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Schedule:
**Policy & Planning
**Science & Statistics

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The course will introduce and develop the participants skills needed for species distribution models (SDMs) and habitat maps for conservation planning, using the appropriate classification model or approach needed by the species under investigation. The choice and array of models will address the need for both ecological understanding and spatial predictive capacity, with the aim of increasing the predictive power of the analyses and reduce the error associated with spatial models.  The four primary predictive approaches examined during the course will include: linear logistic regression (GLM); additive logistic regression (GAM); classification trees (CART); and the Random Forest approach.

College Credit:  2 semester hours

Who Should Attend:  Field, Management, and Research Biologists

Pre-requisites:  Data Analysis II (CSP4210)

Length:  5 days/36 hours

Objectives:  By the end of this session, the participant will be able to:

• develop critical modeling skills based upon reliable analytical techniques and integrated with available GIS technology; whereby, participants will be able to assess and map the distribution of plant and animal species based upon both abiotic and biotic attributes of the species and its environment.