Optimal sample area estimation for medicinal plant biodiversity assessment of a logged over hill forest in Jerantut, Malaysia

In plant inventory, sampling technique was less being considered by botanists. Sometimes the sampling is not enough and sometimes it is more than enough. Thus, it is wasting cost and time consuming. This study attempted to determine an optimal sample area required for medicinal plant biodiversity...

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Main Author:	Mohamad Ehsan, Norhajar Eswani
Format:	Thesis
Language:	English
Published:	2011
Subjects:	Medicinal plants - Pahang Medicinal plants - Variation - Pahang Plant diversity - Pahang
Online Access:	http://psasir.upm.edu.my/id/eprint/84989/1/FH%202011%2011%20ir.pdf
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spelling	my-upm-ir.849892021-12-31T02:56:28Z Optimal sample area estimation for medicinal plant biodiversity assessment of a logged over hill forest in Jerantut, Malaysia 2011-08 Mohamad Ehsan, Norhajar Eswani In plant inventory, sampling technique was less being considered by botanists. Sometimes the sampling is not enough and sometimes it is more than enough. Thus, it is wasting cost and time consuming. This study attempted to determine an optimal sample area required for medicinal plant biodiversity assessment, identify the traded medicinal plant resources available in forest, and examine the relationship between true size and quadrat size on medicinal plant diversity parameters such as species richness, species evenness and species accumulation. This study was conducted in Tekai Tembeling Forest Reserve (TTFR), Jerantut, Pahang. Four l-ha plots (Plotl, Plot2, Plot3 and Plot4) were established within the forest area at the elevation range 300 a.s.l - 550 a.s.l. Each plot was divided into 100 quadrats of size lOx1Om. Dbh, height, species name and number of trees by species were recorded. Species richness, diversity and evenness were estimated using Ecological Methodology Software. IVI was also computed to study the dominance vegetation of forest. Optimal sample area obtained from species area curve or species accumulation curve. Species area curves were constructed from species richness and selection quadrats were based on systematic and random approaches. There are four ways to determine species richness; number of species observed, extrapolation of species area curve, log-normal distribution and nonparametric estimator. Nonparametric estimators included Chao 1, Cha02, Jack 1, Jack2, ACE, ICE and Bootsrap. The entire estimator evaluated based on the Mean Square Deviation (MSD). The smallest MSD is the best estimator. Quadrat selection method has two techniques; systematic and random. Systematic has four approaches while random has two approaches. Species area curve was constructed from each approaches. There were 236 species, 179 genera and 87 families of medicinal plants found. The most abundant family, genera and species were Euphorbiaceae, Macaranga and Lygodium circinnatum respectively. Most of the medicinal plants having dbh below than 5cm and only 33 individuals out of 674 having dbh greater than 50cm. Cinnamomum porrectum is the most dominant species according to IVI. Uses of each medicinal plant were also explained briefly. Species diversity showed Plot2 is the most diverse based on Shannon diversity index and Plot3 is the most even area because possessed highest evenness index. Estimates program estimated 227 species in 4-ha but the true species observed is 236. Extrapolation of species area curve indicates the graph did not approach an asymptote but increase more rapidly. The log-normal distribution showed the LnS = -0.47833 + (0.577954 * Ln(A)) is the estimate regression equation generated for the species accumulation pattern of TTFR. Nonparametric estimator showed ACE is the best estimator. Even though the species observed showed the accurate result but, in term of non parametric estimator ACE is the best. For quadrat selection method, species area curve for even quadrat, odd quadrat, row plot and 75% randomly chosen quadrat showed the graph attain an asymptote or optimal point. Thus, the inventory of medicinal plants did not require to carry out through all plots or quadrats since the sampling technique mentioned before enough to cover the species richness. Medicinal plants - Pahang Medicinal plants - Variation - Pahang Plant diversity - Pahang 2011-08 Thesis http://psasir.upm.edu.my/id/eprint/84989/ http://psasir.upm.edu.my/id/eprint/84989/1/FH%202011%2011%20ir.pdf text en public masters Universiti Putra Malaysia Medicinal plants - Pahang Medicinal plants - Variation - Pahang Plant diversity - Pahang Abd Kudus, Kamziah
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
advisor	Abd Kudus, Kamziah
topic	Medicinal plants - Pahang Medicinal plants - Variation - Pahang Plant diversity - Pahang
spellingShingle	Medicinal plants - Pahang Medicinal plants - Variation - Pahang Plant diversity - Pahang Mohamad Ehsan, Norhajar Eswani Optimal sample area estimation for medicinal plant biodiversity assessment of a logged over hill forest in Jerantut, Malaysia
description	In plant inventory, sampling technique was less being considered by botanists. Sometimes the sampling is not enough and sometimes it is more than enough. Thus, it is wasting cost and time consuming. This study attempted to determine an optimal sample area required for medicinal plant biodiversity assessment, identify the traded medicinal plant resources available in forest, and examine the relationship between true size and quadrat size on medicinal plant diversity parameters such as species richness, species evenness and species accumulation. This study was conducted in Tekai Tembeling Forest Reserve (TTFR), Jerantut, Pahang. Four l-ha plots (Plotl, Plot2, Plot3 and Plot4) were established within the forest area at the elevation range 300 a.s.l - 550 a.s.l. Each plot was divided into 100 quadrats of size lOx1Om. Dbh, height, species name and number of trees by species were recorded. Species richness, diversity and evenness were estimated using Ecological Methodology Software. IVI was also computed to study the dominance vegetation of forest. Optimal sample area obtained from species area curve or species accumulation curve. Species area curves were constructed from species richness and selection quadrats were based on systematic and random approaches. There are four ways to determine species richness; number of species observed, extrapolation of species area curve, log-normal distribution and nonparametric estimator. Nonparametric estimators included Chao 1, Cha02, Jack 1, Jack2, ACE, ICE and Bootsrap. The entire estimator evaluated based on the Mean Square Deviation (MSD). The smallest MSD is the best estimator. Quadrat selection method has two techniques; systematic and random. Systematic has four approaches while random has two approaches. Species area curve was constructed from each approaches. There were 236 species, 179 genera and 87 families of medicinal plants found. The most abundant family, genera and species were Euphorbiaceae, Macaranga and Lygodium circinnatum respectively. Most of the medicinal plants having dbh below than 5cm and only 33 individuals out of 674 having dbh greater than 50cm. Cinnamomum porrectum is the most dominant species according to IVI. Uses of each medicinal plant were also explained briefly. Species diversity showed Plot2 is the most diverse based on Shannon diversity index and Plot3 is the most even area because possessed highest evenness index. Estimates program estimated 227 species in 4-ha but the true species observed is 236. Extrapolation of species area curve indicates the graph did not approach an asymptote but increase more rapidly. The log-normal distribution showed the LnS = -0.47833 + (0.577954 * Ln(A)) is the estimate regression equation generated for the species accumulation pattern of TTFR. Nonparametric estimator showed ACE is the best estimator. Even though the species observed showed the accurate result but, in term of non parametric estimator ACE is the best. For quadrat selection method, species area curve for even quadrat, odd quadrat, row plot and 75% randomly chosen quadrat showed the graph attain an asymptote or optimal point. Thus, the inventory of medicinal plants did not require to carry out through all plots or quadrats since the sampling technique mentioned before enough to cover the species richness.
format	Thesis
qualification_level	Master's degree
author	Mohamad Ehsan, Norhajar Eswani
author_facet	Mohamad Ehsan, Norhajar Eswani
author_sort	Mohamad Ehsan, Norhajar Eswani
title	Optimal sample area estimation for medicinal plant biodiversity assessment of a logged over hill forest in Jerantut, Malaysia
title_short	Optimal sample area estimation for medicinal plant biodiversity assessment of a logged over hill forest in Jerantut, Malaysia
title_full	Optimal sample area estimation for medicinal plant biodiversity assessment of a logged over hill forest in Jerantut, Malaysia
title_fullStr	Optimal sample area estimation for medicinal plant biodiversity assessment of a logged over hill forest in Jerantut, Malaysia
title_full_unstemmed	Optimal sample area estimation for medicinal plant biodiversity assessment of a logged over hill forest in Jerantut, Malaysia
title_sort	optimal sample area estimation for medicinal plant biodiversity assessment of a logged over hill forest in jerantut, malaysia
granting_institution	Universiti Putra Malaysia
publishDate	2011
url	http://psasir.upm.edu.my/id/eprint/84989/1/FH%202011%2011%20ir.pdf
_version_	1747813509339545600

Optimal sample area estimation for medicinal plant biodiversity assessment of a logged over hill forest in Jerantut, Malaysia

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