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Abstract. Bioenergy crop cultivation for lignocellulosic biomass is increasingly important for future climate mitigation, and it is assumed on large scales in Integrated Assessment Models (IAMs) that develop future land use change scenarios consistent with the dual constraint of sufficient food production and deep de-carbonization for low climate warming targets. In most global vegetation models, there is no specific representation of crops producing lignocellulosic biomass, resulting in simulation biases of biomass yields and other carbon outputs, and in turn of future bioenergy production. Here, we introduced four new plant functional types (PFTs) to represent four major lignocellulosic bioenergy crops, eucalypt, poplar and willow, Miscanthus, and switchgrass, in the global process-based vegetation model, ORCHIDEE. New parameterizations of photosynthesis, carbon allocation and phenology are proposed based on a compilation of field measurements. A specific harvest module is further added to the model to simulate the rotation of bioenergy tree PFTs based on their age dynamics. The resulting ORCHIDEE-MICT-BIOENERGY model is applied at 296 locations where field measurements of harvested biomass are available for different bioenergy crops. The new model can generally reproduce the global bioenergy crop yield observations. Biases of the model results related to grid-based simulations versus the point-scale measurements and the lack of fertilization and fertilization management practices in the model are discussed. This study sheds light on the importance of properly representing bioenergy crops for simulating their yields. The parameterizations of bioenergy crops presented here are generic enough to be applicable in other global vegetation models.

China is the world's most populous country and a major emitter of greenhouse gases. Consequently, much research has focused on China's influence on climate change but somewhat less has been written about the impact of climate change on China. China experienced explosive economic growth in recent decades, but with only 7% of the world's arable land available to feed 22% of the world's population, China's economy may be vulnerable to climate change itself. We find, however, that notwithstanding the clear warming that has occurred in China in recent decades, current understanding does not allow a clear assessment of the impact of anthropogenic climate change on China's water resources and agriculture and therefore China's ability to feed its people. To reach a more definitive conclusion, future work must improve regional climate simulations-especially of precipitation-and develop a better understanding of the managed and unmanaged responses of crops to changes in climate, diseases, pests and atmospheric constituents.

AbstractWheat growth is sensitive to temperature, but the effect of future warming on yield is uncertain. Here, focusing on China, we compiled 46 observations of the sensitivity of wheat yield to temperature change (SY,T, yield change per °C) from field warming experiments and 102 SY,T estimates from local process-based and statistical models. The average SY,T from field warming experiments, local process-based models and statistical models is −0.7±7.8(±s.d.)% per °C, −5.7±6.5% per °C and 0.4±4.4% per °C, respectively. Moreover, SY,T is different across regions and warming experiments indicate positive SY,T values in regions where growing-season mean temperature is low, and water supply is not limiting, and negative values elsewhere. Gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project appear to capture the spatial pattern of SY,T deduced from warming observations. These results from local manipulative experiments could be used to improve crop models in the future.

Significance Agricultural production is vulnerable to climate change. Understanding climate change, especially the temperature impacts, is critical if policymakers, agriculturalists, and crop breeders are to ensure global food security. Our study, by compiling extensive published results from four analytical methods, shows that independent methods consistently estimated negative temperature impacts on yields of four major crops at the global scale, generally underpinned by similar impacts at country and site scales. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops, with important implications for developing crop- and region-specific adaptation strategies to ensure future food supply of an increasing world population.

AbstractMicrobial communities in soils are generally considered to be limited by carbon (C), which could be a crucial control for basic soil functions and responses of microbial heterotrophic metabolism to climate change. However, global soil microbial C limitation (MCL) has rarely been estimated and is poorly understood. Here, we predicted MCL, defined as limited availability of substrate C relative to nitrogen and/or phosphorus to meet microbial metabolic requirements, based on the thresholds of extracellular enzyme activity across 847 sites (2476 observations) representing global natural ecosystems. Results showed that only about 22% of global sites in terrestrial surface soils show relative C limitation in microbial community. This finding challenges the conventional hypothesis of ubiquitous C limitation for soil microbial metabolism. The limited geographic extent of C limitation in our study was mainly attributed to plant litter, rather than soil organic matter that has been processed by microbes, serving as the dominant C source for microbial acquisition. We also identified a significant latitudinal pattern of predicted MCL with larger C limitation at mid‐ to high latitudes, whereas this limitation was generally absent in the tropics. Moreover, MCL significantly constrained the rates of soil heterotrophic respiration, suggesting a potentially larger relative increase in respiration at mid‐ to high latitudes than low latitudes, if climate change increases primary productivity that alleviates MCL at higher latitudes. Our study provides the first global estimates of MCL, advancing our understanding of terrestrial C cycling and microbial metabolic feedback under global climate change.

AbstractThe livestock sector is the largest source of anthropogenic methane emissions and is projected to increase in the future with the increased demand for livestock products. Here, we compare livestock methane emissions and emission intensities, defined by the amount of methane emitted per unit of animal proteins, estimated by different methodologies, and identify mitigation potentials in different regions of the world based on possible future projections. We show that emission intensity decreased for most livestock categories globally during 2000–2018, due to an increasing protein‐production efficiency, and the IPCC Tier 2 method should be used for capturing the temporal changes in the emission intensities. We further show that efforts on the demand‐side to promote balanced, healthy, and environmentally sustainable diets in most countries will not be sufficient to mitigate livestock methane emissions without parallel efforts to improve production efficiency. The latter efforts have much greater mitigating effects than demand‐side efforts, and hence should be prioritized in a few developing countries that contribute most of the mitigation potential.