BERING SEA INTEGRATED ECOSYSTEM RESEARCH PROGRAM 2007-2012

1. BERING SEA INTEGRATED ECOSYSTEM RESEARCH PROGRAM 2007-2012 Progress Report on the development of an Implementation Plan Francis K. Wiese

2. September 2006 Board meeting • Adopt 6 questions as suggested by SP, expanded to climate change • $1.2M for 1-2 year modeling and retrospective studies • Set aside funds for Bering Sea IERP planning • Establish and Ecosystem Modeling Committee (EMC) • Develop an Implementation Plan for the BSIERP by August 2006 for incorporation into 2007 RFP

3. GOALS • Predict of future ecosystem states in response to natural variability and human activities • Determine the limits of ecosystem predictability • Develop information useful to resource managers and decision makers

4. BSIERP efforts • Bering Sea Interagency Working Group (BIAW) • BSIERP workshop • Project 502: Integration of Ecological Indicators for the North Pacific with emphasis on the Bering Sea: workshop will be held in Seattle on June 1-2 • Project 516: Seabirds as indicators of marine ecosystems: workshop was held in Girdwood on February 16-18

5. Related efforts • Loss of Sea Ice (HEPR) Implementation Plan • Bering Sea Ecosystem Study (BEST)

6. Implementation Plan • Project components (common) • IERP Committee • Series of 5-6 year modules: • 1-synthesis • 2-4 field work • 5-6 integration and write-up • ~$2.3M/yr ($11-12M): • 1st year: $250K • 2-4 year: $3.5M/yr • 5-6 year: $500K

7. Project components • Assessment of current programs and activities • Synthesis and identification of research and funding gaps • Model framework: integrate with the EMC, and include evidence of linkages between the scientific question and management needs • Interdisciplinary research teams : Co-investigators from both scientific (university) and management (agency) entities to ensure a clear application to resource management issues • Project management: University and agency scientists; management structure with a Team Leader, lead Principle Investigator, or Project Manager, Data Manager, post docs and graduate students (see Gulf of Alaska IERP) • Research Topics • Local Traditional Knowledge (LTK): Links to local research priorities and outline community involvement if possible. NPRB can recommending local expertise to assist in the LTK program development • Data capture, quality control, and transfer: Data management plan, including the storage of data and any collections, transfer of all metadata and data to the AOOS/NPRB data archive at UAF

8. Process • Scientific Steering Committee • Public Input (July 2006) • Pre-Proposals (Oct-Nov 2006) • Start with synthesis-define gaps (BIAW) • Integrate modeling • Teams are multi-disciplinary and multi-institutional • Projects relevant to resource management

9. Timing • Apr-Aug 2006: Development of Implementation Plan - BSIERP SSC • - July BIAW/BEST meeting in Seattle • Sep 2006: Develop 2007 RFP • Oct 2006: Launch 2007 RFP • Spring/Summer 2007: start BSIERP

10. Timing Table 1. Timelines for IERP and regular proposals in the 2007 RFP

11. Six broad questions • Are the distributions (range, spawning and breeding locations) and abundances of species in the Bering Sea ecosystem changing in response to climate change? If so, how? • Are the physical and chemical attributes of the ecosystem changing in response to climate change? If so, how? • Is lower trophic level production (quantity and form) changing in response to climate change? If so, how? • What are the principal processes controlling energy pathways in the Bering Sea? What is the role of climate change in these processes? • What are the linkages between climate change and vital rates of living marine resources in the Bering Sea? • What are the economic and sociological impacts of a changing ecosystem on the coastal communities and resource users of the Bering Sea?

12. Research Topics (initial ideas) • Use of indicators (ecological, economic) • Short/long term, small/large scale, process • Complement existing programs in time, space or organisms (e.g. BEST – spring, AFSC – commercial fish) • High stress areas: e.g. Northern BS • Range shifts and temp effects on ecotones/ecoregions

13. John Piatt et al. 2005

14. Research Topics (initial ideas) • Anticipatory sampling • Hotspots • Broad scale sampling • Functional realms • Multi-forcing mechanisms (ecological analogues between LME’s) • Process studies and prediction • Temperature effects across eco-components • Benthic-pelagic coupling • Key processes for upper level productivity and variability

15. Overall goal of IERP GOAL: Increase predictability of fluctuations in fish stocks over a 3-5 year period by x% NEED: Current accuracy and predictability of models

16. EMC input • General model design criteria (p.147 GOA)

17. EMC input General model design criteria • Define who will use the model and for what • Define the questions the model is supposed to answer and directly link those questions to the key questions and hypotheses for research • Argue convincingly that the model structure is adequate for the purpose, and that no better (cheaper, faster, more comprehensive, more direct) way exists to answer these questions • Show a schematic (flowchart) that is clear, complete and concise • Explain how uncertainty and variability will be represented and analyzed • Describe the system characteristics that will be left out or simplified and how the analysis will evaluate the impacts • Define data needs and show how the modeling effort will be coordinated with data assimilation and data management efforts • Define validation approach • Define how the modeling efforts will be communicated to other scientists, managers, and the public • Describe how the model will assimilate data from lower trophic level models and in turn how the outputs from this model will feed into other models • Describe how model outputs can be compared to other model outputs

18. EMC input • General model design criteria (p.147 GOA) • Overall framework that links modeling, field work and decision making • Determine data sets and data gaps • Identify specific needs for predictability, spatio-temporal resolution, error at each model level, model diversity, links among models • Measures of success • Interaction with current modeling efforts

19. NPRB modeling studies • 305: Monitoring and modeling predator-prey relationships (complete) • 313:Effects of prey availability and predation risk on the foraging ecology and demography of harbor seals in PWS: development and test of a dynamic state variable model (complete) • 419: Modeling of multispecies groundfish interactions in the eastern Bering Sea (complete-525) • 505: EBS walleye pollock: a spatially explicit model (30 APR 06) • 508: Female reproductive output of snow crab in eastern Bering Sea (30 June 06) • 509: Retrospective analysis of Kodiak Red King Crab (30 June 06) • 523: Pollock recruitment and stock structure (30 June 06) • 524: Productivity of capelin and pollock (30 June 06) • 525: Modeling multispecies groundfish interactions (33 Dec 07) • 531: Seabird-fish models (30 Oct 06)

20. 2006 RFP modeling 605: Modeling Growth and Survival of Early Life-Stages of Pacific Cod in Response to Climate-Related Changes in Sea Ice Conditions in the Bering Sea 606: Modeling Climate Effects on Interdecadal Variation in Southeastern Bering Sea Jellyfish Populations 607: Modeling study on the response of lower trophic level production to climate change (link to 613) 608: Response of the Bering Sea Integrated Circulation-Ice-Ecosystem to Past (1955-2005) and Future (2005-2055) Forcing by Climate and the Adjacent North Pacific and Arctic Oceans 613: Bering Sea Lower Trophic Level Responses to Climate Change (link to 607) 614: Optimization of a nutrient-phytoplankton-zooplankton ecological model for quantifying physical and biological interactions on the Gulf of Alaska shelf. 624: Modeling transport and survival of larval crab: Investigating the contraction and variability in snow crab stocks in the Eastern Bering Sea using Individual-Based Models