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 Transition from the acquisitive (‘fast and leaky’) to conservative (‘slow and tight’) strategies Diaz et al JVSWright et al. 2004

Environmental factors only explained 10% of variability among communities McCune and Allen 1985 Can J Botany Field patterns indicate relatively large role of contingency

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. Trowbridge 2007, EcolAp Shugart et al. 1988

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 Alternative States Threshold 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 E.g., for positive feedbacks: Dissimilarity among plots Time Relative Abundance Sp A Sp B Sp C

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 E.g., for negative feedbacks: Dissimilarity among plots Time Relative Abundance Sp A Sp B Sp C

While evidence for both negative and positive feedbacks exist, less clear how they relate to traits Initial Frequency Scaled Population Growth Rate/Yr Harpole and Suding 2007 Measure different types of traits? E.g., ones that indicate complementarity at the community level.

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 Trowbridge 2007 Ecol App. 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.

Dispersal limitation?: species-level priority effects and trait-based assembly rules Fukami et al, 2005 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 The FG convergence greater than would be expected from random formation of trait groups Dispersal limitation?: species-level priority effects and trait-based assembly rules

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 Chalcraft et al, in press, Ecology 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

Convergence and N availability Dissimilarity among plots (ED) Initial Emergence Peak season Seed set Low N Ambient High N 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 Rebecca Aicher, UCI

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 Chase, PNAS 2007 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

Filters control both priority effects and trait distribution Fukami and Lee 2006, Oikos 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

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 Suding et al. 2008, GCB 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.

Elisa Benincà et al, Nature Chaos!

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 plant- soil feedbacks) –Different types of traits, species packing (complementarity, relative species effects) Trade-off between establishment and regenerative traits