Distribution Prediction Model of a Rare Orchid Species (Vanda bicolor Griff.) Using Small Sample Size

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DOI: 10.4236/ajps.2017.86094    1,431 Downloads   3,038 Views  Citations

ABSTRACT

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.

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Deb, C. , Jamir, N. and Kikon, Z. (2017) Distribution Prediction Model of a Rare Orchid Species (Vanda bicolor Griff.) Using Small Sample Size. American Journal of Plant Sciences, 8, 1388-1398. doi: 10.4236/ajps.2017.86094.
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