The Huron Clinton Metropolitan Authority's (HCMA) Natural Resource Department oversees and manages the undeveloped land throughout the thirteen Metroparks surrounding the greater Detroit metropolitan area. Their goal is, "to protect and restore significant elements of natural diversity while balancing ecological stewardship with compatible recreational uses." In order to enact their mission, the Natural Resources Department utilizes a dataset of compiled plant, animal, and natural features information to prescribe management techniques, such as invasive species removal. While maps of natural communities within the parks are available through the Michigan Natural Features Inventory, and detailed ecological information exists for some of the parks' natural areas, the majority of their land is lacking basic ecological quality data, making it difficult for the Natural Resources Department to prioritize their efforts across and within the Metroparks. The Natural Resource Department needs a method for assessing ecological quality that can be consistently applied across all of their parks, while still working within reasonable time and budget constraints.
The master's project group identified several different ecological assessment protocols that are available and applicable for use by the HCMA Natural Resource Department. Each of the identified protocols were examined through a case-study implementation within the Lower Huron and Willow Metroparks. In order to determine a reliable and appropriate method for HCMA to assess ecological quality, the project group compared the results of each protocol against a set of evaluation criteria, including how well the protocols correlate with one another and the resources required for implementation.
- Jessica Gorchow, MS Behavior, Education and Communication/Conservation Biology
- Elizabeth Hood, MS Terrestrial Ecosystems
- Yi Hou, MS Environmental Informatics: GIS and Modeling
- Lillian Peterson, MS Conservation Biology
- Elizabeth Straus, MS Aquatic Sciences, Research and Management