Predicting mortality in novel environments: tests and sensitivity of a behaviour-based model

1. In order to assess the future impact of a proposed development or evalua te the cost effectiveness of proposed mitigating measures, ecologists must be able to provide accurate predictions under new environmental conditions. The difficulty with predicting to new circumstances is that often there is no way of knowing whether the empirical relationships upon which models ar e based will hold under the new conditions, and so predictions are of uncer tain accuracy. 2. We present a model, based on the optimality approach of behavioural ecol ogy, that is designed to overcome this problem. The model's central assumpt ion is that each individual within a population always behaves in order to maximize its fitness. The model follows the optimal decisions of each indiv idual within a population and predicts population mortality rate from the s urvival consequences of these decisions. Such behaviour-based models should provide a reliable means of predicting to new circumstances because, even if conditions change greatly, the basis of predictions - fitness maximizati on - will not. 3. The model was parameterized and tested for a shorebird, the oystercatche r Haematopus ostralegus. Development aimed to minimize the difference betwe en predicted and observed overwinter starvation rates of juveniles, immatur es and adults during the model calibration years of 1976-80. The model was tested by comparing its predicted starvation rates with the observed rates for another sample of years during 1980-91, when the oystercatcher populati on was larger than in the model calibration years. It predicted the observe d density-dependent increase in mortality rate in these years, outside the conditions for which it was parameterized. 4. The predicted overwinter mortality rate was based on generally realistic behaviour of oystercatchers within the model population. The two submodels that predicted the interference-free intake rates and the numbers and dens ities of birds on the different mussel Mytilus edulis beds at low water did so with good precision. The model also predicted reasonably well (i) the s tage of the winter at which the birds starved; (ii) the relative mass of bi rds using different feeding methods; (iii) the number of minutes birds spen t feeding on mussels at low water during both the night and day; and (iv) t he dates at which birds supplemented their low tide intake of mussels by al so feeding on supplementary prey in fields while mussel beds were unavailab le over the high water period. 5. A sensitivity analysis showed that the model's predictive ability depend ed on virtually all of its parameters. However, the importance of different parameters varied considerably. In particular, variation in gross energeti c parameters had a greater influence on predictions than variations in beha vioural parameters. In accord with this, much of the model's predictive pow er was retained when a detailed foraging submodel was replaced with a simpl e functional response relating intake rate to mussel biomass. The behaviour al parameters were not irrelevant, however, as these were the basis of pred ictions. 6. Although we applied the model to oystercatchers, the general principle o n which it is based applies widely. We list the key parameters that need to be measured in order to apply the model to other systems, estimate the tim e scales involved and describe the types of environmental changes that can be modelled. For example, in the case of estuaries, the model can be used t o predict the impact of habitat loss, changes in the intensity or method of shellfishing, or changes in the frequency of human disturbance. 7. We conclude that behaviour-based models provide a good basis for predict ing how demographic parameters, and thus population size, would be affected by novel environments. The key reason for this is that, by being based on optimal decision rules, animals in these models are likely to respond to en vironmental changes in the same way as real ones would.