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Sustainability Science

, Volume 11, Issue 2, pp 179–192 | Cite as

Coupling fishery dynamics, human health and social learning in a model of fish-borne pollution exposure

  • Michael YodzisEmail author
  • Chris T. Bauch
  • Madhur Anand
Original Article
Part of the following topical collections:
  1. Concepts, Methodology, and Knowledge Management for Sustainability Science

Abstract

Pollution-induced illnesses are caused by toxicants that result from human activity and are often entirely preventable. However, where industrial priorities have undermined responsible governance, exposed populations must reduce their exposure by resorting to voluntary protective measures and demanding emissions abatement. This paper presents a coupled human–environment system model that represents the effects of water pollution on the health and livelihood of a fishing community. The model is motivated by an incident from 1949 to 1968 in Minamata, Japan, where methylmercury effluent from a local factory poisoned fish populations and humans who ate them. We model the critical role of risk perception in driving both social learning and the protective feedbacks against pollution exposure. These feedbacks are undermined in the presence of social misperceptions such as stigmatization of the injured. Through numerical simulation and scenario analysis, we compare our model results with historical datasets from Minamata, and find that the conditions for an ongoing pollution epidemic are highly unlikely without social misperception. We also find trade-offs between human health outcomes, the viability of the polluting industry and the survival of the fishery. We conclude that an understanding of human–environment interactions and misperception effects is highly relevant to the resolution of contemporary pollution problems, and merits further study.

Keywords

Human–environment interactions Social learning Pollution abatement Misperception effects Trade-offs 

Notes

Acknowledgments

We give special thanks to Dr. Akiko Satake and her student Keita Honjo for their stimulating discussions. The first author thanks the Ontario Graduate Scholarship program for financial support, and the second author thanks the Natural Sciences and Engineering Research Council of Canada.

Supplementary material

11625_2015_317_MOESM1_ESM.pdf (249 kb)
Supplementary material 1 (pdf 250 KB)

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Copyright information

© Springer Japan 2015

Authors and Affiliations

  1. 1.Department of Mathematics and StatisticsUniversity of GuelphGuelphCanada
  2. 2.Department of Applied MathematicsUniversity of WaterlooWaterlooCanada
  3. 3.School of Environmental SciencesUniversity of GuelphGuelphCanada

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