Modelling shifts in agroclimate and crop cultivar response under climate change

This paper aims: (i) to identify at national scale areas where crop yield formation is currently most prone to climate‐induced stresses, (ii) to evaluate how the severity of these stresses is likely to develop in time and space, and (iii) to appraise and quantify the performance of two strategies for adapting crop cultivation to a wide range of (uncertain) climate change projections. To this end we made use of extensive climate, crop, and soil data, and of two modelling tools: N‐AgriCLIM and the WOFOST crop simulation model. N‐AgriCLIM was developed for the automatic generation of indicators describing basic agroclimatic conditions and was applied over the whole of Finland. WOFOST was used to simulate detailed crop responses at four representative locations. N‐AgriCLIM calculations have been performed nationally for 3829 grid boxes at a 10 × 10 km resolution and for 32 climate scenarios. Ranges of projected shifts in indicator values for heat, drought and other crop‐relevant stresses across the scenarios vary widely – so do the spatial patterns of change. Overall, under reference climate the most risk‐prone areas for spring cereals are found in south‐west Finland, shifting to south‐east Finland towards the end of this century. Conditions for grass are likely to improve. WOFOST simulation results suggest that CO₂ fertilization and adjusted sowing combined can lead to small yield increases of current barley cultivars under most climate scenarios on favourable soils, but not under extreme climate scenarios and poor soils. This information can be valuable for appraising alternative adaptation strategies. It facilitates the identification of regions in which climatic changes might be rapid or otherwise notable for crop production, requiring a more detailed evaluation of adaptation measures. The results also suggest that utilizing the diversity of cultivar responses seems beneficial given the high uncertainty in climate change projections.     

The implication of irrigation in climate change impact assessment: a European‐wide study

This study evaluates the impacts of projected climate change on irrigation requirements and yields of six crops (winter wheat, winter barley, rapeseed, grain maize, potato, and sugar beet) in Europe. Furthermore, the uncertainty deriving from consideration of irrigation, CO₂ effects on crop growth and transpiration, and different climate change scenarios in climate change impact assessments is quantified. Net irrigation requirement (NIR) and yields of the six crops were simulated for a baseline (1982–2006) and three SRES scenarios (B1, B2 and A1B, 2040–2064) under rainfed and irrigated conditions, using a process‐based crop model, SIMPLACE . We found that projected climate change decreased NIR of the three winter crops in northern Europe (up to 81 mm), but increased NIR of all the six crops in the Mediterranean regions (up to 182 mm yr^?1). Climate change increased yields of the three winter crops and sugar beet in middle and northern regions (up to 36%), but decreased their yields in Mediterranean countries (up to 81%). Consideration of CO₂ effects can alter the direction of change in NIR for irrigated crops in the south and of yields for C3 crops in central and northern Europe. Constraining the model to rainfed conditions for spring crops led to a negative bias in simulating climate change impacts on yields (up to 44%), which was proportional to the irrigation ratio of the simulation unit. Impacts on NIR and yields were generally consistent across the three SRES scenarios for the majority of regions in Europe. We conclude that due to the magnitude of irrigation and CO₂ effects, they should both be considered in the simulation of climate change impacts on crop production and water availability, particularly for crops and regions with a high proportion of irrigated crop area.     

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO2

Heat and drought are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO₂ concentrations. This study quantifies the combined and separate impacts of high temperature, heat and drought stresses on the current and future US rainfed maize and soybean production and for the first time characterizes spatial shifts in the relative importance of individual stress. Crop yields are simulated using the Agricultural Production Systems Simulator (APSIM), driven by high‐resolution (12 km) dynamically downscaled climate projections for 1995–2004 and 2085–2094. Results show that maize and soybean yield losses are prominent in the US Midwest by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of loss highly depends on the current vulnerability and changes in climate extremes. Elevated atmospheric CO₂ partially but not completely offsets the yield gaps caused by climate extremes, and the effect is greater in soybean than in maize. Our simulations suggest that drought will continue to be the largest threat to US rainfed maize production under RCP4.5 and soybean production under both RCP scenarios, whereas high temperature and heat stress take over the dominant stress of drought on maize under RCP8.5. We also reveal that shifts in the geographic distributions of dominant stresses are characterized by the increase in concurrent stresses, especially for the US Midwest. These findings imply the importance of considering heat and drought stresses simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management. The modeling framework of partitioning the total effects of climate change into individual stress impacts can be applied to the study of other crops and agriculture systems.     

Climate‐driven simulation of global crop sowing dates

Aim To simulate the sowing dates of 11 major annual crops at the global scale at high spatial resolution, based on climatic conditions and crop‐specific temperature requirements. Location Global. Methods Sowing dates under rainfed conditions are simulated deterministically based on a set of rules depending on crop‐ and climate‐specific characteristics. We assume that farmers base their timing of sowing on experiences with past precipitation and temperature conditions, with the intra‐annual variability being especially important. The start of the growing period is assumed to be dependent either on the onset of the wet season or on the exceeding of a crop‐specific temperature threshold for emergence. To validate our methodology, a global data set of observed monthly growing periods (MIRCA2000) is used. Results We show simulated sowing dates for 11 major field crops world‐wide and give rules for determining their sowing dates in a specific climatic region. For all simulated crops, except for rapeseed and cassava, in at least 50% of the grid cells and on at least 60% of the cultivated area, the difference between simulated and observed sowing dates is less than 1 month. Deviations of more than 5 months occur in regions characterized by multiple‐cropping systems, in tropical regions which, despite seasonality, have favourable conditions throughout the year, and in countries with large climatic gradients. Main conclusions Sowing dates under rainfed conditions for various annual crops can be satisfactorily estimated from climatic conditions for large parts of the earth. Our methodology is globally applicable, and therefore suitable for simulating sowing dates as input for crop growth models applied at the global scale and taking climate change into account.     

Uncertain effectiveness of Miscanthus bioenergy expansion for climate change mitigation explored using land surface,agronomic and integrated assessment models

Large-scale bioenergy plays a key role in climate change mitigation scenarios, but its efficacy is uncertain. This study aims to quantify that uncertainty by contrasting the results of three different types of models under the same mitigation scenario (RCP2.6-SSP2), consistent with a 2°C temperature target. This analysis focuses on a single bioenergy feedstock, Miscanthus × giganteus, and contrasts projections for its yields and environmental effects from an integrated assessment model (IMAGE), a land surface and dynamic global vegetation model tailored to Miscanthus bioenergy (JULES) and a bioenergy crop model (MiscanFor). Under the present climate, JULES, IMAGE and MiscanFor capture the observed magnitude and variability in Miscanthus yields across Europe; yet in the tropics JULES and IMAGE predict high yields, whereas MiscanFor predicts widespread drought-related diebacks. 2040–2049 projections show there is a rapid scale up of over 200 Mha bioenergy cropping area in the tropics. Resulting biomass yield ranges from 12 (MiscanFor) to 39 (JULES) Gt dry matter over that decade. Change in soil carbon ranges from +0.7 Pg C (MiscanFor) to −2.8 Pg C (JULES), depending on preceding land cover and soil carbon.2090–99 projections show large-scale biomass energy with carbon capture and storage (BECCS) is projected in Europe. The models agree that <2°C global warming will increase yields in the higher latitudes, but drought stress in the Mediterranean region could produce low yields (MiscanFor), and significant losses of soil carbon (JULES and IMAGE). These results highlight the uncertainty in rapidly scaling-up biomass energy supply, especially in dry tropical climates and in regions where future climate change could result in drier conditions. This has important policy implications—because prominently used scenarios to limit warming to ‘well below 2°C’ (including the one explored here) depend upon its effectiveness.     

Integrating mechanistic and empirical model projections to assess climate impacts on tree species distributions in northwestern North America

Empirical and mechanistic models have both been used to assess the potential impacts of climate change on species distributions, and each modeling approach has its strengths and weaknesses. Here, we demonstrate an approach to projecting climate‐driven changes in species distributions that draws on both empirical and mechanistic models. We combined projections from a dynamic global vegetation model (DGVM) that simulates the distributions of biomes based on basic plant functional types with projections from empirical climatic niche models for six tree species in northwestern North America. These integrated model outputs incorporate important biological processes, such as competition, physiological responses of plants to changes in atmospheric CO₂ concentrations, and fire, as well as what are likely to be species‐specific climatic constraints. We compared the integrated projections to projections from the empirical climatic niche models alone. Overall, our integrated model outputs projected a greater climate‐driven loss of potentially suitable environmental space than did the empirical climatic niche model outputs alone for the majority of modeled species. Our results also show that refining species distributions with DGVM outputs had large effects on the geographic locations of suitable habitat. We demonstrate one approach to integrating the outputs of mechanistic and empirical niche models to produce bioclimatic projections. But perhaps more importantly, our study reveals the potential for empirical climatic niche models to over‐predict suitable environmental space under future climatic conditions.     

Douglas‐fir plantations in Europe: a retrospective test of assisted migration to address climate change

We evaluate genetic test plantations of North American Douglas‐fir provenances in Europe to quantify how tree populations respond when subjected to climate regime shifts, and we examined whether bioclimate envelope models developed for North America to guide assisted migration under climate change can retrospectively predict the success of these provenance transfers to Europe. The meta‐analysis is based on long‐term growth data of 2800 provenances transferred to 120 European test sites. The model was generally well suited to predict the best performing provenances along north–south gradients in Western Europe, but failed to predict superior performance of coastal North American populations under continental climate conditions in Eastern Europe. However, model projections appear appropriate when considering additional information regarding adaptation of Douglas‐fir provenances to withstand frost and drought, even though the model partially fails in a validation against growth traits alone. We conclude by applying the partially validated model to climate change scenarios for Europe, demonstrating that climate trends observed over the last three decades warrant changes to current use of Douglas‐fir provenances in plantation forestry throughout Western and Central Europe.     

Characterizing drought stress and trait influence on maize yield under current and future conditions

Global climate change is predicted to increase temperatures, alter geographical patterns of rainfall and increase the frequency of extreme climatic events. Such changes are likely to alter the timing and magnitude of drought stresses experienced by crops. This study used new developments in the classification of crop water stress to first characterize the typology and frequency of drought‐stress patterns experienced by European maize crops and their associated distributions of grain yield, and second determine the influence of the breeding traits anthesis‐silking synchrony, maturity and kernel number on yield in different drought‐stress scenarios, under current and future climates. Under historical conditions, a low‐stress scenario occurred most frequently (ca. 40%), and three other stress types exposing crops to late‐season stresses each occurred in ca. 20% of cases. A key revelation shown was that the four patterns will also be the most dominant stress patterns under 2050 conditions. Future frequencies of low drought stress were reduced by ca. 15%, and those of severe water deficit during grain filling increased from 18% to 25%. Despite this, effects of elevated CO₂ on crop growth moderated detrimental effects of climate change on yield. Increasing anthesis‐silking synchrony had the greatest effect on yield in low drought‐stress seasonal patterns, whereas earlier maturity had the greatest effect in crops exposed to severe early‐terminal drought stress. Segregating drought‐stress patterns into key groups allowed greater insight into the effects of trait perturbation on crop yield under different weather conditions. We demonstrate that for crops exposed to the same drought‐stress pattern, trait perturbation under current climates will have a similar impact on yield as that expected in future, even though the frequencies of severe drought stress will increase in future. These results have important ramifications for breeding of maize and have implications for studies examining genetic and physiological crop responses to environmental stresses.     

A realistic meteorological assessment of perennial biofuel crop deployment: a Southern Great Plains perspective

Utility of perennial bioenergy crops (e.g., switchgrass and miscanthus) offers unique opportunities to transition toward a more sustainable energy pathway due to their reduced carbon footprint, averted competition with food crops, and ability to grow on abandoned and degraded farmlands. Studies that have examined biogeophysical impacts of these crops noted a positive feedback between near‐surface cooling and enhanced evapotranspiration (ET), but also potential unintended consequences of soil moisture and groundwater depletion. To better understand hydrometeorological effects of perennial bioenergy crop expansion, this study conducted high‐resolution (2‐km grid spacing) simulations with a state‐of‐the‐art atmospheric model (Weather Research and Forecasting system) dynamically coupled to a land surface model. We applied the modeling system over the Southern Plains of the United States during a normal precipitation year (2007) and a drought year (2011). By focusing the deployment of bioenergy cropping systems on marginal and abandoned farmland areas (to reduce the potential conflict with food systems), the research presented here is the first realistic examination of hydrometeorological impacts associated with perennial bioenergy crop expansion. Our results illustrate that the deployment of perennial bioenergy crops leads to widespread cooling (1–2 °C) that is largely driven by an enhanced reflection of shortwave radiation and, secondarily, due to an enhanced ET. Bioenergy crop deployment was shown to reduce the impacts of drought through simultaneous moistening and cooling of the near‐surface environment. However, simulated impacts on near‐surface cooling and ET were reduced during the drought relative to a normal precipitation year, revealing differential effects based on background environmental conditions. This study serves as a key step toward the assessment of hydroclimatic sustainability associated with perennial bioenergy crop expansion under diverse hydrometeorological conditions by highlighting the driving mechanisms and processes associated with this energy pathway.     

Genetic association with high‐resolution climate data reveals selection footprints in the genomes of barley landraces across the Iberian Peninsula

Landraces are local populations of crop plants adapted to a particular environment. Extant landraces are surviving genetic archives, keeping signatures of the selection processes experienced by them until settling in their current niches. This study intends to establish relationships between genetic diversity of barley (Hordeum vulgare L.) landraces collected in Spain and the climate of their collection sites. A high‐resolution climatic data set (5 × 5 km spatial, 1‐day temporal grid) was computed from over 2,000 temperature and 7,000 precipitation stations across peninsular Spain. This data set, spanning the period 1981–2010, was used to derive agroclimatic variables meaningful for cereal production at the collection sites of 135 barley landraces. Variables summarize temperature, precipitation, evapotranspiration, potential vernalization and frost probability at different times of the year and time scales (season and month). SNP genotyping of the landraces was carried out combining Illumina Infinium assays and genotyping‐by‐sequencing, yielding 9,920 biallelic markers (7,479 with position on the barley reference genome). The association of these SNPs with agroclimatic variables was analysed at two levels of genetic diversity, with and without taking into account population structure. The whole data sets and analysis pipelines are documented and available at https://eead-csic-compbio.github.io/barley-agroclimatic-association . We found differential adaptation of the germplasm groups identified to be dominated by reactions to cold temperature and late‐season frost occurrence, as well as to water availability. Several significant associations pointing at specific adaptations to agroclimatic features related to temperature and water availability were observed, and candidate genes underlying some of the main regions are proposed.     

Quantifying irrigation cooling benefits to maize yield in the US Midwest

Irrigation is an important adaptation strategy to improve crop resilience to global climate change. Irrigation plays an essential role in sustaining crop production in water‐limited regions, as irrigation water not only benefits crops through fulfilling crops' water demand but also creates an evaporative cooling that mitigates crop heat stress. Here we use satellite remote sensing and maize yield data in the state of Nebraska, USA, combined with statistical models, to quantify the contribution of cooling and water supply to the yield benefits due to irrigation. Results show that irrigation leads to a considerable cooling on daytime land surface temperature (?1.63°C in July), an increase in enhanced vegetation index (+0.10 in July), and 81% higher maize yields compared to rainfed maize. These irrigation effects vary along the spatial and temporal gradients of precipitation and temperature, with a greater effect in dry and hot conditions, and decline toward wet and cool conditions. We find that 16% of irrigation yield increase is due to irrigation cooling, while the rest (84%) is due to water supply and other factors. The irrigation cooling effect is also observed on air temperature (?0.38 to ?0.53°C) from paired flux sites in Nebraska. This study highlights the non‐negligible contribution of irrigation cooling to the yield benefits of irrigation, and such an effect may become more important in the future with continued warming and more frequent droughts.     

A process‐based approach to modelling impacts of climate change on the damage niche of an agricultural weed

Predicting the impact of climate change on the damage niche of an agricultural weed at a local scale requires a process‐based modelling approach that integrates local environmental conditions and the differential responses of the crop and weed to change. A simulation model of the growth and population dynamics of winter wheat and a competing weed, Sirius 2010, was calibrated and validated for the most economically damaging weed in UK cereals, Alopecurus myosuroides. The model was run using local‐scale climatic scenarios generated by the LARS‐WG weather generator and based on the HadCM3 projections for the periods 2046–2065 and 2080–2099 to predict the impact of climate change on the population dynamics of the weed and its effect on wheat yields. Owing to rising CO₂ concentration and its effect on radiation use efficiency of wheat, weed‐free wheat yields were predicted to increase. The distribution of the weed was predicted to remain broadly similar with a possible northward shift in range. Local‐scale variation in the impact of climate change was apparent owing to variation in soil type and water holding capacity. The competitive balance was shifted in favour of the deeper rooted crop under climate change, particularly on sites with lighter soils, owing to more frequent and severe drought stress events. Although the damage niche of A. myosuroides was predicted to reduce under climate change, it is likely that weeds with contrasting physiology, such as C4 species, will be better adapted to future conditions and pose a more serious threat.     

Increasing temperature cuts back crop yields in Hungary over the last 90 years

The transformation of climatic regime has an undeniable impact on plant production, but we rarely have long enough date series to examine the unfolding of such effects. The clarification of the relationship between crop plants and climate has a near‐immediate importance due to the impending human‐made global change. This study investigated the relationship between temperature, precipitation, drought intensity and the yields of four major cereals in Hungary between 1921 and 2010. The analysis of 30‐year segments indicated a monotonously increasing negative impact of temperature on crop yields. A 1°C temperature increase reduced the yield of the four main cereals by 9.6%–14.8% in 1981–2010, which revealed the vulnerability of Eastern European crop farming to recent climate change. Climate accounted for 17%–39% of yield variability over the past 90 years, but this figure reached 33%–67% between 1981 and 2010. Our analysis supports the claim that the mid‐20th century green revolution improved yields “at the mercy of the weather”: during this period, the impact of increasing fertilization and mechanisation coincided with climatic conditions that were more favourable than today. Crop yields in Eastern Europe have been stagnating or decreasing since the mid‐1980s. Although usually attributed to the large socio‐economic changes sweeping the region, our analysis indicates that a warming climate is at least partially responsible for this trend. Such a robust impact of increasing temperatures on crop yields also constitutes an obvious warning for this core grain‐growing region of the world.     

Assessing forest vulnerability to climate warming using a process‐based model of tree growth: bad prospects for rear‐edges

Growth models can be used to assess forest vulnerability to climate warming. If global warming amplifies water deficit in drought‐prone areas, tree populations located at the driest and southernmost distribution limits (rear‐edges) should be particularly threatened. Here, we address these statements by analyzing and projecting growth responses to climate of three major tree species (silver fir, Abies alba; Scots pine, Pinus sylvestris; and mountain pine, Pinus uncinata) in mountainous areas of NE Spain. This region is subjected to Mediterranean continental conditions, it encompasses wide climatic, topographic and environmental gradients, and, more importantly, it includes rear‐edges of the continuous distributions of these tree species. We used tree‐ring width data from a network of 110 forests in combination with the process‐based Vaganov–Shashkin‐Lite growth model and climate–growth analyses to forecast changes in tree growth during the 21st century. Climatic projections were based on four ensembles CO₂ emission scenarios. Warm and dry conditions during the growing season constrain silver fir and Scots pine growth, particularly at the species rear‐edge. By contrast, growth of high‐elevation mountain pine forests is enhanced by climate warming. The emission scenario (RCP 8.5) corresponding to the most pronounced warming (+1.4 to 4.8 °C) forecasted mean growth reductions of ?10.7% and ?16.4% in silver fir and Scots pine, respectively, after 2050. This indicates that rising temperatures could amplify drought stress and thus constrain the growth of silver fir and Scots pine rear‐edge populations growing at xeric sites. Contrastingly, mountain pine growth is expected to increase by +12.5% due to a longer and warmer growing season. The projections of growth reduction in silver fir and Scots pine portend dieback and a contraction of their species distribution areas through potential local extinctions of the most vulnerable driest rear‐edge stands. Our modeling approach provides accessible tools to evaluate forest vulnerability to warmer conditions.     

Spatial evaluation of switchgrass productivity under historical and future climate scenarios in Michigan

Switchgrass (Panicum virgatum) productivity on marginal and fertile lands has not been thoroughly evaluated in a systematic manner that includes soil–crop–weather–management interactions and to quantify the risk of failure or success in growing the crop. We used the Systems Approach to Land Use Sustainability (SALUS) model to identify areas with low risk of failing to having more than 8000 kg ha^?1 yr^?1 switchgrass aboveground net primary productivity (ANPP) under rainfed and unfertilized conditions. In addition, we diagnosed constraining factors for switchgrass growth, and tested the effect of nitrogen fertilizer application on plant productivity across Michigan for 30 years under three climate scenarios (baseline climate in 1981–2010, future climate with emissions using RCP 2.6 and RCP 6.0). We determined that <16% of land in Michigan may have at least 8 Mg ha^?1 yr^?1 ANPP under rainfed and unfertilized management with a low risk of failure. Of the productive low‐risk land, about 25% was marginal land, with more than 80% of which was affected by limited water availability due to low soil water‐holding capacity and shallow depth. About 80% of the marginal land was N limited under baseline conditions, but that percentage decreased to 58.5% and 42.1% under RCP 2.6 and RCP 6.0 climate scenarios, respectively, partly due to shorter growing season, smaller plants and less N demand. We also found that the majority of Michigan's land could have high switchgrass ANPP and low risk of failure with no more than 60 kgN ha^?1 fertilizer input. We believe that the methodology used in this study works at different spatial scales, as well as for other biofuel crops.     

Climate sensitivity of crop yields in the former state of Andhra Pradesh,India

Observed meteorological data demonstrates that temperature has increased by 0.74 °C in the last hundred years with the bulk of the warming occurring in the last 50 years. This paper examines the impact of climate change on five major crops in the former state of Andhra Pradesh using district level panel data for the period 1981–2010. Analysis of data shows that crop yields are significantly impacted by climate for rice, tobacco and groundnut. Crops grown in rabi are more susceptible to changes in climate than those in kharif, while drought crops like jowar are found to withstand changes in climate better than others.     

Revisiting projected shifts in the climate envelopes of North American trees using updated general circulation models

Global climate models are constantly being upgraded, but it is often not clear what these changes have on climate change impact projections. We used difference maps to directly compare downscaled projections of temperature and precipitation across North America for two versions (or generations) of three different Atmospheric‐Ocean General Circulation Models (AOGCM)s. We found that AOGCM versions differed in their projections for the end of the current century by up to 4 °C for annual mean temperature and 60% for annual precipitation. To place these changes in an ecological context, we reanalyzed our work on shifts in tree climate envelopes (CEs) using the newer‐generation AOGCM projections. Based on the updated AOGCMs, by the 2071–2100 period, tree CEs shifted up to 2.4 degrees further north or 2.6 degrees further south (depending on the AOGCM) and were about 10% larger in size. Despite considerable differences between versions of a given AOGCM, projections made by the newer version of each AOGCM were in general agreement, suggesting convergence across the three models studied here. Assessing the AOGCM outputs in this way provides insight into the magnitude and importance of change associated with AOGCM upgrades as they continue to evolve through time.     

Crassulacean acid metabolism (CAM) offers sustainable bioenergy production and resilience to climate change

Biomass production on low‐grade land is needed to meet future energy demands and minimize resource conflicts. This, however, requires improvements in plant water‐use efficiency (WUE) that are beyond conventional C3 and C4 dedicated bioenergy crops. Here we present the first global‐scale geographic information system (GIS)‐based productivity model of two highly water‐efficient crassulacean acid metabolism (CAM) candidates: Agave tequilana and Opuntia ficus‐indica. Features of these plants that translate to WUE advantages over C3 and C4 bioenergy crops include nocturnal stomatal opening, rapid rectifier‐like root hydraulic conductivity responses to fluctuating soil water potential and the capacity to buffer against periods of drought. Yield simulations for the year 2070 were performed under the four representative concentration pathway (RCPs) scenarios presented in the IPCC's 5th Assessment Report. Simulations on low‐grade land suggest that O. ficus‐indica alone has the capacity to meet ‘extreme’ bioenergy demand scenarios (>600 EJ yr^?1) and is highly resilient to climate change (?1%). Agave tequilana is moderately impacted (?11%). These results are significant because bioenergy demand scenarios >600 EJ yr^?1 could be met without significantly increasing conflicts with food production and contributing to deforestation. Both CAM candidates outperformed the C4 bioenergy crop, Panicum virgatum L. (switchgrass) in arid zones in the latitudinal range 30°S–30°N.     

Crop production structure and stability under climate change in South America

Southern South America is expected to play an increasingly important role in global food production, but climate change could seriously threaten it. Here we have analysed long‐term historical data for major crops (rice, oats, barley, sunflower, soybean, sorghum, wheat, maize) at subnational scale to (a) look for common features among crop yield dynamics, evaluating their structure and implications for the persistence of that crop; (b) address complex crop responses to changes in environmental growing conditions; and (c) identify climate impact hotspots that are crucial for adaptation and mitigation. We have proposed a novel methodological approach based on dynamics systems in order to understand the processes behind annual crop yield fluctuations. We report the results of general patterns in the internal process (biophysical adjustments by rapid negative feedbacks) regulating crop production and analyse how it influences crop persistence and yield ceilings. The structure of a crop yield dynamic system defines its behaviour, but climate variations could displace it from yield equilibrium and affect its stability. Our findings suggest that weather conditions have a stronger impact on yield growth at high rather than at low yield levels (non‐additive impacts). This allows agriculture management to be refined and applied more efficiently, weakening the relationship between crop productivity and climate change and predicting the response of crop production to yield‐improvement strategies. We have identified those crops and regions which are most vulnerable to the current climate change trends in southern South American agroecosystems. Our results allow us to point to new ways to enhance self‐regulatory success, maximising the efficiency of crop production and reducing climate impacts. We have discussed important implications for crop management and climate change mitigation in an area where agriculture plays a key role in its socioeconomic and ecologic dimensions.     

Cover crops mitigate direct greenhouse gases balance but reduce drainage under climate change scenarios in temperate climate with dry summers

Cover crops provide ecosystem services such as storing atmospheric carbon in soils after incorporation of their residues. Cover crops also influence soil water balance, which can be an issue in temperate climates with dry summers as for example in southern France and Europe. As a consequence, it is necessary to understand cover crops' long‐term influence on greenhouse gases (GHG) and water balances to assess their potential to mitigate climate change in arable cropping systems. We used the previously calibrated and validated soil–crop model STICS to simulate scenarios of cover crop introduction to assess their influence on rainfed and irrigated cropping systems and crop rotations distributed among five contrasted sites in southern France from 2007 to 2052. Our results showed that cover crops can improve mean direct GHG balance by 315 kg CO₂e ha⁻¹ year⁻¹ in the long term compared to that of bare soil. This was due mainly to an increase in carbon storage in the soil despite a slight increase in N₂O emissions which can be compensated by adapting fertilization. Cover crops also influence the water balance by reducing mean annual drainage by 20 mm/year but increasing mean annual evapotranspiration by 20 mm/year compared to those of bare soil. Using cover crops to improve the GHG balance may help to mitigate climate change by decreasing CO₂e emitted in cropping systems which can represent a decrease from 4.5% to 9% of annual GHG emissions of the French agriculture and forestry sector. However, if not well managed, they also could create water management issues in watersheds with shallow groundwater. Relationships between cover crop biomass and its influence on several variables such as drainage, carbon sequestration, and GHG emissions could be used to extend our results to other conditions to assess the cover crops' influence in a wider range of areas.