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Extending community trajectory analysis: New metrics and representation
Ecological Modelling ( IF 2.6 ) Pub Date : 2020-12-24 , DOI: 10.1016/j.ecolmodel.2020.109400
A. Sturbois , M. De Cáceres , M. Sánchez-Pinillos , G. Schaal , O. Gauthier , P. Le Mao , A. Ponsero , N. Desroy

Ecological research focuses on the spatio-temporal patterns of ecosystems and communities. The recently proposed framework of Community Trajectory Analysis considers community dynamics as trajectories in a chosen space of community resemblance and utilizes geometrical properties of trajectories to compare and analyse temporal changes. Here, we extend the initial framework, which focused on consecutive trajectory segments, by considering additional metrics with respect to initial or baseline states. Addressing questions about community dynamics and more generally temporal and spatial ecological variability requires synthetic and efficient modes of representation. Hence, we propose a set of innovative maps, charts and trajectory roses to represent trajectory properties and complement the panel of traditional modes of representation used in community ecology. We use four case studies to highlight the complementarity and the ability of the new metrics and innovative figures to illustrate ecological trajectories and to facilitate their interpretation. Finally, we encourage ecologists skilled in multivariate analysis to integrate CTA into their toolbox in order to quantitatively evaluate spatio-temporal changes.



中文翻译:

扩展社区轨迹分析:新指标和表示形式

生态研究的重点是生态系统和社区的时空格局。最近提出的社区轨迹分析框架将社区动态视为选定的社区相似空间中的轨迹,并利用轨迹的几何特性来比较和分析时间变化。在这里,我们通过考虑有关初始状态或基准状态的其他度量标准,扩展了针对连续轨迹段的初始框架。要解决有关社区动态以及更普遍的时空生态变异性的问题,就需要综合有效的表示方式。因此,我们提出了一组创新的地图,图表和轨迹玫瑰代表了轨迹特性,并补充了社区生态学中使用的传统表示模式。我们使用四个案例研究来强调新指标和创新数据的互补性和能力,以说明生态轨迹并促进其解释。最后,我们鼓励精通多变量分析的生态学家将CTA集成到他们的工具箱中,以便定量评估时空变化。

更新日期:2020-12-24
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