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Analysis of species hyper-diversity in the tropical rain forests of Indonesia: the problem of non-observance

Analysis of species hyper-diversity in the tropical rain forests of Indonesia: the problem of non-observance

Rennolls, Keith and Laumonier, Yves (1998) Analysis of species hyper-diversity in the tropical rain forests of Indonesia: the problem of non-observance. In: Sassa, Kyoji, (ed.) Environmental Forest Science. Proceedings of the IUFRO Division 8 Conference Environmental Forest Science, held 19–23 October 1998, Kyoto University, Japan. Forestry Sciences (54). Springer Netherlands, pp. 355-362. ISBN 978-94-010-6237-4 (doi:10.1007/978-94-011-5324-9_38)

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Abstract

The main interest in the assessment of forest species diversity for conservation purposes is in the rare species. The main problem in the tropical rain forests is that most of the species are rare. Assessment of species diversity in the tropical rain forests is therefore often concerned with estimating that which is not observed in recorded samples. Statistical methodology is therefore required to try to estimate the truncated tail of the species frequency distribution, or to estimate the asymptote of species/diversity-area curves. A Horvitz-Thompson estimator of the number of unobserved (“virtual”) species in each species intensity class is proposed. The approach allows a definition of an extended definition of diversity, ( or generalised Renyi entropy). The paper presents a case study from data collected in Jambi, Sumatra, and the “extended diversity measure” is used on the species data.

Item Type: Book Section
Additional Information: [1] Chapter 2, in Environmental Forest Science. Proceedings of the IUFRO Division 8 Conference Environmental Forest Science, held 19–23 October 1998, Kyoto University, Japan. [2] Print ISBN: 978-94-010-6237-4; Online ISBN: 978-94-011-5324-9 [3] Book Series ISSN: 0924-5480.
Uncontrolled Keywords: species diversity, virtual species, extended species diversity
Subjects: Q Science > QA Mathematics
S Agriculture > SD Forestry
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Department of Computer Science
School of Computing & Mathematical Sciences > Statistics & Operational Research Group
Related URLs:
Last Modified: 14 Oct 2016 08:59
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/238

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