Shifts in the dynamics of productivity signal ecosystem state transitions at the biome-scale

Disturbance amplifies sensitivity of dryland productivity to precipitation variability

Variability of the terrestrial global carbon sink is largely determined by the response of dryland productivity to annual precipitation. Despite extensive disturbance in drylands, how disturbance alters productivity-precipitation relationships remains poorly understood. Using remote-sensing to pair more than 5600 km of natural gas pipeline corridors with neighboring undisturbed areas in North American drylands, we found that disturbance reduced average annual production 6 to 29% and caused up to a fivefold increase in the sensitivity of net primary productivity (NPP) to interannual variation in precipitation. Disturbance impacts were larger and longer-lasting at locations with higher precipitation (>450 mm mean annual precipitation). Disturbance effects on NPP dynamics were mostly explained by shifts from woody to herbaceous vegetation. Severe disturbance will amplify effects of increasing precipitation variability on NPP in drylands.

Response of soil C-, N-, and P- acquisition enzymes to moisture pulses in desert grassland to shrubland state transition

Grassland-shrubland state transition causes profound effects on soil nutrients and microorganisms, yet little is known about how these soil characteristics are influenced by rainfall and litter changes during transition. Here, we examined water (high or low moisture pulse) and litter (grass or shrub) effects on these soil characteristics in grassland-shrubland mosaics consisting of desert grassland (DG), grassland edge (GE), shrubland edge (SE), and shrubland (SL) sites. The results showed that the transition of DG-GE-SE-SL significantly reduced soil moisture, total carbon (C), total nitrogen (N), total phosphorus (P), microbial biomass carbon, and microbial biomass nitrogen, revealing evident soil degradation during this transition. After applying water and litter, soil microbial respiration (SMR) and the activities of all enzymes were promoted to varying degrees among the sites. Specifically, SMR was promoted under a low moisture pulse but suppressed under a high moisture pulse along the transition from DG to SL. Two C-acquisition enzymes, cellobiohydrolase and β-1,4-glucosidase, became increasingly active from DG to SL. Another C-acquisition enzyme of β-1,4-xylosidase and an N-acquisition enzyme of leucine aminopeptidase showed the strongest preferences for low moisture pulses in SL. These results indicated that shrub encroachment retained certain microbes with an advanced ability to acquire to C and N from dry and infertile soil in SL. Although a P-acquisition enzyme of alkaline phosphatase showed a decreasing trend along the transition from DG to SL, similar like those C- and N- acquisition enzymes, it was not sensitive to varying moisture levels, suggesting that alkaline phosphatase was affected by other soil physicochemical properties rather than soil moisture. The joint analysis of soil extracellular enzymes and nutrients indicated that microbial biomass carbon played a more important role than other soil characteristics in determining soil extracellular enzyme activities along the transition from DG to SL. Future research on dissecting soil microbial communities is warranted to better understand the microbiological mechanisms behind these phenomena in the shrub encroachment process.

Using functional indicators to detect state changes in terrestrial ecosystems

Indicators to predict ecosystem state change are urgently needed to cope with the degradation of ecosystem services caused by global change. With the development of new technologies for measuring ecosystem function with fine spatiotemporal resolution over broad areas, we are in the era of 'big data'. However, it is unclear how large, emerging datasets can be used to anticipate ecosystem state change. We propose the construction of indicators based on functional variables (flows) and state variables (pools) to predict future ecosystem state changes. The indicators identified here may be useful signals for doing so. In addition, functional indicators have explicit ecological meanings that can identify the ecological mechanism that is causing state changes, and can thus be used to improve ecosystem models.

The global decline in the sensitivity of vegetation productivity to precipitation from 2001 to 2018

The sensitivity of vegetation productivity to precipitation (S_ppt ) is a key metric for understanding the variations in vegetation productivity under changing precipitation and predicting future changes in ecosystem functions. However, a comprehensive assessment of S_ppt over all the global land is lacking. Here, we investigated spatial patterns and temporal changes of S_ppt across the global land from 2001 to 2018 with multiple streams of satellite observations. We found consistent spatial patterns of S_ppt with different satellite products: S_ppt was highest in dry regions while low in humid regions. Grassland and shrubland showed the highest S_ppt , and evergreen needle-leaf forest and wetland showed the lowest. Temporally, S_ppt showed a generally declining trend over the past two decades (p < .05), yet with clear spatial heterogeneities. The decline in S_ppt was especially noticeable in North America and Europe, likely due to the increase in precipitation. In central Russia and Australia, however, S_ppt showed an increasing trend. Biome-wise, most ecosystem types exhibited significant decrease in S_ppt , while grassland, evergreen broadleaf forest, and mixed forest showed slight increases or non-significant changes in S_ppt . Our finding of the overall decline in S_ppt implies a potential stabilization mechanism for ecosystem productivity under climate change. However, the revealed S_ppt increase for some regions and ecosystem types, in particular global grasslands, suggests that grasslands might be increasingly vulnerable to climatic variability with continuing global climate change.

Stability and asynchrony of local communities but less so diversity increase regional stability of Inner Mongolian grassland

Extending knowledge on ecosystem stability to larger spatial scales is urgently needed because present local-scale studies are generally ineffective in guiding management and conservation decisions of an entire region with diverse plant communities. We investigated stability of plant productivity across spatial scales and hierarchical levels of organization and analyzed impacts of dominant species, species diversity, and climatic factors using a multisite survey of Inner Mongolian grassland. We found that regional stability across distant local communities was related to stability and asynchrony of local communities. Using only dominant instead of all-species dynamics explained regional stability almost equally well. The diversity of all or only dominant species had comparatively weak effects on stability and synchrony, whereas a lower mean and higher variation of precipitation destabilized regional and local communities by reducing population stability and synchronizing species dynamics. We demonstrate that, for semi-arid temperate grassland with highly uneven species abundances, the stability of regional communities is increased by stability and asynchrony of local communities and these are more affected by climate rather than species diversity. Reduced amounts and increased variation of precipitation in the future may compromise the sustainable provision of ecosystem services to human well-being in this region.

Effect of Nitrogen Application on the Sensitivity of Desert Shrub Community Productivity to Precipitation in Central Asia

Precipitation variability and nitrogen (N) deposition caused by anthropogenic activities could profoundly impact ecosystem productivity and carbon cycling. In desert ecosystems, vegetation is sensitive to changes in precipitation and N deposition. However, the impacts of large changes in precipitation, especially with a concurrent increase in N content, on plant community remain unclear. In this study, we carried out experiments to monitor the impacts of five precipitation levels and two N levels on the plant community function and composition from the Junggar desert in Central Asia during the period 2018-2019. Our results showed that: (1) Aboveground net primary production (ANPP) significantly increased with increasing precipitation, it followed a positive linear model under normal precipitation range, and nonlinear mode under extreme precipitation events; (2) N application led to an increase in ANPP, but did not significantly improve the sensitivity of ANPP to precipitation change; (3) Changes in N content and precipitation, and their impacts on ANPP were mainly driven by plant density. These results provide a theoretical basis for predict the future dynamics of terrestrial vegetation more accurately under climate change and increasing nitrogen deposition.

Herbaceous Dominant the Changes of Normalized Difference Vegetation Index in the Transition Zone Between Desert and Typical Steppe in Inner Mongolia, China

Asymmetric responses of aboveground net primary productivity (ANPP) to precipitation were identified as a signal to predict ecosystem state shifts at temperate grassland zones in Inner Mongolia, China. However, mechanism studies were still lacking. This study hypothesized that the enhanced growth and newly emerged herbaceous after increased precipitation resulted in the highest asymmetry at the transition zone between desert and typical steppe. We monitored the responses of the normalized difference vegetation index (NDVI) of different species to precipitation events using un-manned aerial vehicle technology to test this hypothesis. NDVI and species richness were measured twice at fixed points in July and August with a time interval of 15 days. Results showed that: (1) From July to August, NDVI in the transition zone increased significantly after precipitation (P < 0.05), but NDVI in both the desert and typical steppe showed a non-significant change (P > 0.05). (2) In the transition zone, NDVI increases from the shrub and herbaceous contributed to 37 and 63% increases of the site NDVI, respectively. (3) There was a significant difference in species richness between July and August in the transition zone (P < 0.05), mainly caused by the herbaceous (Chenopodiaceae, Composite, Convolvulaceae, Gramineae, Leguminosae, and Liliaceae), which either emerged from soil or tillers growth from surviving plants. This study demonstrated that herbaceous dominant the changes of NDVI in the transition zone, which provides a scientific basis for the mechanism studies of ANPP asymmetric response to precipitation and warrants long-term measurements.

Assessing vegetation stability to climate variability in Central Asia

The dramatic climate change has far-reaching impacts on vegetation in drylands such as Central Asia. Recent attempts to assess vegetation stability to short-term climate variability often account solely for vegetation sensitivity or resilience but ignore the composite effects of these two indicators. Meanwhile, our understanding of the vegetation stability at the seasonal scale remains insufficient. In this study, considering the cumulative effects of vegetation response to three key climate factors, we assessed the stability of vegetation in Central Asia using normalized difference vegetation index (NDVI) and the meteorological data from 1982 to 2014 by integrating vegetation sensitivity and resilience, and further identified the critical regions and seasons of vegetation that experience high risks of pending change. The results show that the sensitivity of vegetation has a strong correlation (R² = 0.83, p < 0.001) with the aridity index (AI), with the vegetation of drier areas having lower sensitivities to climate variability. At the temporal scale, the sensitivity of vegetation to climate variability varied among different seasons. The average vegetation sensitivity index (VSI) is 41.17, 33.32 and 28.63 in spring, summer and autumn, respectively. Spatially, a trade-off between vegetation sensitivity and resilience is found both for the growing season (R² = 0.67) and seasonal scale (R² = 0.71, 0.32 and 0.43 for spring, summer and autumn, respectively), regions with high vegetation sensitivity were always accompanied by strong resilience. Based on the relationship between vegetation sensitivity and resilience, we further identify the critical regions and periods of vegetation with high change risk in Central Asia. Results suggest that herbaceous plants in semi-arid areas present high instability, especially in summer. This study offers a comprehensive perspective to assess vegetation stability to climate variability and the results will facilitate the protection of ecosystems and the implementation of sustainable development goals in Central Asia.

Divergent responses of primary production to increasing precipitation variability in global drylands

Interannual variability in precipitation has increased globally as climate warming intensifies. The increased variability impacts both terrestrial plant production and carbon (C) sequestration. However, mechanisms driving these changes are largely unknown. Here, we examined mechanisms underlying the response of aboveground net primary production (ANPP) to interannual precipitation variability in global drylands with mean annual precipitation (MAP) <500 mm year^-1 , using a combined approach of data synthesis and process-based modeling. We found a hump-shaped response of ANPP to precipitation variability along the MAP gradient. The response was positive when MAP < ~300 mm year^-1 and negative when MAP was higher than this threshold, with a positive peak at 140 mm year^-1 . Transpiration and subsoil water content mirrored the response of ANPP to precipitation variability; evaporation responded negatively and water loss through runoff and drainage responded positively to precipitation variability. Mean annual temperature, soil type, and plant physiological traits all altered the magnitude but not the pattern of the response of ANPP to precipitation variability along the MAP gradient. By extrapolating to global drylands (<500 mm year^-1  MAP), we estimated that ANPP would increase by 15.2 ± 6.0 Tg C year^-1 in arid and hyper-arid lands and decrease by 2.1 ± 0.5 Tg C year^-1 in dry sub-humid lands under future changes in interannual precipitation variability. Thus, increases in precipitation variability will enhance primary production in many drylands in the future.

The Similarity between Species Composition of Vegetation and Soil Seed Bank of Grasslands in Inner Mongolia, China: Implications for the Asymmetric Response to Precipitation

The asymmetric response of productivity to precipitation was recently proposed as an early warning signal for the shifts in temperate grassland function in China. It was hypothesized that the asymmetry was influenced by the increased growth of the newly emerged seedlings from the soil seed bank. Therefore, the seed density in the soil seed bank and the similarity between species composition of the vegetation and the soil seed bank should be maximized where asymmetry was maximized. However, this knowledge was still limited and unconfirmed. In this study, the desert steppe, typical steppe and the transition zone between them (with the highest asymmetry) were selected for studying the similarity index in both 2018 (dry year) and 2019 (wet year). Plant species composition was monitored in situ using an unmanned aerial vehicle. Soil seed bank samples were collected, and the seed bank density and species composition were then examined and identified in the laboratory. Results showed that: (1) The variation in vegetation species richness between the two years was the highest (41%) in the transition zone (p < 0.05), while it was only 7% and 13% for the desert steppe and typical steppe, respectively. The presence of herbaceous species mainly caused the differences in variation among three grassland types. (2) Seed density was the highest in the transition zone (114 seeds/m² and 68 seeds/m² in the transient and persistent soil seed bank, respectively) (p < 0.05). Additionally, herbaceous species were the main components of the soil seed bank. (3) The similarity index was the highest in the transition zone (p < 0.05), with 38%/44% and 33%/44% for the transient/persistent soil seed bank in 2018 and 2019, respectively. Our study demonstrated that variation in vegetation species composition was very similar to the composition of the seeds accumulated in the soil seed bank. These results warrant further investigation for the mechanism of asymmetric response of productivity to precipitation.

Biotic vs abiotic controls on temporal sensitivity of primary production to precipitation across North American drylands

Dryland net primary productivity (NPP) is sensitive to temporal variation in precipitation (PPT), but the magnitude of this 'temporal sensitivity' varies spatially. Hypotheses for spatial variation in temporal sensitivity have often emphasized abiotic factors, such as moisture limitation, while overlooking biotic factors, such as vegetation structure. We tested these hypotheses using spatiotemporal models fit to remote-sensing data sets to assess how vegetation structure and climate influence temporal sensitivity across five dryland ecoregions of the western USA. Temporal sensitivity was higher in locations and ecoregions dominated by herbaceous vegetation. By contrast, much less spatial variation in temporal sensitivity was explained by mean annual PPT. In fact, ecoregion-specific models showed inconsistent associations of sensitivity and PPT; whereas sensitivity decreased with increasing mean annual PPT in most ecoregions, it increased with mean annual PPT in the most arid ecoregion, the hot deserts. The strong, positive influence of herbaceous vegetation on temporal sensitivity indicates that herbaceous-dominated drylands will be particularly sensitive to future increases in precipitation variability and that dramatic changes in cover type caused by invasions or shrub encroachment will lead to changes in dryland NPP dynamics, perhaps independent of changes in precipitation.

Vegetation resistance and resilience to a decade-long dry period in the temperate grasslands in China

The duration of climate anomalies has been increasing across the globe, leading to ecosystem function loss. Thus, we need to understand the responses of the ecosystem to long-term climate anomalies. It remains unclear how ecosystem resistance and resilience respond to long-term climate anomalies, for example, continuous dry years at a regional scale. Taking the opportunity of a 13-year dry period in the temperate grasslands in northern China, we quantified the resistance and resilience of the grassland in response to this periodic dry period. We found vegetation resistance to the dry period increased with mean annual precipitation (MAP), while resilience increased at first until at MAP of 250 mm and then decreased slightly. No trade-off between resistance and resilience was detected when MAP < 250 mm. Our results highlight that xeric ecosystems are most vulnerable to the long-term dry period. Given expected increases in drought severity and duration in the coming decades, our findings may be helpful to identify vulnerable ecosystems in the world for the purpose of adaptation.

Local climate and biodiversity affect the stability of China's grasslands in response to drought

The stability of ecosystems is of great significance to the supply of ecosystem services and human well-being. Frequently occurring drought events seriously threaten the stability of terrestrial ecosystems. In particular, in grasslands with low rainfall, ecosystems are more vulnerable to drought. To date, most studies have focused on forest ecosystems, while the difference in the stability of various types of grassland ecosystems under drought is less studied. Here, we selected China's grasslands as the study system and used the standardized precipitation evapotranspiration index (SPEI) to identify drought years and drought events (2001-2015) that occurred in China. Subsequently, we used the satellite-based enhanced vegetation index (EVI) to calculate the resistance (the ability to maintain the original EVI level in a drought year), resilience (the capacity of ecosystem functioning to recover to its normal state after a drought year), and recovery time (how long an ecosystem requires to recover to its predrought EVI) of different grassland types in China from 2001 to 2015. Finally, random forest analysis was used to identify the factors affecting the spatial patterns of the three indicators of stability. The results showed that the grassland ecosystem vulnerability to drought was significantly different among grassland types. The alpine steppe and alpine meadow ecosystems located on the Qinghai-Tibet Plateau have the strongest resistance, the weakest resilience, and the longest recovery time. The meadow steppe and typical steppe ecosystems located in Inner Mongolia have the weakest resistance, the strongest resilience, and the shortest recovery time. The stability of grassland ecosystems is mainly affected by the characteristics of drought events (drought severity and duration), local climate factors (precipitation and temperature), and biodiversity. These results provide a scientific basis for taking appropriate management measures to address the impacts of future drought events on various types of grassland ecosystems.

Estimating Ecological Responses to Climatic Variability on Reclaimed and Unmined Lands Using Enhanced Vegetation Index

Climatic impact on re-established ecosystems at reclaimed mined lands may have changed. However, little knowledge is available about the difference in vegetation–climate relationships between reclaimed and unmined lands. In this study, ecological responses to climatic variability on reclaimed and neighbouring unmined lands were estimated using remote-sensing data at the Pingshuo Mega coal mine, one of the largest coal mines with long-term reclamation history in China. Time-series MODIS enhanced vegetation index (EVI) data and meteorological data from 1997 to 2017 were collected. Results show significantly different vegetation–climate relationships between reclaimed and unmined lands. First, the accumulation periods of all climatic variables were much longer on reclaimed mining lands. Second, vegetation on reclaimed lands responded to variabilities in temperature, rainfall, air humidity, and wind speed, while undisturbed vegetation only responded to variabilities of temperature and air humidity. Third, climatic variability made a much higher contribution to EVI variation on reclaimed land (20.0–46.5%) than on unmined land (0.7–1.7%). These differences were primarily caused by limited ecosystem resilience, and changed site hydrology and microclimate on reclaimed land. Thus, this study demonstrates that the legacy effects of surface mining can critically change on-site vegetation–climate relationships, which impacts the structure, functions, and stability of reclaimed ecosystems. Vegetation–climate relationships of reclaimed ecosystems deserve further research, and remote-sensing vegetation data are an effective source for relevant studies.

Precipitation-productivity relationships and the duration of precipitation anomalies: An underappreciated dimension of climate change

In terrestrial ecosystems, climate change forecasts of increased frequencies and magnitudes of wet and dry precipitation anomalies are expected to shift precipitation-net primary productivity (PPT-NPP) relationships from linear to nonlinear. Less understood, however, is how future changes in the duration of PPT anomalies will alter PPT-NPP relationships. A review of the literature shows strong potential for the duration of wet and dry PPT anomalies to impact NPP and to interact with the magnitude of anomalies. Within semi-arid and mesic grassland ecosystems, PPT gradient experiments indicate that short-duration (1 year) PPT anomalies are often insufficient to drive nonlinear aboveground NPP responses. But long-term studies, within desert to forest ecosystems, demonstrate how multi-year PPT anomalies may result in increasing impacts on NPP through time, and thus alter PPT-NPP relationships. We present a conceptual model detailing how NPP responses to PPT anomalies may amplify with the duration of an event, how responses may vary in xeric vs. mesic ecosystems, and how these differences are most likely due to demographic mechanisms. Experiments that can unravel the independent and interactive impacts of the magnitude and duration of wet and dry PPT anomalies are needed, with multi-site long-term PPT gradient experiments particularly well-suited for this task.

Patterns and controls of vegetation productivity and precipitation-use efficiency across Eurasian grasslands

Elucidating aboveground net primary production (ANPP) and precipitation-use efficiency (PUE) spatial variations and mechanisms are essential for predicting how ecosystem functioning will respond to future climate change. However, a comprehensive recognition of spatial patterns of ANPP and PUE across continental scale is still lacking. Here, we integrated long-term GIMMS NDVI remote sensing, field survey ANPP and meteorological datasets to reveal the spatial variations and controls of ANPP and PUE across Eurasian grasslands for the first time. The results showed that the mean value of ANPP and PUE of Eurasian grasslands were 40.20 ± 0.40 g C m^-2 yr^-1 and 0.15 ± 0.01 g C m^-2 mm^-1, respectively. At the continental scale, the ANPP and PUE showed unimodal patterns along mean annual precipitation (MAP) and hydrothermal index (HT) gradients, while a piecewise linear pattern along mean annual temperature (MAT) gradients. The MAP exerted positive effect on the ANPP in desert and temperate grasslands, while negative effect on the ANPP in alpine grasslands. Conversely, the MAT negatively affected the ANPP in desert and temperate grasslands, while positively affected the ANPP in alpine grasslands. The results indicated that the hydrothermal conditions coupled with the transition of vegetation types and its different responses combinedly shaped the spatial patterns of ANPP and PUE in Eurasian grasslands. This study advanced our knowledge of the spatial variations of ANPP and PUE at continental scale, providing theoretical information for predicting productivity and water use changes of arid and semi-arid grasslands under climate change in the future.

Biotic stability mechanisms in Inner Mongolian grassland

Biotic mechanisms associated with species diversity are expected to stabilize communities in theoretical and experimental studies but may be difficult to detect in natural communities exposed to large environmental variation. We investigated biotic stability mechanisms in a multi-site study across Inner Mongolian grassland characterized by large spatial variations in species richness and composition and temporal fluctuations in precipitation. We used a new additive-partitioning method to separate species synchrony and population dynamics within communities into different species-abundance groups. Community stability was independent of species richness but was regulated by species synchrony and population dynamics, especially of abundant species. Precipitation fluctuations synchronized population dynamics within communities, reducing their stability. Our results indicate generality of biotic stability mechanisms in natural ecosystems and suggest that for accurate predictions of community stability in changing environments uneven species composition should be considered by partitioning stabilizing mechanisms into different species-abundance groups.

Scaling-up biodiversity-ecosystem functioning research

A rich body of knowledge links biodiversity to ecosystem functioning (BEF), but it is primarily focused on small scales. We review the current theory and identify six expectations for scale dependence in the BEF relationship: (1) a nonlinear change in the slope of the BEF relationship with spatial scale; (2) a scale‐dependent relationship between ecosystem stability and spatial extent; (3) coexistence within and among sites will result in a positive BEF relationship at larger scales; (4) temporal autocorrelation in environmental variability affects species turnover and thus the change in BEF slope with scale; (5) connectivity in metacommunities generates nonlinear BEF and stability relationships by affecting population  synchrony at local and regional scales; (6) spatial scaling in food web structure and diversity will generate scale dependence in ecosystem functioning. We suggest directions for synthesis that combine approaches in metaecosystem and metacommunity ecology and integrate cross‐scale feedbacks. Tests of this theory may combine remote sensing with a generation of networked experiments that assess effects at multiple scales. We also show how anthropogenic land cover change may alter the scaling of the BEF relationship. New research on the role of scale in BEF will guide policy linking the goals of managing biodiversity and ecosystems.

A systemic overreaction to years versus decades of warming in a subarctic grassland ecosystem

Temperature governs most biotic processes, yet we know little about how warming affects whole ecosystems. Here we examined the responses of 128 components of a subarctic grassland to 5-8 or >50 years of soil warming. Warming of >50 years drove the ecosystem to a new steady state possessing a distinct biotic composition and reduced species richness, biomass and soil organic matter. However, the warmed state was preceded by an overreaction to warming, which was related to organisms’ physiologies and was evident after 5-8 years. Ignoring this overreaction yielded errors of more than 100% for 83 variables when predicting their responses to a realistic warming scenario of 1 ºC over 50 years, although some, including soil carbon content, remained stable after 5-8 years. This study challenges long-term ecosystem predictions made from short-term observations, and provides a framework for characterising ecosystem responses to sustained climate change.

Median to Strong Rainfall Intensity Favors Carbon Sink in a Temperate Grassland Ecosystem in China

Over the past 50 years, rainfall events have made significant alterations to environments due to global warming. The grasslands in arid and semi-arid regions are extremely sensitive to variations in rainfall patterns, which are considered to significantly affect ecosystem functions. In this study, an experiment with varying rainfall sizes and frequencies (0 mm, 2 mm, 5 mm, 10 mm, 20 mm, and 40 mm) was conducted during growing seasons in typical grasslands, to study the effect of changes in rainfall regime on net ecosystem exchange (NEE). Our results indicated that NEE exhibited nonlinear responses to rainfall treatments, and reached its peak under 20 mm in middle growing season. Further, the component fluxes of both NEE (i.e., gross primary productivity (GPP)) and ecosystem respiration (ER) illustrated nonlinear responses to treatment gradient, with peak values at 20 mm and 5 mm, respectively. Based on five-year eddy flux measurements, further analyses demonstrated that GPP and ER increased with increasing soil moisture, and net ecosystem carbon uptake (-1*NEE) was significantly stimulated due to a more enhanced GPP than ER, when soil moisture was above 8%. Additionally, we found that the response of root biomass was different from that of carbon fluxes to changes in rainfall patterns. Overall, these findings highlight the importance of both changes in rainfall regimes in controlling ecosystem C exchange and investigation of the potential threshold for ecosystem function shifts, which are crucial to further understand C cycles in grasslands.

High ecosystem stability of evergreen broadleaf forests under severe droughts

Global increase in drought occurrences threatens the stability of terrestrial ecosystem functioning. Evergreen broadleaf forests (EBFs) keep leaves throughout the year, and therefore could experience higher drought risks than other biomes. However, the recent temporal variability of global vegetation productivity or land carbon sink is mainly driven by non-evergreen ecosystems, such as semiarid grasslands, croplands, and boreal forests. Thus, we hypothesize that EBFs have higher stability than other biomes under the increasingly extreme droughts. Here we use long-term Standardized Precipitation and Evaporation Index (SPEI) data and satellite-derived Enhanced Vegetation Index (EVI) products to quantify the temporal stability (ratio of mean annual EVI to its SD), resistance (ability to maintain its original levels during droughts), and resilience (rate of EVI recovering to pre-drought levels) at biome and global scales. We identified significantly increasing trends of annual drought severity (SPEI range: -0.08 to -1.80), area (areal fraction range: 2%-19%), and duration (month range: 7.9-9.1) in the EBF biome over 2000-2014. However, EBFs showed the highest resistance of EVI to droughts, but no significant differences in resilience of EVI to droughts were found among biomes (forests, grasslands, savannas, and shrublands). Global resistance and resilience of EVI to droughts were largely affected by temperature and solar radiation. These findings suggest that EBFs have higher stability than other biomes despite the greater drought exposure. Thus, the conservation of EBFs is critical for stabilizing global vegetation productivity and land carbon sink under more-intense climate extremes in the future.