Difference between revisions of "Morphometric and particle analysis"

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  | part    = Predicting the occurrence of oil and gas traps
 
  | part    = Predicting the occurrence of oil and gas traps
 
  | chapter = Applied paleontology
 
  | chapter = Applied paleontology
  | frompg  = 17-1
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  | frompg  = 17-56
  | topg    = 17-65
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  | topg    = 17-57
 
  | author  = Robert L. Fleisher, H. Richard Lane
 
  | author  = Robert L. Fleisher, H. Richard Lane
 
  | link    = http://archives.datapages.com/data/specpubs/beaumont/ch17/ch17.htm
 
  | link    = http://archives.datapages.com/data/specpubs/beaumont/ch17/ch17.htm
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  | isbn    = 0-89181-602-X
 
  | isbn    = 0-89181-602-X
 
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Evolutionary change within fossil lineages and the morphologic (i.e., size and shape) adaptation of fossil species to different ancient environments can only be inferred from morphologic analysis of fossil populations.<ref name=ch17r76>Scott, G., H., 1980, The value of outline processing in the biometry and systematics of fossils: [[Palaeontology]], vol. 23, p. 757–768.</ref> Until the early 1970s the morphologic study of microfossils involved tedious “eyeball” measurements of large numbers of specimens from many samples, precluding use of the technique in industrial application. Rapid advances in computer, video, and multivariate statistical techniques have greatly reduced the time required to collect quantitative measurements on large numbers of shells.
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Evolutionary change within fossil lineages and the morphologic (i.e., size and shape) adaptation of fossil species to different ancient environments can only be inferred from morphologic analysis of fossil populations.<ref name=ch17r76>Scott, G. H., 1980, The value of outline processing in the biometry and systematics of fossils: Palaeontology, vol. 23, p. 757–768.</ref> Until the early 1970s the morphologic study of microfossils involved tedious “eyeball” measurements of large numbers of specimens from many samples, precluding use of the technique in industrial application. Rapid advances in computer, video, and multivariate statistical techniques have greatly reduced the time required to collect quantitative measurements on large numbers of shells.
  
 
==Morphometric procedure==
 
==Morphometric procedure==
Morphometric analysis involves collecting the measurements of two or three dimensions of fossil form, typically either an outline (silhouette) or the coordinate positions of a morphologic “landmark.” Once a sufficient data set is collected, multivariate methods are used to break out fossil “shape components” statistically and to relate component variability to chronostratigraphic or paleoenvironmental indices.<ref name=ch17r29>Davis, J., C., 1986, Statistics and data analysis in geology: New York, John Wiley, 646 p.</ref> When the relationship between change in fossil shape and environmental and stratigraphic data is established, fossil morphology can increase confidence in geologic correlation and paleoenvironmental inference.<ref name=ch17r73>Reyment, R., A., Blackith, R., E., Campbell, N., A., 1984, Multivariate Morphometrics, 2nd ed.: London, Academic Press, 233 p.</ref><ref name=ch17r74>Rohlf, F., J., Bookstein, F., L., eds., 1990, Proceedings of the Michigan Morphometrics Workshop: University of Michigan Museum of Zoology Special Publication 2, 380 p.</ref>
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[[file:applied-paleontology_fig17-33.png|thumb|300px|{{figure number|1}}Printed with permission of N. Healy-Williams, University of South Carolina.]]
 +
 
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Morphometric analysis involves collecting the measurements of two or three dimensions of fossil form, typically either an outline (silhouette) or the coordinate positions of a morphologic “landmark.” Once a sufficient data set is collected, multivariate methods are used to break out fossil “shape components” statistically and to relate component variability to chronostratigraphic or paleoenvironmental indices.<ref name=ch17r29>Davis, J. C., 1986, Statistics and data analysis in geology: New York, John Wiley, 646 p.</ref> When the relationship between change in fossil shape and environmental and stratigraphic data is established, fossil morphology can increase confidence in geologic correlation and paleoenvironmental inference.<ref name=ch17r73>Reyment, R. A., R. E. Blackith, and N. A. Campbell, 1984, Multivariate Morphometrics, 2nd ed.: London, Academic Press, 233 p.</ref><ref name=ch17r74>Rohlf, F. J., and F. L. Bookstein, eds., 1990, Proceedings of the Michigan Morphometrics Workshop: University of Michigan Museum of Zoology Special Publication 2, 380 p.</ref>
  
 
==Applications==
 
==Applications==
Morphometric analysis of microfossils from stratigraphic sections can augment the resolution of existing biostratigraphic zonations.<ref name=ch17r72>Reyment, R., A., 1980, Morphometric methods in biostratigraphy: London, Academic Press, 168 p.</ref> The illustration to the right shows changes vs. age in the average morphometrically defined shape of tests in populations of the planktonic foraminifera ''Globoquadrina altispira''.
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Morphometric analysis of microfossils from stratigraphic sections can augment the resolution of existing biostratigraphic zonations.<ref name=ch17r72>Reyment, R. A., 1980, Morphometric methods in biostratigraphy: London, Academic Press, 168 p.</ref> [[:file:applied-paleontology_fig17-33.png|Figure 1]] shows changes vs. age in the average morphometrically defined shape of tests in populations of the planktonic foraminifera ''Globoquadrina altispira''.
  
Data for the illustration were compiled from cores taken in the DeSoto Canyon area, eastern Gulf of Mexico. Significant shifts in shape (such as at 7.5 Ma) can augment the resolution of existing biostratigraphic zonations. In addition to analysis from stratigraphic sections, refined paleoenvironmental interpretations can be obtained by comparing morphometric results from fossil populations (e.g., benthic foraminifera) with results obtained from analysis of existing species from known environments.
+
Data for the illustration were compiled from cores taken in the DeSoto Canyon area, eastern [[Gulf of Mexico]]. Significant shifts in shape (such as at {{Ma|7.5}}) can augment the resolution of existing biostratigraphic zonations. In addition to analysis from stratigraphic sections, refined paleoenvironmental interpretations can be obtained by comparing morphometric results from fossil populations (e.g., benthic foraminifera) with results obtained from analysis of existing species from known environments.
  
[[file:applied-paleontology_fig17-33.png|thumb|{{figure number|17-33}}Printed with permission of N. Healy-Williams, University of South Carolina.]]
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[[file:applied-paleontology_fig17-34.png|300px|thumb|{{figure number|2}}After <ref name=ch17r41>Gary, A. C., N. Healy-Williams, and R. Ehrlich, 1989, Water–mass relationships and morphologic variability in the benthic foraminifer Bolivina albatrossi Cushman, northern Gulf of Mexico: Journal of Foraminiferal Research, vol. 19, no. 3, p. 210–221, DOI: [http://jfr.geoscienceworld.org/content/19/3/210.extract 10.2113/gsjfr.19.3.210].</ref>; courtesy Journal of Foraminiferal Research.]]
  
 
==Systematic changes vs. water depth==
 
==Systematic changes vs. water depth==
The illustration below shows systematic changes vs. water depth in the outline shape (lobateness) of the benthic foraminifera ''Bolivina alhatrossi'' as defined by morphometric analysis. Data for this illustration were collected from a transect of bottom samples from the present-day Gulf of Mexico. Similar analyses of ''B. alhatrossi'' specimens from Neogene sections can be compared with the modern relationship to obtain paleobathymetric estimates.
+
[[:file:applied-paleontology_fig17-34.png|Figure 2]] shows systematic changes vs. water depth in the outline shape (lobateness) of the benthic foraminifera ''Bolivina alhatrossi'' as defined by morphometric analysis. Data for this illustration were collected from a transect of bottom samples from the present-day [[Gulf of Mexico]]. Similar analyses of ''B. alhatrossi'' specimens from Neogene sections can be compared with the modern relationship to obtain paleobathymetric estimates.
 
 
[[file:applied-paleontology_fig17-34.png|thumb|{{figure number|17-34}}After .<ref name=ch17r41>Gary, A., C., Healy-Williams, N., Ehrlich, R., 1989, Water–mass relationships and morphologic variability in the benthic foraminifer Bolivina albatrossi Cushman, northern Gulf of Mexico: Journal of Foraminiferal Research, vol. 19, no. 3, p. 210–221., 10., 2113/gsjfr., 19., 3., 210</ref> Copyright: Journal of Foraminiferal Research.]]
 
  
 
==Particle analysis==
 
==Particle analysis==
Particle analysis involves computer-assisted automated measurement and classification of size and color information of fossils and outline shape. To date, analysis of particle images has been applied largely to kerogen particles in transmitted, reflected, and fluorescent light. The results show promise for interpreting paleoenvironments, identifying source rock intervals, estimating thermal maturity of sediments, and refining biostratigraphic correlation.
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Particle analysis involves computer-assisted automated measurement and classification of size and color information of fossils and outline shape. To date, analysis of particle images has been applied largely to [[kerogen]] particles in transmitted, reflected, and fluorescent light. The results show promise for interpreting paleoenvironments, identifying source rock intervals, estimating thermal maturity of sediments, and refining biostratigraphic correlation.
  
 
==See also==
 
==See also==
* [[New directions]]
 
 
* [[Quantitative biostratigraphy]]
 
* [[Quantitative biostratigraphy]]
 
* [[Stable isotope stratigraphy]]
 
* [[Stable isotope stratigraphy]]
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[[Category:Predicting the occurrence of oil and gas traps]]  
 
[[Category:Predicting the occurrence of oil and gas traps]]  
 
[[Category:Applied paleontology]]
 
[[Category:Applied paleontology]]
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[[Category:Treatise Handbook 3]]

Latest revision as of 20:59, 31 January 2022

Exploring for Oil and Gas Traps
Series Treatise in Petroleum Geology
Part Predicting the occurrence of oil and gas traps
Chapter Applied paleontology
Author Robert L. Fleisher, H. Richard Lane
Link Web page
Store AAPG Store

Evolutionary change within fossil lineages and the morphologic (i.e., size and shape) adaptation of fossil species to different ancient environments can only be inferred from morphologic analysis of fossil populations.[1] Until the early 1970s the morphologic study of microfossils involved tedious “eyeball” measurements of large numbers of specimens from many samples, precluding use of the technique in industrial application. Rapid advances in computer, video, and multivariate statistical techniques have greatly reduced the time required to collect quantitative measurements on large numbers of shells.

Morphometric procedure

Figure 1 Printed with permission of N. Healy-Williams, University of South Carolina.

Morphometric analysis involves collecting the measurements of two or three dimensions of fossil form, typically either an outline (silhouette) or the coordinate positions of a morphologic “landmark.” Once a sufficient data set is collected, multivariate methods are used to break out fossil “shape components” statistically and to relate component variability to chronostratigraphic or paleoenvironmental indices.[2] When the relationship between change in fossil shape and environmental and stratigraphic data is established, fossil morphology can increase confidence in geologic correlation and paleoenvironmental inference.[3][4]

Applications

Morphometric analysis of microfossils from stratigraphic sections can augment the resolution of existing biostratigraphic zonations.[5] Figure 1 shows changes vs. age in the average morphometrically defined shape of tests in populations of the planktonic foraminifera Globoquadrina altispira.

Data for the illustration were compiled from cores taken in the DeSoto Canyon area, eastern Gulf of Mexico. Significant shifts in shape (such as at 7.5 Ma) can augment the resolution of existing biostratigraphic zonations. In addition to analysis from stratigraphic sections, refined paleoenvironmental interpretations can be obtained by comparing morphometric results from fossil populations (e.g., benthic foraminifera) with results obtained from analysis of existing species from known environments.

Figure 2 After [6]; courtesy Journal of Foraminiferal Research.

Systematic changes vs. water depth

Figure 2 shows systematic changes vs. water depth in the outline shape (lobateness) of the benthic foraminifera Bolivina alhatrossi as defined by morphometric analysis. Data for this illustration were collected from a transect of bottom samples from the present-day Gulf of Mexico. Similar analyses of B. alhatrossi specimens from Neogene sections can be compared with the modern relationship to obtain paleobathymetric estimates.

Particle analysis

Particle analysis involves computer-assisted automated measurement and classification of size and color information of fossils and outline shape. To date, analysis of particle images has been applied largely to kerogen particles in transmitted, reflected, and fluorescent light. The results show promise for interpreting paleoenvironments, identifying source rock intervals, estimating thermal maturity of sediments, and refining biostratigraphic correlation.

See also

References

  1. Scott, G. H., 1980, The value of outline processing in the biometry and systematics of fossils: Palaeontology, vol. 23, p. 757–768.
  2. Davis, J. C., 1986, Statistics and data analysis in geology: New York, John Wiley, 646 p.
  3. Reyment, R. A., R. E. Blackith, and N. A. Campbell, 1984, Multivariate Morphometrics, 2nd ed.: London, Academic Press, 233 p.
  4. Rohlf, F. J., and F. L. Bookstein, eds., 1990, Proceedings of the Michigan Morphometrics Workshop: University of Michigan Museum of Zoology Special Publication 2, 380 p.
  5. Reyment, R. A., 1980, Morphometric methods in biostratigraphy: London, Academic Press, 168 p.
  6. Gary, A. C., N. Healy-Williams, and R. Ehrlich, 1989, Water–mass relationships and morphologic variability in the benthic foraminifer Bolivina albatrossi Cushman, northern Gulf of Mexico: Journal of Foraminiferal Research, vol. 19, no. 3, p. 210–221, DOI: 10.2113/gsjfr.19.3.210.

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