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 CO₂ 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 region-specific adaptation strategies to ensure food security for an increasing world population.
The global distribution of the optimum air temperature for ecosystem-level gross primary productivity (Formula: see text) is poorly understood, despite its importance for ecosystem carbon uptake ...under future warming. We provide empirical evidence for the existence of such an optimum, using measurements of in situ eddy covariance and satellite-derived proxies, and report its global distribution. Formula: see text is consistently lower than the physiological optimum temperature of leaf-level photosynthetic capacity, which typically exceeds 30 °C. The global average Formula: see text is estimated to be 23 ± 6 °C, with warmer regions having higher Formula: see text values than colder regions. In tropical forests in particular, Formula: see text is close to growing-season air temperature and is projected to fall below it under all scenarios of future climate, suggesting a limited safe operating space for these ecosystems under future warming.
Earlier spring leaf unfolding is a frequently observed response of plants to climate warming. Many deciduous tree species require chilling for dormancy release, and warming-related reductions in ...chilling may counteract the advance of leaf unfolding in response to warming. Empirical evidence for this, however, is limited to saplings or twigs in climate-controlled chambers. Using long-term in situ observations of leaf unfolding for seven dominant European tree species at 1,245 sites, here we show that the apparent response of leaf unfolding to climate warming (ST, expressed in days advance of leaf unfolding per °C warming) has significantly decreased from 1980 to 2013 in all monitored tree species. Averaged across all species and sites, ST decreased by 40% from 4.0 ± 1.8 days °C(-1) during 1980-1994 to 2.3 ± 1.6 days °C(-1) during 1999-2013. The declining ST was also simulated by chilling-based phenology models, albeit with a weaker decline (24-30%) than observed in situ. The reduction in ST is likely to be partly attributable to reduced chilling. Nonetheless, other mechanisms may also have a role, such as 'photoperiod limitation' mechanisms that may become ultimately limiting when leaf unfolding dates occur too early in the season. Our results provide empirical evidence for a declining ST, but also suggest that the predicted strong winter warming in the future may further reduce ST and therefore result in a slowdown in the advance of tree spring phenology.
The reliable detection and attribution of changes in vegetation growth is a prerequisite for the development of strategies for the sustainable management of ecosystems. This is an extraordinary ...challenge. To our knowledge, this study is the first to comprehensively detect and attribute a greening trend in China over the last three decades. We use three different satellite‐derived Leaf Area Index (LAI) datasets for detection as well as five different process‐based ecosystem models for attribution. Rising atmospheric CO₂concentration and nitrogen deposition are identified as the most likely causes of the greening trend in China, explaining 85% and 41% of the average growing‐season LAI trend (LAIGS) estimated by satellite datasets (average trend of 0.0070 yr⁻¹, ranging from 0.0035 yr⁻¹to 0.0127 yr⁻¹), respectively. The contribution of nitrogen deposition is more clearly seen in southern China than in the north of the country. Models disagree about the contribution of climate change alone to the trend in LAIGSat the country scale (one model shows a significant increasing trend, whereas two others show significant decreasing trends). However, the models generally agree on the negative impacts of climate change in north China and Inner Mongolia and the positive impact in the Qinghai–Xizang plateau. Provincial forest area change tends to be significantly correlated with the trend of LAIGS(P < 0.05), and marginally significantly (P = 0.07) correlated with the residual of LAIGStrend, calculated as the trend observed by satellite minus that estimated by models through considering the effects of climate change, rising CO₂concentration and nitrogen deposition, across different provinces. This result highlights the important role of China's afforestation program in explaining the spatial patterns of trend in vegetation growth.
Abstract
Warming has resulted in increases in frequency, intensity and/or duration of droughts in most land regions over the globe. Nevertheless, knowledge on how ecosystem water use efficiency (WUE) ...responds to extreme drought stress and whether the responses are affected by drought timing is still limited. In this study, we examined the changes in ecosystem WUE under extreme drought years over Northern Eurasia during 1982–2011 and further assessed WUE responses to droughts with separate groupings designed to characterize the timing of extreme drought stress. We found that drought timing indeed influenced the responses of ecosystem WUE under extreme drought years. Negative impacts of extreme drought stress during the dry season on ecosystem WUE were more remarkable than those from extreme drought stress during the wet season. Particularly, impacts of droughts on ecosystem carbon–water interactions differed among ecosystem types due to the specific hydrothermal condition of each biome. The information provided by our analyses plays an importance role in identifying water use strategies of terrestrial vegetation in response to drought stress and will help improve our understanding and predictions of the response of ecosystem WUE to global environmental change.
We analyzed the spatiotemporal variations in surface air temperature and key climate change indicators over the Tibetan Plateau during a common valid period from 1979 to 2018 to evaluate the ...performance of different datasets on various timescales. We used observations from 22 in-situ observation sites, the CRA-40/Land (CRA) reanalysis dataset, the China Meteorological Forcing Dataset (CMFD), and the ERA-Interim (ERA) reanalysis dataset. The three datasets are spatially consistent with the in-situ observations, but slightly underestimate the annual mean surface air temperature. The daily mean surface air temperature estimated by the CRA, CMFD, and ERA datasets is closer to the in-situ observations after correction for elevation. The CMFD shows the best performance in simulating the annual mean surface air temperature over the Tibetan Plateau, followed by the CRA and ERA datasets with comparable performances. The CMFD is relatively accurate in simulating the daily mean surface air temperature over the Tibetan Plateau on an annual scale, whereas both the CRA and ERA datasets perform better in summer than in winter. The increasing trends in the annual mean surface air temperature over the Tibetan Plateau from 1979 to 2018 reflected by the CRA dataset and the CMFD are 0.5°C (10 yr)
−1
, similar to the in-situ observations, whereas the warming rate in the ERA dataset is only 0.3°C (10 yr)
−1
. The trends in the length of the growing season derived from the in-situ observations, the CRA, CMFD, and ERA datasets are 5.3, 4.8, 6.1, and 3.2 day (10 yr)
−1
, respectively. Our analyses suggest that both the CRA dataset and the CMFD perform better than the ERA dataset in modeling the changes in surface air temperature over the Tibetan Plateau.
Defined as the ratio between gross primary productivity (GPP) and evapotranspiration (ET), ecosystem‐scale water‐use efficiency (EWUE) is an indicator of the adjustment of vegetation photosynthesis ...to water loss. The processes controlling EWUE are complex and reflect both a slow evolution of plants and plant communities as well as fast adjustments of ecosystem functioning to changes of limiting resources. In this study, we investigated EWUE trends from 1982 to 2008 using data‐driven models derived from satellite observations and process‐oriented carbon cycle models. Our findings suggest positive EWUE trends of 0.0056, 0.0007 and 0.0001 g C m⁻² mm⁻¹ yr⁻¹under the single effect of rising CO₂(‘CO₂’), climate change (‘CLIM’) and nitrogen deposition (‘NDEP’), respectively. Global patterns of EWUE trends under different scenarios suggest that (i) EWUE‐CO₂shows global increases, (ii) EWUE‐CLIM increases in mainly high latitudes and decreases at middle and low latitudes, (iii) EWUE‐NDEP displays slight increasing trends except in west Siberia, eastern Europe, parts of North America and central Amazonia. The data‐driven MTE model, however, shows a slight decline of EWUE during the same period (−0.0005 g C m⁻² mm⁻¹ yr⁻¹), which differs from process‐model (0.0064 g C m⁻² mm⁻¹ yr⁻¹) simulations with all drivers taken into account. We attribute this discrepancy to the fact that the nonmodeled physiological effects of elevated CO₂reducing stomatal conductance and transpiration (TR) in the MTE model. Partial correlation analysis between EWUE and climate drivers shows similar responses to climatic variables with the data‐driven model and the process‐oriented models across different ecosystems. Change in water‐use efficiency defined from transpiration‐based WUEₜ(GPP/TR) and inherent water‐use efficiency (IWUEₜ, GPP×VPD/TR) in response to rising CO₂, climate change, and nitrogen deposition are also discussed. Our analyses will facilitate mechanistic understanding of the carbon–water interactions over terrestrial ecosystems under global change.
Wheat 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 (S
, yield change per °C) from field warming experiments and 102 S
estimates from local process-based and statistical models. The average S
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, S
is different across regions and warming experiments indicate positive S
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 S
deduced from warming observations. These results from local manipulative experiments could be used to improve crop models in the future.
Understanding land-surface biophysical feedbacks to the atmosphere is needed if we are to simulate regional climate accurately. In the Arctic, previous studies have shown that enhanced vegetation ...growth decreases albedo and amplifies warming. In contrast, on the Tibetan Plateau, a statistical model based on in situ observations and decomposition of the surface energy budget suggests that increased vegetation activity may attenuate daytime warming by enhancing evapotranspiration (ET), a cooling process. A regional climate model also simulates daytime cooling when prescribed with increased vegetation activity, but with a magnitude smaller than observed, likely because this model simulates weaker ET enhancement in response to increased vegetation growth.
In the Arctic, climate warming enhances vegetation activity by extending the length of the growing season and intensifying maximum rates of productivity. In turn, increased vegetation productivity reduces albedo, which causes a positive feedback on temperature. Over the Tibetan Plateau (TP), regional vegetation greening has also been observed in response to recent warming. Here, we show that in contrast to arctic regions, increased growing season vegetation activity over the TP may have attenuated surface warming. This negative feedback on growing season vegetation temperature is attributed to enhanced evapotranspiration (ET). The extra energy available at the surface, which results from lower albedo, is efficiently dissipated by evaporative cooling. The net effect is a decrease in daily maximum temperature and the diurnal temperature range, which is supported by statistical analyses of in situ observations and by decomposition of the surface energy budget. A daytime cooling effect from increased vegetation activity is also modeled from a set of regional weather research and forecasting (WRF) mesoscale model simulations, but with a magnitude smaller than observed, likely because the WRF model simulates a weaker ET enhancement. Our results suggest that actions to restore native grasslands in degraded areas, roughly one-third of the plateau, will both facilitate a sustainable ecological development in this region and have local climate cobenefits. More accurate simulations of the biophysical coupling between the land surface and the atmosphere are needed to help understand regional climate change over the TP, and possible larger scale feedbacks between climate in the TP and the Asian monsoon system.
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•PAN-CS composite mats with adherent nanofibers-nanospheres were prepared successfully.•The shoulder-to-shoulder electrospinning and electrospraying techniques were used as a novel ...way to prepare composites.•Nanospheres embedded into nanofibers could enlarge the three dimensional space of nanofibers.•The incorporation of CS into REC and amination process could enhance the adsorption performance for composite adsorbent.•APAN-CS/REC mats always exhibited high adsorption capacity with pH ranging widely from 2.0 to 6.5.
Chitosan (CS) has a high amine group content, while polyacrylonitrile (PAN) contains cyano-groups that can be easily converted to amine groups. Herein, a novel adsorbent consisting of PAN-CS mats was successfully prepared via the shoulder-to-shoulder electrospinning and electrospraying techniques, which could eliminate the obstacle of selecting a co-solvent system for dissolving PAN and CS together. The morphology of the resultant adsorbent with adherent nanofibers-nanospheres was observed due to the immobilization of the CS electrosprayed nanospheres into PAN electrospun nanofibrous mats. Furthermore, CS nanospheres and PAN nanofibers were alternately arranged which could enlarge the space between the nanofibers, facilitating the diffusion of heavy metals in solution. Afterwards, rectorite (REC) was introduced into the mats to achieve the predesigned intercalated structure formed between the CS chains and the interlayer of REC even acquired the desirable enhanced adsorption ability towards heavy metals. Based on this improvement, chemical modification was performed on the surface of PAN nanofibers to form aminated PAN (APAN) with more amine groups for reinforcing the adsorption performance. The adsorption experiments results showed that APAN-CS/REC mats exhibited at least a 2.0 times increase in the adsorption capacity of Pb2+ compared to the original PAN-CS composite mats.
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