基于3S的自然植被光能利用率的时空分布特征的模拟

 光能利用率（LUE）直接影响植被各层中的能量分布和光合速率，在确定环境对光合和地上部生长分配的综合限制上十分有价值，是衡量系统功能的一个重要指标。本研究以遥感图像（TM）作为数据源，获取了影响植被LUE的重要变量——叶面积指数（LAI）；用程序语言编写了描述系统碳循环和水循环的景观尺度生态系统生产力过程模型（EPPML），对长白山自然保护区的太阳总辐射、净初级生产力（NPP）和LUE等的季节动态和空间分布进行了模拟；并用地理信息系统（GIS）手段对空间数据进行处理、分析和显示，从而实现了将植物生理生态研究的结果从小尺度向中尺度进行拓展和转换。EPPML可以比较准确地模拟长白山自然保护区景观尺度上主要植被类型的NPP和太阳总辐射，对LUE的模拟结果也大多在我国森林的LUE范围之内，但对不同植被类型LUE的验证因实测数据不足，仅做了初步比较。模拟结果表明，长白山植被的LUE与NPP的季节进程十分近似，7月可达2.9%。春、夏、秋、冬四个季节植被LUE的模拟平均值分别为0.551%、2.680%、0.551%和0.047%。植被年LUE的模拟值平均为1.075%，在-3.272%～3.556%之间变化，阔叶红松(Pinus koraiensis)林最大（1.653%），高山流砾滩草类最小（0.146%）。阔叶红松林的LUE虽然较高，但仍有很大的增长潜力。

SIMULATION OF TEMPORAL AND SPATIAL DISTRIBUTION OF NATURAL VEGETATION LIGHT UTILIZATION EFFICIENCY BASED ON 3S

Light utilization efficiency (LUE) directly influences the distribution of energy and rate of photosynthesis in all layers of vegetation. LUE is very valuable in deciding the integrated limits of environment to photosynthesis and plant growth allocation of aboveground, and is an important index in weighing functions of system. In China, the studies on LUE focus usually on crops, rarely on natural vegetations, and mostly calculate mean LUE over the country. The studies on LUE of natural vegetations in some regions are limited to one or two types of vegetation. Thus, it is very difficult to reflect the total conditions of all vegetations over these regions in different periods. In the study, leaf area index (LAI) that greatly influences LUE of vegetation was received from remote sensing images. The ecosystem productivity process model at landscape scale (EPPML) that described carbon cycle and water cycle of system was built by computer program (Visual C++), and seasonal dynamics and spatial distributions of total solar radiation, net primary productivity (NPP) and LUE in Changbai Mountain Nature Reserve were simulated. Geographical Information System (GIS) was used to process, analyze and display spatial data. Thus, we could extend and convert the studies on physiological ecology of plants from small scale to a larger scale. EPPML uses the principles of Century, BIOM_BGC, Forest-BGC and BEPS for quantifying the biophysical processes governing ecosystem productivity, but the original model is modified to better represent Changbai Mountain region. A numerical scheme is developed to integrate different data types: remote sensing data (TM), gridded vegetation, soil and topographic maps at 30-m resolution in Albers projection; daily meteorological data in Changbai Mountain station in 1995, including precipitation, maximal temperature, minimal temperature, mean temperature, solar zenith angle at noon, air pressure and wind speed; diameter data from field measurement and national forest survey; data from literatures for inputs to EPPML and validation of EPPML. Vegetation index is derived from remote sensing data for estimating daily LAI and biomass at landscape scale. The information about vegetation type, soil type, elevation, slope and aspect can be derived from vegetation, soil and topographic maps. EPPML uses the biochemical model for photosynthesis of leaves developed by Farquhar et al.(1980) to simulate the rate of photosynthesis. NPP is the organic matter eliminating respiration from gross photosynthetic productivity (GPP). In addition, EPPML uses the sub-module MT-Clim in Forest-BGC to calculate total solar radiation. In EPPML, the spatial scale is 30 m and temporal scale is daily and yearly. The whole simulating process is easily understood and realized. EPPML is run and values are cumulated in each pixel. The major outputs include seasonal dynamics and spatial distributions of some carbon cycle and water cycle variables including NPP and LUE. The results indicated that the seasonal variation of LUE of vegetations in Changbai Mountain was similar to that of NPP with peak value in July (2.9%). The LUE in spring, summer, autumn and winter averaged 0.551%, 2.680%, 0.551% and 0.047% respectively. The annual LUE of all vegetation types averaged 1.075%, varying from -3.272% to 3.556%. The maximal annual LUE appeared in mixed broad-leaved and korean pine forests (1.653%), minimum in alpine grasses (0.146%), others being Changbai larch forest (1.227%), spruce-fir forest (1.019%), meadow (0.983%), broad-leaved forest (0.728%), shrub (0.478%), alpine tundra (0.442%) and Betula ermanii forest (0.298%). Though the LUE of mixed broad-leaved and korean pine forests were very high, it still had great increasing potential. In conclusion, EPPML could well and truly simulate NPP and total solar radiation of main vegetations at landscape scale in Changbai Mountain Nature Reserve. Therefore, it could well reflect the seasonal dynamic and spatial distribution of LUE. The LUE values simulated from EPPML were mostly in the range of those of Chinese forests. It indicates that we can simulate LUE of natural vegetation at the middle and large scale by model. The study supplies a gap in developing dynamic model for LUE of natural vegetation at the middle and large scale in China. However, because of lack of field survey data about LUE of different vegetation types, only limited validations were carried out in the study.