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Acta Prataculturae Sinica ›› 2020, Vol. 29 ›› Issue (12): 73-85.DOI: 10.11686/cyxb2020040

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Potential geographical distribution of Ambrosia trifida in Xinjiang under climate change

Qian-qian MA1(), Tong LIU1(), He-gan DONG1,2, Han-yue WANG1, Wen-xuan ZHAO1, Rui-li WANG1, Yan LIU1, Le CHEN1   

  1. 1.College of Life Sciences,Shihezi University,Shihezi 832003,China
    2.Rural Energy Environment Station,Yili 835000,China
  • Received:2020-02-05 Revised:2020-03-30 Online:2020-12-28 Published:2020-12-28
  • Contact: Tong LIU

Abstract:

Determining the potential distribution of invasive species and their responses to climate change on a regional scale is of great significance for the early warning, specific prevention, and control of invasive species. Ambrosia trifida (giant ragweed) is a globally recognized invasive weed. This plant is now widely distributed in the Yili Valley in Xinjiang which locaded in Central Asian hub of the“Belt and Road”. To predict the potential spread of A. trifida in Xinjiang, a Maxent niche model was used to project its potential distribution under the current climate and the climate in the 2050s and 2070s under two climate change scenarios (RCP4.5 and RCP8.5). The results indicated that the suitable habitat area of giant ragweed in Xinjiang could extend to 24.01×104 km2, accounting for 14% of the total area of Xinjiang under the current climate conditions. Under the RCP4.5 scenario, its suitable habitat area was predicted to increase to 37.36×104 km2 and 39.23×104 km2 by the 2050s and 2070s, respectively. Under the RCP8.5 scenario, its suitable habitat area was predicted to increase to 39.45×104 km2 and 42.94×104 km2 by the 2050s and 2070s, respectively. Under the two future climate scenarios, the potential suitable habitat area will tend to increase and shift northwards, and the decreasing areas will be mainly concentrated in the Junggar Basin. Among all the environmental factors, precipitation and temperature made the strongest contributions to distribution, with total contribution rates of 40.1% and 56.0%, respectively. The individual factors making the strongest contributions to giant ragweed distribution were precipitation in the driest month (36.2%) and temperature seasonality (29.1%). Farmland and construction land were identified as the areas with the highest risk of giant ragweed invasion. On the basis of these results, we suggest that management strategies should focus not only on predicted habitats, but also on farmland, grassland, and roadsides where there is sufficient water and strong disturbance by humans or animals.

Key words: biological invasion, climate change, Maxent niche model, giant ragweed, suitable threshold