming-related data, we expect that the yield forecasting system proposed in our study may be widely extended to other comparable cropping regions to produce sufficiently accurate wheat yield forecasts for stakeholders to develop strategic decisions in their respective roles.

Extensive studies had been conducted to investigate the impacts of climate change on maize growth and yield in recent decades; however, the dynamics of crop husbandry in response and adaptation to climate change were not taken into account. Based on field observations spanning from 1981 to 2009 at 167 agricultural meteorological stations across China, we found that solar radiation and temperature over the observed maize growth period had decreasing trends during 1981–2009, and maize yields were positively correlated with these climate variables in major production regions. The decreasing trends in solar radiation and temperature during maize growth period were mainly ascribed to the adoption of late maturity cultivars with longer reproductive growth period (RGP). The adoption of late maturing cultivars with longer RGP contributed substantially to grain yield increase during the last three decades. The climate trends during maize growth period varied among different production areas. During 1981–2009, decreases in mean temperature, precipitation and solar radiation over maize growth period jointly reduced yield most by 13.2–17.3% in southwestern China, by contrast in northwestern China increases in mean temperature, precipitation and solar radiation jointly increased yield most by 12.9–14.4%. Our findings highlight that the adaptations of maize production system to climate change through shifts of sowing date and genotypes are underway and should be taken into accounted when evaluating climate change impacts.

Using the detailed field experiment data from 1981 to 2009 at four representative agro-meteorological experiment stations in China, along with the Agricultural Production System Simulator (APSIM) rice-wheat model, we evaluated the impact of sowing/transplanting date on phenology and yield of rice-wheat rotation system (RWRS). We also disentangled the contributions of climate change, modern cultivars, sowing/transplanting density and fertilization management, as well as changes in each climate variables, to yield change in RWRS, in the past three decades. We found that change in sowing/transplanting date did not significantly affect rice and wheat yield in RWRS, although alleviated the negative impact of climate change to some extent. From 1981 to 2009, climate change jointly caused rice and wheat yield change by −17.4 to 1.5 %, of which increase in temperature reduced yield by 0.0–5.8 % and decrease in solar radiation reduced it by 1.5–8.7 %. Cultivars renewal, modern sowing/transplanting density and fertilization management contributed to yield change by 14.4–27.2, −4.7– −0.1 and 2.3–22.2 %, respectively. Our findings highlight that modern cultivars and agronomic management compensated the negative impacts of climate change and played key roles in yield increase in the past three decades.

The long-term field experiment data at four representative agro-meteorological stations, together with a crop simulation model, were used to disentangle the contributions of climate change, variety renewal, and fertilization management to rice yield change in the past three decades. We found that during 1981–2009 varieties renewal increased rice yield by 16%–52%, management improvement increased yield by 0–16%, and the contributions of climate change to rice yield varied from — 16% to 10%. Varieties renewal and management improvement offset the negative impacts of climate change on rice production. Among the major climate variables, decreases in solar radiation reduced rice yield on average by 0.1%per year. The impact of temperature change had an explicit spatial pattern. It increased yield by 0.04%–0.4% per year for single rice at Xinbin and Ganyu station and for late rice at Tongcheng station, by contrast reduced yield by 0.2%–0.4% per year for single rice at Mianyang station and early rice at Tongcheng station. During 1981–2009, rice varieties renewal was characterized by increases in thermal requirements, grain number per spike and harvest index. The new varieties were less sensitive to climate change than old ones. The development of high thermal requirements, high yield potential and heat tolerant rice varieties, together with improvement of agronomic management, should be encouraged to meet the challenges of climate change and increasing food demand in future.

As climate change could significantly influence crop phenology and subsequent crop yield, adaptation is a critical mitigation process of the vulnerability of crop growth and production to climate change. Thus, to ensure crop production and food security, there is the need for research on the natural (shifts in crop growth periods) and artificial (shifts in crop cultivars) modes of crop adaptation to climate change. In this study, field observations in 18 stations in North China Plain (NCP) are used in combination with Agricultural Production Systems Simulator (APSIM)-Maize model to analyze the trends in summer maize phenology in relation to climate change and cultivar shift in 1981–2008. Apparent warming in most of the investigated stations causes early flowering and maturity and consequently shortens reproductive growth stage. However, APSIM-Maize model run for four representative stations suggests that cultivar shift delays maturity and thereby prolongs reproductive growth (flowering to maturity) stage by 2.4−3.7 day per decade (d 10a−1). The study suggests a gradual adaptation of maize production process to ongoing climate change in NCP via shifts in high thermal cultivars and phenological processes. It is concluded that cultivation of maize cultivars with longer growth periods and higher thermal requirements could mitigate the negative effects of warming climate on crop production and food security in the NCP study area and beyond.

As an essential part of terrestrial ecosystems, farmland plays a critical role in the carbon cycle. The spatial and temporal characterization of farmland biomass and carbon sequestration capacity is important to understand the carbon cycle of a farmland system. The study area is located in mid-south Hebei Province (MSHP), which is a food production region in North China. Based on land-use data (1980, 1990, 2000 and 2008) and food production data (1984–2008), agricultural biological productivity and carbon capture capacity were estimated. In addition, the spatial-temporal characteristics and related influencing factors were analyzed. Regionwide, aboveground biomass increased from 600 g C·m−2·a−1 (1985) to 1200 g C·m−2·a−1 (2008) with an increase-decrease-increase pattern during the same period. Spatially, it increased in the piedmont plains and declined in the western mountains and piedmont plains. The carbon capture capacity of cropland in the piedmont area increased from 700 g C·m−2·a−1 to 1000 g C·m−2·a−1, and it declined in the low plain area. Mountainous and coastal areas had the lowest capability of agricultural carbon capture. Although farmland is a dynamic carbon pool overall, its carbon sequestration capacity is likely to be enhanced with proper farming practices.

The Simple Biosphere Model (SiB2) and the 2 × 2 km resolution National Land use/Land Cover database were used to investigate the effects of Land Use/Cover Change (LUCC) on land surface energy balance and climate in Jilin Province, northeast China, from 1990 to 2005. The spatial patterns of the components of surface energy balance (i.e., net radiation (R n), latent heat (LH), sensible heat (SH), and albedo (α)) and climate (i.e., canopy temperature (T c), diurnal temperature range (DTR)), as well as the roles of land cover type in variations of energy balance and climate, were investigated. The results showed that there were general similar trends in R n, LH, SH, and α in the LUCC process. The spatial patterns of T c and DTR also showed consistent relationships with LUCC processes. Leaf area index (LAI) and canopy conductance (g c) were found to be the key factors in controlling the spatial patterns of the components of surface energy balance and T c. Using linear correlation method, the gaps of the components of surface energy balance were well-explained by the differences of LAI and g c, and R n had a better correlation with T c and DTR, in the process of LUCC. The surface energy partitioning of R n into LH and SH could not only dampen or strengthen the temperature difference, but also change the relative size of albedo-based R n when the albedo gap was small, between land cover types.