Jeffrey Runge and Andrew Pershing, University of Maine David Kimmel and James Pierson

1. Life histories of Calanus species in the North Atlantic and North Pacific Ocean and responses to climate forcing Jeffrey Runge and Andrew Pershing, University of Maine David Kimmel and James Pierson University of Maryland Center for Environmental Sciences

2. Collaborators A. Leising, NOAA, SWFSC C. Johnson, BIO, Fisheries and Oceans, Canada S. Plourde, IML, Fisheries and Oceans, Canada R. Harris, PML, England D. Bonnet, Univ. Montpellier, France W. Melle, IMR, Norway A. Gislason, Marine Res. Inst. Iceland D. Speirs, Univ. Strathclyde, Scotland D. Mackas, IOS, Fisheries and Oceans, Canada

3. Overall question How will populations of Calanus species in the North Atlantic and North Pacific Oceans respond to interannual and longer term, climate forced variability in water column temperature and food supply?

4. Calanus species of interest:Sibling species in two sympatric species pairs: North Atlantic: C. finmarchicus and C. helgolandicus North Pacific: C. marshallaeand C. pacificus Develop an IBM life cycle model that includes a mechanistic understanding of dormancy and is parameterized for the particular life history traits of each species, tested and refined for regions of interest.

5. Dormancy vs temperature and Chl-a climatologies Chl Temperature Calanusfinmarchicus dormancy dynamics in the NWA Johnson et al. 2008

6. Dormancy vs temperature and SWIFS-derived Chl-a climatologies Calanuspacificus dormancy dynamics in the CCS Leising et al. in prep

7. Lipid accumulation window hypothesis • Individual Calanus can only enter diapause if their food and temperature history allows them to accumulate sufficient lipid for overwintering and gonad development • Decision to proceed to dormancy is initiated when lipid stores reach a preset threshold (30% lipids by weight in stage CIV) • Exit from dormancy by endogenous timer or when lipid stores decrease below a preset threshold

8. The Five Project Objectives • Compile and analyze data sets across species and regions; publish a series of comparative synthesis papers (Pierson, Runge, collaborators) • Demographic data sets • Physiological rate characteristics: egg production, growth and development rate

9. Abundance (no. m-2) Stage Proportion AG: Anticosti Gyre, NW Gulf of St. Lawrence OnsetEmergence

10. Region specific datasets: egg production in NWA Runge and Plourde 1996) Campbell &Head 2000) (Plourde et al. data) Runge et al. 2006)

11. Development Rates vs. Temperature • C. marshallae is outlier, with very long stage durations, primarily due to extra-long relative C5 stage • C. finmarchicus has fastest development-at-temperature • C. pacificus and C. helgolandicus lie between these two extremes

12. The Five Project Objectives • Construct synoptic climatologies in selected regions to examine sensitivities of individual species life histories to climate forcing (Kimmel) • Example: Western, central and eastern North Atlantic Ocean. Each day SLP (NCAR dataset) from 1950-2007 into a weather pattern modes. • Downscaled the patterns to surface winds (u and v) and air temperature from NCEP/NCAR reanalysis data set

13. Frequency of pattern by month Sea Level Pressure Air temperature anomalies Vector-diagram of the average winds D. Kimmel

14. D. Kimmel

15. D. Kimmel

16. The Five Project Objectives • Investigate mortality: compilation of empirical mortality estimates and comparison with “climatological mortality” estimates based on life history theory. (Runge, Pershing, Leising, student) Are there common regional and/or global patterns of mortality? Are the stage-specific, temperature-dependent mortality rates needed to accurately close life cycle models consistent with life history theory?

17. Optimal life history theory Assume populations are at an Evolutionarily Stable Strategy (ESS). A population is at an ESS, with respect to some phenotype or set of phenotypes, if a rare gene introduced into the population, and whose carriers have a different phenotype from the mean of the population, is always eliminated. The ESS will be the survivorship and reproduction schedule, lx and mx (where x is age in d) which maximizes the intrinsic rate of increase for the population. That is, for any other feasible schedules (lx’ and mx’ ):

18. The predictions of mortality in a population of Acartia clausii in Jakle’s Lagoon (Landry’s data) Myers and Runge 1983

19. The Five Project Objectives 4. Refine our stage-structured, IBM life-cycle model with parameterization tuned for each of the sibling species pairs in each region of interest: Leising, F. Maps (post-doc)

20. Life cycle model with lipid diapause rule:comparison with observations MODEL DATA

21. The Five Project Objectives • Using the life cycle model, evaluate the sensitivity of Calanus life histories responses to the climate change scenario climatologies (Leising, Maps, Pershing, all). • How do the sibling species between and within the “finmarchicus” and “helgolandicus” groups respond to similar modes of climate forcing? • Look for opportunities to link the 1-D life cycle model with 3-D circulation and temperature fields to investigate the role of advection on observed distribution and abundance patterns