Linking species richness and size diversity in birds and fishes

Jian D.L. Yen, James R. Thomson, Jonathan M. Keith, David M. Paganin, Erica Fleishman, Andrew F. Bennett, Dale G. Nimmo, Joanne M. Bennett, David S. Dobkin, Ralph Mac Nally

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The 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.

Original languageEnglish
Pages (from-to)1979-1991
Number of pages13
JournalEcography
Volume41
Issue number12
DOIs
Publication statusPublished - 1 Dec 2018

Fingerprint

diversity index
species richness
bird
species diversity
birds
fish
functional diversity
data analysis
community ecology
ecology
distribution
prediction
methodology
method

Cite this

Yen, J. D. L., Thomson, J. R., Keith, J. M., Paganin, D. M., Fleishman, E., Bennett, A. F., ... Mac Nally, R. (2018). Linking species richness and size diversity in birds and fishes. Ecography, 41(12), 1979-1991. https://doi.org/10.1111/ecog.03582
Yen, Jian D.L. ; Thomson, James R. ; Keith, Jonathan M. ; Paganin, David M. ; Fleishman, Erica ; Bennett, Andrew F. ; Nimmo, Dale G. ; Bennett, Joanne M. ; Dobkin, David S. ; Mac Nally, Ralph. / Linking species richness and size diversity in birds and fishes. In: Ecography. 2018 ; Vol. 41, No. 12. pp. 1979-1991.
@article{72df03006ea843dca3ee5ddbb6f32f78,
title = "Linking species richness and size diversity in birds and fishes",
abstract = "The 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.",
keywords = "biological diversity, function regression, size spectrum",
author = "Yen, {Jian D.L.} and Thomson, {James R.} and Keith, {Jonathan M.} and Paganin, {David M.} and Erica Fleishman and Bennett, {Andrew F.} and Nimmo, {Dale G.} and Bennett, {Joanne M.} and Dobkin, {David S.} and {Mac Nally}, Ralph",
year = "2018",
month = "12",
day = "1",
doi = "10.1111/ecog.03582",
language = "English",
volume = "41",
pages = "1979--1991",
journal = "Ecography",
issn = "0906-7590",
publisher = "Wiley-Blackwell",
number = "12",

}

Yen, JDL, Thomson, JR, Keith, JM, Paganin, DM, Fleishman, E, Bennett, AF, Nimmo, DG, Bennett, JM, Dobkin, DS & Mac Nally, R 2018, 'Linking species richness and size diversity in birds and fishes', Ecography, vol. 41, no. 12, pp. 1979-1991. https://doi.org/10.1111/ecog.03582

Linking species richness and size diversity in birds and fishes. / Yen, Jian D.L.; Thomson, James R.; Keith, Jonathan M.; Paganin, David M.; Fleishman, Erica; Bennett, Andrew F.; Nimmo, Dale G.; Bennett, Joanne M.; Dobkin, David S.; Mac Nally, Ralph.

In: Ecography, Vol. 41, No. 12, 01.12.2018, p. 1979-1991.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Linking species richness and size diversity in birds and fishes

AU - Yen, Jian D.L.

AU - Thomson, James R.

AU - Keith, Jonathan M.

AU - Paganin, David M.

AU - Fleishman, Erica

AU - Bennett, Andrew F.

AU - Nimmo, Dale G.

AU - Bennett, Joanne M.

AU - Dobkin, David S.

AU - Mac Nally, Ralph

PY - 2018/12/1

Y1 - 2018/12/1

N2 - The 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.

AB - The 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.

KW - biological diversity

KW - function regression

KW - size spectrum

UR - http://www.scopus.com/inward/record.url?scp=85058982099&partnerID=8YFLogxK

U2 - 10.1111/ecog.03582

DO - 10.1111/ecog.03582

M3 - Article

VL - 41

SP - 1979

EP - 1991

JO - Ecography

JF - Ecography

SN - 0906-7590

IS - 12

ER -

Yen JDL, Thomson JR, Keith JM, Paganin DM, Fleishman E, Bennett AF et al. Linking species richness and size diversity in birds and fishes. Ecography. 2018 Dec 1;41(12):1979-1991. https://doi.org/10.1111/ecog.03582