4.7 Article

Breeding together: modeling synchrony in productivity in a seabird community

期刊

ECOLOGY
卷 94, 期 1, 页码 3-10

出版社

ECOLOGICAL SOC AMER
DOI: 10.1890/12-0500.1

关键词

Bayesian analysis; breeding success; chick survival; clutch size; eastern North Atlantic seabird community; hatchability; integrative indicators; Isle of May, southeast Scotland; JAGS; long-term monitoring; marine birds; random effects

类别

资金

  1. Centre for Ecology and Hydrology
  2. EPSRC National Centre for Statistical Ecology grant
  3. Joint Nature Conservation Committee's Integrated Seabird Monitoring Programme
  4. Engineering and Physical Sciences Research Council [EP/C522702/1] Funding Source: researchfish
  5. Natural Environment Research Council [ceh010010] Funding Source: researchfish

向作者/读者索取更多资源

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.

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