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.