1. Robert M. Ross, Patrick M. Kocovsky, and David S. Dropkin
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
John M. Campbell
Mercyhurst College
Erie, Pennsylvania
This study is an outgrowth of previous NRPP research that AEL and RDL conducted on potential aquatic impacts of eastern hemlock decline
A collaborative project across 3 component laboratories
Funded through the “Exotics in the East” program

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. Watersheds of the Six Major Tributaries to the Susquehanna River in Pennsylvania
WBR
JNR
CDC
SWC
CWC
CSR
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
Transect

10. Integrated HSIs for Blueback Herring on Small Tributaries
Habitat suitability
Transect

11. Methods: Land Use and Geology
Land use data layer
30m resolution digital 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
Area (km2)
Forest (%)
Non-forest
Carbon-ate (%)
Shale
Sandstone
Conestoga
1,125 26 74 57 6 19
Conewago
1,335 35 65 5 4
Swatara
1,479 44 56 14 50 21
Conodo-guinet
1,298 34 66 33 58 3
Juniata
8,814 61 39 15 40 30
West Branch
18,074 73 27 17

14. Plankton/Drift Density and Taxa Richness
Tributary
Plankton/Drift Density (m-3)
Taxa Richness (mean)
Conestoga 95 11
Conewago
129 18
Swatara 58 17
Conodoguinet 46 14
Juniata 47 13
West Branch 7 10

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 (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>CNS 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. Photo courtesy of Bill Baird
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