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Title: Harnessing demographic data for cross-scale analysis of forest dynamics
Author: Needham, Jessica
ISNI:       0000 0004 6497 0276
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2016
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Forests are a critical biome but are under threat from unprecedented global change. The need to understand forest dynamics across spatial, temporal and biological scales has never been greater. Critical to this will be understanding how the demographic rates of individuals translate into patterns of species diversity, biomass and carbon turnover at much larger scales. In this thesis, I present a modelling framework focussed on demography. In Chapter 2, I introduce methods for translating forest inventory data into population models that account for the size-dependency of vital rates and persistent differences in individual performance. Outbreaks of forest pest and pathogens are increasing in frequency and severity, with consequences for biodiversity and forest structure. In Chapter 3, I explore the impact of ash dieback on the community dynamics of a British woodland, describing a spatially explicit individual based model that captures the effect of an opening of the canopy on local competitive interactions. Chapter 4 introduces methods to infer the impact of historical deer herbivory on the juvenile survival of forest trees. The approach is generalisable and could be applied to any forest in which patterns of regeneration and community structure have been impacted by periodic disturbance (e.g. forest fires). Finding meaningful ways of incorporating species diversity into global vegetation models is increasingly recognised as a research priority. In Chapter 5, I explore the diversity of demographic rates in a tropical forest community and identify groups of species with similar life history strategies. I discuss the potential of integrating demographic and physiological traits as a way to aggregate species for inclusion in global models. In summary, translating measurements of individuals into population dynamics provides opportunities to both explore small-scale community responses to disturbance events, and to feed into much larger scale vegetation models.
Supervisor: Leimu-Brown, Roosa ; Metcalf, Jessica ; Hector, Andrew Sponsor: Biotechnology and Biological Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Forest ecology ; Forest dynamics ; Ash dieback ; Integral Projection Models ; Tropical trees ; Vital rates ; Demography