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Advancing impact assessments of non-native species: strategies for strengthening the evidence-base.

Authors :
Strubbe, Diederik
White, Rachel
Edelaar, Pim
Rahbek, Carsten
Shwartz, Assaf
Source :
NeoBiota. 2019, Issue 51, p41-64. 24p.
Publication Year :
2019

Abstract

The numbers and impacts of non-native species (NNS) continue to grow. Multiple ranking protocols have been developed to identify and manage the most damaging species. However, existing protocols differ considerably in the type of impact they consider, the way evidence of impacts is included and scored, and in the way the precautionary principle is applied. These differences may lead to inconsistent impact assessments. Since these protocols are considered a main policy tool to promote mitigation efforts, such inconsistencies are undesirable, as they can affect our ability to reliably identify the most damaging NNS, and can erode public support for NNS management. Here we propose a broadly applicable framework for building a transparent NNS impact evidence base. First, we advise to separate the collection of evidence of impacts from the act of scoring the severity of these impacts. Second, we propose to map the collected evidence along a set of distinguishing criteria: where it is published, which methodological approach was used to obtain it, the relevance of the geographical area from which it originates, and the direction of the impact. This procedure produces a transparent and reproducible evidence base which can subsequently be used for different scoring protocols, and which should be made public. Finally, we argue that the precautionary principle should only be used at the risk management stage. Conditional upon the evidence presented in an impact assessment, decision-makers may use the precautionary principle for NNS management under scientific uncertainty regarding the likelihood and magnitude of NNS impacts. Our framework paves the way for an improved application of impact assessments protocols, reducing inconsistencies and ultimately enabling more effective NNS management. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16190033
Issue :
51
Database :
Academic Search Index
Journal :
NeoBiota
Publication Type :
Academic Journal
Accession number :
139578241
Full Text :
https://doi.org/10.3897/neobiota.51.35940