Relationships between environmental parameters and the microbenthic loop of Posidonia oceanica meadows at small spatial scale

Transcription

1 Relationships between environmental parameters and the microbenthic loop of Posidonia oceanica meadows at small spatial scale Dorothée C. Pête, Alvera Azcárate, A. and Gobert, S. Photo: A. Abadie

2 Introduction P. oceanica meadow : a carbon sink? Leaves and living rhizomes Canopy level Living roots and rhizomes Dead roots and rhizomes Matte = Carbon sink (29-36 % of P. oceanica primary production) Adapted from Boudouresque et al., 2015

3 Introduction P. oceanica meadow : a carbon sink? % of sedimentary OM = Highly refractory material (Danovaro et al., 1996) P. oceanica detritus: - Rich in structural compounds - Low protein content But Velimirov et al. (2016) questioned the carbon balance in this ecosystem How does OM (and carbon) degradation/storage happen in this ecosystem?

4 Introduction Roles of a major sub-system: the microbenthic loop?

5 Aims Aims of this study Role of the microbenthic loop in OM (and carbon) degradation/storage in this ecosystem? Aims: - Heterogeneity at small spatial scale? - Role in structuring communities - Role in ecological processes - Relationships between the microbenthic loop heterogeneity and environmental parameters at small scale?

6 Material & methods Sampling strategy 125 cm cm points randomly chosen - P. oceanica shoot density inside every 25x25 cm frames - Pore water - Cores

7 Material & methods Measured parameters Sampled Core (0-2 cm) Microbenthic loop component Total Organic matter (TOM) (mg.gdw -1 ) Chlorophyll a (Chl-a) (µg.gdw -1 ) Total Bacteria Biomass (TBB) (µgc.gdw -1 ) Total Meiofauna Abundance (TMA) (nb.gdw -1 )

8 Material & methods Measured parameters Sampled Environmental parameters Sampled Environmental parameters Core (0-2 cm) Phaeopigments (Phaeo.) (µg.gdw -1 ) Core (0-2 cm) TOC/TN Frequency of dividing bacteria cells (FDC) (% of total bacteria) Total Phosphorus (TP) (% DW) TOC/TP Gravel (% DW) TN/TP Sand (% DW) Vegetal fibres (% DW) Mud (% DW) Oxygenation status δ 13 C ( ) Pore water [NO 2- + NO 3- ] (µm) Total Carbon (TC) (% DW) [NH 4+ ] (µm) Total Organic Carbon (TOC) (% DW) [HPO 4 2- ] (µm) Total Nitrogen (TN) (% DW)

9 Material & methods Measured parameters Sampled Core (0-2 cm) Grain size Environmental parameters Phaeopigments (Phaeo.) (µg.gdw -1 ) Frequency of dividing bacteria cells (FDC) (% of total bacteria) Gravel (% DW) Sand (% DW) Mud (% DW) δ 13 C ( ) Total Carbon (TC) (% DW) Total Organic Carbon (TOC) (% DW) Total Nitrogen (TN) (% DW) Sampled Core (0-2 cm) Pore water Environmental parameters TOC/TN Total Phosphorus (TP) (% DW) TOC/TP TN/TP Vegetal fibres (% DW) Oxygenation status [NO 2- + NO 3- ] (µm) [NH 4+ ] (µm) [HPO 2-4 ] (µm)

10 Material & methods Measured parameters Sampled Core (0-2 cm) OM and sediment quality Environmental parameters Phaeopigments (Phaeo.) (µg.gdw -1 ) Frequency of dividing bacteria cells (FDC) (% of total bacteria) Gravel (% DW) Sand (% DW) Mud (% DW) δ 13 C ( ) Total Carbon (TC) (% DW) Total Organic Carbon (TOC) (% DW) Total Nitrogen (TN) (% DW) Sampled Core (0-2 cm) OM and sediment quality Pore water Environmental parameters TOC/TN Total Phosphorus (TP) (% DW) TOC/TP TN/TP Vegetal fibres (% DW) Oxygenation status [NO 2- + NO 3- ] (µm) [NH 4+ ] (µm) [HPO 4 2- ] (µm)

11 Material & methods Measured parameters Sampled Core (0-2 cm) Environmental parameters Phaeopigments (Phaeo.) (µg.gdw -1 ) Frequency of dividing bacteria cells (FDC) (% of total bacteria) Gravel (% DW) Sand (% DW) Mud (% DW) δ 13 C ( ) Total Carbon (TC) (% DW) Total Organic Carbon (TOC) (% DW) Total Nitrogen (TN) (% DW) Sampled Core (0-2 cm) Pore water Nutrients Environmental parameters TOC/TN Total Phosphorus (TP) (% DW) TOC/TP TN/TP Vegetal fibres (% DW) Oxygenation status [NO 2- + NO 3- ] (µm) [NH 4+ ] (µm) [HPO 4 2- ] (µm)

12 Total Organic Matter (TOM) C.V. = % of the mean TOM (mg.gdw -1 ) C.V. = SD as a percentage of the mean

13 TOM C.V. = % of the mean TOM (mg.gdw -1 ) No relationship with microbenthic loop components

14 TOM Multiple regression analysis : - Selected parameter and regression coefficient: [NH 4+ ] / Selected model R 2 = (p-value = 0.028) A B TOM (mg.gdw-1)

15 TOM Multiple regression analysis : - Selected parameter and regression coefficient: [NH 4+ ] / Selected model R 2 = (p-value = 0.028) A Negative relationship B TOM when [NH 4+ ] [NH 4+ ] = result of TOM degradation processes? But other processes involved at small scale TOM (mg.gdw-1)

16 Microphytobenthos (Chl-a) C.V. = % of the mean Chl-a (µg.gdw -1 ) Highest of the microbenthic loop

17 Microphytobenthos (Chl-a) C.V. = % of the mean Chl-a (µg.gdw -1 ) Highest of the microbenthic loop No relationship with microbenthic loop components

18 Microphytobenthos (Chl-a) C.V. = % of the mean Chl-a (µg.gdw -1 ) Highest of the microbenthic loop No relationship with microbenthic loop components No significant relationship with any environmental parameter

19 Microphytobenthos (Chl-a) C.V. = % of the mean Highest of the Other parameters are linked with the microphytobenthos microbenthic loop spatial pattern at small scale No relationship with microbenthic loop components Chl-a (µg.gdw -1 ) No significant relationship with any environmental parameter

20 Microphytobenthos (Chl-a) Multiple regression analysis : - Selected parameter and regression coefficient: log(fdc) / Selected model R 2 = (p-value = 0.085) A B Chl-a (µg.gdw-1)

21 Microphytobenthos (Chl-a) Multiple regression analysis : - Selected parameter and regression coefficient: log(fdc) / Selected model R 2 = (p-value = 0.085) A Relationship between Chl-a and bacteria productivity in some B areas Labile material amongst refractory matter Preferred food source for bacteria? Other processes probably predominant in other areas Chl-a (µg.gdw-1)

22 Total Bacteria Biomass (TBB) C.V. = % of the mean TBB (µgc.gdw -1 )

23 Total Bacteria Biomass (TBB) TBB (µgc.gdw -1 ) 2.5 r = (p = 0.026) Phaeo. (µg.gdw -1 ) TBB (µgc.gdw -1 )

24 Total Bacteria Biomass (TBB) TBB (µgc.gdw -1 ) Relationship between bacteria and r dead = vegetal (p = 0.026) material Relationship with results obtained for Chl-a Relationship between bacteria 2.0and living and dead vegetal material Phaeo. (µg.gdw -1 ) TBB (µgc.gdw -1 )

25 Total Bacteria Biomass (TBB) Multiple regression analysis : - Selected parameters and regression coefficients: - Log(FDC) / TC / Log(TOC/TN) / [NH 4+ ] / (N.S.) - Log([HPO 4 2- ]) / Selected model R 2 = (p-value = 0.047)

26 Total Bacteria Biomass (TBB) Multiple regression analysis : - Selected model R 2 = (p-value = 0.047) TBB (µgc.gdw -1 )

27 Total Bacteria Biomass (TBB) Multiple regression analysis : - Relationship Selected parameters between and TBB regression and dead vegetal coefficients: material - Log(FDC) / TC / BUT - Log(TOC/TN) / TBB - [NH spatial 4+ ] / heterogeneity (N.S.) is also related to a combination of FDC, - Log([HPO 2- sediment quality 4 ]) / parameters (TC, TOC/TN) and pore water nutrient contents - Selected model R 2 = (p-value = 0.047) Bacteria probably involved in many processes at small scale

28 Meiofauna (TMA) C.V. = % of the mean TMA (nb.gdw -1 ) Lowest of the microbenthic loop

29 Meiofauna (TMA) C.V. = % of the mean TMA (nb.gdw -1 ) Lowest of the microbenthic loop No relationship with microbenthic loop components

30 Meiofauna (TMA) Multiple regression analysis : - Selected parameter and regression coefficient: TC / Selected model R 2 = (p-value = 0.008) A B TMA (nb.gdw-1)

31 Meiofauna (TMA) Multiple regression analysis : - Selected parameter and regression coefficient: TC / Selected model R 2 = (p-value = 0.008) Relationship with sediment quality parameters (TN and TP correlated A with TC) B Food quality? P. oceanica meadows = carbonate factory (epiphytes, particle trapping) Seems to favour meiofauna abundance at small scale TMA (nb.gdw-1)

32 Microbenthic loop DistLM procedure: Parameter % Variability P-value Marginal tests [NH 4+ ] Log(FDC) Selected models Log([NO 2- +NO 3- ]) [NH 4+ ] + Log([NO 2- +NO 3- ]) Log(FDC) + [NH 4+ ] Log(FDC) + Phaeo. Log([NO 2- +NO 3- ]) + Phaeo

33 Microbenthic loop DistLM procedure: Parameter % Variability P-value Marginal tests [NH 4+ ] Very few of the measured Log(FDC) parameters can 23.36explain the spatial heterogeneity ([NH 4+ ] + FDC ~ 42 %) Selected models Log([NO 2- +NO 3- ]) Relationship with parameters related with degraded material (Phaeo.) or degradation processes linked with bacteria activities [NH 4+ ] + Log([NO 2- +NO 3- ]) Log(FDC) + [NH 4+ ] Log(FDC) + Phaeo. Log([NO 2- +NO 3- ]) + Phaeo

34 Conclusion Conclusions Spatial heterogeneity at small scale No relationship between the microbenthic loop components at small scale Few measured environmental parameters able to explain the observed heterogeneity Bacteria activities seems to be related with living and dead vegetal material Meiofauna seems to be related with the quality of the sediment Globally the spatial heterogeneity seems to be related with degradation processes ([NH 4+ ], phaeo.) and bacteria activities

35 Conclusion Conclusions Spatial heterogeneity at small scale No relationship between the microbenthic loop components at small scale The microbenthic loop seems to be related with degradation processes Few measured at small environmental spatial scale parameters able to explain the observed heterogeneity But only a small part of the observed variability was explained by Bacteria activities seems to be related with living and dead the measured parameters vegetal material Meiofauna seems to be related with the quality of the sediment Globally the spatial heterogeneity seems to be related with degradation processes ([NH 4+ ], phaeo.) and bacteria activities

36 Thank you for your attention!