Life history and biogeography of Calanus copepods in the Arctic Ocean: An
individual-based modeling study
Rubao Ji1, Carin Ashjian1, Robert Campbell2, Changsheng Chen3, Guoping Gao3, Cabell
Davis1, Geoffery Cowles3, Robert Beardsley1
1
Woods Hole Oceanographic Institution, MS # 33, Woods Hole, MA 02543, USA. Email: rji@whoi.edu
2
Graduate School of Oceanography, University of Rhode Island, Narragansett, RI, 02882,
USA
3
University of Massachusetts Dartmouth, School for Marine Science and Technology,
New Bedford, MA 02744, USA
Abstract: Calanus spp. copepods play a key role in the Arctic pelagic ecosystem.
Among four congeneric species of Calanus found in the Arctic Ocean and its marginal
seas, two are expatriates in the Arctic (C. finmarchicus and C. marshallae) and two are
endemic (C. glacialis and C. hyperboreus). The biogeography of these species likely is
controlled by the interactions of their life history traits and physical environment. A
mechanistic understanding of these interactions is critical to predicting their future
responses to a warming environment. Using a 3-D individual-based model, we show that
1) C. finmarchicus is unable to penetrate into the Arctic Ocean under present conditions
of temperature, food availability, and length of the growing season, mainly due to
insufficient time to reach its diapausing stage and slow transport of the copepods into the
Arctic Ocean during the growing season or even during the following winter, at the
depths the copepods are believed to diapause. 2) For the two endemic species, the model
suggests that their capability of diapausing at earlier copepodite stages and utilizing icealgae as a food source (thus prolonging the growth season length) contribute to the
population sustainability in the Arctic Ocean. 3) The inability of C. hyperboreus to
attain diapause in the central basin, as demonstrated by the model, contradicts field
observations and suggests that our current estimation of either the growth parameters or
the growing season length (based on empirical assessment or literature) needs to be
further evaluated.
1. Introduction
Calanus copepods play a key role in the Arctic pelagic ecosystem. When their
biomass is high they can exert a significant impact on the primary production retaining
much of the production in the pelagic food webs (refs). In contrast, most of the primary
production is exported to the benthos when biomass is low (Grebmeier et al., 2006;
Campbell et al., submitted). Due to their large body size and high lipid content, Calanus
are an important high-quality food source for pelagic fish species such as capelin,
herring, and pollack and they can also be an important part of the diet for larval and
juvenile demersal fishes (e.g. cod) as well (refs). Hence, the Calanus species are critical
components of the carbon cycle on Arctic shelves and basins and dictate to a large degree
the extent of pelagic-benthic coupling and the composition of the pelagic ecosystem.
Four congeneric species of Calanus are found in the Arctic Ocean and its marginal
seas, two are expatriates in the Arctic (C. finmarchicus and C. marshallae) and two are
endemic (C. glacialis and C. hyperboreus). For the endemic species, C. glacialis
dominates on the shelves and slopes (refs) while C. hyperboreus is most important in the
deeper basin regions (refs). Both these species can reproduce and grow in the extremely
cold Arctic waters. The population centers of the expatriate species occur in more
southerly waters. C. finmarchicus is advected into the Barents Sea from the Norwegian
Sea and into the Arctic Basin through Fram Strait (Jaschnov, 1970; other refs )and C.
marshallae, if it does enter the Arctic, passes through Bering Strait from the northern
Bering Sea (Frost 1974, Springer et al. 1989, Plourde et al. 2005). Both these species are
better adapted to warmer water conditions than those found in the Arctic Ocean proper.
Biogeogrpahy of copepods, as of many other ectothermic animal species in the ocean,
is strongly affected by temperature tolerance window they can adapt in order sustain
reproduction success and other life functions. However, temperature is certainly not the
only factor. Other environmental factors such as food availability can also be critical, as
well as the life history traits of organisms including development and reproduction
strategies under certain temperature and food conditions. For a Calanus population to
complete a life cycle in the Arctic Ocean, it is necessary that individuals reach a life stage
where diapause can be initiated for overwintering before the end of the growing season
when the food concentration drops below certain threshold. Therefore, even if
temperature and food do not affect the reproductive success, species like C. finmarchicus
may still not able to colonize the Arctic Ocean, simply because development rate under
low-temperature and low-food environment is too slow to reach C5 and store enough
lipid for overwinter. These dynamics could be altered as the environmental conditions
change in the Arctic and marginal seas.
The Arctic is particularly susceptible to climate warming, seen most clearly in the
recent seasonal ice retreat in the western Arctic (Serreze et al., 2003; Stroeve et al.,
2005). It has been predicted that seasonal ice cover in the Arctic Basin could essentially
disappear by ~2040 (Holland et al., 2006).
Warming sea surface temperature and
decreasing seasonal ice cover could enhance phytoplankton production and provide better
growth conditions for C. finmarchicus, making it possible for C. finmarchicus to expand
their range from the northern North Atlantic further into the Arctic and its marginal seas.
Meanwhile, for the endemic species like C. glacialis, who may rely on ice algae to gain
energy to start reproduction process in the beginning of growth season, will be negatively
affected due to the loss of the sea ice and associated algae production. This change of
Calanus species composition might cause a regime shift of ecosystem structure and
function due to the trophic importance of Calanus populations in the Arctic Ocean.
Although such a shift is not yet evident in the Arctic system (refs?), a similar shift has
been observed in the North Sea, where fluctuations in the plankton, primarily a shift in
the abundance of C. finmarchicus to its warmer water congener C. helgolandicus, has led,
through bottom up control to long-term changes in Atlantic cod recruitment (Beaugrand
2003).
It is essential to understand how the combinations of life history, physical advection,
seasonality, and food environment limits the ranges of Calanus populations before we
can assess how climate change might cause the shift of its biogeographic boundaries in
the Arctic Ocean and marginal seas. This is a challenging question mainly due to the
multiple processes involved in controlling the biogeography and limited observational
data available for detailed analysis. In this paper, we present results from a biologicalphysical coupled model to explore factors that control Calanus population dynamics and
biogeographic boundaries in the Arctic Ocean and marginal seas, and to provide base for
further investigating the impacts of various climate warming scenarios on the
biogeography.
2. Material and methods
2.1. Physical model
The physical model used to drive biological model is an updated Arctic Ocean FiniteVolume Community Ocean Model (AO-FVCOM) (Chen et al., 2009). AO-FVCOM was
developed based on the spherical coordinate, semi-implicit version of FVCOM with a full
coupling of an Unstructured Grid version of the Los Alamos sea ice model Community
Ice CodE (UG-CICE) (Gao et al., 2010; Hunke and Lipscomb, 2006). The computational
domain covers the Pan-Arctic region shown in Fig 1. The non-overlapped triangular grid
is used in the horizontal and a hybrid coordinate in the vertical. The horizontal resolution
varies in a range of 10-50 km and the vertical resolution depends on water depth. The
water column has a total of 45 layers. In regions deeper than 225 m, the s-coordinate is
chosen, with ten and five uniform layers specified near the surface and bottom,
respectively. The thickness of each layer is 5 m. In a shallower shelf region of  225, the
-coordinate is used, which provides a vertical resolution of 5 m or less. These two
coordinates merge at the 225-m isobath, where all layers have a uniform thickness of 5
m.
In this study, AO-FVCOM was driven by 1) astronomic tidal forcing constructed
eight tidal constituents (M2, S2, N2, K2, K1, P1, O1 and Q1), 2) the surface wind stress, 3)
the net heat flux at the surface plus shortwave irradiance in the water column, 4) the air
pressure gradient, 5) precipitation minus evaporation, and 6) river discharges. The
meteorological forcing data represent climatologically averaged fields over 1978-1994
and the data are from the database (version 6) of the Arctic Ocean Modeling
Intercomparison Project (AOMIP) derived from the ECMWF reanalysis ERA-15. The
river discharge along the US and Canada coast was specified by the daily climatologic
mean from USGS monitoring sites (on the website: http://www.usgs.gov and
www.ec.gc.ca), while the data outside the US and Canada coast was provided by L. F.
Smedstad at Navy Coastal Ocean Modeling (NCOM) Group. AO-FVCOM ran through
nesting to the Global-FVCOM under the same forcing condition, which provides the
surface elevation, currents, water temperature/salinity and mixing coefficients at the open
boundaries. The Global-FVCOM was spin up for a 50-year run, while AO-FVCOM were
initialized with the Global-FVCOM spin-up field and ran for 6-years with data
assimilation of monthly climatologic temperature and salinity fields. The model-predicted
fields reached the equilibrium state after 5 years, and the integration time selected in was
long enough to conduct the climatologic field used for this study. The time step used to
drive AO-FVCOM is 600 sec. The ice internal stress in UG-CICE was computed by 120
iterations with a time step of 5 sec.
2.2. Biological model
An FVCOM-based i-state Configuration Model (FISCM) has been implemented to
examine biological-physical factors affecting the biogeographic boundary of Calanus
populations. The model has two modules, a Lagrangian tracking module and a generic
stage-based biological module. The tracking module is driven by the current fields
derived from the hourly-stored FVCOM output (so-called “offline” approach).
The
resulting locations of individual particles, along with the temperature field from FVCOM,
provide input for the biological module.
In the Lagrangian tracking module, the movement of each individual particles caused
by advection (and possibly vertical migration) can be computed by solving the following
equation with a classic 4th order 4-stage explicit Runge-Kutta method that has been
implemented in FVCOM (Chen et al., 2006b; Ji et al., 2006; Huret et al., 2007),
dx dt = v ( x (t ), t ) + vb , where x is the particle position at time t, and v is the velocity
interpolated from the surrounding model grids provided by FVCOM. The biological
behavior term v b can be derived from the literature/field measurements. In this study, we
do not include any horizontal swimming behavior, and keep individual particles at certain
depths (e.g. 0 m and 50 m below the surface for active individuals) vertically throughout
model runs.
In the biological module, the whole life cycle of the target zooplankton species is
divided into multiple morphologically distinct stages including egg, nauplii, copepodite
and adult stages. An individual copepod is represented as a vector in the model with
information such as location (x,y,z), sex, age, stage, ovarian status and other population
dynamic variables (referred as i-state by Metz and Diekmann, 1986). Each vector is
updated at each time step according to development rate and reproductive functions
derived from field measurements and lab experiments. The model starts with an initial
population structure and distribution, then monitors the change of each individual by
recording the i-state of individual j at any time t (Miller et al., 1998; Carlotti et al., 2000):
X i , j (t ) = X i , j (t - dt ) + f ( x1, j (t - dt ),... xi , j (t - dt ),..., T , food ,...) ,
(1)
where X i , j (t ) is the value of the i-state of individual j and f is the process modifying X i , j
as a function of the values of different i-states of the organisms, and external parameters
such as the temperature T and food concentration.
Belehrádek’s (1935) temperature function is used to describe the development times
under saturated food conditions as a function of temperature following Corkett et al.
(1986). Development time (D) for any one given stage is given by
D = a (T+α)β,
(2)
where a, α and β are constants and T is temperature. The value for α is assumed to be
fixed for a given species (9.11 for Calanus), and β is taken to be -2.05 from Corkett et al.
(1986), who found this to be the mean for 11 species of copepods. The value for “a” is
fitted for each developmental stage. Here we take advantage of the intra-generic
equiproportional rule for copepod development (Corkett 1984; Corkett et al., 1986;
McLaren, 1986): namely, the proportion of time that an individual spends in a given stage
relative to the entire development time is constant across genera and across different
temperatures. This permits us to use stage-duration proportions determined in laboratory
studies (e.g., Campbell et al., 2001) for a given species (C. finmarchicus) coupled with
measured egg development times from the other Calanus species to derive stage specific
development times at different temperatures for each species of interest. Parameterization
for C. marshallae at Arctic temperatures was unsuccessful. The primary difficulties are
that not only are the data limited, but also that the egg hatching experiments that have
been reported have been carried out in temperatures greater than 9oC (Peterson 1986).
Therefore, we only did a test with an assumption that C. marshallae has the same
parameter as C. finmarchicus. The detailed “a” values for the Calanus species in this
study are listed in Table 1.
In addition to temperature, we also added food dependence to the development rate
equation of C. finmarchicus and C marshallae for further simulations, using a similar
approach by Speirs et al. (???), who fit the function to the observation data from
Campbell et al. (2001). The development duration (D) becomes
D = a (T+α)β[1-exp(-F/K)],
(3)
where F is food concentration (unit: g chl l-1), and K is a constant associated with the
intensity of food limitation (0.8 g chl l-1 in this model).
No experiments with food-
dependent development were conducted for other two species (C. glacialis and C.
hyperboreus), mainly because the lack of food concentration data (ice algae data is very
sparse and can not be readily derived from satellite). Model runs without food limitation
on development represent the best scenario for the populations.
2.3. Numerical experiments
A series numerical experiments have been conducted to test our proposed hypotheses
regarding the potential geographic range of Calanus populations and how temperatureand food-dependent development rates coupled with advection by the prevailing
circulation might dictate its distribution.
The daily temperature distribution was derived from FVCOM model output. Food
concentration and the length of the growth season were derived for each location from
two different sources. For locations that were only seasonally ice covered, a climatology
of 8-day composites of SeaWiFS chlorophyll a data were used to estimate the dates that
food was first and last available, as chlorophyll, at each grid point in the IBM modeled
field (see Fig 2 top panel for the spatial distribution of the beginning of growth season).
Food concentration for each day and location throughout the model run also was
estimated from that climatology. Locations that are perennially ice covered, such as in
the Arctic Basin, do not have SeaWiFS chlorophyll data available and hence the growing
season was computed for each ice covered location using snow melt onset data (data
source ???, see Fig 2 bottom panel for the spatial distribution of the beginning of growth
season in ice covered area), along with AO-FVCOM model-computed sea surface shortwave radiation (to determine the end of growth season). For each location, then a
specific growing season was computed, with those further to the north necessarily having
shorter growth seasons.
The beginning of the growing season was used to determine the onset of egg
production at each of the starting model node points for Calanus finmarchicus, C.
marshallae, and C. glacialis, under the assumption that food is required to fuel significant
reproduction. For C. hyperboreus, the onset of the growth season coincides with the
presence of nauplius stage 3, the first feeding stage, in surface waters, which were
spawned at depth fueled by the lipid reserves of the adult females prior to the bloom.
Once an individual is released, it is advected by the dominant circulation and develops
from node to node according to the temperature at each point and, for some simulations,
the food concentration.
The model also permits us to simulate development and
movement of individuals at different depths, each of which experiences different
temperature conditions.
Development is terminated when the individual reaches a
location specific date where food is no longer available. Development is deemed to be
successful when an individual reaches a life stage where diapause can be initiated (C5 for
finmarchicus, C3 or C4 for hyperboreus, and C4 or C5 for glacialis). Most of our
simulations to date have followed individuals only for one growing season to see the
location of each individual who reaches diapause, with one additional simulation to track
the locations of diapausing individuals. The logic behind this is that failure to reach
diapause can be considered a failure to survive and reproduce. Successful colonization
out of the established range would only occur when individuals can successfully reach
diapause under the prevailing conditions and survive to reproduce the following year.
3. Results
3.1. Physical model results
AO-FVCOM predicted climatological fields of the sea ice coverage and
concentration, water temperature, salinity and currents have been validated by the
comparison with the observational data from satellites, mooring, drifters/floats and
climatologically averaged hydrographic database (Gao et al., 2010; Chen et al., 2010).
The model captured the spatial distribution and seasonal variation of both sea ices and
currents in the Arctic and its adjacent region. To focus our discussion on the FISCM
results, we only include a brief description of physical model results here.
Figures 3 shows examples of monthly mean water temperature and subtidal currents
averaged in the upper 50 m in April (top panel) and September (bottom panel) in the
Arctic region, In early spring, the surface circulation in the Arctic Basin is characterized
as the anti-cyclonic Beaufort Gyre circulation and strong transpolar drifting currents. In
summer, the anti-cyclonic Beaufort Gyre circulation shrinks and is much weaker and also
the transpolar circulation shifts toward North American side. The coastal currents can
reach 20-30 cm/s in September but is as low as 10 cm/s in April. The transports through
Bering Strait for these two months are about 1.4 Sv and 0.6 Sv, respectively. It is close to
the long term mooring observation 1.2Sv and 0.6 Sv in summer and winter (Woodgate et
al, 2005). The net inflow into the Arctic Ocean through the Fram Strait is about 1.6 Sv,
which counts for the outflow along the Greenland shelf. The model-predicted northward
current is about 10-20 cm/s, which is close to the observation (Fahrbach et al., 2001). The
temperature in this strait is as high as 6-8 °C in September and as low to 1-3°C in April.
3.2. Biological model results
3.2.1. Calanus finmarchicus and Calanus marshallae
For C. finmarchicus, the focus is on the North Atlantic side of model domain. Under
development rates that are temperature-dependent only and with the copepods at the
surface, C. finmarchicus was able to successfully reach the diapausing stage of C5 only in
the Barents, southern Kara Sea and southern GIN Seas (Fig 4, Atlantic side).
No
penetration of the species into the Arctic Basin was possible under the constraints of
temperature-dependent development and the length of the growing season at each
location. Note also that even the copepods that failed to reach diapause had not been
advected into the Arctic Basin by the end of the growing season. If development rate is
also food limited (in addition to development only occurring during the growing season),
C. finmarchicus successfully reaches diapause only at locations considerably further
south in the GIN and Barents Seas and in the Spitzbergen Current (Fig. 5).
The C. finmarchicus individuals released and advected at 50 m, under temperaturedependent only development rate, were not able to reach diapause at locations as far
north in the Barents Sea as those at the surface (not shown here). Under both food and
temperature dependent development rate, successful diapause was achieved only in the
southern portions of the GIN and Barents Seas and in the warm Atlantic water running
north along the western side of Spitzbergen (Figure 6), Notice that some eastward
advection of successfully developing copepods along the shelf-break to the north of
Spitzbergen did occur.
For C. marshallae, if the development is temperature-dependent only, surface
individuals released in the Bering Strait and Chukchi-Beaufort shelf was able to
successfully reach C5 (Fig 4, Pacific side). Under the development rate that depends on
both temperature and food, very few surface individuals can reach C5 within the growth
season in the Chukchi-Beaufort shelf region (Fig 5), and no individuals reached C5 if
individuals stayed in 50 m below the surface (Fig 6). Notice that there is no overlap of
successful individuals between the Pacific and Atlantic sides of the Arctic in all the cases.
3.2.2. Calanus glacialis and Calanus hyperboreus
Neither C. glacialis and C. hyperboreus can reach even their earliest diapause stages
in the central Arctic Basin (even without food limitation on development) when the
growth season starts at the onset of snow melt (Fig. 7 and Fig 8). The distribution of C.
glacialis C4 (youngest diapause stage) predicted by the model at the end of the growth
season matches observed distributions fairly well (Fig. 7), with C. glacialis distributed
along the edges of the Arctic Basin and in the marginal seas. Exceptions are the Chukchi
Sea, where C. glacialis may not be present in any abundance following winter. The
inability of C. hyperboreus to attain even the youngest diapause stage (C3) in the central
basin (Fig. 8) is contradictory to the observation reported by ???, suggesting the growing
season may be longer than used in the model, possibly due to earlier ice algal production
or a heterotrophic food-web that extends the length of the growing season, or the vital
rates used in the model is not correct.
Alternatively, C. hyperboreus may exist as
expatriates in the Central Arctic Basin as has been suggested by Olli et al. (2007). This
will be further discussed in the Discussion section.
4. Discussion (Outline only for most subsection…need expansion)
4.1. Processes affecting biogeography of Calanus finmarchicus
Calanus finmarchicus is believed to be an expatriate species in the Arctic Ocean and
marginal seas, with the population being advected into the Barents Seas from the
Norwegian Sea and the Arctic Basin through Fram Strait (Jaschnov, 1970; other refs). It
can be found in the Eurasian Basin of the Arctic Ocean but cannot sustain a population
there, and is not transported throughout the Arctic Ocean (refs). Compared to its two
congeneric species of Calanus (C. glacialis and C. hyperboreus) that are endemic in the
Arctic Ocean, C. finmarchicus is smaller, faster growing, and better adapted to warming
water conditions. Low temperatures have been suggested as the major cause for the low
growth and possibly the reproduction failure, and therefore the failure of C. finmarchicus
to sustain itself in the Arctic Ocean and marginal seas (Jaschnov, 1970, Sameoto, 1984;
Tande 1985; Hansen 1986). However, the question of whether temperature is the only
factor remains to be further examined. For instance, Hirche (1990, 1997) found from lab
experiments that females can continue to spawn at 0 C, and the egg production rate of
female C. finmarchicus from -1.5 to 2 C is similar to that of C. glacialis. Data from
field observations by Hirche and Kosobokova (2007) also showed the presence of
spawning females despite low water temperature between +1 and -1 C. These lab and
field work led to a hypothesis that the late availability of food in addition to low
temperature in the Arctic Ocean limits reproductive success and hence the sustainability
of the population (Hirche and Kosobokova, 2007).
Our results seem to suggest that, even without considering the low temperatureand/or food- induced reproduction failure, the low development rate at low temperature
alone can limit the expansion of C. finmarchicus to the north. If the additional fooddependent development is invoked in the model, the population is much more constrained
in the southern part of the GIN Seas, Barents and Kara Seas. Based on the observation
data (Kosobokova, 1998; Hirche and Kosobokova 2007; Kosobokova and Hirche; 2009),
most of the individuals found along the margin of the Arctic Basin are in C5 and adult
stages, especially in the north-east of the Svalbard (the Northern edge of Barents and
Kara Seas, as well as Leptev Sea). The absence of young copepodids suggests that the
population in those areas are either not reproducing or can not even reach copepodite
stages after hatching (how about nauplii?, I didn’t see data from Kosobokova ???), and
that the observed C5 and adult individual are mainly advected from Atlantic and southern
part of Barents and Kara Seas (possibly as diapause individuals during the previous
winter).
To investigate whether advection would bring copepods that reached diapause into
the Arctic Ocean during the overwintering period, we continued to advect the
successfully diapausing copepods through the winter until July 1 of the following year.
These individuals presumably would be able to continue development to the adult stage
and reproduce. The simulation demonstrated that only a very few of the diapausing
copepods were advected into the Arctic Ocean during the winter (Fig. 9). The C5 and
adult individuals observed by Kosobokova and Hirche (2009) along the northern edge of
Barents, Kara Sea, and Leptev seas, are probably the result of continuous advection of
those individuals emerge from diapause over winter.
Our results suggest that C. finmarchicus is unable to penetrate into the Arctic Ocean
under present conditions of temperature, food availability, and length of the growing
season because of a combination of factors.
The copepods are unable to reach the
diapausing stage under the conditions experienced in the northern portions of the GIN
and Barents Seas. In addition, the prevailing circulation is not fast enough to advect the
copepods into the Arctic Ocean during the growing season or even during the winter
following, at the depths the copepods are believed to diapause. This scenario is not likely
to change even if the water temperature increases by 2oC across the region (see more
discussion in 4.4).
4.2. Intrusion of Calanus marshallae from Pacific to Arctic
Difficulty in estimating vital rates.
What is the observed distribution?
If Cfin rates are applied, intrusion of cmar through Bering Sea to Beaufort shelf is
possible, but not able to cross Canadian Archipelago region, and reach the Atlantic side.
Argue against the Sundt & Melle (1998) on the observation of cmar in Atlantic side.
4.3. C. hyperboreous in the central basin?
Endemic vs. expatriate in the central basin (discuss about observation)
Case tested: start the growth season two weeks earlier (Fig. 10)
Uncertainty in the vital rates estimation (->implication for future observation)?
Difficulty in determining the beginning and end of growth season (-> implication for
future observation).
4.4. Warming scenario
Tested cfin/cmar and Chyp by increase water temperature by 2oC over climatoloty
Notice that the warming scenario testing in the model is not dynamics, no changes in
ice coverage and food change, only temperature change.
Warming/early ice melting caused the timing mismatch: Søreide et al., (2010) talked
about “Females of C. glacialis utilized the high-quality ice algal bloom to fuel early
maturation and reproduction, whereas the resulting offspring had access to ample
high-quality food during the phytoplankton bloom 2 months later. Reduction in sea
ice thickness and coverage area will alter the current primary production regime due
to earlier ice break-up and onset of the phytoplankton bloom. A potential mismatch
between the two primary production peaks of high-quality food and the reproductive
cycle of key Arctic grazers may have negative consequences for the entire lipiddriven Arctic marine ecosystem.”
5. Conclusion
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Table 1. Development-temperature function parameters.