非线性回归模型已应用于森林调查研究和生长量与收获量估测。s形模型可用拟算单株木或群体的生长量,或可用来获得一套特殊数据的“平均”生长曲线,这些数据通常来自临时样地。若抽样不能代表所有立地条件和年龄,则最终的生长曲线将有偏侈。显然,这种偏移很可能是小于最接近与最有价值立地的早期采伐所造成的。随着林业工作者对应用非线性方程经验的积累,对该模型的应用潜力和局限性的认识的不断加深。自 1983年以来,对非线性方程在定量林木管理中的应用和线性回归模型拟合的统一实用方法都有研究和介绍。然而,有关应用中的许多重要的实际与理论问题尚未进行全面评价。样本数据也许不能真正的描述为s形或者是不完全的s形。查普曼一理查德方程提供了最大收获量,最大年平均生长量和达到最大年平均生长量年龄的估测值。这些估测值提高了对潜在允许采伐量的理解,有利于对树种组立地级、立木度(树冠覆盖)和林分密度(相对断 Nonlinear regression models have been applied to forest surveys and to estimates of growth and harvest. The s-shaped model can be used to calculate the growth of a single tree or population of plants or to obtain a “average ” growth curve of a set of special data, usually from temporary plots. If sampling does not represent all site conditions and age, the resulting growth curve will be biased. Obviously, this shift is likely to be caused by less than the early harvesting of the nearest and most valuable site. With the accumulation of forestry workers’ experiences in applying nonlinear equations, the understanding of the potential and limitations of this model has been deepened. Since 1983, both the application of nonlinear equations in quantitative forest management and the uniform and practical methods for fitting linear regression models have been studied and introduced. However, many important practical and theoretical issues concerning applications have not yet been fully evaluated. Sample data may not really be described as s-shaped or incomplete s-shaped. The Chapman-Richard equation provides the maximum harvest, the maximum annual average growth, and the age at which the maximum annual average growth is reached. These estimates increase the understanding of the potential allowances for harvesting and are useful for assessing tree species stand level, standwood density (canopy cover) and stand density