Fei CHAI ( 柴扉 ) and Francisco Chavez

Transcription

1 Fei CHAI ( 柴扉 ) and Francisco Chavez University of Maine Monterey Bay Aquarium Research Institute Outlines: Needs & Challenges of Modeling Ecosystems Physical and Ecosystem Models Peruvian Anchoveta, ENSO Forecasts 1

2 An ecosystem sandwich FISHING/HARVEST: a combination of effort and abundance CLIMATE: exerts important influences on habitat FISHING Marine Ecosystems CLIMATE 2

3 FAO (2004)

4 Trends of climatic and oceanographic variables in the Pacific Basin PDO Anchoveta Sardine (Chavez et al. Science 2003)

5 Fishing spawning recruitment Benthivorous Fish Piscivorous Fish Planktivorous Fish Pre-recruits Pre-recruits Pre-recruits How to Link? Seabirds Marine Mammals Suspensionfeeding Benthos Micro- Zooplankton Meso- Zooplankton Pelagic Invertebrate Predators Deposit-feeding Benthos Phytoplankton Nano- Phytoplankton Bacteri a Detritus Nitrate+Nitrite DO Ammonia 5

6 deyoung, Heath, Werner, Chai, Megrey, Monfray Science, 2004 The difficulty arises because organisms at higher trophic levels are longer lived, with important variability in abundance and distribution at basin and decadal scales. FC 6

7 The rhomboids indicate the conceptual characteristics for models with different species and differing areas of primary focus. 7 Rhomboid is broadest where model has its greatest functional complexity i.e., at the level of the target organism. deyoung, Heath, Werner, Chai, Megrey, Monfray Science, 2004

8 Fei CHAI ( 柴扉 ) and Francisco Chavez University of Maine Monterey Bay Aquarium Research Institute Outlines: Needs & Challenges of Modeling Ecosystems Physical and Ecosystem Models Peruvian Anchoveta, ENSO Forecasts 8

9 Regional Ocean Model System (ROMS): 12-km Res. Sea Surface Temperature (SST) Sea Surface Height (SSH) 3 day averaged, 1993 to 2006 FC 9

10 Carbon, Silicate, Nitrogen Ecosystem Model CoSiNE, Chai et al. 2002; Dugdale et al Fecal Pellet Micro- Zooplankton [Z1] Detritus-N [DN] Sinking Predation Mesozooplankton [Z2] Lost Chai et al., 1996 Fecal Pellet Grazing Excretion Detritus-Si [DSi] Sinking Small Phytoplankton [P1] NH 4 Uptake Ammonium [NH 4 ] Grazing N-Uptake Diatoms [P2] Sinking Iron Iron NO 3 Uptake Si Uptake Biological Uptake Nitrate [NO 3 ] Advaction & Mixing Silicate [Si(OH) 4 ] Air-Sea Exchange Total CO 2 [TCO 2 ] Physical Model

11 Regional Ocean Model Systems (ROMS)-CoSiNE CoSiNE: Carbon, Silicate, and Nitrogen Ecosystem (Chai et al., 2002) Eddy-Resolving Ocean Modeling at 12-km ROMS SST Jan. 1993

12 Fei CHAI ( 柴扉 ) and Francisco Chavez University of Maine Monterey Bay Aquarium Research Institute Outlines: Needs & Challenges of Modeling Ecosystems Physical and Ecosystem Models Peruvian Anchoveta, ENSO Forecasts 12

13 Why Peru? Lima A fishing village in Peru 13

14 The State of World Fisheries and Aquaculture, FAO (2004) 14

15 15

16 Birds and mammals Daily sampling covers all the landing points, and 10% of the active fishing fleet.

17 El Nino and Peruvian Anchovy Fishery Sea Surface Temperature Anomaly 10 x 10 6 MT Annual Anchovy Catch 17

18 Pacific Basin ROMS-CoSINE (12-km) Simulation Annual Mean Sea Surface Temperature (SST) Modeled SST ( o C) Satellite SST ( o C) 18

19 Surfare Chlorophyll Comparison in situ, the modeled, and SeaWiFS 19 Historical Data SeaWiFS

20 ROMS-CoSINE (12-km), Annual Mean Si(OH) 4, Diatoms, Meso-zooplankton along 10 o S Si(OH) 4 Meso zooplankton 21 FC 20

21 ROMS-CoSINE (12-km) Si(OH) 4 and Diatoms along 10 o S 40 Si(OH) 4 Jan mmol/m km Offshore Distance Jan mmol/m 3 2 Diatoms Jan FC 21

22 Seasonal Cycle of Surface Chlorophyll along the Coast of Peru, 0-100km, 4 o S-18 o S in situ Modeled SeaWiFS FC 23

23 Science at the leading and/or bleeding edge Surface chlorophyll, Nov First ever long term forecast of chlorophyll?

24 Forecasting Skill for Peru Coast - about 6 months Forecasted Data Simulated

25 ROMS-CoSINE (12 km) Temperature, Currents, Planktons EGGS DURATION: 24 HR MORTALITY RATE>99% ROMS-CoSINE (12 km) Temperature, Currents, Planktons AGE-2+ LIFE SPAN ~3 YR PREDATOR: SEA BIRDS, MARINE MAMMALS Life Cycle of Peruvian Anchovy Individual Based Model with ROMS-CoSINE YOLK-SAC LARVE LEN: 2-4MM DURATION: HR MORTALITY RATE 80%-98% AGE-2 LEN: ~20CM WT: ~55 gm OPT TEMP: 18.6 C SPAWN ~20 TIMES/YR ROMS-CoSINE-IBM FIRST-FEEDER FEED BY PHYTOPL. LEN: 4.25CM, WT: ~2 gm DURATION: 80 DAYS ROMS-CoSINE (12 km) Temperature, Currents, Planktons AGE-1(JUVENILE) BECOME SEXUAL MATRUE LEN: 8-10CM WT: ~10 gm ROMS-CoSINE (12 km) Temperature, Currents, Planktons 25

26 Current, Food, Temperature, and Behavior Wind Surface Coast Currents Anchovy Zooplankton Phytoplankton 100 m

27 Fish Growth Curves 27

28 Recruitment: Seasonal Cycle Days to recruit to 5cm Total Zooplankton Total Phytoplankton 28

29 Anchovy Recruitment in Response to ENSO Temperature mesozooplankton diatom Recruitment Moderate El Nino Strong El Nino There is a clear seasonal and interannual variability characterized by anchovy recruitment to 5cm.

30 Current, Food, Temperature, and Behavior Wind Surface Coast Currents Anchovy Zooplankton Phytoplankton 100 m

31 3-D model results Passive drift Day 1 Day 31 Day 61 0m release 30m release 31 February 1991

32 3-D model results Swimming Assumptions Fish is able to search a given round area, the radius is determined by swimming speed. The new location is determined by the highest potential growth rate within the search area. If there are more than one preferred place, then randomly choose one

33 3-D model results Swimming Results Dep0m 0m release Dep30m 1 month 6 month 30m release 33 January 1991

34 Fei CHAI ( 柴扉 ) and Francisco Chavez University of Maine Monterey Bay Aquarium Research Institute Outlines: Needs & Challenges of Modeling Ecosystems Physical and Ecosystem Models Peruvian Anchoveta, ENSO Forecasts ROMS-CoSiNE-IBM 34

35 Some final thoughts: New understanding: food web structure, Fe, remote forcing, ENSO and decadal variability and predication. Technical advancement: computing power, observing power and information infrastructure. Cost to resource managers of operational ecological forecasting for fisheries management will be small because society as a whole has already paid for. Need to train new generation of marine scientists and resource managers to integrated all information and understanding. 35

36 Human Consumption of Anchoveta A Japanese restaurant in Lima, Peru 36

37 Fei CHAI ( 柴扉 ) and Francisco Chavez University of Maine Monterey Bay Aquarium Research Institute Outlines: Needs & Challenges of Modeling Ecosystems Physical and Ecosystem Models Peruvian Anchoveta, ENSO Forecasts ROMS-CoSiNE-IBM 37