Krill is a generic name for crustaceans of the order Euphausiids, most of which are known to be Thysanoessa raschii and Meganyctiphanes norvegica in eastern Canada. Krill is an important food resource for many marine mammals, in particular the blue whale. The maps show the points of high krill concentration per month from April to November. Each point gives the number of years of high aggregation probability (6 to 10 years). The data were produced from a mathematical model developed in Plourde et al. 2016. The model has allowed to calculate the probability of meeting a strong aggregation of krill over a period of 10 years. High krill aggregations are defined as the 95th percentile of predicted biomass in 10 x 10 km cells covering the Estuary and Gulf of St. Lawrence. Additional Information Plourde, S., Lehoux, C., McQuinn, I.H., and Lesage, V. (2016). Describing krill distribution in the western North Atlantic using statistical habitat models. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/nnn. vi + xx p. Plourde, S., McQuinn, I.H., Lesage, V., Lehoux, C., Joly, P., Bourassa, M-N. in prep. Spatial distribution of krill in eastern Canadian waters: a climatological approach based on historical plankton net and acoustic data. The data are incomplete upstream of Pointe-des-Monts because of the lack of water height anomalies in the area (variable being used to predict aggregations of krill). A less number of years with a high aggregation of krill is thus represented but that should not be interpreted as a less favorable zone compared to areas East of Pointe-des-Monts.

The objective of the study was to describe the spatial distribution of krill in eastern Canadian waters using a statistical modelling approach in support of the identification of important habitat for the western North Atlantic (WNA) blue whale (Balaenoptera musculus). Generalized Additive Models (GAMs) were used to predict ‘Significant Aggregations of Krill’ (SAK), i.e., areas where dense krill aggregations would have a greater probability of occurring. SAK cover less than 2% of the entire spatial domain and their location varied among krill categories and seasons. These SAK are interpreted as areas where environmental conditions promote krill aggregation on a regular basis and therefore are potentially important for WNA blue whale foraging in eastern Canadian waters. Plourde, S., Lehoux, C., McQuinn, I.H., and Lesage, V. 2016. Describing krill distribution in the western North Atlantic using statistical habitat models. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/111. v + 34 p.

Antarctic krill is a key component of Southern Ocean ecosystems and there is significant interest in identifying regions acting as sources for the krill population. We develop a mechanistic model combining thermal and food requirements for krill egg production, with predation pressure post-spawning, to predict regions that could support high larval production (spawning habitat). We optimise our model on regional data using a maximum likelihood approach and then generate circumpolar predictions of spawning habitat quality. The uploaded datasets represent model predictions of seasonal circumpolar spawning habitat quality of Antarctic krill as well as composite data of the circumpolar mean annual number of weeks in which modelled spawning habitat quality is higher than the summer 80th percentile.

This layer represents the relative summer density of belugas in the St. Lawrence Estuary based on 35 aerial surveys carried out from 1990 to 2009. The boundaries of the areas were determined by combining the highest densities until the desired proportion of the population was obtained using kernel density estimation in order to obtain a smooth and continuous density distribution. Within Fisheries and Oceans Canada (DFO), the ecosystem approach is considered a tool for operational planning, project implementation and preparation of advisory reports. In response to this strategic direction, the DFO science division is committed to implement the ecosystem approach in its activities as Ecosystem Research Initiatives (ERI) in each of the six administrative regions of DFO. In the Quebec region, two pilot projects were implemented, of which one aimed to define and characterize the habitat of the St. Lawrence beluga (Delphinapterus leucas). Data sources and references: DFO. 2016. Ecosystem Research Initiative (ERI): Integrated Advice on the Summer Habitat of the St. Lawrence Estuary Beluga (Delphinapterus leucas). DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2016/030. Mosnier, A., R. Larocque, M. Lebeuf, J.-F. Gosselin, S. Dubé, V. Lapointe, V. Lesage, V., H. Bourdages, D. Lefaivre, S. Senneville and C. Chion. 2016. Définition et caractérisation de l'habitat du béluga (Delphinapterus leucas) de l'estuaire du Saint-Laurent selon une approche écosystémique. Secr. can. de consult. sci. du MPO. Doc. de rech. 2016/052. vi + 93 p.

Robust prediction of population responses to changing environments requires the integration of factors controlling population dynamics with processes affecting distribution. This is true everywhere but especially in polar pelagic environments. Biological cycles for many polar species are synchronised to extreme seasonality, while their distributions may be influenced by both the prevailing oceanic circulation and sea-ice distribution. Antarctic krill (krill, Euphausia superba) is one such species exhibiting a complex life history that is finely tuned to the extreme seasonality of the Southern Ocean. Dependencies on the timing of optimal seasonal conditions has led to concerns over the effects of future climate on krill’s population status, particularly given the species’ important role within Southern Ocean ecosystems. Under a changing climate, established correlations between environment and species may breakdown. Developing the capacity for predicting krill responses to climate change therefore requires methods that can explicitly consider the interplay between life history, biological conditions, and transport. The Spatial Ecosystem And Population Dynamics Model (SEAPODYM) is one such framework that integrates population and general circulation modelling to simulate the spatial dynamics of key organisms. Here, we describe a modification to SEAPODYM, creating a novel model – KRILLPODYM – that generates spatially resolved estimates of krill biomass and demographics. This new model consists of three major components: (1) an age-structured population consisting of five key life stages, each with multiple age classes, which undergo age-dependent growth and mortality, (2) six key habitats that mediate the production of larvae and life stage survival, and (3) spatial dynamics driven by both the underlying circulation of ocean currents and advection of sea-ice. Here we present the first results of KRILLPODYM, using published deterministic functions of population processes and habitat suitability rules. Initialising from a non-informative uniform density across the Southern Ocean our model independently develops a circumpolar population distribution of krill that approximates observations. The model framework lends itself to applied experiments aimed at resolving key population parameters, life-stage specific habitat requirements, and dominant transport regimes, ultimately informing sustainable fishery management. This dataset represents KRILLPODYM modelled estimates of Antarctic krill circumpolar biomass distribution for the final year of a 12-year spin up. Biomass distributions are given for each of the five key life stages outlined above. The accompanying background, model framework and initialisation description can be found in the following reference paper: Green, D. B., Titaud, O., Bestley, S., Corney, S. P., Hindell, M. A., Trebilco, R., Conchon, A. and Lehodey, P. in review. KRILLPODYM: a mechanistic, spatially resolved model of Antarctic krill distribution and abundance. - Frontiers in Marine Science

Antarctic krill (Euphausia superba) have a keystone role in the Southern Ocean, as the primary prey of Antarctic predators. Any decreases in krill abundance could result in a major ecological regime shift, but there is currently limited information on how climate change may affect krill. Increasing anthropogenic carbon dioxide (CO2) emissions are causing ocean acidification, as absorption of atmospheric CO2 in seawater alters ocean chemistry. Ocean acidification increases mortality and negatively affects physiological functioning in some marine invertebrates, and is predicted to occur most rapidly at high latitudes. Here we show that, in the laboratory, adult krill are able to survive, grow, store fat, mature, and maintain respiration rates when exposed to near-future ocean acidification (1000 – 2000 μatm pCO2) for one year. Despite differences in seawater pCO2 incubation conditions, adult krill are able to actively maintain the acid-base balance of their body fluids in near-future pCO2, which enhances their resilience to ocean acidification.

Distribution and abundance of zooplankton, krill and fish were observed on the K-axis transect using deployments of RMT1+8 net. Towing speed of the RMT1+8 were approximately 2 knots. All krill, fish and squid in the catch were sorted, identified to species and counted. The density at each station were determined from the counts per calibrated flow-meter readings attached to the net. Morphometric measures were taken and, for larger taxa. List of files K-Axis Morph combined_for data centre.xlsx: Morphological data for all krill and zooplankton captured in RMT-8 net haul. RMT data entry_v1_for data centre.xlsx: Trawl data. RMT8 filtered volume_for data centre.xlsx: Filtered volume for each haul. Map_all.tif: Map showing all trawl stations. Map_RMTR.tif: Map showing only regular trawl stations. Map_RMTT.tif: Mapn showing only target trawl stations. K-Axis description This dataset includes biological data from “K-Axis voyage, 2016 and “Voyage 3, 2015”. [Data from K-Axis voyage, 2016] Distribution and abundance of zooplankton, krill and fish were observed on the K-axis transect using deployments of RMT1+8 net. Towing speed of the RMT1+8 were approximately 2 knots. All krill, fish and squid in the catch were sorted, identified to species and counted. The density at each station were determined from the counts per calibrated flow-meter readings attached to the net. Morphometric measures were taken and, for larger taxa. -List of files- K-Axis Morph combined_for data centre.xlsx: Morphological data for all krill and zooplankton captured in RMT-8 net haul. Map_all.tif Map_RMTR.tif Map_RMTT.tif RMT data entry_v1_for data centre.xlsx: Trawl data. RMT8 filtered volume_for data centre.xlsx: Filtered volume for each haul. [Data from Voyage 3, 2015] The Australian Antarctic research and resupply vessel, RV Aurora Australis, was directed to undertake an opportunistic marine science survey for 17 days during 21 February to 10 March 2015 using ship time that became available due to unexpectedly favourable ice conditions for Mawson station resupply. The purpose of this opportunistic Marine Science work was to assess: 1. The spatial variability, particularly along the shelf break, of the prey field for penguins, flying seabirds and marine mammals in East Antarctica. 2. The small scale variability of prey in key foraging locations near to land-based colonies of penguins and flying seabirds in East Antarctica. 3. Feasibility and potential of utilising annual station resupply voyages as a cost effective means to undertake monitoring and research to better understand the ecosystem in the region. The survey completed 5 acoustic box surveys including a total of 53 RMT target and routine trawls, 6 demersal trawls, 131 phytoplankton samples from underway sampling, and 214 hourly observations of predators. These activities were successfully supervised remotely. -List of files- emm-15-22.pdf: Prelminary report of the voyage to CCAMLR WG-EMM Figure_V3_all_euphausiids.pdf: Map of Euphausiid abundance distribution. Figure_V3_Clione_antarctica.pdf: Map of Clione antarctica abundance distribution. Figure_V3_crystal_krill.pdf: Map of Euphausia crystallorophias abundance distribution. Figure_V3_frigida.pdf: Map of Euphausia frigida abundance distribution. Figure_V3_larval_fish_abundances.pdf: Map of fish larvae abundance distribution. Figure_V3_superba.pdf: Map of Antarctic krill abundance distribution. Figure_V3_tmacrura.pdf: Map of Thysanoessa macrura abundance distribution. V3_final_for data centre.xlsx: Trawl station data and density data of each taxa caught. Voyage 3 Marine Science Program Final.docx: Voyage report.

11 tagged Blue whales (Balaenoptera musculus) were tracked during the daytime movements as well as the feeding behaviour in the St. Lawrence River estuary. Kernel density was applied to derminate the high density feeding areas of all individuals combined (30, 40, 50, 60, 75, 95 %). Doniol-Valcroze T, Lesage V, Giard J, Michaud R, 2012. Challenges in marine mammal habitat modelling: evidence of multiple foraging habitats from the identification of feeding events in blue whales. Endang Species Res, Vol. 17 : 255–268, doi : 10.3354/esr00427 (English version only)