CO2 Fertilization Research Articles

How climate change and international trade will shape the future global soybean security pattern

Soybean planting is highly concentrated and sensitive to climate change, which makes global soybean security vulnerable to production fluctuations in the main producing countries. As an important trade commodity, the impacts of climate change on soybean production in the main producing countries can ripple globally through international trade. However, little is known about the spatial distribution of soybean security under future climate at the global scale. This study couples an ensemble of multi-crop models and a global economic model (GTAP, Global Trade Analysis Project) to evaluate variations in soybean yield of the top ten soybean-producing countries in the 2050s (2046–2055) and the consequent impacts on global soybean supply and price under a range of future climate scenarios. Our results show that (1) The top ten soybean-producing countries, accounting for nearly 97% of global soybean production, suffer an average soybean yield reduction of 0.82% (specific to each country: −5.81%∼7.05%), 0.43% (−23.5%∼11.72%) and 5.22% (−17.88%∼18.73%) under Representative Concentration Pathway (RCP) 2.6, RCP4.5 and RCP 8.5, respectively, when considering the fertilization effect of CO2. A substantial soybean yield loss of 19.51% (−28.86%∼2.97%) is projected under RCP8.5 without accounting for the CO2 fertilization effect. (2) Climate-induced yield reduction leads to insufficient soybean supply and higher price worldwide through the transmission of international trade, with the largest supply decline of 14.20% in Bolivia and the largest price increase of 91.19% in India. Regionally, soybean net-importing countries are more vulnerable because of the ripple effect of the soybean supply chain. For example, despite a simulated increase in soybean yield of 2.97%–18.73%, China's soybean supply will decline by 0.61%–2.27% due to import shortages from the United States and Brazil where severe soybean yield losses are witnessed. (3) Liberal trade does dampen the negative impact of climate change on global soybean supply and price by reducing trade costs and facilitating trade flows, but in soybean export-oriented regions, trade liberalization can result in increased exports at the expense of domestic soybean supply (e.g., Canada and Russia). Our findings highlight the necessity of developing a liberal trade policy that benefits all regions of the world and improving domestic soybean productivity to adapt to climate change.

Relationship between CO2 Fertilization Effects, and Stand Age, Stand Type, and Site Conditions

The CO2 fertilization effect (CFE) plays a crucial role in the amelioration of climate change. Many physiological and environmental factors, such as stand age, stand type, and site conditions, may affect the extent of the CFE. However, the relationship between the CFE and these factors remains elusive. In this study, we used the emerging gross primary production (GPP) remote sensing products, with GPP predicted using eddy covariance–light use efficiency models (EC-LUE GPP) based on satellite near-infrared reflectance of vegetation (NIRv GPP) and assessed with a random forest model to explore the CFE trends with stand age in a coniferous forest and a broad-leaved forest in Heilongjiang Province, China. We additionally compared the differences among the CFEs under different site conditions. The CFEs in coniferous forests and broad-leaved forests both showed a rapid increase in stands of 10 to 20 years of age, followed by a decline after reaching a maximum, with the rate of decline reducing with age. Eventually, CFE remained stable in stands near 100 years of age. However, the CFE in coniferous forests exhibited more extended periods of rapid increase and a higher maximum than in broad-leaved forests. Moreover, in this study, we used the site class index (SCI) to grade site conditions. The results demonstrate that the CFE differed significantly under different levels of site conditions, and these differences gradually decreased with age. The site with the highest SCI had fewer environmental restrictions on the CFE, and consequently, the CFE rate of decline was faster. Our results are of significance in understanding the CFE and adapting to future changes in atmospheric CO2 concentration.

Terrestrial Phosphorus Cycling: Responses to Climatic Change

Phosphorus (P) limits productivity in many ecosystems and has the potential to constrain the global carbon sink. The magnitude of these effects depends on how climate change and rising CO2 affect P cycling. Some effects are well established. First, P limitation often constrains CO2 fertilization, and rising CO2 often exacerbates P limitation. Second, P limitation and P constraints to CO2 fertilization are more common in warmer and wetter sites. Models that couple P cycling to vegetation generally capture these outcomes. However, due largely to differences between short-term and long-term dynamics, the patterns observed across climatic gradients do not necessarily indicate how climate change over years to decades will modify P limitation. These annual-to-decadal effects are not well understood. Furthermore, even for the well-understood patterns, much remains to be learned about the quantitative details, mechanisms, and drivers of variability. The interface between empirical and modeling work is particularly ripe for development.

Modelling the impact of forest management and CO2-fertilisation on growth and demography in a Sitka spruce plantation

Afforestation and reforestation to meet ‘Net Zero’ emissions targets are considered a necessary policy by many countries. Their potential benefits are usually assessed through forest carbon and growth models. The implementation of vegetation demography gives scope to represent forest management and other size-dependent processes within land surface models (LSMs). In this paper, we evaluate the impact of including management within an LSM that represents demography, using both in-situ and reanalysis climate drivers at a mature, upland Sitka spruce plantation in Northumberland, UK. We compare historical simulations with fixed and variable CO2 concentrations, and with and without tree thinning implemented. Simulations are evaluated against the observed vegetation structure and carbon fluxes. Including thinning and the impact of increasing CO2 concentration (‘CO2 fertilisation’) gave more realistic estimates of stand-structure and physical characteristics. Historical CO2 fertilisation had a noticeable effect on the Gross Primary Productivity seasonal–diurnal cycle and contributed to approximately 7% higher stand biomass by 2018. The net effect of both processes resulted in a decrease of tree density and biomass, but an increase in tree height and leaf area index.

Revisiting Climate-Related Agricultural Losses across South America and Their Future Perspectives

Climate plays a major role in the spatiotemporal distribution of most agricultural systems, and the economic losses related to climate and weather extremes have escalated significantly in the last decades. South America is one of the most productive agricultural areas of the globe. In recent years, remote sensing data and geographic information systems have been used to improve geo-environmental hazard assessment. However, food security is still highly dependent on small farmer practices that are frequently the most vulnerable to climate extremes. This work reviews climate and weather extremes’ impacts on crop production for South American countries, focusing on the projected ones considering different climate scenarios and countries. A positive trend in the productivity of maize, mainly related to agricultural improvements, was recently observed in Colombia, Ecuador, and Uruguay by up to 200%, as well as in the case of soybean in Bolivia and Uruguay by about 125%. Despite the generalized adverse impacts of climate extremes, results from agrometeorological models generally indicate an increase in crop production in southern regions of Chile (and highlands) and Brazil mainly related to increased temperature. Positive impacts in response to CO2 fertilization are also foreseen in Peru and Brazil (southeast, south, and Minas Gerais); in particular, in Brazil, increases in productivity can be raised by about 40%. The use of double-cropping systems, although with very good results in recent years, may also be at risk in a few decades, mainly due to forecasted precipitation decrease, delay in rainy season onset, and temperature increase. The development of timely early warning systems is imperative to produce technically accurate alerts and the interpretation of the risk assessment based on the link between producers and consumers. Promoting climate index insurance is crucial to build resilient food production, but its implementation should rely on regional or international support systems. Moreover, the implementation of adaptation and mitigation also requires climate-resilient technologies that involve an interdisciplinary approach.

Uncertainty in land-use adaptation persists despite crop model projections showing lower impacts under high warming

Climate change is expected to impact crop yields and alter resource availability. However, the understanding of the potential of agricultural land-use adaptation and its costs under climate warming is limited. Here, we use a global land system model to assess land-use-based adaptation and its cost under a set of crop model projections, including CO2 fertilization, based on climate model outputs. In our simulations of a low-emissions scenario, the land system responds through slight changes in cropland area in 2100, with costs close to zero. For a high emissions scenario and impacts uncertainty, the response tends toward cropland area changes and investments in technology, with average adaptation costs between −1.5 and +19 US$05 per ton of dry matter per year. Land-use adaptation can reduce adverse climate effects and use favorable changes, like local gains in crop yields. However, variance among high-emissions impact projections creates challenges for effective adaptation planning.

Using tree rings to detect a CO2 fertilization effect: a global review

Using tree rings to detect a CO2 fertilization effect: a global review

Effects of elevated CO2 concentration and experimental warming on morphological, physiological, and biochemical responses of winter wheat under soil water deficiency.

Global climate change and freshwater scarcity have become two major environmental issues that constrain the sustainable development of the world economy. Climate warming caused by increasing atmospheric CO2 concentration can change global/regional rainfall patterns, leading to uneven global seasonal precipitation distribution and frequent regional extreme drought events, resulting in a drastic reduction of available water resources during the critical crop reproduction period, thus causing many important food-producing regions to face severe water deficiency problems. Understanding the potential processes and mechanisms of crops in response to elevated CO2 concentration and temperature under soil water deficiency may further shed lights on the potential risks of climate change on the primary productivity and grain yield of agriculture. We examined the effects of elevated CO2 concentration (e[CO2]) and temperature (experimental warming) on plant biomass and leaf area, stomatal morphology and distribution, leaf gas exchange and mesophyll anatomy, rubisco activity and gene expression level of winter wheat grown at soil water deficiency with environmental growth chambers. We found that e[CO2] × water × warming sharply reduced plant biomass by 57% and leaf photosynthesis (P n) 50%, although elevated [CO2] could alleviated the stress from water × warming at the amount of gene expression in RbcL3 (128%) and RbcS2 (215%). At ambient [CO2], the combined stress of warming and water deficiency resulted in a significant decrease in biomass (52%), leaf area (50%), P n (71%), and G s (90%) of winter wheat. Furthermore, the total nonstructural carbohydrates were accumulated 10% and 27% and increased R d by 127% and 99% when subjected to water × warming and e[CO2] × water × warming. These results suggest that water × warming may cause irreversible damage in winter wheat and thus the effect of "CO2 fertilization effect" may be overestimated by the current process-based ecological model.

Greening rate in North Korea doubles South Korea

South and North Korea have experienced contrasting economic developments since the 1950s while sharing similar climates. Previous studies revealed an overall long-term greening trend across the Korean Peninsula based on greenness data from coarse-resolution satellite images. However, there has been no comprehensive comparison of the greenness patterns and the driving mechanisms between two countries due to the limitations of coarse-resolution satellite data. Here, we performed cross-calibration among Landsat sensors and adopted a phenology-based approach to generate Landsat annual maximum Normalized Difference Vegetation Index (NDVImax) time series for each pixel from 1986 to 2017. We found that over 1986–2017, the greening rate in North Korea was almost twice that of South Korea. Cropland in South Korea is the main source of the greening discrepancy. The expansion of agricultural facilities in the stable cropland area and urbanization in the cropland loss area of South Korea contributed 57% to the significant negative NDVImax trend, which was dominant over the forest NDVImax increase resulting from rising temperatures, CO2 fertilization effects and afforestation projects. However, in North Korea, CO2 fertilization effects in the stable cropland area and transition from grassland to cropland promoted an increase in NDVImax, despite decreasing NDVImax in forest areas due to deforestation. Our results highlight the need for delineating fine-scale land-use changes to advance our understanding of regional vegetation dynamics.

Unveiling the driver behind China’s greening trend: urban vs. rural areas

Urban and rural areas play an important role in the greenness change in China, despite exhibiting divergent landscape ecologies. Although recent studies have revealed an overall greening pattern in China, the relative contribution of urban and rural vegetation to nationwide greening trend and their driving mechanisms behind these changes remain poorly understood. Here, we first utilized a high-resolution land use/cover dataset (GlobeLand30) to establish a framework for distinguishing between urban and rural areas. We then assessed and compared the greenness changes in both urban and rural areas using multiple vegetation indices from 2000 to 2020. By employing Random Forest model and generalized linear model regression, we further investigated drivers behind the changes in urban and rural vegetation trends. Our results demonstrated a significant greening trend in China, and the greenness increased 13.71% from 2000 to 2020. Vegetation changes in both urban (+4.96%, 0.0011 yr−1) and rural areas (+14.25%, 0.0026 yr−1) have contributed positively to China’s greening trend, with their contribution being 11.3% and 88.7%, respectively. Urban core areas exhibited the largest trend magnitudes (0.0043 ± 0.0035 yr−1) among all the urban–rural subregions. Increased tree cover was identified as the primary driver of greening trends in both urban and rural areas, explaining 36% and 29% of the greening, respectively. However, the pathways of tree cover increase differed between urban and rural areas, with urban areas focusing on green space construction and rural areas implementing afforestation programs. In contrast, climate change and the CO2 fertilization effect had a greater contribution to the greening trend in rural areas than in urban areas. Our study demonstrates the positive role played by both urban and rural areas in China’s greening trends and elucidates the underlying mechanisms driving these changes, highlighting the need for differentiated strategies in urban and rural areas for future vegetation restoration.

Divergent trends in grassland degradation and desertification under land use and climate change in Central Asia from 2000 to 2020

Grassland degradation (within-state change) and desertification (state conversion from grasslands to deserts) are different states in the complex dynamic process of grassland deterioration. However, the dynamics and associated drivers of the two states have been rarely examined separately, which is critical for early warning and conservation policy making. Here, the grassland degradation and desertification in Central Asia (CA) were studied due to their evident vulnerability to climate extremes and human activities. We performed a two-step approach to identify the critical state zones first (i.e., grasslands, deserts, and the desertification zones) and then assess the vegetation dynamics within each zone. Finally, we quantified the roles of CO2 fertilization effect, climate change, climate variability, land use (LU), and anthropogenic climate change (ACC) on the vegetation dynamics in different state zones. The results showed that the areas of grasslands and sparse vegetation regions (including deserts and desertification zones) were stable from 2000 to 2020, but the trends of vegetation greenness were divergent with a reduction in grasslands and an increase in sparse vegetation regions. Furthermore, climate change and climate variability were the main driving force affecting grassland degradation in CA. Yet the vegetation greening in the desertification and desert zones was mainly driven by the rising CO2 and LU. Moreover, ACC degraded 20.63% of grasslands and sparsely vegetated lands in CA on the baseline of 2000. The results highlighted the risks of grassland degradation in CA. This study proposed a methodology to examine grassland degradation and desertification in detail and quantify the associated driving factors (especially ACC) at the pixel scale, which provided some insights on developing region-precise strategies for grassland conservation in CA and other drylands.

Impact of Elevated Atmospheric CO2 in Spartina maritima Rhizosphere Extracellular Enzymatic Activities

Atmospheric CO2 enrichment, which is caused to a large extent by anthropogenic activities, is known to interfere with sediment microbial communities via plant rhizospheres. The present work aimed to evaluate this interaction in Spartina maritima ((Curtis) Fernald.) rhizosediments, aiming to depict the impacts of atmospheric CO2 increase in the biogeochemical processes occurring in the rhizosphere of this pioneer and highly abundant Mediterranean halophyte. For this purpose, mesocosms trials were conducted, exposing salt marsh cores with S. maritima and its sediments to 410 and 700 ppm of CO2 while assessing rhizosediment extracellular enzymatic activities. An evident increase in dehydrogenase activity was observed and directly linked to microbial activity, indicating a priming effect in the rhizosphere community under increased CO2. Phosphatase showed a marked increase in rhizosediments exposed to elevated CO2, denoting a higher requirement of phosphate for maintaining higher biological activity rates. High sulphatase activity suggests a possible S-limitation (microbial or plant) due to elevated CO2, probably due to higher sulphur needs for protein synthesis, thus increasing the need to acquire more labile forms of sulphur. With this need to acquire and synthesize amino acids, a marked decrease in protease activity was detected. Most carbon-related enzymes suffered an increase under increased CO2. Overall, a shift in sediment extracellular enzymatic activity could be observed upon CO2 fertilization, mostly due to priming effects and not due to changes in the quality of carbon substrates, as shown by the sediment stable isotope signatures. The altered recycling activity of organic C, N, and P compounds may lead to an unbalance of these biogeochemical cycles, shifting the rhizosphere ecosystem function, with inevitable changes in the ecosystem services level.

Modelling the terrestrial nitrogen and phosphorus cycle in the UVic ESCM

Abstract. Nitrogen (N) and phosphorus (P) biogeochemical dynamics are crucial for the regulation of the terrestrial carbon cycle. In Earth system models (ESMs) the implementation of nutrient limitations has been shown to improve the carbon cycle feedback representation and, hence, the fidelity of the response of land to simulated atmospheric CO2 rise. Here we aimed to implement a terrestrial N and P cycle in an Earth system model of intermediate complexity to improve projections of future CO2 fertilization feedbacks. The N cycle is an improved version of the Wania et al. (2012) N module, with enforcement of N mass conservation and the merger with a deep land-surface and wetland module that allows for the estimation of N2O and NO fluxes. The N cycle module estimates fluxes from three organic (litter, soil organic matter and vegetation) and two inorganic (NH4+ and NO3-) pools and accounts for inputs from biological N fixation and N deposition. The P cycle module contains the same organic pools with one inorganic P pool; it estimates influx of P from rock weathering and losses from leaching and occlusion. Two historical simulations are carried out for the different nutrient limitation setups of the model: carbon and nitrogen (CN), as well as carbon, nitrogen and phosphorus (CNP), with a baseline carbon-only simulation. The improved N cycle module now conserves mass, and the added fluxes (NO and N2O), along with the N and P pools, are within the range of other studies and literature. For the years 2001–2015 the nutrient limitation resulted in a reduction of gross primary productivity (GPP) from the carbon-only value of 143 to 130 Pg C yr−1 in the CN version and 127 Pg C yr−1 in the CNP version. This implies that the model efficiently represents a nutrient limitation over the CO2 fertilization effect. CNP simulation resulted in a reduction of 11 % of the mean GPP and a reduction of 23 % of the vegetation biomass compared to the baseline C simulation. These results are in better agreement with observations, particularly in tropical regions where P limitation is known to be important. In summary, the implementation of the N and P cycle has successfully enforced a nutrient limitation in the terrestrial system, which has now reduced the primary productivity and the capacity of land to take up atmospheric carbon, better matching observations.

Global evaluation of terrestrial biogeochemistry in the Energy Exascale Earth System Model (E3SM) and the role of the phosphorus cycle in the historical terrestrial carbon balance

Abstract. The importance of carbon (C)–nutrient interactions to the prediction of future C uptake has long been recognized. The Energy Exascale Earth System Model (E3SM) land model (ELM) version 1 is one of the few land surface models that include both N and P cycling and limitation (ELMv1-CNP). Here we provide a global-scale evaluation of ELMv1-CNP using the International Land Model Benchmarking (ILAMB) system. We show that ELMv1-CNP produces realistic estimates of present-day carbon pools and fluxes. Compared to simulations with optimal P availability, simulations with ELMv1-CNP produce better performance, particularly for simulated biomass, leaf area index (LAI), and global net C balance. We also show ELMv1-CNP-simulated N and P cycling is in good agreement with data-driven estimates. We compared the ELMv1-CNP-simulated response to CO2 enrichment with meta-analysis of observations from similar manipulation experiments. We show that ELMv1-CNP is able to capture the field-observed responses for photosynthesis, growth, and LAI. We investigated the role of P limitation in the historical balance and show that global C sources and sinks are significantly affected by P limitation, as the historical CO2 fertilization effect was reduced by 20 % and C emission due to land use and land cover change was 11 % lower when P limitation was considered. Our simulations suggest that the introduction of P cycle dynamics and C–N–P coupling will likely have substantial consequences for projections of future C uptake.

Combining local model calibration with the emergent constraint approach to reduce uncertainty in the tropical land carbon cycle feedback

Abstract. The role of the land carbon cycle in climate change remains highly uncertain. A key source of the projection spread is related to the assumed response of photosynthesis to warming, especially in the tropics. The optimum temperature for photosynthesis determines whether warming positively or negatively impacts photosynthesis, thereby amplifying or suppressing CO2 fertilisation of photosynthesis under CO2-induced global warming. Land carbon cycle models have been extensively calibrated against local eddy flux measurements, but this has not previously been clearly translated into a reduced uncertainty in terms of how the tropical land carbon sink will respond to warming. Using a previous parameter perturbation ensemble carried out with version 3 of the Hadley Centre coupled climate–carbon cycle model (HadCM3C), we identify an emergent relationship between the optimal temperature for photosynthesis, which is especially relevant in tropical forests, and the projected amount of atmospheric CO2 at the end of the century. We combine this with a constraint on the optimum temperature for photosynthesis, derived from eddy covariance measurements using the adjoint of the Joint UK Land Environment Simulator (JULES) land surface model. Taken together, the emergent relationship from the coupled model and the constraint on the optimum temperature for photosynthesis define an emergent constraint on future atmospheric CO2 in the HadCM3C coupled climate–carbon cycle under a common emissions scenario (A1B). The emergent constraint sharpens the probability density of simulated CO2 change (2100–1900) and moves its peak to a lower value of 497 ± 91 compared to 607 ± 128 ppmv (parts per million by volume) when using the equal-weight prior. Although this result is likely to be model and scenario dependent, it demonstrates the potential of combining the large-scale emergent constraint approach with a parameter estimation using detailed local measurements.

Models overestimate ecosystem water use efficiency for northern permafrost regions

Understanding the carbon-water coupling over permafrost regions is essential to projecting global ecosystem carbon sequestration and water dynamics. Ecosystem water use efficiency (EWUE), defined as the ratio of gross primary productivity (GPP) and evapotranspiration (ET), reflects plant acclimation strategies with varying ecosystem functioning against environmental stress. Yet EWUE change and its potential drivers across the northern permafrost regions remain poorly quantified, hampering our understanding of permafrost carbon−climate feedback. Here, we compared and analyzed the difference using satellite observations and process-based models to estimate the spatio-temporal variations of EWUE in 1982–2018 over northern permafrost regions. Using flux measurements as truth data, satellite-derived EWUE was more reliable than model-based EWUE. Satellite-derived EWUE showed biome-dependent spatial patterns, with a steady temporal trend (0.01 g C mm−1 decade−1, P > 0.05) for spatially averaged EWUE over northern permafrost regions. Carbon dioxide (CO2) concentration and nitrogen deposition positively affected interannual variations of EWUE, while vapor pressure deficit and other climatic factors (i.e., temperature, precipitation, and radiation) negatively controlled EWUE. Compared to satellite-derived EWUE, we found that EWUEs derived from an ensemble of process-based carbon cycle models are overestimated in seven out of ten models, with an increasing trend of 0.11 g C mm−1 decade−1 (P < 0.001) for spatially averaged EWUE of the ensemble mean. The relationships between climatic factors and EWUE are partially misinterpreted in model estimates, especially with overstated CO2 sensitivity and the opposite temperature effect. The fluctuating sensitivities to climate over time and the diminishing effect of CO2 fertilization on gross primary productivity (GPP) may partially explain the discrepancy observed between satellite-derived and model-based estimates of EWUE. Thus, this study calls for caution concerning model-based EWUE and aids in understanding permafrost-climate feedbacks and projections of carbon and water cycles.

Dynamic global vegetation models may not capture the dynamics of the leaf area index in the tropical rainforests: A data-model intercomparison

Improving our understanding of the mechanism of the carbon cycle in the Tropical Rainforests (TRFs) requires systematic testing of vegetation and ecosystem response to environmental drivers in Dynamic Global Vegetation Models (DGVMs) over different time scales. Here, we use reprocessed monthly MODIS LAI products from 2003 to 2019, combined with in-situ data, to determine how well 14 state-of-the-art models (CABLE, CLASSIC, CLM5, DLEM, IBIS, ISAM, ISBA, JULES, LPJ, LPX, OCN, ORCHIDEE, and SDGVM) simulate the long-term trend, interannual variability, seasonality, and El Niño impacts in terms of the greenness in the global TRFs. We find that most DGVMs highly overestimate the long-term trend in the TRFs because of the overestimation of the impact of CO2 fertilization. The multi-model ensemble mean (MME) successfully represents the interannual variability of the TRF LAI in the regional scales; however, failed in the pixeled scales. This inconsistency may be due to DGVMs using Plant Function Type (PFT) to parameterize vegetation dynamics. Finally, most DGVMs poorly modelled both the seasonality and the vegetation conditions during El Niño, likely due to the lack of lagged effects for climate drivers and poor acclimation during drought conditions.

Simulation of crop yield using the global hydrological model H08 (crp.v1)

Abstract. A better understanding of the food–water nexus requires the development of an integrated model that can simultaneously simulate food production and the requirements and availability of water resources. H08 is a global hydrological model that considers human water use and management (e.g., reservoir operation and crop irrigation). Although a crop growth sub-model has been included in H08 to estimate the global crop-specific calendar, its performance as a yield simulator is poor, mainly because a globally uniform parameter set was used for each crop type. In addition, the effects of CO2 fertilization and vapor pressure deficit on crop yield were not considered. Here, through country-wise parameter calibration and algorithm improvement, we enhanced H08 to simulate the yields of four major staple crops: maize, wheat, rice, and soybean. The simulated crop yield was compared with the Food and Agriculture Organization (FAO) national yield statistics and the global dataset of historical yield for major crops (GDHY) gridded yield estimates with respect to mean bias (across nations) and time series correlation (for individual nations). Our results showed that the effects of CO2 fertilization and vapor pressure deficit had opposite impacts on crop yield. The simulated yield showed good consistency with FAO national yield. The mean biases of the major producer countries were considerably reduced to 2 %, 2 %, −2 %, and −1 % for maize, wheat, rice, and soybean, respectively. The capacity of our model to capture the interannual yield variability observed in FAO yield was limited, although the performance of our model was comparable to that of other mainstream global crop models. The grid-level analysis showed that our model showed a similar spatial pattern to that of the GDHY yield in terms of reproducing the temporal variation over a wide area, although substantial differences were observed in other places. Using the enhanced model, we quantified the contributions of irrigation to global food production and compared our results to an earlier study. Overall, our improvements enabled H08 to estimate crop production and hydrology in a single framework, which will be beneficial for global food–water nexus studies in relation to climate change.

CO2 fertilization contributed more than half of the observed forest biomass increase in northern extra-tropical land.

The existence of a large-biomass carbon (C) sink in Northern Hemisphere extra-tropical ecosystems (NHee) is well-established, but the relative contribution of different potential drivers remains highly uncertain. Here we isolated the historical role of carbon dioxide (CO2 ) fertilization by integrating estimates from 24 CO2 -enrichment experiments, an ensemble of 10 dynamic global vegetation models (DGVMs) and two observation-based biomass datasets. Application of the emergent constraint technique revealed that DGVMs underestimated the historical response of plant biomass to increasing [CO2 ] in forests ( ) but overestimated the response in grasslands ( ) since the 1850s. Combining the constrained (0.86 ± 0.28 kg C m-2 [100 ppm]-1 ) with observed forest biomass changes derived from inventories and satellites, we identified that CO2 fertilization alone accounted for more than half (54 ± 18% and 64 ± 21%, respectively) of the increase in biomass C storage since the 1990s. Our results indicate that CO2 fertilization dominated the forest biomass C sink over the past decades, and provide an essential step toward better understanding the key role of forests in land-based policies for mitigating climate change.

CO2 fertilization enhances vegetation productivity and reduces ecological drought in India

Higher warming will affect more regions globally with intensified agricultural and ecological droughts. Higher CO2 concentration improves vegetation’s water use efficiency (WUE), but its potential to alleviate extreme agricultural and ecological droughts is unclear. India is the second-highest contributor to global greening, having two of the eight global hottest biodiversity hotspots. Here, for the first time, using the CMIP6 earth system models (ESMs), we found an increase in the net vegetation productivity in India at the rate of 10.552 TgC year−1 with 1% per year increase in atmospheric CO2 concentration from 285 ppm to 1140 ppm, contrary to global trends. The improved WUE resulting from carbon fertilization and higher rain under warming will supersede the increased evapotranspiration water loss due to radiative effects. We found that the substantial increase in vegetation productivity in India attributes to plant physiology, and such factor needs to be considered in the drought projections.