Interspecific Competition Involves Two or More Species

CHAPTER 13

Smith, T. M., & Smith, R. L. (2015). Elements of Ecology (9th ed.). Boston, MA: Pearson.

13.1 Interspecific Competition Involves Two or More Species

A relationship that affects the populations of two or more species adversely (– –) is interspecific competition. In interspecific competition, as in intraspecific competition, individuals seek a common resource in short supply (see Chapter 11). But in interspecific competition, the individuals are of two or more species. Both kinds of competition may take place simultaneously. In the deciduous forest of eastern North America, for example, gray squirrels compete among themselves for acorns during a year when oak trees produce fewer acorns. At the same time, white-footed mice, white-tailed deer, wild turkey, and blue jays vie for the same resource. Because of competition, one or more of these species may broaden the base of their foraging efforts. Populations of these species may be forced to turn away from acorns to food that is less in demand.

Like intraspecific competition, interspecific competition takes two forms: exploitation and interference (see Section 11.3). As an alternative to this simple dichotomous classification of competitive interactions, Thomas Schoener of the University of California–Davis proposed that six types of interactions are sufficient to account for most instances of interspecific competition: (1) consumption, (2) preemption, (3) overgrowth, (4) chemical interaction, (5) territorial, and (6) encounter.

Consumption competition occurs when individuals of one species inhibit individuals of another by consuming a shared resource, such as the competition among various animal species for acorns. Preemptive competition occurs primarily among sessile organisms, such as barnacles, in which the occupation by one individual precludes establishment (occupation) by others. Overgrowth competition occurs when one organism literally grows over another (with or without physical contact), inhibiting access to some essential resource. An example of this interaction is when a taller plant shades those individuals below, reducing available light (as discussed in Chapter  4, Section  4.2). In chemical interactions, chemical growth inhibitors or toxins released by an individual inhibit or kill other species. Allelopathy in plants, in which chemicals produced by some plants inhibit germination and establishment of other species, is an example of this type of species interaction. Territorial competition results from the behavioral exclusion of others from a specific space that is defended as a territory (see Section  11.10). Encounter competition results when nonterritorial meetings between individuals negatively affect one or both of the participant species. Various species of scavengers fighting over the carcass of a dead animal provide an example of this type of interaction.

13.2 The Combined Dynamics of Two Competing Populations Can Be Examined Using the Lotka–Volterra Model

In the early 20th century, two mathematicians—the American Alfred Lotka and the Italian Vittora Volterra—independently arrived at mathematical expressions to describe the relationship between two species using the same resource (consumption competition). Both men began with the logistic equation for population growth that we developed previously in Chapter 11 :

Species1:dN1/dt=r1N1(1−N1/K1)Species2:dN2/dt=r2N2(1−N2/K2)Species1:dN1/dt=r1N1(1−N1/K1)Species2:dN2/dt=r2N2(1−N2/K2)

Next, they both modified the logistic equation for each species by adding to it a term to account for the competitive effect of one species on the population growth of the other. For species 1, this term is αN2, where N2 is the population size of species 2, and α is the competition coefficient that quantifies the per capita effect of species 2 on species 1. Similarly, for species 2, the term is βN1, where β is the per capita competition coefficient that quantifies the per capita effect of species 1 on species 2. The competition coefficients can be thought of as factors for converting an individual of one species into the equivalent number of individuals of the competing species, based on their shared use of the resources that define the carrying capacities (see Chapter 12, Section 12.2 and Figure  12.3, and Quantifying Ecology 12.1). In resource use, an individual of species 1 is equal to β individuals of species 2. Likewise, an individual of species 2 is equivalent to α individuals of species 1. These terms (α and β), in effect, convert the population size of the one species into the equivalent number of individuals of the other. For example, assume species 1 and species 2 are both grazing herbivores that feed on the exact same food resources (grasses and other herbaceous plants). If individuals of species 2 have, on average, twice the body mass as individuals of species 1 and consume food resources at twice the rate, with respect to the food resources, an individual of species 2 is equivalent to two individuals of species 1 (that is, α = 2.0). Likewise, consuming food resources at only half the rate as species 2, an individual of species 1 is equivalent to one-half an individual of species 2 (that is, β = 0.5).

Now we have a pair of equations that consider both intraspecific and interspecific competition.

Species1:dN1/dt=r1N1(1−(N1+αN2)/K1)Species2:dN2/dt=r2N2(1−(N2+βN1)/K2)   (1)   (2)Species1:dN1/dt=r1N1(1−(N1+αN2)/K1)Species2:dN2/dt=r2N2(1−(N2+βN1)/K2)   (1)   (2)

As you can see, in the absence of interspecific competition—either α or N2 = 0 in Equation (1) and β or N1 = 0 in Equation (2)— the population of each species grows logistically to equilibrium at K, the respective carrying capacity. In the presence of competition, however, the picture changes.

For example, the carrying capacity for species 1 is K1, and as N1 approaches K1, the population growth (dN1/dt) approaches zero. However, species 2 is also vying for the limited resource that determines K1, so we must consider the impact of species 2. Because α is the per capita effect of species 2 on species 1, the total effect of species 2 on species 1 is αN2, and as the combined population N1 + αN2 approaches K1, the growth rate of species 1 approaches zero as well. The greater the population size of the competing species (N2), the greater the reduction in the growth rate of species 1 is (see discussion in Section 12.2 and Figure 12.3).

The simplest way to examine the possible outcomes of competition using the Lotka–Volterra equations presented is a graphical approach in which we first define the zero-growth isocline for each of the two competing species. The zero-growth isocline represents the combined values of population size for species 1 (N1) and species 2 (N2) at which the population growth rate of the respective species is zero (dN/dt = 0). This occurs when the combined population sizes are equal to the carrying capacity of that species (see Figure 12.3). We can begin by defining the zero-growth isocline for species 1 (Figure  13.1a). The two axes in the graph shown in Figure  13.1a define the population size of species 1 (x-axis, N1) and species 2 (y-axis, N2). We must now solve for the combined values of N1 and N2 at which the growth rate of species 1 is equal to zero (dN1/dt = 0). This occurs when: (1 – (N1 + αN2)/K1) = 0 or K1 = N1 + αN2 (see Equation 1). In effect, we are determining the combined values of N1 and N2 that equal the carrying capacity of species 1 (K1). This task is made simple because K1 = N1 + αN2 represents a line and all that is necessary to draw the line is to solve for two points. The two simplest solutions are to solve for the two intercepts (where the line intersects the two axes). The x-intercept occurs when N2 = 0, giving us a value of N1 = K1. The y-intercept occurs when N1 = 0, giving us a value of αN2 = K1, or N2 = K1/a. Given these two points (values for N1, N2), we can draw the line defining the zero isocline for species 1 (Figure 13.1a). For any combined value of N1, N2 along this line, N1 + αN2 = K1 and dN1/dt = 0. For combinations of (N1, N2) that fall below the line (toward the origin: 0, 0), N1 + αN2 < K1 and the population of species 1 can continue to grow. An increase in the population of species 1 is represented by a green horizontal arrow pointing to the right. The arrow is horizontal because the x-axis represents the population of species 1. For combinations of N1 and N2 that fall above the line, N1 + αN2 > K1, the population growth rate is negative (as represented by the green horizontal line pointing to the left), and the population size declines until it reaches the line.

We can take this same approach and define the zero isocline for species 2 (Figure 13.1b). The x-intercept is N2 = 0 and N1 = K2/β, and the y-intercept is N2 = K2 and N1 = 0. As with the zero-growth isocline for species 1, for combinations of N1 and N2 that fall below the line, N2 + βN1 < K2 and the population of species 2 can continue to grow. The yellow vertical arrow pointing up represents an increase in the population of species 2. The arrow is vertical because the x-axis represents the population of species 2. For combinations of (N1, N2) that fall above the line, N2 + βN1 > K2, the population growth rate is negative (yellow vertical arrow pointing down), and the population size declines until it reaches the line (see Figure 13.1b). We can now combine the two zero-growth isoclines onto a single graph and examine the combined population dynamics of the two species for different values of N1 and N2.

13.3 There Are Four Possible Outcomes of Interspecific Competition

To interpret the combined dynamics of the two competing species, their isoclines must be drawn on the same x–y graph. Although there are an infinite number of isoclines that can be constructed by using different values of K1, K2, α, and β, there are only four qualitatively different ways in which to plot the isoclines. These four possible outcomes are shown in Figure  13.2. In the first case (Figure 13.2a), the isocline of species 1 is parallel to, and lies completely above, the isocline of species 2. In this case, the isoclines define three areas of the graph. In the lower left-hand area of the graph (point A), the combined values of N1 and N2 are below the zero-growth isoclines for both species, and the populations of both species can increase. The green horizontal arrow representing species 1 points right, indicating an increase in the population of species 1, whereas the orange vertical arrow representing species 2 points up, indicating an increase in the population of species 2. The next point representing the combined values of N1 and N2 must therefore lie somewhere between the two arrows and is represented by the black arrow pointing away from the origin. In the upper right-hand corner of the graph, the combined values of N1 and N2 are above the zero-growth isoclines for both species. In this case, the populations of both species decline (black arrow points toward the origin).

In the interior region between the two isoclines, the dynamics of the two populations diverge. Here (at point C) the combined values of N1 and N2 are below the isocline for species 1, so its population increases in size, and the green horizontal arrow points to the right. However, this region is above the isocline for species 2, so its population is declining, and the yellow vertical arrow is pointing down. The black arrow now points down and toward the right, which takes the populations toward the carrying capacity of species 1 (K1). Note that this occurs regardless of where the initial point (N1, N2) lies within this region. If the isocline of species 1 lies above the isocline for species 2, species 1 is the more competitive species and species 2 is driven to extinction (N2 = 0).

In the second case (Figure 13.2b), the situation is reversed. The zero-growth isocline for species 2 lies above the isocline for species 1, and therefore species 2 “wins” leading to the extinction of species 1 (N1 = 0). Note that in the interior region (between the isoclines), the combined values of N1 and N2 are now below the isocline for species 2 allowing its population to grow (yellow vertical arrow pointing up), whereas it is above the isocline for species 1, causing its population to decline (green horizontal arrow pointing to the left). The result is a movement of the populations toward the upper left (see black arrow), the carrying capacity of species 2 (K2).

In the remaining two cases (Figures 13.2c and 13.2d), the isoclines of the two species cross, dividing the graph into four regions, but the outcomes of competition for the two cases are quite different. As with the previous two cases, we determine the outcomes by plotting the arrows, indicating changes in the two populations within each of the regions. However, the point where the two isoclines cross represents an equilibrium point, a combined value of N1 and N2 for which the growth of both species 1 and species 2 is zero. At this point, the combined population sizes of the two species are equal to the carrying capacities of both species (N1 + αN2 = K1 and N2 + βN1 = K2).

The third case is presented in Figure 13.2c. The region closest to the origin (point A) is below the isocline of both species, and therefore the growth of both populations is positive and the arrows point outward. The upper right-hand region (point B) is above the isoclines for both species, so both populations decline and the arrows point inward toward the axes and origin. In the bottom right-hand region of the graph (point C), we are above the isocline for species 1, but below the isocline for species 2. In this region, the population of species 1 declines (green horizontal arrow points to left), whereas the population of species 2 increases (yellow vertical arrow points up). As a result, the combined dynamics (black arrow) point toward the center of the graph where the two isoclines intersect. The upper left-hand region of the graph (point D) is above the isocline for species 2 but below the isocline for species 1. In this region, the population of species 2 declines, and the population of species 1 increases. Again, the combined dynamics (black arrow) point toward the center of the graph where the two isoclines intersect. The fact that the arrows in all four regions of the graph point to where the two isoclines intersect indicates that this point (combined values of N1 and N2) represents a “stable equilibrium.” The equilibrium is stable when no matter what the combined values of N1 and N2 are, both populations move toward the equilibrium value.

In the fourth case (Figure 13.2d), the isoclines cross, but in a different manner than in the previous case (Figure 13.2c). Again, both populations increase in the region of the graph closest to the origin (point A). Likewise, both populations decline in the upper right-hand region (point B). However, the dynamics differ in the remaining two regions of the graph. In the lower right-hand region, the combined values of N1 and N2 (point C) are below the isocline for species 1 but above the isocline for species 2. In this region, the population of species 1 decreases, whereas the population of species 2 continues to grow. The combined dynamics (black arrow) move away from the equilibrium point where the two isoclines intersect (point E) and toward the carrying capacity of species 1 (K1 on x-axis). In the upper left-hand region of the graph, the combined values of N1 and N2 (point D) are below the isocline for species 2 but above the isocline for species 1. In this region of the graph, the combined dynamics (black arrow) move away from the equilibrium point where the two isoclines intersect (point E) and toward the carrying capacity of species 2 (K2 on y-axis). This case represents an “unstable equilibrium.” If the combined values of N1 and N2 are displaced from the equilibrium (point E), the populations move into one of the two regions of the graph that will eventually lead to one species excluding the other (driving it to extinction: N = 0). Which of the two species will “win” is difficult to predict and depends on the initial population values (N1 and N2) and the growth rates of the populations (r1 and r2

13.4 Laboratory Experiments Support the Lotka–Volterra Model

The theoretical Lotka–Volterra equations stimulated studies of competition in the laboratory, where under controlled conditions an outcome is more easily determined than in the field. One of the first to study the Lotka–Volterra competition model experimentally was the Russian biologist G. F. Gause. In a series of experiments published in the mid-1930s, he examined competition between two species of Paramecium, Paramecium aurelia and Paramecium caudatum. P. aurelia has a higher rate of population growth than P. caudatum and can tolerate a higher population density. When Gause introduced both species to one tube containing a fixed amount of bacterial food, P. caudatum died out (Figure 13.3). In another experiment, Gause reared the species that was competitively displaced in the previous experiment, P. caudatum, with another species, Paramecium bursaria. These two species coexisted because P. caudatum fed on bacteria suspended in solution, whereas P. bursaria confined its feeding to bacteria at the bottom of the tubes. Each species used food unavailable to the other.

In the 1940s and 1950s, Thomas Park at the University of Chicago conducted several classic competition experiments with laboratory populations of flour beetles. He found that the outcome of competition between Tribolium castaneum and Tribolium confusum depended on environmental temperature, humidity, and fluctuations in the total number of eggs, larvae, pupae, and adults. Often, the outcome of competition was not determined until many generations had passed.

In a much later study, ecologist David Tilman of the University of Minnesota grew laboratory populations of two species of diatoms, Asterionella formosa and Synedra ulna. Both species require silica for the formation of cell walls. The researchers monitored population growth and decline as well as the level of silica in the water. When grown alone in a liquid medium to which silica was continually added, both species kept silica at a low level because they used it to form cell walls. However, when grown together, the use of silica by S. ulna reduced the concentration to a level below that necessary for A. formosa to survive and reproduce (Figure 13.4). By reducing resource availability, S. ulna drove A. formosa to extinction.

13.5 Studies Support the Competitive Exclusion Principle

In three of the four situations predicted by the Lotka–Volterra equations, one species drives the other to extinction. The results of the laboratory studies just presented tend to support the mathematical models. These and other observations have led to the concept called the competitive exclusion principle , which states that “complete competitors” cannot coexist. Complete competitors are two species (non-interbreeding populations) that live in the same place and have exactly the same ecological requirements (see concept of fundamental niche in Chapter  12, Section 12.6). Under this set of conditions, if population A increases the least bit faster than population B, then A will eventually outcompete B, leading to its local extinction.

Competitive exclusion, then, invokes more than competition for a limited resource. The competitive exclusion principle involves assumptions about the species involved as well as the environment in which they exist. First, this principle assumes that the competitors have exactly the same resource requirements. Second, it assumes that environmental conditions remain constant. Such conditions rarely exist. The idea of competitive exclusion, however, has stimulated a more critical look at competitive relationships in natural situations. How similar can two species be and still coexist? What ecological conditions are necessary for coexistence of species that share a common resource base? The resulting research has identified a wide variety of factors affecting the outcome of interspecific competition, including environmental factors that directly influence a species’ survival, growth, and reproduction but are not consumable resources (such as temperature or pH), spatial and temporal variations in resource availability, competition for multiple limiting resources, and resource partitioning. In the following sections, we examine each topic and consider how it functions to influence the nature of competition.

13.6 Competition Is Influenced by Nonresource Factors

Interspecific competition involves individuals of two or more species vying for the same limited resource. However, features of the environment other than resources also directly influence the growth and reproduction of species (see Chapters 6 and 7) and therefore can influence the outcome of competitive interactions. For example, environmental factors such as temperature, soil or water pH, relative humidity, and salinity directly influence physiological processes related to growth and reproduction, but they are not consumable resources that species compete over.

For example, in a series of field and laboratory experiments, Yoshinori Taniguchi and colleagues at the University of Wyoming examined the influence of water temperature on the relative competitive ability of three fish species that show longitudinal replacement in Rocky Mountain streams. Brook trout (Salvelinus fontinalis) are most abundant at high elevations, brown trout (Salmo trutta) at middle elevations, and creek chub (Semotilus atromaculatus) at lower elevations. Previous studies have shown that interference competition for foraging sites is an important factor influencing the relative success of individuals at sites where the species co-occur. Based on the distribution of these three species along elevation gradients in the Rocky Mountain streams and differences in physiological performance with respect to temperature, the researchers hypothesized that the brook trout would be competitively superior at cold water temperatures, brown trout at moderate water temperatures, and creek chub would be competitively superior at warmer water temperatures. To test this hypothesis, Taniguchi and his colleagues used experimental streams to examine competitive interactions at seven different water temperatures: 3, 6, 10, 22, 22, 24, and 26°C.

Prior to each test, fish were thermally acclimated by increasing or decreasing the temperature by 1°C per day until the test temperature was reached (see Section 7.9 for discussion of thermal acclimation). For each test, individuals of each species were matched for size (<10%) and placed in the experimental stream together. Aggressive interactions and food intake were monitored. Competitive superiority was based on which species consumed the most food items because food intake is considered a limiting factor for these drift-feeding, stream fishes.

Patterns of food consumption clearly show changes in the relative competitive abilities of the three fish species across the gradient of water temperatures (Figure 13.5). At 3°C, brook trout exhibited the highest rate of food consumption, although differences between the two trout species were minimal below 20°C, and both trout species consumed significantly more food than creek chub. However, as temperature increased, food consumption by creek chub increased. At 24°C, food intake by brook trout dropped to zero, whereas intake rate of brown trout still exceeded that of creek chub. At 26°C, the rate of food intake reversed for the two species and food intake by creek chub exceeded that of brown trout. In an additional series of experiments, the researchers were able to establish that the observed patterns of food intake during the competition trials were a result of differences in competitive ability and no changes in appetite because of water temperature.

The transition in competitive ability from 24 to 26°C in the laboratory experiments are in agreement with the transition in dominance from trout species to creek chub at a similar temperature range in the field. The results of Taniguchi and his colleagues provide a clear example of temperature mediation of competitive interactions. The relative competitive abilities of the three fish species for limiting food resources are directly influenced by abiotic conditions, that is, water temperature.

A similar case of competitive ability being influenced by nonresource factors is illustrated in the work of Susan Warner of Pennsylvania State University. Warner and her colleagues examined the effect of water pH (acidity) on interspecific competition between two species of tadpoles (Hyla gratiosa and Hyla femoralis). The two species overlap broadly in their geographic distribution, yet differ in their responses to water acidity. The researchers conducted experiments using two levels of water pH (4.5 and 6.0) and varying levels of population densities to examine the interactions of pH and population density on both intra- and interspecific competition. The results of the experiments indicated that interspecific interactions were minimal at low water pH (4.5); however, at higher water pH (6.0), interspecific competition from H. fermoralis caused decreased survival and an increased larval period for H. gratiosa. The latter resulted in decreased size at metamorphosis for H. gratiosa individuals.

13.7 Temporal Variation in the Environment Influences Competitive Interactions

When one species is more efficient at exploiting a shared, limiting resource, it may be able to exclude the other species (see Section 13.2). However, when environmental conditions vary through time, the competitive advantages may also change. As a result, no one species reaches sufficient density to displace its competitors. In this manner, environmental variation allows competitors to coexist whereas under constant conditions, one would exclude the other.

The work of Peter Dye of the South African Forestry Research Institute provides an example of shifting competitive ability resulting from temporal variation in resource availability in the grasslands of southern Africa. He examined annual variations in the relative abundance of grass species occupying a savanna community in southwest Zimbabwe. From 1971 to 1981, the dominant grass species shifted from Urochloa mosambicensis to Heteropogon contortus (Figure 13.6a). This observed shift in dominance was a result of yearly variations in rainfall (Figure 13.6b). Rainfall during the 1971–1972 and 1972–1973 rainy seasons was much lower than average. U. mosambicensis can maintain higher rates of survival and growth under dry conditions than can H. contortus, making it a better competitor under conditions of low rainfall. With the return to higher rainfall during the remainder of the decade, H. contortus became the dominant grass species. Annual rainfall in this semiarid region of southern Africa is highly variable, and fluctuations in species composition such as those shown in Figure 13.6 are a common feature of the community.

Peter Adler (Utah State University) and colleagues observed a similar pattern for a prairie grassland site at Hays, Kansas, in the Great Plains region of North America. Adler and colleagues examined the role of interannual climate variability on the relative abundance of prairie grasses over a period of 30 years (1937–1968). The researchers found that year-to-year variations in climate correlated with interannual variations in species performance. The year-to-year variations in the relative competitive abilities of the species functioned to buffer species from competitive exclusion.

Besides shifting the relative competitive abilities of species, variation in climate can function as a density-independent limitation on population growth (see Section 11.13). Periods of drought or extreme temperatures may depress populations below carrying capacity. If these events are frequent enough relative to the time required for the population to recover (approach carrying capacity), resources may be sufficiently abundant during the intervening periods to reduce or even eliminate competition.

13.8 Competition Occurs for Multiple Resources

In many cases, competition between species involves multiple resources and competition for one resource often influences an organism’s ability to access other resources. One such example is the practice of interspecific territoriality, where competition for space influences access to food and nesting sites (see Section 11.10).

A wide variety of bird species in the temperate and tropical regions exhibit interspecific territoriality. Most often, this practice involves the defense of territories against closely related species, such as the gray (Empidonax wrightii) and dusky (Empidonax oberholseri) flycatchers of the western United States. Some bird species, however, defend their territories against a much broader range of potential competitors. For example, the acorn woodpecker (Melanerpes formicivorus) defends territories against jays and squirrels as well as other species of woodpeckers. Strong interspecific territorial disputes likewise occur among brightly colored coral reef fish.

Competition among plants provides many examples of how competition for one resource can influence an individual’s ability to exploit other essential resources, leading to a combined effect on growth and survival. R. H. Groves and J. D. Williams examined competition between populations of subterranean clover (Trifolium subterraneum) and skeletonweed (Chondrilla juncea) in a series of greenhouse experiments. Plants were grown both in monocultures (single populations) and in mixtures (two populations combined). The investigators used a unique experimental design to determine the independent effects of competition for aboveground (light) and belowground (water and nutrients) resources (see Section 11.11). In the monocultures, plants were grown in pots, allowing for the canopies (leaves) and roots to intermingle. In the two-species mixtures (Figure 13.7), three different approaches were used: (1) plants of both species were grown in the same pot, allowing their canopies and roots to intermingle, (2) plants of both species were grown in the same pot allowing their roots to overlap, but with their canopies separated, (3) the plant species were grown in separate pots with their canopies intermingled, but not allowing the roots to overlap.

Clover was not significantly affected by the presence of skeletonweed; however, the skeletonweed was affected in all three treatments where the two populations were grown together. When the roots were allowed to intermingle, the biomass (dry weight of the plant population) of skeletonweed was reduced by 35 percent compared to the biomass of the species when grown as a monoculture. The biomass was reduced by 53 percent when the canopies were intermingled. When both the canopies and roots were intermingled, the biomass was reduced by 69 percent, indicating an interaction in the competition for aboveground and belowground resources. Clover plants were the superior competitors for both aboveground and belowground resources, resulting in a combined effect of competition for these two resources (see Sections 11.11 and 18.4). This type of interaction has been seen in a variety of laboratory and field experiments. The species with the faster growth rate grows taller than the slower-growing species, reducing its available light, growth, and demand for belowground resources. The result is increased access to resources and further growth by the superior competitor.

In a series of field studies, James Cahill of the University of Alberta (Canada) examined the interactions between competition for above- and belowground resources in an old field grassland community in Pennsylvania. With an experimental design in the field similar to that used by Groves and Williams in the greenhouse, Cahill grew individual plants with varying degrees of interaction with the roots of neighboring plants through the use of root exclusion tubes made of PVC pipe. He planted the target plant inside an exclusion tube that was placed vertically into the soil to separate roots of the target plant from the roots of other individuals in the population that naturally surround it. He controlled the degree of belowground competition by drilling varying numbers of holes in the PVC pipe that allowed access to the soil volume from neighboring plants (see Section 11.11 and Figure 11.20 for further description of method). Cahill varied the level of aboveground competition by tying back the aboveground neighboring vegetation. In total, he created 16 combinations of varying intensities of above- and belowground interaction with neighboring plants. This experimental design allowed Cahill to compare the response of individuals exposed to varying combinations of above- and belowground competition to control plants isolated from neighbors. The results of his experiments show a clear pattern of interaction between above- and belowground competition. In general, increased competition for belowground resources functions to reduce growth rates and plant stature, the result of which is reduced competitive ability for light (aboveground resource).

13.9 Relative Competitive Abilities Change along Environmental Gradients

As environmental conditions change, so do the relative competitive abilities of species. Shifts in competitive ability can result either from changes in the carrying capacities of species (values of K; see Quantifying Ecology 13.1) related to a changing resource base or from changes in the physical environment that interact with resource availability.

Many laboratory and field studies have examined the outcomes of competition among plant species across experimental gradients of resource availability. Mike Austin and colleagues at the Commonwealth Scientific and Industrial Research Organization (CSIRO) research laboratory in Canberra, Australia, have conducted several greenhouse studies to explore the changing nature of interspecific competition among plant species across experimental gradients of nutrient availability. In one such experiment, the researchers examined the response of six species of thistle along a gradient of nutrient availability (application of nutrient solution). Plants were grown both in monoculture (single species) and mixture (all six species) under 11 different nutrient treatments, ranging from 1/64 to 16 times the recommended concentration of standard greenhouse nutrient solution. After 14 weeks, the plants were harvested, and their dry weights were determined. Responses of the six species along the nutrient gradient for monoculture and mixture experiments are shown in Figure 13.8.

Interpreting Ecological Data

1. Q1. Which of the three species of thistle included in the graph had the highest biomass production under the 1/64 nutrient treatment? What does this imply about this species’ competitive ability under low nutrient availability relative to other thistle species?

2. Q2. Using relative biomass production at each treatment level as an indicator of competitive ability, which thistle species is the superior competitor under the standard concentration of nutrient solution (1.0)?

3. Q3. At which nutrient level is the relative biomass of the three species most similar (smallest difference in the biomass of the three species)?

Two important results emerged from the experiment. First, when grown in mixture, the response of each species along the resource gradient differed from the pattern observed when grown in isolation—interspecific competition directly influenced the patterns of growth for each species. Second, the relative competitive abilities of the species changed along the nutrient gradient. This result was easily seen when the response of each species in the mixed-species experiments was expressed on a relative basis. The relative response of each species across the gradient was calculated by dividing the biomass (dry weight) value for each species at each nutrient level by the value of the species that achieved the highest biomass at that level. The relative performance of each species at each nutrient level then ranged from 0 to 1.0. Relative responses of the three dominant thistle species along the nutrient gradient are shown in Figure 13.9. Note that Carthamus lanatus was the superior competitor under low nutrient concentrations, Carduus pycnocephalus at intermediate values, and Silybum marianum at the highest nutrient concentrations.

In a series of field experiments, Richard Flynn and colleagues at the University of KwaZulu-Natal (South Africa) examined trade-offs in competitive ability among five perennial C4 grass species at different levels of soil fertility and disturbance. Soil fertility treatments were established through the application of different levels of fertilizer, whereas varying levels of clipping were used to simulate disturbance resulting from grazing by herbivores. Individuals of the five grass species were grown in both monoculture and mixtures at each treatment level. The results of their experiments show a pattern of changing relative competitive abilities of the species along the gradients of soil fertility and disturbance (Figure  13.10). Moreover, in some of the results there were clear interactions between soil fertility and disturbance on competitive outcomes.

Field studies designed to examine the influence of interspecific competition across an environmental gradient often reveal that multiple environmental factors interact to influence the response of organisms across the landscape. In New England salt marshes, the boundary between frequently flooded low marsh habitats and less frequently flooded high marsh habitats is characterized by striking plant zonation in which monocultures of the cordgrass Spartina alterniflora (smooth cordgrass) dominate low marsh habitats, whereas the high marsh habitat is generally dominated by Spartina patens (Figure 13.11a). The gradient from high to low marsh is characterized by changes in nutrient availability as well as increasing physical stress relating to waterlogging, salinity, and oxygen availability in the soil and sediments. In a series of field experiments, ecologist Mark Bertness of Brown University found that S. patens individuals transplanted into the low marsh zone (dominated by S. alterniflora) were severely stunted with or without S. alterniflora neighbors, that is, with or without competition (Figure 13.11b). In contrast, S. alterniflora transplants grew vigorously in the high marsh (zone dominated by S. patens) when neighbors were removed (without competition), but were excluded from the high marsh when S. patens was present, that is, with competition (Figure  13.11c). Bertness also observed that S. alterniflora rapidly invaded the high marsh habitats in the absence of S. patens. He concluded that S. alterniflora dominates the physically stressful low marsh habitats because of its ability to persist in anoxic (low oxygen) soils, but it is competitively excluded from the high marsh by S. patens. S. patens is limited to high marsh habitats as a result of its inability to tolerate the harsh physical conditions in frequently flooded low marsh habitats.

Chipmunks furnish a striking example of the interaction of competition and tolerance to physical stress in determining species distribution along an environmental gradient. In this case, physiological tolerance, aggressive behavior, and restriction to habitats in which one organism has competitive advantage all play a part. On the eastern slope of the Sierra Nevada live four species of chipmunks: the alpine chipmunk (Tamias alpinus), the lodgepole chipmunk (Tamias speciosus), the yellow-pine chipmunk (Tamias amoenus), and the least chipmunk (Tamias minimus). Each of these species has strongly overlapping food requirements, and each species occupies a different altitudinal zone (Figure 13.12).

The line of contact between chipmunks is determined partly by interspecific aggression. Aggressive behavior by the dominant yellow-pine chipmunk determines the upper range of the least chipmunk. Although the least chipmunk can occupy a full range of habitats from sagebrush desert to alpine fields, it is restricted in the Sierra Nevada to sagebrush habitat. Physiologically, it is more capable of handling heat stress than the others, enabling it to inhabit extremely hot, dry sagebrush. In a series of field experiments, ecologist Mark Chappell of Stanford University found that when the yellow-pine chipmunk is removed from its habitat, the least chipmunk moves into vacated open pine woods. However, if the least chipmunk is removed from the sagebrush habitat, the yellow-pine chipmunk does not invade the habitat. The aggressive behavior of the lodgepole chipmunk in turn determines the upper limit of the yellow-pine chipmunk. The lodgepole chipmunk is restricted to shaded forest habitat because it is vulnerable to heat stress. Most aggressive of the four, the lodgepole chipmunk also may limit the downslope range of the alpine chipmunk. Thus, the range of each chipmunk is determined both by aggressive exclusion and by its ability to survive and reproduce in a habitat hostile to the other species.

Quantifying Ecology 13.1 Competition under Changing Environmental Conditions: Application of the Lotka–Volterra Model

Under any set of environmental conditions, the outcome of interspecific competition reflects the relative abilities of the species involved to gain access and acquire the essential resources required for survival, growth, and reproduction. As we have seen in the analysis of interspecific competition using the Lotka–Volterra equations, two factors interact to influence the outcome of competition—the competition coefficients (α and β), and the carrying capacities of the species involved (K1 and K2). The competition coefficients represent the per capita effect of an individual of one species on the other. These values will be a function of both the overlap in diets and the rates of resource uptake of the two species. These values, therefore, reflect characteristics of the species. In contrast, the carrying capacities are a function of the resource base (availability) for each species in the prevailing environment. Changes in environmental conditions that influence resource availability, therefore, influence the relative carrying capacities of the species and can directly influence the nature of competition.

Consider, for example, two species (species 1 and 2) that draw on the same limiting food resource: seeds. The diets of the two species are shown in Figure 1a. Note that the overlap in diet of the two species is symmetric. If the rate of food intake (seeds eaten per unit time) is the same, we can assume that the competition coefficients are the same. For this example, let us assume a value of 0.5 for both α and β.

Now let’s assume that the size distribution of seeds and their abundance vary as a function of environmental conditions. For example, in Figure 1b the average seed size increases from environment A to B and C. As the size distribution of seeds changes, so will the carrying capacity (K) for each species. Now assume that the carrying capacities of the two species vary as shown in the following table.

13.10 Interspecific Competition Influences the Niche of a Species

Previously, we defined the ecological niche of a species as the range of physical and chemical conditions under which it can persist (survive and reproduce) and the array of essential resources it uses and drew the distinction between the concepts of fundamental and realized niche (Chapter 12, Section 12.6). The fundamental niche is the ecological niche in the absence of interactions with other species, whereas the realized niche is the portion of the fundamental niche that a species actually exploits as a result of interactions with other species. As preceding examples have illustrated, competition may force species to restrict their use of space, range of foods, or other resource-oriented activities. As a result, species do not always occupy that part of their fundamental niche where conditions yield the highest growth rate, reproductive rate, or fitness. The work of Jessica Gurevitch of the University of New York–Stony Brook illustrates this point well. Gurevitch examined the role of interspecific competition on the local distribution of Stipa neomexicana, a C3 perennial grass found in the semiarid grassland communities of southeastern Arizona. Stipa is found only on the dry ridge crests where grass cover is low, rather than in moister, low-lying areas below the ridge crests where grass cover is greater. In a series of experiments, Gurevitch removed neighboring plants from individual Stipa plants in ridge-crest, midslope, and lower-slope habitats. She compared the survival, growth, and reproduction of these plants with control individuals (whose neighboring plants were not removed). Her results clearly show that Stipa has a higher growth rate, produces more flowers per plant, and has higher rates of seedling survival in midslope and lower-slope habitats (Figure  13.13). But its population density in these habitats is limited by competition with more successful grass species. Thus, Stipa distribution (or realized niche) is limited to suboptimal habitats because of interspecific competition.

Interpreting Ecological Data

1. Q1. How does the influence of interspecific competition on seedling survival of Stipa differ between the ridge-crest and lower-slope habitats?

2. Q2. Experiment results show that Stipa individuals can effectively grow at the lower slope even under conditions of interspecific competition, as indicated by values of mean basal area in part (b). Based on the results in Figure 13.13, what part(s) of the Stipa life cycle are most heavily influenced by interspecies competition, and how would these limitations affect distribution of the species on the landscape?

Much of the evidence for competition comes from studies, such as the one just presented, demonstrating the contraction of a fundamental niche in the presence of a competitor. Conversely, when a species’ niche expands in response to the removal of a competitor, the result is termed competitive release . Competitive release may occur when a species invades an island that is free of potential competitors, moves into habitats it never occupied on a mainland, and becomes more abundant. Such expansion may also follow when a competing species is removed from a community, allowing remaining species to move into microhabitats they previously could not occupy. Such was the case with the distribution of cattails along the gradient of water depth discussed previously, where in the absence of competition from Typha latifoli, the distribution of Typha angustifolia expanded to areas above the shoreline (expressed as negative values of water depth; see Figure 12.13).

An example of competitive release in a lake ecosystem is presented by Daniel Bolnick and colleagues at the University of Texas. Bolnick and his colleagues tested for short-term changes in the feeding niche of the three-spine stickleback (Gasterosteus aculeatus) after experimentally manipulating the presence or absence of two interspecific competitors: juvenile cut-throat trout (Oncorhynchus clarki) and prickly sculpin (Cottus asper). Direct examination of stomach contents of sculpin and trout reveals overlap with stickleback diets. Sculpin are exclusively benthic feeders, whereas juvenile trout feed at the surface and in the water column. In contrast, stickleback feed in both microhabitats. The experiment consisted of 20 experimental enclosures (made of netting) in Blackwater Lake on northern Vancouver Island, British Columbia. Five replicate blocks of four enclosures each were distributed along the shoreline of the lake. Sticklebacks collected from similar habitats nearby were placed in the enclosures. The enclosures in each of the blocks were assigned to one of four treatments: (1) competition with sculpin and trout present, (2) release from sculpin with trout present, (3) release from trout with sculpin present, and (4) total release with no competitors. The experimental treatments were left undisturbed for 15 days, after which all sticklebacks were removed, and the researchers identified (to the lowest feasible taxonomic level) and counted prey in the stomach of each stickleback. The diversity of prey species in the diet of the sticklebacks in each treatment was used as a measure of niche breadth. Results of the experiment reveal no significant change in the niche breadth (diversity of prey consumed) for the stickleback population when released from competition from sculpin. When released from competition from juvenile cut-throat trout, however, the researchers observed a significant expansion of niche breadth for the stickleback population (Figure 13.14).

13.11 Coexistence of Species Often Involves Partitioning Available Resources

All terrestrial plants require light, water, and essential nutrients such as nitrogen and phosphorus. Consequently, competition between various co-occurring species is common. The same is true for the variety of insect-feeding bird species inhabiting the canopy of a forest, large mammalian herbivores feeding on grasslands, and predatory fish species that make the coral reef their home. How is it that these diverse arrays of potential competitors can coexist in the same community? The competitive exclusion principle introduced in Section 13.5 suggests that if two species have identical resource requirements, then one species will eventually displace the other. But how different do two species have to be in their use of resources before competitive exclusion does not occur (or conversely, how similar can two species be in their resource requirements and still coexist)?

We have seen that the coexistence of competitors is associated with some degree of “niche differentiation”—differences in the range of resources used or environmental tolerances—in the species’ fundamental niches. Observations of similar species sharing the same habitat suggest that they coexist by partitioning available resources. Animals use different kinds and sizes of food, feed at different times, or forage in different areas. Plants require different proportions of nutrients or have different tolerances for light and shade. Each species exploits a portion of the resources unavailable to others, resulting in differences among co-occurring species that would not be expected purely as a result of chance.

Field studies provide many reports of apparent resource partitioning. One example involves three species of annual plants growing together on prairie soil abandoned one year after plowing. Each plant exploits a different part of the soil resource (Figure 13.15). Bristly foxtail (Setaria faberii) has a fibrous, shallow root system that draws on a variable supply of moisture. It recovers rapidly from drought, takes up water rapidly after a rain, and carries on a high rate of photosynthesis even when partially wilted. Indian mallow (Abutilon theophrasti) has a sparse, branched taproot extending to intermediate depths, where moisture is adequate during the early part of the growing season but is less available later on. The plant is able to carry on photosynthesis at low water availability (Section 6.10). The third species, smartweed (Polygonum pensylvanicum), has a taproot that is moderately branched in the upper soil layer and develops mostly below the rooting zone of other species, where it has a continuous supply of moisture.

Apparent resource partitioning is also common among related animal species that share the same habitat and draw on a similar resource base. Tamar Dayan, at Tel Aviv University, examined possible resource partitioning in a group of coexisting species of wild cats inhabiting the Middle East. Dayan and colleagues examined differences among species in the size of canine teeth, which are crucial to wild cats in capturing and killing their prey. For these cats, there is a general relationship between the size of canine and the prey species selected. Dayan found clear evidence of systematic differences in the size of the canine teeth, not only between male and female individuals within each of the species (sexual dimorphism) but also among the three coexisting cat species (Figure 13.16; see also Chapter 10). The pattern observed suggests an exceptional regularity in the spacing of species along the axis defined by the average size of canine teeth (x-axis in Figure 13.16). Dayan and colleagues hypothesize that intraspecific and interspecific competition for food has resulted in natural selection favoring the observed differences, thereby reducing the overlap in the types and sizes of prey that are taken.

The patterns of resource partitioning discussed previously are a direct result of differences among co-occurring species in specific physiological, morphological, or behavioral adaptations that allow individuals access to essential resources while at the same time function to reduce competition (see Chapter  5). Because the adaptations function to reduce competition, they are often regarded as a product of coevolutionary forces (see Chapter 12, Sections 12.3 and Section 12.6 for discussion and example of coevolution driven by competition). Although patterns of resource partitioning observed in nature are consistent with the hypothesis of phenotypic divergence arising from coevolution between competing species, it is difficult to prove that competition functioned as the agent of natural selection that resulted in the observed differences in resource use (observed differences in fundamental niches of the species). Differences among species may relate to adaptation for the ability to exploit a certain environment or range of resources independent of competition. Differences among species have evolved over a long period of time, and we have limited or no information about resources and potential competitors that may have influenced natural selection. This issue led Joseph Connell, an ecologist at the University of California–Santa Barbara, to refer to the hypothesis of resource portioning as a product of coevolution between competing species as the “ghosts of competition past.” Unable to directly observe the role of past competition on the evolution of characteristics, some of the strongest evidence supporting the role of “competition past” comes from studies examining differences in the characteristics of subpopulations of a species that face different competitive environments. A good example is the work of Peter Grant and Rosemary Grant, of Princeton University, involving two Darwin’s finches of the Galápagos Islands. The Grants studied the medium ground finch (Geospiza fortis) and the small ground finch (Geospiza fuliginosa), both of which feed on an overlapping array of seed sizes—for further discussion and illustrations, see Section 5.9. On the large island of Santa Cruz, where the two species of finch coexist, the distribution of beak sizes (phenotypes) of the two species does not overlap. Average beak size is significantly larger for G. fortis than for the smaller G. fuliginosa (Figure  13.17a). On the adjacent—and much smaller—islands of Los Hermanos and Daphne Major, the two species do not coexist, and the distributions of beak sizes for the two species are distinctively different from the patterns observed on Santa Cruz. The medium ground finch is allopatric (lives separately) on the island of Daphne Major, and the small ground finch is allopatric on Los Hermanos. Populations of each species on these two islands possess intermediate and overlapping distributions of beak sizes (Figures 13.17b and 13.17c). These patterns suggest that on islands where the two species coexist, competition for food results in natural selection favoring medium ground finch individuals with a large beak size that can effectively exploit larger seeds while also favoring small ground finch individuals that feed on smaller seeds. The outcome of this competition was a shift in feeding niches. When the shift involves features of the species’ morphology, behavior, or physiology, it is referred to as character displacement .

The preceding example suggests that the competing species on the island of Santa Cruz exhibit character displacement as a result of coevolutionary forces—that is, divergence in phenotypic traits relating to the exploitation of a shared and limited resource. However, until recently, the process of character displacement had never been documented by direct observational data. The first direct evidence of character displacement is provided by the work of Peter and Rosemary Grant on the population of G. fortis inhabiting the small island of Daphne Major.

Before 1982, G. fortis (medium ground finch) was the only species of ground finch inhabiting the island of Daphne Major. The situation changed in 1982 when a new competitor species emigrated from the larger adjacent islands—the large ground finch, Geospiza magnirostris (see Section 5.9 and Figure  5.20). G. magnirostris is a potential competitor on the island as a result of diet overlap with G. fortis. G. magnirostris feeds primarily on seeds of the herbaceous forb, Jamaican feverplant (Tribulus cistoides). The seeds are contained within a hard seed coat and exposed when a finch cracks or tears away the woody outer coating. Large-beaked members of the G. fortis population also feed on these seeds; in fact, during the 1976–1977 drought, the survival of the population depended on this seed resource (see Section 5.6 for a discussion of natural selection in this population).

Initially, the population of G. magnirostris on Daphne Major was too small in relation to the food supply to have anything but a small competitive effect on G. fortis. From 1982 to 2003, however, the population increased. Then little rain fell on the island during 2003 and 2004, and populations of both finch species declined dramatically as a result of declining food resources. During this period, G. magnirostris depleted the supply of large seeds from the Jamaican feverplant, causing the G. fortis population to depend on the smaller seed resources on the island. The result of this shift in resource availability because of competition from G. magnirostris was that during 2004 and 2005, G. fortis experienced strong directional selection against individuals with large beaks. The resulting decrease in the average beak size of the G. fortis population provides a clear example of the coevolutionary process of character displacement.

13.12 Competition Is a Complex Interaction Involving Biotic and Abiotic Factors

Demonstrating interspecific competition in laboratory “bottles” or the greenhouse is one thing; demonstrating competition under natural conditions in the field is another. In the field, researchers (1) have little control over the environment, (2) have difficulty knowing whether the populations are at or below carrying capacity, and (3) lack full knowledge of the life history requirements or the subtle differences between the species.

In the previous sections, we reviewed an array of studies examining the role of competition in the field. Perhaps the most common are removal experiments, in which one of the potential competitors is removed and the response of the remaining species is monitored. These experiments might appear straightforward, yielding clear evidence of competitive influences. But removing individuals may have direct and indirect effects on the environment that are not intended or understood by the investigators and that can influence the response of the remaining species. For example, removing (neighboring) plants from a location may increase light reaching the soil surface, soil temperatures, and evaporation. The result may be reduced soil moisture and increased rates of decomposition, influencing the abundance of belowground resources. These sometimes “hidden treatment effects” can hinder the interpretation of experimental results.

As we have seen in previous sections, competition is a complex interaction that seldom involves the interaction between two species for a single limiting resource. Interaction between species involves a variety of environmental factors that directly influence survival, growth, and reproduction; these factors vary in both time and space. The outcome of competition between two species for a specific resource under one set of environmental conditions (temperature, salinity, pH, etc.) may differ markedly from the outcome under a different set of environmental conditions. As we shall see in the following chapters, competition is only one of many interactions occurring between species—interactions that ultimately influence population dynamics and community structure.

Ecological Issues & Applications Is Range Expansion of Coyote a Result of Competitive Release from Wolves?

Before European settlement, two species of wild dog (genus Canis) were among the most abundant large carnivores occupying the North American continent. The gray wolf, Canis lupus, once ranged from the Atlantic to the Pacific coast and from Alaska to northern Mexico (Figure 13.18). It occurred in virtually all North American habitats (grasslands, eastern deciduous forest, northern conifer forest, southwest desert, etc.). In contrast, the coyote (Canis latrans) had a much more restricted distribution to the prairie grassland and desert habitats of the Great Plains and desert region of the southwest and Mexico (Figure 13.19). Since European settlement of the continent, however, the fate of these two species has taken different paths.

As early as 1630, the Massachusetts Bay Colony paid an average month’s salary for any wolf that was killed. Bounties like this continued until the last wolf in the Northeast was killed around 1897. The fate of the wolf population in other areas of its range was similar. Settlers moving westward depleted the populations of bison, deer, elk, and moose on which the wolves preyed. Wolves then turned to attacking sheep and cattle, and to protect livestock, ranchers and government agencies began an eradication campaign. Bounty programs initiated in the 19th century continued as late as 1965. Wolves were trapped, shot, dug from their dens, and hunted with dogs. Poisoned animal carcasses were left out for wolves, a practice that also killed eagles, ravens, foxes, bears, and other animals that fed on the tainted carrion. By the time wolves were protected by the Endangered Species Act of 1973, only a few hundred remained in extreme northeastern Minnesota and a small number on Isle Royale, Michigan.

In contrast to the gray wolf, the coyote did not originally occur in eastern North America, and with the westward expansion of settlement into the Great Plains, the coyote was perceived as less of a threat to farmers and ranchers. By the turn of the 20th century, it began to take advantage of newly open habitat that agriculture and logging had created, and its distribution expanded eastward. There were two main waves of colonization, northern and southern (Figure 13.19). The northern wave occurred first—coyote were reported in Michigan in about 1900, in southern Ontario by 1919, and in northern New York in the late 1930s. Most of the southeast was not colonized until the 1960s. Whereas the gray wolf population has been virtually eliminated in the continental United States, the range of the coyote has expanded to cover most of the areas once occupied by wolves, and coyote now occupy virtually every habitat in eastern North America (compare Figures 13.18 and 13.19) from forests, wooded areas, grassland, and agricultural land to suburban areas.

The concurrent expansion of the coyote with the decline of the wolf population in North America has caused ecologists to question whether the two occurrences are linked in some way. In North American ecosystems where gray wolves occur, interactions with other large carnivores are common, with competition being most intense with species having a similar ecology. Interference competition (see Section 13.1) occurs between the wolves and coyotes, with wolves limiting coyote access to resources by direct aggression. Field studies in regions where wolves and coyotes overlap indicate that coyotes are excluded from wolf territories and that wolves will go out of their way to kill coyotes. One of the leading hypotheses put forward to explain the dramatic range expansion of the coyote is that the eradication of the gray wolf from its former range may have reduced the competitive pressures limiting coyotes to their former range: range expansion is a result of “competitive release” (see Section 13.10). Now as a result of recent conservation efforts, ecologists are able to test this hypothesis directly.

Thanks to conservation efforts, the gray wolf is beginning to make a comeback. The wolf’s comeback within the United States is as a result of its listing under the Endangered Species Act, which provided protection from unregulated killing and resulted in increased scientific research, along with reintroduction and management programs. As of 2013 about 2200 wolves live in Minnesota, 8 on Lake Superior’s Isle Royale, about 650 in Michigan’s Upper Peninsula, and at least 800 in Wisconsin. In the northern Rocky Mountains, the U.S. Fish and Wildlife Service reintroduced gray wolves into Yellowstone National Park and U.S. Forest Service lands in central Idaho in 1995 and 1996. The reintroduction was successful, and as of 2013 there were at least 1650 wolves in the northern Rocky Mountains of Montana, Idaho, and Wyoming. These reintroductions of wolves into areas now occupied by coyotes have enabled ecologists to directly examine the role of competition on the populations of the two carnivores and test the hypothesis that the range expansion of the coyote in the United States is in part the result of competitive release from wolves.

Kim Berger and Eric Gese of Utah State University used data collected on wolf and coyote distribution and abundance to test the hypothesis that interference competition with wolves limits the distribution and abundance of coyotes in two regions of the Northern Rocky Mountains in which wolves have been recently reintroduced. From August 2001 to August 2004, the two researchers gathered data on cause-specific mortality and survival rates of coyotes captured at wolf-free and wolf-abundant sites in Grand Teton National Park (GTNP), and data on population densities of both species at three study areas across the Greater Yellowstone Ecosystem (GYE), to determine whether competition with wolves is sufficient to reduce coyote densities in these areas.

Berger and Gese found that although coyotes were the numerically dominant predator, across the GYE, densities varied spatially and temporally as a function of wolf abundance. Mean coyote densities were 33 percent lower at wolf-abundant sites in GTNP, and densities declined 39 percent in Yellowstone National Park following wolf reintroduction. A strong negative relationship between coyote and wolf densities (Figure 13.20), both within and across study sites, supports the hypothesis that competition with wolves limits coyote populations. Overall mortality of coyotes resulting from wolf predation was low but differed significantly for resident and transient individuals. Resident coyotes were members of packs that defended well-defined territories, whereas transients were associated with larger areas that encompassed the home ranges of several resident packs but were not associated with a particular pack or territory. Wolves were responsible for 56 percent of transient coyote deaths. In addition, dispersal rates of transient coyotes captured at wolf-abundant sites were 117 percent higher than for transients captured in wolf-free areas.

The work by Jerod Merkle and colleagues at the Yellowstone Wolf Project (Yellowstone Center for Resources, Yellowstone National Park) provides a detailed picture of the nature of competitive interactions between wolves and coyotes in areas where wolves have been reintroduced. In a series of field studies, the researchers examined interference competition between gray wolves and coyotes in Yellowstone National Park using radio-collared wolves (Figure 13.21). Merkle and colleagues documented 337 wolf–coyote interactions from 1995 to 2007. The majority (75 percent) of interactions occurred at the sites of wolf-killed ungulate carcasses (elk, buffalo, moose, mule deer, etc.) with coyotes attempting to scavenge. Wolves initiated the majority of encounters (85 percent), generally outnumbered coyotes (39 percent), and dominated (91 percent) most interactions. Wolves typically (79 percent) chased coyotes without physical contact; however, 7 percent of encounters resulted in a coyote death. Interactions decreased over time, suggesting coyote adaptation or a decline in coyote density. The results clearly show that wolves dominate interactions with coyotes.

Although data are limited to the few regions in which wolf populations have been successfully introduced, when combined with the results of studies of wolf–coyote interactions and population studies for regions of North America where these two species naturally co-occur (regions of Minnesota and Canada), a consistent picture emerges that the dramatic range expansion of coyote over the past century is as a result, at least in part, of the decline of wolf populations throughout most of its former range.

Summary

Interspecific Competition 13.1

In interspecific competition, individuals of two or more species share a resource in short supply, thus reducing the fitness of both. As with intraspecific competition, competition between species can involve either exploitation or interference. Six types of interactions account for most instances of interspecific competition: (1) consumption, (2) preemption, (3) overgrowth, (4) chemical interaction, (5) territorial, and (6) encounter.

Competition Model 13.2–13.3

The Lotka–Volterra equations describe four possible outcomes of interspecific competition. species 1 may outcompete species 2; species 2 may outcompete species 1. Both of these outcomes represent competitive exclusion. The other two outcomes involve coexistence. One is unstable equilibrium, in which the species that was most abundant at the outset usually outcompetes the other. A final possible outcome is stable equilibrium, in which two species coexist but at a lower population level than if each existed without the other.

Experimental Tests 13.4

Laboratory experiments with species interactions support the Lotka–Volterra model.

Competitive Exclusion 13.5

Experiment results led to the formulation of the competitive exclusion principle—two species with exactly the same ecological requirements cannot coexist. This principle has stimulated critical examinations of competitive relationships outside the laboratory, especially of how species coexist and how resources are partitioned.

Nonresource Factors 13.6

Environmental factors such as temperature, soil or water pH, relative humidity, and salinity directly influence physiological processes related to growth and reproduction but are not consumable resources that species compete over. By differentially influencing species within a community, these nonresource factors can influence the outcome of competition.

Environmental Variability 13.7

Environmental variability may give each species a temporary advantage. It allows competitors to coexist, whereas under constant conditions one would exclude the other.

Multiple Factors 13.8

In many cases, competition between species involves multiple resources. Competition for one resource often influences an organism’s ability to access other resources.

Environmental Gradients 13.9

As environmental conditions change, so may the relative competitive ability of species. Shifts in competitive ability can result either from changes in the carrying capacities related to a changing resource base or from changes in the physical environment that interact with resource availability. Natural environmental gradients often involve the covariation of multiple factors—both resource and nonresource factors—such as salinity, temperature, and water depth.

Niche 13.10

A species’ fundamental niche compresses or shifts when competition restricts the species’ type of food or habitat. In some cases, the realized niche may not provide optimal conditions for the species. In the absence of competition, the species may experience competitive release, and its niche may expand.

Resource Partitioning 13.11

Many species that share the same habitat coexist by partitioning available resources. When each species exploits a portion of the resources unavailable to others, competition is reduced. Resource partitioning is often viewed as a product of the coevolution of characteristics that function to reduce competition. Interspecific competition can reduce the fitness of individuals. If certain phenotypes within the population function to reduce competition with individuals of other species, those individuals will encounter less competition and increased fitness. The result is a shift in the distribution of phenotypes (characteristics) within the competing population(s). When the shift involves features of the species’ morphology, behavior, or physiology, it is referred to as character displacement.

Complexity of Competition 13.12

Competition is a complex interaction that seldom involves the interaction between two species for a single limiting resource. Competition involves a variety of environmental factors that directly influence survival, growth, and reproduction—factors that vary in both time and space.

Wolves and Coyotes Ecological Issues & Applications

The decline of gray wolf populations throughout much of North America have been paralleled by a dramatic expansion in the range of coyotes. Evidence from areas in which wolves have been reintroduced suggests that the expansion of coyotes was in part a result of competitive release from wolf populations over the past century.