Figure 2. Ecosystem spatial pattern modelling workflow. The sequenced workflow includes steps to: (a) incorporate field-based biotic and abiotic ecosystem response data and remotely-sensed predictors; (b) design and implement independent ecosystem, abiotic, and biotic response models; (c) select model data and assemble a site-pair table for GDM; (d) fit GDM models; (e) apply GDM model outputs to inform decision making and generate follow-up research (e.g., empirical testing). Tree and shrub graphics (Natural Resources Canada 2015); other graphics (Microsoft 365 premium creative content; Creative Commons; or original content).
classes that performed the best and top performing models were subsequently run with matrix permutation (see S1). Matrix permutation was used to cross-validate our models and to assess both model and predictor significance. Here, model significance was determined by comparing the deviance explained between permuted and unpermuted formulations (Fitzpatrick et al. 2024). Matrix permutation was implemented with backward elimination to exclude non-significant (p that included significant predictors, identified through matrix permutation. We report the outputs of the final ecosystem, biotic, and abiotic response models (see S1).