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dc.contributor.authorSchut, Tom
dc.contributor.authorWardell-Johnson, Grant
dc.contributor.authorYates, C.
dc.contributor.authorKeppel, Gunnar
dc.contributor.authorBaran, I.
dc.contributor.authorFranklin, S.
dc.contributor.authorHopper, S.
dc.contributor.authorVan Niel, K.
dc.contributor.authorMucina, L.
dc.contributor.authorByrne, M.
dc.date.accessioned2017-01-30T14:44:58Z
dc.date.available2017-01-30T14:44:58Z
dc.date.created2014-05-14T20:00:35Z
dc.date.issued2014
dc.identifier.citationSchut, T. and Wardell-Johnson, G. and Yates, C. and Keppel, G. and Baran, I. and Franklin, S. and Hopper, S. et al. 2014. Rapid characterisation of vegetation structure to predict refugia and climate change impacts across a global biodiversity hotspot. PLoS ONE. 9 (1): pp. e82778-1 - e82778-15.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/40704
dc.identifier.doi10.1371/journal.pone.0082778
dc.description.abstract

Identification of refugia is an increasingly important adaptation strategy in conservation planning under rapid anthropogenic climate change. Granite outcrops (GOs) provide extraordinary diversity, including a wide range of taxa, vegetation types and habitats in the Southwest Australian Floristic Region (SWAFR). However, poor characterization of GOs limits the capacity of conservation planning for refugia under climate change. A novel means for the rapid identification of potential refugia is presented, based on the assessment of local-scale environment and vegetation structure in a wider region. This approach was tested on GOs across the SWAFR. Airborne discrete return Light Detection And Ranging (LiDAR) data and Red Green and Blue (RGB) imagery were acquired. Vertical vegetation profiles were used to derive 54 structural classes. Structural vegetation types were described in three areas for supervised classification of a further 13 GOs across the region.Habitat descriptions based on 494 vegetation plots on and around these GOs were used to quantify relationships between environmental variables, ground cover and canopy height. The vegetation surrounding GOs is strongly related to structural vegetation types (Kappa = 0.8) and to its spatial context. Water gaining sites around GOs are characterized by taller and denser vegetation in all areas. The strong relationship between rainfall, soil-depth, and vegetation structure (R2 of 0.8–0.9) allowed comparisons of vegetation structure between current and future climate. Significant shifts in vegetation structural types were predicted and mapped for future climates. Water gaining areas below granite outcrops were identified as important putative refugia. A reduction in rainfall may be offset by the occurrence of deeper soil elsewhere on the outcrop. However, climate change interactions with fire and water table declines may render our conclusions conservative. The LiDAR-based mapping approach presented enables the integration of site-based biotic assessment with structural vegetation types for the rapid delineation and prioritization of key refugia.

dc.publisherPublic Library of Science
dc.titleRapid characterisation of vegetation structure to predict refugia and climate change impacts across a global biodiversity hotspot
dc.typeJournal Article
dcterms.source.volume9
dcterms.source.number1
dcterms.source.startPagee82778
dcterms.source.endPagee82778
dcterms.source.issn19326203
dcterms.source.titlePLoS ONE
curtin.note

This article is published under the Open Access publishing model and distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0. Please refer to the licence to obtain terms for any further reuse or distribution of this work.

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curtin.accessStatusOpen access


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