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: