1. Fish and epibenthic assemblages in the Chukchi Sea: observations and predictions BA Bluhm, BL Norcross, K Iken, F Huettmann, BA Holladay (all University of Alaska Fairbanks), BI Sirenko (Zoological Institute RAS)

2. Demersal fish and epifauna Plumb-staff beam trawl, 7 mm mesh (4 mm in cod end) 2-5 min hauls on bottom Sort, count, weight, identify 2004-2009, 165 fish st, 42 epifauna st

3. Why care? Commitment to Circum- polar Biodiversity Monitoring Program (Arctic Council) Climate signal integrators Prey for subsistence species Species of potential subsistence and commercial fisheries (snow crab) Contribution to carbon cycling

4. Transform: Square root Resemblance: S17 Bray Curtis similarity d h i j c f e g b a Similarity 30 2D Stress: 0.22 North Coastal Central Northeast East Siberian Sea Herald Valley Coastal Central east Southwest Faunal similarity Fish Fish-Epifauna

5. Chukotka Alaska East Siberian Sea Wrangel Isl. Herald Canyon Icy Cape Observed fish assemblages Clustering based on fish biomass, square-root transformed, Bray-Curtis similarity

6. Chukotka Alaska East Siberian Sea Wrangel Isl. Herald Canyon Icy Cape Characteristic species Taxa contributing ≥10% to within cluster similarity

7. Observed fish-epifauna assemblages Kotzebue Sound Bering Strait Point Hope Clustering based on fish and epifauna biomass, square-root transformed, Bray-Curtis similarity

8. Characteristic species Kotzebue Sound Bering Strait Point Hope Taxa contributing ≥10% to within cluster similarity (fish species contributed ≤7%) Mean fish biomass per cluster 2-10% of total haul biomass

9. Environmental variables considered VariableUnitSource Distance to mean summer ice edge MetersU.S. National Ice Center Bottom temperature ºC Compiled by S. Okkonen (Univ. of Alaska Fairbanks) for PacMARS project Integrated chlorophyll a concentration Mg chl a/m 2 Matrai et al., integrated by C. Ashjian (WHOI) for PacMARS Water depthMeters IBCAO Grain size % phi 5 (silt) J. Grebmeier, U Maryland, compiled for PacMARS Sea surface Temp. (10 m) ºCWorld Ocean Atlas Bottom salinityPSU Compiled by S. Okkonen (UAF) for PacMARS VariableUnitSource AspectDegrees IBCAO Distance to run- off MetersR-ArcticNet SlopeDegreesIBCAO Distance to coastMeters Worldcoastline webportal Sea surface salinity PSUWorld Ocean Atlas Silicate conc.Mmol/m 3 World Ocean Atlas Phosphate concentration Mmol/m 3 World Ocean Atlas Apparent O 2 utilization Mol O 2 /m 3 World Ocean Atlas

10. Predicted assemblages north coastal central northeast Bering Sea Bathymetry (m) 0 - 25 26 - 50 51 - 75 76 - 150 151 - 1000 1001 - 4000 Chukotka Alaska East Siberian Sea Wrangel Isl. Herald Canyon Icy Cape

11. Environmental niches for fish assemblages North: near mean summer sea ice extent, low bottom temperature Central : high chlorophyll a, near ice edge, muddy sediment, >40 m Coastal: near coast, high surface and bottom temperatures, far from ice edge Northeast: coarse sediment, <40 m, high(er) bottom temperature, rel. low chlorophyll Figure 3: Examples of response curves from the TreeNet routine. One example of the highest or second highest ranking predictors is shown for each of the four dominant fish clusters. Examples were chosen to document the importance of predictors related to hydrography, sediment characteristics and food availability. High relative values in the y-axis of the response curve indicate presence of a given cluster while low values indicate absence. Larger distances between the two values imply stronger niche preferences than smaller distances. north coastal central northeast

12. Thanks! Funding through RUSALCA (NOAA- CIFAR), PEW Environmental Group (US Arctic Program), CMI (Fish), Species identifications aided by Drs L Cole, K Coyle, D Fautin, A Gebruk, M Hoberg, P Kuklinski, C Mah, CW Mecklenburg, E Rodriguez, A Rogaecheva, I Smirnov, O Tendal Vessel support, Ship crews and trawl teams of Prof. Khromov, Oscar Dyson /AFSC/NOAA, Oshoru Maru / Hokkaido Univ.

14. Temporal comparison of epifauna and food web in the southern Chukchi Sea (2004, 2009, 2012): First results BA Bluhm, KB Iken, C Serratos (all University of Alaska Fairbanks), B Sirenko (Zoological Institute RAS)

15. Why care? Food web Carbon flow Food web length – carbon transfer efficiency Pelagic-benthic coupling Epifauna Climate signal integrators (long-lived) Prey for subsistence species Species of potential subsistence and commercial fisheries (snow crab) Contribution to carbon cycling Commitment to Circum- polar Biodiversity Monitoring Program (Arctic Council) Plumb-staff beam trawl, 7 mm mesh (4 mm in cod end) 2-5 min hauls on bottom Sort, count, weight, identify

16. Time series stations E C A F B G Chukchi Sea D Bering Sea AW BSW ACW Freshwater inflow, gravel Hard substrate

17. Biomass and composition Caveat: No replicate trawl hauls AB C G D EF Russian coast Anadyr Water Alaskan coast Bering Shelf Water

18. Biomass trend

19. Snow crab: abundant but small in Chukchi Mean 69 SD 29 N=344 Mean 40 SD 11 N=2669

20. Community structure stable Anadyr Water Point Hope Russian coast Coastal Current

21. Food web – trophic levels 2012

22. Food web – carbon source -25 -24 -23 -22 -21 -20 -19 -18 -17 -16 -15 -14 2009 2004 AW ACW AW ACW δ 13 C POM Surface deposit - bivalves Neptunea sp. Pagurus rathbuni Leptasterias sp. Nephtys sp. Hyas coarctatus Chionoecetes opilio Argis lar Gymnocanthus tricuspis Myoxocephalus scorpius Lumpenus fabricii Boreogadus saida Strongylocentrotus droebach.  Consumer δ 13 C depleted in ACW – possible freshwater signal  Depleted δ 13 C POM in AW in 2009 – strong freshwater signal in 2009 2004 results: Iken K et al (2010) Deep-Sea Research II 57: 71- 85 2012

23. Learned so far? Food web Food web reflects water masses (tight pelagic- benthic coupling in AW) Food web structure stable between 2004 and 2009 Food source signal variable at point measurement Epifauna Biomass variable between years Individual species can drive tends (stock fluctuations in snow crab? Community structure stable in area, different by substrate and water mass Combination of metrics tell more than one metric

24. Thanks! Funding through NOAA-CIFAR NA08OAR4320870, CIFAR IPY Ship crews and trawl team of Prof. Khromov, B. Holladay Crab funding (CMI, BOEM), and lab team Stable isotope lab team Species identifications aided by Drs L Cole, K Coyle, D Fautin, A Gebruk, M Hoberg, P Kuklinski, C Mah, CW Mecklenburg, E Rodriguez, A Rogaecheva, I Smirnov, O Tendal

26. RUSALCA Synthesis - Bio Need from phys-chem-geo Spatial and temporal patterns of environmental conditions on different scales (next slide) for water column and (near) bottom (latitude / longitude, depth, value) Joint interpretation! Mapping support across projects for special issue? Bio: Have Species distributions Community distributions Biomass / abundance distributions Food web Some fluxes Some rates (benthic respiration, copepod egg production) Variability / change over time (to varying degrees)

27. Life cycles provide integration scales Day month yeardecadecentury µm mm cm dm m Bacteria larvae zooplankton fishes benthos mammals

28. Possible papers One overarching highlights paper (or extended editorial to special issue) Regional highlight, system description as multi-year composite: Herald Canyon area Temporal variability highlight: focus on DBO 3 All multidisciplinary, multi-author, multinational Unique and complementary to other synthesis efforts Need lead team (Russia/USA) or interdisciplinary post- doc based in both countries (Liza-Maria concept)

29. RUSALCA Synthesis - Bio Future Need next decade? Continue time series (minimum DBO transect 3?) Increased integration with phys-chem-geo More rates: Current rates, e.g. grazing, growth, age Future rates through experiments? Thermal windows and physiological plasticity? Link to sea ice? Predictive capability? Carbon flux model? Interdisciplinary post-docs with Russia-US advisory team, based in two countries?