Southern resident killer whales encounter higher prey densities than northern resident killer whales during summer

The decline of southern resident killer whales (Orcinus orca) may be due to a shortage of prey, but there is little data to test this hypothesis. We compared the availability of prey (Chinook salmon, Oncorhynchus tshawytscha) sought by southern residents in Juan de Fuca Strait during summer with the abundance and distribution of Chinook available to the much larger and growing population of northern resident killer whales feeding in Johnstone Strait. We used ship-based multifrequency echosounders to identify differences in prey fields that may explain the dynamics of these two killer whale populations. Contrary to expectations, we found that both killer whale habitats had patchy distributions of prey that did not differ in their frequencies of occurrence, nor in the size compositions of individual fish. However, the density of fish within each patch was 4–6 times higher in the southern resident killer whale habitat. These findings do not support the hypothesis that southern resident killer whales are experiencing a prey shortage in the Salish Sea during summer and suggest a combination of other factors is affecting overall foraging success.

A clustering approach to determine biophysical provinces and physical drivers of productivity dynamics in a complex coastal sea

The balance between ocean mixing and stratification influences primary productivity through light limitation and nutrient supply in the euphotic ocean. Here, we apply a hierarchical clustering algorithm (Ward's method) to four factors relating to stratification and depth-integrated phytoplankton biomass extracted from a biophysical regional ocean model of the Salish Sea to assess spatial co-occurrence. Running the clustering algorithm on four years of model output, we identify distinct regions of the model domain that exhibit contrasting wind and freshwater input dynamics, as well as regions of varying watercolumn-averaged vertical eddy diffusivity and halocline depth regimes. The spatial regionalizations in physical variables are similar in all four analyzed years. We also find distinct interannually consistent biological zones. In the Northern Strait of Georgia and Juan de Fuca Strait, a deeper winter halocline and episodic summer mixing coincide with higher summer diatom abundance, while in the Fraser River stratified Central Strait of Georgia, shallower haloclines and stronger summer stratification coincide with summer flagellate abundance. Cluster based model results and evaluation suggest that the Juan de Fuca Strait supports more biomass than previously thought. Our approach elucidates probable physical mechanisms controlling phytoplankton abundance and composition. It also demonstrates a simple, powerful technique for finding structure in large datasets and determining boundaries of biophysical provinces.

Clustering coupled biochemical-physical model results formalizes regional provinces in a coastal region

<p>Coastal regions by their very nature are dynamically diverse.  Within one geographical region there are often multiple areas dominated by substantially different dynamics that shape not only the physical characteristics but also the ecosystem.  The Salish Sea, in the northeast Pacific, is an excellent example with strongly tidally mixed regions, freshwater-dominated regions, and regions directly influenced by the open ocean.  These regions are generally well known and multiple disciplines refer to them with various boundaries and under various names.  Here we use unsupervised clustering on numerical model results to formalize these regional provinces.  The model is SalishSeaCast,  a three-dimensional real-time coupled bio-chem-physical model based on the NEMO framework.  We find that the regions clustered on ecosystem variables (phytoplankton biomass) spatially coincide with those clustered on physical variables, particularly the stratification as diagnosed by the halocline depth.  The clusters are robust across years with interannual variability manifesting mostly in changes in the size of the clusters.  As the clusters are dynamically distinct, they provide a natural framework on which to evaluate the model against observations.  We find that the model accurately simulates each of the major clusters.  The spatial and temporal resolution of the model can then characterize these different clusters more systematically than the observations, revealing biases associated with sparse sampling in the observations. Two examples will be given, one addressing a long-standing issue of the productivity gradient in the stratified main basin, the Strait of Georgia, and another concerning the seasonal cycle of productivity in the ocean-influenced Juan de Fuca Strait.</p>

Fourier Representation of Quadratic Friction

If a current is composed of a number of constituents with different frequencies, then quadratic friction may be analyzed at the same frequencies. The ratios of the constituents of the friction differ from the ratios for the current itself, with a classic result being that for unidirectional flow a very weak current constituent experiences proportionately 50% more friction than a strong constituent. Here, exact results for the magnitude of the friction constituents are derived and confirmed numerically. The results are applied to the tidal currents in Juan de Fuca Strait and the Strait of Georgia, showing that minor constituents experience proportionately more friction than the main constituent by an amount that varies spatially but is typically less than the classic result of 50%. For two-dimensional currents it is shown that, if there are two current constituents with the same ellipticity and major axis direction, the friction coefficients are separable functions of the current constituent ratio and the ellipticity. Some results are derived for two constituents with different ellipticity and major axis direction. For the case of two constituents with rectilinear but misaligned currents, each constituent experiences friction inclined at an angle to its current. Last, the effect of a tidal current on the bottom friction experienced by a steady flow is investigated for arbitrary relative magnitudes and directions of the tide and steady flow. In particular, the inclination of the mean friction to the mean flow is quantified.

Lateral Reynolds Stress and Eddy Viscosity in a Coastal Strait

The lateral Reynolds stress uυ, representing the transfer of along-strait momentum toward the sides of Juan de Fuca Strait, is measured with an array of ADCPs. The contributions to the stress from a number of frequency bands are analyzed to highlight the roles of different processes. Motion in a frequency band that includes internal waves and Doppler-shifted subinertial eddies gives a Reynolds stress that, when scaled by the observed shear, is consistent with an eddy viscosity of O(10 m2 s−1). This viscosity acts on the tides and the estuarine flow. The tides can also impart a viscous stress upon the low-frequency estuarine flow. These tidal currents, although strong, are largely nondivergent within the area of the array and thus appear to be less important for the cross-strait transfer of momentum. The long-term mean estuarine circulation can be acted upon by meanders of the estuarine flow, defined as features with periods of 3–5 days. These meanders are found to also have a horizontal eddy viscosity of O(10 m2 s−1). The measured Reynolds stress divergences are consistent with both the strongly curved profile of the estuarine mean flow and also the more slablike tidal current profile. This paper represents the first direct calculation of eddy viscosity on the medium-sized scale of the array, O(1 km).