<p>The response variables (RV; FPT, maximum dive depth (MDD), dive duration (DD, surface duration (SuD)) were investigated in relation to geographic location (GL), bottom depth (BD), month (M) and TCI. The behavioural models included FPT as a predictor variable (P). Loglik is the loglikelihood, K is the number of parameters in the model. AIC<sub>i</sub> is AIC for model i, and ΔAIC is the difference between the AIC of the best fitting model and that of model i. Exp(−0.5Δ<sub>i</sub>) represent the relative likelihoods and the w<sub>i</sub> is the Akiake weight. D.E (%) is the deviance explained by the model. Tables showing all candidate models are presented in the supplementary material (<a href="http://www.plosone.org/article/info:doi/10.1...
<p>Model with best fit for each analysis highlighted (bold).</p><p>AIC: Akaike's Information Criteri...
Time series plot of maximum depth (MD), duration of dive (DT), and post-dive duration (PD) from dive...
<p>All variables included in linear predictor are significant (*p<0.05, **p<0.01, ***p<0.001). R<sup...
<p>Predicted results for a) FPT (h), b) Month (blue columns represent approximate fasting periods), ...
<p><b>Notes–</b><i>Wi = </i> Akaike weight; <i>K</i> = number of parameters; Max dive depth = h...
<p>Generalised Additive Models which best fitted (estimated using Δ BIC) daily temperature at the bo...
<p>Candidate models which best fitted the standardized residuals obtained from the multiple linear r...
For diving animals, animal-borne sensors are used to collect time–depth information for studying beh...
<p>BIC and BIC weight of Linear Mixed Effect models (LME’s) which best fitted average dive depth, du...
<p>The strip-charts in the left column represent time vs depth (cf. <a href="http://www.plosone.org/...
<p>LL: Maximum Log Likelihood, df: degrees of freedom, dAICc: difference of AICc of a given model to...
1<p>p: number of parameters in the model.</p>2<p>ΔAIC: difference in AIC value between best fitting ...
<p>SFT1 = surface feeding tactic I, SFT2 = surface feeding tactic II, NSF = near-surface foraging, D...
<p>Number of crawling individuals (per 0.25×0.25 m quadrat) was log transformed to improve normality...
<p>The first section (above solid line) compares a fixed-effect only model with a mixed model, which...
<p>Model with best fit for each analysis highlighted (bold).</p><p>AIC: Akaike's Information Criteri...
Time series plot of maximum depth (MD), duration of dive (DT), and post-dive duration (PD) from dive...
<p>All variables included in linear predictor are significant (*p<0.05, **p<0.01, ***p<0.001). R<sup...
<p>Predicted results for a) FPT (h), b) Month (blue columns represent approximate fasting periods), ...
<p><b>Notes–</b><i>Wi = </i> Akaike weight; <i>K</i> = number of parameters; Max dive depth = h...
<p>Generalised Additive Models which best fitted (estimated using Δ BIC) daily temperature at the bo...
<p>Candidate models which best fitted the standardized residuals obtained from the multiple linear r...
For diving animals, animal-borne sensors are used to collect time–depth information for studying beh...
<p>BIC and BIC weight of Linear Mixed Effect models (LME’s) which best fitted average dive depth, du...
<p>The strip-charts in the left column represent time vs depth (cf. <a href="http://www.plosone.org/...
<p>LL: Maximum Log Likelihood, df: degrees of freedom, dAICc: difference of AICc of a given model to...
1<p>p: number of parameters in the model.</p>2<p>ΔAIC: difference in AIC value between best fitting ...
<p>SFT1 = surface feeding tactic I, SFT2 = surface feeding tactic II, NSF = near-surface foraging, D...
<p>Number of crawling individuals (per 0.25×0.25 m quadrat) was log transformed to improve normality...
<p>The first section (above solid line) compares a fixed-effect only model with a mixed model, which...
<p>Model with best fit for each analysis highlighted (bold).</p><p>AIC: Akaike's Information Criteri...
Time series plot of maximum depth (MD), duration of dive (DT), and post-dive duration (PD) from dive...
<p>All variables included in linear predictor are significant (*p<0.05, **p<0.01, ***p<0.001). R<sup...