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Rationalising Biodiversity Conservation in Dynamic Ecosystems www.rubicode.net Rationalising Biodiversity Conservation in Dynamic Ecosystems (RUBICODE)

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Presentation on theme: "Rationalising Biodiversity Conservation in Dynamic Ecosystems www.rubicode.net Rationalising Biodiversity Conservation in Dynamic Ecosystems (RUBICODE)"— Presentation transcript:

1 Rationalising Biodiversity Conservation in Dynamic Ecosystems 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 Rationalising Biodiversity Conservation in Dynamic Ecosystems Predicting the response of ecosystem functioning to environmental change Chapin et al. Nature 2000

3 Rationalising Biodiversity Conservation in Dynamic Ecosystems 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 Rationalising Biodiversity Conservation in Dynamic Ecosystems 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 Rationalising Biodiversity Conservation in Dynamic Ecosystems 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 Rationalising Biodiversity Conservation in Dynamic Ecosystems Structure-function relationships in plants: « soft traits » Density, diameter Specific root length Absorption (nutrients, water) Carbon fluxes (exsudation…) Plant canopy heightLight interception Competitive ability Soft trait Seed mass Function Fecundity Dispersal Establishment Resorption of nutrients; decomposability of litter Traits of living leaves NIRS spectrum

7 Rationalising Biodiversity Conservation in Dynamic Ecosystems Scaling plant function to ecosystems Enquist et al Nature

8 Rationalising Biodiversity Conservation in Dynamic Ecosystems 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 Rationalising Biodiversity Conservation in Dynamic Ecosystems Functional traits of phytoplankton Litchmann & Klausmeier Annu. Rev. Ecol. Evol. Syst. 2007

10 Rationalising Biodiversity Conservation in Dynamic Ecosystems 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 Range of trait values Trait values Relative abundance Weighted mean Particular trait values CWM

12 STAGE 1: Identifying abiotic & biotic factors STAGE 2: 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 the mean trait value of the community Relationships between EF and abundance of growth forms Relationships between EF and the diversity of trait values in a community

14 Plant functional traits at community level The mass-ratio hypothesis Fortunel et al Ecology Weighted mean trait value at the community level. Species effects depend on: 1)their trait value 2)their relative contribution to the community

15 Functional complementarity: Considering the variance rather than the mean Heemsbergen et al Litter decomposition Net effect of diversity Functional dissimilaritySpecies richness 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.

16 Rationalising Biodiversity Conservation in Dynamic Ecosystems 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 Environmental variable Ecosystem function Environmental variable Trait value RESPONSE TRAIT Trait value Ecosystem function EFFECT TRAIT 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 Suding et al GCB Uncertainty +

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

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

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

23 Framework elements and associated assumptions (1)  Assumption 1: Response traits to environmental pressures can be identified - pressure response traits PR i 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: TE i - effects of organisms within trophic level i on the adjacent trophic level i+1 – trophic response traits: TR i+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)  Assumption 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 FE i 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 L i 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: NO 3 - /NH 4 + 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 NH 4 + / urea levels NITRIFIERS Maintenance of soil fertility NH 4 + NO 3 - / NH 4 + NH 4 + supply Urea input TR2 = TE2 = FE2: Growth rate PR3 = TR3 = FE3: Urease activity Growth rate C & energy supply. OM quality NO 3 - Defoliation, trampling, labile N redistribution

30 PR1 = TE1: Leaf traits: N, size, toughness, secondary compounds (lignin), phenology Tree size Branch shedding Riparian buffer restoration PLANTS TR2 bottom : Feeding behaviour, leaf fragmentation rate LEAF SHREDDERS FISH Fish for angling Food supply TR2 bottom = TE2 : Growth rate, development time ~ TE 2 Phenology ~ TR2 top : Body size, weight per unit length TR3 = FE3 = TE3: Body size, growth rate OM quantity & quality Wood provision PR1: suckering, resistance to root anoxia, resistance to shear stress Predation Accounting for more complex trophic networks

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

32 Rationalising Biodiversity Conservation in Dynamic Ecosystems 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 Rationalising Biodiversity Conservation in Dynamic Ecosystems 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 Rationalising Biodiversity Conservation in Dynamic Ecosystems 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


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