1. Rationalising Biodiversity Conservation in Dynamic Ecosystems
(RUBICODE)
How trait linkages within and across trophic levels underlie the response of ecosystem functioning to environmental change
For further information contact Sandra Lavorel
Funded under the European Commission
Sixth Framework Programme
Contract Number:

2. Predicting the response of ecosystem functioning to environmental change
Chapin et al. Nature 2000

3. Key challenges
Taking into account biotic variability into projections of ecosystem functioning – at different scales
Linking biotic responses and changes in ecosystem functioning
Biodiversity – ecosystem functioning relationships
Original question: does biodiversity affect ecosystem functioning?
1990 – 2000 : Biodiversity can matter (Loreau et al. 2001, Balvanera et al. 2006)
Current question: which components of biodiversity affect ecosystem functioning and through which mechanisms ?
Functional diversity (Hooper et al. 2005, Diaz et al. 2006)
Interactions within trophic levels (Chesson et al. 2002)
Interactions among trophic levels (Thébault & Loreau 2006, Suding et al. 2008)
New challenge: understanding the role of functional diversity across trophic levels

4. Presentation outline
Functional traits and prediction of ecosystem functioning: some basics
Going dynamic: linking organisms responses and ecosystem effects through functional traits (the ‘Holy Grail’)
Going multi-trophic : a new framework for the understanding and projection of ecosystem functions determined by multiple trophic levels using functional traits (the next Holy Grail)
Framework applications and challenges

5. Defining functional effect traits
Relationships between organisms’ characters and key ecosystem functions
Traits through which organisms :
Consume or transform resources
Modify the physical structure of the habitat
Modify the chemistry of the environment
Interact with other organisms (incl. dispersal)
In some cases (e.g. microbes) the traits sensu stricto are actually not known, just the participation to specific processes
Traits as tools to quantify ecosystem delivery
Functional diversity*
Ecosystem
function
* Trait value at species or community level; functional divergence

6. Structure-function relationships in plants: « soft traits »
Seed mass
Function
Fecundity
Dispersal
Establishment
Plant canopy height
Light interception
Competitive ability
Resorption of nutrients;
decomposability of litter
Traits of living leaves
NIRS spectrum
Density, diameter
Specific root length
Absorption (nutrients, water)
Carbon fluxes (exsudation…)

7. Scaling plant function to ecosystems
Enquist et al Nature

8. Functional traits in other organisms
Morphological characteristics:
Body size, feeding apparatus, wings…
Life history
Diet and feeding behaviour
Ecosystem effects
e.g. microbial activities
And…
Taxonomic groups with specific functions
Habitat
Key point: characteristics of individuals that can be related to mechanisms through which they are affected by environmental factors and/or they affect ecosystem functioning

9. Functional traits of phytoplankton
Litchmann & Klausmeier Annu. Rev. Ecol. Evol. Syst. 2007

10. Review of evidence for relationships between traits and ecosystem functioning
247 references, 548 entries for trait-ES relationships across organisms (De Bello et al. 2008)

11. Abiotic factors Ecosystem processes and services Functional diversity
Trait values
Relative abundance
Range of trait values
Weighted mean
Particular trait values
CWM

12. STAGE 1: Identifying abiotic & biotic factors
Finding the best predictive model
What are the relative contributions of abiotic factors, community mean trait values, trait value distribution, and individual species effects on ecosystem functioning?

13. Available evidence: which dimensions of functional diversity?
Measures of ecosystem function for cultures of single species
Relationships between EF and abundance of growth forms
Relationships between EF and the diversity of trait values in a community
Relationships between EF and the mean trait value of the community

14. Plant functional traits at community level The mass-ratio hypothesis
Weighted mean trait value at the community level.
Species effects depend on:
their trait value
their relative contribution to the community
Fortunel et al Ecology

15. Net effect of diversity
Functional complementarity: Considering the variance rather than the mean
Litter decomposition
Net effect of diversity
Species richness
Functional dissimilarity
Effects of soil macrofauna on the maintenance of soil fertility :
In the presence of several functional groups (earthworms, isopods, chilopods) species number has no effect on decomposition.
Functional diversity is the driving variable.
Heemsbergen et al. 2004

16. Going dynamic: Projecting ecosystem functioning
Determine how the presence / abundance of organisms (with different effect traits) is modified by environmental change
Response traits: Traits that determine organisms’ ability to:
Cope with different environmental conditions
Abiotic: temperature, water, pH, light…
Nutritional
Disturbances
Colonize newly available habitat
Dispersal abilities (propagules, individuals)
Regeneration potential
Environmental variable
Trait value

17. The Holy Grail: Overlapping response and effect traits
Trait value
Ecosystem
function
EFFECT TRAIT
Environmental variable
Trait value
RESPONSE TRAIT
Environmental variable
Ecosystem
function
Lavorel & Garnier Funct. Ecol. 2002

18. Overlapping response / effect traits
Can include three types of relationships:
Response trait = effect trait
Example: leaf nitrogen content determines response to grassland management and affects fodder production, maintenance of soil fertility
Response trait correlated with effect trait through functional linkage
Example: defence mechanisms in alternative preys for natural enemies (effect trait) are correlated with body size (response trait to vegetation composition)
Response trait linked with effect trait without functional linkage, through developmental or phylogenetic constraints
Example: legumes decrease following grassland management intensification; legume flowers are those favoured by vulnerable bee species (long-tongued)

19. Varying degrees of response-effect overlap
Uncertainty +
Suding et al GCB

20. Response – effect traits overlap: Soil water retention through summer in mountain grasslands
Gross et al. New Phytol. 2008
Suding & Goldstein New Phytol. 2008

21. Beyond plants: multi-trophic control of ecosystem functioning
de Bello et al. 2008

22. Environmental pressure
A new framework to account for the multi-trophic control of ecosystem functioning
Environmental pressure
Pressure
response traits
PR1
Trophic
response traits
TR2
Trophic level 1
Trophic level 2
Linkage L1
Linkage L2
Trophic
effect traits
TE1
Functional
effect traits
FE2
Ecosystem function

23. Framework elements and associated assumptions (1)
Assumption 1: Response traits to environmental pressures can be identified - pressure response traits PRi
Environmental variable
Trait value *
* Trait value: single species, or community-level functional diversity metric: community weighted mean, functional divergence…

24. Framework elements and associated assumptions (2)
Assumption 2: interactions between trophic levels can be related to:
trophic effect traits: TEi - effects of organisms within trophic level i on the adjacent trophic level i+1
trophic response traits: TRi+1 - response of organisms within trophic level i+1 to organisms from trophic level i

25. Evidence for trait-related interactions
Fenster et al Annu. Rev. Ecol. Evol. Syst.
Trophic effect traits: plant traits and pollinators
Stang et al Oecologia
Trophic response traits:
traits of pollinators associated with floral traits

26. Framework elements and associated assumptions (3)
The effects of organisms within each trophic level i on the ecosystem function of interest can be related to particular functional traits - functional effect traits FEi
Functional diversity*
Ecosystem
function
* Single species, or community-level functional diversity metric: community weighted mean, functional divergence…

27. Framework elements and associated assumptions (4)
Assumption 4 : Within each trophic level i, linkages Li among the different types of response and effect traits can be identified

28. Summary of framework features
Applying the original ‘Holy Grail’ assumptions (1, 3 and 4) to more than one trophic level to examine trait overlaps within each of several trophic levels
Considering new sets of effect and response traits associated with biotic interactions among levels (assumption 2)
Extending assumption 4 to overlaps and associations among different kinds of response and effect traits

29. Influence of grassland management through grazing
on soil N provision via nitrogen transformations
PR1c = TE1:
leaf N, phenolics, and root exudates
PR1a: Stature,
meristem location
PR1b: NO3-/NH4+ assimilation
Grazing intensity
PLANTS
FE2:
Specific activity
TR2: Ability to use
fresh versus
recalcitrant OM
MINERALISERS
FE3a: Specific activity nitifiiers. FE3b: Ability use urea as substrate
PR3 = TR3:
Sensitivity to high NH4+/ urea levels
NITRIFIERS
Maintenance of soil fertility
NH4+
NO3- / NH4+
supply
Urea input
TR2 = TE2 = FE2:
Growth rate
PR3 = TR3 = FE3:
Urease activity
C & energy
supply.
OM quality
NO3-
Defoliation, trampling,
labile N redistribution

30. Accounting for more complex trophic networks
Riparian buffer restoration
PLANTS
LEAF SHREDDERS
FISH
PR1: suckering, resistance to root anoxia, resistance to shear stress
TR2bottom : Feeding behaviour,
leaf fragmentation rate
OM quantity
& quality
Wood provision
Food
supply
PR1 = TE1:
Leaf traits: N, size, toughness, secondary compounds (lignin), phenology
Tree size
Branch shedding
TR2bottom = TE2 :
Growth rate, development time
~ TE2 Phenology
~ TR2top: Body size, weight per unit length
TR3 = FE3 = TE3: Body size, growth rate
Predation
Fish for angling

31. Combining several interaction networks: Impact of field margin management on multiple ecosystem services

32. A framework for functional biodiversity research
A heuristic tool to summarise existing knowledge, test hypotheses, and identify knowledge and data gaps on biotic relationships and processes that underpin different ecosystem functions
Flexbility of the framework:
Number and arrangement of trophic levels
Types of biotic interactions : trophic but not only
Diversity of possible configurations
Using trait syndromes rather than traits
Comparing implementations under different contexts (climate, fertility...)
Main current limitations :
Knowledge and data availability for traits in many organisms other than plants
Quantitative relationships between trait-based metrics (functional diversity) and ecosystem processes

33. Challenges: Analysing complex dynamics underlying ecosystem functioning
Do stronger linkages between response and effect traits lead to more predictable effects of environmental change on ecosystem services?
When do feedbacks to environmental pressures or between trophic levels enhance or reduce predictability of ecosystem services?
Do trait effects on ecosystem functioning weaken with increasing trophic levels, scales, and with multiple driver interactions?

34. Applications
Quantitative assessments of the effects of environmental change on ecosystem services provided by biodiversity
Indication of ecosystem services
Guiding ecological engineering through the choice of plant trait assemblages that promote the recovery of a multi-trophic community most likely to provide the desired ecosystem services