PURPOSE:In this study, we examined the structure and function of the Southampton Island marine food web across 149 species of benthic and pelagic invertebrates, fishes, marine mammals and seabirds collected from 2016 to 2019, to provide a baseline for future studies that aim to quantify temporal changes in food web structuring. More specifically,we used a multi-biomarker approach combining stable isotopes and HBIs to: (i) determine the vertical trophic structure of the marine food web, (ii) investigate the contribution of benthic and pelagic-derived prey to the higher trophic level species of the Arctic food web, and (iii) determine the role of ice algae and phytoplankton carbon source use across different trophic levels and compartments (pelagic and benthic). By shedding new light on the functioning of the Southampton Island food web and specifically how the contribution of ice algae and benthic habitat shapes its structure, these results will be relevant to adaptive management and conservation initiatives implemented in response to anthropogenic stressors and climate change. DESCRIPTION:Climate-driven alterations of the marine environment are most rapid in Arctic and subarctic regions, including Hudson Bay in northern Canada, where declining sea ice, warming surface waters and ocean acidification are occurring at alarming rates. These changes are altering primary production patterns that will ultimately cascade up through the food web. Here, we investigated (i) the vertical trophic structure of the Southampton Island marine ecosystem in northern Hudson Bay, (ii) the contribution of benthic and pelagic-derived prey to the higher trophic level species, and (iii) the relative contribution of ice algae and phytoplankton derived carbon in sustaining this ecosystem. For this purpose, we measured bulk stable carbon, nitrogen and sulfur isotope ratios as well as highly branched isoprenoids in samples belonging to 149 taxa, including invertebrates, fishes, seabirds and marine mammals. We found that the benthic invertebrates occupied 4 trophic levels and that the overall trophic system went up to an average trophic position of 4.8. The average δ34S signature of pelagic organisms indicated that they exploit both benthic and pelagic food sources, suggesting there are many interconnections between these compartments in this coastal area. The relatively high sympagic carbon dependence of Arctic marine mammals (53.3 ± 22.2 %) through their consumption of benthic invertebrate prey, confirms the important role of the benthic subweb for sustaining higher trophic level consumers in the coastal pelagic environment. Therefore, a potential decrease in the productivity of ice algae could lead to a profound alteration of the benthic food web and a cascading effect on this Arctic ecosystem.Collaborators:Centre for Earth Observation Science, University of Manitoba, Winnipeg, Manitoba, Canada - R´emi Amiraux, C.J. Mundy, Jens K. Ehn, Z.A. Kuzyk.Quebec-Ocean, Sentinel North and Takuvik, Biology Department, Laval University, Quebec, Quebec, Canada - Marie Pierrejean.Scottish Association for Marine Science, Oban, UK - Thomas A. Brown.Department of Natural Resource Sciences, McGill University, Ste. Anne de Bellevue, Quebec, Canada - Kyle H. Elliott.Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada - Steven H. Ferguson, Cory J.D. Matthews, Cortney A. Watt, David J. Yurkowski.School of the Environment, University of Windsor, Windsor, Ontario, Canada - Aaron T. Fisk.Science and Technology Branch, Environment and Climate Change Canada, Ottawa, Ontario, Canada - Grant Gilchrist.College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Fairbanks, AK, USA - Katrin Iken.Department of Earth Sciences, University of New Brunswick, Fredericton, NB, Canada - Audrey Limoges.Department of Integrative Biology, University of Windsor, Windsor, Ontario, Canada - Oliver P. Love, Wesley R. Ogloff.Department of Arctic Biology, The University Centre in Svalbard, Longyearbyen, Norway - Janne E. Søreide.

Bay-scale empirical demonstrations of how bivalve aquaculture alters plankton composition, and subsequently ecological functioning and higher trophic levels, are lacking. Temporal, inter- and within-bay variation in hydrodynamic, environmental, and aquaculture pressure limit efficient plankton monitoring design to detect bay-scale changes and inform aquaculture ecosystem interactions. Here, we used flow cytometry to investigate spatio-temporal variations in bacteria and phytoplankton (< 20 µm) composition in four bivalve aquaculture embayments. We observed higher abundances of bacteria and phytoplankton in shallow embayments that experienced greater freshwater and nutrient inputs. Depleted nutrient conditions may have led to the dominance of picophytoplankton cells, which showed strong within-bay variation as a function of riverine vs freshwater influence and nutrient availability. Although environmental forcings appeared to be a strong driver of spatio-temporal trends, results showed that bivalve aquaculture may reduce near-lease phytoplankton abundance and favor bacterial growth. We discuss aquaculture pathways of effects such as grazing, benthic-pelagic coupling processes, and microbial biogeochemical cycling. Conclusions provide guidance on optimal sampling considerations using flow cytometry in aquaculture sites based on embayment geomorphology and hydrodynamics.Cite this data as: Sharpe H, Lacoursière-Roussel A, Barrell J (2024). Monitoring bay-scale bivalve aquaculture ecosystem interactions using flow cytometry. Version 1.2. Fisheries and Oceans Canada. Samplingevent dataset. https://ipt.iobis.org/obiscanada/resource?r=monitoring_bay-scale_bivalve_aquaculture_ecosystem_interactions_using_flow_cytometry&v=1.2

PURPOSE:This Archer fiord data is associated with a larger program ArcticCORE, which was created to fulfill knowledge gaps and develop long term protection in the extremely remote Tuvaijuittuq region. The main objectives of this expedition were to improve our comprehension of the key drivers for productive capacity, diversity and ecosystem structure in areas connected to Baffin Bay and Tuvaijuittuq, including Archer fiord.DESCRIPTION:ArcticCORE is a 5-year broader program aiming to characterize Tuvaijuittuq’s unique ecosystem and its influence and connectivity with the adjacent ecosystems to inform sustainable management and conservation initiatives in Tuvaijuittuq and the eastern Arctic. In an Arctic Ocean with rapidly declining sea ice, Tuvaijuittuq area retains the oldest and thickest sea ice, and can act as a refuge for ice-dependent species. This program aims to characterize the Arctic marine ecosystem and establish baseline measurements for future comparisons in the region. From 2023, water collection was carried out at four stations throughout Archer Fiord and analyzed for primary productivity, chlorophyll a, phytoplankton flow cytometry and phytoplankton taxonomy down to the lowest identifiable level. These data will contribute to a better understanding of the key drivers for productive capacity, diversity and ecosystem structure in Archer fiord. Characterization of these upstream areas are relevant for an ecosystem-based approach to fisheries management in Baffin Bay, a priority for DFO and an intrinsic part of mandated activities, as they influence the ecosystem and fisheries resources downstream.

Pepin et al. (2014) stated that three nested spatial scales were identified as relevant for the development of ecosystem summaries and management plans: Bioregion, Ecosystem Production Unit (EPU), and Ecoregion. A bioregion is composed by one or more EPUs, while an EPU consists of a combination of ecoregions, which represent elements with different physical and biological characteristics based on the analytical criteria applied. Pepin et al. (2014) reported on the consolidation of data and analyses of ecoregion structure for the continental shelf areas from the Labrador Sea to the mid-Atlantic Bight and provided recommendations on the definition of EPUs in the NAFO Convention Area. The results of two K-means clustering analyses (one geographically constrained and one un-constrained) and expert knowledge (including and considering location of ecoregions, knowledge of the distribution of major marine resources and fish stocks, and geographic proximity for delineation/definition of potential management units) served as guides for evaluation by NAFO’s (North Atlantic Fisheries Organization) working group on ecosystem science and assessments (WG-ESA). The final consensus from the discussions identified eight (8) major EPUs that can serve as practical candidate management units (from the 50 m isobaths, where research vessel data were available, seaward to the 1500 m isobaths) that consist of the Labrador Shelf (NAFO subareas 2GH), the northeast Newfoundland Shelf (subareas 2J3K), the Grand Banks (subareas 3LNO), Flemish Cap (subarea 3M), the Scotian Shelf (subareas 4VnsWX), Georges Bank (parts of subareas 5Ze and 5Zw), the Gulf of Maine (subarea 5Y and part of 5Ze) and the mid-Atlantic Bight (part of subarea 5Zw and subareas 6ABC). Southern Newfoundland (subarea 3Ps) was not included in the original analysis because fall survey data were unavailable. However, it was later added as an EPU after additional analysis of the fish community structure and trends using survey data from the spring, which indicated that this area is heavily influenced by the surrounding EPUs (NAFO 2015).The proposed candidate management units correspond to the EPUs that define major areas within the bioregions which contain a reasonably well defined food web/production system. The working group noted that the consensus solution represents a compromise that aims to define management units based on the boundaries of existing NAFO subareas that are appropriate for estimation of ecosystem and fishery production. References: NAFO. 2015. Report of the 8th Meeting of the NAFO Scientific Council (SC) Working Group on Ecosystem Science and Assessment (WGESA). 17-26 November 2015, Dartmouth, Canada. NAFO SCS Doc. 15/19.Pepin, P., Higdon, J., Koen-Alonso, M., Fogarty, M., and N. Ollerhead. 2014. Application of ecoregion analysis to the identification of Ecosystem Production Units (EPUs) in the NAFO Convention Area. NAFO SCR Doc. 14/069.

Identification of ecological and biological significant areas (EBSA) in the Estuary and the Gulf of St. Lawrence according to six groups of the food chain : primary production (Lavoie et al, 2007), secondary production (Plourde et McQuinn, 2010), meroplankton (Ouellet, 2007), benthic invertebrates (Chabot et al, 2007), demersal fishes (Castonguay et Valois, 2007) and pelagic fishes (McQuinn et al, 2012). The distribution area of each group has been evaluated using five criteria in order to determine the EBSA (DFO, 2004):1. Uniqueness: Ranked from areas whose characteristics are unique, rare, distinct, and for which alternatives do not exist to areas whose characteristics are widespread with many areas which are similar.2. Aggregation: Ranked from areas where most individuals of a species are aggregated to areas where individuals of the species are widespread3. Fitness consequence: Ranked from areas where the life history activity(ies) undertaken make a major contribution to the fitness of the population or species present to areas where the life history activity(ies) undertaken make only marginal contributions to fitness.4. Resilience: Ranked from areas where the habitat structures or species are highly sensitive, easily perturbed, and slow to recover to areas where the habitat structures or species are robust, resistant to perturbation, or readily return to the pre-perturbation state.5. Naturalness: Ranked from areas which are pristine and characterized by native species to areas which are highly perturbed by anthropogenic activities and/or with high abundances of introduced or cultured species.Castonguay, M. and Valois, S. 2007. Zones d’importance écologique et biologique pour les poissons démersaux dans le nord du Golfe du Saint-Laurent. DFO Can. Sci. Advis. Sec. Res. Doc. 2007/014. iii + 34 p.Chabot, D., Rondeau A., Sainte-Marie B., Savard L., Surette T. et Archambault P. 2007. Distribution des invertébrés benthiques dans l’estuaire et le golfe du Saint-Laurent. DFO Can. Sci. Advis. Sec. Res. Doc. 2007/018. iii + 118 p.DFO, 2004. Identification of Ecologically and Biologically Significant Areas. DFO Can. Sci. Advis. Sec. Ecosystem Status Rep. 2004/006. Lavoie, D., Starr, M., Zakardjian, B. and Larouche, P. 2007. Identification of ecologically and biologically significant areas (EBSA) in the Estuary and Gulf of St. Lawrence: Primary production. DFO Can. Sci. Advis. Sec. Res. Doc. 2007/079. iii + 29 p. McQuinn, I.H., Bourassa, M-N., Tournois, C., Grégoire, F., and Baril, D. 2012. Ecologically and biologically significant areas in the Estuary and Gulf of St. Lawrence: small pelagic fishes. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/087. iii + 76 p.Ouellet P. 2007. Contribution à l’identification de zones d’importance écologique et biologique (ZIEB) pour l’estuaire et le golfe du Saint-Laurent : La couche des oeufs et des larves de poissons et de crustacés décapodes. DFO Can. Sci. Advis. Sec. Res. Doc. 2007/011. iii + 76 p. (Mise à jour novembre 2010)Plourde, S. et McQuinn, I.A. 2010. Zones d’importance écologique et biologique dans le golfe du Saint-Laurent : zooplancton et production secondaire. DFO Can. Sci. Advis. Sec. Res. Doc. 2009/104. iv + 27 p.

Fisheries and Oceans Canada (DFO) has been conducting surface water trawl surveys since 1992 in the coastal waters of British Columbia, Washington, Oregon and Alaska and in the high seas of the Gulf of Alaska. These surveys initially focused on determining the migratory patterns (1992-2002) and on the growth and physiology (2003-2016) of juvenile Pacific Salmon. Since 2016, these surveys have been broadened to monitor the whole pelagic ecosystem, retaining a focus on juvenile Pacific Salmon. Data were collected from sites in the inland sea waters of British Columbia and Washington State, USA, that comprise the Strait of Georgia, Strait of Juan de Fuca and Puget Sound since 2001 and are ongoing.

The objective of this project was to locate the mixing zones in the coastal environment on the north shore of the lower estuary, which are caused by the friction of the waters on the bottom and measure the effects of these mixing zones on the modification of the water bodies and the productivity potential of adjacent areas, using phytoplankton biomass and size structure as an indicator of productivity. Temperature and salinity profiles were measured using CTD and water sampling was done with a Niskin bottle to try to detect the signature of the mixture and to determine if nutrient salts and/or productivity are greater in adjacent areas.Sampling took place in 3 outings from 3 stations organized in a 100 NN transect which were carried out at the start of the season (June 30), mid-season (August 16) and end of the season (October 9). The transects were each composed of three stations ranging from 10 m depth near the coast to 50 and 75 m, depending on the transect, moving away from the coast. Samples were collected for nutrients and phytoplankton biomass (> 0.7 µm and > 5 µm) analysis at depths of 1, 10, 25 and 50 m. The optical transparency of water was also measured by Secchi disk. The first file provided “donnees_profils_data” is a summary of the CTD profils of every station. The second file “donnees_discretes_discret_data” contains the results of the water sample analysis. The file “Identification_station_identification” describe the repartition of consecutives among stations.This project was funded by DFO Coastal Environmental Baseline Program under Canada’s Oceans Protection Plan. This initiative aims to acquire environmental baseline data contributing to the characterization of important coastal areas and to support evidence-based assessments and management decisions for preserving marine ecosystems.

Fisheries and Oceans Canada (DFO) has been conducting surface water trawl surveys since 1992 in the coastal waters of British Columbia, Washington, Oregon and Alaska and in the high seas of the Gulf of Alaska. These surveys initially focused on determining the migratory patterns (1992-2002) and on the growth and physiology (2003-2016) of juvenile Pacific Salmon. Since 2016, these surveys have been broadened to monitor the whole pelagic ecosystem, retaining a focus on juvenile Pacific Salmon. Surveys have been conducted on the continental shelf of north and west Vancouver Island, included associated sounds and inlets since 1992 and are ongoing. These data are for tows conducted in the continental shelf area for depths shallower than 400 meters.

Bivalve aquaculture has direct and indirect effects on plankton communities, which are highly sensitive to short-term (seasonal, interannual) and long-term climate changes, although how these dynamics alter aquaculture ecosystem interactions is poorly understood. Here, we investigate seasonal patterns in plankton abundance and community structure spanning several size fractions from 0.2 µm up to 5 mm, in a deep aquaculture embayment in northeast Newfoundland, Canada. Using flow cytometry and FlowCam imaging, we observed a clear seasonal relationship between fraction sizes driven by water column stratification (freshwater input, nutrient availability, light availability, water temperature). Plankton abundance decreased proportionally with increasing size fraction, aligning with size spectra theory. Within the bay, greater mesozooplankton abundance, and a greater relative abundance of copepods, was observed closest to the aquaculture lease. No significant spatial effect was observed for phytoplankton composition. While the months of August to October showed statistically similar plankton composition and size spectra slopes (i.e., food chain efficiency) and could be used for interannual variability comparisons of plankton composition, sampling for longer periods could capture long-term phenological shifts in plankton abundance and composition related to various processes, including climate change. Conclusions provide guidance on optimal sampling to monitor and assess aquaculture pathways of effects.Cite this data as: Sharpe H, Lacoursière-Roussel A, Gallardi D (2024). Ecological insight of seasonal plankton succession to monitor shellfish aquaculture ecosystem interactions. Version 3.2. Fisheries and Oceans Canada. Sampling event dataset. https://doi.org/10.25607/2ujdvh

A derivative of DFO’s benthic species survey for the Strategic Program for Ecosystem-based Research and Advice (SPERA) (open data record ID: e736c0f0-b19e-4842-903d-28bfc756d48a), this benthic survey funded through the Canadian Healthy Oceans Network (CHONeII) looks at the presence/absence and abundance of two biogenic habitat-forming species that are listed as vulnerable to disturbance in a subset of 50 drift camera transects in the ‘Head Harbour/West Isles Archipelago/The Passages’ Ecologically and Biologically Significant Area (EBSA) in the Bay of Fundy, New Brunswick, Canada (~113km2). Presence/absence and abundance data of the stalked sea squirt (Boltenia ovifera) and horse mussel (Modiolus modiolus) were derived from the use of high-resolution Nikon D800 36.1 megapixel still images (n=2576, see link to parent record for more descriptive survey information) to be used in species distribution modelling. Image field of view (FOV) was estimated using a 10 cm-wide trigger weight for scale,and standardized across images using the average FOV estimate (0.75 x 0.5 m) across a subset of 200 images. Species counts were then converted to abundance estimates (number of individuals per square-meter) by dividing counts by 0.375m2. Boltenia ovifera was observed at densities reaching 456 ind./m2, while Modiolus modiolus density reached a maximum of 240 ind./m2.Cite this data as: Mireault C.A., Lawton P., Devillers R. and Teed L. Presence/absence and abundance of vulnerable marine ecosystem species Boltenia ovifera and Modiolus modiolus in the lower Bay of Fundy derived from high resolution still imagery. Published September 2023. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. https://open.canada.ca/data/en/dataset/152ae3f1-d2b9-43d9-a7b4-d769d9e9fc41