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根据森林资源监测体系的特点，将年龄隐含的生长模型应用于森林资源连续清查。这种模型不需要年龄，其误差与预测年限ΔＡ有关，当ΔＡ＝Ｏ时，误差为零。用Ｊｏｈｎｓｏｎ－Ｓｃｈｕｍａｃｈｅｒ模型作为以年龄为自变量的模型，以此模型为基础模型导出的年龄隐含模型为例进行了试验，数据为浙江省的一类连续清查数据中的１９８９～１９９４年的马尾松复位样木数据。计算例子表明，５ａ定期生长量的总和估计精度在９５％的概率保证下可达８０％以上。文章给出了模型的推导，模型的性质分析，误差及精度估计方法等。这种模型用复位样木建模，应用方便。可以以省为建模单元，一个树种（组）建一个模型，而不区分人工林、天然林，异龄林、同龄林，优势树种、组成树种，林木或散生木。
According to the characteristics of forest resource monitoring system, the age-dependent growth model is applied to the continuous inventory of forest resources. This model does not require age and its error is related to the predicted age, ΔA, and when ΔA = O, the error is zero. Using the Johnson-Schumacher model as the age-dependent model and the age-based implicit model derived from the model as an example, the data were collected from a series of continuous inventory data in Zhejiang province from 1989 to 1994 Pine reset woody data. The calculation example shows that the accuracy of the total sum of the 5 a regular growth amounts to more than 80% under the 95% probability guarantee. The article gives the derivation of the model, the nature of the model, the error and the precision estimation method. This model is modeled with resetting wood and is easy to use. You can build a model with province as modeling unit and one tree species (group), without distinction of plantation, natural forest, different age forest, same age forest, dominant species, composition tree species, forest tree or natural wood.