Ecological forecasting, hindcasting and nowcasting in the intertidal zone:

From weather to body temperatures and

demography

David S. Wethey, T. J Hilbish, V. Lakshmi, B. Helmuth

University of South CarolinaColumbia SC 29208 USA

wethey@biol.sc.edu

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-•Tube builders – habitat creators: Diopatra•Bioturbators – habitat disturbers: Arenicola

Wethey & Woodin 2008, Hydrobiol 606:139; Berke et al. 2010 GlobEcolBiog 19:223

Intertidal Temperature Models • Barnacle –

– Wethey 2002 Integ Comp Biol 42:872-880 , – Wethey & Woodin 2008 Hydrobiologia 606:139-151

• Mussel – – Gilman, Wethey, Helmuth 2006.PNAS 103:9560-9565

• Starfish –– Szathmary, Helmuth, Wethey 2009 Marine Ecol Prog Ser 374:

43–56• Sandflat • Salt Marsh Sediment

• New “vegetation types” in NOAH land surface model• Models capture seasonal trend and amplitude of daily variation

measured with biomimetic data loggers in the field– Mussel model Average Bias 0.66°C– Mussel model Average RMS error 2.47°C– Errors largely derive from poor hindcasts of solar radiation

Forecasting• Forecasting products for coastal managers

– Warnings of die-offs– Sublethal effects on dominant space-occupiers

• Short term forecasts (7-days) – Run Daily– US East/West, Europe, Chile/Peru, Hokkaido/Sakhalin, NZ, S Africa

– http://tbone.biol.sc.edu/forecasting_test• Forcing data from NOAA operational products

– North American Mesoscale Model/Global Forecast System– Climate Forecast System– Wave Watch III

• SST (5 km) from GHRSST– OSTIA – UK Met Office

• Climate Scenarios– NASA/GISS, NOAA/GFDL, NCAR, NARCCAP, EU ENSEMBLES Models

• Tides from Xtide

Whangateau Harbor Cockle Mass Mortality 2009

High cockle mortality occurredduring unusually hot conditionsin the intertidal:

>35°C at 1cm depth in sediment

Forecasts of intertidal temperatures 2007-2010

Cockle data: Karen Tricklebank

Nowcasting • Experimental Product• Real Time – 1 hour time delay

– GOES Sounder 8km imagery– Use land surface temperature

adjacent to shore– Has similar thermal trajectory

to our data loggers• Tide Model –OregonState OTPS

Best r2 = 0.57 Slope = 0.90 Intercept = 1.73RMS error=0.36°C Bias=0.13°C

http://tbone.biol.sc.edu/forecasting_test/westcoast_goes.html

Modeling Biogeographic Response to Climate Change

• Mussel – Mytilus

• Population Response to Climate Variables– Mortality (Lethal Temperature 32°C)– Energy Balance (Fails if higher than 18-20°C)

• Hindcast of Climate Variables– Sea Surface Temperature– Air Temperature– Organism Body Temperature

Thermal Tolerance Data Used to Construct a Model of Survival

Date

Julian Day

Temperature (°C)

Tem

pera

ture

(°C

)%

Sur

viva

l

% S

urvi

val

Jones et al. 2009. Biol. Bull. 217: 73-85

Field Temperatures Lab tolerance

Cumulative Survival Daily Survival

Mytilus edulis yearly survival hindcastsfrom daily SST and air temperature records

(modeling the last individual to die in the shade)OISST NARR Air T

1982

2005

Sierra Jones

Model results match field observations both in timing and magnitude of mortality from the Carolinas to New England.

Results also consistent with observed pattern of biogeographic change since 1950s.

Totally different mechanism in Europe:Mytilus edulis distribution cannot be explained by thermal mortality – should be able to survive far south of its actual geographic limit

Serious overprediction error – likely due to differences in mechanism between the two sides of the Atlantic

Sierra Jones

Geographic limit

Thermal survival limit

Allelefreq

Energetics Models Improve Predictive Power on European Coast

Energetics Model Adult Mortality Model Low Food Ration Aquatic Thermal MortalityJulian Day Zero Energy Remaining Cumulative Thermal Survival December

Geog Limit

Geog Limit

European coast is not hot enough to kill mussels outright, but Southern Europeis hot enough that they likely run out of energy before the year is over.

Modeling Biogeographic Response to Climate Change

• Barnacle – Semibalanus; • Population Response to Climate Variables

– Mortality (Lethal Temperature 42°C)– Reproduction (Fails if higher than 10.5-11.5°C)– Age structured demographic model with dispersal

• Hindcast/Forecast of Climate Variables– Sea Surface Temperature– Organism Body Temperature

• Average Dispersal Distance 10 km• Seed whole ocean with animals and let the

population grow and disperse.

Biogeography

Ensembleprobabilityof occurrence ofspeciesMatches data1955 & 2006

Forecasts of 2050 and 2099

EU ENSEMBLESProjectDownscaledGCM output17 models

Collaborators and Support

• PIs: Brian Helmuth, Jerry Hilbish, Venkat Lakshmi, Sarah Woodin• Post docs: Sarah Gilman, Fernando Lima, Nova Mieszkowska,

Srinivas Chintalapati, Sylvain Pincebourde, Nils Volkenborn • Students: Sarah Berke, Pamela Brannock, Lindsay Brin, Nicholas Burnett,

Elizabeth Fly, Sierra Jones, Karlie Jones, Jennifer Jost, Christel Lopez, Rhiannon Rognstad, Kimberly Schneider,

Allison Smith*, Lauren Szathmary, Lauren Yamane * NASA graduate fellow – see her poster at the meeting