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. 2015 Jun 24;10(6):e0128182. doi: 10.1371/journal.pone.0128182

Table 5. Ranking of candidate models describing variables influencing daily individual abundance of Great Egrets, White Ibises, and Wood Storks in the Florida Everglades (Proc Mixed).

GREAT EGRET MODEL Kb AICcc modelid ΔAICcd wie R2
Depth A, Depth SD, Depth2, DSD SD, Reversal, Depth Use*Depth 9 797.6 12 0.00 0.44 0.35
Depth A, Depth SD, Depth2, Recess2, DSD SD, Reversal, Depth Use*Depth 9 797.6 2 0.08 0.42
Variable N Avg PE SE Importance
Intercept 27 3.176 0.54 1.00
Reversal 10 -2.482 0.44 1.00
Depth Use*Depth 11 0.005 0.00 1.00
Depth SD 9 0.268 0.05 1.00
DSD SD 9 0.005 0.00 1.00
Depth2 11 -0.003 0.00 1.00
Depth A 9 -0.109 0.04 1.00
WHITE IBIS MODEL Kb AICcc modelid ΔAICcd wie R2
Depth A, Depth SD, Depth2, Recess SD, DSD, DSD2, Reversal, Depth Use*Depth 10 888.3 4 0.00 0.75 0.31
Depth SD, Depth2, Recess SD, DSD, Reversal, DSD Use*DSD 8 891.3 11 2.98 0.17
Variable N Avg PE SE Importance
Intercept 27 2.764 0.72 1.00
DSD 13 0.008 0.00 1.00
Reversal 9 -2.946 0.66 1.00
Depth SD 9 0.336 0.10 1.00
Recess SD 11 1.590 0.63 1.00
Depth2 9 -0.003 0.00 1.00
Depth A 9 -0.167 0.08 0.87
DSD2 10 0.000 0.00 0.76
Depth Use*Depth 9 0.007 0.00 0.76
WOOD STORK MODEL Kb AICcc modelid ΔAICcd wie R2
Depth A, Depth SD, Depth2, Recess SD, Recess2, Reversal, Depth Use*Depth 9 481.1 5 0.00 0.79 0.30
Depth A, Depth, Depth SD, Depth2, Recess, Recess SD, Recess2, DSD SD, Reversal, Depth Use*Depth 12 484.9 6 3.72 0.12
Variable N Avg PE SE Importance
Intercept 27 2.794 0.39 1.00
Depth SD 11 0.141 0.38 1.00
Depth A 10 -0.114 0.03 1.00
Reversal 9 -1.471 0.58 0.99
Recess SD 9 0.907 0.48 0.98
Recess2 13 -0.338 0.13 0.98
Depth Use*Depth 9 0.003 0.00 0.94
Depth2 9 -0.001 0.00 0.94

Models are ranked by differences in Akaike’s information criterion and only candidate models within ΔAICc d ≤ 4.0 are presented. Model selection results are followed by model averaging results for each species. The R2 represents the model fit for the estimated daily individual abundance vs. model averaged predicted values.