| Reference: |
HIROYUKI YOKOMIZO, HUGH P. POSSINGHAM, MATTHEW B. THOMAS, AND YVONNE M. BUCKLEY Managing the impact of invasive species: the value of knowing the density-impact curve Ecological Applications, 19(2), 376-386, 2009. |
| Abstract | Economic impacts of invasive species worldwide are substantial. Management strategies have been incorporated in population models to assess the effectiveness of management for reducing density, with the implicit assumption that economic impact of the invasive species will also decline. The optimal management effort, however, is that which minimizes the sum of both the management and impact costs. The relationship between population density and economic impact (what we call the "density-impact curve") is rarely examined in a management context and could take several nonlinear forms. Here we determine the effects of population dynamics and density-impact curves of different shapes on optimal management effort and discover cases where management is either highly effective or a waste of resources. When an inaccurate density-impact curve is used, the increase in total costs due to over -- or under investment in management can be large. We calculate the increase in total costs incurred if the density-impact curve is incorrect and find that the greater the maximum impact caused by an invasive species, the more important it is not only to reduce its density, but also to know the shape of the density-impact relationship accurately. Lack of information regarding the relationship between density and economic impact causes the most acute problems for invaders that cause high impact at low density, where management typically will be too little, too late. For species that are only problematic at high density, ignorance of the density-impact curve can lead to over investment in management with little reduction in impact. |
| Acknowledgement | This work was supported by a Grant-in-Aid for Scientific Research of JSPS to H. Yokomiizo and by the Australian Research Council's "Discovery Projects" funding scheme (project number DP0771387) grant to Y. M. Buckley and additional ARC grants to H. P. Possingham. We thank Peter Baxter, Peter Brown, Céline Clech-Goods, John Dwyer, Jennifer Firn, Niels Hintzen, Andy Sheppard, and two anonymous referees for helpful comments. |
| Scores | TUIGF:100% SNHNSNDN:100% GIGO:100% |
This article does not deal with Info-Gap decision theory as such. Nevertheless, it is on my list to illustrate how the misconceptions about Info-Gap decision theory are disseminated in various disciplines, in this case applied ecology.
The complete reference to Info-Gap decision theory in this article is as follows (page 384, emphasis is mine):
An extension of the current study would be to determine the optimal management effort under uncertainty of the density-impact curve by, for example, assuming a probability distribution for the parameters of the density-impact relationship or information-gap decision theory (Ben-Haim 2001). Information-gap decision theory derives the most robust management option to meet a minimum performance requirement under severe uncertainty (Ben-Haim 2001, Regan et al. 2005).
Sounds great, doesn't it?
So, if this is your introduction to Info-Gap decision theory, you may interpret this reference to Info-Gap decision theory as follows:
An article in a refereed journal in the area of applied ecology describes Info-Gap decision theory as a theory that "... derives the most robust management option to meet a minimum performance requirement under severe uncertainty ...". This allows me to refer to Info-Gap in my research work and articles as the theory that actually delivers these goods, citing the above references as "proof".
No wonder then that Info-Gap decision theory is used uncritically in the areas of applied ecology and conservation biology. More on this can be found in my Decision Point articles (2008, issue 22, issue 24), in my online Call for the Reassessment of the Use and Promotion of Info-Gap Decision Theory in Australia, and in my article
| Info-Gap decision theory and the small applied world of environmental decision-making |
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