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Ecological Forecasting and Hindcasting in the Intertidal Zone

This study explores the relationship between weather, oceanography, body temperatures, mortality risks, and biogeography in the intertidal zone. It examines the measurement and prediction of risks to coastal populations and the development of forecasting, hindcasting, and nowcasting tools. The study also discusses the impact of climate change on biogeographic change in intertidal species.

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Ecological Forecasting and Hindcasting in the Intertidal Zone

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  1. Ecological forecasting and hindcasting in the intertidal zone:From weather and oceanography to body temperatures, mortality risks and biogeography David S. Wethey, Brian Helmuth, Sarah A. Woodin, Thomas J. Hilbish, Venkataraman Lakshmi University of South Carolina Columbia SC 29208 USA wethey@biol.sc.edu

  2. How hot is it on the shore?How do we measure and predict risks to coastal populations? • Measurements • Biomimetic temperature sensors • Mortality and heat-shock protein expression • Forecasting, Hindcasting, Nowcasting • Mechanistic simulation models • tbone.geol.sc.edu/forecasting • Based on ground and satellite climate data • Tide model to predict inundation times • tbone.geol.sc.edu/tide

  3. Model Cartoon Models based on NOAH Land Surface Model used in NOAA Global Forecast System and North American Model. We developed a new “vegetation type” : intertidal mussel bed. All of the physics is from NOAH. Tides: xtide, SST: GHRSST, wave runup: Wavewatch III

  4. Hindcast Verification of Model US West Coast 2000-2004 95% of model months are within range of biomimetic logger observations of average daily maximum temperature Gilman, Wethey, Helmuth 2006. PNAS 103:9560-9565

  5. What is the relationship between climate change and biogeographic change in intertidal species? • Major space occupiers / habitat modifiers • Barnacles – • Semibalanus balanoides • Mussels – • Mytilus californianus, M. edulis • M. galloprovincialis, M. trossulus • Worms- • Diopatra neapolitana, Diopatra cuprea • Abarenicola pacifica, Arenicola marina Wethey and Woodin 2008, Hydrobiologia 606: 139-151

  6. Forecasting • Forecasting products for coastal managers • Warnings of die-offs • Sublethal effects on dominant space-occupiers • Short term forecasts (7-days) • Seasonal forecasts (8-months) • Derived from operational products • North American Model/Global Forecast System • Climate Forecast System • Wave Watch III • GHRSST • Climate Scenarios • NOAA/GFDL Model • NASA/GISS Model

  7. Rock temperatures: Barnacles/mussels Forecasts capture magnitude and amplitude of both Seasonal trends and Daily fluctuations Bias 1.12°C RMS error 3.22°C

  8. Seven Day Forecast of Intertidal Mussel Bed Temperatures Worldwidehttp://tbone.geol.sc.edu/forecasting/7day.html Forecast runs daily, using midnight GMT forecasts from NOAA Global Forecast System, North American Model and GHRSST as input. US East/West, Europe, S Africa, New Zealand, Hokkaido/Sakhalin

  9. Seasonal Forecast of Intertidal Mussel Bed Temperature Anomalies Worldwidehttp://tbone.geol.sc.edu/forecasting/8month_anomaly.html Forecast runs biweekly, using midnight GMT forecasts from NOAA Climate Forecast System as input. US East/West, Europe, S Africa, New Zealand, Hokkaido/Sakhalin

  10. Forecasts on US West Coast Predicted Mass Mortality of Keystone Species July 8-15, 2006 July 23-30, 2006 Aug 1-8, 2006 Mass mortality of Pisaster starfish In Oregon, but not In Central California Pisaster is keystone predator on West Coast

  11. Forecasts In New Zealand Predicted Mass Mortality Feb 1-4, 2007 Feb 5-8,2007 Feb 14-17,2007 Feb 18-21,2007 Mass mortality of Burrowing echinoids Echinocardium At Warkworth NZ Feb 21, 2007

  12. Mytilus mussel survival in lab and field Field Temperatures Lab Survival Daily Survival temperature Cumulative Survival Sierra J Jones

  13. 0/year 0 to 2/year > 2/year West Coast Mussel Mortality Risk: Frequency of 36 C temperatures for at least 2 hours over 3 consecutive days Allison Smith

  14. Hindcasting Historical Sea SurfaceTemperature to 1900 • ICOADS data from ships of opportunity • Monthly data interpolated to 1 km grid • 12-point inverse squared distance weighting • Sampled at 10 km intervals along coast • Verified 1985-2000 vs AVHRR • Used in CART bioclimatic envelope models Lima et al. 2006. J. Biogeography 33: 812-822

  15. Centennial Scale Climate Change and Biogeographic Shifts

  16. Conclusions • Proof of concept of ecological forecasting tools • Short term intertidal forecasts predicted unusually high temperatures during two local mass mortality events • Pisaster starfish in Oregon, 2006 • Echinocardium urchins in New Zealand, 2007 • Laboratory data on thermal tolerance for Mytilus species allow prediction of heat shock protein expression and mortality • Hindcasting can be used to explain historical range shifts • Seasonal forecasts can be used to predict reproductive success or failure in some species. • Web-based tools can be used to provide warning of potential die-offs in intertidal habitats worldwide. • See Poster 268 (Allison Smith) – worldwide risk analysis • See Poster 239 (Lauren Yamane) – climate & predators

  17. Collaborators and Support • PIs: Brian Helmuth, Sarah Woodin, Jerry Hilbish, Venkat Lakshmi • Post docs: Sarah Gilman, Fernando Lima, Nova Mieszkowska, Srinivas Chintalapati, Sylvain Pincebourde • Students: Sarah Berke, Pam Brannock, Sierra Jones, Karlie Jones, Jennifer Jost, Christel Lopez, Kim Schneider, Allison Smith, Lauren Szathmary, Lauren Yamane

  18. Classification and Regression Tree Analysis of Barnacle Biogeography and SSTDemographic population model of geographic limitsUS East Coast Europe 2007 1850 2007 1900 Maine Cape Cod C Hatteras Eng Chan Biarritz N Portugal Gibraltar Semibalanus reproductive failure if winter temperature >10-12C (Crisp & Patel 1969, Barnes 1963)

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