Sato and Benoit-Bird, in their 2024 publication, explore how animals remain in a productive yet highly advective environment in the Northern California Current System using NSF OOI Regional Cabled Array (RCA) and Endurance Array (EA) data from the Oregon Shelf site. They characterized fish biomass using upward-looking active bio-acoustic sonar data from the RCA and interpreted results in consideration of upwelling and downwelling using EA wind data and combined cross-shelf velocity data from the RCA and EA.
Acoustic scatterers, consistent with swim bladder-bearing fish, were only present during the downwelling season as these animals avoided the cold waters associated with strong upwelling conditions in summer and fall. Fish responded to short-term upwelling events by increasing the frequency of diel vertical migration. Throughout the study, their vertical positions corresponded to the depth of minimum cross-shelf transport, providing a mechanism for retention. The observed behavioral response highlights the importance of studying ecological processes at short timescales and the ability of pelagic organisms to control their horizontal distributions through fine-tuned diel vertical migration in response to upwelling.
Time series data provided by the combined EA and RCA data made it possible for Sato and Benoit-Bird to perform consistent statistical analyses of bio-acoustic sonar, wind and ocean velocity data [Figure 22, after Figure 4, Sato and Benoit-Bird (2023)]. The vertical positions of scattering layers relative to the cross-shelf velocities revealed the careful positioning of animals at the depth of minimum onshore- offshore transport. The authors focused on cross-shelf transport, the most significant mechanism affecting population dynamics of pelagic organisms. During strong upwelling periods, cross-shelf velocities were strong near the surface and became nearly zero below 15-m depth. The peak scattering layers were in the upper 20 m of the water column during daytime, but organisms avoided the strong offshore currents at the surface (Figure 22a). At night, the scattering layers expanded their vertical distributions, but avoided the region nearest the bottom where onshore currents were strong (Figure 22b). During downwelling periods, scattering layers were located at the depth of minimal transport during day and night and animals avoided strong onshore currents near the surface and offshore currents near the bottom (Figures 22c and 22d).[media-caption path="https://oceanobservatories.org/wp-content/uploads/2024/02/Science-Highlight-Feb-2024.jpg" link="#"]Figure 22: The influence of upwelling and downwelling on diel vertical migration[/media-caption]
Sato and Benoit-Bird show that animals respond to the risk of offshore advection through active changes in their vertical movement that depend on upwelling conditions at daily time scales. Rapid behavioral response of animals to short-term upwelling events highlights their ability to finely tune their vertical positions relative to physical forcing which ultimately controls their horizontal distributions. This work expands our understanding of the ecological role of diel vertical migration beyond its role as a predator avoidance strategy and reveals a tight coupling between animal behavior and physical forcing.
Vertical profiles of cross-shelf velocities (u; gray, solid lines) and volume backscattering strength (Sv; colors, dotted lines), shown as mean ± standard deviations, during (a, b) strong upwelling periods with diel vertical migration and (c, d) strong downwelling periods without diel vertical migration. Data points qualified for strong upwelling and downwelling periods were selected from the time series over 14 months. Negative values in u indicate offshore transport and positive values indicate onshore transport, and larger Sv values suggest higher density of swim bladdered fish.
Soundscape Ecology Through Use of Automated Acoustic-Based Biodiversity Indices: A Test Using RCA Broadband Hydrophone Data. Adapted by OOI from Ferguson et al., 2023.[media-caption path="https://oceanobservatories.org/wp-content/uploads/2023/07/Screenshot-2023-07-27-at-3.53.41-PM.png" link="#"]Figure a) Location of Regional Cabled Array broadband hydrophones used in this study. b) Acoustic Complexity Index associated with mammal calls, fish sounds, and anthropogenic noise. (After Ferguson et al., 2023).[/media-caption]
Ferguson’s et al., 2003 paper explores the use of myriad biodiversity indices, generated by automated acoustic classifications, using data from three of the Regional Cabled Array (RCA) broadband hydrophones. As the authors point out, human in-the-loop evaluation of marine species and anthropogenic noise from very large data volumes generated by passive acoustic sensors is formidable. Yet, identification of marine organisms and anthropogenic noise is increasingly important for biodiversity conservation and ecosystem monitoring. Automated biodiversity indices have been utilized in terrestrial environments, but only limited studies have used machine learning to study soundscape ecology in marine systems. This study used broadband hydrophone (HYDBBA) data from Slope Base on the Shallow Profiler Mooring (200 m water depth and ~ 100 km offshore), at Oregon Offshore (580 m water depth and ~ 72 km offshore), and the Oregon Shelf site (80 m water depth and ~ 16 km offshore) (Figure 28a) to examine seven diversity indices. Note, these study sites are valuable to making progress in soundscape ecology because the Cascadia Margin is characterized by very high biological productivity impacted by the California current, it is the site of intense shipping lanes, and because of the availability of continuous, real-time acoustic data streams provide by the RCA.
In this initial study, Ferguson et al., evaluated one month of data from the three sites: January 2017 for HYBDDA 103 and 106 and April 2018 for HYBDDA 105. Five minute files were used with 7,101 files for Slope Base, 4,725 files for Oregon Offshore, and 6,410 files for the Oregon Shelf. Data from these instruments had been previously annotated, providing ground truthing for machine learning results. Periods of vocalization of marine mammals occurred less frequently at Slope Base. Three months of data were reviewed to examine periods of mammal vocalizations and anthropogenic sounds.
Identifying the relationship between numerous acoustic indices and species characteristics is complex and requires attention to a significant number of factors and computation of multiple tests, as described in detail in this paper. The Acoustic Complexity Index (ACI, Figure 28b), is generated from an algorithm to quantify biological sounds based on intensity, it is the most commonly used index to assess acoustic indices in marine systems, and has been demonstrated useful in identifying species diversity. Results from this work show that ACI measurements increased during vocalizations by dolphins and sperm whales. However, evaluation of the seven indices show that biodiversity cannot be explicitly determined from any single acoustic index. A significant finding from this study is that true assessment of large-scale ecosystem health and changes in indicator species, which may be due to differences in seasonal and interannual variability, requires co-located physical and chemical oceanographic data. The authors note that the RCA and Endurance Array instrumentation provides “an ideal scenario for accurately monitoring system health”.
Ferguson, E.L., H.M. Clayton, and T. Sakai (2023) Acoustic Indices Respond to Marine Mammal Vocalizations and Sources of Anthropogenic Noise. Frontiers in Marine Science. 10:1025464; doi: 10.3389/fmars.2023.1025464.Read More
The Great Salinity Anomaly of 2015-2020. Adapted by OOI from Biló et al., 2022.[media-caption path="https://oceanobservatories.org/wp-content/uploads/2023/07/Bilo-.png" link="#"]Figure: Time series of salinity anomalies from OSNAP moorings near the Reykjanes Ridge (RR) and within the western boundary current of the Irminger Sea (CF6), and from OOI Flanking Mooring (FLB) in the Irminger Sea (FLB). The eighteen-month low-passed anomalies are averaged between 0 and 200 m depth and computed relative to the mean of the moored data record. Error bars show 95% confidence intervals for annual salinity averages. The blue (red) triangles and diamonds represent the start and end of the freshening period in the CF6 (FLB) records, respectively.[/media-caption]
Unusual surface freshening episodes in the Subpolar North Atlantic have been documented since the 1960s when the term Great Salinity Anomaly (GSA) was coined to refer to the first documented event (Dickson et al., 1988). GSAs are of great importance because the reduction in surface density of North Atlantic surface waters increases vertical stratification, suppresses deep water formation, and weakens the Atlantic Meridional Overturning Circulation (AMOC). Deep (700-1000 m) wintertime convection in the Irminger and Labrador Seas creates the water mass constituting the northern portion of the AMOC’s lower limb, which transports cold water back to southern latitudes. Thus, sustained changes to deep water formation due to a GSA will impact the global climate system.
New work by Bilo et al. (2022) argues that there has been another GSA during 2015-2020, with significant salinity reduction in the upper 200 m of the Iceland Basin and Irminger Sea. The authors use hydrographic data and moored observations to document the spatial extent and propagation pathways of the GSA.
Hydrographic data come from the Argo float monthly climatology and from UK Met Office Hadley Centre “enhanced” version 4 (EN4) historical hydrography. These spatial data sets allow the basin-wide salinity changes to be diagnosed, and show that between 2015 and 2020 the upper 200 m of the central Irminger Sea freshened by 0.1-0.2 PSU. The observed freshening rate of up to 0.04 PSU per year is among the fastest salinity decreases ever recorded in the region. The regional maps show the freshening first in the Iceland Basin and later in the Irminger Sea.
Moored observations come from the Overturning in the Subpolar North Atlantic Program (OSNAP) and from the OOI Irminger Sea Array. Two OSNAP moorings are evaluated, one on the eastern side of the Irminger Sea near the Reykjanes Ridge and one on the western side within the southward-flowing boundary current. OOI Flanking Mooring B was used to represent conditions in the central Irminger Sea. The results (Figure above) show a salinity minimum near the Reykjanes Ridge in 2017 followed by a minimum at the western boundary in 2018 and finally a significant (~0.1 PSU) salinity reduction in the Irminger Sea interior in 2019. Estimated transit times from the mooring data indicate that the salinity signal is advected quickly (months) by Irminger Sea boundary currents after crossing the Reykjanes Ridge and then spreads more slowly to the interior, taking of order two years to impact the central Irminger Sea.
The authors note that although climatologies are important to determine regional changes, these data are mostly limited to deep water. Moorings can provide data within the boundary currents, as well as well-resolved temporal evolution at multiple locations. This underscores the importance of a hybrid ocean observing system combining historical climatologies, broad spatial coverage (Argo), and time series data (OSNAP, OOI).
Biló, T.C., F. Straneo, J. Holte and I. Le Bras, (2022). Arrival of new Great Salinity Anomaly weakens convection in the Irminger Sea. Geophysical Research Letters, 49, e2022GL098857, doi:10.1029/2022GL098857.
Dickson, R.R., J. Meincke, S.-A. Malmberg, and A.J. Lee (1988). The great salinity anomaly in the Northern North Atlantic 1968–1982″. Progress in Oceanography, 20 (2): 103–151, doi:10.1016/0079-6611(88)90049-3.Read More
A Three Stream Ocean Optics Model: Regional Implementation and Validation. Adapted by OOI from Miller M., 2022.[media-caption path="https://oceanobservatories.org/wp-content/uploads/2023/07/EA-science-highlight.png" link="#"](Figure 3.10 from Miller (2022) Top: The black line shows the mean OOI absorption as a function of wavelength for OOI Endurance CSPP Oregon shelf deployment 15 (August – Sept 2019). The gray shading shows the OOI absorption extent between the 20% and 80 % quantiles. The tan shading shows the maximum and minimum extent of OOI absorption. The colored lines correspond to the modeled absorption for different single species approximations. Bottom: Same as top, but for scattering instead of absorption.[/media-caption]
Miles Miller used OOI data as part of this MS thesis awarded September 2022 from the Univ. California, Santa Cruz. The goal of his work was to develop the potential to estimate phytoplankton community structure from remotely sensed optical information and not direct in situ phytoplankton observations. As a step towards this goal, he estimated phytoplankton community structure using spectrally dependent optical absorption and scattering data from an AC-S on the Oregon Shelf profiler. Miller developed linear relationships between modeled phytoplankton absorption and scattering and corresponding observations and solved them by constrained least squares inversion over a field of thirteen wavelengths using six phytoplankton types. He solved the problem for independent absorption and scattering as well as coupled absorption and scattering. He estimated phytoplankton communities as a function of profile depth and for multiple profiles in time.
The model produced accurate downward irradiance fields when using observed absorption and scattering profiles obtained from the Ocean Observatories Initiative’s Oregon Shelf Surface Piercing Profiler Mooring. Through this forward modeling-based comparison to observations it was found that the optical model can produce accurate profiles under certain conditions, making it promising for data assimilation of remote sensing reflectance as a function of wavelength. Miller identified several outstanding issues remaining to be addressed to move from using in situ measured absorption and scattering to estimates from remote sensing reflectance. Because the optical model accuracy is primarily dependent on absorption and scattering, he argued that remote sensing reflectance accuracy can be improved with enhanced phytoplankton community structure and CDOM estimations (see Figure 3.10 from Miller (2022). This figure shows that the modeled phytoplankton light attenuation agrees well with the measurements but that modeled absorption underestimates measurements. This underestimation hints that chromophoric dissolved organic matter (CDOM) is not being properly resolved as CDOM affects only total absorption and not scattering.
Miller, M. (2022). A Three Stream Ocean Optics Model: Regional Implementation and Validation (master’s thesis). University of California, Santa Cruz. 62 pp.Read More
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