The experiment was carried out in L. Chinensis grassland of northeast China. It simulated main quantity characteristics of yield ecology, such as biomass dynamics, vertical spatial pattern of biomass as well as their relationships with environmental factors, also it studied internal relativity. The results showed that the rule of aboveground biomass growth of the grassland appeared as “single peak” type in growing season. The maximum aboveground biomass was 1973 g ·m-2 which occurred on Aug.5, then the biomass declined. It conformed to Logistic model Ba=k(1+ea－rt) before the peak. Further analysis on related characteristic values of the model gave us a very important information parameter of yield ecology, the effective management period that should be from the 73th day to the 119th day after the grassland returnes green. During growing season, aboveground biomass dynamics had strikingly positive correlation with both average temperature of the former month (R=08287) and accumulated rainfall (R=08932). This was the important parameter to carry on scientific management of water and fertilizer.Maximum absolute growth rate of aboveground biomass occurred during June 20 and July 5, its average was 33533 g·m-2·d-1 DM (dry matter), and maximum relative growth rate (00662 g·g-1·d-1 DM) occurred during May 20 and June 5. Both absolute growth rate (AGR) and relative growth rate (RGR) appeared negative increase in late stage of growing season. It suggested that the highest efficiency of aboveground biomass be in early stage of growing season. The vertical spatial pattern of the aboveground biomass decreased as positive exponential function with height increasing, the model was: Bn=axb. The yield of the plants under 40cm height made up 93% of the total yield. This provided a basis for choosing different animal to use and mowing use. Different population of the grassland played a different role in yield formation, and positive effect of L.chinensis was the biggest . For this reason, features of height, cover-degree and density of edificato-L.chinensis were used as index to set up nondestructive model of yield prediction. It was a simple, accurate predictive method, the model was Ba=-1697343+08368H+08631D+36231C. The vertical spatial pattern of underground biomass decreased as negative exponential function with depth increasing, the model was: Bu=a(D+10)－b. The variation of underground biomass was not marked, but more or less increased in late autumn. Underground biomass of the grassland plants above 30cm depth made up 77％~82% of the total underground biomass. According to such yield ecology parameter, when ecological improvement on root system problems was considered , the depth of 0~20 cm would give good effect. The significance of the study was to obtain relative important information parameters of yield ecology in L.chinensis grassland and to provide scientific basis for establishing the best management scheme and utilizing grassland rationally.%通过对中国北方羊草草原生物量动态、生物量垂直空间格局及其与环境因子相互关系等主要产量生态数量特征的模拟与内在相关性的研究,结果表明,草地地上生物量的生长规律呈"单峰"型,最大地上生物量出现在8月5日,其值为197.3g*m-2干物质,而后下降;在达到峰值前,符合logistic模型,进一步分析模型有关特征值获得了草地有效管理期为返青后的第73天到第119天等十分重要的产量生态信息参数.生长季内地上生物量动态与前一个月的平均气温(R=0.8287)和积累降雨量(R=0.8932)均呈极显著正相关,这是实施科学水肥管理的重要参数;而地上部生物量最大绝对增长速率(AGR)出现在6月20日至7月5日,平均为3.3533g*m-2*d-1干物质;而地上部生物量最大相对增长速率(RGR)出现在5月20日至6月5日,平均为0.0662g*g-1*d-1干物质;在生长后期绝对增长速率和相对增长速率均出现负值,这表明地上部生物量的生长效率在生长初期最高.地上生物量垂直空间格局由下向上呈幂函数变化,其模型为:Bn=aXb,其中93%的产量集中在40cm以下,这对不同的家畜的选择利用与刈割利用提供了依据;不同种群对草原牧草产量形成的作用是不同的,羊草种群对草原牧草产量形成的正向效应最大,因此以建群种羊草的高度、盖度和密度特征为指标建立起来的牧草产量非破坏性预测模型,是一种简单可行、预测准确的好方法,其预测模型为:Ba=-169.7343+0.8368H+0.8631D+3.6231C;地下生物量垂直空间格局由上至下呈负幂函数变化,其模型为Bu=a(D+10)-b,而且在生长季内地下生物量的变化不明显事例是到秋后有所增加，其中在0～30cm深度中地十生物量占总地下生物量的77%～82%。根据这样的产量生态信息参数，在考虑相关根系问题的生态改良时，则深度在0～20cm即能达到良好的改良效果。该项研究的意义在于获得羊草草原有关重要的产量生态信息参数，为建立优化管理方案及合理利用草地提供科学依据。
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