Ecology. 2014 Aug;95(8):2109-20. doi: 10.1890/13-1014.1.
The Tibetan Plateau (TP) is experiencing high rates of climatic change. We present a novel combined mechanistic-bioclimatic modeling approach to determine how changes in precipitation and temperature on the TP may impact net primary production (NPP) in four major biomes (forest, shrub, grass, desert) and if there exists a maximum rain use efficiency (RUE(MAX)) that represents Huxman et al.'s "boundary that constrain[s] site-level productivity and efficiency." We used a daily mechanistic ecosystem model to generate 40-yr outputs using observed climatic data for scenarios of decreased precipitation (25-100%); increased air temperature (1 degrees - 6 degrees C); simultaneous changes in both precipitation (+/- 50%, +/- 25%) and air temperature (+1 to +6 degrees C) and increased interannual variability (IAV) of precipitation (+1 sigma to +3 sigma, with fixed means, where sigma is SD). We fitted model output from these scenarios to Huxman et al.'s RUE(MAX) bioclimatic model, NPP = alpha + RUE x PPT (where alpha is the intercept, RUE is rain use efficiency, and PPT is annual precipitation). Based on these analyses, we conclude that there is strong support (when not explicit, then trend-wise) for Huxman et al.'s assertion that biomes converge to a common RUE(MAX) during the driest years at a site, thus representing the boundary for highest rain use efficiency; the interactive effects of simultaneously decreasing precipitation and increasing temperature on NPP for the TP is smaller than might be expected from additive, single-factor changes in these drivers; and that increasing IAV of precipitation may ultimately have a larger impact on biomes of the Tibetan Plateau than changing amounts of rainfall and air temperature alone.
青藏高原(TP)正在经历快速的气候变化。我们提出了一种新颖的综合机械-生物气候建模方法,以确定 TP 上降水和温度的变化如何影响四大生物群落(森林、灌木、草地、沙漠)的净初级生产力(NPP),以及是否存在最大雨利用效率(RUE(MAX)),它代表了 Huxman 等人的“限制[站点生产力和效率的边界”。我们使用每日机械生态系统模型,使用观测到的气候数据生成 40 年的输出,模拟降水减少(25-100%)、空气温度升高(1-6°C)、降水和空气温度同时变化(+/- 50%,+/- 25%)以及降水年际变异性(IAV)增加(+1 到+3 个标准差,固定平均值,其中标准差是 SD)的情况。我们将这些情景下的模型输出拟合到 Huxman 等人的 RUE(MAX)生物气候模型中,NPP = alpha + RUE x PPT(其中 alpha 是截距,RUE 是雨利用效率,PPT 是年降水量)。基于这些分析,我们得出结论,有力地支持了 Huxman 等人的断言,即在一个地点最干旱的年份,生物群落趋向于一个共同的 RUE(MAX),从而代表了最高雨利用效率的边界;降水和温度同时减少对 TP 上 NPP 的交互影响小于这些驱动因素单独变化时的预期;增加降水的 IAV 可能最终对青藏高原的生物群落产生比单独改变降雨量和空气温度更大的影响。