362
John D. GAGE
radiotracers such as
210 Pb. These have made it possible
to progress beyond describing links quantifying flows
between broadly based compartments. But the difficulty
is that the integrated values employed may have no
relevance to rates in small size groups such as microorganisms and meiofauna, let alone individual species.
Furthermore, biomass-specific respiration or feeding
rates, when used to estimate carbon transfer between
functional groups or model compartments, arguably
have too broad a range to apply to individual links in
a model (Eldridge and Jackson, 1992). Nevertheless
it is only such bulk measurements that are presently
available. Furthermore, despite the diversity of organisms comprising the various consumer groups, data
plotted by K.L. Smith (1992) show a reasonably tight
fit to a linear relationship between biomass and carbon
demand. But the effort needed to construct a budgetary
box model based on relatively large functional or size
categories of organisms which includes contemporaneous flux data even for just one site is extraordinarily
large.
One approach by French workers has been to
link such diagenetic modelling with trophodynamic
simulations. This employs numerical modelling to
project behaviour of state variables (size of component
categories of organisms) from measured parameter
variables and initial conditions. A typical trophodynamic model consists of size- or function-determined
compartments as state variables where interactions
between compartments are modelled using known
predation relationships and a forcing function provided
by the measured organic carbon flux. The limitation of
such models lies in uncertainty in feeding relationships
among the large number of different species comprising
the assemblage within a model compartment, and
in uncertainty in assimilation efficiency and the true
magnitude of organic flux. Because of this, there is a
danger that output of such modelling may sometimes
seem unrealistic. One solution to the frequent dilemma
of incomplete data was developed for the planktonic
food web (V´ ezina and Platt, 1988). Here, inverse
analytic techniques use known information on state
variables to estimate the parameter fluxes and initial
conditions. The method then fits a “best” estimate
of the complete set of flows in a way analogous to
regression analysis. As yet, models have been limited to
linear relationships, with flow parameters as constants,
generating ‘snapshots’ in time. However, they have
been robust and informative on the relative importance
of different types of flows and compartments. For
example, a flow network model applied to the diverse
range of bathyal areas off the southern Californian
coastal margin was able to include and assess the
relative importance of anaerobic, as well as aerobic,
pathways in the benthic system (Eldridge and Jackson,
1992, 1993).
Conclusions from organic carbon and energy flow
models of abyssal ecosystems
Assuming that organic carbon arriving at the bottom
represents approximately 0.5 to 4% of new carbon flux
from the upper layer of the ocean (Deuser and Ross,
1980; Bender and Heggie, 1984; Martin et al., 1987),
various studies suggest that about 50 mg m
−2 yr
−1 of
meio- and macrofauna would be supported on a
particle flux of 10 mg m
−2 yr
−1 – that is, about 0.5 to
2 mg m
−2 yr
−1 of fresh organic carbon (Sibuet et al.,
1989). Various studies during the 1980s have indicated
that most of the organic matter reaching the sediment
would be consumed before burial within a few months
(Honjo et al., 1984; Sibuet et al., 1984). Therefore
burial flux, amounting to 0.5 to 2% of the total arriving
at the deep-sea floor, may effectively be disregarded.
One obvious conclusion is that all studies, whether
at bathyal depths or in the abyss, show the sediment
community overall as the most important component of
the benthic boundary layer community, followed by the
epibenthic megafauna and the bacterioplankton, both
of which are deserving of greater study (K.L. Smith,
1992).
Attempts at modelling energy flows using carbon
have addressed sites in the abyssal benthic environment, because of its supposed simplicity and because
the enormous area has an importance in carbon cycling
at the global scale. One of the best known and most
comprehensive of these has been developed over many
years for the central North Pacific by K.L. Smith and
his associates at Scripps Institution of Oceanography in
California (K.L. Smith, 1992). Their budgetary model
encompasses the entire sediment community and the
organisms inhabiting the water up to 600 metres above
the bottom (metres above bottom). It was assembled
from an extensive existing data base, along with many
new observations, for a site in the abyssal central North
Pacific, where organic carbon pools and fluxes are
better known than anywhere else in the deep ocean.
A similar box-model, flow-network approach has
been undertaken by French workers in the Northeast
Atlantic (Mahaut, 1990; Sibuet et al., 1993). In all
John D. GAGE
radiotracers such as
210 Pb. These have made it possible
to progress beyond describing links quantifying flows
between broadly based compartments. But the difficulty
is that the integrated values employed may have no
relevance to rates in small size groups such as microorganisms and meiofauna, let alone individual species.
Furthermore, biomass-specific respiration or feeding
rates, when used to estimate carbon transfer between
functional groups or model compartments, arguably
have too broad a range to apply to individual links in
a model (Eldridge and Jackson, 1992). Nevertheless
it is only such bulk measurements that are presently
available. Furthermore, despite the diversity of organisms comprising the various consumer groups, data
plotted by K.L. Smith (1992) show a reasonably tight
fit to a linear relationship between biomass and carbon
demand. But the effort needed to construct a budgetary
box model based on relatively large functional or size
categories of organisms which includes contemporaneous flux data even for just one site is extraordinarily
large.
One approach by French workers has been to
link such diagenetic modelling with trophodynamic
simulations. This employs numerical modelling to
project behaviour of state variables (size of component
categories of organisms) from measured parameter
variables and initial conditions. A typical trophodynamic model consists of size- or function-determined
compartments as state variables where interactions
between compartments are modelled using known
predation relationships and a forcing function provided
by the measured organic carbon flux. The limitation of
such models lies in uncertainty in feeding relationships
among the large number of different species comprising
the assemblage within a model compartment, and
in uncertainty in assimilation efficiency and the true
magnitude of organic flux. Because of this, there is a
danger that output of such modelling may sometimes
seem unrealistic. One solution to the frequent dilemma
of incomplete data was developed for the planktonic
food web (V´ ezina and Platt, 1988). Here, inverse
analytic techniques use known information on state
variables to estimate the parameter fluxes and initial
conditions. The method then fits a “best” estimate
of the complete set of flows in a way analogous to
regression analysis. As yet, models have been limited to
linear relationships, with flow parameters as constants,
generating ‘snapshots’ in time. However, they have
been robust and informative on the relative importance
of different types of flows and compartments. For
example, a flow network model applied to the diverse
range of bathyal areas off the southern Californian
coastal margin was able to include and assess the
relative importance of anaerobic, as well as aerobic,
pathways in the benthic system (Eldridge and Jackson,
1992, 1993).
Conclusions from organic carbon and energy flow
models of abyssal ecosystems
Assuming that organic carbon arriving at the bottom
represents approximately 0.5 to 4% of new carbon flux
from the upper layer of the ocean (Deuser and Ross,
1980; Bender and Heggie, 1984; Martin et al., 1987),
various studies suggest that about 50 mg m
−2 yr
−1 of
meio- and macrofauna would be supported on a
particle flux of 10 mg m
−2 yr
−1 – that is, about 0.5 to
2 mg m
−2 yr
−1 of fresh organic carbon (Sibuet et al.,
1989). Various studies during the 1980s have indicated
that most of the organic matter reaching the sediment
would be consumed before burial within a few months
(Honjo et al., 1984; Sibuet et al., 1984). Therefore
burial flux, amounting to 0.5 to 2% of the total arriving
at the deep-sea floor, may effectively be disregarded.
One obvious conclusion is that all studies, whether
at bathyal depths or in the abyss, show the sediment
community overall as the most important component of
the benthic boundary layer community, followed by the
epibenthic megafauna and the bacterioplankton, both
of which are deserving of greater study (K.L. Smith,
1992).
Attempts at modelling energy flows using carbon
have addressed sites in the abyssal benthic environment, because of its supposed simplicity and because
the enormous area has an importance in carbon cycling
at the global scale. One of the best known and most
comprehensive of these has been developed over many
years for the central North Pacific by K.L. Smith and
his associates at Scripps Institution of Oceanography in
California (K.L. Smith, 1992). Their budgetary model
encompasses the entire sediment community and the
organisms inhabiting the water up to 600 metres above
the bottom (metres above bottom). It was assembled
from an extensive existing data base, along with many
new observations, for a site in the abyssal central North
Pacific, where organic carbon pools and fluxes are
better known than anywhere else in the deep ocean.
A similar box-model, flow-network approach has
been undertaken by French workers in the Northeast
Atlantic (Mahaut, 1990; Sibuet et al., 1993). In all