Fish use of turbulence around wood: Habitat variability and selection

Transcription

1 Fish use of turbulence around wood: Habitat variability and selection Ecological and Evolutionary Ethology of Fishes June 25, 2014 Desirée Tullos, Cara Walter, Jason Dunham

2 Restoring wood in rivers large woody debris provides important salmonid habitat (Burnett et. al., 2008). Large wood re-introduction is a popular restoration technique (Nagayama and Nakamura, 2010) Objectives of reintroducing wood into channel include (Brooks et. al., 2006): sediment and wood retention habitat heterogeneity increased hydraulic variability Ryan Couture, ODFW

3 bioenergetics of juvenile salmonids predation avoidance energy expenditure foraging selection of habitat Are fish responding to mean velocities? Or velocity gradients (spatial and temporal)?

4 Drift foraging/habitat models Lots of work on modeling habitat selection for drift foragers >1600 articles in a Google scholar search of drift + foraging + salmon Recent special issue from Env. Biol. of fishes Net Energy Intake (NEI) models Fausch s (1984) NEI model of profitability of foraging positions Hayes et al. s (2007) process-based model of carrying capacity, steady state Railsback et al. s (2009) InSTREAM, an individual based models (IBMs) with some spatial and temporal resolution Limitations (see Piccolo et al. 2014) Spatial variability and detection of drift Hydraulic conditions defined by depth, cover, and steady/uniform 1D velocities

5 The 1D problem 45 velocity (cm/s) Time (s) Growing evidence on the importance of turbulent fluctuations on habitat selection (e.g. Shtaf et al. 1983, Lupandin and Pavlov 1996, Pavlov et al. 2000, Enders et al. 2003; Liao et al. 2003, Smith et al. 2005)

6 so what about flow variability? Objective: relate the behavior of fluids and juvenile salmonids around ELJs to advance understanding on why and how fish use flow fields Where are the fish? What is the hydraulic environment like there? What flow regions are they selecting? And why?

7 Methods: physical model 1:1 scale physical models Full channel jam and root wad outdoor experimental channels at the Oregon Hatchery Research Center (OHRC) Q baseflow =0.045 cms (1.6 cfs) Fr = 0.1; Re = 9 x 10 5 Invertebrates filtered from channels, 70% shade cloth

8 Methods: Fish observations 33 juvenile coho were collected from Fall Creek observed in the experimental channels using three pairs of GoPro cameras Observed for two hour intervals, as individuals and in groups of 5 and 12 Used videos to identify focal point and tail fork coordinates

9 Methods: characterizing fish behavior Videos were rectified and post-processed in VidSync (Neuswanger 2013; Walter et al. 2013) observations and coordinates documented every 20 seconds, total of >1100 fish observations.

10 Methods: flow field characterization Array of four ADVs for 5 minutes at 50 Hz 0.1m x 0.1 m grid + additional, irregularly-spaced measurements 1503 measurement locations; 16.8 M velocity measurements

11 Methods: characterizing fluid behavior fish traffic rule for hydrodynamic cues fish respond to Goodwin 2004 Average velocity: Flow strength (and direction) Variability over space - Flow field distortion (strain) Hydrostatic pressure IPOS: effects of turbulence on swimming performance Lacey et al Variability over time turbulence Intensity (turbulent kinetic energy) Periodicity dominant energy spectra Orientation vectors, vorticity Scale eddy length scales

12 Results: depths

13 Results: resultant velocities Fluid: Velocities low, with highest values within jet and downstream of wood Fish: observed primarily near the bed, both within and adjacent to areas of high velocity a) 0.044m b) 0.129m t a) 0.044m b) 0.129m

14 Results: turbulent kinetic energy Fluid: TKE values are generally low, with concentrated peaks elevated near bed and at slope transitions Fish: most common near the bed in areas of low turbulence intensity a) 0.044m b) 0.129m t

15 Results: hydraulic strain Fluid: Strain values higher near the bed Fish: distributed across range, but most common in low strain a) 0.044m b) 0.129m

16 Ratio of frequency per bin to total Ratio of frequency per bin to total Ratio of frequency per bin to total habitat selection: depth Depth [m] Observed: Group of 5 fish Expected: Group of 5 fish Depth [m] Observed: All fish groups Expected: All fish groups Selected habitat: largest depths available Strength of selection: strong Group size effect: yes Observed: Group of 12 fish Depth [m] Expected: Group of 12 fish

17 Ratio of frequency per bin to total Ratio of frequency per bin to total Ratio of frequency per bin to total habitat selection: velocity Velocity [m/s] 0.4 Observed: Group of 5 fish Expected: Group of 5 fish Velocity [m/s] Observed: All fish groups Expected: All fish groups Selected habitats: near zero, + velocities Strength of selection: weak Group size effect: yes Velocity [m/s] Observed: Group of 12 fish Expected: Group of 12 fish

18 Ratio of frequency per bin to total Ratio of frequency per bin to total Ratio of frequency per bin to total habitat selection: TKE TKE [x 10-2 m2/s2] Observed: All fish groups TKE [x 10-2 m2/s2] Expected: All fish groups Selected habitat: low-moderate turbulence Strength of selection: weak to moderate Group size effect: yes Observed: Group of 5 fish Expected: Group of 5 fish TKE [x 10-2 m2/s2] Observed: Group of 12 fish Expected: Group of 12 fish

19 Ratio of frequency per bin to total Ratio of frequency per bin to total Ratio of frequency per bin to total habitat selection: strain Strain [1/s] Observed: Group of 5 fish Expected: Group of 5 fish Strain [1/s] Observed: All fish groups Expected: All fish groups Selected habitat: low-moderate strain Strength of selection: moderate Group size effect: weak Strain [1/s] Observed: Group of 12 fish Expected: Group of 12 fish

20 Ratio of frequency per bin to total Ratio of frequency per bin to total Ratio of frequency per bin to total Ratio of frequency per bin to total Summary: habitat selection Fish predominantly found in regions of: High depths Low to moderate velocities low turbulence intensity Low-moderate strain Selection strength binary, not relative weak for velocity Weak/moderate for turbulence and strain strong for depth Group size matters for all but strain Depth [m] Velocity [m/s] TKE [x 10-2 m2/s2] Strain [1/s]

21 Implications and limitations Implications Use of 1D velocities in habitat selection models warrants further investigation due to apparently weak selection Depth, 3D temporal variability (TKE), and 3D spatial variability (strain) may be more important in the selection of habitats Limitations Hydraulics and habitat selection will vary with jam type samples of fish observation not independent

22 Lots more to do Investigate how the scale of observation influences the strength of selection. Developing logistical models of dominant variables influencing fish selection Evaluating hypotheses that selection is weakened by: Decreasing spatial resolution of velocity Increasing radius of availability Machine learning: discovering behavioral rules guiding habitat selection around the wood.

23 A request

24 Questions and Acknowledgements This work is funded by NSF award # Jason Dunham for his knowledge, patience, and humor Cara Walter for her incredible work ethic, attention to detail, and nonstop crisis management. We gratefully acknowledge the staff at OHRC for their tireless support and Jin Parisien, Tessa Hanson, Julianne Robinson, Emily Flock, Anna Leitschuh, Randi Mendes & Lisa Thompson for their diligent work and unrelenting enthusiasm. Thanks to Jeremy Monroe and Freshwaters Illustrated for outreach images and videos and relentless questions on relevance.