AN ABSTRACT OF THE DISSERTATION OF
Michael S. Wetz for the degree of Doctor of Philosophy in Oceanography presented on
August 2, 2006.
Title: Dynamics of Organic Matter Production and Degradation During Coastal Diatom
Blooms.
Abstract approved:
________________________________________________________________________
Patricia A. Wheeler
Experiments were designed to answer key questions about diatom-derived organic
matter cycling (i.e., production and degradation) in coastal systems. Dissolved organic
matter (DOM) production was examined in axenic batch cultures of five diatom species.
Dissolved organic carbon (DOC) release rates varied between species, but were
significantly higher for all species in exponential versus stationary growth. The DOM
produced by several of the species adhered to filters and was measured as POM when
cells were separated from the medium by fractionation. Thus, field measurements of
POM and DOM may be biased by species-specific differences in the quality of the DOM.
Experiments were also conducted to examine particulate organic matter (POM) and
DOM degradation by coastal microbial assemblages. In each experiment, POM and
DOM concentrations were elevated above those found in recently upwelled waters,
indicative of bloom activity. Reductions in bacterial grazers resulted in significant
increases in bacterial biomass in these experiments, suggesting that grazing is the primary
control on bacteria. However, on two dates, there was no significant net loss of bacteria
in treatments with grazers, indicating a close coupling between bacterial growth and
mortality. DOC degradation was initially rapid and then slowed. After 3 d, 47 % of the
DOC was degraded and reductions in grazing or nutrient additions did not significantly
enhance the degradation. On average, 33 % of the POC was degraded after 3 d, although
some portion was converted to DOC and not respired. Despite the DOC and POC
degradation, there was little evidence of DON and PON degradation. These results
suggest that at least half of the diatom-derived DOC is rapidly degraded, but that there is
also a less labile fraction that may accumulate if retained in coastal waters. Additionally,
the slow degradation time of the less labile fraction relative to potential offshelf transport
mechanisms suggests that Oregon’s coastal waters may be a significant source of organic
matter to adjacent offshore waters. Finally, because of its lability, the POC will
contribute to shelf bottom water oxygen utilization as it decays.
©
Copyright by Michael S. Wetz
August 2, 2006
All Rights Reserved
Dynamics of Organic Matter Production and Degradation During Coastal Diatom Blooms
by
Michael S. Wetz
A DISSERTATION
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Doctor of Philosophy
Presented August 2, 2006
Commencement June 2007
Doctor of Philosophy dissertation of Michael S. Wetz presented on August 2, 2006.
APPROVED:
________________________________________________________________________
Major Professor, representing Oceanography
________________________________________________________________________
Dean of the College of Oceanic and Atmospheric Sciences
________________________________________________________________________
Dean of the Graduate School
I understand that my dissertation will become part of the permanent collection of Oregon
State University libraries. My signature below authorizes release of my dissertation to
any reader upon request.
________________________________________________________________________
Michael S. Wetz, Author
ACKNOWLEDGEMENTS
I am blessed to have been able to interact with a great group of people, some in COAS
and some not in COAS, over the past 5 ½ years. Some of the more notables (in no
particular order) are:
1) My wife, Jennifer, who helped me get through many tough spots and who makes
me keep an eye on things in this life that are bigger than work and science. She
deserves my sincere admiration for her continued support (+ dental insurance)
these past 5 years.
2) My advisor, Pat Wheeler, who I thank for her guidance and encouragement. Pat
was always willing to let me follow my own path in terms of generating and
testing ideas, which really helped me to grow as a scientist and to gain confidence
in my abilities. I have been so fortunate to have Pat as an advisor, and I owe her a
debt of gratitude.
3) Ricardo Letelier, who was one of the first faculty here other than Pat who I had
significant interactions with. Ricardo has always been willing to share his time
and ideas, and I have benefited from being able to work with him. Thanks
Ricardo!
4) Burke Hales, who I have had significant interaction with lately on proposals and
papers, and from whom I have tried to learn how geochemists look at ocean
dynamics, which hopefully will benefit me down the road. Burke’s willingness to
work among disciplines and to take an interest in my biologically-oriented work is
encouraging for someone like me who aspires to think across disciplines. With
any luck, I’ll be able to interact with Burke after I leave OSU.
5) Fred Prahl and Ev Sherr, my remaining COAS committee members, who have
been willing to spend time discussing various aspects of my research, again to my
benefit. Thank you both for everything. I would also like to thank both Ev and
Barry Sherr for generously allowing me to use their microscopes and flow
cytometer during my time in COAS.
6) The many students who I have interacted with and learned from during my time
here. Thanks to all of you, but especially to my fellow “two-months-‘tilgraduation-and-my-dissertation-stinks” drunkards, Sam Laney and Angel White.
7) Julie Arrington, former resident of the Dungeon annex of the Wheeler lab, who
taught me make TOC measurements. Julie was a wonderful cruisemate and
labmate. I honestly can say that my progression as a student was facilitated by
her willingness to teach me these new lab techniques, and without her, who
knows where I’d be at right now (probably over with the aforementioned
drunkards, only without a dissertation in hand). Thanks Julie!
8) Amanda Ashe, for her willingness to spend time teaching me how to run 14C
experiments. Like Julie, my interactions with Amanda helped to greatly improve
the quality of work that I was able to do for my dissertation. Thanks Amanda!
9) Tony D’Andrea and Kelly Benoit-Bird, who were always willing to share advice
and personal experiences about job searches. I thank you both for helping me to
greatly improve my marketability (and my salesmanship).
10) Finally, my parents. As a little kid, my parents were always willing to take me to
the library or on trips to museums, aquariums, etc., so that I could learn more
about ocean life… not easy to do when you live in the farmlands of SE Ohio. I
know that they sacrificed a lot for my brother and I over the years, and I did not
always outwardly show appreciation for their efforts, but I am truly thankful and
can say that it is because of my parents that I am still in oceanography, pursuing
my lifelong dream. I hope that I will be as good a parent to my kids as my parents
were to me. Thanks Mom and Dad!
CONTRIBUTION OF AUTHORS
Dr. Patricia A. Wheeler provided valuable critiques that greatly improved the
manuscripts found in Chapters 2, 3, and 4. Dr. Wheeler will be a co-author on the
submitted manuscripts from these chapters. Dr. Burke Hales provided considerable
insight into the interpretation of data presented in Chapter 4. Dr. Hales will be a coauthor on the submitted manuscript from this chapter.
TABLE OF CONTENTS
Page
Chapter 1. Introduction..................................................................................
1
Chapter 2. Release of Dissolved Organic Matter by Coastal Diatoms..........
4
Chapter 3. Environmental Controls on Coastal Bacterioplankton...........…..
39
Chapter 4. Degradation of Diatom-Derived Organic Matter: Implications
for C and N Biogeochemistry....................................................................
62
Chapter 5. Conclusions..................................................................…………
97
Bibliography.....................................................................................…..........
101
Appendix........................................................................................................
110
LIST OF FIGURES
Figure
Page
2.1 Growth curves (cells L-1) for three diatom species used in bulk
measurement experiments. Arrows indicate where nitrate was depleted…
33
2.2. Concentrations of POC and DOC (µmol L-1) in bulk measurement
experiments for (A) Chaetoceros decipiens, (B) Cylindrotheca closterium
and (C) Bellerochea sp. Also indicated in (B) is TEP (µg L-1 Xanthan
Gum equivalent). ………………………………………………………….
34
2.3. Concentrations of PON, DON and TN (µmol L-1) in bulk measurement
experiments for (A) Chaetoceros decipiens, (B) Cylindrotheca closterium
and (C) Bellerochea sp. ……………………………………………………
35
2.4. Molar C:N of the total accumulated POM, daily accumulated POM, total
accumulated DOM, and daily accumulated DOM for (A) Chaetoceros
decipiens, (B) Cylindrotheca closterium and (C) Bellerochea sp. ……….
36
2.5. DOC release rates (pmol DOC pmol cell C-1 h-1) for cells in exponential,
transition or stationary growth phases and (A) over a 24 h light/dark cycle,
or (B) at night. (C) PR for cells in exponential, transition or stationary
growth phases. ……………………………………………………………
37
2.6. Net accumulated DOC (µmol L-1) in Chaetoceros decipiens bulk
measurement experiment vs. predicted net accumulated DOC (µmol L-1)
for that species based on 14C DOC release rates. …………………………
38
3.1. Bacterial abundance change (x 106 cells ml-1) in A) April, B) August and
C) September experiments. ……………………………………………….
60
3.2. Bacteria C biomass change (µmol C L-1) in A) April, B) August and C)
September experiments. …………………………………………………..
61
4.1. DOC change in (A) April, (B) August, and (C) September. ……………...
92
4.2. Percentage of excess DOC degraded in (A) April, (B) August, and (C)
September. ………………………………………………………………...
93
LIST OF FIGURES (Continued)
Figure
Page
4.3. DIN change in (A) April, (B) August, and (C) September. ………………
94
4.4. DON change in (A) April, (B) August, and (C) September. ……………..
95
4.5. (A) Change in POC and excess TOC, (B) percentage of POC and excess
TOC degraded, and (C) change in PON and DON in April, August, and
September. ………………………………………………………………..
96
LIST OF TABLES
Table
Page
2.1. Description of diatom species used in this study. …………………………
32
3.1. Experimental treatments used to test whether nutrients and/or grazing
control bacterial abundance/biomass. ……………………………………..
57
3.2. Initial concentrations of dissolved inorganic nitrogen, dissolved inorganic
phosphorous, excess (above upwelled concentrations) dissolved organic
carbon, excess dissolved organic nitrogen, and the C:N (mol:mol) of the
excess DOM pool. …………………………………………………………
58
3.3. Initial bacterial abundances (x 106 cells ml-1), bacterial carbon biomass
(µmol L-1) and HNAN abundances (x 103 cells ml-1). Note that due to a
sample processing error, no HNAN abundances are available for the April
< 0.8 µm treatment. ………………………………………………………..
59
4.1. Experimental treatments used to test whether nutrients and/or grazing
control bacterial abundance/biomass. ……………………………………...
89
4.2. Initial concentrations of dissolved inorganic nitrogen, dissolved inorganic
phosphorous, organic carbon (µmol L-1; top number on each date- mean
DOC in five treatments, bottom number on each date- mean POC in whole
water treatment), organic nitrogen (µmol L-1; top number on each datemean DON in five treatments, bottom number on each date- mean PON in
whole water treatment), and the C:N (mol:mol) of the DOM (top number
on each date) or POM (bottom number on each date). …………………….
90
4.3. Decay constants and the percentage of POC and TOC that would be
degraded at select time points. klinear is the decay constant where decay
was linear over time, and k1 and k2 are the initial and secondary decay
constants where decay was initially rapid followed by slower rates. ……...
91
DYNAMICS OF ORGANIC MATTER PRODUCTION AND DEGRADATION
DURING COASTAL DIATOM BLOOMS
Chapter 1. Introduction
Carbon and nutrient dynamics in the ocean margins are of global significance. Despite
their relatively small contribution to the global ocean surface area (~10% of total),
margins account for a disproportionate amount of oceanic net primary production, new
production and export production (e.g., Chen et al. 2003). Eastern boundary current
upwelling systems, which account for about 10% of margin surface area, are sites of
intense seasonal organic matter production, mainly by diatoms. Only in the past decade
have researchers begun to make progress in understanding the partitioning of
phytoplankton bloom- derived organic matter (i.e., particulate organic matter (POM) vs.
dissolved organic matter (DOM)), the timescales of transformations between particulate
and dissolved pools, and ultimately the fate of fixed organic matter. All of these factors
converge to determine how much of the organic matter is available for trophic transfer vs.
remineralization vs. export through sinking and/or advection.
Because upwelling systems support high upper trophic level biomass, some of the
fixed organic matter must be in particulate form. Field and laboratory studies in
upwelling systems have shown that during active growth of upwelling-induced diatom
blooms, most of the fixed organic matter (C and N) is in particulate form (Doval et al.
1997; Hill and Wheeler 2002; Wetz and Wheeler 2003). Aside from being a food source
for higher trophic levels, POM (as phytoplankton biomass) may also sink rapidly or
subduct to shelf bottom waters (e.g., Karp-Boss et al. 2004) and if exported offshelf to
2
deeper waters, it may serve as a sink for atmospheric CO2 (Hales et al. 2006). Upon
bloom senescence, a significant portion of the fixed organic matter may be in the form of
accumulated dissolved organic matter (DOM), resulting mainly from excretion by
diatoms. Unlike POM, which can sink, export of DOM is largely limited to advection.
In addition to complicating C export estimates and estimates of C available for trophic
transfer, DOM release is generally not accounted for in field-based primary production
studies (i.e., from satellites, 14C uptake studies, etc.), adding a degree of uncertainty to C
budgets that rely on those types of measurements. Several lines of anecdotal evidence
suggests that DOM release rates may differ depending on the growth stage of the
phytoplankton and on the taxonomic composition of the phytoplankton. These potential
species-specific and growth stage differences need to be understood, because if they are
real, it would make use of a single “correction factor” to account for DOM release
unadvisable.
In coastal systems, including areas influenced by upwelling, accumulation of C-rich
DOM implies that its rate of production must be greater than its rate of removal over the
timescales of the accumulation (event-scale to seasonal) (Williams 1995; AlvarezSalgado et al. 2001a; Hill and Wheeler 2002). It is not entirely clear what factors control
bacterial production to the point of allowing DOM accumulation in coastal systems.
Grazing (Sanders et al. 1992; Li et al. 2004), nutrients (Zweifel et al. 1993; Barbosa et al.
2001), grazing and nutrients (Thingstad et al. 1997), or quality of the accumulated
organic matter (Fry et al. 1996; Søndergaard et al. 2000) have all been proposed as
controlling bacterial abundance and/or production in coastal waters. Recent studies
3
suggest that some of the autochthonous DOM may be exported from coastal systems
(Alvarez-Salgado et al. 2001a,b; Hopkinson et al. 2002). Alvarez-Salgado et al. (2001a)
argued that depending on the lability of the DOM, the magnitude of DOM exported to
oligotrophic offshore surface waters from coastal upwelling systems might be sufficiently
large to alter the balance between heterotrophy and autotrophy. Thus, it is important to
understand what regulates DOM degradation in coastal systems, as this will ultimately
determine the magnitude of DOM export fluxes. Likewise, it is important to quantify
POM degradation, as this combined with knowledge of circulation patterns and shelf
water residence times will help to better understand and model ecosystem-level process
and biogeochemical cycles in coastal systems.
In this study, several important aspects of diatom POM and DOM cycling were
examined. Chapter 2 focuses on elucidation of diatom DOM release rates in relation to
growth stage and species composition. Chapter 3 focuses on understanding what
environmental factors control bacterial abundance and biomass during senescent diatom
blooms. Chapter 4 focuses on elucidation of diatom-derived POM and DOM degradation
rates and on understanding what environmental factors might control DOM degradation
rates. Finally, Chapter 5 synthesizes the results of this study and discusses several
aspects of diatom organic matter cycling that require future work.
4
Chapter 2. Release of Dissolved Organic Matter by Coastal Diatoms
Michael S. Wetz
Submitted to Limnology and Oceanography
343 Lady MacDonald Crescent
Canmore, Alberta T1W 1H5
Canada
5
ACKNOWLEDGEMENTS
We wish to thank A. Ashe, J. Wetz, and J. Arrington for their invaluable technical
assistance. Thanks also to R. Letelier for constructive comments on an earlier version of
this manuscript. This research was supported by a NSF Graduate Research Fellowship, a
Sigma Xi Grant-in-Aid-of-Research and the Oregon State University Lenore Bayley
Graduate Fellowship to MSW.
6
ABSTRACT
Dissolved organic matter (DOM) production was examined in axenic batch cultures of
three diatom species and 14C-DOC release rates were determined for five species. For
Chaetoceros decipiens, dissolved organic carbon (DOC) and dissolved organic nitrogen
(DON) accumulated beginning in late exponential growth due to increased cell density.
For Cylindrotheca closterium, DOC actually decreased in late exponential growth and
reached zero by the end of the experiment. This coincided with continued particulate
organic carbon (POC) production following nutrient depletion and a 3-fold increase in the
per-cell concentration of transparent exopolymer particle-C.
14
C-determined DOC
release rates varied between species, but were significantly higher for all five species in
exponential or transition growth than during stationary growth. On average, 5% of the
total fixed C was released as DOC for four of the diatoms, varying little with growth
stage. Chaetoceros released an average of 21% of its fixed C as DOC. This study
showed that the DOM produced by some diatom species (i.e., TEP) adheres to filters and
is measured in the POM fraction when cells are separated from the medium by filtration.
We speculate that this is an important problem when diatom species with known benthic
life histories are prevalent. In contrast, for species like Chaetoceros that have no benthic
life history, DOM release rates estimated using bulk measurements and 14C appear to be
accurate. Future work should determine whether field measurements of POM and DOM
are biased by species-specific differences.
7
INTRODUCTION
Diatoms are ubiquitous in surface water of the world’s oceans. They are capable of
fast growth relative to other phytoplankton taxa and are well adapted to form large
blooms in high-nutrient coastal systems and in oceanic systems that are subjected to
pulses of nutrients (Margalef 1978). Indeed, diatoms are the largest contributor to
oceanic primary production and new production (e.g., Dugdale and Wilkerson 1992;
Sarthou et al. 2005). Given the magnitude of diatom production relative to other
phytoplankton taxa in the ocean, their fate has important implications for global carbon
(C) and nitrogen (N) cycles. For instance, diatoms are capable of relatively rapid sinking
rates, both as individual cells and in aggregates, and are responsible for a significant
portion of the sinking C flux out of the euphotic zone (Smetacek 1985). Diatoms are also
an important component of marine food webs, fueling both pelagic (Ryther 1969) and
benthic secondary production (Graf 1992).
Several recent studies have shown that the dissolved organic matter (DOM) pool may
be an important, but overlooked, fate for fixed C and N. For instance, in highproductivity upwelling systems where diatoms dominate production, autochthonouslyproduced DOM may accumulate on several timescales, ranging from that of bloom
duration (days to weeks) to seasonal (months) (Williams 1995; Alvarez-Salgado et al
2001; Hill and Wheeler 2002). Given that phytoplankton cells are permeable to a variety
of organic compounds (Bjørnsen 1988), release by the blooming phytoplankton is likely a
significant source of the accumulating DOM. That this DOM accumulates in situ
indicates that a fraction of the C fixed by phytoplankton, including diatoms, will not be
8
capable of sinking and will be a less efficient substrate for trophic-transfer than the
phytoplankton particulate C.
Early DOM research was hampered by methodological problems that prevented
unambiguous determination of whether healthy phytoplankton released DOM (Sharp
1977). The careful study by Mague et al. (1980) showed that healthy phytoplankton do
in fact release DOM and that under certain conditions, this released DOM could be a
significant component of total primary production. Diffusion is a possible mechanism
leading to the release of small organic compounds out of phytoplankton cells, owing to
the permeability of their cell membranes (Bjørnsen 1988). However, Baines and Pace
(1991) argued that DOM release is tied to the pool of recently fixed organic matter and
not to the total cellular biomass on which the diffusion model is based. Other studies
have shown that high C:N DOM, comprised mainly of carbohydrates, may also
accumulate in blooms that have become nutrient-starved (e.g., Ittekott et al. 1981;
Goldman et al. 1992; Biddanda and Benner 1997). This lead to the suggestion that DOM
production may be enhanced under nutrient-depleted conditions as a mechanism for
dissipating cellular energy, particularly under relatively high-light conditions (e.g., Fogg
1983; Wood and Van Valen 1990). Support for (e.g., Smith and Underwood 2000) and
against this idea (e.g., Marañón et al. 2004) point to the fact that this issue has been
difficult to resolve.
In addition to complicating C export estimates and estimates of C available for trophic
transfer, DOM release is generally not accounted for in field-based primary production
studies (i.e., from satellites, 14C uptake studies, etc.), adding a degree of uncertainty to C
9
budgets that rely on those types of measurements. Potential variability in DOM release
rates with growth stage makes use of a single “correction factor” to account for DOM
release unadvisable. Further complications arise when one considers that there may be
species-specific differences in DOM release rates. If diffusion is important, then
theoretically DOM release rates should be positively correlated with the surface area to
volume relationship of cells. There is little information in this regard, although
Malinsky-Rushansky and Legrand (1996) provide some evidence for enhanced release by
small phytoplankton compared to larger phytoplankton. However, that study, like many
other studies on this subject, involved use of non-axenic cultures, making interpretation
of C fluxes tenuous at best. Furthermore, the assumption that size/morphology alone
determines DOM release rates may be an oversimplification, given that it does not take
into account the various life histories of phytoplankton (i.e., benthic vs. pelagic species,
pennate vs. centric diatoms, etc.) or ambient environmental conditions. In this study,
DOM and POM production was examined using axenic cultures of five diatom species.
The fluxes of fresh phytoplankton C and N to these pools were determined under
controlled environmental conditions, with specific goals of addressing whether there are
growth stage and species-specific differences in these fluxes.
METHODS
Diatom Cultures – Axenic cultures of three diatom species, Chaetoceros decipiens,
Cylindrotheca closterium, and Bellerochea sp., were obtained from the Center for the
Culture of Marine Organisms (Table 1.). Cultures of two other species, Odontella
10
longicruris and Skeletonema sp., were isolated from inner-shelf surface waters collected
off Oregon during the summer (Table 2.1). Axenic strains of these cultures were
established through single cell isolations and transfer to sterile media containing
antibiotics. Cultures were maintained on a 14:10 L:D cycle at 205 µmol quanta m-2 s-1
(with 8 40-W cool white fluorescent bulbs and 2 full-spectrum aquarium lights), at 12 oC,
and in f/40 media. Release of DOM was studied using two methods; measurement of
bulk DOM accumulation and tracking 14C-bicarbonate uptake and release as DOC.
Because of the cost and tedious nature of the bulk measurements, only three species were
studied using that technique. DOM release from all five species was studied using the
14
C tracer technique.
Bulk DOM Accumulation Experiments - Three of the five diatoms; Chaetoceros,
Cylindrotheca and Bellerochea were grown as batch cultures for determination of how
their bulk organic matter is partitioned. For each species, triplicate acid-washed 20-L
polycarbonate ClearboyTM carboys were filled with sterile filtered (0.2 µm) seawater
collected from Yaquina Bay (Newport, OR) on the incoming tide. Salinities for all
experiments were 31-32. After the carboys were filled with seawater, they were
autoclaved and allowed to cool to 12 oC. Nutrients were then added using sterile
techniques to achieve ~ f/40 concentrations. Finally, a small (~ 5 ml) inoculum of
exponentially growing culture was added to each carboy 1 d prior to the start of
experiments and the carboys were placed under the lights described above. The carboys
were manually mixed twice daily. Samples were collected daily at 2.5 h prior to the
beginning of the dark period. To ensure that there was no bacterial contamination, 5 ml
11
samples were collected at select time points (beginning, middle and end) during each
experiment, fixed with 1% formalin, stained with DAPI, and filtered onto 0.2 µm
polycarbonate filters. The filters were examined using epifluorescence microscopy.
Whole water samples were vacuum filtered (< 200 mm Hg) onto GF/F filters for
chlorophyll a measurement. After filtration, all samples were stored in glass
VacutainersTM and immediately frozen at –30 oC until laboratory analysis. Chlorophyll a
was extracted from the filters for ≥12 h in the dark at –20 oC using 95% methanol.
Fluorescence was measured with a Turner 10-au fluorometer. Cell counts and biomass
measurements were made using the Utermöhl technique from samples that had been fixed
with 3% Lugols solution and settled for 18-24 h immediately after collection. Size
measurements were made on approximately 25-50 cells from each sample using a
calibrated ocular micrometer. Menden-Deuer et al. (2001) found that diatom cell
volumes were not significantly different after 24 h of fixation from live volumes; thus no
correction for shrinkage is needed.
Nutrient samples were collected in acid-washed 30 ml HDPE bottles and immediately
frozen at –30 oC. Samples were analyzed on a Technicon AA-II according to standard
wet chemical methods of Gordon et al. (1995). Standard curves with four different
concentrations were run daily at the beginning and end of each run. Fresh standards were
made prior to each run by diluting a primary standard with low nutrient surface seawater.
Deionizied water (DIW) was used as a blank, and triplicate DIW blanks were run at the
beginning and end of each run to correct for baseline shifts. Nitrate was determined by
subtracting nitrite from nitrate plus nitrite (N+N). The standard deviation for nitrate was
12
calculated by propagation of error using standard deviations for N+N and nitrite
(Bevington 1969).
Total nitrogen (TN) samples were collected in acid washed 30 ml Teflon bottles and
immediately frozen at –30 oC until analysis. Organic N was converted to nitrate using a
persulfate wet oxidation method (Libby and Wheeler 1997), and then analyzed using a
Technicon AA-II. Instrument calibration was performed daily using a standard curve
prepared from triplicate digested leucine standards at three concentrations. Fresh
standards were made prior to each run by diluting a primary standard with artificial
seawater. Digested artificial seawater was used as a blank, and the standard curve was
corrected for N content of the blank by determining the concentration of N in the
persulfate solution and then calculating the amount of N in the artificial seawater.
Artificial seawater N content was estimated as the difference between the blank and
persulfate signals.
Total organic carbon (TOC) samples were collected in triplicate in acid-washed
borosilicate vials with Teflon cap liners. Each vial contained approximately 5 ml of
seawater that was preserved with 50 µl of 90% phosphoric acid. Samples were stored at
room temperature until processing using the High Temperature Catalytic Combustion
method on a Shimadzu TOC-5000A analyzer. Standard curves were run twice daily
using a DIW blank and four concentrations of an acid potassium phthalate solution.
Three to five subsamples were taken from each standard and water sample and injected in
sequence. Variance between subsamples was ≤ 6.8 % (mean = 1.2 ± 0.9 %). Certified
Reference Material Program (CRMP) deep-water standards of known TOC concentration
13
were injected in triplicate at the beginning, middle, and end of every run to check for
baseline shifts. For the Chaetoceros and Cylindrotheca experiments, average daily
CRMP TOC concentrations (12-00 batch) were 45.3 ± 2.2 µmol L-1. For the Bellerochea
experiment, the average daily CRMP TOC concentration (05-04 batch) was 43.2 ± 2.9
µmol L-1. Baseline drift was calculated from changes in the deep-water concentrations
during a run, and a drift correction was applied to the raw data. The data from each date
were then normalized to the average daily CRMP TOC concentration.
Particulate organic carbon (POC) and nitrogen (PON) were determined from material
collected on precombusted GF/F filters. Depending on the expected amount of material
in a sample, between 50 to 1000 ml of experimental water was vacuum filtered (< 200
mm Hg) onto precombusted GF/F filters. After filtration, samples were stored in glass
VacutainersTM and immediately frozen at –30 oC until laboratory analysis. Samples were
processed within 3-4 months of collection. Filters were fumed with concentrated HCl to
remove inorganic C and dried, followed by analysis using a Control Equipment Corp.
440HA CHN elemental analyzer calibrated with acetanilide. During analysis, filter
blanks were run after every twelve samples. Filter blanks averaged 18.1 ± 2.6 µg C and
0.6 ± 0.8 µg N, and these values were subtracted from each measured value as a blank
correction.
Dissolved organic nitrogen (DON) was determined by subtracting PON and DIN
(NH4, N+N) from TN (Eq. 1).
DON = TN – PON – DIN
(1)
14
The standard deviation for DON was calculated by propagation of error using standard
deviations for TN, PON, and DIN (Bevington 1969). Dissolved organic carbon (DOC)
was determined by subtracting POC values from TOC values (Eq. 2).
DOC = TOC – POC
(2)
The standard deviation for DOC was calculated by propagation of error using standard
deviations for TOC and POC (Bevington 1969).
Transparent exopolymer particles (TEP) were determined from 5-10 ml samples that
had been filtered (< 200 mm Hg) onto 0.4 µm polycarbonate filters. The filtered samples
were stained with 500 µl of pre-filtered (through 0.2 µm filter) 0.02% alcian blue (pH
2.5) for < 5 s. Finally, the filters were rinsed twice with DIW and frozen until analysis.
Sample filters, blank filters and standard filters were soaked in 80% H2SO4 for 2 h,
during which they were gently agitated 3-5 times. Standards consisted of six different
concentrations of Xanthan Gum filtered onto 0.4 µm filters and extracted as above.
Absorption of each extracted sample, blank or standard was measured
spectrophotometrically at 787 nm.
14
C tracer experiments - 14C was used to assess POC and DOC accumulation rates for
the five diatom species described above. For each species, rates were measured over the
light period (14 h) or over the entire light/dark period (24 h) for cells in exponential or
stationary growth. Dark period rates were determined by subtracting the cumulative light
period production from the cumulative daily (light/dark) production and dividing that by
the duration of the dark period (10 h). Under subdued lighting and within 30 min prior to
the start of the light period, ~16 µCi of NaH14CO3-, previously determined not to contain
15
organic 14C, was added to each of 12- 50 ml acid-washed and DIW rinsed transparent
polyethylene media bottles containing the diatom cultures. Coincident with addition of
14
C label, an additional 300-350 ml of culture was collected for determination of total
CO2 concentrations according to Bandstra et al. (2006). One of the 14C labeled bottles
was processed immediately for determination of specific activity, which involved
collection of a 50 µl subsample, addition of the subsample to 300 µl of βphenelethylamine in a glass scintillation vial, and finally addition of 10 ml of scintillation
cocktail. Another bottle was used for a t = 0 blank and was processed immediately upon
addition of the isotope. The additional ten bottles were incubated in the light (previously
described) or in darkness and processed after 14 h (light period) or 24 h (light/dark
period). For processing of the t = 0 and time course samples, a 5 ml subsample was
withdrawn from each bottle under subdued lighting and gently vacuum filtered through a
0.2 µm polycarbonate filter. The filter and filtrate from each were placed in glass
scintillation vials, and 100 µl of 50% HCl or 1 ml of 10% HCl was added to the filtrate or
filter, respectively, for removal of DIC. The samples were exposed to acid for 24 h, then
15 ml or 10 ml of scintillation cocktail was added to the filtrate or filter, respectively.
Finally, samples were analyzed using a Wallac 1409 liquid scintillation counter with an
internal quenching curve. Results from the acidified t = 0 samples showed that inorganic
14
C was completely removed through the acidification process. POC/DOC production
rates were determined by subtracting dark bottle POC/DOC values from light-exposed
bottle values.
16
RESULTS
Bulk DOM accumulation experiments – All three species in these experiments grew
exponentially until depletion of both N and P, after which growth ceased within 1 d (Fig.
2.1). Cylindrotheca exhibited the highest growth rate, averaging 1.16 ± 0.46 d-1,
followed by Chaetoceros, which averaged 0.95 ± 0.58 d-1, and Bellerochea, which
averaged 0.55 ± 0.35 d-1. Cell death (lysis), determined from the abundance of empty
frustules, only amounted to 0.5-3.0% of live cell abundances throughout each of the
experiments.
POC increased exponentially for Chaetoceros until ~ 1 d after the transition to the
stationary growth phase, when accumulation ceased (Fig. 2.2A). Likewise, PON
increased exponentially until N-depletion, then subsequently decreased by ~ 6.8 µmol L-1
through the end of the experiment (Fig. 2.3A). During exponential growth, the C:N
(mol:mol) of each days’ newly produced POM averaged 7.2 ± 1.3, similar to the C:N of
the total accumulated POM pool (Fig. 2.4A). However, the newly produced material that
accumulated during the transition and early stationary growth phases had an infinitely
high C:N, indicative of carbohydrate accumulation. Likewise, the C:N of the total
accumulated POM pool increased to 12.1 ± 1.7 in the stationary growth phase.
Noticeable accumulation of both DOC and DON began in the late exponential growth
phase and continued until termination of the experiment (Figs. 2.2A, 2.3A). The average
C:N of each days’ newly produced DOM averaged 17.2 ± 9.8, indicative of mainly
carbohydrate accumulation, but also some N-containing organic compounds.
17
POC increased exponentially for Cylindrotheca, but unlike results for Chaetoceros,
production continued for more than 3 d after N-depletion and the accumulation rate only
decreased slightly by the end of the experiment (Fig. 2.2B). PON increased
exponentially until N-depletion, after which production stopped (Fig. 2.3B). The C:N of
the newly produced POM varied considerably with growth stage, averaging 6.3 ± 1.0
during exponential growth, 13.1-82.8 during the transition to stationary growth, and
finally reaching infinity in stationary growth (Fig. 2.4B). Likewise, the C:N of the total
accumulated POM pool averaged 6.7 ± 2.0 during exponential growth, but increased to
22.0 by the end of the experiment. DOC began to decrease in late-exponential and
reached 0 by the end of the experiment (Fig. 2.2B). In contrast, DON increased
dramatically for two days during late-exponential (by 9.9 µmol L-1), then subsequently
increased by only ~ 2.2 µmol L-1 during the rest of the experiment (Fig. 2.3B). There is
some degree of uncertainty associated with the PON and DON measurements,
particularly during the mid-to late exponential phase, as recovery of TN was incomplete.
The error associated with this missing TN ranged from ~ 6.7 µmol L-1 in late exponential
to ~ 1.8 µmol L-1 at the end of the experiment (Fig. 2.3B). TEP production followed
POC production during N-replete conditions, but increased dramatically for 1-2 days
following N-depletion, then ceased (Fig. 2.2B). Maximum TEP concentrations were
~14,000 µg L-1 Xantham Gum. Using the conversion factors reported by Engel and
Passow (2001), this would equate to ~600-1030 µmol C L-1. Given the estimated diatom
biomass of ~150-200 µmol C L-1 and the maximum TOC concentrations of ~800 µmol C
18
L-1, it is likely that the actual TEP-C concentration is toward the lower end of the
estimate, or ~600 µmol C L-1.
Bellerochea POC increased exponentially until N-depletion, as did PON (Figs. 2.2C,
2.3C). Unfortunately, the experiments were terminated within 1 d of the cells reaching
stationary growth, and coincident with complete N-depletion. Therefore, we cannot say
anything about POM dynamics during the latter stages of stationary growth. The daily
C:N of the accumulating POM was much more variable than the other species, averaging
11.7 ± 11.5 but reaching infinity on one date, while the cells were in exponential growth
(Fig. 2.4C). This variability is likely due to the slower growth and daily accumulation
rates of POC/PON of Bellerochea, which (the smaller daily changes in POC/PON) adds
uncertainty to estimates of the POM C:N. DOC began to decrease in mid-exponential
growth and reached 0 by the end of the experiment (Fig. 2.2C). However, DON did not
significantly increase (Fig. 2.3C).
14
C tracer experiments – The three species used in the bulk measurement experiments
(Chaetoceros, Cylindrotheca, Bellerochea) grew at similar rates in the 14C tracer
experiments as in the bulk measurement experiments. Odontella longicruris grew at 0.86
± 0.52 d-1, while Skeletonema sp. grew at 0.90 ± 0.58 d-1 in the 14C tracer experiments.
Cell-C normalized DOC release rates during the entire light/dark cycle (i.e., 24 h period)
varied between species, ranging from 0.4-5 x 10-3 pmol DOC pmol cell C-1 h-1 for cells in
exponential growth or at the transition to stationary growth (Fig. 2.5A). Stationary phase
release rates were much lower, ranging from <0.1-0.7 x 10-3 pmol DOC pmol cell C-1 h-1.
Nighttime DOC release rates were not significantly different than light/dark rates for
19
Bellerochea, but were reduced on average by 21-32% for Cylindrotheca, Odontella and
Skeletonema (Fig. 2.5B). For Chaetoceros, nighttime rates were reduced to near 0 in the
exponential growth phase, although there was considerable variability associated with
that sample. In the other two growth phases, nighttime release rates were reduced by 4345% relative to day/night rates. Unlike nighttime DOC release rates, there was no
statistically significant accumulation of POC at night for any species except
Cylindrotheca (data not shown). Cylindrotheca continued to fix POC at night, but only
in the transition and stationary growth phases and albeit at reduced rates relative to light
period or daily (light/dark) rates. Nighttime POC fixation rates for that species were
reduced by ~33% over daily rates and ~46% over light period rates in the transition
phase, and by ~75% over daily rates and ~83% over light period rates in the stationary
phase. The percentage of DOC released to total C fixed (hereafter “PR”) ranged from 0.8
to 10.1% (mean = 4.6 ± 3.1%) for the diatoms, excluding Chaetoceros (Fig. 2.5C). There
were no discernible trends in relation to growth stage, with some species (Bellerochea,
Odontella) showing slightly reduced PR in stationary growth, and one (Skeletonema)
showing slightly elevated PR in stationary growth. Chaetoceros PR was consistently
higher than the other species, averaging 21.0 ± 4.6% and varying little with growth stage.
Multiplying the cell-C normalized DOC release rates for Chaetoceros in each growth
phase (Fig. 2.5A) by the accumulated POC in the bulk experiments yields an estimated
DOC accumulation curve that is nearly identical to the measured bulk DOC accumulation
(Fig. 2.6).
20
DISCUSSION
Studies of DOM production have often relied on non-axenic field samples or cultures
and/or short-term (< few h) 14C tracer studies. When designed properly, valuable
information has been obtained from these types of studies. However, in many cases,
bacteria acting on and influencing the fresh phytoplankton DOM pool creates
uncertainties in the magnitude of C and N fluxes to that pool. In the case of the shortterm 14C tracer studies, Underwood et al (2004) found that there was an ~ 3 h time-lag
between addition of 14C label to diatom cultures and the subsequent production of labeled
extracellular polysaccharides, a potentially large component of phytoplankton-derived
DOM. Thus, short (< few h) 14C studies may completely miss C dynamics associated
with the extracellular polysaccharide pool, a point noted in the earlier studies of Mague et
al. (1980) and Smith (1982). Our study shows that even with careful accounting for
possible sources of error associated with POM and DOM measurements (e.g., through
use of axenic cultures, careful analytical techniques, accounting for DOM adsorption to
filters, etc.), the dynamics of those pools is still quite complex and their interpretation in
the context of phytoplankton physiology/bloom dynamics remains a daunting task.
Per cell-C rates of 14C DOC production were much higher for all species in
exponential and transition growth phases than during stationary growth. DOC release
rates (cell-C normalized or non-normalized) were not proportional to cell biomass, as
predicted by the diffusion model (Bjørnsen 1988). Instead, DOC release rates appeared
to be better correlated with particulate primary production rates (e.g., Baines and Pace
1991) (data not shown), although this interpretation is complicated by the fact that some
21
of the DOC (i.e., the TEP fraction) is measured as POC. Higher DOC release rates in the
exponential/transition growth phases compared to the stationary growth phase have been
noted previously in batch cultures of other diatom species (Granum et al. 2002;
Underwood et al. 2004). Even if some of the DOC were actually measured as POC,
which we suspect for Cylindrotheca and Bellerochea, the stationary growth phase rate of
14
C TOC production (i.e., true DOC + attached or TEP DOC + true POC) was lower on
average by 59 ± 3% for Cylindrotheca and Bellerochea, and by 90 ± 5% for the other
three diatoms.
In the bulk measurement experiments, Chaetoceros POC production ceased within 1 d
of N-depletion and DOC production slowed by late stationary growth, which was
expected based on the results of the 14C work. As N became limiting, the C:N of newly
produced POM approached infinity, pointing to carbohydrate accumulation (Myklestad
1974; Biddanda and Benner 1997). The C:N of the newly produced DOM was also
elevated over Redfield stoichiometry, averaging ~17 and indicative of the presence of
mainly carbohydrates, but also some N-containing compounds and probably TEP-like
material (e.g., Corzo et al. 2000). However, even if TEP production occurred in
stationary growth, the rapid slowdown of C production after N-depletion would imply
that the cumulative effect on both POC and DOC and the potential for conversion of
DOC to POC through coagulation may have been lessened. Thus, it appears that for this
species, bulk POM and DOM measurements may actually provide accurate measures of
true POM and DOM. It should be noted that PR was much higher for Chaetoceros than
the other diatom species, as has been reported in the literature (e.g., Hellebust 1965;
22
Myklestad 1974, 1977). However, the reason for this is not well understood. The fact
that PR was not elevated for Chaetoceros under N-limitation, that the bulk DOC
accumulation could be accounted for without necessity for elevated release rates under Nlimitation, and that some of the DOC release continued at night in two of three growth
phases argues that the overflow mechanism may not be as pronounced in this species as
opposed to other phytoplankton, at least under these conditions.
In contrast to results for Chaetoceros, the dynamics of the POM and DOM pools were
more complex and the distinction between the two pools less evident for Cylindrotheca
and Bellerochea. During exponential growth, the newly-accumulated C:N of POM for
Cylindrotheca was near Redfield stoichiometry. Unlike with Chaetoceros, Cylindrotheca
POC did not cease in stationary growth, as ca. 270 µmol L-1 accumulated in the 3 d
following nutrient depletion, coinciding with DOC decreasing to 0. This newly produced
POM had an infinitely high C:N, indicative of carbohydrate production. Some of this
POC may have been intracellular carbohydrates, as Underwood et al. (2004) showed that
the per cell concentration of intracellular carbohydrates for Cylindrotheca closterium
increased 2-fold in stationary growth. However, a significant portion of the continued
POC increase (≥ 50%), especially that which occurred in the last few days of the
experiment, is likely due to release of TEP-precursors (polysaccharides) and to the
conversion of the DOC in the media to TEP-like particles. TEP and TEP-precursors
released by diatoms can rapidly coagulate and bind to other organic molecules in
seawater and are often measured as POC instead of DOC (Passow 2002). TEP-C per cell
increased dramatically just after nutrient depletion and was 3-fold higher in stationary
23
growth. Previous work with this species has demonstrated that the proportion of excreted
carbohydrates that are polymeric (i.e., TEP) vs. non-polymeric increases drastically in
stationary growth (e.g., Smith and Underwood 2000; Underwood et al. 2004). The DOC
in the media of Bellerochea also disappeared as POC increased. By the time nutrients
became depleted, this species’ newly produced POM approached 15, indicating the
accumulation of a mixture of carbohydrates and N-containing compounds. The
disappearance of the DOC coincident with the accumulation of POC suggests that this
species may also be producing TEP-like material that binds to the background DOC.
These results suggest that the carbohydrate-based “overflow” mechanism may be more
relevant to some species, including Cylindrotheca closterium (Staats et al. 1999;
Alcoverro et al. 2000; Smith and Underwood 2000; Underwood et al. 2004) and
presumably Bellerochea.
In this study, we have shown that PR averaged ~ 5% for four of five species tested,
and was ~ 21% for Chaetoceros decipiens. Several recent reviews of PR from the
literature indicate that PR generally averages 5-15% (e.g., Baines and Pace 1991; Nagata
2000), although elevated PR values for various Chaetoceros species has been noted. PR
in this study also remained relatively constant in nutrient-replete vs. nutrient-deplete
conditions. Recent work by Marañón et al. (2004) has shown that PR is relatively
invariant across eutrophic-oligotrophic environmental gradients, arguing against the
overflow mechanism as being important in marine systems. However, as demonstrated in
our study, this interpretation may be complicated by the fact that for some species, DOC
may actually be measured as POC. PR values for Cylindrotheca and Bellerochea were
24
within the average ranges previously reported for other diatom species, but it appears that
a significant portion of the DOC that they produce is measured as POC. Hence, PR may
be underestimated for these species. Cylindrotheca closterium is commonly found in the
benthos and is known to retain an extracellular polysaccharidic capsule and also produces
copious amounts of extracellular polysaccharides (Hoagland et al. 1993; Smith and
Underwood 2000). These traits are well known to many other species of diatoms that
have some form of benthic life-history (e.g., Smith and Underwood 2000). Hence, we
speculate that in field and culture situations where these types of diatoms are prevalent,
routine POM and DOM measurements using GF/F filters may give misleading results in
terms of the dynamics of those pools. However, Cylindrotheca is known to form blooms
in coastal surface waters and thus its distribution is not limited to the benthos (e.g.,
Cabrini et al. 1992; Gilabert 2001). This is probably the case for most other benthic
diatom species as well, especially in shallow coastal systems subjected to wind-driven
resuspension (e.g., Shaffer and Sullivan 1988; de Jonge and van Beusekom 1995). In
contrast to those species, it appears that the DOC release rates and PR estimated for
Chaetoceros in this study may be accurately used to predict bulk DOC accumulation,
despite the fact that this genus of diatoms is known to produce extracellular
polysaccharides (Myklestad 1974, 1977; Corzo et al. 2000). The PR estimated for
Skeletonema, 2.5-10 %, is also consistent with previous studies of this species (Myklestad
1974; Granum et al. 2002) and its DOC appears to be measured as DOC with separation
using GF/F filters (e.g., Biddanda and Benner 1997). Therefore, we speculate that for
some diatom species, particularly pelagic species, organic matter dynamics studied using
25
either bulk measurements (w/ GF/F filters) or 14C to measure both POC and/or DOC
accumulation rates may be accurate.
It is important to note that our studies were done under carefully controlled
environmental conditions (nutrients, temperature and light). How do the DOM release
processes described in this study compare to field situations where different nutrients
may limit bloom growth and temperature and light conditions fluctuate? Several lab and
field studies have shown that as with the N and P limiting conditions here, the release of a
variety of organic compounds (including extracellular polysacchardes) also occurs under
strictly N or P limiting conditions (e.g., Alcoverro et al. 2000). DOM release relative to
total C fixation has been shown to be relatively invariant under normal growth
temperatures ranging from 5 oC to 20 oC (Verity 1981). Less clear is the effect of light
conditions on DOM release. The DOM release rate relative to total C fixed may be
elevated at extremely high or low light levels, but under those conditions, the absolute
rate of DOM release will probably be reduced due to reductions in cell growth and
photosynthesis (Zlotnik and Dubinsky 1989). In nature though, phytoplankton are
exposed to fluctuating, not static, light conditions. To the best of our knowledge, only
one study has looked at how sudden changes in light intensity may affect DOM release.
Mague et al. (1980) shifted a water sample collected at 12 m depth in the Gulf of Maine
and incubated at the corresponding light intensity (~10% of surface light intensity) to
either higher or lower light intensities (i.e., from 1-100% of surface light intensity).
Their results were variable and DOC release was only measured several hours after the
shift in light intensity. Nonetheless, when the phytoplankton were shifted to 100%
26
surface light intensities, extracellular DOM release was enhanced. Clearly, more work is
needed to characterize the impact that fluctuating light (and nutrient) conditions may
have on phytoplankton photosynthesis and DOM release, particularly over shorter timesscales (i.e., seconds to minutes) than the Mague et al. (1980) study.
This study highlights the necessity for future work to determine whether field
measurements of POM and DOM are biased by species-specific differences. The bound
or aggregated polysaccharides may have a much different fate than “true” DOC. For
instance, several studies have shown that the turnover time for diatom-derived
polysaccharides is much slower than that of non-polysaccharidic compounds such as
glucose (Aluwihare and Repeta 1999; Hama and Yanagi 2001). Hence, the relative
amount of these different types of organic matter that are produced during blooms may
significantly affect the C cycle dynamics. Determining whether there are species-specific
biases in POM/DOM production may be difficult given the likely need for time-course
measurements during bloom development and because blooms are often dominated by
mixtures of phytoplankton. Nonetheless, it is an important issue that needs to be
addressed because of reliance by many large field programs (i.e., JGOFS, GLOBEC, etc.)
and local studies on separation of DOM from POM using GF/F filters. Controversy has
already arisen over these types of measurements because of the frequent neglect of the
DOM adsorption blank (Moran et al. 1999; Gardner et al. 2003), and our work adds
further complexity to interpretation of POM/DOM dynamics.
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Underwood, G.J.C., M. Boulcott, C.A. Raines, and K. Waldron. 2004.
Environmental effects on exopolymer production by marine benthic diatoms:
dynamics, changes in composition, and pathways of production. J. Phycol. 40:
293-304.
Verity, P.G. 1981. Effects of temperature, irradiance, and daylength on the marine
diatom Leptocylindrus danicus Cleve. II. excretion. J. Exp. Mar. Biol. Ecol. 55:
31
159-169.
Williams, P.J.L. 1995. Evidence for the seasonal accumulation of carbon-rich
dissolved organic material, its scale in comparison with changes in particulate
material and the consequential effect on net C/N assimilation ratios. Mar. Chem.
51: 17-29.
Wood, A.M., and L.M. van Valen. 1990. Paradox lost? On the release of energyrich compounds by phytoplankton. Mar. Microb. Food Webs 4: 103-116.
Zlotnik, I., and Z. Dubinsky. 1989. The effect of light and temperature on DOC
excretion by phytoplankton. Limnol. Oceanogr. 34: 831-839.
32
Table 2.1. Description of diatom species used in this study.
Species
Bellerochea sp.
Source
Morphology
Biovolume (µm3)
SA:Biovol.
CCMP (#143)
Prism on Triangle
Cylindrotheca
closterium
CCMP (#1855)
Prolated Spheroid + 2 Cylinders
75 to 150
1.5 to 2.0
110 to 340
1.1 to 1.9
Species
Chaetoceros
decipiens
CCMP (#173)
Elliptical Prism
Odontella
longicruris
Inner shelf, OR coast
Elliptical Prism
Inner shelf, OR coast
Cylinder + 2 Half Spheres
18,000 to 24,000
0.2
500 to 2,000
0.5 to 0.9
Source
Morphology
Biovolume (µm3) 1,500 to 9,000
SA:Biovol.
0.3 to 0.7
Skeletonema sp.
33
1 x 10
1.00E+09
8
1.00E+08
1 x 10
Abundance (cells L )
-1
9
7
1.00E+07
1 x 10
6
1.00E+06
1 x 10
Chaetoceros
Cylindrotheca
Bellerochea
5
1.00E+05
1 x 10
4
1.00E+04
1 x 10
3
1.00E+03
1 x 10
0
2
4
6 8 10 12 14 16 18
Day of experiment
Figure 2.1. Growth curves (cells L-1) for 3 diatom species used in bulk measurement
experiments. Arrows indicate where nitrate was depleted.
34
500
A
400
300
200
100
POC
DOC
0
0
2
4
6
8
10
12
14
16
18
16000
B
14000
-1
12000
700
10000
500
300
100
-100
8000
POC
DOC
TEP
6000
4000
2000
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
400
15
16
17
18
19
TEP (µg L-1 Xanthan
Gum equivalent)
Organic C (µmol L )
900
0
C
300
POC
DOC
200
100
0
-100
0
2
4
6 8 10 12 14 16 18
Day of experiment
Figure 2.2. Concentrations of POC and DOC (µmol L-1) in bulk measurement
experiments for (A) Chaetoceros decipiens, (B) Cylindrotheca closterium and (C)
Bellerochea sp. Also indicated in (B) is TEP (µg L-1 Xantan Gum equiv.).
35
75
A
60
45
30
TN
PON
DON
15
0
-1
Organic N (µmol L )
75
0
2
4
6
8
10
12
14
16
18
B
60
45
30
TN
PON
DON
15
0
75
0
2
4
6
8
10
12
14
16
18
C
60
45
TN
PON
DON
30
15
0
0
2
4
6
8 10 12
Day of experiment
14
16
18
Figure 2.3. Concentrations of PON, DON and TN (µmol L-1) in bulk measurement
experiments for (A) Chaetoceros decipiens, (B) Cylindrotheca closterium and (C)
Bellerochea sp.
36
C:N (mol:mol)
90
80
70
60
50
40
30
20
10
0
90
80
70
60
50
40
30
20
10
0
A
Infinity
Accum. POM
Daily POM
Accum. DOM
Daily DOM
1
90 1
80
70
60
50
40
30
20
10
0
1
3
5
7
9
11
13
15
17
19
B
Infinity
3
5
7
9
11
13
15
17
19
C
3
5
7
9 11 13
Day of experiment
15
17
19
Figure 2.4. Molar C:N of the total accumulated POM, daily accumulated POM, total
accumulated DOM, and daily accumulated DOM for (A) Chaetoceros decipiens, (B)
Cylindrotheca closterium and (C) Bellerochea sp.
37
DOC release rate (pmol DOC pmol cell-C -1 h-1)
0.006
A
0.005
Bellerochea
Chaetoceros
Cylindrotheca
Odontella
Skeletonema
0.004
0.003
0.002
0.001
0.000
0.006
Exponential
Transition
Stationary
B
0.005
0.004
0.003
0.002
0.001
0.000
Exponential
50
Transition
Stationary
C
PER
40
30
20
10
0
Exponential
Transition
Stationary
Growth phase
Figure 2.5. DOC release rates (pmol DOC pmol cell C-1 h-1) for cells in exponential,
transition or stationary growth phases and (A) over a 24 h light/dark cycle, or (B) at
night. (C) PR for cells in exponential, transition or stationary growth phases.
-1
Accumulated DOC (µmol L )
38
170
150
130
110
90
70
50
30
10
-10
Estimated DOC
Observed DOC
1
2 3 4 5 6 7 8 9 10
Day of experiment (from day 0)
Figure 2.6. Net accumulated DOC (µmol L-1) in Chaetoceros decipiens bulk
measurement experiment vs. predicted net accumulated DOC (µmol L-1) for that species
based on 14C DOC release rates.
39
Chapter 3. Environmental Controls on Coastal Bacterioplankton
Michael S. Wetz
For submission to Aquatic Microbial Ecology (Note)
Inter-Research
Nordbunte 23 (+21, 26, 28, 30)
21385 Oldendorf/Luhe
Germany
40
ACKNOWLEDGEMENTS
I would like to thank Jennifer Wetz, Julie Arrington and Leah Bandstra for their
technical assistance. This research was supported by a NSF Graduate Research
Fellowship and Sigma Xi Grant In Aid of Research to MSW, and NSF Award OCE0434810 to Patricia A. Wheeler.
41
ABSTRACT
Experiments were conducted on three dates in 2005 to test whether inorganic nutrients
or grazing limit the bacterial response to senescing phytoplankton bloom. The April
experiment was run using water from a senescing laboratory diatom bloom that was
initiated from a natural coastal microbial assemblage. The August and September
experiments were run using surface water collected from the mid-shelf off Newport,
Oregon. Upwelling was occurring at the time of the August experiment and a large
diatom bloom was in place. A prolonged (> 1 wk) period of weak winds preceded the
September experiment. On all dates, nitrate, ammonium and phosphate were near limits
of detection, while DOC and DON concentrations were elevated above those found in
recently upwelled waters, indicating that blooms had supplied DOM. Only modest shortterm increases in bacterial abundance and biomass were observed in enclosures amended
with nutrients. These increases were rapidly grazed to initial levels or less. Reductions
in grazing resulted in significant increases in bacterial abundance and biomass in several
of the experiments, suggesting that grazing is the primary control on bacteria. However,
on the first two dates there was no significant loss of bacteria in treatments with grazers,
indicating a close coupling between bacterial growth and mortality.
42
INTRODUCTION
Carbon and nutrient dynamics in the ocean margins are of global significance.
Despite their relatively small contribution to the global ocean surface area (~10% of
total), margins account for a disproportionate amount of oceanic net primary production,
new production and export production (e.g., Chen et al. 2003). Eastern boundary current
upwelling systems, which account for about 10% of margin surface area, are sites of
seasonally intense organic matter production. Only in the past decade have researchers
begun to make progress in understanding the forms of phytoplankton-derived organic
matter (i.e., particulate organic matter (POM) vs. dissolved organic matter (DOM)), the
timescales of transformations between particulate and dissolved pools, and ultimately the
fate of the fixed organic matter. All of these factors converge to determine how much of
the organic matter is available for trophic transfer vs. remineralization vs. export through
sinking and/or advection.
Because upwelling systems support high upper trophic level biomass, some of the
fixed organic matter must be in particulate form. Field and laboratory studies in
upwelling systems have shown that during active growth of phytoplankton blooms, most
of the fixed organic matter (C and N) is in particulate form (Doval et al. 1997; Hill and
Wheeler 2002; Wetz and Wheeler 2003). Aside from being a food source for higher
trophic levels, POM (as phytoplankton biomass) may also sink rapidly or subduct to shelf
bottom waters (e.g., Karp-Boss et al. 2004) and if exported offshelf to deeper waters, it
may serve as a sink for atmospheric CO2 (Hales et al. in press). Upon bloom senescence,
a significant portion of the fixed organic matter may be in the form of accumulated
43
dissolved organic matter. This DOM is derived from either excretion by phytoplankton
or trophic interactions leading to DOM liberation (i.e., grazing, viral lysis) (reviewed by
Carlson 2002). Unlike POM, which can sink, export of DOM is largely limited to
advective processes.
In coastal systems, including areas influenced by upwelling, C-rich DOM has been
shown to accumulate over timescales ranging from bloom duration (days to weeks) to
seasonal (months) (Williams 1995; Alvarez-Salgado et al. 2001; Hill and Wheeler 2002).
The fact that the DOM accumulates implies that its rate of production must be greater
than its rate of removal over those timescales. In oligotrophic open ocean waters, it is
believed that availability of energy sources (i.e., labile carbon) and/or nutrients may
control bacterial production and utilization of seasonally accumulated DOM (Carlson and
Ducklow 1996; Carlson et al. 2002; Skoog et al. 2002). However, it is less clear what
factors control bacterial production to the point of allowing DOM accumulation in coastal
systems. Several studies have shown that the theoretical upper limit to bacterial biomass
may not be reached in these systems due to flagellate grazing (McManus and Peterson
1988; Sanders et al. 1992; Li et al. 2004). Nonetheless, DOM degradation is influenced
not only by bacterial biomass, but also by the relative metabolic activity and growth rates
of the bacteria. Zweifel et al. (1993) and Barbosa et al. (2001) argued that nutrient
availability may limit the ability of coastal bacteria to utilize DOM, and Barbosa et al.
suggested that either nutrient limitation or the recalcitrant nature of a portion of the DOM
facilitates net DOM accumulation in the upwelling system off the Iberian Peninsula.
Others have suggested that a portion of the autochthonous DOM pool is, in fact, simply
44
resistant to degradation over relevant timescales (Fry et al. 1996; Søndergaard et al.
2000). Finally, Thingstad et al. (1997) argued that a combination of grazing pressure and
nutrient limitation prevented bacteria from using phytoplankton-derived DOM, thus
allowing for its accumulation.
Recent studies have shown that a considerable amount of autochthonous DOM may be
exported from coastal systems (Hopkinson et al. 2002), including those influenced by
seasonal upwelling (Alvarez-Salgado et al. 2001). Alvarez-Salgado et al. (2001) suggest
that depending on the lability of the DOM, the magnitude of DOM exported to
oligotrophic offshore surface waters from coastal upwelling systems may be sufficiently
large to alter the balance between heterotrophy and autotrophy. Thus, it is important to
understand what regulates bacterial biomass and ultimately DOM degradation rates, as
this will ultimately determine the magnitude of DOM export fluxes. Here I report results
from three experiments designed to test whether inorganic nutrients or grazing limit the
bacterial response to organic matter derived from senescing phytoplankton blooms. A
companion paper (Chapter 4) describes the degradation rates of POM and DOM from
these experiments.
METHODS
Background and experimental design - Experiments were run on three dates in 2005;
18 April, 4 August and 16 September. The April experiment was run using water from a
laboratory grown diatom-dominated bloom that had depleted nitrate 1 d prior to the start
of these experiments. The bloom was initiated from a natural microbial assemblage
45
collected on the incoming tide in Yaquina Bay, Newport, Oregon. March/April is
typically a transitional period off the Oregon coast, when the predominant wind direction
shifts from wintertime downwelling favorable to upwelling favorable. The August and
September experiments were run using surface water collected from the mid-shelf off
Newport, Oregon. Upwelling off Oregon typically peaks in July/early August and
declines in late August through September. Upwelling was occurring at the time of the 4
August experiments and a large diatom bloom had depleted nitrate in the surface water.
Conditions on 15 September showed no indication of active upwelling based on the T and
S characteristics of the water and followed a prolonged (> 1 wk) period of relatively light
winds.
Experimental water was exposed to four treatments designed to test whether nutrient
limitation and/or grazing control the abundance and biomass of coastal bacteria (Table
3.1). The < 3 µm treatments essentially represent the natural microbial communities
except that nearly all fresh algal POM is removed (M.S. Wetz, unpubl. data). This was
accomplished by gently filtering raw seawater through 142 mm GF/D filters. The < 0.8
µm treatments were achieved by filtering raw seawater through 142 mm 0.8 µm
polycarbonate membrane filters. Prior to filtering seawater through the membrane filters,
~500-1000 ml of deionized water was filtered to try to minimize contamination and
leaching of organic matter. Treatments involving nutrient additions were spiked with ca.
11-16 µmol L-1 NH4Cl and 3-5 µmol L-1 KH2PO4. These relatively large nutrient
additions were made to ensure that those nutrients would not be depleted over the course
of the experiments and were not intended to mimic natural conditions during upwelling
46
bloom senescence, when recycling within the euphotic zone is the only significant source
of nutrients.
After the treatments were prepared, the seawater was placed in either 15-20 L trilaminate gas impermeable bags (April experiment; Kruse 1993) or 3-10 L high-density
polyethylene Cubitainers (August and September experiments) and incubated in the dark
at 12oC. Recently upwelled water off the Oregon coast generally averages ~8-10oC, but
as a parcel of water advects away from the core zone of active upwelling, temperatures
may rise to ≥ 12oC over a period of days to a week due to surface heating (e.g., Barth et
al. 2005). It would be during this time period that phytoplankton blooms would mature
and reach senescence, and when the potential for heterotrophic bacterial utilization of
DOM is maximal. For the April experiment, water was continuously circulated through
the bags, while in August and September, the Cubitainers were mixed manually 1-2 times
per day. Samples were collected every 24 h over a 72 h period.
Biological and chemical measurements – Bacterial and heterotrophic nanoflagellate
(HNAN) abundances were determined from duplicate samples taken from each
experimental bag. Upon collection, bacteria samples were preserved with 3% (final.
conc.) borate-buffered formalin. Immediately after preservation, 5 ml samples were
stained with 2.5x (final. conc.) SYBR Gold in the dark for 10 min. After staining, the
samples were filtered (< 5 mm Hg) onto 0.02 µm Acrodisc filters and stored at –20oC
until analysis. Slides were viewed on an Olympus BX-61 epifluorescent microscope at
1000x magnification and ~5 fields were counted per slide. Size measurements were
made on ≥ 100 cells per slide with a SensiCamQE CCD camera calibrated with an ocular
47
micrometer. Length, width and areal dimensions of the cells were converted to
biovolume, and cell C estimated assuming a relatively conservative carbon:volume ratio
of 120 fg C µm-3 (reviewed by Ducklow 2000). Samples for HNAN abundance
determinations were preserved in a three-step process with additions of 0.06% (final
conc.) alkaline Lugols solution, 3% (final conc.) borate buffered formalin and 0.12%
(final conc.) sodium thiosulfate. After preservation, the samples were stored at 4oC for
12 h to allow the HNAN to shrink and harden. A subsample from each replicate was
stained with DAPI (final conc. ~ 25 µg ml-1 sample) for 10 min in the dark, then filtered
through a 0.8 µm polycarbonate membrane filter. Samples were analyzed at 600x
magnification using an Olympus BX-61 epifluorescent microscope and at least 20 fields
per slide were counted. Dissolved nutrients were measured using standard wet chemical
techniques on a Technicon AA-II analyzer (Gordon et al. 1995).
Statistical analyses – Due to cost and time constraints, we were unable to replicate
each treatment on each date. Thus, we cannot use inferential statistics to analyze the data
within each date, as this would be pseudoreplication (Hurlbert 1984). Instead, we
repeated the experiments three times and treated the responses over all dates as replicates.
Multi-factor analysis of variance (ANOVA) was used to test for significant effects of
nutrients and/or grazing on bacterial abundance/biomass (Zar 1996). Analyses were
performed using SPSS 13.0 (SPSS Inc.).
RESULTS AND DISCUSSION
48
Off Oregon and in other coastal upwelling systems, periods of upwelling tend to last
for several days to a week and are interspersed between periods of relaxed or even
downwelling-favorable winds (Huyer 1983). As surface water moves away from the core
of the upwelling front or after wind relaxation or reversals, large phytoplankton blooms
can rapidly (< 1 wk) deplete inorganic nutrients while producing significant amounts of
organic matter. Nitrate was completely depleted in the raw seawater used to start each
experiment, and ammonium and phosphate were near the limits of detection (Table 3.2).
Initial DOM concentrations exceeded those typically found in recently upwelled waters,
which averages ~49 µmol L-1 DOC and ~5 µmol L-1 DON (P.A. Wheeler, unpubl. data).
The amount of “excess” DOM, or the DOM concentration that was in excess of upwelled
concentrations, ranged from 27-117 µmol L-1 DOC and 5.1-7.3 µmol L-1 DON (Table
3.2). The molar C:N ratio of this “excess” DOM was ~17 in April, ~10 in August, and
~6 in September. From our limited sampling, it is impossible to tell whether this
progressive decrease is a true seasonal temporal sequence or if it is strictly event related.
Initial POM concentrations were also high, ranging from 109-325 µmol L-1 POC and 1626 µmol L-1 PON (data not shown). The molar C:N ratio of the POM was ~12 in the
April experiment, ~10 in August, and ~7 in September.
Initial bacterial abundances and C biomass were generally similar between April and
August, ranging from 2.2-5.9 x 105 cells ml-1 and 0.6-2 µmol C L-1 (Table 3.3). There
were few differences between the treatments in terms of abundance or biomass. Initial
abundances and C biomass were much higher in September, ranging from 1.1-1.7 x 106
cells ml-1 and 8.1-18.7 µmol L-1. There were some initial differences between treatments
49
in September, as mean cell biovolume (data not shown) and biomass (Table 3.3) was
twice as high in the < 3 µm treatments compared with the < 0.8 µm treatments. Overall,
mean cell biovolumes were about 1.5-3 times higher in September than on the other two
dates (data not shown). The cause of this increased bacterial abundance and cell size
relative to the other two dates is unclear, though it could be a consequence of a short-term
event (i.e., pulse of labile organic matter, advection of high bacteria patch, etc.) (e.g.
Sherr et al. 2001). Wetz and Wheeler (2004) observed order of magnitude changes in
bacterial abundance and in the proportion of high nucleic acid content bacteria, which are
relatively large cells, over a period of a few days. Hydrographic variability has also been
proposed to exert some influence on bacterial growth in these types of systems.
McManus and Peterson (1988) found that bacterial biomass maxima occurred during
periods of relaxed winds and stratification in the upwelling system off Chile. Wind
intensity was relatively low for at least 1 wk prior to collection of the September seawater
used here, while the August sample was collected during a period of active upwelling.
These differences in hydrographic forcing may partially explain the differences in
bacterial biomass.
HNAN abundances in the < 3 µm treatments in each experiment ranged from 1.5-11.6
x 103 cells ml-1 (Table 3.3). Few, if any, HNAN were observed in the < 0.8 µm
treatments. However, our use of 0.8 µm filters to collect the HNAN for microscopy may
have missed small HNAN, which have been reported in the literature (e.g., Fuhrman and
McManus 1984). Nonetheless, few particles larger than bacterial-size were present on
the 0.02 µm filters used to measure the bacteria in those treatments, indicating that we
50
likely did not significantly underestimate the abundance of HNAN in these experiments.
HNAN abundances varied little over the course of each experiment (data not shown).
In the April experiments, there was only a small net increase in bacterial abundances
and biomass in the < 3 µm treatment after 3 d (Figs. 3.1A, 3.2A). Abundances and
biomass increased slightly after 1 d in the < 3 um + nutrients treatment, but subsequently
decreased to near initial levels (Figs. 3.1A, 3.2A). In August, abundances and biomass in
the < 3 µm and < 3 µm + nutrients treatments initially increased after 1 d (Figs. 3.1B,
3.2B), but subsequently decreased to initial levels. The fact that overall there was little
net loss or gain of the bacteria parameters in these treatments with grazers implies that
bacteria growth and grazing mortality were closely coupled. Much of the increased
(relative to previous sampling dates) bacterial biomass in September appeared to be
readily grazed over the 3 d period. Bacterial abundances and biomass in the < 3 µm
treatment decreased dramatically throughout the experiment (Figs. 3.1C, 3.2C).
Abundances and biomass in the < 3 µm + nutrients treatment increased slightly after 1 d,
but subsequently decreased over the next 2 d (Figs. 3.1C, 3.2C). Additionally, the
average cell biovolume dropped by ~ 27% after 1 d in these treatments and by 47% after
3 d (data not shown), indicating that selective feeding on the larger cells may have been
occurring, consistent with previous bacterivory studies (Sherr et al. 1992; del Giorgio et
al. 1996). Abundances and biomass in the treatment without grazers (i.e., < 0.8 µm)
increased by various degrees on all three dates (Figs. 3.1A-C, 3.2A-C) and remained
elevated over the 3 d period. Likewise, abundances and biomass in the < 0.8 µm +
nutrients treatments increased and remained elevated throughout the April and August
51
experiments (Figs. 3.1A-B, 3.2A-B). However, it appears that a filter may have ruptured
during the set-up process of the September sample. Hence, that sample was
contaminated (w/ high POC, bacteria, flagellates, etc.) and is not included in this analysis.
Overall, there was no significant treatment effect on either bacterial abundance or
biomass after 1 d (p > 0.05; ANOVA). However, after 3 d, grazing had a significant
effect on bacterial abundance (p = 0.006), although the effect on bacterial biomass was
lessened (p = 0.08) and may have been masked by changes in the size structure of the
bacterioplankton and/or selective grazing.
CONCLUSIONS
Based on the lack of measurable nutrients at the start of these experiments, typical of
post-bloom situations in upwelling systems, it would be tempting to speculate that
nutrients limit the bacterial response to the potentially large supplies of fresh
phytoplankton organic matter. However, our results suggest that grazing is a much more
important control on bacterial abundances and biomass as opposed to nutrients, which
supports the findings of previous studies of high-productivity coastal systems (e.g.,
Sanders et al. 1992; Li et al. 2004). Thus, factors that lead to reductions in bacterivory
(i.e., grazing on HNAN by micro- and macrozooplankton; Jurgens et al. 1996) or that
prevent significant development of HNAN communities (i.e., hydrographic variability;
McManus and Peterson 1988) may lead to an enhanced bacterial response to coastal
phytoplankton blooms. In addition to grazing, viruses are known to exert some control
on bacterial biomass in coastal systems (reviewed by Fuhrman 2000) and diatom
52
allelopathy may also be important (e.g., Sherr et al. 2006). In terms of viruses, given the
host density dependence of viral activity it seems likely that viral activity was minimal
relative to grazing in the April and August experiments that had low bacterial
abundances. In the September experiment where bacterial abundances were much
higher, grazing still seemed to be responsible for much of the bacterial mortality. No
determination can be made of the importance of diatom allelopathy, as nearly all diatoms
should have been removed by our pre-filtration through the 3.0 µm filters. However, this
is clearly an idea requiring further field and laboratory studies.
While reductions in grazing may lead to net increases in bacterial abundance and
biomass, it might not lead to any enhancement of organic matter degradation. When
considering degradation of organic matter, bacterial metabolic activity in addition to
biomass is also an important factor. On the first two dates of these experiments, there
was no significant loss of bacteria in treatments with grazers, indicating a close coupling
between bacterial growth and mortality. Thus, despite the grazing pressure on bacteria,
organic matter may still be degraded efficiently (see Chapter 4). Furthermore, the
responses of bacteria to reduced grazing in these experiments should not lead one to
conclude that nutrients or the quality of the organic matter are unimportant, because these
may still affect the activity of bacteria without having a noticeable effect on abundance or
biomass (see Chapter 4). Additionally, it appears that pulses of nutrients may briefly
stimulate bacterial growth (i.e., increases in our Day 1 samples), although these gains
were quickly grazed down to pre-pulse levels or even less. Finally, grazing reductions
alone led to increases in biomass and abundance of bacteria in August and September,
53
but grazing reduction combined with nutrients was necessary to stimulate growth in
April. This implies that in April, the bacteria may have been reliant on the excretion of
nutrients (i.e., ammonium) by the HNAN to support their growth (reviewed by Strom
2000), while on the other dates they may have been able to use DON. The excess DOM
pool in April had a relatively high C:N (~17), favoring uptake of ammonium by bacteria
(Goldman et al. 1987). Indeed, ammonium was drawn down (by 6.8-7.6 µmol L-1) in the
nutrient amended enclosures in April (data not shown). On the other dates, the C:N of
the excess DOM was much lower (~6-10), favoring remineralization of DON to
ammonium. Slight drawdowns of DON and increases in ammonium were observed on
those dates. These results suggest that there may be some degree of temporal variability
(seasonal, event scale, etc.) in what controls coastal bacterioplankton growth. While
difficult to discern from our limited sampling, this is an important topic requiring further
study.
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Prog. Ser. 101: 23-32
57
Table 3.1. Experimental treatments used to test whether nutrients and/or grazing control
bacterial abundance/biomass.
Treatment
< 0.8 µm + Nutrients
< 0.8 µm
< 3 µm + Nutrients
< 3 µm
Description
0.8 µm filtered water w/ ammonium
and phosphate additions
0.8 µm filtered water
3.0 µm filtered water w/ ammonium
and phosphate additions
3.0 µm filtered water
58
Table 3.2. Initial concentrations of dissolved inorganic nitrogen, dissolved inorganic
phosphorous, excess (above upwelled concentrations) dissolved organic carbon, excess
dissolved organic nitrogen, and the C:N (mol:mol) of the excess DOM pool.
Experiment
Treatment
[DIN]
[DIP] [DOC]ex (SE) [DON]ex (SE) DOMex C:N (SE)
April
< 0.8 + Nuts
< 0.8
< 3 + Nuts
<3
17.7
0.3
14.6
0.3
3.2
0.1
2.8
0.1
117.3 (4.3)
7.3 (0.9)
16.8 (2.1)
August
< 0.8 + Nuts
< 0.8
< 3 + Nuts
<3
13.5
0.2
11.3
0.4
4.3
0.3
4.4
0.3
63.3 (10.3)
6.6 (3.3)
10.3 (1.4)
September
< 0.8 + Nuts
< 0.8
< 3 + Nuts
<3
27.3 (2.3)
5.1 (2.9)
5.7 (1.0)
0.3
14.5
0.3
0.2
4.9
0.2
59
Table 3.3. Initial bacterial abundances (x 106 cells ml-1), bacterial carbon biomass (µmol
L-1) and HNAN abundances (x 103 cells ml-1). Note that due to a sample processing
error, no HNAN abundances are available for the April < 0.8 µm treatment.
Experiment
Treatment
April < 0.8 + Nuts
< 0.8
< 3 + Nuts
<3
Bact. abundance
0.33
0.59
0.53
0.53
Bact. C
1.57
1.96
1.45
1.30
HNAN abundance
0.05
August < 0.8 + Nuts
< 0.8
< 3 + Nuts
<3
0.26
0.23
0.22
0.22
1.36
0.85
0.70
0.62
0.08
0.11
11.60
9.94
September < 0.8 + Nuts
< 0.8
< 3 + Nuts
<3
1.44
1.60
1.66
8.05
18.66
15.01
0.00
5.14
5.33
1.54
1.73
60
< 0.8 + nuts
< 0.8
< 3 + nuts
<3
A
-1
Bacteria abundance change (x 10 cells ml )
3.0E+06
3.0
2.5E+06
2.0E+06
2.0
1.5E+06
1.0
1.0E+06
5.0E+05
0.0E+00
0.0
-5.0E+05
-1.0E+06
-1.0
-1.5E+06
0
1
2
3
6
3.0E+06
3.0
2.5E+06
2.0E+06
2.0
1.5E+06
1.0E+06
1.0
5.0E+05
0.0E+00
0.0
-5.0E+05
-1.0E+06
-1.0
-1.5E+06
3.0
3.0E+06
2.5E+06
2.0E+06
2.0
1.5E+06
1.0E+06
1.0
5.0E+05
0.0
0.0E+00
4
B
0
1
2
3
4
C
-5.0E+05
-1.0
-1.0E+06
-1.5E+06
0
1
2
3
4
Day
Figure 3.1. Bacterial abundance change (x 106 cells ml-1) in A) April, B) August and C)
September experiments.
Bacteria biomass change (µmol L-1)
61
16
12
8
4
0
-4
-8
-12
-16
-20
A
< 0.8 + nuts
< 0.8
< 3 + nuts
<3
0
1
2
3
16
12
8
4
0
-4
-8
-12
-16
-20
4
B
0
1
2
3
16
12
8
4
0
-4
-8
-12
-16
-20
4
C
0
1
2
Day
3
4
Figure 3.2. Bacteria C biomass change (µmol C L-1) in A) April, B) August and C)
September experiments.
62
Chapter 4. Degradation of Diatom-Derived Organic Matter: Implications for C and N
Biogeochemistry
Michael S. Wetz
For submission to Limnology and Oceanography
343 Lady MacDonald Crescent
Canmore, Alberta T1W 1H5
Canada
63
ACKNOWLEDGEMENTS
I would like to thank Jennifer Wetz, Julie Arrington and Leah Bandstra for their
technical assistance. This research was supported by a NSF Graduate Research
Fellowship and a Sigma Xi Grant In Aid of Research to MSW, NSF grant OCE-0434810
to Patricia A. Wheeler and NSF grant OCE-9907854 to Patricia A. Wheeler and Burke
Hales.
64
ABSTRACT
Experiments were conducted to determine rates of phytoplankton-derived particulate
(POM) and dissolved (DOM) organic matter degradation by natural microbial
communities and to determine if degradation is limited by nutrients or by grazing on
bacteria. On each date, nutrients were depleted and organic matter concentrations were
elevated above concentrations found in recently upwelled water. Degradation of DOC
was initially rapid and then proceeded at a slower rate. After 3 d, 47 % of the DOC was
degraded and neither reductions in grazing on bacteria or nutrient additions significantly
enhanced the degradation. On average, 33 % of the POC was degraded after 3 d,
although some portion was converted to DOC and not respired. Despite the degradation
of the C components of the organic matter, there was little evidence of degradation of the
N components. Overall, these results suggest that while at least half of the
phytoplankton-derived DOC is rapidly degraded, a significant amount of less labile DOC
may still accumulate if retained in coastal waters. Additionally, the long degradation
time of the less labile fraction relative to potential offshelf transport mechanisms suggests
that Oregon’s coastal waters may be a significant source of organic matter to adjacent
offshore waters of the North Pacific. Finally, because of its lability, the POC will
contribute to shelf bottom water oxygen utilization as it decays.
65
INTRODUCTION
Eastern boundary current upwelling systems are sites of seasonally intense organic
matter production and processing, accounting for ~10-15% of global ocean new
production (Chavez and Toggweiler 1995). Important exchanges of carbon (C) take
place between the air and sea in these regions, with significant implications for global C
budgets. For example, the upwelling system off Oregon is a major sink for atmospheric
CO2 during both the summer upwelling season and on an annual basis (Hales et al. 2005).
This net influx of CO2 from the atmosphere is facilitated through the transfer of
particulate organic matter (POM; i.e., phytoplankton biomass) from surface to bottom
waters and ultimately offshelf to deeper waters (Hales et al. 2006). However, some of
this POM is undoubtedly respired on the shelf and likely contributed to a recent episode
of widespread hypoxia on the Oregon shelf (Grantham et al. 2004).
In addition to production of POM, some of the phytoplankton-derived organic C may
accumulate as dissolved organic matter (DOM). This DOM is derived from either
excretion by phytoplankton or trophic interactions leading to DOM liberation (i.e.,
grazing, viral lysis) (reviewed by Carlson 2002). In contrast to export of POM via
sinking flux, export of DOM is largely limited to advective processes. In coastal
systems, including areas influenced by upwelling, C-rich DOM has been shown to
accumulate over timescales ranging from bloom duration (days to weeks) to seasonal
(months) (Williams 1995; Alvarez-Salgado et al. 2001a; Hill and Wheeler 2002). Recent
studies suggest that autochthonous DOM may be exported from coastal systems
(Hopkinson et al. 2002), including those influenced by seasonal upwelling (Alvarez-
66
Salgado et al. 2001a,b). Alvarez-Salgado et al. (2001a) argued that depending on the
lability of the DOM, the magnitude of DOM exported to oligotrophic offshore surface
waters from coastal upwelling systems may be sufficiently large to alter the balance
between heterotrophy and autotrophy. Thus, it is important to understand what regulates
DOM degradation in coastal systems, as this will ultimately determine the magnitude of
DOM export fluxes. Likewise, it is important to quantify POM degradation, as this
combined with knowledge of circulation patterns and shelf water residence times will
help to better understand and model ecosystem-level process and biogeochemical cycles
off Oregon and in other similar systems.
The fact that the DOM accumulates implies that its rate of production must be greater
than its rate of removal over the timescales of the accumulation. It is not entirely clear
what factors control bacterial production to the point of allowing DOM accumulation in
coastal systems. Grazing (Sanders et al. 1992; Li et al. 2004), nutrients (Zweifel et al.
1993; Barbosa et al. 2001), grazing and nutrients (Thingstad et al. 1997), diatom
allelopathy (Sherr et al. 2006), or quality of the accumulated organic matter (Fry et al.
1996; Søndergaard et al. 2000) have all been proposed as controlling bacterial abundance
and/or production in coastal waters. In Chapter 3, evidence was presented showing that
off Oregon, grazing is an important control on bacterial abundance and biomass.
Reductions in grazer biomass by size fractionation allowed the bacteria population to
increase. However, in the unfiltered treatments, bacterial growth and grazing mortality
were balanced in two of three experiments. If the bacteria were actively dividing, but
67
their population biomass did not increase due to grazing, organic matter could still have
been degraded.
In this chapter, results are presented from three experiments designed to quantify
DOM and POM degradation rates. Enclosures containing only DOM (i.e., with POM
removed) were either left unaltered or exposed to nutrient additions and/or grazing
reductions to determine if degradation rates are limited by nutrient supplies to bacteria or
by grazing on the bacteria.
METHODS
Background and experimental design - Experiments were run on three dates in 2005;
18 April, 4 August and 16 September. The April experiment was run using water from a
laboratory grown diatom-dominated bloom that had depleted nitrate 1 d prior to the start
of these experiments. The bloom was initiated from a natural microbial assemblage
collected on the incoming tide in Yaquina Bay, Newport, Oregon. March/April is a
transitional period off the Oregon coast, when the predominant winds shift from
wintertime downwelling favorable to upwelling favorable. The August and September
experiments were run using surface water collected from mid-shelf locations off
Newport, Oregon (44o39.1’ N, 124o17.7’ W and 44o39.3’ N, 124o24.7’ W respectively).
Upwelling off Oregon typically peaks in July/early August and declines in late August
through September. Upwelling was occurring at the time of the 4 August experiments
and a large diatom bloom that had depleted nitrate was in place. Conditions on 15
September showed no indication of active upwelling based on the temperature and
68
salinity characteristics of the water and followed a prolonged (> 1 wk) period of
relatively light winds.
Experimental water was exposed to five treatments designed to test whether nutrient
limitation and/or grazing control the abundance and biomass of coastal bacteria and affect
degradation of organic matter (Table 4.1). The < 3 µm treatments essentially represent
the natural microbial communities except that nearly all fresh algal POM is removed.
This was accomplished by gently filtering raw seawater through 142 mm GF/D filters.
The < 0.8 µm treatments were achieved by filtering raw seawater through 142 mm 0.8
µm polycarbonate membrane filters. Prior to filtering seawater through the membrane
filters, ~500-1000 ml of deionized water was filtered to minimize contamination from
leaching of organic matter. Treatments involving nutrient additions were spiked with ca.
11-16 µmol L-1 NH4Cl and 3-5 µmol L-1 KH2PO4. It should be noted that these additions
were not designed to mimic natural conditions during upwelling bloom senescence, when
recycling within the euphotic zone is the only significant source of nutrients. An
additional treatment to control for abiotic losses of TOC was prepared from the < 0.8 µm
filtered water. To this water, concentrated mercuric chloride was added to stop all
biological activity.
After the treatments were prepared, the seawater was placed in either 15-20 L trilaminate gas impermeable bags (April experiment; Kruse 1993) or 3-10 L high-density
polyethylene Cubitainers (August and September experiments) and incubated in the dark
at 12oC. Recently upwelled water off the Oregon coast generally averages ~8-10oC, but
as a parcel of water advects away from the core zone of active upwelling, temperatures
69
may rise to ≥ 12oC over a period of days to a week due to surface heating (e.g., Barth et
al. 2005). It would be during this 3-7 d time period that upwelling phytoplankton blooms
mature and reach senescence, and this would also be when the potential for degradation
of the phytoplankton-derived organic matter is maximal. For the April experiment, water
was continuously circulated through the bags, while in August and September, the
Cubitainers were mixed manually 1-2 times per day. Samples were collected every 12-24
h over a 3 d period.
Chemical measurements – Nutrient samples were collected in acid-washed 30 ml
HDPE bottles and immediately frozen at –30oC. Samples were analyzed on a Technicon
AA-II according to standard wet chemical methods of Gordon et al. (1995). Standard
curves with four different concentrations were run daily at the beginning and end of each
run. Fresh standards were made prior to each run by diluting a primary standard with low
nutrient surface seawater. Deionizied water (DIW) was used as a blank, and triplicate
DIW blanks were run at the beginning and end of each run to correct for baseline shifts.
Nitrate was determined by subtracting nitrite from nitrate plus nitrite (N+N).
Total nitrogen (TN) samples were collected in acid washed 30 ml Teflon bottles and
immediately frozen at –30oC until analysis. Organic N was converted to nitrate using a
persulfate wet oxidation method (Libby and Wheeler 1997), and then analyzed using a
Technicon AA-II. Instrument calibration was performed daily using a standard curve
prepared from triplicate digested leucine standards at three concentrations. Fresh
standards were made prior to each run by diluting a primary standard with artificial
seawater. Digested artificial seawater was used as a blank, and the standard curve was
70
corrected for N content of the blank by determining the concentration of N in the
persulfate solution and then calculating the amount of N in the artificial seawater.
Artificial seawater N content was estimated as the difference between the blank and
persulfate signals.
Total organic carbon (TOC) samples were collected in acid-washed borosilicate vials
with Teflon cap liners. Each vial contained approximately 5 ml of seawater that was
preserved with 50 µl of 90% phosphoric acid. Samples were stored at room temperature
until processing using the High Temperature Catalytic Combustion method on a
Shimadzu TOC-5000A analyzer. Standard curves were run twice daily using a DIW
blank and four concentrations of an acid potassium phthalate solution. Three to five
subsamples were taken from each standard and water sample and injected in sequence.
Variance between subsamples averaged 1.5 ± 1.2 %. Certified Reference Material
Program (CRMP) deep-water standards of known TOC concentration were injected in
triplicate at the beginning, middle, and end of each run to check for baseline shifts.
Baseline drift was calculated from changes in the deep-water concentrations during a run,
and a drift correction was applied to the raw data. The data from each date were then
normalized to the average daily CRMP TOC concentration. Average daily CRMP TOC
concentrations (05-04 batch) were 43.1 ± 2.2 µmol L-1.
Particulate organic carbon (POC) and nitrogen (PON) were determined from material
that was vacuum filtered (< 200 mm Hg) onto precombusted GF/F filters. After
filtration, filters were stored in glass VacutainersTM and immediately frozen at –30 oC
until laboratory analysis. Filters were fumed with concentrated HCl to remove inorganic
71
C and dried, followed by analysis using a Control Equipment Corp. 440HA CHN
elemental analyzer calibrated with acetanilide. During analysis, filter blanks were run
after every twelve samples. Filter blanks averaged 17.6 ± 2.9 µg C and 1.1 ± 0.8 µg N,
and these values were subtracted from each measured value as a blank correction.
Dissolved organic nitrogen (DON) was determined by subtracting PON and DIN
(NH4, N+N) from TN (Eq. 1).
DON = TN – PON – DIN
(1)
Dissolved organic carbon (DOC) was determined by subtracting POC values from TOC
values (Eq. 2).
DOC = TOC – POC
(2)
Calculation of degradation rate constants - Degradation rate constants for the POC
and DOC pools were calculated using a simple first-order equation (Eq. 3).
Ct = C0e-kt
(3)
Ct is the concentration at time t (in this case 3 d), C0 is the initial concentration, and k is
the degradation constant.
Statistical analyses – Due to cost and time constraints, we were unable to replicate
each treatment on each date. Thus, we cannot use inferential statistics to analyze the data
within each date, as this would be pseudoreplication (Hurlbert 1984). Instead, we
repeated the experiments three times and treated the responses over all dates as replicates.
Multi-factor analysis of variance (ANOVA) was used to test for significant effects of
nutrients and/or grazing on DOM degradation rates (Zar 1996). Analyses were
performed using StatGraphics Centurion XV (StatPoint, Inc.).
72
RESULTS
Initial conditions - On each date, nutrients were depleted and organic matter
concentrations were elevated above concentrations found in recently upwelled water.
Upwelled water off Oregon contains ~ 49 µmol L-1 DOC and ~ 5 µmol L-1 DON (P.A.
Wheeler, unpubl. data). Initial mean DOC concentrations ranged from 67-155 µmol L-1
(Table 4.2). Likewise, initial mean DON concentrations ranged from 10-12 µmol L-1.
The molar C:N ratio of this DOM was ~13 in April, ~11.5 in August, and ~6.9 in
September. Initial POM concentrations were also high, ranging from 109-325 µmol L-1
POC and 16-26 µmol L-1 PON (Table 4.2). The molar C:N ratio of this POM was ~12 in
April, ~10 in August, and ~ 7 in September.
Before proceeding with discussion of organic matter degradation dynamics, it is
important to point out that oxygen could not have been depleted over the course of these
3 d experiments. While oxygen was not directly measured, it is possible to
conservatively estimate the minimum amount of oxygen that would be left after 3 d based
on other data. The April experimental water was collected just after the peak of a large
laboratory grown diatom bloom and was free to exchange with the laboratory air. The
August and September experiments were from surface waters off the Oregon coast and
both had elevated phytoplankton biomass and organic matter, indicative of bloom
conditions. Shelf surface waters off Oregon during the summer are usually
supersaturated with respect to oxygen, and surface O2 concentrations of ~300 µmol L-1
are common (Hales et al. 2006). The maximum amount of organic C that was degraded
73
and the maximum amount of CO2 that accumulated in our experiments was ~87 µmol L-1.
If we assume that O2 consumption proceeds at 138 mol O2 per 106 mol C, then the
maximum oxygen loss would be on the order of 113 µmol L-1. Thus, after 3 d, the lowest
amount of oxygen would be ~187 µmol L-1, clearly nowhere near hypoxic (~2 mg L-1 or
63 µmol L-1; Rabalais et al. 2002) or anoxic levels.
Impact of nutrient amendments and/or grazing reduction on DOM degradation –
TOC/DOC concentrations varied little in the fixed control treatment (M.S. Wetz, unpubl.
data). For clarity and to eliminate minor day-to-day analytical variability in the
TOC/DOC analyses, the data from each daily analysis of TOC/DOC has been normalized
to the mean fixed TOC/DOC value for each experiment. On the first two dates, DOC
degradation began in the first 12 h of the experiments (Figs. 4.1A,B). The only exception
was the August < 0.8 µm treatment, in which noticeable degradation did not start until
between 12-24 h (Fig. 4.1B). In September, there was a lag of 12 h before DOC
degradation was observed (Fig. 4.1C). In general, the largest DOC decreases occurred in
the first 24 h and then continued in lesser amounts through the end of the experiments.
The total amount of DOC that was degraded after 3 d on the first two dates ranged from
31-59 µmol L-1 (Figs. 4.1A,B), while only 7-10 µmol L-1 was degraded in September
(Fig. 4.1C). As a percentage of the initial excess DOC pool, which eliminates variations
in the total starting DOC pool between treatments, 14-68 % of the excess DOC was
degraded after 1 d (mean = 32.4 ± 17.8 %) and 26-73 % was degraded after 3 d (mean =
47.3 ± 17.4 %) (Figs. 4.2A-C). Despite the fact that reductions in grazing resulted in
statistically significant increases in bacterial abundance, there was no effect on DOC
74
degradation after 1 d (p = 0.99) or 3 d (p = 0.92). Likewise, nutrient addition treatments
resulted in slightly higher but not statistically significant (p = 0.34) DOC degradation
rates after 3 d.
The DON pool varied amongst the experiments in response to the experimental
treatments. In April, nutrient additions resulted in large DIN decreases (6.8-7.6 µmol L-1
after 3 d) (Fig. 4.3A) and an accumulation of DON (7.2-8 µmol L-1 after 3 d; Fig. 4.4A).
In the non-nutrient addition treatments, there were only slight (< 1 µmol L-1) net
increases in DON or decreases in DIN after 3 d. In contrast to the April results, nutrient
additions resulted in DIN increases (0.8-5.7 µmol L-1; Figs. 4.3B,C) and DON decreases
(2.7-6.6 µmol L-1) (Figs. 4.4B,C) after 3 d in August and September. As observed in the
April experiment, non-nutrient addition treatments in August and September resulted in
relatively little change in the DON or DIN pools over 3 d, except in the September < 0.8
µm treatment in which DON decreased by ca. 3.4 µmol L-1 after 3 d (Fig. 4.4C).
Organic matter degradation in whole water - POC degradation was not noticeable in
the April experiment until after 1 d, when degradation proceeded rapidly for 1 d followed
by a lesser amount of degradation (Fig. 4.5A). In August and September, POC
degradation began in the first 12 h and proceeded almost linearly over the 3 d period (Fig.
4.5A). Maximum POC losses in the three experiments after 3 d ranged from 34-159
µmol L-1. Not all of this POC was respired however, as some was broken down and
converted to DOC. This was especially apparent in April and to a lesser extent in
September. Nonetheless, on all dates the TOC pool decreased over time and maximum
TOC losses after 3 d ranged from 29-87 µmol L-1 (Fig. 4.5A). TOC degradation was
75
nearly linear over the 3 d in April and August, but occurred rapidly in the first 24 h in
September before slowing drastically (Fig. 4.5A). After 1 d, 0-13 % of the POC had been
degraded and the net loss of TOC ranged from 6-29 % (Fig. 4.5B). After 3 d, 17-49 % of
the POC had been degraded and the net loss of TOC ranged from 16-32 % (Fig. 4.5B).
In contrast to the relatively large amount of organic C degradation that took place,
there was very little evidence of organic nitrogen losses in these experiments (Fig. 4.5C).
In April, PON concentrations varied around the starting concentration, but were always
within the precision of the measurement. After 2-3 d in September, there was a
noticeable decrease in PON (~1.8-3 µmol L-1). However, TN concentrations dropped by
~1-2.3 µmol L-1 after 2-3 d, indicative of incomplete sampling of the PON pool. Hence,
probably only half of the observed PON decrease was real. The DON results are fairly
similar to those seen in the < 3 µm treatments described above, in which little net change
in DON was observed. This lack of organic nitrogen degradation, coupled with the
significant degradation of organic C, implies that the C component of the organic matter
was selectively remineralized, both for the POM and DOM.
In the two experiments where POC degradation was linear over 3 d, decay constants
were 0.06 and 0.13 d-1 (Table 4.3). In April, POC decayed rapidly for a day at 0.68 d-1
and then more slowly at 0.04 d-1. Extrapolating the decay rates of POC from each
experiment through time shows that 50.2 ± 12.9 % would decay after 7 d, 69.4 ± 12.5 %
after 14 d, and 88.3 ± 8.2 % after 30 d (Table 4.3). Rates of TOC decay in the two
experiments in which decay proceeded linearly were 0.06 and 0.13 d-1 (Table 4.3). In
September, TOC decay proceeded rapidly for 1 d at 0.35 d-1, followed by a slower decay
76
rate of 0.01 d-1. Extrapolating the decay rates of TOC from each experiment through
time shows that 41.6 ± 15.5 % would decay after 7 d, 57.9 ± 24.9 % after 14 d, and 73.3
± 30.7 % after 30 d (Table 4.3).
DISCUSSION
There are several important findings from this study. First, neither grazing reductions
nor nutrient amendments resulted in statistically significant increases in the rates of
phytoplankton-derived DOC degradation. Second, a fraction of the phytoplanktonderived organic C (both DOC and POC) was rapidly degraded over a period of a few
days, while it appears that another fraction remains intact. Finally, there was little
evidence of significant organic nitrogen degradation, suggesting that remineralization of
phytoplankton-derived organic matter may proceed by preferentially favoring C
remineralization, at least over short timescales used in this study. The ecological
implications of these will be discussed in the following sections.
Degradation of significant amounts of phytoplankton-derived DOC occurred in all
three experiments. Despite the fact that reductions in grazing resulted in increased
bacterial abundance and biomass (see Chapter 3) and that nutrient concentrations were
near detection limits, neither grazing reductions nor nutrient additions significantly
enhanced DOC degradation. This is consistent with the work of Sondergaard et al.
(2000), who showed that nutrient additions did not enhance degradation of DOM
originating from a phytoplankton bloom. Those authors argued that the chemical
composition of a large portion of the DOM made it resistant to bacterial degradation.
77
Likewise, Fry et al. (1996) found that ~ 35% of the DOM derived from a coastal diatom
bloom remained intact after 2.5 y, and that nutrient additions did not stimulate further
degradation. One potential mechanism for enhancing DOM degradation that cannot be
assessed using dark incubations as in this study and the Sondergaard et al. (2000) and Fry
et al. (1996) studies is photochemical breakdown. In recent years, studies have shown
that photochemical processes can strongly impact DOM cycling, sometimes by
enhancing its breakdown and other times by making it more refractory (reviewed by
Mopper and Kieber 2002). Most of this literature has focused on photochemical effects
on terrestrial DOM rather than phytoplankton-derived DOM. One recent study by
Obernosterer and Benner (2004) did find that photochemical processes enhanced
terrestrial DOM degradation, while having no effect on plankton-derived DOM. Clearly
more work is needed on this topic, especially in coastal systems such as off Oregon
where the C cycle is driven by autochthonous production.
In general, DOC degradation appeared to occur rapidly over the first day or so before
slowing down. The DOC decay constants during the rapid degradation phase ranged
from 0.16-0.38 d-1, consistent with previously reported constants from diatom blooms
(e.g., Chen and Wangersky 1996). After 3 d, 27-68 % (mean = 41 ± 24 %) of the DOC
had been degraded. In a laboratory grown diatom culture, Biddanda (1988) observed an
average DOC degradation of ~25 % after 3 d. In two of the three experiments reported
here, it appears that degradation ceased after 2 or 3 d. However, it is likely that
degradation continued (or would continue over time), albeit at much slower rates, and
that the lack of high temporal resolution sampling combined with termination of the
78
experiments after 3 d precluded elucidation of the degradation rates in the slower phase.
In fact, several workers have shown that DOC degradation proceeds rapidly for a few
days, followed by continued degradation at much slower rates (e.g., Biddanda 1988;
Chen and Wangersky 1996). Applying the decay constant obtained by Chen and
Wangersky (1996) for the second phase of DOC decay from a natural phytoplankton
assemblage (0.03 d-1) to data from these experiments, it is estimated that on average, a
maximum of 65 and 78 % of the DOC would degrade after 14 d and 30 d respectively.
This is undoubtedly an overestimate however, because in the subsequent degradation
phases (post- second phase), decay constants are an order of magnitude lower (e.g., Chen
and Wangersky 1996). Thus, in coastal upwelling regions for example, accumulations of
DOC may be due to the retention of water masses containing the semilabile (resistant)
DOC for periods longer than its turnover time, perhaps through wind relaxation or
reversals that restrict offshelf movement of surface waters, combined with continued
DOC production by phytoplankton. This was a key finding of Sondergaard et al. (2000),
who suggested that this may be common to most coastal regions where seasonal
accumulations of DOM take place.
Unlike results reported for DOC, there was very little evidence of DON degradation,
at least in the whole water treatments and the < 3 µm treatment, which are the most
representative of the natural microbial community compared to the other filtered
treatments. This C-selective DOM degradation is somewhat surprising given that most
field studies tend to show that the N and P components of DOM are selectively
remineralized, particularly over timescales of offshelf movement of coastal water masses
79
(weeks to months) (e.g., Hopkinson et al. 2002). Also, considering the low ambient DIN
concentrations, one might speculate that the N portion of the DOM would be
preferentially degraded over the C portion. However, it is important to remember that
especially in the whole water and < 3 µm treatments, micrograzers were present and
while they consume bacteria, they also excrete nutrients that promote continued bacterial
growth and metabolism (Strom 2000). Thus although DIN concentrations may have been
low, rates of DIN cycling may have been high. Furthermore, during coastal diatom
blooms, there is a tendency towards high rates of polysaccharide production (Nieto-Cid et
al. 2004), which contain very little N and are known to be labile (Aluwihare and Repeta
1999). This polysaccharide production can temporarily drive the C:N of the DOM (and
total organic matter) pool well above the Redfield ratio. Because of the labile nature of
this material however, it may be selectively remineralized, sometimes on timescales as
short as bloom duration (e.g., Kepkay et al. 1997). The net effect of this selective
remineralization of C-rich compounds, at least on short timescales, is that the C:N of the
DOM may be reduced back to near Redfield stoichiometry (e.g., Kepkay et al. 1997;
Koeve 2005).
In contrast to DOC results, nutrient additions seemed to have an affect on DON
cycling, but in the opposite sense in two of the experiments. In April, nutrient additions
stimulated DON production. The C:N of the excess DOM was ~ 13, which favored the
uptake of NH4+ (Goldman et al. 1987) and accumulation of DON, likely as bacterial
biomass. In contrast, some DON degradation was observed in the nutrient amended
incubations in August where the C:N of the excess DOM was slightly lower (~11.5).
80
These results suggest that there may be some degree of temporal variability in DON
cycling, which may be related to nutrient supplies to bacteria and/or the chemical nature
of the DOM compounds that are present.
As mentioned previously, it is estimated that a minimum average of 35 and 22 % of
the excess DOC would remain intact after 14 d and 30 d respectively. This may have
extremely important consequences for in situ net ecosystem metabolism in shelf waters
and perhaps more importantly, adjacent oligotrophic waters. Coastal upwelling regions
have been suspected to be sites of net DOC production (Hansell and Carlson 1998), and
recent work by Alvarez-Salgado et al. (2001a) showed that on the order of 20 % of net
primary production in the Iberian upwelling system was present as DOC. AlvarezSalgado et al. (2001a) further argued that depending on the lability of the DOM, the
magnitude of DOM exported to oligotrophic offshore surface waters from coastal
upwelling systems might be sufficiently large to alter the balance between heterotrophy
and autotrophy. Subsequent studies have been published from the Iberian margin
showing that filaments, which break off from shelf waters and carry shelf water masses
away from the coast, are capable of transporting significant amounts of autochthonous
(and labile) DOM to adjacent oligotrophic waters (Alvarez-Salgado et al. 2001b, Barbosa
2001). Off central and northern Oregon, Barth et al. (2005) have identified several
locations where offshelf transport of shelf surface waters may regularly occur during the
upwelling season, with offshelf movement happening on the order of < 1-4 wks. Thus
given the long degradation times of a portion of the excess DOC and DON (relative to
potential offshelf transport mechanisms), Oregon’s coastal waters may also be a
81
significant source of organic matter to adjacent offshore waters of the North Pacific, as
has been observed in the Iberian system. This phenomenon clearly needs more study in
the field setting.
In addition to DOC degradation, significant quantities of POC were also degraded in
these experiments. After 3 d, 17-49 % (mean = 32.5 ± 16.1 %) of the phytoplanktonderived POC had been degraded. Based on the observed decay rates, it is estimated that a
maximum average of 69 and 88 % of the POC would degrade after 14 d and 30 d
respectively. The rate constants from the two experiments where POC degradation was
linear with time (0.06 and 0.13 d-1) are similar to that from the first rapid phase of
degradation reported by Pett (1989), which was ~0.08 d-1. The maximum estimated
losses of POC in these experiments are likely overestimates, as degradation would have
undoubtedly slowed had the experiments been run for longer durations. Both Biddanda
(1988) and Pett (1989) found that POC (and DOC) degradation proceeds rapidly for
several days and then slows. Only a fraction of the POC that was degraded was
apparently respired, with some of it instead being converted to DOC. Nonetheless, in all
experiments, there was still significant net degradation of the TOC. It is estimated that
58 % and 73 % of the TOC would be degraded after 14 d and 30 d respectively.
In two of three experiments, there was no evidence of significant PON degradation
accompanying the POC degradation, while a small amount of PON was degraded in a
third experiment. This preferential degradation of the C component of POM relative to
the N component again is contrary to various geochemical studies showing that while
POM sinks to bottom waters, N is preferentially remineralized (Lee and Wakeham 1988;
82
Grossart and Ploug 2001). There is some anecdotal evidence from the Oregon upwelling
system that may support this notion of preferential POC degradation, at least over short
timescales. Karp-Boss et al. (2004) found that at a shelf location off central Oregon,
POM in surface waters and coinciding with elevated phytoplankton biomass had a C:N
ranging from ~8-10 (Fig. 11 from Karp-Boss et al. 2004). The C:N of POM in the
underlying bottom boundary layer was much lower, averaging < 6. If the surface POM
pool were to be the ultimate source of the bottom POM, as determined for a site off
northern Oregon, then this would indicate preferential POC degradation. One possible
explanation for this preferential POC degradation would be that phytoplankton cellular
POM was not noticeably affected by bacterial degradation, and instead the POC loss was
due to degradation of transparent exopolymer particle-like material (Koeve 2005), which
contains little N and is often included in the POC component when using glass fiber
filters to collect particulate organic material (Passow 2002; Wetz and Wheeler in review).
This would have to be coupled with limited micro- or macrozooplankton grazing on the
senescent phytoplankton, as grazing results in liberation of both DOC and DON (+ NH4+)
from the breakdown of POM. Only in the September experiment did small increases in
DON and NH4+ occur concomitantly with the limited PON degradation.
The fate of POM is much different than that of DOM in coastal upwelling systems.
Whereas DOM is subject to advection, most of the POM derived from diatom blooms
sinks or is mixed to bottom waters via downwelling, sometimes in as little as a few days
(e.g., Karp-Boss et al. 2005). As demonstrated here, a portion of this POM decays
rapidly and would contribute to oxygen utilization in bottom waters. Off Oregon in 2002,
83
severe hypoxic conditions persisted in shelf bottom waters over a several month period
during the summer. Grantham et al. (2004) attributed this to anomalous inputs of low
oxygen water onto the shelf, possibly exacerbated by input of organic matter from the
water column. The 2002 hypoxia developed coincident with a prolonged (several month)
period of generally upwelling favorable winds (Fig. 2a from Grantham et al. 2004),
which according to Hales et al. (2006) may prevent the predominant offshelf transport of
POM through the bottom boundary layer. Hence, it may be that the almost continuous
upwelling spurred surface organic matter production that was continuously deposited in
bottom waters and then degraded. Under normal conditions where frequent wind
relaxations/reversals are interspersed between upwelling events, the less labile fraction
would be transported offshelf (e.g., Hales et al. 2006). This interplay between physical
forcing (i.e., winds) and organic matter retention and degradation may in itself be a novel
aspect of the 2002 hypoxia event that requires further study. Additionally, water that is
upwelled onto the Oregon shelf in normal years is still typically near hypoxic (1.8-3.6 ml
L-1, reported in Grantham et al. 2004). This, combined with the potential for rapid (days)
transport of phytoplankton POM to the bottom off Oregon (Karp-Boss et al. 2004) and
the significant POM degradation that occurs over a few days, suggests that the 2002
hypoxia event was novel in the sense of its duration, but that shelf hypoxia may be more
common than previously thought and is difficult to detect with typical sampling
frequencies of a few cruises per season.
CONCLUSIONS
84
This study demonstrates that while some phytoplankton-derived DOM and POM is
labile and rapidly degraded, a significant portion may not be easily degraded, even with
additions of nutrients. Combined with the results from previous studies, it seems likely
that the less labile fraction of DOM escapes degradation for periods longer than the
timescales of water mass residence times on continental margins and thus may be
exported off the shelf. The portion of POM that is labile likely contributes to respiration
signals in shelf bottom waters, while the less easily degraded fraction may be transported
off the shelf through the bottom boundary layer. Selective C degradation (relative to N)
was observed and is a phenomenon that requires further study in the context of field
observations of C and N export. Also needed are laboratory or field studies to determine
what specific compounds are more or less easily degraded over relevant timescales.
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89
Table 4.1. Experimental treatments used to test whether nutrients and/or grazing control
bacterial abundance/biomass.
Treatment
< 0.8 µm + Nutrients
< 0.8 µm
< 3 µm + Nutrients
< 3 µm
Whole
Description
0.8 µm filtered water w/ ammonium
and phosphate additions
0.8 µm filtered water
3.0 µm filtered water w/ ammonium
and phosphate additions
3.0 µm filtered water
Whole water (unamended)
90
Table 4.2. Initial concentrations of dissolved inorganic nitrogen, dissolved inorganic
phosphorous, organic carbon (µmol L-1; top number on each date- mean DOC in five
treatments, bottom number on each date- mean POC in whole water treatment), organic
nitrogen (µmol L-1; top number on each date- mean DON in five treatments, bottom
number on each date- mean PON in whole water treatment), and the C:N (mol:mol) of
the DOM (top number on each date) or POM (bottom number on each date).
Experiment
April
August
September
Treatment
< 0.8 + Nuts
< 0.8
< 3 + Nuts
<3
Whole
[DIN]
17.7
0.3
14.6
0.3
0.4
[DIP]
3.2
0.1
2.8
0.1
0.8
[OC] (SE)
155.3 (11.7)
[ON] (SE)
12.0 (0.8)
OM C:N (SE)
13.1 (0.9)
324.5
26.3
12.3
< 0.8 + Nuts
< 0.8
< 3 + Nuts
<3
Whole
13.5
0.2
11.3
0.4
0.2
4.3
0.3
4.4
0.3
0.4
104.5 (11.3)
10.0 (1.8)
11.5 (1.6)
246.9
24.5
10.1
67.1 (9.6)
9.9 (0.7)
6.9 (1.2)
108.5
15.8
6.9
< 0.8 + Nuts
< 0.8
< 3 + Nuts
<3
Whole
0.3
14.5
0.3
0.9
0.2
4.9
0.2
0.2
91
Table 4.3. Decay constants and the percentage of POC and TOC that would be degraded
at select time points. klinear is the decay constant where decay was linear over time, and k1
and k2 are the initial and secondary decay constants where decay was initially rapid
followed by slower rates.
0.06
% degraded7d
56.6
34.0
% degraded14d
67.2
56.5
% degraded30d
82.7
83.2
POC
TOC
0.06
0.13
35.3
59.4
58.2
83.5
84.6
97.9
POC
TOC
0.13
58.6
31.3
82.9
33.7
97.7
38.8
OC pool
POC
TOC
klinear
August
September
Experiment
April
k1
0.68
0.35
k2
0.04
0.01
92
0
A
-10
-20
-30
-40
< 0.8 + nuts
< 0.8
< 3 + nuts
<3
-50
-60
-1
DOC change (µmol L )
0
0
1
2
3
4
B
-10
-20
-30
-40
-50
-60
0
1
2
3
0
4
C
-10
-20
-30
-40
-50
-60
0
1
2
Day
3
4
Figure 4.1. DOC change in (A) April, (B) August, and (C) September.
93
75
< 0.8 + nuts
< 0.8
< 3 + nuts
<3
60
A
45
30
15
0
% DOCexcess degraded
75
B
60
45
30
15
0
75
C
60
45
30
15
0
0
1
2
3
4
Day
Figure 4.2. Percentage of excess DOC degraded in (A) April, (B) August, and (C)
September.
94
9
< 0.8 + nuts
< 0.8
< 3 + nuts
<3
6
3
A
0
0
0.5
1
1.5
2
2.5
3
3.5
4
-3
-6
-9
-1
DIN change (µmol L )
9
B
6
3
0
-3
0
1
2
3
4
-6
-9
9
C
6
3
0
-3
-6
-9
0
1
2
3
4
Day
Figure 4.3. DIN change in (A) April, (B) August, and (C) September.
95
9
A
6
3
0
0
-3
-6
1
< 0.8 + nuts
< 0.8
< 3 + nuts
<3
2
3
4
-9
-1
DON change (µmol L )
9
B
6
3
0
-3
-6
-9
0
1
2
3
4
9
C
6
3
0
-3
-6
-9
0
1
2
3
4
Day
Figure 4.4. DON change in (A) April, (B) August, and (C) September.
Organic C change (µmol L-1)
96
50
A
0
-50
-100
Apr POC
Apr TOCex
Aug POC
Aug TOCex
Sep POC
Sep TOCex
-150
-200
-250
60
0
0.5
1
1.5
2
2.5
3
% OC degraded
4
B
50
40
30
20
10
0
Organic N change (µmol L-1)
3.5
0
5
4
3
2
1
0
-1
-2
-3
-4
-5
1
Apr PON
Sep PON
Aug DON
0
1
2
3
Aug PON
Apr DON
Sep DON
2
4
C
3
4
Day
Figure 4.5. (A) Change in POC and excess TOC, (B) percentage of POC and excess
TOC degraded, and (C) change in PON and DON in April, August, and September.
97
Chapter 5. Conclusions
In this dissertation, results are presented from several experiments that were designed
to answer key questions about diatom-derived organic matter cycling in coastal systems.
Some of the most important findings are: 1) DOC release rates vary between diatom
species and is significantly higher in exponential versus stationary growth, 2) the DOM
produced by some diatom species adheres to filters and is measured as POM when cells
are separated from the medium by fractionation, 3) nanoflagellate grazing is an important
control on coastal bacterioplankton biomass, and 4) POC and DOC degradation
proceeded rapidly, with ~ 33-50 % degrading after 3 d, but DOC degradation slows and a
less labile fraction may accumulate if retained in coastal waters. It is important to keep in
mind that these studies were limited to enclosures and as always, the difficulty is
translating the results into field dynamics. As I will argue in the following paragraphs,
indeed the next step is to study and quantify these processes in the field. This caveat
should not downplay the significance of the findings however, as organic matter
production and degradation is fiercely difficult to study in situ and will require truly
interdisciplinary collaboration to advance our understanding.
It appears that as a percentage of the total amount of C fixed, DOC release varies little
with growth stage. However, the absolute DOC release rates were much higher in
nutrient replete versus nutrient deplete conditions, reflective of the overall photosynthetic
capacity of the cells. Because these measurements were made under constant light levels,
future efforts should be directed to incorporate conditions of fluctuating light, to which
cells would be exposed in situ (i.e., from vertical movement, clouds, etc.). Studies of in
98
situ DOC production often involve incubating phytoplankton samples at multiple fixed
depths (light levels) and have provided useful information on DOC release rates at high
versus low light. Nonetheless, there are essentially no studies that have attempted to
quantify this process under truly natural (fluctuating) light conditions. Furthermore,
relatively little is known about the effects of variable light either on the photosynthetic
physiology of phytoplankton or on DOC production. Based on the C:N of the diatom
DOM and POM produced in nutrient replete versus depleted conditions, it seems that the
quality of the organic matter produced by some species varies with growth stage,
favoring C-rich compounds in nutrient depleted conditions. While this in itself is not
necessarily novel, the C-rich DOM in some cases was largely measured as POM using
standard filtration techniques (i.e., GF/F filters). Hence, these results suggest that
depending on the composition of the phytoplankton community, interpretation of POM
and DOM measurements made during blooms may be fatally compromised by DOM
retention on the filters. To the best of my knowledge, this phenomenon has received
surprisingly little attention in the literature and this study is the first comprehensive study
of species-specific differences in DOM production. In addition to the necessity for
studying DOM release under natural light conditions, the results from this study highlight
two other critical areas requiring further study. First, much more work is needed to
characterize the chemical composition of DOM produced by diatoms under different
growth conditions. In my opinion, most of the advances in this area have come from
benthic ecologists studying polysaccharide production by benthic diatoms, and relatively
little work has been devoted to pelagic diatoms. Second, and not unrelated, is that studies
99
are urgently needed to determine of field POM and DOM measurements are biased by
species-specific differences in the quality of organic matter produced. This problem will
likely be more pronounced in coastal systems, where dense blooms of temporally and
spatially varying species compositions occur, and if this phenomenon is real, it would
raise serious questions about how we interpret data from these types of measurements.
What happens to the diatom-derived organic matter during bloom senescence? To
begin to address this, it is important to understand what is happening at the level of the
main decomposers, the bacteria. In two of my experiments, bacterial growth and
mortality were nearly balanced, and in only one did bacterial mortality actually exceed
growth. Furthermore, in one experiment, bacterial biomass accumulation was only
stimulated in reduced grazing treatments where extra nutrients were added, indicating
that in the unaltered incubations, the bacteria may have been reliant on nutrients excreted
by their grazers. In the other two experiments, bacteria were apparently able to use DON.
Thus, there may be some degree of temporal (and spatial?) variability in environmental
controls on coastal bacterioplankton. However, it is unclear what the ecological
consequences of this variability may be. In general, it does not look like there was a clear
effect of either grazing or nutrient supplies on DOM degradation. Based on these results
and those of previous studies, it seems that the chemical composition of the DOM must
determine, to a degree, how fast it is degraded. These experiments captured degradation
of a significant amount of labile DOM, but also show that there is another portion that
degrades more slowly. As mentioned previously, I feel that significant efforts need to be
devoted to characterizing the diatom- derived DOM in order to better understand the
100
production and cycling of different compounds. More generally, efforts need to be
devoted to study DOM and POM cycling in situ in a net sense (i.e., by constructing C and
N budgets in the context of physical dynamics; e.g., Hales et al. 2006). This will require
significant interdisciplinary collaboration, as well as the ability to make high spatialtemporal resolution measurements of both DOM and POM. I have highlighted two
potentially important aspects of DOM and POM production and cycling off Oregon,
including offshelf advective export of the slower degrading fraction of the DOM to
oligotrophic waters, and POM degradation in shallow coastal waters and its role in
hypoxia dynamics. These processes may have significant implications for global ocean
biogeochemistry and coastal ecosystem functioning, but have received relatively little
attention to date and now need to be addressed in field studies.
101
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110
APPENDICES
111
Appendix A: Data from bulk DOM release studies
The following data are from the three bulk diatom DOM release experiments. Blanks
in the tables indicate that the data point was not available due to analytical error.
112
Chaetoceros decipiens
Abundance
Day
0
1
2
3
4
5
6
7
8
9
10
Replicate
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
6
-1
(x 10 cells L )
0.02
0.02
0.03
0.03
0.09
0.08
0.20
0.19
Avg. Biovol.
3
-1
(µm cell )
6926
5776
6630
7038
5674
6038
8276
6864
1.48
1.41
9597
9352
8328
8889
7916
3.23
4.36
6978
7780
12.7
12.8
13.6
18.0
17.3
13.3
17.0
17.4
15.1
17.5
17.6
16.9
16.0
15.9
13.6
6690
8468
4066
4435
3806
3254
1974
2919
3408
3467
2594
3724
3341
2322
Avg. Surface Area
(µm2 cell-1)
2449
2098
2409
2463
2161
2269
2650
2458
3179
2973
2916
2737
2844
2719
2192
2383
2621
1727
2358
2725
1721
1938
1908
1766
1685
1239
1511
1636
1692
1499
1804
1695
1502
113
Chaetoceros decipiens
Day
0
1
2
3
4
5
6
7
8
9
10
Replicate
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
TN (µM) DIN (µM) PON (µM) DON (µM) TOC (µM) POC (µM) DOC (µM)
71.30
51.64
0.38
19.28
193.45
4.65
188.80
72.10
50.28
0.33
21.49
182.80
2.96
179.84
69.52
48.39
179.27
5.71
173.56
72.90
51.71
0.50
20.68
188.89
5.33
183.56
72.10
48.06
0.46
23.57
183.94
4.79
179.15
69.52
49.66
185.55
70.41
50.82
0.96
18.63
196.45
9.14
187.31
72.10
50.88
0.93
20.28
184.47
8.91
175.56
70.41
45.32
214.13
70.59
2.54
200.81
20.45
180.36
70.50
45.39
2.71
22.40
193.77
20.68
173.09
70.32
49.36
70.59
44.07
6.77
19.75
231.78
52.07
179.70
71.83
44.23
7.60
20.00
233.25
60.06
173.19
68.46
69.79
31.89
13.27
24.63
302.59
103.25
199.35
70.06
29.36
19.31
21.38
326.41
145.29
181.11
67.13
68.90
10.17
34.54
24.19
469.66
267.16
202.50
67.84
7.44
37.65
22.75
470.68
292.93
177.75
67.75
38.13
68.64
0.03
42.74
25.87
581.16
366.21
214.94
68.64
0.03
41.80
26.80
621.30
401.58
219.72
67.66
0.05
36.86
440.56
67.84
0.03
38.99
28.82
673.68
411.83
261.85
70.32
0.00
40.39
29.93
717.99
470.50
247.48
67.57
0.12
33.94
33.51
761.69
450.53
311.17
70.94
0.10
36.13
34.71
749.36
447.05
302.32
68.46
0.05
38.00
30.41
787.78
498.65
289.12
67.93
0.14
32.33
35.46
810.14
456.67
353.48
67.66
0.09
32.36
35.21
788.75
428.56
360.18
68.37
0.14
34.61
33.63
797.06
487.88
309.18
67.39
0.10
34.00
33.30
780.63
456.05
324.58
114
Cylindrotheca closterium
Abundance
Day
0
1
2
3
4
5
6
7
8
9
10
11
12
Replicate
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
6
-1
(x 10 cells L )
0.00
0.00
0.01
0.01
0.02
0.03
0.11
0.10
0.26
0.54
0.89
1.81
1.79
9.98
9.79
20.5
22.8
60.0
66.9
70.5
88.1
87.0
81.1
76.5
76.6
79.0
75.6
77.8
71.6
79.4
71.5
70.4
Avg. Biovol.
3
-1
(µm cell )
195
201
192
205
222
249
232
250
261
257
284
290
304
302
297
306
343
301
320
311
304
288
293
287
146
141
138
125
143
148
143
131
126
136
Avg. Surface Area
(µm2 cell-1)
292
286
274
320
286
299
316
306
329
319
321
318
336
340
356
350
344
354
372
350
363
358
355
349
348
348
300
253
251
280
252
246
251
223
253
254
245
243
243
115
Cylindrotheca closterium
-1
Day Rep. TN (µM) DIN (µM) PON (µM) DON (µM) TOC (µM) POC (µM) DOC (µM)
0
a
67.89
49.97
0.39
17.53
183.82
5.75
178.07
b
70.28
52.94
0.35
16.99
177.43
5.73
171.70
c
67.12
51.45
0.37
15.31
178.53
7.63
170.90
1
a
67.63
50.44
0.38
16.81
178.65
6.87
171.77
b
67.38
52.32
0.38
14.68
178.11
5.34
172.77
c
67.12
51.86
0.35
14.91
171.42
5.62
165.81
2
a
68.91
50.83
0.38
17.69
170.91
6.16
164.75
b
69.85
52.25
0.38
17.23
172.56
6.64
165.92
c
67.98
50.05
0.38
17.54
168.43
5.96
162.47
3
a
70.19
50.32
0.37
19.50
193.97
5.75
188.22
b
68.83
51.31
0.50
17.01
170.83
7.42
163.41
c
68.40
50.82
0.38
17.20
176.04
5.90
170.14
4
a
67.38
47.02
0.70
19.66
172.84
7.44
165.41
b
71.38
51.03
0.78
19.57
171.28
8.94
162.34
c
70.53
46.22
0.94
23.37
170.74
9.34
161.40
5
a
67.21
46.96
1.56
18.69
177.28
13.17
164.11
b
68.83
48.73
1.71
18.39
177.84
13.70
164.14
c
64.91
46.44
2.24
181.06
16.61
164.45
6
a
64.48
36.68
7.54
20.26
204.45
48.49
155.96
b
67.98
35.54
7.36
25.08
195.19
48.58
146.61
c
64.57
30.35
223.73
7
a
59.29
19.86
16.35
23.08
237.74
116.12
121.63
b
70.70
20.85
16.05
33.80
241.08
115.56
125.53
c
61.33
8
a
59.71
0.99
31.78
26.95
414.06
318.37
95.68
b
62.01
1.29
33.44
27.29
406.76
342.74
64.02
c
63.38
1.18
9
a
65.42
1.07
31.83
32.52
634.05
512.98
121.07
b
67.98
0.52
39.33
28.13
654.72
619.72
35.00
c
64.48
0.75
35.75
27.97
648.19
603.56
44.63
10
a
64.57
1.18
29.24
34.16
733.23
590.76
142.46
b
66.36
1.16
35.70
29.50
787.08
703.90
83.18
c
59.20
1.28
33.56
24.36
717.62
670.11
47.51
11
a
71.89
1.15
36.91
33.84
809.07
832.34
-23.27
b
66.95
1.18
35.47
30.31
761.27
762.99
-1.72
c
66.27
0.73
37.89
27.66
737.50
814.47
-76.98
12
a
67.38
0.72
27.16
39.50
803.91
771.08
32.83
b
64.57
0.72
39.74
24.12
784.55
910.63
-126.08
c
67.81
0.51
38.93
28.36
804.37
854.97
-50.60
TEP (µg L
XG equiv.)
1598.98
1122.79
1757.71
2392.63
170.41
1837.07
567.23
1281.52
805.33
1519.61
170.41
1678.34
646.60
725.96
1757.71
2075.17
1519.61
1995.80
1360.88
2789.46
2472.00
2154.54
3265.65
5261.45
2563.04
5737.64
6055.10
3197.96
12880.50
15261.45
13515.42
14785.26
11610.66
10975.74
116
Bellerochea sp.
Abundance
Day
0
1
2
3
4
5
6
7
8
9
10
11
12
13
Replicate
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
6
-1
Avg. Biovol.
3
-1
Avg. Surface Area
2
-1
(x 10 cells L )
(µm cell )
(µm cell )
0.01
0.01
0.04
72.4
77.8
74.0
63.2
82.4
68.9
77.6
62.7
78.9
70.0
60.3
134.3
145.0
139.5
130.4
144.2
131.7
133.1
116.0
139.8
130.8
118.2
145.3
99.5
87.2
104.4
122.2
109.4
86.6
106.9
103.7
98.5
104.2
96.9
112.0
103.2
124.0
73.3
92.4
104.4
105.2
117.5
98.4
75.2
96.0
89.3
91.0
81.3
94.7
87.6
151.9
80.1
0.04
0.06
0.05
0.10
0.08
0.08
0.19
0.18
12.3
15.7
33.3
50.1
43.1
57.9
65.4
59.7
41.9
54.0
54.8
49.7
58.3
49.4
58.2
50.8
72.0
35.6
46.3
57.5
57.6
65.5
50.2
36.8
46.5
45.0
45.9
42.2
45.5
48.9
22.9
37.5
0.46
0.32
0.97
0.80
1.55
1.38
3.36
2.56
2.53
3.59
3.03
3.25
5.22
5.32
10.6
7.18
10.0
117
Bellerochea sp.
Abundance
Day
14
15
16
17
18
19
Replicate
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
6
-1
Avg. Biovol.
123
155
(µm2 cell-1)
92.8
77.8
76.8
103.4
94.1
87.4
110.5
102.0
110.0
93.4
100.7
94.9
110.3
114.8
111.2
149
126
49.3
51.7
96.7
100.7
69.3
59.8
108
96.2
-1
Avg. Surface Area
(µm cell )
46.0
38.2
36.8
48.3
45.7
43.9
69.1
56.6
58.6
52.7
55.3
52.7
57.2
66.2
66.2
(x 10 cells L )
47.1
37.8
33.0
63.1
44.7
46.3
3
118
Bellerochea sp.
Day
0
1
2
3
4
5
6
7
8
9
10
11
12
13
Replicate
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
TN (µM) DIN (µM) PON (µM) DON (µM) TOC (µM) POC (µM) DOC (µM)
48.91
38.15
0.32
10.44
3.86
52.73
39.34
0.55
12.84
108.81
5.62
103.18
53.51
40.80
0.33
12.38
109.11
5.00
104.11
54.36
39.17
0.48
14.71
115.03
5.17
109.87
56.56
40.89
0.53
15.14
107.53
4.63
102.89
52.45
40.68
0.37
11.40
114.63
4.66
109.97
52.31
39.75
0.59
11.97
120.56
5.12
115.43
52.38
40.72
0.58
11.07
122.01
5.61
116.39
52.17
40.72
0.40
11.05
112.16
4.54
107.62
51.46
38.99
0.71
11.76
107.93
4.70
103.23
52.95
40.89
0.63
11.42
108.54
4.88
103.66
53.65
40.81
0.55
12.30
107.13
4.16
102.97
52.17
38.82
0.74
12.60
109.48
5.52
103.96
57.27
40.77
0.61
15.89
101.47
5.44
96.03
53.80
40.30
0.48
13.01
99.82
5.58
94.24
52.31
38.60
0.97
12.74
104.03
6.52
97.51
52.87
40.52
0.56
11.80
104.04
5.11
98.94
52.31
40.52
0.74
11.05
107.72
5.11
102.61
52.24
39.49
1.11
11.64
103.44
8.43
95.01
53.80
40.59
0.74
12.47
107.17
5.40
101.77
53.30
40.51
0.75
12.04
105.55
6.78
98.77
50.32
38.49
1.25
10.58
119.27
9.43
109.83
53.09
40.48
1.00
11.62
113.16
8.75
104.42
53.72
40.22
0.98
12.53
112.32
7.87
104.44
51.53
38.71
1.97
10.84
112.23
12.71
99.52
55.07
39.19
1.97
13.91
10.48
164.80
53.72
40.14
114.99
12.59
102.40
51.17
37.02
2.03
12.12
115.44
97.93
54.43
39.42
2.25
12.76
114.66
11.13
103.53
55.00
39.69
2.08
13.22
113.63
10.62
103.01
50.40
2.25
120.23
98.43
54.86
39.54
2.42
12.90
118.92
15.08
103.84
55.21
39.32
1.98
13.91
15.19
269.99
49.47
36.43
3.84
9.21
129.07
99.39
51.53
38.67
3.62
9.24
104.73
20.68
84.05
52.17
38.72
3.24
10.21
101.80
22.79
79.01
55.78
35.35
3.56
16.86
114.95
30.57
84.38
55.07
37.76
3.02
14.29
105.29
30.22
75.07
52.95
37.14
4.11
11.69
109.88
30.71
79.17
50.32
32.74
119.71
71.99
56.49
36.12
4.99
15.38
114.14
40.66
73.48
55.99
35.90
4.49
15.60
117.79
39.25
78.54
119
Bellerochea sp.
Day
Replicate
14
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
15
16
17
18
19
TN (µM) DIN (µM) PON (µM) DON (µM) TOC (µM) POC (µM) DOC (µM)
53.09
53.09
55.07
52.31
51.03
52.31
50.11
49.40
49.40
45.22
46.43
52.24
51.17
29.37
32.83
32.84
5.40
6.31
14.86
15.92
28.57
29.25
8.35
9.76
14.11
13.29
153.41
132.96
133.97
172.05
141.63
152.52
21.90
23.04
13.16
14.34
14.35
12.02
169.88
176.80
109.10
115.27
13.10
14.72
18.25
22.27
15.08
15.25
184.01
192.62
151.82
168.69
51.46
4.50
5.42
22.95
29.62
16.41
217.32
243.92
205.19
246.48
68.72
78.32
75.98
59.53
66.71
68.49
52.53
60.79
61.53
20.90
32.18
23.94
24.13
12.13
-2.56
39.42
45.08
0.14
0.11
26.72
34.92
12.56
10.05
236.76
256.56
273.31
315.32
-36.55
-58.76
54.64
57.99
74.92
84.03
120
Appendix B: Data from 14C DOM release and POM production experiments
The following data are from the five diatom 14C DOM release and POM production
experiments. Blanks in the tables indicate that the data point was not available due to
analytical error.
121
Growth Stage
Exponential
Transition
Stationary
Exponential
Transition
Stationary
Exponential
Transition
Stationary
Bellerochea
27.9
85.4
95.8
Abundance (x 106 cells L-1)
Chaetoceros
Cylindrotheca
Odontella
1.28
5.50
0.79
10.3
83.7
3.44
8.25
80.0
3.07
Skeletonema
17.8
63.2
53.6
Bellerochea
79.2
64.1
52.5
Avg. Biovol. (µm3 cell-1)
Chaetoceros
Cylindrotheca
Odontella
1752.1
186.1
18094.1
3465.9
149.5
21144.9
4944.2
125.4
23899.4
Skeletonema
299.8
429.7
391.6
Bellerochea
63.1
156.0
210.0
Chaetoceros
8.8
140.6
347.7
Cell C (µM)
Cylindrotheca
16.1
196.4
422.1
Odontella
53.5
265.6
261.5
Skeletonema
43.5
206.9
162.9
122
Bellerochea sp.
Growth Stage Replicate
Exponential
Transition
Stationary
a
b
c
a
b
c
a
b
c
POC (x 106 pmol C hr-1)
Day
Night
24 hr
2.24
2.58
2.29
7.19
5.64
5.67
3.51
3.92
3.71
-0.04
-0.82
-0.42
-0.49
-0.49
0.42
-0.95
-1.62
-0.30
1.27
1.13
1.13
3.92
3.04
3.44
1.61
1.56
2.01
DOC (x 106 pmol C hr-1)
Day
Night
24 hr
0.01
0.02
0.01
0.06
0.06
0.05
0.02
0.01
0.01
0.09
0.03
0.03
0.09
0.03
0.04
0.01
0.02
0.01
0.05
0.02
0.02
0.07
0.05
0.05
0.01
0.02
0.01
Chaetoceros decipiens
Growth Stage Replicate
Exponential
a
b
c
Transition
a
b
c
Stationary
a
b
c
POC (x 106 pmol C hr-1)
Day
Night
24 hr
0.20
-0.04
0.09
0.23
0.20
-0.04
0.10
4.97
1.00
3.27
5.22
2.24
3.94
6.68
-1.46
3.19
1.38
-0.34
0.65
1.22
-0.15
0.64
1.03
0.09
0.63
DOC (x 106 pmol C hr-1)
Day
Night
24 hr
0.07
-0.02
0.03
0.05
0.00
0.03
0.04
0.03
0.04
0.83
0.20
0.56
0.88
0.58
0.75
1.00
0.32
0.71
0.21
0.12
0.17
0.20
0.20
0.20
0.27
-0.02
0.15
Cylindrotheca closterium
Growth Stage Replicate
Exponential
a
b
c
Transition
a
b
c
Stationary
a
b
c
POC (x 106 pmol C hr-1)
Day
Night
24 hr
0.76
-0.34
0.28
0.76
0.04
0.45
0.96
-0.47
0.34
11.04
6.52
9.12
11.33
5.77
8.96
11.61
5.99
9.22
6.57
0.43
3.91
5.94
0.57
3.62
4.83
1.64
3.44
DOC (x 106 pmol C hr-1)
Day
Night
24 hr
0.04
0.02
0.03
0.04
0.03
0.04
0.04
0.01
0.03
0.44
0.47
0.45
0.63
0.19
0.44
0.42
0.36
0.39
0.29
0.38
0.33
0.32
0.23
0.28
0.30
0.20
0.26
123
Odontella longicruris
Growth Stage Replicate
Exponential
a
b
c
Transition
a
b
c
Stationary
a
b
c
POC (x 106 pmol C hr-1)
Day
Night
24 hr
5.07
2.73
4.06
7.26
-2.68
2.97
6.35
-0.88
3.23
6.60
-1.51
3.04
4.97
17.08
10.29
1.75
1.83
1.83
1.10
-0.22
1.20
1.48
0.95
1.56
DOC (x 106 pmol C hr-1)
Day
Night
24 hr
0.33
0.22
0.28
0.40
0.08
0.26
0.36
0.09
0.25
0.28
0.02
0.17
0.26
0.36
0.31
0.02
0.03
0.03
0.02
0.02
0.01
0.02
0.02
0.02
Skeletonema sp.
Growth Stage Replicate
Exponential
a
b
c
Transition
a
b
c
Stationary
a
b
c
POC (x 106 pmol C hr-1)
Day
Night
24 hr
7.14
3.24
5.49
8.86
2.60
6.22
10.45
-3.45
4.58
9.94
2.64
6.86
12.07
-2.95
5.73
2.17
2.18
3.12
0.19
-0.02
-1.27
1.33
1.24
1.25
DOC (x 106 pmol C hr-1)
Day
Night
24 hr
0.13
0.14
0.14
0.13
0.17
0.15
0.15
0.12
0.14
0.74
0.83
0.78
0.75
0.49
0.64
0.09
0.10
0.12
0.04
0.04
0.00
0.07
0.07
0.07
124
Appendix C: Data from POM and DOM degradation experiments.
The following data are from the three organic matter degradation experiments. Blanks
in the tables indicate that the data point was not available due to analytical error.
125
Whole Water
Date
April
Day
0
0.5
1
2
3
August
0
0.5
1
2
3
September
0
0.5
1
2
3
Replicate POC (µM) PON (µM)
a
321.3
26.6
b
327.7
26.1
a
b
a
379.4
26.4
b
300.5
22.3
a
173.1
26.2
b
170.7
25.8
a
155.4
26.1
b
175.0
27.3
a
b
a
b
a
b
a
b
a
b
247.0
246.8
238.0
242.4
233.7
231.4
213.6
222.2
24.0
25.0
24.5
25.1
24.7
24.8
24.1
25.7
204.8
25.0
a
b
a
b
a
b
a
b
a
b
108.1
108.9
98.4
100.6
94.4
93.5
85.4
82.3
75.4
73.3
15.9
15.8
15.3
15.5
15.1
15.5
14.2
13.9
13.2
12.4
126
< 0.8 + Nuts
Date
April
Day
0
0.5
1
2
3
August
0
0.5
1
2
3
September
0
0.5
1
2
3
Replicate
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
a
b
c
<3
Whole
TOC (µM) TOC (µM) TOC (µM) TOC (µM)
167.1
177.2
153.9
163.0
161.7
177.5
150.8
163.1
164.4
175.2
163.8
168.2
153.0
154.5
136.2
143.7
137.7
166.6
141.8
146.3
139.3
165.5
136.4
146.6
145.0
152.3
136.4
148.1
145.6
153.0
142.4
146.7
140.6
157.4
140.1
149.1
148.4
122.0
134.2
140.7
154.1
132.2
132.9
143.7
158.8
126.0
121.2
148.0
117.4
132.5
117.0
143.8
118.7
135.4
120.3
144.4
113.3
137.1
TOC (µM)
439.8
428.5
427.6
133.2
132.4
127.8
128.9
126.9
125.8
85.5
84.9
86.6
71.6
71.5
75.0
71.1
69.9
73.9
< 0.8
< 3 + Nuts
396.7
423.7
420.5
334.3
452.1
387.0
370.9
375.1
369.8
131.6
128.6
131.5
129.5
128.1
132.6
94.5
91.3
90.8
83.5
78.9
86.0
79.3
79.7
77.4
100.1
92.6
92.4
84.5
86.5
89.2
65.6
63.2
62.7
69.1
68.0
73.2
63.9
61.0
59.3
95.7
90.8
99.4
88.2
88.2
91.1
71.2
72.5
74.7
71.9
71.3
72.3
66.2
62.0
63.0
326.3
323.0
311.7
305.1
297.0
300.5
276.4
270.3
268.0
78.7
83.8
76.7
72.9
76.5
83.9
77.9
73.6
75.4
71.0
73.8
72.0
78.5
70.5
76.5
72.1
74.0
74.8
75.6
65.5
75.7
74.2
71.9
76.9
79.3
75.7
151.4
143.3
146.8
129.9
135.1
68.2
66.8
61.1
64.7
65.9
63.0
69.6
67.9
63.5
66.0
64.6
67.2
69.6
64.6
264.9
240.7
230.2
233.2
232.3
115.6
119.9
120.1
115.5
120.6
118.1
119.2
116.3
127
< 0.8 + Nuts
Date
April
Day
0
0.5
1
2
3
August
0
0.5
1
2
3
September
0
0.5
1
2
3
< 0.8 < 3 + Nuts
<3
Whole
Replicate
a
b
a
b
a
b
a
b
a
b
TN (µM)
28.25
27.44
27.84
27.57
27.44
27.98
29.25
29.73
28.18
28.25
TN (µM)
14.39
13.38
14.39
13.72
14.05
14.66
15.40
17.35
14.72
13.92
TN (µM)
23.94
24.75
24.14
24.95
25.76
25.42
25.35
26.09
23.40
26.03
TN (µM)
13.11
13.65
14.39
13.18
15.20
14.46
14.72
14.59
13.38
14.25
TN (µM)
36.25
38.34
a
b
a
b
a
b
a
b
a
b
27.07
29.52
28.23
26.81
26.43
28.94
26.55
25.65
24.81
27.65
12.62
13.20
12.43
14.55
12.30
12.23
13.46
11.65
11.91
13.97
20.68
21.78
20.49
21.07
21.01
23.01
21.20
21.14
19.07
21.65
9.59
8.81
8.55
9.97
9.07
9.52
9.78
8.43
8.23
7.65
28.49
28.94
26.43
27.78
27.46
26.88
26.88
29.59
29.01
28.49
9.38
10.20
8.78
12.06
12.36
11.02
8.04
9.38
7.96
7.89
26.76
25.34
25.12
25.94
25.64
25.79
25.86
26.61
23.85
25.57
8.56
25.27
11.62
8.41
7.66
7.44
7.22
8.78
10.80
9.45
25.04
23.63
22.28
24.22
23.48
24.89
22.95
a
b
a
b
a
b
a
b
a
b
36.78
37.80
37.13
37.45
37.03
37.55
128
< 0.8 + Nuts
Date
April
Day
0
0.5
1
2
3
August
0
0.5
1
2
3
September
0
0.5
1
2
3
Replicate
a
b
a
b
a
b
a
b
a
b
a
b
a
b
a
b
a
b
a
b
a
b
a
b
a
b
a
b
a
b
< 0.8 < 3 + Nuts
<3
Whole
DIN (µM) DIN (µM) DIN (µM) DIN (µM) DIN (µM)
0.29
14.03
0.15
0.45
15.10
0.25
15.22
0.35
0.37
13.26
0.00
10.33
0.01
0.43
15.81
0.00
9.07
0.02
0.74
9.26
0.07
9.22
0.00
0.00
9.27
0.00
11.02
0.00
0.12
9.53
0.00
9.99
0.00
0.00
7.98
0.00
12.02
0.00
0.00
8.30
0.00
7.05
0.00
0.00
8.19
0.07
7.00
0.07
0.00
13.54
13.54
12.47
14.00
14.01
15.21
13.17
16.68
14.77
13.99
0.18
0.18
1.43
0.16
0.13
0.13
0.10
0.10
0.08
0.08
10.31
12.30
10.63
10.71
12.70
13.37
13.31
12.13
18.75
15.32
0.42
0.15
0.39
0.12
0.12
0.26
1.04
0.07
0.72
0.17
0.17
0.15
0.14
0.12
0.12
0.09
0.09
0.19
0.06
0.21
0.30
0.67
0.51
0.86
1.20
1.03
1.20
3.02
0.49
14.48
14.55
13.83
12.61
18.33
15.81
16.53
15.75
15.34
16.33
0.26
0.25
0.68
1.10
0.78
0.95
1.85
1.49
0.91
0.73
0.89
0.83
1.55
1.10
1.78
1.70
0.35
4.96
0.73
4.71
129
< 0.8 + Nuts
Bact. Abund.
Date
April
August
< 3 + Nuts
Bact. Abund.
<3
Bact. Abund.
Whole
Bact. Abund.
Day Replicate (x 106 cells ml-1) (x 106 cells ml-1) (x 106 cells ml-1) (x 106 cells ml-1) (x 106 cells ml-1)
0
a
0.39
0.69
0.53
0.42
b
0.26
0.50
0.53
0.26
1
a
1.20
0.81
2.29
b
1.68
0.83
1.25
0.50
2
a
1.07
0.91
0.65
1.12
1.42
b
1.70
1.01
0.65
1.55
1.06
3
a
1.81
1.04
0.75
0.76
1.19
b
1.38
0.81
0.53
1.00
0
1
2
3
September
< 0.8
Bact. Abund.
0
1
2
3
a
b
a
b
a
b
a
b
a
b
a
b
a
b
a
b
0.29
0.23
2.68
3.41
2.64
1.48
2.84
0.23
2.62
1.81
2.70
2.09
1.78
2.41
1.46
0.76
3.11
2.60
1.35
1.71
2.32
1.94
0.24
0.21
2.73
2.65
0.80
0.10
0.08
0.24
0.20
1.22
1.24
0.52
0.28
0.10
0.06
0.54
0.53
0.39
0.33
0.23
0.24
0.28
0.31
1.98
1.34
1.75
1.45
1.28
1.47
1.25
2.33
1.27
0.93
0.77
0.50
0.53
0.76
2.22
0.90
0.37
0.35
0.45
0.97
0.36
0.46
130
< 0.8 + Nuts
Bact. C
Date
April
Day
0
1
2
3
August
0
1
2
3
September
0
1
2
3
Replicate
a
b
a
b
a
b
a
b
(µM)
1.96
1.18
7.49
6.34
3.13
6.83
7.46
4.52
a
b
a
b
a
b
a
b
1.51
1.22
9.89
15.41
5.46
2.75
7.07
a
b
a
b
a
b
a
b
< 0.8 < 3 + Nuts
Bact. C
Bact. C
(µM)
2.65
1.27
(µM)
4.60
5.82
6.39
5.76
2.97
6.42
3.05
1.70
2.28
1.79
0.85
19.65
9.59
6.38
4.05
5.14
5.62
8.98
3.73
9.83
13.79
5.00
13.62
12.94
9.11
<3
Bact. C
Whole
Bact. C
(µM)
1.30
(µM)
1.28
0.81
1.45
0.78
0.61
15.35
9.74
3.91
0.71
0.68
15.56
14.45
17.88
4.92
2.98
1.84
2.90
4.13
2.56
3.64
6.25
2.51
4.01
9.61
7.97
3.63
5.14
0.77
0.46
4.29
4.64
4.24
1.54
0.61
0.56
4.81
3.37
2.11
2.81
2.16
2.49
1.94
2.80
21.22
16.09
7.31
14.59
13.10
15.58
7.08
11.95
6.39
3.39
4.25
5.64
5.26
1.87
2.70
131
Day
0
1
2
3
0
1
2
3
0
1
2
3
< 0.8 + Nuts
Flag. Abund.
< 0.8
Flag. Abund.
Replicate
a
b
a
b
a
b
a
b
(cells ml-1)
106
0
563
387
111
264
93
194
(cells ml-1)
(cells ml-1)
1795
1278
1179
1186
871
778
2323
1743
(cells ml-1)
1584
1878
1075
1260
945
810
4260
3928
(cells ml-1)
22113
25271
13442
21807
22883
25523
18658
16018
a
b
a
b
a
b
a
b
93
59
148
259
37
93
123
137
106
111
176
229
70
70
88
371
13319
9901
7111
5633
10109
9241
6415
9549
10461
9417
8625
8214
13378
8669
10360
10360
11197
9329
10913
10616
6513
6645
0
0
0
19
27
36
102
115
5205
5457
3536
4003
4828
5712
3964
3880
5331
4952
5279
4332
5527
5820
3655
3621
5721
7217
4221
2832
2992
3170
2226
2200
a
b
a
b
a
b
a
b
< 3 + Nuts
<3
Flag. Abund. Flag. Abund.
Whole
Flag. Abund.
4759