Ecosystem, Abiotic, and Biotic Responses – Overview of Models
The final ecosystem, abiotic, and biotic response models explained,
41.4, 29.03, and 50.9 percent of deviance in observed dissimilarity.
These values are consistent with those in published generalized
dissimilarity models (Mokany et al. 2022) (see S1 for detailed model
overviews). Matrix permutation tests, employed to cross-validate model
performance, revealed all three formulations were statistically
significant, with p-values ranging from 0.04 to < 0.01. The
three models were each fit with relatively low numbers of predictors,
ranging from 4 to 8 (Table 1).
The final ecosystem response model had six significant predictors (Table
1), including leaf area index, softwood basal area, canopy height,
normalized vegetation difference index, hardwood basal area, and terrain
ruggedness. The strongest predictors were biotic (jointly explaining
41.31% of deviance), and much of the variation in dissimilarity was
accounted for by leaf area index (19.72%) and softwood basal area
(11.55%). Terrain ruggedness was the only abiotic predictor making a
significant, albeit minor (1.55%), contribution to model fit.
Terrain ruggedness, depth-to-water, canopy height, and geographic
distance were significant predictors in the final abiotic model (Table
1). Two of these predictors were abiotic (jointly explaining 23.14% of
deviance), with terrain ruggedness making the most important
contribution (12.81%). Overall, the most influential biotic predictor
was canopy height (5.46%). Among the significant predictors, geographic
distance had the lowest strength (<1%).
Table 1. Summary of the relative contribution of predictors
employed in the ecosystem, abiotic, and biotic response models. For each
model, individual predictor coefficient sums are reported, while the
proportion of total deviance in dissimilarity, explained by each
predictor, is in parentheses. Predictors with higher values, have
greater importance, for each given model. The three most important
predictors per model are bolded; predictor types are distinguished by
font colour: green (biotic), brown (abiotic), and black (geographic
distance). Only those significant (p <0.05) predictors retained
after matrix permutation with backward elimination (Fitzpatrick et al.
2024) are shown. Predictor data and acronyms are described in S1.