Comparing the results of this study to similar studies conducted previously, the results of this project demonstrated that a Multi-Criteria Evaluation model and Least-Cost Pathway analysis can improve the siting of a potential ecological corridor. Improved siting from MCE and LCP application is due to the relevant siting criteria analysis that can be conducted before siting occurs. This can allow for problem identification before development occurs, such as possible contradictions between criteria that were encountered within this model, that resulted in low overall suitability. This project demonstrated the ability to better understand how diverse landscapes and multiple spatial variables can be integrated to improve decision making in ecologically significant locations in the future. The implementation of an ecological corridor based on this model's analysis has the potential to reduce habitat fragmentation, and the resulting edge effects related to ecological decline in future study areas, while simultaneously minimizing disturbance to human activities. This is demonstrated by the successful path of the LCP model in this study, which avoided anthropogenic land uses, and traversed through the most suitable land uses when possible. The criteria of slope was also adhered to with significant success as seen in the results, which improves the moose usability likelihood in this mountainous region. Road crossings were inevitable, however the few areas that were further from roads were traversed through successfully by the LCP, which helps reduce the noise of the corridor and therefore improves moose usability. To build upon this study, future GIS analyses should factor in a variety of weighting schemes to obtain a better understanding of how criteria contradictions effect overall suitability. Considerations such as these have the potential to improve this model for future applications in alternative study areas, and resolve the implications of the low suitability of this model. Additionally, application of this model to other moose habitat areas located within fragmented landscapes could strengthen the model by identifying areas of the model that can be improved further to increase universal transferability.
We would like to give thanks to our professor, Dr. Wanhong Yang and teaching assistants, Olivia Carpino and Jenelle White for their continued guidance and assistance throughout the duration of this project. We would also like to thank John Barge of Adirondack Park Agency, for assisting us with obtaining much of the essential data for this study.