Archaeal communities in the sediments of different mangrove stands at Dongzhaigang, China - Li, Wei; Guan, Wei; Chen, Huai; Liao, Baowen; Hu, Ji; Peng, Changhui; Rui, Junpeng; Tian, Jianqing; Zhu, Dan; He, Yixin (Journal of Soils and Sediments, 2016)

Variations of Sediment Archaea Communitiesin Different Distribution Areasof Bruguiera gymnoihiza Mangrovein Dongzhaigang, China - Li, Wei; Guan, Wei; Chen, Huai; Liao, Baowen; Hu, Ji; Rui, Junpeng; Peng, Changhui; Zhu, Dan; He, Yixin; Tian, Jianqing (Polish Journal of Environmental Studies, 2019)

Leaf Trait Covariation and Its Controls: A Quantitative Data Analysis Along a Subtropical Elevation Gradient - Yang, Yanzheng; Gou, Ruikun; Li, Wei; Kassout, Jalal; Wu, Jun; Wang, Liming; Peng, Changhui; Lin, Guanghui (Journal of Geophysical Research: Biogeosciences, 2021)
Abstract Elevation gradients are frequently treated as useful space‐for‐time substitutions for inferring trait variations in response to different environmental conditions. The independent variations in leaf traits in response to elevation are well understood, but far less is known about trait covariation and its controls. This limits our understanding of the principles and mechanisms of leaf trait covariation, especially along elevation gradients in subtropical forests. Here, we studied the covariation among seven functional traits, including leaf size (LS), leaf nitrogen per unit mass ( N mass ), leaf nitrogen per unit area ( N area ), leaf mass per area (LMA), leaf dry matter content (LDMC), leaf thickness (LT) and the leaf internal‐to‐ambient CO 2 ratio ( C i : C a , termed χ ). Sampling was conducted on 41 species in a subtropical forest on Mount Huangshan, China, and the data were analyzed using multivariate analysis and variance partitioning procedures. We found that (a) The first three principal components captured 79% of the total leaf trait covariation, which was caused mainly by within site differences; (b) N mass and LDMC were positively correlated with soil water content (SW) and negatively correlated with vapor pressure deficit (VPD), while χ showed negative relationships with elevation; and (c) 78% of the variation in the studied plant functional traits could be explained by climate, soil, and family controls in combination, while family distribution was the most important determining factor for trait covariation along the elevation gradient. Our findings provide relevant insights into plant adaptation to environmental gradients and present useful guidelines for ecosystem management and planning. , Plain Language Summary Changes of plant functional traits along elevation gradient are important indicators which reflect the behaviors and adaptations of plants. In this study we first analyzed the dominant signals of seven leaf functional traits and then we depicted the response of seven traits to changing elevation environments, and finally we quantified the contributions of climate, soil, and vegetation distribution. Our findings validate the hypothesis that trait covariation, and thus adaptation, occurs in response to the elevation gradients that most plant species experience. , Key Points The first three principal components captured 79% of the total leaf trait covariation Leaf nitrogen content ( N mass ) and leaf dry mass content (LDMC) were positively correlated with soil water content and negatively correlated with vapor pressure deficit Vegetation (family) distribution was the most important determining factor for trait covariation along the elevation gradient

Spatiotemporal Variations in Nitrous Oxide Emissions from an Open Fen on the Qinghai–Tibetan Plateau: a 3-Year Study - Chen, Huai; Wang, Yanfen; Wu, Ning; Zhu, Dan; Li, Wei; Gao, Yongheng; Zhu, Qiu’an; Yang, Gang; Peng, Changhui (Water, Air, & Soil Pollution, 2012)

The carbon stock of alpine peatlands on the Qinghai–Tibetan Plateau during the Holocene and their future fate - Chen, Huai; Yang, Gang; Peng, Changhui; Zhang, Yao; Zhu, Dan; Zhu, Qiuan; Hu, Ji; Wang, Mei; Zhan, Wei; Zhu, Erxiong; Bai, Zengzhi; Li, Wei; et al. (Quaternary Science Reviews, 2014)

Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand? - Paschalis, Athanasios; Fatichi, Simone; Zscheischler, Jakob; Ciais, Philippe; Bahn, Michael; Boysen, Lena; Chang, Jinfeng; De Kauwe, Martin; Estiarte, Marc; Goll, Daniel; Hanson, Paul J.; Harper, Anna B.; et al. (Global Change Biology, 2020)
Abstract Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model‐data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter‐model variation is generally large and model agreement varies with timescales. In severely water‐limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily–monthly) timescales and reduces on longer (seasonal–annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter‐model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.