Por favor, use este identificador para citar o enlazar a este item:
Compartir / Impacto:
|Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL|
Keystone species: a restored and operational concept to inform marine biodiversity conservation
|Autor:||Valls, Audrey; Coll, Marta ; Christensen, Villy|
|Fecha de publicación:||10-nov-2014|
|Citación:||Fisheries Centre Research Reports 22(3): 54-55 (2014)|
Ecopath 30 Years Conference Proceedings: Extended Abstracts: 54-55 (2014)
|Resumen:||The metaphorical terminology of ‘keystone species’ was introduced in aquatic food web ecology by R.T. Paine (1969). Variations in the keystone species abundance or activity would have greater impacts on biodiversity and trophic structure, compared to other coexisting species with similar or higher abundance in the ecosystem (Paine 1969). Since Paine’s analogy, the concept of keystone species rapidly expanded, as it was applied to an ever-growing number of aquatic and terrestrial species, playing a wide variety of critical roles in the ecosystem (Paine 1995; Power and Mills 1995; Power et al. 1996). In our approach, we extricated the keystone species concept of all overlapping concepts describing other ecologically important species, and we defined a keystone species as a species characterized by a high and wide impact on its food web, despite a low biomass. Two alternative indices measuring the potential for being a keystone species, or ‘keystoneness’ (KS), have been implemented in the Ecopath with Ecosim software (Christensen et al. 2008). The first index was proposed by Libralato et al. (2006), and the second one was adapted from a methodology proposed by Power et al. (1996). Both indices were applied to several modeled food webs, but led to inconsistent results in terms of species identified as potential keystone ones (e.g., Coll et al. 2013; Tecchio et al. 2013). In our study, we intended to explain and overcome the limitations of the existing functional KS indices. We derived a new functional index estimating species keystoneness from a meta-analysis on a selection of food web models. 101 Ecopath models, representative of the variety of marine ecosystems worldwide, were selected with a scoring method. A suite of KS indices, comprising new and existing ones, were formulated, by combining measures of the Mixed Trophic Impact (Ulanowicz and Puccia 1990) and biomass. The 12 KS indices were applied to the 101 selected models, and the identified keystone species were recorded. Two statistical methods were used to select the new KS index: Spearman rank correlation tests and a classification tree, in which ecosystem-specific thresholds were defined.The selected KS index was shown to be more balanced than the ones previously proposed in the literature and implemented in Ecopath, thus attributing high keystoneness to species having both low biomass and high trophic impact. Species were ranked according to their estimates of keystoneness with the selected KS index, so that potential keystone species were quantitatively identified in the 101 modeled food webs, and compared across models. Cartilaginous fishes and toothed whales obtained the highest occurrences over all models. Keystone species, by maintaining the food web structure of their community, are critical species, which play an important ecological function, performed by few other species in the ecosystem (Perry 2010). The identification of functionally important species, such as keystone species, not only helps developing effective conservation strategies for species-level prioritization, but also better understanding ecosystem functioning and processes (Jordán 2009; Clemente et al. 2010)|
|Descripción:||Conference and workshops Ecopath 30 years – Modelling ecosystem dynamics: beyond boundaries with EwE, 4-14 November 2014, Barcelona, Spain.-- 2 pages|
|Versión del editor:||http://ewe30.ecopathinternational.org/proceedings/|
|Aparece en las colecciones:||(ICM) Artículos|
Ficheros en este ítem:
No hay ficheros asociados a este ítem.
Mostrar el registro completo
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.