Table 3.
Best supported and competing models (using binomial and positive models) for Funiculina quadrangularis.
| Model | Depth | Slope | Rugosity | AspectNS | AspectEW | CurrentNS | CurrentWE | SBT | SBS | Fishing effort | ΔAIC | AICw | Adj-R2 | Dev % | rs | ROC AUC | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Best model | Binomial | ##### | ##### | ##### | ##### | ##### | 0 | 0.08 | 0.16 | 15.6 | 0.29 *** | 0.77 | |||||
| Positive | ##### | ##### | ##### | ##### | ##### | ##### | ##### | ##### | 0 | 0.07 | 0.61 | 64.9 | |||||
| Competing m1 | Binomial | ##### | ##### | ##### | ##### | ##### | ##### | 0.5 | 0.06 | 0.15 | 15.6 | — | — | ||||
| Competing m2 | Binomial | ##### | ##### | ##### | ##### | ##### | ##### | 1.13 | 0.04 | 0.15 | 15.5 | — | — | ||||
| Competing m3 | Binomial | ##### | ##### | ##### | ##### | ##### | ##### | ##### | 1.39 | 0.03 | 0.15 | 15.5 | — | — | |||
| Competing m4 | Binomial | ##### | ##### | ##### | ##### | ##### | ##### | 1.78 | 0.03 | 0.15 | 15.5 | — | — | ||||
| Competing m5 | Binomial | ##### | ##### | ##### | ##### | ##### | ##### | ##### | 1.89 | 0.03 | 0.15 | 16.2 | — | — | |||
| Competing m6 | Binomial | ##### | ##### | ##### | ##### | ##### | ##### | 1.93 | 0.03 | 0.15 | 15.5 | — | — | ||||
| Competing m1 | Positive | ##### | ##### | ##### | ##### | ##### | ##### | ##### | ##### | 0.96 | 0.04 | 0.60 | 63.3 | — | — | ||
| Competing m2 | Positive | ##### | ##### | ##### | ##### | ##### | ##### | ##### | 1.25 | 0.03 | 0.59 | 61.9 | — | — | |||
| Competing m3 | Positive | ##### | ##### | ##### | ##### | ##### | ##### | ##### | ##### | 1.25 | 0.03 | 0.59 | 62.2 | — | — | ||
| Competing m4 | Positive | ##### | ##### | ##### | ##### | ##### | ##### | ##### | ##### | ##### | 1.45 | 0.02 | 0.60 | 63.9 | — | — | |
| Competing m5 | Positive | ##### | ##### | ##### | ##### | ##### | ##### | 1.7 | 0.02 | 0.58 | 61.4 | — | — |
Variables included in model are indicated with the symbol #. Predictors include depth, slope, rugosity, aspectNS, aspectEW, CurrentNS, CurrentWE, sea bottom temperature (SBT), sea bottom salinity (SBS) and fishing effort. ΔAIC: delta AIC (difference in AIC between the best model and current model); AICw: Akaike’s Information Criteria (corrected) weights, values range from 0 to 1, and high values indicate strong support for a given predictor. Models were evaluated by R2-adjusted coefficient and deviance (Dev): percentage of deviance explained. Only for the binomial model the Receiver Operating Characteristic (ROC) and Area Under the Curve (AUC) were calculated. Significance value of the Spearman’s correlation coefficient (rs) (corrected for spatial autocorrelation) for the delta model is given as ***p value < 0.001, **p value < 0.01, *p value < 0.05.