Ecophysiological Impacts of Climate Change: Performance, Fitness and Extinction
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Join Caroline Williams, PhD and Eric Riddell, PhD as they discuss their research involving climate change and the ecophysiological effects of changing global temperatures on organismal biology and survival. Key Topics Include: Energy use models using microclimate data can accurately predict whole winter energy use. Colder soils in a warmer world: Snow modulates a trade-off between cold exposure and energy use for soil dwelling organisms. How processes at the genetic level can influence ecological processes, such as geographic ranges. Complex methods to make realistic predictions on the ecological impact of climate change.
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Ecophysiological Impacts of Climate Change: Performance, Fitness and Extinction
- 1. Ecophysiological Impacts of Climate Change: Performance, Fitness, and Extinction Eric Riddell, PhD Assistant Professor Ecology, Evolution, and Organismal Biology (EEOB) Iowa State University Caroline Williams, PhD Associate Professor Integrative Biology University of California, Berkeley
- 2. Experts discuss their research involving climate change and the ecophysiological effects of changing global temperatures on organismal biology and survival. Ecophysiological Impacts of Climate Change: Performance, Fitness, and Extinction
- 3. Winter in a Changing World: The Critical Importance of Snow Copyright 2021 C. Williams and InsideScientific. All Rights Reserved. Caroline Williams, PhD Associate Professor Integrative Biology University of California, Berkeley
- 4. Winter is warming faster than summer
- 5. Winter warming is having widespread impacts on biodiversity Osland et al. 2021 Global Change Biology
- 6. Winter warming decreases snowpack Mote et al. 2018. Clim. Atmos. Sci. Northern hemisphere spring snowpack anomalies, 1980 - 2020 Marshall et al. 2020 Curr Opin Insect Sci Red = decreased snowpack Spring snowpack changes, 1955-2016 Sierra Nevada mountain range, California USA
- 7. Snow cover fluctuates in the Sierra Nevada Joshua Cripps Photography June 22nd 2006 June 22nd 2007 Nathan Rank
- 8. Many ectotherms overwinter beneath snow AgPest.co.nz Ferdinand Bada Andy Murray Joseph Berger Tristram Brelstraff Jon Costanza
- 9. Snow determines soil microclimate, and thermal stress Cold snap Big snow fall “Colder soils in a warmer world” -Groffman, 2001
- 10. Sources of mortality in winter Energy depletion Cold mortality Colder soils in a warmer world: Loss of snow cover will increase cold stress but decrease energy stress
- 11. Organismal traits determine response to microclimate temperatures Sinclair et al. 2015 J. Therm Biol Irwin & Lee. 2003 Oikos Energy use Cold tolerance Metabolic rate Temperature LT50 (1hr exposure)
- 12. Moving up a mountain… We do not know how thermal stress on overwintering ectotherms in the soil changes along a snowy elevational gradient Energy depletion Cold mortality Soil temperature ??? Air temperature Snow cover
- 13. Research question How does changing snow cover impact cold and energetic stress, for organisms that overwinter in the soil in snowy mountains?
- 14. Sierra willow leaf beetle, Chrysomela aeneicollis Southern range edge of species range illustrations: Hiroko Udaka Sierra Nevada
- 15. Rich history of study 1980 – 2020 Microclimate monitoring network Beetle surveys Physiology and genetics Collaborators Elizabeth Dahlhoff and Nathan Rank, with PhD candidate Kevin Roberts Bishop CA
- 16. How does snow impact cold stress and energy stress on overwintering beetles along an elevational gradient? Environment Microclimate temperatures Spatial and temporal variation in snow cover Laboratory Metabolic rate-temperature curves Cold tolerance limits (acute and chronic exposures) Energy reserve assays Field Population surveys (phenology) Snow manipulation experiments Ecophysiological Models Energy and Cold Stress test test Kevin Roberts
- 17. Environment: spatial and temporal variation in snow cover Roberts et al. in review GCB Snowy Dry 28 sites, 1980 – 2020 Hourly soil temperatures 5 replicate transects Bishop CA Spatial variation Interannual variation climate change
- 18. Snow alters elevational gradients in cold exposure Cold exposure peaks at mid-elevation, and is higher in dry years Roberts et al. in review GCB
- 19. Ecophysiological energy use model 1) Estimate metabolic rate – temperature curves using respirometry 2) Input microclimate data to estimate oxygen consumption throughout winter 3) Select start and end dates and sum to get oxygen used over winter (repeat iteratively for range of start and end dates observed in field) 4) Convert to energy used (2L oxygen = 1g lipid, compare to empirical measurements Snow Present Snow Excluded Field Experiment 0.589 mg 0.398 mg Model Estimate 0.591 mg 0.417 mg Model Accuracy 99.7% 95.2% Validated model is >95% accurate in predicting energy use in snowy and dry conditions
- 20. Lab validation of energy use models Roberts et al. in prep
- 21. Energy use across elevation Energy use declines with increasing elevation, steeper decline in snowy years due to very high energy use at low elevations Snowy years are longer, and more energetically demanding Roberts et al. in review GCB
- 22. Climate change will alter cold exposure and energy use across the mountains Long Lake, Bishop Creek Roberts et al. in review GCB
- 23. Cold mortality likely occurs due to long freezing periods LT50 (1hr exposure) Lethal time frozen
- 24. Cold and energy stress across elevation • Probability of lethal cold is highest at mid-elevations, not impacted by interannual variation in snow cover Roberts et al. in review GCB
- 25. • Probability of lethal cold is highest at mid-elevations, not impacted by interannual variation in snow cover • Probability of lethal energy depletion is highest at low elevations, and in snowy years Cold and energy stress across elevation Roberts et al. in review GCB
- 26. Conclusions • Trade-off between cold mortality and energy depletion is modulated by interannual variation in snow cover • Snow alters elevational gradients in cold and energy stress, potentially altering selective gradients on these traits for overwintering ectotherms • Impact of interannual variation in snow cover depends on elevation – high elevations will be buffered due to persistent snow cover, and mid elevations will experience increased cold stress • Environment (microclimate) and organismal traits together determine stress exposure
- 27. Take-home message: Climate Change Global Warming “Colder soils in a warmer world” – Groffman 2001
- 28. Thank you! Collaborators: Kevin Roberts Nathan Rank Elizabeth Dahlhoff Jonathon Stillman Doris Bachtrog Ryan Bracewell Andre Szejner Sigal Lisa Treidel Christina Lee Varun Bahl Rose Kang Kamalakar Chatla Colleagues: Brent Sinclair Dan Hahn Ray Huey John Smiley Greg Ragland Michael Kearney Research Facilitation: White Mountain Research Station Denise Waterbury Williams lab: Ecological and Evolutionary Physiology https://www.cmwilliamslab.com/ Sable Systems for all the great respirometry equipment!
- 29. Using Ecophysiology to Predict Extinction Risk From Climate Change Copyright 2021 E. Riddell and InsideScientific. All Rights Reserved. Eric Riddell, PhD Assistant Professor Ecology, Evolution, and Organismal Biology (EEOB) Iowa State University
- 31. How does physiology determine the niche?
- 35. Ecophysiology Understanding how organisms function in their environment
- 36. Ecophysiology Understanding how organisms function in their environment
- 38. Organism
- 39. Organ Organism
- 45. Temperature
- 46. Humidity
- 53. Biophysics links physiology to the local environment
- 54. 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics links physiology to the local environment
- 55. 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Environment Performance Biophysics links physiology to the local environment
- 56. 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Organism Environment
- 57. Organism 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Environment 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics
- 58. Southern Grey-cheeked Salamander Plethodon metcalfi
- 59. Southern Grey-cheeked Salamander Plethodon metcalfi Natural and life history Fossorial Nocturnal Fully terrestrial Lungless
- 60. High water loss rates restrict salamanders to high elevations
- 62. 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2
- 63. 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics
- 64. 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics Physiology
- 65. 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Activity Biophysics Physiology
- 66. 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Foraging Activity Biophysics Physiology
- 67. 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Foraging Activity Biophysics Physiology Fitness
- 68. Foraging Activity 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics Physiology Fitness
- 69. Net energy balance (J) Activity time (hr) 30- 0 - -30- 7- 3.5- 0- Riddell et al. 2017; Ecol. Monogr. 83% of known localities can reproduce Physiology helps to predict geographic range of salamanders
- 70. 30- 0 - -30- 7- 3.5- 0- Physiology helps to predict geographic range of salamanders Riddell et al. 2017; Ecol. Monogr. Net energy balance (J) Activity time (hr) 83% of known localities can reproduce
- 71. Organism 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Environment 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics
- 72. Organism 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics
- 73. Organism 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics
- 74. Organism 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 Climate Change 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics
- 75. Will climate change threaten salamanders with extinction?
- 76. Phenotypic plasticity The expression of multiple phenotypes from a single genotype
- 77. Temperature (°C) VPD (kPa) Riddell et al. 2018, Science Advances Salamanders experience seasonal changes in the environment
- 78. N = 180 N = 180 Resistance (s/cm) Oxygen Consumption (uL/hr) Salamanders adjust metabolism and water loss to seasonal changes
- 79. Linking plasticity to extinction risk from climate change
- 80. Climate Linking plasticity to extinction risk from climate change
- 81. Climate Microclimate Linking plasticity to extinction risk from climate change
- 82. Climate Microclimate Physiology 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Linking plasticity to extinction risk from climate change
- 83. Climate Microclimate Physiology 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics Linking plasticity to extinction risk from climate change
- 84. Climate Microclimate Physiology Activity 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics Linking plasticity to extinction risk from climate change
- 85. Climate Microclimate Physiology Activity Foraging 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics Linking plasticity to extinction risk from climate change
- 86. Climate Microclimate Physiology Activity Foraging 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics Fitness Linking plasticity to extinction risk from climate change
- 87. Climate Microclimate Physiology Activity Foraging 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics Fitness Linking plasticity to extinction risk from climate change
- 88. Climate Microclimate Physiology Activity Foraging Extirpation 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics Fitness Linking plasticity to extinction risk from climate change
- 89. 5 - 0 - -5 - Current 0 200 km Net energy balance (kJ) Energy balance and extinction without plasticity Riddell et al. 2018, Science Advances
- 90. 5 - 0 - -5 - 2100 0 200 km Net energy balance (kJ) Energy balance and extinction without plasticity Riddell et al. 2018, Science Advances
- 91. 5 - 0 - -5 - Current 0 200 km Net energy balance (kJ) Energy balance and extinction without plasticity Riddell et al. 2018, Science Advances
- 92. 5 - 0 - -5 - 0 200 km Net energy balance (kJ) Current Energy balance and extinction with plasticity Riddell et al. 2018, Science Advances
- 93. 5 - 0 - -5 - 2100 0 200 km Net energy balance (kJ) Riddell et al. 2018, Science Advances Energy balance and extinction with plasticity
- 94. 5 - 0 - -5 - 0 200 km Net energy balance (kJ) Current Identify mechanisms and targets of selection Riddell et al. 2018, Science Advances
- 95. Riddell et al. 2019, Nature Commun. Lower water loss rates were associated with more skin lipids
- 96. Vasoconstriction Angiogenesis Lower water loss rates were associated vasoconstriction Riddell et al. 2019, Nature Commun.
- 98. Can physiology predict responses to climate change?
- 102. Grinnell Resurvey Project: 100 Years of Ecology
- 103. the wind came up again about 9 o’clock and has blown disgustingly all day. Grinnell Resurvey Project: 100 Years of Ecology
- 104. MVZ, UC Berkeley Retracing the steps of Grinnell et al.
- 105. Birds and mammals sampled at the same sites over the last 100 yrs
- 107. Physiological consequences of habitat selection Riddell et al. 2021, Science
- 108. Physiological consequences of habitat selection Riddell et al. 2021, Science
- 114. Organism 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Environment 𝜇 = 𝜇0 𝑇0 + 𝐶 𝑇 + 𝐶 × 𝑇 𝑇0 3 2 𝐹𝑝 = 1 + (𝑥2 − 1) × 𝑐𝑜𝑠2𝜉 2𝑥 2𝑠𝑖𝑛−1 1 − 𝑥2 1 − 𝑥2 𝑟𝑏 = 0.93 × 𝜌 × 𝐶𝑝 ℎ𝑐 ℎ𝑐 = 0.48 × 𝐺𝑟 1 4 + 𝑘 𝐷 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 𝐺𝑟 = 𝑔 × 𝛽 × 𝛿𝑇 × 𝐷3 𝑣2 Biophysics
- 116. Collaborators Steve Beissinger Mike Sears Blair Wolf Barry Sinervo Cameron Ghalambor Kelly Zamudio Christina Wells Robert Baldwin Kyle Barrett Michael Carlo Ofir Levy Scott Sillett Evan Apanovich Danielle Perryman Richard Ramirez Kelly Iknayan Undergraduates Carlie Blankenship Justyn Plaskon Jared McPhail Jonathan Odom Jason Damm Meredith Rutledge Megan Matlack Lunden Simpson Chris Gerstle Faye Romero Megan Banke Josh Vanee Walid Naseri Emma Roback Jennifer Tutijan Riggs Mathews Acknowledgements
- 117. Eric Riddell, PhD Assistant Professor Ecology, Evolution, and Organismal Biology (EEOB) Iowa State University Caroline Williams, PhD Associate Professor Integrative Biology University of California, Berkeley Thank you for participating! CLICK HERE to learn more and watch the webinar