45 th International Liege Colloquium 13 th – 17 th May 2013 Liege , Belgium

1. Trait-based representation of diatom diversity in a Plankton Functional Type modelN. Terseleer1, J. Bruggeman2, C. Lancelot1 and N. Gypens11Écologie des Systèmes Aquatiques, Université Libre de Bruxelles, Belgium2Department of Earth Sciences, University of Oxford, UK 45th International LiegeColloquium 13th – 17th May 2013 Liege, Belgium

2. The MIRO model Trait-based approach Trait-based module Results Conclusions • MIRO: a Plankton Functional Type (PFT) model Data 1989-1999: diatoms counts + spp identification Diatom diversity ↑ Relative presence of size classes in the community & Mean Cell Vol MIRO (Lancelot et al., 2005) PFT models: aggregation of many species into one single group (e.g. diatoms) • “average behaviour” • prediction ability with scenarios? • Represent diatom diversity in MIRO • (based on size)

3. The MIRO model Trait-based approach Trait-based module Results Conclusions • How to characterize diversity among phytoplankton?  The trait-based approach Ecological function Reproduction Resource acquisition Predator avoidance Trait values  ecological functions Morphological Trade-offs (cannot maximize all trait values) Fitness is environment-dependent Physiological Trait type Principle Many spp in competition, selection of the fittest Behavioral Size Many key traits co-vary with size Life history Phytoplankton functional traits* Litchman and Klausmeier 2008 *Trait: a well-defined, measurable property of organisms, usually measured at the individual level and used comparatively across species (McGill et al., 2006)

4. The MIRO model Trait-based approach Trait-based module Results Conclusions • How to characterize diversity among phytoplankton?  The trait-based approach Ecological function Reproduction Resource acquisition Predator avoidance Trait values  ecological functions Morphological Cell size Trade-offs (cannot maximize all trait values) Susceptibility to grazing Fitness is environment-dependent Physiological Photosynthesis Biomass synthesis Trait type Principle Many spp in competition, selection of the fittest Nutrient uptake Behavioral Size Many key traits co-vary with size Life history Phytoplankton functional traits • Diatoms diversity is represented, based on size • Size is related to ecological functions

5. The MIRO model Trait-based approach Trait-based module Results Conclusions • Trait-based diatom module in MIRO Diatom Copepods Biomass (DA) affinity growth grazing 00 sed lysis Nutrients (N, P, Si) Cell volume (VDA) Diatom dynamics: growth

6. The MIRO model Trait-based approach Trait-based module Results Conclusions • Trait-based diatom module in MIRO Diatom Copepods Biomass (DA) affinity growth grazing 00 sed lysis Nutrients (N, P, Si) Cell volume (VDA) Diatom dynamics: growth The diatom community is approximated in terms of total biomass and mean Cell volume (Wirtz and Eckhardt, 1996; Norberg et al., 2001; Merico et al., 2009) Mean cell volume dynamics: • the mean cell volume depends on environmental conditions • (nutrients, light, zooplankton)

7. The MIRO model Trait-based approach Trait-based module Results Conclusions • Variability in diatom parameters Many diatom traits co-vary with their cell volume  allometric relationships : (linear on log-log scale) slope and scaling factor : optimized photosynthetic efficiency max growth rate half-saturation constant susceptibility to grazing BCZ range Gismervik et al., 1996 (Mar Pollut Bull) Sarthou et al., 2005 (JSR) Litchman et al., 2007 (Ecol. Lett.) Geider et al., 1986 (MEPS) trade-off Small vs Large diatoms

8. The MIRO model Trait-based approach Trait-based module Results Conclusions • Results: seasonal cycle (climatology 1989-1999) • Diatom biomass (optimized) • 2 blooms

9. The MIRO model Trait-based approach Trait-based module Results Conclusions • Results: seasonal cycle (climatology 1989-1999) • Diatom biomass (optimized) • 2 blooms • Mean cell volume (validation) • information on the community structure

10. The MIRO model Trait-based approach Trait-based module Results Conclusions • Results: seasonal cycle (climatology 1989-1999) • Diatom biomass (optimized) • 2 blooms • Mean cell volume (validation) • information on the community structure • spring bloom: smaller diatoms (102-104 µm3) Chaetocerosspp Thalassiosiraspp • summer bloom: larger diatoms (103-106 µm3) Rhizosoleniaspp Guinardiaspp

11. The MIRO model Trait-based approach Trait-based module Results Conclusions • Results: seasonal cycle (climatology 1989-1999) • Diatom biomass (optimized) • 2 blooms • Mean cell volume (validation) • information on the community structure • Sink and source terms of the mean cell volume • Evolving environmental constrains top-down pressure • bottom-up pressure “pushes” towards smaller size • light: more limiting in winter • nutrients: abundant in winter, progressively depleted… import from adjacent waters • top-down pressure “pushes” towards larger size • copepods: build on 1st bloom  present for the 2d bloom bottom-up pressure

12. The MIRO model Trait-based approach Trait-based module Results Conclusions • Conclusions/perspectives • Trait-based approach • attractive way to add details without increasing uncertainty (allometric relationships) • enables the use of additional data set (+ requires quantitative knowledge about trade-offs) • Application to the Belgian Coastal Zone (MIRO) • good representation of the mean cell volume • understanding of the drivers of changes in community structure • Perspectives • added benefit under different scenarios • model portability in space (variation across regions) and time (interannual runs)

13. THANK YOU