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Assessing mercury exposure to aquatic ecosystems of the Mackenzie watershed using a Bayesian Network analysis

Description: Additional data to support the publication under the same name. Includes partial data from Hg monitoring datasets, the datasets and code (in R) used to define some conditional probability tables in Bayesian network model, and the spatial datasets reported in the Supplemental Figures files.
Authors: Jermilova, Una; Trent University; ORCID iD 0009-0003-5407-1824
Hintelmann, Holger; Trent University; ORCID iD 0000-0002-5287-483X
Keywords: Risk assessment
Arctic
Mercury
Aquatic ecosystem
Bayesian network
Field of Research: 
Environmental engineering and related engineering
>
Environmental engineering
>
Environmental impacts
Publication Date: 2024-05-28
Publisher: Federated Research Data Repository / dépôt fédéré de données de recherche
Funder: Arctic Contaminants Action Program (ACAP); Mercury Risk Evaluation, Risk Management and Risk Reduction Measures in the Arctic (ARCRISK); 190204
URI: https://doi.org/10.20383/103.0957
Related Identifiers: 


This dataset is derived from


This dataset is derived from

This dataset is derived from

This dataset is derived from


This dataset is derived from

This dataset is derived from

This dataset is derived from

This dataset is derived from

This dataset is derived from

This dataset is derived from


This dataset is derived from

This dataset is derived from

Geographic Coverage: 
Place Name
Mackenzie River Basin
Province /
Province / Territory
Northwest Territories
Territory
 
Country
Canada
Geolocation Box: 
West Longitude
-142.455284
East Longitude
-105.0517673
North Latitude
69.1330261
South Latitude
58.1673976

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Access to this dataset is subject to the following terms:
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0) https://creativecommons.org/licenses/by-nc-sa/4.0/
Citation
Jermilova, U., Hintelmann, H. (2024). Assessing mercury exposure to aquatic ecosystems of the Mackenzie watershed using a Bayesian Network analysis. Federated Research Data Repository. https://doi.org/10.20383/103.0957