TABLE 3.

Statistics for models from CCA^a

Transformation	Sensitivity (FU)	Model	Σλi	Trace	ARISA-env (%)
Presence or absence	50	Region, LP, May, temp, Secchi, pH	0.347	2.419	54.4
	100	Region, LP, May, temp, Secchi, pH, DOC	0.437	2.674	47.8
	150	Region, LP, May, July, Oct, Secchi, pH, DOC	0.490	2.979	47.6
	200	Region, LP, May, July, Oct, Secchi, pH, DOC, TP	0.586	3.181	45.85
Semiquantitative	50	Region, LP, May, temp, Secchi, pH	0.799	4.419	58.6
	100	Region, LP, May, temp, Secchi, pH	0.816	4.527	58.6
	150	Region, LP, May, temp, Secchi, pH	0.837	4.675	58.6
	200	Region, LP, May, temp, Secchi, pH	0.860	4.799	58.6
Partial		May, temp, Secchi, pH	0.393	4.799	63.1
Quantitative	50	Region, LP, May, temp, Secchi, pH, DOC, DN, DP	0.994	4.031	42.8
	100	Region, LP, May, temp, Secchi, pH, DOC, DN, DP	1.003	4.077	42.8
	150	Region, LP, May, temp, Secchi, pH, DOC, DN, DP	1.020	4.166	42.8
	200	Region, LP, May, temp, Secchi, pH, DOC, DN, DP	1.039	4.238	42.7
Partial		May, temp, Secchi, pH, DOC, DN, DP	0.629	4.238	41.1

^aTransformation refers to whether peak data from ARISA profiles were used quantitatively, semiquantitatively, or as presence or absence only. Only peaks exceeding the reported sensitivity fluorescence cutoffs were analyzed. Model, environmental variables included in the analysis following forward selection with sequential Bonferroni adjustments applied for significance. Underlined terms were determined to be significant in all 12 models. Partial CCA models used region and LP as covariables. Σλ_i is the sum of all canonical eigenvalues; trace is the sum of all eigenvalues (Σλ_i/trace = proportion of variance of ARISA peaks explained by the model). ARISA-env refers to the fraction of the ARISA fragment-environment relationship explained by the first two CCA axes (see Fig. 5 and 6).