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Using ecological niche theory to avoid uninformative biodiversity surrogates

Barton, Philip; Westgate, Martin; Foster, Claire; Cuddington, Kim; Hastings, Alan; O'Loughlin, Luke; Sato, Chloe; Willig, Michael R; Lindenmayer, David B

Description

Surrogates and indicators of biodiversity are used to infer the state and dynamics of species populations and ecosystems, as well as to inform conservation and management actions. Despite their widespread use, few studies have examined how ecological theory can guide the selection or surrogates and indicators, and thus reduce the likelihood of failure or cost of validation. We argue that ecological niche theory and knowledge of the extent to which particular limiting factors (e.g. physiological...[Show more]

dc.contributor.authorBarton, Philip
dc.contributor.authorWestgate, Martin
dc.contributor.authorFoster, Claire
dc.contributor.authorCuddington, Kim
dc.contributor.authorHastings, Alan
dc.contributor.authorO'Loughlin, Luke
dc.contributor.authorSato, Chloe
dc.contributor.authorWillig, Michael R
dc.contributor.authorLindenmayer, David B
dc.date.accessioned2020-05-25T03:16:23Z
dc.identifier.issn1470-160X
dc.identifier.urihttp://hdl.handle.net/1885/204585
dc.description.abstractSurrogates and indicators of biodiversity are used to infer the state and dynamics of species populations and ecosystems, as well as to inform conservation and management actions. Despite their widespread use, few studies have examined how ecological theory can guide the selection or surrogates and indicators, and thus reduce the likelihood of failure or cost of validation. We argue that ecological niche theory and knowledge of the extent to which particular limiting factors (e.g. physiological tolerances, limits to growth rates, or competitive exclusion) affect species distributions, abundance and coexistence could inform the choice of potential surrogates. Focusing on the environmental characteristics that define species niches makes it possible to identify situations where surrogates are likely to be ineffective, such as when there is no mechanistic basis for a candidate surrogate to be related to a biodiversity target. We describe two case studies where different candidate surrogate variables are shown to have contrasting potential as indicators of sustainable farming. Variables not mechanistically linked to the driver of change or responsive over appropriate timeframes or spatial scales are suggested a priori to be uninformative. The niche concept provides a framework for exploring ecological relationships that can inform the selection or exclusion of potential biodiversity surrogates. We think that this new approach to integrating ecological theory and application could lead to improved effectiveness of biodiversity monitoring and conservation.
dc.description.sponsorshipDBL was funded by an ARC Laureate Fellowship (LF120100108). MRW was supported in part by a grant from the US National Science Foundation (DEB-1546686).
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.publisherElsevier
dc.rights© 2019 Elsevier Ltd
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceEcological Indicators
dc.titleUsing ecological niche theory to avoid uninformative biodiversity surrogates
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume108
dc.date.issued2020
local.identifier.absfor050202 - Conservation and Biodiversity
local.identifier.ariespublicationu1055894xPUB193
local.publisher.urlhttps://www.elsevier.com/
local.type.statusAccepted Version
local.contributor.affiliationBarton, Philip, College of Science, ANU
local.contributor.affiliationWestgate, Martin, College of Science, ANU
local.contributor.affiliationFoster, Claire, College of Science, ANU
local.contributor.affiliationCuddington, Kim, University of Waterloo
local.contributor.affiliationHastings, Alan, University of California
local.contributor.affiliationO'Loughlin, Luke, College of Science, ANU
local.contributor.affiliationSato, Chloe, College of Science, ANU
local.contributor.affiliationWillig, Michael R, University of Connecticut
local.contributor.affiliationLindenmayer, David, College of Science, ANU
local.description.embargo2022-01-31
dc.relationhttp://purl.org/au-research/grants/arc/FL120100108
local.bibliographicCitation.startpage1
local.bibliographicCitation.lastpage7
local.identifier.doi10.1016/j.ecolind.2019.105692
local.identifier.absseo960599 - Ecosystem Assessment and Management not elsewhere classified
dc.date.updated2019-12-19T06:48:29Z
dcterms.accessRightsOpen Access
dc.provenancehttp://sherpa.ac.uk/romeo/issn/1470-160X/..."Author's post-print on open access repository after an embargo period of 24 months. Author's post-print must be released with a Creative Commons Attribution Non-Commercial No Derivatives License" from SHERPA/RoMEO site (as at 11/06/2020).
dc.rights.licenseCreative Commons Attribution Non-Commercial No Derivatives License
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