Summary and reflection

A brief review of this module

Take a minute to reflect on what you’ve just learnt

In this module we looked at how to incorporate covariates into our distance sampling models, to test hypotheses on which environmental variables affect density and detectability

We discovered how to interpret coefficients in biological terms

🤔 Reflection: Minute questions

A sketch of a confused cartoon tiger

Ruby Wang, CC BY-SA 3.0, via Wikimedia Commons

Take one minute to reflect on and answer the following questions

Further resources

So far, we’ve only considered linear effects and additive combinations of factors.  It’s also possible to model:

  • Non-linear effect such as a curved response, for example where medium vegetation cover promotes high densities, but low/high cover reduces density
  • Interactions between variables, where the effect of one variable depends on the level of another variable, e.g. reed-cutting only affects density in small marshy patches, not larger wetlands
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