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Background and aimsNitrogen (N) enrichment usually weakens the stabilizing effect of biodiversity on productivity. However, previous studies focused on plant species richness and thus largely ignored the potential contributions of plant functional traits to stability, even though evidence is increasing that functional traits are stronger predictors than species richness of ecosystem functions.MethodsWe conducted a common garden experiment manipulating plant species richness and N addition levels to quantify effects of N addition on relations between species richness and functional trait identity and diversity underpinning the ‘fast–slow’ economics spectrum and community stability.ResultsNitrogen addition had a minor effect on community stability but increased the positive effects of species richness on community stability. Increasing community stability was found in the species-rich communities dominated by fast species due to substantially increasing temporal mean productivity relative to its standard deviation. Furthermore, enhancement in ‘fast–slow’ functional diversity in species-rich communities dominated by fast species under N addition increased species asynchrony, resulting in a robust biodiversity–stability relationship under N addition the artificial grassland communities.ConclusionThe findings demonstrate mechanistic links between plant species richness, ‘fast–slow’ functional traits, and community stability under N addition, suggesting that dynamics of biodiversity–stability relations under global changes are the results of species-specific responses of ‘fast–slow’ traits on the plant economics spectrum.

Predicting the potential influences of climate change on the richness and distribution is essential for the protection of endangered species. Most orchid species are narrowly distributed in specific habitats and are very vulnerable to habitat disturbance, especially for endangered orchid species on the Qinghai-Tibetan Plateau (QTP). In this study, we simulated the potential influences of climate change on the richness and distribution of 17 endangered orchid species on the QTP using the MaxEnt model based on the shared socioeconomic pathways scenarios (SSPs) in the 2050s and 2070s. The results showed that aspect, annual precipitation, elevation, mean temperature of driest quarter, topsoil pH (H2O), and topsoil sand fraction had a large influence on the potential distribution of endangered orchid species on the QTP. The area of potential distribution for orchid species richness ranging from 6 to 11 under the current climate scenario was 14,462 km2 (accounting for 0.56% of QTP), and it was mostly distributed in the southeastern part of QTP. The area of orchid species richness ranging from 6 to 11 under SSP370 in the 2070s was the smallest (9,370 km2: only accounting for 0.36% of QTP). The largest area of potential distribution for orchid species richness ranging from 6 to 11 was 45,394 km2 (accounting for 1.77% of QTP) under SSP585 in the 2070s. The total potential distribution area of 17 orchid species richness all increased from the 2050s to the 2070s under SSP126, SSP245, SSP370, and SSP585. The orchid species richness basically declined with the increasing elevation under current and future climate scenarios. The mean elevation of potential distribution for orchid species richness ranging from 6 to 11 under different climate scenarios was between 3,267 and 3,463 m. The mean elevation of potential distribution for orchid species richness ranging from 6 to 11 decreased from SSP126 (3,457 m) to SSP585 (3,267 m) in the 2070s. Based on these findings, future conservation plans should be concentrated on the selection of protected areas in the southeastern part of QTP to protect the endangered orchid species.

Global warming is one of the most pressing environmental issues today. Our study aimed to investigate how warming affected plant and soil nematode communities in alpine meadows on the Qinghai–Tibetan Plateau over the past seven years. An artificial warming experiment with different gradients was conducted from 2011 to 2018, including temperature increases of 0 °C (CK), 0.53 °C (A), 1.15 °C (B), 2.07 °C (C), and 2.17 °C (D), respectively. Cyperaceae plants were shown to be eliminated by increasing temperature, and plant community composition tended to cluster differently under different warming gradients. The number of nematodes decreased with the increase in soil depth, and the majority of them were observed in the topsoil layer. The individual densities of soil nematodes were 197 ind.·100 g−1 dry soil at 10–20 cm and 188 ind.·100 g−1 dry soil at 20–30 cm in the A treatment, which was significantly higher than the CK (53 and 67 ind.·100 g−1 dry soil) (p < 0.05). The lowest relative abundance of bacterivore nematodes (Ba) was 31.31% in treatment A and reached the highest of 47.14% under the warming gradient of D (p < 0.05). The abundance of plant parasitic nematodes (Pp) was significantly reduced to 26.03% by excessive warming (2.17 °C increase) in comparison to CK (41.65%). The soil nematode community had the highest diversity with a 0.53 °C increase in soil temperature; 1.15 °C warming gradients were lower, and nematode communities tended to be simplified (p < 0.05). All nematode channel ratio (NCR) values were above 0.5, indicating that warming did not change the decomposition pathway of soil organic matter dominated by the bacterial channels. The Wasilewska Index (WI) in the D treatment increased significantly compared to other treatments (p < 0.05), indicating that the mineralized pathway of the food web was primarily involved with Ba and fungivores nematodes (Fu), which is conducive to the growth of micro-biophagous nematodes. The plant parasite index (PPI) decreased significantly in the D treatment compared with other treatments (p < 0.05), indicating that a high warming gradient caused a reduction in the maturity of Pp nematodes. The maturity index (MI) increased in the D treatment compared with A, B, and C treatments, indicating that overheating affected the nematode community in the later stage of succession and caused the soil to be less disturbed. A partial least squares path model (PLSPM) showed that warming indirectly affects Fu and Pp diversity by directly impacting the plant community as well as indirectly affecting Ba by directly affecting soil properties. In conclusion, plant diversity and community composition profoundly affect the soil nematode communities, thus reflecting the dynamic processes and evolution of soil ecosystems.

Few studies have focused on the response of plant community phenology to temperature change using manipulative experiments. A lack of understanding of whether responses of community reproductive and vegetative phenological sequences to warming and cooling are asymmetrical or symmetrical limits our capacity to predict responses under warming and cooling. A reciprocal transplant experiment was conducted for 3 years to evaluate response patterns of the temperature sensitivities of community phenological sequences to warming (transferred downward) and cooling (transferred upward) along four elevations on the Tibetan Plateau. We found that the temperature sensitivities of flowering stages had asymmetric responses to warming and cooling, whereas symmetric responses to warming and cooling were observed for the vegetative phenological sequences. Our findings showed that coverage changes of flowering functional groups (FFGs; i.e., early-spring FFG, mid-summer FFG, and late-autumn FFG) and their compensation effects combined with required accumulated soil temperatureto codetermined the asymmetric and symmetric responses of community phenological sequences to warming and cooling. These results suggest that coverage change in FFGs on warming and cooling processes can be a primary driver of community phenological variation and may lead to inaccurate phenlogical estimation at large scale, such as based on remote sensing.

Abstract Global warming and changes in precipitation are altering the phenology of plants that significantly impact the functioning and services of ecosystems. Although a number of studies have addressed responses of plant phenology to warming and altered precipitation individually, their interactions can alter plant phenology differently than either does independently. To explore how the interactions between global change drivers alter alpine ecosystems, we conducted a factorial experiment manipulating warming (ambient and +2°C) and altered precipitation (50% decrease, control, and 50% increase) simultaneously in an alpine meadow on the Tibetan Plateau. Over two years, we monitored plant phenological events, leaf‐out day and first flowering day, for 11 common plant species that account for 74.4% of the total above biomass. Surprisingly, there was no interaction between warming and changes in precipitation on community plant phenology, but warming advanced leaf‐out and first flowering day by 7.10 and 9.79 d, respectively. Unlike the community response, plant functional groups had a variety of direct and interactive responses to the experimental climate drivers. While the phenology of legumes was most influenced by temperature, temperature and precipitation interacted to alter the phenology of grasses and forbs. To explore how plant phenological sensitivity on the Tibetan Plateau is compared with other meadow ecosystems, we combined our dataset with a global plant phenology dataset. Interestingly, the phenological sensitivity of leaf‐out day and first flowering day on the Tibetan Plateau is 7.3 and 37.8 times greater than global phenological sensitivity, respectively. This result highlights that a meta‐analysis of global phenological sensitivity may significantly underestimate change in some regions—even regions as large as the Tibetan Plateau. Together, our results suggest that the Tibetan Plateau may experience rapid change as temperatures warm and that these changes will likely be more rapid than in other regions of the world. Further, our study highlights that if we are to make accurate predictions of how plant phenology may change with warming, we need to understand the specific environmental cues that drive phenological responses across different areas.