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International audience; Droughts cause extreme anomalies in tropical forest growth, but the direction and magnitude of tropical forests in response to droughts are still widely debated. Here, we used four satellite-based canopy growth proxies (CGPs), including three optical and one passive microwave, and in situ fluxes observations from eddy covariance (EC) measurements for a retrospective investigation of the impacts of historical droughts on tropical forest growth from a statistical point of view. Results indicate two opposite directions in drought-related canopy dynamics across pantropical forests. The canopy of tropical forests with higher CGPs is more vulnerable to drought stress and recovers faster in the post-drought recovery period. In contrast, the canopy of tropical forests with lower CGPs increases during the drought period and declines in the subsequent recovery period, which is beyond general expectation. In situ measurements from eddy-covariance flux towers showed that forests with higher gross primary production and latent heat flux decreased photosynthesis and evapotranspiration during the drought period but increased photosynthesis and evapotranspiration faster during the post-drought recovery period, supporting the findings from satellite observations. Our statistical analysis against climatic factors predicts that higher-CGPs tress with probably taller and bigger canopies are more responsive to shortage of water availability caused by drought; while lower-CGPs tress with shorter and smaller canopies are more responsive to sunlight availability and tend to increase their canopy leaves and enhance photosynthesis in sunnier days during the drought period. Our results highlight the differences in tropical forests in responding to drought stress, which are worth incorporated in Earth system models for time-series evaluations.

Satellite-based methods have been widely used to identify the critical phenophases of terrestrial vegetation and detect responses of phenophases to climate change. However, few studies have been conducted to evaluate the performance of satellite-based methods for identifying the spatial and temporal changes of phenophases based on site-based phenophase observations. This study used the ground observations of leaf unfolding date (LUD) of woody and herbaceous plants over 31 sites in China to evaluate the accuracy of LUDs modeled by eight satellite-based methods using Moderate resolution imaging spectroradiometer (MODIS) vegetation index product. Our results showed an observed 2.62 and 2.45 days advance of LUD over the spatial scale with an increased mean annual temperature of 1 °C over the forest and grassland ecosystems respectively, but almost all eight methods underestimated the advance rates. In addition, the trends for the observed LUD varied from site to site, and the eight methods showed the poor performance in capturing the long-term trends, mostly because low temporal resolution of satellite data. Most methods tended to overestimate the trend of LUD over more than 40% forest sites. Our results highlight that there is a need for further improvements in the methods and satellite datasets used for identifying LUD.

Plant roots play a critical role in regulating the uptake of soil water and nutrients. Shifts in root growth and biomass distribution resulting from climate change can impact ecosystem water and carbon cycling. Such interactions between root growth and ecosystem functioning have not been integrated into current terrestrial ecosystem models. Here a three‐dimensional dynamic root model (DyRoot) was developed and implemented into the Integrated Biosphere Simulator (IBIS) ecosystem model for simulating root growth, architecture (i.e., fine and coarse roots), and distribution driven by soil water and nitrogen availabilities. Field root biomass observations were used for model calibration and validation. Results showed that DyRoot was able to simulate the root biomass distribution across five forest ecosystem types with good performance (R2 = 0.79, P < 0.01). The validations of root distribution in three forest chronosequences suggested that DyRoot captured the changes in rooting depth with the increase in stand age. The sensitivity of simulated root distribution to soil water availability was compared against root biomass observations from two precipitation reduction experiments. Results indicated that DyRoot reasonably represented the decrease of root biomass in topsoil layers in response to the deficits of soil moisture simulated by (IBIS). The DyRoot model algorithm in this study has great implications for representing an optimized root distribution in ecosystem models, which can improve model performance by simulating the feedbacks of root evolution in response to climate change. Furthermore, allowing explicit root architecture in the DyRoot model also sheds light on depicting the responses of root traits to environmental changes.

China’s urban agglomerations contribute 64 percent to China’s energy-related CO2 emissions and thus play a vital role in determining the future of climate change. There is little information availa...

The CO2 efflux from soil (soil respiration (SR)) is one of the largest fluxes in the global carbon (C) cycle and its response to climate change could strongly influence future atmospheric CO2 concentrations. Still, a large divergence of global SR estimates and its autotrophic (AR) and heterotrophic (HR) components exists among process based terrestrial ecosystem models. Therefore, alternatively derived global benchmark values are warranted for constraining the various ecosystem model output. In this study, we developed models based on the global soil respiration database (version 5.0), using the random forest (RF) method to generate the global benchmark distribution of total SR and its components. Benchmark values were then compared with the output of ten different global terrestrial ecosystem models. Our observationally derived global mean annual benchmark rates were 85.5 ± 40.4 (SD) Pg C yr−1 for SR, 50.3 ± 25.0 (SD) Pg C yr−1 for HR and 35.2 Pg C yr−1 for AR during 1982–2012, respectively. Evaluating against the observations, the RF models showed better performance in both of SR and HR simulations than all investigated terrestrial ecosystem models. Large divergences in simulating SR and its components were observed among the terrestrial ecosystem models. The estimated global SR and HR by the ecosystem models ranged from 61.4 to 91.7 Pg C yr−1 and 39.8 to 61.7 Pg C yr−1, respectively. The most discrepancy lays in the estimation of AR, the difference (12.0–42.3 Pg C yr−1) of estimates among the ecosystem models was up to 3.5 times. The contribution of AR to SR highly varied among the ecosystem models ranging from 18% to 48%, which differed with the estimate by RF (41%). This study generated global SR and its components (HR and AR) fluxes, which are useful benchmarks to constrain the performance of terrestrial ecosystem models.

International audience; Our limited understanding of the impacts of drought on tropical forests significantly impedes our ability in accurately predicting the impacts of climate change on this biome. Here, we investigated the impact of drought on the dynamics of forest canopies with different heights using time-series records of remotely sensed Ku-band vegetation optical depth (Ku-VOD), a proxy of top-canopy foliar mass and water content, and separated the signal of Ku-VOD changes into drought-induced reductions and subsequent non-drought gains. Both drought-induced reductions and non-drought increases in Ku-VOD varied significantly with canopy height. Taller tropical forests experienced greater relative Ku-VOD reductions during drought and larger non-drought increases than shorter forests, but the net effect of drought was more negative in the taller forests. Meta-analysis of in situ hydraulic traits supports the hypothesis that taller tropical forests are more vulnerable to drought stress due to smaller xylem-transport safety margins. Additionally, Ku-VOD of taller forests showed larger reductions due to increased atmospheric dryness, as assessed by vapor pressure deficit, and showed larger gains in response to enhanced water supply than shorter forests. Including the height-dependent variation of hydraulic transport in ecosystem models will improve the simulated response of tropical forests to drought.

There has been much debate on the temporal change trend and existence of a turning point in spring green-up date (GUD) of plants on the Qinghai–Tibetan Plateau (QTP). Most previous studies on the QTP used remote sensing data, which have large uncertainties. In this study, using a large amount of long-term ground observation data at 27 phenological stations across the QTP (1694 GUD records), we showed that on the whole, QTP herbaceous plant GUD insignificantly advanced during 1982–2017. Although the direction of the GUD trend did not change from 1982 to 2017, the magnitude of the advancing trend greatly weakened after 1999. According to our estimated results from 28 paired GUD time series, the overall GUD trend shifted from −2.70 days/decade during 1982–1999 to −0.56 days/decade during 2000–2017. This finding contrasts with the conclusions of previous satellite-based studies, which either reported a continuous significant advancement of GUD or a turning point in the mid-to-late 1990s. Through partial correlation analysis and partial least squares regression, we found that winter and spring air temperatures were the primary climatic factors that influenced the temporal change in GUD, and both had negative effects on GUD. The decreased GUD trend was mainly attributable to the warming slowdown in spring. On average, the spring warming rate decreased by 52.43% after 1999, whereas the winter warming rate displayed no obvious change. This study also found that the GUD of forbs showed stronger sensitivity to air temperature change than that of sedges and grasses. This indicates that forbs are more competitive in adaptation to climate warming, which might shift plant community structure and affect ecosystem service function. Moreover, the declined advancement in GUD implies that the spring phenologically driven increase in carbon uptake may have also slowed in the past two decades.

In recent decades, rapid urbanization and intensified global climate change have resulted in a significant difference of environment and resources distribution on space, which would cause trouble for accurate assessment of regional ecological sustainable development, especially in the large urban agglomerations. The parameters used in previous assessment methods have normally ignored spatial heterogeneity, leading to deviations in the evaluation accuracies against the context above. By incorporating remote sensing technology, this study proposed an improved emergy ecological footprint (EEF) method and a novel ecological sustainability index to comprehensively analyze the variability of ecological security states (ESS) from 1994 to 2018 in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and to predict its sustainable growth potential based on a combined factorial decomposition and scenario analysis. Results showed that the pixel-based emergy analysis revealed significant heterogeneity over time and space under the impact of climate change and intense land use activities during the study period. The emergy carrying capacity per capita (ecc) and the emergy ecological footprint per capita (eef) also showed a significant difference between the nine cities in the GBA. In addition, the traditional EEF method, which does not consider the spatiotemporal variation, has indeed overestimated the GBA's ecc by 15% compared with our results. The ESS of the GBA gradually worsened from slight insecurity in the 1990s to moderate insecurity in 2018. If the current trends in socio-economic activities and climate change continue according to the RCP8.5 scenario in the IPCC, the ESS of the GBA will reach the extreme insecurity state in 2050. However, our scenarios show that industrial structure adjustment, energy structure optimization, and especially biological resource conservation can reduce the EFI by approximately 6.52%, 23.4%, and 30.6%, respectively. Consequently, effective implementation of the above measures can limit the increase both in emergy ecological deficit and emergy ecological footprint intensity (EFI) and, together, contribute to a higher security status in the GBA in 2050.

To limit global temperature rise, scientists have proposed significant potentials for climate change mitigation from protecting and managing natural systems. However, depending on the time taken for technology deployment and natural carbon gain, actual mitigation can be dramatically delayed, and total mitigation by 2030 or 2050 can be more than halved compared to the estimated potential. Delayed or lack of action on implementation would push back the timeline to reduce greenhouse gas emissions, largely undermining the Paris goals. Launching actions now and learning from past experience can help deliver climate mitigation and sustainable development goals.

Soil organic carbon (SOC) plays critical roles in stabilizing atmospheric CO2 concentration, but the mechanistic controls on the amount and distribution of SOC on global scales are not well understood. In turn, this has hampered the ability to model global C budgets and to find measures to mitigate climate change. Here, based on the data from a large field survey campaign with 2600 plots across China's forest ecosystems and a global collection of published data from forested land, we find that a low litter carbon-to-nitrogen ratio (C/N) and high wetness index (P/PET, precipitation-to-potential-evapotranspiration ratio) are the two factors that promote SOC accumulation, with only minor contributions of litter quantity and soil texture. The field survey data demonstrated that high plant diversity decreased litter C/N and thus indirectly promoted SOC accumulation by increasing the litter quality. We conclude that any changes in plant-community composition, plant-species richness and environmental factors that can reduce the litter C/N ratio, or climatic changes that increase wetness index, may promote SOC accumulation. The study provides a guideline for modeling the carbon cycle of various ecosystem scales and formulates the principle for land-based actions for mitigating the rising atmospheric CO2 concentration.

The well-documented energy balance dynamics within forest ecosystems are poorly implemented in studies of the biophysical effects of forests. This results in limitations to the accurate quantification of forest cooling/warming on local air temperature. Taking into consideration the forest air space, this study proposes a three-layered (canopy, forest air space and soil [CAS]) land surface energy balance model to simulate air temperature within forest spaces (Taf) and subsequently to evaluate its biophysical effects on forest cooling/warming, i.e., the air temperature gradient (∆Ta) between the Taf and air temperature of open spaces (Tao) (∆Ta = Taf − Tao). We test the model using field data for 23 sites across 10 cities worldwide; the model shows satisfactory performance with the test data. High-latitude forests show greater seasonal dynamics of ∆Ta, generating considerable cooling of local air temperatures in warm seasons but minimal cooling or even warming effects during cool seasons, while low-latitude tropical forests always exert cooling effects with less interannual variability. The interannual dynamics of ∆Ta are significantly related to the seasonality of solar geometry and canopy leaf phenology. The differences between forest canopy temperature (Tc) and Tao, which are the two most important terms attributed by the CAS model in impacting Taf, explain a large part of forest cooling and warming (May–July: R2 = 0.35; November–January: R2 = 0.51). The novel CAS model provides a feasible way to represent the energy balance within forest ecosystems and to assess its impacts on local air temperatures globally. Keywords: Forest cooling/warming, Forest biophysical effects, Radiative transfer equation, Land-atmosphere model, Local environmental health, Climate warming mitigation

Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings provide insights for decision makers to evaluate drought risk and vegetation-related develop drought mitigation strategies over China in a warming world. The proposed methodology also has a great potential to be applied for vegetation-related drought risk assessment in other regions worldwide.

Understanding the historical trends and driving mechanism of China's soil moisture change is an important step in combating climate change. Using the time series satellite-derived Essential Climate Variable Soil Moisture (ECV_SM) product, we detected a significant decrease trend in land surface soil moisture in eastern China over a 32-year period (1979–2010). Theoretical sensitivity analysis suggested that soil moisture is regulated collectively by precipitation (P), potential evapotranspiration (PET), land surface conditions such as land cover/use changes, landscape features, irrigation and urban expansion etc. (m), and the water balance between input and output water supplies (O) (the input water supplies minus the output). The change in spatial pattern and temporal trend of C is highly consistent with the corresponding change in soil moisture. The magnitude of soil moisture variation is also well correlated with that of P/PET (R2=0.43; p

We appreciate the comments by Berghuijs and Woods1 on our study2 that investigates how land cover and climate affect watershed water yield at the global scale. We used published data worldwide to examine the validity of Fuh's equation and address the interactions of water yield coefficient (R/P) with wetness index (P/PET) and watershed characteristics (m). Berghuijs and Woods1 argue that we implicitly assumed that there is symmetry between spatial and temporal partitioning of precipitation into streamflow and evaporation. We, however, disagree. Fuh and other Budyko frameworks are based on energy and climate under a steady state3,4. If a system is at steady state (for example, change in water storage is zero), the equations apply. It can be applied to different watersheds (spatial scale) and a single watershed over different intervals (temporal scales; again each interval must meet the steady-state condition). More importantly, Fuh's is a theoretical framework. Thus, when it applies to a real-life data set, asymmetry from real-life data is likely expected. The difference identified (27.9%) by Berghuijs and Woods1 can be attributed to various sources, including the quality of the data set, non-stationarity of time-series data (as caused by climate change) and the inconsistent application of methods (in Berghuijs and Woods1, the first method is based on the theoretical framework while the second is a simplified linear regression without any physical basis). Application of an empirical linear equation by Berghuijs and Woods1 is problematic, as evidenced by impossible negative α values in their Fig. 1 (ref. 1). In addition, α value in Berghuijs and Woods1 (equivalent to ∂R/P/∂P/PET) is a regressed slope of their equation (2) based on long-term observations in a watershed. As a result, a watershed has only one α value. How does it reflect temporal change? In fact, no temporal sensitivity is shown by Berghuijs and Woods1. Thus, we do not believe that they provide sufficiently robust evidence to support their claims regarding space-time asymmetry. Berghuijs and Woods1 state that m should include the effects of climate intra-annual variability (for example, precipitation seasonality). As described above, Fuh's equation describes the climate and energy balances in a steady watershed. Thus, climate intra-annual variability should not be involved. Because climate is already represented in Fuh's equation, m is considered by many authors5 as a parameter for representing watershed properties or characteristics. However, Berghuijs and Woods1 do raise an important question regarding possible interactions between climate and m, which we feel is an open question for future research. The two critical values shown in Fig. 1b and Fig. 1c of Zhou et al.2 define the boundaries of the sensitivities of R/P to both P/PET and m values. They classify the possible combinations of variables P/PET (0, ∞) and m (1, ∞) into four different ranges in which the sensitivities of R/P to both P/PET and m are varied (Zhou et al.2, Table 1). Berghuijs and Woods1 state that comparisons of those two sensitivities are not meaningful for assessing water yield changes (ΔR/P) unless they are combined with typical changes of climate (ΔP/PET) and watershed parameter (Δm). We agree that comparisons can be more meaningful if those two sensitivities are integrated with those typical changes for assessing water yield changes. However, our paper2 attempts to validate whether Fuh's equation is an appropriate framework for assessing the effects of climate and land cover on watershed hydrology using the global published data. Our evaluation is thus within a more theoretical context. With our theoretical analysis, we were able to quantify the sensitivities and relative importance of climate (P/PET) and m to water yield changes, which we feel is meaningful and important. We do, however, agree that more testing on critical values and their sensitivities should be done with field data in the future. Berghuijs and Woods1 further questions the extent to which Zhou et al.2 provided an explanation for cases where water yields from forests can potentially exceed those from grasslands. Zhou et al.2 show that the sensitivity of R/P to m is very low in the situations of P/PET>>1 and m>>2 (Zhou et al.2, Fig. 1b,c), and, under those conditions, any land cover change (for example, afforestation or deforestation) may play a limited role in influencing R/P. Therefore, if afforestation cools local land surface temperature6,7 and consequently increases P/PET, then afforestation can potentially increase water yield. This conclusion is based on Fuh's theoretical equation, not on speculation. In summary, we feel that the claim of ‘space-time asymmetry' by Berghuijs and Woods1 lacks sufficient evidence to undermine the conclusions of Zhou et al.2, and that some claims may be the result of a mis-interpretation of our original study.

Research results on the effects of land cover change on water resources vary greatly and the topic remains controversial. Here we use published data worldwide to examine the validity of Fuh's equation, which relates annual water yield (R) to a wetness index (precipitation/potential evapotranspiration; P/PET) and watershed characteristics (m). We identify two critical values at P/PET=1 and m=2. m plays a more important role than P/PET when m 2. When P/PET 1, suggesting that any land cover changes in non-humid regions (P/PET

Investigating the spatiotemporal changes of regional surface soil moisture in responses to climate and land cover changes is vital for understanding the underlying mechanisms of hydrological processes. While previous studies mainly attributed the causes of soil moisture changes to climatic factors, few took land cover into consideration. We analyzed the seasonal-differentiated effects of climate and land cover changes on surface soil moisture of China's 80 drainage basins using the Essential Climate Variable Soil Moisture (ECV_SM) product spanning the 1979-2010 period. The low-low spatial clusters of annual (Jan ~ Dec), warm-season (Apr ~ Sept) and cool-season (Oct ~ Dec, Jan ~ Mar) surface soil moisture have spread from northwest China to northeast and even central China during past three decades. In cool seasons, significant decreasing trends of surface soil moisture in most drainage basins of northwest, northeast, central and south China were detected. But in warm seasons, the surface soil moisture in central and south China showed significant increasing trends. Precipitation, potential evapotranspiration and the ratio of the two are three driving forces for warm-season surface soil moisture changes in northeast and northwest China. These climatic factors are main contributors to the declining trends of cool-season surface soil moisture in central and south China. Land cover changes showed to be the major factor driving the significant decreasing trends of cool-season surface soil moisture in northwest, central and south China. Due to vegetation's self-shading effect, the large-scale reforestation and vegetation growth are believed as main causes of the increasing trends of warm-season surface soil moisture in central and south China.