Resurrecting Shannon's surprise: landscape heterogeneity complements information use and population growth

Autor: Kenneth A. Schmidt, Francois Massol, Jakub Szymkowiak
Přispěvatelé: Centre d’Infection et d’Immunité de Lille - INSERM U 1019 - UMR 9017 - UMR 8204 (CIIL), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Centre National de la Recherche Scientifique (CNRS)
Rok vydání: 2022
Předmět:
Zdroj: Oikos
Oikos, 2022, 2022 (10), pp.155102. ⟨10.1111/oik.09305⟩
ISSN: 1600-0706
0030-1299
DOI: 10.1111/oik.09305
Popis: International audience; Shannon's information (H) has two meanings: information and surprise (Shannon's original term.) This terminology characterizes the dual nature of H: 1) a reduction in uncertainty, and 2) heterogeneity, the enabler of surprise, for there is no information in a heterogeneity continuously homogeneous world. Embracing the dual nature of information/heterogeneity produces common ground between behavioral ecology and its sister fields: landscape, population, community and evolutionary ecology. In particular, we explore connections between variance and heterogeneity in resources distributions within landscapes and how such heterogeneity facilitates or hinders individuals' to be informed and utilize the appropriate tail of a resource distribution, and the consequences thereof. We examine both short-and long-term consequences of two scenarios informed breeding habitat selection (site fidelity and conspecific prospecting). We emphasize two main conclusions: 1) the ecological role of heterogeneity to enhance the ability to discriminate between options (poor versus good breeding sites) in ecological time, and 2) how landscape heterogeneity feedbacks on the evolution information use when populations are small to ameliorate negative consequences of global change.
Databáze: OpenAIRE
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