Original language | English |
---|---|
Title of host publication | Encyclopedia of animal behavior |
Editors | Jae C. Choe |
Place of Publication | Amsterdam |
Publisher | Elsevier Academic Press |
Pages | 209-216 |
Number of pages | 8 |
Volume | 2 |
Edition | 2nd |
ISBN (Electronic) | 9780128132524 |
ISBN (Print) | 9780128132517 |
DOIs | |
Publication status | Published - 2019 |
Abstract
Co-evolution occurs when one species evolves in response to evolutionary changes in another, the result being an evolutionary feedback involving two or more species.
It is an important and ubiquitous process in nature that can occur any time populations of different species interact through evolutionary time, with foraging behaviour involved whenever interactions include an animal species.Rather than continuing indefinitely, co-evolution is expected to reach an equilibrium, with no further evolutionary change in the interacting species, because of ‘trade-offs’ experienced by individuals of the species involved.Co-evolution can therefore be thought of as an ‘evolutionary game’, with various different species as ‘players’, that reaches an Evolutionarily Stable Strategy (ESS) at equilibrium, such that mutants for each interacting species, deviating slightly from average members of population, are selected against.It is thus possible to develop mathematical models of co-evolution as evolutionary games between species, with ESS’s as the hypothesised end result, and therefore predicted to agree with our observations. But this is unlikely to be easy! Because foraging behaviour is generally involved, but foraging decisions are difficult to determine directly, Optimal Foraging Theory (OFT) will frequently be necessary as part of model development. Developing such models will also likely be complex, given the number of component relationships involved and the need to evaluate them quantitatively, and little development of such models has so far occurred.As an example of how mathematical models of co-evolution can be developed, with foraging behaviour included, I consider co-evolution between plants and their pollinators in terms of floral nectar production (in this case by the plant commonly known as scarlet gilia – Ipomopsis aggregata) and its utilisation by nectar-feeding birds (in this case hummingbirds). This example illustrates how it is possible to deal with the inherent complexity of co-evolution and determine an ESS for floral nectar production and hummingbird foraging behaviour. It also illustrates how, in the absence of appropriate models of co-evolution, explanations for observed patterns are often unsatisfactory. Furthermore, in this example, good agreement was obtained between observations and the predicted ESS!This example therefore illustrates the potential for development of mathematical models of co-evolution, leading to quantitative comparisons of observations and predictions, and to thus better understand both the process of co-evolution and its outcomes, while demonstrating the importance of foraging behaviour. Hopefully, this potential will continue to be realised.
It is an important and ubiquitous process in nature that can occur any time populations of different species interact through evolutionary time, with foraging behaviour involved whenever interactions include an animal species.Rather than continuing indefinitely, co-evolution is expected to reach an equilibrium, with no further evolutionary change in the interacting species, because of ‘trade-offs’ experienced by individuals of the species involved.Co-evolution can therefore be thought of as an ‘evolutionary game’, with various different species as ‘players’, that reaches an Evolutionarily Stable Strategy (ESS) at equilibrium, such that mutants for each interacting species, deviating slightly from average members of population, are selected against.It is thus possible to develop mathematical models of co-evolution as evolutionary games between species, with ESS’s as the hypothesised end result, and therefore predicted to agree with our observations. But this is unlikely to be easy! Because foraging behaviour is generally involved, but foraging decisions are difficult to determine directly, Optimal Foraging Theory (OFT) will frequently be necessary as part of model development. Developing such models will also likely be complex, given the number of component relationships involved and the need to evaluate them quantitatively, and little development of such models has so far occurred.As an example of how mathematical models of co-evolution can be developed, with foraging behaviour included, I consider co-evolution between plants and their pollinators in terms of floral nectar production (in this case by the plant commonly known as scarlet gilia – Ipomopsis aggregata) and its utilisation by nectar-feeding birds (in this case hummingbirds). This example illustrates how it is possible to deal with the inherent complexity of co-evolution and determine an ESS for floral nectar production and hummingbird foraging behaviour. It also illustrates how, in the absence of appropriate models of co-evolution, explanations for observed patterns are often unsatisfactory. Furthermore, in this example, good agreement was obtained between observations and the predicted ESS!This example therefore illustrates the potential for development of mathematical models of co-evolution, leading to quantitative comparisons of observations and predictions, and to thus better understand both the process of co-evolution and its outcomes, while demonstrating the importance of foraging behaviour. Hopefully, this potential will continue to be realised.
Keywords
- co-evolution
- evolutionarily stable strategy
- floral nectar
- game theory
- optimal foraging theory
- pollination syndrome