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作 者:景天忠[1] 李田宇 JING Tianzhong;LI Tianyu(School of Forestry, Northeast Forestry University, Harbin 150040, China)
出 处:《生态学报》2018年第10期3414-3421,共8页Acta Ecologica Sinica
基 金:国家自然科学基金项目(31370591);黑龙江省博士后科研启动金项目(LBH-Q14012)
摘 要:森林昆虫种群表现出多样的时空模式,空间同步性是其中最常见的。回顾了森林昆虫空间同步性的特点、形成机制及研究方法方面的进展。森林害虫发生的同步性是广泛存在的,但不同昆虫种类的同步性大小不同。空间同步性常随距离的增大而下降,还与时间尺度有关。Moran效应和扩散是解释空间同步性的两种主要机制,通常Moran效应的影响要比扩散大。从虫害发生数据的获取、同步性的度量及成因3个方面介绍了空间同步性的研究方法方面的进展。利用树轮生态学原理重建森林虫害发生历史的方法可在事后获取可靠的数据,很值得国内研究者借鉴和应用。在空间自相关度量上,空间统计学方法和地统计学方法都是非常有力的手段,但由于不能处理多时间点数据而限制了其在同步性研究中的应用。在同步性成因研究中,利用变异分解将基于距离的Moran特征向量图(dbMEM)作为空间变量研究害虫发生的驱动力是比较新颖的研究方法。Forest insect populations show some spatio-temporal patterns,and spatial synchrony is the most common one.The properties,causes,and study methods of spatial synchrony of forest insects are reviewed in this paper. Spatial synchrony of forest insects is ubiquitous,but varies among species. Spatial synchrony often decreases with distance,and is related to temporal scale. The Moran effect and dispersal are two of the main mechanisms that explain spatial synchrony,and the Moran effect is usually larger than that of dispersal. Research methods involved in the acquisition of pest occurrence data,the measurement and the causes of synchrony were also reviewed. The reconstructed occurrence history of forest insects using dendroecological analysis can provide reliable data many years after the occurrence,worthy of use as a reference for researchers in China. Both spatial statistics and geostatistical methods are powerful measures of spatial autocorrelation; however,they have not been applied extensively to spatial synchrony studies as they do not deal with multiple samples over a period of time. Variation partitioning,using distance-based Moran's eigenvector maps(dbMEMs) as spatial variables,is a relatively novel method to study the driver of forest insect outbreaks.
关 键 词:暴发机制 空间同步性 空间自相关 树轮生态学分析 Moran特征向量图
分 类 号:S763.3[农业科学—森林保护学]
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