Trajectory analysis in community ecology

Abstract

Ecologists have long been interested in how communities change over time.Addressing questions about community dynamics requires ways of representing and compar-ing the variety of dynamics observed across space. Until now, most analytical frameworks havebeen based on the comparison of synchronous observations across sites and between repeatedsurveys. An alternative perspective considers community dynamics as trajectories in a chosenspace of community resemblance and utilizes trajectories as objects to be analyzed and com-pared using their geometry. While methods that take this second perspective exist, for exampleto test for particular trajectory shapes, there is a need for formal analytical frameworks thatfully develop the potential of this approach. By adapting concepts and procedures used for theanalysis of spatial trajectories, we present a framework for describing and comparing commu-nity trajectories. A key element of our contribution is the means to assess the geometric resem-blance between trajectories, which allows users to describe, quantify, and analyze variation incommunity dynamics. We illustrate the behavior of our framework using simulated data andtwo spatiotemporal community data sets differing in the community properties of interest(species composition vs. size distribution of individuals). We conclude by evaluating the advan-tages and limitations of our community trajectory analysis framework, highlighting its broaddomain of application and anticipating potential extensions.

We thank anonymous reviewers of previous versions of this manuscript for their constructive comments. We acknowledge the use of Craigieburn forest data drawn from the New Zealand National Vegetation Survey databank for this study. We thank R. Foster, R. Pérez, S. Aguilar, S. Lao, S. Dolins, and hundreds of field workers for the BCI census work, now over 2 million tree measurements; the National Science Foundation, Smithsonian Tropical Research Institute, and MacArthur Foundation for the bulk of the financial support. M. De Cáceres was supported by projects CGL2014-59742-C2-2-R and CGL2017-89149-C2-2-R (Spanish Ministry of Economy and Competitiveness) and by a Spanish “Ramon y Cajal” fellowship (RYC-2012-11109). S. K. Wiser was supported by the Strategic Science Investment Fund of the New Zealand Ministry of Business, Innovation and Employment's Science and Innovation Group. M. De Cáceres and L. Coll conceived the idea; M. De Cáceres developed the methods and conducted the data analyses; P. Legendre, R. B. Allen, S. K. Wiser, R. Condit, and S. Hubbell provided data for examples and helped in the interpretation of results; M.-J. Fortin and P. Legendre contributed to frame the contribution within a broader context; M. De Cáceres, L. Coll, P. Legendre, R. B. Allen, M.-J. Fortin, and S. K. Wiser contributed to manuscript writing.