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Populations: r- and K-Selection
Evolutionary Ecology | Populations: r- and K-Selection
boundaries, and habitat refuges are important topics for research and development. Finally, most PVAs are parametrized using time series of population counts. But, such data are scarce for the threatened and endangered species that are the focus of PVA. Further, time series contain information only about fluctuations of populations at observed population sizes – extrapolations based on such models are particularly unreliable. Thus, new tools need to be developed to incorporate additional information about species’ demography from knowledge of their ecologies and natural histories. The suite of tools that are available for performing PVA is developing rapidly and users should recognize that a large variety of models and techniques are available for population forecasting.
See also: Adaptation; Age-Class Models; Allee Effects; Application of Ecological Informatics; Metapopulation Models; Sex Ratio; Statistical Methods.
Further Reading Akc¸akaya HR (2002) Estimating the variance of survival rates and fecundities. Animal Conservation 5: 333–336. Bailey NTJ (1964) The Elements of Stochastic Processes with Application to the Natural Sciences. New York: Wiley. Beissinger SR and McCullough DR (2002) Population Viability Analysis. Chicago: University of Chicago Press. Boyce MS (1992) Population viability analysis. Annual Review of Ecology and Systematics 23: 481–497.
2907
Brook BW, Cannon JR, Lacy RC, Mirande C, and Frankham R (1999) Comparison of the population viability analysis packages GAPPS, INMAT, RAMAS, and VORTEX for the whooping crane (Grus Americana). Animal Conservation 2: 23–31. Brook BW, O’Grady JJ, Chapman AP, et al. (2000) Predictive accuracy of population viability analysis in conservation biology. Nature 404: 385–387. Caswell H (2001) Matrix Population Models, 2nd edn. Sunderland, MA: Sinauer. Dennis B, Munholland P, and Scott JM (1991) Estimation of growth and extinction parameters for endangered species. Ecological Monographs 61: 115–143. Drake JM (2004) Population viability analysis: Theoretical advances and research needs. Endangered Species UPDATE 21: 93–96. Holmes EE (2004) Beyond theory to application and evaluation: Diffusion approximations for population viability analysis. Ecology 14: 1272–1293. Lande R, Engen S, and Sæther B-E (2003) Stochastic Population Dynamics in Ecology and Conservation. Oxford: Oxford University Press. Morris WF and Doak DF (2002) Quantitative Conservation Biology: Theory and Practice of Population Viability Analysis. Sunderland, MA: Sinauer. Renshaw E (1991) Modelling Biological Populations in Space and Time. Cambridge: Cambridge University Press. Soule´ M (1987) Viable Populations for Conservation. Cambridge: Cambridge University Press. Tuljapurkar SD (1990) Population Dynamics in Variable Environments. New York: Springer.
Relevant Websites http://www.mathworks.com – The MathWorks: MATLAB. http://www.r-project.org – The r-Project for Statistical Computing.
Populations: r- and K-Selection E R Pianka, University of Texas, Austin, TX, USA ª 2008 Elsevier B.V. All rights reserved.
Further Reading
Periodic disturbances, including droughts, fires, floods, and hurricanes, often result in catastrophic densityindependent mortality, suddenly reducing population densities well below the maximal sustainable level for a particular habitat. Populations of annual plants and insects typically grow rapidly during spring and summer but are greatly reduced at the onset of cold weather. Because populations subjected to such forces grow in erratic or regular bursts, they have been termed opportunistic populations. In contrast, populations such as those of many vertebrates may usually be closer to an equilibrium with
their resources and generally exist at much more stable densities (provided that their resources do not fluctuate); such populations are called equilibrium populations. Clearly, these two sorts of populations represent endpoints of a continuum; however, the dichotomy is useful in comparing different populations. The significance of opportunistic versus equilibrium populations is that density-independent and density-dependent factors and events differ in their effects on natural selection and on populations. In highly variable and/or unpredictable environments, catastrophic mass mortality presumably
2908 Evolutionary Ecology | Populations: r- and K-Selection
often has relatively little to do with the genotypes and phenotypes of the organisms concerned or with the size of their populations. (Some degree of selective death and stabilizing selection has been demonstrated in winter kills of certain bird flocks.) By way of contrast, under more stable and/or predictable environmental regimes, population densities fluctuate less and mortality is more directed, favoring individuals that are better able to cope with high densities and strong competition. Organisms in highly rarefied environments seldom deplete their resources to levels as low as do organisms living under less rarefied situations; as a result, the former usually do not encounter such intense competition. In a ‘competitive vacuum’ (or an extensively rarefied environment), the best reproductive strategy is often to invest maximal amounts of matter and energy into reproduction and to produce as many total progeny as possible, as soon as possible. Because competition is weak, these offspring often can thrive even if they are quite small and therefore energetically inexpensive to produce. However, in a ‘saturated’ environment, where density effects are pronounced and competition is keen, the best strategy may often be to put more energy into competition and maintenance and to produce offspring with more substantial competitive abilities. This usually requires larger offspring, and because they are energetically more expensive, fewer can be produced. These two opposing selective forces were designated ‘r-selection’ and ‘K-selection’ by MacArthur and Wilson, after the two terms in the Pearl–Verhulst logistic equation (however, one should not take these terms too literally, as the concepts are independent of the equation). Of course,
things are seldom so black and white, but there are usually all shades of gray. No organism is completely r-selected or completely K-selected; rather all must reach some compromise between the two extremes. Indeed, one can think of a given organism as an ‘r-strategist’ or a ‘K-strategist’ only relative to some other organism; statements about r- and K-selection are invariably comparative. Thus, when compared to a microbe, a mouse would be considered to be a K-strategist, but when compared to a larger longer-lived mammal, it would be labeled an r-strategist. It is best to think in terms of an r- to K-selection continuum and a particular organism’s position along it in a particular environment at a given instant in time. Table 1 lists a variety of correlates of these two kinds of selection. An interesting special case of an opportunistic species is the fugitive species, envisioned as a predictably inferior competitor that is always excluded locally by interspecific competition but persists in newly disturbed regions by virtue of a high dispersal ability. Such a colonizing species can persist in a continually changing patchy environment in spite of pressures from competitively superior species. Another argument was used to explain the apparent ‘paradox of the plankton’, the coexistence of many species in diverse planktonic communities under relatively homogeneous physical conditions, with limited possibilities for ecological separation. Such temporally changing environments may promote diversity by periodically altering relative competitive abilities of component species, thereby allowing their coexistence. The relative strength of sexual selection is also related to life-history strategy, with r-strategists being less likely to be subjected to strong sexual selection than K-strategists.
Table 1 Some of the correlates of r- and K-selection
Climate Mortality Survivorship Population size
Intra- and interspecific competition Selection favors
Length of life Leads to Stage in succession
r-Selection
K-Selection
Variable and unpredictable; uncertain Often catastrophic, nondirected, density independent Often type III Variable in time, nonequilibrium; usually well below carrying capacity of environment; unsaturated communities or portions thereof; ecologic vacuums; recolonization each year Variable, often lax
Fairly constant or predictable; more certain More directed, density dependent
1. Rapid development 2. High maximal rate of increase, rmax 3. Early reproduction 4. Small body size 5. Single reproduction 6. Many small offsprings Short, usually less than a year Productivity Early
1. Slower development 2. Greater competitive ability 3. Delayed reproduction 4. Larger body size 5. Repeated reproduction 6. Fewer, larger progeny Longer, usually more than a year Efficiency Late, climax
From Pianka ER (1970) On r and K selection. American Naturalist 102: 592–597.
Usually types I and II Fairly constant in time, equilibrium; at or near carrying capacity of the environment; saturated communities; no recolonization necessary Usually keen
Human Ecology | Precaution and Ecological Risk
Reproductive tactics among fish (and probably all organisms) can be placed on a two-dimensional triangular surface in a three-dimensional space with the coordinates: juvenile survivorship, fecundity, and age of first reproduction or generation time. This two-dimensional triangular surface has three vertices corresponding to equilibrium (K-strategists), opportunistic, and seasonal species. The r- to K-selection continuum runs diagonally across this surface from the equilibrium corner to the opportunistic-seasonal edge. In fish, seasonal breeders exhibit little sexual dimorphism, whereas both opportunistic and equilibrium species display marked sexual dimorphisms. Under situations where survivorship of adults is high but juvenile survival is low and highly unpredictable, there is a selective disadvantage to putting all one’s eggs in the same basket, and a consequent advantage to distributing reproduction out over a period of time. This sort
2909
of reproductive tactic has become known as ‘bet hedging’ and occurs in both r- and K-strategists.
See also: Body Size, Energetics, and Evolution.
Further Reading MacArthur RH and Wilson EO (1967) The Theory of Island Biogeography. Princeton: Princeton University Press. Pianka ER (1970) On r and K selection. American Naturalist 102: 592–597. Pianka ER (1972) r and K selection or b and d selection? American Naturalist 106: 581–588. Pianka ER (2000) Evolutionary Ecology, 6th edn. San Francisco: Benjamin-Cummings, Addison-Wesley-Longman. Winemiller KO (1989) Patterns of variation in life history among South American fishes in seasonal environments. Oecologia 81: 225–241.
Precaution and Ecological Risk O Renn, University of Stuttgart, Stuttgart, Germany ª 2008 Elsevier B.V. All rights reserved.
The Different Meanings of Precaution The Precautionary Principle Components of Risk Risk Management Principles
Political Relevance Summary Further Reading
The Different Meanings of Precaution
The focus on ecological risk should be seen as a segment of a larger and wider perspective on how humans transform the natural into a cultural environment with the aims of improving living conditions and serving human wants and needs. These transformations are performed with a purpose in mind (normally a benefit to those who initiate them). When implementing these changes, intended (or tolerated) and unintended consequences may occur that meet or violate other dimensions of what humans value. These are the risks. It is the major task of risk assessment to identify and explore, preferably in quantitative terms, the types, intensities, and likelihood of the (normally undesired) consequences related to the consequences that human actions or events exert on ecosystems. In addition, these consequences are associated with special concerns that individuals, social groups, or different cultures may associate with these risks. Ecosystem changes can be physically measured or observed but they only get meaning through
This article presents a scientific overview of the meanings and applications of the precautionary principle in ecological risk assessment and management. The term risk is understood in this document as an uncertain consequence of an event or an activity with respect to something that humans value. Risks always refer to a combination of two components: the likelihood or chance of potential consequences and the severity of consequences of human activities, natural events, or a combination of both. Such consequences can be positive or negative, depending on the values that people associate with them. In addition to the strength and likelihood of these consequences, characterizing risks includes contextual aspects such as the distribution of risks over time, space, and populations. With respect to ecology, risk denotes the probability of ecosystem damage as a result of human interventions or natural events (such as earthquakes, wildfires, or flooding).
boundaries, and habitat refuges are important topics for research and development. Finally, most PVAs are parametrized using time series of population counts. But, such data are scarce for the threatened and endangered species that are the focus of PVA. Further, time series contain information only about fluctuations of populations at observed population sizes – extrapolations based on such models are particularly unreliable. Thus, new tools need to be developed to incorporate additional information about species’ demography from knowledge of their ecologies and natural histories. The suite of tools that are available for performing PVA is developing rapidly and users should recognize that a large variety of models and techniques are available for population forecasting.
See also: Adaptation; Age-Class Models; Allee Effects; Application of Ecological Informatics; Metapopulation Models; Sex Ratio; Statistical Methods.
Further Reading Akc¸akaya HR (2002) Estimating the variance of survival rates and fecundities. Animal Conservation 5: 333–336. Bailey NTJ (1964) The Elements of Stochastic Processes with Application to the Natural Sciences. New York: Wiley. Beissinger SR and McCullough DR (2002) Population Viability Analysis. Chicago: University of Chicago Press. Boyce MS (1992) Population viability analysis. Annual Review of Ecology and Systematics 23: 481–497.
2907
Brook BW, Cannon JR, Lacy RC, Mirande C, and Frankham R (1999) Comparison of the population viability analysis packages GAPPS, INMAT, RAMAS, and VORTEX for the whooping crane (Grus Americana). Animal Conservation 2: 23–31. Brook BW, O’Grady JJ, Chapman AP, et al. (2000) Predictive accuracy of population viability analysis in conservation biology. Nature 404: 385–387. Caswell H (2001) Matrix Population Models, 2nd edn. Sunderland, MA: Sinauer. Dennis B, Munholland P, and Scott JM (1991) Estimation of growth and extinction parameters for endangered species. Ecological Monographs 61: 115–143. Drake JM (2004) Population viability analysis: Theoretical advances and research needs. Endangered Species UPDATE 21: 93–96. Holmes EE (2004) Beyond theory to application and evaluation: Diffusion approximations for population viability analysis. Ecology 14: 1272–1293. Lande R, Engen S, and Sæther B-E (2003) Stochastic Population Dynamics in Ecology and Conservation. Oxford: Oxford University Press. Morris WF and Doak DF (2002) Quantitative Conservation Biology: Theory and Practice of Population Viability Analysis. Sunderland, MA: Sinauer. Renshaw E (1991) Modelling Biological Populations in Space and Time. Cambridge: Cambridge University Press. Soule´ M (1987) Viable Populations for Conservation. Cambridge: Cambridge University Press. Tuljapurkar SD (1990) Population Dynamics in Variable Environments. New York: Springer.
Relevant Websites http://www.mathworks.com – The MathWorks: MATLAB. http://www.r-project.org – The r-Project for Statistical Computing.
Populations: r- and K-Selection E R Pianka, University of Texas, Austin, TX, USA ª 2008 Elsevier B.V. All rights reserved.
Further Reading
Periodic disturbances, including droughts, fires, floods, and hurricanes, often result in catastrophic densityindependent mortality, suddenly reducing population densities well below the maximal sustainable level for a particular habitat. Populations of annual plants and insects typically grow rapidly during spring and summer but are greatly reduced at the onset of cold weather. Because populations subjected to such forces grow in erratic or regular bursts, they have been termed opportunistic populations. In contrast, populations such as those of many vertebrates may usually be closer to an equilibrium with
their resources and generally exist at much more stable densities (provided that their resources do not fluctuate); such populations are called equilibrium populations. Clearly, these two sorts of populations represent endpoints of a continuum; however, the dichotomy is useful in comparing different populations. The significance of opportunistic versus equilibrium populations is that density-independent and density-dependent factors and events differ in their effects on natural selection and on populations. In highly variable and/or unpredictable environments, catastrophic mass mortality presumably
2908 Evolutionary Ecology | Populations: r- and K-Selection
often has relatively little to do with the genotypes and phenotypes of the organisms concerned or with the size of their populations. (Some degree of selective death and stabilizing selection has been demonstrated in winter kills of certain bird flocks.) By way of contrast, under more stable and/or predictable environmental regimes, population densities fluctuate less and mortality is more directed, favoring individuals that are better able to cope with high densities and strong competition. Organisms in highly rarefied environments seldom deplete their resources to levels as low as do organisms living under less rarefied situations; as a result, the former usually do not encounter such intense competition. In a ‘competitive vacuum’ (or an extensively rarefied environment), the best reproductive strategy is often to invest maximal amounts of matter and energy into reproduction and to produce as many total progeny as possible, as soon as possible. Because competition is weak, these offspring often can thrive even if they are quite small and therefore energetically inexpensive to produce. However, in a ‘saturated’ environment, where density effects are pronounced and competition is keen, the best strategy may often be to put more energy into competition and maintenance and to produce offspring with more substantial competitive abilities. This usually requires larger offspring, and because they are energetically more expensive, fewer can be produced. These two opposing selective forces were designated ‘r-selection’ and ‘K-selection’ by MacArthur and Wilson, after the two terms in the Pearl–Verhulst logistic equation (however, one should not take these terms too literally, as the concepts are independent of the equation). Of course,
things are seldom so black and white, but there are usually all shades of gray. No organism is completely r-selected or completely K-selected; rather all must reach some compromise between the two extremes. Indeed, one can think of a given organism as an ‘r-strategist’ or a ‘K-strategist’ only relative to some other organism; statements about r- and K-selection are invariably comparative. Thus, when compared to a microbe, a mouse would be considered to be a K-strategist, but when compared to a larger longer-lived mammal, it would be labeled an r-strategist. It is best to think in terms of an r- to K-selection continuum and a particular organism’s position along it in a particular environment at a given instant in time. Table 1 lists a variety of correlates of these two kinds of selection. An interesting special case of an opportunistic species is the fugitive species, envisioned as a predictably inferior competitor that is always excluded locally by interspecific competition but persists in newly disturbed regions by virtue of a high dispersal ability. Such a colonizing species can persist in a continually changing patchy environment in spite of pressures from competitively superior species. Another argument was used to explain the apparent ‘paradox of the plankton’, the coexistence of many species in diverse planktonic communities under relatively homogeneous physical conditions, with limited possibilities for ecological separation. Such temporally changing environments may promote diversity by periodically altering relative competitive abilities of component species, thereby allowing their coexistence. The relative strength of sexual selection is also related to life-history strategy, with r-strategists being less likely to be subjected to strong sexual selection than K-strategists.
Table 1 Some of the correlates of r- and K-selection
Climate Mortality Survivorship Population size
Intra- and interspecific competition Selection favors
Length of life Leads to Stage in succession
r-Selection
K-Selection
Variable and unpredictable; uncertain Often catastrophic, nondirected, density independent Often type III Variable in time, nonequilibrium; usually well below carrying capacity of environment; unsaturated communities or portions thereof; ecologic vacuums; recolonization each year Variable, often lax
Fairly constant or predictable; more certain More directed, density dependent
1. Rapid development 2. High maximal rate of increase, rmax 3. Early reproduction 4. Small body size 5. Single reproduction 6. Many small offsprings Short, usually less than a year Productivity Early
1. Slower development 2. Greater competitive ability 3. Delayed reproduction 4. Larger body size 5. Repeated reproduction 6. Fewer, larger progeny Longer, usually more than a year Efficiency Late, climax
From Pianka ER (1970) On r and K selection. American Naturalist 102: 592–597.
Usually types I and II Fairly constant in time, equilibrium; at or near carrying capacity of the environment; saturated communities; no recolonization necessary Usually keen
Human Ecology | Precaution and Ecological Risk
Reproductive tactics among fish (and probably all organisms) can be placed on a two-dimensional triangular surface in a three-dimensional space with the coordinates: juvenile survivorship, fecundity, and age of first reproduction or generation time. This two-dimensional triangular surface has three vertices corresponding to equilibrium (K-strategists), opportunistic, and seasonal species. The r- to K-selection continuum runs diagonally across this surface from the equilibrium corner to the opportunistic-seasonal edge. In fish, seasonal breeders exhibit little sexual dimorphism, whereas both opportunistic and equilibrium species display marked sexual dimorphisms. Under situations where survivorship of adults is high but juvenile survival is low and highly unpredictable, there is a selective disadvantage to putting all one’s eggs in the same basket, and a consequent advantage to distributing reproduction out over a period of time. This sort
2909
of reproductive tactic has become known as ‘bet hedging’ and occurs in both r- and K-strategists.
See also: Body Size, Energetics, and Evolution.
Further Reading MacArthur RH and Wilson EO (1967) The Theory of Island Biogeography. Princeton: Princeton University Press. Pianka ER (1970) On r and K selection. American Naturalist 102: 592–597. Pianka ER (1972) r and K selection or b and d selection? American Naturalist 106: 581–588. Pianka ER (2000) Evolutionary Ecology, 6th edn. San Francisco: Benjamin-Cummings, Addison-Wesley-Longman. Winemiller KO (1989) Patterns of variation in life history among South American fishes in seasonal environments. Oecologia 81: 225–241.
Precaution and Ecological Risk O Renn, University of Stuttgart, Stuttgart, Germany ª 2008 Elsevier B.V. All rights reserved.
The Different Meanings of Precaution The Precautionary Principle Components of Risk Risk Management Principles
Political Relevance Summary Further Reading
The Different Meanings of Precaution
The focus on ecological risk should be seen as a segment of a larger and wider perspective on how humans transform the natural into a cultural environment with the aims of improving living conditions and serving human wants and needs. These transformations are performed with a purpose in mind (normally a benefit to those who initiate them). When implementing these changes, intended (or tolerated) and unintended consequences may occur that meet or violate other dimensions of what humans value. These are the risks. It is the major task of risk assessment to identify and explore, preferably in quantitative terms, the types, intensities, and likelihood of the (normally undesired) consequences related to the consequences that human actions or events exert on ecosystems. In addition, these consequences are associated with special concerns that individuals, social groups, or different cultures may associate with these risks. Ecosystem changes can be physically measured or observed but they only get meaning through
This article presents a scientific overview of the meanings and applications of the precautionary principle in ecological risk assessment and management. The term risk is understood in this document as an uncertain consequence of an event or an activity with respect to something that humans value. Risks always refer to a combination of two components: the likelihood or chance of potential consequences and the severity of consequences of human activities, natural events, or a combination of both. Such consequences can be positive or negative, depending on the values that people associate with them. In addition to the strength and likelihood of these consequences, characterizing risks includes contextual aspects such as the distribution of risks over time, space, and populations. With respect to ecology, risk denotes the probability of ecosystem damage as a result of human interventions or natural events (such as earthquakes, wildfires, or flooding).