中国土地生产力变化态势是当前国内外学术界、决策界关注的焦点问题之一.介绍了土地生产力估算系统(ESLP)的原理与功能模块并利用该系统研究了中国土地生产力的变化态势.ESLP是在气温、降水、辐射水平、土壤质地等自然因素控制下,受土地利用方向与强度影响的,考虑土地系统不同的投入水平和管理措施的区域土地生产力估算系统.ESLP关注土地生产力变化的时空动态,能表达出不同投入管理水平下土地生产力的时空变化.文章应用ESLP研究了1988年和2000年中国土地生产力变化及其空间分异特征,将估算结果与1988年和2000年全国分县粮食产量数据的比较与验证表明,基于ESLP估算的各县土地生产力与各县粮食总产量具有很高的相关性,在一定程度上反映一个区域的粮食生产能力.在此基础上,应用ESLP预测了2010与2020年在气候变化情景下土地生产力的变化,预测结果显示,虽然局部地区土地生产力有小幅减少趋势,但从全国来看,土地生产力增长趋势明显.平均来看,2010年比2000年增长4.4%,而到2020年,土地生产力的增长幅度达到10.7%.不过在各个农业生态分区上,不同年份土地生产力变化差异较大,在2010年和2020年长江中下游区土地生产力均呈一定幅度的下降,而甘新区和西藏区只在2010年土地生产力有小幅下降.该研究结论对我国编制土地利用规划与粮食生产方面的决策具有重要的参考价值.%Changes in land productivity in China have been one of the foci for the scientific research and the decision making circles. This paper introduced the principle and function modules of an estimation system for land productivity (ESLP) which include the input intensity and management measures in addition to various geophysical factors such as climate, rainfall, solar radiation, soil properties, and the direction and intensity of land uses in order to estimate the land productivity in China. Considering the spa-tial-temporal dynamics of land productivity, ESLP is capable to express spatial-temporal pattern of land productivity under various kinds of management measures. ESLP is employed to estimate the land productivity at the national scale of China in this paper. Re-search results showed that, land productivity is influenced by a bunch of factors including solar radiation, air temperature, rainfall, soil properties, etc. All these factors made land productivity present with a descending trend from the south to the north in China. And because of differences of rainfall and irrigation conditions as well as terrain conditions, land productivity in the east China are higher than that in west China. Viewed from a regional perspective, changing directions and speeds of land productivity are charac-terized with an obvious spatial heterogeneity in China. Land productivities in most of ago-ecological zones of China showed an increasing trend during 1990s. Among the nine agro-ecological zones of China, there are an increase of land productivity in Ganxin district and southwest district as fast as 85.0 kg·hm~(-2)·a~(-1) and 55.4 kg·hm~(-2)·a~(-1) respectively; the following regions with higher increas-ing speeds of land productivity are south-China district and northeast district, at a speed of 52.0 kg·hm~(-2)·a~(-1) and 47.6 kg·hm~(-2)·a~(-1); speeds in Inner Mongolia, the Great Wall district, loess plateau district, Tibet district slowed down; in Yangtze River district and Huang-Huai-Hai region, the increasing speeds of land productivities are marginal. By comparing the estimated result by using ESLP and the county-level statistical data of grain production, this paper validated the accuracy of model-based estimates of land produc-tivity and found out that the model-based estimates of land productivity is closely related with the county-level statistics of grain yield. In addition to exploring the characteristics of spatial and temporal heterogeneity of land productivity in the period between 1988 and 2000 for each agro-ecological zones at national level, the paper predict changes of land productivity in the period between 2000 and 2010 and the period between 2010 and 2020 under given settings of climate changes scenarios. The prediction results illus-trated that the land productivity will continue increasing at national level in these two periods. At national level, land productivity will increase 4.4% in the period between 2000 and 2010, and the increase rate would rise to 10.7% in the period between 2010 and 2020 at the national level although there are some regions with the net loss of land productivity moderately in this period. However there are exits a spatial heterogeneity for the changes of land productivity among agroecological zones in two periods, 2000 to 2010, and 2010 to 2020. For example, model-based estimation shows that there is a dramatic decreasing trend for land productivity in Yangtze River region while a moderate decrease speed could be seen in Ganxin district and the Tibet region in the period between 2000 and 2010. Changes of land productivity with various speeds are in part due to the climate change and land use change syntheti-cally. The research results would definitely provide useful information for the policy makings of land use planning and for formula-tion of the grain production planning in China.
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