Quantifying the impact of density, extrinsic climatic fluctuations, and demography on population fluctuations is a persistent challenge in ecology. We analyzed the effect of these processes on the irregular pattern of population crashes of Soay sheep on the St. Kilda archipelago, United Kingdom. Because the age and sex structure of the population fluctuates independently of population size, and because animals of different age and sex respond in different ways to density and weather, identical weather conditions can result in different dynamics in populations of equal size. In addition, the strength of density-dependent processes is a function of the distribution of weather events. Incorporating demographic heterogeneities into population models can influence dynamics and their response to climate change.

In studies of wild animals, one frequently encounters both census and mark-recapture-recovery data. We show how a state-space model for census data in combination with the usual multinomial-based models for ring-recovery data provide estimates of productivity not available from either type of data alone. The approach is illustrated on two British bird species. For the lapwing, we calibrate how its recent decline could be due to a decrease in productivity. For the heron, there is no evidence for a decline in productivity, and the combined analysis increases significantly the strength of logistic regressions of survival on winter severity.

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We present a survival analysis of Soay sheep mark recapture and recovery data. Unlike previous conditional analyses, it is not necessary to assume equality of recovery and recapture probabilities; instead these are estimated by maximum likelihood. Male and female sheep are treated separately, with the higher numbers and survival probabilities of the females resulting in a more complex model than that used for the males. In both cases, however, age and time aspects need to be included and there is a strong indication of a reduction in survival for sheep aged 7 years or more. Time variation in survival is related to the size of the population and selected weather variables, by using logistic regression. The size of the population signi®cantly affects the survival probabilities of male and female lambs, and of female sheep aged 7 or more years. March rainfall and a measure of the North Atlantic oscillation are found to in¯uence survival signi®cantly for all age groups considered, for both males and females. Either of these weather variables can be used in a model. Several phenotypic and genotypic individual covariates are also ®tted. The only covariate which is found to in¯uence survival signi®cantly is the type of horn of ®rst-year female sheep. There is a substantial variation in the recovery probabilities over time, re¯ecting in part the increased effort when a population crash was expected. The goodness of ®t of the model is checked by using graphical procedures.

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We describe the results of 357 experimental fires conducted in an environmentally controlled large wind tunnel. The fires were burned over a range of particle sizes, fuel bed depths, packing ratios, moisture contents and windspeeds. We find that spread rate decreases with moisture content in a way which depends on the fuel type and diameter. It decreases as the square root of the packing ratio. Fuel bed depth has little elfect on spread rate, and fuel diameter has significant effect only for diameters above I mm. The relationship between rate of spread and windspeed is virtually linear.We develop a predictive model for rate of-spread based on energy transfer considerations and the laboratory results. Other laboratory-based models for spread rate are compared with our model, and tested against the laboratory data. The other models have forms similar to ours, but do not predict our data well. Our model predicts well the spread rates for fires burned in windspeeds below 3 mlsec in other laboratories. The scale of the experiments and the similarity of the dependence on windspeed to that found in the field indicate that a field model may be developed from the laboratory model with relatively few modifications.

A simple elliptic model is developed for the spread of a fire front through grassland. This is used to predict theoretical fire fronts, which agree closely with those obtained in practice.