摘要
Advancement in field of GIS and Information Technology has taken conservation works and strategies a step further as most conservation works are now dependent on these technologies. The present study explores the prediction ability of MAXENT using a very low sample size by applying jackknife analysis over a well defined smaller region and using only climate data. Vanda bicolor is a horticulture important orchid grown in certain patches of North Eastern region of India and the species considered to be “Vulnerable”. Present study reports a distribution prediction model using different geo-climatic parameters for a small area. Model validation by ground truthing gives a significant successful result which clearly defines the ability of MAXENT prediction model to give high success rate (71%) with low training samples. Use of the low sample size over a larger area results in unstable models however application of these samples in smaller radius around the occurrence points could provide good working models.
Advancement in field of GIS and Information Technology has taken conservation works and strategies a step further as most conservation works are now dependent on these technologies. The present study explores the prediction ability of MAXENT using a very low sample size by applying jackknife analysis over a well defined smaller region and using only climate data. Vanda bicolor is a horticulture important orchid grown in certain patches of North Eastern region of India and the species considered to be “Vulnerable”. Present study reports a distribution prediction model using different geo-climatic parameters for a small area. Model validation by ground truthing gives a significant successful result which clearly defines the ability of MAXENT prediction model to give high success rate (71%) with low training samples. Use of the low sample size over a larger area results in unstable models however application of these samples in smaller radius around the occurrence points could provide good working models.
