A remote sensing method for mapping alpine grasslines based on graph-cut.

Climate change has induced substantial shifts in vegetation boundaries such as alpine treelines and shrublines, with widespread ecological and climatic influences. However, spatial and temporal changes in the upper elevational limit of alpine grasslands ("alpine grasslines") are still poorly understood due to lack of field observations and remote sensing estimates. In this study, taking the Tibetan Plateau as an example, we propose a novel method for automatically identifying alpine grasslines from multi-source remote sensing data and determining their positions at 30-m spatial resolution. We first identified 2895 mountains potentially having alpine grasslines. On each mountain, we identified a narrow area around the upper elevational limit of alpine grasslands where the alpine grassline was potentially located. Then, we used linear discriminant analysis to adaptively generate from Landsat reflectance features a synthetic feature that maximized the difference between vegetated and unvegetated pixels in each of these areas. After that, we designed a graph-cut algorithm to integrate the advantages of the Otsu and Canny approaches, which was used to determine the precise position of the alpine grassline from the synthetic feature image. Validation against alpine grasslines visually interpreted from a large number of high-spatial-resolution images showed a high level of accuracy (R2 , .99 and .98; mean absolute error, 22.6 and 36.2 m, vs. drone and PlanetScope images, respectively). Across the Tibetan Plateau, the alpine grassline elevation ranged from 4038 to 5380 m (5th-95th percentile), lower in the northeast and southeast and higher in the southwest. This study provides a method for remotely sensing alpine grasslines for the first-time at large scale and lays a foundation for investigating their responses to climate change.

Critical role of water conditions in the responses of autumn phenology of marsh wetlands to climate change on the Tibetan Plateau.

The Tibetan Plateau, housing 20% of China's wetlands, plays a vital role in the regional carbon cycle. Examining the phenological dynamics of wetland vegetation in response to climate change is crucial for understanding its impact on the ecosystem. Despite this importance, the specific effects of climate change on wetland vegetation phenology in this region remain uncertain. In this study, we investigated the influence of climate change on the end of the growing season (EOS) of marsh wetland vegetation across the Tibetan Plateau, utilizing satellite-derived Normalized Difference Vegetation Index (NDVI) data and observational climate data. We observed that the regionally averaged EOS of marsh vegetation across the Tibetan Plateau was significantly (p < .05) delayed by 4.10 days/decade from 2001 to 2020. Warming preseason temperatures were found to be the primary driver behind the delay in the EOS of marsh vegetation, whereas preseason cumulative precipitation showed no significant impact. Interestingly, the responses of EOS to climate change varied spatially across the plateau, indicating a regulatory role for hydrological conditions in marsh phenology. In the humid and cold central regions, preseason daytime warming significantly delayed the EOS. However, areas with lower soil moisture exhibited a weaker or reversed delay effect, suggesting complex interplays between temperature, soil moisture, and EOS. Notably, in the arid southwestern regions of the plateau, increased preseason rainfall directly delayed the EOS, while higher daytime temperatures advanced it. Our results emphasize the critical role of hydrological conditions, specifically soil moisture, in shaping marsh EOS responses in different regions. Our findings underscore the need to incorporate hydrological factors into terrestrial ecosystem models, particularly in cold and dry regions, for accurate predictions of marsh vegetation phenological responses to climate change. This understanding is vital for informed conservation and management strategies in the face of current and future climate challenges.

Plant phenology and global climate change: Current progresses and challenges.

Plant phenology, the annually recurring sequence of plant developmental stages, is important for plant functioning and ecosystem services and their biophysical and biogeochemical feedbacks to the climate system. Plant phenology depends on temperature, and the current rapid climate change has revived interest in understanding and modeling the responses of plant phenology to the warming trend and the consequences thereof for ecosystems. Here, we review recent progresses in plant phenology and its interactions with climate change. Focusing on the start (leaf unfolding) and end (leaf coloring) of plant growing seasons, we show that the recent rapid expansion in ground- and remote sensing- based phenology data acquisition has been highly beneficial and has supported major advances in plant phenology research. Studies using multiple data sources and methods generally agree on the trends of advanced leaf unfolding and delayed leaf coloring due to climate change, yet these trends appear to have decelerated or even reversed in recent years. Our understanding of the mechanisms underlying the plant phenology responses to climate warming is still limited. The interactions between multiple drivers complicate the modeling and prediction of plant phenology changes. Furthermore, changes in plant phenology have important implications for ecosystem carbon cycles and ecosystem feedbacks to climate, yet the quantification of such impacts remains challenging. We suggest that future studies should primarily focus on using new observation tools to improve the understanding of tropical plant phenology, on improving process-based phenology modeling, and on the scaling of phenology from species to landscape-level.

Mismatch in elevational shifts between satellite observed vegetation greenness and temperature isolines during 2000-2016 on the Tibetan Plateau.

Climate warming on the Tibetan Plateau tends to induce an uphill shift of temperature isolines. Observations and process-based models have both shown that climate warming has resulted in an increase in vegetation greenness on the Tibetan Plateau in recent decades. However, it is unclear whether the uphill shift of temperature isolines has caused greenness isolines to shift upward and whether the two shifts match each other. Our analysis of satellite observed vegetation greenness during the growing season (May-Sep) and gridded climate data for 2000-2016 documented a substantial mismatch between the elevational shifts of greenness and temperature isolines. This mismatch is probably associated with a lagging response of greenness to temperature change and with the elevational gradient of greenness. The lagging response of greenness may be associated with water limitation, resources availability, and acclimation. This lag may weaken carbon sequestration by Tibetan ecosystems, given that greenness is closely related to primary carbon uptake and ecosystem respiration increases exponentially with temperature. We also found that differences in terrain slope angle accounted for large spatial variations in the elevational gradient of greenness and thus the velocity of elevational shifts of greenness isolines and the sensitivity of elevational shifts of greenness isolines to temperature, highlighting the role of terrain effects on the elevational shifts of greenness isolines. The mismatches and the terrain effect found in this study suggest that there is potentially large micro-topographical difference in response and acclimation/adaptation of greenness to temperature changes in plants. More widespread in situ measurements and fine-resolution remote sensing observations and fine-gridded climate data are required to attribute the mismatch to specific environmental drivers and ecological processes such as vertical changes in community structure, plant physiology, and distribution of species.

Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years.

The uncertainties of China's gross primary productivity (GPP) estimates by global data-oriented products and ecosystem models justify a development of high-resolution data-oriented GPP dataset over China. We applied a machine learning algorithm developing a new GPP dataset for China with 0.1° spatial resolution and monthly temporal frequency based on eddy flux measurements from 40 sites in China and surrounding countries, most of which have not been explored in previous global GPP datasets. According to our estimates, mean annual GPP over China is 6.62 ± 0.23 PgC/year during 1982-2015 with a clear gradient from southeast to northwest. The trend of GPP estimated by this study (0.020 ± 0.002 PgC/year2 from 1982 to 2015) is almost two times of that estimated by the previous global dataset. The GPP increment is widely spread with 60% area showing significant increasing trend (p < .05), except for Inner Mongolia. Most ecosystem models overestimated the GPP magnitudes but underestimated the temporal trend of GPP. The monsoon affected eastern China, in particular the area surrounding Qinling Mountain, seems having larger contribution to interannual variability (IAV) of China's GPP than the semiarid northwestern China and Tibetan Plateau. At country scale, temperature is the dominant climatic driver for IAV of GPP. The area where IAV of GPP dominated by temperature is about 42%, while precipitation and solar radiation dominate 31% and 27% respectively over semiarid area and cold-wet area. Such spatial pattern was generally consistent with global GPP dataset, except over the Tibetan Plateau and northeastern forests, but not captured by most ecosystem models, highlighting future research needs to improve the modeling of ecosystem response to climate variations.

Evaporative cooling over the Tibetan Plateau induced by vegetation growth.

In the Arctic, climate warming enhances vegetation activity by extending the length of the growing season and intensifying maximum rates of productivity. In turn, increased vegetation productivity reduces albedo, which causes a positive feedback on temperature. Over the Tibetan Plateau (TP), regional vegetation greening has also been observed in response to recent warming. Here, we show that in contrast to arctic regions, increased growing season vegetation activity over the TP may have attenuated surface warming. This negative feedback on growing season vegetation temperature is attributed to enhanced evapotranspiration (ET). The extra energy available at the surface, which results from lower albedo, is efficiently dissipated by evaporative cooling. The net effect is a decrease in daily maximum temperature and the diurnal temperature range, which is supported by statistical analyses of in situ observations and by decomposition of the surface energy budget. A daytime cooling effect from increased vegetation activity is also modeled from a set of regional weather research and forecasting (WRF) mesoscale model simulations, but with a magnitude smaller than observed, likely because the WRF model simulates a weaker ET enhancement. Our results suggest that actions to restore native grasslands in degraded areas, roughly one-third of the plateau, will both facilitate a sustainable ecological development in this region and have local climate cobenefits. More accurate simulations of the biophysical coupling between the land surface and the atmosphere are needed to help understand regional climate change over the TP, and possible larger scale feedbacks between climate in the TP and the Asian monsoon system.

Varying responses of vegetation activity to climate changes on the Tibetan Plateau grassland.

Vegetation activity on the Tibetan Plateau grassland has been substantially enhanced as a result of climate change, as revealed by satellite observations of vegetation greenness (i.e., the normalized difference vegetation index, NDVI). However, little is known about the temporal variations in the relationships between NDVI and temperature and precipitation, and understanding this is essential for predicting how future climate change would affect vegetation activity. Using NDVI data and meteorological records from 1982 to 2011, we found that the inter-annual partial correlation coefficient between growing season (May-September) NDVI and temperature (RNDVI-T) in a 15-year moving window for alpine meadow showed little change, likely caused by the increasing RNDVI-T in spring (May-June) and autumn (September) and decreasing RNDVI-T in summer (July-August). Growing season RNDVI-T for alpine steppe increased slightly, mainly due to increasing RNDVI-T in spring and autumn. The partial correlation coefficient between growing season NDVI and precipitation (RNDVI-P) for alpine meadow increased slightly, mainly in spring and summer, and RNDVI-P for alpine steppe increased, mainly in spring. Moreover, RNDVI-T for the growing season was significantly higher in those 15-year windows with more precipitation for alpine steppe. RNDVI-P for the growing season was significantly higher in those 15-year windows with higher temperature, and this tendency was stronger for alpine meadow than for alpine steppe. These results indicate that the impact of warming on vegetation activity of Tibetan Plateau grassland is more positive (or less negative) during periods with more precipitation and that the impact of increasing precipitation is more positive (or less negative) during periods with higher temperature. Such positive effects of the interactions between temperature and precipitation indicate that the projected warmer and wetter future climate will enhance vegetation activity of Tibetan Plateau grassland.

Strong impacts of daily minimum temperature on the green-up date and summer greenness of the Tibetan Plateau.

Understanding vegetation responses to climate change on the Tibetan Plateau (TP) helps in elucidating the land-atmosphere energy exchange, which affects air mass movement over and around the TP. Although the TP is one of the world's most sensitive regions in terms of climatic warming, little is known about how the vegetation responds. Here, we focus on how spring phenology and summertime greenness respond to the asymmetric warming, that is, stronger warming during nighttime than during daytime. Using both in situ and satellite observations, we found that vegetation green-up date showed a stronger negative partial correlation with daily minimum temperature (Tmin ) than with maximum temperature (Tmax ) before the growing season ('preseason' henceforth). Summer vegetation greenness was strongly positively correlated with summer Tmin , but negatively with Tmax . A 1-K increase in preseason Tmin advanced green-up date by 4 days (P < 0.05) and in summer enhanced greenness by 3.6% relative to the mean greenness during 2000-2004 (P < 0.01). In contrast, increases in preseason Tmax did not advance green-up date (P > 0.10) and higher summer Tmax even reduced greenness by 2.6% K(-1) (P < 0.05). The stimulating effects of increasing Tmin were likely caused by reduced low temperature constraints, and the apparent negative effects of higher Tmax on greenness were probably due to the accompanying decline in water availability. The dominant enhancing effect of nighttime warming indicates that climatic warming will probably have stronger impact on TP ecosystems than on apparently similar Arctic ecosystems where vegetation is controlled mainly by Tmax . Our results are crucial for future improvements of dynamic vegetation models embedded in the Earth System Models which are being used to describe the behavior of the Asian monsoon. The results are significant because the state of the vegetation on the TP plays an important role in steering the monsoon.

Changes in autumn vegetation dormancy onset date and the climate controls across temperate ecosystems in China from 1982 to 2010.

Vegetation phenology is a sensitive indicator of the dynamic response of terrestrial ecosystems to climate change. In this study, the spatiotemporal pattern of vegetation dormancy onset date (DOD) and its climate controls over temperate China were examined by analysing the satellite-derived normalized difference vegetation index and concurrent climate data from 1982 to 2010. Results show that preseason (May through October) air temperature is the primary climatic control of the DOD spatial pattern across temperate China, whereas preseason cumulative precipitation is dominantly associated with the DOD spatial pattern in relatively cold regions. Temporally, the average DOD over China's temperate ecosystems has delayed by 0.13 days per year during the past three decades. However, the delay trends are not continuous throughout the 29-year period. The DOD experienced the largest delay during the 1980s, but the delay trend slowed down or even reversed during the 1990s and 2000s. Our results also show that interannual variations in DOD are most significantly related with preseason mean temperature in most ecosystems, except for the desert ecosystem for which the variations in DOD are mainly regulated by preseason cumulative precipitation. Moreover, temperature also determines the spatial pattern of temperature sensitivity of DOD, which became significantly lower as temperature increased. On the other hand, the temperature sensitivity of DOD increases with increasing precipitation, especially in relatively dry areas (e.g. temperate grassland). This finding stresses the importance of hydrological control on the response of autumn phenology to changes in temperature, which must be accounted in current temperature-driven phenological models.

Precipitation impacts on vegetation spring phenology on the Tibetan Plateau.

The ongoing changes in vegetation spring phenology in temperate/cold regions are widely attributed to temperature. However, in arid/semiarid ecosystems, the correlation between spring temperature and phenology is much less clear. We test the hypothesis that precipitation plays an important role in the temperature dependency of phenology in arid/semiarid regions. We therefore investigated the influence of preseason precipitation on satellite-derived estimates of starting date of vegetation growing season (SOS) across the Tibetan Plateau (TP). We observed two clear patterns linking precipitation to SOS. First, SOS is more sensitive to interannual variations in preseason precipitation in more arid than in wetter areas. Spatially, an increase in long-term averaged preseason precipitation of 10 mm corresponds to a decrease in the precipitation sensitivity of SOS by about 0.01 day mm(-1) . Second, SOS is more sensitive to variations in preseason temperature in wetter than in dryer areas of the plateau. A spatial increase in precipitation of 10 mm corresponds to an increase in temperature sensitivity of SOS of 0.25 day °C(-1) (0.25 day SOS advance per 1 °C temperature increase). Those two patterns indicate both direct and indirect impacts of precipitation on SOS on TP. This study suggests a balance between maximizing benefit from the limiting climatic resource and minimizing the risk imposed by other factors. In wetter areas, the lower risk of drought allows greater temperature sensitivity of SOS to maximize the thermal benefit, which is further supported by the weaker interannual partial correlation between growing degree days and preseason precipitation. In more arid areas, maximizing the benefit of water requires greater sensitivity of SOS to precipitation, with reduced sensitivity to temperature. This study highlights the impacts of precipitation on SOS in a large cold and arid/semiarid region and suggests that influences of water should be included in SOS module of terrestrial ecosystem models for drylands.

Long-term species-level observations indicate the critical role of soil moisture in regulating China's grassland productivity relative to phenological and climatic factors.

As a sensitive indicator of climate change and a key variable in ecosystem surface-atmosphere interaction, vegetation phenology, and the growing season length, as well as climatic factors (i.e., temperature, precipitation, and sunshine duration) are widely recognized as key factors influencing vegetation productivity. Recent studies have highlighted the importance of soil moisture in regulating grassland productivity. However, the relative importance of phenology, climatic factors, and soil moisture to plant species-level productivity across China's grasslands remains poorly understood. Here, we use nearly four decades (1981 to 2018) of in situ species-level observations from 17 stations distributed across grasslands in China to examine the key mechanisms that control grassland productivity. The results reveal that soil moisture is the strongest determinant of the interannual variability in grassland productivity. In contrast, the spring/autumn phenology, the length of vegetation growing season, and climate factors have relatively minor impacts. Generally, annual aboveground biomass increases by 3.9 to 25.3 g∙m2 (dry weight) with a 1 % increase in growing season mean soil moisture across the stations. Specifically, the sensitivity of productivity to moisture in wetter and colder environments (e.g., alpine meadows) is significantly higher than that in drier and warmer environments (e.g., temperate desert steppes). In contrast, the sensitivity to the precipitation of the latter is greater than the former. The effect of soil moisture is the most pronounced during summer. Dominant herb productivity is more sensitive to soil moisture than the others. Moreover, multivariate regression analyses show that the primary climatic factors and their attributions to variations in soil moisture differ among the stations, indicating the interaction between climate and soil moisture is very complex. Our study highlights the interspecific difference in the soil moisture dependence of grassland productivity and provides guidance to climate change impact assessments in grassland ecosystems.

Daytime warming strengthened delaying effect of precipitation on end of the vegetation growing season on the Tibetan Plateau.

Many studies have reported that daytime warming advances the end of the vegetation growing season (EOS) in arid and semi-arid ecosystems in the northern middle latitudes. This finding, however, seems to contradict the fact that low temperature constrains alpine vegetation activity. Using EOS from 1982 to 2015 retrieved from satellite observations, we show that daytime warming could facilitate a delay in EOS on the Tibetan Plateau, the world's largest and highest alpine region, with a dry and cold climate. Our analysis revealed a positive partial correlation (REOS-Tmax) between EOS and preseason mean daily maximum temperature (Tmax) on 57 % of the Plateau in wetter years, but on only 41 % of it in drier years. At a regional level, REOS-Tmax was 0.69 (P < 0.05, t-test) during wetter years and -0.56 (P = 0.11) during drier years, indicating that daytime warming could directly delay EOS on the Plateau. On the other hand, we found a positive partial correlation (REOS-Prec) between EOS and preseason cumulative precipitation on 62 % of the Plateau during warmer years, but on only 47 % during colder years. At a regional level, REOS-Prec was 0.68 (P < 0.05) during warmer years and - 0.28 (P = 0.46) during colder years. Moreover, REOS-Prec increased on 60 % of the Plateau under increasing Tmax during 1982-2015, suggesting that daytime warming facilitates a delay in EOS on the Tibetan Plateau by regulating the effect of precipitation on EOS. Thus, to improve autumn phenology models in this region, researchers should consider the interactive effects of temperature and precipitation on EOS.

Increasing Interspecific Difference of Alpine Herb Phenology on the Eastern Qinghai-Tibet Plateau.

The phenology of alpine grassland on the Qinghai-Tibet Plateau (QTP) is critical to regional climate change through climate-vegetation feedback. Although many studies have examined QTP vegetation dynamics and their climate sensitivities, the interspecific difference in the phenology response to climate change between alpine species is poorly understood. Here, we used a 30-year (1989-2018) record of in situ phenological observation for five typical alpine herbs (Elymus nutans, Kobresia pygmaea, Plantago asiatica, Puccinellia tenuiflora, and Scirpus distigmaticus) and associated climatic records at Henan Station in the eastern QTP to examine the species-level difference in spring and autumn phenology and then quantify their climate sensitivities. Our results show that with significantly warming, the green-up dates of herbs were insignificantly shifted, while the brown-off dates in four out of the five herbs were significantly delayed. Meanwhile, the interspecific difference in brown-off dates significantly increased at a rate of 0.62 days/annual from 1989 to 2016, which was three times larger than that in green-up dates (0.20 days/annual). These diverse rates were attributed to the different climate controls on spring and autumn phenology. In particular, green-up dates in most herbs were sensitive to mean surface temperature, while brown-off dates were sensitive to the night surface temperature. Furthermore, brown-off dates are less sensitive to the warming in high ecological niche (with higher herb height and aboveground biomass) herbs than low niche herbs (with lower herb height and aboveground biomass). The increased phenology interspecific difference highlights the complex responses of herbs to future climate change even under the same alpine environment and indicates a potential alternation in the plants community of alpine QTP, which may further influence the regional climate-vegetation feedback.

An earlier start of the thermal growing season enhances tree growth in cold humid areas but not in dry areas.

Climatic warming alters the onset, duration and cessation of the vegetative season. While previous studies have shown a tight link between thermal conditions and leaf phenology, less is known about the impacts of phenological changes on tree growth. Here, we assessed the relationships between the start of the thermal growing season and tree growth across the extratropical Northern Hemisphere using 3,451 tree-ring chronologies and daily climatic data for 1948-2014. An earlier start of the thermal growing season promoted growth in regions with high ratios of precipitation to temperature but limited growth in cold-dry regions. Path analyses indicated that an earlier start of the thermal growing season enhanced growth primarily by alleviating thermal limitations on wood formation in boreal forests and by lengthening the period of growth in temperate and Mediterranean forests. Semi-arid and dry subalpine forests, however, did not benefit from an earlier onset of growth and a longer growing season, presumably due to associated water loss and/or more frequent early spring frosts. These emergent patterns of how climatic impacts on wood phenology affect tree growth at regional to hemispheric scales hint at how future phenological changes may affect the carbon sequestration capacity of extratropical forest ecosystems.

Limited increase in asynchrony between the onset of spring green-up and the arrival of a long-distance migratory bird.

For many migrant bird species around the world, climate change has been shown to induce changes in the timings of arrival and the onset of spring food availability at breeding sites. However, whether such changes enlarged asynchrony between the timings of spring arrival of long-distance migratory birds and onset of vegetation greenness increase remain controversial. We used a 29-year phenological dataset to investigate the temporal changes in spring first-sighting date (FSD) of a long-distance migratory bird (barn swallow, Hirundo rustica), from observations at 160 local breeding sites across northern China, and the vegetation green-up onset date (VGD), determined from satellite observations of vegetation greenness. We found that both FSD and VGD trended earlier at over two-thirds of the breeding sites. FSD significantly advanced at 26.9% of the sites, and VGD significantly advanced at 23.8% of the sites. The degree of asynchrony between FSD and VGD changed significantly at one-third of the breeding sites (22.5% with an increase versus 11.3% with a decrease), leading to a limited increase of phenological mismatch. We speculated that climate change did not disrupt the climatic connections between most breeding sites and corresponding non-breeding sites (wintering grounds and migration routes). Our findings suggest that climate change may not greatly increase phenological mismatch between first arrival date of barn swallows and VGD at breeding sites. Importantly, this study should serve as a cue to encourage ecologists and conservation biologists to expand the context under which to explore the ecological consequences of phenological shifts beyond asynchrony, such as individual survival, population demography and ecosystem-level consequences.

Transformation of China's urbanization and eco-environment dynamics: an insight with location-based population-weighted indicators.

Within a short period, rapid urbanization has reshaped China's eco-environment, especially at the beginning of the new century. Many studies have focused on the changes in certain physical indicators of eco-environments; however, these indicators cannot directly explain or only slightly consider the eco-environmental benefits of urban residents. Therefore, we analysed location-based population-weighted eco-environmental changes with indicators of the vegetation index and fine particulate matter (PM2.5) concentration at each pixel in China's prefectures and combined the changes with urban expansion to provide an expanded understanding of the transformation of China's urbanization and its eco-environmental dynamics. We discovered that China's urban areas expanded by 38,350 km2 from 2000 to 2015 with an increase in the population-weighted vegetation and PM2.5 concentration, but the changes varied among different periods. From 2005 to 2010, urban areas expanded by 20,970 km2 with an increase in the population-weighted vegetation and PM2.5 concentration. The period from 2000 to 2005 was a key transforming period that experienced an urban expansion of 9081 km2 with a decrease in the population-weighted vegetation and an increase in the population-weighted PM2.5 concentration. An urban expansion of 8299 km2 with an increase in the population-weighted vegetation and a decrease of the population-weighted PM2.5 concentration occurred from 2010 to 2015. The results of this research indicate that China's urbanization and environmental changes have facilitated eco-environmental improvements.

Grassland restoration reduces water yield in the headstream region of Yangtze River.

Large-scale ecological restoration programs are considered as one of the key strategies to enhance ecosystem services. The Headstream region of Yangtze River (HYZR), which is claimed to be China's Water Tower but witnessed the rapid grassland deterioration during 1970s-2000, has seen a series of grassland restoration programs since 2000. But few studies have thoroughly estimated the hydrological effect of this recent grassland restoration. Here we show that restoration significantly reduces growing-season water yield coefficient (WYC) from 0.37 ± 0.07 during 1982-1999 to 0.24 ± 0.07 during 2000-2012. Increased evapotranspiration (ET) is identified as the main driver for the observed decline in WYC. After factoring out climate change effects, vegetation restoration reduces streamflow by 9.75 ± 0.48 mm from the period 1982-1999 to the period 2000-2012, amounting to 16.4 ± 0. 80% of climatological growing-season streamflow. In contrary to water yield, restoration is conducive to soil water retention - an argument that is supported by long-term in-situ grazing exclusion experiment. Grassland restoration therefore improves local soil water conditions but undercuts gain in downstream water resources associated with precipitation increases.