1.  PIs: B. Helmuth, T. J. Hilbish, V. Lakshmi, D. Wethey, S. Woodin  Post Docs: S. Chintalapati, S. Gilman, N. Mieszkowska, S. Pincebourde, A. Zenone  Students and Techs: P. Brannock, S. Chhotray, E. Fly, K. Jones, S. Jones, R. Rognstad, A. Smith, L. Yamane  Teachers: C. Dryden, B. Gill

2. Variable of interest (e.g. Temperature) Space (e.g. Latitude) Time (years, decades, centuries) Ecological and Environmental Gradients

3. Variable of interest (e.g. Temperature) Space (e.g. Latitude) Time (years, decades, centuries) Reality

4. Variable of interest (e.g. Temperature) Space (e.g. Latitude) Time (years, decades, centuries)

5.  Environmental “gradients” exist comprise signals of different frequencies; however, we often only pay attention to the low frequency components (e.g. long term trends)  E.g. Effects of PDO, ENSO in time counteract or amplify warming trends; effects of factors such as upwelling, local fog, etc. in space can trump latitude  Do we really know how patterns of environmental stressors change in space and time?  What is signal and what is noise? (and what frequencies do we need to measure and record?)

6. To an organism, all weather, climate, and climate change is local, at the level of the microhabitat Seastar at ~12°C Mussel at ~21°C

7.  Two organisms exposed to identical microclimates can often show very different body temperatures  Physiological effects are both direct and indirect: ◦ Mussels die at body temperatures in excess of 36°C when exposed at low tide (KA Smith) and/or when food supply is low (Schneider et al.) and/or when winter water temps <10.5°C (Wethey) ◦ Seastars reduce foraging on mussels when exposed to aerial body temperatures above 14°C (Pincebourde et al.)

8. Climate Models and Weather Data Theoretical Models of Organism Body Temperature Make and Test Hypotheses in space and Time Realized Niches Experimental Physiological and Ecological Data Primary Space Occupiers Invasive spp. Keystone spp. Fundamental Niches Species Interactions (Competition, Predation, Facilitation) (spatially and temporally explicit maps of distribution, abundance, and growth)

10. Mussel temperatures have been steadily increasing since 2000: why?

11.  Not surprisingly, magnitude of variables such as air and water temperature often vary from physiologically relevant factors such as body temperature  However, patterns both quantitatively and qualitatively vary

12. Out of phase In phase Body temperature vs air and water temperature of intertidal mussels Helmuth 2009 J. Exp. Biol.

13. Comparative Patterns of Autocorrelation

14. ’00’01‘02’03’04’05’06 Tatoosh Boiler Bay Strawberry Hill Cape Arago Trinidad Cape Mendocino Bodega Santa Cruz Monterey Cambria Jalama Alegria 0/year0 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

15.  M gallo  Moving north in English Channel  Abundant in Brittany  Rarer on French Biscay Coast  Abundant in Iberia  Cold days in winter inhibitory RW Reynolds, NOAA NCDC, GHRSST OISST-AVHRR Daily 1985-present 1985 2007

16. Latitude Temperature (°C) Alive Dead Present Day Barrier Dispersal Dead Alive

17. Latitude Temperature (°C) Alive Dead Barrier Dispersal

18. Latitude Temperature (°C) Barrier: sp 1 only No barriers Species 2 Species 1 Sp. 1 threshold Sp. 2 threshold Barrier: both spp.

19. Marine Protected Areas: must work now and in the future 20-50 years Now Climate Change Abundance Latitude Abundance Climate Change

20. Now Climate Change 20-50 years 4) Plan network of “stepping stones” in advance By forecasting changes in abundance of key species, we can design MPAs so that distance between current and future stepping stones is set by dispersal ability of key species

21.  Mechanistic forecasting has similar goals to statistical modeling, but does not assume all edges are set by same environmental factors  Time intensive, so focus on key “foundation” species that directly or indirectly drive patterns of biodiversity and ecosystem function  Can complement statistical approaches by targeting specific needs of resource managers

22.  NASA grants NNG04GE43G and NNX07AF20G  NOAA Ecofore grant NA04 NOS4780264