Breeding together: modelling synchrony in productivity in a seabird community

Lahoz-Monfort, Jose J. and Morgan, Byron J. T. and Harris, Michael P. and Daunt, Francis and Wanless, Sarah and Freeman, Stephen N. (2013) Breeding together: modelling synchrony in productivity in a seabird community. Ecology, 94 (1). pp. 3-10. ISSN 0012-9658 . (doi:https://doi.org/10.1890/12-0500.1) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Official URL
http://dx.doi.org/10.1890/12-0500.1

Abstract

With environmental conditions changing rapidly, there is a need to move beyond single-species models and consider how communities respond to environmental drivers. We present a modeling approach that allows estimation of multispecies synchrony in productivity, or its components, and the contribution of environmental covariates as synchronizing and desynchronizing agents. We apply the model to long-term breeding success data for five seabird species at a North Atlantic colony. Our Bayesian analysis reveals varying degrees of synchrony in overall productivity, with a common signal indicating a significant decline in productivity between 1986 and 2009. Productivity in seabirds reflects conditions in the marine ecosystem so the estimated synchronous component is a useful indicator of local marine environment health. For the two species for which we have most data, the environmental contribution to overall productivity synchrony is driven principally by effects operating at the chick stage rather than during incubation. Our results emphasize the importance of studying together species that coexist in a community. The framework, which accommodates interspecific clutch-size variation, is readily applicable to any species assemblage in any ecosystem where long-term productivity data are available.

Item Type: Article
Uncontrolled keywords: Bayesian analysis; breeding success; chick survival; clutch size; hatchability; integration indicators; Isle of May, southeast Scotland; JAGS; long-term monitoring; marine birds; eastern North Atlantic seabird community; random effects.
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Q Science > QH Natural history > QH541 Ecology
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science
Depositing User: Byron Morgan
Date Deposited: 18 Jan 2013 14:24 UTC
Last Modified: 02 Jun 2014 11:23 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/33031 (The current URI for this page, for reference purposes)
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