Ecosystem Research Initiative (ERI) for the Gulf of Maine Area (GoMA)

ActivityOutputsOutcomes Analyses and Interpretations of Observed Oceanographic and Ecosystem Variability Syntheses of observations Evaluation of climate change and variability impacts on GoMA ecosystems from plankton to fish. Contributions to climate change scenarios and climate indicators Population and NPZ models to investigate climate sensitivity Ecosystem responses to climate variability and change (key commercial species: scallop) Databases on recruitment and environmental data. Particle tracking simulations Effect of environmental variability on recruitment Downscaling climate change scenarios Update of climate change reports Climate change scenarios (with CCSI) Climate change and ecosystem indicators Theme I – Influence of climate change on ecosystems

1. Analyses and Interpretations of Observed Oceanographic and Ecosystem Variability 1.Physical oceanographic variability in the GoM-GB region and linkages with large- scale variability (Brickman, Petrie) 2.Nutrient inventories and supply to the GoMA (Harrison, Yeats, Greenan) 3.Zooplankton and lower-trophic–level variability in the GoMA (Johnson, Head) 4.Ecosystem-level evaluation and analysis of oceanographic and fish distributions in extreme states (e.g. different NAO regimes) in the GoMA (Frank, Shackell, Petrie) 5.Model simulations of oceanographic and lower-trophic-level variability in the GoMA (Brickman) 2. Ecosystem Responses to Climate Variability and Change 6.Key commercial species - scallops (Dibacco, Johnson) 3. Downscaling climate change scenarios (linkage with CCSI) 7.Update of the Wright et al. and Frank et al. reports (Loder, Frank) 8.Climate change indicators for the GoMA (all) 9.Oceanographic scenarios of changes for NW Atlantic focussed on the GoM-GB region (all)

Analyses and Interpretations of Observed Oceanographic and Ecosystem Variability 1. Physical oceanographic variability in the GoM-GB region and linkages with large-scale variability (Brickman, Petrie) Investigate long term temperature time-series from single stations in the GoMA (e.g. Prince-5, St. Andrews), Quantify inflow to eastern Gulf of Maine at Cape Sable, Develop climatological indicators, Establish relation of GoMA hydrographic variability to large scale forcing.

2. Nutrient inventories and supply to the GoMA (Harrison, Yeats, Greenan) Improve estimates of the advective components of the nutrient fluxes and their fate in the Gulf, particularly the relative proportions of Warm Slope and cold Labrador Slope source waters, Examine the stratification pattern in the GOM and its relationship to wind forcing, focusing particularly on winter nutrient inventories and mixing in the late summer/fall and relationship to phytoplankton. NOTE: Link with IGS Hypoxia project. Analyses and Interpretations of Observed Oceanographic and Ecosystem Variability (cont’d) Temporal trends in source water nitrate

Analyses and Interpretations of Observed Oceanographic and Ecosystem Variability (cont’d) 3. Zooplankton and lower-trophic–level variability in the GoMA (Johnson, Head) Seasonal and spatial variability in zooplankton and phytoplankton communities and abundance of dominant species in GoMA and WSS - identify interannual variability patterns in the time series, Correlate physical and biological properties (e.g. salinity, stratification, abundance indices of primary producers, zooplankton predators) on seasonal and spatial scales, Relate changes in zooplankton community structure or abundance, and/or in primary producer and predator indices to environmental extreme states, Develop simple population models for the dominant zooplankton species, including differences in growth, development, and egg production rates as a function of temperature and food, as well as life history traits. Calanus finmarchicus Centropages typicus Oithona spp. Pseudocalanus spp.

Analyses and Interpretations of Observed Oceanographic and Ecosystem Variability (cont’d) 4. Ecosystem-level evaluation and analysis of oceanographic and fish distributions in extreme states (e.g. different NAO regimes) in the GoMA (Frank, Shackell, Petrie) Update and expand existing abiotic, biotic, human activities databases (SS and GoMA), Complete WSS and BoF State of the Ecosystem Overviews, including analysis interpreting the differences in trophic changes/cascades, Analyses expanded in GoMA, including spatial statistical analyses using GIS software and newly developed temporal algorithms for regime shift detection. Western Scotian Shelf Body size, condition, Growth rate Lower trophic biomass, pelagics, Med benthos

5. Model simulations of oceanographic and lower-trophic-level variability in the GoMA (Brickman) Nemo ocean model enhanced for shelf processes and evaluated for the Scotian Shelf and adjacent regions. Nemo coupled with plankton dynamics (N-P-Z) models to hindcast and interpret physical, nutrient and plankton variability in the Gulf of St. Lawrence and Scotian Shelf. Enhanced Mercator model, at a demonstration level, for similar applications in GoMA. The model and associated plankton models will be used for preliminary simulations of interannual hydrographic, circulation and related biological variability in the GoMA, drawing on and complementing the results of the observational analyses. NOTE: Link with CCSI modelling project Analyses and Interpretations of Observed Oceanographic and Ecosystem Variability (cont’d) APDM APDM adaptive biological model (BIO, Vézina/Casault) (BIO, Vézina/Casault) GSS4 model (GFC-BIO) OPTIMAL OPTIMAL BIOLOGICAL MODEL (DFO, Zonal) (DFO, Zonal) IML/ISMER Biological model

Ecosystem Responses to Climate Variability and Change 6. Key commercial species – scallops (DiBacco, Johnson) Retrospective analysis of biological and environmental data and particle tracking simulations to document how large-scale physical forcing affects spawning periodicity and larval dispersal of scallops in the GoMA. The goal is to gain a mechanistic understanding of how variability in egg production, recruitment and larval transport influence scallop recruitment. Key Collaborators: Ian Jonsen, Steve Smith (PED); Wendy Gentleman (Dalhousie) GSC NEP Connectivity between GSC and NEP, May

Downscaling Climate Change Scenarios 7. Revision of the Wright et al. and Frank et al. reports (Loder, Frank) 8. Climate change indicators for the GoMA (all)

Downscaling Climate Change Scenarios 9. Oceanographic/ecosystem scenarios of change for NW Atlantic focussed on the GoMA (all) A climate change scenario is not a prediction of future climate! A climate change scenario is: a coherent, internally consistent and plausible description of a possible future state of the world …a coherent, internally consistent and plausible description of a possible future state of the world … [Environment Canada, [Environment Canada,

ERI-GoMA Climate ERI-GoMA Benthic Patterns ERI-GoMA Eco-Models EBM Framework