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Article: Assessing the impacts of fragmentation on plant communities in New Zealand: Scaling from survey plots to landscapes

TitleAssessing the impacts of fragmentation on plant communities in New Zealand: Scaling from survey plots to landscapes
Authors
KeywordsBiodiversity indicators
Fragmentation
New Zealand
Plant communities
Similarity index
Spatial modelling
Issue Date2010
Citation
Global Ecology and Biogeography, 2010, v. 19, n. 5, p. 741-754 How to Cite?
AbstractAim: Few studies have attempted to assess the overall impact of fragmentation at the landscape scale. We quantify the impacts of fragmentation on plant diversity by assessing patterns of community composition in relation to a range of fragmentation measures. Location: The investigation was undertaken in two regions of New Zealand - a relatively unfragmented area of lowland rain forest in south Westland and a highly fragmented montane forest on the eastern slopes of the Southern Alps. Methods: We calculated an index of community similarity (Bray-Curtis) between forest plots we regarded as potentially affected by fragmentation and control forest plots located deep inside continuous forest areas. Using a multiple nonlinear regression technique that incorporates spatial autocorrelation effects, we analysed plant community composition in relation to measures of fragmentation at the patch and landscape levels. From the resulting regression equation, we predicted community composition for every forest pixel on land-cover maps of the study areas and used these maps to calculate a landscape-level estimate of compositional change, which we term'BioFrag' . BioFrag has a value of one if fragmentation has no detectable effect on communities within a landscape, and tends towards zero if fragmentation has a strong effect. Results: We detected a weak, but significant, impact of fragmentation metrics operating at both the patch and landscape levels. Observed values of BioFrag ranged from 0.68 to 0.90, suggesting that patterns of fragmentation have medium to weak impacts on forest plant communities in NewZealand. BioFrag values varied in meaningful ways among landscapes and between the ground-cover and tree and shrub communities. Main conclusions: BioFrag advances methods that describe spatial patterns of forest cover by incorporating the exact spatial patterns of observed species responses to fragmentation operating at multiple spatial scales. BioFrag can be applied to any landscape and ecological community across the globe and represents a significant step towards developing a biologically relevant, landscape-scale index of habitat fragmentation. © 2010 Blackwell Publishing Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/250955
ISSN
2023 Impact Factor: 6.3
2023 SCImago Journal Rankings: 2.744
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLafortezza, Raffaele-
dc.contributor.authorCoomes, David A.-
dc.contributor.authorKapos, Valerie-
dc.contributor.authorEwers, Robert M.-
dc.date.accessioned2018-02-01T01:54:10Z-
dc.date.available2018-02-01T01:54:10Z-
dc.date.issued2010-
dc.identifier.citationGlobal Ecology and Biogeography, 2010, v. 19, n. 5, p. 741-754-
dc.identifier.issn1466-822X-
dc.identifier.urihttp://hdl.handle.net/10722/250955-
dc.description.abstractAim: Few studies have attempted to assess the overall impact of fragmentation at the landscape scale. We quantify the impacts of fragmentation on plant diversity by assessing patterns of community composition in relation to a range of fragmentation measures. Location: The investigation was undertaken in two regions of New Zealand - a relatively unfragmented area of lowland rain forest in south Westland and a highly fragmented montane forest on the eastern slopes of the Southern Alps. Methods: We calculated an index of community similarity (Bray-Curtis) between forest plots we regarded as potentially affected by fragmentation and control forest plots located deep inside continuous forest areas. Using a multiple nonlinear regression technique that incorporates spatial autocorrelation effects, we analysed plant community composition in relation to measures of fragmentation at the patch and landscape levels. From the resulting regression equation, we predicted community composition for every forest pixel on land-cover maps of the study areas and used these maps to calculate a landscape-level estimate of compositional change, which we term'BioFrag' . BioFrag has a value of one if fragmentation has no detectable effect on communities within a landscape, and tends towards zero if fragmentation has a strong effect. Results: We detected a weak, but significant, impact of fragmentation metrics operating at both the patch and landscape levels. Observed values of BioFrag ranged from 0.68 to 0.90, suggesting that patterns of fragmentation have medium to weak impacts on forest plant communities in NewZealand. BioFrag values varied in meaningful ways among landscapes and between the ground-cover and tree and shrub communities. Main conclusions: BioFrag advances methods that describe spatial patterns of forest cover by incorporating the exact spatial patterns of observed species responses to fragmentation operating at multiple spatial scales. BioFrag can be applied to any landscape and ecological community across the globe and represents a significant step towards developing a biologically relevant, landscape-scale index of habitat fragmentation. © 2010 Blackwell Publishing Ltd.-
dc.languageeng-
dc.relation.ispartofGlobal Ecology and Biogeography-
dc.subjectBiodiversity indicators-
dc.subjectFragmentation-
dc.subjectNew Zealand-
dc.subjectPlant communities-
dc.subjectSimilarity index-
dc.subjectSpatial modelling-
dc.titleAssessing the impacts of fragmentation on plant communities in New Zealand: Scaling from survey plots to landscapes-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/j.1466-8238.2010.00542.x-
dc.identifier.scopuseid_2-s2.0-78149358029-
dc.identifier.volume19-
dc.identifier.issue5-
dc.identifier.spage741-
dc.identifier.epage754-
dc.identifier.eissn1466-8238-
dc.identifier.isiWOS:000280633800014-
dc.identifier.issnl1466-822X-

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