Developing Rigorous Monitoring Programs: Power and Sample Size Evaluations of a Robust Method for Monitoring Bird Assemblages

Abstract

Abstract Wildlife population monitoring programs are useful for identifying ecological impacts such as those from local management actions and broader scale influences such as climate change. Increasing the number of species monitored improves robustness of the program towards meeting monitoring objectives. In addition, monitoring at multiple spatial scales should increase the sensitivity of the monitoring program. We developed a monitoring program using unbiased estimates of occupancy at both local and regional scales, and unbiased estimates of density for multiple species of birds with a single protocol. We used transects for sampling ∼1,000-ha pastures that consisted of twelve 200-m radius sampling points. We conducted 10-min point counts and recorded distance to each observation using two independent observers, and resampled each of 30 transects over two study sites in South Texas, for a total of four visits in each of 2015 and 2016. We estimated occupancy at two scales using the multiscale model in Program MARK and estimated density using the Distance package in R. We predicted that it would be possible to detect a 50% decline over 25 y with a power of 0.90 in regional occupancy, local occupancy, and density for 36, 37, and 30 species, respectively, on our larger study site, and for 29, 33, and 12 species, respectively, on our smaller study site using two independent observers and four visits. Our work shows it is possible to monitor numerous species within a complex bird assemblage with a simple field protocol. For those interested in implementing a long-term monitoring program that is sensitive to a wide range of potential stressors at local and regional scales, we suggest considering multiscale occupancy and density monitoring for multiple species of birds.