Premise: Applied ecology can significantly influence policy decisions on environmental issues. Therefore, research in this field should be as transparent and reproducible as possible. Existing expertise from a broad range of disciplines should also be integrated into ecological research to allow researchers to maximize understanding of complex systems. Methods: We illustrate how Pearl's causality can contribute to applied ecology. We demonstrate the implications of causal diagrams for assessing the effects of anthropogenic and abiotic factors in ecological systems, using Myricaria germanica in Italian river systems as an example. In particular, we showcase the interplay between explicit causal modeling and classical statistical techniques. Results: In our example, we find that river channel width and riverbank protections are the most important factors affecting the survival of M. germanica juveniles in northern Italy. Other factors such as altitude and other human activity also impact M. germanica survival through channel width as a mediator. Discussion: We demonstrate that causal diagrams can be an effective new language for ecological research. The causal diagram highlights that integrating hydrological, historical, or anthropological data could strengthen understanding of M. germanica populations in river systems. This framework facilitates interdisciplinary research and realizes the full potential of ecological datasets.

Pearl's causality for integrating ecological datasets: A case study on Myricaria germanica in northern Italy

Sitzia, Tommaso;
2026

Abstract

Premise: Applied ecology can significantly influence policy decisions on environmental issues. Therefore, research in this field should be as transparent and reproducible as possible. Existing expertise from a broad range of disciplines should also be integrated into ecological research to allow researchers to maximize understanding of complex systems. Methods: We illustrate how Pearl's causality can contribute to applied ecology. We demonstrate the implications of causal diagrams for assessing the effects of anthropogenic and abiotic factors in ecological systems, using Myricaria germanica in Italian river systems as an example. In particular, we showcase the interplay between explicit causal modeling and classical statistical techniques. Results: In our example, we find that river channel width and riverbank protections are the most important factors affecting the survival of M. germanica juveniles in northern Italy. Other factors such as altitude and other human activity also impact M. germanica survival through channel width as a mediator. Discussion: We demonstrate that causal diagrams can be an effective new language for ecological research. The causal diagram highlights that integrating hydrological, historical, or anthropological data could strengthen understanding of M. germanica populations in river systems. This framework facilitates interdisciplinary research and realizes the full potential of ecological datasets.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3595698
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