Processes controlling abundance of dominant copepod species on Georges Bank:
Local dynamics and large-scale forcing
PIs: Cabell Davis (WHOI), Robert Beardsley (WHOI), Changsheng Chen (UMassD),
Rubao Ji (WHOI), Edward Durbin (URI), David Townsend (UMaine),
Jeffrey Runge (UNH), Charles Flagg (SUNY), Richard Limeburner (WHOI)
A fundamental goal of
Biological Oceanography is to understand how underlying biological-physical
interactions determine abundance of marine organisms. For animal populations, it is well known
that factors controlling survival during early life stages (i.e., recruitment)
are strong determinants of adult population size, but understanding these
processes has been difficult due to model and data limitations. Recent advances in numerical
modeling, together with new 3D data sets, provide a unique opportunity to study
in detail biological-physical processes controlling zooplankton population
size. We propose to use an existing
state-of-the-art biological/physical numerical model (FVCOM) together with the
recently-processed large 3D data set from the Georges Bank GLOBEC program to
conduct idealized and realistic numerical experiments that explore the detailed
mechanisms controlling seasonal evolution of spatial patterns in dominant
zooplankton species on
GLOBEC approach —
Understanding complex marine ecosystems requires use of simplifying
assumptions, which historically has involved trophodynamic analysis of energy
or mass flow by measurement and modeling (Lindeman, 1942; Teal, 1962; Odum,
1957; Steele, 1974). In regions of
high diversity such as the oligotrophic ocean this approach remains the only
feasible method of analysis (e.g., Sarmiento et al., 1993). As an alternative in low diversity
regions, it is possible to model the population dynamics of a few dominant
species to understand processes controlling their abundance and to obtain
information about system level functioning (e.g.,
Bank GLOBEC: dominant zooplankton species —
Georges Bank was chosen as the first GLOBEC study site due to its sensitivity
to climate change, definable populations, importance as a fishing ground, and
significant historical database (GLOBEC, 1992). The goal of this program is to
understand the biological and physical processes controlling abundance of cod
and haddock larvae and their dominant prey species. In the program implementation plan we
emphasized the copepods Calanus
finmarchicus and Pseudocalanus
spp. as target species, since these are dominant prey items for larval cod and
haddock. Subsequent studies have
found that small copepods (Pseudocalanus
spp., Oithona similis, Centropages spp., Temora longicornis) are dominant prey items for cod and haddock
larvae on Georges and Western Banks (Lough and Mountain, 1996; Lough et al,
1996; McLaren and Avendano. 1995; McLaren et al., 1997). This contrasts sharply with the
situation in the eastern
Local dynamics — Georges Bank (GB), the Gulf of Maine (GOM), and Scotian Shelf (SS) are part of a single regional coastal current system, driven in large part by upstream mass and buoyancy forcing (Fig. 1). The bank itself is a quasi-flow-through system, with water from offshore and upstream sources arriving on the bank, being modified locally by surface forcing and tidal mixing before moving off-bank to the Mid-Atlantic Bight or re-circulated northward along the Great South Channel.
The strongest currents over the bank are of tidal origin, and turbulent mixing associated with the tidal bottom boundary layer is most intense over the shallow cap of the bank, effectively eliminating local vertical temperature and salinity stratification throughout the year. As seasonal stratification increases on the flanks of the bank, the tidal mixing front forms with associated secondary flow. The clockwise around-bank residual flow increases with seasonal stratification, becoming partially closed from June through
Figure 1. Circulation: 1 flow across GSC into the north flank jet, 2 tidal-pumping of deep water onto GB, 3 wind-driven near-surface flow, 4 small-scale cross-frontal processes, 5 SS cross-over
Figure 2. Schematic of the western
(Fratantoni and Pickart, 2005)
September until fall storms
and surface cooling destroy the local stratification. Surface heating drives the development
of the seasonal thermocline.
Salinity on the bank is controlled by advective and mixing processes
along the northern and southern flanks.
On the southern flank salinity is influenced by on-bank intrusions of
saline shelf-break frontal water and very saline warm-core ring water (Fig.
1). Along the northern flank
salinity is controlled by advection from the western Gulf across the northern
Great South Channel (Fig. 1, 1), tidally-driven near-bottom residual flow (the
“tidal pump”, Fig. 1, 2), wind-driven near-surface flow (Fig. 1, 3),
small-scale cross-frontal processes (Fig. 1, 4), and intermittent cross-over of
low salinity SS surface water (Fig. 1, 5).
The tidal pump in particular provides a strong mechanism for bringing
deep water from
Figure 3. Schematic showing the strong westward
penetration of LSW and northward position of the
Large-scale forcing — Water enters the GOM via two primary
paths: (1) the flow of relatively
fresh water above 100m from the SS and (2) warmer, more saline Slope Water (SW)
at depths greater than 100m through the Northeast Channel (NEC). The primary
source of SS water is the West Greenland/Labrador Current system, with
additional input from the St. Lawrence system (Fig. 2). As the Labrador Current
flows around the Grand Banks, the large shoaling in shelf-break depth from
~300m in the north to ~100m to the southwest helps force the deeper Labrador
Current water to flow along the upper slope, thus forming Labrador Slope Water
(LSW), which flows west into the Laurentian Channel and along the Scotian upper
slope. The westward extent of LSW depends on its source strength, thought to
depend on basin-scale forcing (NAO) (Fig 3), and degree of mixing with ambient
Warm Slope Water (WSW) of
Fig. 4. GB salinity anomaly (Mountain, 2005)
Fig. 5. Percent LSW in bottom water (150-
200 m) in 1998. (Drinkwater et al, 2003)
Data from the 1995-1999 GB GLOBEC field study provide an excellent example of the flow-through nature of the GB/GOM system and its linkage to larger basin-scale forcing. The salinity on GB exhibited two significant freshening events between early 1996 to early 1997 and between late 1997 through 1998, with a net drop of ~1 psu (Fig. 4). These two events also were observed in surface (0-30m) GOM waters, suggesting significant increases in freshwater influx from the SS (Smith et al., 2001). In the NEC, WSW was replaced by cooler, fresher LSW in January 1998 as the leading edge of LSW flow extended west due to an increase in the Labrador Current associated with a low NAO. As LSW entered the GOM during early 1998, it mixed with resident GOM water (Fig 5). By early 1999, WSW was again flowing into the GOM through the NEC. Since the tidal pump mechanism can carry deep water up on the northern flank of GB, advection of LSW in Georges Basin onto the bank can occur on relative short time scales (>=1 month), suggesting that part of the freshening on GB observed during 1998 was due to the influx of LSW into the GOM. Clearly, variations in the primary upstream sources (the SS Water, the mix of WSW versus LSW) linked to basin-scale forcing strongly control the water properties (including heat, salt and nutrients) through the GOM and onto GB.
Fig. 5a. Scenario of nutrient input onto GB from the NEC (Townsend et al., 2004).
1.2. Connection between NAO and plankton productivity on GB
intrusions of LSW and WSW through the NEC greatly influence the nutrient (N,
Si) input into the GOM. It is believed that the tidal pumping
mechanism along the northern edge of the bank can quickly transport nutrients
1.3. Characteristics of GB zooplankton
GB zooplankton is dominated by Calanus finmarchicus, Pseudocalanus spp., Oithona similis, Centropages spp., and Temora longicornis, and Paracalanus parvus (Bigelow, 1926; Davis, 1984, 1987b; Sherman et al, 1987; Durbin et al., 2003; Durbin and Casas, submitted). Each species exhibits a characteristic life cycle and seasonal/spatial pattern in the GB/GOM region. Calanus finmarchicus and Pseudocalanus spp. are cold-water species that avoid the warm surface layer (>10-12oC) during summer and fall and produce large spring populations. Centropages spp, Temora, and Paracalanus are warm water species and are most abundant during late summer and fall. Oithona is plentiful throughout the GB/GOM region year round.
Fig. 6. Calanus finmarchicus abundance (log10(#/10m2) in the GB/GOM, mean 1977-1987, (MARMAP data redrawn from Meise and OReilly, 1998).
Calanus finmarchicus— This species spends the warmer months in a state of diapause as stage CV in cooler waters (5-7 oC) at depth in the GOM (Fig. 6). During late December, it emerges from diapause (mechanism unknown), swims to the surface and molts to adult. Subsequent egg production depends on availability of phytoplankton (Durbin et al., 2003), with the first generation born in late December-early January (Durbin et al., 1997). Generation time is ~2 months at the cold winter/spring temperatures (~5 oC), so G1 adults appear in March, and there is time for a total of 3 generations by the end of its growing season in July. Overwintering females produce eggs for a prolonged period, smearing out cohorts (Durbin and Casas, submitted). This annual cycle in the GB/GOM appears stable, having persisted for many decades (Bigelow, 1926; Clarke et al, 1946; Meise-Munns et al., 1991), but the extent to which this population is self-sustaining is unknown.
Fig. 7. Calanus finmarchicus abundance in the
Calanus finmarchicus is an open ocean species, occurring throughout the
northern North Atlantic from the eastern US to the Barents Sea, with centers of
population abundance in the Norwegian and
may well be that the resident diapausing GOM population is sufficient to
produce the large spring GOM/GB population. At the end of the growing season,
downward migrating diapausing CVs cannot reach their normal open ocean depths
of 500-2000m, and they become trapped in the GOM basins. A similar effect has been observed on
the SS basins (Sameoto and Herman, 1990) and for C. pacificus in the
Fig. 8. GLOBEC monthly mean Calanus abundance
on GB, showing abundance “hole”
Fig. 9. Pseudocalanus abundance in the GB/GOM. MARMAP bi-monthly means 1977-1987 (from McGillicuddy et al., 1998).
Although C. finmarchicus may be able to sustain itself in the GB/GOM system, it does not maintain itself on GB, since the bulk of the population disappears from the bank during the off-season (Fig. 6) and even during the growing season its abundance appears to be driven by GOM concentrations, with a well-defined “hole” in abundance in the center of the bank (Fig. 8, Durbin and Casas, submitted). This hole results from a combination of advection around the bank of the large GOM population and possibly high predation over the crest. A huge literature exists for C. finmarchicus egg production, development and growth as a function of food and temperature including several studies done as part of the GLOBEC GB process work (Campbell and Head, 2000; Campbell et al., 2001a,b; Runge et al. submitted). Such data can be incorporated into the population model for this species and used together with the large field data base to conduct targeted forward modeling to examine biological/physical processes controlling observed patterns.
Pseudocalanus spp.— Like Calanus, the growth season for Pseudocalanus is winter/spring (Fig. 9, 10). Its abundance is higher in shallower areas (<100m) and is highest in the crest region of the bank in June. Pseudocalanus does not overwinter in the GOM as does Calanus and is not normally present in the central Gulf during winter. This genus is an egg carrier and consequently has lower egg production and egg mortality rates (Corkett and McLaren, 1978; Ohman et al., 2002). Pseudocalanus in the GB/GOM
Fig. 10. GLOBEC data for Pseudocalanus
Fig. 11. A) Temora, B) Centropages hamatus C) Centropages typicus, D) Oithona similis. Mean monthly GLOBEC data for 1995-1999, A,B,D May; C January; log10(#/m3+1)
comprises two species: P. newmani and P. moultoni (Frost, 1989; McLaren et
al., 1989a; Bucklin et al., 1998, 2001; McGillicuddy and Bucklin, 2002). P. moultoni appears to be a colder water species and more abundant
during winter/spring, while P. newmani
is more plentiful during spring/summer (McLaren et al., 1989a,b). P.
moultoni is a coastal species and P.
newmani an offshore one (Frost, 1989).
Thus P. moultoni may be
carried onto the bank from western GOM coastal waters (e.g.,
Dominant Copepod Species —
Each dominant copepod species on GB has its own characteristic temporal-spatial
patterns and life histories (e.g.,
Fig. 12. Abundance trends in GB copepod, GLOBEC 1995-1999.
Abundance trends during the GLOBEC years — Abundance of the dominant copepod species, except Calanus, increased significantly during the five-year GLOBEC GB field program (Fig. 12.). While this trend may reflect a change toward smaller species, indicative of a warming trend, no concomitant increase in temperature was observed. These changes were negatively correlated with salinity (Durbin and Casas, submitted.). High abundances in 1999 appear to be related to a phytoplankton bloom that took place during winter in the central GOM, leading to high reproductive rates and abundances (Durbin et al 2003). The elevated abundances may have been advected onto GB. It is possible that low surface salinity during winter increased stability of the water column and led to the bloom. A negative correlation between salinity and chlorophyll on GB also was found at this time (Durbin and Casas, submitted), the reason for which is unknown. The proposed modeling work will examine the potential causes of the zooplankton increase and its relationship to large-scale forcing and climate change.
1.4. Available Data Sets
GLOBEC GB — The GLOBEC GB field program was conducted from 1995-1999 and included a combination of monthly broadscale and process-oriented cruises (GLOBEC, 1992; Wiebe et al, 2002). Broadscale cruises provided 3D maps of the plankton species based on net tows (1-m2 MOCNESS, Wiebe et al., 1985) at a set of 41 standard stations covering the bank and adjacent waters, and plankton pump sampling (Durbin et al 1997, 2000) at ~18 of the standard stations. CTD bottle casts were made at all stations. MOCNESS (0.15 mm mesh nets) zooplankton samples were collected from 0-15, 15-40 m, and 40-100 m or the bottom (if shallower than 100 m) and 100 m to the bottom or 450 m (if >100 m). Pump (0.035-mm nets) samples were collected over the same depth ranges as the MOCNESS in the upper water column but the maximum depth it was deployed to was 70-100 m depending on wind and tides, or to the bottom on shallower parts of the bank. For complete description of collection and processing methods see (Durbin et al. 1997; 2000). Samples were sorted, and processed data now are available for all life stages of Calanus finmarchicus and Pseudocalanus spp. (N1-N6, C1-Adult). For other copepod species life stages were sorted as adult males and females, copepodids, and nauplii. These data are stored in an Oracle database together with all of the CTD and chlorophyll data (http://globec.gso.uri.edu). The complete GLOBEC GB data set for broadscale zooplankton includes >3500 net samples (41 stations, 3 depths, 30 cruises), plus >1500 pump samples (18 stations, 3 depths, 30 cruises). In addition, vertically stratified data from several other cruises have been collected in deeper regions of the GOM.
Other Data Sets — Data from the bimonthly cruises of the
MARMAP program 1977-87 and its follow-on program, ECOMON (1992-present),
include shelf-wide distributions of hydrography and zooplankton (0.333mm
bongos). The complete data set is
available to us via an NMFS Oracle database (D. Mountain, pers. comm.) Although the zooplankton data are from
integrated hauls, these data cover a broader area than the GLOBEC GB data, and,
together with GLOBEC vertical data from deeper GOM, will allow us to
approximate 3D spatial patterns of each species throughout the GOM region. Further data from the GOM CPR transect,
1.5. Previous modeling
previous biological/physical models of the GB/GOM region have been
1.6. Combining existing models and data
Over the past decade, the GLOBEC GB program has acquired and processed an exceptional 5-year 3D data set of plankton and physical variables, while at the same time developing a high-resolution state-of-the-art prognostic 3D biological/physical model of this region (FVCOM). Data processing and model development recently have reached the point where they can be effectively combined. By the start of the proposed study, the FVCOM model will have been ported to a massively-parallel supercomputer. We now have the unique opportunity to use the data and model together to study the detailed mechanisms controlling zooplankton abundance patterns on GB, explicitly including boundary forcing determined by basin-scale dynamics.
have assembled a team of PIs who are leading experts on the plankton and
physical dynamics of this area.
Beardsley and Flagg are physical oceanographers with a long background
in this region. Chen is a physical oceanographer and developer of the FVCOM
model. Durbin is the scientist in charge of the broadscale data acquisition and
processing. Runge is an expert in
copepod biology specializing in Calanus
fertility and population dynamics.
Townsend is the lead scientist studying nutrient-plankton production in
the GB/GOM region.
2. Proposed Research
Working Hypothesis – The seasonal evolution of characteristic mean spatial abundance patterns of each dominant copepod species on GB is predictable from the interaction between its characteristic life-history traits and physical transport. These life-history traits include egg production, development, and growth rates (temperature/food dependent) as well as other traits such as vertical migration and diapause. Both the long-term, multi-year, mean and year-to-year variations in seasonal-spatial patterns are predictable by these interactions. Within this working hypothesis, we will address three specific null hypotheses:
H10: The abundance of copepod species on the bank is controlled by food availability (bottom-up control). Here we will examine the scenario that GB productivity, and thus food availability for the dominant copepod species, is controlled by nutrient input into the GOM through the NEC, which is determined by the intrusions of Labrador Slope Water versus Warm Slope Water. Alternative hypotheses include: 1) predatory control of copepod seasonal cycles (top-down control), 2) a combination of food-limitation and predation (time-space dependent), and 3) purely physical control by direct effects of temperature on vital rates or advection. In 3), we will examine causes of the observed increase in warm-water copepod species during the GLOBEC years (1995-1999).
Copepod populations on GB and/or the GOM region are not
self-sustaining. We will examine
the need for immigration from different sources to maintain the copepod
populations over multiple years.
Key source regions will be examined including the SS and SW. For self-sustainability on GB itself, we
will examine potential sources from the coastal regions (e.g.,
H30: Catastrophic global warming (e.g., total polar ice melt), parameterized as a lack of Labrador Sea water at the NEC, causes a regime shift on GB from cold-water copepod species to warm-water ones.
The overall goal of the proposed study is to understand the underlying biological-physical mechanisms controlling the seasonal development of spatial patterns of dominant copepod species on GB. Our specific objectives are: 1) to examine how local-dynamics and external forcing control the abundance of these species on GB, 2) to determine the degree to which top-down versus bottom up processes control the dominant copepod species on GB, and 3) to use existing state-of-the-art 3D physical/biological numerical models together with existing high-quality 3D data sets from the GLOBEC GB field program (and other historical data sets), to conduct targeted numerical experiments that explore the likelihood of the hypotheses listed above.
2.3.1. The Integrated Model System
The UMASSD-WHOI research
team has developed an integrated model system for the GOM/GB region (Fig. 13).
The major components of this system include: (1) the modified fifth-generation
community mesoscale atmospheric model (MM5), (2) the unstructured grid
MM5— The current version of the meteorological model
utilizes the fifth-generation mesoscale regional weather model (MM5) developed
by NCAR/Penn State (Dudhia et al., 2003; Grell et al., 1994) for community use.
MM5 uses NCAR/NCEP or ETA weather model fields as initial and boundary
conditions with two-way nesting capability, and can provide continuous
hindcasts and three-day forecasts. We have used MM5 to construct the surface
weather hindcast and forecast system for fishery studies in the GOM/GB (Chen et
al., 2004). This model (called GOM-MM5) is configured with a regional domain
GOM-MM5 is presently in operational use, with 3-day forecasts of the surface conditions, (including wind stress, heat flux, P-E) over the GOM/GB region posted on the SMAST website (http://www.smast.umassd.edu/research_projects/GB/mm5/mm5_eta/) for research, education, and public use. By this summer, we will complete the hindcast of the surface forcing fields with mesoscale (10-km) resolution covering the FVCOM domain for the 1995-1999 GLOBEC field period. This is the first calibrated mesoscale meteorological database built in the GLOBEC GB Phase 4 program.
is a prognostic, unstructured grid, finite-volume, free-surface, 3D primitive
equation coastal ocean circulation model (Chen et al., 2003; Chen et al.
2004a). In common with other coastal models, FVCOM uses the modified Mellor and
Yamada level 2.5 (MY-2.5) and Smagorinsky turbulent closure schemes for
vertical and horizontal mixing, respectively (Mellor and Yamada, 1982; Galperin
et al., 1988; Smagorinsky, 1963), and a sigma coordinate to follow bottom
topography. The General Ocean Turbulent Model (GOTM) developed by
Burchard’s research group in
FVCOM has been validated through direct comparison with analytical solutions for idealized cases (Chen et al., 2005b; Huang et al., 2005a-c) and other models for application in estuaries (Chen et al., 2005d-e; Huang et al., 2005d), inter-bays (Zhao et al., 2005) and the GOM/GB region (Chen et al, 2003b; Chen et al., 2005c). These studies show that different physical processes controlling currents and stratification in the coastal ocean have inherent time and space scales that must be carefully considered when determining model grid resolution for accurate simulation. This is particularly important with freshwater discharge, buoyancy-driven coastal plumes and currents, tidally-forced flows and upwelling, and fronts in the GOM/GB region (Chen et al 2005a). For example, model dye experiments made to simulate Houghton’s May/June 1999 dye dispersion observations on GB suggest that the horizontal resolution needed to resolve the diffusive flux is 500 m (Chen et al., 2005c). This resolution is also required to have a convergence solution of the tidal-induced residual current and buoyancy-induced current at the shelfbreak on GB (Chen et al., 2005b). These requirements will be used to refine the final FVCOM grid used in the proposed work. FVCOM has been used to hindcast currents and hydrography in the GOM/GB region for 1995 and 1999 using GOM-MM5 surface forcing, 4D data assimilation of 5-day averaged satellite SST and available moored current data, and open boundary conditions (Chen et al., 2003b). The model tidal currents compare very well with available surface elevation and current data, with overall uncertainties for the dominant M2 component of less than 3 cm in amplitude, 5° in phase, and 3 cm/s in the tidal current major axis (Chen et al., 2005c). The model subtidal currents and stratification also compare well with existing in-situ measurements, capturing the seasonal cycle in vertical stratification and increased around-bank circulation during June-September. These two hindcasts clearly illustrate significant short-term (daily to weekly) and long-term (seasonal and interannual) variability in the subtidal currents on GB. For example, surface winds in March 1999 were stronger and more variable than in 1995, resulting in stronger monthly-mean offbank near-surface flow in 1999 than in 1995 (Fig 15).
FVCOM Biological Module— Various ecosystem models have been implemented in FVCOM, including NPZ, NPZD, NPZDB, and water quality models. To make FVCOM more flexible for ecosystem studies, we have built a generalized biological module into FVCOM to allow users to select either a pre-built biological model (such as NPZ, NPZD, etc) or construct their own biological model using the pre-defined pool of biological variables and parameterization functions, including zooplankton life-stage models. This module acts like a platform that allows us to examine the relative importance of different physical and biological processes under well-calibrated physical fields.
Boundary Conditions— For this study, we plan to move the
“upstream” boundary of the GOM/GB FVCOM domain eastward to cut
across the SS and upper slope through Banquereau Bank. This choice simplifies
the cross-shelf bathymetry and separation of along-shelf flow into inner-shelf
and shelfbreak components (Han et al, 1997), and was used in the Hannah et al
(2001) model simulations of the seasonal circulation on the western and central
SS. They used the
We will not include the potential influence of warm core rings (eg., Flierl and Wroblewski, 1985) and other eddy features originating in the Gulf Stream (Fig. 1), because the larger regional and basin-scale models do not yet produce these features accurately enough in this region for us to use them to construct the boundary conditions along the open ocean part of FVCOM. The influence of rings may be minor (e.g., Churchill et al., 2003), however, and we will be able to infer their potential importance by their omission. As the larger-scale models mature in this respect, follow-on studies of these processes can be developed.
FVCOM Computational Aspects— With GLOBEC GB Phase 4 support, FVCOM has been converted into a FORTRAN 95/2K parallelized program to take advantage of multi-processor computing (Cowles et al., 2003). This implementation uses a SPMD (Single Program Multiple Data) approach with a message-passing model to perform the necessary inter-processor communication and synchronization. The physical domain is decomposed into sub-domains using the METIS graph partitioning libraries. Each sub-domain is assigned to a processor for integration of the model equations. The exchange subroutines utilize non-blocking sends and receive from the MPI (Message Passing Interface) 2.0 library. The efficiency of the code can be measured in terms of its speedup and/or scalability on a multiprocessor computer. Chen’s modeling lab will install a new high-performance 256-processor super-cluster computer this summer. With this computer, 1-yr model run with data assimilation and the existing GOM/GB FVCOM grid should take less than 1-day clocktime. We plan to use this computer with attached mass storage for the proposed Phase 4B model experiments (1995-1999 hindcasts and process studies), model/data comparisons, model result analysis and visualization, and archiving model output and results.
2.3.2. Biological Models
We will incorporate a copepod population model and a simple food web model (NPZ) into the plug-in modules of FVCOM. We will draw from our previous modeling work involving Calanus, Pseudocalanus, and other copepod species (Davis, 1984a,c, 1987; Lynch et al., 1998; McGillicuddy et al., 1998; Zakardjian et al., 2003), as well as our food web modeling (Davis, 1987b; Flierl and Davis, 1993; Lewis et al., 1994; Davis and Steele, 1994; Zeldis et al., 1995; Dadou et al. 1996; Ji, 2003, submitted a,b,c).
Copepod dynamics will be modeled using a stage-structured population model
containing 15 life stages (egg, N1-6, C1-3, C4M-F, C5M-F, Adult) plus
additional diapause stages (e.g. eggs or CV) as needed. A standard formulation for the stage-based
model will be used (e.g., Zakardjian
et al., 2003). A
potential problem with using only 15 life stages is artificial diffusion of
individuals through the life stages, and, to prevent this, age-within-stage
models have been developed (
Lower trophic level food web
model — We will explore the possibility of generating
temporally evolving 3D phytoplankton fields from a lower trophic level food web
model (e.g. NPZ or NPZD) to provide food for the copepod population model. We will use one-way coupling whereby the
copepods depend on the food field but do not affect it (e.g. Carlotti, 1998;
Batchelder et al., 2002). In this
case, the Z will represent microzooplankton grazers used solely as a closure
term. We can generate realistic 3D
phytoplankton fields using a simple NPZ model (Ji, 2003). It may also be possible to allow the
copepods to graze the P and Z (e.g., Carlotti, 1996), but this approach may not
be necessary or feasible in 3D. The
NPZ model will be adjusted so that the resulting fields approximate the 3D
chlorophyll and satellite data. The
concept of using an NPZ model to generate spatially explicit prey fields has
been used with an IBM of larval pollock in the
Plankton food web models are variously complex, ranging from simple NPZ to models with multiple subcomponents. In the GOM/GB a simple NPZ (Klein, 1987; Lewis et al., 1994; Franks and Chen, 1996; Franks and Chen, 2001) and a nine-compartment model (Ji, 2003) have been used. The NPZ model coupled with a 3-D nonlinear, primitive equation, finite-difference ocean circulation model (ECOM-si, Blumberg and Mellor, 1987) can successfully approximate 3D phytoplankton fields observed on GB from summer cruises and satellite data. Robust features, such as the subsurface maximum and mixing-front induced productivity were produced with this model (Franks and Chen, 2001). More recently, a nine-compartment model (Ji, 2003), coupled to ECOM_si and FVCOM, captured the basic seasonal and spatial patterns of nutrients and phytoplankton on GB. This model includes 3-N (nitrate, ammonia and silicate), 2-P (large and small), 2-Z (large and small), and two detrital pools (N and Si). Silicate can limit the spring diatom bloom on GB (Townsend and Thomas, 2001; Townsend and Thomas, 2002, Ji, 2003).
In the proposed study, the simple NPZ model will be used due to its capability and robustness, as well as the availability of observation data for the initial and boundary conditions. We also will explore the use of separate pools in the model for Si and N and for P (diatom, non-diatom). The model will run continuously for 3 years from January 1997 to December 1999, a period when we have both nutrient and phytoplankton data from the GLOBEC GB program. Initial horizontal distributions of nitrogen, phytoplankton and zooplankton during winter will be derived from climatological data (e.g. Petrie and Yeats, 2003), satellite imagery and MARMAP data, respectively. An initial homogenous vertical distribution also will be specified (as observed in winter). While the NPZ model is being tested against the observed data, these same data will be used to generate spatially and temporally interpolated 3D static prey fields for the copepod population model. This empirical approach is complementary to the model-based approach.
data – Biological
data for the SS and SW will be obtained from our Canadian colleagues, who
have been actively involved in the GB and Canadian GLOBEC programs as well as
in other studies of the SS and
Biological transport — We will use concentration-based (Eulerian) rather than individual-based (Lagrangian) transport for the copepod and food web models. While we have used both types of models in the past, the use of concentration-based models allow us to compute fluxes and mass balances directly and more accurately. This approach is necessary for quantifying such factors as sustainability of populations in particular areas. The concentration-based approach lends itself easily to stage-structured population models. This straightforward method avoids the necessity of using super-individual particles or spawning and removing particles at each time step.
2.3.3. Numerical experiments
We will conduct a series of targeted numerical experiments using prognostic forward model runs (rather than inverse methods) to address each of the above hypotheses. Data and model will be compared using a maximum-likelihood method (Stock, 2005; Stock et al., submitted). These process studies will help interpret the basic behavior and inter-annual variability shown in the 1995-99 hindcast. Detailed tasks and time table for this work are given in the required supplement on project management and data exchange.
Working hypothesis— We will initialize the model with the mean winter concentrations of each copepod species (in separate model runs). The same model structure will be used for all species, changing only the parameter values (temperature/food/life-stage dependent egg production rate, development rate, growth rate, and normalized stage-dependent mortality) and behaviors, and thus expediting the model runs. The inputs of characteristic life history traits of each species together with its initial abundance patterns should generate its observed characteristic seasonal/spatial patterns. The model will be run for a complete annual cycle and compared with the 5-year monthly mean abundance patterns. To examine inter-annual variation we will model each copepod species during the complete 5-year GLOBEC period 1995-1999, first year by year, then continuously over the 5 years. The result will be a complete 5-year biological/physical hindcast.
Food versus Predation— We will examine the degree of food-dependence and mortality with regard to inter-annual variability for each species. First we will confirm that the NPZ model can be used to approximate the 3D distribution of phytoplankton for the multi-year monthly mean and year-to-year changes. In parallel, we will use fixed 3D phytoplankton fields approximated from monthly averaged satellite and in situ data. We will interpolate the phytoplankton fields between monthly values to avoid discontinuities. We will use the NPZ model together with scenarios of salinity and nutrient (N, Si) input through the NEC, to determine the extent to which phytoplankton biomass/production on GB is determined by this forcing and the extent to which the copepod species are affected by it. We will examine possible effects of temperature and transport during 1995-1999 on the trends in mean abundances of each species.
Self-sustainabilty— We will initialize the model with the observed distribution of each species and exclude input from other regions, to determine whether the local population is self-sustaining. In particular we will examine the importance of Calanus input from SW and/or SS to the GOM/GB population, the input of Pseudocalanus from western GOM to the GB population, the key source regions for Oithona similis, and whether Centropages typicus depends on immigration to sustain its population on GB. We will further examine whether resting eggs can explain high abundance of Centropages hamatus and Temora longicornis on the crest of GB. We will initialize the population as resting eggs on the crest and determine whether the resulting plume of nauplii and subsequent copepodids matches the observed distributions. We will examine the formation of the Calanus “hole” on GB by initializing with CVs in the GOM during December and determining the extent to which the hole forms as a result of gradient advection versus high crest mortality.
Catastrophic global warming— Finally we will use boundary forcing that represents a scenario of catastrophic warming (see FVCOM section). We will run the model for single and multiple years to determine the impact on the NPZ fields and on each dominant copepod species.
2.3.4. Work schedule— The schedule for the proposed modeling work together with a description of individual tasks, project management, dissemination, and timeline are described in the required supplemental documents.
3. Significance of Proposed Research– Intellectual Merit
The proposed work will provide new insights into the role of local dynamics and large-scale forcing in controlling population dynamics of marine copepods. We believe that the physical/biological model resulting from the proposed work will be a legacy of the Georges Bank GLOBEC program by providing a valuable tool that subsequent researchers can use to study the dynamics of this system in hindcast, nowcast, and forecast modes. The results of the targeted experiments will provide insights into the degree of bottom-up and top-down control and the degree of sustainability of copepod populations under different conditions of external forcing. The work will provide a new understanding of the impact of basin-scale forcing, including catastrophic change, on local-scale plankton dynamics. The resulting spatially explicit model of small and large copepod species will provide dynamic prey fields for concurrent and subsequent larval fish modeling studies, leading to a better understanding of recruitment in fish populations.
4. Broader Impacts
Ban, S., H.
Lee, A. Shinada, and T. Toda. 2000. In situ egg production and hatching success of the marine copepod Pseudocalanus
H. B. 1926. Plankton of the offshore waters of the
A., A. M. Bentley and S. P. Franzen. 1998. Distribution and relative abundance
of the copepods Pseudocalanus moultoni and P. newmani on
A., M. Guarnieri, D. J. McGillicuddy and R. S. Hill. 2001. Spring-summer
evolution of Pseudocalanusspp. abundance of
H., 2002. Applied turbulence modeling in marine waters. Springer:
R W, Head E J H 2000 Egg production rates of Calanus finmarchicus in the western
F. and G. Radach, 1996. Seasonal dynamics of phytoplankton and Calanus finmarchicus in the
Carlotti, F. and K.U. Wolf, 1998. A Lagrangian ensemble model of Calanus finmarchicus coupled with a 1-D ecosystem model. Fish. Oceanogr., 7, 191-204.
Chen, C, G. Cowles and R. C. Beardsley, 2004a. An unstructured grid, finite-volume coastal ocean model: FVCOM User Manual. SMAST/UMASSD Technical Report-04-0601, pp183.
and R. C. Beardsley. 1998. Tidal mixing over finite-amplitude banks: a model
study with application to
Chen, C., H. Liu, and R. Beardsley, 2003a. An unstructured grid, finite-volume, three-dimensional, primitive equations ocean model: Application to coastal ocean and estuaries. Journal of Atmospheric and Ocean Technology, 20 (1), 159–186.
Chen, C., H. Liu, R. C. Beardsley, G. Cowles, J. Pringle, R. Schlitz, and B. Rothschild, 2003b. Application of FVCOM to the Gulf of Maine/Georges Bank: Simulated and assimilated modeling studies of stratification and subtidal circulation. EOS Trans, AGU, 84(52), Ocean Science Meeting Suppl., Abstract OS51G-08.
Chen, C., J. Qi, H. Liu, C. Li, H. Lin, R. Walker and K. Gates, 2005d. Tidal Flushing Dynamics in the Satilla River, Georgia: A Comparison between FVCOM and ECOM-si. Journal of Geophysical Research, to be submitted.
C., Q. Xu, R. C. Beardsley, and P. J. S. Franks., 2003. Modeling Studies of the
Cross-Frontal Water Exchange on
Chen, C., R. C. Beardsley, H. Huang, H. Liu, and Q. Xu, 2005b. A finite-volume numerical approach for coastal ocean studies: Comparisons with the finite-difference models. Journal of Geophysical Research, in revision.
C., R. C. Beardsley, Q. Xu, G. Cowles, and R. Limeburner, 2005c. Tidal Dynamics
C., R. Houghton, R. C. Beardsley, Q. Xu, and H. Liu, 2003c. Preliminary results
of model dye experiments on
Chen, C., Wang, T, L. Wang, J. Blanton, C. Li, H. Huang
and H. Lin, 2005e. Tidal-induced flushing
process over the estuarine-tidal creek-salt marsh complex of the
Okatee/Collection River in
C., Z. Wu, R. C. Beardsley, S. Shu, and C. Xu, 2005a. Using MM5 to hindcast the
ocean surface forcing fields over the
Churchill, J. H., J. P. Manning, and R. C.
Beardsley, 2003. Slope water
Clarke, G.L., 1946. Dynamics of production in a marine area. Ecol. Monogr. 16, 321–337.
Cohen, E. B., and M. D. Grosslein. 1987. Production on Georges Bank Compared with other shelf ecosystems. Pp. 383–391, In R.H. Backus and D.W. Bourne (eds.) Georges Bank. MIT Press. Cambridge, MA. 593 pp.
C J, and
D. H. and J. J. Walsh. 1976. The Ecology of the Seas.
Davis, C. S. 1983. Laboratory rearing of marine calanoid copepods. J. Exp. Mar. Biol. Ecol., 71, 119-133.
C. S. 1984a. Predatory control of copepod seasonal cycles on
C. S. 1984b. Food concentrations on
C. S. 1984c. Interaction of a copepod population with the mean circulation on
Davis, C. S. 1987a. Components of the zooplankton production cycle in the temperate ocean. J. Mar. Res., 45, 947-983.
C. S. 1987b. Zooplankton Life Cycles.
pp. 256-267. In:
Davis, C. S. and J. H. Steele. 1994. Modeling upper ocean biological-physical processes. URIP Workshop Report, WHOI TECH RPT 94-32, 65 pp.
K. F., D. B. Mountain, and A. Herman.
2003. Variability in the Slope Water Properties off
J., D. Gill, K. Manning, W. Wang, C. Bruyere, J. Wilson, and S. Kelly, 2003:
PSU/NCAR mesoscale modeling system tutorial class notes and user’s guide,
MM5 modeling system version 3, Mesoscale and Microscale Meteorology Division,
Durbin, E. G., J. A. Runge, R. G. Campbell, P. R. Garrahan, M. C. Cascas and S. Plourde. 1997. Late fall-early winter recruitment of Calanus finmarchicus on Georges Bank., Mar. Ecol. Prog. Ser., 151, 103-14.
E.G., Garrahan, P.R., Casas, M.C. 2000. Abundance and distribution of Calanus
E.G., M.C. Casas. Abundance, spatial distribution, and interannual variability
of copepods on
E.G., R. Campbell, M. Casas, B. Niehoff, J. Runge, M. Wagner. 2003. Interannual
Variation in phytoplankton blooms and zooplankton productivity and abundance in
Dzierzbicka-Glowacka, L. 2004. Growth and development of copepodite stages of Pseudocalanus spp., J. Plankton Res., 26, 49-60.
Fairall, C. W., E. F. Bradley, D. P. Rogers, J. B. Edson, and G. S. Young, 1996. Bulk parameterization of air-sea fluxes for tropic ocean global atmosphere coupled-ocean atmosphere response experiment. Journal of Geophysical Research, 101 (C2), 3747-3764.
Fairall, C. W., E. F. Bradley, J.E. Hare, A.A. Grachev, and J. B. Edson, 2003. Bulk parameterization of air-sea fluxes: updates and verification for the COARE algorithm. J. Climate, 16, 571-590.
G. R. and C. S. Davis. 1993.
Biological effects of
and Wroblewski, J.S. 1985. The
possible influence of warm core
P.J.S. and C. Chen, 1996. Plankton
production in tidal fronts: A model of
P.J.S. and C. Chen, 2001. A 3-D
prognostic numerical model study of the
Fratantoni, P. S. and R. S. Pickart, 2005a. The
Fratantoni, P. S. and R. S. Pickart, 2005b.
Structure and alongstream evolution of the shelfbreak jet in the western
Frost B W. 1989. A taxonomy of the marine calanoic copepod genus Pseudocalanus. Can J Zool 67: 525±551
Galperin, B., L. H. Kantha, S. Hassid, and A. Rosati, 1988. A quasi-equilibrium turbulent energy model for geophysical flows. Journal of the Atmospheric Sciences, 45, 55–62.
GLOBEC, 1991a. U. S. GLOBEC: Initial Science Plan, Report Number 1.
1991b. U. S. GLOBEC:
1992. U. S. GLOBEC:
GLOBEC, 1996. U. S. GLOBEC: Northeast Pacific Implementation Plan, Report No. 17.
GLOBEC, 1997. U. S. GLOBEC: Workshop on Modeling the Southern Ocean Ecosystem, Report No. 18.
2000. GLOBEC in the
Grell, G. A., J. Dudhia, and D. R. Stauffer, 1994: A description of the Fifth-Generation Penn State/NCAR Mesoscale Model (MM5). NCAR Technical Note, NCAR/TN 398+STR, 117pp.
M. S., and R. C. Hennemuth, 1973.
Spawning stock and other factors related to recruitment of haddock on
Hall, D. J. 1964. An experimental approach to the dynamics of a natural population of Daphnia galeata mendotae . Ecology 45 (1), 94-112.
Han, G., C. E. Hannah, J. W. Loder, and P. C. Smith, 1997. Seasonal variation of the three-dimensional mean circulation over the Scotian Shelf. J. Geophysical Research, 102(C1), 1011-1025.
Hannah, C. G., J. A. Shore, J. W. Loder, and C. E. Naimie, 2001. Seasonal circulation on the western and central Scotian Shelf. J. Phys. Oceanography, 31(2), 591-615.
C.G., Naimie, C.E., Loder, J.W., Werner, F.E. 1998 Upper-ocean transport
mechanisms from the
Head, E.J.H., Harris, L.R., Petrie, B., 1999. Distribution of Calanus spp. on and around the Nova Scotia Shelf in April: evidence for an offshore source of Calanus finmarchicus to the central and western regions. Canadian Journal of Aquatic Sciences 56, 2463-2476.
M.R., Backhaus, J.O., Richardson, K., McKenzie, E., Slagstad, D., Beare, D.,
Dunn, J., Fraser, J.G., Gallego, A., Hainbucher, D., Hay, S., Jónasdóttir,
S., Madden, H., Mardaljevic, J., Schacht, A., 1999. Climate fluctuations and
the spring invasion of the
Hermann, A. J., S. Hinckley, B. A. Megrey and J. M. Napp. 2001 Applied and theoretical considerations for constructing spatially explicit individual-based models of marine larval fish that include multiple trophic levels, ICES J. Mar. Sci. 58:1030-1041
Hinrichsen, H.H., C.
Möllmann, R. Voss, F.W. Köster, and G. Kornilovs. 2002. Biophysical modeling
of larval Baltic cod (Gadus morhua) growth and survival.
. 1914. Fluctuations in the great fisheries of
H., C. Chen, G. Cowles, R. C. Beardsley, and K. Hedstrom, 2005a. Sensitivity of
the numerical solution to unstructured triangular grids: A validation
experiment of FVCOM for the Rossby equatorial soliton.
Huang, H., C. Chen, J. O. Blanton, and F. A. Andrade, 2005d. Tidal current asymmetry and implication to variability of the dissolved oxygen over shallow tidal creeks: an application of FVCOM to the Okatee River, South Carolina. Journal of Geophysical Reseqarch, to be submitted.
Huang, H., C. Chen, R. C. Beardsley, and K. Hedstrom, 2005c. Validation experiments of FVCOM for the wind-driven flow in an elongated rotating basin: A comparison with analytical solution. Deep Sea Research II-GLOBEC/GB special issue, to be submitted.
H., C. Chen, R. C. Beardsley, and K. Hedstrom. 2005b. Capability and Accuracy
of the unstructured grid model to simulate the coastal hydraulic jump: A
validation experiment of FVCOM via horizontal advection schemes.
Ji, R., 2003. Biological and physical processes controlling the
spring phytoplankton bloom dynamics on
C. Chen, P. J. S. Franks, D.W. Townsend, E.G. Durbin, R. C. Beardsley, R.G.
Lough, and R.W. Houghton, 2004. Spring bloom and associated lower trophic level
food web dynamics on
C. Chen, P. J. S. Franks, D.W. Townsend, E.G. Durbin, R. C. Beardsley, R.G.
Lough, and R.W. Houghton, 2004. Effects of topography and tidal mixing front on
the spring phytoplankton bloom on
C. Chen, P. J. S. Franks, D.W. Townsend, E.G. Durbin, R. C. Beardsley, R.G.
Lough, and R.W. Houghton, 2004. The impact of Scotian Shelf Water
“cross-over” on the plankton dynamics on
C., J. Pringle, and C. Chen.
Transport and retention of dormant copepods in the
Klein Breteler WCM, Fransz HG, Gonzalez SR (1982)
Growth and development of four calanoid copepod species under experimental and
Klein Breteler WCM, Gonzalez SR (1986) Culture and development of Temora longicornis (Copepoda, Calanoida) at different conditions of temperature and food. Syllogeus 58:71–84
Klein Breteler WCM, Gonzalez SR, Schogt N (1995) Development of Pseudocalanus elongatus (Copepoda, Calanoida) cultured at different temperature and food conditions. Mar Ecol Prog Ser 119:99–110
1987. A simulation of some physical
and biological interactions.
Lee, H., S. Ban, T. Ikeda and T. Matsuishi. 2003. Effect of temperature on development, growth and reproduction in the marine copepod Pseudocalanus newmani at satiating food condition. J. Plankton Res. 25, 261-271.
C. V. W., C. Chen, and C. S. Davis. 2001. Variability in wind forcing and its
effect on circulation and plankton transport over
Lewis, C. V., C. S. Davis, and G. Gawarkiewcz. 1994. Wind-forced biological-physical dynamics on an isolated off-shore bank. Deep-Sea Res. 41, 51–73.
D. J. McGillicuddy, E. G. Durbin, P. H. Wiebe. Biological control of the vernal
population increase of Calanus
Lindeman, R. L. 1942. The trophic-dynamic aspect of ecology. Ecology, 23, 399-418.
J A, and H G Hunt. 1989. The
distribution of Labidocera wollastoni
and Centropages hamatus in the
JA 1990 Distribution of overwintering calanoid copepods eggs in sea bed
sediments around southern
R. G., and D. G. Mountain. 1996. Effect of small-scale turbulence on feeding
rates of larval cod and haddock in stratified water on
R.G., E. M. Caldarone, L. J. Buckley, E. A. Broughton, M. E. Kiladis, and B. R.
Burns, 1996. Vertical distribution of cod and haddock eggs and larvae feeding
and condition in stratified and mixed waters on southern
D. R., Gentleman, W. C., McGillicuddy, D. J. and C. S. Davis, 1998. Biological/
physical simulations of Calanus
finmarchicus population dynamics in the
F., J.A. Runge, B. Zakardjian and P. Joly. 2005. Egg production and hatching
success of Temora longicornis (Copepoda,
Calanoida) in the southern
Marcus, N. 1996. Ecological and evolutionary significance of resting eggs in marine copepods: past, present, and future studies. Hydrobiologia, 320: 141–152.
N. H. and R. V. Lutz. 1998. Longevity of subitaneous and diapause eggs of Centropages hamatus (Copepoda: Calanoida)
from the northern
D. J. Jr. and A. Bucklin. 2002. Intermingling of two Pseudocalanus species
D. J., D. R. Lynch, A. M. Moore, W. C. Gentleman, C. S. Davis, and C. J. Meise.
1998. An adjoint data assimilation approach to the diagnosis of physical and
biological controls on Pseudocalanus
spp. populations in the
McLaren IA, Laberge E, Corkett CJ, Sevigny J-M 1989a Life cycles of four species of Pseudocalanus in Nova Scotia. Can J Zool 67: 552-558
C.J. and J. E. O'Reilly, 1996. Spatial and seasonal patterns in abundance and
age-composition of Calanus finmarchicus in the
C., J. Green, M. Ingham, and D. Mountain, 1990. Interannual variability in the copepod
populations of Georges Bank and the western
Mellor, G. L. and T. Yamada, 1982. Development of a turbulence closure model for geophysical fluid problem. Reviews of Geophysics and Space. Physics, 20, 851–875.
Miller, C. B., T. J. Cowles, P. H. Wiebe, N. J. Copley, and H. Grigg, 1991. Phenology in Calanus finmarchicus: Hypotheses about control mechanisms, Mar. Ecol. Progr. Ser., 72, 79-91,.
C.B., Lynch, D.R., Carlotti, F., Gentleman,W., Lewis,V.W., 1998. Coupling of an
individual-based population dynamic model of Calanus finmarchicus to a
circulation model for the
Nixon, S. W. 1988. Physical energy inputs and the comparative ecology of lake and marine ecosystems. Limnol. Oceanogr., 33, 1005-1025
T. 1957. Trophic structure and productivity of
Ohman, M. D., J. A. Runge, E. G. Durbin, D. B. Field and B. Niehoff. 2002. On birth and death in the sea. Hydrobiol., 480, 55-68.
K. E. and D. M. Checkley. 1997. Seasonal variations in a deep aggregation of Calanus
pacificus in the
B. and P. Yeats, 2000. Annual and
interannual variability of nutrients and their estimated fluxes in the Scotian
Plourde, S., and J. A. Runge. 1993. Reproduction of the planktonic copepod, Calanus finmarchicus, in the Lower St. Lawrence Estuary: Relation to the cycle of phytoplankton production and evidence for a Calanus pump, Mar.\ Ecol. Progr. Ser., 102, 217-227.
J.A., S. Plourde, P. Joly, E.
Durbin and B. Niehoff.
Characteristics of egg production of the planktonic copepod, Calanus finmarchicus, on
Sabatini, M. and Kiørboe,T. 1994. Egg production, growth and development of the cyclopoid copepod Oithona similis. J. Plankton Res., 16, 1329–1351.
J. L., R. Slater, M. J. R. Fasham, H. W. Ducklow, J. R. Toggeweiler and G. T.
Evans, 1993. A seasonal three-dimensional ecosystem model of nitrogen cycling
Saumweber, W. J. and E. G. Durbin. The implications of energetic limitation for diapausing Calanus finmarchicus: Towards a Gulf of Maine Calanus budget. submitted to Deep Sea Res. II
M. P., E. B. Cohen, and M. D. Grosslein, 1984. Structure of the
Smagorinsky, J., 1963. General circulation experiments with the primitive equations, I. The basic experi-ment. Monthly Weather Review, 91, 99–164.
P.C., R.W. Houghton, R.G. Fairbanks, and
J. H., 1974. The Structure of Marine Ecosystems.
C. A., 2005. Testing hypotheses concerning the Initiation and development of
blooms of the toxic dinoflagellate Alexandrium fundyense in the western
Sundby, S. 2000. Recruitment of Atlantic cod stocks in relation to temperature and advection of copepod populations. Sarsia, 85, 277-298.
M. 1962. Energy Flow in the Salt Marsh Ecosystem of
D.W. and A.C. Thomas, 2001. Winter-spring transition of phytoplankton
chlorophyll and inorganic nutrients on
D.W. and M. Thomas, 2002.
Springtime nutrient and phytoplankton dynamics on
Townsend, D.W. and N.R. Pettigrew. 1997. Nitrogen limitation of secondary
Townsend, D.W.,A.C. Thomas, L.M. Mayer, M. Thomas and
J. Quinlan. 2004. Oceanography of the
J. T. 2004. The importance of small planktonic copepods
roles in pelagic marine food webs. Zoological Studies, 43, 255-266.
Wiebe, P. H., R. Beardsley, D. Mountain, and A. Bucklin. 2002. U.S. GLOBEC Northwest Atlantic/Georges Bank Program, Oceanography, 15, 12-29.
Wiebe, P.H., A.W. Morton, A.M. Bradley, R.H. Backus, J.E. Craddock, T.J. Cowles, V.A.Barber, and G.R. Flierl. 1985. New developments in the MOCNESS, an apparatus for sampling zooplankton and micronekton. Mar. Biol. 87: 313-323.
Zakardjian, Bruno. A., J. Sheng, J. A. Runge, I.
McLaren, S. Plourde, K. R. Thompson, and Y. Gratton . 2003. Effects of
temperature and circulation on the population dynamics of Calanus
finmarchicus in the
Zeldis, J. R., C. S. Davis, M. R. James, S. L. Ballara, W. E. Booth, and F. H. Chang. 1995. Salp grazing in a larval fish habitat: effects on phytoplankton abundance, vertical distribution, and species composition. Mar. Ecol. Prog. Ser., 126, 267–283.
L., C. Chen, and B. Rothschild, 2005. Tidal dynamics and eddy shedding in the
 We note that several groups of other investigators (e.g., J. Wilkens and D. Haidvogel at Rutgers and D. Wright, C. Hannah, and others at BIO) are examining how well existing North Atlantic large regional (the Rutgers Northeast North Atlantic ROMs) and basin-scale (e.g., HYCOM, MERCATOR, OPA, POP3) models can hindcast observed physical conditions over the Northeast America continental margin between Cape Hatteras and the Grand Banks. In particular, Loder and co-workers at BIO have just completed a long-term moored array study over the Scotian slope and the ongoing physical/biological transect data being collected in AZMP both provide an extensive data set for detailed comparison with large-scale model hindcasts. We will follow their work closely during Phase 4B to help determine to what extent these larger-scale models can provide accurate boundary conditions along the North American Atlantic margin, including the shelfbreak/slope current system and the influence of Gulf Stream eddies and warm-core rings as they move along the margin, with the idea of using this capability when proven to drive our regional FVCOM integrated model system in future studies.