A theoretical basis for bioindication in complex ecosystems. (July 2022)

• Record Type: Journal Article
• Authors: Sperlea, Theodor; Heider, Dominik; Hattab, Georges
• Is Part Of: Ecological indicators. Volume 140(2022)
• Publication Date: 2022-07
• Subjects: Ecology -- Biomonitoring -- Ecological theory -- Information theory -- Bioindication; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2022.109050
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Develops a abstract but actionable theory of how ecological bioindicators function. Draws from information theory, semiotics, and complex systems theory. Bioindication can be descibed as second-order observation of pragmatic information. Structural coupling between indicator and the indicated can be quantified. Abstract: With increasing levels of anthropogenic stress, monitoring the state of ecosystems or their pollution levels is of growing importance. Central to this is an information transfer that results in biotic factors reflecting the ecosystem's condition or any ecosystem state variable. However, most information theories cannot describe this process as they do not apply to complex systems such as ecosystems. In this paper, we draw upon theoretical ecology, information theory, semiotics, and the study of complex systems in sociology to develop a theoretical basis for bioindication that takes the complex nature of ecosystems into account. From this follows that the relationship between the bioindicator and the variable(s) of interest in bioindication must be regarded as one of structural coupling, and biomonitoring schemes with the goal of bioindication are best described as cases of second-order observation. These theoretical results are highly relevant for the development of machine learning-based methods for bioindication.