Thesis icon

Thesis

Harnessing demographic data for cross-scale analysis of forest dynamics

Abstract:

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.

Actions


Access Document


Files:

Authors


More by this author
Division:
MPLS
Department:
Plant Sciences
Department:
Plant Sciences
Role:
Author

Contributors

Department:
Plant Sciences
Role:
Supervisor
Department:
Plant Sciences
Role:
Supervisor
Department:
Princeton University
Role:
Supervisor


DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford


Language:
English
Keywords:
Subjects:
UUID:
uuid:156850fa-3148-45a6-b2f8-ada9dd3f6a7f
Deposit date:
2017-04-09

Terms of use



Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP