Latitudinal Variation in Plankton Size Spectra along the Atlantic Ocean
The allometric models of microbial community respiration and production provide a complementary method for understanding the metabolic balance of the upper ocean. Latitudinal Variation in Plankton Size Spectra along in large areas the Atlantic Ocean.
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Latitudinal Variation in Plankton Size Spectra along the Atlantic Ocean
Abundance-size distributions of organisms within a community reflect fundamental properties underlying population dynamics. These include characteristics such as predator to prey biomass ratios, given the relationships that exist between body mass and metabolic activity, and between body mass and the ecological regulation of population density. In this way, plankton size has an important role in structuring the rates and pathways of material transfer in the marine pelagic food web, and consequently the oceanic carbon cycle. The transfer of energy between trophic levels can be inferred from regular patterns in population size structure, where plots of abundance within size classes, also known as plankton size spectra, typically show a power-law dependence on size. Metabolic theory, based on such size relations, has provided the basis for using an allometric approach to investigate the metabolic balance of the Atlantic Ocean and to identify the main drivers of trophic status in the plankton community.
Samples were collected during three Atlantic Meridional Transect (AMT) cruises with further samples from a Marine Productivity (MarProd) cruise in the Irminger Sea. Three image analysis instruments were used to obtain plankton size spectra in the pico- to mesozooplankton size range. Data from a decadal time series at a coastal station off Plymouth, UK additionally enabled seasonal trends in plankton size spectra to be interpreted. Allometric relationships were also derived from physiological rates of individual plankton and scaled from organisms to ecosystems using community size structure data that were obtained from six earlier AMT cruises.
Contrary to common perception, the transfer efficiency between phytoplankton and mesozooplankton in the Atlantic was not related to ecosystem productivity in oceanic and coastal systems. The flow of carbon up the food web was controlled by how quickly the consumers are able to respond to a resource pulse. These findings have fundamental implications for upper ocean carbon flux and suggest that global carbon flux models should reconsider the differences in carbon transfer efficiency between productive and oligotrophic areas of the world's ocean.
The allometric models of microbial community respiration and production provide a complementary method for understanding the metabolic balance of the upper ocean. Respiration exceeded photosynthesis in large areas of the Atlantic Ocean, suggesting that planktonic communities act as potential net sources of CO2. Large-sized phytoplankton are suggested as the main drivers of the balance between net autotrophy and heterotrophy.
CHAPTER 1: INTRODUCTION
1.1 Atlantic Meridional Transect (AMT) Programme
1.2 Community size structure
1.2.1 Why size matters
1.2.2 Scaling in biology
Energetic equivalence rule
1.2.3 Community size spectra
Theory of plankton size spectra
Limitations to size spectra theory
1.2.4 Factors shaping plankton size spectra
Pelagic food web
Flux of organic matter
Metabolic balance in the oceans
Mesozooplankton of the Atlantic Ocean
1.3 Hypothesis and objectives
CHAPTER 2: METHODS
2.1 Sample collection
2.1.1 AMT cruise programme
2.1.2 CTD sampling
2.1.3 Net sampling
2.2 Sample analysis
2.2.1 Carbon and Nitrogen analysis
2.2.2 Size structure analysis
Nanoplankton and microplankton
Direct measurements versus estimates of carbon biomass
2.2.3 Marine Productivity research programme
2.3 Data processing
2.3.1 L4 plankton monitoring programme
2.3.2 Quantification of plankton size structure
i. Size classes
ii. Normalised biomass-size spectra
iii. Mean organism size
2.4 Scaling the metabolic balance of the oceans
2.4.1 Error propagation
CHAPTER 3: LATITUDINAL VARIATION IN PLANKTON SIZE SPECTRA ALONG THE ATLANTIC
3.1.1 Atlantic Ocean Circulation
3.1.2 Oceanic provinces
3.2 Large scale changes in community size structure
3.2.1 Vertical structure
Nano- to microplankton NB-S spectra
3.2.2 Latitudinal variation
Community NB-S spectra
Mesozooplankton size structure
Total biomass and abundance
3.3 Comparison between cruises
3.3.1 AMT 12 and 14
3.3.2 AMT 13
3.4.2 Vertical structure
CHAPTER 4: CAN THE SLOPE OF A PLANKTON SIZE SPECTRUM BE USED AS AN INDICATOR OF CARBON FLUX?
4.1.1. Ocean carbon cycle
4.1.2 Trophic transfer efficiency
4.2 Large scale spatial variability
4.2.1 Latitudinal distributions of temperature
4.2.2 Spatial structure of nitrate
4.2.3 Chlorophyll a
4.3 Factors influencing plankton size spectra
4.4 Consumer versus resource control of the pelagic community
4.4.1 Chlorophyll a
4.4.2 Primary Production
4.4.3 Community interactions
4.5 Other carbon flux descriptors
4.5.1 Metabolic balance
4.5.2 Thorium estimates of C export
4.6.2 Turnover of material
4.6.3 Trophic status
4.6.4 Carbon export
4.6.5 Trophic transfer efficiency
4.6.6 Some limitations to the size spectra approach
CHAPTER 5: TEMPORAL VARIABILITY OF PLANKTON SIZE SPECTRA
5.1.1 The continental shelf
5.2 Community structure
5.2.1 Microbial community
5.2.2 Mesozooplankton community
5.3 Plankton size spectra
5.3.1 Average size spectrum
Across trophic levels
Within trophic levels
5.3.3 Interannual variability
5.4.1 Between trophic levels
5.4.2 Within trophic levels
CHAPTER 6: SCALING THE METABOLIC BALANCE IN THE OCEANS
6.1.2 Abundance-size structure
6.2 Empirical allometric models
6.2.2 Primary production
6.3 Comparison between allometric estimates with traditional in situ measurements
6.3.2 Primary production
6.4 Metabolic balance in the Atlantic
Implications to the global CO2 budget
Traditional incubations versus metabolic theory
Energetic equivalence rule
CHAPTER 7: DISCUSSION
APPENDICES ON SUPPLEMENTARY CD
Appendix 1: Literature survey of plankton respiration rates
Appendix 2: Literature survey of plankton growth rates
LIST OF TABLES
Table 2.1. Summary of cruises.
Table 2.2. Plankton size categories.
Table 2.3. Results of the least-squares (model 1) regression of size fractionated biomass estimates derived from CHN and PVA analyses.
Table 3.1. Methods used to measure the community size structure.
Table 3.2. Mean parameters of the least-squares (model 1) regression of the NB-S model for each % light level.
Table 3.3. Mean parameters of depth-integrated community NB-S slopes for each oceanic province on the AMT (50-0 m) and the MarProd cruises (120-0 m).
Table 3.4. Mean 50-0 m depth-integrated mesozooplankton and nano-/microplankton biomass, abundance and size for each oceanic province.
Table 4.1. List of data obtained to compare to plankton NB-S slopes.
Table 4.2. Regression analysis of the least squares (model 1) regression between the community slope and biomass.
Table 5.1. Data available for community and within trophic level spectra analysis at L4.
Table 5.2. Regression analyses of the least-squares (model 1) regression between NB-S slopes and biomass.
Table 5.3 Least-squares (model 1) regression of within trophic level spectra.
Table 6.1. Summary statistics for the metabolic scaling of the individual physiological rates of marine plankton. 25
LIST OF FIGURES
Figure 1.1. SeaWIFS image of mean surface chlorophyll concentration in the Atlantic Ocean with AMT cruise tracks shown.
Figure 1.2. A graphical model to explain the variance of biomass as a function of body size of pelagic organisms in ocean and lake ecosystems a) within trophic levels and b) across trophic levels.
Figure 1.3. A schematic of the NB-S spectrum (Platt and Denman 1978).
Figure 1.4. A simplified diagram of the main trophic pathways in the planktonic food web.
Figure 2.1. AMT cruise tracks.
Figure 2.2. Comparison between CHN and PVA estimates of mesozooplankton a) total biomass and b) size fractionated biomass estimates.
Fig. 2.3. Location of L4 coastal station.
Figure 2.4. 50-0 m depth-integrated NB-S spectra of the pico-, nano- to microplankton and mesozooplankton community at a) 1?N on AMT 12, b) 35?N on AMT 13, c) 41?S on AMT 13 and d) 24?S on AMT 14.
Figure 3.1. Major surface currents and upwelling zones of the Atlantic Ocean.
Figure 3.2. Location of the 82 AMT and 13 MarProd stations sampled and the oceanic provinces that were crossed.
Figure 3.3. Cluster analysis of the pigment distribution on AMT 12.
Figure 3.4. Latitudinal variation in i) the vertical structure of discrete nano-/microplankton NB-S slopes with superimposed temperature contours in black and ii) the depth of the mixed layer along AMT 12-14.
Figure 3.5. All the depth profiles from AMT 12-14 of discrete nano-/microplankton NB-S slopes plotted against percentage light level.
Figure 3.6. Regression of nano-/microplankton abundance against the y-intercepts of the linear fits to discrete NB-S spectra.
Figure 3.7. The latitudinal pattern of AMT (50-0 m) and MarProd (120-0 m) depth-integrated community NB-S slopes in each oceanic province.
Figure 3.8. Relationship between latitude and depth-integrated community NB-S slopes.
Figure 3.9. MDS ordination of size fractionated plankton biomass integrated from 50-0 m along AMT 12-14 with superimposed a) total biomass b) oceanic provinces and c) cruise tracks.
Figure 3.10. Percentage of total mesozooplankton abundance in each size fraction in 200-0 and 120-0 m for AMT 12-14 and MarProd cruises respectively. a) >1000, b) 500-1000 and c) 200-500 мm.
Figure 3.11. Scanned images from a) the Mauritenean upwelling station at 21?N on AMT 13 and b) the arctic station in the Irminger Sea at 61?N on the MarProd cruise.
Figure 3.12. Latitudinal variation in mean mesozooplankton equivalent spherical diameter (ESD) in the upper 50 m along AMT 12-14 and upper 120 m on MarProd.
Figure 3.13. The variation in total mesozooplankton carbon from a) 200-0 m and b) 50-0 m nets along the AMT.
Figure 3.14. Scanned images from the northern temperate stations on AMT 14 at a) 42?N and b) 49?N, which were analysed using the Plankton Visual Analyser (PVA).
Figure 3.15. Latitudinal variation in a) estimated biomass and b) abundance of (i) mesozooplankton and (ii) nano-/microplankton integrated over the upper 50 m and 120 m along AMT 12-14 and MarProd respectively.
Figure 3.16. Relationship between nano-/microplankton biomass and NB-S slopes of depth-integrated community over the upper 50 m and 120 m along AMT 12-14 and MarProd respectively.
Figure 3.17. Regression between mean nano-/microplankton ESD (мm) and discrete nano-/microplankton NB-S slopes.
Figure 4.1. The oceanic carbon cycle.
Figure 4.2. Spatial distribution of temperature along AMT 12-14.
Figure 4.3. Spatial distribution of the concentration of nitrate from discrete bottle data during AMT 12-14.
Figure 4.4. Latitudinal distribution of chlorophyll a concentration during AMT 12-14.
Figure 4.5. Relationship between discrete in situ temperature and the discrete nano-/microplankton NB-S slope.
Figure 4.6. Effect of sea surface temperature (SST) on 50-0 m depth-integrated NB-S slopes of a) the nano- to mesozooplankton community and b) the pico- to mesozooplankton community.
Figure 4.7. Relationship between the concentration of in situ nitrate and the NB-S slope of the discrete nano-/microplankton community size spectrum.
Figure 4.8. Regression between maximum nitrate concentrations in 300-0 m and NB-S slopes of the nano- to mesozooplankton and pico- to mesozooplankton community.
Figure 4.9. Regression between depth-integrated chlorophyll a levels and NB-S slopes of the nano- to mesozooplankton and pico- to mesozooplankton community size spectra.
Figure 4.10. Relationship between 50-0 m depth-integrated normalised primary production and NB-S slopes of the pico- to mesozooplankton community.
Figure 4.11. Relationship between the biomass and mean size of phytoplankton and mesozooplankton.
Figure 4.12. Relationship between abundance and biomass of phytoplankton and mesozooplankton on a vertically integrated basis.
Figure 4.13. Relationship between cell size, represented by the NB-S slope, versus biomass and abundance of phytoplankton.
Figure 4.14. Regression between NB-S slopes of the pico- to mesozooplankton community versus the mesozooplankton: pico- to microplankton biomass ratio.
Figure 4.15. Regression between the NB-S slopes of the pico- to mesozooplankton community versus a) pico- to microplankton, b) mesozooplankton and c) total plankton biomass.
Figure 4.16. Variability in pico- to mesozooplankton abundance along the Atlantic.
Figure 4.17. Relationship between 50-0 m depth-integrated a) production:respiration (P:R) and b) dark community respiration (DCR) versus pico- to mesozooplankton community NB-S slopes.
Figure 4.18. Relationship between the organic carbon flux from the surface of the ocean to the deep ocean, against the NB-S slopes of the pico- to mesozooplankton and nano- to mesozooplankton community.
Fig. 5.1. Average seasonal cycle of the microbial community biomass structure for phytoplankton and picoplankton at the L4 coastal staton.
Fig. 5.2. Yearly average of the microbial community biomass structure between 1992 and 2003 at the L4 station.
Figure 5.3. Mean mesozooplankton abundance structure at the L4 station.
Figure 5.4. Average a) seasonal and b) annual cycle of mesozooplankton at L4 between 1988 and 2003.
Figure 5.5. Monthly-averaged spectra for the entire community (pico- to mesozooplankton) at L4 between July 1998 and March 1999.
Figure 5.6. Regression of the slopes of a) phyto- to mesozooplankton and b) micro- to mesozooplankton versus pico-to mesozooplankton community.
Figure 5.7. Three seasonal groupings of complete community size spectra in winter, bloom and post-bloom periods.
Figure 5.8. Seasonal variation in slopes of “across trophic levels” spectra at L4.
Figure 5.9. Regression of the NB-S slopes versus biomass of depth-integrated a) phytoplankton, b) mesozooplankton and c) complete community for different community composites
Figure 5.10. Seasonal variability of within trophic-level NB-S slopes at the L4 station.
Figure 5.11. The annual mean cycle in community and within trophic level spectra between 1992 and 2003.
Figure 5.12. Regression between slopes of the phyto-microzooplankton community and phyto-mesozooplankton community.
Figure 6.1. Effect of a) body size and b) temperature on temperature-normalised and weight-normalised respiration rate respectively for bacteria, phytoplankton, micro- and mesozooplankton species.
Figure 6.2. Effect of a) body size, b) temperature and c) irradiance on primary production rate corrected for by the other two variables in each plot.
Figure 6.3. a) AMT stations where data for the allometric models were available and b) the abundance-size structure of the plankton community at each of these stations.
Figure 6.4. Relationship between the allometric estimate and the direct measurement (Winkler titration) of community respiration.
Figure 6.5. Relationship between the allometric estimate and the direct measurement of a) net and b) gross primary production.
Figure 6.6. Relationship between volumetric allometric estimates of community respiration and gross primary production.
Figure 6.7. Spatial distribution of the net community production using the allometric method.
DECLARATION OF AUTHORSHIP
I, [please print name]
declare that the thesis entitled [enter title] and the work presented in it are my own. I confirm that:
this work was done wholly while in candidature for a research degree at this University;
no part of this thesis has previously been submitted for a degree or any other qualification at this University or any other institution;
where I have consulted the published work of others, this is always clearly attributed;
where I have quoted from the work of others, the source is always given. With the exception of such quotations, this thesis is entirely my own work;
I have acknowledged all main sources of help;
where the thesis is based on work done by myself jointly with others, I have made clear exactly what was done by others and what I have contributed myself;
none of this work has been published before submission; or [delete as appropriate] parts of this work have been published as: [please list references]
There are a number of people I would like to express my thanks to for their help and support during this study:
Firstly, to my supervisors, Dr Roger Harris (PML), Dr Xabier Irigoien (AZTI) and Prof Patrick Holligan (NOC) for their support and guidance throughout this project.
To all the postdoctoral colleagues who provided advice. Special thanks to Бngel Lуpez-Urrutia (Centro Oceanogrбfico de Gijуn) for his mathematical knowledge and comments with regards to our collaborative work in Chapter 6. To Delphine Bonnet and Lidia Yebra (PML) for their statistical advice on data analysis.
To all the colleagues who helped in the analysis of plankton samples. To Tania Smith (NOC) for assistance with the CHN and FlowCAM analysis, as well as general technical support. To Lucia Zarauz (AZTI) for training me in the use of FlowCAM. To Carmen Garcia-Comas and Lea Roselli for their help with the PVA analysis of the MarProd mesozooplankton samples. To Dr Fidel Echevarria for analysing and providing mesozooplankton size-frequency data from the L4 coastal station.
To the Atlantic Meridional Transect Programme, in particular all the participants who collected, analysed samples and conducted experiments during the AMT cruises. To the British Oceanographic Data Centre for providing data from past and present AMT cruises. To Derek Harbour for providing plankton size structure data. To AMT scientists for allowing me to use unpublished data that helped in the interpretation of my results. To Dr Mike Zubkov and Jane Heywood (NOC) for supplying me the picoplankton counts. To Chris Lowe (PML) for his mixed layer depth calculations and general advice. To Dr Alex Poulton (NOC) for allowing me to use his primary production data. To Dr Niki Gist and Dr Carol Robinson (PML) for their production and respiration measurements. To Sandy Thomalla (UCT) for providing preliminary carbon export estimates. To Katie Chamberlain and Malcolm Woodward for supplying nitrate concentrations.
To all the principal scientists for their help during the work at sea, as well as the captain, crew and UKORS engineers on board RRS James Clark Ross for their excellent support. To the other participants of the cruises (you know who you are) for the notable teamwork and enthusiasm.
This work was supported by the Natural Environmental Research Council through the Atlantic Meridional Transect consortium (NER/0/5/2001/00680), a CASE award from Plymouth Marine Laboratory and a small Marine Productivity thematic Grant NE/C508342/1.
Finally, last but by no means least, to my friends, family and Dougal for their continual encouragement and optimism.
LIST OF ABBREVIATIONS
AMT Atlantic Meridional Transect
ANOVA Analysis of variance
AZTI Arrantza eta Elikaigintzarako Institutu Teknologikoa
BODC British Oceanographic Data Centre
BOFS Biogeochemical Ocean Flux Study
CNRY Eastern Coastal Boundary
CO2 Carbon dioxide
CR Community respiration
CTD Conductivity, temperature, density
CV Coefficient of variation
DCM Deep chlorophyll maximum
DCR Dark community respiration
DOC Dissolved organic carbon
DOM Dissolved organic matter
ESD Equivalent spherical diameter
FKLD Southwest Atlantic Shelves
GP Gross primary production
H:A Heterotrophic to autotrophic biomass ratio
HPLC High Performance Liquid Chromatography
LWCC Liquid waveguide capillary cell
MarProd Marine Productivity
MLD Mixed layer depth
MDS Multidimensional scaling
NADR North Atlantic Drift
NAST North Atlantic Subtropical Gyre
NATR North Atlantic Tropical Gyre
NB-S Normalised biomass-size
NCP Net community production
NERC Natural Environment Research Council
NOC National Oceanography Centre
NP Net primary production
OPC Optical plankton counter
PAR Photosynthetically active radiation
PML Plymouth Marine Laboratory
POC Particulate organic carbon
PP Primary production
P:R Production to respiration ratio
PRIME Plankton Reactivity in the Marine Environment
PRIMER Plymouth Routines in Multivariate Ecological Research
PVA Plankton Visual Analyser
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