abstract
- Long-term monitoring programs can identify environmental trends or reveal limitations to protocols, as long as their results are analysed appropriately. While monitoring programs are not necessarily hypothesis-driven, their data are important for conservation and can guide improvements to monitoring programs. Here, we present a case study using dynamic occupancy models to guide the optimization of time and effort in a long-term terrestrial salamander monitoring program. To ensure a detailed analysis, we analysed the available long-term data to first identify estimates of occupancy and detection parameters for the salamanders. Using these estimates, we created simulations to identify the optimal number of years for monitoring and the optimal allocation of spatial and temporal survey replicates. Our data support previous claims that monitoring programs should be allowed to run for at least a decade. We also found that in order to obtain accurate estimates of species occupancy, programs should consider appropriate partitioning of monitoring effort across spatial and temporal scales. We show how analyses of long-term monitoring datasets are valuable not only for trend detection but also for the development of templates to guide the design and optimization of similar programs.