植物生态学报 ›› 2016, Vol. 40 ›› Issue (10): 1100-1109.DOI: 10.17521/cjpe.2016.0152
所属专题: 生态系统结构与功能
郝蕊芳1, 于德永1,,A;*(), 邬建国1,2, 郭勤峰3, 刘宇鹏1
出版日期:
2016-10-10
发布日期:
2016-11-02
通讯作者:
于德永
基金资助:
Rui-Fang HAO1, De-Yong YU1,*(), Jian-Guo WU1,2, Qin-Feng GUO3, Yu-Peng LIU1
Online:
2016-10-10
Published:
2016-11-02
Contact:
De-Yong YU
摘要:
生态系统格局和过程往往受到多个因子的共同影响, 故此反映两个生态学变量相互关系的散点图常常会表现为有边界的散点云。基于数据均值或中值分析的传统统计方法不适用于散点云数据的分析。散点云所表征的不是两变量之间的相关关系, 而是限制作用关系。约束线(包络)方法为提取散点云边界、理解限制变量对响应变量的作用, 以及预测响应变量的潜在最大值提供了有效手段。该文对应用约束线方法研究生态学问题所取得的成果进行总结与归纳, 介绍了约束线概念的发展历程、提取方法, 从物种分布、种群行为及作物产量优化三个方面总结了约束线方法的优点及适用性, 概述了当前约束线方法应用研究面临的问题与挑战, 指出约束线方法应结合其他统计方法, 实现对生态过程的准确理解, 此外, 还应重视约束线方法的尺度依赖性。最后, 该文展望了约束线方法在研究生态系统服务关系和土地系统优化等方面的应用前景。
郝蕊芳, 于德永, 邬建国, 郭勤峰, 刘宇鹏. 约束线方法在生态学研究中的应用. 植物生态学报, 2016, 40(10): 1100-1109. DOI: 10.17521/cjpe.2016.0152
Rui-Fang HAO, De-Yong YU, Jian-Guo WU, Qin-Feng GUO, Yu-Peng LIU. Constraint line methods and the applications in ecology. Chinese Journal of Plant Ecology, 2016, 40(10): 1100-1109. DOI: 10.17521/cjpe.2016.0152
图1 理想状态和现实情况下测量因子与生物体响应的散点分布图(修改自Cade和Noon (2003))。
Fig. 1 The scatter diagrams showing the relationships be- tween an independent factor and organism response under the ideal (top: single causality) and more realistic situations (bot- tom: multicausality) (Adopted from Cade & Noon (2003)).
图2 邻近种群密度与生物量之间的异速自疏关系, 横坐标为种群密度的对数, 纵坐标为种群平均生物量的对数(修改自Guo等(1998))。R, 轨迹。
Fig. 2 The allometric thinning relationship between the neighborhood population density and the average biomass (Modified from Guo et al. (1998)). R, trajectory.
图3 植物组织的养分比率与某种作物相对产量的关系(修改自Sumner (1978))。
Fig. 3 Relationship between relative yield of a crop and the value of a nutrient ratio in a given tissue (Modified from Sumner (1978)).
图4 生态系统服务关系示意图(横纵坐标分别代表两种生态系统服务, 修改自Lester等(2013))。
Fig. 4 Examples of some common types of relationships between ecosystem services (Modified from Lester et al. (2013)).
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