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. 2020 Apr 23;15(4):e0231732. doi: 10.1371/journal.pone.0231732

Table 2. Comparison of 9 additive and interactive linear mixed-effects models fit independently for ocelots and bobcats.

Model Main effects df Species AIC Δ AIC BIC logLik
1 SunAlt 5 Ocelot 98458 290 98502 -49224
Bobcat 37303 46 37341 -18646
2 MoonIlluminatedFrac 5 Ocelot 110042 11874 110086 -55016
Bobcat 38008 751 38046 -18999
3 TMAX 5 Ocelot 110042 11874 110086 -55016
Bobcat 37999 741 38037 -18994
4 SunAlt + MoonIlluminatedFrac 6 Ocelot 98460 292 98512 -49224
Bobcat 37305 48 37351 -18646
5 SunAlt + TMAX 6 Ocelot 98370 202 98422 -49179
Bobcat 37300 43 37346 -18644
6 SunAlt + MoonIlluminatedFrac + TMAX 7 Ocelot 98372 204 98433 -49179
Bobcat 37302 45 37356 -18644
7 SunAlt * MoonIlluminatedFrac 7 Ocelot 98461 293 98522 -49224
Bobcat 37305 48 37358 -18645
8 SunAlt * TMAX 7 Ocelot 98178 10 98239 -49082
Bobcat 37259 1 37312 -18622
9 SunAlt * MoonIlluminatedFrac * TMAX 11 Ocelot 98168 0 98264 -49073
Bobcat 37257 0 37341 -18618

Inclusion of variables as additive terms without interaction is indicated by “+” in the Main effects column. Inclusion of an interaction term between independent variables is indicated by “*” in the Main effects column. Models were ranked according to AIC, with the model displaying the lowest AIC per species considered the top model. Bayesian Information Criterion (BIC) and log likelihood (logLik) are included for comparison purposes. All models included individual ID and “Type” (i.e., True Velocity or Predicted Velocity) as random effects. A first-order autoregressive structure was incorporated into all models to account for temporal autocorrelation in the data sets.