Covariates listed here were used only on detection probability (p). For all models, cutting class was the sole covariate used on abundance and is not listed in the table.
For each of the models contrasted, degrees of freedom (df), maximum log-likelihood (-LL), AICc, AIC weight (wAICc), and the % deviation explained (%DE) are shown. Splines are natural cubic, and Polyno
Classical tests of goodness-of-fit aim to validate the conformity of a postulated model to the data under study. Given their inferential nature, they can be considered a crucial step in confirmatory d
Shown are unstandardized parameter estimates, the difference in Akaike (AIC) and Bayesian information criterion (BIC) between each model and the highest ranked model (ΔAIC and ΔBIC, respectively), and
Summary of model selection statistics for the competing models and model-averaged coefficients predicting bee abundance, diversity, and community composition as a function of land cover variables meas
