A session on chesson or More equations Than you Probably Want to See at 10:30Am

1. A session on chessonorMore equations Than you Probably Want to See at 10:30Am Benjamin Adams

2. Contents • Background • Interest and Role in Community Ecology • His work • The Lottery Model • Variable Environment Theory • The Storage Effect • Scale-Transition Theory • Issues

3. Background • 1974 B.Sc. University of Adelaide, Australia • 1978 Ph.D. (Departments of Statistics and Zoology), University of Adelaide, Australia • 1978-81 Postgraduate Research Biologist, University of California, Santa Barbara • 1981-90 Professor of Zoology, Botany and Statistics, Ohio State University • 1990-97 Senior Fellow, Research School of Biological Sciences, Australian National University • 1998-05 Professor, Section of Evolution and Ecology, University of California, Davis • 2005-present  Professor, Ecology and Evolutionary Biology, University of Arizona http://www.environment.arizona.edu/peter-chesson https://www.facebook.com/peter.chesson

4. Interest • How organisms interactions and adaptation to variability promotes species diversity and affects ecosystem functioning. http://www.futurity.org/earth-environment/nature%E2%80%99s-eternal-rock-paper-scissors/

5. Role • Theoretical Biologist or Mathematical Modeler Chesson and Warner 1981 Chesson and Elner1989

6. The Work The Lottery Model and derivatives Variable Environmental Theory The Storage Effect Scale-Transition Theory http://whitneyfehr.wordpress.com/2010/03/13/exploring-biomes/ http://www.intelligentspeculator.net/2009/08/page/2/ http://www.vector1media.com/spatialsustain/neon-aims-to-create-a-common-ecological-observation-platform.html

7. The Work The Lottery Model and derivatives

8. The Sale’s Lottery System • L is the number of larvae of species i available • c is a constant representing the relative competitive ability of species i Chesson and Warner 1981

9. Chesson’s Population Model Incorporates stochasticity variable among species Portion of homes filled by species “i” Surviving individuals in species “i” Dead individuals of all other species Birthrate of “i” divided by the birthrate of the rest Chesson and Warner 1981

10. Population Model - Non-overlapping i J i J i J i i i J i i i J J J i i i J i i i J i i i J i i J i i J i J J J J J i J

11. Population Model - Non-overlapping i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i i

12. Population Model - Overlapping i J i J i J i i i J i i i J J J i i i J i i i J i i i J i i J i i J i J J J J J i J

13. Chesson and Warner 1981

14. Chesson and Warner 1981

15. The Work Variable Environmental Theory

16. Variable Environment Model • ri = Long term growth rate of species i • ΔE = relative mean effect of the environment • ΔC = relative mean effect of competition • ΔI = relative mean of the interactions between environment and competition. Chesson 1989

17. ΔC – the competition term • Consists of two parts: • The difference between inter- and intraspecific competition independent of fluctuation • The difference between inter- intraspecific competition which is dependent on competition in the previous time period and nonlinear response. • Example of nonlinear: two species with different dependence on same resource.

18. Chesson 1994

19. ΔI – the interaction term • Composed of three parts • Species specific response to the environment • e.g. different responses to temperature fluctuation • Covariance between environment and competition • e.g. improved condition increase density thereby increasing demand on resources • The growth rates response to both competition and environmental fluctuation • Three different results – additive, subadditive, superadditive • Storage Effect

20. Chesson 1994

21. The Work The Storage Effect

22. The Storage Effect • Competing species can coexist when intraspecific competition outweighs interspecific competition • Fluctuation-dependent 3 part mechanism (ΔI) • Fluctuation must effect birth rate, death rate, or recruitment • Buffered population • Examples = seed banks, hibernation, long-lived adults, refuges for spatial storage effect Chesson 1994 Chesson 2000a Chesson 2000b

23. Buffered population growth • Subadditive results from previous model.

24. The equation Long term growth rate at low populatons Equalizing mechanism Stabilizing mechanism

25. Storage effect i i i i i J i i J i i J i i i i i i i i J i i i i i i J i i i J J i i i i i i J i i i i i i i J i i i i i i J i i i i i i J J i i J i i i J i i J J J J i i J i i i i i J J J i

26. Test of Storage Effect • Pake and Venable 1995 – Sonoran annuals use seed banks to store maintain populations. Variation due to germination factors. • Caceres 1997 – 30 years of plankton data of two species. Diapaused eggs. Extinction for one definite without storage effect • Sears and Chesson 2007 – use of neighborhood competition to show spatial storage effect.

27. The Work Scale-Transition Theory

28. Scale-transition Theory Chesson 2009 Chesson 2011

29. Scale-transition equation Number of individuals in following time point Variability introduced to local dynamics or physical environment Variability introduced by nonlinearity on population density Chesson 2009

30. Scale-transition models • Allows you to incorporate emergent variability produced into a model where data is scaled up to a larger perspective. • Produces testable prediction as to how those emergent properties will relate to smaller scale data (i.e. through nonlinearity and variation) • Propose as a potential alternative to meta-community theory for large scale ecological systems

31. The Work The Lottery Model and derivatives Variable Environmental Theory The Storage Effect Scale-Transition Theory http://whitneyfehr.wordpress.com/2010/03/13/exploring-biomes/ http://www.intelligentspeculator.net/2009/08/page/2/ http://www.vector1media.com/spatialsustain/neon-aims-to-create-a-common-ecological-observation-platform.html

32. Issues with models • No Allee effects • No extinction possible • No effect of location on dispersal • Deriving actual numbers to represent variables still difficult

33. References • Caceres, C. 1997. Temporal variation, dormancy, and coexistence: a field test of the storage effect. Proc. Natl. Acad. Sci. USA 94:9171–75 • Chesson P, Warner R. 1981 Environmental variability promotes coexistence in lottery competitive systems. Am. Nat. 117 (6): 923-943 • Chesson P, Ellner S. 1989. Invasibility and stochastic boundedness in monotonic competition models. J. Math. Biol. 27:117–38 • Chesson, P. 1989. A general model of the role of environmental variability in communities of competing species, in “Lectures of Mathematics in Life Sciences,” 20:97-123 Amer. Math. Soc., Providence. • Chesson, P. 1994. Multispecies competition in variable environments. Theo. Pop. Bio. 45:227–276. • Chesson, P. 2000a. Mechanisms of maintenance of species diversity. Ann. Rev. Ecol. System. 31: 343-366. • Chesson, P. 2000b. General theory of competitive coexistence in spatially varying environments. Theor. Popul. Biol. 58:211-237 • Chesson, P. 2009. Scale transition theory with special reference to species coexistence in variable environments. J. Bio. Dynamics. 3 (2-3):149-163 • Chesson, P. 2012. Scale transition theory: Its aims, motivations and predictions. Ecol. Complex. doi:10.1016/j.ecocom.2011.11.002 • Pake C, Venable L. 1995. Is coexistence of Sonoran desert annual plants mediated by temporal variability reproductive success. Ecology 76 (1): 246–261. • Sears A, Chesson P. 2007. New methods for quantifying the spatial storage effect: an illustration with desert annuals. Ecology 88 (9): 2240–2247