Climate effects on the ecosystem dynamics of the Barents Sea

Transcription

1 08 Mai 2012 A conference on Ecology and Evolution Norwegian Academy of Science and Letters Climate effects on the ecosystem dynamics of the Barents Sea Joël Durant, Dag Ø. Hjermann, Leif Chr. Stige Evolutionary Synthesis (CEES) University of Oslo, Norway CEES: A Centre of Excellence funded by the Research Council of Norway

2 Overview of lecture 1. Mechanisms of climate effects Leif Chr. Stige 2. Effects of climate varies in space and time: examples from cod Dag. Ø. Hjermann 3. The match-mismatch hypothesis Joël Durant

3 Overview of lecture 1. Mechanisms of climate effects Leif Chr. Stige 2. Effects of climate varies in space and time: examples from cod Dag. Ø. Hjermann 3. The match-mismatch hypothesis Joël Durant

4 Cod Capelin Herring

5 The foodweb of the Barents Sea 2009 by The Royal Society Bodini A et al. Phil. Trans. R. Soc. B 2009; 364:

6 The foodweb of the Barents Sea simplified Large cod (arrows show who is eaten by whom) Small cod Capelin Young herring Zooplankton Phytoplankton

7 Trends in climate and cod Cod spawning biomass Barents Sea sea temperature Year

8 SSB (mill. tons) Trends in climate and herring t o C 16 Herring spawning biomass Barents Sea sea temperature 4,3 12 4,1 8 3,9 4 3,7 0 3, Year

9 Causal relationships disputed - mechanisms poorly understood SSB (mill. tons) t o C , , , , Year 0 3, Year Evolutionary Synthesis CLIMATE VARIATION Evolutionary Synthesis; A Centre of Excellence founded by the Research Council of Norway

10 Possible mechanisms behind climate effects PREDATORS & COMPETITORS TEMPERATURE PREY TEMPERATURE Evolutionary Synthesis CLIMATE VARIATION Evolutionary Synthesis; A Centre of Excellence founded by the Research Council of Norway

11 Understanding the mechanisms: time-series analysis of early life stages of cod TEMPERATURE PREY CLIMATE VARIATION (Stige & al. PRSB 2010)

12 The best monitoring data for the Norwegian coast Russian bi-annual surveys April-May + June-July - Zooplankton - Ichthyoplankton (Stige & al. PRSB 2010)

13 showed: TEMPERATURE ZOOPLANKTON CANNIBALISM POSITIVE EFFECTS ON GROWTH POSITIVE EFFECTS ON SURVIVAL NEGATIVE EFFECT ON SURVIVAL (Stige & al. PRSB 2010)

14 Cod CANNIBALISM TEMPERATURE PREY CLIMATE VARIATION (Stige & al. PRSB 2010)

15 Herring TEMPERATURE PREY CLIMATE VARIATION (Stige & al. PRSB 2010)

16 Capelin PREDATORS & COMPETITORS TEMPERATURE PREY TEMPERATURE CLIMATE VARIATION (Stige & al. PRSB 2010)

17 Net effect of warming Large cod + + Small cod + - Capelin + Young herring Evolutionary Synthesis CLIMATE VARIATION (Stige & al. PRSB 2010) Evolutionary Synthesis; A Centre of Excellence founded by the Research Council of Norway

18 Net effect of warming Large cod + + Small cod + - Capelin + Young herring CLIMATE AFFECTS SPECIES DIRECTLY and INDIRECTLY THROUGH SEVERAL MECHANISMS WITH DIFFERENT TIME-LAGS Evolutionary Synthesis CLIMATE VARIATION (Stige & al. PRSB 2010) Evolutionary Synthesis; A Centre of Excellence founded by the Research Council of Norway

19 The effect of climate varies in space between populations The effect of NAO (North Atlantic Oscillation) on cod recruitment Barents Sea population (spawning ground) Stige et al. MEPS 2006

20 The (indirect) effect of climate varies in space within populations The effect of capelin on zooplankton biomass in the Barents Sea Capelin Zooplankton Evolutionary Centre Synthesis for Ecological and Evolutionary Synthesis; A Centre of Excellence founded by the Research Council Stige of Norway et al. in prep.

21 The (indirect) effect of climate varies in space but differently for different zooplankton size groups The effect of capelin on zooplankton biomass in the Barents Sea a. b. c. d. Young capelin Older capelin Older capelin Total capelin Evolutionary Synthesis Small zooplankton Intermediate-size zooplankton Large zooplankton Total zooplankton Stige et al. in prep. Evolutionary Synthesis; A Centre of Excellence founded by the Research Council of Norway

22 Zooplankton: direct and indirect effects of climate Cod Zooplankton biomass depends on balance between production and predation Capelin Young herring Zooplankton Climate Phytoplankton

23 Zooplankton (ln (mg m -3 )) Zooplankton (ln (mg m -3 )) Zooplankton: direct and indirect effects of climate control varies between regions, seasons and years North Atlantic Oscillation (NAO) + spring - summer, SE Barents Sea <3.9 mill. tons capelin NAO NAO NAO index >3.9 mill. tons capelin Stige et al. Limn Oceanogr 2009

24 The oscillating control hypothesis Hunt 2002: In cold (unproductive) periods, planktivores are controlled by food availability. In warm (productive) periods, by predators. Adult piscivorous fish Planktivores (including larvae and juveniles of piscivorous fish) Zooplankton

25 Oscillating trophic control in the Barents Sea? Cod Capelin Young herring Climate Zooplankton Phytoplankton Warm regime Cold regime Climate

26 Mechanisms of climate effects - DIRECT or INDIRECT - e.g., TEMPERATURE on physiological rates - through PREDATORS, COMPETITORS and PREY - TIME-LAGS - IMPORTANCE varies in SPACE and TIME BETWEEN and WITHIN populations - Between SEASONS - Between YEARS Evolutionary Synthesis NAO Evolutionary Synthesis; A Centre of Excellence founded by the Research Council of Norway

27 Overview of lecture 1. Mechanisms of climate effects Leif Chr. Stige 2. Effects of climate varies in space and time: examples from cod Dag. Ø. Hjermann 3. The match-mismatch hypothesis Joël Durant

28 Outline 1. Is the effect of temperature on fish always equally strong? (cod in the Barents Sea) 2. How does climate affect the survival of cod larvae along the Norwegian coast? 3. How does the effect of climate on cod vary throughout the North Sea?

29 The Barents Sea: Recruitment of cod is affected by temperature in (at least) two ways: - Effects on abundance of cod larvae - Effects on prey species for large cod; i.e., cannibalism

30 The Barents Sea food chain, simplified Cod Capelin Young herring Zooplankton Phytoplankton

31 Recruitment Largely positive effects of temperature on recruitment of cod and herring... Recruitment Per capita corrected reproduction Per capita corrected reproduction Cod (1946-) Herring (1921-) Annual average sea temperature Annual average temperature Annual average sea temperature

32 ...but herring has a strongly negative effect on capelin (key food item of the cod) > 1 million tons of young herring Capelin abundance

33 So climate has both positive and negative effects on cod + Cod CLIMATE Capelin Young herring Zooplankton Phytoplankton

34 Cod recruitment with capelin effect log(ncod age 3, t ) = log( a*bmcod spawners, t-3 1+c*BMcod spawners, t-3 ) + f Temp t-3 g (Beverton-Holt) (climate effect) Ncod age 3-6, t-dt BMcapelin t-dt (cannibalism) Fitted back to 1973 (start of capelin time series): p < p = 0.01

35 But how was cod affected by temperature and the herring-capelin link on longer time-scales? SSB (mill. tons) t o C 16 Herring spawning biomass Barents Sea sea temperature 4,3 12 4,1 8 3,9 4 3, ,5 Year Capelin data

36 log(capelin biomass) Solution: replacing capelin by F(herring) log(ncod age 3, t ) = log( a*bmcod spawners, t-3 1+c*BMcod spawners, t-3 ) + f Temp t-3 g (Beverton-Holt) (climate effect) Ncod age 3-6, t-dt BMcapelin t-dt (cannibalism) F(Herring age 1-2) Evolutionary Synthesis BMcapelin log(hit) BM herring age 1-2 (with time lags) Now the cod model can be fitted from 1921 (no longer limited by capelin data) Hjermann, Bogstad, et al. Proc. Roy Soc. Lond. B 2007 Evolutionary Synthesis; A Centre of Excellence founded by the Research Council of Norway

37 Solution: replacing capelin by F(herring) log(ncod age 3, t ) = log( a*bmcod spawners, t-3 1+c*BMcod spawners, t-3 ) + f Temp t-3 g Ncod age 3-6, t-dt BMcapelin t-dt Fitted back to 1921: p = F(Herring age 1-2) p = Evolutionary Synthesis Hjermann, Bogstad, et al. Proc. Roy Soc. Lond. B 2007 Evolutionary Synthesis; A Centre of Excellence founded by the Research Council of Norway

38 Look at time periods separately: the capelin effect is constant, temperature effect isn t Correlation temperature-cod recruitment (21-year window) Ottersen, Hjermann, Stenseth; Fisheries Oceanography 2006

39 With less old cod, climate is more important? Big mothers: spawn more eggs, larger eggs, and over a longer period of time 1st year cod spawner No. of eggs 2nd year spawner Cod 80 cm 3rd year spawner Cod 10 years (Ottersen et al., Fisheries Oceanography 2006

40 Outline 1. Is the effect of temperature on fish always equally strong? (cod in the Barents Sea) 2. How does climate affect the survival of cod larvae along the Norwegian coast? 3. How does the effect of climate on cod vary throughout the North Sea?

41 Spatial models for larval survival Where is larval survival best? and is the position of best survival affected by climate?

42 60º N 0º 10º W Grid Location Y Spatial models for larval survival 70º N 80º N 150 Larvae distribution (data: May/June) 0 Grid Location X º E 20º E 30º E 40º E 50º E 60º E Spawning areas (data: March/April)

43 Spatial models for larval survival Map of spawning areas Currents modelled by Norw. Met. Institute Advection (drift) Map of cod larvae Where should one find cod larvae?

44 Larval survival: statistical GAM model Larvae Physical drift distribution = from spawning + locations Environment (Temperature, salinity and currents) Spatial position (not explained by anything else) Drift model Temperature Salinity Currents L t, ( x, y) year s( x, y) f [ D( x, y) ] g[ T( x, y) ] h[ S( x, y) ] j[ CD( x, y) ] ( x, y)

45 Larval survival: effect of hi/lo NAO year? LOW NAO HIGH NAO

46 Larval survival: result L t, ( x, y) year s( x, y) f [ D( x, y) ] g[ T( x, y) ] h[ S( x, y) ] j[ CD( x, y) ] ( x, y) LOW NAO (<1) Maximum survival more strongly related to temperature Year LOW NAO (<1) HIGH NAO (<1) High NAO (>1) Survival optimum moves Northwards at high NAO Temp. Drift Con/Div

47 Outline 1. Is the effect of temperature on fish always equally strong? (cod in the Barents Sea) 2. How does climate affect the survival of cod larvae along the Norwegian coast? 3. How does the effect of climate on cod vary throughout the North Sea?

48 The cod-herring relationship in the North Sea - resolved in space

49 Cod-herring in the North Sea The conventional explanation(s): Fishing (too much) Young cod Mature cod Climate (warmer) -> C. finmarchicus (less)

50 Cod-herring in the North Sea Additional explanation? Fishing (too much) Young cod (increased predation/competition) Mature cod (reduced) Climate (warmer) -> C. finmarchicus (less)? Increased stocks of planktivores Decreased predation on planktivores (e.g. herring)

51 Cod-herring in the North Sea Could exist two alternative equilibria Fishing (too much) Temperatures (high) Much cod little herring Little cod much herring?

52 Individuals per hour trawled Cod-herring in the North Sea Individuals per hour trawled Individuals per hour trawled Individuals per hour trawled Degrees Celcius Young cod Young herring Sea temperature CodSpawn CodR ec r HerrSpawn HerrYoung SST

53 Cod-herring in the North Sea What affects cod recruitment? Cod spawners SST Young herring

54 Cod-herring in the North Sea What affects herring recruitment? Herring SST Cod

55 Cod spawners Cod-herring in the North Sea SST Young herring Hypothetic mechanism seems to fit for western German Bight Young cod (increased predation/competition) Herring Mature cod SST Cod (reduced) Young herring Climate (warmer) -> C. finmarchicus (less)? Increased stocks of planktivores Decreased predation on planktivores (e.g. herring)

56 Conclusions 1. Is the effect of temperature on fish always equally strong? (cod in the Barents Sea) 2. How does climate affect the survival of cod larvae along the Norwegian coast? 3. How does the effect of climate on cod vary throughout the North Sea? Temperature has become more influentional, perhaps because the fish has become younger Both local temperature and whether we are in a high or low NAO year has an effect The relative effects of climate and predators/competors appear to vary throughout the area

57 Overview of lecture 1. Mechanisms of climate effects Leif Chr. Stige 2. Effects of climate varies in space and time: examples from cod Dag. Ø. Hjermann 3. The match-mismatch hypothesis Joël Durant

58 Match-Mismatch Hypothesis

59 Critical period Match/Mismatch Johan Hjort 1914 David Cushing 1969

60 Match or mismatch D.H. Cushing 1969 The match-mismatch hypothesis was developed in order to explain the variation in recruitment of fish population If recruitment-production at a given trophic level matches food availability, effective recruitment will be profound. If there is a mismatch between food requirement and food availability, effective recruitment will be low. Frequency Larvae Larval food (herring) Match Mismatch Time

61 Match or mismatch 1. Role of abundance 2. Ecosystem approach 3. Spatial mismatch 4. Climate change 5. Reverse Match-mismatch

62 Role of abundance Frequency Larval food Fish larvae Match Mismatch Time Match-Mismatch Abundance The difference in abundance of predator/prey can disrupt or amplify the phenomenon described by the matchmismatch hypothesis Time

63 Cod and plankton in the North Sea Beaugrand et al. 2003

64 Model on cod data R 2 = Success = residuals Calanus abundance Degree of mismatch Durant et al. 2005

65 Summary 1: Match-Mismatch and food abundance General importance of the food abundance for recruitment and Match-Mismatch analysis An ecosystem approach?

66 Ecosystem approach Atlantic puffin (Fratercula arctica) Latitude Norwegian sea Norwegian Coastal Current Feb-Mar Herring spawning Røst May-Aug Puffin breedin g Longitude Fledging success (0-1) Nestling period duration, d Fledging success Good 0 Poor 4.0 Failed Salinity, Year Sea temperature, C Durant et al Durant et al Evolutionary Synthesis; A Centre of Excellence Durant founded et al. by 2006 the Research Council of Norway Evolutionary Synthesis

67 An ecosystem approach of the Matchmismatch hypothesis The zooplankton-herring synchrony affects Herring reproduction, which again affects the Puffin reproduction. First results (r 2 = 0.24, F 1,21 = 7.876, p = 0.011) A question of mismatch for the Herring Plankton availability, First-year herrings growth & survival Spawning Climate Food availability Quantity Quality Chick survival Not a question of Mismatch for the puffin Evolutionary Synthesis D J F M A M J J Month Evolutionary Synthesis; A Centre of Excellence founded by the Research Council of Norway A

68 Ecosystem approach Coal tit Blue tit Great tit Pied flycatcher Sparrowhawk Climate change Both et al Evolutionary Synthesis; A Centre of Excellence founded by the Research Council of Norway Evolutionary Synthesis

69 Summary 2: Ecosystem approach General importance of the food abundance for recruitment and Match-Mismatch analysis An ecosystem approach A mismatch can hide another one Climate effect may be even stronger at this level Spatial mismatch?

70 A spatial mismatch? Distance Overlap Abundance 0 Distance Time Distance match Distance mismatch e.g., the King penguin Aptenodytes patagonica Evolutionary Synthesis Evolutionary Synthesis; A Centre of Excellence Photo founded H. Weimerskirch by the Research Council of Norway

71 Variation of the polar front and foraging range of king penguins S mean 338 km PF mean 642 km 5 C 4 C 1998 E mean 537 km mean 366 km mean 526 km mean 523 km 2001 Foraging range (mean, Km) Bost et al Polar front position ( S)

72 Breeding success of king penguins from Crozet Islands Fixed Random Birds status Explanatory variables ΔAIC ANOVA effect effect X1 X2 P-value P-value P-value Early breeders SOI t Val. [Chla] Cro t 0 < < SOI t Val. [Chla] Cro t < SOI t Date [Chla] Cro t < < SOI t Lat.SST iso4 C t < SOI t Date SST Cro t < SOI t Lat.SST iso2 C t < SOI t < Late breeders SOI t Val. SST Cro t SOI t Lat.SST iso2 C t SOI t Date SST Cro t-2 location 0.78 of the 4 C SOI t Lat.SST iso4 C t 0.96 isotherm SOI t Date [Chla] Cro t SOI t Le Bohec et al. 2008

73 Summary 3: Spatial Match-Mismatch General importance of the food abundance for recruitment and Match-Mismatch analysis An ecosystem approach A mismatch can hide another one Climate effect may be even stronger at this level Spatial mismatch Similar to food abundance, the spatial distribution can disrupt the match between predators and prey Climate change?

74 Abundance Abundance Abundance Abundance Climate Change and Match-Mismatch Today Some hypotheses After climate change a Different time window t 0 creating a permanent mismatch, e.g., Baltic tellin Macoma balthica (Philippart et al. 2003). If some overlap exists, there will be a a strong selection pressure on phenological extremes, hence on the phenotype. t 1 Time b t 0 t 1 Time Same time window but not enough prey for a successful predator reproduction, e.g. North Sea cod Gadus morhua L. (Beaugrand et al. 2004). t 0 Extreme amplitude of inter-annual variation prey population creating an on-off pattern. This pattern may occur in regions where the inter-annual temperature variability is strongest (e.g., polar regions, Schär et al. 2004). Cury et al Evolutionary Synthesis; A Centre of Excellence founded by the Research Council t 1 of Norway Evolutionary Synthesis c t 1 t 0 Time Time

75 Summary 4: Climate change and Match-Mismatch General importance of the food abundance for recruitment and mismatch analysis An ecosystem approach A mismatch can hide another one Climate effect may be even stronger at this level Spatial mismatch Similar to food abundance, the spatial distribution can disrupt the match between predators and prey Climate change Due to climate change, we will have to get used to a world where our knowledge on ecosystem and trophic interactions is not anymore accurate or at least reliable

76 Abundance Reverse Match-Mismatch What is bad for the predator should be good for the prey. When recruitment-production of the predator matches prey recruitment-production, effective recruitment of the prey will be low. If there is a mismatch between prey and predator, effective recruitment of the prey will be high. Prey controlled system Predator Predator controlled system The Match Mismatch Hypothesis (MMH) Prey Prey controlled MMH Predator controlled MMH Statistical representation of the predator-prey relationship Prey controlled MMH Predator controlled MMH y= f(x 1, x 2 ) Match m 1 t 0 m 2 Mismatch Time Model 1 y = predator recruitment x 1 = prey abundance x 2 = degree of synchrony Model 2 y = prey recruitment x 1 = predator abundance x 2 = degree of synchrony

77 Narragansett Bay system Bay System 160 Acartia tonsa AT abundance Mnemiopsis leidyi Ctenophore abundance Degree of synchrony 50 Costello et al Durant et al. in prep Synchrony between predator-prey can be used to explain the changes of the prey dynamics

78 Match or mismatch The role of abundance: General importance of the food abundance for recruitment and mismatch analysis An ecosystem approach: A mismatch can hide another one Climate effect may be even stronger at this level Spatial mismatch: Similar to food abundance, the spatial distribution can disrupt the match between predators and prey Climate change: Due to climate change, we will have to get used to a world where our knowledge on ecosystem and trophic interactions is not anymore accurate or at least reliable Reverse Match-mismatch: The increase of the asynchrony lead to a better survival/recruitment for the prey

79 Conclusion A question of perspective Mismatch Match

80 Overall conclusions - CLIMATE affects species both directly and INDIRECTLY through other species - relative importance of different mechanisms varies in SPACE and TIME - relative importance of different mechanisms vary in SPACE and TIME - In space: different effects at the northern/southern edges of the species range than in the middle - The population may change (e.g. the younger cod) - Community structure may change - The Match Mismatch Hypothesis can serve as an unifying tool to explore the effect of climate change

81 Thanks Nils Chr. Stenseth, CEES, Oslo Philippe Sabarros, CEES, Oslo Geir Ottersen, IMR/CEES, Oslo Padmini Dalpadado, IMR, Bergen Dmitry Lajus, St.Petersburg State Univ. Kung-Sik Chan, Iowa State Univ. Natalia Yaragina, PINRO, Murmansk Sünnje Basedow, Bodø Univ. Coll. Igor Berchenko, MMBI, Murmansk Keith Brander, DTU Aqua, Copenhagen Dian Gifford, Univ. Rhode Island, Narragansett Rob Crawford, Dept. Env. Affairs,Cape Town Céline Le Bohec, CSM, Monaco Tycho Anker-Nilssen, NINA, Trondheim Grégory Beaugrand, CNRS, Wimereux