Abstract/Summary

Biodiversity is declining across the globe, threatening ecosystem functioning, and the services that humans rely upon. Biodiversity monitoring schemes have provided a wealth of information on population changes across space and time and are used to advise and influence environmental legislation and policy. Despite the utilisation of monitoring data, there are still gaps in the application of this data in policy making and addressing unanswered questions. This thesis focuses on using long-term monitoring data and trait datasets to develop novel methodological techniques, and further understand the key drivers of population dynamics, and our ability to detect changes in community dynamics. First, long-term population monitoring data are used to develop a novel technique to measure functional connectivity of butterflies and birds across the UK. Current methodologies to measure functional connectivity are constrained by time and data-availability. However, using a method based on correlations between species population dynamics offers a ‘species-eyed view’ of functional connectivity which can be easily updated. Second, the two key drivers of synchronised population dynamics, dispersal, and climate, are further investigated. After accounting for climate effects on population synchrony, temporal changes in population synchrony are associated with mobility-attributes of UK butterflies and birds. This represents an important contribution to the understanding of what drives spatiotemporal changes in population dynamics. For the next two chapters, the community dynamics of British birds is investigated, to determine how different functional trait approaches can affect our ability to detect community changes of functionally important birds. Extensive functional trait data alongside long-term monitoring data are used to show how different types of traits in metrics of functional diversity affect our ability to detect changes in community dynamics and ecosystem functioning. Furthermore, using traits that provide highly refined information alongside abundance data in measures of functional diversity increases our ability to predict community dynamics of functionally important birds. This work highlights the use of long-term monitoring data and functional trait approaches to further understand changes in population dynamics, in particular to develop a new method to measure functional connectivity and linking changes in functional diversity to changes in community dynamics related to ecosystem functioning. In the final chapter, the limitations of the work are discussed along with the wide range of future applications.