Spatial random effects

[lcgodoy]

Spatial random effects are extremely important in Ecology as they may mimic the sum of different important processes.

A quick way to include spatial random effects to our model is by using the code from Morris et al. 2019 to define ICAR and BYM priors for random effects.

Then, the code need to be slightly adjusted because we have many observations per site across time (as opposed to a spatial only dataset).

[mpinsky]

We should also consider random effects in the context of causal inference and omitted variable bias: https://onlinelibrary.wiley.com/doi/10.1111/ele.70023 (and so, whether random effects are a good idea depends on the modeling goal)