A high-resolution dynamic vegetation model based on ecological mechanisms and the vegetation patterns at the geographic-scale

基于蒙古地区的观测资料，建立了基于坡向依赖的不连续植被过渡模式的精细尺度植被过渡模型。在网格化的目标空间（res=90m）中，计算生物相互作用下植物生物量和土壤含水量（SWC）的动态变化。植物对土壤水分的“促进效应”放大了地形引起的SWC差异，是产生观测到的不连续植被格局的关键。通过在模型中加入具有可行参数的草食效应，我们可以在气候和牲畜密度变化的不同情景下对未来植被变化的可能预测。它告诉我们，在降水减少和/或牲畜增加的某个临界点，可能会发生剧烈和不可逆转的植被退化和森林砍伐。

A fine-scale vegetation transition model was developed based on the observation data from Mongolia, where slope aspect-dependent and discontinuous vegetation transition pattern is widely observed. The dynamics of plants' biomass and soil water content(SWC) with biological interactions are calculated in the meshed target space(res=90m). The"facilitation effect"among plants over soil water amplified the difference in SWC caused by the topography and was the key to generate the observed discontinuous vegetation pattern. By adding the herbivory effect with feasible parameters to this model, we could show the possible future projections for vegetation change under various scenarios with changing climate and livestock density. It tells that drastic and irreversible vegetation degradation, deforestation might occur at some critical point of decrease of precipitation and/or increase in livestock.