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Table 2.

Urchin use of the habitat model selection and averaging. DOI: https://doi.org/10.1525/elementa.2021.00013.t2

Predictors
ModelBottom Type (% Cover)Algal Cover (% Cover)Spatial ConfigurationReef SetupΔAICaAkaike WeightsbRank
Bottom + Spatial + Setup 
SG1 BLD CAG dSND dBLD dBLOCK 4.56 0.033 
M1 BLD CAG dSND dBLD  3.92 0.045 
M2 BLD CAG dBLOCK 4.35 0.036 
M3 BLD CAG  3.04 0.070 
Bottom + Biological + Setup 
SG2 BLD CAG Algae AlgaeNeib CCA dBLOCK 0.98 0.195 3 
M4 BLD CAG Algae AlgaeNeib CCA 0.10 0.303 2 
M5 Algae AlgaeNeib CCA dBLOCK 43.00 0.000 14 
M6 Algae AlgaeNeib CCA 41.64 0.000 13 
M7 Algae CCA 46.82 0.000 15 
M8 BLD CAG Algae CCA 0.00 0.318 1 
M9 Algae CCA dBLOCK 48.43 0.000 16 
Biological + Spatial + Setup 
SG3 Algae AlgaeNeib CCA dSND dBLD dBLOCK 16.09 0.000 10 
M10 Algae AlgaeNeib CCA dSND dBLD 16.03 0.000 
M11 dSND dBLD dBLOCK 33.04 0.000 12 
M12 dSND dBLD 32.51 0.000 11 
M13 Algae CCA dSND dBLD 15.05 0.000 
M14 dBLOCK 104.79 0.000 17 
Predictors
ModelBottom Type (% Cover)Algal Cover (% Cover)Spatial ConfigurationReef SetupΔAICaAkaike WeightsbRank
Bottom + Spatial + Setup 
SG1 BLD CAG dSND dBLD dBLOCK 4.56 0.033 
M1 BLD CAG dSND dBLD  3.92 0.045 
M2 BLD CAG dBLOCK 4.35 0.036 
M3 BLD CAG  3.04 0.070 
Bottom + Biological + Setup 
SG2 BLD CAG Algae AlgaeNeib CCA dBLOCK 0.98 0.195 3 
M4 BLD CAG Algae AlgaeNeib CCA 0.10 0.303 2 
M5 Algae AlgaeNeib CCA dBLOCK 43.00 0.000 14 
M6 Algae AlgaeNeib CCA 41.64 0.000 13 
M7 Algae CCA 46.82 0.000 15 
M8 BLD CAG Algae CCA 0.00 0.318 1 
M9 Algae CCA dBLOCK 48.43 0.000 16 
Biological + Spatial + Setup 
SG3 Algae AlgaeNeib CCA dSND dBLD dBLOCK 16.09 0.000 10 
M10 Algae AlgaeNeib CCA dSND dBLD 16.03 0.000 
M11 dSND dBLD dBLOCK 33.04 0.000 12 
M12 dSND dBLD 32.51 0.000 11 
M13 Algae CCA dSND dBLD 15.05 0.000 
M14 dBLOCK 104.79 0.000 17 

Models selected for averaging are in bold (ΔAIC < 2). Subglobal models are named “SG.” AIC = Akaike information criterion; BLD = boulder; CAG = cobble and gravel; AlgaeNeib = neighboring foliose algae; CCA = crustose coralline algae; dSND, dBLD, dBLOCK = distance to sand, boulder, block, respectively.

aDifference between AIC of a given model and the AIC of the best model.

bRatio of the ΔAIC of a given model relative to the whole set of candidate models. Higher scores indicate the probability that the model is the best among the whole set of candidate models (Mazerolle, 2006).

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