MOESM3 of Environmental influence on the seasonal movements of satellite-tracked ocean sunfish Mola mola in the north-east Atlantic

Additional file 3: Table S2. Relative importance of each variable to the final model. Step-wise models were generated excluding each variable at a time and deviances were calculated informing on the significance of each parameter to the full model (deviance, AIC, Δdeviance, ΔAIC, p value, relative l...

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Bibliographic Details
Main Authors: Sousa, Lara, Queiroz, Nuno, Mucientes, Gonzalo, Humphries, Nicolas, Sims, David
Format: Report
Language:unknown
Published: Figshare 2016
Subjects:
Molecular Biology
Physiology
FOS Biological sciences
39999 Chemical Sciences not elsewhere classified
FOS Chemical sciences
Ecology
Sociology
FOS Sociology
69999 Biological Sciences not elsewhere classified
Marine Biology
Inorganic Chemistry
110309 Infectious Diseases
FOS Health sciences
North East Atlantic
Online Access:https://dx.doi.org/10.6084/m9.figshare.c.3607028_d5.v1
https://springernature.figshare.com/articles/journal_contribution/MOESM3_of_Environmental_influence_on_the_seasonal_movements_of_satellite-tracked_ocean_sunfish_Mola_mola_in_the_north-east_Atlantic/4350554/1
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Summary:Additional file 3: Table S2. Relative importance of each variable to the final model. Step-wise models were generated excluding each variable at a time and deviances were calculated informing on the significance of each parameter to the full model (deviance, AIC, Δdeviance, ΔAIC, p value, relative likelihood and wAIC). Clearly, gradients of SST and SST were the most influent variables providing the highest % of significant variability explained (Δdeviance) and both features had the lowest wAIC if removed.

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