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Coupling localized Noah-MP-Crop model with the WRF model improved dynamic crop growth simulation across Northeast China

Croplands play a critical role in regulating the energy and moisture exchanges between the land surface and atmosphere. However, the interactions between cropland and climate are usually poorly represented due to a lack of detailed representation in crop types and field management. Here, we coupled the Noah-MP-Crop model with the state-of-the-art Weather Research and Forecasting (WRF) model to explore and evaluate the crop growth dynamics in response to climate variations across Northeast China. The default parameters of the crop model were not exactly suitable for the agricultural ecosystems in Northeast China. The detailed cropland distribution, and crop phenology parameters including growing degree days (GDD) and planting (harvesting) date were first created using multi-source remote sensing products and reanalysis data, and was then successfully used to simulate the growth and yield for corn and soybean and associated energy exchanges. We also optimized and calibrated other crop parameters using the time-series of the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface products. The modified crop model substantially improved the simulation of crop growth, plant physiology, and biomass accumulation for both corn and soybean. Coupling the localized dynamic crop model into the WRF led to considerable decreases in the simulated mean-absolute-errors (MAEs) and biases of the leaf area index, evapotranspiration, and gross primary production compared with the MODIS observed values. Compared with the statistical yield from each province, the modified crop model underestimated the corn yield from 11.1% to 48.6%, whereas overestimated the soybean yield from 16.5% to 162.6%.

54 ENVIRONMENTAL SCIENCES↗

Irrigation in the Earth System

Irrigation accounts for ~70% of global freshwater withdrawals and ~90% of consumptive water use, driving myriad Earth system impacts. In this Review, we summarize how irrigation currently impacts key components of the Earth system. Estimates suggest that more than 3.6 million km 2 of currently irrigated land, with hot spots in the intensively cultivated US High Plains, California Central Valley, Indo-Gangetic Basin and northern China. Process-based models estimate that ~2,700 ± 540 km 3 irrigation water is withdrawn globally each year, broadly consistent with country-reported values despite these estimates embedding substantial uncertainties. Expansive irrigation has modified surface energy balance and biogeochemical cycling. A shift from sensible to latent heat fluxes, and resulting land–atmosphere feedbacks, generally reduce regional growing season surface temperatures by ~1–3 °C. Irrigation can ameliorate temperature extremes in some regions, but conversely exacerbates moist heat stress. Modelled precipitation responses are more varied, with some intensive cropping regions exhibiting suppressed local precipitation but enhanced precipitation downstream owing to atmospheric circulation interactions. Additionally, irrigation could enhance cropland carbon uptake; however, it can also contribute to elevated methane fluxes in rice systems and mobilize nitrogen loading to groundwater. Cross-disciplinary, integrative research efforts can help advance understanding of these irrigation–Earth system interactions, and identify and reduce uncertainties, biases and limitations.

Climate sciences↗

Land-use and atmospheric shifts jointly amplify U.S. drought-driven crop losses

Agricultural drought (AD) poses a major threat to food security, yet its future risk remains uncertain under co-evolving atmospheric conditions and land-use trajectories. Using an integrated, multi-sector modeling framework, we project AD risks for major crops across the contiguous United States (CONUS) through 2055 under a range of plausible futures that capture thermodynamic changes and land-use and land-cover change (LULCC) trajectories. Model projections reveal that drought-driven crop production losses increase sharply by nearly 60% for corn, 250% for wheat, and 135% for soybean relative to historical levels. The primary drivers of these increases, which include atmospheric shifts and LULCC, vary by region and crop type. LULCC acting as an important risk amplifier in regions experiencing cropland expansion into drought-prone regions, such as the Great Plains and northwestern U.S. Wheat exhibits the largest projected loss increases, a result that remains robust across scenarios. These findings highlight that interactions between atmospheric conditions and land-use trajectories shape future agricultural drought risk and should be jointly considered to support effective adaptation and food-system planning.

Yao, Lili↗

FIFE data analysis: Testing BIOME-BGC predictions for grasslands

The First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) was conducted in a 15 km by 15 km research area located 8 km south of Manhattan, Kansas. The site consists primarily of native tallgrass prairie mixed with gallery oak forests and croplands. The objectives of FIFE are to better understand the role of biology in controlling the interactions between the land and the atmosphere, and to determine the value of remotely sensed data for estimating climatological parameters. The goals of FIFE are twofold: the upscale integration of models, and algorithm development for satellite remote sensing. The specific objectives of the field campaigns carried out in 1987 and 1989 were the simultaneous acquisition of satellite, atmospheric, and surface data; and the understanding of the processes controlling surface energy and mass exchange. Collected data were used to study the dynamics of various ecosystem processes (photosynthesis, evaporation and transpiration, autotrophic and heterotrophic respiration, etc.). Modelling terrestrial ecosystems at scales larger than that of a homogeneous plot led to the development of simple, generalized models of biogeochemical cycles that can be accurately applied to different biomes through the use of remotely sensed data. A model was developed called BIOME-BGC (for BioGeochemical Cycles) from a coniferous forest ecosystem model, FOREST-BGC, where a biome is considered a combination of a life forms in a specified climate. A predominately C4-photosynthetic grassland is probably the most different from a coniferous forest possible, hence the FIFE site was an excellent study area for testing BIOME-BGC. The transition from an essentially one-dimensional calculation to three-dimensional, landscape scale simulations requires the introduction of such factors as meteorology, climatology, and geomorphology. By using remotely sensed geographic information data for important model inputs, process-based ecosystem simulations at a variety of scales are possible. The second objective of this study is concerned with determining the accuracy of the estimated fluxes from BIOME-BGC, when extrapolated spatially over the entire 15-km by 15-km FIFE site. To accomplish this objective, a topographically distributed map of soil depth at the FIFE site was developed. These spatially-distributed fluxes were then tested with data from aircraft by eddy-flux correlation obtained during the FIFE experiment.

Hunt, E. Raymond, Jr.↗

Evaluating ecosystem water use efficiency under drought stress: a case study of the Helan Mountain region, northwest China

Context Water use efficiency (WUE) is a fundamental ecological indicator links carbon assimilation and water loss in terrestrial ecosystems. Understanding its responses to drought stress is essential for adaptive ecosystem management, particularly in climate-sensitive mountain landscapes. Objectives This study aimed to investigate drought-driven variations in WUE across major vegetation types in the Helan Mountain region of Northwest China. Specifically, we sought to identify dominant ecological drivers of WUE variability and to disentangle their relative importance and causal pathways. Methods We quantified WUE using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Drought Severity Index (DSI) data from 2001 to 2020. To examine WUE – drought relationships across contrasting vegetation types, we employed a spatially explicit analytical framework integrating Random Forest (RF) modeling, partial correlation analysis, and structural equation modeling (SEM). Results Regional WUE exhibited relatively stable interannual dynamics, yet pronounced spatial heterogeneity that was strongly modulated by drought conditions. Vegetation properties, particularly Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI), emerged as the dominant determinants of WUE, with NDVI alone explaining over 20% of its spatial variance in forest and grassland during non-drought periods. SEM analyses revealed that climate forcing influenced WUE mainly through indirect pathways mediated by soil moisture availability and vegetation structural dynamics, rather than through direct climatic controls. Among all regulating factors, LAI acted as the central control node governing ecosystem carbon–water coupling. In contrast, short-term climatic stress, especially atmospheric demand and drought duration, exerted weak or negative direct effects on WUE. Ecosystem-specific responses were observed, with croplands mainly regulated by soil water availability, whereas forests and grasslands showed more sensitive to atmospheric drought stress. Together, these results reveal a hierarchical control framework where soil–vegetation interactions mediate climate impacts on WUE, driving strong spatial heterogeneity in drought responses across mountain landscapes. Conclusions Our findings highlight the pivotal role of indirect drought effects mediated by vegetation and soil processes in shaping ecosystem WUE. The identified soil–vegetation–climate regulatory hierarchy provides mechanistic insight into landscape–scale drought sensitivity and supports integrated modeling approaches for evaluating ecosystem resilience and sustainable management in arid mountain regions.

China↗

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

Abstract 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.

54 ENVIRONMENTAL SCIENCES↗

Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem

Coastal terrestrial-aquatic interfaces (TAIs) are crucial contributors to global biogeochemical cycles and carbon exchange. A systematic evaluation of the interaction between coastal catchment properties and carbon dioxide (CO2) emission by soil respiration is significant for assessing carbon dynamics and predicting the future trajectory of atmospheric CO2 concentrations in coastal TAIs. The soil CO2 efflux in these transition zones is however poorly understood due to the high spatiotemporal dynamics of TAIs, as various sub-ecosystems in this region are compressed and expanded by complex influences of tides, changes in river levels, climate, and land use. We focus on the Chesapeake Bay region to (i) investigate the spatial heterogeneity of the coastal ecosystem and identify spatial zones with similar environmental characteristics based on the spatial data layers, including vegetation index (kNDVI), climate, landcover, diversity, topography, soil property, and relative tidal elevation; (ii) understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. Specifically, we employed hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, followed by the determination of main driving factors using Random Forest regression and SHapley Additive exPlanations. Maximum and minimum temperature are the main drivers common to all sub-ecosystems, while each region also has additional unique major drivers that differentiate them from one another. Precipitation exerts an influence on vegetated lands, while soil pH value holds importance specifically in forested lands. In croplands characterized by high clay content and low sand content, the significant role is attributed to bulk density. Wetlands demonstrate the importance of both elevation and sand content, with clay content being more relevant in non-inundated wetlands than in inundated wetlands. The topographic wetness index significantly contributes to the mixed vegetation areas, including shrub, grass, pasture, and forest. Additionally, our research reveals that dense vegetation land covers and urban/developed areas exhibit distinct soil property drivers. Overall, there is no one-size-fits-all approach to modeling carbon fluxes in coastal TAIs, and our study highlights the importance of further research and monitoring practices to improve our understanding of carbon dynamics and promote the sustainable management of coastal TAIs.

54 ENVIRONMENTAL SCIENCES↗

Reduced accrual of mineral-associated organic matter after two years of enhanced rock weathering in cropland soils, though no net losses of soil organic carbon

Abstract Enhanced rock weathering (ERW), the application of crushed silicate rock to soil, can remove atmospheric carbon dioxide by converting it to (bi) carbonate ions or solid carbonate minerals. However, few studies have empirically evaluated ERW in field settings. A critical question remains as to whether additions of crushed rock might positively or negatively affect soil organic matter (SOM)—Earth’s largest terrestrial organic carbon (C) pool and a massive reservoir of organic nitrogen (N). Here, in three irrigated cropland field trials in California, USA, we investigated the effect of crushed meta-basalt rock additions on different pools of soil organic carbon and nitrogen (i.e., mineral-associated organic matter, MAOM, and particulate organic matter, POM), active microbial biomass, and microbial community composition. After 2 years of crushed rock additions, MAOM stocks were lower in the upper surface soil (0–10 cm) of plots with crushed rock compared to unamended control plots. At the 2 sites where baseline pre-treatment data were available, neither total SOC nor SON decreased over the 2 years of study in plots with crushed rock or unamended control plots. However, the accrual rate of MAOM-C and MAOM-N at 0–10 cm was lower in plots with crushed rock vs. unamended controls. Before ERW is deployed at large scales, our results suggest that field trials should assess the effects of crushed rock on SOM pools, especially over multi-year time scales and in different environmental contexts, to accurately assess changes in net C and understand the mechanisms driving interactions between ERW and SOM cycling.

58 GEOSCIENCES↗

A meta-analysis of global cropland soil carbon changes due to cover cropping

Including cover crops within agricultural rotations may increase soil organic carbon (SOC). However, contradictory findings generated by on-site experiments make it necessary to perform a comprehensive assessment of interactions between cover crops, environmental and management factors, and changes in SOC. In this study, we collected data from studies that compared agricultural production with and without cover crops, and then analyzed those data using meta-analysis and regression. Our results showed that including cover crops into rotations significantly increased SOC, with an overall mean change of 15.5% (95% confidence interval of 13.8% to 17.3%). Whereas medium-textured soils had highest SOC stocks with (mean = 39 Mg ha-1) and without (mean = 37 Mg ha-1) cover crops, fine-textured soils showed the greatest increase in SOC after the inclusion of cover crops (mean change of 39.5%). Coarse-textured (11.4%) and medium-textured soils (10.3%) had comparatively smaller changes in SOC. Cover crop mixtures resulted in greater increases in SOC compared to mono-species cover crops, and using legumes resulted in greater SOC increases than grasses and broadleaf species. Cover cropping was associated with significant SOC increases in shallow soils (= 30 cm), but not in subsurface soils (> 30 cm). The regression analysis revealed that SOC changes from cover cropping were correlated with improvements in soil quality, specifically decreased runoff and erosion and increased mineralizable carbon, mineralizable nitrogen, and soil nitrogen. Soil carbon change was also affected by annual temperature, number of years after start of cover crop usage, latitude, and initial SOC concentrations. Finally, the mean rate of carbon sequestration from cover cropping across all studies was 0.56 Mg ha-1 yr-1. If 15% of current global cropland were to adopt cover crops, this value would translate to 0.17 Pg of carbon sequestered per year or ~1-2% of current fossil fuels emissions. Altogether, these results indicated that inclusion of cover crops into agricultural rotations can enhance soil carbon concentrations, improve many soil quality parameters, and serve as a potential sink for atmosphere CO2.

Cover crop, soil organic carbon, soil quality, soi↗

Role of Forest Carbon Change in Shaping Future Land Use and Land Cover Change

Global change, particularly the changes in atmospheric CO 2 concentration, climatic variables, and nitrogen deposition, has been widely recognized and examined to have worldwide impacts on forest carbon. However, its influence on forest area required to meet the demand for timber and carbon storage and subsequent land use and land cover change (LULCC) is rarely studied. This study explores the role of global change-driven forest carbon change in shaping future global LULCC projections and investigates underlying drivers. We incorporated the global change impacts on forest carbon from the Canadian Land Surface Scheme Including Biogeochemical Cycles model simulations (driven by meteorological forcing projections from two Earth system models [ESMs]) into the Global Change Analysis Model, under three combinations of shared socioeconomic pathways and representative concentration pathways (SSP126, SSP370, and SSP585). Including forest carbon change decreases the projected expansion of managed forest and managed pasture, reduces the loss of unmanaged pastures and forests, and provides more cropland. The relative change in managed forest by 2100 is -4.0%, -21.7%, and -31.9%, under SSP126, SSP370, and SSP585, respectively, when forest carbon change is considered. CO 2 fertilization is the dominant driver, increasing forest vegetation and soil carbon by 37% and 4.1%, and leading to 78.6% of the total area with a change in land use types by 2100 under SSP585. In comparison, climate change reduces forest vegetation and soil carbon by -3.5% and -0.8%, influencing 23.9% of the total area with a change in land use types by 2100 under SSP585, while nitrogen deposition has minor impacts. Using meteorological forcing data from two ESMs leads to similar impacts of forest carbon change on LULCC in terms of sign and trend but different magnitudes. This study highlights the large impact of forest carbon change on shaping future LULCC dynamics and the critical role of CO 2 fertilization.

54 ENVIRONMENTAL SCIENCES↗