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Multi-scale sampling of native and n...

Chong, Geneva Wai-Leng.

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Multi-scale sampling of native and non-native plant diversity: Examples of data analyses and applications.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Multi-scale sampling of native and non-native plant diversity: Examples of data analyses and applications./
Author:	Chong, Geneva Wai-Leng.
Description:	116 p.
Notes:	Adviser: Thomas J. Stohlgren.
Contained By:	Dissertation Abstracts International63-09B.
Subject:	Biology, Botany. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3063980
ISBN:	0493828788

Multi-scale sampling of native and non-native plant diversity: Examples of data analyses and applications.
Chong, Geneva Wai-Leng.

Multi-scale sampling of native and non-native plant diversity: Examples of data analyses and applications. - 116 p.

Adviser: Thomas J. Stohlgren.

Thesis (Ph.D.)--Colorado State University, 2002.

Multi-scale vegetation data were collected in Rocky Mountain National Park, Colorado, USA. Analyses were conducted on subsets of data depending on specific study objectives, the area of the Park in question, and the appropriate statistical approach.

ISBN: 0493828788Subjects--Topical Terms:

1017825
Biology, Botany.

Multi-scale sampling of native and non-native plant diversity: Examples of data analyses and applications.
LDR:03286nam 2200337 a 45 001 933002
005 20110505
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020 $a 0493828788
035 $a (UnM)AAI3063980
035 $a AAI3063980
040 $a UnM $c UnM
100 1 $a Chong, Geneva Wai-Leng. $3 1256742
245 1 0 $a Multi-scale sampling of native and non-native plant diversity: Examples of data analyses and applications.
300 $a 116 p.
500 $a Adviser: Thomas J. Stohlgren.
500 $a Source: Dissertation Abstracts International, Volume: 63-09, Section: B, page: 4019.
502 $a Thesis (Ph.D.)--Colorado State University, 2002.
520 $a Multi-scale vegetation data were collected in Rocky Mountain National Park, Colorado, USA. Analyses were conducted on subsets of data depending on specific study objectives, the area of the Park in question, and the appropriate statistical approach.
520 $a Species-area curves and measures of heterogeneity combined with information on the area covered by each vegetation type showed that the types making the greatest contributions to biodiversity at the landscape-scale covered the smallest areas. This approach may provide an accurate and relatively rapid way to rank landscape-scale hotspots of plant diversity within regions of interest.
520 $a Butterfly diversity was sampled in conjunction with vegetation in the Beaver Meadows area of the Park. Over 180 vascular plant species were unique to the aspen vegetation type (N = 32 plots). The slope of the mean species-area curve for the aspen vegetation type was the steepest of the 10 types sampled, and aspen plots contained the greatest number of native butterfly species. However, aspen plots were the most heavily invaded by non-native plant species, which could have negative effects on native plant and butterfly species diversity.
520 $a I used stepwise multiple regression and modified residual kriging to estimate the numbers of native and exotic species, and the probability of observing a non-native species in 30 m x 30 m cells over a 54,000 ha area. These models can efficiently direct resource managers to areas in need of further inventory, monitoring, and non-native species control efforts.
520 $a I compared the abilities of trend surface analysis alone and in combination with regression tree analysis to develop full-coverage surfaces of the cover and richness of total, native, and non-native plant species in an 80,000 ha portion of the Park. The combination of approaches consistently outperformed the trend surface analysis alone with an increase in average R<super>2</super> from 0.17 to 0.54.
520 $a Future applications of this research approach could be useful for developing the concept of “scalable models” where the area modeled is adjusted to produce the most accurate models given sparse data in complex terrain. These models could then be used to estimate variables of interest in the unsampled area to direct future work.
590 $a School code: 0053.
650 4 $a Biology, Botany. $3 1017825
650 4 $a Biology, Ecology. $3 1017726
690 $a 0309
690 $a 0329
710 2 0 $a Colorado State University. $3 675646
773 0 $t Dissertation Abstracts International $g 63-09B.
790 $a 0053
790 1 0 $a Stohlgren, Thomas J., $e advisor
791 $a Ph.D.
792 $a 2002
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3063980