Ecological surveys provide data that act as the evidence-base for modern conservation. These surveys have traditionally been conducted by human observers, and the associated statistical methods developed for drawing inferences from these surveys. However, modern ecological data is often collected using a range of digital devices leading to new statistical challenges. For example, data are now commonly collected from automated devices (e.g. motion/audio-sensitive devices), via citizen science projects, drone or autonomous vehicle surveys, etc. These new data collection methods provide many statistical challenges, due to, for example, the collection of data at higher temporal resolution and over much longer periods; recorded data at different spatial and temporal resolutions (e.g. very high resolution satellite data and drone-survey data); much larger volumes of data to process; and observational data that combines signal with noise.

 

This workshop focused on developing new statistical solutions to address these new ecological data-driven challenges. In particular, the objectives of the workshop were:

 

1 To continue to build international leadership in the area of statistical ecology, and be at the cutting-edge of the development of advanced statistical techniques that utilise digital devices to gather ecological data, including automated devices, citizen science data, and the emerging area of remote sensing data.

 

2 To provide an engaging research environment to encourage cross-fertilisation of research ideas over various application areas and academic disciplines and stimulate statistical innovations.

 

3 To establish new collaborations, and strengthen existing interdisciplinary collaborations, particularly for early career researchers to enable the next generation of data scientists and statisticians to better tackle challenging data-driven questions in ecology.

 

Speaker: Koustubh Sharma, International Snow Leopard Trust