植被的ＰＥ（可能蒸散）指标与植被－气候分类（二）——几种主要方法与ＰＥＰ程序介绍

应用C．W．Thorn thwaite计算PE与气候分类方法对我国671个气候台站资料计算分析结果,得出可能蒸散的地理回归模型为：APE=2037.98-18.8308LAT(纬度)-4.5801LONG(经度)-0.157861ALT(海拔)APE与湿度指数Im与我国植被的主要类型及其分布格局有密切相关性。其热量指标(APE)界限与北美颇相符合,但Im明显偏低,反映了中国植被的生态特点。研究表明该方法在我国有明显的应用前景。     

中国陆地生态系统净初级生产力时空变化特征及影响因素

为揭示气候变化背景下我国各陆地生态系统净初级生产力(NPP)的时空分布特征与驱动机制,引入重心模型分析2000—2017年我国NPP的空间分布格局变化,并利用相关分析方法结合Thornthwaite Memorial模型定量区分气候变化与人类活动影响NPP的相对作用。结果表明：(1)2000—2017年全国NPP均值为325.86 g C/m²,整体呈现出南方高北方低,东南向西北逐渐递减的特点。(2)近18年全国与各陆地生态系统NPP均呈现增长趋势,全国NPP增长速率为4.4597 g C m^-2 a^-1,总净增加约0.391 Pg C。空间上全国与森林、草地、荒漠生态系统的NPP重心向东北方向移动,农田与城市生态系统的NPP重心向西北方向移动,表明NPP在该方向上的增速和增量最大。(3)全国NPP在华北、西北地区与四川盆地主要受降水的影响,在青藏高原与云贵高原的东部主要受气温的影响,各陆地生态系统之间城市生态系统NPP对降水响应的敏感度相对最高,荒漠生态系统NPP对温度响应的敏感度相对最高。(4)气候变化和人类活动对全...     

云南省气候生产潜力的时空变化

利用云南省1961-2017年101个国家级气象站年平均气温、年降水量资料,运用Miami模型、Thornthwaite Memorial模型计算了云南省3种气候生产潜力,用Mann-Kendell法进行突变检验,并分析了时空分布特征及未来趋势.结果表明:研究期间,云南平均温度气候生产潜力(Yt)、降水气候生产潜力(Yr)和蒸散气候生产潜力(Ye)值分别为1968、1477、1434 g·m^-2·a^-1,Yt呈波动上升状态,Yr/Yt值显示地区间水热配比差异大,约束性条件也明显不同;气候生产潜力存在突变现象,Yt在2001年开始明显突变,Yr没有突变,Ye在2002-2004年有突变;气候生产潜力及气候倾向性空间分布不均,全省各地年平均Yt、Yr和Ye分别在1030~2465、927~2341和832~1995 g·m^-2·a^-1,3种气候生产潜力均为滇西北和滇东北最低,滇西南和滇南最高,大部分地区Yt、Yr和Ye的气候倾向率分别为增长、减小和增长趋势;8种模拟未来气候变化的方案(仅气温增加1℃、仅降水增加10%、仅气温降低1℃、仅降水减少10%、气温增加1℃且降水减少10%、气温增加1℃且降水增加10%、气温降低1℃且降水增加10%、气温降低1℃且降水减少10%)将导致研究区Ye分别变化6~45、13~77.2、15~67、-87^-17、-74~46、58~96、-54~57、-101^-59 g·m^-2·a^-1.整体上,如果未来气候趋于"暖湿"化,将有利于研究区农作物增产,如果趋于"冷干"化,将不利于农作物生产.     

广东省植被潜在生产力的估算及其分布

本文应用Miami模型和Thornthwaite纪念模型,结合降水量、气温、蒸发量等气候资料,分别计算了广东省植被的可能净第一性生产力、谷物产量和木材生产量。并根据计算结果,绘制出植物气候生产力图。结果表明：广东省植被潜在生产力较大,因此,提高作物产量的潜力还很大;除局部小范围外,植被潜在生产力由沿海向内陆递减,并且等值线走向大致与海岸线平行;沿海的阳江、海丰和内陆的清远、佛冈等地的气候生产力最高,相反,粤北、粤东北山区和雷州半岛的生产力最低。     

ET come home: potential evapotranspiration in geographical ecology

Aim Many macroecological analyses are based on analyses of climatological data, within which evapotranspiration estimates are of central importance. In this paper we evaluate and review the use of evapotranspiration models and data in studies of geographical ecology to test the likely sensitivity of the analyses to variation in the performance of different metrics of potential evapotranspiration. Location Analyses are based on: (1) a latitudinal transect of sites (FLUXNET) for 11 different land‐cover types; and (2) globally gridded data. Methods First, we review the fundamental concepts of evapotranspiration, outline basic evapotranspiration models and describe methods with which to measure evapotranspiration. Next, we compare three different types of potential evapotranspiration models – a temperature‐based (Thornthwaite type), a radiation‐based (Priestley–Taylor) and a combination (Penman–Monteith) model – for 11 different land‐cover types. Finally, we compare these models at continental and global scales. Results At some sites the models differ by less than 7%, but generally the difference was greater than 25% across most sites. The temperature‐based model estimated 20–30% less than the radiation‐based and combination models averaged across all sites. The combination model often gave the highest estimates (22% higher than the radiation‐based model averaged across all sites). For continental and global averages, the potential evapotranspiration was very similar across all models. However, the difference in individual pixels was often larger than 150 mm year^?1 between models. Main conclusions The choice of evapotranspiration model and input data is likely to have a bearing on model fits and predictions when used in analyses of species richness and related phenomena at geographical scales of analysis. To assist those undertaking such analyses, we provide a guide to selecting an appropriate evapotranspiration model.     

Climatic water deficit,tree species ranges,and climate change in Yosemite National Park

Aim (1) To calculate annual potential evapotranspiration (PET), actual evapotranspiration (AET) and climatic water deficit (Deficit) with high spatial resolution; (2) to describe distributions for 17 tree species over a 2300‐m elevation gradient in a 3000‐km² landscape relative to AET and Deficit; (3) to examine changes in AET and Deficit between past (c. 1700), present (1971–2000) and future (2020–49) climatological means derived from proxies, observations and projections; and (4) to infer how the magnitude of changing Deficit may contribute to changes in forest structure and composition. Location Yosemite National Park, California, USA. Methods We calculated the water balance within Yosemite National Park using a modified Thornthwaite‐type method and correlated AET and Deficit with tree species distribution. We used input data sets with different spatial resolutions parameterized for variation in latitude, precipitation, temperature, soil water‐holding capacity, slope and aspect. We used climate proxies and climate projections to model AET and Deficit for past and future climate. We compared the modelled future water balance in Yosemite with current species water‐balance ranges in North America. Results We calculated species climatic envelopes over broad ranges of environmental gradients – a range of 310 mm for soil water‐holding capacity, 48.3°C for mean monthly temperature (January minima to July maxima), and 918 mm yr^?1 for annual precipitation. Tree species means were differentiated by AET and Deficit, and at higher levels of Deficit, species means were increasingly differentiated. Modelled Deficit for all species increased by a mean of 5% between past (c. 1700) and present (1971–2000). Projected increases in Deficit between present and future (2020–49) were 23% across all plots. Main conclusions Modelled changes in Deficit between past, present and future climate scenarios suggest that recent past changes in forest structure and composition may accelerate in the future, with species responding individualistically to further declines in water availability. Declining water availability may disproportionately affect Pinus monticola and Tsuga mertensiana. Fine‐scale heterogeneity in soil water‐holding capacity, aspect and slope implies that plant water balance may vary considerably within the grid cells of kilometre‐scale climate models. Sub‐grid‐cell soil and topographical data can partially compensate for the lack of spatial heterogeneity in gridded climate data, potentially improving vegetation‐change projections in mountainous landscapes with heterogeneous topography.