Movement rules for individual-based models of stream fish

Spatially explicit individual-based models (IBMs) use movement rules to det ermine when an animal departs its current location and to determine its mov ement destination; these rules are therefore critical to accurate simulatio ns. Movement rules typically define some measure of how an individual's exp ected fitness varies among locations, under the assumption that animals mak e movement decisions at least in part to increase their fitness. Recent res earch shows that many fish move quickly in response to changes in physical and biological conditions, so movement rules should allow fish to rapidly s elect the best location that is accessible. The theory that a fish's fitnes s is maximized by minimizing the ratio of mortality risk to food intake is not applicable to typical IBM movement decisions and can cause serious erro rs in common situations. Instead, we developed fitness measures from unifie d foraging theory that are theoretically and computationally compatible wit h individual-based fish models. One such fitness measure causes a fish to s elect habitat that maximizes its expected probability of survival over a sp ecified time horizon, considering both starvation and other risks. This fit ness measure is dependent on the fish's current state, making fish with low energy reserves more willing to accept risks in exchange for higher food i ntake. Another new measure represents the expectation of reaching reproduct ive maturity by multiplying expected survival by a factor indicating how cl ose to the size of first reproduction the fish grows within the time horizo n. One of the primary benefits of the individual-based approach is avoiding the need for simplifying assumptions; this benefit is best realized by bas ing movement decisions on such simple, direct measures of fitness as expect ed survival and expected reproductive maturity. (C) 1999 Elsevier Science B .V. All rights reserved.