Response of North American ecosystem models to multi-annual periodicities in temperature and precipitation

Ecosystem models typically use input temperature and precipitation data generated stochastically from weather station means and variances. Although the weather station data are based on measurements taken over a few decades, model simulations are usually on the order of centuries. Consequently, observed periodicities in temperature and precipitation at the continental scale that have been correlated with largscale forcings, such as ocean-atmosphere dynamics and lunar and sunspot cycles, are ignored. We investigated how these natural climatic fluctuations affect aboveground biomass in ecosystem models by incorporating some of the more pronounced continental-scale cycles in temperature (4, 11, 80, 180 year periods) and precipitation (11 and 19 year periods) into models of three North American forests (using LINKAGES) and one North American grassland (using STEPPE). Even without inclusion of periodicities in climate, long-term dynamics of these models were characterized by internal frequencies resulting from vegetation birth, growth and death processes. Our results indicate that long-term temperature cycles result in significantly lower predictions of forest biomass than observed in the control case for a forest on a biome transition (northern hardwoods/boreal forest). Lower-frequency, higher-amplitude temperature oscillation caused amplification of forest biomass response in forests containing hardwood species. Shortgrass prairie and boreal ecosystems, dominated by species with broad stress tolerance ranges, were relatively insensitive to climatic oscillations. Our results suggest periodicities in climate should be incorporated within long-term simulations of ecosystems with strong internal frequencies, particularly for systems on biome transitions.     

小兴安岭不同年龄林分对气候变化的潜在响应

应用林窗模型LINKAGES分别对小兴安岭原始林不同年龄林分在5种气候变暖情景下的未来演替动态进行了模拟预测.5种气候变暖情景分别为:OSU、GISS、GFDL、UKMO和CGCM2.不同年龄林分的运行结果均表明:在OSU、GISS情景下,温度升高较平缓,小兴安岭的主要树种分布基本保持现有状态,总生物量有升高趋势;在GFDL、UKMO温度大幅度升高情景下,小兴安岭森林不能适应生态环境的急剧改变,存在全部衰退的可能;而CGCM2情景下,红松生物量先上升后下降,红松针阔混交林将逐渐演替为以色木槭和蒙古栎占优势的阔叶混交林.不同年龄林分间比较发现:当增温幅度未超过红松的耐受范围时,过熟林对气候变化的抗干扰能力显著优于其他林龄类型,但总生物量水平略低;中幼林对气候变化的适应能力最强,能够在气候变化过程中朝着最有利于充分利用光照、养分等环境因子的方向演替,树种组成达到稳定后的总生物量水平通常最高.反之,当超过红松的耐受范围时,过熟林的抗干扰能力和恢复能力均下降,表现为林分的迅速衰退及总生物量的明显波动;中幼林对气候变化的适应能力仍然较强,演替动态最平稳.      

气候变暖对小兴安岭主要树种的潜在影响

分别以单一树种与复合树种作为模拟对象,采用LINKAGES模型模拟预测了气候变暖对小兴安岭主要树种的潜在影响,结果表明:气候变暖对各树种的影响趋势与增温幅度关系密切。当温度上升不超过3℃时,云杉、枫桦将面临退化危险,但红松及其他阔叶树种的生长优势均更加明显;当温度上升超过5℃时,大部分树种均显示出不同程度的衰退趋势,仅蒙古栎等耐高温、干旱的阳性树种能够较好地适应未来的高温环境。