Influence des niveaux d’eau sur la distribution et la connectivité des habitats de reproduction du grand brochet. MARIANNE BACHAND, JULIEN HÉNAULT-RICHARD, SYLVAIN MARTIN, JEAN MORIN, ANNE TIMM Section Hydrologie et Écohydraulique Service Météorologique du Canada Environnement Canada, Québec 40e congrès de la Société Québécoise d’Étude Biologique du Comportement Le dimanche 8 novembre 2015
Human structures and fish • Water levels are controlled by dams • Barrier to the movement of fish – By the physical structures – By the changes in water level (dictated by rule curves) • Reproduction habitats of fish can change/disapear according to water level
Integrated response of habitat modeling Physical variables • Water depth • Slope • Wave energy • Etc.
2D Quarter-month time step
Water level series
Topography and bathymétry
Priority Elevation Dataset 1 2 3 4 5 6 7 8 9 10
Harrison Narrow King Williams Narrow Little Vermillion Narrow Namakan Narrow LiDAR terrestrial Canada 2013 Bathymetry USGS 2014 LiDAR TopoBathy Kabetogama LiDAR Minnesota Bathymetry LakeMaster DEM v3 Ontario
Several point /m² Several point /m² Several point /m² Several point /m² Several point /m² 1 point/20 m 1 point/m² 1 point/m² Contour - 1 foot 1 point/ 30m²
Digital elevation model
Bottom slope
Curvature
Ratio of incident light at the bottom
Wave energy(UBOT) Winds at17 km/h, Water level scenario 5 (337.4 m Rainy and 340.1 m Namakan)
Final grid (20 m spacing), 1.7 million points
• • • • • •
Water depth Wave energy Number of cycles Slope Curvature Light
Mean water level (Rainy)
Integrated response of habitat modeling Physical variables • Water depth • Slope • Wave energy • Etc.
HSI DP * CP *VP Three « potentials » – Depth (DP) during the period: • Between 0.15 and 1.50 m: DP = 1.00 • Outside DP = 0,00
– Presence of cattail monotypic stand (CP): • Absence of monotypic cattail : CP = 1,00 • Presence of monotypic cattail : CP = 0,00 The presence of monotypic stand of cattail is given by a 2D habitat model of cattail
– Vegetation type (VP): • • • •
Shrubby swamps and wet meadows: VP = 1,00 Emergent vegetation: VP = 0,50 Submerged vegetation: VP = 0,10 Others : VP = 0,00 The vegetation type is determined by 2D habitat models of wetlands, emergent vegetation and submerged vegetation.
Surface area of suitable habitat for spawning: Measured water level series
Surface area of suitable habitat for spawning: Simulated water level series
Surface area of suitable habitat for spawning: Simulated water level series
Surface area of suitable habitat for spawning: Simulated water level series
Logistic model for the larval habitat 1. Presence/Absence of larvae
2. Interpolation of physical and biological data
232 sites in 2012 (calibration) 318 sites in 2013 (validation)
3. Binomial logistic regression + model selection with AIC
4. Running the equation for all the study area for every year of every water level series
Physical and biological variables of the larval habitat model Regression terms Constant Simple terms Bottom slope Bottom curvature Ratio of incident light at the bottom Water depth Total UBOT during spawning Emergent plant in the previous year High density of submerged vegetation in the previous year
Coefficient (βx) 100.4
Stand. Err.
1.584 6 066 -282.8 -81.06 -243.7 -3.754 -1.773
0.595 3 670 123.8 28.13 120.2 2.638 1.598
43.6
Quadratic terms Ratio of incident light at the bottom 2 Interaction terms Bottom slope * Bottom curvature Bottom slope * Ratio of incident light at the bottom
186.7
81.1
46.30 -2.096
20.03 0.703
Bottom curvature * Ratio of incident light at the bottom
-6 251
3 868
Bottom curvature * Water depth Ratio of incident light at the bottom * Water depth
-3 374 141.4
1 864 50.2
Observed vs predicted presence of larvae
Model evaluation Total classification rate Sensitivity Specificity Kappa (p
