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. 2024 Dec 30;15:10759. doi: 10.1038/s41467-024-54954-z

Table 2.

Generalized Additive Models for alpha diversity and environmental conditions

Component Term Estimate Std Error t-value p-value
A. parametric coefficients (Intercept) - Richness 4.831 0.035 137.197 <0.0001
Component Term edf Ref. df F-value p-value
B. smooth terms s(Mean σ-SST) 3.305 3.739 12.961 0.0068
s(Mean SST) 3.078 3.534 35.091 <0.0001
Adjusted R-squared: 0.152, Deviance explained 0.194 -REML: 1619.032, Scale est: 1.000, N: 178
Component Term Estimate Std Error t-value p-value
A. parametric coefficients (Intercept) - Evenness 0.696 0.030 23.033 0.0000
Component Term edf Ref. df F-value p-value
B. smooth terms s(Raft Time) 5.398 6.329 19.560 0.0037
s(Mean σ-SST) 5.325 6.200 20.353 0.0025
s(Mean SST) 2.729 3.258 6.814 0.0942
Adjusted R-squared: 0.261, Deviance explained 0.324 -REML: −277.821, Scale est: 1.000, N: 178

Results from generalized additive models for predicting richness and evenness of microbial communities associated with Durvillaea. Richness was modelled using negative binomial family, and evenness with a beta regression family. In both instances, final models were chosen based on concurvity values and AIC scores. GAMs were produced using the mgcv R package.