9:30 – 10:00 PM – moosecounter: A Shiny desktop application for adaptive moose surveys in the Yukon Territory, Canada

Managing wildlife populations requires knowledge about the distribution and abundance of species. To gather information needed to determine hunting quotas for Moose, the Yukon Government runs annual surveys. However surveying large areas with helicopters is costly ($2.5 M spent over the last decade), therefore, we developed an adaptive sampling design to get the most accurate population size estimates while being as cost efficient as possible. Adaptive surveys require biologists to analyze data daily which is then used to inform the next day’s flight route. Such analyses are conducted in remote areas and are best served by software with a straightforward GUI that does not rely on an unpredictable Internet connection. We first made an rJava based Deducer plugin, which became unmaintainable after R 4.0. Thus we turned the plugin into a Shiny app. In this talk I will share the evolution of the project over the last decade, how technology choices were made, and the impact these had on the Moose monitoring program. The Shiny app includes upload/download functionality to fit with the geospatial workflow. It contains steps for data exploration and modelling for total moose abundance and population composition (cows, calves, bulls). It also has options to scrutinize predictions and associated uncertainty, which in turn informs the survey design. Shiny has become an indispensable tool for bringing custom statistical workflows to a large scale field program. We hope our experiences and the open source software we created can help similar initiatives worldwide.