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Ahead of statistical analyses, data had been thinned in order to a-1 s interval, complimentary the latest temporal quality from which relevant reaction parameters (age.g., TBC and VV) was basically calculated.
(2016) and Andrzejaczek et al. (2019a). For each shark, mean TBC was calculated over 15 min windows, and then related to time since release (TSR) as the predictor. An exploratory generalized additive mixed model (GAmM, “mgcv” package; Wood, 2011) suggested an asymptotic relationship between these variables (p < 0.001). Thus the effect of TSR on mean TBC was quantified using a non-linear self-starting asymptotic mixed model (“nlme” package; Pinheiro et al., 2020) with an individual random effect on the asymptote (Asym), initial (R0) and natural log of rate constant (lrc) coefficients to allow for individual variability in recovery patterns (Whitney et al., 2016), and a first-order autoregressive [AR(1)] correlation structure to accommodate within-individual temporal autocorrelation. Model fit was assessed via diagnostic plots (fitted vs. normalized residuals plots, Q-Q plots and normalized residual recensioni solo incontri sobrio autocorrelation plots). The TBC recovery period was then calculated at the population and individual level (using random effect coefficients) as the time taken for the TBC to increase 80% of the difference between its initial (R0) and predicted asymptotic (Asym) value (Whitney et al., 2016).
To explore factors influencing TBC-derived recovery periods, several candidate generalized linear models (GLM) were then fit (“stats” package; R Core Team, 2020) with individual sharks’ recovery periods as the response variable, a gamma error (recovery periods were non-negative, continuous, and positively skewed) and inverse link, and varying combinations of sex, FL and capture duration (total time from hooking until release of the shark) as predictors. (далее…)