TITLE:
Distribution Prediction Model of a Rare Orchid Species (Vanda bicolor Griff.) Using Small Sample Size
AUTHORS:
Chitta Ranjan Deb, N. S. Jamir, Zubenthung P. Kikon
KEYWORDS:
MAXENT Distribution Prediction Model, ENM, Ground Truthing, Vanda bicolor
JOURNAL NAME:
American Journal of Plant Sciences,
Vol.8 No.6,
May
26,
2017
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.