Seabird populations are considered an important and accessible indicator of the health of marine environments: variations have been linked with climate change and pollution , as well as changes in fish stock levels. However, manual monitoring of large populations is labour-intensive, and so necessarily limited in scope. In this paper we present work currently being conducted as a pilot to develop computer vision as a means of automatically monitoring nesting birds. The long-term objective is to provide ecology researchers with behavioural data on a scale not currently available. We begin by describing the context and objectives for our work, which are centred around on-going manual monitoring of a specific population of Common Guillemots on Skomer Island, West Wales (UK). Thi
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