Rosenzweig, M. L. 2001: Optimality — the biologist’s tricorder. — Ann. Zool. Fennici 38: 1–3.
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Bednekoff, P. A. 2001: Coordination of safe, selfish sentinels based on mutual benefits. — Ann. Zool. Fennici 38: 5–14.
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Dall, S. R. X., Kotler, B. P. & Bouskila, A. 2001: Attention, ‘apprehension’ and gerbils searching in patches. — Ann. Zool. Fennici 38: 15–23.
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McNamara, J. M. 2001: The effect of adaptive behaviour on the stability of population dynamics. — Ann. Zool. Fennici 38: 25–36.
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Morris, D. W. 2001: Learning from the games animals play: using behavior to assess spatial structure and stochasticity in natural populations. — Ann. Zool. Fennici 38: 37–53.
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Bouskila, A. 2001: A habitat selection game of interactions between rodents and their predators. — Ann. Zool. Fennici 38: 55–70.
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Brown, J. S., Kotler, B. P. & Bouskila, A. 2001: Ecology of fear: Foraging games between predators and prey with pulsed resources. — Ann. Zool. Fennici 38: 71–87.
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Mitchell, W. A. & Porter, W. P. 2001: Foraging games and species diversity. — Ann. Zool. Fennici 38: 89–98.
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Bednekoff, P. A. 2001: Coordination of safe, selfish sentinels based on mutual benefits. — Ann. Zool. Fennici 38: 5–14.

Sentinels are group members that watch from prominent positions. Sentinel interchanges often appear orderly and the number of sentinels changes little despite the turnover of individuals. I modeled why solitary individuals or group members might take up prominent positions. Such positions can be safe places to rest because they provide a good view of approaching predators, even if undetected predators preferentially attack sentinels. In pairs, coordinated sentinel behavior is favored whenever information spreads from a detecting to a non-detecting individual more than half the time. Under these conditions, safety for a sentinel produces safety for a forager as a by-product. Thus sentinel behavior occurs for selfish safety reasons but coordination of sentinels is based on mutualism. If sentinels can coordinate their individual actions, evidence of the game is hidden from view. The fitness consequences of some games may be best indicated by the strategies organisms take to avoid playing them.

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Dall, S. R. X., Kotler, B. P. & Bouskila, A. 2001: Attention, ‘apprehension’ and gerbils searching in patches. — Ann. Zool. Fennici 38: 15–23.

In this paper, we consider the attentional demands associated with detecting and responding to predators, or ‘apprehension’, and the within-patch search of Allenby’s gerbils, Gerbillus andersoni allenbyi. We, thus, present a first empirical investigation of the indirect, informational consequences of perceived predation risk. Specifically, we focus on the ability to track the quality of seed patches in sandy habitats. There are two potential effects here; since instantaneous intake rate (or some proxy) is the key parameter of interest to an optimal forager, apprehension can interfere with the estimation of: (1) the number of food items captured, and/or (2) the time taken to capture them (the ability to locate food items). Only (2) will have a consistent effect on patch quality, and we test the hypothesis that increased predation risk reduces gerbil search efficiency. We therefore quantified gerbil search paths in patches of uniform seed distribution that differed in their associated risks of predation by manipulating the presence of barn owls, Tyto alba, and light in an aviary. Gerbil search was more random under risky conditions. We discuss the implications of this result for information processing and patch use under predation risk, and the foraging games between gerbils and owls in the Negev Desert.

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McNamara, J. M. 2001: The effect of adaptive behaviour on the stability of population dynamics. — Ann. Zool. Fennici 38: 25–36.

I consider how adaptive changes in behaviour with population size affect the stability of the population dynamics. In any given year the behavioural rule of a member of a single-species population is determined by the value of a certain trait. I allow for the possibility that this trait value can change from year to year. The number of descendants left in one year’s time by an individual depends on its trait value, the values of other population members and the population size. The population dynamics is modelled as the change in population size from one year to the next. I focus on a population that is at a fixed point of the dynamics and in which members adopt the evolutionarily stable trait value for that equilibrium size. I compare the stability of the population dynamics under the following two assumptions about the dependence of trait values on population size: (i) trait values do not change from that at the equilibrium size, and (ii) trait values change so as to be evolutionarily stable for the current size. In a range of examples, I show that adaptive behaviour tends to destabilise population dynamics in the sense that stability under assumption (ii) implies stability under assumption (i). In other words, the region of parameter space for which there is instability under an adaptive response contains the region of instability under no response. Various equivalent general criteria for this to hold are given.

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Morris, D. W. 2001: Learning from the games animals play: using behavior to assess spatial structure and stochasticity in natural populations. — Ann. Zool. Fennici 38: 37–53.

Population densities are heterogeneous across a variety of spatial scales. The variation in density reflects a similar variety of processes ranging from density-dependent habitat selection at small scales to independently regulated populations at much larger ones. I measured each scale with experiments capitalizing on the behavior of individual deer mice foraging in badland habitats in Alberta, Canada. First, I used patterns in rodent density along transects crossing badland and prairie habitats to measure the scale of habitat selection. Consistent with theoretical predictions, differences in the intercepts of isodars (graphs of density in adjacent habitats assuming ideal habitat selection) comparing prairie and badland densities revealed a maximum scale of habitat selection on the order of only 140 m. Second, I used foraging experiments to estimate density-dependent declines in fitness measured by the surrogate of giving-up-density of mice foraging in artificial foraging patches. Habitat selection should tend to equalize giving-up-densities among replicated, but spatially segregated, grids containing different numbers of foragers. Contrary to predictions from habitat selection theory, giving-up-densities declined with increased forager density in the majority of grids. Giving-up densities in nine of 12 grids increased linearly as population density was reduced in 1997. Giving-up densities in eight of 10 grids increased linearly with resource supplements in 1998. The results of both experiments are consistent with independent resource harvest by varying numbers of foraging mice. The identity of “outlier” grids, that showed little response to either manipulation, varied between years. The combined results document spatially-structured populations and allow us to estimate the frequency of stochastic dynamics that may have a profound influence on evolution and conservation strategies in heterogeneous landscapes.

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Bouskila, A. 2001: A habitat selection game of interactions between rodents and their predators. — Ann. Zool. Fennici 38: 55–70.

I developed a game theoretic model for habitat selection of prey and a generalist predator. In the model, both prey and predator may choose between either a simple or a complex habitat. A second predator is restricted to hunting only in the simple habitat. The model is applied to a system of rodents and their predators: snakes (the generalist predator) and owls. The simplest version of the model predicts that snakes and rodents distribute themselves among the two microhabitats according to the relative magnitude of risk for rodents. Under various conditions (moonlight, competition among rodents and dilution of the risk) the model predicts that snakes distribute themselves among habitats in a way that dampens rodent reactions to variation in owl predation risk and to effects of competition. When rodents are abundant the model predicts that snakes will show a weaker reaction to moonlight. The predictions of the model are qualitatively comparable to field data of microhabitat use of kangaroo rats and sidewinders from the Mojave Desert. The model can also describe a habitat selection game at a larger scale (e.g., movements of snakes into a rich desert oasis). Although a game between predators and prey may not be the cause for all their movements among habitats in the field, a game perspective may contribute explanations for what would otherwise be unintuitive habitat shifts.

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Brown, J. S., Kotler, B. P. & Bouskila, A. 2001: Ecology of fear: Foraging games between predators and prey with pulsed resources. — Ann. Zool. Fennici 38: 71–87.

We model the foraging game between a prey and predator when the prey experiences a temporally pulsed resource (e.g., seed-eating gerbils). Animals have the options of foraging or remaining inactive. Prey harvest resources and incur a mortality risk only while foraging. ESS levels of prey and predator activity have three distinct phases over the time course of a resource pulse. During the first phase, resources are sufficiently abundant to permit profitable foraging by all prey and predators. During the second phase, only a fraction of prey and predator are active. The fraction of active prey is sufficient to allow profitable foraging by the predators. Resource abundances and activity level of predators decline synchronously, balancing the prey’s needs for food and safety. During the third phase, resources decline to where both prey and predator cease activity. These adaptive behaviors of prey and predator to resources and to each other promote the stability of the predator-prey dynamics.

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Mitchell, W. A. & Porter, W. P. 2001: Foraging games and species diversity. — Ann. Zool. Fennici 38: 89–98.

We analyze a game theory model in which individuals foraging on a habitat continuum choose behaviors that are the “best responses” to the behaviors and densities of competitors. These behaviors determine community invasibility and coexistence. By making fitness an explicit function of maintenance metabolic cost, we can show that changes in maintenance cost have an indirect but important effect on the best response behaviors, and hence, on community dynamics. In particular, decreasing maintenance cost has the effect of decreasing habitat resource levels by increasing the efficiency with which individuals convert resources into offspring. The resulting decrease in habitat resource levels increases each phenotype’s relative foraging advantage in whatever habitat(s) it holds an absolute advantage. As a result, more phenotypes can successfully invade the community. Indeed, low enough maintenance costs results in species inhabiting evolutionary minima in the adaptive landscape, which promotes disruptive selection and provides the potential for an evolutionary bifurcation.

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