Species distribution prediction modeling plays a key role in Bio-diversity research. There are increasing needs for species distribution modeling ranging from basic ecological and biogeography research to routine conservation practices. Currently forest scientists and conservationists are looking for web enabled customized tools to model species loss on the fly since they have enormous field data available with them to analyze and visualize. Though they have many desktop tools developed under open source initiative for understanding species loss with regard to climate change scenarios. Nevertheless web enabled Web Processing Services are still unavailable to them to perform modeling. We propose to publish an Open Geospatial Consortium’s (OGC) Web Processing Service (WPS) that performs species distribution modeling process as a Web service and composite them into modeling systems using the scientific workflow approach. Our work demonstrates how a Species Distribution Model can be hosted as a WPS web service. As the requirements of Species Distribution Modeling deal with data, algorithms, calculation models and computing capability, we use 52 degree North Web Processing Service with R-backend (WPS4R) framework that allows to upload and expose R scripts dynamically as WPS processes with the support of high computation capabilities. We predict the distribution model of the species Hippophae Rhamnoides. L (Sea Buckthorn) in the area Lahaul and Spiti (Bounding Box: 76.3700, 31.7439, 78.6541, 33.2653) district, Himachal Pradesh using Maximum Entropy (MaxEnt) modeling technique to predict the distribution of species. We use species occurrence data collected from Global Biodiversity Informatics Facility and DOS-DBT project. The primary advantage of this approach being, scientists no longer need to use the desktop tools while predicting the species distribution model. They can, on the fly, use their data, request for predicting the species by combining with geospatial processes to produce the prediction map over the web unswervingly. Henceforth the project aims to develop an OGC WPS services for species niche modeling making this applicable to a wide range of species of significant importance for the research and industry community.
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