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dc.contributor.authorBale, Shannon Lindsay
dc.date.accessioned2017-12-14T16:22:43Z
dc.date.available2017-12-14T16:22:43Z
dc.identifier.urihttp://hdl.handle.net/10222/73520
dc.descriptionIn the first research paper of this thesis, I investigated the unresolved issues of sample bias and choice of environmental covariate subset in Maxent, the most popular presence-only SDM algorithm, in order to improve the reliability of model predictions. I found that spatially filtering species occurrence data (a sample bias correction strategy) reduced model complexity when environmental covariates were selected using reverse stepwise elimination; however, changing the bias correction strategy had a limited effect on model results overall. Conversely, using alternative subsets of environmental covariates led to non-trivial differences in model outputs. In the second research paper of this thesis, I developed landscape-scale Maxent models for 3 at-risk migratory forest landbirds in the province of Nova Scotia, Canada: the Rusty Blackbird (Euphagus carolinus), the Olive-sided Flycatcher (Contopus cooperi), and the Canada Warbler (Cardellina canadensis). One objective of this research was to investigate whether topographic covariates, which may be considered more resilient to the effects of climate change, can be used alongside forest covariates to predict bird occurrence. Topographic covariates were found to have moderate to strong predictive power in all bird models. As topography (1) should be relatively unaffected by a changing climate and (2) helps regulate the structure and composition of forest habitat, I posited that topographic covariates may be useful in identifing areas that are more likely to support the persistence of species over the long term as climate changes. In the third research paper of this thesis, I proposed a novel approach to single-species conservation planning that (1) targets individual species which may be missed by more general planning strategies, while also (2) contributing towards the maintenance of overall biodiversity in an era of climate change. Specifically, the proposed approach combines elements of predictive modeling and an existing resilience-based conservation planning strategy known as “conserving nature’s stage” (CNS) to delineate climate-resilient refugial habitat and reduce uncertainty in conservation plans.en_US
dc.description.abstractHabitat loss and fragmentation have precipitated a mass extinction. Therefore, maintaining a functionally connected habitat network is an effective response to biodiversity loss. However, climate change poses challenges for conservation planning, as areas that are protected for unique biodiversity values may not retain those values in the face of shifting temperature and precipitation regimes. Furthermore, range shift predictions can be notoriously uncertain, and planning efforts that seek to achieve broad species representation are unlikely to confer sufficient protection to individual species. In this thesis, I addressed 2 key limitations that challenge single-species conservation planning: variable reliability of presence-only species distribution models (SDMs) and uncertainty of conservation plans developed for an era of climate change. Specifically, I performed 3 studies that investigated (1) parameterization choices in Maximum Entropy (Maxent) presence-only modeling, (2) the use of resilient topographic features as covariates in models, and (3) strategies to reduce uncertainty in conservation planning.en_US
dc.language.isoenen_US
dc.subjectspecies distribution modelingen_US
dc.subjectecological resilienceen_US
dc.subjectresilient habitaten_US
dc.subjectclimate changeen_US
dc.subjectclimate refugiaen_US
dc.subjecttopographyen_US
dc.subjectRusty blackbirden_US
dc.subjectOlive-sided Flycatcheren_US
dc.subjectCanada warbleren_US
dc.subjectsample biasen_US
dc.subjectcovariate selectionen_US
dc.subjectreverse stepwise eliminationen_US
dc.titleBUILDING AN ARC IN THE ANTHROPOCENE: APPLYING PRINCIPLES OF ENVIRONMENTAL RESILIENCE TO IMPROVE SINGLE-SPECIES CONSERVATION PLANNING IN AN ERA OF CLIMATE CHANGEen_US
dc.date.defence2017-08-03
dc.contributor.departmentSchool for Resource & Environmental Studiesen_US
dc.contributor.degreeMaster of Environmental Studiesen_US
dc.contributor.external-examinern/aen_US
dc.contributor.graduate-coordinatorKate Sherrenen_US
dc.contributor.thesis-readerDr. Peter Bushen_US
dc.contributor.thesis-readerDr. Peter Duinkeren_US
dc.contributor.thesis-supervisorDr. Karen Beazleyen_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.manuscriptsYesen_US
dc.contributor.copyright-releaseYesen_US
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