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- Herausgeber: Bentham Science Publishers
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
This brief book is dedicated to the quantitative analyses and systematic discussion of spatial biodiversity and biogeographic patterns in the Asia‐pacific region comprised of China, India and adjacent countries. The book is split into two sections. The first section presents readers with detailed statistical methods to conduct spatial macro‐biodiversity and biogeography analyses. Step-by-step instructions on how to perform these statistical methods by using the statistical program R are also provided. In the second part, different quantitative case studies are presented covering several topics, including phylogenetics, spatial statistics, multivariate statistics and ecological genomics. Each case study concludes with a detailed interpretation of the quantitative results and how these results are relevant to local and regional ecological processes. This reference is suitable for academics interested in biostatistics biodiversity and ecological studies specific to the Asia Pacific region and China.
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Veröffentlichungsjahr: 2015
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Biodiversity and Biogeographic Patterns
in Asia-Pacific Region I: Statistical
Methods and Case Studies
Authored By
Youhua Chen
BENTHAM SCIENCE PUBLISHERS LTD.
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FOREWORD
Juan J. MorroneBiogeography is the biological discipline that studies the geographic distribution of plant and animal taxa and their attributes in space and time. Nowadays, it is passing through a revolution concerning its foundations, basic concepts, and methods. As part of this revolution, biogeographers are increasingly recognizing the need of integration with other disciplines, in order to develop a truly interdisciplinary and pluralist science. The recent discipline of conservation biogeography shows clearly the possibilities of interdisciplinary collaboration. Additionally, during the last decades, there has been a considerable progress in the quantitative analysis of biogeographical patterns, with statistical multivariate and phylogenetic methods proposed to analyse particular ecological and biogeographical patterns and to establish meaningful comparisons.
The book written by Youhua Chen presents a thoughtful analysis of different biogeographical methods and their application to the analysis of biotic patterns in the Asia-Pacific region, which encompasses China, India and southeast Asia, and represents a very interesting region, which possesses an outstanding biodiversity. The analyses of different plant and animal taxa, using several biogeographical methods, led Youhua to identify clear patterns and to correlate them with climatic and biological data. Finally, he highlighted the relevance of these patterns for biodiversity conservation.
There are different reasons to read this book. Biogeographers will be interested in an outstanding region of the world, with specific chapters on birds and plants as case studies. Conservationists will appreciate the identified biogeographical patterns, which might help them establish conservation priorities. Ecologists will have a modern review of several methods used to analyse species-area relationships, species abundance and modelling species' potential distributions, among other patterns. Naturalists will be delighted with the rich biological information conveyed in the analyses. Students will learn about theoretical issues, and the case studies will surely make them think about biogeographic questions and how to answer them. I am sure that all of them will enjoy this very interesting book!
PREFACE
Youhua ChenIn the past several decades, biodiversity conservation has gradually become a mainstream sub-discipline in contemporary biology. The importance of biodiversity conservation is straightforward for non-scientists to understand because in this post-industrialization and information-based era, people become more aware about the harmony between human being, society and nature. Biodiversity science is a leading multidisciplinary science in 21st century.
In tropical and temperate Asia, there are two BRICS countries: India and China, both are giant and developing countries. At the end of 2013, human population sizes of both countries rank at the top two across the nations of the whole world. Species extinction and biodiversity conservation in these areas is definitely challenging and urgent because of the expanding population, environmental pollution, rapid urbanization and industrialization.
In comparison to developed countries, biodiversity survey in most Asian countries seems not so comprehensive. New species are growingly discovered in the region, and the mega-biodiversity and original forests in the region provide invaluable resources for ecologists to explore biodiversity patterns over there. It is a great opportunity to present biodiversity and biogeography patterns at the region. My book can convey valuable information for researchers interested in the conservation issues of the Asian countries.
This book is dedicated to the quantitative analyses and systematic discussion of spatial biodiversity and biogeographic patterns in Asia-pacific region, including China, India and other south-eastern Asian countries. In the book, for the first part, the modern statistical and numerical methods have been introduced to the readers to tell them how to conduct spatial macro-biodiversity and biogeography analyses. These statistical methods have been widely used by researchers that are still active in the field of biodiversity and ecology. In second part of the book, different case studies over the region were provided, which covered very broad topics using many quantitative methods that have been introduced in the first part of the book, including phylogenetics, spatial statistics, multivariate statistics and others. As case studies, I provided detailed interpretation of the quantitative results and how these results are relevant to local and regional ecological processes. The book is suitable for anyone interested in biodiversity conservation to read. In particular, it is adequate for the undergraduate students that need a textbook to learn ecological methods and graduate students and scholars that need to know the recent advances in the field of biodiversity conservation, biogeography and macroecology.
The key features of my book are,
The book focuses on Asia-Pacific region, which is a very unique region and mega-biodiversity hotspot in the world. As far as I know, there is no book contributing to the biodiversity conservation knowledge over the region. Thus, my book is the first one that only focuses on biodiversity and biogeography in Asia-Pacific region systematically and comprehensively.The book focuses on discussing the statistical methods on spatial biodiversity and biogeography patterns, thus may be of interests to academic researchers.The statistical methods in my book cover a broad range and represent the most up-to-dated ones that are widely used in current biodiversity and macroecology studies, including spatial statistics, phylogenetic theory, neutral networks and ecological genomics.The audience of the book includes university libraries, academic scholars and professors, graduate and undergraduate students.
Writing of the book has been generously supported by the China Scholarship Council. I am very grateful to Prof. Juan J. Morrone, one of the most eminent biogeographers, for kindly writing the foreword for my book and supporting my researches for a long time since we know each other. At last, this book is dedicated to my parents (Fashen Chen and Yuying Zhong) and my sisters (Ying, Fang and Yuan) for their love and support. Definitely, I can not complete this book without them behind my back.
ACKNOWLEDGEMENTS
This work is supported by the China Scholarship Council (No. 201308180004).
CONFLICT OF INTEREST
The author confirms that this eBook contents have no conflict of interest.
Species Richness and Diversity
Abstract
This chapter provides some metrics for measuring species diversity, the most basic and important diversity component in ecological studies. The metrics for species diversity covered only some common used ones in this book, like Shannon and Simpson indices. The closed forms for computing the variance of the relevant indices are also provided. Typical methods for the extrapolation of species richness are also mentioned in the text.
INTRODUCTION
Species richness is simply the number of species in your ecological system. Species diversity is a bit complex, in addition to quantify the total number of species in the system, it also evaluated how even of the population sizes (or abundance) over different species in the system. Thus, diversity should be measured in two facets: count and evenness.
The concept of species diversity could be extended to taxonomic classes that are beyond the species concept. For example, at population level, diversity is usually called as genetic diversity. At taxonomic classification level, diversity is termed as taxonomic diversity and/or phylogenetic diversity, depending on the metrics that are used to quantify diversity. At last, at trait perspective, diversity is termed as functional diversity. Thus, biological diversity is a definition with tremendous meanings. Biological diversity constitutes the beautiful nature surrounding our humans on the earth.
In this Chapter, I will present some common statistical methods for quantifying species diversity. Also, the methods for extrapolating the diversity patterns will be presented. For other diversity components, like phylogenetic diversity and functional diversity, they will be presented in other sectors.
MEASURE OF SPECIES DIVERSITY
Species Richness
Species richness for a local sample is simply to count the number of species found in the sample. It’s calculation reads,
Where I(pi) is an indicator function, I(pi)=1 if pi>0, and I(pi)=0 ifpi=0.
Shannon Diversity Index
Shannon index [1] is the most classical index for measuring species diversity, its calculation reads,
Where N is the total individuals found the sample from all the species. S is the total number of species in the sample. ni is the abundance for species i.
The evenness of the Shannon index is computed as,
Where H'max is computed as H'max=−∑i=1S1Sln{1S}=lnS.
Thus, evenness is calculated as,
The variance of Shannon’s index is given by,
or,
The second one is more accurate [2], especially for small sample cases.
Simpson Diversity Index
Simpson’s index D [3] might be the most meaningful measure of evenness. D is the probability that two randomly sampled individuals are from two different species. Such a definition is analogous to the genetic concept-heterozygosity.
where N is the total individuals found the sample from all the species. S is the total number of species in the sample. ni is the abundance for species i.
For computing 95% confidence interval, the variance of the Simpson’s index D should be known, which reads,
or a more accurate closed form as follows,
The above formula is said to very suitable for small sample cases [2].
Renyi Entropy
The Rényi entropy is a generalization of the Shannon entropy to other values of q than unity. It can be expressed:
q defines the order of the entropy.
EXTRAPOLATION OF SPECIES RICHNESS
Chao1 and Chao2 Indices
Chao1 and Chao2 indices [4] might be the most common used ones for extrapolating regional species richness based on the data from local samples (Chao2 index) or the species’ richness in a fixed sample (Chao1 index, if we measure the abundance of each species in the fixed sample). Its calculation formula is given by,
If F2=0, then SChao=Sobs+F1(F1−1)/2.
where SChao is the estimated richness at regional scale (or sample) or a fixed sample, Sobs is the number of species that are found across all the local samples in the fixed sample, F1is the number of singletons (i.e., the number of species with only one individual in the fixed sample or the number of species that are found in only one local sample across all the samples at regional perspective) and F2 is the number of doubletons (the number of species with only two individuals in the fixed sample or the number of species that are found in only one local sample across all the samples if regional richness is extrapolated).
The simple idea behind the estimator is that if a sampled site contains a lot of rare species that are not found in other sites (that is, they are only distributed in the focused site, being singletons), it is very likely that there are more rare species in the site required to be detected or discovered.
To get the 95% confidence interval for the Chao1 estimator, the variance of the index should be computed, which followed [5],
To get lower and upper bounds of the 95% confidence interval, the following statistics should be calculated,
where LCI95% and UCI95% represent the lower and upper bounds of the 95% confidence interval.
Jackknife Estimators
The Jackknife estimator [6] is also commonly used for estimating regional richness (not abundance-based), which is given by,
Where m denotes the total number of local samples. In particular, here, F1 only denotes the number of species that are found in only one local sample across the whole region.
The above index is a first-order estimator; there is a second-order version [7] of the estimator, which is given by,
Rarefaction Curve
Rarefaction is also widely used to interpolate species richness. Let Sind(m) denotes the expected number of species from a random sample with m individuals which is drawn from a reference pool with S species and n individuals in a total (n>m) [8]. If the true probabilities/relative abundance of each species ipi was known prior, then the species frequencies {n1,n2,...,nS} follow a multinomial distribution with the probabilities {p1,p2,...,pS}. Then the expected number of species in the local sample with m individuals is given by,
however, as a matter of fact, the true pi are unknown, and its abundance in the reference pool is observed as ni and the total species observed is Sobs, then an unbiased estimator of Sind(m) is given by [9],
Calculate S^ind(m) over a range of m, we could plot them together to generate the rarefaction curve.
REMARKS
Comparison of species diversity across different sampling sites is one of the major tasks in ecological studies. A proper diversity index for doing the comparison will be extremely important. Otherwise the results based on unsuitable diversity metrics might be biased or totally misleading. Rarefaction methods introduced in this chapter would be of great helps in the comparison of species diversity across sites with various species number and abundance.
