Journal of Forest and Environmental Science

Institute of Forest Science, kangwon National University (강원대학교 산림과학연구소)
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Spatio-Temporal Projection of Invasion Using Machine Learning Algorithm-MaxEnt

  • Singye Lhamo (Natural Resource Management, College of Natural Resources, Royal University of Bhutan) ;
  • Ugyen Thinley (Environment and Climate Studies, College of Natural Resources, Royal University of Bhutan) ;
  • Ugyen Dorji (Department of Forest Science, College of Natural Resources, Royal University of Bhutan)
  • Received : 2023.03.09
  • Accepted : 2023.05.27
  • Published : 2023.06.30
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Abstract

Climate change and invasive alien plant species (IAPs) are having a significant impact on mountain ecosystems. The combination of climate change and socio-economic development is exacerbating the invasion of IAPs, which are a major threat to biodiversity loss and ecosystem functioning. Species distribution modelling has become an important tool in predicting the invasion or suitability probability under climate change based on occurrence data and environmental variables. MaxEnt modelling was applied to predict the current suitable distribution of most noxious weed A. adenophora (Spreng) R. King and H. Robinson and analysed the changes in distribution with the use of current (year 2000) environmental variables and future (year 2050) climatic scenarios consisting of 3 representative concentration pathways (RCP 2.6, RCP 4.5 and RCP 8.5) in Bhutan. Species occurrence data was collected from the region of interest along the road side using GPS handset. The model performance of both current and future climatic scenario was moderate in performance with mean temperature of wettest quarter being the most important variable that contributed in model fit. The study shows that current climatic condition favours the A. adenophora for its invasion and RCP 2.6 climatic scenario would promote aggression of invasion as compared to RCP 4.5 and RCP 8.5 climatic scenarios. This can lead to characterization of the species as preferring moderate change in climatic conditions to be invasive, while extreme conditions can inhibit its invasiveness. This study can serve as reference point for the conservation and management strategies in control of this species and further research.

Keywords

Acknowledgement

We remain grateful to the Bhutan Ecological Society for the financial assistance to carry out field survey and data collection on species records from our study sites. We also thank the College of Natural Resources for providing this opportunity to carry out this research with technical assistance and other facilities such as GPS handsets and ICT facilities. The authors thank Idea Wild for generously providing the laptop and camera.

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