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 16901 John M. Campbell Mercyhurst College Erie, Pennsylvania 16546 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

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

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

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

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)

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

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

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

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

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

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)

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

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

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

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

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

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

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)

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

Dam Removal Prioritization for River Herring (4 Factors)

Dam Removal Prioritization for American Shad, Eel, Overall

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

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

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)

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

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

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