A river runs through it How Culverts Disrupt Salmonid Habitat Connectivity in Rivers Normand Bergeron, INRS-Eau Terre et Environnement WHAT WORKS? A WORKSHOP ON WILD ATLANTIC SALMON RECOVERY PROGRAM SEPTEMBER 18-19, 2013
Schlosser s dynamic landscape model of stream fish population ecology and life history Needs to be met in order to complete life cycle 1. Hatch Importance of : 4. Reproduce 2. Grow Habitat heterogenity in providing all habitats necessary for the completion of life-cycle 3. Survive (Schlosser 1991; Schlosser and Angermeier 1995) Fish movement and habitat connectivity in allowing individuals to access these habitats Schlosser et Angermeier (1995)
Obstacles to fish movement Hydroelectric dams Culverts Big, impressive Definetely impassable Smaller, incredibly large number of them Passable?
Effect of culverts on channel hydraulics Culverts are designed to evacuate peak discharge Lower roughness, linear, steeper slope, uniform cross-section Flow velocity increase Water depth decrease Erosion capacity increase Outlet drop and velocity barrier
Effect of culverts on habitat connectivity 5 Lost or reduced access to productive habitats Population isolation and extripation Importance of determining if a culvert is passable or not
How is culvert passability determined? 6 From approaches using fish swimming and jumping capacity data obtained in the laboratory
Ln Temps de fatigue (s) Velocity barrier: how far can a fish swim at a certain speed? 14 12 10 8 6 FL = 6 cm Relation between swim speed and fatigue time in prolonged swim mode (Peake et al., 1997). 4 2 0 Related to fish length and water temperature. 0 2 4 6 8 10 12 Swim speed U s (bl/s) Distance achieved = Groundspeed x Fatigue time
Optimum swim speed maximizes distance achieved 8 Castro-Santos T (2005) J Exp. Biol. 208: 421-432.
Inventory of culvert passability by brook trout in the Saint-Louis River Basin using litterature criteria 9 Use model brook trout of 6, 16 and 26 cm fork length Jumping capacity of 10-15 cm brook trout (Kondratieff and Myrick 2006) Swimming capacity data for brook trout (Peake, 1997) For each culvert: Compute distance achieved if swimming at optimum speed against mean flow velocity in culvert at time of survey Compare predicted distance achieved to culvert length
Large proportion of impassable culverts Criteria Passable Impassable n Hanging culvert 40 (58%) 29 (42%) 69 Velocity barrier Lf 6 cm 17 (30%) 40 (70%) 57 Lf 16 cm 35 (61%) 22 (39%) 57 Lf 26 cm 48 (84%) 9 (16%) 57 Gibson et al. (2005) : 53% of studied culverts on Trans Labrador Highway were limiting juvenile salmon passage success Langill et Zamora (2002): 58% of culverts studied in Nova-Scotia were barrier to salmonids Very few field validations of predictions
Observed vs predicted brook trout passage success in natural culverts Goerig E. (Ph.D student), Bergeron N. and Castro-Santos T. Measure of fish passage attempts, swim speed, maximum distance of ascent and passage success using PIT antennas inside culverts Photos Elsa Goerig
Study sites: 13 culverts of southern Québec Range of culvert characteristics: Rough corrugated and smooth concrete and plastic Slopes from 0,3 to 4,5% Length from 9 to 45 m. Range of hydraulic conditions: mean flow velocities from 0.4 to 2 m/s flow depth from 0.03 to 0.46 m Stream water temperatures from 1.4 to 18ºC
Fish passage attempts, progression and success monitored with four PIT antennas inside culvert. Modified from Cahoon et al. (2004) 23 mm half-duplex PIT-tags (Texas Instrument)
Semi-experimental approach Fish passage trials conducted at various discharges and water temperatures For each trial, a group of 24 PITtagged brook trout was released for 48h in a cage fixed at culvert outlet 3 size groups (F l ) Small: 90 à 119 mm Medium: 120-149 mm Large: 150-230 mm (E. Goerig, 2009)
Two complementary approaches 1. Semi-experimental 48h trials with a cage fixed downstream of the culvert 2. «Free conditions» 72h trials with no cage Fish released downstream (E. Goerig, 2009) N = 1090 fish of 90-230 mm in 50 trials
Observed vs predicted : passage success Passage Success (%) All Rough culvert Smooth culvert Observed 45 50 41 Predicted 28 28 28 N= 958 fish. 493 (51%) did at least one attempt Predictive model underestimates passage success How good is the model at predicting the possible outcomes of an attempt? In what situations does it perform better or worst?
Prédictions Prédictions Observed vs predicted : effect of culvert type Corrugated metal culverts Observations Correct classification rate (CCR): 50 % Misclassifications Underpredict : 72% Overpredict : 28% Smooth concrete culverts Observations Correct classification rate (CCR) : 73 % Misclassifications Underpredict : 73% Overpredict : 27%
Effect of fish size Fish length (FL =mm) n CCR (%) TP (%) TN (%) FP (%) overpredict FN (%) underpredict Small (90-119 ) 176 63 87 13 5 95 Medium (120-149) 197 59 73 27 30 70 Large (150 +) 126 63 49 51 57 43
Laboratory fish swimming capacity data do not transfer well in natural field situations Photo by Elsa Goerig Different swimming behaviour in nature: sequence of burst swim / glide Small fish use corrugations for resting : not possible for larger fish Small fish better at using near-wall lower velocity zones
Riverscape genetics of rivière St-Louis Torterotot (MSc student), Perrier, Bernatchez, Bergeron 23 22 25 4 clusters génétiques (BAPS) 19 24 17 16 18 20 21 11 14 15 12 13 Ponceau obstrué 10 9 6 7 3 4 5 8 2 1 Chutes naturelles 20
Effect of culverts on genetic richness and structure Richness (A) AR Structure (B) Pairwise F ST β P-value β P-value Intercept 12.0121 < 0.0001 0.0174 0.0998 Elevation -0.0096 < 0.0001-0.0001 0.1300 Culverts -0.2298 0.0765 0.0090 0.0150 River distance - - 0.0010 0.0010 Waterfalls - - 0.0091 0.0900
Culvert replacement: rough to smooth Elsa Goerig (INRS) 2011
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