Quantifying the variability and changes in phenology and gross primary production (GPP) of alpine wetlands in the Qinghai–Tibetan Plateau under climate change is essential for assessing carbon (C) balance dynamics at regional and global scales. In this study, in situ eddy covariance (EC) flux tower observations and remote sensing data were integrated with a modified, satellite-based vegetation photosynthesis model (VPM) to investigate the variability in climate change, phenology, and GPP of an alpine wetland ecosystem, located in Zoige, southwestern China. Two-year EC data and remote sensing vegetation indices showed that warmer temperatures corresponded to an earlier start date of the growing season, increased GPP, and ecosystem respiration, and hence increased the C sink strength of the alpine wetlands. Twelve-year long-term simulations (2000–2011) showed that: (1) there were significantly increasing trends for the mean annual enhanced vegetation index (EVI), land surface water index (LSWI), and growing season GPP (R² ≥ 0.59, p < 0.01) at rates of 0.002, 0.11 year⁻¹ and 16.32 g·C·m⁻²·year⁻¹, respectively, which was in line with the observed warming trend (R² = 0.54, p = 0.006); (2) the start and end of the vegetation growing season (SOS and EOS) experienced a continuous advancing trend at a rate of 1.61 days·year⁻¹ and a delaying trend at a rate of 1.57 days·year⁻¹ from 2000 to 2011 (p ≤ 0.04), respectively; and (3) with increasing temperature, the advanced SOS and delayed EOS prolonged the wetland’s phenological and photosynthetically active period and, thereby, increased wetland productivity by about 3.7–4.2 g·C·m⁻²·year⁻¹ per day. Furthermore, our results indicated that warming and the extension of the growing season had positive effects on carbon uptake in this alpine wetland ecosystem.

Grazing is an important modulator of both plant productivity and biodiversity in grassland community, yet how to determine a suitable grazing intensity in alpine grassland is still controversy. Here, we explore the effects of different grazing intensities on plant biomass and species composition, both at community level and functional group level, and examines the productivity–species richness relationship under four grazing patterns: no grazing (CK), light grazing (LG), moderate grazing, (MG) and heavy grazing (HG), attempt to determine a suitable grazing intensity in alpine grassland. The results were as follows. The total aboveground biomass (AGB) reduced with increasing grazing intensity, and the response of plant functional groups was different. AGB of both sedges and legumes increased from MG to HG, while the AGB of forbs reduced sharply and the grass AGB remained steady. There was a significant positive relationship between productivity and species richness both at community level and functional group level. In contrast, the belowground biomass (BGB) showed a unimodal relationship from CK to HG, peaking in MG (8,297.72 ± 621.29 g/m²). Interestingly, the grassland community tends to allocate more root biomass to the upper soil layer under increasing grazing intensities. Our results suggesting that moderate levels of disturbance may be the optimal grassland management strategy for alpine meadow in terms of root production.

The Qinghai–Tibet Plateau (QTP) is particularly sensitive to global climate change, especially to elevated temperatures, when compared with other ecosystems. However, few studies use long‐term field measurements to explore the interannual variations in plant biomass under climate fluctuations. Here, we examine the interannual variations of plant biomass within two vegetation types (alpine meadow and alpine shrub) during 2008–2017 and their relationships with climate variables. The following results were obtained. The aboveground biomass (AGB) and belowground biomass (BGB) response differently to climate fluctuations, the AGB in KPM was dominated by mean annual precipitation (MAP), whereas the AGB in PFS was controlled by mean annual air temperature (MAT). However, the BGB of both KPM and PFS was only weakly affected by climate variables, suggesting that the BGB in alpine ecosystems may remain as a stable carbon stock even under future global climate change. Furthermore, the AGB in PFS was significantly higher than KPM, while the BGB and R/S in KPM were significantly higher than PFS, reflecting the KPM be more likely to allocate more photosynthates to roots. Interestingly, the proportion of 0–10 cm root biomass increased in KPM and PFS, whereas the other proportions both decreased, reflecting a shift in biomass toward the surface layer. Our results could provide a new sight for the prediction how alpine ecosystem response to future climate change.

Aboveground biomass (AGB) and belowground biomass (BGB) allocation and productivity–richness relationship are controversial. Here, we assessed AGB and BGB allocation and the productivity–richness relationship at community level across four grassland types based on the biomass data collected from 80 sites across the Qinghai Plateau during 2011–2012. The reduced major axis regression and general linear models were used and showed that (a) the median values of AGB were significantly higher in alpine meadow than in other three grassland types; the ratio of root to shoot (R/S) was significantly higher in desert grassland (36.06) than intemperate grassland (16.60), alpine meadow (13.35), and meadow steppe (19.46). The temperate grassland had deeper root distribution than the other three grasslands, with about 91.45% roots distributed in the top 30 cm soil layer. (b) The slopes between log AGB and log BGB in the temperate grassland and meadow steppe were 1.09 and 1, respectively, whereas that in the desert grassland was 1.12, which was significantly different from the isometric allocation relationship. A competitive relationship between AGB and BGB was observed in the alpine meadow with a slope of −1.83, indicating a trade‐off between AGB and BGB in the alpine meadow. (c) A positive productivity–richness relationship existed across the four grassland types, suggesting that the positive productivity–richness relationship might not be affected by the environmental factors at the plant location. Our results provide a new insight for biomass allocation and biodiversity–ecosystem functioning research.