基于干扰的汪清林区森林生态系统健康评价

Abstract

以汪清林区60个林班为研究对象,提出基于干扰的森林生态系统健康评价模型H=∑B₂W₂-∑B₁W₁,构建了基于干扰理论的汪清林区森林生态系统健康评价体系。其中,有害干扰指标层选取4个指标:森林病害、森林虫害、森林火险以及人为干扰,生态系统内部的增益指标层选取4个指标:树种多样性、群落层次结构、林分更新状况以及近自然度。利用层次分析法和变异系数结合的主客观赋权法计算得到各指标的权重,提出基于干扰的健康评价模型和等级划分标准。最终评价结果显示:汪清林区60个样地中,处于优质状态的样地有6块,占总样地数的10%,健康指数均大于0.2;处于健康状态的林分13块,占总样地数的21.67%,健康指数在0.1-0.2之间;处于亚健康状态的林分23块,占总样地数的38.33%,健康指数在0-0.1之间;处于不健康的林分18块,占总样地数的30%,健康指数小于0。结果表明,在天然林中,无论是针叶纯林还是针阔混交林、阔叶混交林,大多处于亚健康和健康的状况,这与他们近自然度高,物种多样性丰富、具有良好的自我调节能力有关。而在落叶松人工林分中,由于林分物种多样性低,群落结构简单,近自然度最小,林分的增益能力弱,因此不健康的占有绝大多数。该评价结果可为该林场展开相关的健康经营措施提供参考。;Currently, the study of forest ecosystem health, a new and controversial research field within forestry and forest ecology, provides a scientific basis for forest protection. The study of forest ecosystem health also provides a significant practical service by suggesting ways to increase the level of sustainability in forest management although the definition of forest health remains controversial. The concept of health is well understood as applied to humans but the human concept of health may not be appropriate for ecosystems. The difficulties of defining the optimal conditions for ecosystem health have led to a lack of universally accepted indicators used to measure ecosystem health. Several forest ecosystem health assessment systems have already been developed. For example, ecosystem health can be assessed using measures of resilience, vigor and organization and most of today's assessment systems are based on these concepts. In this research, the forest ecosystem health of 60 sample plots in Wangqing Forest was investigated. A new assessment model of forest ecosystem health based on the disturbance, H=∑B₂W₂-∑B₁W₁, is proposed and used in this study, where <em>H</em> represents a measure of ecosystem health and <em>B</em>₁, <em>B</em>₂, <em>W₁</em> and <em>W</em>₂ represent harmful sources of disturbance, forest ecosystem stability, the weights of <em>B</em>₁ and <em>B</em>₂, respectively. Based on qualitative analysis of existing data, eight indices which were divided into two categories were selected as assessment indices of forest ecosystem health in Wangqing Forest. Several harmful sources of disturbance were considered including forest diseases, forest pest species, wildfires and human-caused disturbances. Measurements of forest ecosystem stability include measurements of biological diversity, forest community structure and measurements documenting how closely a forest study plot resembles expected natural forest conditions. These types of data have frequently been used to measure ecosystem complexity and health. Additionally, two types of analysis, the Analytic Hierarchy Process and coefficient of variation analysis, were used in combination with weighted evaluation indictors to objectively evaluate the forest health of the study plots. We propose a new forest ecosystem healthy assessment model and classification system. The 60 sample plots of Wangqing Forest were divided into four health risk categories: very healthy, healthy, fairly healthy and unhealthy. By calculating a composite value for forest health, the status of forest ecosystem health of individual Wangqing Forest plots was determined. As the results showed, 6, 13, 23 and 18 (or 10%, 21.67%, 38.33%, and 30% of all plots) plots were categorized as very healthy, healthy, fairly healthy, and unhealthy, respectively; the health indices for these four groups of plots were measured as 0.5 ≥ 0.2, 0.2 ≥ 0.1, 0 ≥ 0.1,-0.5< 0, respectively. Most of the forest plots with conditions resembling natural forest conditions, high levels of biodiversity and a strong ability to adjust to environmental change, such as pure natural forest, natural mixed needleleaf/broadleaf forest and mixed broadleaf forest, were categorized as healthy or fairly-healthy, while nearly all plantation forests plots which did not have conditions resembling natural forest conditions, but had low levels of biodiversity and a weak ability to adjust to environmental change were classified as unhealthy. This forest health assessment/indicator system establishes a scientific basis for conducting forest health analysis, provides a context for planning ecosystem restoration, and contributes to the understanding of the physical, biological, and human dimensions of these ecosystems. This research may enrich current theories and methods used in assessing the health of ecological systems.