4.5 Article

Extending community trajectory analysis: New metrics and representation

Journal

ECOLOGICAL MODELLING
Volume 440, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.ecolmodel.2020.109400

Keywords

Ecological variability; Impact assessment; Initial state; Community dynamics; Trajectory analysis; Representation tools

Categories

Funding

  1. Agence de l'eau Loire-Bretagne [180212501]
  2. Region Bretagne [OSIRIS PFEA621219CR0530023]
  3. Europe for the European maritime and fisheries fund [FEAMP 621-B]
  4. Ministere de la transitionecologique et solidaire [2102930123]

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The paper introduces a new framework for analyzing community dynamics and expands it by incorporating additional metrics related to initial states. It proposes using innovative maps, charts, and trajectory roses to represent ecological trajectories and enhance their interpretation. The authors urge ecologists skilled in multivariate analysis to integrate this Community Trajectory Analysis into their toolbox to quantitatively evaluate spatio-temporal changes.
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.

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