Filling the Information Gap in Meta-Ecosystem Ecology

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.

Downloads

Download Preprint

Authors

Chelsea J. Little, Matteo Rizzuto , Thomas M. Luhring, Julia D. Monk , Rob Nowicki, Rachel E. Paseka, James Stegen, Celia C. Symons, Frieda B. Taub, Jian Yen

Abstract

Fluxes of matter, energy, and information over space and time contribute to ecosystems’ functioning. The meta-ecosystem framework addresses the dynamics of ecosystems linked by these fluxes, however, to date, meta-ecosystem research focused solely on fluxes of energy and matter, neglecting information. This is problematic due to organisms’ varied responses to information, which influence local ecosystem dynamics and can alter spatial flows of energy and matter. Furthermore, information itself can move between ecosystems. Therefore, information should contribute to meta-ecosystem dynamics, such as stability and productivity. Specific subdisciplines of ecology currently consider different types of information (e.g., social and cultural information, natural and artificial light or sound, body condition, genotype, and phenotype). Yet neither the spatiotemporal distribution of information nor its perception are currently accounted for in general ecological theories. Here, we provide a roadmap to synthesize information and meta-ecosystem ecology. We begin by defining information in a meta-ecological context. We then review and identify challenges to be addressed in developing information meta-ecology. Finally, we present new hypotheses for how information could impact dynamics across scales of spatio-temporal and biological organization.

DOI

https://doi.org/10.32942/osf.io/hc83u

Subjects

Ecology and Evolutionary Biology, Life Sciences, Other Ecology and Evolutionary Biology

Keywords

animal movement, Behavior, dispersal, ecosystem function, energy flux, information theory, life history, meta-community, Social information, spatial processes

Dates

Published: 2020-09-01 07:05

License

CC-By Attribution-ShareAlike 4.0 International