Use of Habitat Suitability Index Models with Landscape-scale Factors to Prioritize Dam Removal in the Susquehanna River

1. Use of Habitat Suitability Index Models with Landscape-scale Factors to Prioritize Dam Removal in the Susquehanna River Robert M. Ross, Patrick M. Kocovsky, and David S. Dropkin Leetown Science Center Wellsboro, Pennsylvania 16901 John M. Campbell Mercyhurst College Erie, Pennsylvania 16546

2. Background / Problem • 76,000 dams control >0.5M river miles in U.S. • States where restoration of diadromous fishes is a goal: fish passage has only had limited success • Many dams no longer provide societal benefits and may be considered for removal • Diadromous fish habitat quantification has not been used to prioritize dam removal • Landscape influence has not been factored into migratory fish habitat suitability models

3. Objectives • Assist river managers with dam-removal prioritization using fish habitat information • Provide a landscape-scale perspective for prioritizing dam removal • Identify links between fish habitat suitability and landscape-scale factors in streams with unnatural blockages

4. Methods: Study Site/Design • Conduct both modeling and field work on PAs Susquehanna River and tributaries • Use/develop existing/new HSI models for diadromous fishes to assess habitat quality on tributaries of management interest • ID useful landscape variables for all tributary watersheds • Link landscape variables to HSI using canonical correlation analysis (CANCOR), ID relationships

5. Methods: Field Sampling • 6 Susquehanna River tributaries assessed in June 99/00 • Transects (21-34) placed every 5 km through 3rd-order reaches • Physical, chemical, biological data taken at each transect (5 points) for HSI models • Biological samples: macroinverts (Am. eel) and drift/zooplankton (river herring)

6. WBR SWC JNR CSR CDC CWC Watersheds of the Six Major Tributaries to the Susquehanna River in Pennsylvania WBR – West Branch JNR – Juniata CDC – Conodoguinet SWC – Swatara CWC – Conewago CSR - Conestoga

7. Low-head dam on the West Branch Susquehanna River at Lock Haven Wooden-crib dam on Bald Eagle Creek Sampling for macroinvertebrates on the West Branch Susquehanna River

8. Methods: HSI Models • Anadromous fish: Am. shad, river herring (alewife and blueback) • Life stages: spawning adults, eggs/larvae, juveniles • HSI models • FWS: Stier & Crance ’83, Pardue ’83, Ross et al. ’93/’97 • PSU: Carline et al. ’97 • New model: Am. eel juveniles (<40 cm) • Trophic quality (macroinvertebrate taxa, numbers) • Based on diet studies: Odgen 70, L&A 92, D&S 93

9. HSIs by Lifestage for American Shad on Conestoga River Habitat suitability 1 5 10 15 20 Transect

10. Integrated HSIs for Blueback Herring on Small Tributaries Habitat suitability 1 5 10 15 20 25 30 Transect

11. Methods: Land Use and Geology • Land use data layer • 30m resolutiondigital GAP maps • 24 LUs reduced to 2 (forested, non-forested) • Surface geology digital map: 10 → 3 types (carbonate, shale, sandstone) • Geo-referenced and Albers projected (PASDA) • GIS work done on ArcView 3.2 • Watershed delineation: DRGs for USGS topo maps (upstream of all transects)

12. Methods: Data Analysis • CANCOR multivariate analysis used to evaluate HSI & landscape relations • Structure coefficients used to ID gradients in LU/geology in canonical variables • Univariate correlations (original x-variables) used to verify CANCOR results • Separate CANCORs performed on FWS (3 species, life stages) and PSU (river herring) HSIs • Linear regression performed on log (micro-crustacean density) vs. mean instream pH

13. Susquehanna Tributary Landcover and Geology

14. Plankton/Drift Density and Taxa Richness

15. Results: CANCOR • FWS models • 1st 5 pairs (HSI/LU) of canonical variates significant • 42% of total variance explained • Structure coeffs. → gradients in LU/G with HSIs • CANCOR showed + effect of carbonate rock on all HSIs but Am. eel (-) and juvenile Am. shad (-) • Univariate correlations agreed well except for blueback herring

16. Results: CANCOR • PSU models • 1st 4 pairs of canonical variates significant • 36% of total variance explained • Structure coeffs. → gradients in LU/G • CANCOR showed + effect of carbonate rock on all HSIs except Am. eel (-) • Univariate correlations agreed well except blueback herring

17. Results: Regression • Micro-crustacean density vs. tributary pH • pH explained 60% of variation (R2=0.60) • Log(density) = 0.82pH -5.56 (p=0.035) • Stream pH correlated well with % carbonate rock in watershed (upstream), except CWC • Macroinvertebrates (drift) showed same relationship as micro-crustaceans • HSI linkage now shown between landscape (% limestone) and reach (stream pH) scale factors

18. Results: Dam Removal Prioritizaton Criteria (4) • HSI Scores (segment-specific, 4 species) • Landscape-scape factors (LU, geology) • Stream miles opened by dam removal (habitat gain) • Distance to Chesapeake Bay (predator risk)

19. Dam Removal Algorithm • Calculate rank for each of 4 criteria (variables) for all dams • Calculate mean rank for all criteria at each dam • Rank the mean ranks for all dams • Prioritize • Lowest rank = highest priority • Must also be lowest dam on tributary

20. Dam Removal Prioritization for River Herring (4 Factors)

21. Dam Removal Prioritization for American Shad, Eel, Overall

22. Conclusions • Habitat suitability of all species/lifestages of alosines (except juv. Am. shad) correlated (+) to % carbonate rock in watershed • Habitat suitability of juvenile Am. eel correlated (-) to % carbonate geology • Corroboration of importance of landscape factors in both HSI models (multiple species/life stages) suggests influence of carbonate rock • Mechanism for landscape influence on HSI • Physiologic Hypothesis: ↑ stream pH/buffering (↓acid episodes) • Trophic Hypothesis: ↑ stream productivity/µ-crustacean density

23. Conclusions (cont.) • Four criteria basis for dam removal priority • HSIs for anadromous fishes, life stages • Landscape-scape factors (LU, geology) • Stream miles opened by dam removal (habitat gain) • Distance to Chesapeake Bay (predator risk) • Prioritization algorithm: lowest mean-criteria rank that is also the lowest dam on tributary • Integrated species dam removal strategy: • SWA1>CNS1>CNW1>CNS2..3..4 etc. • CND and WBR ranked 13th , 15th priority

24. Application to Resource Management • Tool to assist managers in prioritizing dam removal (goal: restore diadromous fishes) • Links landscape factors (easy to measure) to instream habitat suitability • Helps to provide a more holistic assessment for restoration • Amenable to adaptive management approach (remove dam, evaluate/test predictions)

25. Future Research Direction and Recommendations • Validate method in other mid-Atlantic rivers • Assess changes in HS after dam removal (how reliable were predictions?) • Mechanism linking HSI to carbonate rock? • Buffering capacity for acid episodes • Stream productivity • Instream habitat structure • Resident fish benefits from dam removal

26. Acknowledgements • Field Assessment: Chris Frese (Kleinschmidt Assoc.) • DRGs: Scott Hoffman (USGS Water Resources) • Data Analysis: Lori Redell (USGS-LSC) • Review: Bob Carline (USGS), Dick St. Pierre (USFWS), Andy Shiels (PAFBC) Photo courtesy of Bill Baird

27. Landscape-scale and other factors for prioritizing dam removal on Susquehanna tributaries