The Great Lakes Basin Riparian Opportunity Assessment began April 1, 2015 and spanned one year. The New York Natural Heritage Program (NYNHP) of the State University of New York College of Environmental Science and Forestry (SUNY ESF) completed this project for the New York State Department of Environmental Conservation’s (NYS DEC) Great Lakes Watershed Program. The goal of the project was to support strategic identification and prioritization of sites for implementation in DEC’s Trees for Tribs program, which enlists the help of volunteers to plant native trees and shrubs in riparian buffers of streams to improve wildlife habitat, water quality, climate resiliency, and to provide flood protection during storm events. While this was the primary goal of our assessment, we maintained additional goals of riparian protection as well as other restoration efforts. This assessment directly supports multiple goals and actions included in New York’s Interim Great Lakes Action Agenda and advances an ecosystem-based management approach to riparian restoration and protection work in the Basin by promoting strategic, science-based decision-making to achieve multiple benefits.
NY Natural Heritage Program staff on the project included Amy Conley, Spatial Ecologist, Tim Howard, Director of Science, and Erin White, Zoologist. The project steering committee was made up of the NYS DEC's Great Lakes Program, Division of Water, Division of Lands and Forests, and Division of Fish and Wildlife. In addition, there was representation from The Nature Conservancy Central/Western NY Chapter, NYS Soil & Water Conservation Committee, the NYS Department of Agriculture and Markets, and additional staff from SUNY Environmental Science and Forestry. The Steering Committee met at regular intervals throughout the project to provide feedback on the following tasks:
Task 1: Develop and document a proposed assessment methodology.
The Steering Committee met in June to review our recommended methods. We compiled feedback and revised this to produce our working Assessment Methodology to be used in later tasks. Full descriptions of our proposed habitat indicators, methods for identifying riparian habitat, critical zone and location analysis, and site prioritization can be found in this document.
Task 2: Identify sub-watersheds (or HUC 12 hydrologic units) for water quality and habitat quality management.
For this task, we created health indicator scores, stress indicator scores, as well as an overall comprehensive score for each sub-watershed in the Great Lakes Basin. Further details and draft results for this task are found here (10/1/2015): Critical Zones. The steering committee met to review this product in October 2015.
Deliverable 1: PDF of Summary Results Results for this task are presented in pdf form, and can be found here with further details (10/1/2015):
Deliverable 2: Geodatabase Data The full data set, including polygons for all 687 sub-watersheds in the Great Lakes Basin, and an attribute table that includes raw and normalized scores for all indicators, can be found in an ArcGIS feature class inside this geodatabase:
Task 3: Identify locations (catchments) within the sub-watersheds where Trees for Tribs can have a tangible effect on improving water quality and habitat quality management.
For the most part, the same suite of indicators and methods of scoring that were used to classify sub-watersheds, were used to classify catchments within the sub-watersheds, with improvements suggested by the steering committee during review of our critical zone analysis.
Deliverable 1: PDF of Summary Results Results for this task are presented in pdf form with separate maps for each sub-region in the basin, and can be found here with further details (12/31/2015):
Open file in pdf reader. NOT Browser
Right click and select "Save Link As". DO NOT OPEN IN BROWSER
Deliverable 2: Geodatabase Data The full data set, which contains the catchment polygons for the entire study area, and an attribute table that includes raw and normalized scores for all indicators, can be found in an ArcGIS feature class inside this geodatabase (12/31/2015):
This task was completed on March 31, 2016 and a final report and final products can be found here:
Results: PDF Format
Results: ArcGIS Feature Class Format
Results:Online Data Explorer