Recent leveling off of vegetation greenness and primary production reveals the increasing soil water limitations on the greening Earth

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.

Satellite-observed increasing coupling between vegetation productivity and greenness in the semiarid Loess Plateau of China is not captured by process-based models

Global vegetation has experienced notable changes in greenness and productivity since the early 1980s. However, the changes in the relationship between productivity and greenness, i.e., the coupling, and its underlying mechanisms, are poorly understood. The Loess Plateau (LP) is one of China's most significant areas for vegetation greening. Yet, it remains poorly documented what changes in the coupling between productivity and greenness are and how environmental and anthropogenic factors affect this coupling in the LP over the past four decades. We investigated the interannual trend of coupling between Gross Primary Productivity (GPP) and Leaf Area Index (LAI), i.e., the GPP-LAI coupling, and its response to climate factors and afforestation in the LP using long-term remote-sensed LAI, GPP and Solar-induced Chlorophyll Fluorescence (SIF). We found a monotonically increasing trend in the GPP-LAI coupling in the LP from 1982 to 2018 (0.0043 yr-1, p < 0.05), in which the significant trend in the northwest LP was driven by increasing soil water and landcover change, e.g., increased grassland and afforestation. An ensemble of 11 state-of-the-art ecosystem models from the TRENDY project failed to capture the observed monotonically increasing trend of the GPP-LAI coupling in the LP. The consistent projection of a decreasing GPP-LAI coupling in LP during 2019-2100 by 22 Earth System Models (ESMs) under various future scenarios should be treated with caution due to the identified inherent uncertainties in the ecosystem component in ESMs and the notable biases in the simulation of future climate conditions. Our study highlights the need to enhance the key mechanisms that regulate the coupling relationships between photosynthesis and canopy structure in indigenized ecosystem models to accurately estimate the ecosystem change in drylands under global climate change.

Vegetation browning: global drivers, impacts, and feedbacks

As global climate conditions continue to change, disturbance regimes and environmental drivers will continue to shift, impacting global vegetation dynamics. Following a period of vegetation greening, there has been a progressive increase in remotely sensed vegetation browning globally. Given the many societal benefits that forests provide, it is critical that we understand vegetation dynamic alterations. Here, we review associative drivers, impacts, and feedbacks, revealing the complexity of browning. Concomitant increases in browning include the weakening of ecosystem services and functions and alterations to vegetation structure and species composition, as well as the development of potential positive climate change feedbacks. Also discussed are the current challenges in browning detection and understanding associated impacts and feedbacks. Finally, we outline recommended strategies.

Compound droughts slow down the greening of the Earth

Vegetation response to soil and atmospheric drought has raised extensively controversy, however, the relative contributions of soil drought, atmospheric drought, and their compound droughts on global vegetation growth remain unclear. Combining the changes in soil moisture (SM), vapor pressure deficit (VPD), and vegetation growth (normalized difference vegetation index [NDVI]) during 1982-2015, here we evaluated the trends of these three drought types and quantified their impacts on global NDVI. We found that global VPD has increased 0.22 ± 0.05 kPa·decade^-1 during 1982-2015, and this trend was doubled after 1996 (0.32 ± 0.16 kPa·decade^-1 ) than before 1996 (0.16 ± 0.15 kPa·decade^-1 ). Regions with large increase in VPD trend generally accompanied with decreasing trend in SM, leading to a widespread increasing trend in compound droughts across 37.62% land areas. We further found compound droughts dominated the vegetation browning since late 1990s, contributing to a declined NDVI of 64.56%. Earth system models agree with the dominant role of compound droughts on vegetation growth, but their negative magnitudes are considerably underestimated, with half of the observed results (34.48%). Our results provided the evidence of compound droughts-induced global vegetation browning, highlighting the importance of correctly simulating the ecosystem-scale response to the under-appreciated exposure to compound droughts as it will increase with climate change.

Reversal of soil moisture constraint on vegetation growth in North China

The response of vegetation growth to soil moisture varies greatly from space and time under climate change and anthropogenic activities. As an important grain producer in China, the vegetation growth and grain production of North China are constrained by the region's water resources. With the significant increase in vegetation greenness in North China over the last 40 years, it is essential to explore the changes in soil moisture constraints on vegetation growth to water management. However, to what degree vegetation growth responds to soil moisture and how the response varies spatiotemporally in North China remain unclear. In this study, the response patterns of vegetation growth to soil moisture at different depths and the spatiotemporal trend patterns of their relationships were explored thoroughly based on long time series remote sensing data in North China over the past 40 years. The results showed that compared to forests, the growth of grasslands and crops with one maturity per year and two maturity per year in North China was more constrained by soil moisture. Due to the combined effects of climatic conditions and human activities, vegetation growth in North China has been significantly less constrained by soil moisture over the last 40 years. This was especially seen in one maturity per year crop and natural vegetation in Shanxi and central Shandong. However, with the significant increase in temperature, potential evapotranspiration and water demand of the crop, the moisture constraints on vegetation growth in North China have begun to show an increasing trend since the early 2000s, especially for irrigated crop in central and southern North China. These findings highlight a comprehensive understanding of the vegetation response to soil moisture from the time-varying perspective and provide a theoretical basis for water management and appropriate planning of agricultural water use in North China.

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.

Pan-Arctic soil moisture control on tundra carbon sequestration and plant productivity

Long-term atmospheric CO₂ concentration records have suggested a reduction in the positive effect of warming on high-latitude carbon uptake since the 1990s. A variety of mechanisms have been proposed to explain the reduced net carbon sink of northern ecosystems with increased air temperature, including water stress on vegetation and increased respiration over recent decades. However, the lack of consistent long-term carbon flux and in situ soil moisture data has severely limited our ability to identify the mechanisms responsible for the recent reduced carbon sink strength. In this study, we used a record of nearly 100 site-years of eddy covariance data from 11 continuous permafrost tundra sites distributed across the circumpolar Arctic to test the temperature (expressed as growing degree days, GDD) responses of gross primary production (GPP), net ecosystem exchange (NEE), and ecosystem respiration (ER) at different periods of the summer (early, peak, and late summer) including dominant tundra vegetation classes (graminoids and mosses, and shrubs). We further tested GPP, NEE, and ER relationships with soil moisture and vapor pressure deficit to identify potential moisture limitations on plant productivity and net carbon exchange. Our results show a decrease in GPP with rising GDD during the peak summer (July) for both vegetation classes, and a significant relationship between the peak summer GPP and soil moisture after statistically controlling for GDD in a partial correlation analysis. These results suggest that tundra ecosystems might not benefit from increased temperature as much as suggested by several terrestrial biosphere models, if decreased soil moisture limits the peak summer plant productivity, reducing the ability of these ecosystems to sequester carbon during the summer.

Revegetation affects the response of land surface phenology to climate in Loess Plateau, China

Land surface phenology (LSP), defined as the plant's growth rhythm retrieved from satellite sensing products, is proven to shift with climate change and affect the carbon cycles of terrestrial ecosystems. Global afforested area is largely increasing and consequently affecting local and global climate. However, how and to what extent revegetation affects LSP remains relatively unexplored. Here we investigated the difference in four LSPs (i.e., greenup, maturity, senescence, and dormancy) and the response of LSP to climate between restored and native vegetation on Loess Plateau, China, where a remarkable process of vegetation restoration happened during 1982-2015. Most study regions showed a longer growing season (LOS) over time, specifically, with a slight delay in greenup but a relatively large delay in senescence. We found that air temperature was the dominant factor affecting greenup and maturity, while precipitation mostly controlled the senescence and dormancy in the study area. Under similar climate conditions, the LSP of restored vegetation (i.e., restored forest and grassland) showed a significant difference (p < 0.05) from native ones during 1999-2015. Compared to the native forest, restored forest from cropland and grassland showed a delayed greenup date by 0.3 and 3.6 days (p < 0.05) and an advanced dormancy date of 6.6 and 9.0 days (p < 0.05), respectively. Furthermore, the restored vegetation became less sensitive to air temperature than native vegetation, while the restored forest was more sensitive to precipitation, and its growth was affected by the water limitation to a larger extent in the study area. Our study highlights the necessity of considering land use management and its effect on the LSP change to better understand the effect of afforestation on global climate and carbon cycles.

Processes and mechanisms of vegetation ecosystem responding to climate and ecological restoration in China

Vegetation is an essential component of the earth's surface system and its dynamics is a clear indicator of global climate change. However, the vegetation trends of most studies were based on time-unvarying methods, cannot accurately detect the long-term nonlinear characteristics of vegetation changes. Here, the ensemble empirical mode decomposition and the Breaks for Additive Seasonal and Trend algorithm were applied to reconstruct the the normalized difference vegetation index (NDVI) data and diagnose spatiotemporal evolution and abrupt changes of long-term vegetation trends in China during 1982-2018. Residual analysis was used to separate the influence of climate and human activities on NDVI variations, and the effect of specific human drivers on vegetation growth was obtained. The results suggest that based on the time-varying analysis, high vegetation browning was masked by overall vegetation greening. Vegetation growth in China experienced an abrupt change in the 1990s and 2000s, accounting for 50% and 33.6% of the whole China respectively. Of the area before the breakpoint, 45.4% showed a trend of vegetation decrease, which was concentrated mainly in east China, while 43% of the area after the breakpoint also showed vegetation degradation, mainly in northwest China. Climate was an important driving force for vegetation change in China. It played a positive role in south China, but had a negative effect in northwest China. The impact of human activities on vegetation growthchanged from an initial negative influence to a positive one. In terms of human activities, an inverted-U-shaped relation was detected between CO₂ emissions and vegetation growth; that is, the fertilization effect of CO₂ had a certain threshold. Once that threshold was exceeded, it would hinder vegetation growth. Population density had a slight constraint on vegetation growth, and the implementation of ecological restoration projects (e.g., the Grain for Green Program) can promote vegetation growth to a certain extent.

Divergent Climate Sensitivities of the Alpine Grasslands to Early Growing Season Precipitation on the Tibetan Plateau

Warming is expected to intensify hydrological processes and reshape precipitation regimes, which is closely related to water availability for terrestrial ecosystems. Effects of the inter-annual precipitation changes on plant growth are widely concerned. However, it is not well-known how plant growth responds to intra-annual precipitation regime changes. Here, we compiled reanalysis climate data (ERA5) and four satellite-based vegetation indices, including the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the Solar-induced Chlorophyll Fluorescence (SIF), and the Modified Triangular Vegetation Index (MTVI2), to evaluate the response of alpine grasslands (including alpine meadow and alpine steppe) to the change of precipitation regimes, especially to the intra-annual precipitation regimes on the Tibetan Plateau. We found monthly precipitation over the alpine steppe significantly increased in the growing season (May–September), but precipitation over the alpine meadow significantly increased only in the early growing season (May–June) (MJP) during the past four decades (1979–2019). The inter-annual plant growth (vegetation indices changes) on the alpine meadow was dominated by temperature, but it was driven by precipitation for the alpine steppe. On the intra-annual scale, the temperature sensitivity of the vegetation indices generally decreased but precipitation sensitivity increased during the growing season for both the alpine meadow and steppe. In response to the increase in MJP, we found the temperature sensitivity of the vegetation indices during the mid-growing season (July–August) (MGNDVI, MGEVI, MGSIF, and MGMTVI2) in the alpine meadow significantly increased (p < 0.01) while its precipitation sensitivity significantly decreased (p < 0.01). We infer that more MJP over the meadow may be the result of enhanced evapotranspiration, which is at the expense of soil moisture and even induces soil “drought” in the early growing season. This may be to elevate community water acquisition capacity through altering root mass allocation and community composition, consequently regulating the divergent climate sensitivities of vegetation growth in the mid-growing season. Our findings highlight that it is inadequate to regard precipitation as an indicator of water availability conditions for plant growth, which may limit our understanding of the response and acclimatization of plants to climate change.

The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model

This work tests the hypothesis that jointly assimilating satellite observations of leaf area index and surface soil moisture into a land surface model improves the estimation of land vegetation and water variables. An Ensemble Kalman Filter is used to test this hypothesis across the Contiguous United States from April 2015 to December 2018. The performance of the proposed methodology is assessed for several modeled vegetation and water variables (evapotranspiration, net ecosystem exchange, and soil moisture) in terms of random errors and anomaly correlation coefficients against a set of independent validation datasets (i.e., Global Land Evaporation Amsterdam Model, FLUXCOM, and International Soil Moisture Network). The results show that the assimilation of the leaf area index mostly improves the estimation of evapotranspiration and net ecosystem exchange, whereas the assimilation of surface soil moisture alone improves surface soil moisture content, especially in the western US, in terms of both root mean squared error and anomaly correlation coefficient. The joint assimilation of vegetation and soil moisture information combines the results of individual vegetation and soil moisture assimilations and reduces errors (and increases correlations with the reference datasets) in evapotranspiration, net ecosystem exchange, and surface soil moisture simulated by the land surface model. However, because soil moisture satellite observations only provide information on the water content in the top 5 cm of the soil column, the impact of the proposed data assimilation technique on root zone soil moisture is limited. This work moves one step forward in the direction of improving our estimation and understanding of land surface interactions using a multivariate data assimilation approach, which can be particularly useful in regions of the world where ground observations are sparse or missing altogether.

Vegetation Greenness Variations and Response to Climate Change in the Arid and Semi-Arid Transition Zone of the Mongo-Lian Plateau during 1982–2015

Vegetation greenness dynamics in arid and semi-arid regions are sensitive to climate change, which is an important phenomenon in global climate change research. However, the driving mechanism, particularly for the longitudinal and latitudinal changes in vegetation greenness related to climate change, has been less studied and remains poorly understood in arid and semi-arid areas. In this study, we investigated changes in vegetation greenness and the vegetation greenness line (the mean growing season normalized difference vegetation index (NDVI) = 0.1 contour line) and its response to climate change based on AVHRR-GIMMS NDVI3g and the fifth and latest global climate reanalysis dataset from 1982 to 2015 in the arid and semi-arid transition zone of the Mongolian Plateau (ASTZMP). The results showed that the mean growing season NDVI increased from the central west to east, northeast, and southeast in ASTZMP. The vegetation greenness line migrated to the desert during 1982–1994, to the grassland during 1994–2005, and then to the desert during 2005–2015. Vegetation greenness was positively correlated with precipitation and negatively correlated with temperature. The latitudinal variation of the vegetation greenness line was mainly affected by the combination of precipitation and temperature, while the longitudinal variation was mainly affected by precipitation. In summary, precipitation was a key climatic factor driving rapid changes in vegetation greenness during the growing season of the transition zone. These results can provide meaningful information for research on vegetation coverage changes in arid and semi-arid regions.