DOCSLIB.ORG

Scale Dependence of the Beta Diversity-Scale Relationship

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Scale Dependence of the Beta Diversity-Scale Relationship COMMUNITY ECOLOGY 16(1): 39-47, 2015 1585-8553/$ © AKADÉMIAI KIADÓ, BUDAPEST DOI: 10.1556/168.2015.16.1.5 Scale dependence of the beta diversity-scale relationship 1 1,4P 2 3 1 Y. ZhangP , K. MaP , M. AnandP , W. Ye and B. FuP 1 State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China 2 Global Ecological Change Laboratory, School of Environmental Sciences, University of Guelph, Guelph, Ontario, N1G 2W1, Canada 3 Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China 4 Corresponding author. Tel/Fax: 86-10-62849104, Email: [email protected] Keywords: Alpha diversity, Diversity partitioning, Gamma diversity, Power law, Scaling. Abstract: Alpha, beta, and gamma diversity are three fundamental biodiversity components in ecology, but most studies focus only on the scale issues of the alpha or gamma diversity component. The beta diversity component, which incorporates both alpha and gamma diversity components, is ideal for studying scale issues of diversity. We explore the scale dependency of beta diversity and scale relationship, both theoretically as well as by application to actual data sets. Our results showed that a power law exists for beta diversity-area (spatial grain or spatial extent) relationships, and that the parameters of the power law are dependent on the grain and extent for which the data are defined. Coarse grain size generates a steeper slope (scaling exponent z) with lower values of intercept (c), while a larger extent results in a reverse trend in both parameters. We also found that, for a given grain (with varying extent) or a given extent (with varying grain) the two parameters are themselves related by power laws. These findings are important because they are the first to simultaneously relate the various components of scale and di- versity in a unified manner. Abbreviations: DBH–Diameter at Breast Height, SAR–Species-area relationship. Introduction for nature reserves (He and Legendre 1996, Dengler 2009). Actually, the power law scaling relationship of SAR is also Ecologists have long distinguished three fundamental dependent on scale, as it has been shown that its parameters components of species diversity: alpha diversity (α), which (especially the scaling exponent z) vary with spatial scale measures the species diversity at the local scale, beta diver- (Crawley and Harral 2001, Drakare et al. 2006). sity (β), which measures the extent of local diversity change Spatial scale can be separated into several components, in a region, and gamma diversity (γ), which measures the total including grain, extent, and lag (Wiens 1989), but grain and diversity of a region (Whittaker 1972). All of these diversity extent are used primarily for SAR scale dependence studies. components are scale dependent: alpha diversity depends on Grain is the size of the individual units of observation—the the size of the local scale, gamma diversity depends on the quadrats of a field ecologist or the sampling units of a statisti- size of the regional scale, and beta diversity, which links al- cian—which correspond to the minimum scale sampled (of- pha and gamma diversity, depends on both local and regional ten the size of individual quadrats) in a study, and extent is the scales (Loreau 2000). However, considerable attention has overall area encompassed by a study (Wiens 1989). Palmer been given primarily to the scale dependency issues of alpha and White (1994) observed that spatial grain and extent in- (or gamma) diversity. fluence the shape of the SAR curve in a plant community. The species-area relationship (SAR) is well-known for Crawley and Harral (2001) considered the spatial extent ef- describing the scale dependency behavior of alpha or gamma fects on slope of the power SAR of plant communities, and diversity components when measured by species richness found that scaling exponent z has a unimodal pattern which (the species richness and diversity are use synonymously in shows the peak at intermediate spatial extent sizes with low this paper). The most common form of SAR is the power law values at small and large spatial extent size. Drakare et al. scaling relationship (S=cAz, where S is number of species or (2006) considered the effects of both spatial grain and spa- species richness; A is area measured; parameter z is the scal- tial extent on SARs and provided evidence of the fact that ing exponent with value less than 1, and parameter c is a con- coarse spatial grain follows a steeper slope (z), while spatial stant, Arrhenius 1921). This can help determine the minimal extent does not show clear pattern on scaling exponent z. The sampling area for biodiversity surveys, extrapolate species inconsistency between these two works on the spatial extent richness in response to habitat loss, and plan optimal sizes effect on the SAR is due partially to the fact that the results 40 Zhang et al. of Drakare et al. (2006) were based on 794 SARs from differ- while varying extent, 2) fixing extent while varying grain, and ent geographical location and taxonomic groups which also 3) co-varying extent and grain. The main purpose of our work impact on the slope of SAR. Drakare et al. (2006) found that is to explore whether scale dependence properties exist for steeper slope of SAR are generated at lower latitudes and by scaling relationship between beta diversity and scale (spatial larger organisms also. The scale dependency of SAR is still extent and spatial grain). Specifically, we want to analyze the an open issue, especially for the extent effects. To our knowl- spatial grain effects on the scaling relationship between beta edge, there have been surprisingly few attempts to quantify diversity and spatial extent and the spatial extent effects on both spatial extent and grain dependence of the power law the scaling relationship between beta diversity and spatial SAR in one dataset analytically and systematically. Spatial grain. Therefore, the first two ways suggested by Barton et grain and extent exist simultaneously for any dataset. In the al. (2013) for spatial scaling of beta diversity were used in SAR, the minimum area (A ) sampled for analysis corre- min our work. The scaling relationship between beta diversity and sponds to the spatial grain, and the maximum area (A ) sam- max scale is assumed in power law form. This assumption is based pled for analysis corresponds to the spatial extent which made on the fact that alpha diversity and gamma diversity could the spatial grain and spatial extent have been included in an be scaling up by power law. As previously stated that beta implicit way. Therefore, it is hard to explore the scale (spatial diversity is a function of alpha diversity and gamma diversity, grain and spatial extent) dependency of SAR analytically and when exploring beta diversity and extent scaling relationship, systematically in an explicit way. namely fixing alpha diversity but changing gamma diversity, Beta diversity, which is considered as important as alpha and given the power law scaling of gamma diversity, it is diversity in understanding ecosystem functions and man- reasonable to assume beta and extent may have power law agement and biodiversity conservation (Wilson and Shmida scaling relationship. Similarly, when exploring beta diversity 1984; Legendre et al. 2005), has the potential to include the and grain scaling relationship, namely fixing gamma diver- spatial grain and extent explicitly when dealing with scale de- sity but changing alpha diversity, and given the power law pendency issues. Although diverse definitions and measures for beta diversity have been reviewed, discussed, and recom- scaling of alpha diversity, it is reasonable to assume beta and mended extensively (see papers of Wilson and Schmida 1984, extent may have power law scaling relationship also. Based Vellend 2001, Koleff et al. 2003, Tuomisto 2010a, 2010b, on this power law scaling relationship assumption between Anderson et al. 2011), the beta diversity in our work refers beta diversity and scale, we explored the scale dependency to that which is related directly to alpha and gamma diversity of this relationship by the mathematical inference. The power components. It is well known that two different perspectives law beta diversity scaling assumption and mathematical pre- exist for relating beta diversity components directly with al- dictions on the scale dependency of this scaling relationship pha and gamma diversity components: the multiplicative per- were also verified through the analysis of forest community spective (betamul=gamma/alpha-1; Whittaker 1972) and the data from an elevational transect of warm, temperate de- additive perspective (betaadd=gamma-alpha; MacArthur et al. ciduous broadleaf oak (Quercus liaotungensis Koidz) forest 1966). There have been extensive discussions with respect in Beijing, North China and a 20-ha subtropical, evergreen to which perspective is better in partitioning an “independ- broadleaf forest plot in Guangdong province, South China. ent” beta diversity (Jost 2007, Ricotta and Marignani 2007, Ricotta 2008, de Bello et al. 2010, Chao et al. 2012, c.f. a Methods recent Forum in Ecology [2010] edited by Ellison, and papers in it). However, there is no perfect metric for measuring beta Mathematical inference diversity (Ricotta 2010) and both additive and multiplicative partitioning can be extremely useful
Load more

Recommended publications
  • Gamma Diversity: Derived from and a Determinant of Alpha Diversity and Beta Diversity
    Acta Zoologica Mexicana (n.s.) 90: 27-76 (2003) GAMMA DIVERSITY: DERIVED FROM AND A DETERMINANT OF ALPHA DIVERSITY AND BETA DIVERSITY. AN ANALYSIS OF THREE TROPICAL LANDSCAPES Lucrecia ARELLANO y Gonzalo HALFFTER Instituto de Ecología, A.C. Departamento de Ecología y Comportamiento Animal Apartado Postal 63, 91000 Xalapa, Veracruz, MÉXICO E-mail: [email protected] [email protected] RESUMEN Utilizando tres grupos taxonómicos en este trabajo examinamos como las diversidades alfa y beta influyen en la riqueza de especies de un paisaje (diversidad gamma), así como el fenómeno recíproco. Es decir, como la riqueza en especies de un paisaje (un fenómeno histórico-biogeográfico) contribuye a determinar los valores de la diversidad alfa por sitio, por comunidad, la riqueza acumulada de especies por comunidad y la intensidad del recambio entre comunidades. Los grupos utilizados son dos subfamilias de Scarabaeoidea: Scarabaeinae y Geotrupinae, y la familia Silphidae. En todos los análisis los tres grupos taxonómicos son manejados como un grupo indicador: los escarabajos copronecrófagos. De una manera lateral se incluye información sobre la subfamilia Aphodiinae (Scarabaeoidea), escarabajos coprófagos no incorporados al manejo del grupo indicador. Los paisajes estudiados son tres (tropical, de transición y de montaña), situados en un gradiente altitudinal en la parte central del estado de Veracruz. Partimos de las premisas siguientes. La diversidad alfa de un grupo indicador refleja el número de especies que utiliza un mismo ambiente o recurso en un lugar o comunidad. La diversidad beta espacial se relaciona con la respuesta de los organismos a la heterogeneidad del espacio. La diversidad gamma depende fundamentalmente de los procesos histórico-geográficos que actúan a nivel de mesoescala y está también condicionada por las diversidades alfa y beta.
    [Show full text]
  • Patterns of Alpha, Beta and Gamma Diversity of the Herpetofauna in Mexico’S Pacific Lowlands and Adjacent Interior Valleys A
    Animal Biodiversity and Conservation 30.2 (2007) 169 Patterns of alpha, beta and gamma diversity of the herpetofauna in Mexico’s Pacific lowlands and adjacent interior valleys A. García, H. Solano–Rodríguez & O. Flores–Villela García, A., Solano–Rodríguez, H. & Flores–Villela, O., 2007. Patterns of alpha, beta and gamma diversity of the herpetofauna in Mexico's Pacific lowlands and adjacent interior valleys. Animal Biodiversity and Conservation, 30.2: 169–177. Abstract Patterns of alpha, beta and gamma diversity of the herpetofauna in Mexico’s Pacific lowlands and adjacent interior valleys.— The latitudinal distribution patterns of alpha, beta and gamma diversity of reptiles, amphibians and herpetofauna were analyzed using individual binary models of potential distribution for 301 species predicted by ecological modelling for a grid of 9,932 quadrants of ~25 km2 each. We arranged quadrants in 312 latitudinal bands in which alpha, beta and gamma values were determined. Latitudinal trends of all scales of diversity were similar in all groups. Alpha and gamma responded inversely to latitude whereas beta showed a high latitudinal fluctuation due to the high number of endemic species. Alpha and gamma showed a strong correlation in all groups. Beta diversity is an important component of the herpetofauna distribution patterns as a continuous source of species diversity throughout the region. Key words: Latitudinal distribution pattern, Diversity scales, Herpetofauna, Western Mexico. Resumen Patrones de diversidad alfa, beta y gama de la herpetofauna de las tierras bajas y valles adyacentes del Pacífico de México.— Se analizaron los patrones de distribución latitudinales de la diversidad alfa, beta y gama de los reptiles, anfibios y herpetofauna utilizando modelos binarios individuales de distribución potencial de 301 especies predichas mediante un modelo ecológico para una cuadrícula de 9.932 cuadrantes de aproximadamente 25 km2 cada uno.
    [Show full text]
  • Diversity Partitioning in Phanerozoic Benthic Marine Communities
    Diversity partitioning in Phanerozoic benthic marine communities Richard Hofmanna,1, Melanie Tietjea, and Martin Aberhana aMuseum für Naturkunde Berlin, Leibniz Institute for Evolution and Biodiversity Science, 10115 Berlin, Germany Edited by Peter J. Wagner, University of Nebraska-Lincoln, Lincoln, NE, and accepted by Editorial Board Member Neil H. Shubin November 19, 2018 (received for review August 24, 2018) Biotic interactions such as competition, predation, and niche construc- formations harbor a pool of species that were principally able to tion are fundamental drivers of biodiversity at the local scale, yet their interact at the local and regional scale and thus can be regarded as long-term effect during earth history remains controversial. To test their the constituents of metacommunities in the geological record. role and explore potential limits to biodiversity, we determine within- Beta diversity among collections from the same formation is habitat (alpha), between-habitat (beta), and overall (gamma) diversity expected for two reasons, even though many benthic marine in- of benthic marine invertebrates for Phanerozoic geological formations. vertebrates have planktonic larval stages and thus high dispersal We show that an increase in gamma diversity is consistently generated capabilities. First, the distribution of species within a meta- by an increase in alpha diversity throughout the Phanerozoic. Beta community is predicted to be patchy (17). Even if the habitats diversity drives gamma diversity only at early stages of diversifica- represented by a formation were homogeneous, local differences tion but remains stationary once a certain gamma level is reached. This mode is prevalent during early- to mid-Paleozoic periods, in species distributions would result in compositional differences whereas coupling of beta and gamma diversity becomes increas- among sites.
    [Show full text]
  • BROAD-SCALE PATTERNS and DETERMINANTS of BETA-DIVERSITY Meghan Wilde Mcknight a Dissertation Submitted to the Faculty of The
    BROAD-SCALE PATTERNS AND DETERMINANTS OF BETA-DIVERSITY Meghan Wilde McKnight A dissertation submitted to the faculty of the University of North Carolina at Chapel Hill in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Curriculum in Ecology. Chapel Hill 2007 Approved by: Advisor: Peter S. White Reader: John Bruno Reader: Aaron Moody Reader: Robert K. Peet Reader: Dean L. Urban © 2007 Meghan Wilde McKnight ALL RIGHTS RESERVED ii ABSTRACT MEGHAN WILDE MCKNIGHT: Broad-Scale Patterns and Determinants of Beta-Diversity (Under the direction of Peter S. White) Ecologists recognize two components of biodiversity: inventory diversity, the species composition of a single place, and differentiation diversity, more commonly called beta-diversity, which is derived by several different methods from the change in species composition between places. Beta-diversity is determined through a complex array of processes relating to the interaction of species traits and characteristics of the physical landscape over time. Geographic variation in beta- diversity reflects past and present differences in environment, ecological interactions, and biogeographic history, including barriers to dispersal. As beta-diversity quantifies the turnover in species across space, it has important applications to the scaling of diversity, the delineation of biotic regions and conservation planning. Despite the importance of beta-diversity, relatively little is known about diversity’s “other component”, particularly at broad scales. In this dissertation, I trace the conceptual evolution of beta-diversity in order to reconcile the different views surrounding it, and examine empirical patterns of terrestrial vertebrate beta-diversity at broad spatial scales in order to gain insight into this important diversity component.
    [Show full text]
  • Partitioning Diversity1
    FORUM Partitioning diversity1 Contemporary ecologists work with three measures of diversity: alpha, beta, and gamma diversity. Alpha diversity is local diversity, and it is measured within a place, such as a single plot, an individual forest stand, or a single stream. Gamma diversity is regional diversity, and it is the total diversity measured for a group of places—all plots in the study, all streams in a watershed, all Costa Rican dry forest stands. Beta diversity links alpha and gamma, or local and regional, diversities and is defined as ‘‘the extent of differentiation of communities along habitat gradients’’ (Whittaker, R. H. 1972. ‘‘Evolution and measurement of species diversity.’’ Taxon 21:213–251; the quotation is from p. 214). Alpha and gamma diversity can be measured directly, either as numbers of species (species richness) or as numbers of species weighted by their relative abundance in the sample. There are many versions of these latter species diversity measures; familiar ones include the Shannon-Weiner and Simpson’s index, among others. Beta diversity, on the other hand, is a derived quantity, but how to best derive this quantity from measurements of alpha and gamma diversities, and how to interpret beta, has been a vexing and at times contentious problem for ecologists since Robert H. Whittaker first presented the concept in 1960 (‘‘Vegetation of the Siskiyou Mountains, Oregon and California.’’ Ecological Monographs 30:279–338; see especially pp. 319–323). Whittaker himself asserted that gamma equals the product of alpha and beta (and hence beta can be calculated by dividing gamma by alpha), but Russell Lande asserted that an additive ‘‘partition’’ of diversity (alpha þ beta ¼ gamma) provides a more natural measure of beta diversity (Lande, R.
    [Show full text]
  • A Proposed Revision of Diversity Measures
    Diversity 2013, 5, 613-626; doi:10.3390/d5030613 OPEN ACCESS diversity ISSN 1424-2818 www.mdpi.com/journal/diversity Article A Proposed Revision of Diversity Measures Vic Semeniuk 1 and Ian David Cresswell 2,* 1 V & C Semeniuk Research Group, 21 Glenmere Rd., Warwick, WA 6024, Australia; E-Mail: [email protected] 2 CSIRO Wealth from Oceans Flagship, GPO Box 1538, Hobart, Tasmania 7001, Australia * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel.: +61-428-473-705. Received: 3 July 2013; in revised form: 13 July 2013 / Accepted: 22 July 2013 / Published: 9 August 2013 Abstract: The current measures of diversity for vegetation, namely alpha, beta, and gamma diversity are not logically consistent, which reduces their effectiveness as a framework for comparative vegetation analysis. The current terms mix concepts: specifically, while alpha diversity measures floristic diversity at a site, and gamma diversity measures floristic diversity regionally, beta diversity is a measure of diversity between two sites and measures a different phenomenon. We seek to rationalise measures of diversity providing a scalar set of measures. Our approach recognises vegetation diversity extends beyond species diversity and should include the various ways plants express themselves phenotypically. We propose four types of diversity, with a new set of prefixes: Type 1 diversity = the largest scale−the regional species pool; Type 2 diversity = the large habitat scale−where species in a habitat have been selected from the regional species pool; Type 3 diversity = intra-habitat expression of floristics, structure, and physiognomy; and Type 4 diversity = the finest scale of expression of vegetation diversity reflecting site selection of floristics, physiography, and phenotypic expression and reproductive strategy.
    [Show full text]
  • A Consistent Terminology for Quantifying Species Diversity
    Oecologia DOI 10.1007/s00442-008-1190-z CONCEPTS, REVIEWS AND SYNTHESES Inventory, differentiation, and proportional diversity: a consistent terminology for quantifying species diversity Gerald Jurasinski Æ Vroni Retzer Æ Carl Beierkuhnlein Received: 18 December 2007 / Accepted: 13 August 2008 Ó Springer-Verlag 2008 Abstract Almost half a century after Whittaker (Ecol characteristics. A literature review reveals that the multi- Monogr 30:279–338, 1960) proposed his influential tude of measures used to assess beta diversity can be sorted diversity concept, it is time for a critical reappraisal. into two conceptually different groups. The first group Although the terms alpha, beta and gamma diversity directly takes species distinction into account and com- introduced by Whittaker have become general textbook pares the similarity of sites (similarity indices, slope of the knowledge, the concept suffers from several drawbacks. distance decay relationship, length of the ordination axis, First, alpha and gamma diversity share the same charac- and sum of squares of a species matrix). The second group teristics and are differentiated only by the scale at which relates species richness (or other summary diversity mea- they are applied. However, as scale is relative––depending sures) of two (or more) different scales to each other on the organism(s) or ecosystems investigated––this is not (additive and multiplicative partitioning). Due to that a meaningful ecological criterion. Alpha and gamma important distinction, we suggest that beta diversity should diversity can instead be grouped together under the term be split into two levels, ‘‘differentiation diversity’’ (first ‘‘inventory diversity.’’ Out of the three levels proposed by group) and ‘‘proportional diversity’’ (second group).
    [Show full text]
  • An Overview of Bioinformatics Tools for DNA Meta-Barcoding Analysis of Microbial Communities of Bioaerosols: Digest for Microbiologists
    life Review An Overview of Bioinformatics Tools for DNA Meta-Barcoding Analysis of Microbial Communities of Bioaerosols: Digest for Microbiologists Hamza Mbareche 1,2,* , Nathan Dumont-Leblond 3,4, Guillaume J. Bilodeau 5 and Caroline Duchaine 3,4,* 1 Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada 2 Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A1, Canada 3 Centre de Recherche de l’Institut Universitaire de Cardiologie et de Pneumologie de Québec, Quebec City, QC G1V 4G5, Canada; [email protected] 4 Département de Biochimie, de Microbiologie et de Bio-informatique, Faculté des Sciences et de Génie, Université Laval, Quebec City, QC G1V 0A6, Canada 5 Pathogen Identification Research Lab, Canadian Food Inspection Agency (CFIA), Ottawa, ON K2J 1G3, Canada; [email protected] * Correspondence: [email protected] (H.M.); [email protected] (C.D.); Tel.: +1-418-656-8711 (ext. 5837) (C.D.); Fax: +1-418-656-4509 (C.D.) Received: 21 July 2020; Accepted: 7 September 2020; Published: 8 September 2020 Abstract: High-throughput DNA sequencing (HTS) has changed our understanding of the microbial composition present in a wide range of environments. Applying HTS methods to air samples from different environments allows the identification and quantification (relative abundance) of the microorganisms present and gives a better understanding of human exposure to indoor and outdoor bioaerosols. To make full use of the avalanche of information made available by these sequences, repeated measurements must be taken, community composition described, error estimates made, correlations of microbiota with covariates (variables) must be examined, and increasingly sophisticated statistical tests must be conducted, all by using bioinformatics tools.
    [Show full text]
  • Straightening up a Concept Gone Awry. Part 1. Defining Beta Diversity As a Function of Alpha An
    Ecography 33: 2Á22, 2010 doi: 10.1111/j.1600-0587.2009.05880.x # 2010 The Author. Journal compilation # 2010 Ecography Subject Editor: Robert K. Colwell. Accepted 18 November 2009 A diversity of beta diversities: straightening up a concept gone awry. Part 1. Defining beta diversity as a function of alpha and gamma diversity Hanna Tuomisto H. Tuomisto ([email protected]), Dept of Biology, FI-20014 Univ. of Turku, Finland. The term beta diversity has been used to refer to a wide variety of phenomena. Although all of these encompass some kind of compositional heterogeneity between places, many are not related to each other in any predictable way. The present two-part review aims to put the different phenomena that have been called beta diversity into a common conceptual framework, and to explain what each of them measures. In this first part, the focus is on defining a beta component of diversity. This involves deciding what diversity is and how the observed total or gamma diversity (g) is partitioned into alpha (a) and beta (b) components. Several different definitions of ‘‘beta diversity’’ that result from these decisions have been used in the ecological literature. True beta diversity is obtained when the total effective number of species in a dataset (true gamma diversity g) is multiplicatively partitioned into the effective number of species per compositionally distinct virtual sampling unit (true alpha diversity ad) and the effective number of such compositional units (bMd g/ad). All true diversities quantify the effective number of types of entities. Because the other variants of ‘‘beta diversity’’ that have been used by ecologists quantify other phenomena, an alternative nomenclature is proposed here for the seven most popular beta components: regional-to-local diversity ratio, two-way diversity ratio, absolute effective species turnover (regional diversity excess), Whittaker’s effective species turnover, proportional effective species turnover, regional entropy excess and regional variance excess.
    [Show full text]
  • Community Characteristics, Types of Biodiversity, Diversity Index, Abundance, Species Richness, Vertical and Horizontal Stratification: Part II
    Paper No. : 12 Principles of Ecology Module : 18 Community: Community characteristics, types of biodiversity, diversity index, abundance, species richness, vertical and horizontal stratification: Part II Development Team Principal Investigator: Prof. Neeta Sehgal Head, Department of Zoology, University of Delhi Co-Principal Investigator: Prof. D.K. Singh Department of Zoology, University of Delhi Paper Coordinator: Prof. D.K. Singh Department of Zoology, University of Delhi Content Writer: Dr. Haren Ram Chiary and Dr. Kapinder Kirori Mal College, University of Delhi Content Reviewer: Prof. K.S. Rao Department of Botany, University of Delhi 1 Principles of Ecology ZOOLOGY Community: Community characteristics, types of biodiversity, diversity index, abundance, species richness, vertical and horizontal stratification: Part II Description of Module Subject Name ZOOLOGY Paper Name Zool 12, Principles of Ecology Module Name/Title Community Module Id M18, Community characteristics, types of biodiversity, diversity index, abundance, species richness, vertical and horizontal stratification: Part-II Keywords Biodiversity, Species diversity, genetic diversity, community/Ecosystem diversity, alpha-, beta- and gamma diversity, biogeography Contents 1. Learning Objectives 2. Introduction to Biodiversity 3. Types of Biodiversity a. Species Diversity b. Genetic Diversity c. Community or Ecosystem Diversity i. Alpha Diversity ii. Beta Diversity iii. Gamma Diversity 4. Evolution of Biodiversity 5. Factors that Promotes High Diversity 6. Measurement of
    [Show full text]
  • Biodiversity in Music Scores
    challenges Article Biodiversity in Music Scores David G. Angeler 1,2 1 Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Box 7050, 750 07 Uppsala, Sweden; [email protected] 2 School of Natural Resources, University of Nebraska–Lincoln, Lincoln, NE 68583-0961, USA Received: 15 April 2020; Accepted: 11 May 2020; Published: 14 May 2020 Abstract: Nature has inspired music since the dawn of humankind and has contributed to the creation and development of music as an art form. However, attempts to use the science of nature (i.e., quantitative ecology) to inform music as a broader art-science system is comparatively underdeveloped. In this paper an approach from biodiversity assessments is borrowed to quantify structural diversity in music scores. The approach is analogous in its nature and considers notations with distinct pitches and duration as equivalents of species in ecosystems, measures within a score as equivalents of ecosystems, and the sum of measures (i.e., the entire score) as a landscape in which ecosystems are embedded. Structural diversity can be calculated at the level of measures (“alpha diversity”) and the entire score (“gamma diversity”). An additional metric can be derived that quantifies the structural differentiation between measures in a score (“beta diversity”). The approach is demonstrated using music scores that vary in complexity. The method seems particularly suitable for hypothesis testing to objectively identify many of the intricate phenomena in music. For instance, questions related to the variability within and between musical genres or among individual composers can be addressed. Another potential application is an assessment of ontogenetic structural variability in the works of composers during their lifetime.
    [Show full text]
  • On the Efficiency of Some Alpha Diversity Indices: a Simulation Study Using Bootstrap Resampling
    Volume 5 (1): 32-39 (2021) (http://www.wildlife-biodiversity.com/) Research Article On the Efficiency of Some Alpha Diversity Indices: A Simulation Study Using Bootstrap Resampling Jan Nino Gabayran Tinio*, Carl Jericho Sebual Caraga State University, Department of Mathematics, Butuan City, Philippines *Email: [email protected] Received: May 15 2020 / Revised: July 02 2020 / Accepted: July 02 2020 / Published online: August 31, 2020. Ministry of Sciences, Research, and Technology, Arak University, Iran. How to cite: Tinio J.N.G., Sebual C.J. (2021). On the Efficiency of Some Alpha Diversity Indices: A Simulation Study Using Bootstrap Resampling, 5(1), 32-39. https://doi.org/10.22120/jwb.2020.127654.1142 Abstract It is essential to measure biodiversity to determine the stability of a community of species. A good measure gives precise, reliable, and efficient information about the community structure. This study was conducted to evaluate the statistical properties and test some alpha diversity indices' efficiency through a bootstrap resampling. The available birds' data were being applied in some alpha diversity indices. Moreover, the Shapiro-Wilk test is being used to test the normality of the index. All indices analyzed have p-values higher than the alpha level of significance (α=0.05), indicating that the index's bootstrap sampling distribution is normally distributed. Mostly, all indices are consistently efficient at large sample sizes. The Menhinick richness index is more efficient in measuring birds' species richness since it has the smallest means squared error (MSE) values. Among the diversity indices studied in this paper, Simpson's diversity index generated smaller mean squared error (MSE) values; thus, it is a more efficient diversity index in measuring birds' diversity.
    [Show full text]