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V. Anabalón, J. Arístegui, C.E. Morales ,

The structure of planktonic communities under variable coastal upwelling conditions conditions off cape Ghir (31ºN), in the Canary Current System (NW Africa). V. Anabalón, J. Arístegui, C.E. Morales ,

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V. Anabalón, J. Arístegui, C.E. Morales ,

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  1. The structure of planktonic communities under variable coastal upwelling conditions conditions off cape Ghir (31ºN), in the Canary Current System (NW Africa) V. Anabalón, J. Arístegui, C.E. Morales, I. Andrade, M. Benavides, M.A. Correa-Ramirez, M. Espino, O. Ettahiri, S. Hormazabal, A. Makaoui, M.F. Montero, A. Orbi

  2. Background Area of permanent upwelling, narrow shelf, fronts & filaments, low NO3 concentration compared to other areas and regions. Pelegri et al. 2005

  3. MOTIVATION Do changes in upwelling intensity produce significant spatio-temporal variations in the structure of planktonic communities (coastal and coastal transition zones -CTZ)? Alonshore wind stress SST Chl-a Samplings

  4. APPROACHES AND METHODS • Oceanographiccruises(5): Dec-2008; Feb-, June, Aug, Oct-2009; transectperpendicular to the coast (7 stations, coast to app. 150 Km offshore. - Hydrographic data: CTD with fluorescence sensor. Estimates of water density (as sigma-t) and stratification intensity (J m-3) according to Bowden (1983). - Seawatersamplesat 5 levels (0, 25, maximum fluorescence depth, 90, 150 m depth): Niskinbottles (5 L); analyses: * Macro-nutrients (NO2+NO3, PO4, Si) * Chl-a (total, <20 and <3 µm) * Micro-organisms: picoplankton (flow-cytometry; only 3 cruises), nanoplankton (epifluorescence and Utermöhl), and microplankton (Utermöhl). • Satellite time series data: the wider perspective - Winds (CCMP; ¼° x ¼° resolution); - SST (AVHRR Pathfinder V5.0 from NOAA; ftp://data.nodc.noaa.gov/pub/data.nodc/Pathfinder) at 2x2 Km resolution; - Sealevelanomaly (combinedprocessing of TOPEX/JASON at ¼° x ¼°resolution - ERS altimeter data distributed by AVISO (http://aviso.oceanos.com)  surface geostrophic flow field; - Chl-a form HERMES (combinedsensors (MODIS, MERIS, SeaWiFS), obtainedfromGlobColorWeb (ftp.fr-acri.com).

  5. APPROACHES AND METHODS (2) • Planktonbiomass (C): - Nanoplankton and microplankton: geometricmodels for cell volume estimates (Chrzanowski & Simek, 1990; Sun & Liu 2003). C/biovolume conversion factors: Menden-Deuer & Lessard (2000) for CIL, DIN, and DIAT; Heinbokel (1978) for Tintinnids; and Borsheim & Bratbak (1987) for FLA. - Autotrophicpicoplankton: 29 fg C/cell - PRO, 100 fg C/cell - SYN (Zubkov et al., 2000), 1.5 pg C/cell - PEUK (Zubkov et al., 1998); HB: 12 fg C/cell (Fukuda et al., 1998). - Mixotrophy (DIN + CIL), literature recognition of mixotrophyatspecies/genuslevel (40% autotrophy) in the case of microplankton (no autofluorescence data available). • Statistics: multivariate analyses, PRIME software v.6 (Clarke & Warwick, 2001; Clarke & Gorley, 2006) - MDS (nonmetricmultidimensionalscaling) for cluster identification; hydrographic and biological matrices; significance of the clusters – SIMPROF - ANOSIM for analysis of similarities; SIMPER for groups/species contributions to similarities and dissimilaritiesbetween clusters in the biological matrix. - BIO-ENV and RELATE to analyze the associations between the biological data and the environmental variables. The best combinations of variables determined by BIO-ENV weresubjected to furtheranalysis (LINKTREE) to identify the variable(s) which best represented the separation of the biological components intodifferent groups/cluster.

  6. WEUP SST: 16-17ºC SST grad.: <2ºC Wind: 8-12 m/s NE Low stability RELAX SST: 18ºC SST grad.: 3.5ºC Wind: 4-8 m/s NW MOUP SST: 19-20ºC SST grad.: 4ºC Wind: 4-8 m/s NE Shoaling of isopycnals at the coast & counterflow

  7. HYDROGRAPHIC CLUSTERS Variables contribution to cluster separation: - nutrient concentration: WEUP vs. E1 - nutrient concentration and SST: MOUP vs. E1 - water density, SST and Nº daysfavourable to upwelling: WEUP vs. MOUP Cross-shore variability (E2-E4 vs. CTZ E5-E7 stations)

  8. BIOLOGICAL CLUSTERS • DINOFLAGELLATES (43%) contributedmost to cluster separation (E1 vs. rest). DIATOMS (21%) and CILIATES (21%). • Dissimilaritybetween: WEUP - RELAX: DINOFLAGELLATES (38%) and CILIATES (32%). WEUP - MOUP: DINOFLAGELLATES (37%) and DIATOMS (34%). RELAX - MOUP: DIATOMS (34%); CILIATES (24%) and DINOFLAGELLATES (22%). • Inclusion of the picoplankton fraction (only 3 samplings): minimal influence in terms of biomass.

  9. BIOMASS: micro+nanoplankton • Dominance of microplankton (>53%): DINOFLAGELLATES + CILIATES • Nanoplankton: DINOFLAGELLATES + FLAGELLATES • Autotrophic-C: DIATOMS exceptions Dec-08: APP, AFL, ADIN Aug-09: ADIN + DIAT As Chl-a: nanoautotrophs. • Heterotrophic-C: DINOFLAG.

  10. RELEVANCE OF MIXOTROPHY Mean H:A biomass ratios (pico-to micro): 3 samplings - No correction mixotrophy: >1 (invertedpyramid) - Correction for mixotrophy: <1 (normal pyramid)

  11. BIOMASS-C STRUCTURE IN CAPE GHIR: micro+nanoplankton BIOMASS DIFFERENCES (Linktree)

  12. CONCLUSIONS RESTRICTIONS: SNAPSHOT OF THE SYSTEM Two main upwelling phases  weak (no gradients acrosshore) and moderate (strong crosshore gradients). Separation of the most coastal station (depth effect). Cluster formation influenced by nutrient concentration (spatial), SST and upwelling constancy (temporal). Hydrographic clusters were representative of the spatio- temporal variability in planktonic assemblages  changes in the upwelling intensity do influence community structure. The dominant functional groups (C-biomass) were mixed assemblages of DIN and CIL (>51%); DIAT contributions were moderate to low (<35%). Total Chl-a was dominated by the nanoplankton and mixotrophy is important in H:A evaluation for this system.

  13. QUESTIONS UNSOLVED Is upwelling intensity in the region (NW Africa) increasing or decreasing ??? Is the presence of mixed autotrophic assemblages a consequence of recent changes in upwelling intensity in this region ??? How well can be represent mixotrophs in primary production (PP) estimates and in ecosystem models??? How well can be represent other types of PP or nutrient requirements ??? Heterotrophic:autotrophic ratios – how well can be estimate the biomass of the diverse components ??? (basic!) Biomass estimates: Chl-a versus Carbon; relevance in remote sensing estimates of primary production (changing C:Chl-a ratios)

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