Estimating number of species

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Species richness estimators were frequently applied to various [[taxa]]; application of the estimators to [[Tree Definition|tree]] species from [[forest inventory|forest inventories]] include Chazdon et al. (1998<ref name="chazdon1998">Chazdon R.L., R.K. Colwell, J.S. Denslow and M.R. Guariguata. 1998. Statistical methods for estimating species richness of woody regeneration in primary and secondary rain forests of Northeastern Costa Rica. In: Dallmeier F and JA Comisky. (Eds.), Forest biodiversity research, monitoring and modelling. The Parthenon Publishing Group, Paris, France, pp. 285–309.</ref>), Condit et al. (1996<ref name="condit1996">Condit R.G. 1998. Tropical forest census plots: methods and results from Barro Colorado Island, Panama and a comparison with other plots. Heidelberg: Springer-Verlag.</ref>); Hellmann and Fowler (1999<ref name="hellmann_fowler1999">Hellmann J.J. and G.W. Fowler. 1999. Bias, precision, and accuracy of four measures of species richness. Ecol. Applic. 9, 824–834.</ref>), Magnussen et al. (2006<ref name="magnussen2006">Magnussen S., R. Pélissier, F.  He and B.R. Ramesh. 2006. An assessment of sample-based estimators of tree species richness in two wet tropical forest compartments in Panama and India. Int. For. Rev. 8, 417–431.</ref>), Palmer (1990<ref name="palmer1990">Palmer M.W. 1990. The estimation of species richness by extrapolation. Ecology 71, 1195–1198.</ref>, 1991<ref name="palmer1991">Palmer M.W. 1991. Estimating species richness: the second-order jackknife reconsidered. Ecology 72, 1512–1513.</ref>) and Schreuder et al.(1999<ref name="schreuder1999">Schreuder, H.T., R.C. Czaplewski and R.G. Bailey. 1999. Combining mapped and statistical data in forest ecological inventory and monitoring-supplementing an existing system. Env Mon Asst 56:269-291.</ref>).
 
Species richness estimators were frequently applied to various [[taxa]]; application of the estimators to [[Tree Definition|tree]] species from [[forest inventory|forest inventories]] include Chazdon et al. (1998<ref name="chazdon1998">Chazdon R.L., R.K. Colwell, J.S. Denslow and M.R. Guariguata. 1998. Statistical methods for estimating species richness of woody regeneration in primary and secondary rain forests of Northeastern Costa Rica. In: Dallmeier F and JA Comisky. (Eds.), Forest biodiversity research, monitoring and modelling. The Parthenon Publishing Group, Paris, France, pp. 285–309.</ref>), Condit et al. (1996<ref name="condit1996">Condit R.G. 1998. Tropical forest census plots: methods and results from Barro Colorado Island, Panama and a comparison with other plots. Heidelberg: Springer-Verlag.</ref>); Hellmann and Fowler (1999<ref name="hellmann_fowler1999">Hellmann J.J. and G.W. Fowler. 1999. Bias, precision, and accuracy of four measures of species richness. Ecol. Applic. 9, 824–834.</ref>), Magnussen et al. (2006<ref name="magnussen2006">Magnussen S., R. Pélissier, F.  He and B.R. Ramesh. 2006. An assessment of sample-based estimators of tree species richness in two wet tropical forest compartments in Panama and India. Int. For. Rev. 8, 417–431.</ref>), Palmer (1990<ref name="palmer1990">Palmer M.W. 1990. The estimation of species richness by extrapolation. Ecology 71, 1195–1198.</ref>, 1991<ref name="palmer1991">Palmer M.W. 1991. Estimating species richness: the second-order jackknife reconsidered. Ecology 72, 1512–1513.</ref>) and Schreuder et al.(1999<ref name="schreuder1999">Schreuder, H.T., R.C. Czaplewski and R.G. Bailey. 1999. Combining mapped and statistical data in forest ecological inventory and monitoring-supplementing an existing system. Env Mon Asst 56:269-291.</ref>).
  
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Walther and Moore (2005<ref name="walther_moore2005">Walther B.A. and J.L. Moore. 2005. The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance. Ecography 28, 815–829</ref>) gathered an extensiv list of additional studies and summarized them by the species richness estimators. They also provided various definitions and measures of bias, [[Accuray and precision|precision and accuracy]] to evaluate the estimators´ performances. Colwell and Coddington (1994<ref name="colwell_coddington1994">Colwell R.K. and J.A. Coddington. 1994. Estimating terrestrial biodiversity through extrapolation. Philos. T. Roy. Soc. B. 345, 101–118.</ref>) and Gotelli and Colwell (2001<ref name="gotelli_colwell2001">Gotelli N.J. and R.K. Colwell. 2001. Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecol. Lett. 4, 379–391.</ref>) provided in depth discussion on issues related to pitfalls and cautions.
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Walther and Moore (2005<ref name="walther_moore2005">Walther B.A. and J.L. Moore. 2005. The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance. Ecography 28, 815–829</ref>) gathered an extensiv list of additional studies and summarized them by the species richness estimators. They also provided various definitions and measures of bias, [[Accuracy and precision|precision and accuracy]] to evaluate the estimators´ performances. Colwell and Coddington (1994<ref name="colwell_coddington1994">Colwell R.K. and J.A. Coddington. 1994. Estimating terrestrial biodiversity through extrapolation. Philos. T. Roy. Soc. B. 345, 101–118.</ref>) and Gotelli and Colwell (2001<ref name="gotelli_colwell2001">Gotelli N.J. and R.K. Colwell. 2001. Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecol. Lett. 4, 379–391.</ref>) provided in depth discussion on issues related to pitfalls and cautions.
  
 
There are at least two species richness estimation softwares: EstimateS (Colwell, 2007<ref name="colwell2007">Colwell R.K. 2007. EstimateS: Statistical estimation of species richness and shared species from samples. Version 8.0. User's Guide and application published at: http://purl.oclc.org/estimates.</ref>) and SPADE (Chao and Shen, 2006<ref name="chao_shen2006">Chao A. and T.J. Shen. 2006. Program SPADE (Species Prediction And Diversity Estimation). Program User’s Guide published at http://chao.stat.nthu.edu.tw/.</ref>), both easily accessible.
 
There are at least two species richness estimation softwares: EstimateS (Colwell, 2007<ref name="colwell2007">Colwell R.K. 2007. EstimateS: Statistical estimation of species richness and shared species from samples. Version 8.0. User's Guide and application published at: http://purl.oclc.org/estimates.</ref>) and SPADE (Chao and Shen, 2006<ref name="chao_shen2006">Chao A. and T.J. Shen. 2006. Program SPADE (Species Prediction And Diversity Estimation). Program User’s Guide published at http://chao.stat.nthu.edu.tw/.</ref>), both easily accessible.
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Large area forest inventories such as national forest inventories are carried out in many regions so as to provide baseline information for forest and related policy formulation. A relatively large number (commonly between about 500 and several 1000s) of relatively small [[:Category:Plot design|field plots]] (commonly of areas between about 0.1 and 1 ha), usually laid out in a systematic grid over the entire inventory area, constitute the backbone of estimation (for example FAO 2003<ref name="FAO2003">FAO. 2003. Workshop on the FAO approach to national forest resources assessment and ongoing project. FAO Forest Resources Assessment Working Paper No.70/E. Food and Agriculture Organization of the United Nations, Rome. 25p.</ref>). While the area of one field plot is small, the total tallied sample area is large. Thus, such data set should be, also because of the homogeneous geographical cover, an excellent basis for species richness estimation in the inventory region.
 
Large area forest inventories such as national forest inventories are carried out in many regions so as to provide baseline information for forest and related policy formulation. A relatively large number (commonly between about 500 and several 1000s) of relatively small [[:Category:Plot design|field plots]] (commonly of areas between about 0.1 and 1 ha), usually laid out in a systematic grid over the entire inventory area, constitute the backbone of estimation (for example FAO 2003<ref name="FAO2003">FAO. 2003. Workshop on the FAO approach to national forest resources assessment and ongoing project. FAO Forest Resources Assessment Working Paper No.70/E. Food and Agriculture Organization of the United Nations, Rome. 25p.</ref>). While the area of one field plot is small, the total tallied sample area is large. Thus, such data set should be, also because of the homogeneous geographical cover, an excellent basis for species richness estimation in the inventory region.
  
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This chapter discusses some issues in this context and is largely based on based on (Lam and Kleinn 2008<ref name="lam_kleinn2008">Lam T.Y. and C. Kleinn. 2008. Estimation of tree species richness from large area forest inventory data: evaluation and comparison of Jackknife estimators. Forest Ecology and Management (3/4):1002-1010.</ref>) and we look here exclusively at estimating the number of tree species. However, the principles can, of course, be applied to any other taxa group.
+
This chapter discusses some issues in this context and is largely based on based on (Lam and Kleinn 2008<ref name="lam_kleinn2008">Lam T.Y. and C. Kleinn. 2008. Estimation of tree species richness from large area forest inventory data: evaluation and comparison of Jackknife estimators. Forest Ecology and Management (3/4):1002-1010.</ref>) and we look here exclusively at estimating the number of tree species. However, the principles can, of course, be applied to any other taxa group.
  
 
==Estimators==
 
==Estimators==

Revision as of 18:04, 18 March 2011

Forest Inventory lecturenotes
Category Forest Inventory lecturenotes not found


Contents


General observations

Species richness, that is the total number of species existing in a given area, is a common biodiversity indicator because it is simple and intuitive. However, determining the number of species (either in total or for a species group such as trees) in a given region is difficult and time consuming. Full enumeration of individuals and species is expensive. The unbiased sample-based estimation of species richness has been studied for decades. In the 1920s, Arrhenius (1921[1], 1923[2]) used extrapolation techniques to estimate species richness, and later the great R.A. Fisher (Fisher et al., 1943[3]) initiated intensive research into this matter. Bunge and Fitzpatrick (1993[4]), revealing an extraordinary variety of estimators and estimation procedures, provided an excellent theoretical review of existing species richness estimators. Up till now, however, there is no unbiased estimator available.

Species richness estimators were frequently applied to various taxa; application of the estimators to tree species from forest inventories include Chazdon et al. (1998[5]), Condit et al. (1996[6]); Hellmann and Fowler (1999[7]), Magnussen et al. (2006[8]), Palmer (1990[9], 1991[10]) and Schreuder et al.(1999[11]).

Walther and Moore (2005[12]) gathered an extensiv list of additional studies and summarized them by the species richness estimators. They also provided various definitions and measures of bias, precision and accuracy to evaluate the estimators´ performances. Colwell and Coddington (1994[13]) and Gotelli and Colwell (2001[14]) provided in depth discussion on issues related to pitfalls and cautions.

There are at least two species richness estimation softwares: EstimateS (Colwell, 2007[15]) and SPADE (Chao and Shen, 2006[16]), both easily accessible.

Estimation of species richness for larger regions is a generic sampling issue. The basic question is in principle the same as with the estimation of growing stock or tree size in a given region. However, there is also a basic difference with respect to statistical analysis: while growing stock and tree size are metric variables – species richness is a nominal variable. Thus, conventional models such as expansion factor in estimating metric variables on a per unit area basis are not applicable to species richness estimation.

Large area forest inventories such as national forest inventories are carried out in many regions so as to provide baseline information for forest and related policy formulation. A relatively large number (commonly between about 500 and several 1000s) of relatively small field plots (commonly of areas between about 0.1 and 1 ha), usually laid out in a systematic grid over the entire inventory area, constitute the backbone of estimation (for example FAO 2003[17]). While the area of one field plot is small, the total tallied sample area is large. Thus, such data set should be, also because of the homogeneous geographical cover, an excellent basis for species richness estimation in the inventory region.

This chapter discusses some issues in this context and is largely based on based on (Lam and Kleinn 2008[18]) and we look here exclusively at estimating the number of tree species. However, the principles can, of course, be applied to any other taxa group.

Estimators

Species identification

Species estimation in large area forest inventory

References

  1. ↑ Arrhenius O. 1921. Species and man. J. Ecol. 9, 95–99.
  2. ↑ Arrhenius O. 1923. Statistical investigation in the constitution of plant associations. Ecology 4, 68–73.
  3. ↑ Fisher R.A., A.S. Corbet and C.B. Williams. 1943. The relation between the number of species and the number of individuals in a random sample of an animal population. J. Anim. Ecol. 12, 42–58.
  4. ↑ Bunge J. and M. Fitzpatrick. 1993. Estimating the number of species: a review. J. Am. Stat. Assoc. 88, 364–373.
  5. ↑ Chazdon R.L., R.K. Colwell, J.S. Denslow and M.R. Guariguata. 1998. Statistical methods for estimating species richness of woody regeneration in primary and secondary rain forests of Northeastern Costa Rica. In: Dallmeier F and JA Comisky. (Eds.), Forest biodiversity research, monitoring and modelling. The Parthenon Publishing Group, Paris, France, pp. 285–309.
  6. ↑ Condit R.G. 1998. Tropical forest census plots: methods and results from Barro Colorado Island, Panama and a comparison with other plots. Heidelberg: Springer-Verlag.
  7. ↑ Hellmann J.J. and G.W. Fowler. 1999. Bias, precision, and accuracy of four measures of species richness. Ecol. Applic. 9, 824–834.
  8. ↑ Magnussen S., R. Pélissier, F. He and B.R. Ramesh. 2006. An assessment of sample-based estimators of tree species richness in two wet tropical forest compartments in Panama and India. Int. For. Rev. 8, 417–431.
  9. ↑ Palmer M.W. 1990. The estimation of species richness by extrapolation. Ecology 71, 1195–1198.
  10. ↑ Palmer M.W. 1991. Estimating species richness: the second-order jackknife reconsidered. Ecology 72, 1512–1513.
  11. ↑ Schreuder, H.T., R.C. Czaplewski and R.G. Bailey. 1999. Combining mapped and statistical data in forest ecological inventory and monitoring-supplementing an existing system. Env Mon Asst 56:269-291.
  12. ↑ Walther B.A. and J.L. Moore. 2005. The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance. Ecography 28, 815–829
  13. ↑ Colwell R.K. and J.A. Coddington. 1994. Estimating terrestrial biodiversity through extrapolation. Philos. T. Roy. Soc. B. 345, 101–118.
  14. ↑ Gotelli N.J. and R.K. Colwell. 2001. Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecol. Lett. 4, 379–391.
  15. ↑ Colwell R.K. 2007. EstimateS: Statistical estimation of species richness and shared species from samples. Version 8.0. User's Guide and application published at: http://purl.oclc.org/estimates.
  16. ↑ Chao A. and T.J. Shen. 2006. Program SPADE (Species Prediction And Diversity Estimation). Program User’s Guide published at http://chao.stat.nthu.edu.tw/.
  17. ↑ FAO. 2003. Workshop on the FAO approach to national forest resources assessment and ongoing project. FAO Forest Resources Assessment Working Paper No.70/E. Food and Agriculture Organization of the United Nations, Rome. 25p.
  18. ↑ Lam T.Y. and C. Kleinn. 2008. Estimation of tree species richness from large area forest inventory data: evaluation and comparison of Jackknife estimators. Forest Ecology and Management (3/4):1002-1010.

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