Linking species richness and size diversity in birds and fishes

dc.contributor.authorYen, Jian D.L.en
dc.contributor.authorThomson, James R.en
dc.contributor.authorKeith, Jonathan M.en
dc.contributor.authorPaganin, David M.en
dc.contributor.authorFleishman, Ericaen
dc.contributor.authorBennett, Andrew F.en
dc.contributor.authorNimmo, Dale G.en
dc.contributor.authorBennett, Joanne M.en
dc.contributor.authorDobkin, David S.en
dc.contributor.authorMac Nally, Ralphen
dc.date.accessioned2026-01-01T14:42:06Z
dc.date.available2026-01-01T14:42:06Z
dc.date.issued2018en
dc.description.abstractThe rapid development of mechanistic, trait-based models has resulted in increasingly reliable predictions of the functional diversity of individuals in populations and communities. However, a focus on individuals’ traits differs from the prevailing focus on species in much of community ecology. We sought to identify correlative links between species richness and size diversity, focusing on size diversity as one component of functional diversity. These links could be used to extend individual, size-based models to predict patterns of species richness. We used the distribution of the sizes of individuals in a community – the individual–size distribution (ISD) – as a measure of size diversity, and constructed Bayesian regression models with species richness as the response variable and ISDs as the predictor variables. We used two methods to include ISDs in our analyses. First, we summarized the ISD with five common diversity indices and used these indices as predictor variables in our analyses. Second, we used functional data analysis to include the entire ISD (a continuous function) as a predictor variable in our analyses. Analyses of diversity indices identified consistent, positive associations between species richness and size diversity. Analyses of entire ISDs revealed that these associations were driven by numbers of small- and medium-sized individuals. In general, a combination of diversity indices predicted species richness as well as or better than continuous ISDs. However, models with ISDs as predictor variables were less sensitive to technical details of model fitting (e.g. discretization method) than those based on diversity indices, and the use of ISDs avoids the arbitrary selection of one or several diversity indices. Our use of functional data analysis allows any trait distribution to be included as a variable in statistical analyses, and has the potential to reveal new diversity patterns in ecology.en
dc.description.sponsorshipAcknowledgements – The views expressed herein are those of the authors and are not necessarily those of the Australian Government or Australian Research Council. For contributions to surveys of birds in the box-ironbark region we thank G. Horrocks, G. Cheers, and J. Radford. H. Possingham and A. Magurran provided insightful feedback on a draft manuscript. Funding – This research was conducted by the Australian Research Council Centre of Excellence for Environmental Decisions (CE11001000104) and was funded by the Australian Government. Data on fishes were available due to the efforts of the many researchers involved in the NAWQA program (USGS). Australian bird-mass data were collated by C. Catterall, R. Loyn, and T. Sloane, with support from the Arthur Rylah Institute for Environmental Research. Funds for collection and archiving of data on birds in the Great Basin were provided by the Joint Fire Science Program via cooperative agreements with the Rocky Mountain Research Station (JFSP 00-2-15, 01B-3-3-01, 05-2-1-94, and 09-1-08-4), by the National Fish and Wildlife Foundation (2005-0294-000), and by the Strategic Environmental Research and Development Program of the Department of Defense (contract W912HQ-12-C-0033, project RC-2202). JDLY was funded by a Monash University Sir James McNeill Foundation Postgraduate Research Scholarship and Monash University Postgraduate Publications Award and received financial support from the Victorian Life Sciences Computation Initiative.en
dc.description.statusPeer-revieweden
dc.format.extent13en
dc.identifier.issn0906-7590en
dc.identifier.otherORCID:/0000-0002-7883-3577/work/163623798en
dc.identifier.scopus85058982099en
dc.identifier.urihttps://hdl.handle.net/1885/733801116
dc.language.isoenen
dc.rightsPublisher Copyright: © 2018 The Authorsen
dc.sourceEcographyen
dc.subjectbiological diversityen
dc.subjectfunction regressionen
dc.subjectsize spectrumen
dc.titleLinking species richness and size diversity in birds and fishesen
dc.typeJournal articleen
dspace.entity.typePublicationen
local.bibliographicCitation.lastpage1991en
local.bibliographicCitation.startpage1979en
local.contributor.affiliationYen, Jian D.L.; University of Melbourneen
local.contributor.affiliationThomson, James R.; State Government of Victoriaen
local.contributor.affiliationKeith, Jonathan M.; Monash Universityen
local.contributor.affiliationPaganin, David M.; Monash Universityen
local.contributor.affiliationFleishman, Erica; University of California at Davisen
local.contributor.affiliationBennett, Andrew F.; State Government of Victoriaen
local.contributor.affiliationNimmo, Dale G.; Charles Sturt Universityen
local.contributor.affiliationBennett, Joanne M.; German Centre for Integrative Biodiversity Research (iDiv) Halle–Jena–Leipzigen
local.contributor.affiliationDobkin, David S.; High Desert Ecological Research Inst.en
local.contributor.affiliationMac Nally, Ralph; La Trobe Universityen
local.identifier.citationvolume41en
local.identifier.doi10.1111/ecog.03582en
local.identifier.puredd083ad0-1783-43f7-aa0e-ccd2ddb4389ben
local.identifier.urlhttps://www.scopus.com/pages/publications/85058982099en
local.type.statusPublisheden

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