Data from: Mapping and exploring variation in post-fire vegetation recovery following mixed severity wildfire using airborne LiDAR
Gordon, Christopher E., University of Wollongong
Price, Owen F., University of Wollongong
Tasker, Elizabeth M., Science Division; New South Wales Office of Environment and Heritage; 43 Bridge Street Hurstville 2220 New South Wales Australia
Published Mar 21, 2017 on Dryad.
Cite this dataset
Gordon, Christopher E.; Price, Owen F.; Tasker, Elizabeth M. (2017). Data from: Mapping and exploring variation in post-fire vegetation recovery following mixed severity wildfire using airborne LiDAR [Dataset]. Dryad. https://doi.org/10.5061/dryad.jq32s
There is a public perception that large high severity wildfires decrease biodiversity and increase fire hazard by homogenising vegetation composition and increasing the cover of mid-story vegetation. But a growing literature suggests that vegetation responses are nuanced. LiDAR technology provides a promising remote sensing tool to test hypotheses about post-fire vegetation regrowth because vegetation cover can be quantified within different height strata at fine-scales over large areas. We assess the usefulness of airborne LiDAR data for measuring post-fire mid-story vegetation regrowth over a range of spatial resolutions (10x10m, 30x30m, 50x50m, 100x100m cell size) and investigate the effect of fire severity on regrowth amount and spatial pattern following a mixed severity wildfire in Warrumbungle National Park, Australia. We predicted that recovery would be more vigorous in areas of high fire severity, because park managers observed dense post-fire regrowth in these areas. Moderate to strong positive associations were observed between LiDAR and field surveys of mid-story vegetation cover between 0.5–3m. Thus our LiDAR survey was an apt representation of on-ground vegetation cover. LiDAR-derived mid-story vegetation cover was 22–40% higher in areas of low and moderate than high fire severity. Linear mixed-effects models showed that fire severity was among the strongest biophysical predictors of mid-story vegetation cover irrespective of spatial resolution. However much of the variance associated with these models was unexplained, presumably because soil seedbanks varied at finer-scales than our LiDAR maps. Dense patches of mid-story vegetation regrowth were small (median size 0.01ha) and evenly distributed between areas of low, moderate and high fire severity, demonstrating that high severity fires do not homogenise vegetation cover. Our results are relevant for ecosystem conservation and fire management because they: indicate that native vegetation are responsive and resilient to high severity fire, and show the usefulness of remote sensing tools such as LiDAR to monitor post-fire vegetation recovery over large area in situ.
Data presented in the manuscript "Mapping and exploring variation in post-fire vegetation recovery following mixed severity wildfire using airborne LiDAR"