Impact Assessment of Mikania Micrantha on Land Cover and Maxent Modeling to Predict Its Potential Invasion Sites

Abstract

ABSTRACT:Mikania micrantha is one of the major invasive alien plant species in tropical moist forest regions of Asia including Nepal. Recently, this weed is spreading at an alarming rate in Chitwan National Park (CNP) and threatening biodiversity. This paper aims to assess the impacts of Mikania micrantha on different land cover and to predict potential invasion sites in CNP using Maxent model. Primary data for this were presence point coordinates and perceived Mikania micrantha cover collected through systematic random sampling technique. Rapideye image, Shuttle Radar Topographic Mission data and bioclimatic variables were acquired as secondary data. Mikania micrantha distribution maps were prepared by overlaying the presence points on image classified by object based image analysis. The overall accuracy of classification was 90% with Kappa coefficient 0.848. A table depicting the number of sample points in each land cover with respective Mikania micrantha coverage was extracted from the distribution maps to show the impact. The riverine forest was found to be the most affected land cover with 85.98% presence points and sal forest was found to be very less affected with only 17.02% presence points. Maxent modeling predicted the areas near the river valley as the potential invasion sites with statistically significant Area Under the Receiver Operating Curve (AUC) value of 0.969. Maximum temperature of warmest month and annual precipitation were identified as the predictor variables that contribute the most to Mikania micrantha"s potential distribution.

Geospatial Analysis of Habitat Suitability for Greater One-horned Rhino Rhinoceros unicornis (Linnaeus, 1758) in Central lowlands of Nepal using MaxEnt Model

“…Similarly, in Nepal, several studies have been carried out regarding species habitat suitability using MaxEnt (Bai et al, 2018). The habitat suitability for mammals, birds, vegetation, and even invasive plant species habitat analysis was previously conducted (Khadka & Pandey, 2014;Baidar et al, 2017;Linshan et al, 2017;Acharya et al, 2018;Bista et al, 2018;Chhetri et al, 2018;Lamsal et al, 2018;Rana et al, 2018;Thapa et al, 2018). More specifically, Kafley et al (2009) used data for MaxEnt modelling of species geographic distributions for predicting the probability of occurrence of rhinos in Chitwan National Park and found that the national park can sustain more individuals (then time individuals; 512).…”