1. Composition and ecological drivers of the kwongan scrub and woodlands in the northern Swan Coastal Plain, Western Australia
- Author
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Erik J. Veneklaas, Mark P. Dobrowolski, Sarah J. Broomfield, Paul D. Macintyre, Michael Renton, Ladislav Mucina, and James L. Tsakalos
- Subjects
0106 biological sciences ,geography ,geography.geographical_feature_category ,Ecology ,biology ,Coastal plain ,010604 marine biology & hydrobiology ,Plant community ,Woodland ,Vegetation ,15. Life on land ,biology.organism_classification ,010603 evolutionary biology ,01 natural sciences ,Shrubland ,Banksia ,Litter ,Ordination ,14. Life underwater ,Ecology, Evolution, Behavior and Systematics - Abstract
The nature of community patterns and environmental drivers in kwongan mediterranean‐type shrubland on nutrient‐poor soils occurring in Western Australia remain poorly examined. We aimed to determine whether (i) classification of the kwongan vegetation of the northern Swan Coastal Plain would be ecologically informative and (ii) which environmental drivers underpin the plant community patterns. The study area was positioned on the northern Swan Coastal Plain, locality of Cooljarloo (30°39′ S, 115°22′ E), situated 170 km north of Perth, Western Australia. Compositional (518 species × 337 releves) and environmental data set (29 variables × 87 releves) describing time since last fire, soil chemical and physical properties, and terrain characteristics were analysed using classification and ordination techniques. OptimClass assisted in the selection of a robust data transformation, resemblance function and clustering algorithm to identify the vegetation patterns. Major ecological drivers of the vegetation patterns were detected using distance‐based redundancy analysis (db‐RDA). Classification revealed major groupings of Wet Heath and Banksia Woodland distinguishable by the high prevalence of myrtyoid and proteoid taxa, respectively. On floristic‐sociological grounds, we recognised four Wet Heath and two Banksia Woodland communities. The Wet Heath was constrained to areas of higher litter depth (db‐RDA axis 1: 9%). Soil chemical and physical properties explained the highest proportion (17%) of the compositional variance, while the terrain‐ and fire‐related variables explained 2% and
- Published
- 2019
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