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The long-term understanding of the carbon budget of cropping systems needs to consider varying meteorological conditions, site/soil conditions, crop selection, and management decisions. On the Canadian Prairies, a variety of crops are used in yearly rotation, often not repeating the same crop within a 3-year period. We measured net ecosystem production (NEP) in two cropping systems in southern Manitoba, Canada, for the 2006–2016 period. One system had continuous annual crops, whereas the other had a perennial phase for 4 years. NEP was calculated using the flux-gradient method, where the carbon dioxide gradient was measured with a tunable-diode laser analyser and the transfer coefficient was based on momentum similarity theory with inputs from sonic anemometer-thermometers. NEP varied from −100 (source) to +300 (sink) g C m −2 y −1 among four adjacent 4-ha fields and 10 years, depending on annual crop (corn, faba, spring wheat, barley, rapeseed, soybean) and environmental conditions. There was no period of 3 years or greater when NEP in the continuous annual crop rotation was different from carbon neutral. Inserting a 4-year perennial phase of an alfalfa/grass mix created a statistically significant carbon sink for NEP (P = 0.04), but the perennial period itself was carbon neutral. Enhanced ecosystem respiration was observed following termination of the perennial crop. Harvest practices varied from no harvest (in the establishment year of the perennial crop), grain removal only, grain + straw removal, and straight cutting of green biomass for silage. Once harvest removals were included, 3 of the 4 fields were carbon neutral, but one annual field had net carbon losses for some periods. Ecosystem respiration averaged about twice as large as harvest removals. Net carbon (mean ±S.E.) over the 11-year period for the annual cropping system (−78 ± 51 g C m −2 y −1 ) was not different from the annual-perennial system (−48 ± 47 g C m −2 y −1 ). [ABSTRACT FROM AUTHOR]

This study provides statistical emulators of crop yields based on global gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project Fast Track project. The ensemble of simulations is used to build a panel of annual crop yields from five crop models and corresponding monthly summer weather variables for over a century at the grid cell level globally. This dataset is then used to estimate, for each crop and gridded crop model, the statistical relationship between yields, temperature, precipitation and carbon dioxide. This study considers a new functional form to better capture the non-linear response of yields to weather, especially for extreme temperature and precipitation events, and now accounts for the effect of soil type. In- and out-of-sample validations show that the statistical emulators are able to replicate spatial patterns of yields crop levels and changes overtime projected by crop models reasonably well, although the accuracy of the emulators varies by model and by region. This study therefore provides a reliable and accessible alternative to global gridded crop yield models. By emulating crop yields for several models using parsimonious equations, the tools provide a computationally efficient method to account for uncertainty in climate change impact assessments. [ABSTRACT FROM AUTHOR]

Highlights: [•] RZ-SHAW model simulated actual evapotranspiration (AET) well as compared to latent heat fluxes obtained from the eddy covariance measurement. [•] RZ-SHAW model also simulated potential evapotranspiration (PET) well as compared to PET from weighing lysimeter. [•] Canopy temperature is well simulated with the RZ-SHAW model, which may be used as an index for crop water stresses. [Copyright &y& Elsevier]

• We determined frequency of environment types (ENVT) for US maize, soybean, and wheat. • Each ENVT corresponded to a combination of drought and heat stress during critical period. • Inter-annual variation in drought and heat stress was higher than spatial variation. • The ENVT scheme explained observed variation in average actual yield for the three crops. • ENVTs can be used to link field-year experiments with target production environments. The impact of agricultural technologies on crop yield is influenced by the environment type (ENVT) as determined by weather and soil. Understanding the correlation between the ENVT of the testing site in relation to the ENVT of the target production region is important for the evaluation and scaling out of agricultural technologies. Here we propose and apply the first explicit method to characterize ENVTs for major rainfed maize, soybean, and wheat producing regions in the United States. We combined a tested spatial framework, Technology Extrapolation Domain (TED), with crop modeling, long-term (30-y) daily weather records, and soil and management databases to calculate the frequency of ENVTs per crop for major harvested areas. Each ENVT was determined based on the intensity of drought and heat stress during key crop stages for yield determination. The ENVT repeatability was calculated based on the frequency of the most dominant ENVT in each TED. We found that inter-annual variation in drought and heat stress was larger than spatial variation. Our ENVTs explained 2x to 7x larger portion of the variance in actual yield compared to the existing TED framework that is based on long-term annual climate means and soil water storage. For maize and soybean, ca. 30% of their harvested area was located in TEDs with highly repeatable ENVTs (>66% of years). In contrast, only 15% of the wheat harvested area was located in TEDs with high ENVT repeatability. In comparison to the TED framework, the ENVTs defined here can help better capture G×E×M interactions and determine the environmental correlation between testing sites and target production environments. [ABSTRACT FROM AUTHOR]

• LAI can explain 41%−64% T/ET variation;. • WUE c was mainly controlled by climatic factors (i.e., T a , VPD, R n , T s);. • WUE e was jointly controlled by LAI and climatic factors (T a , EF);. • LAI exerted stronger controls on WUE e than climatic factors by regulating T/ET. • Carbon uptake regulated WUE e more, while water consumption controlled WUE c. Understanding the interactive responses of agroecosystem water use efficiency (WUE) to climatic and vegetation factors is significant for revealing how ecohydrological processes vary between the carbon and water cycles in the changing climate. Based on data from 11 eddy covariance flux sites for a total of 32 site-years in four typical agroecosystems, including winter wheat (Triticum aestivum L.), paddy rice (Oryza sativa L.), soybean (Glycine max L. Merr.) and summer maize (Zea mays L.), evapotranspiration (ET) of the four crops was partitioned based on the theory of underlying WUE. Seasonal dynamics of transpiration (T), ET, gross primary production (GPP), T-based WUE at the canopy level (WUE c) and ET-based WUE at the agroecosystem level (WUE e) were investigated. A series of climatic and vegetation factors affecting WUE c and WUE e were quantified using the path analysis method. T/ET was 0.67 ± 0.04 for summer maize, followed by winter wheat, soybean and paddy rice, with values of 0.65 ± 0.07, 0.60 ± 0.05 and 0.57 ± 0.02, respectively. T, ET, GPP and WUE e increased as crops grew but decreased as crops matured. However, WUE c did not change as apparently as WUE e since T and GPP changed synchronously throughout the growing season. Summer maize possessed the largest WUE c of 5.69 ± 0.29 g C kg−1 H 2 O, followed by winter wheat, soybean and paddy rice, with values of 4.47 ± 0.87, 3.79 ± 0.20 and 2.60 ± 0.17 g C kg−1 H 2 O, respectively. WUE e followed the same order as that of WUE c among the four croplands, with values of 3.32 ± 0.71, 2.73 ± 0.81, 1.90 ± 0.10 and 1.47 ± 0.09 g C kg−1 H 2 O, respectively. WUE c was mainly regulated by canopy water consumption than carbon sequestration, while carbon sequestration regulated WUE e more than water consumption at the ecosystem scale. WUE c was mainly controlled by climatic factors (vapor pressure deficit, net radiation, air temperature and soil temperature) in the croplands, while the leaf area index exerted stronger controls on WUE e variations than climatic factors by its strong regulation on T/ET in the four croplands. [ABSTRACT FROM AUTHOR]

• Intercropped wheat had higher water use efficiency than sole wheat. • Wheat outcompeted maize for soil water during the co-growth period. • Transpiration was higher in wheat border rows than sole wheat, especially during the dry period. • A method for evapotranspiration partitioning in wheat/maize strips was proposed. Climate change will likely intensify water shortages, so more attention should be given to the efficient use of agricultural water in agricultural production, especially under rainfed conditions. Therefore, studying and understanding crop water consumption amounts and patterns is of great importance. However, the amount of water consumed by the component crops in strip intercropping systems has received little attention. To close this knowledge gap, a two-year field experiment of sole wheat (Triticum aestivum L.), sole maize (Zea mays L.), and wheat/maize strip intercropping was carried out under rainfed conditions. Soil water content, sap flow, soil water evaporation, and evaporation of canopy interception were measured both in intercrops and sole crops. Soil water movement between strips, evapotranspiration components, and water use efficiency were calculated. Compared with corresponding sole crops, intercropping increased water consumption of wheat and maize during the growing period of each crop. Intercropped wheat obtained soil water from the adjacent maize strip during the co-growth period, while intercropped maize obtained soil water from the adjacent wheat strip after wheat harvest. The amount of water obtained by maize was much less than the amount of water obtained by wheat. The transpiration of intercropped wheat was greater than that of sole wheat, but the transpiration of intercropped maize was lower than that of sole maize. Compared with sole cropping, intercropping increased the sap flow rate of wheat in border rows but reduced sap flow rate of maize in border rows, and this phenomenon was pronounced in the case of drought. After wheat harvest, soil water evaporation from the intercropped wheat strip was less than that from sole wheat, and evaporation from the intercropped maize strip was significantly higher than that of sole maize. The two-year average water use efficiency of intercropped wheat was 32% more than that of sole wheat, and water use efficiency of intercropped maize was 10% less than that of sole maize. These results can improve the understanding of water consumption in wheat and maize of intercropping from the point of evapotranspiration partitioning, and provide implications for water management of intercropping system under rainfed conditions. [ABSTRACT FROM AUTHOR]

• A plastic phenology model was developed for simulating crop reproductive phase. • The model assumes a dynamic response of development rate to temperature. • Wheat, rice, and maize phenology observations under varied conditions were used. • The model effectively reduced phenology simulation error in a simple and effective way. Understanding how crop development rate responds to the environment provides the basis for evaluating the impact of climate change on crop yield. In most crop simulation models, temperature response functions of development rate during the reproductive growth period (RGP) are assumed to only vary with temperature and not with other environmental factors. However, studies have indicated that the response functions may be plastic with other factors. Until now, little attention has been paid to this type of response. Here, using extensively collected field observations and data from intentionally designed interval planting experiments with winter wheat (Triticum aestivum L.), rice (Oryza sativa L.), and spring maize (Zea mays L.), we show that temperature response functions during RGP are plastic with day of year of flowering/heading (DOY R). Coefficients of determination between DOY R and development rate were significant for 69% sites. Partial correlation coefficients between development rate, temperature, and DOY R suggest that DOY R explains almost the same variability in maturity date as temperature. The plastic model was developed by coupling DOY R with a linear temperature response function. The model can improve the fitting efficiency by 112%, while dependency between DOY R and temperature explains less than 25% of this improvement. The average RMSEs of simulated maturity date estimated by the plastic model in the three crops were 2.1, 2.5, and 3.7 d, respectively, while the corresponding values given by widely applied traditional models were 3.1, 6.5, and 7.4 d, respectively. Therefore, the plastic model can reduce simulation error by half. Moreover, simulation errors resulting from the plastic model have less systematic bias than traditional models. The plastic model simply and effectively provides accurate estimates of crop maturity and reduces the system deviation of the estimates. Coupling the plastic model of crop development with crop simulation models will likely decrease uncertainties in simulated yield under warming conditions. Additionally, results of this study will encourage future studies of other phenotype plasticity considered in current crop simulation models. [ABSTRACT FROM AUTHOR]