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.

FM radio transmission is greatly affected by geography. Nepal faces particular problems in relation to variations in signal reach because of its varying topography. Radio signal coverage mapping indicates service areas of radio communication transmitting stations. The objectives of this study are to map the signal coverage of local radios (Kavre district) and to assess parameters affecting FM signal strength. The primary data were GPS coordinates of FM transmission stations and bearing of antenna. The secondary data regarding frequency of station, transmitter model, transmitter power, antenna model, and height of antenna from ground level were collected from respective FM stations. For elevation data freely available SRTMv3 was used. Combined Cartesian coverage maps for each FM stations were prepared using Radio Mobile software that showed varying signal strength of station in dBμV/m. The accuracy of the maps through field validation was observed to be 85%. Assessment of parameters affecting FM signal strength concluded that increase in antenna elevation, gain of antenna and power of transmitter increases the signal coverage.