Functional traits, trade-offs and community structure in phytoplankton and other microbes

Elena Litchman, Christopher Klausmeier and Kyle Edwards

Michigan State University

Z

NI

P

NPZ

P2

P1

Z

NI

P3

P4

Plankton Functional Groups

P1 P1 P1 P1P1 P1 P1 P1

P1 P1 P1 P1P3

Z

P1 P2 P4

P1P1

P1P5

P1P1

P1P6

P28

P21

P14

P7

Many Species

NI

Z

Continuum of Strategies

NI

Continuum of Strategies

lightcompetitive

nutrientcompetitive

grazing

resistant

com-

petitive

Trait-Based Approaches

• Traits • Environmental gradients• Species interactions• Performance currencies (fitness measures)

McGill et al. 2006 TREE

Trait-Based Approach

1. Ecologically relevant traits2. Trade-offs between these traits3. Mechanistic models of population

interactions4. Fitness5. Source of novel phenotypes

Questions1. What are key traits of (phyto)plankton?2. What are the constraints on and trade-offs

between traits? Can they be predicted from first principles? (How) can they be broken?

3. How are traits distributed along environmental gradients? Can traits explain species distributions?

4. How to link traits below (genomes, gene regulation, physiology) and above (community assembly evolutionary dynamics, phylogeny)?

Ecologically relevant traits (phytoplankton)

Litchman and Klausmeier 2008Annual Rev. Ecol. Evol. Syst.

Example: Nutrient Utilization TraitsBasic model (modified Droop)

nutrientuptake

growth

Traits: µ∞, growth rate at infinite quotaQmin , minimum internal nutrient contentQmax , maximum internal nutrient contentVmax, maximum uptake rate of nutrientK, half-saturation constant for nutrient uptake

Qmin

Vmax

V

K R QQmaxQmin

Q

Trait relationships

Linking traits and community structure:Resource competition

R* decreases (competitive ability increases) when

•m∞ (growth at max Q)•Vmax (max uptake rate)

•K (half-saturation constant)

•Qmin (min quota)

•m (mortality)

Species with the lowest minimum nutrient requirements to sustain growth, R* (Tilman 1982)

What are the trade-offs between traits?

Functional Group Distribution along a Trade-off Curve

Niche differentiation?

diatoms

coccolith

dinoflagellates

greens

Litchman et al. 2007 Ecol. Lett.

Other measures of nutrient competitive ability

Nutrient affinity

Three-way trade-offs

Assembled trait information for all species we could find the data for

Considerable number of missing traits Used statistical imputation techniques to infer missing

trait values Examined relationships between traits and competitive

abilities for N and P

Three-way trade-off

Edwards et al. in press

Three-way trade-off

Edwards et al. in press

Three-way trade-off

Edwards et al. in press

Light utilization traits vs group distribution in nature (US lakes)

Using traits to explain species distributionsEnglish Channel phytoplankton time series

Using traits to explain species distributionsEnglish Channel phytoplankton time series

When N is low

Traits in a Food Web Perspective

Litchman et al. 2010

Traits in a Food Web Perspective

• Need to find ways to reduce dimensionality of traits that describe interactions between trophic levels

• Use scaling relationships and stoichiometry to define traits

• Phenotypic plasticity• Species/group replacements• Trait evolution, niche shifts• Combinations of the above

Possible responses to changing environmental conditions

Adaptive Dynamics Approach(a trait-based approach to evolutionary ecology)

Eco-physiological traits&

allometric relationships Abiotic factors

Growth rate of invader vs resident(competition)

ESS or other long-term evolutionary outcome (size)

Marine vs Freshwater Diatom Cell Sizes

Litchman et al. 2009 PNAS

Diatom Size Evolution

BQR

Litchman et al. 2009 PNAS

Qmin

Q

Vmax

K R

QQmaxQmin

×

Allometries (power relationships)Freshwater Marine

R2=0.49

R2=0.73

R2=0.76

R2=0.61

Litchman et al. 2009 PNAS

ESS (N limitation) at different fluctuation periods, mixed layer depth and sinking

Evolution Experiments3. Assess trait distribution (mean and variance)

before and after experiment under identical conditions

Selection pressure

Mean change Variance changeor both!

Single strain (mutation)Multiple strains (mutation or clonal selection)

A. Single species experiments (single or multiple strains)

B. Species in a community– Limits on trait evolution– Species replacement instead?

Evolution Experiments

Challenges and future directions

• Still very few species with known traits• Significant gaps in trait coverage• With sparse trait data it is difficult to infer

trade-offs, especially their shape• Need to characterize intraspecific variation

and compare with interspecific differences—important for potential evolutionary changes