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The colour of environmental fluctuations associated with terrestrial animal population dynamics

David Gilljam, Jonas Knape, Andreas Lindén, Marianne Mugabo, Steven M. Sait, Mike Fowler Orcid Logo

Global Ecology and Biogeography, Volume: 28, Issue: 2

Swansea University Authors: David Gilljam, Mike Fowler Orcid Logo

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DOI (Published version): 10.1111/geb.12824

Abstract

AIM:The temporal structure (colour) of environmental variation influences population fluctuations, extinction risk and community stability. However, it is unclear whether environmental covariates linked to population fluctuations are distinguishable from a purely random process (white noise). We aim...

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Published in: Global Ecology and Biogeography
ISSN: 1466822X
Published: 2018
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fullrecord <?xml version="1.0"?><rfc1807><datestamp>2020-07-08T15:13:20.5941395</datestamp><bib-version>v2</bib-version><id>41196</id><entry>2018-07-31</entry><title>The colour of environmental fluctuations associated with terrestrial animal population dynamics</title><swanseaauthors><author><sid>1111e464ce36ca7b0e690d7d354f49b4</sid><firstname>David</firstname><surname>Gilljam</surname><name>David Gilljam</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>a3a29027498d4b43a3f082a0a5ba16b4</sid><ORCID>0000-0003-1544-0407</ORCID><firstname>Mike</firstname><surname>Fowler</surname><name>Mike Fowler</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2018-07-31</date><deptcode>SBI</deptcode><abstract>AIM:The temporal structure (colour) of environmental variation influences population fluctuations, extinction risk and community stability. However, it is unclear whether environmental covariates linked to population fluctuations are distinguishable from a purely random process (white noise). We aim to estimate colour coefficients and relative support for three models commonly representing coloured stochastic processes, in environmental series linked to terrestrial animal population fluctuations. LOCATION:North-America and Eurasia.TIME PERIOD:1901-2002MAJOR TAXA STUDIED:Birds, insects and mammals.METHODS:We analysed multiple abiotic environmental covariates, comparing point estimates and confidence intervals of temporal structure in competing models fitted using white noise, autoregressive (AR[1]) and 1/f processes in the time-domain and frequency-domain (where time-series were analysed following decomposition into different sinusoidal frequencies and their relative powers). All animal time-series were sampled annually for &#x2264; 50 years, potentially inflating Type-II errors. We also considered 101-year series of matched environmental covariates, performing a statistical power analysis evaluating our ability to draw robust conclusions.RESULTS:Temperature-related variables were associated with the largest fraction of population fluctuations. 93% of shorter environmental series were indistinguishable from white noise, limited by time-series length and associated with wide confidence intervals. The longer environmental series analysed in the time-domain offered sufficiently high statistical power to correctly identify colour estimates &#x2265; |0.27|, indicating 20% of series were best described by a slightly reddened noise process.MAIN CONCLUSIONS:Focusing on the short time-scales typically available for ecologists, most environmental variables associated with terrestrial animal population fluctuations are best characterised by white noise processes, although Type-II errors are common. Correctly detecting intermediately coloured noise with power 0.8 requires at least 16 data points in the time or 47 points in the frequency-domain. Over longer time-scales, where Type-II errors are less likely, one-fifth of populations are associated with coloured (often reddened) variables.</abstract><type>Journal Article</type><journal>Global Ecology and Biogeography</journal><volume>28</volume><journalNumber>2</journalNumber><publisher/><issnPrint>1466822X</issnPrint><keywords>spectral colour, environmental forcing, environmental variation, fluctuations, population dynamics, climate, time-series, frequency-domain, time-domain</keywords><publishedDay>31</publishedDay><publishedMonth>12</publishedMonth><publishedYear>2018</publishedYear><publishedDate>2018-12-31</publishedDate><doi>10.1111/geb.12824</doi><url/><notes>Acknowledgements DG, MSF, MM and SMS were supported by the Natural Environment Research Council (NERC) grant NE/N002849/1 and NE/N00213X/1.Biosketch:DG is an ecologist with a background in computer engineering whose research focus lies on the effects of environmental variation and within and between species interactions on the dynamics, stability and functioning of ecological networks. MSF is interested in understanding how interactions among species and the environment shape the fluctuations we observe in population and community dynamics in ecosystems.</notes><college>COLLEGE NANME</college><department>Biosciences</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>SBI</DepartmentCode><institution>Swansea University</institution><degreesponsorsfunders>RCUK, NE/N002849/1</degreesponsorsfunders><apcterm/><lastEdited>2020-07-08T15:13:20.5941395</lastEdited><Created>2018-07-31T15:48:37.0905979</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Biosciences, Geography and Physics - Biosciences</level></path><authors><author><firstname>David</firstname><surname>Gilljam</surname><order>1</order></author><author><firstname>Jonas</firstname><surname>Knape</surname><order>2</order></author><author><firstname>Andreas</firstname><surname>Lind&#xE9;n</surname><order>3</order></author><author><firstname>Marianne</firstname><surname>Mugabo</surname><order>4</order></author><author><firstname>Steven M.</firstname><surname>Sait</surname><order>5</order></author><author><firstname>Mike</firstname><surname>Fowler</surname><orcid>0000-0003-1544-0407</orcid><order>6</order></author></authors><documents><document><filename>0041196-12112018112333.pdf</filename><originalFilename>41196.pdf</originalFilename><uploaded>2018-11-12T11:23:33.1830000</uploaded><type>Output</type><contentLength>985818</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><embargoDate>2018-11-11T00:00:00.0000000</embargoDate><documentNotes>Released under the terms of a Creative Commons Attribution License (CC-BY).</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language></document></documents><OutputDurs/></rfc1807>
spelling 2020-07-08T15:13:20.5941395 v2 41196 2018-07-31 The colour of environmental fluctuations associated with terrestrial animal population dynamics 1111e464ce36ca7b0e690d7d354f49b4 David Gilljam David Gilljam true false a3a29027498d4b43a3f082a0a5ba16b4 0000-0003-1544-0407 Mike Fowler Mike Fowler true false 2018-07-31 SBI AIM:The temporal structure (colour) of environmental variation influences population fluctuations, extinction risk and community stability. However, it is unclear whether environmental covariates linked to population fluctuations are distinguishable from a purely random process (white noise). We aim to estimate colour coefficients and relative support for three models commonly representing coloured stochastic processes, in environmental series linked to terrestrial animal population fluctuations. LOCATION:North-America and Eurasia.TIME PERIOD:1901-2002MAJOR TAXA STUDIED:Birds, insects and mammals.METHODS:We analysed multiple abiotic environmental covariates, comparing point estimates and confidence intervals of temporal structure in competing models fitted using white noise, autoregressive (AR[1]) and 1/f processes in the time-domain and frequency-domain (where time-series were analysed following decomposition into different sinusoidal frequencies and their relative powers). All animal time-series were sampled annually for ≤ 50 years, potentially inflating Type-II errors. We also considered 101-year series of matched environmental covariates, performing a statistical power analysis evaluating our ability to draw robust conclusions.RESULTS:Temperature-related variables were associated with the largest fraction of population fluctuations. 93% of shorter environmental series were indistinguishable from white noise, limited by time-series length and associated with wide confidence intervals. The longer environmental series analysed in the time-domain offered sufficiently high statistical power to correctly identify colour estimates ≥ |0.27|, indicating 20% of series were best described by a slightly reddened noise process.MAIN CONCLUSIONS:Focusing on the short time-scales typically available for ecologists, most environmental variables associated with terrestrial animal population fluctuations are best characterised by white noise processes, although Type-II errors are common. Correctly detecting intermediately coloured noise with power 0.8 requires at least 16 data points in the time or 47 points in the frequency-domain. Over longer time-scales, where Type-II errors are less likely, one-fifth of populations are associated with coloured (often reddened) variables. Journal Article Global Ecology and Biogeography 28 2 1466822X spectral colour, environmental forcing, environmental variation, fluctuations, population dynamics, climate, time-series, frequency-domain, time-domain 31 12 2018 2018-12-31 10.1111/geb.12824 Acknowledgements DG, MSF, MM and SMS were supported by the Natural Environment Research Council (NERC) grant NE/N002849/1 and NE/N00213X/1.Biosketch:DG is an ecologist with a background in computer engineering whose research focus lies on the effects of environmental variation and within and between species interactions on the dynamics, stability and functioning of ecological networks. MSF is interested in understanding how interactions among species and the environment shape the fluctuations we observe in population and community dynamics in ecosystems. COLLEGE NANME Biosciences COLLEGE CODE SBI Swansea University RCUK, NE/N002849/1 2020-07-08T15:13:20.5941395 2018-07-31T15:48:37.0905979 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Biosciences David Gilljam 1 Jonas Knape 2 Andreas Lindén 3 Marianne Mugabo 4 Steven M. Sait 5 Mike Fowler 0000-0003-1544-0407 6 0041196-12112018112333.pdf 41196.pdf 2018-11-12T11:23:33.1830000 Output 985818 application/pdf Version of Record true 2018-11-11T00:00:00.0000000 Released under the terms of a Creative Commons Attribution License (CC-BY). true eng
title The colour of environmental fluctuations associated with terrestrial animal population dynamics
spellingShingle The colour of environmental fluctuations associated with terrestrial animal population dynamics
David Gilljam
Mike Fowler
title_short The colour of environmental fluctuations associated with terrestrial animal population dynamics
title_full The colour of environmental fluctuations associated with terrestrial animal population dynamics
title_fullStr The colour of environmental fluctuations associated with terrestrial animal population dynamics
title_full_unstemmed The colour of environmental fluctuations associated with terrestrial animal population dynamics
title_sort The colour of environmental fluctuations associated with terrestrial animal population dynamics
author_id_str_mv 1111e464ce36ca7b0e690d7d354f49b4
a3a29027498d4b43a3f082a0a5ba16b4
author_id_fullname_str_mv 1111e464ce36ca7b0e690d7d354f49b4_***_David Gilljam
a3a29027498d4b43a3f082a0a5ba16b4_***_Mike Fowler
author David Gilljam
Mike Fowler
author2 David Gilljam
Jonas Knape
Andreas Lindén
Marianne Mugabo
Steven M. Sait
Mike Fowler
format Journal article
container_title Global Ecology and Biogeography
container_volume 28
container_issue 2
publishDate 2018
institution Swansea University
issn 1466822X
doi_str_mv 10.1111/geb.12824
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Biosciences{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Biosciences
document_store_str 1
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description AIM:The temporal structure (colour) of environmental variation influences population fluctuations, extinction risk and community stability. However, it is unclear whether environmental covariates linked to population fluctuations are distinguishable from a purely random process (white noise). We aim to estimate colour coefficients and relative support for three models commonly representing coloured stochastic processes, in environmental series linked to terrestrial animal population fluctuations. LOCATION:North-America and Eurasia.TIME PERIOD:1901-2002MAJOR TAXA STUDIED:Birds, insects and mammals.METHODS:We analysed multiple abiotic environmental covariates, comparing point estimates and confidence intervals of temporal structure in competing models fitted using white noise, autoregressive (AR[1]) and 1/f processes in the time-domain and frequency-domain (where time-series were analysed following decomposition into different sinusoidal frequencies and their relative powers). All animal time-series were sampled annually for ≤ 50 years, potentially inflating Type-II errors. We also considered 101-year series of matched environmental covariates, performing a statistical power analysis evaluating our ability to draw robust conclusions.RESULTS:Temperature-related variables were associated with the largest fraction of population fluctuations. 93% of shorter environmental series were indistinguishable from white noise, limited by time-series length and associated with wide confidence intervals. The longer environmental series analysed in the time-domain offered sufficiently high statistical power to correctly identify colour estimates ≥ |0.27|, indicating 20% of series were best described by a slightly reddened noise process.MAIN CONCLUSIONS:Focusing on the short time-scales typically available for ecologists, most environmental variables associated with terrestrial animal population fluctuations are best characterised by white noise processes, although Type-II errors are common. Correctly detecting intermediately coloured noise with power 0.8 requires at least 16 data points in the time or 47 points in the frequency-domain. Over longer time-scales, where Type-II errors are less likely, one-fifth of populations are associated with coloured (often reddened) variables.
published_date 2018-12-31T03:52:31Z
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score 11.037581

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