目的 采用青海省湟水规模化林场3种常见乔木树种桦木、杨树和青海云杉的立地形指数,通过分析其与生长域的地貌、坡向、坡度、土壤类型、土壤厚度以及年平均气温、年降雨量、年日照辐射等因子的关系,对规模化林场进行立地质量评价,构建林地质量评价综合数据库,指导林场科学造林和科学营林,发挥林地生产力和生态服务价值的目标。方法 根据建模区域范围内的一类清查数据,获取每个样地的优势高,求出该样地的立地形指数。分析立地形指数与地貌、坡向、坡度、土壤类型、土壤厚度以及年平均气温、年降雨量、年日照辐射等因子的关系,利用因子分析法选择影响立地形指数的主导因子,并建立回归模型;根据计算出的3个常见树种的立地形指数的平均值,进行聚类分析,把林地分为Ⅰ、Ⅱ、Ⅲ、Ⅳ、Ⅴ5个等级,并作出林地质量分布图;最后,根据分类结果进行了验证,并提出了相应的经营措施。结果 Ⅰ级林地3 409.37 hm²,占整个林地面积的1.39%;Ⅱ级林地38 765.07 hm²,占15.77%;Ⅲ级林地78 989.17 hm²,占32.14%;Ⅳ级林地77 102.74 hm²,占31.38%;Ⅴ级林地47 477.50 hm²,占19.32%。从整个分类结果来看,规模化林场林地质量等级较低,以Ⅲ、Ⅳ级林地为主;现场验证质量等级正确率为88%,正确率较高。结论 通过一类清查数据中的标准木、样木库、样地库获取优势高的方法可行;评价因子选择了地形因子、土壤因子、气象因子,多因子的引入使评价的结果更为客观,提高了评价的准确性;采用多树种立地指数进行综合评价,特别是对非林地的立地质量进行评价是一种更为有效的方法。

【Objective】 The site form index of three common tree species birch, poplar and Picea crassifolia in the Huangshui Large-scale Forest Farm in Qinghai Province was used to analyze the landform, aspect, slope, soil type, soil thickness, and annual average temperature, annual rainfall, annual solar radiation, and other factors of the growing area. The site quality evaluation of large-scale forest farms was carried out, and a comprehensive database of forestland quality evaluation was constructed to achieve the goal of guiding the scientific afforestation and management of forest farms and maximizing the value of forest land productivity and ecological services. 【Method】 First, according to the type of inventory data within the modeling area, the advantage of each plot was obtained, and the site form index of the plot was obtained. Following this, to analyze its relationship with landform, aspect, slope, soil type, soil thickness, annual average temperature, annual rainfall, annual solar radiation, and other factors, the factor analysis was used to select the dominant factors affecting the topographic index, and a regression model was established. According to the calculated average of the site form index of the three common tree species, the cluster analysis was carried out, and the forest land was divided into five grades: Ⅰ, Ⅱ, Ⅲ, Ⅳ and Ⅴ, and the forest land quality distribution map was prepared. Finally, according to the classification, the results were verified, and corresponding management measures were proposed. 【Result】 Grade Ⅰ forest land area was 3 409.37 hm ², accounting for 1.39% of the total forest land area; Grade Ⅱ forest land area was 38 765.07 hm ², accounting for 15.77%; Grade Ⅲ forest land area was 78 989.17 hm ², accounting for 32.14%; Grade Ⅳ forest land area was 77 102.74 hm ², accounting for 31.38%; and Grade Ⅴ forest land area was 47 477.50 hm ², accounting for 19.32%. Based on the overall classification results, the forest land quality grade of large-scale forest farms was low, mainly Ⅲ and Ⅳ forest land. The corrected rate of on-site verification quality grade was 88%, and the corrected rate was high. 【Conclusion】 It is feasible to obtain high advantages through the standard wood, sample wood bank, and sample base bank in the first type of inventory data. Following this, the topographic factors, soil factors, and meteorological factors can be selected as the evaluation factors. The introduction of multiple factors makes the evaluation results more objective and improves the accuracy of the evaluation. Using multi-tree species site form indexes for a comprehensive evaluation, especially the evaluation of site quality of non-forest land is a more effective method.