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Title: Climate variation, plant productivity, herbivore performance and population dynamics
Author: Bento, Ana Isabel Ramos
ISNI:       0000 0004 2732 4232
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2012
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Prediction is one of the hardest things in ecological science. Predicting the weather is one of the hardest things of all. This is what makes predicting the ecological consequences of climate change so exceptionally demanding. As a first step, we would like to understand the effects of weather variation on the behaviour of those ecological systems for which we have the best long-term data. The Park Grass Experiment at Rothamsted allows us to model the effects of the timing of rainfall and the accumulation of day-degrees in spring on primary productivity in an ungrazed grassland. I use the insights gained from this model to interpret the effects of weather variation in two classic long-term studies of plant-herbivore interactions: the Red Deer on Rum and the Soay Sheep on St Kilda. In both cases, direct effects of extreme weather on animal populations (“killing weather”) turn out to be much less important than weather-driven changes in plant production. Because most of the important effects of weather on animal population dynamics act via changes in food availability, it is the interaction between weather and population density that matters more than anything else, rather that weather effects alone. The same weather that would lead to mass starvation at high population densities, might have no measurable impact on animal performance when numbers were low. The analysis is focused on the following questions: which weather variables are most important; when do they have their most important effects; what effect sizes do they generate; and what is the shape of the relationship between the weather variable and the ecological response variable? The answers to these questions will help to guide subsequent analyses of demography and genetics on these two Hebridean Island systems.
Supervisor: Crawley, Mick Sponsor: Natural Environment Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral