Interspecific Competition
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You should understand the concept of the ecological niche as a multidimensional hypervolume defined by resource use, and be familiar with the logistic growth equation \( \frac{dN}{dt} = rN \left(1 - \frac{N}{K} \right) \).
Why this matters
Competition is the primary driver of community structure and species distribution.
When two species require the same limiting resource, their populations are coupled; the growth of one directly inhibits the growth of the other. Understanding interspecific competition allows ecologists to predict which species will dominate a habitat, how biodiversity is maintained through niche partitioning, and how invasive species disrupt native communities. It bridges individual physiology and population dynamics, explaining why no two species occupy identical ecological roles in stable environments.
The Logic of Resource Sharing
Imagine two species of birds feeding on the same type of seed in a forest. If the seed supply is abundant, both populations grow independently. However, if the seed supply is limited, every seed consumed by one bird is a seed not available to the other. This creates a negative interaction where the presence of one species reduces the carrying capacity for the other. Unlike predation, where one species benefits, in competition both parties suffer a cost in terms of reduced growth rate, survival, or reproduction. The intensity of this interaction depends on how similar their resource requirements are. If Species A prefers large seeds and Species B prefers small seeds, they overlap only partially, and competition is weak. If both require exactly the same medium-sized seeds, they overlap completely, and competition is intense. This overlap is the fundamental mechanism that drives the competitive exclusion principle: in a stable environment, complete competitors cannot coexist indefinitely because one will inevitably outcompete the other for the limiting resource, leading to the local extinction or displacement of the inferior competitor. This process is not always violent; it can be subtle, manifesting as reduced body size, lower fecundity, or shifted activity times, but the mathematical outcome is the same: the population with the higher efficiency in resource acquisition will drive the other toward zero.
The Lotka–Volterra Competition Model
To quantify this interaction, ecologists extend the logistic growth equation by adding terms that account for the inhibitory effect of the other species. For Species 1, the growth rate is reduced by a term proportional to the density of Species 2. The modified equation is \( \frac{dN_1}{dt} = r_1 N_1 \left(1 - \frac{N_1 + \alpha_{12} N_2}{K_1} \right) \). Here, \( \alpha_{12} \) is the competition coefficient, representing the per-capita effect of Species 2 on Species 1. If \( \alpha_{12} = 1 \), one individual of Species 2 has the same impact on resources as one individual of Species 1. If \( \alpha_{12} = 0 \), Species 2 has no effect on Species 1. The term \( \alpha_{12} N_2 \) effectively converts the population of Species 2 into an equivalent number of Species 1 individuals in terms of resource consumption. This allows us to treat the combined resource usage as a single effective population size relative to the carrying capacity \( K_1 \). The same logic applies to Species 2 with the coefficient \( \alpha_{21} \). These coefficients are not fixed constants but depend on the specific resources being contested and the physiological efficiency of each species in utilizing them. By analyzing the isoclines where \( \frac{dN_1}{dt} = 0 \) and \( \frac{dN_2}{dt} = 0 \), we can map the phase plane to determine whether coexistence, exclusion, or bistability occurs. The relative magnitudes of \( K_1, K_2, \alpha_{12} \), and \( \alpha_{21} \) dictate the outcome, providing a rigorous framework for predicting competitive dynamics.
Conditions for Coexistence
Coexistence is possible only if intraspecific competition (competition within a species) is stronger than interspecific competition (competition between species). Mathematically, this requires that each species limits its own population growth more strongly than it limits the other. Specifically, the condition is \( \alpha_{12} < \frac{K_1}{K_2} \) and \( \alpha_{21} < \frac{K_2}{K_1} \). If these inequalities hold, the zero-growth isoclines intersect within the first quadrant, creating a stable equilibrium point where both species persist. This biological reality often arises through resource partitioning, where species evolve to use different portions of the resource spectrum. For example, in Darwin’s finches, different species specialize on different seed sizes, reducing the overlap in their niches. This reduces the effective competition coefficients \( \alpha_{12} \) and \( \alpha_{21} \), allowing them to coexist in the same habitat. If the inequalities are reversed, such that \( \alpha_{12} > \frac{K_1}{K_2} \) and \( \alpha_{21} > \frac{K_2}{K_1} \), the system exhibits bistability. In this case, the outcome depends on initial population densities: whichever species starts with a higher relative abundance will drive the other to extinction. This hysteresis effect means that small perturbations can lead to dramatic shifts in community composition, making the ecosystem sensitive to initial conditions and historical contingencies.
Apparent Competition and Indirect Effects
Not all competitive interactions are direct. Apparent competition occurs when two species share a common predator or parasite, and the predator’s population is regulated by the sum of both prey populations. In this scenario, an increase in Species 1 leads to an increase in the predator population, which in turn increases predation pressure on Species 2. Species 2 suffers a decline even though it does not directly compete with Species 1 for resources. This indirect interaction mimics interspecific competition in its negative effect on population growth. The strength of apparent competition depends on the predator’s functional response and the relative abundance of the two prey species. If Species 1 is abundant, it can support a large predator population that suppresses Species 2, effectively excluding it from the habitat. This mechanism is crucial in understanding why some species are rare or absent from areas where their resources are abundant. It highlights that community structure is shaped not only by direct resource competition but also by the trophic interactions that link species through shared enemies. Ecologists must therefore consider the entire food web when assessing competitive outcomes, as indirect effects can be as strong as, or stronger than, direct competition for limiting resources.
The concept
Competition and the niche
Two species cannot occupy the same niche indefinitely.
A common misconception is that competition always leads to the extinction of the weaker species. In reality, if the competition coefficients are low enough due to niche differentiation, stable coexistence is possible. The key is not the absence of competition, but the balance between intra- and interspecific competition. If students assume that any overlap in resource use results in exclusion, they will fail to explain the high biodiversity observed in many ecosystems. The Lotka–Volterra model shows that coexistence is a stable equilibrium only when each species is a better competitor against itself than against the other, a condition that is frequently met in nature through evolutionary adaptation. C
Worked example
Problem. Two species of algae, Species A and Species B, compete for light. The carrying capacity of Species A in the absence of Species B is \( K_A = 100 \) individuals. The carrying capacity of Species B is \( K_B = 50 \) individuals. The competition coefficient \( \alpha_{AB} \) (effect of B on A) is 0.5, and \( \alpha_{BA} \) (effect of A on B) is 1.2. Determine if stable coexistence is possible and calculate the equilibrium population sizes if they coexist.
- Check the coexistence conditions: \( \alpha_{AB} < \frac{K_A}{K_B} \) and \( \alpha_{BA} < \frac{K_B}{K_A} \). Calculate \( \frac{K_A}{K_B} = \frac{100}{50} = 2 \). Since \( 0.5 < 2 \), the first condition is satisfied.
- Calculate \( \frac{K_B}{K_A} = \frac{50}{100} = 0.5 \). Since \( 1.2 \) is not less than \( 0.5 \), the second condition is violated. Therefore, stable coexistence is not possible.
- Since \( \alpha_{BA} > \frac{K_B}{K_A} \), Species A has a stronger effect on Species B than Species B has on Species A relative to their carrying capacities. This suggests Species A will outcompete Species B.
- To confirm, examine the isoclines. The zero-growth isocline for Species A is \( N_A + 0.5 N_B = 100 \). The zero-growth isocline for Species B is \( 1.2 N_A + N_B = 50 \). The intercepts for Species A are \( (100, 0) \) and \( (0, 200) \). The intercepts for Species B are \( (41.67, 0) \) and \( (0, 50) \).
- Since the isocline for Species A lies entirely outside the isocline for Species B (both intercepts are larger), Species A can reach its carrying capacity even in the presence of Species B, while Species B cannot. Thus, Species B is driven to extinction, and Species A persists at \( N_A = 100 \).
Units check. The population sizes are dimensionless counts of individuals, consistent with the definition of \( N \) in the Lotka–Volterra equations.
Three quick tests
- If \( \alpha_{12} = 0 \), what does this imply about the interaction between Species 1 and Species 2?
Answer
Species 2 has no effect on the growth rate of Species 1; they do not compete for the same limiting resources. - Why is intraspecific competition generally stronger than interspecific competition in stable communities?
Answer
Because individuals of the same species have identical resource requirements, leading to maximum overlap, whereas different species often partition resources, reducing overlap. - What is the outcome of competition if \( \alpha_{12} > \frac{K_1}{K_2} \) and \( \alpha_{21} > \frac{K_2}{K_1} \)?
Answer
Bistability; the species with the higher initial population density will exclude the other.
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Lecture notes checked line by line by the editor; every number in the worked example was recomputed.