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Abstract
A probability model is presented to determine the age structure of a fish population from length-frequency data. It is shown that when the age-length key is available, maximum-likelihood estimates of the age structure can be obtained. When the key is not available, approximate estimates of the age structure can be obtained. The model is used for determination of the age structure of populations of channel catfish and white crappie. Practical applications of the model to impact assessment are discussed.
Authors: Adams, S MPublication Date: Sat Jan 01 00:00:00 EST 1977Research Org.: Oak Ridge National Lab., TN (USA)OSTI Identifier: 7312272Report Number(s): CONF-770501-2
TRN: 77-012072DOE
Contract Number: W-7405-ENG-26Resource Type: ConferenceResource Relation: Conference: Conference on accumulating the effects of power plant induced mortality on fish population, Gatlinburg, TN, USA, 2 May 1977Country of Publication: United StatesLanguage: EnglishSubject: 54 ENVIRONMENTAL SCIENCES; 59 BASIC BIOLOGICAL SCIENCES; FISHES; AGE ESTIMATION; AQUATIC ECOSYSTEMS; LENGTH; MATHEMATICAL MODELS; MAXIMUM-LIKELIHOOD FIT; POPULATION DYNAMICS; PROBABILITY;
STATISTICS; ANIMALS; AQUATIC ORGANISMS; DIMENSIONS; ECOSYSTEMS; MATHEMATICS; NUMERICAL SOLUTION; VERTEBRATES; 520100* - Environment, Aquatic- Basic Studies- (-1989); 551000 - Physiological Systems
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Kumar, K D, and Adams, S M. Estimation of age structure of fish populations from length-frequency data. United States: N. p., 1977.
Web.
Kumar, K D, & Adams, S M. Estimation of age structure of fish populations from length-frequency data. United States.
Kumar, K D, and Adams, S M. 1977. "Estimation of age structure of fish populations from length-frequency data". United States. //www.osti.gov/servlets/purl/7312272.
@article{osti_7312272,
title = {Estimation of age structure of fish populations from length-frequency data},
author = {Kumar, K D and Adams, S M},
abstractNote = {A probability model is presented to determine the age structure of a fish population from length-frequency data. It is shown that when the age-length key is available, maximum-likelihood estimates of the age structure can be obtained. When the key is not available, approximate estimates of the age structure can be obtained. The model is used for determination of the age structure of populations of channel catfish and white crappie. Practical applications of the model to impact assessment are discussed.},
doi = {},
url = {//www.osti.gov/biblio/7312272},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Jan 01 00:00:00 EST 1977},
month = {Sat Jan 01 00:00:00 EST 1977}
}
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Abstract
Long-term studies of plant populations are reviewed, and their dynamics summarized in three categories. Many short-lived plants have ephemeral, pulsed dynamics lasting only a single generation, with recruitment determined almost entirely by germination biology and by the frequency and intensity of disturbance. Such populations are not amenable to traditional population models. At the other extreme, some long-lived plants have such protracted tenancy of their microsites that it is impossible to establish what pattern of dynamics (if any) their populations exhibit. A relatively small number of species show what we would traditionally regard as population dynamics at a given point in space (i.e. reasonably predictable trajectories that can be modelled by Nt+1 = f(Nt)). A major difficulty in generalizing about plant dynamics is that the majority of species are successional; their recruitment depends upon the death, through senescence or disturbance, of the dominant plants. Where we do have data spanning several generations, it is clear that: (i) the populations are regulated by density dependent processes; (ii) in contrast to some animal populations, numbers appear to vary less from year to year in places where mean density is higher, and less from place to place in years when mean density is high than when density is low; (iii) few, if any, plant populations show persistent cyclic or chaotic dynamics, but (iv) there are several robust generalizations that stem from the immobility and phenotypic plasticity of plants (the law of constant yield; self-thinning rules, etc.). These generalizations are analysed in the context of simple theoretical models of plant dynamics, and the patterns observed in long-term studies are compared with similar data from animal populations. Two important shortcomings of traditional plant demography are emphasized; (i) the dearth of simple manipulative experiments on such issues as seed limitation, and (ii) the tendency to locate study plots around existing mature individuals (the omission of `empty quadrats' may introduce serious bias into the estimation of plant recruitment rates).
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Philosophical Transactions: Biological Sciences © 1990 Royal Society
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