Simulating Plant Community Dynamics

1. Simulating Plant Community Dynamics Processes of plant communities - Competition - Facilitation - Mutualism - Resilience Temporal Components - Climax Communities - Stable States - Dynamic Equilibrium Spatial Components - Environmental filters - Local interactions - Distributions - Biodiversity

2. Simulating Plant Community Dynamics Processes of plant communities - Competition - Facilitation - Mutualism - Resilience www.nature.com Temporal Components - Climax Communities - Stable States - Dynamic Equilibrium Platt W.J. 1994. Spatial Components - Environmental filters - Local interactions - Distributions - Biodiversity D’Odorico et al. Global desertification: Drivers and feedbacks..

3. Simulating Plant Community Dynamics Konza LTER Processes of plant communities - Competition - Facilitation - Mutualism - Resilience Temporal Components - Climax Communities - Stable States - Dynamic Equilibrium http://aknhp.uaa.alaska.edu/botany/rare-plant-species-information/ Spatial Components - Environmental filters - Local interactions - Distributions - Biodiversity http://www.saguaro-juniper.com/i_and_i/san_pedro/ecoregions/plant_distribution.html

4. Simulating Plant Community Dynamics Experimental Design - Rarely includes spatial data - Small scale plots - Sessile organisms – long timescale Cedar Creek, MN. LTER. University of Houston: mobile ecosystems

5. Parrott. 2004 Simulating Plant Community Dynamics Simulated Data - Test hypotheses - Suggest future experiments Common Model Frameworks - Probabilistic - Mechanistic - Phenomenological Two Methods Discussed - Cellular Automata -Point process model simulation Silvertown. 1996. Colosanti & Hunt. 2004.. Levin. 1997..

6. Simulating Plant Community Dynamics Cellular Automata

7. Simulating Plant Community Dynamics Cellular Automata: GAMA - Four main sections

8. Simulating Plant Community Dynamics Cellular Automata - Simulated dynamics - Numerous scenarios - Simple rule-based simulations The Ruderal functional group (green) can be thought of as simulating the performance of annual species. Competitors (blue) and Stress tolerators (red) can be thought of as simulating perennial species. Typically, annuals are outcompeted by perennials. However, at a certain level of fecundity (~200 offspring), annual are able to coexist.

9. Simulating Plant Community Dynamics Point process model simulation - spatstat package in R - Point patterns - Create, refine, plot - Correlations and Marks - Point process models - Poisson models - Random patterns & spatial trends Field data. Field data. spatstat generated random patterns.

10. Simulating Plant Community Dynamics Density and Intensity Analysis - Spatial analysis of densities (intensity) - Fit point patterns to models - Analyze performance Relative density by plant type. 3D density plot. 3D Density plots. Envelope plot Smoothed residuals plot.

11. References Balzter, H., Braun, P., & Kohler, W. (1998). Cellular automata models for vegetation dynamics. Ecological Modelling 107, 113-125. Begon, M. T. (2007). Ecology: from individuals to ecosystems 4th Edition. Malden, MA: Blackwell Publishing Ltd. Begon, M., & Wall, R. (1987). Individual variation and competitor coexistence: a model. Functional Ecology, 1, 237-241. Berry, J. K. (1987). A mathematical structure for analyzing maps. Journal of environmental management 11, 317-325. Colasanti, R. L., & Grime, J. P. (1993). Resource dynamics and vegetation processes - A deterministic model using 2 dimensional cellular automata. Functional ecology 7, 169-176. Connell, J. H. (1978). Diversity in tropical rainforests and coral reef. Science 199, 1302-1310. Cowles, H. C. (1899). The ecological relations of the vegetation on the sand dunes of Lake Michigan. The Botanical Gazette, 95-117. Grime, J. P. (1977). Evidence for the existence of three primary strategies in plants and its relevance to ecological and evolutionary theory. American Naturalist 111, 1169-1194. Levin, S. (1998). Ecosystems and the biosphere as complex adaptive systems. Ecosystems I:, 431-436. Molofsky J., B. D. (2004). A new kind of ecology? BioScience Vol. 54 No. 5, 440-446. Pacala, S. L. (1997). Spatial ecology. Princeton: Princeton University press. Silverton J, H. S. (1992). Cellular automaton models of interspecific competition for space--the effect of pattern on process. Journal of Ecology 80, 527-534. Takeyama, M., & Couclelis, H. (1997). Map dynamics: integrating cellular automata and GIS through Geo-Algebra. International Journal of Geographical Information Science 11:1, 73-91. Tomlin, C. D. (1983). A map algebra. Proceedings of the 1983 Harvard Computer Graphics Conference Volume 2, 127-150. Webb, C. e. (2010). A structured and dynamic framework to advance traits-based theory and prediction in ecology. Ecology Letters, 267-283. Wolfram, S. (1986). Theory and applications of cellular automata: Advanced series on complex systems. Singapore: World Scientific Publishing. Wolfram, S. (2002). A new kind of science. Urbana: Mathematica. Yang, Q., Xia, L., & Xun, S. (2008). Cellular automata for simulating land use changes based on support vector machines. Computers & Geosciences 34, 592-602. Zuur, A. F. (2007). Analysing ecological data. New York: Springer.