The models
Statistical analysis of imagery collected along temporally repeated transects at monitoring sites needs to account for the possibility of spatial and temporal correlation in the ecological response data. Failure to account for spatial and/or temporal correlation can lead to biases in model coefficients and confound subsequent statistical inference, often leading to underestimation of residual variance and erroneous conclusions regarding the importance of covariates (Dormann, 2007, Legendre, 1993). To test for the importance of spatio-temporal dependence, three models were fit: 1) model M 1with neither spatial nor temporal dependence, 2) modelM 2 with only spatial dependence, and 3) modelM 3 with both spatial and temporal dependence. All models included the same covariates (depth and rugosity) and were nested within the most complex model, M 3, which is described as a Bernoulli separable space-time model: