1 of 38

GRAD STUDENTS & POSTDOCS

University of Alaska Fairbanks | University of Washington | Oregon State University

2 of 38

Hauke Schulz

University of Alaska Fairbanks | University of Washington | Oregon State University

3 of 38

Marine mesoscale observation network

Hauke Schulz

4 of 38

Observations for the next generation of climate models

  • Next generation of climate simulations aim towards higher spatial resolutions than most dense observing networks and satellite missions.
  • Measurements of the ocean, the atmosphere above and their interaction are particularly lacking on these scales.
  • Denser networks of observations are needed to develop and evaluate higher resolution simulations

haschulz@uw.edu

Hauke Schulz - University of Washington

Stevens et al. (2019)

5 of 38

Correct representation of mesoscale structures is crucial for an accurate cloudiness in the tropics

  • How marine, tropical shallow clouds change with warming remains uncertain
  • Recent studies emphasize the influence of mesoscale structures and processes on the cloud fraction
  • High resolution simulations of mesoscale extent indicate current challenges in representing the macrophysical characteristics
  • Precipitation and their temperature anomalies on the ocean surface are particularly important to represent mesoscale features correctly

Animation of surface temperature in the tropical North Atlantic with frequent cold pools

6 of 38

Capturing mesoscale processes with the help of the sailing community

  • Conventional research vessels are expensive and not available at scale
  • 300+ sailboats cross the Atlantic each year in close proximity
  • Equiping majority of boats with basic meteorological sensors to capture mesoscale variability
  • First test phase planned for the coming winter season

haschulz@uw.edu

Hauke Schulz - University of Washington

Curious? Like to get the data for your own project? Contact me!

7 of 38

Shuting Zhai

University of Alaska Fairbanks | University of Washington | Oregon State University

8 of 38

Email: stzhai@uw.edu

Implications of Snowpack Reactive Bromine Production for Arctic Ice Core Bromine Preservation

9 of 38

Email: stzhai@uw.edu

10 of 38

Email: stzhai@uw.edu

11 of 38

Yang Xiang

University of Alaska Fairbanks | University of Washington | Oregon State University

12 of 38

Subtropical gyre nutrient cycling in the upper ocean: Insights from a nutrient-ratio budget method

Yang Xiang*, Paul D. Quay, Rolf E. Sonnerup, Andrea J. Fassbender

13 of 38

13

An updated nutrient-ratio budget method

Classic view of surface nutrient budgets

Updated view of surface nutrient budgets

Nexp = Nsup + Nsrc

Pexp = Psup

Nexp = Nsup + Nsrc

Pexp = Psup

14 of 38

14

Quantify the relative importance of P sources and sinks

Station ALOHA

P sources

P sinks

  • Importance of vertical inorganic nutrients in P sources

  • Importance of DOM and zooplankton in P sinks

15 of 38

A more quantitative understanding of biological pump

C sinking flux (mol/m2/y)

Depth (m)

Martin Curve

Martin et al., 1987; Siegel et al., 2023

16 of 38

Megan Feddern

University of Alaska Fairbanks | University of Washington | Oregon State University

17 of 38

Non-stationary relationships between climate and fisheries in the California Current and Gulf of Alaska�Megan L. Feddern, Eric J. Ward, Mary Hunsicker, William H. Satterwaite, Curry J. Cunningham

Litzow et al. 2020a

Litzow et al. 2020b

Stationarity: the idea that natural system fluctuate within an unchanging envelope of variability

18 of 38

Challenge: how do we incorporate physical-biological relationships into forecasts when relationships are varying?

Step 1.  Investigate relationship between atmospheric processes and biologically meaningful climate dynamics that may have contributed to the marine heatwave “era”

Spring PDO - upwelling

Data:

Sea level pressure, SST, PDO, NPGO, upwelling, freshwater discharge, wind

Analysis:

Bayesian linear model,

Dynamic factor analysis (HMM),

self-organizing maps

19 of 38

Challenge: how do we incorporate physical-biological relationships into forecasts when relationships are varying?

Step 2.  identify if these changing relationships are reflected in protected and commercially important species in the California Current

Data:

Chinook salmon indicator stocks, CalCOFI juvenile fish, Newport hydrologic line, RREAS, groundfish

Analysis:

Multivariate dynamic linear modelling

Step 3: Identify future forecast ability of best predictive models using alternative measures for cross validation (LFOCV)

20 of 38

Genoa Sullaway

University of Alaska Fairbanks | University of Washington | Oregon State University

21 of 38

Genoa Sullaway

22 of 38

Genoa Sullaway

23 of 38

Genoa Sullaway

24 of 38

Veronica Farrugia Drakard

University of Alaska Fairbanks | University of Washington | Oregon State University

25 of 38

26 of 38

27 of 38

Email: vhfarrugiadrakard@alaska.edu

28 of 38

Alexandra McInturf

University of Alaska Fairbanks | University of Washington | Oregon State University

29 of 38

Alexandra McInturf

30 of 38

Alexandra McInturf

31 of 38

Alexandra McInturf

32 of 38

33 of 38

34 of 38

Samuel May

University of Alaska Fairbanks | University of Washington | Oregon State University

35 of 38

Growing concerns over impacts of salmon hatcheries to wild populations

  • Billions of juvenile salmon released each year
  • Some hatchery salmon stray into wild populations
  • Hatchery fish have fewer offspring
  • Hatchery fish are less phenotypically variable
  • Are hatchery fish negatively impacting wild population recruitment and resilience?

Release Year

Sockeye

Chum

Pink

Juveniles Released (Millions)

Samuel May

36 of 38

Individual-based simulations to examine evolutionary and demographic effects of strays to wild populations

Results suggest that greater hatchery straying:

    • Increases wild recruitment
    • Causes rapid introgression of hatchery-origin alleles into wild populations
    • Increases synchrony among populations
      • Reduces portfolio effects and therefore resilience

May et al. (2023) Evolutionary Applications

github.com/SMay1

Proportion Hatchery-Origin Spawners

Mean Return Day

Generation

Samuel May

37 of 38

Simulations help to explore management options for reducing impacts

  • Reduce the number of hatchery fish in the wild
    • Reduce release sizes
    • Decrease straying
  • Change run timing of hatchery fish
  • Parameterize with empirical data to predict outcomes of proposed changes

Thank You!�samay3@alaska.edu�github.com/SMay1

Samuel May

38 of 38

Next: NOAA Leadership

University of Alaska Fairbanks | University of Washington | Oregon State University