Table 2.

Significant multiple linear regression models for normally distributed alligator sightings that incorporate environmental cofactors and various measures of land use (LU) at levels of 0.1, 1, 3, and 5 km buffers surrounding each transect.

Data set	Model parameters	P	|AICc|
Spring sightings
Environmental data only	Salinity + light	0.001	0.532
	Salinity	0.004	6.094
0.1 km LU	Salinity	0.001	0.532
	Salinity + light	< 0.001	5.501
	Salinity + light + forests LU	0.004	6.094
1 km LU	Salinity + forests LU	0.001	0.805
	Salinity	0.004	6.094
3 km LU	Salinity + forests LU	0.001	0.557
	Salinity	0.004	6.094
5 km LU	Nonforested LU + salinity	0.002	1.843
	Nonforested LU + salinity + light	0.001	3.843
	Nonforested LU	0.003	5.762
Summer sightings
All data sets	Salinity	0.035	–
Average sightings
All data sets	Salinity	0.003	–

Specific data sets are outlined for spring sightings since model parameters were variable across buffer sizes. Summer and average sightings each generated one significant model with salinity as the only parameter across all LU buffer sizes. AIC_c values are used to rank spring sightings models within a data set where a smaller absolute value indicates a more parsimonious model.