三种判定落叶阔叶混交林土壤损害基线的方法研究——以吉林省抚松县为例

生态环境损害鉴定评估是生态系统修复与保护管理工作的基础，而生态环境损害基线作为一个地区生态水平原始状态的表征，是鉴定评估生态环境损害的基准。森林土壤是森林生态系统的重要组成部分，是维系森林生态系统生物及化学循环的关键部分，同时也是森林生态系统是否受到损害及损害程度大小的重要表征指标。在已有的生态环境损害基线判定方法的基础上，针对森林土壤的特点，改进森林土壤损害基线的判定方法并用这些方法对吉林省长白山抚松县地区落叶阔叶混交林进行研究。运用的3种方法包括群体分布法、三分位法和回归模型法。计算结果显示，运用三分位法确定的基线值最高，运用群体分布法确定的基线值最低。从方法的适用范围考虑，群体分布法和三分位法计算简便，结果可比性强，适用于无明显人为干扰的地区；回归模型法灵活度高，应用性广，适用于有较强人为干扰的地区；在数据充足的情况下应首选回归模型法，在回归模型法无法确认基线时，另外两种方法作为补充。

Study on three methods to determine the soil damage baseline of deciduous broad-leaved mixed forests: A case of Fusong County in Jilin Province

The assessment of ecological damage is the basis of ecosystem protection and recovery management. Representing an original ecological level in a region, an ecosystem damage baseline is foundational in defining the degree of ecological damage. Forest soil is a key element in maintaining the chemical cycle of forest ecosystems and is also an important characterization factor in identifying the degree of damage in an ecosystem. Based on the systematic analysis of existing methods for ecological damage baselines and the characteristics of forest soil, this paper suggests several improvements to existing methods for forest soil damage baselines. We evaluated the Changbai Mountain area''s deciduous broad-leaved mixed forest in Fusong County of Jilin Province as the case study. Three methods-the population distribution method, the trisection method, and the regression model method-were applied in this study. Results showed that these methods can be used successfully in determining the soil damage baseline. The baseline value determined by the trisection method was the highest while the baseline value by population distribution method was the lowest. The calculation steps for the population distribution and trisection methods were easy with results having strong comparability, and these methods were suitable in areas without substantial anthropogenic disturbance. Regression models had higher flexibility and wider application in practice. This method would be preferred in areas with sufficient data or that have experienced significant anthropogenic disturbance. If the regression model was not feasible, the other two methods could be utilized instead.