Mon, Aug 15, 2022: 2:45 PM-3:00 PM
516A
Background/Question/Methods
Protected areas are necessary for both biodiversity conservation and the provision of dynamic ecosystem services. In recent times, invasive plant species have wreaked havoc on maintaining protected areas for threatened species. In the post-monsoon period of 2019, we conducted a vegetation survey in 108 plots of size 30 × 30 m2 in India's Manas National Park of the Terai ecoregion. Mikania micrantha (climber) and Chromolaena odorata (shrub) were found to be the most prevalent invasive species of the park. We compared the invasive density of the present time with our survey data of 2011 (for 83 of the 108 plots) to evaluate the change in invasive abundance over the eight years. Then we put together a set of environmental variables that are either direct measurements or proxies for resource availability, plant density, disturbance, and moisture stress, factors known to impact an ecosystem's invasibility. We used decision tree-based regression and prediction to assess the influence of these variables on the distribution and abundance of these two invasive species and create risk maps of their distributions. The impacts of the two invasives on plant communities were also analysed by comparing 20 pairs of non-invaded and invaded quadrats for each species.
Results/Conclusions
Chromolaena density has increased in approximately 80% of the plots, whereas 64% have increased by more than twice as much. Mikania abundance has grown in 53% of plots during the same period, with 36% increasing by more than twofold. The regression models had explained the abundance of Chromolaena (R2 = 0.47) and Mikania (R2 = 0.82) with significant predictive power. Fire frequency, distance to road and moisture index had a significant influence in Mikania, and distance to road and distance to the river had the strongest influence on Chromolaena. Chromolaena has influenced plant community structure, resulting in a considerable reduction in plant species richness and diversity. We could not make any significant conclusions on Mikania's influence on the native plant community. The rapid growth in the number and range of these two invasive species over the last eight years is concerning. Predicted invasion risk maps can be used as an early detection tool for invasive species control, thereby reducing invasions' ecological and economic impact. The findings of this study will assist forest authorities in managing, taking the appropriate actions in the designated region, and developing a complete plan for invasive species control.
Protected areas are necessary for both biodiversity conservation and the provision of dynamic ecosystem services. In recent times, invasive plant species have wreaked havoc on maintaining protected areas for threatened species. In the post-monsoon period of 2019, we conducted a vegetation survey in 108 plots of size 30 × 30 m2 in India's Manas National Park of the Terai ecoregion. Mikania micrantha (climber) and Chromolaena odorata (shrub) were found to be the most prevalent invasive species of the park. We compared the invasive density of the present time with our survey data of 2011 (for 83 of the 108 plots) to evaluate the change in invasive abundance over the eight years. Then we put together a set of environmental variables that are either direct measurements or proxies for resource availability, plant density, disturbance, and moisture stress, factors known to impact an ecosystem's invasibility. We used decision tree-based regression and prediction to assess the influence of these variables on the distribution and abundance of these two invasive species and create risk maps of their distributions. The impacts of the two invasives on plant communities were also analysed by comparing 20 pairs of non-invaded and invaded quadrats for each species.
Results/Conclusions
Chromolaena density has increased in approximately 80% of the plots, whereas 64% have increased by more than twice as much. Mikania abundance has grown in 53% of plots during the same period, with 36% increasing by more than twofold. The regression models had explained the abundance of Chromolaena (R2 = 0.47) and Mikania (R2 = 0.82) with significant predictive power. Fire frequency, distance to road and moisture index had a significant influence in Mikania, and distance to road and distance to the river had the strongest influence on Chromolaena. Chromolaena has influenced plant community structure, resulting in a considerable reduction in plant species richness and diversity. We could not make any significant conclusions on Mikania's influence on the native plant community. The rapid growth in the number and range of these two invasive species over the last eight years is concerning. Predicted invasion risk maps can be used as an early detection tool for invasive species control, thereby reducing invasions' ecological and economic impact. The findings of this study will assist forest authorities in managing, taking the appropriate actions in the designated region, and developing a complete plan for invasive species control.