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    Average profiles of (left)–(right) temperature T, salinity S, density ρ, buoyancy frequency N, 16-m shear, turbulent kinetic energy dissipation rate ε, and diapycnal eddy diffusivity K (assuming mixing efficiency γ = 0.2) at OSP. The horizontal axes for (middle)–(right) panels are logarithmic.

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    Sample profile time series of 120-kHz acoustic backscatter (grayscale) and turbulent kinetic energy dissipation rate ε (red) from the (top) 6 Jun 2007 dusk and (bottom) 7 Jun 2007 dawn near OSP in the eastern subarctic North Pacific (48°–50°N, 145°W). The red index bar at the bottom of the rightmost profile ranges from log(ε) = −9 to −7 (in W kg−1). This open-ocean site is characterized by (i) thick nonmigrating acoustic backscatter layers at 40–50 m and, to a lesser extent, 110–120 and 170–180 m, and (ii) two migrating backscatter layers that rest below 250-m depth during the day and migrate into the upper 50 m at night with the more intense migrating layer lagging about half an hour at dusk and leading about half an hour at dawn. The acoustic backscatter data also reveals considerable finestructure. Persistent layers of high dissipation rate ε are found in the 40–50-m-depth nonmigrating backscatter layer, which coincides with the seasonal thermocline, and near 100–120 m, coincident with the permanent halocline (Fig. 1). Higher 16-m ADCP shears are found at both these depths.

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    Probability distribution functions of log(ε) at OSP; the station 180 km south is similar. Probability distribution functions in the migrating acoustic backscatter layer (green) and where the acoustics detected no zooplankton (black) are similar, whereas those in the 40–50-m-depth near-surface layer (red) are skewed toward values over an order of magnitude higher.

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    Average profiles of temperature T, salinity S, density ρ, buoyancy frequency N, 16-m shear, turbulent kinetic energy dissipation rate ε, and diapycnal eddy diffusivity K (assuming γ = 0.2) in Saanich Inlet.

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    Sample profile time series of 200-kHz acoustic backscatter (grayscale) and turbulent kinetic energy dissipation rate ε (red) from (top) 9 and 10 Jun 2006 dusks and (bottom) 10 Jun 2006 and 10 May 2007 dawns in Saanich Inlet (48°40′N, 123°30′W). The red index bar at the bottom of the rightmost profile ranges from log(ε) = −9 to −7 (in W kg−1). This coastal inlet is characterized by extremely dense swarms of Euphausia pacifica of up to 104 individuals per cubic meter that migrate from a dense surface layer at night to depths of ∼80 m during the day, although the acoustic backscatter layer often appears more dispersed during the day.

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    Average dissipation rates 〈ε〉 with 95% confidence limits below 30-m depth for 11 dawn and dusk time series collected in Saanich Inlet during 2006–08 binned by high and low acoustic backscattering signal (−67 dB in 2006 and 2007 and −70 dB in 2008, based on the backscattering probability distribution function). Dissipation rates are on average a factor of 2 larger in high acoustic backscattering.

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On Turbulence Production by Swimming Marine Organisms in the Open Ocean and Coastal Waters

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  • 1 SEOS, University of Victoria, Victoria, British Columbia, Canada
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Abstract

Microstructure and acoustic profile time series were collected near Ocean Station P in the eastern subarctic North Pacific and in Saanich Inlet at the south end of Vancouver Island, British Columbia, Canada, to examine production of turbulent dissipation by swimming marine organisms. At Ocean Station P, although a number of zooplankton species are large enough to generate turbulence with Reynolds numbers Re > 1000, biomass densities are typically less than 103 individuals per cubic meter (<0.01% by volume), and turbulent kinetic energy dissipation rates ε were better correlated with 16-m vertical shear than acoustic backscatter layers. In Saanich Inlet, where krill densities are up to 104 individuals per cubic meter (0.1% by volume), no dramatic elevation of dissipation rates ε was associated with dusk and dawn vertical migrations of the acoustic backscatter layer. Dissipation rates are a factor of 2 higher [〈ε〉 = 1.4 × 10−8 W kg−1, corresponding to buoyancy Re = 〈ε〉/(νN2) ∼ 140] in acoustic backscatter layers than in acoustically quiet waters, regardless of whether they are vertically migrating. The O(1 m) thick turbulence patches have vertical wavenumber spectra for microscale shear commensurate with the Nasmyth model turbulence spectrum. However, the turbulence bursts of O(10−5 W kg−1) proposed to occur in such dense swarms appear to be rare. Thus far, intense turbulent bursts have been found infrequently, even in very dense aggregations O(104 individuals per cubic meter) characteristic of coastal and high-latitude environs. Based on sampling to date, this corresponds to a frequency of occurrence of less than 4%, suggesting that turbulence production by the marine biosphere is not efficient.

* Current affiliation: Québec-Océan, Département de Biologie, Université Laval, Quebec City, Quebec, Canada

Corresponding author address: Eric Kunze, SEOS, University of Victoria, P.O. Box 3055, STN CSC, Victoria BC V8W 3P6, Canada. Email: kunze@uvic.ca

Abstract

Microstructure and acoustic profile time series were collected near Ocean Station P in the eastern subarctic North Pacific and in Saanich Inlet at the south end of Vancouver Island, British Columbia, Canada, to examine production of turbulent dissipation by swimming marine organisms. At Ocean Station P, although a number of zooplankton species are large enough to generate turbulence with Reynolds numbers Re > 1000, biomass densities are typically less than 103 individuals per cubic meter (<0.01% by volume), and turbulent kinetic energy dissipation rates ε were better correlated with 16-m vertical shear than acoustic backscatter layers. In Saanich Inlet, where krill densities are up to 104 individuals per cubic meter (0.1% by volume), no dramatic elevation of dissipation rates ε was associated with dusk and dawn vertical migrations of the acoustic backscatter layer. Dissipation rates are a factor of 2 higher [〈ε〉 = 1.4 × 10−8 W kg−1, corresponding to buoyancy Re = 〈ε〉/(νN2) ∼ 140] in acoustic backscatter layers than in acoustically quiet waters, regardless of whether they are vertically migrating. The O(1 m) thick turbulence patches have vertical wavenumber spectra for microscale shear commensurate with the Nasmyth model turbulence spectrum. However, the turbulence bursts of O(10−5 W kg−1) proposed to occur in such dense swarms appear to be rare. Thus far, intense turbulent bursts have been found infrequently, even in very dense aggregations O(104 individuals per cubic meter) characteristic of coastal and high-latitude environs. Based on sampling to date, this corresponds to a frequency of occurrence of less than 4%, suggesting that turbulence production by the marine biosphere is not efficient.

* Current affiliation: Québec-Océan, Département de Biologie, Université Laval, Quebec City, Quebec, Canada

Corresponding author address: Eric Kunze, SEOS, University of Victoria, P.O. Box 3055, STN CSC, Victoria BC V8W 3P6, Canada. Email: kunze@uvic.ca

1. Introduction

Turbulence production in the stratified ocean interior is largely attributed to breaking internal gravity waves generated by (i) atmospheric forcing at the surface and (ii) tidal flow over topography (Munk and Wunsch 1998). While it has long been known that swimming marine organisms produce a turbulent wake (Wiese and Ebina 1995; Yen 2000; Yen et al. 2003; Catton et al. 2008), the research focus has been on the energetic and detection consequences for these organisms (e.g., Enders et al. 2003; Pitchford et al. 2003). Little has been done to quantify the possible impact on ocean turbulence and mixing.

Energetic arguments suggest that significant turbulent dissipation rates might be generated by aggregations of swimming marine organisms. Based on the Reynolds numbers of individual organisms, Huntley and Zhou (2004) predicted turbulent kinetic energy dissipation rates ε ∼ O(10−5 W kg−1) for organisms ranging from 0.5-cm-long zooplankton to cetaceans, a value comparable to that driven by storms in surface waters. Globally, Dewar et al. (2006) estimated that up to 1 TW might be available from swimming marine organisms, assuming 30 Gt of biomass [equivalent to ∼O(0.1%) by volume if distributed over the upper 100 m], comparable to the 2 TW needed for abyssal mixing, 0.8 TW of deep-ocean tidal dissipation (Egbert and Ray 2001), and 1 TW of deep-ocean wind forcing (Wunsch and Ferrari 2004); for comparison, global human power consumption was 15 TW in 2008. Munk (1966) came up with similar numbers for the energy available for biologically generated turbulence by assuming that 20% of biological consumption was used for swimming. Because the bulk of the ocean’s biomass is found in the upper few hundred meters and his primary interest was in abyssal mixing, he did not pursue this thread further. Biologically generated turbulence is unlikely to play a significant role in the meridional thermohaline circulation because of biomass’s intensification toward the surface and coastal zones.

If 1 TW is distributed over the upper 100 m, it implies average turbulent kinetic energy dissipation rates 〈ε〉 ∼ 5 × 10−8 W kg−1 [corresponding to a buoyancy Reynolds number 〈ε〉/(νN2) = 500]. This is well within the detection limit of conventional microstructure profilers (Dewey et al. 1987).

Much of any turbulence generated by swimming marine organisms is likely to occur in the surface boundary layer, which is already well mixed by atmospheric forcing. However, many schooling species exhibit diel vertical migration through stratified waters of the upper pycnocline. During daylight, they evade predation by resting in the dark below 100-m depth, surfacing at nightfall to feed (Forward 1988). Biologically generated turbulence from such diel vertical migratory species could potentially mediate transport of nutrients and dissolved gases between the surface mixed layer and underlying stratified waters where mixing processes are not well understood (Johnston and Rudnick 2009). This could contribute to providing nutrients to maintain biological productivity in the often nutrient-depleted euphotic zone. Assuming an upper-ocean buoyancy frequency N = 10−2 rad s−1 and an upper-bound mixing efficiency γ ∼ 0.2 (Osborn 1980; Oakey 1982), 〈ε〉 ∼ 5 × 10−8 W kg−1 corresponds to diapycnal eddy diffusivities K = γ〈ε〉/N2 ∼ 10−4 m2 s−1. Purely physical mesoscale (McGillicuddy and Robinson 1997; McGillicuddy et al. 1998, 1999) and submesoscale (Mahatavan and Tandon 2006) mechanisms have also been proposed for transporting nutrients into the euphotic zone (Klein and Lapeyre 2009).

Kunze et al. (2006) reported observational evidence for biologically generated turbulence in Saanich Inlet, British Columbia (BC), Canada, a sheltered fjord at the south end of Vancouver Island. During the 28 April 2005 dusk upward migration of an acoustic backscatter layer composed of the krill species Euphausia pacifica with up to 104 individuals per cubic meter (0.1% by volume; De Robertis et al. 2003), they observed a coincident 10–15-min burst of turbulence with dissipation rates of 10−5 to 10−4 W kg−1 between 50- and 100-m depths, consistent with the predictions of Huntley and Zhou (2004). These measurements had microstructure shear spectra that fit the Nasmyth (1970) model turbulence spectra. Buoyancy Reynolds numbers Re = ε/(νN2) = 104 to 105 are high enough that a high turbulent mixing efficiency (γ ∼ 0.2) would be expected. Moreover, they were accompanied by strong temperature-gradient microstructure (though the complicated thermohaline variability in Saanich Inlet precludes quantifying a reliable mixing efficiency) and density overturns on the length scales expected for the observed dissipation rates [LO = (ε/N3)1/2].

Even more anecdotal evidence comes from a single profile collected in a dense aggregation of krill being fed upon by a pod of humpback whales in Soquel Canyon, California, during August 2008, which revealed dissipation rates of 10−6 W kg−1, the highest during the cruise, exceeding dissipation rates found in the near-bottom stratified turbulent layer (Kunze et al. 2010) by an order of magnitude. In contrast, Rippeth et al. (2007) found no elevated turbulence associated with diel migration of the acoustic backscatter layer in 13 dawn and dusk time series from the western continental shelf of the British Isles.

Another issue is how often biologically generated turbulence does any mixing. Measurements by Gregg and Horne (2009) in Monterey Bay fish aggregations exhibited high turbulent kinetic energy dissipation rates, as previously reported by Farmer et al. (1987), but with (i) microscale shear spectra depleted at low wavenumber and (ii) very weak temperature-gradient microstructure χT and hence low mixing efficiency γ = N2χT/(Tz2ε) ≤ 0.0022, where χT is the turbulent temperature variance dissipation rate. On the other hand, Lorke and Probst (2010) inferred mixing efficiencies γ = 0.2 associated with turbulence generated by shoals of perch in Lake Constance but reported dissipation rates ε two orders of magnitude smaller than predicted by either the biomechanical arguments of Huntley and Zhou (2004) or metabolic arguments. Gregg and Horne (2009) suggested that the fish aggregations responsible for their high turbulent dissipation rates created shear too close to the Kolmogorov scale (ν3/ε)1/4O(1 cm) (Tennekes and Lumley 1972), which was then viscously squelched rather than generating broadband turbulence and efficient mixing, an argument consistent with grid-generated turbulence experiments (Itsweire et al. 1986). In contrast, shear-driven turbulence [reduced shear Vz − 2N > 0 (Sun et al. 1998) or, equivalently, gradient Richardson number Ri < 0.25] is generated at the largest (Ozmidov) scales (ε/N3)1/2O(1 m), allowing turbulence to overcome stratification and cascade energy down to Kolmogorov scales through nonlinear interactions, provided LOLK, before being viscously damped.

Although capable of generating turbulence, individual zooplankton and small fish may not be able to mix efficiently because their lengths are comparable to the Kolmogorov length scales. However, the coordinated movement of a dense aggregation might produce turbulence at the thickness of such aggregations with outer (Ozmidov) scales of O(1–10 m) (Kunze et al. 2007; Catton et al. 2008). If so, the density and swimming behavior of such aggregations will be important factors in the generation of turbulent mixing. This parameter space remains unexplored.

Katija and Dabiri (2009) examined the problem of water being dragged with an object moving in a fluid and concluded that this transport may be important regardless of whether turbulence is produced. More thorough analysis of the problem, albeit in the inviscid limit (Thiffeault and Childress 2010), suggests very low induced diffusivities K = 0.27Un4 ∼ 10−6 m2 s−1 associated with krill swarm densities even as high as 104 individuals per cubic meter, where U is the swimming speed, n is the density in individuals per cubic meter, and ℓ is the organism’s length scale. The strong dependence on length scale ℓ in this expression is at odds with Katija and Dabiri’s claims. It suggests that aggregations of larger organisms may be important for mixing. Both of these works ignore the role of molecular diffusion, which will eradicate microscale property differences and reduce net mixing efficiency.

Saanich Inlet has weak background dissipation rates O(10−9 W kg−1) (Gargett et al. 2003; Kunze et al. 2006), corresponding to diffusivities K ≤ 0.02 × 10−4 m2 s−1. If the elevated dissipation rates reported by Kunze et al. (2006) occurred every dusk and dawn, they would dominate mixing in the inlet, raising daily average diffusivities to (4–40) × 10−4 m2 s−1, a factor of 200–2000 higher than the background level. If a 10−5 W kg−1 burst (Huntley and Zhou 2004) were to occur for 20–30 min day−1, daily averaged dissipation rates ε ∼ O(10−6 W kg−1) would be produced. In the open ocean, such a burst needs only to occur every 2–30 days to produce an average diffusivity of 10−4 m2 s−1 and only once every 1–12 months to produce average dissipation rates comparable to those of a Garrett–Munk internal wave field (ε = 5K0N2, where K0 = 0.1 × 10−4 m2 s−1; Garrett 1979; Gregg 1987).

The impact of biologically generated turbulence on ocean mixing will depend on (i) the distribution and density of dense swimming aggregations, (ii) how often and effectively such aggregations generate turbulence, and (iii) the mixing efficiency γ of such turbulence. Their detection will also depend on the strength of turbulence generated by physical processes: for example, wind forcing or nocturnal cooling of the surface mixed layer might mask any biological signal. Dense krill swarms in the open ocean are typically 10–1000 m long and separated by several kilometers (Weber et al. 1986; Nicol 1986; Barrange et al. 1993; Zhou and Dorland 2004), suggesting anywhere from a 1 in 10 to 1 in 1000 chance of sampling (i) in an aggregation. Our Saanich Inlet data were collected in a regime of widespread krill aggregations, so the chance of sampling is O(1). We will focus on the efficacy of turbulence production (ii) in this paper.

To accumulate statistics of biologically generated turbulence and better constrain the occurrence of turbulence production in conjunction with aggregations of swimming marine organisms, an observational program was embarked on to collect more data over a 3-yr period.

2. Data and background

a. Field methods

To examine turbulence generation by swimming zooplankton, microstructure and acoustic backscatter profile time series were collected during the dusk and dawn vertical migrations of acoustic backscatter layers. Six time series were gathered near Ocean Station P (OSP) in the eastern subarctic North Pacific (48°–50°N, 145°W) during 7–11 June 2007 and 11 were gathered in Saanich Inlet, British Columbia (48°40′N, 123°30′W), during May and June of 2006–08. A total of 394 microstructure profiles were collected using a Rockland Scientific tethered freefall vertical profiler (available online at http://www.rocklandscientific.com): 62 near OSP and 332 in Saanich Inlet. The profiler is instrumented with finescale Seabird temperature and conductivity as well as microscale shear, temperature and conductivity sensors. With a fall speed of about 0.6 m s−1, each cast took roughly 20 min near OSP and 6 min in Saanich Inlet.

Simrad EK60 multiple-frequency (only 38-, 120-, and 200-kHz, equivalent to 4-, 1-, and 0.8-cm wavelengths, are used here) acoustic backscatter data are utilized for the OSP datasets while a 200-kHz (0.8-cm wavelength, 12-cm resolution) single-frequency ASL bioacoustics sensor (MacLennan and Simmonds 1992) was used in Saanich Inlet. At OSP, the 120-kHz proved to be most useful for identifying and tracking acoustic backscatter layers. ADCP velocity profiles were also collected at OSP (38-kHz, 16-m resolution) and during the 2008 Saanich Inlet time series (300-kHz, 4-m resolution).

b. Data processing

The turbulent kinetic energy dissipation rate ε = (15/2)νuz2 under the assumption of isotropy, where ν = 10−6 m2 s−1 is the kinematic molecular viscosity and uz is the microscale vertical shear. Where quoted, turbulent eddy diffusivities K = γε/N2 were inferred assuming a mixing efficiency γ = 0.2 following standard microstructure practice (Osborn 1980; Oakey 1982). This might lead to overestimates of K because lower mixing efficiencies are expected for low-Reynolds-number (Re < 200) turbulence (Gargett et al. 1984) and were reported in aggregations of small fish in Monterey Bay (Gregg and Horne 2009). Onboard accelerometers were checked to ensure no contamination of the microscale shear by instrument vibration. After despiking the microscale shear uz to remove particle impacts, vertical wavenumber spectra resembled the Nasmyth (1970) turbulence model spectrum. Despiked shear profiles were broken into half-overlapping 4-m segments, Fourier transformed, then fit iteratively to the Nasmyth (1970) model spectrum (Oakey 1982) over the resolved wavenumber range, which typically lies between but includes neither the (i) Ozmidov (0.1–1 m) nor (ii) Kolmogorov (0.001–0.01 m) length scales. Dissipation rates ε are then based on the shear variance integrated over the Nasmyth model spectrum. This methodology resolves dissipation rates in the range 10−10 < ε < 10−6 W kg−1 with a factor of 2 uncertainty. The 4-m segments do not allow detection of turbulence at the length scale of an individual euphausiid but were used to relate dissipation rate to the presence and movement of O(1 m) thick groups of krill. Temperature microstructure confirmed that strong temperature gradients accompanied strong microscale shear signals. However, the complicated small-scale thermohaline structure of Saanich Inlet precludes accurately quantifying turbulent χT and mixing efficiency γ, so this was not pursued here.

Backscattering intensity is expressed in terms of volume backscattering strength Sv = TS + 10 log10(n), where n is the number of individuals per cubic meter and TS is the individual target strength (Clay and Medwin 1977). Diel biases in acoustic sampling of krill that appear to be due to differences in their orientation while feeding and resting have been reported by Simard and Sourisseau (2009).

c. Ocean Station P site

OSP has been studied for more than 50 yr (Tabata and Weichselbaumer 1992; Mackas et al. 1993; Freeland et al. 1997), starting with data collected by Canadian weatherships from 1956 to 1982 and continuing with the ongoing Institute of Ocean Sciences Line P program (DFO 2009). OSP lies near the confluence of the subpolar and subtropical gyres in one of three high-nitrate, low-chlorophyll regions in the World Ocean (Boyd et al. 1999). Annual primary productivity is about 140 compared to 250–500 gC m−2 yr−1 in BC coastal waters, the highest range corresponding to Saanich Inlet’s typical productivity (Timothy and Soon 2001). As a consequence, the zooplankton biomass, composed primarily of four species of 0.2–0.6-cm copepods (Mackas et al. 1993), is orders of magnitude below that in coastal waters (Goldblatt et al. 1999; Miller et al. 1984; Mackas and Tsuda 1999), with densities up to 103 individuals per cubic meter. None of these four species exhibits strong or consistent diel vertical migration (Mackas et al. 1993). Chaetognaths are the most abundant vertically migratory species (Goldblatt et al. 1999) but are acoustically transparent. Migrating acoustic backscatter layers are dominated by 1.5-cm euphausiids, 0.15-cm pteropods, and 2.8-cm myctophid fish of O(1 individual per cubic meter) (Trevorrow 2005).

d. Saanich Inlet site

A 75–80-m sill at the mouth of Saanich Inlet limits circulation of its deep-basin waters. The inlet is a reverse estuary with its primary sources of freshwater outside the inlet: Cowichan River to the north during winter and the Fraser River freshet during summer (Takahashi et al. 1977; Gargett et al. 2003). Both wind and tidal forcing are weak, so background turbulence dissipation rates are low O(10−9 W kg−1).

In addition to major spring and autumn phytoplankton blooms, smaller blooms occur fortnightly during neap tides throughout the summer (Parsons et al. 1983). Several mechanisms have been proposed for the high primary productivity in Saanich Inlet (∼490 gC m−2 yr−1, Timothy and Soon 2001; Grundle et al. 2009). Parsons et al. suggested intrusions of a strong tidal mixing front near the mouth of the inlet, but these excursions proved not to penetrate far enough into the fjord and Gargett et al. (2003) reported that the surface flow was outward during spring tides. Gargett et al. reported weak surface flow during neaps. They suggested that stronger spring tidal mixing just outside the inlet led to pressure gradients that drove surface waters outward and intermediate waters inward, upwelling the nutrient-rich intermediate waters into the euphotic zone. Given expected lags in the system, this is consistent with primary production peaks every neap; nutrients are stirred throughout the inlet in about a week by a counterclockwise circulation and a tidally generated eddy field (E. Kunze 2010, unpublished manuscript). Because the inlet’s circulation is weak, primary production remains local (Gargett et al. 2003). The spring–neap cycle is unresolved by our sampling. The high primary productivity and low deep-water renewal rate induce seasonally anoxic conditions below 100-m depth (Jaffe et al. 1999).

High primary productivity also supports dense aggregations of 1–2-cm-long Euphausia pacifica with up to 104 individuals per cubic meter (De Robertis 2002; De Robertis et al. 2003; Parsons et al. 1983; Mackie and Mills 1983; Beveridge 2007), one to two orders of magnitude higher than typical open-ocean densities (Greenlaw 1979) and corresponding to 0.1% by volume. We rely on these extensive past measurements to assume that the migrating acoustic backscatter layer is dominated by Euphausia pacifica. This species dominates the diel migrating acoustic backscatter signal (−78 to −71 dB re 1 m), though the layer may also contain less abundant amphipods, ctenophores, copepods, juvenile fish and acoustically transparent chaetognaths. Using the same bioacoustic profiler, Beveridge (2007) inferred higher zooplankton densities near the inlet mouth during spring and summer, in agreement with Parsons et al. (1983) finding a front at the inlet’s mouth. Individual krill swim at speeds up to 19 cm s−1. However, even during vertical migration, their swimming activity tends to be more random and episodic than synchronized (De Robertis et al. 2003). Swimming speeds in Saanich are reduced during daylight, when the acoustic backscatter layer rests just above the ∼100-m-deep oxycline.

3. Results

a. Ocean Station P

During our 6–11 June 2007 sampling, typical summer stratification was observed (Fig. 1; Freeland et al. 1997), with a well-mixed surface layer overlying a seasonal thermocline between 40 and 60 m of buoyancy frequency 2 × 10−2 rad s−1 (period ∼5 min). A remnant winter mixed layer of weaker stratification was observed between 60 and 90 m (Ueno et al. 2007) above the permanent halocline spanning 100–150-m depth (buoyancy frequency 2 × 10−2 rad s−1). Greater depths are characterized by a weaker pycnocline stratified by both temperature and salinity (buoyancy frequency 0.4 × 10−2 rad s−1). ADCP 16-m shear was elevated in both the seasonal thermocline (10−2 s−1) and permanent halocline (0.7 × 10−2 s−1).

A single vertical open 236-μm mesh net tow at the OSP open-ocean site found that four 0.2–0.6-cm-long copepod species and three 0.8–2-cm-long chaetognath species contributed 60% and 20% of the biomass, respectively, in the upper 250 m, consistent with Mackas et al. (1993). Euphausiids were relatively low in abundance, though the 0.56-m diameter of the net may have been too small to sample accurately this species due to net avoidance (Lawson et al. 2008; Zhou et al. 1994). Previous studies at OSP have found abundant euphausiids in summer (Goldblatt et al. 1999).

A nonmigrating 10–25-m-thick acoustic backscatter layer at 50-m depth (Fig. 2) coincided with the seasonal halocline and shallow high-shear (0.8 × 10−2 s−1) layer. Its acoustic signature as a function of frequency was consistent with copepods and euphausiids (Lavery et al. 2007). Based on the volume backscattering strength Sv, copepod abundances are 102 to 103 individuals per cubic meter in the near-surface zooplankton layer, consistent with both our net tows and sampling during May 1996 by Goldblatt et al. (1999).

The 25–90-m-thick migrating layer observed above 300-m depth at OSP also had an acoustic signature consistent with euphausiids and copepods, although less pronounced than in the nonmigrating layer and often consistent with Trevorrow’s (2005) finding of a mixed signal from euphausiids and myctophid fish. Trevorrow (2005) and Marlowe and Miller (1975) inferred 0.03 individuals per cubic meter for myctophids at 15−30-m depth and 1–10 individuals per cubic meter shallower than 100-m depth during night for euphausiids, although the euphausiids may have been undersampled due to net avoidance. Trevorrow (2005) reported pteropods and chaetognaths in this layer as well, although the latter are acoustically transparent.

Species composition at the station 180 km south of OSP differed from that at Station P. Two layers were observed to migrate downward at dawn with similar speeds, one preceding the other by 40 min. The acoustics suggest a greater abundance of the larger myctophids in the earlier denser migrating layer that descends below 250-m depth, whereas smaller euphausiids, copepods, or pteropods likely dominate in the later 25–30-m-thick layer, which rested at 180-m depth during daylight.

The migrating acoustic backscatter layers traveled at 4.4 cm s−1, at the low end of the average 5−10 cm s−1 swimming speeds of individual euphausiids during migration reported by De Robertis et al. (2003). Using Huntley and Zhou’s (2004) equation 1.5 × 105M0.63 < Rec < 6.7 × 105M0.52 with euphausiid mass M = 10−5 kg yields 1600 < Rec < 1700, whereas Re = uL/ν = 800–1700 for 1.7-cm-long euphausiids and 900 for 2–6-cm-long myctophid fish (Trevorrow 2005) swimming at 3 cm s−1 (Baird and Jumper 1995), transitional for generation of turbulence with mixing (Thorpe 2005; Gargett et al. 1984).

Dissipation rates rarely exceed 10−8 W kg−1 (Fig. 2) in our measurements, with background levels of 10−10 W kg−1. Microstructure shear spectra are consistent with the universal Nasmyth (1970) turbulence model spectrum at both short and long wavelengths (λz = 0.02–1 m), in contrast to Gregg and Horne’s (2009) finding turbulent shear spectra depleted at longer turbulent wavelengths within Monterey Bay fish aggregations. With buoyancy Reynolds numbers Re = ε/(νN2) ∼ O(100), lower than those from Huntley and Zhou’s formula, turbulence may not be isotropic and mixing efficiencies may fall below 0.2.

At stratified depths of 60–250 m, dissipation rate distributions were not significantly different inside and outside layers of high acoustic backscatter (Fig. 3), with averages of (1.1 ± 0.9) × 10−9 W kg−1 [Re = 10–100]. In contrast to many measurements in the pycnocline (e.g., Gregg and Sanford 1988), our dissipation rates ε are not proportional to N2, so inferred turbulent diffusivities K were not independent of stratification, perhaps because of the sharpness of the two pycnoclines. In both the migrating acoustic backscatter layer and acoustically quiet waters, the average dissipation rate was at the low end of typical pycnocline values (Moum and Osborn 1986; Gregg 1987; Ledwell et al. 1993).

In the nonmigrating acoustic backscatter layer, which spans 20–60-m depth, including waters inside the surface mixed layer and the high-shear seasonal thermocline, dissipation rates were significantly higher with an average (4 ± 1) × 10−8 W kg−1 [Re ∼ O(100)] at OSP and (4 ± 1) × 10−7 W kg−1 [Re ∼ O(1000)] 180 km south. However, because this is at the base of the surface mixed layer, these values could also be due to atmospheric forcing (Brainerd and Gregg 1993; Hosegood et al. 2008). In both cases, the buoyancy Reynolds numbers are low. In two of the surface-layer acoustic backscatter time series, dissipation rates were distributed identically to those in the deeper waters. These probability distribution functions were not lognormal, pointing to the presence of multiple processes (Gurvich and Yaglom 1967; Yamazaki and Lueck 1990). Mean dissipation rates and 95% confidence limits were therefore calculated using the bootstrap method (Efron and Gong 1983).

The weak turbulence measured at OSP is better correlated with 16-m shear (or gradient Richardson number Ri) than with acoustic backscatter. Dissipation rates ε are better correlated (Spearman p < 0.05, r = 0.3–0.8) with 16-m Ri below 60-m depth than with 120-kHz volume backscattering strength Sv (−0.36 < r < 0.37). The Spearman rank correlation coefficient,
i1520-0485-40-9-2107-eq1
is the nonparametric equivalent of the Pearson correlation coefficient but uses rank order xi and yi rather than numeric values Xi and Yi (Sokal and Rohlf 1981), so it is suitable for variables with non-Gaussian distributions such as dissipation rate. Correlation was higher with both 16-m Ri and volume backscattering (r = 0.5–0.8) if 15–60-m depths were included. However, in the shallow nonmigrating backscatter layer, high shear and high backscatter are collocated, so their impacts cannot be separated.

Given that turbulence dissipation may lag the generation mechanism by as much as one buoyancy period (Tennekes and Lumley 1972), we also performed lagged correlations ranging up to one buoyancy period. Lagged correlations did not have higher values than the unlagged results.

b. Saanich Inlet

Saanich Inlet measurements were collected over 9–11 June 2006, 8–10 May 2007, and 7–9 May 2008. With the exception of two time series in 2007 during flood tide, all time series were collected during slack tide. The buoyancy frequency is 2 × 10−2 rad s−1 in the upper 20–80 m, falling to 10−2 rad s−1 at 80–120-m depth, mostly because of salt stratification (Fig. 4). ADCP 1-m shears were only collected during the May 2008 measurements and were about 0.5 × 10−2 s−1 throughout the water column, although higher shears were sometimes observed near the surface.

Eleven dawn and dusk time series were collected in Saanich Inlet where intense biologically generated turbulence was previously reported in 1 of 2 dusk time series (Kunze et al. 2006). A strong 20–50-m-thick migrating acoustic backscatter layer was present in all Saanich Inlet dawn and dusk time series (Fig. 5), traversing from a 100-m daytime resting depth to the surface at dusk in 60–90 min with migration speeds of 0.7–3.1 cm s−1. The migrating layer sometimes appeared to spread over the entire sampled water column (Fig. 5) and sometimes appeared to abruptly change depth, although this was possibly aliased horizontal variability because of ship drift. During the June 2006 dusks, a second more diffuse layer migrated 20 m below the first. Volume backscattering strength Sv was higher (−40 dB) at the surface during night than during the migration period (−69 to −52 dB), consistent with the organisms orienting vertically while migrating (Simard and Sourisseau 2009), then aggregating densely at the surface. Nonmigrating zooplankton near the surface will also contribute to the acoustic signal and fish may join the aggregation to feed (Greenlaw 1979). Reasons for the slower migration rate in Saanich Inlet compared to OSP are not known. The depth range traversed by the backscatter layer is smaller. As well, most zooplankton species are thought to use light intensity as a proxy for vulnerability to visual predators (Boden and Kampa 1965). Thus, variations in water opacity, cloud cover, sunlight, and lunar cycle may all influence migration rates. This dependence on light intensity is also likely size dependent (De Robertis 2002). Responses to light intensity can be modified by chemical cues from visual predators and food availability (Ringelberg 1995; Forward and Rittschoft 2000).

Individual Euphausia pacifica swim at speeds of 3–19 cm s−1 at 60° to the horizontal to reduce visibility to predators (De Robertis et al. 2003), with the bulk swimming at the low end of the speed range. With lengths of 0.012–0.022 m, this implies Reynolds numbers UL/ν of up to 2400 for individuals (Torres 1984). Using 20–50-m aggregation thicknesses implies Reynolds numbers of 3 × 105, suggesting that krill swarms would generate turbulence much more effectively than individuals. With typical target strength of −79 dB (Trevorrow et al. 2005), we deduce densities of 30–800 individuals per cubic meter in the migrating layer and up to 8000 near the surface at night. However, these results are uncertain as they assume a monospecific euphausiid population, which was not confirmed.

Dissipation rates exceeding 10−6 W kg−1 (Re = 104) were observed in 73 out of 376 profiles (Fig. 5). However, high dissipation rates were observed in acoustically quiet waters as well as in the acoustic backscatter layers, suggesting other sources of turbulence production in the inlet. For dissipation rates exceeding 10−9 W kg−1, (i) the microscale shear spectra match the Nasmyth (1970) model spectra over wavelengths of 0.01–1 m, (ii) microscale temperature-gradient spectra are well resolved over 0.003–3 m, and (iii) resolved microstructure temperature-gradient variance is well correlated with kinetic energy dissipation rates ε, although the complicated finescale water-mass variability in Saanich Inlet precludes reliable estimates of turbulent temperature variance dissipation χT and mixing efficiency γ. Dissipation rates ε of 10−7 W kg−1 (buoyancy Reynolds numbers Re ∼ 103) were frequently observed at depth, whereas values of 10−5 W kg−1 were only found shallower than 20-m depth and may have been generated by surface cooling.

Average turbulent diapycnal diffusivities were about 0.1 × 10−4 m2 s−1 between 20- and 80-m depth and 0.01 × 10−4 m2 s−1 over 80–160-m depth assuming γ = 0.2. For the inferred buoyancy Reynolds numbers below 200, mixing efficiencies γ may be smaller (Gargett et al. 1984). No significant correlation (Spearman coefficient p = 0.71) could be found between dissipation rates ε and 4-m ADCP shear.

Excluding the upper 30 m to remove the influence of nocturnal cooling, average dissipation rates 〈ε〉 are a factor of 2 higher when volume backscattering strength Sv is high in 8 of the 11 time series using threshold Sv of −67 (2006–07) and −70 (2008) dB (Fig. 6). Average dissipation rates are 1.4 × 10−8 W kg−1 [buoyancy Reynolds number Re = ε/(νN2) = 140] in high acoustic backscatter and 0.7 × 10−8 W kg−1 (Re = 70) in acoustically quiet waters. Dissipation rates ε were highest for the June 2006 sampling (time series 1–4) during full moon and slack tide, lowest for May 2007 (time series 5–7) during a third quarter moon, also during slack. The May 2008 sampling (time series 8–11) also had a quarter moon and slack tide. Average volume backscattering strengths Sv were significantly (by 2–12 dB) higher in high dissipation rates in 5 of 11 time series using a threshold ε = 10−8 W kg−1. Spearman coefficients indicated significant positive correlations (p < 0.05) between volume backscattering strength Sv and kinetic energy dissipation rates ε over 30–120-m depth in all but the May 2008 time series.

Mean dissipation rates did not differ significantly between migrating and nonmigrating acoustic backscatter layers, suggesting that nonmigrating krill produce similar turbulence levels as migrating swarms. Lagging up to one buoyancy period in time increased the correlations in five time series but did not change overall results. Migrating and daylight resting layers exhibit the same nonlognormal probability density functions for dissipation rate seen at OSP. The dusk time series collected on 28 April 2005 (Kunze et al. 2006) was the only one exhibiting dramatically higher dissipation rates within the migrating acoustic backscatter layer. No patterns could be discerned in the standard deviations or skewnesses of the probability distribution functions.

During a dusk time series collected during July 2009, there was again no intensified turbulence associated with upward migration of the acoustic backscatter layer. However, earlier in the day, three bursts of 10−6 W kg−1 (Re = 104) appeared in single profiles (separated by less than 6 min) as the ship drifted over the western slope of the inlet. These bursts appeared to be correlated with elevated horizontal and vertical velocity rather than high acoustic backscatter. Similar phenomena may have been responsible for the 28 April 2005 burst (Kunze et al. 2006), although the latter’s duration was 5–7 profiles.

Of five dawn time series collected during August 2006 in California continental margin waters (water depth 1000 m) off Point Sur, only one exhibited evidence for elevated dissipation rates in the upper 50 m. This coincided with the highest acoustic backscatter signal of the cruise.

4. Summary

To obtain statistics of turbulence production by swimming marine organisms, profile time series were collected of acoustic backscatter, finescale vertical shear, and microscale kinetic energy dissipation rates spanning the diel dawn and dusk vertical migration of the acoustic backscatter layer. Six time series were collected near OSP during June 2007, representing the first attempt to look for biologically generated turbulence in the deep open ocean. Eleven time series were collected in Saanich Inlet, a sheltered coastal fjord, during May or June of 2006, 2007, and 2008.

At OSP, turbulent dissipation rates ε were better correlated with 16-m vertical shear or gradient Richardson number (r = 0.4–0.8) than with acoustic volume backscattering strength Sv. Below a nonmigrating layer at 40–50-m depth, average ε was similar inside and outside acoustic backscattering layers. In a nonmigrating backscatter layer, ε was comparably correlated with backscatter and 16-m Ri. Based on the acoustic backscatter strength from three frequencies, we infer zooplankton densities of less than 103 individuals per cubic meter in the nonmigrating backscatter layer, comparable to what is found elsewhere in the open ocean. The migrating backscatter layer was likely composed of euphausiids and myctophid fish. Overall, we conclude that no unambiguous evidence for biologically generated turbulence could be identified near open-ocean site OSP where abundances were orders of magnitude lower than in the coastal ocean. The intermittent occurrence of higher dissipation rates ε seemed best explained by shear-driven turbulence below 60 m and atmospheric forcing in the nonmigrating layer.

In Saanich Inlet, the krill species Euphausia pacifica dominates the acoustic backscatter signal with densities of up to 104 individuals per cubic meter. These are among the densest aggregations in the world, comparable to those found in swarms off Antarctica (Hamner et al. 1983; Zhou and Dorland 2004) and in the Arctic (Siegel 2000). No recurrence of a burst of 10−5 W kg−1 dissipation rate ε (Kunze et al. 2006) was observed in our 11 dawn and dusk time series. Below the surface layer, dissipation rates were elevated by a factor of 2 in acoustic backscattering layers (ε = 1.4 × 10−8 W kg−1, implying K ≤ 0.3 × 10−4 m2 s−1 for N = 10−2 rad s−1 and a mixing efficiency γ ≤ 0.2) compared to acoustically quiet waters.

At both sites, turbulent dissipation rates associated with vertically migrating acoustic backscatter layers were an order of magnitude below predictions (Huntley and Zhou 2004). Thus, turbulence production by the marine biosphere appears to be inefficient, particularly in the deep ocean.

5. Discussion

At the OSP open-ocean site, where zooplankton densities are up to 103 individuals per cubic meter in the nonmigrating surface layer and 1–10 individuals per cubic meter in the migrating layer, no elevated turbulence was identified unambiguously associated with the acoustic backscatter layer. This suggests that the frequency of intense turbulence production by swimming marine organisms in the open ocean is low, although we caution that, based on the statistics outlined in the introduction, sampling with six time series may be inadequate.

In Saanich Inlet, where krill densities are up to 104 individuals per cubic meter (0.1% by volume), events of O(10−5 W kg−1) (Kunze et al. 2006), as predicted by Huntley and Zhou (2004), also occur infrequently (not more than 8% of the time). Because of the spatial heterogeneity of aggregations of swimming marine organisms, biologically generated turbulence is expected to be an intermittent phenomenon. However, the inlet measurements were in laterally broad layers of high acoustic backscatter where, if Huntley and Zhou were correct, turbulence should be expected consistently. Taken together with the findings of (i) Rippeth et al. (2007) of no elevated turbulence in 13 dawn and dusk time series on the western continental shelf of the British Isles, (ii) Lorke and Probst (2010) of dissipation rates associated with shoals of perch two orders of magnitude below the predictions of Huntley and Zhou (2004), and (iii) Gregg and Horne (2009) that dense aggregations of small fish can generate elevated turbulent kinetic dissipation rates ε not accompanied by elevated mixing, our results suggest that intense biologically generated turbulence occurs infrequently and biologically generated turbulent mixing occurs even more rarely. Thus, production of turbulence by the ocean biosphere does not appear to be an effective process in contrast to the energetic arguments (Munk 1966; Huntley and Zhou 2004; Dewar et al. 2006). With measured dissipation rates ε low, the issue of whether the mixing efficiency γ is high (0.2) or low (0.0022; Gregg and Horne 2009) in our data is moot, so it was not examined.

Based on the ∼4% occurrence of turbulence bursts in the limited sampling to date, we suggest that, rather than 1 TW being available for turbulence production by swimming marine organisms (Dewar et al. 2006), turbulence generation by the global marine biosphere may be no more than 0.04 TW (40 GW). Biologically generated turbulence may contribute most of the mixing in locations of weak physically generated turbulence and high biomass concentration such as the Arctic, but these are unlikely to be important for the global ocean.

In light of the very different results of Gregg and Horne (2009) and Lorke and Probst (2010), generation of efficient turbulent mixing by marine organisms may depend on the synchronized behavior of individuals within an aggregation, but the nature of this behavior is poorly known. At high densities, they may engage in synchronized swimming to improve their swimming efficiency and reduce risks of predation (Abrahams and Colgan 1985; Jensen et al. 1998), but only a few studies exist on krill aggregation behavior (Hamner et al. 1983; Jensen et al. 1998). They are thought to respond to the presence of predators, potential mates, and even turbulence. In Saanich Inlet, individual euphausiids swim in bursts punctuated by rests and swim somewhat erratically, even during diel migration (De Robertis et al. 2003).

Given the heterogeneity of dense (104 individuals per cubic meter) aggregations, even in most highly productive coastal and high-latitude waters (Weber et al. 1986; Nicol 1986; Barrange et al. 1993; Zhou and Dorland 2004), and the less than 4% frequency with which they apparently generate intense turbulence, exploring these questions presents a considerable sampling challenge. The shipboard campaign approach taken here is neither cost effective nor efficient. Continuous time series are needed to place a lower bound on the frequency of intense turbulent bursts associated with swimming marine organisms and relate such bursts to swimming behavior.

Acknowledgments

We thank the captains and crews of the MSV John Strickland and CCGS John P. Tully for their assistance. Chris MacKay and Ian Beveridge played critical roles in the data collection, Moira Galbraith analyzed the OSP zooplankton samples, Doug Yelland instructed us in operation of the Tully acoustics, and Marie Robert served as chief scientist. MATLAB routines were used to process data from the EK60 were developed by Richard Towler (NOAA Alaska Fisheries Science Center 2009, personal communication), ADCP by Richard Dewey (University of Victoria 2009, personal communication), and VMP by Kevin Bartlett (University of Victoria 2009, personal communication). Ann Gargett and an anonymous reviewer are thanked for their useful comments on the manuscript. The VENUS observatory program kindly loaned us the ZAP bioacoustic profiler. The Rockland Scientific microstructure instrumentation was purchased with an NSERC CFI grant. Additional support for this work came from NSERC Discovery Grants, an NSERC Shiptime Grant, and ONR Grant N0000140810700.

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Fig. 1.
Fig. 1.

Average profiles of (left)–(right) temperature T, salinity S, density ρ, buoyancy frequency N, 16-m shear, turbulent kinetic energy dissipation rate ε, and diapycnal eddy diffusivity K (assuming mixing efficiency γ = 0.2) at OSP. The horizontal axes for (middle)–(right) panels are logarithmic.

Citation: Journal of Physical Oceanography 40, 9; 10.1175/2010JPO4415.1

Fig. 2.
Fig. 2.

Sample profile time series of 120-kHz acoustic backscatter (grayscale) and turbulent kinetic energy dissipation rate ε (red) from the (top) 6 Jun 2007 dusk and (bottom) 7 Jun 2007 dawn near OSP in the eastern subarctic North Pacific (48°–50°N, 145°W). The red index bar at the bottom of the rightmost profile ranges from log(ε) = −9 to −7 (in W kg−1). This open-ocean site is characterized by (i) thick nonmigrating acoustic backscatter layers at 40–50 m and, to a lesser extent, 110–120 and 170–180 m, and (ii) two migrating backscatter layers that rest below 250-m depth during the day and migrate into the upper 50 m at night with the more intense migrating layer lagging about half an hour at dusk and leading about half an hour at dawn. The acoustic backscatter data also reveals considerable finestructure. Persistent layers of high dissipation rate ε are found in the 40–50-m-depth nonmigrating backscatter layer, which coincides with the seasonal thermocline, and near 100–120 m, coincident with the permanent halocline (Fig. 1). Higher 16-m ADCP shears are found at both these depths.

Citation: Journal of Physical Oceanography 40, 9; 10.1175/2010JPO4415.1

Fig. 3.
Fig. 3.

Probability distribution functions of log(ε) at OSP; the station 180 km south is similar. Probability distribution functions in the migrating acoustic backscatter layer (green) and where the acoustics detected no zooplankton (black) are similar, whereas those in the 40–50-m-depth near-surface layer (red) are skewed toward values over an order of magnitude higher.

Citation: Journal of Physical Oceanography 40, 9; 10.1175/2010JPO4415.1

Fig. 4.
Fig. 4.

Average profiles of temperature T, salinity S, density ρ, buoyancy frequency N, 16-m shear, turbulent kinetic energy dissipation rate ε, and diapycnal eddy diffusivity K (assuming γ = 0.2) in Saanich Inlet.

Citation: Journal of Physical Oceanography 40, 9; 10.1175/2010JPO4415.1

Fig. 5.
Fig. 5.

Sample profile time series of 200-kHz acoustic backscatter (grayscale) and turbulent kinetic energy dissipation rate ε (red) from (top) 9 and 10 Jun 2006 dusks and (bottom) 10 Jun 2006 and 10 May 2007 dawns in Saanich Inlet (48°40′N, 123°30′W). The red index bar at the bottom of the rightmost profile ranges from log(ε) = −9 to −7 (in W kg−1). This coastal inlet is characterized by extremely dense swarms of Euphausia pacifica of up to 104 individuals per cubic meter that migrate from a dense surface layer at night to depths of ∼80 m during the day, although the acoustic backscatter layer often appears more dispersed during the day.

Citation: Journal of Physical Oceanography 40, 9; 10.1175/2010JPO4415.1

Fig. 6.
Fig. 6.

Average dissipation rates 〈ε〉 with 95% confidence limits below 30-m depth for 11 dawn and dusk time series collected in Saanich Inlet during 2006–08 binned by high and low acoustic backscattering signal (−67 dB in 2006 and 2007 and −70 dB in 2008, based on the backscattering probability distribution function). Dissipation rates are on average a factor of 2 larger in high acoustic backscattering.

Citation: Journal of Physical Oceanography 40, 9; 10.1175/2010JPO4415.1

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