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Streamside forests reduce nutrient pollution of aquatic ecosystems

Streamside forests reduce nutrient pollution of aquatic ecosystems. Donald E. Weller, Thomas E. Jordan, and Matthew E. Baker. Smithsonian Environmental Research Center. Ecosystem services. Terrestrial Wildlife habitat Carbon sequestration Forest products Aquatic Aquatic food chain

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Streamside forests reduce nutrient pollution of aquatic ecosystems

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  1. Streamside forests reduce nutrient pollution of aquatic ecosystems Donald E. Weller, Thomas E. Jordan, and Matthew E. Baker Smithsonian Environmental Research Center

  2. Ecosystem services • Terrestrial • Wildlife habitat • Carbon sequestration • Forest products • Aquatic • Aquatic food chain • Control temperature • Pollutant regulation • Nutrient removal

  3. Field studies of nitrogen removal

  4. Mid-Atlantic removal results Nitrate concentration (mg N/l) Distance from field toward stream (m)

  5. National stream and river restoration Riparian restorations 1990-2003 > $5 billion > 20,000 projects

  6. Buffer prevalence varies widely

  7. Problems “scaling up” . . . Watershed results mixed ? Transect results striking

  8. (Mal)adaptive management Knowledge Evaluation Implementation Measurement

  9. New geographic analysis sources flowpaths sinks Well-buffered pathway transport pathway for 1 pixel Not so well-buffered Overlay sources and streams on elevation Identify downhill transport pathways Quantify width & aggregate paths

  10. Prioritizing management efforts

  11. Chesapeake Bay example • 321 watersheds • 3 physiographic provinces • focus on cropland and buffers • empirical models for stream nitrate

  12. Benefits differ among regions Stream Nutrient Levels <no buffers <current buffers <complete buffer <no cropland

  13. Overall reductions 16% 32% 68%

  14. Policy implications • Protect riparian areas • Conserve existing forest buffers • Restore missing forest buffers • Outreach and education • Focus incentive funding • Regional targeting • Site level targeting • Implement adaptive management • Improve models for estimating benefits • Measure outcomes

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