Hi Alex, I'm working with Strava metro to look at recreational effects on wildlife in the Cairngorms! Happy to chat more

🚨 So "How many sites do I need"? The answer = it depends on inference objective! We provide recommended minimum sample sizes for different contexts based on our simulation outputs here ⬇️ P.s. all our code is freely available on OSF, so have a play around!

Take home 4: In all scenarios, far fewer sites were needed to estimate the conditional and marginal occupancy probabilities (i.e. prediction), compared to the exact interaction term (i.e. inference)

Take home 3: Adding covariates to the model also upped the sample sizes needed to estimate interaction terms without bias 💻🌲

Take home 2: Adding more species to the models reduced the power to detect interactions of a similar strength. For example, a null model with 5 species needed 400 sites compared to 250 sites with 3 species

Take home 1: Under the simplest model structure, we needed around 200 sites to detect and estimate strong interactions without bias. These requirements increased when (1) detection probability was lower and (2) species interactions were weaker

We did an extensive simulation study to show how well the Rota et al multispecies occupancy model estimates interaction terms under different detection probabilities, interaction strengths, interaction directions (positive/negative) and model structures, from 20 to ~3000 sites