SCIRP Mobile Website
Paper Submission

Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.

 

Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
   
Paper Publishing WeChat
Book Publishing WeChat
(or Email:book@scirp.org)

Article citations

More>>

Groff, L.A., Marks, S.B. and Hayes, M.P. (2014) Using Ecological Niche Models to Direct Rare Amphibian Surveys: A Case Study Using the Oregon Spotted Frog (Rana Pretiosa). Herpetological Conservation and Biology, 9, 354-368.

has been cited by the following article:

  • 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.