Habitat Selection

The world is heterogeneous. Resource density, cover from predators, foraging substratum, and types and numbers of competitors and predators are just some of the things that can vary in space or time. Specializations that increase a forager's ability to exploit particular conditions often come at the expense of decreasing its ability to exploit others. Consequently, selection can favor the ability ofa forager to direct its activity to situations where it profits most. This coadaptation of ability and behavior can affect species interactions and community structure. For example, habitat selection can reduce competition iftwo species select different habitats. In fact, the strengths ofspecies interactions emerge from the optimal behaviors of the interacting individuals. Box 12.1 explains two graphical tools (isodars and isolegs) that reveal properties of habitat selection as well as community organization based on habitat selection. The following examples apply these tools.

In the Rocky Mountains of southern Alberta, pine chipmunks (Tamias amoenus) coexist with deer mice (Peromyscus maniculatus) and red-backed voles (Clethrionomys gapperi) across a range of conditions differing in aspect and plant community, from xeric open meadow to mesic fir forest. Chipmunks are diurnal, forest-dwelling ground squirrels that larder-hoard seeds and nuts. Deer mice are nocturnal caching omnivores that climb well, while red-backed voles are terrestrial herbivores that are active day and night and eat seeds and

BOX 12.1 Isolegs and Isodars

The ideal free distribution (IFD) of Fretwell and Lucas (1969) provides the basis for understanding how individuals should distribute themselves

IFD is described in box 10.1. Isodars (Morris 1988) and isolegs (Rosenzweig 1981) link the habitat choices of individuals with the dynamics of populations and communities.

Isodars

The ideal free distribution assumes that foragers can change habitats without cost. Individuals choose the habitat that offers the highest fitness, and individuals can enter a habitat on an equal basis with those already there. Furthermore, the ideal free distribution assumes that fitness (per capita population growth rate) in a habitat declines with the habitat's population density (fig. 12.1.1). For example, the relationship between density and fitness may be linear:

where Na equals population density in habitat A, ta equals maximum per capita population growth rate in habitat A, and ¿a is the strength of density dependence in habitat A.

Consider two habitats, A and B. If habitat A offers higher fitness at low population density, then all individuals should choose habitat A at low density. As density in A increases, fitness decreases for each individual there. Eventually, fitness in habitat A drops to the point at which fitness in a crowded habitat A equals fitness in an unoccupied habitat B. At that point, individuals should be indifferent to habitat choice because both habitats offer equal returns. As population density grows further, individuals should distribute themselves such that fitnesses across the two habitats are equal:

among habitats in response to habitat quality and population density. The which is equivalent to

Figure 12.1.1. Ideal free distribution. The graphs show how per capita fitness declines in each of two habitats with each habitat's population density. At low population sizes, all individuals crowd into the preferred habitat A, as it provides a higher fitness reward than habitat B (shown by the upper solid circle emanating from the highest horizontal lines). At a critical population size in habitat A (shown by the solid squares), unoccupied habitat B offers the same reward as habitat A. At this critical density, individuals should be indifferent to the choice between habitat A and habitat B. At total population sizes above this critical density, individuals should spread themselves between habitats A and B such that expected fitnesses are the same for A and B, as shown by the solid circles emanating from the lowest horizontal equal fitness lines. (A) Habitat A has twice the productivity of habitat B. (B) Habitat B offers resources that are twice as easy to encounter as those in habitat A. (After Brown 1998b.)

Figure 12.1.1. Ideal free distribution. The graphs show how per capita fitness declines in each of two habitats with each habitat's population density. At low population sizes, all individuals crowd into the preferred habitat A, as it provides a higher fitness reward than habitat B (shown by the upper solid circle emanating from the highest horizontal lines). At a critical population size in habitat A (shown by the solid squares), unoccupied habitat B offers the same reward as habitat A. At this critical density, individuals should be indifferent to the choice between habitat A and habitat B. At total population sizes above this critical density, individuals should spread themselves between habitats A and B such that expected fitnesses are the same for A and B, as shown by the solid circles emanating from the lowest horizontal equal fitness lines. (A) Habitat A has twice the productivity of habitat B. (B) Habitat B offers resources that are twice as easy to encounter as those in habitat A. (After Brown 1998b.)

Morris (1988) noted that this equation can be rewritten as

NA = (AA — AB)/b A + (b B/b A)NB- (12.1.3) This equation specifies an isodar: the relationship between population densities (Na and Nb) in two habitats for animals following the ideal free distribution (Morris 1988; fig. 12.1.2). We define an isodar as all combinations of population densities in habitats A and B such that both habitats offer the same fitness reward.

Figure 12.1.2. Isodars. The solid lines show the relationship between the numbers of individuals in habitat A and in habitat B such that individuals experience the same fitness in each habitat. (A) Habitat A offers twice the productivity of habitat B (same parameters as in fig. 12.1.1A). (B) Habitat B offers twice the ease of encountering prey as habitat A (same parameters as in fig. 12.1.1B). The dashed line ("centrally planned") represents the distribution that maximizes total productivity, rather than fitness. (After Brown 1998b.)

Figure 12.1.2. Isodars. The solid lines show the relationship between the numbers of individuals in habitat A and in habitat B such that individuals experience the same fitness in each habitat. (A) Habitat A offers twice the productivity of habitat B (same parameters as in fig. 12.1.1A). (B) Habitat B offers twice the ease of encountering prey as habitat A (same parameters as in fig. 12.1.1B). The dashed line ("centrally planned") represents the distribution that maximizes total productivity, rather than fitness. (After Brown 1998b.)

We can construct isodars from census data (e.g., Morris et al. 2000) by plotting estimated density in habitat A against estimated density in habitat B. By convention, we plot the density of the habitat with the higher productivity on the y-axis. The isodar's intercept [(Aa — Ab)/&a] gives the difference between the habitats in per capita growth rate at low population densities (i.e., in the productivities of the habitats). Morris refers to differences in habitats revealed by nonzero y-intercepts of the isodar as quantitative differences. The isodar's slope is the ratio ofthe terms that describe the intensity of density-dependent effects in habitats A and B (often due to differences in risk of predation). Morris refers to differences in habitats revealed by slopes different from 1 as qualitative differences.

We can extend isodars to examine species interactions. If two species, 1 and 2, share habitats A and B, then we can rewrite equation (12.1.3) as follows:

N1a + «Na = [C + |3(N1b + PNb)], where a = bnA/b^A and gives the average competitive effect of one individual of species 2 on species 1 in habitat A; C = (A1A - A^)b1A and gives the quantitative differences between the two habitats; and p = (b^/b^A) and gives the average competitive effect of one individual of species 2 on species 1 in habitat B. Or, more conveniently, we can rewrite equation (12.1.3) as

We can use multiple regression to estimate the parameters in this relationship [eq. (12.1.4)]. Isodar analysis accurately detects exploitative competition (Morris 1988), but may fail to detect interference competition (Ovadia andAbramsky 1995).

Isolegs

Isolegs provide a different perspective on habitat selection (Rosenzweig 1981) (fig. 12.1.3). Again, the ideal free distribution provides the conceptual foundation. Isolegs give combinations of population densities at which two habitats provide equal fitness. Again, consider two species, 1 and 2, that share habitats A and B. The two species can either show a shared preference for the same, best habitat (say, A), or they can do better in different habitats (say, species 1 does best in A and species 2 does best in B) and show distinct

Figure 12.1.3. Isolegs and isoclines (A) The isolegs and isoclines for distinct-preference, two-species, density-dependent habitat selection. Below species 1's isoleg (solid, positively sloped line), species 1 resides in both habitats, while above its isoleg it occupies habitat A only. Below species 2's isoleg (dashed, positively sloped line), species 2 resides in habitat B only, while above its isoleg it occupies both habitats. Each species' isocline (thinner lines) has a negative slope in region I (species 1 is opportunistic and species 2 is selective), a vertical (species 2) or zero (species 1) slope in region II (both species are selective on their preferred habitat type), and a negative slope in region III (species 1 is selective and species 2 opportunistic). The point where the two isoclines cross in region II indicates the ghost of competition past—neither species appears to have a negative effect on the other at the equilibrium point. (B) Isolegs for shared-preference habitat selection where species 1 is the superiorcompetitor in the preferred habitat. Species 1 and 2's isolegs have the same interpretation as in part A, with the addition of a second isoleg for species 2 (the short negative line). Inside this second isoleg, species 2 is selective on habitat 1. This creates a fourth region in the state space, IV, where both species are selective on habitat A and absent from habitat B. (After Brown 1998b.)

Figure 12.1.3. Isolegs and isoclines (A) The isolegs and isoclines for distinct-preference, two-species, density-dependent habitat selection. Below species 1's isoleg (solid, positively sloped line), species 1 resides in both habitats, while above its isoleg it occupies habitat A only. Below species 2's isoleg (dashed, positively sloped line), species 2 resides in habitat B only, while above its isoleg it occupies both habitats. Each species' isocline (thinner lines) has a negative slope in region I (species 1 is opportunistic and species 2 is selective), a vertical (species 2) or zero (species 1) slope in region II (both species are selective on their preferred habitat type), and a negative slope in region III (species 1 is selective and species 2 opportunistic). The point where the two isoclines cross in region II indicates the ghost of competition past—neither species appears to have a negative effect on the other at the equilibrium point. (B) Isolegs for shared-preference habitat selection where species 1 is the superiorcompetitor in the preferred habitat. Species 1 and 2's isolegs have the same interpretation as in part A, with the addition of a second isoleg for species 2 (the short negative line). Inside this second isoleg, species 2 is selective on habitat 1. This creates a fourth region in the state space, IV, where both species are selective on habitat A and absent from habitat B. (After Brown 1998b.)

habitat preferences. Assume that species 1 does best in habitat A, and species 2 does best in habitat B. There are two important isolegs, one for species

1 and one for species 2. The isoleg for species 1 maps where species 1 goes from being selective on its best habitat (to the left of the isoleg) to being opportunistic in its use of both habitats (to the right of the isoleg). This is simply the effect of density dependence that we have seen previously in chapter 10, in the ideal free distribution (see box 10.1), and above. The other isoleg maps the same for species 2.

Consider the problems of species 1 without species 2. At low density, all members of species 1 select their preferred habitat A. As population density increases, fitness in A drops to the same level as fitness in B. This gives the x-intercept of species 1's isoleg. At this point, individuals can choose either habitat with the same consequences, and they should be indifferent. If density increases beyond this point, foragers should choose habitats opportunistically. Thus, the isoleg separates a region of selectivity (species 1 resides only in habitat A) from a region ofopportunism (species 1 occupies both habitats A and B).

But what if species 2 is also present? At low density, individuals of species

2 will select their preferred habitat B. With some individuals of species 2 in habitat B, it now takes more individuals ofspecies 1 in habitat A to reduce the value of habitat A to equal that of habitat B. The point at which fitnesses equilibrate now occurs at a higher density ofspecies 1 (in A), and the isoleg moves up and to the right: as species 2 increases in B, the point where species 1 switches from being selective on A to being Isolegs and isoclines. opportunistic occurs at ever higher densities of species 1. This results in an isoleg that intercepts the x-axis and has a positive slope. We use a similar argument to find the species 2 isoleg, which also has a positive slope, but intercepts the y-axis. The result is a system of two isolegs, both with a positive slope, that separate the state space of N1 and N2 into three regions (fig. 12.1.3A). Above species 2's isoleg (region III in fig. 12.1.3A), species 1 selects habitat A and species 2 is opportunistic; between the isolegs (region II), both species select their own best habitat; to the right of species 1's isoleg (region I), species 2 selects habitat B and species 1 is opportunistic.

As optimal habitat selection behavior changes across these three regions, the intensity of competition also changes. The two species compete most intensely in the upper and lower regions (I and III), where one species selects its preferred habitat and the other occupies both habitats opportunistically. In the central region (II), however, the two species do not compete, because the two species avoid each other by selecting their own preferred, best habitats. If population densities typically fall in this "no competition" region, the two species may evolve fixed habitat selection behavior that no longer responds to density. When this occurs, not even removal experiments can detect the interspecific competition that produced each species' habitat specialization. Rosenzweig (1991) calls this phenomenon "the ghost of competition past."

Zero population growth rate isoclines give the combinations of densities of each species at which the population growth rate for a species is zero. These isoclines reveal the dynamic stability properties of the ecological system of two interacting species and can show the ghost of competition past (see fig. 12.1.3A). The resulting changes in optimal habitat selection behavior in the different regions also change the intensity of competition between the species there. The isoclines change slope as they pass from one region to the next. This results in isoclines that kink as they cross the behavioral isolegs. The isoclines are vertical or horizontal between the isolegs and have negative slopes elsewhere (see fig. 12.1.3A). The kinking of the isoclines can produce a stable equilibrium point where one otherwise would not exist. Thus, the magnitudes of the competition coefficients emerge from behavior, and in fact, change as behavior changes (compare this with the models of mass action in which competition coefficients are givens).

In other cases, two species may prefer the same habitat (fig. 12.1.3B). Assume that both species prefer habitat A, but that species 1 is more despotic and specialized while species 2 is more tolerant across habitats. There can be three isolegs in this system. The dominant species has a single isoleg that, as in shared preference habitat selection, has a positive slope, and for the same reason. At low density, species 1 will inhabit habitat A exclusively, but increasing population density will eventually reduce fitness in habitat A to the level of habitat B, so species 1 will become opportunistic and begin to use habitat B. The presence ofspecies 2 decreases the quality ofalternative habitat B and leads to a positively sloped isoleg. The subordinate species has up to two isolegs. One separates the lower densities at which the subordinate species selects the preferred habitat from the higher densities at which it becomes opportunistic. For species 2 by itself, individuals will select habitat 1, and as its density rises, there will come a point where fitness in habitats A and B are equal. This point forms the isoleg's y-intercept. Below this point, species 2 selects habitat A; above this point, it chooses opportunistically. However, species 2's isoleg has a negative slope: increases in the density of species 1 (also inhabiting habitat A at low density) will decrease the quality of habitat A and lower the point where habitats A and B are of equal quality. Species 2's isoleg will intercept the x-axis at or below species 1's isoleg, and that is why we can assume that there will be at least some members of species 2 in habitat B when we calculate the species 1 isoleg.

Finally, another isoleg for the subordinate species may exist above the first. At sufficiently high densities of species 1 (which mostly uses habitat A and may interfere with species B there), species 2 may choose to avoid the best habitat altogether due to intolerable costs of interference from the dominant species and instead select habitat B. This creates the new species 2 isoleg (to the right of the original) that separates opportunistic choice of the two habitats from a region of high species 1 density where species 2 should select the poorer habitat. This isoleg has a positive slope because adding more species 2 individuals to habitat B reduces its quality and makes habitat A more attractive.

The three isolegs create four regions with different combinations ofop-timal habitat selection behaviors (see fig. 12.1.3B). In region IV at the bottom left, both species select the best habitat, A. In region III, species 1 selects habitat A, but species 2 is opportunistic. In region I, species 1 chooses opportunistically, while species 2 shows an apparent preference for habitat B. The species compete most intensely in this region because both species occupy both habitats and population densities are high. And finally, in region II, species 1 chooses habitat A, but species 2 selects the poorer habitat. As in the case of distinct preference, shared preference habitat selection causes the zero population growth rate isoclines to kink as they pass from one region to the next.

We derive isodars and isolegs from the ideal free distribution, and we use them to reveal aspects ofpopulation growth, population regulation, species interactions, and community organization. Although they both explore habitat selection, notice that they consider different quantities. When we plot isodars, we plot density in habitat A versus density in habitat B; when we plot isolegs, we plot density of species 1 versus density of species 2. We can find both isodars and isolegs from simple census data. Additionally, experiments that give foragers a choice between habitats at different competitor densities can reveal the zero population growth rate isoclines of the system (e.g., Rosenzweig and Abramsky 1997). Thus, the ideal free distribution forms the basis for a comprehensive analysis of populations and ecological communities.

vegetation. Figure 12.2 shows the isodars for each species (Morris 1996). The isodars reveal a habitat generalist (chipmunk) and two habitat specialists (xeric habitat: deer mouse; mesic habitat: vole). Habitat selection responds to intraspecific density only, though the opportunism of the chipmunk occurs at a fine scale, and the habitat selection of the deer mouse and red-backed vole occur at a coarse scale. Theory suggests that a generalist and two specialists can coexist if the generalist experiences the environment as relatively fine-grained (Brown 1996), as do these rodents.

Morris et al. (2000) calculated isodars for two competing herbivorous rodents from the wet heathlands of eastern Australia. The heathlands are seasonally dry and burn frequently. There, the swamp rat (Rattus lutreolus) co-occurs with the eastern chestnut mouse (Pseudomys gracilicaudatus) in habitats that vary in age and edaphic conditions. The eastern chestnut mouse is especially common in recently burned sites, but is gradually replaced by the swamp rat as the effects of fire recede. In intermediate-aged stands, the two species co-occur across the range of edaphic conditions. The isodar analysis confirmed the asymmetric competitive dominance of the swamp rat over the eastern chestnut mouse in both wet and dry heath habitat, with stronger effects in drier sites. Isodars also revealed the superiority of P. gracilicaudatus in recently burned areas. Applying principles of density-dependent habitat selection corroborated the results of previous removal experiments that revealed much the same information, at much greater cost and effort (Higgs and Fox 1993).

Although isodars can reveal aspects of community organization, they are better suited for studying intraspecific behavior. In contrast, isolegs are defined only for two or more interacting species in heterogeneous environments. We can use experimental manipulations of population densities to find isolegs. The isoleg for a species gives all combinations of the densities of two (or more) species such that the species is indifferent in its use of the two habitats. Usually this isoleg considers the point at which a species goes from being selective on one habitat to being opportunistic on two habitats. There is a separate isoleg for each species. The isolegs exist in the same state space of species densities as the population growth rate isoclines from ecology (see box 12.1).

Abramsky, Rosenzweig, and colleagues manipulated the densities of ger-bils in 1 ha field enclosures where two gerbil species, Allenby's gerbil and the greater sand gerbil, could choose between stabilized and semi-stabilized sand dunes within a mosaic of habitats (Abramsky et al. 1990, 1991; Rosenzweig and Abramsky 1997). The results supported the shared preference model (see fig. 12.1.3B) and the existence of a single isoleg for the dominant species, but two isolegs for the subordinate species. More importantly, the investigators deduced the general shapes of the zero population growth rate isoclines (indicators of the dynamic stability of the system, i.e., whether the two species

Figure 12.2. Population densities in xeric versus mesic habitats and isodars (dashed lines) forthree species of montane rodents in the Rocky Mountains of southern Alberta, Canada: (A) deer mouse, (B) red-backed vole, and (C) pine chipmunk. Isodars are based on the ideal free distribution and are obtained by regressing population densities in one habitat versus the other. Isodar intercepts that differ from 0 reveal quantitative differences between habitats, and slopes that differ from 1 reveal qualitative differences (see box 12.1). For the deer mouse, the xeric habitat is both quantitatively and qualitatively superior; forthe vole, the mesic habitat is quantitatively superior; forthe chipmunk, the habitats are equally valuable. Symbols referto different trapping sessions: firstB, second o, third +. (After Morris 1996.)

Figure 12.2. Population densities in xeric versus mesic habitats and isodars (dashed lines) forthree species of montane rodents in the Rocky Mountains of southern Alberta, Canada: (A) deer mouse, (B) red-backed vole, and (C) pine chipmunk. Isodars are based on the ideal free distribution and are obtained by regressing population densities in one habitat versus the other. Isodar intercepts that differ from 0 reveal quantitative differences between habitats, and slopes that differ from 1 reveal qualitative differences (see box 12.1). For the deer mouse, the xeric habitat is both quantitatively and qualitatively superior; forthe vole, the mesic habitat is quantitatively superior; forthe chipmunk, the habitats are equally valuable. Symbols referto different trapping sessions: firstB, second o, third +. (After Morris 1996.)

coexist) through the application of the ideal free distribution. They did so by connecting pairs of enclosures with gates. By allowing only one species to pass through the gates, Abramsky and Rosenzweig could fix competitor densities in the two connected enclosures while allowing the target species to adjust its distribution and activity. Using this technique, Abramsky and Rosenzweig measured the effect of the species with a fixed density on the level and distribution offoraging activity ofthe species that could move freely between enclosure halves. In this way, the species that is free to move reveals the effect of competition with the other species on it (the competition coefficient) through its habitat selection behavior. By repeating this treatment over a range and combination ofcompetitor densities, Abramsky and Rosenzweig could render the shape of the isoclines. Remarkably, their data support the nonlinear isoclines that foraging theory predicts (Abramsky et al. 1991, 1994; Abramsky, Rosenzweig, and Subach 1992; fig. 12.3).

The data from these experiments can also be examined with isodar analysis (Ovadia and Abramsky 1995). The isodars confirm shared preference habitat selection for the semi-stabilized habitat, with G. pyramidum experiencing the stabilized and the semi-stabilized sand as qualitatively similar, but G. a. allenbyi experiencing the stabilized sand as qualitatively superior. The isodars reveal a flip-flop in the habitat preferences of G. a. allenbyi. At low population densities it prefers the semi-stabilized sand habitat, but at high densities it prefers the stabilized habitat. The isodars also revealed resource competition between the two species, but failed to detect interference. Abramsky and Rosenzweig's ability to set conditions in different enclosures and then allow the animals to perform their own titrations made this a successful experiment.

We can use this approach to address other questions in community ecology. Abramsky et al. (2000), for example, used it to measure the energetic cost of interspecific competition. They established four G. pyramidum individuals in one of two connected enclosures, along with 40 or 50 G. a. allenbyi individuals. The G. a. allenbyi could move freely between the two enclosures (through species-specific gates); the G. pyramidum could not (as in the above experiments). G. a. allenbyi individuals adjusted their enclosure-specific activities in response to the differing competitive regimes in the two enclosures. More G. a. allenbyi activity occurred in the enclosure without the competitor. Next, Abramsky et al. carried out an experimental titration, adding seeds to the enclosure with G. pyramidum until G. a allenbyi was equally active in both enclosures. Adding 4.5 g of seeds to each of 24 trays balanced the effect of four competitors. To date, similar titrations have measured the benefits of habitat selection, the cost of temporally partitioning the night, and the cost of apprehensive foraging under predation risk (Abramsky et al. 2001, 2002a, 2002b).

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