Warming-induced carbon loss through terrestrial ecosystem respiration (Re) is likely getting stronger in high latitudes and cold regions because of the more rapid warming and higher temperature sensitivity of Re (Q₁₀). However, it is not known whether the spatial relationship between Q₁₀ and temperature also holds temporally under a future warmer climate. Here, we analyzed apparent Q₁₀ values derived from multiyear observations at 74 FLUXNET sites spanning diverse climates and biomes. We found warming-induced decline in Q₁₀ is stronger at colder regions than other locations, which is consistent with a meta-analysis of 54 field warming experiments across the globe. We predict future warming will shrink the global variability of Q₁₀ values to an average of 1.44 across the globe under a high emission trajectory (RCP 8.5) by the end of the century. Therefore, warming-induced carbon loss may be less than previously assumed because of Q₁₀ homogenization in a warming world.

The natural shift in land cover from non-vegetated to vegetated land is termed as vegetation expansion, which has substantial impacts on regional climate conditions and land surface energy balance. Barrens dominate the northwestern Tibetan Plateau, where vegetation is predicted to expand northwestward with the ongoing climate warming. However, rare studies have confirmed such a forecast with large-scale vegetation monitoring. In this study, we used a landcover dataset, classified according to the International Geosphere–Biosphere Program criteria, to examine previous model-based predictions and the role of climate on the expansion rate across the plateau. Our results showed that shrublands, open forests, grasslands, and water bodies expanded while evergreen and deciduous broadleaf forests, croplands and barrens shrank during the period 2001–2018. Vegetation expanded by 33,566 km² accounting for about 1.3% of the total area of this plateau and the land cover shifting from barrens to grasslands was the primary way of vegetation expansion. Spatially, the vegetation expanded northwestward to lands with colder, drier, and more radiation in the climate. Increasing precipitation positively correlated with the vegetation expansion rate for the arid and semi-arid northwest Tibetan Plateau and warming contributed to the vegetation expanding in the semi-humid southeast Tibetan Plateau. Our results verified the predictions of models and highlighted the “greening” on barrens in recent years.

The timing regimes of precipitation can exert profound impacts on grassland ecosystems. However, it is still unclear how the peak aboveground biomass (AGB_peak) of alpine grasslands responds to the temporal variability of growing season precipitation (GSP) on the northern Tibetan Plateau. Here, the temporal variability of precipitation was defined as the number and intensity of precipitation events as well as the time interval between consecutive precipitation events. We conducted annual field measurements of AGB_peak between 2009 and 2016 at four sites that were representative of alpine meadow, meadow-steppe, alpine steppe, and desert-steppe. Thus, an empirical model was established with the time series of the field-measured AGB_peak and the corresponding enhanced vegetation index (EVI) (R² = 0.78), which was used to estimate grassland AGB_peak at the regional scale. The relative importance of the three indices of the temporal variability of precipitation, events, intensity, and time interval on grassland AGB_peak was quantified by principal component regression and shown in a red–green–blue (RGB) composition map. The standardized importance values were used to calculate the vegetation sensitivity index to the temporal variability of precipitation (VSIP). Our results showed that the standardized VSIP was larger than 60 for only 15% of alpine grassland pixels and that AGB_peak did not change significantly for more than 60% of alpine grassland pixels over the past decades, which was likely due to the nonsignificant changes in the temporal variability of precipitation in most pixels. However, a U-shaped relationship was found between VSIP and GSP across the four representative grassland types, indicating that the sensitivity of grassland AGB_peak to precipitation was dependent on the types of grassland communities. Moreover, we found that the temporal variability of precipitation explained more of the field-measured AGB_peak variance than did the total amount of precipitation alone at the site scale, which implies that the mechanisms underlying how the temporal variability of precipitation controls the AGB_peak of alpine grasslands should be better understood at the local scale. We hypothesize that alpine grassland plants promptly respond to the temporal variability of precipitation to keep community biomass production more stable over time, but this conclusion should be further tested. Finally, we call for a long-term experimental study that includes multiple natural and anthropogenic factors together, such as warming, nitrogen deposition, and grazing and fencing, to better understand the mechanisms of alpine grassland stability on the Tibetan Plateau.

Alpine swamp meadow on the Tibetan Plateau is among the most sensitive areas to climate change. Accurate quantification of the GPP in alpine swamp meadow can benefit our understanding of the global carbon cycle. The 8-day MODerate resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) products (GPP_MOD) provide a pathway to estimate GPP in this remote ecosystem. However, the accuracy of the GPP_MOD estimation in this representative alpine swamp meadow is still unknown. Here five years GPP_MOD was validated using GPP derived from the eddy covariance flux measurements (GPP_EC) from 2009 to 2013. Our results indicated that the GPP_EC was strongly underestimated by GPP_MOD with a daily mean less than 40% of EC measurements. To reduce this error, the ground meteorological and vegetation leaf area index (LAI_G) measurements were used to revise the key inputs, the maximum light use efficiency (ε_max) and the fractional photosynthetically active radiation (FPAR_M) in the MOD17 algorithm. Using two approaches to determine the site-specific ε_max value, we suggested that the suitable ε_max was about 1.61 g C MJ⁻¹ for this alpine swamp meadow which was considerably larger than the default 0.68 g C MJ⁻¹ for grassland. The FPAR_M underestimated 22.2% of the actual FPAR (FPAR_G) simulated from the LAI_G during the whole study period. Model comparisons showed that the large inaccuracies of GPP_MOD were mainly caused by the underestimation of the ε_max and followed by that of the undervalued FPAR. However, the DAO meteorology data in the MOD17 algorithm did not exert a significant affection in the MODIS GPP underestimations. Therefore, site-specific optimized parameters inputs, especially the ε_max and FPAR_G, are necessary to improve the performance of the MOD17 algorithm in GPP estimation, in which the calibrated MOD17A2 algorithm (GPP_MODR3) could explain 91.6% of GPP_EC variance for the alpine swamp meadow.

The allocation of net primary production (NPP) between above- and belowground components is a key step of ecosystem material cycling and energy flows, which determines many critical parameters, e.g., the fraction of below ground NPP (BNPP) to NPP (f_BNPP) and root turnover rates (RTR), in vegetation models. However, direct NPP estimation and partition are scarcely based on field measurements of biomass dynamics in the alpine grasslands on the Northern Tibetan Plateau (NTP). Consequently, these parameters are unverifiable and controversial. Here, we measured above- and belowground biomass dynamics (monthly from May to September each year from 2013 to 2015) to estimate NPP dynamics and allocations in four typical alpine grassland ecosystems, i.e., an alpine meadow, alpine meadow steppe, alpine steppe and alpine desert steppe. We found that NPP and its components, above and below ground NPP (ANPP and BNPP), increased significantly from west to east on the NTP, and ANPP was mainly affected by temperature while BNPP and NPP were mainly affected by precipitation. The bulk of BNPP was generally concentrated in the top 10 cm soil layers in all four alpine grasslands (76.1% ± 9.1%, mean ± SD). Our results showed that f_BNPP was significantly different among these four alpine grasslands, with its means in alpine meadow (0.93), alpine desert steppe (0.92) being larger than that in the alpine meadow steppe (0.76) and alpine steppe (0.77). Both temperature and precipitation had significant and positive effects on the f_BNPP, while their interaction effects were significantly opposite. RTR decreased with increasing precipitation, but increased with increasing temperature across this ecoregion. Our study illustrated that alpine grasslands on the NTP, especially in the alpine meadow and alpine desert steppe, partitioned an unexpected and greater NPP to below ground than most historical reports across global grasslands, indicating a more critical role of the root carbon pool in carbon cycling in alpine grasslands on the NTP.