Designing drone surveys for N-mixture models

Performance and optimal design of N-mixture models for spatiotemporally replicated drone-based surveys

 

This website is provided as a supplementary material of the manuscript Optimally designing drone surveys for wildlife abundance modeling with N-mixture models, Brack I.V., Kindel A., Oliveira L.F.B., Lahoz-Monfort J.J. 2021.

 

In that study, we explore, in a very wide scan study with several scenarios, the performance and optimal survey effort allocation for hierarchical N-mixture models, focusing on their application for drone-based surveys. We also investigate the use of a double observer protocol in image reviewing to decompose the detection process in availability and perception.

We specifically addressed three aspects:

1. optimal design of count surveys for N-mixture abundance estimation
2. exploring the benefit of the double-observer protocol
3. reducing fieldwork effort by employing a double-observer protocol

This website contains:

• a basic explanation of the required sampling design and (binomial and multinomial) N-mixture models
• an interactive tool to run single examples with customizable scenario and survey - design
• visualize the simulation results on the performance and optimal survey design for predefined scenarios

 

Code (R) to reproduce the same results or explore other scenarios are available at the GitHub repo.
We also provide code to fit the models with the unmarked R package using maximum likelihood estimation and JAGS code for Bayesian analysis.

For more details of the simulation study, check the paper!