项目名称: 流域景观格局对河流大型底栖动物的影响研究
项目编号: No.41501204
项目类型: 青年科学基金项目
立项/批准年度: 2016
项目学科: 天文学、地球科学
项目作者: 张海萍
作者单位: 中国水利水电科学研究院
项目金额: 24万元
中文摘要: 流域尺度景观格局变化对河流水生生物的影响研究是目前生态学关注的热点和前沿,对流域管理、河流生物多样性保护都具有重要的意义。在传统的“景观格局—河流大型底栖动物”关系研究中,格局定量化描述最常采用的指标为流域不同景观类型面积百分比,忽略了景观单元在空间上的距离衰减效应,因为即使是同一景观类型,景观单元由于空间位置不同,对河流的影响程度也将不同。本研究基于高精度遥感数据、水文分析等多种手段,采用3种不同的距离衰减函数,分别构建流域尺度景观指数。采用多元回归等统计方法,分析景观格局与底栖动物(分类单元数、敏感性、摄食类群)之间的关系,获得对底栖动物群落结构解释能力最强的景观格局指数,识别影响底栖动物的关键景观类型,揭示景观单元的距离衰减规律。基于筛选出的景观指数,结合河段尺度环境因子(水质、底质组成、粗颗粒有机质),分析“流域景观格局—河段尺度因子—底栖动物”的影响路径。
中文关键词: 景观格局;景观单元;景观类型;生态过程;大型底栖动物
英文摘要: The impacts of landscape pattern changes on river organisms is the a topic of river ecology. These researches are important for watershed management and river biodiversity protection. In the previous studies, area percent of landscape pattern was the widely used indicator. These indicators rarely considered the spatial weighting which was calculated using distance-decay functions. For the same landscape pattern, the spatial location has impacts on the influence degree of landscape pixel on river ecosystems. Based on high resolution remote sensing data, we used three distance-decay functions to calculate watershed-scale landscape indicators. Using multivariate statistical regression model, the key landscape pattern indicators can be identified to indicate macroinvertebrate attributes, including taxa, sensitivity and feeding groups. The distance-decay function from the key landscape pattern indicators can identify the distance-decay effect of landscape pixels. Reach-scale indicators are used to analysis the impact pathways depicting linkages among watershed landscape pattern, reach-scale indicator and macroinvertebrate attributes.
英文关键词: landscape pattern;landscape cell;lanscape type;ecological process;macroinvertebrate