Our new article has been accepted in Ecological Indicator:
Sperlea T, Heider D, Hattab G: A theoretical basis for bioindication in complex ecosystems. Ecologial Indicators 2022. 140 (2022) 109050. (Link)
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.