1 Maukus

Interspecific Interactions Hypothesis Statement

The dual effect of ecological interactions on species' population size and production efficiency

In both experimental settings and natural ecosystems, ecological interactions among species are expected to affect ecosystem functioning in two different ways: i) by changing the population size of the various species, and ii) by changing their production efficiency, defined here broadly as the capacity of a species to produce biomass, through adaptive changes.

Traditional models in theoretical ecology have considered only the effects of species interactions on population size and have ignored their potential effects on species' adaptive changes. For instance, Lotka–Volterra models assume constant carrying capacities and interaction coefficients, but omit potential changes in species' production efficiency. These models predict that competitive interactions generate concave-down BEF relationships whereas mutualistic interactions generate concave-up relationships15,16. However, ecological interactions (e.g., competition, predation, etc) can also induce considerable adaptive changes20, which in turn may affect ecosystem functioning substantially. Adaptive responses to ecological interactions can range from short-term behavioral responses, to medium-term physiological and developmental phenotypic plasticity, to long-term evolutionary changes21. As an example, competition and predation can reduce individual body mass because of investment of energy to defend territories or to cover larger foraging areas or because of reduction in foraging time and places to avoid predators. Ecological interactions can also lead to niche shift over ecological time or character displacement over evolutionary time. These adaptive changes often result in increasing specialization-or more efficient use of available resources- in the presence of interacting species. For instance, studies of dietary and habitat specialization, potentially caused by intense competition, have shown that fishes increase their growth when feeding upon their preferred prey22 or when they reside on specific habitats23. Predation and competition are also known to trigger faster somatic growth to gain competitive advantage or escape size-dependent predation24,25,26,27,28; this will rapidly add to both production and standing stock of the community since prey body size will be larger and prey will growth faster to escape early mortality. Predation and competition can also cause early sexual maturation, leading to greater offspring production to compensate for induced mortality24. Several recent studies have showed that niche shifts contribute to the positive BEF relationships in both plants29 and insect pollinators30 even in small-scale experimental settings. Differential exploitation by predators creates a new niche axis that allows niche differentiation and hence complementarity between species17,31,32. Another ecological interaction, which is often underestimated, is facilitation, which can favor population and body size growth in at least one of the interacting species while causing harm to neither12,33. In short, by influencing species' production efficiency, ecological interactions have the potential to greatly influence ecosystem functioning.

To account for the dual effect of species interactions on ecosystem functioning through changes in the population size and production efficiency of the various species when species richness varies, we make three simplifying assumptions. First, ecosystem functioning (EF), as measured by some aggregate ecosystem properties such as total biomass, is the product of three terms:

  1. the average contribution of each species to ecosystem functioning in the absence of species interactions (),
  2. the net effect of species interactions on the contribution of each species (NE), and

  3. the number of species (SR).

Second, the net effect of species interactions on the contribution of each species (NE) is itself the product of two terms, one due to changes in population size (PS) and another due to changes in production efficiency (PE). Third, the effects of ecological interactions on population size and on production efficiency are power functions of species richness (e.g. Fig 3a). These assumptions yield the following equations:

and hence

In these equations, c is the power coefficient that captures the effect of species interactions on ecosystem functioning through changes in population sizes (where c measures the strength of the reduction in population size generated by competition or predation), and d is the power coefficient that captures the effect of species interactions on ecosystem functioning through changes in production efficiency. In turn, d-c determines the net effect of species interactions on the contribution of each species to ecosystem functioning (equation 5), and the sum 1+d-c determines the total effect of species richness on ecosystem functioning.

Figure 3

Effect of ecological interactions on biodiversity-ecosystem functioning relationships.

In a symmetrical community obeying Lotka–Volterra dynamics, there is a simple approximate relationship between the interspecific competition coefficient, α, and the power coefficient, c, that measures the strength of the reduction in population size generated by species interactions at low species richness (see demonstration in Fig. 4):

Although equation (7) is valid only at low species richness, since the BEF relationships predicted by the power and Lotka–Volterra models are both monotonic and their shape is governed by the single parameters c and α, equation (7) ensures that the qualitative shape of the BEF relationships is governed equivalently by c and α. Thus, ecosystem functioning (equation 6) is unaffected by species richness through changes in population sizes when interspecific competition is maximum (c = α = 1; note that α can technically be larger than 1 but then no stable coexistence is possible); it increases linearly when interspecific competition is minimum (c = α = 0); and it yields a concave-down BEF relationship when interspecific competition is intermediate (0 < c, α < 1), in agreement with previous theory16,18. In traditional Lotka-Volterra models, the only way the BEF relationship can be concave-up is when changes in population size are driven by mutualistic interactions (c, α < 0).

Figure 4

Lotka-Volterra competition models including changes in population size.

But as noted earlier, the Lotka-Volterra model ignores changes in species' production efficiency. If ecological interactions among species increase specialization and potential of facilitation, leading to increased production efficiency (which is likely as we illustrated with multiple examples earlier), the power parameter d is positive; d could also be negative in cases where interactions reduce production efficiency. The potential for d ranging from negative to positive broadens the spectrum of possible BEF relationships since even in purely competitive communities BEF relationships can be concave-up provided species respond to ecological interactions through production efficiency positively and more strongly than through population size (d > c). Under these conditions, adding more species will increase ecosystem functioning (equation 5) (i.e., the exponent 1+d-c > 1 in equation 6). Alternative scenarios of this framework are presented in Fig. 3.

The effect of ecological interactions on ecosystem functioning through changes in species' production efficiency is an important theoretical result as prior theory considered mainly the role of competitive interactions on population sizes and always predicted concave-down BEF relationships. Expanding traditional theory of communities obeying Lotka–Volterra dynamics (to include adaptive changes in species' production efficiency) shows that concave-down relationships in competitive communities can be changed into concave-up relationships. This occurs when the effect of ecological interactions on species' production efficiency is positive and larger than their effect on population size. This suggests that experiments can easily fail to reveal the positive role of ecological interactions on species' production efficiency, as competition, instead of specialization, is more likely to prevail in experimental settings. In other words, the “ghost of competition past” may not be evident in experiments as much as it is in natural systems. That is, when species are put together in a contained artificial experimental setup they are forced to compete or interact, which may lead to greater energy loss than under field conditions where specialization may have already occurred. Gravel et al.34 showed, for instance, that the BEF relationship changes as a result of niche evolution. Likewise, Reich et al.35 showed that over time the BEF relationship gets steeper, thus supporting the hypothesis of a greater specialization and a decrease in the energetic costs associated with competitive interactions early on in the experiments. Experiments are also carried out using small number of species, which reduces the spectrum and strength of ecological interactions likely to occur on natural systems. In all the studies reviewed in Covich et al.10, for instance, the highest number of species considered was 22, 75% of the studies considered less than 7 species. It is interesting to notice that if the data reported here were limited to the first 22 species encountered, the exponential relationships reported would not be evident nor significant.

The role of ecological interactions on species' production efficiency provides a parsimonious explanation for concave-up BEF relationships in diverse ecosystems like coral reefs or the deep-sea, where ecological interactions are likely to be strong and numerous and may have already led to resource specialization. We acknowledge that providing empirical support for this hypothesis will be challenging as measuring changes in species' production efficiency will require detailed measurements of individual-level responses, perhaps over evolutionary scales. Recent experiments have shown that evolutionary and long-term responses can have complex effects on BEF relationships. For instance, Gravel et al.34,36 found that evolving strains of bacteria can lead to the loss of BEF relationships over evolutionary time. In contrast, Reich et al.35 found that BEF become steeper among plant assemblages over time.

The effect of non-random community assembly

Several theoretical studies have documented the role of ordered extinctions in the BEF relationship16,18,37. These studies suggest that the order of sequential extinctions can yield concave-down relationships when species go extinct in an ordered sequence from the least efficient to the most efficient, or on the contrary, concave-up relationships when species go extinct in an ordered sequence from the most efficient to the least efficient.

An alternative interpretation for these patterns is that ecosystems are assembled in a successional order. For instance, ecosystems are likely to be colonized initially by small-bodied species (because they disperse faster or because they are more common than large-bodied species) and by lower trophic levels. Over time, colonization by larger-bodied species and higher trophic levels will occur as the presence of smaller species and lower trophic levels provides the energetic conditions for their persistence. Since species that are larger and belong to higher trophic levels tend to accumulate more biomass than smaller species from lower trophic levels, the former have a higher production efficiency. Mathematically, the ordered addition of more efficient species will tend to increase the power parameter 1+d-c in equation 6 and thus increase the slope of the BEF relationship. Patterns of BEF relationships for contrasting ordered additions by body size or production efficiency are shown in Fig. 5.

Figure 5

Effect of the order of community assembly on biodiversity-ecosystem functioning relationships.

It should be noted that ordered colonizations (through succession) and ordered extinctions are different mechanisms dealing with different aspects of community assembly and disassembly, respectively. Yet both of these processes cause similar effects on the shape of the BEF relationship. Ordered colonization from the least to the most efficient species yield a concave-up BEF relationship, just as do ordered extinction from the most to the least efficient species (see blue lines in Fig. 4). The prevalence of either mechanism (i.e., succession or ordered extinction) in natural ecosystems is to be determined, although they are both differentially supported for the marine observational studies considered here. Ordered colonization is likely to occur in both coral reef fishes and deep-sea nematodes whereas ordered extinctions may only apply to coral-reef fishes. Reef fishes can be differentially fished according to their body size and trophic level, while deep-sea small invertebrates (such as nematodes) occupy a relatively stable environment and thus there is little indication they will be driven to extinction preferentially by body size or trophic level given human activities.

Interspecific competition, in ecology, is a form of competition in which individuals of differentspecies compete for the same resources in an ecosystem (e.g. food or living space). This can be contrasted with interspecific cooperation, a type of symbiosis. Competition between members of the same species is called intraspecific competition.

If a tree species in a dense forest grows taller than surrounding tree species, it is able to absorb more of the incoming sunlight. However, less sunlight is then available for the trees that are shaded by the taller tree, thus interspecific competition. Leopards and lions can also be in interspecific competition, since both species feed on the same prey, and can be negatively impacted by the presence of the other because they will have less food.

Competition is only one of many interacting biotic and abiotic factors that affect community structure. Moreover, competition is not always a straightforward, direct, interaction. Interspecific competition may occur when individuals of two separate species share a limiting resource in the same area. If the resource cannot support both populations, then lowered fecundity, growth, or survival may result in at least one species. Interspecific competition has the potential to alter populations, communities and the evolution of interacting species. On an individual organism level, competition can occur as interference or exploitative competition.

Direct competition has been observed between individuals, populations and species, but there is little evidence that competition has been the driving force in the evolution of large groups. For example, between amphibians, reptiles and mammals.[1]


All of the types described here can also apply to intraspecific competition, that is, competition among individuals within a species. Also, any specific example of interspecific competition can be described in terms of both a mechanism (e.g., resource or interference) and an outcome (symmetric or asymmetric).

Based on mechanism[edit]

Exploitative competition, also referred to as resource competition, is a form of competition in which one species consumes and either reduces or more efficiently uses a shared limiting resource and therefore depletes the availability of the resource for the other species.[2] Thus, it is an indirect interaction because the competing species interact via a shared resource.

Interference competition is a form of competition in which individuals of one species interacts directly with individuals of another species via antagonistic displays or more aggressive behavior.

In a review and synthesis of experimental evidence regarding interspecific competition, Schoener[3] described six specific types of mechanisms by which competition occurs, including consumptive, preemptive, overgrowth, chemical, territorial, and encounter. Consumption competition is always resource competition, but the others are cannot always be regarded as exclusively exploitative or interference.

Separating the effect of resource use from that of interference is not easy. A good example of exploitative competition is found in aphid species competing over the sap in plant phloem. Each aphid species that feeds on host plant sap uses some of the resource, leaving less for competing species. In one study, Fordinae geoica was observed to out-compete F. formicaria to the extent that the latter species exhibited a reduction in survival by 84%. Another example is the one of competition for calling space in amphibians, where the calling activity of a species prevents the other one from calling in an area as wide as it would in allopatry[4]. A last example is driving of bisexual rock lizards of genus Darevskia from their natural habitats by a daughter unisexual form;[5] interference competition can be ruled out in this case, because parthenogenetic forms of the lizards never demonstrate aggressive behavior.

This type of competition can also be observed in forests where large trees dominate the canopy and thus allow little light to reach smaller competitors living below. These interactions have important implications for the population dynamics and distribution of both species.

Based on outcome[edit]

Main articles: Scramble competition and Contest competition

Scramble and contest competition refer to the relative success of competitors. Scramble competition is said to occur when each competitor is equal suppressed, either through reduction in survival or birth rates. Contest competition is said to occur when one or a few competitors are unaffected by competition, but all others suffer greatly, either through reduction in survival or birth rates. Sometimes these types of competition are referred to as symmetric (scramble) vs. asymmetric (contest) competition. Scramble and contest competition are two ends of a spectrum, of completely equal or completely unequal effects.

Apparent competition[edit]

Apparent competition is actually an example of predation that alters the relative abundances of prey on the same trophic level. It occurs when two or more species in a habitat affect shared natural enemies in a higher trophic level.[6] If two species share a common predator, for example, apparent competition can exist between the two prey items in which the presence of each prey species increases the abundance of the shared enemy, and thereby suppresses one or both prey species.[7] This mechanism gets its name from experiments in which one prey species is removed and the second prey species increases in abundance. Investigators sometimes mistakenly attribute the increase in abundance in the second species as evidence for resource competition between prey species. It is "apparently" competition, but is in fact due to a shared predator, parasitoid, parasite, or pathogen.


Many studies, including those cited previously, have shown major impacts on both individuals and populations from interspecific competition. Documentation of these impacts has been found in species from every major branch of organism. The effects of interspecific competition can also reach communities and can even influence the evolution of species as they adapt to avoid competition. This evolution may result in the exclusion of a species in the habitat, niche separation, and local extinction. The changes of these species over time can also change communities as other species must adapt.

Competitive exclusion[edit]

Main article: Gause's law

The competitive exclusion principle, also called "Gause's law"[8] which arose from mathematical analysis and simple competition models states that two species that use the same limiting resource in the same way in the same space and time cannot coexist and must diverge from each other over time in order for the two species to coexist. One species will often exhibit an advantage in resource use. This superior competitor will out-compete the other with more efficient use of the limiting resource. As a result, the inferior competitor will suffer a decline in population over time. It will be excluded from the area and replaced by the superior competitor.

A well-documented example of competitive exclusion was observed to occur between Dolly Varden charr (Trout)(Salvelinus malma) and white spotted char (Trout)(S. leucomaenis) in Japan. Both of these species were morphologically similar but the former species was found primarily at higher elevations than the latter. Although there was a zone of overlap, each species excluded the other from its dominant region by becoming better adapted to its habitat over time. In some such cases, each species gets displaced into an exclusive segment of the original habitat. Because each species suffers from competition, natural selection favors the avoidance of competition in such a way.

Niche differentiation[edit]

Main article: Niche differentiation

Niche differentiation is a process by which competitive exclusion leads to differences in resource use. In the previous example, niche differentiation resulted in spatial displacement. In other cases it may result in other changes that also avoid competition. If competition avoidance is achievable, each species will occupy an edge of the niche and will become more specialized to that area thus minimizing competition. This phenomenon often results in the separation of species over time as they become more specialized to their edge of the niche, called niche differentiation. The species do not have to be in separate habitats however to avoid niche overlap. Some species adapt regionally to utilizing different resources than they ordinarily would in order to avoid competition.

There have been several well-documented cases in birds where species that are very similar change their habitat use where they overlap. For example, they may consume different food resources or use different nesting habitat or materials. On the Galapagos Islands, finch species have been observed to change dietary specializations in just a few generations in order to utilize limited resources and minimize competition.

In some cases, third party species interfere to the detriment or benefit of the competing species. In a laboratory study, coexistence between two competing bacterial species was mediated by phage parasites.[9] This type of interaction actually helped to maintain diversity in bacterial communities and has far reaching implications in medical research as well as ecology. Similar effects have been documented for many communities as a result of the action of a keystone predator that preys on a competitively superior species.

Local extinction[edit]

Main article: Local extinction

Although local extinction of one or more competitors has been less documented than niche separation or competitive exclusion, it does occur. In an experiment involving zooplankton in artificial rock pools, local extinction rates were significantly higher in areas of interspecific competition.[10] In these cases, therefore, the negative effects are not only at the population level but also species richness of communities.

Impacts on communities[edit]

As mentioned previously, interspecific competition has great impact on community composition and structure. Niche separation of species, local extinction and competitive exclusion are only some of the possible effects. In addition to these, interspecific competition can be the source of a cascade of effects that build on each other. An example of such an effect is the introduction of an invasive species to the United States, purple-loosestrife. This plant when introduced to wetland communities often outcompetes much of the native flora and decreases species richness, food and shelter to many other species at higher trophic levels. In this way, one species can influence the populations of many other species as well as through a myriad of other interactions. Because of the complicated web of interactions that make up every ecosystem and habitat, the results of interspecific competition are complex and site-specific.

Competitive Lotka-Volterra model[edit]

Main article: Competitive Lotka–Volterra equations

The impacts of interspecific competition on populations have been formalized in a mathematical model called the Competitive Lotka–Volterra equations, which creates a theoretical prediction of interactions. It combines the effects of each species on the other. These effects are calculated separately for the first and second population respectively:

In these formulae, N is the population size, t is time, K is the carrying capacity, r is the intrinsic rate of increase and α and β are the relative competition coefficients.[11] The results show the effect that the other species has on the species being calculated. The results can be graphed to show a trend and possible prediction for the future of the species. One problem with this model is that certain assumptions must be made for the calculation to work. These include the lack of migration and constancy of the carrying capacities and competition coefficients of both species. The complex nature of ecology determines that these assumptions are rarely true in the field but the model provides a basis for improved understanding of these important concepts.

An equivalent formulation of these models[12] is:

In these formulae, is the effect that an individual of species 1 has on its own population growth rate. Similarly, is the effect that an individual of species 2 has on the population growth rate of species 1. One can also read this as the effect on species 1 of species 2. In comparing this formulation to the one above, we note that , and .

Coexistence between competitors occurs when and . We can translate this as coexistence occurs when the effect of each species on itself is greater the effect of the competitor.

There are other mathematical representations that model species competition, such as using non-polynomial functions.[13]

See also[edit]


  1. ^Sahney, S.; Benton, M.J.; Ferry, P.A. (2010). "Links between global taxonomic diversity, ecological diversity and the expansion of vertebrates on land"(PDF). Biology Letters. 6 (4): 544–547. doi:10.1098/rsbl.2009.1024. PMC 2936204. PMID 20106856. 
  2. ^Tilman, D. (1982). Resource Competition and Community Structure. Princeton, NJ: Princeton University Press.
  3. ^Schoener T. W. (1983). "Field experiments on interspecific competition". The American Naturalist. 122 (2): 240–285. doi:10.1086/284133. 
  4. ^Borzée, Amaël; Kim, Jun Young; Jang, Yikweon (7 Sep 2016). "Asymmetric competition over calling sites in two closely related treefrog species". Scientific Reports. 6: 32569. doi:10.1038/srep32569. PMC 5013533. PMID 27599461. 
  5. ^Tarkhnishvili David (2010). "Unisexual rock lizard might be outcompeting its bisexual progenitors in the Caucasus". Biological Journal of the Linnean Society. 101: 447–460. doi:10.1111/j.1095-8312.2010.01498.x. 
  6. ^Holt R. D., Lawton J. H. (1994). "The ecological consequences of shared natural enemies". Annual Review of Ecology and Systematics. 25: 495–520. doi:10.1146/annurev.ecolsys.25.1.495. 
  7. ^Holt, R. D. (1977.) Predation, apparent competition, and the structure of prey communities. Theoretical Population Biology 12: 197-229.
  8. ^Iannelli, Mimmo; Pugliese, Andrea (2014-01-01). Competition among species. UNITEXT. Springer International Publishing. pp. 175–208. doi:10.1007/978-3-319-03026-5_7. ISBN 978-3-319-03025-8. 
  9. ^Brockhurst, M.A., A. Fenton, B. Roulston and P.B. Rainey. 2006. The impact of phages on interspecific competition in experimental populations of bacteria. BMC Ecology6:19.
  10. ^Bengtsson J (1989). "Interspecific competition increases local extinction rate in a metapopulation system". Nature. 340: 713–715. doi:10.1038/340713a0. 
  11. ^Gotelli, N.J. 2008. A Primer of Ecology, 4th ed. Sinauer Associates, Sunderland, MA, USA.
  12. ^Stevens, M. H. H. (2009). A Primer of Ecology with R. (R. Gentleman, Hornik K., & G. Parmigiani, Eds.). Springer.
  13. ^Rabajante JF, Talaue CO (April 2015). "Equilibrium switching and mathematical properties of nonlinear interaction networks with concurrent antagonism and self-stimulation". Chaos, Solitons & Fractals. 73: 166–182. doi:10.1016/j.chaos.2015.01.018. 

Further reading[edit]

  • Begon, M., C.R. Townsend and J.L. Harper. 2006. Ecology: From Individuals to Ecosystems. Blackwell Publishing, Malden, MA.
  • Connell J.H. (1961). "Factors on the distribution of the barnacle Chthamalus stellatus". Ecology. 42 (4): 710–723. doi:10.2307/1933500. 
  • Giller, P. S. 1984. Community Structure and the Niche. Chapman & Hall, London.
  • Holekamp, K.E. 2006. Interspecific competition and anti-predator behavior. National Science Foundation. http://www.nsf.gov/
  • Inbar M., Eshel A., Wool D. (1995). "Interspecific competition among phloem-feeding insects mediated by induced host-plant sinks". Ecology. 76 (5): 1506–1515. doi:10.2307/1938152. 
  • Schoener T.W. (1983). "Field experiments on interspecific competition". American Naturalist. 122: 240. doi:10.1086/284133. 
  • Solomon, E. P., Berg, L. R., & Martin, D. W. (2002). Biology, sixth edition. (N. Rose, Ed.). Stamford, CT: Thomson Learning
  • Taniguchi Y. and S. Nakano 2000. Condition-Specific Competition: Implications for the Altitudinal Distribution of Stream Fishes. Ecology, 81. 7: 2027-2039
  • Weiner, J. 1994. The Beak of the Finch. Cambridge University Press, New York.

External links[edit]

Subadult male lion and spotted hyena in the Masai Mara. The two species share the same ecological niche, and are thus in competition with each other.
Naturalised purple-loosestrife plants growing in the Cooper Marsh Conservation Area, near Cornwall Ontario.

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