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14 December 2007 The influence of management history on spatial prediction of Eryngium spinalba, an endangered endemic species
Damien Marage, Luc Garraud, Jean-Claude Rameau(†)
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Abstract

Question: Spatial prediction of plant populations is essential for conservation management. This is especially true for rare and/or threatened endemic species, for which knowledge of determinants of distribution is necessary to mitigate threats and counteract decline. We therefore ask if the distribution of an endemic species can be accurately predicted by georeferenced environmental variables or, if anthropogenic variables also need to be taken into account.

Location: Alps, Hautes-Alpes, France.

Methods: Potential distribution area and abundance of Eryngium spinalba were predicted with logistic regression and ordinal logistic regression, respectively, in a 57-km2 watershed.

Results: Aspect, global solar radiation in March, elevation and grazing pressure were the main predictors of the probability of occurrence of Eryngium spinalba. Taking into account the persistence of agro-pastoral activities by diachronic analysis (Napoleonic cadastral map and orthorectified photographs) improved predictions from the model and the level of spatial concordance with independent surveys.

Conclusions: Niche modelling improved our understanding of the distribution of this threatened species which, in the context of land abandonment, is diminishing as a result of the decline of its favoured habitats. The key role of pastoral activities and historic continuity for its distribution and persistence was clearly demonstrated.

Nomenclature: Kerguélen & Brisse (1994).

Damien Marage, Luc Garraud, and Jean-Claude Rameau(†) "The influence of management history on spatial prediction of Eryngium spinalba, an endangered endemic species," Applied Vegetation Science 11(1), 139-148, (14 December 2007). https://doi.org/10.3170/2007-7-18337
Received: 13 November 2006; Accepted: 1 June 2007; Published: 14 December 2007
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KEYWORDS
Calcareous grassland
conservation management
Endemism
geographical information system
grazing
Land abandonment
spatial modelling
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