Evaluating Forest Site Quality Using the Biomass Potential Productivity Approach

Site quality evaluation involves an assessment of the stand productivity potential of a forest stand with a certain method adopted, which is a necessary theoretical basis for the full utilization of the productive potential of the land and achieving scientific management of forest resources [1]. Since the 1920s, site type and site quality assessments have been receiving widespread attention [2]. So far, significant theoretical and technical progress has been made within research on forest site quality evaluation, and many evaluation methods have been proposed, such as the index plant method [3,4], the site index method [5,6], the growth index method [7,8,9], and the advanced exponential method [10]. On the one hand, traditional forest site quality evaluation is mainly aimed at plantation forests. For natural forests with a complex stand structure, an irregular matching of tree height class, age structure, and other factors, the method of forest site quality evaluation could be difficult to meaningfully unity [11]. On the other hand, the current research methodology assesses only the realistic growth of the forest, which essentially reflects the real productivity of the stand. In contrast, it is difficult for forest sites to reach maximum productivity under natural conditions, as there could be disturbances caused by human and natural factors. Researchers have attempted to accurately evaluate forest quality by constructing ecological models, but data acquisition (climate, soil, etc.) problems increase the difficulty of subsequent large-scale applications [12,13]. The remote sensing approach, which helps identify and distinguish the stand features (species composition and structure, etc.) is also commonly applied for site quality assessment [14]. However, the results can be substantially affected by the environment and accuracy. The existing methods of site quality evaluation are still limited in practice, and thus, we need a comprehensive method that is suitable for evaluation of site quality on a large scale.

For assessing forest site quality on a large-scale, data availability is the basis for developing forest quality indicators. Since forest biomass is a major driver of forest structure and diversity, its accumulation or decrease determines the forest site quality, and hence, forest biomass can be used as a reliable indicator of site productivity [15,16,17,18]. Accurate computation of forest biomass productivity and its dynamics can have a reference value, which can be used for forest development, management, and utilization, and such an estimate may also solve the ecological problems [19,20,21]. The forest site quality depends on the forest and growth potential [22]. Biomass potential productivity (BPP) is the maximum annual biomass growth that can be achieved at a given stand age for the given site type and stand type [23].

To overcome the difficulties mentioned above, this study assumes that under the same site conditions and stand type (similar species composition) with a similar stand structure and stand density, there would be an approximately similar growth in the stand height, stand basal area, and stand biomass. Based on the concept of basal area potential productivity and volume potential productivity, this study proposes a biomass potential productivity that is applicable to multi-aged and multi-layered mixed forests [24,25]. The methods of forest site quality evaluation presented in this study can provide practical guidance for scientific forest management [26,27]. The ninth national forest resources inventory in the Jilin Province, which is one of the key provinces for forest development in China [28], shows that the forest area is 7.85 million hectares, and the standing volume is 101.296 million cubic meters. Thus, scientific evaluation of forest site quality in the Jilin Province is conducive to raising social awareness of improvements to the current state of forests. Forest site quality evaluation in the Jilin Province is considered very important, as this helps improve the prediction performance of future stand productivity and can also lay the methodological foundation for effective forest management strategies, the sustainable development of China’s future forest ecosystems, and achieving carbon neutrality. This study aims to (1) propose a new forest site quality evaluation index: biomass potential productivity; (2) provide detailed computational methods of biomass potential productivity; (3) demonstrate the application of the computational methods using real data of the larch and Mongolian oak in the Jilin Province as an example; and (4) verify and validate the proposed methods and models. The methods and models proposed in this paper will provide both theoretical and practical knowledge that will be useful for forest site quality evaluation—one of the necessary informational inputs for scientific forest management.