{'fraction_non_alphanumeric': 0.025245441795231416, 'fraction_numerical': 0.016830294530154277, 'mean_word_length': 5.294117647058823, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Geographic Distribution Shift of Invasive Plant Austroeupatorium inulifolium in the Future Climate Projection

Aims: This study aims to predict the future geographic distribution shift of invasive plant species Austroeupathorium inulifolium as the impact of global climate change. Study Design: The rising temperature and precipitation change lead to the geographic distribution shift of organisms. A. inulifolium belongs to invasive plant species that often causes a substantial economic loss and ecological degradation in the invaded areas. Modelling of species distribution using the climate-based model could be used to understand the geographic distribution shift of invasive species in the future scenario under global climate change. Place and Duration of Study: Center for Plant Conservation and Botanic Gardens – LIPI and 6 months. Methodology: The total 2228 of occurrence records were derived from the Global Biodiversity Original Research Article Yudaputra et al.; ARRB, 36(5): 38-47, 2021; Article no.ARRB.68482 39 Information Facility (GBIF) database. The seven climatic variables were selected from 19 variables using a pairwise correlation test (vifcor) with a threshold >0.7. The ensemble model was used by combining Random Forest (RF) and Support Vector Machine (SVM). Results: Both two models are well-performed either using AUC or TSS evaluation methods. RF and SVM have AUC >0.95, and TSS >0.8. The predicted current distribution tends to have larger distribution areas compared to observed occurrence records. The predicted future distribution seems to be shifted in several parts of North America and Europe. Conclusion: The geographic distribution of invasive plant species A. inulifolium will be shifted to the Northern part of globe in 2090. Mean temperature of driest quarter and precipitation of warmest quarter are the two most important variables that determine the distribution pattern of the A. inulifolium. The predictive distribution pattern of invasive plant A. inulifolium would be important to provide information about the impact of climate change to the geographic distribution shift of this species.