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Potential distribution of two Ambrosia species in China under projected climate change
Authors:Z Qin  A DiTommaso  R S Wu  H Y Huang
Institution:1. The Department of Ecology, College of Agriculture, South China Agricultural University, , Guangzhou, China;2. Department of Crop and Soil Sciences, Cornell University, , Ithaca, NY, USA;3. Department of Biology, Shaoguan University, , Shaoguan, China
Abstract:The invasion of Ambrosia artemisiifolia and Ambrosia trifida from their native range to occupy large areas in China has raised considerable concern. Using the maximum entropy (Maxent) method, we developed models for each Ambrosia species, based on occurrence records from both native ranges (North America) and their invaded ranges (e.g. northern and south‐western Europe) to predict the availability and distribution of suitable habitats for these two species in China. For each species, we also assessed potential shifts in habitat suitability for the year 2050, using three general circulation models (GCMs) and two emission scenarios. Elevation and average mean precipitation in October contributed most to model development for both species. Potential distribution projections under future climatic change scenarios suggested an averaged percentage of suitable area (2.21%) and habitat gain (1.49%) in A. artemisiifolia distribution, with further expansion to environmentally favourable locations in south‐east coastal regions, northern Taiwan and the Beijing–Tianjin–Tangshan area in northern China. Future predicted percentage of suitable area for A. trifida was 0.03% with a very limited suitable habitat gain of <1% although this species had the potential to continue to spread in northern China. Our findings suggest that management priorities should be focused on A. artemisiifolia, whilst effective control strategies for A. trifida may be optimised by concentrating efforts on those relatively fewer regions of China where the species is currently abundant.
Keywords:ragweed  climate change  distribution models  invasive plants  Maxent
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