Large influence of soil moisture on long-term terrestrial carbon uptake

Deep learning-based quantitative analyses of feedback in the land-atmosphere interactions over the Vietnamese Mekong Delta

During the past several decades, the Vietnamese Mekong Delta (VMD) has experienced many severe droughts, resulting in significant impacts on both agriculture and aquaculture. In the evolution and intensification of droughts, local feedbacks in the Land-Atmosphere (LA) interactions were considered to play a crucial role. It is critical to quantify the impact of LA variables on drought processes and severity with the feedback loop of water and energy balances (e.g., soil moisture-latent and sensible heat-precipitation). In this study, a deep learning model, named Long- and Short-term Time-series Network (LSTNet), was applied to simulate the LA interactions over the VMD. With the ERA5 data as modelling inputs, the role of each key variable (e.g., soil moisture, sensible and latent heat) in the LA interactions over the period of 2011-2020 was quantified, and the variations of their inter-relationships in the future period (2015-2099) were also investigated based on the CMIP6 data. The LSTNet model has demonstrated that the deep learning algorithm can effectively capture the relative importance of key variables in the LA interactions. We found that it is crucial to evaluate the effects of soil moisture and sensible heat on the LA interactions, particularly in the dry periods when negative anomalies in soil moisture and sensible heat would significantly reduce the amount of precipitation. In addition, the decline in soil moisture and the rise in sensible heat are anticipated to further diminish precipitation in the future under the changing climate.

The impacts of rising vapour pressure deficit in natural and managed ecosystems

An exponential rise in the atmospheric vapour pressure deficit (VPD) is among the most consequential impacts of climate change in terrestrial ecosystems. Rising VPD has negative and cascading effects on nearly all aspects of plant function including photosynthesis, water status, growth and survival. These responses are exacerbated by land-atmosphere interactions that couple VPD to soil water and govern the evolution of drought, affecting a range of ecosystem services including carbon uptake, biodiversity, the provisioning of water resources and crop yields. However, despite the global nature of this phenomenon, research on how to incorporate these impacts into resilient management regimes is largely in its infancy, due in part to the entanglement of VPD trends with those of other co-evolving climate drivers. Here, we review the mechanistic bases of VPD impacts at a range of spatial scales, paying particular attention to the independent and interactive influence of VPD in the context of other environmental changes. We then evaluate the consequences of these impacts within key management contexts, including water resources, croplands, wildfire risk mitigation and management of natural grasslands and forests. We conclude with recommendations describing how management regimes could be altered to mitigate the otherwise highly deleterious consequences of rising VPD.

Incorporating photosynthetic acclimation improves stomatal optimisation models

Stomatal opening in plant leaves is regulated through a balance of carbon and water exchange under different environmental conditions. Accurate estimation of stomatal regulation is crucial for understanding how plants respond to changing environmental conditions, particularly under climate change. A new generation of optimality-based modelling schemes determines instantaneous stomatal responses from a balance of trade-offs between carbon gains and hydraulic costs, but most such schemes do not account for biochemical acclimation in response to drought. Here, we compare the performance of six instantaneous stomatal optimisation models with and without accounting for photosynthetic acclimation. Using experimental data from 37 plant species, we found that accounting for photosynthetic acclimation improves the prediction of carbon assimilation in a majority of the tested models. Photosynthetic acclimation contributed significantly to the reduction of photosynthesis under drought conditions in all tested models. Drought effects on photosynthesis could not accurately be explained by the hydraulic impairment functions embedded in the stomatal models alone, indicating that photosynthetic acclimation must be considered to improve estimates of carbon assimilation during drought.

Dataset of soil hydraulic parameters in the Yellow River Basin based on in situ deep sampling

Soil hydraulic parameters are vital for precisely characterizing soil hydrological processes, which are critical indicators for regulating climate change effects on terrestrial ecosystems and governing feedbacks between water, energy, and carbon-nitrogen cycles. Although many studies have integrated comprehensive soil datasets, data quality and cost challenges result in data completeness deficiencies, especially for deep soil information. These gaps not only impede methodological endeavours but also constrain soil parameter-based ecosystem process studies spanning from local profiles to global earth system models. We established a soil dataset across the entire Yellow River Basin (YRB) (795,000 km2) using high-density in situ field sampling. This observation-based dataset contains records of soil texture (2924), bulk density (2798), saturated hydraulic conductivity (2782), and water retention curve parameters (1035) down to a maximum depth of 5 m. This dataset, which extends the recorded data range for deep soil hydraulic parameters, is valuable as a direct data resource for environmental, agronomical and hydrological studies in the YRB and regions with similar pedological and geological backgrounds around the world.

Excessive climate warming exacerbates nitrogen limitation on microbial metabolism in an alpine meadow of the Tibetan Plateau: Evidence from soil ecoenzymatic stoichiometry

Soil ecoenzymatic stoichiometry reflects the dynamic equilibrium between microorganism's nutrient requirements and resource availability. However, uncertainties persist regarding the key determinants of nutrient restriction in relation to microbial metabolism under varying degrees of warming. Our long-term and multi-level warming field experiment (control treatment, +0.42 °C, +1.50 °C, +2.55 °C) in a typical alpine meadow unveiled a decline in carbon (C)- and nitrogen (N)-acquired enzymes with escalating warming magnitudes, while phosphorus (P)-acquired enzymes displayed an opposite trend. Employing enzymatic stoichiometry modeling, we assessed the nutrient limitations of microbial metabolic activity and found that C and N co-limited microbial metabolic activities in the alpine meadow. Remarkably, high-level warming (+2.55 °C) exacerbated microbe N limitation, but alleviate C limitations. The structural equation modeling further indicated that alterations in soil extracellular enzyme characteristics (SES) were more effectively elucidated by microbial characteristics (microbial biomass C, N, P, and their ratios) rather than by soil nutrients (total nutrient contents and their ratios). However, the microbial control over SES diminished with higher levels of warming magnitude. Overall, our results provided novel evidence that the factors driving microbe metabolic limitation may vary with the degree of warming in Tibet alpine grasslands. Changes in nutrient demand for microorganism's metabolism in response to warming should be considered to improve nutrient management in adapting to different future warming scenarios.

Mollisol Erosion-Driven Efflux of Energetic Organic Carbon and Microflora Increases Greenhouse Gas Emissions from Cold-Region Rivers

Massive soil erosion occurs in the world's Mollisol regions due to land use change and climate warming. The migration of Mollisol organic matter to river systems and subsequent changes in carbon biogeochemical flow and greenhouse gas fluxes are of global importance but little understood. By employing comparative mesocosm experiments simulating varying erosion intensity in Mollisol regions of northeastern China, this research highlights that erosion-driven export and biomineralization of terrestrial organic matter facilitates CO2 and CH4 emission from receiving rivers. Stronger Mollisol erosion, as represented by a higher soil-to-water ratio in suspensions, increased CO2 efflux, particularly for the paddy Mollisols. This is mechanistically attributable to increased bioavailability of soluble organic carbon in river water that is sourced back to destabilized organic matter, especially from the cultivated Mollisols. Concurrent changes in microbial community structure have enhanced both aerobic and anaerobic processes as reflected by the coemission of CO2 and CH4. Higher greenhouse gas effluxes from paddy Mollisol suspensions suggest that agricultural land use by supplying more nitrogen-containing, higher-free-energy organic components may have enhanced microbial respiration. These new findings highlight that Mollisol erosion is a hidden significant contributor to greenhouse gas emissions from river water, given that the world's four major Mollisol belts are all experiencing intensive cultivation.

Global critical soil moisture thresholds of plant water stress

During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θcrit). Better quantification of θcrit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θcrit. We find an average global θcrit of 0.19 m3/m3, varying from 0.12 m3/m3 in arid ecosystems to 0.26 m3/m3 in humid ecosystems. θcrit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θcrit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θcrit, has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points.

Soil respiration induces co-emission of greenhouse gases and methylated selenium from cold-region Mollisols: Significance for selenium deficiency

Mollisols rich in natural organic matter are a significant sink of carbon (C) and selenium (Se). Climate warming and agricultural expansion to the cold Mollisol regions may enhance soil respiration and biogeochemical cycles, posing a growing risk of soil C and Se loss. Through field-mimicking incubation experiments with uncultivated and cultivated soils from the Mollisol regions of northeastern China, this research shows that soil respiration remained significant even during cold seasons and caused co-emission of greenhouse gases (CO2 and CH4) and methylated Se. Such stimulus effects were generally stronger in the cultivated soils, with maximum emission rates of 7.45 g/m2/d C and 1.42 μg/m2/d Se. For all soil types, the greatest co-emission of CO2 and dimethyl selenide occurred at 25 % soil moisture, whereas measurable CH4 emission was observed at 40 % soil moisture with higher percentages of dimethyl diselenide volatilization. Molecular characterization with three-dimensional fluorescence and ultra-high resolution mass spectrometry suggests that CO2 emission is sensitive to the availability of microbial protein-like substances and free energy from organic carbon biodegradation under variable moisture conditions. Predominant Se binding to biodegradable organic matter resulted in high dependence of Se volatilization on rates of greenhouse gas emissions. These findings together highlight the importance of dynamic organic carbon quality for soil respiration and consequent Mollisol Se loss risk, with implications for science-based management of C and Se resources in agricultural lands to combat with Se deficiency.

Importance of soil moisture conservation in mitigating climate change

A troubling feedback loop, where drier soil contributes to hotter climates, has been widely recognized. This study, drawing on climate model simulations, reveals that maintaining current global soil moisture levels could significantly alleviate 32.9% of land warming under low-emission scenarios. This action could also postpone reaching critical warming thresholds of 1.5 °C and 2.0 °C by at least a decade. Crucially, preserving soil moisture at current levels could prevent noticeable climate change impacts across 42% of the Earth's land, a stark deviation from projections suggesting widespread impacts before the 2060s. To combat soil drying, afforestation in mid-to-low latitude regions within the next three decades is proposed as an effective strategy to increase surface water availability. This underscores the substantial potential of nature-based solutions for managing soil moisture, benefiting both climate change mitigation and ecological enhancement.

Soil moisture conditions alter behavior of entomopathogenic nematodes

BACKGROUND

A variety of environmental factors can disrupt biotic interactions between plants, insects and soil microorganisms with consequences for agricultural management and production. Many of these belowground interactions are mediated by volatile organic compounds (VOCs) which can be used for communication under appropriate environmental conditions. Behavioral responses to these compounds may likewise be dependent on varying soil conditions which are influenced by a changing climate. To determine how changing environmental conditions may affect VOC-mediated biotic interactions, we used a belowground system where entomopathogenic nematodes (EPNs) - tiny roundworm parasitoids of soil-borne insects - respond to VOCs by moving through the soil pore matrix. Specifically, we used two genera of EPNs - Heterorhabditis and Steinernema - that are known to respond to four specific terpenes - α-pinene, linalool, d-limonene and pregeijerene - released by the roots of plants in the presence of herbivores. We assessed the response of these nematodes to these terpenes under three moisture regimes to determine whether drier conditions or inundated conditions may influence the response behavior of these nematodes.

RESULTS

Our results illustrate that the recovery rate of EPNs is positively associated with soil moisture concentration. As soil moisture concentration increases from 6% to 18%, substantially more nematodes are recovered from bioassays. In addition, we find that soil moisture influences EPN preference for VOCs, as illustrated in the variable response rates. Certain compounds shifted from acting as a repellent to acting as an attractant and vice versa depending on the soil moisture concentration.

CONCLUSION

On a broad scale, we demonstrate that soil moisture has a significant effect on EPN host-seeking behavior. EPN efficacy as biological control agents could be affected by climate change projections that predict varying soil moisture concentrations. We recommend that maintaining nematodes as biological control agents is essential for sustainable agriculture development, as they significantly contribute not only to soil health but also to efficient pest management. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Characteristics and drivers of vegetation productivity sensitivity to increasing CO2 at Northern Middle and High Latitudes

Understanding and accurately predicting how the sensitivity of terrestrial vegetation productivity to rising atmospheric CO2 concentration (β) is crucial for assessing carbon sink dynamics. However, the temporal characteristics and driving mechanisms of β remain uncertain. Here, observational and CMIP6 modeling evidence suggest a decreasing trend in β at the Northern Middle and High Latitudes during the historical period of 1982-2015 (-0.082 ± 0.005% 100 ppm-1 year-1). This decreasing trend is projected to persist until the end of the 21st century (-0.082 ± 0.005% 100 ppm-1 year-1 under SSP370 and -0.166 ± 0.006% 100 ppm-1 year-1 under SSP585). The declining β indicates a weakening capacity of vegetation to mitigate warming climates, posing challenges for achieving the temperature goals of the Paris Agreement. The rise in vapor pressure deficit (VPD), that triggers stomata closure and weakens photosynthesis, is considered as the dominated factor contributing to the historical and future decline in β, accounting for 62.3%-75.2% of the effect. Nutrient availability and water availability contribute 15.7%-21.4% and 8.5%-16.3%, respectively. These findings underscore the significant role of VPD in shaping terrestrial carbon sink dynamics, an aspect that is currently insufficiently considered in many climate and ecological models.

Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field

Gamma-ray spectroscopy (GRS) enables continuous estimation of soil water content (SWC) at the subfield scale with a noninvasive sensor. Hydrological applications, including hyper-resolution land surface models and precision agricultural decision making, could benefit greatly from such SWC information, but a gap exists between established theory and accurate estimation of SWC from GRS in the field. In response, we conducted a robust three-year field validation study at a well-instrumented agricultural site in Nebraska, United States. The study involved 27 gravimetric water content sampling campaigns in maize and soybean and 40K specific activity (Bq kg-1) measurements from a stationary GRS sensor. Our analysis showed that the current method for biomass water content correction is appropriate for our maize and soybean field but that the ratio of soil mass attenuation to water mass attenuation used in the theoretical equation must be adjusted to satisfactorily describe the field data. We propose a calibration equation with two free parameters: the theoretical 40K intensity in dry soil and a, which creates an "effective" mass attenuation ratio. Based on statistical analyses of our data set, we recommend calibrating the GRS sensor for SWC estimation using 10 profiles within the footprint and 5 calibration sampling campaigns to achieve a cross-validation root mean square error below 0.035 g g-1.

Projected decline in the strength of vegetation carbon sequestration under climate change in India

Tropical vegetation plays a critical role in terrestrial carbon budget and supply many ecological functions such as carbon sequestration. In recent decades, India has witnessed an increase in net primary productivity (NPP), an important measure of carbon sequestration. However, uncertainties persist regarding the sustainability of these land carbon sinks in the face of climate change. The enhanced NPP is driven by the strong CO2 fertilization effect (CFE), but the temporal patterns of this feedback remain unclear. Using the carbon flux data from the Earth System Models (ESMs), an increasing trend in NPP was observed, with projections of NPP to 2.00 ± 0.12 PgCyr-1 (25 % increase) during 2021-2049, 2.36 ± 0.12 PgCyr-1 (18 % increase) during 2050-2079, and 2.67 ± 0.07 PgCyr-1 (13 % increase) during 2080-2099 in Indian vegetation under SSP585 scenario. This suggests a significant decline in the NPP growth rate. To understand the feedback mechanisms driving NPP, the relative effects of CFE and warming were analyzed. Comparing simulations from the biogeochemically coupled model (BGC) with the fully coupled model, the BGC model projected a 74.7 % increase in NPP, significantly higher than the 55.9 % increase projected by the fully coupled model by the end of the century. This indicates that the consistent increase in NPP was associated with CO2 fertilization. More importantly, results reveal that the decrease in the NPP growth rate was due to the declining contribution of CFE at a rate of -0.62 % per 100 ppm CO2 increase. This decline could be attributed to factors such as nutrient limitations and high temperatures. Additionally, significant shifts in the strength of carbon sinks in offsetting the CO2 emissions were identified, decreasing at a rate of -1.15 % per decade. This decline in the strength of vegetation carbon sequestration may increase the societal dependence on mitigation measures to address climate change.

Monotonic trends of soil microbiomes, metagenomic and metabolomic functioning across ecosystems along water gradients in the Altai region, northwestern China

To investigate microbial communities and their contributions to carbon and nutrient cycling along water gradients can enhance our comprehension of climate change impacts on ecosystem services. Thus, we conducted an assessment of microbial communities, metagenomic functions, and metabolomic profiles within four ecosystems, i.e., desert grassland (DG), shrub-steppe (SS), forest (FO), and marsh (MA) in the Altai region of Xinjiang, China. Our results showed that soil total carbon (TC), total nitrogen, NH4+, and NO3- increased, but pH decreased with soil water gradients. Microbial abundances and richness also increased with soil moisture except the abundances of fungi and protists being lowest in MA. A shift in microbial community composition is evident along the soil moisture gradient, with Proteobacteria, Basidiomycota, and Evosea proliferating but a decline in Actinobacteria and Cercozoa. The β-diversity of microbiomes, metagenomic, and metabolomic functioning were correlated with soil moisture gradients and have significant associations with specific soil factors of TC, NH4+, and pH. Metagenomic functions associated with carbohydrate and DNA metabolisms, as well as phages, prophages, TE, plasmids functions diminished with moisture, whereas the genes involved in nitrogen and potassium metabolism, along with certain biological interactions and environmental information processing functions, demonstrated an augmentation. Additionally, MA harbored the most abundant metabolomics dominated by lipids and lipid-like molecules and organic oxygen compounds, except certain metabolites showing decline trends along water gradients, such as N'-Hydroxymethylnorcotinine and 5-Hydroxyenterolactone. Thus, our study suggests that future ecosystem succession facilitated by changes in rainfall patterns will significantly alter soil microbial taxa, functional potential, and metabolite fractions.

Transition from positive to negative indirect CO2 effects on the vegetation carbon uptake

Although elevated atmospheric CO2 concentration (eCO2) has substantial indirect effects on vegetation carbon uptake via associated climate change, their dynamics remain unclear. Here we investigate how the impacts of eCO2-driven climate change on growing-season gross primary production have changed globally during 1982-2014, using satellite observations and Earth system models, and evaluate their evolution until the year 2100. We show that the initial positive effect of eCO2-induced climate change on vegetation carbon uptake has declined recently, shifting to negative in the early 21st century. Such emerging pattern appears prominent in high latitudes and occurs in combination with a decrease of direct CO2 physiological effect, ultimately resulting in a sharp reduction of the current growth benefits induced by climate warming and CO2 fertilization. Such weakening of the indirect CO2 effect can be partially attributed to the widespread land drying, and it is expected to be further exacerbated under global warming.

Dryness stress weakens the sustainability of global vegetation cooling

Dryness stress can limit vegetation growth, and the cooling potential of vegetation will also be strongly influenced. However, it is still unclear how dryness stress feedback weakens the sustainability of vegetation-based cooling. Based on the long-time series of multi-source remote sensing product data for the period 2001-2020, the relative contribution rate, and the method of decoupling and boxing, we determined that greening will likely mitigate global warming by 0.065 ± 0.009 °C/a, but nearly 47 % of the area is unsustainable. This phenomenon is strongly related to dryness stress. The restricted area of soil moisture (SM: 68.35 %) to vegetation is larger than that of the atmospheric vapor pressure deficit (VPD: 34.19 %). With the decrease in SM, vegetation will decrease by an average of 14.9 %, and with the increase in VPD, vegetation will decrease by 3.8 %. With the continuous increase in the dryness stress area, the sustainability of the vegetation cooling effect will be threatened in an area of about 21.03 million km2, which is equivalent to the area of North America. Specifically, we found that with the decrease in SM and the increase in VPD, the contribution of vegetation to the cooling effect has been weakened by 10.8 %. This conclusion confirms that dryness stress will threaten the sustainability of vegetation-based climate cooling and provides further insight into the effect of dryness stress on vegetation cooling.

Global predictions of topsoil organic carbon stocks under changing climate in the 21st century

The organic carbon (OC) stored in global topsoil (0-30 cm) will be the most active participant in the carbon cycle under future climate change. Due to differences in focus regions or research methods, the spatio-temporal changes of future global topsoil OC stocks and how they will be affected by climate change are not systematically understood, which needs to be further explored. In this study, we developed data-driven models to predict the spatio-temporal dynamics of global topsoil OC stocks by combining 32,579 soil profiles with environmental variables and comprehensively explored the impact of future climate change on topsoil OC. It was found that the topsoil OC stocks were 1249.29 Pg in the baseline period (1971-1990). By 2100, under the normal and high representative concentration paths, it is predicted that the global topsoil OC stocks will decrease by 113.67 ± 25.93 Pg and 193.71 ± 39.76 Pg, respectively. In the future, the largest global topsoil carbon loss will occur in boreal forest areas, which are expected to lose 17.03-27.90 % (66.01-108.13Pg) of their carbon stocks. The influence of climate on topsoil OC stocks is mainly manifested in temperature, which has a negative influence on the global topsoil OC stock, and the contribution rate of temperature to the effect on the global topsoil OC stock is about 26.96 %. Overall, our results provide a high spatio-temporal resolution assessment of global topsoil OC stocks and their relationship to environmental factors, and highlight the spatial heterogeneity, which has been generally ignored in many experimental frameworks and prediction models. These results will help governments to make appropriate management decisions to mitigate climate change.

Warming, rather than drought, remains the primary factor limiting carbon sequestration

Steppe ecosystems in arid and semiarid regions are particularly sensitive to climate change and strongly regulate the global carbon balance. However, carbon fluxes respond differently to climate change in different growing seasons, and the mechanism of this control is not yet clear. Therefore, we (i) obtained carbon flux data observed by a field eddy station in Inner Mongolia from 2006 to 2021; (ii) investigated the constraint effects of climatic factors on carbon fluxes; (iii) explored the response mechanisms of carbon fluxes to coupled changes in temperature and moisture; (iv) investigated the adaptation of steppe ecosystem to changes in temperature and drought. The results showed that (i) the steppe ecosystem was a carbon sink, with an average annual carbon fixation of 73.55 g C m-2 yr-1 and a roughly N-shaped carbon sink accumulation process within one year. (ii) The constraint effect of temperature and Vapor Pressure Deficit (VPD) on Net Ecosystem Productivity (NEP) and Gross Primary Productivity (GPP) was parabolic, with a clear optimum point. (iii) Temperature and moisture in the soil played a greater role in ecosystem carbon sequestration. Soil Water Content (SWC) could alleviate the inhibitory effect of temperature changes on the carbon sequestration of ecosystem. (iv) This ecosystem was capable of adapting well to changes in temperature and drought. However, warming, rather than drought, remains the primary factor limiting carbon sequestration. Specifically, it was GPP that drives the adaptation of ecosystem carbon sequestration to changes in temperature and drought, rather than Ecosystem Respiration (RECO). Although the steppe ecosystem has a good adaptation to changes in temperature and drought, it is still in the boundary region of warming. We hope that our study will deepen our comprehensive understanding of the relationship between temperature and moisture and ecosystem carbon fluxes and provide evidence for steppe ecosystem adaptation to climate change.

Contrasting effects of intensified dry-season drought and extended dry-season length on soil greenhouse gas emissions in a subtropical forest

Over two-thirds of the Earth's land surface is subjected to seasonal precipitation changes along with climate warming, including the subtropical forests that represent one of the Earth's most important carbon sink and source. However, few experiments have been conducted to understand the response of soil greenhouse gas (GHGs) emissions from these forests to seasonal changes in precipitation. Herein, we conducted a field experiment in a subtropical forest of southern China including two precipitation seasonality treatments: an intensified dry-season (Oct-Mar) drought and wetter wet-season (Jun-Sep) treatment (ID) and an extended dry-season (Apr-May) length and wetter wet-season treatment (ED); for both ID and ED, the annual precipitation amount was kept the same as under ambient control (AC). Compared to AC, the decreased annual CO2 emissions for ID were mainly due to decreased WFPS in Oct-Mar of 2013-2014 and increased WFPS during Jun-Sep of 2013; the increased annual CH4 uptake for ID was predominantly attributed to decreased WFPS in Oct-Mar of 2013-2014; the decreased annual N2O emissions for ID were mainly due to decreased WFPS in Oct-Mar of 2013; the increased annual N2O emissions for ID in 2014 were mainly attributed to increased WFPS in Jun-Sep (p < 0.05). Relative to AC, the increased annual CO2 and N2O emissions from ED were predominantly attributed to decreased WFPS in Apr-May and increased WFPS in Jun-Sep during 2013-2014, respectively (p < 0.05). The average annual CO2-equivalent CH4 and N2O emissions increased under ED but decreased under ID compared to AC (p < 0.05). Although our two precipitation manipulation scenarios simulated seasonal drought impacts without changing annual precipitation amount, ED and ID had distinct impacts on soil GHGs emissions, which have important implications for modeling the subtropical forests GHG emissions and managing the forests to mitigate climate change.

Leaf-cutter ants - mycorrhizal fungi: observations and research questions from an unexpected mutualism

Leaf-cutter ants (LCAs) are widely distributed and alter the physical and biotic architecture above and below ground. In neotropical rainforests, they create aboveground and belowground disturbance gaps that facilitate oxygen and carbon dioxide exchange. Within the hyperdiverse neotropical rainforests, arbuscular mycorrhizal (AM) fungi occupy nearly all of the forest floor. Nearly every cubic centimeter of soil contains a network of hyphae of Glomeromycotina, fungi that form arbuscular mycorrhizae. Our broad question is as follows: how can alternative mycorrhizae, which are-especially ectomycorrhizae-essential for the survival of some plant species, become established? Specifically, is there an ant-mycorrhizal fungus interaction that facilitates their establishment in these hyperdiverse ecosystems? In one lowland Costa Rican rainforest, nests of the LCA Atta cephalotes cover approximately 1.2% of the land surface that is broadly scattered throughout the forest. On sequencing the DNA from soil organisms, we found the inocula of many AM fungi in their nests, but the nests also contained the inocula of ectomycorrhizal, orchid mycorrhizal, and ericoid mycorrhizal fungi, including Scleroderma sinnamariense, a fungus critical to Gnetum leyboldii, an obligate ectomycorrhizal plant. When the nests were abandoned, new root growth into the nest offered opportunities for new mycorrhizal associations to develop. Thus, the patches created by LCAs appear to be crucial sites for the establishment and survival of shifting mycorrhizal plant-fungal associations, in turn facilitating the high diversity of these communities. A better understanding of the interactions of organisms, including cross-kingdom and ant-mycorrhizal fungal interactions, would improve our understanding of how these ecosystems might tolerate environmental change.

Estimation of photosynthetic dynamics in forests from daily measured fluorescence and PRI data with adjustment for canopy shadow fraction

We conducted year-long measurements of the photochemical reflectance index (PRI) and solar-induced fluorescence in the O2A oxygen band (SIFA) at a Norway spruce forest and a European beech forest to study relationships of these remote sensing variables to photosynthesis by trees in grown forest stands. Measured PRI and SIFA values were linked to changes in forest gross primary productivity (GPP) and light-use efficiency (LUE). Changes in the shadow fraction (αS) within tree crowns influenced PRI and fluorescence signals. In the spruce forest, the quantum yield of SIFA (FYSIFA) decreased around midday together with photosynthesis and GPP. Such decreases in FYSIFA were accompanied by an increase in the αS. In the beech forest, we detected an increase in FYSIFA together with a decrease in αS in the afternoon hours. The overall sensitivity of PRI to LUE was variable according to the season, presumably influenced by complex changes in photosynthetic pigments. PRI and FYSIFA showed weak correlations with canopy LUE; however, when considered together, the correlation was strengthened (R2 was 0.63 and 0.34 in spruce and beech forest, respectively). Our model predicting LUE dynamics includes a diurnal minimum of PRI and canopy αS to make allowances for seasonal changes in photosynthetic pigments and for diurnal variability of the shadow fraction in forests. The incorporation of these correcting factors allowed us to estimate LUE at R2 = 0.68 (spruce) and 0.53 (beech). The modeling equations appeared sensitive to the absorbed photosynthetically active radiation (APAR), but less sensitive to the GPP of these forests. Substituting pigments correction with introducing differential PRI (ΔPRI) into the model did not significantly improve the LUE estimation across the season. Our results show that the joint use of PRI and fluorescence improves LUE and GPP estimation accuracy in both daily and seasonal observations.

Grazing livestock move by Lévy walks: Implications for soil health and environment

Grazing livestock plays an important role in the context of food security, agricultural sustainability and climate change. Understanding how livestock move and interact with their environment may offer new insights on how grazing practices impact soil and ecosystem functions at spatial and temporal scales where knowledge is currently limited. We characterized daily and seasonal grazing patterns using Global Positioning System (GPS) data from two grazing strategies: conventionally- and rotationally-grazed pastures. Livestock movement was consistent with the so-called Lévy walks, and could thus be simulated with Lévy-walk based probability density functions. Our newly introduced "Moovement model" links grazing patterns with soil structure and related functions by coupling animal movement and soil structure dynamics models, allowing to predict spatially-explicit changes in key soil properties. Predicted post-grazing management-specific bulk densities were consistent with field measurements and confirmed that rotational grazing produced similar disturbance as conventional grazing despite hosting higher stock densities. Harnessing information on livestock movement and its impacts in soil structure within a modelling framework can help testing and optimizing grazing strategies for ameliorating their impact on soil health and environment.

The fusion of multiple scale data indicates that the carbon sink function of the Qinghai-Tibet Plateau is substantial

BACKGROUND

The Qinghai-Tibet Plateau is the "sensitive area" of climate change, and also the "driver" and "amplifier" of global change. The response and feedback of its carbon dynamics to climate change will significantly affect the content of greenhouse gases in the atmosphere. However, due to the unique geographical environment characteristics of the Qinghai-Tibet Plateau, there is still much controversy about its carbon source and sink estimation results. This study designed a new algorithm based on machine learning to improve the accuracy of carbon source and sink estimation by integrating multiple scale carbon input (net primary productivity, NPP) and output (soil heterotrophic respiration, Rh) information from remote sensing and ground observations. Then, we compared spatial patterns of NPP and Rh derived from the fusion of multiple scale data with other widely used products and tried to quantify the differences and uncertainties of carbon sink simulation at a regional scale.

RESULTS

Our results indicate that although global warming has potentially increased the Rh of the Qinghai-Tibet Plateau, it will also increase its NPP, and its current performance is a net carbon sink area (carbon sink amount is 22.3 Tg C/year). Comparative analysis with other data products shows that CASA, GLOPEM, and MODIS products based on remote sensing underestimate the carbon input of the Qinghai-Tibet Plateau (30-70%), which is the main reason for the severe underestimation of the carbon sink level of the Qinghai-Tibet Plateau (even considered as a carbon source).

CONCLUSIONS

The estimation of the carbon sink in the Qinghai-Tibet Plateau is of great significance for ensuring its ecological barrier function. It can deepen the community's understanding of the response to climate change in sensitive areas of the plateau. This study can provide an essential basis for assessing the uncertainty of carbon sources and sinks in the Qinghai-Tibet Plateau, and also provide a scientific reference for helping China achieve "carbon neutrality" by 2060.

Comparison of plant diversity-carbon storage relationships along altitudinal gradients in temperate forests and shrublands

Understanding the mechanisms underlying the relationship between biodiversity and ecosystem function (BEF) is critical for the implementation of productive and resilient ecosystem management. However, the differences in BEF relationships along altitudinal gradients between forests and shrublands are poorly understood, impeding the ability to manage terrestrial ecosystems and promote their carbon sinks. Using data from 37962 trees of 115 temperate forest and 134 shrubland plots of Taihang Mountains Priority Reserve, we analyzed the effects of species diversity, structural diversity, climate factors and soil moisture on carbon storage along altitudinal gradients in temperate forests and shrublands. We found that: (1) Structural diversity, rather than species diversity, mainly promoted carbon storage in forests. While species diversity had greater positive effect on carbon storage in shrublands. (2) Mean annual temperature (MAT) had a direct negative effect on forest carbon storage, and indirectly affected forest carbon storage by inhibiting structural diversity. In contrast, MAT promoted shrubland carbon storage directly and indirectly through the positive mediating effect of species diversity. (3) Increasing altitudinal gradients enhanced the structural diversity-carbon relationship in forests, but weakened the species diversity-carbon relationship in shrublands. Niche and architectural complementarity and different life strategies of forests and shrubs mainly explain these findings. These differential characteristics are critical for our comprehensive understanding of the BEF relationship and could help guide the differentiated management of forests and shrublands in reaction to environmental changes.

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 (β Forest Mod ) but overestimated the response in grasslands (β Grass Mod ) since the 1850s. Combining the constrainedβ Forest Mod (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.

Decline in stability of forest productivity in the tropics as determined by canopy water content

The impacts of low soil moisture (SM) and high vapour pressure deficit (VPD) on tree's photosynthesis and productivity are ultimately realized by changing water content in the canopy leaves. In this study, variations in canopy water content (CWC) that can be detected from microwave remotely sensed vegetation optical depth (VOD) have been proposed as a promising measure of vegetation water status, and we first reported that the regulation of CWC on productivity stability is universally applicable for global forests. Results of structural equation model (SEM) also confirmed the significant negative effect of CWC on coefficient of variation (CV) of productivity, indicating that the decrease in CWC could inevitably induce the instability of forest productivity under climate change. The most significant decrease (p < 0.01) of CWC is observed primarily in evergreen broadleaf forest in the tropics, implying an increasing instability of the most important carbon sink in terrestrial ecosystem.

Ecohydrological insight: Solar farms facilitate carbon sink enhancement in drylands

Solar farms are critical to tackling climate change and achieving carbon neutrality. Besides producing renewable energy, a solar farm modifies microclimates and changes water distribution, consequently affecting local carbon sequestration capacity (CSC). Yet, how the CSC of an ecosystem responds to these changes after solar farm construction remains inadequately understood. Herein, the SOFAR model was adopted to reveal the effects of large-scale solar farms (LSFs) on CSC in arid northern China, with a series of numeric experiments along a climate gradient (with precipitation ranging from 70 to 500 mm yr^-1). The results show that relative to pristine vegetation background, CSC was non-linearly increased by averages of 3.49-6.68%, 4.43-10.25%, 5.07-9.71% and 5.6% each year after the installation of LSFs in hyper-arid climates (with aridity index or AI = 0.04-0.05), arid climates (AI = 0.14-0.16), semi-arid climates (AI = 0.21-0.3) and semi-humid climates (AI = 0.55), respectively. The increase in available water for plants growing under the drip lines of photovoltaic panels (PVs) in LSFs is confirmed to be the overwhelming factor responsible for CSC enhancement. Although biases remain in the estimation of increased CSC in hyper- and semi-humid regions due to the high variability of climate (e.g., extreme drought events) and serious radiation reduction beneath PVs, it is certain that solar farms facilitate CSC without increasing external land use. These results will deepen our understanding of the feedback between solar farms and ambient environments and be meaningful for vegetation management in solar farms, especially in the context of climate change and carbon neutrality aims.

A Long-term Consistent Artificial Intelligence and Remote Sensing-based Soil Moisture Dataset

The Consistent Artificial Intelligence (AI)-based Soil Moisture (CASM) dataset is a global, consistent, and long-term, remote sensing soil moisture (SM) dataset created using machine learning. It is based on the NASA Soil Moisture Active Passive (SMAP) satellite mission SM data and is aimed at extrapolating SMAP-like quality SM back in time using previous satellite microwave platforms. CASM represents SM in the top soil layer, and it is defined on a global 25 km EASE-2 grid and for 2002-2020 with a 3-day temporal resolution. The seasonal cycle is removed for the neural network training to ensure its skill is targeted at predicting SM extremes. CASM comparison to 367 global in-situ SM monitoring sites shows a SMAP-like median correlation of 0.66. Additionally, the SM product uncertainty was assessed, and both aleatoric and epistemic uncertainties were estimated and included in the dataset. CASM dataset can be used to study a wide range of hydrological, carbon cycle, and energy processes since only a consistent long-term dataset allows assessing changes in water availability and water stress.

Ecological engineering induced carbon sinks shifting from decreasing to increasing during 1981-2019 in China

Substantial evidence shows that most of China's terrestrial ecosystems are important carbon sinks. However, the nonlinear trend of the carbon sinks and their nonlinear response to driving factors are unclear. Taking the net ecosystem productivity (NEP) as a proxy for the ecosystem carbon sink, the nonlinear relationships between the monotonically increasing trends and decreasing to increasing shifts in the carbon sink to climate change and ecological engineering were investigated based on ensemble empirical mode decomposition (EEMD) and machine learning algorithm (boosted regression tree model, BRT). The results suggest that 16.75 % of the carbon sinks in China experienced a monotonic increase. Additionally, 20.55 % of the carbon sinks shifted from decreasing to increasing trends, primarily after 1995, and these carbon sinks were located in the key ecological engineering areas, such as the middle reaches of the Yellow River shelterbelt program area, the Liaohe shelterbelt program area, the Grain to Green program area, and the Three-North Forest shelterbelt program area. Moreover, carbon sinks exhibited strong spatial autocorrelation with low-low clustering in the north and high-high clustering in the south. The increase in CO₂ (slope of CO₂ < 1.8 g/m²/s/y) and solar radiation (slope of radiation >1 w/m²/y) promoted the monotonic increase in the carbon sinks in the center of China. The increase in the areas of forest and grassland shifted the carbon sink trend from decreasing to increasing in the key ecological engineering program areas, and economic development reversed the carbon sink reduction in the Pearl River shelterbelt program area. These findings highlight the positive effect of ecological engineering on carbon sinks and provide adaptation strategies and guidance for China to achieve the "carbon neutrality" target.

Continued decline of global soil moisture content, with obvious soil stratification and regional difference

Soil is an important component connecting atmosphere and vegetation, and is an important 'regulator' of slope hydrological process. Global warming accelerates the global water cycle, and Soil Moisture Content (SMC) will change, but this change is not yet clear. Here, we study the global trend of SMC at different depths over the past 70 years and the next 70 years, based on the GLDAS-NOAH025 dataset and precipitation and temperature data from 15 CMIP6 models. We found that compared with the long-term average of 70 years, the global 0-200 cm SMC is decreasing at a rate of 1.284 kg/m² per year from 2000 to 2020, and the area showing a significant decreasing trend accounts for 31.67 % of the global. Over the past decade, 0-200 cm SMC reduction rate (2.251 kg/m²) doubled. Global warming and precipitation reduction are the main reasons for the attenuation of SMC at different depths in the global from 2000 to 2020. Under the SSP126, SSP245, SSP370 and SSP585 scenarios, the global 0-200 cm SMC will continue to decay in the future, and the area showing a significant reduction trend accounts for 22.73-49.71 % of the global, but the stratified soil and regional differences are obvious. The attenuation of SMC will further aggravate the global water cycle and enhance the variability of extreme meteorological disasters. We will face more severe soil drought problems.

Recent decrease of the impact of tropical temperature on the carbon cycle linked to increased precipitation

The atmospheric CO₂ growth rate (CGR) variability is largely controlled by tropical temperature fluctuations. The sensitivity of CGR to tropical temperature [Formula: see text] has strongly increased since 1960, but here we show that this trend has ceased. Here, we use the long-term CO₂ records from Mauna Loa and the South Pole to compute CGR, and show that [Formula: see text] increased by 200% from 1960-1979 to 1979-2000 but then decreased by 117% from 1980-2001 to 2001-2020, almost returning back to the level of the 1960s. Variations in [Formula: see text] are significantly correlated with changes in precipitation at a bi-decadal scale. These findings are further corroborated by results from a dynamic vegetation model, collectively suggesting that increases in precipitation control the decreased [Formula: see text] during recent decades. Our results indicate that wetter conditions have led to a decoupling of the impact of the tropical temperature variation on the carbon cycle.

Construction and application of Optimized Comprehensive Drought Index based on lag time: A case study in the middle reaches of Yellow River Basin, China

Drought is a complex and dynamic natural phenomenon. A single drought index can hardly reflect the multi-type characteristics of drought, and comprehensive drought indices that incorporate data from multiple sources have been proposed recently. In this study, an Optimized Comprehensive Drought Index (OCDI) was constructed by taking into account the lag time of meteorological drought, agricultural drought and hydrological drought. The Standardized Precipitation Evapotranspiration Index (SPEI), Vegetation Condition Index (VCI), and Water Storage Deficit Index (WSDI) represented the three types of droughts, respectively. Specifically, we used the Solar-induced Chlorophyll Fluorescence (SIF) to characterize the vegetation condition instead of the Normalized Difference Vegetation Index (NDVI). The application results of the proposed drought index in the middle reaches of Yellow River basin (MRYRB) showed that the lag time of different types of drought indices had seasonal differences, with a shorter lag time in summer (0-4 months) and a longer lag time in winter and spring (> 4 months). For typical drought events, the drought intensity and duration identified by OCDI were compatible with the drought evolution characteristics and consistent with the historical records, therefore, OCDI is more suitable for drought monitoring in the study area. Based on the monitoring results of the OCDI, the average number of droughts in the MRYRB was 16 times, with a duration of 2.8 months and an average drought intensity of 0.28 (at moderate drought grade). Drought times and intensity were higher in the northwestern part of the study area, and spring was a high-frequency period for drought occurrences.

Interannual and seasonal relationships between photosynthesis and summer soil moisture in the Ili River basin, Xinjiang, 2000-2018

Soil moisture (SM) is essential for controlling terrestrial carbon uptake, as it directly provides moisture for photosynthesis, especially in arid and semiarid regions. We selected the arid and semiarid Ili River basin (IRB) of Xinjiang as the study area, and investigated the spatial and temporal characteristics and interrelationships with SM and photosynthesis from 2000 to 2018 using the ERA5 products and solar-induced chlorophyll fluorescence (SIF). SM and photosynthesis showed a decreasing trend during the study period. Compared with those in spring and autumn, the variation of summer SM and SIF was more consistent with the interannual variation. Anomaly analysis showed that negative SM anomalies were most profound in 2012-2015, 2008, and 2014. Additionally, we quantified the effect of seasonal SM deficits on photosynthesis by performing model-based experiments. The results indicated that the gross primary productivity (GPP) simulated by the P-model could capture the characteristics of photosynthesis in the IRB, which had a high correlation with SIF (R² = 0.82, p < 0.001). In 2012-2015, 2008, and 2014, SM deficits caused more GPP reduction in the summers than in the springs or the autumns. The trends were mainly visible in the northern IRB, where GPP was below 40 % of the multi-year mean, and SM was below 23 %. GPP decreased more significantly in grassland than in the forest under the influence of SM deficit. This study reveals seasonal differences in the effects of SM deficit on photosynthesis and emphasizes that the summer SM deficit was the main factor responsible for decreases in GPP in the IRB during the study period. These findings contribute to a better understanding of the relationships between photosynthesis and environmental factors, and provide a reference for an accurate assessment of the regional carbon cycle.

Trends in drought and effects on carbon sequestration over the Chinese mainland

Recently, drought events have occurred frequently and have profoundly altered the carbon sequestration in terrestrial ecosystems. How drought affects carbon sequestration is an important issue which may assist in understanding and confronting the challenges of extreme climate change. Nevertheless, drought-induced carbon-cycle effects remain scarce from the perspective of drought indices. In this study, we quantified the impacts of potential evapotranspiration (PET), standardized precipitation evapotranspiration index (SPEI), downward short-wave radiation flux (SWDown), and soil water (Soil_w) on net ecosystem productivity (NEP). We showed that the spatiotemporal heterogeneity of drought was extremely significant, and the hot spots of aridification were mainly distributed in the southwestern Yungui Plateau (YG) and Northwest China (NW). Moreover, the "pan evaporation paradox" appeared across the Chinese mainland before the 1990s and subsequently disappeared. Similarly, in contrast to the moderate NEP fluctuation between 1981 and 1999, since the beginning of the 21st century, NEP has increased significantly across Chinese mainland, YG, the plains region of Changjiang (CJ), and Southeast China (SE). Meanwhile, there are obvious directional, temporal, and spatial differences in the effects of the drought indices on NEP. Specifically, a higher SPEI value results in a more obvious promoting effect on NEP in SE, North China (NN), and northeastern YG. An increase in SWDown can promote an increase in NEP, especially in the northeastern YG and central SE. The increase in Soil_w in parts of the Qinghai-Tibetan Plateau, Xinjiang Region (XJ), southeastern NW, NN, and Northeast China with poor water conditions can promote carbon sinks. The inhibition effect is particularly obvious in some areas of CJ, where water resources are abundant. The fluctuation in PET has a relatively low influence on NEP. This study provides a comprehensive assessment of drought change and its impact on carbon sequestration and may help in formulating appropriate policies for carbon management and ecological security.

Soil moisture drives the spatiotemporal patterns of asymmetry in vegetation productivity responses across China

Increasingly drastic global change is expected to cause hydroclimatic changes, which will influence vegetation productivity and pose a threat to the terrestrial carbon sink. Asymmetry represents an imbalance between vegetation growth and loss of growth during dry and wet periods, respectively. However, the mechanisms of asymmetric plant responses to hydrological changes remain poorly understood. Here, we examined the spatiotemporal patterns of asymmetric responses of vegetation productivity across terrestrial ecosystems in China. We analyzed several observational and satellite-based datasets of plant productivity and several reanalyzed datasets of hydroclimatic variables from 2001 to 2020, and used a random forest model to assess the importance of hydroclimatic variables for these responses. Our results showed that the productivity of >50 % of China's vegetated areas showed a more positive asymmetry (2.3 ± 9.4 %) over the study period, which were distributed broadly in northwest China (mainly grasslands and sparse vegetation ecosystems). Negative asymmetries were most common in forest ecosystems in northeast China. We demonstrated that one-third of vegetated areas tended to exhibit significant changes in asymmetry during 2001-2020. The trend towards stronger positive asymmetry (0.95 % yr^-1) was higher than that towards stronger negative asymmetry (-0.55 % yr^-1), which is beneficial for the carbon sink. We further showed that in China, soil moisture was a more important driver of spatiotemporal changes in asymmetric productivity than precipitation. We identified thresholds of surface soil moisture (20-30 %, volume water content) and root-zone soil moisture (200-350 mm, equivalent water height) that were associated with changes in asymmetry. Our findings highlight the necessity of considering the dynamic responses of vegetation to hydrological factors in order to fully understand the physiological growth processes of plants and avoid the possible loss of productivity due to future climate change.

Assessing the impact of drought-land cover change on global vegetation greenness and productivity

Drought-land cover change (D-LCC) is considered to be an important stress factor that affects vegetation greenness and productivity (VG&P) in global terrestrial ecosystems. Understanding the effects of D-LCC on VG&P benefits the development of terrestrial ecosystem models and the prediction of ecosystem evolution. However, till today, the mechanism remains underexploited. In this study, based on the Theil-Sen median estimator and Mann-Kendall test, Hurst exponent evaluation and rescaled range analysis (R/S), Pearson and Partial correlation coefficient analyses, we explore the spatiotemporal distribution characteristics and future trends of Leaf area index (LAI), Net primary productivity (NPP), Solar-induced chlorophyll fluorescence (SIF), Standardized precipitation evapotranspiration index (SPEI), Soil moisture (SM), Land cover type (LC), and the impact mechanism of D-LCC on global VG&P. Our results provide four major insights. First, three independent satellite observations consistently indicate that the world is experiencing an increasing trend of VG&P: LAI (17.69 %), NPP (20.32 %) and SIF (16.46 %). Nonetheless, productivity-reducing trends are unfolding in some tropical regions, notably the Amazon rainforest and the Congo basin. Second, from 2001 to 2020, the frequency, severity, duration, and scope of global droughts have been increasing. Third, the impact of land cover change on global VG&P is region-dependent. Finally, our results indicate that the continuous growth of VG&P in the global vegetation area is likely to become more difficult to maintain.

Divergent responses of cropland soil organic carbon to warming across the Sichuan Basin of China

Cropland soils are considered to have the potential to sequester carbon (C). Warming can increase soil organic C (SOC) by enhancing primary production, but it can also cause carbon release from soils. However, the role of warming in governing cropland SOC dynamics over broad geographic scales remains poorly understood. Using over 4000 soil samples collected in the 1980s and 2010s across the Sichuan Basin of China, this study assessed the warming-induced cropland SOC change and the correlations with precipitation, cropland type and soil type. Results showed mean SOC content increased from 11.10 to 13.85 g C kg^-1. Larger SOC increments were observed under drier conditions (precipitation < 1050 mm, dryland and paddy-dryland rotation cropland), which were 1.67-2.23 times higher than under wetter conditions (precipitation > 1050 mm and paddy fields). Despite the significant associations of SOC increment with crop productivity, precipitation, fertilization, cropland type and soil type, warming also acted as one of major contributors to cropland SOC change. The SOC increment changed parabolically with the rise in temperature increase rate under relatively drier conditions, while temperature increase had no impact on cropland SOC increment under wetter conditions. Meanwhile, the patterns of the parabolical relationship varied with soil types in drylands, where the threshold of temperature increase rate, the point at which the SOC increment switched from increasing to decreasing with warming, was lower for clayey soils (Ali-Perudic Argosols) than for sandy soils (Purpli-Udic Cambosols). These results illustrate divergent responses of cropland SOC to warming under different environments, which were contingent on water conditions and soil types. Our findings emphasize the importance of formulating appropriate field water management for sustainable C sequestration and the necessity of incorporating environment-specific mechanisms in Earth system models for better understanding of the soil C-climate feedback in complex environments.

Soil moisture-atmosphere feedback dominates land N2 O nitrification emissions and denitrification reduction

Soil moisture (SM) is essential to microbial nitrogen (N)-cycling networks in terrestrial ecosystems. Studies have found that SM-atmosphere feedbacks dominate the changes in land carbon fluxes. However, the influence of SM-atmosphere feedbacks on the N fluxes changes, and the underlying mechanisms remain highly unsure, leading to uncertainties in climate projections. To fill this gap, we used in situ observation coupled with gridded and remote sensing data to analyze N₂ O fluxes emissions globally. Here, we investigated the synergistic effects of temperature, hydroclimate on global N₂ O fluxes, as the result of SM-atmosphere feedback impact on N fluxes. We found that SM-temperature feedback dominates land N₂ O emissions by controlling the balance between nitrifier and denitrifier genes. The mechanism is that atmospheric water demand increases with temperature and thereby reduces SM, which increases the dominant N₂ O production nitrifier (containing amoA AOB gene) and decreases the N₂ O consumption denitrifier (containing the nosZ gene), consequently will potential increasing N₂ O emissions. However, we find that the spatial variations of soil-water availability as a result of the nonlinear response of SM to vapor pressure deficit caused by temperature are some of the greatest challenges in predicting future N₂ O emissions. Our data-driven assessment deepens the understanding of the impact of SM-atmosphere interactions on the soil N cycle, which remains uncertain in earth system models. We suggest that the model needs to account for feedback between SM and atmospheric temperature when estimating the response of the N₂ O emissions to climatic change globally, as well as when conducting field-scale investigations of the response of the ecosystem to warming.

China's terrestrial ecosystem carbon balance during the 20th century: an analysis with a process-based biogeochemistry model

BACKGROUND

China's terrestrial ecosystems play a pronounced role in the global carbon cycle. Here we combine spatially-explicit information on vegetation, soil, topography, climate and land use change with a process-based biogeochemistry model to quantify the responses of terrestrial carbon cycle in China during the 20th century.

RESULTS

At a century scale, China's terrestrial ecosystems have acted as a carbon sink averaging at 96 Tg C yr^- 1, with large inter-annual and decadal variabilities. The regional sink has been enhanced due to the rising temperature and CO₂ concentration, with a slight increase trend in carbon sink strength along with the enhanced net primary production in the century. The areas characterized by C source are simulated to extend in the west and north of the Hu Huanyong line, while the eastern and southern regions increase their area and intensity of C sink, particularly in the late 20th century. Forest ecosystems dominate the C sink in China and are responsible for about 64% of the total sink. On the century scale, the increase in carbon sinks in China's terrestrial ecosystems is mainly contributed by rising CO₂. Afforestation and reforestation promote an increase in terrestrial carbon uptake in China from 1950s. Although climate change has generally contributed to the increase of carbon sinks in terrestrial ecosystems in China, the positive effect of climate change has been diminishing in the last decades of the 20th century.

CONCLUSION

This study focuses on the impacts of climate, CO₂ and land use change on the carbon cycle, and presents the potential trends of terrestrial ecosystem carbon balance in China at a century scale. While a slight increase in carbon sink strength benefits from the enhanced vegetation carbon uptake in China's terrestrial ecosystems during the 20th century, the increase trend may diminish or even change to a decrease trend under future climate change.

Smart Soil Water Sensor with Soil Impedance Detected via Edge Electromagnetic Field Induction

To address the problems in the calibration of soil water content sensors, in this study, we designed a low-cost edge electromagnetic field induction (EEMFI) sensor for soil water content measurement and proposed a normalized calibration method to eliminate the errors caused by the measurement sensor's characteristics and improve the probe's consistency, replaceability, and calibration efficiency. The model calibration curve-fitting coefficients of the EEMFI sensors were above 0.98, which indicated a significant correlation. The experimental results of the static and dynamic characteristics showed that the measurement range of the sensor varied from 0% to 100% saturation, measurement accuracy was within ±2%, the maximum value of the extreme difference of the stability test was 1.09%, the resolution was 0.05%, the delay time was 3.9 s, and the effective measurement diameter of the EEMFI sensor probe was 10 cm. The linear fit coefficient of determination of the results was greater than 0.99, and the maximum absolute error of the measurement results with the drying method was less than ±2%, which meets the requirements of soil water content measurement in agriculture and forestry fields. The field experiment results further showed that the EEMFI sensor can accurately respond to changes in soil water content, indicating that the EEMFI sensor is reliable.

Spectral index selection method for remote moisture sensing under challenging illumination conditions

Remote sensing using passive solar illumination in the Short-Wave Infrared spectrum is exposed to strong intensity variation in the spectral bands due to atmospheric changing conditions and spectral absorption. More robust spectral analysis methods, insensitive to these effects, are increasingly required to improve the accuracy of the data analysis in the field and extend the use of the system to “non ideal” illumination condition. A computational hyperspectral image analysis method (named HIAM) for deriving optimal reflectance indices for use in remote sensing of soil moisture content is detailed and demonstrated. Using histogram analysis of hyperspectral images of wet and dry soil, contrast ratios and wavelength pairings were tested to find a suitable spectral index to recover soil moisture content. Measurements of local soil samples under laboratory and field conditions have been used to demonstrate the robustness of the index to varying lighting conditions, while publicly available databases have been used to test across a selection of soil classes. In both cases, the moisture was recovered with RMS error better than 5%. As the method is independent of material type, this method has the potential to also be applied across a variety of biological and man-made samples.

Widespread increasing vegetation sensitivity to soil moisture

Global vegetation and associated ecosystem services critically depend on soil moisture availability which has decreased in many regions during the last three decades. While spatial patterns of vegetation sensitivity to global soil water have been recently investigated, long-term changes in vegetation sensitivity to soil water availability are still unclear. Here we assess global vegetation sensitivity to soil moisture during 1982-2017 by applying explainable machine learning with observation-based leaf area index (LAI) and hydro-climate anomaly data. We show that LAI sensitivity to soil moisture significantly increases in many semi-arid and arid regions. LAI sensitivity trends are associated with multiple hydro-climate and ecological variables, and strongest increasing trends occur in the most water-sensitive regions which additionally experience declining precipitation. State-of-the-art land surface models do not reproduce this increasing sensitivity as they misrepresent water-sensitive regions and sensitivity strength. Our sensitivity results imply an increasing ecosystem vulnerability to water availability which can lead to exacerbated reductions in vegetation carbon uptake under future intensified drought, consequently amplifying climate change.

Regional Contributions and Climate Attributions to Interannual Variation of Global Net Ecosystems Production by an ECOSYSTEM Processed Model Driven by Remote Sensing Data over the Past 35 Years

Global climate change has significantly affected terrestrial carbon sinks. Net ecosystem production (NEP) plays a critical role in the global carbon cycle. However, interannual variability (IAV) of the NEP and its regional contributions and climate attributions are not well-understood on a global scale. This study used a diagnostic model driven by remote sensing leaf area index (LAI) to investigate the NEP IAV and analyze regional and climate contributions on a global scale from 1982 to 2016. We found large NEP IAV during the study period, with the NEP detrended anomaly ranging from −2.3 Pg C in 1998 to 1.6 Pg C in 2013 at a global scale. Furthermore, 63.7% and 34.1% of the areas showed positive and negative contributions to NEP IAVs globally, respectively. Evergreen broadleaf forest (EBF) contributed the most (31.1%) to NEP IAV, followed by cropland (21.7%) and grassland (20.8%). Temperature played the most critical roles in the global NEP IAV, with a contribution of 45.5%. However, the partial correlation between NEP and temperature was negative, and the correlation with precipitation was positive in most areas of the globe, indicating that global warming is not conducive to the global carbon sink, but abundant rainfall is important for the global carbon cycle. This study suggests that, to increase the global carbon sink, we should pay more attention to tropical forests (EBFs) and highlight the importance of water availability.

Towards species-level forecasts of drought-induced tree mortality risk

Predicting species-level responses to drought at the landscape scale is critical to reducing uncertainty in future terrestrial carbon and water cycle projections. We embedded a stomatal optimisation model in the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model and parameterised the model for 15 canopy dominant eucalypt tree species across South-Eastern Australia (mean annual precipitation range: 344-1424 mm yr^-1 ). We conducted three experiments: applying CABLE to the 2017-2019 drought; a 20% drier drought; and a 20% drier drought with a doubling of atmospheric carbon dioxide (CO₂ ). The severity of the drought was highlighted as for at least 25% of their distribution ranges, 60% of species experienced leaf water potentials beyond the water potential at which 50% of hydraulic conductivity is lost due to embolism. We identified areas of severe hydraulic stress within-species' ranges, but we also pinpointed resilience in species found in predominantly semiarid areas. The importance of the role of CO₂ in ameliorating drought stress was consistent across species. Our results represent an important advance in our capacity to forecast the resilience of individual tree species, providing an evidence base for decision-making around the resilience of restoration plantings or net-zero emission strategies.

Seasonal and Inter-Annual Variations of Carbon Dioxide Fluxes and Their Determinants in an Alpine Meadow

The alpine meadow is one of the most important ecosystems on the Qinghai-Tibet Plateau (QTP) due to its huge carbon storage and wide distribution. Evaluating the carbon fluxes in alpine meadow ecosystems is crucial to understand the dynamics of carbon storage in high-altitude areas. Here, we investigated the carbon fluxes at seasonal and inter-annual timescales based on 5 years of observations of eddy covariance fluxes in the Zoige alpine meadow on the eastern Tibetan Plateau. We found that the Zoige alpine meadow acted as a faint carbon source of 94.69 ± 86.44 g C m^-2 y^-1 during the observation periods with large seasonal and inter-annual variations (IAVs). At the seasonal scale, gross primary productivity (GPP) and ecosystem respiration (Re) were positively correlated with photosynthetic photon flux density (PPFD), average daily temperature (Ta), and vapor pressure (VPD) and had negative relationships with volumetric water content (VWC). Seasonal variations of net ecosystem carbon dioxide (CO₂) exchange (NEE) were mostly explained by Ta, followed by PPFD, VPD, and VWC. The IAVs of GPP and Re were mainly attributable to the IAV of the maximum GPP rate (GPP_max) and maximum Re rate (Re_max), respectively, both of which increased with the percentage of Cyperaceae and decreased with the percentage of Polygonaceae changes across years. The IAV of NEE was well explained by the anomalies of the maximum CO₂ release rate (MCR). These results indicated that the annual net CO₂ exchange in the alpine meadow ecosystem was controlled mainly by the maximum C release rates. Therefore, a better understanding of physiological response to various environmental factors at peak C uptake and release seasons will largely improve the predictions of GPP, Re, and NEE in the context of global change.

Effect of Assimilating SMAP Soil Moisture on CO2 and CH4 Fluxes through Direct Insertion in a Land Surface Model

Soil moisture impacts the biosphere–atmosphere exchange of CO2 and CH4 and plays an important role in the terrestrial carbon cycle. A better representation of soil moisture would improve coupled carbon–water dynamics in terrestrial ecosystem models and could potentially improve model estimates of large-scale carbon fluxes and climate feedbacks. Here, we investigate using soil moisture observations from the Soil Moisture Active Passive (SMAP) satellite mission to inform simulated carbon fluxes in the global terrestrial ecosystem model LPJ-wsl. Results suggest that the direct insertion of SMAP reduces the bias in simulated soil moisture at in situ measurement sites by 40%, with a greater improvement at temperate sites. A wavelet analysis between the model and measurements from 26 FLUXNET sites suggests that the assimilated run modestly reduces the bias of simulated carbon fluxes for boreal and subtropical sites at 1–2-month time scales. At regional scales, SMAP soil moisture can improve the estimated responses of CO2 and CH4 fluxes to extreme events such as the 2018 European drought and the 2019 rainfall event in the Sudd (Southern Sudan) wetlands. The simulated improvements to land–surface carbon fluxes using the direct insertion of SMAP are shown across a variety of timescales, which suggests the potential of SMAP soil moisture in improving the model representation of carbon–water coupling.

Terrestrial carbon sinks in China and around the world and their contribution to carbon neutrality

Enhancing the terrestrial ecosystem carbon sink (referred to as terrestrial C sink) is an important way to slow down the continuous increase in atmospheric carbon dioxide (CO₂) concentration and to achieve carbon neutrality target. To better understand the characteristics of terrestrial C sinks and their contribution to carbon neutrality, this review summarizes major progress in terrestrial C budget researches during the past decades, clarifies spatial patterns and drivers of terrestrial C sources and sinks in China and around the world, and examines the role of terrestrial C sinks in achieving carbon neutrality target. According to recent studies, the global terrestrial C sink has been increasing from a source of (-0.2±0.9) Pg C yr^-1 (1 Pg=10¹⁵ g) in the 1960s to a sink of (1.9±1.1) Pg C yr^-1 in the 2010s. By synthesizing the published data, we estimate terrestrial C sink of 0.20-0.25 Pg C yr^-1 in China during the past decades, and predict it to be 0.15-0.52 Pg C yr^-1 by 2060. The terrestrial C sinks are mainly located in the mid- and high latitudes of the Northern Hemisphere, while tropical regions act as a weak C sink or source. The C balance differs much among ecosystem types: forest is the major C sink; shrubland, wetland and farmland soil act as C sinks; and whether the grassland functions as C sink or source remains unclear. Desert might be a C sink, but the magnitude and the associated mechanisms are still controversial. Elevated atmospheric CO₂ concentration, nitrogen deposition, climate change, and land cover change are the main drivers of terrestrial C sinks, while other factors such as fires and aerosols would also affect ecosystem C balance. The driving factors of terrestrial C sink differ among regions. Elevated CO₂ concentration and climate change are major drivers of the C sinks in North America and Europe, while afforestation and ecological restoration are additionally important forcing factors of terrestrial C sinks in China. For future studies, we recommend the necessity for intensive and long term ecosystem C monitoring over broad geographic scale to improve terrestrial biosphere models for accurately evaluating terrestrial C budget and its dynamics under various climate change and policy scenarios.

Can Surface Soil Moisture Information Identify Evapotranspiration Regime Transitions?

The transition of evapotranspiration between energy- and water-limitation regimes also denotes a nonlinear change in surface water and energy coupling strength. The regime transitions are primarily dominated by available moisture in the soil, although other micro-meteorological factors also play a role. Remotely sensed soil moisture is frequently used for detecting evapotranspiration regime transitions during inter storm dry downs. However, its sampling depth does not include the entire soil profile, over which water uptake is dominated by plant root distribution. We use flux tower, surface (θ _s ; observations at 5 cm), and vertically integrated in situ soil moisture ( θ v ; 0-50 cm) observations to address the question: Can surface soil moisture robustly identify evapotranspiration regime transitions? Results demonstrate that θ _s and θ _v are hydraulically linked and have synchronized evapotranspiration regime transitions. As such, θ _s and θ _v capture comparable statistics of evapotranspiration regime prevalence, which supports the utility of remote-sensing θ _s for large-scale land-atmosphere exchange analysis.

The coupling interaction of soil organic carbon stock and water storage after vegetation restoration on the Loess Plateau, China

Vegetation restoration may increase the soil organic carbon stock (SOCS) but decrease the soil water storage (SWS) of terrestrial ecosystems in arid and semiarid regions. To guarantee the sustainability of restoration, it is critical to evaluate the coupling interaction of SOCS and SWS. Here, we examined the spatial distributions of SOCS and SWS across a 0-200 cm soil profile in a grassland, forestland and shrubland on the Loess Plateau and determined the driving factors that affected their variations. Our results showed that SOCS and SWS varied across the 0-200 cm soil profile and considerably accumulated in the deep soil layers (100-200 cm). In comparison to SOCS, SWS generally had higher relative benefits in most studied plant communities, which ensured sustainable restoration. In addition, land use played a less important role than local environmental conditions in determining the variations in SOCS and SWS. Specifically, the interaction between SOCS and SWS was mainly strong in the surface soil layers (0-20 cm). Topography was a predominant factor that affected SOCS and SWS in the deep soil layers (100-200 cm), while soil texture was a stable driving factor influencing their variations across the whole soil profile (0-200 cm). Given the low moisture consumption of grasslands and the lowest root mean square deviation (RMSD) of Hippophae rhamnoides, we proposed an advanced scenario for ecological restoration on the Loess Plateau: establishing reasonably large Hippophae rhamnoides patches with fewer edges in a contiguous grassland matrix. Furthermore, this scenario should be tailored to local environmental conditions, such as soil water, texture and topography, followed by natural vegetation succession.

Amplified signals of soil moisture and evaporative stresses across Poland in the twenty-first century

In Poland, recent summer droughts have had devastating environmental, social, and economic consequences, but the trend of growing season dryness remains unclear. This study focuses on the soil moisture and evaporative stress conditions, analyzed in a multiyear period between 1981 and 2019. Country scale trends in growing season drought severities are assessed using indices derived from the model-based estimates of soil moisture and evapotranspiration. These are compared with indices derived from meteorological variables. Soil droughts are assessed by the Standardized Soil Index (SSI), while the ecological droughts are related to evapotranspiration by the Standardized Evaporative Stress Ratio (SESR). Moreover, the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and self-calibrating Palmer Drought Severity Index (sc-PDSI) are used for comparison. A Drought-Prone Area (DPA) is delineated based on a criterion defined as simultaneous occurrence of statistically significant drying trends in surface and root zone soil moisture and evaporative stress. It was found that soil and ecological drought severities have remarkably increased in the growing season. This confirms the hypothesis that intensified soil drying is accompanied by intensified water stress imprinted in evapotranspiration. The most severe drought sequence has occurred in recent years, amplified by exceptionally high air temperature, low precipitation, and high deficit in the climatic water balance. The highest correlation is observed between annual growing season drought severities derived from the SSI and SESR; only SPEI approximates an increasing trend, while the SPI and sc-PDSI do not follow such a trajectory. The study shows an almost contiguous spatial pattern of DPA, which takes 42% of the country. One important implication of this study is that soil moisture and evapotranspiration should be considered in assessing drought severity in addition to traditionally used meteorological variables.