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Obey the LAW: Calanus finmarchicus dormancy explained

Obey the LAW: Calanus finmarchicus dormancy explained. Jeffrey Runge School of Marine Sciences, University of Maine and Gulf of Maine Research Institute Andrew Leising NOAA, Southwest Fisheries Science Center Catherine Johnson University of British Columbia. Objectives:

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Obey the LAW: Calanus finmarchicus dormancy explained

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  1. Obey the LAW: Calanus finmarchicus dormancy explained Jeffrey RungeSchool of Marine Sciences, University of Maine and Gulf of Maine Research Institute Andrew LeisingNOAA, Southwest Fisheries Science Center Catherine JohnsonUniversity of British Columbia

  2. Objectives: • Identify environmental processes that control dormancy in Calanus finmarchicus • Develop a mechanistic understanding of dormancy for inclusion in population dynamics modeling • Approach: • Compile Calanus and environmental data across regions in the NW Atlantic • Look for common patterns and cues • Using individual-based models, develop quantitative hypotheses to explain patterns

  3. Adults Copepodids Nauplii Proxies for dormancy entry and exit Entry:Fifth copepodid (CV) half-max proxyDormant when… CV proportion >= x-bar /2where x-bar = average max. CV proportion over all years • Exit:Emergence when… 1. Adult (CVI) proportion >= 0.1 2. Back-calculation from early copepodid appearance, using development time-temperature relationship Dormancyat CV stage

  4. Data sources Data from: DFO – AZMP: 1999 – 2005 (E.Head, P.Pepin) DFO – IML:1990 – 1991 (S. Plourde, P. Joly) US-GLOBEC: 1995 – 1999 (E. DurbIn, M. Casas) PULSE – NEC: 2003 – 2005 (R. Jones)

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

  6. Emergencedate Previous and nextdate Photoperiod at emergence and onset Newfoundland Anticosti Gyre Daylength (h) Rimouski Scotian Shelf Day of Year

  7. Newfoundland Temperature at 5 m Anticosti Gyre Temperature (°C) Rimouski Onset Emergence Scotian Shelf

  8. Climatological temperature at 5 m Newfoundland Anticosti Gyre Temperature (°C) Rimouski Onset Emergence Scotian Shelf

  9. Mean chlorophyll-a, 0 – 50 m Chl-a values truncated at 1.6 mg m-3 (threshold for growth) Newfoundland Anticosti Gyre Chl-a (mg m-3) Rimouski Onset Emergence Scotian Shelf

  10. Conclusions • No single observed environmental cue explains dormancy patterns • Dormancy entry and emergence occur over a broad range of times, both among individuals and years • The mechanistic understanding of dormancy transitions must involve interaction of multiple environmental factors. We propose a “Lipid-Accumulation Window” hypothesis to explain observed life history patterns.

  11. Growth of Neocalanus plumchrus copepodids in the southeastern Bering Sea

  12. Development time is a function of temperature and food concentration in Calanus finmarchicus Campbell, R. M. Wagner, G. Teegarden, C. Boudreau and E. Durbin. 2001. Growth and development rates of the copepod Calanus finmarchicus reared in the laboratory. Mar. Ecol. Prog. Ser. 221: 161-183

  13. Miller et al. 1977. Growth rules in the marine copepod genus Acartia. L&O. 22: 326-335.

  14. Lipid Accumulation Window hypothesis:Step 1 - Conditions allowing dormancy: suppose only copepods with > 50% lipid content can enter 0.5 Fraction lipid content at end of CV stage 0.4 Integrated Food 0.3 0.2 0.1 0.0 Integrated Temperature

  15. Lipid accumulation window hypothesis:Step 2 - Temporal Filter Cumulative conditions that will allow dormancy in CIV and CV Favorable Env. Conditions Lipid Threshold Time

  16. Lipid accumulation window hypothesis: Step 2 - Temporal Filter Cumulative conditions that will allow dormancy Resulting period when they go dormant Favorable Env. Conditions Time

  17. Lipid accumulation window hypothesis: Step 3 - Predation Filter Missing cohort here Resulting population entering dormancy Favorable Env. Conditions Predation Removal here Time

  18. Lipid accumulation window hypothesis: Step 4 - Emergence Timing linked to EntryEmergence survival linked to entry and Env. Population entering dormancy Population exiting dormancy Favorable Env. Conditions Successful females Jan Jan Time Dormancy Length, f(T during dormancy,% lipids at entry)

  19. Chlorophyll (mg m-3) Temperature (°C) Time  … Potential lipid accumulation Threshold for onset of dormancy Time  Testing the hypothesis • Identify lipid accumulation windows by starting individual-based model runs, driven by temperature and chlorophyll, at each date 2. CVs produced during the lipid accumulation window can enter dormancy

  20. Utility of the model for this calculation • Growth and development are decoupled • Ability to include temporally variable forcing data (food and temperature) • Can include or ignore predation filter • Mechanistic and physiological basis for growth and development

  21. Example Results for C. pacificus • Top figure is based on climatology from NH20, Newport Line, OR; Bottom figure based on SCB climatology • In the south, copepods spawned as early as day 50 can enter dormancy, whereas in the north, it’s 40 days later. • Peak dormancy entrance date is between days 125-175 in the S, and between days 175-225 in N. • Predation during the “Green” period would remove potentially successful copepods • Suboptimal cold temperatures(and low food) in the N during the early part of the year limit success then, whereas overly warm temperatures later in the year limit success in S during that time (recall the optimal window)

  22. Final Conclusions • Our findings for C. finmarchicus, C. pacificus and C. marshallae strongly suggest that multiple environmental factors are the likely cues for dormancy, as these copepods enter and exit dormancy over a wide range of times and conditions. • Our modeling results (for C. pacificus so far) suggest that lipid accumulation (or some equivalent storage compound) is a likely player in how dormancy is triggered. • OBEY THE LAW!!!!

  23. Implications • Previous coupled 3-d physical-biological models of Calanus have forced dormancy transitions empirically using an advective-diffusive approach • While these models provide diagnostic insight, they cannot be used for prediction • A mechanistic, coupled IBM-physical model that tracks lipid accumulation is needed to understand and predict Calanus population responses to climate changes

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