A comparison of distance sampling methods in Saxaul (Halloxylon ammodendron (C.A. Mey Bunge) shrub-lands

• Autorzy: Kiani B. , Fallah A. , Tabari M. , Hosseini S. M. , In Parizi M.-H.
• Języki publikacji: EN

Abstrakty

EN

The primarily goal of plot-less sampling methods is to reduce costs and rapid survey of plant communities. First full inventory was conducted in two 30-ha sites of Saxaul populations geo-morphologically different. In first site (site I), population had random pattern while in second site (site II) clumped pattern was observed. Crown diameters and spatial situation of all trees were recorded using distance and azimuth. Data were transferred to computer and stem map was generated with ArcGIS Software. Distance sampling methods include point-centred quarter method (PCQ), joint-point method (JP), Random pairs method (RP), T-Square method (T-Sq) and Quartered neighbour methods beside fixed area plot (FAP), n-tree and variable area transect (VAT) methods were conducted on generated stem maps. A time study was done aiding indices determined in field works. In site I, point centred quarter estimator with measurements to the second closest individual in each quadrant had the lowest relative bias (RBIAS) in estimating density followed by 3-tree and closest individual methods. In clumped pattern (site II), variable area transect method with measurements to the 4^th and 5^th closest individuals in each transect brought the best results. The most time consuming methods after fixed area plot, were point centred quarter estimators while methods considering measurement to the closest individual were rapid. Considering RBIAS and Time together, VAT method was the best sampling method in clumped pattern followed by point centred quarter estimator with measurements to the second closest individual in each quadrant and closest individual estimators. In random pattern, point centred quarter estimator with measurements to the second closest individual in each quadrant was the best method followed by 3-treeandclosest individualestimators. But for estimating cover per unit area N-tree methods performed well. As in this site, VAT method located in 4^th grade, and due to simplicity of field works related to this method, in the case that the investigator would not be able to clearly define spatial pattern of the population, this method can be recommended as well.

Słowa kluczowe

EN

accuracy; density; inventory activities; percent cover; plot-less methods; time study

PL

dokładność; gęstość; inwentarz; okres badania

• Wydawca: Museum and Institute of Zoology, Polish Academy of Sciences
• Czasopismo: Polish Journal of Ecology
• Rocznik: 2013
• Tom: Vol. 61, nr 2
• Strony: 207--219
• Opis fizyczny: Bibliogr. 45 poz., il.

Twórcy

autor

Kiani B.

• Department of Forest Sciences, Faculty of Natural Resources, Tarbiat Modares University, Noor, Mazandaran, Iran

autor

Fallah A.

• Department of forest Science, Faculty of Natural Resources, University of Agricultural and Natural Resource Sciences, Sari, Iran

autor

Tabari M.

• Department of Forest Sciences, Faculty of Natural Resources, Tarbiat Modares University, Noor, Mazandaran, Iran

autor

Hosseini S. M.

• Department of Forest Sciences, Faculty of Natural Resources, Tarbiat Modares University, Noor, Mazandaran, Iran

autor

In Parizi M.-H.

• Department of Forestry, Faculty of Natural Resources, Yazd University, Iran

Bibliografia

• 1. Barbour M.G., Burk J.H., Pitts W.D. 1987 - Terrestrial Plant Ecology, Chapter 9: Method of sampling the plant community - Menlo Park, CA: Benjamin/Cummings Publishing Co., 634 pp.
• 2. Batcheler C.L. 1971 - Estimation of density from a sample of joint point and nearest neighbour distances - Ecology, 52: 703-709.
• 3. Batcheler C.L. 1975 - Development of a deer census from pellet groups - J. Wildlife Man-age. 39: 641-652.
• 4. Beasom S.L., Haucke H.H. 1975 - A comparison of four distance sampling techniques in South Texas live oak mottes - J. Range Manage. 28: 142-144.
• 5. Besag J. E., Cleaves J.T. 1973 - On the detection of spatial pattern in plant communities Bulletin of the international Statistical Institute, 45: 153-158.
• 6. Byth K. 1982 - On robust distance-based intensity estimators - Biometrics, 38: 127-135.
• 7. Byth K., Ripley B.D. 1980 - On sampling spatial patterns by distance methods - Biometrics, 36: 279-284.
• 8. Cottam G. 1947 - A point method for making rapid surveys of woodlands - Bull. Ecol. Soc. Am. 28: 60.
• 9. Cottam G., Curtis J.T. 1949 - A method for making rapid surveys of woodlands by means of pairs of randomly selected trees - Ecology, 30: 101-104.
• 10. Cottam G., Curtis J.T. 1954 - The use of distance measures in phytosociological sampling -Ecology, 37:451-461.
• 11. Cottam G., Curtis J.T., Hale B.W. 1953-Some sampling characteristics of e population of randomly dispersed individuals - Ecology, 34:41-57.
• 12. Cox G. 1990 - Laboratory manual of general ecology - 6^th Ed. Dubuque, Iowa: William C. Brown, 272 pp.
• 13. Diggle P.J. 1975-Robust density estimation using distance methods - Biometrika, 62:39-48.
• 14. Diggle P.J. 1976 - Note on the dark ane Evans test of spatial randomness - Appendix to Hodder and Orton, pp. 246-248.
• 15. Dobrowski S.Z., Murphy SH.K. 2006 -A practical look at the variable are transect -Ecology, 87: 1856-1860.
• 16. Engeman R.M., Sugihara R.T. 1998 - Optimizations of variable area transect sampling using Monte Carlo simulation - Ecology, 79: 1425-1434.
• 17. Engeman R.M., Pank L.F., Sugihara R.T., Dusenberry R.T. 1994 - A comparison of Plot-less density estimators using Monte Carlo simulation - J. Ecol. 75:1769-1779.
• 18. Heidari R.H., Zobeiri M., Namiranian M., Sobhani H. 2007 - Application of T-square sampling method in Zagross forests (Case Study: Kerman-shah province) - Iran. J. For. Poplar Res. 15: 32-42.
• 19. Heidari R.H., Zobeiri M., Namiranian M., Sobhani H., Safari A. 2011 -Study of accuracy of nearest individual sampling method in Zagross forests - Iran. J. For. 2: 323-330.
• 20. Iran Nejad Parizi, M. H., Sarhangzadeh, J., Azimzadeh, H., Elmi, M., Hosseini, S. Z., Hazeri, F. 2006 - Capabilities and difficulties of Siahkooh protected area, Yazd, Iran - J. Environ. Sc. 39: 89-100.
• 21. Kiani B., Tabari M., Fallah A., Hosseini S.M., Iran-Nejad Parizi M.H. 2011 - Optimal method to determine density of the Scarce vegetation in dry desert, variable area transect (VAT) applied to Saxaul (Haloxylon ammodendron) community - Pol. J. Ecol. 59: 823-828.
• 22. Klein C. H., Vilkco F. 2005 - On estimation in k-tree sampling - Proceedings of 7^th Annual Forest Inventory and Analysis Symposium, Portland, pp. 203-208.
• 23. Klein C.H., Vilkco F. 2006 - Design unbiased estimation for point to tree distance sampling Can. J. For. Res. 36: 1407-1414.
• 24. Lewis S.M. 1975 - Robust estimation of density for a two-dimensional point process -Biometrika, 625: 19-521.
• 25. Lynch TH.B., Rusydi R. 1998 - Distance sampling for forest inventory in Indonesian teak plantations - For. Ecol. Manage. 113: 215-221.
• 26. Lynch T.H.B., Wittwer R.F. 2003 - Per tree estimates with n-tree distance sampling: an application to increment core data - Proceedings of the 3rd Annual Forest Inventory and Analysis Symposium, Michigan, USA.
• 27. Magnussen S., Kleinn C., Picard N. 2008 - Two new density estimators for distance sampling - Europ. J. For. Res. 127: 213-224.
• 28. Marcy L.E. 1988 - Distance sampling techniques, Technical Report EL-88-23 - Environmental Laboratory, Department of the Army, US Army Corps of Engineers, 83 pp.
• 29. Mitchell K. 2007 - Quantitative analysis by the point-centered quarter method, department of mathematics and computer sciences - Hobart and William Colleges, Geneva, NY 14456, 34 pp.
• 30. Morisita M. 1954 - Estimation of population density by a spacing method - Memoirs of the faculty of science, Kyushu University, 1: 187-197.
• 31. Morisita M. 1957 - A new method for the estimation of density by spacing method applicable to non-randomly distributed populations Physiol. Ecol. 7: 134-144.
• 32. Morisita M. 1971 - Comparison of la Index -Researches on Populations Ecology, 13: 1- 27.
• 33. Moosaee Sanjerehei M., Basiri M. 2008 -Comparison and evaluation of various density estimation methods in Artemisia populations of Yazd province, Iran - Iran. J. Nat. Res., 61: 235-251.
• 34. Nielson R.M., Sugihara R.T., Boardman THJ,, Engeman R.M. 2004 - Optimization of ordered distance sampling - Environ-metrics, 15: 119-128 (DOI: 10.1002/env.627).
• 35. Parker K.R. 1979 - Density estimation by variable area transect - J. Wild. Manage. 43: 484-492.
• 36. Picard N., Bar-Hen A. 2007 - Estimation of density of a clustered point pattern using a distance method - Environ. Ecol. Sta. 14: 341-353.
• 37. Picard N., Kouyate A.M., Dessard H. 2005 - Tree density estimations using a distance method in Mali Savanna - J. For. Sci. 31: 7-18.
• 38. Pollard J. H. 1971 - On distance estimators of density in randomly distributed forests - Biometrics, 27: 991-1002.
• 39. Prodan M. 1969 - Punktstichprobe fur die Forsteinrichtung - Forst- und Holzwirt, 23: 225-226.
• 40. Sabeti K. 1994 - Forests, trees and shrubs of Iran - Yazd University Press, pp. 383-387.
• 41. Sheil D., Ducey M.J., Sidiyasa K., Sam-soedin I. 2003 - A new type of sample unit for the efficient assessment of diverse tree communities in complex forest landscapes - J. Trop. For. Sci. 15:117-135.
• 42. Sheng Y., Zheng W., Pei K., Ma K. 2005 - Genetic variation within and among populations of a dominant desert tree Haloxylon ammodendron in China - Annals of Botany, 96: 245-252.
• 43. Sparks J.C., Masters R.E., Payton M.E. 2002 - Comparative evaluation of accuracy and efficiency of six forest sampling methods - Proc. Oklahoma Academic Sciences, 82: 49-56.
• 44. Xunzhi Z., Jintun Z. 2009 - Quartered neighbor method: A new distance method for density estimation - College of Life Sciences, Beijing Normal University, China.
• 45. Zobeiry M. 1978 - Tree sampling in natural forests of northern Iran - For. Chronicle, 54: 171-172.