Download Characterizing man-made and natural modifications of microbial

Antonie van Leeuwenhoek 81: 487–507, 2002.
© 2002 Kluwer Academic Publishers. Printed in the Netherlands.
487
Characterizing man-made and natural modifications of microbial
diversity and activity in coastal ecosystems
Hans W. Paerl1,∗ , Julianne Dyble1 , Luke Twomey1 , James L. Pinckney2 , Joshua Nelson3 & Lee
Kerkhof3
1
Institute of Marine Sciences, University of North Carolina at Chapel Hill, 3431 Arendell Street, Morehead City,
NC 28557, USA; 2 Department of Oceanography, Texas A & M University, College Station, TX 77843-3146, USA;
3 Institute of Marine and Coastal Sciences, Rutgers University, New Brunswick, NJ 08901-8521, USA (∗ Author for
correspondence; E-mail: [email protected])
Key words: Bacteria, climate change, eutrophication, microbial consortia, nutrient cycling, phytoplankton,
pollution, water quality
Abstract
The impacts of growing coastal pollution and habitat alteration accompanying human encroachment are of great
concern at the microbial level, where much of the ocean’s primary production and biogeochemical cycling takes
place. Coastal ecosystems are also under the influence of natural perturbations such as major storms and flooding.
Distinguishing the impacts of natural and human stressors is essential for understanding environmentally-induced
change in microbial diversity and function. The objective of this paper is to discuss the applications and merits of
recently developed molecular, ecophysiological and analytical indicators and their utility in examining anthropogenic and climatic impacts on the structure and function of coastal microbial communities. The nitrogen-limited
Neuse River Estuary and Pamlico Sound, North Carolina are used as examples of ecosystems experiencing both
anthropogenic (i.e., accelerating eutrophication) and climatic stress (increasing frequencies of tropical storms and
hurricanes). Additional examples are derived from a coastal monitoring site (LEO) on the Atlantic coast of New
Jersey and Galveston Bay, on the Gulf of Mexico. In order to assess structure, function, and trophic state of these
and other coastal ecosystems, molecular (DNA and RNA-based) characterizations of the microbial taxa involved in
carbon, nitrogen and other nutrient transformations can be combined with diagnostic pigment-based indicators of
primary producer groups. Application of these methods can reveal process-level microbial community responses
to environmental variability over a range of scales. Experimental approaches combined with strategic monitoring
utilizing these methods will facilitate: (a) understanding organismal and community responses to environmental
change, and (b) synthesizing these responses in the context of ecosystem models that integrate physical, chemical
and biotic variability with environmental controls.
Introduction
We have entered a new millennium with the notable
distinction that more than 70% of the world’s human population resides within 100 km of the coast
(Vitousek et al. 1997). Understanding man-induced
ecological change and the subsequent impacts on
biodiversity, coastal water quality, habitat and fisheries
resources are major research and management challenges worldwide. Deterioration of coastal ecosystems
appears to be accelerating, but there is a paucity of
knowledge on how complex aquatic communities are
being altered in structure and function.
To further complicate matters, anthropogenic
stresses are often accompanied by large-scale climatic
perturbations, possibly signaling a period of climatic
change (Gray et al. 1996; Landsea et al. 1998; Goldenberg et al. 2001). During Fall 1999, Hurricanes Dennis, Floyd and Irene inundated the eastern seaboard
of the USA. Coastal North Carolina received up to
1 m of rainfall, causing a 200–500 year flood in the
watershed of the Pamlico Sound, the US’s 2nd largest
estuarine system. Sediment and nutrient-laden floodwaters displaced over 80% of the Sound’s volume,
depressed salinity by 70%, and accounted for half the
annual nitrogen (N) load to this N-sensitive system
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Figure 1. Top frame: SeaWiFS satellite image (23 Sept. 1999) of
brown sediment-laden waters from Hurricane Floyd discharge entering the Pamlico Sound system, coastal North Carolina, USA
(figure from Paerl et al. 2001). The location of the monitoring station from which data for salinity (middle frame) and chlorophyll a
(lower frame) are presented before and after the fall 1999 hurricanes
is shown (x). Middle frame: Salinity (in practical salinity units or
PSU) at 0.5m depth at reference station "x" in the western Pamlico
Sound. Landfall of the 1999 hurricanes is shown by arrows and
the initial letter of each hurricane (D=Dennis, F=Floyd, I=Irene).
Lower frame: Chlorophyll a, an indicator of phytoplankton biomass,
in near surface waters of station “x”. Values are presented as µg
Chlorophyll a per liter.
(Figure 1) (Paerl et al. 2000, 2001). Ecological effects
included hypoxic (<4 mg O2 L−1 ) bottom waters, a 3fold increase in suspended microalgal (phytoplankton)
biomass (Figure 1), altered fish distributions, reduced
catches, and an increase in fish disease. Predicted
elevated hurricane activity may promote long-term
biogeochemical and trophic change in this and other
coastal fisheries nursery habitats. Distinguishing and
integrating the impacts of natural from man-made
stressors is difficult but essential to understanding and
managing coastal biotic resources.
Because bacteria and microalgae have fast growth
rates and dominate marine primary production and
nutrient cycling, they are direct, sensitive indicators
of ecosystem status and change. A change in supply rates of nutrients and other pollutants (i.e., heavy
metals, synthetic organics), sediment loads, hydrology and optical quality of impacted waters frequently
translates into altered microbial community structure
and function (Figure 2). Changes in microbial populations often emerge well before signs appear in larger,
higher ranked consumers. For example, specific algal
taxa, including harmful (toxic, hypoxia-generating)
species are excellent indicators of ecological change
(i.e., eutrophication) in response to perturbations. As
such, microbial indicators of coastal ecosystem health
are useful for coastal process-related research and
management.
Here, we discuss how complex interactive microbial producer, nutrient cycling and consumer assemblages, or consortia, respond and adapt to environmental perturbations. Using microbial indicators as
tools, we will investigate how anthropogenic stressors
interact with natural forcing features to determine
the diversity, distribution, and activities of consortia
in estuarine and coastal ecosystems experiencing increasing nutrient loading and climatic perturbations.
We stress that the case studies presented below are
limited by available background knowledge, advancement, applicability and comprehensiveness of techniques and approaches. However, we are encouraged
by the improved knowledge of ecosystem dynamics
they have thus far provided. Included are the: (1) the
Neuse River Estuary, and downstream Pamlico Sound,
North Carolina, (2) a nearshore mid-Atlantic intensive monitoring location, LEO, located off the coast of
New Jersey, and (3) Galveston Bay, Texas, located on
the northern Gulf of Mexico (Figure 3).
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Figure 2. Conceptual diagram, showing the interactions between nutrient (emphasizing nitrogen, the limiting nutrient in coastal waters) loading,
physical forcing features (i.e., irradiance, mixing and transport), phytoplankton productivity and community structure, bacterial community
composition and activity, and higher trophic level consumers (i.e., grazers, fish). These factors impact and modulate ecosystem responses to
chronic and acute environmental perturbations. The region inside the dashed box indicates ecosystem-level interactions. The lines and arrows
depict major fluxes and directions of nutrient and organic matter transfer in the ecosystem. Specifically, we have demonstrated those interactions
mediating hypoxia (low oxygen conditions), a major and often detrimental ecosystem-level response to nutrient-enhanced primary production,
or eutrophication.
Case study #1 – The Neuse River/Pamlico Sound
System
The Pamlico Sound (PS) and its sub-estuaries form
the US’s largest lagoonal ecosystem and is an important mid-Atlantic and Southeast fisheries nursery
(Figures 1 and 3). The Neuse River Estuary (NRE) is
a key tributary of the PS and is downstream of rapidly
expanding agricultural (hog, poultry and rowcrop operations), urban (Raleigh-Durham-Research Triangle)
and industrial activities in North Carolina coastal watersheds. As is true for most estuarine and coastal
waters, nitrogen (N) is the nutrient controlling primary
production in the NRE and PS (Paerl 1983; Boyer et
al. 1994; Paerl et al. 1995, 1998, 2001). Growing
non-point N discharge associated with agricultural and
urban expansion has led to accelerating primary production, or eutrophication, accompanied by nuisance
algal blooms, hypoxia, toxicity and food web alterations in this system (Copeland & Gray 1991; Paerl
et al. 1995, 1998). The amounts, ratios and modes
(episodic vs. chronic) of nutrient loading play important roles in structuring phytoplankton communities
(Harrington 1999; Pinckney et al. 2001).
Diffuse, non-point sources contribute approximately 80% of externally-supplied, or ‘new’ N to the
system, with wastewater and industrial effluent point
sources contributing the rest. Among ‘new’ N inputs
to the NRE, atmospheric deposition of N (AD-N) from
fossil fuel combustion (NOx ) and agricultural emissions (NH3 ) accounts for approximately 30% (Whitall
& Paerl 2001). Direct AD-N to the estuary surface
contributes additional N. The percent ‘new’ N input attributable to AD-N may be even greater further downstream in the PS, since most land-based N sources are
‘stripped’ during transit through the N-limited estuaries to the Sound. The recent growth of intensive animal
operations in eastern North Carolina (from <1 million
hogs in the late 1980s to >11 million in the late 1990s)
has led to a precipitous rise in N-rich animal waste,
which is stored in open liquid waste lagoons and is applied to land. This form of ‘waste management’ causes
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Figure 3. Locations of the three US coastal case study sites that are discussed. These include the LEO long-term environmental monitoring site
off the Atlantic coast of New Jersey, the Pamlico Sound system in coastal North Carolina, and Galveston Bay, Texas, an estuary on the northern
coast of the Gulf of Mexico.
ammonia volatilization, which is suspected of being
a large local and regional atmospheric N emission
source. A multi-decadal record of AD-N (wet deposition) at a National Acid Deposition Program (NADP)
site in Sampson County, eastern North Carolina (NC
35) reveals a three-fold rise in AD-NH4 relative to
AD-NOx (Paerl and Whitall 1999). AD-N and surface
N runoff have increased in this region. The changing amounts and input ratios of biologically-available
forms of N may affect both phytoplankton and bacterioplankton species compositional responses (Pinckney et al. 2002), which has potential trophodynamic
and biogeochemical ramifications.
Case study #2 – The Long Term Ecosystem
Observatory (LEO-15)
The Mid Atlantic Bight (MAB) National Undersea
Research Center has established a Long-Term Ecosystem Observatory site (LEO-15) on the continental
shelf, off the New Jersey Coast (Figure 3). LEO-15
is centered on a sand ridge in 15 m of water approximately 20 km offshore from the Rutgers University
Marine Field Station. These sand ridges are found
throughout much of the continental shelf of the US
east coast (McBride & Moslow 1991) and include
both sandy and finer grain sediments. Additionally, the
LEO-15 study area is near one of the most pristine
estuarine systems in the northeast US and is part of
an observational network able to provide the realtime data necessary for understanding how oscillations
in the physical environment drive both the chemical
environment and biological activity within the MAB.
The LEO-15 site is very dynamic. Major physical changes include the warming of waters during
the springtime, which is correlated with increased
phytoplankton activity. Phytoplankton biomass levels
remain low throughout fall and winter. During spring
and summer there are episodic phytoplankton blooms
dominated by diatoms. MAB also experiences episodic upwelling events. Off the coast of New Jersey,
southwesterly winds result in the upwelling of offshore bottom waters into well-lit surface layers (Hicks
& Miller 1980). Upwelling is observable in satellite
imagery, and can last for days to weeks, long enough
to result in phytoplankton blooms and subsequent
organic matter accumulation. Additionally, these upwelling events stimulate recurring hypoxia offshore of
many of the estuaries/inlets of NJ (Pearce et al. 1985;
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(Santschi 1995). Although Galveston Bay is one of
the most industrialized estuaries in the Gulf of Mexico, trace metal concentrations in the sediments, water
column, and biota are similar to those in more pristine
bays elsewhere (Morse et al. 1993).
The shallow bay waters are susceptible to rapid
changes in water turbidity caused by the resuspension
of silty sediments following moderate wind events that
blow across the Bay. The increased turbidity reduces
the amount of light available for phytoplankton photosynthesis while simultaneously increasing the nutrient
concentrations in the water column (Warnken 1998).
Figure 4. Diagrammatic representation of the ChemTax approach
for determining the contributions of phytoplankton functional
groups to chlorophyll a-based total phytoplankton biomass. For a
detailed description of this approach, see Mackey et al. (1996).
Glenn et al. 1996), demonstrating the importance of
microbial remineralization.
Case study #3 – Galveston Bay, Gulf of Mexico
Galveston Bay, the second largest estuary in the Gulf
of Mexico, encompasses 1554 km2 of water surrounded by 526 km2 of marshland (Figures 3 and 4). The
bay is shallow (∼2 m) and receives freshwater inputs
from the Trinity (83%) and San Jacinto (8%) Rivers.
These rivers deliver dissolved organic matter (DOM,
5–8 mg C l−1 ) and suspended particulate organic matter (POM, 4–200 mg l−1 ) to the Bay (Benoit et al.
1994; Guo & Santschi 1997). The tidal range in the
bay averages 40 cm, is primarily diurnal, and fosters
the long hydraulic residence time of the estuary (40–
88 days) (Santschi 1995). Winds are more important
than tides for circulation in Galveston Bay.
Phytoplankton dominate primary production in
Galveston Bay. The most common algal functional
groups are diatoms, cyanobacteria, chrysophytes, and
cryptophytes (Sheridan et al. 1988; Örnólfsdóttir et
al. pers. comm.). Dinoflagellates, chlorophytes, and
euglenoids are occasionally abundant, but on an annual basis are minor components in the phytoplankton
community. Seasonal cycling of nutrients in Galveston
Bay has been described in Santschi (1995) and Twilley
et al. (1999). Nutrient inputs from the Trinity River
extend well into Trinity Bay, especially during spring
periods of high river discharge. Nitrate concentrations
are inversely correlated with salinity and benthic regeneration of P leads to a P maximum in late summer
Molecular approaches to monitoring biological
change in aquatic systems
Standard approaches for the identification of biogeochemically- and ecologically-important taxa, such
as selective culture methods, require knowledge of
their ecological niches; such information is not easily
determined. As a consequence, only a small portion
(<1%) of microorganisms from the environment are
believed to be cultivatable using routine techniques
(Head et al. 1997; Suzuki et al. 1997). However, molecular characterization techniques obviate the need
for culture-based analyses. These techniques characterize a mixture of complex biomolecules in order to
discern the members of the microbial commmunity
(both eukaryotic and prokaryotic). For our purposes,
‘molecular approaches’ will be defined as any procedure that tracks a specific cellular constituent which
can differentiate the various ‘players within the microbial community. These biomarkers can include lipids,
proteins, and nucleic acids. Due to space limitations,
not all biomarkers will be considered here. However,
a number of excellent reviews exist for many of the
biogeochemical processes discussed.
Diagnostic photopigments
Microalgal biomass may be estimated by photopigment content. To this end, chlorophyll a (Chl a), which
is common to all microalgae and higher plants, has
been used for many years. It is easily and sensitively measured by spectrophotometry and/or fluorometry. There are, however, substantial differences in
cellular Chl a content among and within microalgal
and higher plant taxa, depending on the interaction of nutrients, light, temperature and seasonality,
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as well as physiology of different species. A limitation of Chl a-based techniques is their inability
to distinguish major microalgal functional groups.
To circumvent this problem, high-performance liquid chromatography (HPLC), coupled to photodiode array spectrophotometry (PDAS), can be used to
characterize and quantify phytoplankton community
composition based on diagnostic photopigments, including diverse chlorophylls, carotenoids and phycobilins. Distinct spectral absorbance characteristics make photopigments useful and sensitive indicators of phytoplankton functional groups (Gieskes
& Kraay 1986; Wright et al. 1991; Millie et al.
1993; Jeffrey et al. 1997). Useful photopigments include Chl b and lutein (chlorophytes), zeaxanthin,
myxoxanthophyll, echinenone (cyanobacteria), fucoxanthin (diatoms), peridinin (dinoflagellates) and alloxanthin (cryptomonads) (Van Heukelem et al. 1994;
Pinckney et al. 1996). Specific phycobilins, including phycoerythrin and phycocyanin, have been used
to characterize cyanobacteria. HPLC-PDAS is now
routinely used by researchers and water quality agencies in diverse aquatic ecosystems. Statistical procedures (ChemTax; Mackey et al. 1996) can be applied
to partition the total pool of Chl a (total community
biomass) into the major algal groups, allowing calculation of the relative and absolute contribution of
each algal group (Mackey et al. 1996; Pinckney et al.
1998, 2000; Figure 4). HPLC measurements of phytoplankton community structure also provide ground
truthing, calibration and verification for aircraft and
satellite-based imagery of distributions in relation to
environmental perturbations.
An example of the utility of HPLC-ChemTax
derived determinations of phytoplankton functional
groups on the community-level is provided for Galveston Bay. Since May 1999, a biweekly sampling
program has been monitoring water quality parameters, including nutrients and phytoplankton dynamics,
in Galveston and Trinity Bays (Pinckney et al. in prep.,
Figure 5). Ten nutrient addition bioassays conducted
during 1999 and 2000 indicated that the phytoplankton
community is consistently N limited. Evidence of P or
Si limitation was not detected. The picoplankton (<
2 µm), nanoplankton (2–20 µm), and microplankton
(20–200 µm) fractions constituted 18, 50 and 32% of
the total community biomass, respectively. All major algal groups are represented in these size ranges,
nanoplankton being most diverse. Diatom blooms of
large species (Rhizosolenia, Coscinodiscus) occurred
during the summer. These successional patterns are
distinguishable and quantifiable by HPLC-ChemTax.
The measurement of growth rates of natural phytoplankton populations in estuaries and coastal waters
is difficult but fundamental to our understanding of
primary productivity and algal bloom dynamics. The
problem has been in determining the contribution of
phytoplankton to the total pool of particulate organic
carbon (POC), a value that is required for calculations of in situ growth rate based on measurements
of photosynthetic rates (Redalje & Laws 1981). Development of the photopigment radiolabeling method
by Redalje & Laws (1981) is a significant step towards the direct determination of specific growth rates
of phytoplankton. The method relies on quantifying
the rate of photopigment synthesis using 14 C incubation techniques. When phytoplankton are exposed to
14 C (as NaH14 CO ), 14 C passes through the Calvin–
3
Benson cycle and into a pool of low molecular weight
compounds used for photopigment synthesis. Under
conditions of balanced growth, the rate of 14 C incorporation into photopigment equals the rate of C incorporation into total cell biomass (i.e., the C-specific
growth rate). The calculation of µ (d−1 ) is based on
∗
ln(1 − 1.05( RI ∗ ))
µ=
t
In this equation, 1.05 is the 14 C isotope discrimination factor, R∗ (disintegrations per minute (dpm)
µg C−1 ) is the C-specific activity of chl a, I∗ (dpm
µg C−1 ) is the C-specific activity of the incubation
water and t (days) is the duration of the incubation
(Redalje 1993). More common methods of growth rate
measurements based on the assimilation index require
accurate determinations of the C:Chl ratio, respiration rates, and grazing rates (Cullen 1990; Cloern
et al. 1995). Quantification of the C:Chl ratio is especially difficult for natural phytoplankton samples
because of problems in measuring POC (Banse 1977;
Cloern et al. 1995; Geider et al. 1997). The photopigment radiolabeling method provides an alternative approach that is insensitive to grazer impacts,
respiration rates, and C:Chl ratios (Redalje 1993).
Detailed descriptions and validation of the photopigment radiolabeling method are provided in Redalje &
Laws (1981), Redalje (1993), Riemann et al. (1993)
and Goericke & Welschmeyer (1993a,b). HPLC combined with photopigment radiolabeling can be used
to determine growth rates of phytoplankton functional
groups in natural mixed assemblages (Goericke &
Welschmeyer 1993a,b; Redalje 1993).
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Figure 5. Spatiotemporal contour plots of the relative abundance of the major phytoplankton groups in Galveston Bay, Texas as determined by
HPLC photopigments data analyzed with ChemTax. The location of the sampling transect is shown by the dashed line on the inset map, with
the mouth of the bay defined as 0 km and the upper end of the transect at 50 km. In 1999 and 2000, Texas experienced a prolonged drought,
with little freshwater input into Galveston Bay. This was followed by a near-record rainfall period (from September 2000 to March 2001).
Cyanobacterial abundance was highest during the drought period and blooms of cryptophytes and diatoms occurred during the wet period.
Galveston Bay also experienced a red-tide bloom (the dinoflagellate Karenia brevis) in September 2000.
Characterization of microbial target genes from
DNA and RNA
Currently, the simplest way to identify bacteria is by
PCR amplification of target genes and traditional cloning and sequencing. This approach is now routinely
used by a number of laboratories for 16S rRNA gene
characterization (Head et al. 1997; Suzuki et al. 1997).
A similar approach using functional genes encoding for enzymes directly involved in transformation
processes has also been employed to study natural
microbial assemblages. Target genes involved in denitrification (nosZ) (Scala & Kerkhof 1998), nitrification (amoA) (Hastings et al. 1998), nitrogen fixation
(nifH) (Kirshstein et al. 1991), sulfur cycling (dsrA)
(Karkhoffschweizer et al. 1995; Wagner et al. 1998),
and methane oxidation (pmoA) (Mcdonald & Murrell
1997) have been successfully utilized to identify microbial populations. Numerous modifications and variations of these molecular techniques have been used
to suit specific needs for identifying and characterizing environmental impacts on microbial community
structure and function.
Assessing phytoplankton community responses to
N loading dynamics
The availability of nitrogen (N) has been identified
as the key factor controlling estuarine and coastal
productivity, trophic state and resultant water quality. Both the total amount and composition of ‘new’
N entering coastal waters are important determinants
of microbial community responses to N enrichment
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(Stolte et al. 1994; Collos 1994; Pinckney et al. 2001).
To determine possible ecological impacts of shifting
amounts and sources of ‘new’ N, we have experimentally determined phytoplankton community responses
to different forms of N under varying irradiance levels.
Bioassays of water samples from the Neuse R. estuary
were amended with equimolar (10 µM) amounts of
N in different forms (ammonium-only, nitrate-only,
urea-only, and combined ammonium, nitrate, and
urea), then either incubated at ambient (100%) irradiance or shaded to 10% of ambient irradiance. HPLCbased diagnostic photopigment analyses (ChemTax)
were used to characterize the relative abundance of
major phytoplankton groups. Results showed that different forms of N caused community shifts at both
100% and 10% of ambient irradiance, reflecting the
range of natural light conditions in the estuary (Harrington 1999; Figure 6).
Additional bioassays were designed to test the effect of varying the supply of dissolved inorganic and
dissolved organic N. Neuse River estuary water was
saturated with potentially growth limiting nutrients
(P, Si, Fe, trace metals and vitamins) and treatments
were designed to assess the effect of adding different N types. The treatments were set-up using the
following combination of nutrients: all nutrients + ammonium, nitrate and urea; all + ammonium; all +
nitrate; all + urea; and all without N. These results confirm previous studies showing that phytoplankton and
their microbial consorts may exhibit species-specific
growth responses to different N concentrations (Stolte
et al. 1994; Collos 1994) and thus community composition is influenced by supply rates of specific dissolved
nitrogen compounds (e.g. NO3 − , NH4 + , dissolved
organic N) (Figure 7). Changes in N:P supply ratios can also affect microbial community structure
and function (Smith 1985, 1990). Inherent physiological differences between taxonomic groups mean that
changes in N and P loading may affect competition
between harmful and non-harmful phytoplankton taxa,
associated microflora and grazers, and higher trophic
levels. For example, if the phytoplankton community
is dominated by species that were not effectively
consumed, then the efficiency of trophic transfer of
the nutrients associated with the phytoplankton biomass would be reduced. Consequently, there would
be potentially less nutrient transfer to higher order
commercially-valuable shellfish and finfish species.
The episodicity, timing, and rates of flushing and
vertical mixing may also impact phytoplankton community responses (Pinckney et al. 1999, 2001). Meso-
Figure 6. Neuse River Estuary phytoplankton functional group responses (using HPLC data processed via ChemTax) to various forms
of nitrogen (ammonium, nitrate and urea) and different light levels,
using in situ bioassays (from Harrington 1999). Nitrogen additions
were equimolar (10 µM N). Identical additions were incubated at
100 and 10% of ambient irradiance and temperature conditions during May 1998. The pie graphs represent the fractions of chlorophyll
a attributable to major phytoplankton functional groups.
cosm bioassays showed that under mixed conditions
there was higher productivity, particulate C:N ratios,
and chlorophyte, diatom, and cyanobacteria biomass.
In contrast, the static (unmixed) mesocosms promoted
higher community growth rates and cryptomonad biomass. Total community biomass (Chl a) was similar
for both treatments. The absence of mixing may enhance sedimentation of non-flagellated species, reducing competitive interactions between cryptomonads
and other species. Adding high nitrate concentrations
to the mixed mesocosms promoted an overall increase
in phytoplankton biomass.
The bacterial taxa involved in N transformations
(i.e. nitrification, denitrification, and nitrogen (N2 ) fixation) are also impacted by natural and man-made perturbations. Nitrification, the oxidation of ammonium
to nitrate, is carried out by gram-negative, oblig-
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Figure 7. Cell counts of the major phytoplankton species from Neuse River Bioassays conducted on 18 June 2001. Bioassays were conducted
using the methods of Twomey & Thompson (2001). During this period, the NRE was potentially N limited (significant difference between
control and treatment with all nutrients, significant difference between all-N and all). There was a major change in the relative proportion of
cells in the ammonium addition treatments versus the treatments in which nitrate, urea or all N types were added.
ate aerobic chemolithotrophs (Voytek & Ward 1995).
Denitrification, the reductive respiration of nitrate or
nitrite to N2 or N2 O, is carried out by a diverse group
of bacteria under anaerobic conditions (Zumft 1997).
N2 fixation, the reduction of N2 gas to ammonia, is
performed solely by prokaryotes under both aerobic
(largely cyanobacteria) and anaerobic (bacteria and
cyanobacteria) conditions. As N inputs are altered,
so are the relative activities and interactions of these
microbial groups.
Activities of populations mediating these N cycling steps are closely linked to carbon and oxygen
availability. Denitrification and N2 fixation occur under hypoxic/anoxic conditions, which are promoted by
organic carbon loading resulting from eutrophication.
Studies on the Baltic Sea, Chesapeake Bay and other
periodically stratified estuarine and coastal waters sus-
ceptible to hypoxia, suggest a feedback interaction
between N enhanced eutrophication, hypoxia and its
controls on N cycling and availability within affected
ecosystems (Boynton et al. 1995) (Figure 8). Increases
in hypoxia resulting from eutrophication may enhance
denitrification, thereby increasing the rate of N loss
(as atmospheric N2 ) from the system (i.e. negative
feedback or net loss of N). This is particularly important when high rates of external N loading (as
NO3 − ) flux over hypoxic bottom waters. However,
hypoxia will also decrease nitrification, because the
volume of oxic water available to nitrifiers decreases.
Since nitrification of sediment-released NH4 + can be
closely coupled to denitrification, the shift to increasing hypoxia accompanying eutrophication will reduce
coupled denitrification and hence N loss as N2 , leading to more N (as NH4 + ) remaining in the system,
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Figure 8. Conceptual diagram, showing potential impacts of changes in phytoplankton composition and biomass on estuarine carbon flux,
sediment oxygen demand and nutrient cycling. If increased nitrogen (ammonium, nitrate, organic N) loading leads to selective stimulation of
phytoplankton that are not effectively grazed and utilized in the food web, these cells will form a relatively large proportion of sedimented
organic matter, thereby increasing sediment oxygen demand (SOD), hypoxia and anoxia, and affecting denitrification potentials. In contrast,
readily-grazed phytoplankton will tend to be exported out of the estuary (by invertebrates and fish), thereby confining organic matter cycling to
the water column and adjacent coastal waters. When extensive hypoxia prevails in the water column, ammonium diffusing from the sediments
cannot be effectively nitrified and subsequently denitrified. This reduces potential N loss from the ecosystem via denitrification, representing a
positive feedback (i.e., from the ecosystem perspective, N is retained to further exacerbate eutrophication). In contrast, if water column hypoxia
is moderate and anoxic conditions are largely confined to the sediments, nitrification of ammonium fluxing from the sediments coupled to
denitrification is high, thus enhancing N loss from the system via denitrification (negative feedback).
potentially exacerbating eutrophication (i.e., positive
feedback). This has ramifications for microbial community preference for certain forms of N, as well as N
budgets of impacted systems.
Application to hypoxia and anoxia
To demonstrate the feasibility of using a molecular
approach to fingerprint microbial communities under
shifting oxygen regimes, time series samples were
analyzed from microbial biomass samples collected
from the water column in the LEO study area during
1994–1997 (Nelson et al. in preparation). To charac-
terize the bacterial populations, a rapid fingerprinting
technique utilizing fluorescent end labeling of PCR
product (target genes) and screening by terminal restriction fragment length polymorphism has been used
(TRFLP; Avaniss-Aghajani et al. 1994; Liu et al.
1997; Phelps et al. 1998; Kerkhof et al. 2000). The
various target genes in the amplification are sorted
by restriction analysis on an automated fluorescent
sequencer. A software package is used to automatically detect and size the labeled restriction fragments
and display the data as a series of peaks, with each
peak representing a different target gene in the original
mixture.
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Figure 9. Oxygen profiles in the LEO-15 study area (A) and overlay of two TRFLP fingerprints of microbial populations (B) from 9/96 and
10/96. The arrows indicate the low and high oxygen samples collected (A) and the specific 16S rRNA target genes unique to the low oxygen
condition (red profile in B) from coastal microbial communities. The oxygen data were kindly provided by R. Sherrell, C. Reimers and S.
Boehme.
Recently, we have shown that highly reproducible
fingerprints can be obtained from complex samples
(Kerkhof et al. 2000; Scala & Kerkhof 2000). Additionally, it is possible to rapidly identify specific
target genes using TRFLP analysis of clonal libraries
to minimize the time necessary to identify specific target gene clones (Kerkhof et al. 2000; Scala & Kerkhof
2000). An example of the TRFLP approach coupled to
chemical and biological measurements that have been
made at this site is shown in Figure 9. Panel A contains
bottom water oxygen profiles at LEO demonstrating
transient hypoxic conditions in summertime. A comparison of microbial communities from low oxygen
and high oxygen samples taken 1 month apart at one
offshore station (A3) is shown in panel B. This study
has facilitated identifying specific 16S rRNA target
genes associated with hypoxic waters at LEO-15. Although a single TRFLP analysis will not be able to
resolve all possible target genes in an amplification,
this technology represents a significant improvement
498
in sample processing time. The crux of the TRFLP
technique is judicious selection of restriction enzymes.
Furthermore, we are not bound to a single enzyme for
the analysis. The simplest way to increase resolution
is to perform additional diagnostic digests.
N, S or C cycling. Nevertheless, these PCR approaches
to study mRNA should gain wide use since they generally require small sample size and can be incorporated
in routine field monitoring.
Abundance and activity measurements of bacteria
Harmful algal taxa as indicators of estuarine and
coastal eutrophication
Determining the number of a particular bacterium
present within a sample, when only the 16S rDNA
sequence from that microorganism is known, can be
a daunting task. A number of methods are in use to
monitor changes in abundance of specific microorganisms present in natural samples, including specific
hybridization to rRNA or rDNA (DeLong 1992; Gordon & Giovannoni 1996) or in situ hybridization with
fluorescently labelled oligonucleotide probes (for review see Amann et al. 1995). An alternative method
involves a modification of the most probable number
(MPN) method to assess changes in abundance of specific bacteria in space and time. In classical MPN,
serial dilutions of samples are grown on selective media to ascertain the numbers of a bacterium present
in the original sample. Recently, replacement of this
growth step with PCR detection has been implemented
(Degrange & Bardin 1995). This modification circumvents the need for culturing and has detection limits in
the 10–100 cell range. The only requirement is a vigorous extraction method and species-specific primers for
PCR amplification. Finally, application of real-time
quantitative PCR for rapid quantitation of microbes in
aquatic or sediment samples using various target genes
is now feasible (Suzuki et al. 2000; Bowers et al. 2000;
Gruntzig et al. 2001).
Bacterial activity can be determined using mRNA
approaches. For example, one way to ascertain
whether bacteria capable of denitrification are actually active under particular environmental conditions
involves determining if a functional gene (i.e., nosZ) is
being transcribed (Kerkhof in prep.). Additional wellstudied functional target genes are Rubisco (RUBP
carboxylase) and nitrogenase. There is evidence from
both pure cultures and environmental samples that
rbcL mRNA levels correlate with CO2 fixation rates
(Pichard et al. 1996; Paul 2000). Additionally, nitrogenase transcription has been shown to coincide with
nitrogenase activity (Wyman 1996). However, there
is little information on how levels of gene expression
(mRNA transcription) correlate with the biogeochemical rates associated with other target genes involved in
Overall, the effects of changes in nutrient loading on
microbial community dynamics remain poorly characterized. This aspect of environmental control of
biodiversity warrants further attention however, since
it may be a key link between nutrient enrichment and
trophic changes, including harmful algal bloom formation. Cyanobacteria, cryptophytes, dinoflagellates
and other algal groups have exploited anthropogenic
nutrient enrichment of estuarine and coastal waters.
(Fogg 1969; Paerl 1988a; Sellner 1997). Certain species in these groups are particularly problematic since
they can produce toxins, disrupt food webs and cause
hypoxia and anoxia. Nutrient fluxes and trophodynamics may also be altered by the presence of harmful taxa
(Porter & Orcutt 1980; Paerl 1988a).
Molecular techniques can be utilized for characterizing harmful algal bloom (HAB) taxa, as shown
for cyanobacteria (Zehr & Paerl 1998). Briefly, DNA
is extracted from water or sediment samples. It is
then isolated, purified, and PCR amplified using specific primers for genes of interest. The nucleic acid
sequences for these genes are determined and compared with a database of previously identified genetic
sequences. The sequences are compared in a phylogenetic tree, which is used to visualize the degree of
similarity between organisms based on genetic data.
All prokaryotes, including cyanobacteria, contain the
16S rRNA gene, making it useful for comparing both
N2 fixing and non N2 fixing cyanobacteria (Figure 10).
Diazotrophs (N2 fixers) have the nifH gene, which encodes one of the subunits of the nitrogenase enzyme
complex that is necessary for N2 fixation (Paerl &
Zehr 2000). NifH is highly conserved among diazotrophs, but still maintains enough diversity to be useful
in differentiating genera. The high degree of genetic
similarity among heterocystous cyanobacteria, for example, is evident in the close clustering of these genera
in nifH phylogenetic trees while still being able to
identify individual species (Figure 11). Many diazotrophs can be identified in this manner, regardless of
whether they are actively fixing N2 .
499
Figure 10. Cyanobacterial phylogenetic tree based upon 16S rRNA sequences. This tree was constructed by the neighbor-joining method and
bootstrap values >50% are given above or beside the corresponding nodes.
Using nifH sequence analysis, the genetic potential for expansion of genetically diverse N2 -fixing and
non-fixing cyanobacterial HAB species into eutrophying mesohaline and euhaline waters was identified
along the length of the Neuse R. estuary (Affourtit
et al. 2001; Dyble et al. in prep). NifH was also
present throughout most of the year, even at times
when cyanobacteria were not numerically dominant
in the water column. Heterocystous cyanobacterial
nifH sequences (Anabaena spp., Anabaenopsis sp.)
were the most common, and their presence throughout
the estuary indicates that cyanobacterial N2 fixers are
present even at higher salinities and colder temperatures than usually required for bloom development
(Affourtit et al. 2001, Dyble et al. in prep). This ge-
netic potential for N2 fixation has been confirmed by
microscopic observations and isolation of Anabaena
spp. and Anabaenopsis spp. filaments in the oligo- and
mesohaline segments of this estuary (Moisander et al.
in press). Active N2 fixation associated with these taxa
has also been detected in near-surface samples during
mid-summer.
Cyanobacteria are symptomatic of eutrophication
in geographically-diverse, nutrient-enriched coastal
rivers, estuaries, embayments, brackish coastal and
pelagic seas (i.e., Baltic), and lagoonal estuaries
(Peele-Harvey, Australia) (Horstmann 1975; Niemi
1979; Huber 1986). Historically, potentially toxic
nuisance diazotrophic genera, including Anabaena,
Aphanizomenon, Lyngbya, Nodularia and Oscillatoria
500
Figure 11. Cyanobacterial phylogenetic tree based upon nifH sequences. This tree was constructed by the neighbor-joining methods and
bootstrap values >50% are given above or beside the corresponding nodes.
have been confined to heavily-nutrified freshwater
impoundments (Francis 1878; Fogg 1969; Paerl &
Tucker 1995). However, regional and global expan-
sion into more incipient eutrophying waters appears to
be underway. Examples include the appearance, persistence and expansion of toxic (to wildlife, cattle,
501
domestic animals and humans) heterocystous, N2 fixing genera (Anabaena, Aphanizomenon, Nodularia)
in brackish fjords in Norway and Sweden, estuaries and coastal embayments in South Africa, Australia and New Zealand, Brazil, Columbia, Canada
and the US (e.g., L. Ponchartrain, LA; Florida Bay,
FL; Albemarle-Pamlico Sound System, NC; Puget
Sound, WA) (Carmichael 1997). These locations are
experiencing increasing surface, groundwater and atmospheric loading of nutrients (Paerl 1997). Toxin
and taste/odor producing N2 fixing taxa (Anabaena,
Aphanizomenon, Nodularia, Cylindrospermopsis) are
becoming increasingly prevalent and problematic in
US and Canadian brackish and coastal aquaculture
operations (Paerl & Tucker 1995; Carmichael 1997).
The Baltic Sea exemplifies the impacts of longterm (several centuries) eutrophication on cyanobacterial bloom potentials (Ambio 1990). Incipient yet
expanding invasions and outbreaks appear to be taking
place in more-recently impacted systems. Nodularia
sp. has recently been observed in Lake Michigan
plankton (McGregor et al. 2001), possibly an indication of eutrophication in this large lake. Recently,
Piehler et al. (in press) observed N2 -fixing Anabaena
strains in previously cyanobacteria-free mesohaline
(5–15 ppt salinity) segments of the eutrophying Neuse
R. estuary. In a parallel laboratory study, Moisander
et al. (2000) showed that 2 toxic Baltic Sea Nodularia
strains (Sivonen et al. 1989) were capable of growth
and bloom formation in Neuse R. Estuary water over
a wide range of salinities (0–15 ppt) (Table 1). Recent work has shown that salinity does not necessarily
represent a barrier to either the establishment or expansion of diverse diazotrophic cyanobacterial genera
(Paerl 1990; Moisander et al. 2000).
These examples are testimony that waters downstream of expanding urban and agricultural regions
are increasingly prone to invasion by N2 fixing cyanobacterial bloom genera (Anabaena, Anabaenopsis,
Aphanizomenon, Cylindrospermopsis, Lyngbya, Nodularia) (Paerl 1988; Sellner 1997). This trend is of
concern, since these genera should enjoy a competitive growth advantage in chronically N-deficient
waters, typical of many estuarine and coastal ecosystems. Smith (1983) showed a strong relationship
between total N:P ratios <20 (by weight) and the
development and periodic persistence of N2 fixing
cyanobacterial bloom genera in lakes and reservoirs.
This stoichiometric predictor of cyanobacterial dominance has received little scrutiny in coastal systems,
which generally exhibit N:P ratios well below 20 and P
sufficiency (Nixon 1986; D’Elia 1986; Paerl & Millie
1996).
Some diazotrophic cyanobacteria can also thrive
on combined N sources (both inorganic and organic)
(Paerl 1988). This nutritional flexibility may enable
such ‘cockroach’ taxa to take advantage of acute N
loading events. Pulses of N-laden agricultural and
urban runoff have increased markedly in coastal watersheds and may be key ‘drivers’ of eutrophication
(Nixon 1995; Paerl 1997). In the N-limited Neuse R.
estuary, cyanobacterial growth responses closely track
(in time and space) such events (Pinckney et al. 1997).
In particular, organic N- and ammonium-enriched
conditions may favor cyanobacterial dominance in
these waters (Pinckney et al. 1997).
Phytoplankton growth in these waters is generally
P and trace element sufficient. Thus, supply rates
of these nutrients do not seem to play a dominant
role in explaining the distribution and proliferation
of N2 fixing cyanobacterial bloom taxa (Paerl 1990).
Clearly, the freshwater-based approach that cyanobacterial bloom expansion can largely be controlled by reducing P loading (Vollenweider 1982) requires further
evaluation with regard to estuarine and coastal waters
experiencing bloom expansion. While these waters
exhibit ‘favorable conditions’ for cyanobacterial expansion based on N:P ratios (Smith 1983), they do not
appear to conform to this paradigm, as most estuarine
and coastal waters currently supporting diazotrophic
genera are N, rather than P limited. This indicates that
nutrient loading interacts with other environmental
factors (mixing, turbulence, light, grazing, etc.) in the
regulation of eutrophication.
Bottom up – top down controls: interactive
impacts of nutrient enrichment and consumers on
microbial community structure and function
Grazers can influence microbial community composition in several ways. Through selective grazing, which
may be based on size, morphology, or prey chemical
composition, grazers can cause differential mortality
in their food resources. Grazers may also affect the microbial composition through release of dissolved inorganic nutrients. Most grazers release metabolic wastes
in reduced form, thereby possibly changing relative
availability of different forms of dissolved nutrients.
For example, nitrate-based diatom blooms frequently
‘crash’ when nitrate is depleted, with subsequent
blooms of nanoflagellates or picoplankton utilizing
502
Table 1. Salinity tolerance of bloom-forming cyanobacteria
Genus
Salinity limits for
growth (PSU)
Reference
(N2 fixing)
Anabaena aphanizomenoides
Anabaena torulosa
Anabaenopsis
Aphanizomenon
Cylindrospermopsis
Nodularia
0–15
0–>14.6
0–>20
0–5
0–4
0>30
0–35
Moisander et al. in prep.
Apte et al. 1987
Moisander et al. in press.
Lehtimäki et al. 1997
Moisander et al. in prep.
Lehtimäki et al. 1997
Apte et al. 1987
(non-N2 fixing)
Microcystis
Oscillatoria
0–2
0–>30
Paerl et al. 1984; Sellner 1997
Fogg 1969
ammonium or urea derived from grazers and bacteria.
Anthropogenic nutrient inputs can interact with grazing to cause even greater changes in phytoplankton
communities. For example, Riegman (1995) found
that excessive nutrient inputs to European coastal waters favored growth of Phaeocystis, which formed
blooms that persisted because they were not grazed
by microzooplankton. These are complex, non-linear
processes. Without detailed information on the composition of producer and consumer communities, and
quantification of the fluxes between them, it will not
be possible to predict changes in ecosystem function
resulting from even small anthropogenic or natural
perturbations.
An example of how changes in nutrient supplies
can interact with grazing on the ecosystem level is
provided by the brown tide blooms that have plagued
shallow estuaries around Long Island, New York for
the past 15 years. In part, it appears that climatic
factors (drought) led to a change in the relative proportions of inorganic and organic N supplied to this
system (Laroche et al. 1997). This caused a shift from
a mixed phytoplankton assemblage to one dominated
by a single picoplankter, Aureococcus anophagefferens. Because overall availability of dissolved N was
not increased, Chl a levels in these blooms have not
been greatly elevated, but the change in phytoplankton
species composition has proven deleterious. Aureococcus is not effectively grazed, and as such persists in
the system. Since it is a smaller cell, light scattering is
increased, resulting in a shallower photic zone (Cosper
et al. 1987). Lack of sufficient light to the benthos has
caused sharp declines in seagrasses and associated loss
of shellfish habitat.
Selective grazing by bacterivores includes preferences for motile bacterial prey (Gonzalez et al. 1993)
and for larger, growing cells (Monger & Landrey
1992). This preference may also be reflected in the
preference for picocyanobacteria over heterotrophic
bacteria exhibited by many ciliates (Simek et al.
1995). Flagellates, ciliates, and rotifers appear to ingest both cyanobacteria and heterotrophic picoplankton, but at least some cyanobacteria are poorly digested and cannot serve as a sole food source (Weisse
1993). Different crustacean and ciliate genera can
have varied impacts on bacterial communities (Simek
et al. 1995). Clearly, grazing strongly interacts with
nutrient enrichment and physical forcing features to
determine the structure and function of autotrophic
and heterotrophic microbial communities.
Concluding remarks
Human-vs climatically-induced alteration of microbial
community structure and function (biodiversity), and
its cascading impacts on ecosystem processes, has received a great deal of attention in both the general
public and scientific sectors of our society. Despite
the recognized importance of this problem, means
of assessment and evaluation on ecosystem, regional
and global scales remain elusive and are in a state
of evolution. We have been hampered by a lack of:
(1) appropriate tools for characterizing biotic community structure and function, and (2) integration of
physical, chemical and biotic forcing features that determine the composition, expression and interaction
of biotic components in response to environmental
503
change. Biochemical and molecular microbial characterization techniques have advanced to the point
that they can be routinely applied as indicators of
community structural and functional responses to a
wide range of anthropogenic and natural environmental stressors. Photopigment-based methods can
be coupled to aircraft or satellite-based remote sensing platforms. This will enable us to identify roles
of microbial species in productivity, nutrient cycling,
food web and water quality dynamics across ecosystem and regional scales. These approaches will prove
particularly useful in the identification and characterization of harmful species, which may be transported or proliferate across such scales. Using this
information, such species can be appropriately targeted for nutrient or other environmental controls.
In this manner, molecular, physiological and analytical tools may be deployed for assessing community
compositional and functional responses to single and
combined stressors over a range of scales and levels of
complexity stretching from controlled microcosms to
meteorologically-driven ecosystems and regions.
Acknowledgements
We appreciate the technical assistance and input of
M. Go, M. Harrington, B. Hendrickson, K. McFarlin, G. McManus, B. Peierls, V. Winkelmann and
P. Wyrick. This work was supported by the National
Science Foundation (DEB 9815495) an NSF Graduate Fellowship to J. Dyble, US Dept. of Agriculture
NRI Project 00-35101-9981, U.S. EPA STAR Projects
R82-5243-010 and R82867701, NOAA/North Carolina Sea Grant Program R/MER-43, and the North
Carolina Dept. of Natural Resources and Community
Development/UNC Water Resources Research Institute (Neuse River Estuary Monitoring and Modeling
Project-ModMon).
References
Affourtit J, Zehr JP & Paerl HW (2001) Distribution of nitrogenfixing microorganisms along the Neuse River Estuary, North
Carolina. Microbial Ecol. 41: 114–123.
Amann RI, Ludwig W & Schleifer K-H (1995) Phylogentic identification and in situ detedction of individual microbial cells
without cultivation. Microbiol. Rev. 59(1): 143–169.
Ambio (1990) Marine Eutrophication. Ambio 19: 101–176.
Antia NP, Harrison, G & Oliveira L (1991) The role of dissolved
organic nitrogen in phytoplankton nutrietion, cell biology and
ecology. Phycologia 30: 1–89.
Avaniss-Aghajani E, Jones K, et al. (1994) A molecular technique
for identification of bacteria using small subunit ribosomal RNA
sequences. Biotechniques 17(1): 144–6.
Azam F, Fenchel T, Field JG, Gray JS, Meyer-Reil LA & Thingstadt
F (1983) The ecological role of water-column microbes in the
sea. Marine Ecol. Prog. Ser. 10: 257–263.
Banse K (1977) Determining the carbon-to-chlorophyll ratio of
natural phytoplankton. Marine Biology 41: 199–212.
Benoit G, Oktay S, Cantu A, Hood ME, Coleman C, Corapcioglu
O & Santschi PH (1994) Partitioning of Cu, Pb, Ag, Zn, Fe, Al,
and Mn between filter-retained particles, colloids and solution in
six Texas estuaries. Marine Chem. 45: 307–336.
Bowers HA, Tengs T, Glasgow, HBJr, Burkholder JM, Rublee PA
& Oldach DW (2000) Development of real-time PCR assays for
rapid detection of Pfiesteria piscicida and related dinoflagellates.
Appl. Environ. Microbiol. 66: 4641–4648.
Boyer JN, Stanley DW, & Christian RR (1994) Dynamics of NH4 +
and NO3 − uptake in the water column of the Neuse River
Estuary, North Carolina. Estuaries 17: 361–371.
Boyton WR., Garber JH, Summers R & Kemp WM (1995) Inputs,
transformations, and transport of nitrogen and phosphorus in
Chesapeake Bay and selected tributaries. Estuaries 18: 285–314.
Collos Y (1989) A linear model of external interactions during uptake of different forms of inorganic nitrogen by microalgae. J.
Plankton Res. 11: 521–533.
Copeland BJ & Gray J (1991) Status and Trends Report of the
Albemarle-Pamlico Estuary. steel J (Ed), Albemarle-Pamlico Estuarine Study Report 90-01. NC Dept. of Environ. Health & Nat.
Resources, Raleigh.
Carmichael WW (1997) The cyanotoxins. Adv. Bot. Res. 27: 211–
256.
Cloern JE, Grenz C & Vidergar-Lucas L (1995) An empirical model
of the phytoplankton chlorophyll: carbon ratio – the conversion
factor between productivity and growth rate. Limnol. Oceanogr.
40: 1313–1321.
Cosper EM, Dennison WC, Carpenter EJ, Bricelj VM, Mitchell JG,
Kuenstner SH, Colflesh D & Dewey M (1987) Recurrent and
persistent brown tide blooms perturb coastal marine ecosystem.
Estuaries 10: 284–290.
Cullen JJ (1990) On models of growth and photosynthesis in
phytoplankton. Deep-Sea Res. 37: 667–683.
D’Elia CF, Sanders JG & Boynton WR (1986) Nutrient enrichment
studies in a coastal plain estuary: phytoplankton growth in large
scale, continuous cultures. Can. J. Fish aquat. Sci. 43: 397–406.
Degrange V & Bardin R (1995) Detection and counting of Nitrobacter populations in soil by PCR. Appl. Environ. Microbiol. 61(6):
2093–2098.
DeLong EF (1992) Archaea in coastal marine environments. Proc.
Natl. Acad. Sci. 89: 5685–5689.
DeLong EF, Wickham GS & Pace NR (1989) Phylogenetic strains:
Ribosomal RNA-based probes for the identification of single
cells. Science 243: 1360–1363.
DeLong EF, Franks DG & Alldredge AL (1993) Phylogenetic diversity of aggregate-attached vs. free-living marine bacterial
assemblages. Limnol. Oceanogr. 38: 924–934.
Fogg GE (1969) The physiology of an algal nuisance. Proc. Roy.
Soc. Lond. B. 173: 175–189.
Field KG, Gordon D, Wright T, Rappe’ M, Urbach E, Vergin K &
Giovannoni SJ (1997) Diversity and depth-specific distribution
of SAR11 cluster rRNA genes from marine planktonic bacteria.
Appl. Environ. Microbiol. 63: 63–70.
Francis G (1878) Poisonous Australian lake. Nature (London) 18:
11–12.
504
Fuhrman JA, McCallum K & Davis AA (1992) Novel major archaebacterial group from marine plankton. Nature (London) 356:
148–149.
Fuhrman JA, McCallum K & Davis AA (1993) Phylogenetic diversity of subsurface marine microbial communities from the
Atlantic and Pacific oceans. Appl. Environ. Microbiol. 59: 1294–
1302.
Geider RJ, MacIntyre HL & Kana TM (1997) Dynamic model of
phytoplankton growth and acclimation: responses of the balanced growth rate and the chlorophyll a: carbon ratio to light,
nutrient-limitation and temperature. Marine Ecology Progress
Series 148: 187–200.
Gieskes W & Kraay G (1986) Floristic and physiological differences
between the shallow and deep nanophytoplankton community
in the eutrophic zone of the open tropical Atlantic revealed by
HPLC analysis of pigments. Marine Biol. 91: 567–576.
Giovannoni SJ, Britschgi TB, Moyer CL & Field KG (1990) Genetic
diversity in Sargasso Sea bacterioplankton. Nature (London)
345: 148–149.
Glenn S, Crowley M, Haidvogel D & Song Y (1996) Underwater
observatory captures coastal upwelling events off New Jersey.
Eos 77: 233–36.
Goericke R & Welschmeyer N (1993a) The carotenoid-labeling
method: measuring specific rates of carotenoid synthesis in natural phytoplankton communities. Marine Ecol. Progr. Ser. 98:
157–171.
Goericke R & Welschmeyer N (1993b) The chlorophyll-labeling
method: measuring specific rates of chlorophyll a synthesis in
cultures and in the open ocean. Limnol. Oceanogr. 38: 80–95.
Goldenberg SB, Landsea CW, Mestas-NuZes AM & Gray WM
(2001) The recent increase in Atlantic Hurricane Activity:
Causes and implications. Science 293: 474–479.
Gonzalez JM, Sherr EB & Sherr BF (1993) Differential feeding
by marine flagellates on growing versus starving, and on motile
versus nonmotile, bacterial prey. Marine Ecol. Progr. Ser. 102:
257–267.
Gordon DA & Giovannoni SJ (1996) Detection of stratified microbial populations related to Chlorobium and Fibrobacter species
in the Atlantic and Pacific Oceans. Appl. Environ. Microbiol. 2:
1171–1177.
Gray WM, Sheaffer JD & Landsea CW (1996) Climate trends associated with multi-decadal variability of intense Atlantic hurricane
activity. In: Diaz HF & Pulwarty PS (Eds) Hurricanes, Climatic
Change and Socioeconomic Impacts: A Current Perspective (pp
293–312). Westview Press, Denver, Co.
Gray WM et al. (1999) On the mark prediction caps 1999
season for Colorado State University Hurricane Forecast
Team: Five year active trend bears out theory. http: //tropical.atmos.colostate.edu/fo recasts/1999/press99nov.html.
Gruntzig V, Nold SC, Zhou JZ & Tiedje JM (2001) Pseudomonas stutzeri nitrite reductase gene abundance in environmental
samples measured by real-time PCR. Appl. Environ. Microbiol.
67(2): 760–768.
Guo L & Santschi PH (1997) Isotopic and elemental characterization of colloidal organic matter from the Chesapeake Bay and
Galveston Bay. Marine Chem. 59: 1–15.
Harrington MB (1999) Responses of natural phytoplankton communities from the Neuse River Estuary, NC to changes in
nitrogen supply and incident irradiance. MSc thesis, Univ. of
North Carolina, Chapel Hill, North Carolina, 89 p.
Harrison P & Turpin D (1982) The manipulation of physical,
chemical, and biological factors to select species from natural
phytoplankton populations. In: Grice G & Reeve M (Eds) Marine
Mesocosms: Biological and Chemical Research in Experimental
Ecosystems (pp 275–287). Springer-Verlag, New York.
Harrison W, Platt T & Lewis M (1987) F-ratio and its relationship to
ambient nitrate concentration in coastal waters. J. Plankton Res.
9: 235–245.
Hastings RC, Saunders JR, Hall GH, Pickup RW & McCarthy AJ
(1998) Application of molecular biological techniques to a seasonal study of ammonia oxidation in a eutrophic freshwater lake.
Appl. Environ. Microbiol. 64: 3674–3682.
Head IM, Saunders JR & Pickup RW (1998) Microbial evolution,
diversity, and ecology: a decade of ribosomal RNA analysis of
uncultivated microorganisms. Microbial Ecol. 35: 1–21.
Hicks DC & Miller JR (1980) Meteorological forcing and bottom
water movement off the northern New Jersey coast. Estuarine
Coastal Sci. 2: 563–571.
Horstmann U (1975) Eutrophication and mass production of bluegreen algae in the Baltic. Havforsk Skr 239: 83–90.
Huber AL (1986) Nitrogen fixation by Nodularia spumigena
Martens (Cyanobacteria). I. Field studies on the contribution
of blooms to the nitrogen budget of the Peel-Harvey Estuary,
Western Australia. Hydrobiologia 131: 193–203.
Hung C-C, Tang D, Warnken K & Santschi PH (2001) Distributions
of carbohydrates, including uronic acids, in estuarine waters of
Galveston Bay. Marine Chem. 73: 301–318.
Jeffrey S, Mantoura R & Wright S (Eds) (1997) Phytoplankton
Pigments in Oceanography: Guidelines to Modern Methods.
UNESCO, Paris.
Karkhoff-Schweizer RR, Huber DPW & Voordouw G (1995) Conservation of the genes for dissimilatory sulfite reductase from
Desulfovibrio vulgaris and Archaeoglobus fulgidus allows their
detection by PCR. Appl. Environ. Microbiol. 61: 290–296.
Kerkhof L (1992) A Comparison of substrates for quantifying the
signal from a non-radiolabeled DNA probe. Anal. Biochem. 205:
359–364.
Kerkhof L & Ward BB (1993) Comparison of nucleic acid hybridization and fluorometry for measurement of the relationship
between RNA/DNA ratio and growth rate in a marine bacterium.
Appl. Environ. Microbiol. 59: 1303–1309.
Kerkhof L & Kemp P (1999) Small ribosomal RNA content in marine bacteria during non-steady state growth. FEMS Microbial
Ecol. 30: 253–260.
Kerkhof L, Santor, M & Garland J (2000) Response of Soybean Rhizosphere Communities to human hygiene water addition as determined by community-level physiological profiling
(CLPP) and terminal restriction fragment length polymorphism
(TRFLP). FEMS Microbiol. Lett. 184: 95–101.
Kirshtein JD, Paerl HW & Zehr JP (1991) Amplification, cloning,
and sequencing of a nifH segment from aquatic microorganisms
and natural communities. Appl. Environ. Microbiol. 57: 2645–
2650.
Laroche J, Nuzzi R, Waters R, Wyman K, Falkowski PG & Wallace
DWR (1997) Brown tide blooms in Long Island’s coastal waters linked to interannual variability in groundwater flow. Global
Change Biol. 3: 397–410.
Landsea CW, Pielke RA Jr., Mestaz-Nunez AM & Knaff JA (1999)
Atlantic basin hurricanes: Indices of climatic changes. Climatic
Changes 42: 89–129.
Liu WT et al. (1997). Characterization of microbial diversity by
determining terminal restriction fragment length polymorphisms
of genes encoding 16s rRNA. Appl. Environ. Microbiol. 63:
4516–4522.
MacGregor BJ, Van Mooy B, Baker BJ, Mellon M, Moisander PH,
Paerl HW, Zehr JP, Hollander D & Stahl DA (2001) Microbiological, molecular biological, and stable isotopic evidence for
505
nitrogen fixation in the open waters of Lake Michigan. Environ.
Microbiol. 3: 205–219.
Mackey M, Mackey D, Higgins H & Wright S (1996) CHEMTAX
– a program for estimating class abundances from chemical
markers: application to HPLC measurements of phytoplankton.
Marine Ecol. Progr. Ser. 144: 265–283.
Massana R, Taylor LT, Murray AE, Wu KY, Jeffrey WH & DeLong
EF(1998) Vertical distribution and temporal variation of marine
planktonic Archaea in the Gerlache Strait, Antarctica, during
early spring. Limnol. Oceanogr. 43: 607–617.
McBride R & Moslow T (1991) Origin, evolution, and distribution
of shoreface sand ridges, Atlantic inner shelf. USA. Marine Geol.
97: 57–85.
McCarthy J (1981) The kinetics of nutrient utilization. In: Platt T
(Ed.) Physiological Bases of Phytoplankton Ecology. Can. Bull.
Fish. aquat. Sci. 210: 211–233.
McDonald IR & Murrell JC (1997) The particulate methane monoxigenase gene pmoA and its use as a functional gene probe for
methanotrophs. FEMS Microbiol. Lett. 156: 205–210.
Millie DF, Paerl HW & Hurley J (1993) Microalgal pigment assessments using high performance liquid chromatography: A
synopsis of organismal and ecological applications. Can. J. Fish.
aquat. Sci. 50: 2513–2527.
Moisander PH, Kononen K & Paerl HW (2000) Growth, primary
productivity, and nitrogen fixation potential of Nodularia spp.
(Cyanophyceae) in water from a subtropical estuary in the United
States. J. Phycol. 36: 645–658.
Molloy C & Syrett P (1988) Interrelationships between uptake of
urea and uptake of ammonium by microalgae. J. Exp. Marine
Biol. 118: 85–95.
Monger BC & Landry MR (1990) Direct-interception feeding by
marine zooflagellates: The importance of surface and hydrodynamic forces. Marine Ecol. Progr. Ser. 65: 123–140.
Morse J, Presley B, Taylor R, Benoit G & Santschi P (1993) Trace
metal chemistry of Galveston Bay: Water, sediments, and biota.
Marine Environ. Res. 36: 1–37.
Munson MA, Nedwell DB & Embley TM (1997) Phylogenetic diversity of Archaea in sediment samples from a coastal salt marsh.
Appl. Environ. Microbiol. 63: 4729–4733.
Murray AE, Hollibaugh JT & Orrego C (1996) Phylogenetic compositions of bacterioplankton from two California estuaries compared by denaturing gradient gel electrophoresis of 16S rDNA
fragments. Appl. Environ. Microbiol. 62: 2676–2680.
Niemi A (1979) Blue-green algal blooms and N: P ratio in the Baltic
Sea. Acta Botanica Fennica 110: 57–61.
Nixon SW (1986) Nutrient dynamics and the productivity of marine
coastal waters. In: Halwagy R, Clayton D & Behbehani M (Eds)
(pp 97–115). The Alden Press, Oxford.
Nixon SW (1995) Coastal marine eutrophication: A definition,
social causes, and future concerns. Ophelia 41: 199–220.
Olson JB, Litaker RW & Paerl HW (1999) Ubiquity of heterotrophic
diazotrophs in marine microbial mats. Aquatic Microbial Ecol.
19: 29–36.
Paerl HW (1982) Interactions with bacteria. In: Carr NG & Whitton BA (Eds) The Biology of Cyanobacteria (pp 441–461).
Blackwell Scientific, Oxford.
Paerl HW (1983) Factors regulating nuisance blue-green algal
bloom potentials in the lower Neuse River. Report No. 177, UNC
Water Resources Research Institute, Raleigh, NC. 139 p.
Paerl HW (1987) Dynamics of blue-green algal (Microcystis aeruginosa) blooms in the lower Neuse River, NC: causative factors
and potential controls. Report No. 229. UNC Water Resources
Research Institute, Raleigh, NC. 164 p.
Paerl HW (1988a) Nuisance phytoplankton blooms in coastal,
estuarine, and inland waters. Limnol. Oceanogr. 33: 823–847.
Paerl HW (1988b) Growth and reproductive strategies of freshwater
blue-green algae (cyanobacteria). In: Sandgren CD (Ed) Growth
and Reproductive Strategies of Freshwater Phytoplankton (pp
261–315). Cambridge Univ. Press, Cambridge.
Paerl HW (1990) Physiological ecology and regulation of N2
fixation in natural waters. Adv. Microbial Ecol. 11: 305–344.
Paerl HW (1995) Coastal eutrophication in relation to atmospheric
nitrogen deposition: current perspectives. Ophelia 41: 237–259.
Paerl HW (1996) A comparison of cyanobacterial bloom dynamics
in freshwater, estuarine and marine environments. Phycologia
35: 25–35.
Paerl HW (1997) Coastal eutrophication and harmful algal blooms:
Importance of atmospheric deposition and groundwater as “new”
nitrogen and other nutrient sources. Limnol. Oceanogr. 42:
1154–1165.
Paerl HW & Bowles ND (1987) Dilution bioassays: Their application to assessments of nutrient limitation in hypereutrophic
waters. Hydrobiologia 146: 265–273.
Paerl HW & Fogel ML (1994) Isotopic characterization of atmospheric nitrogen inputs as sources of enhanced primary production in coastal Atlantic Ocean waters. Marine Biol. 119:
635–645.
Paerl HW & Pinckney JL (1996) Microbial consortia: Their role in
aquatic production and biogeochemical cycling. Microbial Ecol.
31: 225–247.
Paerl HW, Rudek J & Mallin MA (1990) Stimulation of phytoplankton production in coastal waters by natural rainfall inputs:
nutritional and trophic implications. Marine Biol. 107: 247–254.
Paerl HW, Mallin MA, Donahue CA, Go M & Peierls BL (1995)
Nitrogen loading sources and eutrophication of the Neuse River
Estuary, NC: Direct and indirect roles of atmospheric deposition.
Report. 291, UNC Water Resources Research Institute, Raleigh,
NC 119 p.
Paerl HW & Millie DF (1996) Physiological ecology of toxic
cyanobacteria. Phycologia 35(6): 160–167.
Paerl HW & Zehr JP (2000) Nitrogen Fixation. In: Kirchman D (Ed)
Microbial Ecology of the Oceans (pp 387–426). Academic Press,
New York.
Paerl HW, Bales JD, Ausley LW, Buzzelli CP, Crowder LB, Eby
LA, Go M, Peierls BL, Richardson TL & Ramus JS (2000)
Hurricanes’ hydrological, ecological effects linger in major US
estuary. EOS 81(40): 457–462.
Paerl HW, Bales JD, Ausley LW, Buzzelli CP, Crowder LB, Eby LA,
Fear JM, Go M, Peierls BL, Richardson TL & Ramus JS (2001)
Ecosystem impacts of 3 sequential hurricanes (Dennis, Floyd and
Irene) on the US’s largest lagoonal estuary, Pamlico Sound, NC.
Proc. Natl. Acad. Sci. USA 98: 5655–5660.
Paul JH, Kang B & Tabita RF (2000) Diel Patterns of Regulation of
rbcL Transcription in a Cyanobacterium and a Prymnesiophyte.
Marine Biotechnol. 2: 429–436.
Pearce JB, Berman CR Jr & Rosen MR (1982) Annual NEMP
report on the health of the northeast coastal waters. NOAA
Technical Memorandum NMFS-F/NEC-35, Northeast Fisheries
Center. Woods Hole. MA.
Peierls BL & HW Paerl (1997) The bioavailability of atmospheric
organic nitrogen deposition to coastal phytoplankton. Limnol.
Oceanogr. 42: 1819–1880.
Phelps C, Kerkhof L & Young L (1998) Molecular characterization of a sulfate-reducing consortium which mineralizes benzene.
FEMS Microbial Ecol. 27: 269–279.
Pichard SL, Campbell L & Paul JH (1997) Diversity of the ribulose
bisphosphate carboxylase/oxygenase form I gene (rbcL) in nat-
506
ural phytoplankton communities. Appl. Environ. Microbiol. 63:
3600–3606.
Pinckney JL, Millie DF, Howe KE, Paerl HW & Hurley J (1996)
Flow scintillation counting of 14C-labeled microalgal photosynthetic piments. J. Plankton Res. 18: 1867–1880.
Pinckney JL, Millie DF, Vinyard B & Paerl HW (1997) Environmental controls of phytoplankton bloom dynamics in the Neuse
River Estuary (North Carolina, USA). Can. J. Fish. aquat. Sci.
54: 2491–2501.
Pinckney JL, Paerl HW & Harrington MB (1999) Responses of
the phytoplankton community growth rate to nutrient pulses in
variable estuarine environments. J. Phycol. 35: 1455–1463.
Pinckney LJ, Richardson TL, Millie DF & Paerl HW (2001) Application of photopigment biomarkers for quantifying microalgal
community composition and in situ growth rates. Organic Geochem. 32: 585–595.
Porter KG & Orcutt JD (1980) Nutritional adequacy, manageability,
and toxicity as factors that determine the food quality of green
and blue-green algae as food for Daphnia. In: Kerfoot WC (Ed)
Evolution and Ecology of Zooplankton Communities (pp 268–
281). Univ. Press of New England, Hannover.
Rappe MS, Suzuki MT, Vergin KL & Giovannoni SJ (1998) Phylogenetic diversity of ultraplankton plastid small-subunit rRNA
genes recovered in environmental nucleic acid samples from the
Pacific and Atlantic coasts of the United States. Appl. Environ.
Microbiol. 64: 294–303.
Redalje D (1993) The labeled chlorophyll a technique for determining photoautotrophic carbon specific growth rates and carbon
biomass. In: Kemp P, Sherr B, Sherr E & Cole J (Eds) Handbook
of Methods in Aquatic Microbial Ecology (pp 563–572) Lewis
Publishing Co., Boca Raton, FL.
Redalje DG & Laws EA (1981) A new method for estimating phytoplankton growth rates and carbon biomass. Marine Biol. 62:
73–79.
Richardson K (1997) Harmful or exceptional phytoplankton blooms
in the marine ecosystem. Adv. Marine Biol. 31: 302–385.
Riegman R (1995) Nutrient-related selection mechanisms in marine
phytoplankton communities and the impact of eutrophication on
the planktonic food web. IAWQ SIL Conference on Selection
Mechanisms Controlling Biomass Distribution. Noordwykerhout, the Netherlands 32: 4.
Riemann B, Lignell R & Laws E (1993) Time-course development
of 14 C specific activity of chlorophyll a, carbon, and proteins in
algal cultures. Limnol. Oceanogr. 38: 96–111.
Rizzo WG, Lackey G & Christian RR (1992) Significance of euphotic, subtidal sediments to oxygen and nutrient cycling in a
temperate estuary. Marine Ecol. Progr. Ser. 86: 51–61.
Rowan K (1989) Photosynthetic Pigments of the Algae. Cambridge
Univ. Press, N.Y., 334 p.
Rudek J, Paerl HW, Mallin MA & Bates PW (1991). Seasonal and
hydrological control of phytoplankton nutrient limitation in the
lower Neuse River Estuary, North Carolina. Marine Ecol. Progr.
Ser. 75: 133–142.
Santschi PH (1995) Seasonality of nutrient concentrations in Galveston Bay. Marine Environ. Res. 40: 337–362.
Scala DJ & Kerkhof LJ (1998) Nitrous oxide reductase (nosZ) genespecific PCR primers for detection of denitrifiers and three nosZ
genes from marine sediments. FEMS Microbiol. Lett. 162: 61–
68.
Scala DJ & Kerkhof LJ (1999) Diversity of nitrous oxide reductase
(nosZ) genes in continental shelf sediments. Appl. Environ.
Microbiol. 65: 1681–1687.
Sellner KG (1997) Physiology, ecology, and toxic properties of marine cyanobacterial blooms. Limnol. Oceanogr. 42: 1089–1104.
Sheridan PF, Slack RD, Ray SM, McKinney LW, Klima EF & Calnan TR (1988) Biological components of Galveston Bay. In:
Whitledge TE & Ray SM (Eds) Galveston Bay: Issues, Resources, Status and Management (pp 23–51). U.S. Department
of Commerce.
Simek K et al. (1995) Ciliate grazing on picoplankton in a eutrophic reservoir during the summer phytoplankton maximum:
A study at the species and community level. Limnol. Oceanogr.
40: 1077–1090.
Sivonen KK, Kononen K, Esala A-L & Niemela SI (1989) Toxicity
and isolation of the cyanobacterium Nodularia spumigena from
the southern Baltic Sea in 1986. Hydrobiologia 185: 3–8.
Steppe TF, Olson JB, Paerl HW & Belnap J (1996) Consortial
N2 fixation: A strategy for meeting nitrogen requirements of marine and terrestrial cyanobacterial mats. FEMS Microbiol. Ecol.
21: 149–156.
Stolte W, McCollin T, Noodeloos A & Riegman R (1994) Effect of nitrogen source on the size distribution within marine
phytoplankton populations. J. Exp. Marine Biol. Ecol. 184:
83–97.
Suzuki MT, Rappe MS, Haimberger ZW, Winfield H, Adair N,
Strobel J & Giovannoni SJ (1997) Bacterial diversity among
small-subunit rRNA gene clones and cellular isolates from the
same seawater sample. Appl. Environ. Microbiol. 63: 983–989.
Suzuki MT, Taylor LT & DeLong EF (2000) Quantitative analysis of
small-subunit rRNA genes in mixed microbial populations via 5
-nuclease assays. Appl. Environ. Microbiol. 66(11): 4605–4614.
Syrett P (1981) Nitrogen metabolism in microalgae. Physiological
bases of phytoplankton ecology. Can. Bull. Fish. aquat. Sci. 210:
182–210. bTwilley R, Cowan J, Miller-Way T, Montagna P &
Mortazavi B (1999) Benthic nutrient fluxes in selected estuaries
in the Gulf of Mexico. In: Bianchi TS, Pennock JR & Twilley
R (Eds) Biogeochemistry of Gulf of Mexico Estuaries (pp 163–
209). John Wiley & Sons.
Twomey L & Thompson P (2001) Nutrient limitation of phytoplankton in a seasonally open bar-built estuary: Wilson Inlet, Western
Australia. J. Phycol. 37: 16–29.
Valigura RA, Alexander RB, Castro MS, Meyers TP, Paerl HW,
Stacey PE & Turner RE (Eds) (2000) Nitrogen Loading in
Coastal Water Bodies: An Atmospheric Perspective. Coastal and
Estuarine Studies No. 57. American Geophysical Union Press,
Washington, DC.
Van Heukelem L, Lewitus A, Kana T & Craft N (1994). Improved
separations of phytoplankton pigments using temperaturecontrolled high performance liquid chromatography. Marine
Ecol. Progr. Ser. 114: 303–313.
Vetriani C, Reysenbach A-L & Doré J (1998) Recovery and phylogenetic analysis of archaeal rRNA sequences from continental
shelf sediments. FEMS Microbiol. Lett. 161: 83–88.
Vitousek PM, Mooney HA, Lubchenko J & Mellilo JM (1997)
Human domination of Earth’s ecosystem. Science 277: 494–499.
Vollenweider RA (1982) Eutrophication of Waters: Monitoring,
Assessment and Control. OECD, Paris.
Voytek MA & Ward BB (1995) Detection of ammonium-oxidizing
bacteria in the beta subclass of the class Proteobacteria in
aquatic samples with the PCR. Appl. Environ. Microbiol. 61:
1444–1450.
Wagner M, Roger AJ, Flax JL, Brusseau GA & Stahl DA (1998)
Phylogeny of dissimilatory sulfite reductases supports an early
origin of sulfate respiration. J. Bacteriol. 180: 2975–2982.
Warnken KL (1998) Sediment Water Exchange of Trace Metals and
Nutrients in Galveston Bay, Texas. Masters Thesis, Texas A&M
University.
507
Wagner M, Roger AJ, Flax JL, Brusseau GA & Stahl DA (1998)
Phylogeny of dissimilatory sulfite reductases supports an early
origin of sulfate respiration. J. Bacteriol. 80: 2975–2982.
Weisse T (1993) Dynamics of autotrophic picoplankton in marine and freshwater ecosystems. In: Jones JG (Ed) Advances in
Microbial Ecology (pp 327–370). Plenum Press, New York.
Whitall DR & Paerl HW (2001) Spatiotemporal variability of wet
atmospheric nitrogen deposition to the Neuse River Estuary, NC.
J. Environ. Qual. 30: 1508–1515.
Wright S, Jeffrey S, Mantoura R, Llewellyn C, Bjørnland T,
Repeta D & Welschmeyer N (1991) An improved HPLC method
for the analysis of chlorophylls and carotenoids from marine
phytoplankton. Marine Ecol. Prog. Ser. 77: 183–196.
Wyman M, Zehr JP & Capone DG (1996) Temporal variability in
nitrogenase gene expression in natural populations of the marine cyanobacterium Trichodesmium thiebautii. Appl. Environ.
Microbiol. 62: 1073–1075.
Zehr JP & Paerl HW (1998) Nitrogen fixation in the marine environment: Genetic potential and nitrogenase expression. In: Cooksey
KE (Ed) Molecular Approaches to the Study of the Ocean (pp
285–302). Chapman and Hall, London.
Zumft WG (1997) Cell biology and molecular basis of denitrification [Review]. Microbiol. Mol. Biol. Rev. 61: 533–616.