CONFERENCE PROCEEDINGS "DECISION MAKING AND SCIENCE"

Journal für Verbraucherschutz und Lebensmittelsicherheit

, Volume 6, Supplement 1, pp 27-31

First online:

How might science misdirect policy? Insights into the threats and consequences of invasive species

  • Martin A. SchlaepferAffiliated withInstitut National de Recherche Agronomique (INRA) Email author 
  • , Michel PascalAffiliated withInstitut National de Recherche Agronomique (INRA)
  • , Mark A. DavisAffiliated withMacalester College

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Abstract

Humans frequently introduce novel organisms (e.g., non-native species and, more recently, genetically modified organisms) into ecosystems for economic or biological purposes. However, prior to this, risk analysis is an inherent part of the decision about which species to release. In this contribution we draw upon our experience with non-native species to illustrate two ways in which science can potentially misdirect policy and management of novel organisms. The first involves scientific error, and the challenges in evaluating risk in complex systems. For example, predicting the ecological impact of an evolutionary novel organism on its proposed new ecosystem carries substantial uncertainty, which, depending on how it is explained or framed, can result in different policy outcomes. The second category involves potential biases amongst scientists. As a result of their training scientists may be inclined towards particular opinions that are not necessarily shared by the larger public. Moreover, differences in values also exist among scientists due to different cultures. Examples include a predisposition among scientists against non-native species which can result in an overstatement of perceived risks, as well as an under-appreciation of potential benefits. We illustrate how both scientific and epistemological error can result in sub-optimal policy. Scientists as experts can, and should, express their personal positions, but these should be clearly distinguished from scientific analyses.

Keywords

Exotic species Conservation Biases Policy