摘要
评价了三峡库区兰陵溪流域257个小班的森林生态系统健康水平,为林地小班的空间对位配置和结构调整提供理论依据。构建植被结构、生态服务和生态环境等3项一级指标,林龄结构、郁闭度、灌木层盖度等16项二级指标,利用物元模型和二类调查数据评价兰陵溪流域小班尺度的森林生态系统健康水平。结果表明:综合评价等级为"优良"的小班有83个,占32.30%;"一般"的小班有115个,占44.75%;"较差"的小班有59个,占22.96%;土壤有机质密度、郁闭度与小班综合生态系统健康水平呈极显著正相关(P<0.01),裸岩率、土壤孔隙度与小班生态系统健康水平相关性显著(P<0.05)。植被类型间差异明显,小班综合生态系统健康水平排序为:阔叶林、乔灌林>针叶林>经济林;通过可拓变换,在单项指标评价的基础上,物元模型综合评价信息更为丰富,评价结果更为客观,物元模型适用于小班生态系统健康水平的评价。
This paper aims to offer theory on the spatial contraposition allocation and land-use structural adjustment in Lanlingxi watershed in Three Gorges area. With the data collected from forest inventory survey and obtained from Forest Ecological Station in Three Gorges area （Zigui） of Yangtze River, an indicator system including three level indicators （i.e. vegetation structure, ecological service and ecological environment） and 16 secondary indicators （i.e. forest age structure, canopy density, shrub layer coverage, etc.） were selected to assess forest ecosystem health level based on matter-element model and forest subcompartment scale. The numbers of subcompartments with the integrated assessment grades of “better”, “normal” and “poor” were 83, 115 and 59, accounting for 32.30%, 44.75% and 22.96% of total subcompartments, respectively. An extremely significant positive relationship existed between forest ecosystem health level and soil organic matter density, canopy density （P〈0.01）, and a significant correlation was found between forest ecosystem health level and bare rock rate, soil porosity. The forest ecosystem health level for the different vegetation types was in order of broadleaf forest, arbor and shrub forest 〉 coniferous forest 〉 economic forest. With extension transformation, the matter-element model can provide more information of every single index, therefore, it is suitable to assess the forest ecosystem health level.
出处
《生态学杂志》
CAS
CSCD
北大核心
2017年第5期1458-1464,共7页
Chinese Journal of Ecology
基金
国家科技支撑计划项目(2015BAD07B04)资助
关键词
兰陵溪流域
林地
物元模型
小班尺度
生态系统健康
评价
Lanlingxi watershed
forest land
matter-element model
subcompartment scale
ecosystem health
assessment.
