title: Test of a behavior-based individual-based model: response of shorebird mortality to habitat loss.
abstract: In behavior-based individual-based models (IBMs), demographic functions are emergent properties of the model and are not built into the model structure itself, as is the case with the more widely used demography-based IBMs. Our behavior-based IBM represents the physiology and behavioral decision making of individual animals and, from that, predicts how many survive the winter nonbreeding season, an important component of fitness. This paper provides the first test of such a model by predicting the change in winter mortality of a charadriid shorebird following removal of intertidal feeding habitat, the main effect of which was to increase bird density. After adjusting one calibration parameter to the level required to replicate the observed mortality rate before habitat loss, the model predicted that mortality would increase by 3.65%, which compares well with the observed increase of 3.17%. The implication that mortality was density-dependent was confirmed by predicting mortality over a range of bird densities. Further simulations showed that the density dependence was due to an increase in both interference and depletion competition as bird density increased. Other simulations suggested that an additional area of mudflat, equivalent to only 10% of the area that had been lost, would be needed by way of mitigation to return mortality to its original level. Being situated at a high shore level with the flow of water in and out impeded by inlet pipes, the mitigating mudflat would be accessible to birds when all mudflats in the estuary were covered at high tide, thus providing the birds with extra feeding time and not just a small replacement mudflat. Apart from providing the first, and confidence-raising, test of a behavior-based IBM, the results suggest (1) that the chosen calibration procedure was effective; (2) that where no new fieldwork is required, and despite being parameter rich, a behavior-based IBM can be parameterized quickly (few weeks), and thus cheaply, because so many of the parameter values can be obtained from the literature and are embedded in the model; and (3) that behavior-based IBMs can be used to explore system behavior (e.g., the role of depletion competition and interference competition in density-dependent mortality).
authors.affiliation: Centre for Ecology and Hydrology, Winfrith Technology Centre, Dorchester, Dorset DT2 8ZD, United Kingdom. j.d.goss-custard@exeter.ac.uk
authors.forename: John D
authors.initials: JD
authors.lastname: Goss-Custard
authors.forename: Niall H K
authors.initials: NH
authors.lastname: Burton
authors.forename: Nigel A
authors.initials: NA
authors.lastname: Clark
authors.forename: Peter N
authors.initials: PN
authors.lastname: Ferns
authors.forename: Selwyn
authors.initials: S
authors.lastname: McGrorty
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Reading
authors.forename: Mark M
authors.initials: MM
authors.lastname: Rehfisch
authors.forename: Richard A
authors.initials: RA
authors.lastname: Stillman
authors.forename: Ian
authors.initials: I
authors.lastname: Townend
authors.forename: Andrew D
authors.initials: AD
authors.lastname: West
authors.forename: David H
authors.initials: DH
authors.lastname: Worrall
mesh_terms: D000818:Animals; D001522:Behavior, Animal; D046091:Charadriiformes; D017753:Ecosystem; D005544:Forecasting; D008954:Models, Biological; D009026:Mortality / Q000639:trends*; D012621:Seasons