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Trajectories of Community Change: using traits to understand convergence and divergence When are traits important? “the agony of community ecology” • Convergence and Ecological Dynamics – Deterministic, Contingent, Stochastic • Mechanisms – Local interactions – Regional processes – Productivity and disturbance • Few experimental tests – Even fewer that link convergence with traits • Synthesis and hypotheses to test Determinism Convergence to a stable deterministic endpoint Same conditions = same structure Getis, Getis, Feldman, Introduction to Geography, 11th ed., 2008 Global Convergence Photos © Encyclopedia Britannica Predictable and parallel changes in the trait values across a productivity gradient Diaz et al. 2004 JVS Wright et al. 2004 Transition from the acquisitive (‘fast and leaky’) to conservative (‘slow and tight’) strategies Field patterns indicate relatively large role of contingency Environmental factors only explained 10% of variability among communities McCune and Allen 1985 Can J Botany Narrowing the scale: Community Assembly • Different components of community structure change differently • Different views of community dynamics • When should assembly be deterministic? Views of Community Assembly • Deterministic: environmental conditions and interspecific interactions cause community structure to converge. Shugart et al. 1988 Trowbridge 2007, EcolAp Views of Community Assembly • Deterministic: environmental conditions and interspecific interactions cause community structure to converge. • Contingent: Stochasticity, priority effects, and random drift causes community structure to diverge (or not to converge). – Both stochastic or deterministic (alternative state) dynamics diverge, but differ in the number and predictability of endpoints. Cramer and Hobbs, 2006 Scheffer, 2004 Contingent effects can be deterministic, but still cause divergence. Are traits less predictive? Single Equilibrium Threshold Alternative States Cyclic Mechanisms • Local interactions: – negative feedbacks (resource partitioning, negative freq dependence) lead to high local diversity and convergence – Positive feedbacks (priority effects, self-beneficial species effects on ecosystem processes) lead to high regional diversity and divergence Sp A Sp B Sp C Time Dissimilarity among plots Relative Abundance • E.g., for positive feedbacks: Time Mechanisms • Local interactions: – negative feedbacks (resource partitioning, negative freq dependence) lead to high local diversity and convergence – Positive feedbacks (priority effects, self-beneficial species effects on ecosystem processes) lead to high regional diversity and divergence Sp A Sp B Sp C Time Dissimilarity among plots Relative Abundance • E.g., for negative feedbacks: Time While evidence for both negative and positive feedbacks exist, less clear how they relate to traits Scaled Population Growth Rate/Yr Measure different types of traits? E.g., ones that indicate complementarity at the community level. Initial Frequency Harpole and Suding 2007 Mechanisms • Regional processes: – – – – Dispersal limitation lead to divergence due to chance colonization Large regional pool lead to divergence (Law and Morton 1993) Strong connectedness lead to convergence Distance as a proxy for dispersal Chase (2003) Field patterns: dispersal limitation Dispersal limitation (distance as proxy): study plots that were far apart became more similar over time. Environmental filtering (elevation as proxy): study plots with a large elevation differences became less similar over time But then processes REVERSED direction in southern floodplain. Trowbridge 2007 Ecol App. Dispersal limitation?: species-level priority effects and trait-based assembly rules Composition was compared using Euclidian distance in the first four PCA composition axes Trait groups constructed using hierarchical clustering (Ward’s method) of 87 species and 17 traits into 14 groups. Contrast indicative of dispersal limitation? Fukami et al, 2005 Dispersal limitation?: species-level priority effects and trait-based assembly rules The FG convergence greater than would be expected from random formation of trait groups Fukami et al, 2005 Mechanisms • Environmental influence: Productivity – High Productivity, where competition is important, more rapid trait convergence (Grime 2007) – High productivity, greater potential for priority effects, more divergence (Chase 2003, Fukami and Lee 2006) • Lower species pool at low productivity = convergence • As productivity rises, invading species can alter resource environment or change predator density, which can create positive feedbacks through priority effects • Unclear if at high productivities there can be a shift back to convergence Chase 2003 Effect of nitrogen on convergence varies with productivity average pairwise jaccard distance (dissimilarity) in species composition among all replicate plots within the treatment N fertilization often causes divergence (positive ln RR) Less productive communities are more likely to diverge Chalcraft et al, in press, Ecology • Initial convergence, then divergence • From emergence to seed set, high N does not diverge while low N and ambient diverge. • Traits of the dominant species? Amsinckia shows positive frequency dependence Dissimilarity among plots (ED) Convergence and N availability Low N Ambient Rebecca Aicher, UCI High N Initial Emergence Peak season Seed set Mechanisms • Environmental influence: Disturbance – High disturbance, more regeneration which is stochastic, trait divergence (Grime 2007) – High disturbance, more convergence (Chase 2003) • Less species of the regional pool can persist in disurbed ares compared to undisturbed • Lower densities make positive feedbacks through species effects less likely. Species with colonist traits will be less likely to preclude establishment by other species through interspecific interactions. Chase 2003 Disturbance: drought decreases stochastic community assembly All ponds assembled in identical environmental conditions, after 2 years ½ had drought treatment Ponds that experienced a drought 2 years before were very similar in species composition – deterministic Ponds lacking drought more dispersed, indicating larger role of contingencies Chase, PNAS 2007 Filters control both priority effects and trait distribution • disturbance filter – Reduction in disturbance increases importance of competition – Increase priority effects, alternative states – Increased trait over-dispersion (trait variability among species, trait-group composition divergence) • productivity filter Decreased disturbance or increased production will lead to trait divergence Fukami and Lee 2006, Oikos trait convergence in the established phase and trait divergence in the regenerative phase • productivity filter – convergence in traits related to the physical and chemical processes – These are “effect” traits that drive ecosystems: dry matter production, carbon storage, nutrient cycling, anti-herbivore defense and litter decomposition. • disturbance filter – divergence in regenerative and phenological traits. – these are more likely to be “response” rather than “effect” traits. Grime, 2006, JVS Relationship between effect and response traits • If response and effect traits are not correlated, expect change in ecosystem function to be highly variable • If they are correlated, then change may be either dampened or accelerated • If uniformly distributed, system should be most resilient. Suding et al. 2008, GCB Chaos! Elisa Benincà et al, Nature 2008. Synthesis • Traits may be most predictive of simple deterministic dynamics • Distinction between random divergence and divergence to two or more “states” • Complex contingencies may be very hard to predict with traits – Process strength (systems with strong plantsoil feedbacks) – Different types of traits, species packing (complementarity, relative species effects) • Trade-off between establishment and regenerative traits