Developing a Better Approach to Ecological Projection Models Using a GIS-Based Mechanistic Model Framework

Albrecht, Jeff

Developing a Better Approach to Ecological Projection Models Using a GIS-Based Mechanistic Model Framework

Persistent URL

http://hdl.handle.net/10456/41605

Author(s)

Albrecht, Jeff

Date Issued

May 9, 2016

Abstract

There is an increasing societal need to develop better strategies for managing our habitats and ecosystems that are threatened by climate change. In a world where our past is no longer a clear guide to our future, our ability to model and anticipate the effects of climate change on our ecosystems is more critical than ever. Commonly used ecological projection models have been useful in projecting how habitat ranges of species will shift due to climatic variables, however these models have many downfalls. This paper proposes a new GIS-based mechanistic ecological projection model that overcomes these downfalls and operates as a decision support tool for scientists and policy makers. The proposed model was created in ArcGIS Desktop 10.3 using the model builder capability and utilizes fuzzy membership classification combined with data from standard climate change models to create multiple habitat suitability indexes (initial and projected) which assign temporally changing suitability scores to anticipate how climate change will affect species habitat. For example, an area that originally receives a high suitability score but a low suitability score in a future year represents an area where habitat for the respective species is being degraded. The initial and projected suitability indexes were overlaid in the GIS to spatially display how habitats of the three modelled species will change. These results are then discussed with respect to the underlying assumptions of the model framework and take into consideration environmental, biological, and anthropogenic variables that exist outside of the model. In this way, the model results are used to suggest conservation and management decisions.

Major

Environmental Science

Honors

Environmental Science, 2016

First Reader(s)

Shaffer, Chris