Bont Leo Gallus, Blattert Clemens, Rath Lioba, Schweier Janine
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Sustainable Forestry Group, Zuercherstrasse 111, CH 8903, Birmensdorf, Switzerland.
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Sustainable Forestry Group, Zuercherstrasse 111, CH 8903, Birmensdorf, Switzerland.
J Environ Manage. 2024 Dec;372:123276. doi: 10.1016/j.jenvman.2024.123276. Epub 2024 Nov 18.
Mountain forests provide not only wood as a raw material but also numerous ecosystem services, such as protection against natural hazards, recreation and carbon sequestration, and they are important hosts for biodiversity. To manage these forests efficiently and in a target-oriented manner, both forest management planning and efficient harvesting operations are required. However, in most cases these two aspects are handled independently from each other. To link planning with forest operations, it is essential to divide forests into smaller areas with characteristics that are as homogeneous as possible, so-called forest management units (FMUs). The goal is that each FMU has self-contained fine access (e.g. skid roads, cable roads), and that the FMUs can be managed and planned independently. The aim of this study was to develop a spatial optimisation model that automatically identifies FMUs. The optimisation has three goals: [I] FMUs should be as compact as possible (spatially contiguous as the best case); [II] forest management should be technically and operationally coordinated within an FMU; and [III] FMUs should be as homogeneous as possible, for example regarding site properties, ecosystem service provided, and administrative affiliation. Results showed that our presented spatial optimisation model is a capable method for automatically identifying FMUs. The approach used to set up the model based on a p-median problem formulation (mixed integer linear programming) led to clearly comprehensible solutions that can be achieved in a reasonable computation time. Three solving strategies for successful computation implementation are described. Although the raw results must be reviewed by experts, they facilitate the planning process. More scenarios can be evaluated compared with the classical manual planning approach, ultimately leading to higher-quality solutions.
山区森林不仅提供木材这种原材料，还提供众多生态系统服务，如抵御自然灾害、休闲娱乐和碳固存，并且它们是生物多样性的重要宿主。为了高效且有针对性地管理这些森林，既需要森林经营规划，也需要高效的采伐作业。然而，在大多数情况下，这两个方面是相互独立处理的。为了将规划与森林作业联系起来，必须将森林划分为尽可能同质的较小区域，即所谓的森林经营单元（FMU）。目标是每个FMU都有自成体系的良好通道（例如集材道、索道），并且FMUs可以独立管理和规划。本研究的目的是开发一种自动识别FMUs的空间优化模型。该优化有三个目标：[I] FMUs应尽可能紧凑（在空间上连续为最佳情况）；[II] 在一个FMU内，森林经营应在技术和操作上进行协调；[III] FMUs应尽可能同质，例如在立地属性、提供的生态系统服务和行政隶属关系方面。结果表明，我们提出的空间优化模型是一种自动识别FMUs的有效方法。基于p中位数问题公式（混合整数线性规划）建立模型所采用的方法产生了清晰易懂的解决方案，并且可以在合理的计算时间内实现。描述了三种成功进行计算实现的求解策略。虽然原始结果必须由专家审查，但它们有助于规划过程。与传统的人工规划方法相比，可以评估更多的方案，最终产生更高质量的解决方案。
