Ecological forecasting in the rocky intertidal zone: an inside out perspective Brian Helmuth, David

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Ecological forecasting in the rocky intertidal
zone an inside out perspectiveBrian Helmuth,
David Wethey, Jerry Hilbish, Venkat Lakshmi,
Sarah GilmanUniversity of South Carolina
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Intertidal zone has long served as a model for
how climate affects species distribution patterns
Chthamalus (barnacle)
Balanus (barnacle)
Mytilus (mussel)
Increasing Abiotic Stress
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Are intertidal ecosystems early warning systems
for the effects of climate change?

• Rocky intertidal algae and invertebrates are
  assumed to live very close to their thermal
  tolerance limits
• New biochemical and molecular techniques show
  that significant thermal damage can occur during
  exposure to temperatures experienced during low
  tide
• Evidence of responses of species distributions to
  temperature changes

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However.

• Thermal damage often occurs after exposure to
  temperatures experienced during low tide, when
  body temperature is driven by terrestrial climate
• Body temperature during low tide is driven by
  multiple climatic factors, and can be different
  from skin (surface), air or water temperature
• What are patterns of intertidal temperature in
  nature?
• Where and when do we look for the effects of
  climate change on intertidal communities?
• How do we link studies conducted under controlled
  laboratory conditions with those in the field
  (what are patterns of intertidal organism
  temperature in nature?)

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Change in heat stored Heat in - Heat out
Tair
Qstored
m, cp
Tbody
Twater
Tground
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Heat flux is determined largely by the
characteristics of the organism
m cp d(Tb/dt) Heat in - Heat out
Cblah Ablah (Tblah - Tb)
where m mass f (size, materials) cp
specific heat f (materials) Cblah
coefficient f (size, morphology) Ablah
area of transfer f (size, morphology) (Tblah
- Tb) temperature gradient
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Two organisms exposed to identical microclimates
can experience very different body temperatures
Seastar at 12C
Mussel at 21C
Helmuth 2002. Integrative and Comparative Biology
42 837-845.
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Instrument characteristics determine the
temperatures that they record
Unmatched loggers regularly create errors of
gt14C Thermally matched loggers incur errors of
2C
Robomussel
California mussel, Mytilus californianus
Fitzhenry et al. 2004 Marine Biology 145
339-349.
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Thermal mosaic over a large geographic range
Shady Cove Cattle Point Tatoosh Boiler
Bay Strawberry Hill Monterey Piedras
Blancas Cambria Lompoc Landing Jalama Alegria Boat
House Coal Oil Pt
(Helmuth et al. 2002 Science 2981015-1017)
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Maximum Daily Temp (C)
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In part this pattern is due to variability in the
timing of low tides in summer..
(Helmuth et al. 2002 Science 2981015-1017)
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Topex-Poseidon R/S Data for Tidal Height
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Patterns of thermal stress in M. californianus

• Geographic patterns of stress based on actual
  measurements of intertidal body temperature show
  us a fundamentally different pattern - and make
  very different predictions of where trouble
  spots may emerge - than do predictions based
  only on environmental variables such as air or
  water temperature

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Patterns of thermal stress in M. californianus

• Temperatures are not always hotter at equatorial
  (southern) sites, mainly due to the timing of low
  tide in summer (mid-day in North)
• Suggests presence of hot spots (e.g. central
  Oregon, Puget Sound) where summertime low tides
  coincide with periods of low wave splash and hot
  climatic conditions
• Climate change may not cause simple range shifts,
  but instead may punch holes in distributions,
  if they exceed larval dispersal distances

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Poleward Shift?
Disjunct Distributions?
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Heat budget model
Qrad,sky
Qsolar
Tair
Qevap.
Qconv
Qstored
Wind
Tb
Qrad, ground
Twater
Tground
Qcond
NASA R/S climate data NOAA Weather and wave
data Our weather stations
Verify using ground-based msmts
Generate thermal maps of risk
Helmuth, Wethey, Hilbish, Lakshmi, Woodin, and
Power labs
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Multiple Working Hypotheses Based on
Physiological Stress

• Lethal thermal stress during aerial exposure at
  low tide (high or low)
• Sublethal thermal stress during aerial exposure
  (high or low)
• Failure to reproduce due to elevated water
  temperature
• Salinity or sediment stress

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Microclimate Model

• Predict rock/animal temperature from
• air temperature, humidity, wind, cloud cover
• NOAA ground buoy observations
• NERR (US National Estuarine Research Reserve)
  SWMP
• Satellite observations
• water temperature
• NOAA tide station, CMAN buoy observations
• NERR SWMP
• Satellite observations
• Tides
• NOAA model /observations or WxTide
• Wave height adjustment (NOAA buoy observations)
• NERR SWMP
• http//tbone.geol.sc.edu/tide
• OSU Topex/Poseidon Inverse Solution (TPXO)
• Solar radiation
• angle of incidence of direct sunlight - Jet
  Propulsion Lab ephemeris of the sun
• NOAA GEWEX-GCIP Solar Radiation from GOES imagery
• NERR SWMP Ground-based pyranometers

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Satellite Data Sets

• Variable Sensor Spatial Res Temporal Res
• Surface Air TOVS 1º
  2/day
  1980-present
• Temperature AIRS 50 km
  2/day 2002-present
• SST / ASTER 90 m
  on Request 2000-present
• Ground MODIS 0.5-1 km
  2-4/day 2002-present
• Surface AVHRR 1 5 km
  1-2/day 1980-present
• Temperature AMSR-E 10 km
  1-2/day 2002-present
• TOVS 1º
  2/day 1980-present
• AIRS
  50 km 2/day 2002-present
• Solar Rad GOES 0.5 º
  hourly 1996-present
• Clouds

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Ground Based Datasets

• Weather stations that we have deployed
• National Climatic Data Center Integrated Surface
  Hourly (TD 3505)
• Air Temperature, Wind, Clouds, Precip., Dewpoint
• Global coverage (online 1990s present)
• NOAA NERR System Wide Monitoring Program
• Water quality, Meteorological, Solar Radiation
• U.S. National Data Buoy Center offshore buoy/CMAN
  data set
• Air Temperature, Wind, Wave height
• NOAA CO-OPS
• Tide observations, some meteorological data, some
  SST

Model-Based Datasets

• NOAA/NWS North American Model (ETA)
• NOAA/NWS Global Forecast System
• NOAA/NCEP GFS Reanalysis 1948-2005
• GFDL Long Term Climate Scenarios

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Average error in model prediction of daily max.
2 - 2.5C
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Model Performance vs. Field Data
too cold too hot
Difference in Monthly Average Maximum
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Biogeography and climate - the Mediterranean
mussel
Black winter SST 8C Red summer SST 30 C
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Geographic Model PredictionsMussel species in
Hokkaido
67 of species distribution patterns is explained
by independent environmental variables
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US West Coast Mytilus galloprovincialis


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Mussel Genotype Frequencies in California1995
and 2005
The arctic species M. trossulus has increased in
abundance since 1995
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Geographic Model Predictions Barnacles in
EuropeReproductive Failure if SST gt 10C in
winter

• Sea surface temperatures (AVHRR 36km) in
  February 1984 and 1998. The 10C winter isotherm
  moved from northern Spain to Brittany. The left
  arrow is the southern limit of S. balanoides in
  1985, the right arrow was our prediction for 2003
  in our grant proposal.
• 2005 Field surveys from Southern Portugal to
  Denmark by our group indicate our prediction was
  correct.

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Ecological Forecasting /Nowcasting/ Hindcasting
in the Intertidal Zone

• Validated body temperature model
• Linked to output of North American / Global
  Forecast System
• 7-14 day forecasts of intertidal body temperature
  on demand for locations worldwide
• Hindcasts of intertidal body temperature back to
  1948 for locations worldwide to test hypotheses
  of links between climate change and biogeographic
  change
• We are currently building a module for intertidal
  skin and subsurface (body) temperature within the
  structure of the land surface module (NOAH) of
  the NAM/GFS used by NWS for weather prediction.

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Collaborators

• PIs J. Hilbish, V. Lakshmi, H. Power, S. Woodin
• Post doc S. Gilman
• Students and teachers P. Brannock, S. Jones, K.
  Jones, J. Jost, A. Smith, L. Szathmary
• Logistical support C. Blanchette, B. Broitman,
  P. Halpin, C. Harley, G. Hofmann, M. ODonnell,
  Packard-PISCO techs

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Related Value Added Projects

• NOAA Ecological Forecasting
• Biogeography and climate (E Pacific, W Atlantic)
• PI Wethey, Co PIs Helmuth, Hilbish, Lakshmi,
  Woodin, Power
• Barnacles, Mussels, Sedimentary Organisms
• Baja California to Alaska
• South Carolina to Maine
• ONR Science Technology
• Real time measurement of behavior in infauna
• PI Woodin, CoPIs Wethey, Marinelli
• Worms and burrowing shrimp - pressure sensor
  development

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• NASA Earth Science Enterprise
• National Science Foundation (IBN 9985878 and OCE
  0320064)
• National Oceanic and Atmospheric Administration
  (Ecofore NA04 NOS4780264)
• Office of Naval Research