Abstract

MILESI, Fernando A  and  LOPEZ DE CASENAVE, Javier. The niche concept in Applied Ecology: there´s many a slip twixt the reality and the niche. Ecol. austral [online]. 2005, vol.15, n.2, pp.131-148. ISSN 1667-782X.

Our objective is to analyse the use of the niche concept into what we generally call Applied Ecology. In the first place, we emphasize the problems in defining and understanding what is the niche. We go quickly through the ideas and properties that had been associated with it since its origins. The diversity of analyses, concepts and opinions make the attempts of making a tool out of the niche concept very confusing. This is mainly because the properties or theory of one "niche" cannot be extrapolated to other "niches" just because they have all used the same name for it. Secondly, we highlight the problems when trying to obtain data from reality to describe or build a niche that is useful for applied goals. We cannot assume that a "measured" niche has a consistent and applicable meaning. This can be either because the present conditions have disrupted the expected correlation between the niche and the distribution or the use of resources, or because it is already known why that association is not evidence of the potential to respond to changes. Lastly, we show some of the problems to build realistic predictive models. Many of them are connected with the fact that the niche concept carries with it a series of obsolete criteria in view of the present understanding of reality and the problems involved when trying to modify it or predict it at the usual scales of management problems. We use some examples of biological invasions, one of the subjects where the models based on the niche concept are focussed, to illustrate these problems. We conclude that all of the revised factors turn the niche concept, as used nowadays, to be inadequate for the bulk of applied aspects that pretend to be solved. It also results hardly suitable to contribute to any "ecological technology".

Keywords : Ecological theory; Predictive models; Ecological technology; Adaptive management; Biological invasions.

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