The meadow ecosystem on the Qing- hai-Tibetan Plateau is considered to be sensitive to climate change. An understanding of the alpine meadow ecosystem is therefore important for pre- dicting the response of ecosystems...The meadow ecosystem on the Qing- hai-Tibetan Plateau is considered to be sensitive to climate change. An understanding of the alpine meadow ecosystem is therefore important for pre- dicting the response of ecosystems to climate change. In this study, we use the coefficients of variation (Cv) and stability (E) obtained from the Haibei Alpine Meadow Ecosystem Research Station to characterize the ecosystem stability. The results suggest that the net primary production of the alpine meadow eco- system was more stable (Cv = 13.18%) than annual precipitation (Cv = 16.55%) and annual mean air temperature (Cv = 28.82%). The net primary produc- tion was insensitive to either the precipitation (E = 0.0782) or air temperature (E = 0.1113). In summary, the alpine meadow ecosystem on the Qinghai- Tibetan Plateau is much stable. Comparison of alpine meadow ecosystem stability with other five natural grassland ecosystems in Israel and southern African indicates that the alpine meadow ecosystem on the Qinghai-Tibetan Plateau is the most stable ecosys- tem. The alpine meadow ecosystem with relatively simple structure has high stability, which indicates that community stability is not only correlated with biodiversity and community complicity but also with environmental stability. An average oscillation cycles of 3―4 years existed in annual precipitation, annual mean air temperature, net primary production and the population size of consumers at the Haibei natural ecosystem. The high stability of the alpine meadow ecosystem may be resulting also from the adaptation of the ecosystem to the alpine environment.展开更多
Generalized linear mixed models(GLMMs)have been widely used in contemporary ecology studies.However,determination of the relative importance of collinear predictors(i.e.fixed effects)to response variables is one of th...Generalized linear mixed models(GLMMs)have been widely used in contemporary ecology studies.However,determination of the relative importance of collinear predictors(i.e.fixed effects)to response variables is one of the challenges in GLMMs.Here,we developed a novel R package,glmm.hp,to decompose marginal R2^(2)explained by fixed effects in GLMMs.The algorithm of glmm.hp is based on the recently proposed approach‘average shared variance’i.e.used for multivariate analysis.We explained the principle and demonstrated the use of this package by simulated dataset.The output of glmm.hp shows individual marginal R2^(2)s that can be used to evaluate the relative importance of predictors,which sums up to the overall marginal R2^(2).Overall,we believe the glmm.hp package will be helpful in the interpretation of GLMM outcomes.展开更多
文摘The meadow ecosystem on the Qing- hai-Tibetan Plateau is considered to be sensitive to climate change. An understanding of the alpine meadow ecosystem is therefore important for pre- dicting the response of ecosystems to climate change. In this study, we use the coefficients of variation (Cv) and stability (E) obtained from the Haibei Alpine Meadow Ecosystem Research Station to characterize the ecosystem stability. The results suggest that the net primary production of the alpine meadow eco- system was more stable (Cv = 13.18%) than annual precipitation (Cv = 16.55%) and annual mean air temperature (Cv = 28.82%). The net primary produc- tion was insensitive to either the precipitation (E = 0.0782) or air temperature (E = 0.1113). In summary, the alpine meadow ecosystem on the Qinghai- Tibetan Plateau is much stable. Comparison of alpine meadow ecosystem stability with other five natural grassland ecosystems in Israel and southern African indicates that the alpine meadow ecosystem on the Qinghai-Tibetan Plateau is the most stable ecosys- tem. The alpine meadow ecosystem with relatively simple structure has high stability, which indicates that community stability is not only correlated with biodiversity and community complicity but also with environmental stability. An average oscillation cycles of 3―4 years existed in annual precipitation, annual mean air temperature, net primary production and the population size of consumers at the Haibei natural ecosystem. The high stability of the alpine meadow ecosystem may be resulting also from the adaptation of the ecosystem to the alpine environment.
基金This work was supported by the National Natural Science Foundation of China(32271551)the Metasequoia funding of Nanjing Forestry University.Conflict of interest statement.The authors declare that they have no conflict of interest.
文摘Generalized linear mixed models(GLMMs)have been widely used in contemporary ecology studies.However,determination of the relative importance of collinear predictors(i.e.fixed effects)to response variables is one of the challenges in GLMMs.Here,we developed a novel R package,glmm.hp,to decompose marginal R2^(2)explained by fixed effects in GLMMs.The algorithm of glmm.hp is based on the recently proposed approach‘average shared variance’i.e.used for multivariate analysis.We explained the principle and demonstrated the use of this package by simulated dataset.The output of glmm.hp shows individual marginal R2^(2)s that can be used to evaluate the relative importance of predictors,which sums up to the overall marginal R2^(2).Overall,we believe the glmm.hp package will be helpful in the interpretation of GLMM outcomes.
