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The Land and Water Connection

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The Land and Water Connection

  1. 1. The Land and Water Connection
  2. 2. The Pocono Kittatinny Cluster • Conservation Cluster • Goal: Maintain Water Quality • Target: Big Woods, Clean Streams, Undisturbed Wetlands Focus Areas selected per results of NLT, TNC, NF WF, USFS
  3. 3. . Goal Target those Ecologically Significant Lands that are most important to the maintenance of Healthy Waters Ecologically Significant Lands “Headwaters, Wetlands, Floodplains” Healthy Waters “Fishable, Swimmable, Drinkable”
  4. 4. How do we identify those ecologically significant lands that provide the most benefit to maintaining water quality?
  5. 5. What have others looked at: USFS Forests to Faucets Conservation Priority Index Ability to Produce Clean Water (Forest, Ag, Rip For Cover, Rd Density, Soil Erodibility, Housing Density) Land Use Importance for Drinking Water Supply Distance to Streams and Wetlands Dependence on Private Forestlands Soils (depth & permeability) Slope Threat of forest conversion or poor management Projections of Future Housing Density Natural Infrastructure: Investing in Forested Landscapes for Source Water Protection World Resources Institute, 2013 From the Forest to the Faucet: Identifying the Connections of Forests, Water and People Rebecca Whitney U.S. Forest Service Northeastern Area S&PF, 2007
  6. 6. Pocono Kittatinny Cluster Draft Metrics Size Forest (habitat) Condition Land Cover Percent Impervious Cover (parcel and floodplain) Feet/Miles of Riverfront Wetland and Floodplain Abundance Development Potential (modeled Impervious Cover) Ecological Significance
  7. 7. Other Metrics for Consideration Finding the Balance Resiliency Groundwater Soils Slopes Relating to Water Uses (wellhead protection areas, proximity to surface water intakes, etc.)
  8. 8. Other Methods --Models Watershed Modeling Soil and Water Assessment (SWAT) Generalized Watershed Loading Function Hydrological Simulation Program – Fortran (HSPF) Combining with Economic Modeling Resource Investment Optimization System (RIOS) Resources for the Future Requirements: Expertise, Extensive Data, Calibration (Capacity and Time)
  9. 9. State of the Science  We don’t know the exact connection between land protection and water quality….. (how much, where, what configuration)  We acknowledge the uncertainty “We are now looking to set priorities using the best available knowledge and data” Peter Howell
  10. 10. Discussion
  11. 11. Methods Evaluate the Landscape’s Ability to Maintain Water Quality •Percent Impervious Cover •Terrestrial & Aquatic Habitat Condition •Wetland, Riparian, & Floodplain Density Evaluate Project Constraints and Opportunities •Percent Match Available •Total Capital Needed & Cost/Acre •Probability of Protection in 3-yrs Identify Significant Headwaters and Floodplains •Ensure Conservation Benefits Accrue to Meaningful Level •Compare to other Studies
  12. 12. Resilience: Definition The capacity for renewal in a dynamic environment - Gunderson 2000 The ability of a social or ecological system to absorb disturbances while retaining Network Complexity the same basic structure and ways of functioning – Number of size classes - IPCC 2007 Physical Diversity – Length of connected linear miles – Diversity of Temperatures – Diversity of Gradients Ecological Condition – Lateral connectivity – naturalness of floodplain – Unimpeded flow – Pervious /permeable watersheds © Anderson and Olivero, The Nature Conservancy
  13. 13. Limitations Certain datasets are limited and/or inconsistent across state lines Knowledge is limited and inconsistent in defining ecologically significant thresholds in most measured variables Single indices do not address synergy of different threats Multi-variable indices can begin to estimate the synergy of different threats, but assigning weights and how variables interact is very difficult given current knowledge GIS has enabled us to use and present so many different data layers that sometimes there’s a piling on in priority setting exercises - particularly when you’re trying to represent multiple perspectives and interests, or aren’t sure of what you’re doing that obscures what’s most important.
  14. 14. Summary Variability among the Cluster may be a limiting factor, so resulting ranks may be somewhat flat- Are we splitting hairs ?

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