Assessment of the importance of increasing temperature and decreasing soil moisture on global ecosystem productivity using solar-induced chlorophyll fluorescence

Nonlinear influences of climatic, vegetative, geographic and soil factors on soil water use efficiency of global karst landscapes: Insights from explainable machine learning

Soil Water Use Efficiency (SWUE) represents a vital metric for assessing the relationship between carbon acquisition and soil moisture (SM) depletion in terrestrial ecosystems. However, the elucidation of time-lagged and cumulative effects, nonlinear influences, and indirect contributions of explanatory variables, including climate and vegetation characteristics, on SWUE in global karst landscapes remains limited. In this study, we analyzed the time-lagged and cumulative effects of climatic and biological factors on SWUE in global karst landscapes using the Autoregressive Distributed Lag Model. By comparing nine machine learning models, we further revealed the nonlinear effects, as well as the direct and indirect contributions of climatic, geographic, soil, and biological explanatory variables on SWUE across varying aridity, using the Random Forest Model, SHapley Additive exPlanations, Generalized Additive Model, and Partial Least Squares-Structural Equation Modeling (PLS-SEM). The findings suggested that precipitation and wind speed exert the most substantial time-lagged and cumulative impacts on SWUE in global karst landscapes, respectively. The Random Forest model outperforms eight other machine learning models, including CatBoost, LightGBM, and XGBoost, in accurately simulating SWUE. In global karst landscapes, SWUE was significantly affected by the positive contributions of evapotranspiration, leaf area index, and temperature, as well as the negative impacts of latitude and longitude. These influences exhibited varying degrees of nonlinearity across the aridity gradient. Using PLS-SEM based on the 'geo-climatic-soil-biological' cascade effect, it was found that gross primary production directly and significantly influences karst SWUE under both drought-prone and water-abundant conditions, significantly exceeding the impact of SM. Geographic, climatic, and biological factors indirectly influenced karst SWUE by affecting gross primary production. The impact of soil type, soil carbon and nitrogen content, and rootable depth on SWUE was minimal. This study enhances our understanding of carbon sinks and the water‑carbon cycle, providing valuable insights into resource use efficiency within karst environments.

Tropospheric ozone pollution increases the sensitivity of plant production to vapor pressure deficit across diverse ecosystems in the Northern Hemisphere

Tropospheric ozone (O3) pollution often accompanies droughts and heatwaves, which could collectively reduce plant productivity. Previous research suggested that O3 pollution can alter plant responses to drought by interfering with stomatal closure while drought can reduce stomatal conductance and provide protection against O3 stress. However, the interactions between O3 pollution and drought stress remain poorly understood at ecosystem scales with diverse plant functional types. To address this research gap, we used 10-year (2012-2021) satellite near-infrared reflectance of vegetation (NIRv) observations, reanalysis data of vapor pressure deficit (VPD), soil moisture (SM), and air temperature (Ta), along with O3 measurements and reanalysis data across the Northern Hemisphere to statistically disentangle the interconnections between NIRv, VPD, SM, and Ta under varying O3 levels. We found that high O3 concentrations significantly exacerbate the sensitivity of NIRv to VPD while have no notable impacts on the sensitivity of NIRv to Ta or SM for all plant functional types, indicating an enhanced combined impact of VPD and O3 on plants. Specifically, the sensitivity of NIRv to VPD increased by >75 % when O3 anomalies increased from the lowest 10 to the highest 10 percentiles across diverse plant functional types. This is likely because long-term exposure to high O3 concentrations can inhibit stomatal closure and photosynthetic enzyme activities, resulting in reduced water use efficiency and photosynthetic efficiency. This study highlights the need to consider O3 in understanding plant responses to climate factors and that O3 can alter plant responses to VPD independently of Ta and SM.

Disentangling the impact of climate change, human activities, vegetation dynamics and atmospheric CO2 concentration on soil water use efficiency in global karst landscapes

Soil Water Use Efficiency (SWUE), which quantifies the carbon gain against each unit of soil moisture depletion, represents an essential ecological parameter that delineates the carbon-water coupling within terrestrial ecosystems. However, the spatiotemporal dynamics of SWUE, its sensitivity to environmental variables, and the underlying driving mechanisms across various temporal scales in the global karst region are largely uncharted. This study utilized the sensitivity algorithm of partial least squares regression, partial differential equations, and elasticity coefficients to investigate the characteristics of SWUE variations across different climatic zones in the global karst region and their responsiveness to environmental variables. Moreover, the study quantified the individual contributions of climate variability, atmospheric carbon dioxide concentration, human activities, and vegetation changes to SWUE variations. The results indicated that SWUE across different climatic zones in the global karst region demonstrated an increasing trend from 2000 to 2018, with the most notable improvement observed in the humid zone. SWUE presented regular distribution and variation characteristics across different latitudinal zones at a monthly scale. The sensitivity of SWUE to precipitation was significantly higher compared to its responsiveness to other environmental factors. Additionally, the trend in SWUE's sensitivity to precipitation demonstrated the most significant change. The sensitivity of SWUE to various environmental factors and the trend of this sensitivity in the arid zone revealed significant variation compared to other climatic zones. Gross primary productivity and soil moisture were identified as the intrinsic factors influencing SWUE changes, contributing 16 % and - 84 %, respectively. Climate variability and human activities were identified as the primary exogenous factors contributing to the increase in SWUE, accounting for 76 % and 16 %, respectively. This study advances the understanding of carbon-water coupling in karst regions, providing significant insights into the ecological management of global karst environments amidst climate variations.

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.

Assessing urban wetlands dynamics in Wuhan and Nanchang, China

Urban wetlands play a crucial role in sustainable social development. However, current research mainly focuses on specific wetland types, and fine extraction of urban wetlands remains a challenge. This study proposes a fine extraction framework based on hierarchical decision trees and shape features for urban wetlands, using Sentinel-2 remote sensing data to obtain detailed wetland data of Wuhan and Nanchang from 2016 to 2022. Our framework applies random forests to classify land cover, extracts urban fine wetlands by hierarchical decision trees and shape features, and assesses the dynamics of wetlands in the two cities. We also analyzed and discussed the characteristics of urban wetlands in the two cities. The results show that wetland accuracies of Wuhan and Nanchang are greater than 84.5 % and 82.9 %, respectively. The wetland areas of Wuhan in 2016, 2019, and 2022 are 1969.4 km2, 1713.8 km2, and 1681.1 km2, while those in Nanchang are 1405.9 km2, 1361.6 km2, and 766.9 km2. Inland wetlands are the main wetland types in both regions, with lake wetlands accounting for the highest proportion (over 40 %). The urban wetlands in the two cities exhibit different spatial and temporal evolution patterns, with varying change trends of wetland area and the structural proportions of fine wetlands. Besides, Wuhan's urban wetlands are primarily located in the south, while Nanchang's urban wetlands are concentrated in the east, exhibiting higher spatial and temporal dynamics. Analysis suggests that the reduced urban wetlands from 2016 to 2022 are related to fluctuating decreasing precipitation, growing population, and gross domestic product (GDP). Our study provides support for the conservation of urban wetland resources in Wuhan and Nanchang and highlights the need for targeted management strategies.

Soil moisture dominates the variation of gross primary productivity during hot drought in drylands

The frequency and severity of hot drought will increase in the future due to impact of climate change and human activities, threatening the sustainability of terrestrial ecosystems and human societies. Hot drought is a typical type of drought event, high vapor pressure deficit (VPD) and low soil moisture (SM) are its main characteristics of hot drought, with increasing water stress on vegetation and exacerbating hydrological drought and ecosystem risks. However, our understanding of the effects of high VPD and low SM on vegetation productivity is limited, because these two variables are strongly coupled and influenced by other climatic drivers. The southwestern United States experienced one of the most severe hot drought events on record in 2020. In this study, we used SM and gross primary productivity (GPP) datasets from Soil Moisture Active and Passive (SMAP), as well as VPD and other meteorological datasets from gridMET. We decoupled the effects of different meteorological factors on GPP at monthly and daily scales using partial correlation analysis, partial least squares regression, and binning methods. We found that SM anomalies contribute more to GPP anomalies than VPD anomalies at monthly and daily scales. Especially at the daily scale, as the decoupled SM anomalies increased, the GPP anomalies increased. However, there is no significant change in GPP anomalies as VPD increases. For all the vegetation types and arid zones, SM dominated the variation in GPP, followed by VPD or maximum temperature. At the flux tower scale, decoupled soil water content (SWC) also dominated changes in GPP, compared to VPD. In the next century, hot drought will occur frequently in dryland regions, where GPP is one of the highest uncertainties in terrestrial ecosystems. Our study has important implications for identifying the strong coupling of meteorological factors and their impact on vegetation under climate change.

Vegetation as the catalyst for water circulation on global terrestrial ecosystem

Global climate change is expected to further intensify the global water cycle, leading to more rapid evaporation and more intense precipitation. At the same time, the growth and expansion of natural vegetation caused by climate change and human activities create potential conflicts between ecosystems and humans over available water resources. Clarifying how terrestrial ecosystem evapotranspiration responds to global precipitation and vegetation facilitates a better understanding of and prediction for the responses of global ecosystem energy, water, and carbon budgets under climate change. Relying on the spatial and temporal distribution of evapotranspiration, precipitation, and solar-induced chlorophyll fluorescence (SIF) from remote sensing platforms, we decouple the interaction mechanism of evapotranspiration, precipitation, and vegetation in linear and nonlinear scenarios using correlation and partial correlation analysis, multiple linear regression analysis, and binning. Major conclusions are as follows: (1) As a natural catalyst of the global water cycle, vegetation plays a crucial role in regulating the relationship between climate change and the water‑carbon-energy cycle. (2) Vegetation, a key parameter affecting the water cycle, participates in the entire water cycle process. (3) The increase in vegetation productivity and photosynthesis plays a dominant role in promoting evapotranspiration in vegetated areas, while the increase in precipitation dominates the promotion of evapotranspiration in non-vegetated areas.

Contrasting ecosystem vegetation response in global drylands under drying and wetting conditions

Increasing aridity is one major consequence of ongoing global climate change and is expected to cause widespread changes in key ecosystem attributes, functions, and dynamics. This is especially the case in naturally vulnerable ecosystems, such as drylands. While we have an overall understanding of past aridity trends, the linkage between temporal dynamics in aridity and dryland ecosystem responses remain largely unknown. Here, we examined recent trends in aridity over the past two decades within global drylands as a basis for exploring the response of ecosystem state variables associated with land and atmosphere processes (e.g., vegetation cover, vegetation functioning, soil water availability, land cover, burned area, and vapor-pressure deficit) to these trends. We identified five clusters, characterizing spatiotemporal patterns in aridity between 2000 and 2020. Overall, we observe that 44.5% of all areas are getting dryer, 31.6% getting wetter, and 23.8% have no trends in aridity. Our results show strongest correlations between trends in ecosystem state variables and aridity in clusters with increasing aridity, which matches expectations of systemic acclimatization of the ecosystem to a reduction in water availability/water stress. Trends in vegetation (expressed by leaf area index [LAI]) are affected differently by potential driving factors (e.g., environmental, and climatic factors, soil properties, and population density) in areas experiencing water-related stress as compared to areas not exposed to water-related stress. Canopy height for example, has a positive impact on trends in LAI when the system is stressed but does not impact the trends in non-stressed systems. Conversely, opposite relationships were found for soil parameters such as root-zone water storage capacity and organic carbon density. How potential driving factors impact dryland vegetation differently depending on water-related stress (or no stress) is important, for example within management strategies to maintain and restore dryland vegetation.

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.

Climate Controls on the Spatial Variability of Vegetation Greenup Rate across Ecosystems in Northern Hemisphere

Variations in individual phenological events in response to global change have received considerable attentions. However, the development of phenological stages is relatively neglected, especially based on in situ observation data. In this study, the rate of vegetation greenup (Vgreenup) across the Northern Hemisphere was examined for different plant functional types (PFTs) by using eddy covariance flux data from 40 sites (417 site-years). Then, the controls of climatic variables on the spatial distribution of Vgreenup across PFTs were further investigated. The mean Vgreenup was 0.22 ± 0.11 g C m^-2 day^-2 across all sites, with the largest and lowest values observed in cropland and evergreen needle-leaf forest, respectively. A strong latitude dependence by Vgreenup was observed in both Europe and North America. The spatial variations of Vgreenup were jointly regulated by the duration of greenup (Dgreenup) and the amplitude of greenup (Agreenup). However, the predominant factor was Dgreenup in Europe, which changed to Agreenup in North America. Spring climatic factors exerted significant influences on the spatial distribution of Vgreenup across PFTs. Specifically, increasing temperature tended to shorten Dgreenup and promote Agreenup simultaneously, resulting in an acceleration of Vgreenup. Dryness had a depression effect on Vgreenup for the whole study area, as exhibited by a lower Vgreenup with increasing vapor pressure deficit or decreasing soil moisture. However, Vgreenup in North America was only significantly and positively correlated with temperature. Without the limitation of other climatic factors, the temperature sensitivity of Vgreenup was higher in North America (0.021 g C m^-2 day^-2 °C^-1) than in Europe (0.015 g C m^-2 day^-2 °C^-1). This study provides new cognitions for Vgreenup dynamics from in situ observations in complement to satellite observations, which can improve our understanding of terrestrial carbon cycles.

Assessing the Potential of Downscaled Far Red Solar-Induced Chlorophyll Fluorescence from the Canopy to Leaf Level for Drought Monitoring in Winter Wheat

Solar-induced chlorophyll fluorescence (SIF) from ground, airborne, and satellite-based observations has been increasingly used in drought monitoring recently due to its close relationship with photosynthesis. SIF emissions respond rapidly to droughts, relative to the widely used vegetation indices (VIs), thus indicating their potential for early drought monitoring. The response of SIF to droughts can be attributed to the confounding effects of both the physiology and canopy structure. In order to reduce the reabsorption and scattering effects, the total emitted SIF (SIFtot) was proposed and served as a better tool to estimate GPP compared with the top-of-canopy SIF (SIFtoc). However, the response time and response magnitude of SIFtot to droughts and its relationships with the environmental parameters and soil moisture (SM) (i.e., the knowledge of drought monitoring using SIFtot) remains unclear. Here, the continuous ground data of F760toc (SIFtoc at 760 nm) from a nadir view that was downscaled to F760tot (SIFtot at 760 nm), NIRv, and the NDVI, SM, meteorological, and crop growth parameters were measured from four winter wheat plots with different intensities of drought (well-watered, moderate drought, severe drought, and extreme drought) over 2 months. The results indicated that F760tot was more closely correlated with the SM than the VIs at short time lags but weaker at longer time lags. The daily mean values of F760tot and NIRv were able to distinguish the differences between different drought levels, and F760tot responded quickly to the onset of drought, especially for the moderate drought intensity. These findings demonstrated that F760tot has potential for early drought monitoring and may contribute to mitigating the risk of agricultural drought.