Why are generalized additive models (GAMs) so popular in ecology? As the title suggests, what is it about the nature of GAMs that make them so popular in ecology? Is it their ability to model latent variables? If so, why wouldn't they be more universally popular, since everything is affected by more than meets the eye.

TL;DR: GAMs are useful models when specific functional relationships are not hypothesized.
Ecology as a science (and like many other sciences, particularly population sciences) often has hypotheses for its statistical models which do not take specific functional forms. For example, causal relationships may be specified qualitatively in terms of direction of effect (e.g., ‘species $A$ causes a decrease in species $B$ in some trophic system,’ but perhaps not ‘$A$ causes some specified $f(B,\Theta)$’ in the way that we often encounter in physics or chemistry). GAMs are an appealing kind of model in such circumstances, because they are agnostic to the functional form relating $A$ and $B$.
