Data-based modelling and environmental sensitivity of vegetation in China

摘要

A process-oriented niche specification (PONS) model was constructed toquantify climatic controls on the distribution of ecosystems, based on thevegetation map of China. PONS uses general hypotheses about bioclimaticcontrols to provide a "bridge" between statistical niche models and morecomplex process-based models. Canonical correspondence analysis provided anoverview of relationships between the abundances of 55 plant communities in0.1° grid cells and associated mean values of 20 predictor variables.Of these, GDD₀ (accumulated degree days above 0 °C),Cramer–Prentice α (an estimate of the ratio of actual to equilibriumevapotranspiration) and mGDD₅ (mean temperature during the period above5 °C) showed the greatest predictive power. These three variableswere used to develop generalized linear models for the probability ofoccurrence of 16 vegetation classes, aggregated from the original 55 types byk-means clustering according to bioclimatic similarity. Each class washypothesized to possess a unimodal relationship to each bioclimate variable,independently of the other variables. A simple calibration was used togenerate vegetation maps from the predicted probabilities of the classes.Modelled and observed vegetation maps showed good to excellent agreement(κ = 0.745). A sensitivity study examined modelled responses ofvegetation distribution to spatially uniform changes in temperature,precipitation and [CO₂], the latter included via an offset to α(based on an independent, data-based light use efficiency model for forestnet primary production). Warming shifted the boundaries of most vegetationclasses northward and westward while temperate steppe and desert replacedalpine tundra and steppe in the southeast of the Tibetan Plateau. Increasedprecipitation expanded mesic vegetation at the expense of xeric vegetation.The effect of [CO₂] doubling was roughly equivalent to increasingprecipitation by ~ 30%, favouring woody vegetation types,particularly in northern China. Agricultural zones in northern Chinaresponded most strongly to warming, but also benefited from increases inprecipitation and [CO₂]. These results broadly conform to previouslypublished findings made with the process-based model BIOME4, but they addregional detail and realism and extend the earlier results to includecropping systems. They provide a potential basis for a broad-scale assessmentof global change impacts on natural and managed ecosystems.