Methane (CH4) is the second most important atmospheric greenhouse gas (GHG) and forest soils are a significant sink for atmospheric CH4. Uptake of CH4 by global forest soils is affected by nitrogen (N) deposition; clarifying the effect of N deposition helps to reduce uncertainties of the global CH4 budget. However, it remains an unsolved puzzle why N input stimulates soil CH4 flux (RCH4) in some forests while suppressing it in others. Combining previous findings and data from N addition experiments conducted in global forests, we proposed and tested a “stimulating-suppressing-weakening effect” (“three stages”) hypothesis on the changing responses of RCH4 to N input. Specifically, we calculated the response factors (f) of RCH4 to N input for N-limited and N-saturated forests across biomes; the significant changes in f values supported our hypothesis. We also estimated the global forest soil CH4 uptake budget to be approximately 11.2 Tg yr–1. CH4 uptake hotspots were located predominantly in temperate forests. Furthermore, we quantified that current level of N deposition reduced global forest soil CH4 uptake by ~3%. This suppression effect was more pronounced in temperate forests than in tropical or boreal forests, likely due to differences in N status. The proposed “three stages” hypothesis in this study generalizes the diverse effects of N input on RCH4, which could help improve experimental design. Additionally, our findings imply that by regulating N pollution and reducing N deposition, soil CH4 uptake can be significantly increased in the N-saturated forests in tropical and temperate biomes.

Knowledge of vertical structural complexity (VSC) is important, because the resulting spatial partitioning is closely linked to resource utilization and environmental adaptation. How VSC responds to environmental changes on large scales and its mechanisms are poorly understood. We investigated 2,013 plant communities on the Tibetan Plateau (TP). VSC was quantified as the maximum height (Height-max), height variation (Height-var), and height evenness (Height-even). Precipitation dominated the VSC variation in forests and shrublands, supporting the classic physiological tolerance and hydraulic limitation hypotheses. In contrast, for alpine grasslands in extreme environments, non-resource limiting factors dominate VSC variation. Generally, with the shifting of climate from optimal to extreme, the effect of resource availability gradually decreases, but the effect of non-resource limiting factors increases. Using machine learning models, maps of VSC at 1-km resolution were firstly produced for the TP. These findings provide new insights into macroecological studies, especially for adaptation mechanisms and model optimization.

Plant biochemical reactions are dependent on the combined action of multiple elements. However, it remains unclear how these elements co-vary to adapt to environmental change. Here, we propose a novel concept of the multi-element network (MEN) including the mutual effects between elements to more effectively explore the alterations in response to long-term nitrogen (N) deposition simulations. MENs were constructed with 18 elements and were species specific. Macroelements were more stable, but microelements were more susceptible to N deposition. Interestingly, higher MEN plasticity determined increased relative aboveground biomass (species importance) for different species in one functional group under simulated N deposition. Furthermore, the association between MEN plasticity and species importance was consistently verified along a dry–wet transect. In summary, MENs provide a novel approach for exploring the adaptation strategies of plants and to better predict community composition under altering nutrient availability or environmental stress associated with future global climate change.