Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO 2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop-and regionspecific adaptation strategies to ensure food security for an increasing world population.climate change impact | global food security | major food crops | temperature increase | yield C rops are sensitive to climate change, including changes in temperature and precipitation, and to rising atmospheric CO 2 concentration (1, 2). Among the changes, temperature increase has the most likely negative impact on crop yields (3, 4), and regional temperature changes can be projected from climate models with more certainty than precipitation. Meteorological records show that mean annual temperatures over areas where wheat, rice, maize, and soybean are grown have increased by ∼1°C during the last century (Fig. 1A) and are expected to continue to increase over the next century (Fig. 1B) -more so if greenhouse gas emissions continue to increase. It is thus necessary to quantify the impact of temperature increase on global crop yields, including any spatial variations, to first assess the risk to world food security, and then to develop targeted adaptive strategies to feed a burgeoning world population (5).Several methods have been developed to assess the impact of temperature increase on crop yields (6). Process-based crop models characterize crop growth and development in daily time steps and can be used to simulate the temperature response of yield either in areas around the globe defined by grids or at selected field sites or points (1, 7). A third method, statistical modeling, uses observed regional yields and historical weather records to fit regression functions to predict crop responses (8,9). A fourth method is to artificially warm crops under nearnatural field conditions to directly measure the impact of increased Significance Agricultural production is vulnerable to climate change. Understanding climate change, especially the temperature impacts, is...

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The uncertainties of China's gross primary productivity (GPP) estimates by global data-oriented products and ecosystem models justify a development of high-resolution data-oriented GPP dataset over China. We applied a machine learning algorithm

Photorefractive polymers with high diffraction efficiency in the visible and near-infrared regions of the electromagnetic spectrum have been developed. These polymers, which have a large dynamic range because of their high orientational birefringence, incorporate a dye designed to have a large dipole moment and a high linear polarizability anisotropy. Such polymers have enabled demonstrations of imaging through scattering media, using a holographic time-gating technique at a wavelength that is compatible with the transparency of biological tissues and with the emission of low-cost semiconductor laser diodes.

Abstract Resolving regional carbon budgets is critical for informing land-based mitigation policy. For nine regions covering nearly the globe, we collected inventory estimates of carbon stock changes complemented by satellite estimates of biomass changes where inventory data are missing. The net land-atmospheric carbon exchange (NEE) was calculated by taking the sum of carbon stock change and lateral carbon fluxes from crop and wood trade and riverine carbon export to the ocean. Summing up NEE from all regions, we obtained a global ‘bottom-up’ NEE for net land anthropogenic CO2 uptake of -2.2 ± 0.6 PgC yr−1 consistent with the independent top-down NEE from the global atmospheric carbon budget during 2000–2009. This estimate is so far the most comprehensive global bottom-up carbon budget accounting, which set up an important milestone for global carbon cycle studies. By decomposing NEE into component fluxes, we found that global soil heterotrophic respiration (SHR) amounts to a source of CO2 of 39 PgC yr−1 with an inter-quartile of 33 to 46 PgC yr−1, a much smaller portion of Net Primary Productivity than previously reported.

No consensus has yet been reached on the major factors driving the observed increase in the seasonal amplitude of atmospheric CO in the northern latitudes. In this study, we used atmospheric CO records from 26 northern hemisphere stations with a temporal coverage longer than 15 years, and an atmospheric transport model prescribed with net biome productivity (NBP) from an ensemble of nine terrestrial ecosystem models, to attribute change in the seasonal amplitude of atmospheric CO . We found significant (p < .05) increases in seasonal peak-to-trough CO amplitude (AMP ) at nine stations, and in trough-to-peak amplitude (AMP ) at eight stations over the last three decades. Most of the stations that recorded increasing amplitudes are in Arctic and boreal regions (>50°N), consistent with previous observations that the amplitude increased faster at Barrow (Arctic) than at Mauna Loa (subtropics). The multi-model ensemble mean (MMEM) shows that the response of ecosystem carbon cycling to rising CO concentration (eCO ) and climate change are dominant drivers of the increase in AMP and AMP in the high latitudes. At the Barrow station, the observed increase of AMP and AMP over the last 33 years is explained by eCO (39% and 42%) almost equally than by climate change (32% and 35%). The increased carbon losses during the months with a net carbon release in response to eCO are associated with higher ecosystem respiration due to the increase in carbon storage caused by eCO during carbon uptake period. Air-sea CO fluxes (10% for AMP and 11% for AMP ) and the impacts of land-use change (marginally significant 3% for AMP and 4% for AMP ) also contributed to the CO measured at Barrow, highlighting the role of these factors in regulating seasonal changes in the global carbon cycle.

Pronounced warming occurring on the Tibetan Plateau is expected to stimulate alpine grassland growth but could also increase atmospheric aridity that limits photosynthesis. But there lacks a systematic assessment of the impact of atmospheric aridity on alpine grassland productivity. Here we combine satellite observations, flux‐tower‐based productivity, and model simulations to quantify the effect of atmospheric aridity on grassland productivity and its temporal change between 1982 and 2011. We found a negative impact of atmospheric vapor pressure deficit on grassland productivity. This negative effect becomes increasingly intensified in terms of the impact severity and extent, suggesting an increasingly important role of atmospheric aridity on productivity. We further demonstrated that this negative effect is mitigated but cannot be overcompensated by the positive effect of rising CO2. Given that vapor pressure deficit is projected to further increase by ~10–38% in the future, Tibetan alpine grasslands will face an increasing stress of atmospheric drought.

Ecosystem water-use efficiency (EWUE) is an indicator of carbon-water interactions and is defined as the ratio of carbon assimilation (GPP) to evapotranspiration (ET). Previous research suggests an increasing long-term trend in annual EWUE over many regions and is largely attributed to the physiological effects of rising CO2 . The seasonal trends in EWUE, however, have not yet been analyzed. In this study, we investigate seasonal EWUE trends and responses to various drivers during 1982-2008. The seasonal cycle for two variants of EWUE, water-use efficiency (WUE, GPP/ET), and transpiration-based WUE (WUEt , the ratio of GPP and transpiration), is analyzed from 0.5° gridded fields from four process-based models and satellite-based products, as well as a network of 63 local flux tower observations. WUE derived from flux tower observations shows moderate seasonal variation for most latitude bands, which is in agreement with satellite-based products. In contrast, the seasonal EWUE trends are not well captured by the same satellite-based products. Trend analysis, based on process-model factorial simulations separating effects of climate, CO2 , and nitrogen deposition (NDEP), further suggests that the seasonal EWUE trends are mainly associated with seasonal trends of climate, whereas CO2 and NDEP do not show obvious seasonal difference in EWUE trends. About 66% grid cells show positive annual WUE trends, mainly over mid- and high northern latitudes. In these regions, spring climate change has amplified the effect of CO2 in increasing WUE by more than 0.005 gC m(-2)  mm(-1)  yr(-1) for 41% pixels. Multiple regression analysis further shows that the increase in springtime WUE in the northern hemisphere is the result of GPP increasing faster than ET because of the higher temperature sensitivity of GPP relative to ET. The partitioning of annual EWUE to seasonal components provides new insight into the relative sensitivities of GPP and ET to climate, CO2, and NDEP.