The rich krill aggregation of the Saguenay - St. Lawrence Marine Park: hydroacoustic and geostatistical biomass estimates, structure, variability, and significance for whales
“…; Simard & Lavoie 1999) is on the order of magnitude of the estimated 4 × 10 5 to 10 6 t found in the estuary and gulf (Runge & Joly 1995). At the boundaries, no organisms were introduced, assuming that the import of euphausiids is negligible, an assumption in agreement with several studies considering the Gulf of St. Lawrence as an exporter of organisms that can greatly influence euphausiid populations as far as the Scotian Shelf and Georges Bank (Herman et al 1991).…”
Section: Methodsmentioning
confidence: 77%
“…Its general estuarine circulation leads to high biological production and high biomass at all trophic levels (Dickie & Trites 1983). In particular, some extensive krill aggregations occur in the gulf (Sameoto 1976, Simard & Lavoie 1999, with average densities of 0.5 to 2.4 g dry weight m -3 and values of up to 50 g dry weight m -2 (Simard et al 1986a, Simard & Lavoie 1999. These aggregations, mainly consisting of Meganyctiphanes norvegica and Thysanoessa raschi (Simard et al 1986a), attract populations of fishes and marine mammals (de Lafontaine et al 1991, Kingsley & Reeves 1998.…”
Persistent high-density krill aggregations make the St. Lawrence Estuary and the Gulf of St. Lawrence important feeding-grounds for large marine mammals. To estimate the effects of the circulation on the seasonal krill distribution, a krill biomass-concentration equation with active vertical migration was coupled to a 3D regional sea ice-ocean circulation model. The results show recurrent spatial patterns of aggregation and advection controlled by the circulation and a high sensitivity to the parameters of the biological model. The time spent in the surface layer is crucial for the retention of organisms in the estuary. The simulated krill aggregation areas are associated with 3 processes (tidal interactions with bathymetry, wind-driven upwelling and mean circulation). Zooplankton generally aggregate near the edges of the Laurentian Channel and other secondary channels, at locations that are consistent with the sparse synoptic information on the distributions of large marine mammals in the gulf. The simulations also indicate that changes in the seasonal circulation significantly affect the krill distribution within the gulf through gyre intensities, the seasonal thermocline and the strength of the estuarine circulation. Finally, the variability of zooplankton transport to the estuary from the gulf appears to be controlled by processes acting on the circulation mode at the mouth of the estuary and estuarine pumping of the krill layer towards the head of the Laurentian Channel. The simulated krill biomass imported into the estuary changed by a factor of 2 over the 3 simulated years.
“…; Simard & Lavoie 1999) is on the order of magnitude of the estimated 4 × 10 5 to 10 6 t found in the estuary and gulf (Runge & Joly 1995). At the boundaries, no organisms were introduced, assuming that the import of euphausiids is negligible, an assumption in agreement with several studies considering the Gulf of St. Lawrence as an exporter of organisms that can greatly influence euphausiid populations as far as the Scotian Shelf and Georges Bank (Herman et al 1991).…”
Section: Methodsmentioning
confidence: 77%
“…Its general estuarine circulation leads to high biological production and high biomass at all trophic levels (Dickie & Trites 1983). In particular, some extensive krill aggregations occur in the gulf (Sameoto 1976, Simard & Lavoie 1999, with average densities of 0.5 to 2.4 g dry weight m -3 and values of up to 50 g dry weight m -2 (Simard et al 1986a, Simard & Lavoie 1999. These aggregations, mainly consisting of Meganyctiphanes norvegica and Thysanoessa raschi (Simard et al 1986a), attract populations of fishes and marine mammals (de Lafontaine et al 1991, Kingsley & Reeves 1998.…”
Persistent high-density krill aggregations make the St. Lawrence Estuary and the Gulf of St. Lawrence important feeding-grounds for large marine mammals. To estimate the effects of the circulation on the seasonal krill distribution, a krill biomass-concentration equation with active vertical migration was coupled to a 3D regional sea ice-ocean circulation model. The results show recurrent spatial patterns of aggregation and advection controlled by the circulation and a high sensitivity to the parameters of the biological model. The time spent in the surface layer is crucial for the retention of organisms in the estuary. The simulated krill aggregation areas are associated with 3 processes (tidal interactions with bathymetry, wind-driven upwelling and mean circulation). Zooplankton generally aggregate near the edges of the Laurentian Channel and other secondary channels, at locations that are consistent with the sparse synoptic information on the distributions of large marine mammals in the gulf. The simulations also indicate that changes in the seasonal circulation significantly affect the krill distribution within the gulf through gyre intensities, the seasonal thermocline and the strength of the estuarine circulation. Finally, the variability of zooplankton transport to the estuary from the gulf appears to be controlled by processes acting on the circulation mode at the mouth of the estuary and estuarine pumping of the krill layer towards the head of the Laurentian Channel. The simulated krill biomass imported into the estuary changed by a factor of 2 over the 3 simulated years.
“…5) and those where recurrent krill aggregations have been observed or predicted to be substantial in eastern Canada. These include several areas along the slope of the Laurentian Channel, the continental shelf edge, and sectors within shelf habitats (depth <100 m) of the SLE and GSL (Simard & Lavoie 1999, Lavoie et al 2000, Sourisseau et al 2006, Plourde et al 2016. The classical depiction of the annual cycle of capital breeding mysticetes involves alternating feast and famine as the animals move from their feeding to breeding areas (Lockyer & Brown 1981, Clapham 1996; although see exceptions in Geijer et al 2016).…”
The blue whale Balaenoptera musculus is a wide-ranging cetacean that can be found in all oceans. In the North Atlantic, little is known about blue whale distribution and genetic structure, or about the interconnections between areas of aggregations in Icelandic waters, the Azores, N orthwest Africa, and the N orthwest Atlantic. Seasonal movements and habitat use of blue whales, including the location of breeding and wintering areas, are also poorly understood. We used satellite telemetry to track movements of 23 blue whales from eastern Canada, providing the first record of the migratory movements and winter destinations of western North Atlantic blue whales. Cabot Strait, the largest outlet connecting the Gulf of St. Lawrence to the Atlantic, was identified as the main corridor for movements in and out of this high-latitude feeding area. The Mid-Atlantic Bight, located off the southeastern USA, was identified as a wintering, and possibly breeding or calving, area. We confirmed the extended use of key summer feeding areas in the St. Lawrence Estuary and northwestern Gulf of St. Lawrence into the fall, and provided evidence for new feeding areas off southern Newfoundland and Nova Scotia. Our results indicate that there is likely a strong connectivity among blue whale areas of concentration at northern latitudes. They also suggest sporadic foraging outside the feeding season, and highlight seamounts and other deep ocean structures as potentially important blue whale habitats. Globally, our study emphasizes the large scale (i.e. many thousands of square kilometers) one needs to consider when addressing the conservation issues faced by blue whale populations.
“…This technology has the ability to measure the underwater orientation of whales and track changes in their behavior over time, which, in some cases, can be corroborated with observations of whales at the surface. Traditional fisheries acoustics provide an accurate means for detecting, quantifying, and continuously documenting changes in the distribution, abundance, and behavior of prey throughout the water column (Misund et al 1995, Simard & Lavoie 1999. Thus, the potential now exists to combine previously unattainable information on the behaviors of cetaceans and their prey in a way that allows for hypothesis-driven experimental research on how the behavior of individual cetaceans relates to that of their prey.…”
Humpback whales Megaptera novaeangliae have adopted unique feeding strategies to take advantage of behavioral changes in their prey. However, logistical constraints have largely limited ecological analyses of these interactions. Our objectives were to (1) link humpback whale feeding behaviors to concurrent measurements of prey using scientific echo-sounders, and (2) quantify how sand lance behavior influences the feeding behaviors and foraging ecology of humpback whales. To measure, in fine detail, the 3-dimensional orientation and movement patterns of humpback whales underwater, we used a multi-sensor tag attached via suction cups (DTAG). We tested the specific hypothesis that the diel movement patterns of sand lance between bottom substrate and the water column correlates to changes between surface and bottom feeding strategies of humpback whales on Stellwagen Bank, MA. We collected over 96 h of both day-and nighttime data from 15 whales in 2006, and recorded 393 surface and 230 bottom feeding events. Individual whales exhibit both surface and bottom feeding behaviors, switching from one to the other in relation to changing light and prey conditions. Surface feeding behaviors were individually variable in their constitution but ubiquitously biased towards daylight hours, when prey was most abundant in the upper portion of the water column. Bottom feeding behavior occurred largely at night, coincident with when sand lance descend to seek refuge in the substrate. Our data provide novel insights into the behavioral ecology of humpback whales and their prey, indicating significant diel patterns in foraging behaviors concurrent with changes in prey behavior.
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