A new era for ERA? Using Bayesian Network Models to improve ERA, with Jannicke Moe

Credit: antishock – stock.adobe.com

“Not difficult, just different,” is how one author in the latest IEAM podcast describes Bayesian Network models (BNs) to researchers that are unfamiliar with—and often intimidated by—them. A recent special series aims to dispel the esoteric aura that surrounds this approach by showing how BNs have improved ecological risk assessments in the past 20 years, with the goal of encouraging more practitioners to employ BNs and continue evolving the practices of ERA and environmental management. The Guest Editors of the series are Jannicke Moe, John Carriger, and Miriam Glendell.

Guest Editor Jannicke Moe talks to us about advantages of BNs, recent developments, and highlights the research presented in the series—10 articles demonstrating the application of BNs to various environmental assessment and management scenarios involving climate change, ecological and socioeconomic endpoints, machine learning, diagnostic inference, and model evaluation.

Listen on iTunes or YouTube.

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From individuals to populations: Assessing endocrine impacts of pesticides, with Mark Crane

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Starling murmuration. Credit: Airwolfhound, CC BY-ND 2.0.

The European Commission recently proposed to protect vertebrate wildlife using hazard-based approaches for regulating pesticides with endocrine-disrupting properties. Researchers are familiar enough with using lab-based studies to test whether chemicals cause adverse effects in the usual animal models, but how do we identify those substances that will have adverse effects at the population level? Mark Crane and co-authors present an approach for evaluating protection goals for these compounds based on population responses within an ecosystem services framework. Read More »