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

Abstract

Summary1. In order to assess the future impact of a proposed development or evaluate the cost eectiveness of proposed mitigating measures, ecologists must be able to provide accurate predictions under new environmental conditions. The diculty with predicting to new circumstances is that often there is no way of knowing whether the empirical relationships upon which models are based will hold under the new conditions, and so predictions are of uncertain accuracy. 2. We present a model, based on the optimality approach of behavioural ecology, that is designed to overcome this problem. The model's central assumption is that each individual within a population always behaves in order to maximize its ®tness. The model follows the optimal decisions of each individual within a population and predicts population mortality rate from the survival 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 ± ®tness maximization ± will not. 3. The model was parameterized and tested for a shorebird, the oystercatcher Haematopus ostralegus. Development aimed to minimize the dierence between predicted and observed overwinter starvation rates of juveniles, immatures 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 population was larger than in the model calibration years. It predicted the observed 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 densities of birds on the dierent mussel Mytilus edulis beds at low water did so with good precision. The model also predicted reasonably well (i) the stage of the winter at which the birds starved; (ii) the relative mass of birds using dierent feeding methods; (iii) the number of minutes birds spent feeding on mussels at low water during both the night and day; and (iv) the dates at which birds supplemented their low tide intake of mussels by also feeding on supplementary prey in ®elds while mussel beds were unavailable over the high water period. 5. A sensitivity analysis showed that the model's predictive ability depended on virtually all of its parameters. However, the importance of dierent parameters varied considerably. In particular, variation in gross energetic parameters had a greater in¯uence on predictions than variations in behavioural parameters. In accord with this, much of the model's predictive power was retained when a detailed foraging submodel was replaced with a simple functional response relating intake rate to Correspondence: R. A. Stillman. CEH Dorset, Winfrith Technology Centre, Winfr...

Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology

“…For example, models of fish schools and bird flocks are clearly based on multi-criteria model selection, having evolved over a long series of increasingly sophisticated field observations and simulation experiments that contrasted alternative submodels [37][38][39]. The highly predictive shorebird models of Stillman, Goss-Custard and co-workers [1,40] reproduce numerous patterns at multiple levels of organization, but these patterns have not been comprehensively listed and discussed. The following sections highlight studies illustrating the potential of POM for predictive ecology.…”

Assessment of Blue Mussel Mytilus edulis Fisheries and Waterbird Shellfish-predator Management in the Danish Wadden Sea

“…Birds can not extract all the energy available from their food intake, and digestion efficiency was estimated at 75% for the eiders, which swallow whole mussels (Nehls 1995) and 85.4% for oystercatchers, which pick out the flesh from the mussel shells (Stillman et al 2000). The latter figure was also used for herring gulls, although the species has mixed feeding patterns: swallowing whole mussels, cracking larger shells by dropping them, and acting as a kleptoparasite.…”

“…BMR for eiders and herring gulls were calculated from the allometric formula given by Lasiewski and Dawson (1967) for non-passerines, using body weights from Simmons (1977, 1983), and for oystercatchers we used values from Stillman et al (2000). DEE for eiders were calculated as 3.0 * BMR in months when water temperature was more than 15°C (May-October) and as 4.3 * BMR when it was less than 15°C (Nehls 1995).…”

“…DEE for eiders were calculated as 3.0 * BMR in months when water temperature was more than 15°C (May-October) and as 4.3 * BMR when it was less than 15°C (Nehls 1995). DEE for oystercatchers were calculated according to the formulae given by Stillman et al (2000), which correct for an increasing energy demand of 31.8 kJ day -1 for every degree that the air temperature drops below 10°C. In absence of species specific data for herring gulls, their DEE was calculated as the average value of estimates given by Drent et al, Walsberg and Nagy (Ebbinge and Weijand 1978;Walsberg 1983;Nagy 1987).…”

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“…1997 (Lomnicki 1988, Sutherland 1996 (Clemmons & Buchholz 1997) (Caro & Durant 1995, Clemmons & Buchholz 1997, Goss-Custard & Sutherland 1997, Caro 1998, Sutherland 1998) (Clemmons & Buchholz 1997, Caro 1998) (Caro 1998) 19801990(Clemmons & Buchholz 1997 1970 (Caro 1998) 2 (Lomnicki 1988, Sutherland 1996 15 (Lomnicki 1988, DeAngelis & Gross 1992, Sutherland 1996 (Sutherland 1996, Goss-Custard & Sutherland 1997 Goss-Custard (Haematopus ostralegus ostralegus) (Goss-Custard et al 1995a, 1995b, Stillman et al 2000 ostralegus Goss-Custard …”