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.
ABSTRACT:Anthropogenic climate change is already impacting native vegetation world-wide. Thus accurate mapping of current vegetation condition is necessary for benchmarking and conservation planning. We examine the potential for the mapping of native vegetation of forested ecosystems in south-western Australia using LiDAR data. Airborne LiDAR (distance between data points 1.2 m) and RGB imagery was acquired with a discrete 4-return Leica ALS 50-II system in April 2011 and vertical canopy profiles determined in Boyagin Nature Reserve. Elevation, slope and geomorphological descriptions of the terrain in combination with vertical canopy profiles based on presence/absence of returns within voxels were derived from the LiDAR data and processed at a spatial resolution of 4.0 meters. Based on these profiles, crown height and depth, ground cover, mean intensity of crown returns, presence of understory and number of vegetation layers were determined for each grid cell. Unsupervised classification revealed distinctive canopy profiles. Vegetation is strongly linked to geomorphology in this old landscape. Thus Kwongan shrubland occurs on the plateaus, Allocasuarina heugeliana woodland on the fringes of rock outcrops, Eucalyptus astringens and E. accedens woodland on breakaways and E. wandoo and Corymbia calophylla woodland in more fertile valley systems. The vegetation types present within distinctive spatial clusters were determined in two field visits. Vegetation types were mapped with an object-based image analysis approach at geomorphological, vegetation and tree scales using the geomorphology of the terrain and structural, textural and reflective characteristics of the canopy. All vertical profiles identified were present on each geomorphological unit. Tree species with a distinctive vertical profile such as Eucalyptus astringens and Allocasuarina heugeliana were defined and distinguished in combination with object-based geomorphological and spatial characteristics. Vegetation types were mapped accurately with a kappa coefficient of 0.80. We conclude that vertical profiles and geomorphology of the terrain derived from commercially available discrete return LiDAR systems provides a valuable means to benchmark the mapping of native vegetation in the forested ecosystems of south-western Australia.
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