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Canyon conditions impact carbon flows in food webs
of three sections of the Nazaré canyon
Dick van Oevelen1,*, Karline Soetaert1, Rosa García Novoa2,3, Henko de Stigter4,
Marina da Cunha5, Antonio Pusceddu6, Roberto Danovaro6
1 Centre for Estuarine and Marine Ecology, Netherlands Institute of Ecology (NIOO-
KNAW), POB 140, 4400 AC Yerseke, The Netherlands
2 Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany
3 Department of Global Change Research, IMEDEA (CSIC-UIB) Instituto
Mediterráneo de Estudios Avanzados, Miquel Marqués 21, 07190 Esporles, Spain
4 Royal Netherlands Institute for Sea Research (NIOZ), POB 59, 1790 AB Den Burg -
Texel, The Netherlands
5 Centro de Estudos do Ambiente e do Mar (CESAM) & Departamento de Biologia,
Universidade de Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal
6 Department of Marine Science, Polytechnic University of Marche, Via Brecce
Bianche, 60131 Ancona, Italy
* corresponding author: [email protected]
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Abstract
Submarine canyons directly transport large amounts of sediment and organic
matter (OM) from the continental shelf to the abyssal plain. Three carbon-based food
web models were constructed for the upper (300 – 750 m water depth), middle (2700
– 3500 m) and lower section (4000 – 5000 m) of the Nazaré canyon (eastern Atlantic
Ocean) using linear inverse modeling to examine how the food web is influenced by
the characteristics of the respective canyon section. The models were based on an
empirical dataset consisting of biomass and carbon processing data, and general
physiological data constraints from the literature. Environmental conditions, most
notably organic matter (OM) input and hydrodynamic activity, differed between the
canyon sections and strongly affected the benthic food web structure. Despite the
large difference in depth, the OM inputs into the food webs of the upper and middle
sections were of similar magnitude (7.98±0.84 and 9.30±0.71 mmol C m-2 d-1,
respectively). OM input to the lower section was however almost 6-7 times lower
(1.26±0.03 mmol C m-2 d-1). Canyon conditions greatly influenced OM processing
within the food web. Carbon processing in the upper section was dominated by
prokaryotes (70% of total respiration), though there was a significant meiofaunal
(21%) and smaller macrofaunal (9%) contribution. The high total faunal contribution
to carbon processing resembles that found in shallower continental shelves and upper
slopes, although the meiofaunal contribution is surprisingly high and suggest that high
current speeds and sediment resuspension in the upper canyon favor the role of the
meiofauna. The high OC input and conditions in the accreting sediments of the middle
canyon section were more beneficial for megafauna (holothurians), than for the other
food web compartments. The high megafaunal biomass (516 mmol C m-2), their large
contribution to respiration (56% of total respiration) and secondary production (0.08
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mmol C m-2 d-1) shows that these accreting sediments in canyons are megafaunal
hotspots in the deep-sea. Conversely, carbon cycling in the lower canyon section was
strongly dominated by prokaryotes (86% of respiration) and the food web structure
therefore resembled that of lower slope and abyssal plain sediments. This study shows
that elevated OM input in canyons may favor the faunal contribution to carbon
processing and create hotspots of faunal biomass and carbon processing along the
continental shelf.
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Introduction
Submarine canyons are incisions of the continental margin and directly link
the continental shelf with deep-sea plains by transporting large amounts of sediment
(Canals et al., 2006; de Stigter et al., 2007) and OM (Epping et al., 2002; Vetter and
Dayton, 1999). The comparatively rapid transport in active canyons results in the
sedimentary OM being also of higher quality as compared to slope sediments at
similar water depth (Garcia et al., 2007; Pusceddu et al., 2010; Vetter and Dayton,
1999). The high quantity and quality of the OM in canyon sediments results in carbon
oxidation rates (Epping et al., 2002; Rabouille et al., 2009) and benthic standing
stocks of nematodes (Ingels et al., 2009) and deposit feeding holothurians (Amaro et
al., 2009; De Leo et al., 2010; Vetter and Dayton, 1999) that are higher as compared
to adjacent open slopes and indicate extensive carbon cycling in the benthic food web.
These latter studies focus on individual components of the benthic food web
and suggest that different benthic components may benefit from the enhanced influx
of OM into canyons. These comparisons are, however, based on single biomass-to-
biomass or process-by-process comparisons. It is unclear how the structure of the
whole food web and carbon partitioning within the food web is affected by canyon
conditions. Moreover, it is unclear whether and how emerging properties at the whole
food web level are impacted by canyon conditions. Network analysis has been
developed to condense information contained in complex networks, such as food
webs, into interpretable indices (Fath and Patten, 1999; Ulanowicz, 2004). The index
total system throughput ( ) sums carbon flows in the food web to obtain a measure
of total food web activity. The Finn cycling index summarizes the fraction of total
carbon cycling that is generated by recycling processes (Allesina and Ulanowicz,
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2004). Another index that is claimed to be related to food web maturity is average
mutual information (AMI), that gauges how orderly and coherently flows are inter-
connected (Ulanowicz, 2004 and references therein). It is claimed that AMI is
indicative of the developmental status of an ecosystem and that while a food web
develops specialization results in higher values of AMI.
The Nazaré canyon intersects the Portuguese continental shelf and extends
from a water depth of 50 m near the coast down to 5000 m at the abyssal plain and
presents an interesting case study because of the varying conditions within the
canyon. The upper canyon section (50 – 2700 m water depth) is characterized by a V-
shaped valley that is deeply incised in the continental shelf. The middle canyon (2700
– 4000 m) is a broad meandering valley with terraced slopes that may experience high
rates of particle and organic matter sedimentation (Masson et al., this issue). The
upper and middle canyon sections capture suspended particulate matter from the
adjacent shelf and are affected by internal tide circulation of water with high bottom
current speeds, thereby imposing physical disturbance on the sedimentary
environment (de Stigter et al., 2007). Finally, the lower canyon is a kilometers-wide
flat-floored valley that gently descends from 4000 to 5000 m depth (de Stigter et al.,
2007; Masson et al., this issue).
The physical disturbance of sediments is especially strong in the narrow V-
shaped valley of the upper canyon section and this may impose constraints on the
development of the food web. Especially large and longer-lived components of the
food web may be affected and carbon cycling may be shifted towards microbes as
compared to sediments with similar OM input that are less frequently disturbed (Aller
and Aller, 2004). Carbon recycling, quantified with the Finn cycling index, may
therefore be lower because fewer food web components give rise to more limited
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recycling in the food web. Also food web maturity, as measured with the network
index AMI, is expected to be lower as compared to the middle and lower canyon
sections.
The terraced slopes of the middle canyon section experience high rates of
sedimentation and associated organic matter input. Transport of (semi)-labile OM to
these greater depths in the canyon may imply a deviation from the archetypical
relation between water depth and sediment oxygen consumption (SOC). The SOC and
the network index “total system throughput” is expected to be comparatively elevated
in the middle section of the canyon due to the enhanced OM input as compared to
open slope sediments at similar water depth. The enhanced input OM may not be
partitioned equally among the food web compartments and may be influenced by the
environmental conditions in the respective canyon. De Leo et al. (2010) for example,
reported extremely high biomass levels of particularly deposit-feeding holothurians in
a low relief muddy sediment at 900 – 1100 m in the Kaikoura Canyon (New Zealand).
The conditions in the Kaikoura canyon are reported to be similar to the middle section
of the Nazaré canyon and indeed high holothurian abundances are found there too
(Amaro et al., 2009). With a whole food web approach as followed here it will be
possible to study quantitatively whether different food web compartments take
proportional advantage of the enhanced OM input in this section of the Nazaré
canyon.
The deeper canyon section is where the canyon widens into a kilometres-broad
channel in the abyssal plain (de Stigter et al., 2007). This deep canyon section, which
only intermittently receives material derived from up-canyon sections via sediment
gravity flows, better resembles regular abyssal plain conditions with an associated
lower OM input. Under these lower OM inputs, lower faunal contributions to carbon
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cycling are expected and the more steady conditions may imply a higher food web
maturity and higher recycling within the food web.
Verifying how specific conditions in the three canyon sections impose on the
benthic food web requires an analysis of the trophic structure of the complete benthic
food web. The quantification of complete food webs is however a data-demanding
effort and canyon data sets are typically incomplete and limited in scope. To
overcome these limitations and maximize the amount of information gained from the
available data, so-called linear inverse models (LIM) have been developed. LIM
allow quantifying biological interactions in a complex food web from an incomplete
and uncertain data set such as encountered in the deep-sea (Soetaert and Van Oevelen,
2009). For example, Van Oevelen et al. (2009) using linear inverse modeling to
quantify the interactions in the complex food web of a cold-water coral community at
Rockall Bank and provided evidence that coral communities are hot-spots of biomass
and carbon cycling along continental margins.
Here we develop linear inverse models (LIM) to quantify carbon flows in the
complex food webs characterizing upper, middle and lower sections of the Nazaré
canyon. The observed food web structures and selected network indices are examined
as a function of the characteristics of the respective canyon section.
Methods
2.1 Nazaré canyon characteristics
The Nazaré canyon, one of the largest submarine canyons in Europe, intersects
the Portuguese continental shelf and has been intensively studied in the framework of
different European projects such as OMEX-II, EUROSTRATAFORM and HERMES.
Expeditions carried out within these projects have resulted in comparatively high data
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availability on different physical, chemical and biological aspects of the canyon
system. De Stigter et al. (2007) proposed a division of the canyon into three sections
based on hydrographic and physical characteristics. The upper canyon is characterized
by a V-shaped valley that is deeply incised in the continental shelf and starts at 50 m
water depth and runs down to a depth of 2700 m. The middle canyon (2700 – 4000 m)
is a broad meandering valley with terraced slopes and the lower canyon is a flat
floored valley that gently descends from 4000 to 5000 m depth. The water column
along the Western Iberian Margin is stratified, with relatively warm (14 to 18ºC) and
saline (35.4 to 35.8) water at the surface (North Atlantic Central Water) to cold (2ºC)
and less saline (34.8) water at 5000 m depth (North Atlantic Deep Water). The upper
and middle canyon sections capture suspended particulate matter from the adjacent
shelf and are affected by internal tide circulation of water with high bottom current
speeds (de Stigter et al., 2007).
The seabed of the Nazaré canyon is heterogeneous and consists of a highly
dynamic thalweg filled with coarse sandy and gravelly deposits, steep sloping canyon
walls with rocky outcrops, and terraces with thick accumulations of soft muddy
sediments (Tyler et al., 2009). The hard substrata in the thalweg and on steep walls
and outcrops are covered in places with a thin, centimeter-thick drape of soft mud,
where it is impossible to sample with box- or multicorer to estimate biomass.
Moreover, to avoid large heterogeneity in the data set due to seabed differences, the
focus of this manuscript is on soft-sediments outside the thalweg, which were split
into the three sections as described above. The depth range of the upper section was
here limited to 300 – 700 m.
Chemical and biological data were available on the concentration of total
carbohydrates, lipids and proteins in the sediment (Pusceddu et al., 2010),
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sedimentary chl a content (Garcia and Thomsen, 2008), sediment diagenesis (Epping
et al., 2002), prokaryotic heterotrophic carbon production (Danovaro, unpub. data),
nematode trophic structure (Danovaro et al., 2009) and the macro- and megafaunal
community structure (Cunha et al., this issue and unpub. data). Such data on biotic
and abiotic carbon stocks and transformation rates are perfectly suited to quantify
food webs of the three sections of the Nazaré canyon using linear inverse modeling.
2.2 Linear inverse models
The food web models developed for the Nazaré canyon are constructed using
linear inverse modeling (Van Oevelen et al., 2010). In an inverse model, the food web
compartments and flows between them are fixed a priori (see ‘Food web structure’
below). The flow magnitudes are constrained within the boundaries that are defined
by the inclusion of empirical data on standing stocks, flux data and physiology into
the model. The food web topology and empirical data are included in a matrix
equation with equalities and in a matrix equation with inequalities. These matrix
equations are solved simultaneously to recover quantitative values for the flow values,
such that the flow values in a model solution are within the boundaries defined by the
matrix equations. The model was run 10,000 times and each time a different solution
is generated to allow estimating the mean and standard deviation of each unknown
flow. It is important to note that by running the model 10,000 times, the uncertainty in
the empirical data (see ‘Data availability’ below) is propagated onto an uncertainty
estimate of the carbon flows as indicated by its standard deviation. Convergence of
the mean and standard deviation of the flows was used to verify whether the set of
10,000 model solutions was sufficiently large.
Several reviews on the technical and methodological aspects of linear inverse
modeling have been published and will therefore not be repeated here (Soetaert and
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Van Oevelen, 2009; Van Oevelen et al., 2010). These reviews contain simple models
to exemplify the setup and solution of linear inverse food web models using the
software packages LIM (Soetaert and Van Oevelen, 2008; Van Oevelen et al., 2010)
and limSolve (Soetaert et al., 2008) that run in the R software (R Development Core
Team, 2008). The Nazaré food web models are made publically available in the LIM
package.
2.3 Food web structure
The compartments in the food web models were chosen based on the classical
size distribution of prokaryotes (Pro), meiofauna (Mei), macrofauna (Mac) and
megafauna (Meg). The faunal compartments were further subdivided based on the
feeding classification for nematodes (Wieser, 1953) and feeding types for macro- and
megafauna were surface deposit-feeder (SDF), deposit-feeder (DF), suspension feeder
(SF) and predator+scavenger (PS) (see below). The sedimentary organic matter was
divided into dissolved organic carbon (DOC) and labile (lDet), semi-labile (sDet) and
refractory detritus (rDet).
Inputs to the food web are deposition and/or suspension feeding of suspended
labile (lDet_w), semi-labile (sDet_w) and refractory detritus (rDet_w). Outputs from
the food web are respiration to dissolved inorganic carbon (DIC), burial of rDet, DOC
efflux to the water column and export by the macro- and megafaunal compartments
(e.g. consumption by fish).
The detritus pools in the sediment can be hydrolyzed to DOC and the labile
and semi-labile detritus pools are grazed upon by meiofauna and MacSDF, MacDF,
MacPS, MegSDF and MegDF. DOC is taken up by prokaryotes or fluxes out of the
sediment to the water column. Predatory feeding links are primarily defined based on
size class; prokaryotes are consumed by all meiofaunal and non-suspension feeding
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macro- and megafaunal compartments, meiofaunal compartments are consumed by
non-suspension feeding macro- and megafaunal compartments, the macrofaunal
compartments MacSDF, MacDF and MacSF are preyed upon by MacPS.
Part of the ingested matter by the faunal compartments is not assimilated but
instead expelled as feces, the non-assimilated labile (e.g. labile detritus, prokaryotes
and faunal compartments) and semi-labile (semi-labile detritus) carbon, flows into
semi-labile and refractory detritus, respectively. Respiration by faunal compartments
is defined as the sum of maintenance respiration (biomass-specific respiration) and
growth respiration (overhead on new biomass production). Prokaryotic mortality is
represented here as a flux to DOC and faunal mortality is defined as a flux to labile
detritus.
2.4 Data availability
The Nazaré canyon is one of the best studied canyons in Europe, with studies
on sediment transport and/or fate of organic matter (e.g. de Stigter et al., 2007; Epping
et al., 2002; García et al., 2008), concentration of total carbohydrates, lipids and
proteins in the sediment (Pusceddu et al., 2010) heterotrophic prokaryotic C
production (Danovaro unpub. data), nematode community structure (Garcia et al.,
2007; Danovaro et al., 2009; Ingels et al., 2009), meiofaunal abundance (Bianchelli et
al., 2010), macro- and megafaunal community structure (Tyler et al., 2009, Cunha et
al., this issue and unpub. data). As stated above, empirical data were only included if
they were collected from the soft-sediments of the upper, middle or lower section of
the canyon.
Detritus stocks were delineated as follows (Table 1): the stock of labile
detritus was defined as all carbon associated with chlorophyll a. Chlorophyll a
concentrations were taken from the top 5 cm in sediments of the off-thalweg stations
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(Garcia and Thomsen, 2008), which were converted to carbon units by assuming a
carbon to chl a ratio of 40. Semi-labile detritus was defined as the sum of the
carbohydrates, lipids and proteins (i.e. biopolymeric carbon) that were converted to
carbon equivalents (Pusceddu et al., 2010). Biopolymeric carbon concentrations were
measured only in the top 1 cm and were linearly extrapolated to 5 cm depth under the
assumption that all semi-labile detritus is degraded in the top 5 cm. The latter
assumption is supported by Epping et al. (2002) who showed that carbon degradation
occurs primarily in the top 5 cm of the sediment. Refractory detritus was defined as
the degradable fraction of the particulate organic carbon in the top 5 cm of the
sediment (derived from organic carbon content profiles in Epping et al., 2002), minus
the labile and semi-labile detritus pools.
Biomass data were available for prokaryotes and all faunal compartments (i.e.,
meiofaunal, macrofauna and megafauna; Table 1). Nematodes dominated the
metazoan meiofauna (on average 90% of total abundance) and the Wieser feeding
classification based on nematode mouth morphology was used to designate biomass
to selective feeding (Wieser type 1A + 2A), non-selective feeding (Wieser type 1B)
and omnivore/predatory (Wieser type 1B). Polychaetes dominated the macrofaunal
compartments and these were grouped into surface-deposit, deposit, suspension and
predatory+scavenging feeding compartment based on standard feeding type
classification from Fauchald and Jumars (1979). Biomass-dominant polychaete
families in the upper section are Onuphidae (57%) and Sigalionidae (36%), in the
middle section Spionidae (61%), Fauveliopsidae (9%) and Ampharetidae (8%), and in
the lower section Spionidae (40%), Goniadidae (15%) and Siboglinidae (12%). Other
contributions to the macrofaunal biomass from Mollusca, Bivalvia and Crustacea are
low (< 3%) in the upper section, higher in the middle section with 48%, 14% and
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19%, and negligible in the lower section (<1%), respectively. Finally, the megafaunal
surface-deposit feeding community consists of Ypsilothuria bitentaculata
(Holothuroidea) and deposit feeding community of Molpadia musculus
(Holothuroidea).
Since there were no data available on the temporal variability in benthic
biomass, these were neglected and it was assumed that the mass balances of all
compartments are in steady-state, i.e., . This assumption introduces only
limited bias in the model solution (Vézina and Pahlow, 2003), primarily because net
biomass increases (e.g. for the fauna and bacteria) are small as compared to the other
flows in the food web.
In addition to the standing stock measurements, a variety of data on process
rates were available for the different sections of the Nazaré canyon (Table 2). These
data were implemented as inequalities by setting the minimum and maximum value
found in each section as lower and upper bounds, respectively.
The determination of prokaryotic C production in sediment samples was
carried out according to the procedure described for marine sediments by Danovaro et
al. (2002). Sediment subsamples from the top 1 cm were mixed with a solution of 3H-
leucine (final concentration 0.2 mmol L-1), were incubated at in situ temperature for 1
hour in the dark. After incubation, samples were supplemented with ethanol (80%)
and processed according to Van Duyl and Kop (1994) before scintillation counting.
Sediment blanks were made adding ethanol immediately after 3H-leucine addition.
The incorporated radioactivity in all samples was measured by a liquid scintillation
counter. The following equation was used for calculating prokaryotic C production:
PCP ~ LI · 131.2 · (%Leu) – 1 · (C: protein) · ID
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where PCP is prokaryotic C production, LI is the leucine incorporation rate
(mol ml-1 h-1), 131.2 is the molecular weight of leucine, %Leu is the fraction of
leucine in protein (0.073), C:protein is the ratio of cellular carbon to protein (0.86),
and ID is the isotope dilution assuming a value of 2.
The prokaryotic C production was determined in the top 1 cm and this value was
taken as lower bound on prokaryotic production (Table 2). Prokaryote production
typically decreases with depth in the sediment due to reduced availability of
degradable detritus and electron acceptors (e.g. Nodder et al., 2003; Glud and
Middelboe, 2004). The upper bound on prokaryotic C production for the top 5 cm was
set to five times the prokaryotic C production of the top 1 cm. As such, we impose
that the integrated prokaryotic C production does not increase within the top 5 cm of
the sediment, because the model solution is found between the lower bound
(production in top 1 cm layer) and the upper bound (5 times the production in the top
1 cm layer). Carbon burial rates, total respiration rates, total carbon deposition and
burial efficiencies for each section were taken from the diagenetic modeling work of
Epping et al. (2002) (Table 2). We imposed that total respiration and carbon
deposition in Epping et al. (2002) did not include the respiration and uptake by
megafauna, respectively, because the activity of these large burrowing or surface-
dwelling organisms is missed in a diagenetic modeling approach that is based on
small cores incubations and oxygen profiles in the sediment.
An additional number of general inequality constraints were taken from the
literature to constrain degradation rates of the labile, semi-labile and refractory
detritus pools, prokaryote growth efficiency, release of DOC from the sediment,
assimilation efficiency of all faunal compartments, net growth efficiency of all faunal
compartments, production and mortality rates of all faunal compartments (Table 2).
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Since measurements of assimilation and growth efficiencies of deep-sea benthos are
very rare, we decided to use an extensive literature review (Van Oevelen et al.,
2006b) of temperate benthos as basis for these constraints. Biomass-specific
maintenance respiration of all faunal compartments was defined as 0.01 d-1 at 20°C
(see references in Van Oevelen et al., 2006b) and is corrected with Q10 of 2, giving a
temperature-correction factor (Tlim) for each canyon section (Table 2).
Benthic organisms do not feed indiscriminately on the available food sources.
Both surface-deposit and deposit-feeding holothurians and echinoderms ingest
organic matter with higher than ambient chlorophyll a and total hydrolysable amino
acid concentrations (Ginger et al., 2001; Witbaard et al., 2001; Amaro et al., 2010),
though selectivity differs between feeding modes with surface-deposit feeders
typically exhibiting stronger selectivity than deposit feeders (Wigham et al., 2003).
Selectivity between labile detritus and semi-labile detritus for megafauna was defined
as the ratio of chlorophyll a concentrations in the gut with respect to the ambient
surface sediment. The level of selectivity varies from 1 to 10 for deposit feeding
holothurians to >500 for the surface deposit feeding holothurians Amperima rosea
(Porcupine Abyssal Plain, Wigham et al., 2003). Selectivity at the Antarctic Peninsula
was less evident (selectivity of 2 to 7), possibly because of the existence of a food
bank, but there was a clear separation between deposit and surface deposit feeders
(Wigham et al., 2008). Therefore, no to moderate selectivity of 1 to 10 for deposit
feeders and strong selectivity (50 to 100) for surface-deposit feeders was assumed in
the model (Table 2). Since no comparable data are available for macrofauna, similar
selectivity ranges were defined for these compartments (Table 2). Finally, few
organisms in benthic food webs can be considered as sole predators (Fauchald and
Jumars, 1979), therefore the predatory meio-, macro- and megafaunal compartments
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were assumed rely between 75% and 100% through predatory feeding to account for
this (Table 2).
2.5 Network indices
The network indices , and were directly calculated from the
output of the sampling algorithm in R using the newly developed R-package
NetIndices (Kones et al., 2009). Details on the calculation of the indices can be found
in Ulanowicz (2004) and Kones et al. (2009), but a summary of the nomenclature
(Table 3) and calculation algorithms (Table 4) are included in this manuscript.
Network indices were calculated for the complete set of food web solutions
(10,000 for each section). The network indices were compared between canyon
sections by calculating the fraction of which the randomized set of indices of one
canyon section is larger than that of another section. For example, when this fraction
is 0.90, this implies that 90% of the values of section 1 are larger than the ones of
section 2 (and consequently 10% of the values are lower). We define differences of
>90% and <10% as significant difference and >95% and <5% as highly significant
difference.
Results
3.1 Food web structure
The models of the upper and middle canyon could be solved with the default
equality and inequality constraints. However, the first attempt to solve the model of
the lower section with the default set of constraints was unsuccessful, which indicates
that some of the data embedded in the linear inverse model are in conflict with each
other. Subsequent analysis showed that the minimum degradation of semi-labile
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detritus (4761 · 8.21·10-4 = 3.9 mmol C m-2 d-1, Table 1 & 2) was higher than the
maximum rates of total carbon oxidation and carbon deposition (0.90 and 1.3 mmol C
m-2 d-1, respectively). Since the latter two data are site-specific field data, it was
decided to modify the literature bound on the minimum rate of semi-labile
degradation through pre-multiplication with the temperature limitation factor (Tlim =
0.30, Table 2). This allowed the model to be solved and its implications will be
discussed below.
The mean flow values and standard deviations for the three sections of the
Nazaré canyon are reported in Web appendix 1.
The quality of the model solutions was evaluated with the Coefficient of
Variation (CoV), which is the standard deviation of a flow divided by the mean flow
value. As such, the CoV provides an indication for the residual uncertainty in the
solution, where flows with a relatively large residual uncertainty have a comparatively
high CoV and flows with a relatively small residual uncertainty have a comparatively
low CoV. All flows in all three canyon sections had a CoV that was smaller than 1.
Maximum CoV were 0.86, 0.90 and 0.86 for the upper, middle and lower canyon
section, respectively and were associated with transfer of one the nematode
compartments to the (surface) deposit-feeding macrobenthos. The CoV was smaller
than 0.75 for 81%, 73% and 82% of the flows of the upper, middle and lower canyon
section, respectively, and the CoV was smaller than 0.50 for 40%, 40% and 45% of
the flows.
Total carbon input (mmol C m-2 d-1) to the different food webs was 7.98±0.84
(5% labile, 75% semi-labile and 20% refractory detritus), 9.30±0.71 (9% labile, 89%
semi-labile and 2% refractory detritus) and 1.26±0.03 (6% labile, 90% semi-labile and
4% refractory detritus) for the upper, middle and lower canyon section, respectively.
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Total respiration was 4.52±0.28, 5.06±0.30 and 0.86±0.02 mmol C m-2 d-1 and organic
carbon burial was 3.05±0.80, 3.85±0.35 and 0.34±0.04 mmol C m-2 d-1 for the upper,
middle and lower canyon section, respectively. Prokaryotes dominated carbon
respiration in the upper (70%) and lower (82%) section, but their contribution to total
respiration is lower (38%) than the total megafaunal respiration in the middle section
(57%) (Table 5). Summed meiofaunal respiration contributes 21% tot total respiration
in the upper, 3% in the middle and 13% in the lower canyon section, whereas summed
macrofaunal respiration contributes 8% in the upper, 1% in the middle and 5% in the
lower section. Summed export fluxes (i.e. secondary production not consumed within
the food web) differed between the sections with 0.18±0.08, 0.10±0.05 and
0.02±0.006 mmol C m-2 d-1 for the upper, middle and lower section, respectively.
The structural differences between the food webs become apparent when
flows are plotted as mean net values in a circular food web structure (Fig. 1). The
main differences between the upper and lower section are the more important role of
the non-selective feeding meiofauna compartment (Fig. 1A vs. 1C) and MacPS
compartment (Fig. 1D vs 1F) in carbon cycling in the upper canyon section. Of
similar importance, however, is the pathway of deposition of semi-labile, dissolution
to dissolved organic carbon, prokaryotic uptake of this DOC and prokaryotic
respiration in the upper and lower sections (Fig. 1A vs. 1C). Consistent with their
comparatively low contribution to total respiration, the carbon flows related to the
macrofaunal compartments are small, except for the MacPS compartment in the upper
canyon section that show up mostly in the lower row of Fig.1. The food web structure
of the middle canyon section stands out primarily because of the dominant role of the
MegDF and, to a lesser extent, MegSDF compartments (Fig. 1B and 1H). Moreover,
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carbon cycling by the macrobenthic compartments, especially MacPS, is less
important as compared to the upper and lower canyon section.
There is a dominance of semi-labile detritus in the diets of most faunal
compartments in the upper section of the Nazaré canyon, with semi-labile detritus
supplying between 53% and 95% of carbon of the non-predatory compartments and
11-12% of the predatory compartments MeiPS and MacPS, respectively (Fig. 2A).
Labile detritus (2 – 15%) and prokaryotes (2 – 22%) supply a comparable lower
fraction of carbon to the non-predatory compartments and 4 – 5% to the predatory
compartments. Non-predatory meiofaunal compartments fuels the meiofaunal and
macrofaunal predatory compartments in similar amounts (21 – 50%). Faunal diets of
the non-predatory compartments in the middle section are comparable to the upper
section, with a dominance of semi-labile detritus (42 – 93%) and labile (2 – 21%)
detritus (Fig. 2B). The diet contribution of prokaryotes to non-predatory faunal
compartments varies between 2 and 21%. Dependence on selective and non-selective
feeding meiofaunal compartments is highest for predatory meiofauna (80%), followed
by predatory macrofauna (48%) and <10% for the other macrofaunal and megafaunal
compartments. The diet of the predatory/scavenging macrofaunal compartment is
diverse, with no clear dominance of any resource (3 – 25%).
The diet compositions in the lower section of the Nazaré canyon resemble
overall those of the upper section (Fig. 2A vs. 2C). Again, semi-labile detritus is most
important (between 76 – 98%) in the diets of non-predatory faunal compartments.
Diet contributions of labile detritus and prokaryotes are similar for selective feeding
meiofauna (9-10%), non-selective meiofauna (each 1%), predatory/omnivore
meiofaunal (each 5%), surface-deposit feeding macrofauna (each 5%), deposit-
feeding macrofauna (each 1%) and predatory/scavenging macrofauna (4-5%) (Fig.
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2C). The meiofaunal compartments MeiSF + MeiNF are important resources for the
meiofaunal predators/omnivores (together 80% of the diet) and predatory (69%)
macrofauna, but are of lesser importance for surface-deposit (10%), deposit feeding
(1%). The diet composition of predatory/scavenging macrofauna is diverse though
with a high importance of selective feeding meiofauna (54%) and lower contributions
ranging from 1 - 11% from other resources.
The diet of suspension-feeding macrofauna is similar among the canyon
sections and is partitioned among labile (32 – 36%) and semi-labile (64 – 68%)
detritus from the water column.
The dominant fate of prokaryotic production in all three sections is mortality
(52 – 88%) and grazing by meiofauna in the upper canyon section (31%) and by
megafauna in the middle section (36%) (Fig. 3A-C). The majority of the meiofaunal
secondary production is grazed by macrofauna in the upper (56%) and lower (47%)
canyon section, while megafaunal grazing is important in the middle section (36%)
and grazing by meiofauna (MeiPO) is important with a consistent contribution of 18 –
23% in the three sections (Fig. 3D-F). The fate of macrofaunal production is
partitioned similarly in all three canyon sections with maintenance representing 22 –
24%, mortality 29 – 34%, predation by macrofauna (MacPS) 2 – 20% and export 29 –
42% (Fig. 3G-I). The fate of megafauna is dominated by maintenance respiration
(91%) and with limited contributions of mortality (5%) and export (4%) (Fig. 3J).
3.2 Network indices
The network indices total system throughput ( ), Finn cycling index ( )
and average mutual information ( ) were calculated for the three sections (Fig. 4)
and compared (Table 6). The does not differ significantly between the upper and
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middle sections with median values of 41.1 and 39.7 mmol C m-2 d-1, respectively, but
is significantly lower in the lower section with a median of 6.7 mmol C m-2 d-1
(Table 6). Differences in are highly significant between canyon sections (Table
6) and median values are 0.13, 0.06 and 0.17 for the upper, middle and lower section,
respectively. is not significantly different between the upper (median of 2.21)
and middle (2.22) canyon section, but significantly lower for the lower section (2.12).
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Discussion
In this paper, we present the first quantitative analysis of carbon flows within
food webs of different sections of a submarine canyon. This provides a unique
opportunity to study how different characteristics within a canyon influence food web
structure and attributes such as total system throughput, recycling within the food web
and food web maturity. The modeled food webs of the upper, mid and lower canyon
sections are based on a large variety of site-specific biological and biogeochemical
data and are combined with physiological constraints and empirical relations from the
literature. Despite the large amount of data that are implemented, this is insufficient to
uniquely quantify all carbon flows (Van Oevelen et al., 2010). This implies that a
“solution space” exists, within which an infinite number of solutions are present that
are consistent with the data (Soetaert and Van Oevelen, 2009). Conventional single-
solution modeling approaches typically find a final solution at or close to boundaries
of the solution space, making the final solution sensitive to the exact boundaries of the
solution space ( Vézina et al., 2004; Kones et al., 2006; Van Oevelen et al., 2010).
The multi-solution approach followed here, samples the solution space (Van den
Meersche et al., 2009) such that the mean of this sampled set represents the best
central flow value that is less sensitive to the boundaries of the solution space (Van
Oevelen et al., 2010). Moreover, the standard deviation on each carbon flow indicates
how the uncertainty in the data set propagates to an uncertainty on its value (Van
Oevelen et al., 2010). The Coefficient of Variation (CoV) was smaller than 0.75 for
73 – 82% flows in the three sections (Web appendix), which indicates that the
residual uncertainty on the flows is comparatively low and that the food web is well-
constrained. The lowest CoVs are associated with the respiration flows of the biotic
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compartments, whereas highest CoVs are predominantly associated with carbon flows
that exist between biotic compartments. This directly relates to the data availability.
The carbon requirement of faunal compartments is constrained primarily by the
available biomass data. There are however few data that constrain the origin of this
carbon, such that the residual uncertainty on diet contributions and fates of secondary
production are comparatively high. Perhaps even more important than the residual
uncertainty on the flows, are the limitations and uncertainties with respect to the
assumptions that were needed to setup the model. These sources of uncertainty mainly
concern substrate heterogeneity and combining different data sets and will be
discussed now.
The seafloor in the Nazaré canyon is heterogeneous and consists of rocks,
boulders, coarse gravel sediments, steep walls, a highly dynamic thalweg and terraces
consisting of soft-sediments. The hard substrata may be draped with a thin soft muddy
layer. Not surprisingly, also the associated fauna changes with substratum type and
condition. Rocky surfaces for example are dominated by suspension feeders such as
hard and soft corals, gorgonians, anemones, sea pens and crinoids (Tyler et al., 2009).
In thalweg sediments, the biomass of nematodes (Garcia et al., 2007) is about one
order of magnitude lower than in soft-sediment terraces (Ingels et al., 2009), which is
attributed to repeated sediment disturbance of thalweg sediments that prevents the
development of a mature nematode community (Garcia et al., 2007). In addition,
megafauna and the giant epifaunal protozoans (xenophyophores) were not observed in
the thalweg (Tyler et al., 2009) but are found outside the thalweg. Up to now, there
are no quantitative data available on the biomass and activity of the filter-feeding
community in the Nazaré canyon on rocky substrata. Moreover, quantitative data on
the faunal community in the thalweg is only sparsely available and its food web
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structure is not representative for that of large sections of the canyon. Hence, in this
study we restricted our analysis to the soft-sediments of the terraces adjacent to the
thalweg and excluded other substrate types. This implies for example that we may
miss the potentially high carbon processing activity associated with the canyon walls.
In terms of areal coverage however, these soft-sediments with net mud deposition
represent an appreciable ~70% of the total surface area of the canyon (Masson et al.,
2010), such that a significantly large part of the Nazaré canyon is addressed here.
One compartment that is not included in the food web is Foraminifera, which
are protozoans that are typically of meiofaunal size but can occur as giant epifauna
(xenophyophores). Meiofaunal foraminifera (Koho et al., 2008) and epifaunal
xenophyophores (Tyler et al., 2009) have a high abundance in especially the muddy
terraces with stable redox conditions and low disturbance. Foraminifera have been
shown to play an important role in the initial processing of fresh phytodetritus under
deep-sea conditions (Moodley et al., 2002) although their contribution may also be
more limited (Woulds et al., 2007). Moreover, their contribution to total respiration in
continental shelf sediments was recently found to be limited to <3% (Geslin et al.,
2010). Unfortunately, the available abundance data could not be converted to biomass
with reasonable accuracy, and since biomass is essential to constrain their activity in
the food web we therefore decided to omit this compartment in this analysis.
The site-specific data that we include in this study were lumped into the three
canyon sections (Table 1 and 2). However, since deep-sea research is time
consuming, conducted over large spatial areas and depends on ship time availability
and meteorological/sea conditions, the data were not collected synoptically.
Inevitably, this data ‘lumping’ into canyon sections will introduce errors in the food
web analysis linked to the spatial and temporal variability of the data collected.
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Nevertheless, the Nazaré canyon is comparatively well-studied and one of the
strengths of linear inverse modeling is that datasets are merged and tested for internal
consistency (Van Oevelen et al., 2010). Given the amount of data in the models
(Table 1 and 2), the inverse model analysis at least showed that the different data sets
are consistent. The only exception was that the minimum degradation rate of semi-
labile detritus in the lower canyon section was higher than the maximum rates of
carbon oxidation and total carbon deposition. The carbon oxidation and deposition
data are site-specific data and were therefore maintained. Instead, the minimum bound
on semi-labile degradation was reduced by multiplication with the temperature
limitation factor, which allowed solving the food web model. Several explanations
may apply here. First, water temperature in the deep canyon section is about 2.5°C
and lowest of the three sections. This low temperature may cause degradation to
proceed slower than in the higher sections of the canyon with comparatively higher
water temperatures. Moreover, the quality of the semi-labile detritus may have
decreased during transport through the canyon and this may also lower the
degradation rates further. Despite this minor adaptation that was needed, the results
from the present analysis serve as a significant first step in gaining insight in the food
web structure of submarine canyons.
4.1 Upper canyon section
The dynamic upper canyon receives about 8±0.84 mmol C m-2 d-1, which is
lower than the 15 – 23 mmol C m-2 d-1 that is predicted using an empirical relation for
continental shelf sediments (i.e. summed burial and mineralization rates at 700 and
300 m, respectively, Middelburg et al., 1997). However, carbon inputs at the open
slope sediments of the adjacent Iberian margin are substantially lower than predicted
by the empirical relation by Middelburg et al. (1997) and are between 2.3 and 4.3
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mmol C m-2 d-1 (Epping et al., 2002). Thus, carbon inputs to the upper canyon section
is higher those of adjacent slopes, but not extremely high as compared to other slope
sediments. Burial rates in the upper and middle canyon are substantial flows in the
food web (Fig. 1A, B), but burial efficiencies are comparable to Iberian open slopes
and relate to sediment accumulations rates (Epping et al., 2002). Hence, the efficiency
with which the food web processes organic carbon is similar to open slope sediments.
The model results allow detailed deciphering of the biotic compartments that
are responsible for carbon processing within the canyon. Woulds et al. (2009) used
the results of isotope tracer experiments from different slope sediments to define
different categories of biological C-processing. In this categorization, the “active-
faunal-uptake” category contains mostly shallow (<300 m) slope sediments and is
characterized by 10 – 25% metazoan uptake. This category matches best with the
upper canyon section that has a faunal contribution of ~40% and bacterial
contribution of 60% to total carbon assimilation.
The faunal contribution to total respiration and carbon processing typically
decreases with increasing water depth and associated decrease in carbon input (Heip
et al., 2001; Rowe et al., 2008; Woulds et al., 2009). Henceforth, the high faunal
contribution in the upper canyon section is probably related to the higher OM content
and quality as compared to slope sediments at comparable water depth (Garcia et al.,
2007; Garcia and Thomsen, 2008; Pusceddu et al., 2010). One striking difference
however is that meiofauna dominated faunal processing and contributed around 33%
of the total carbon assimilation in the upper canyon section, which is much higher
than in open slopes sediments included in the overview of Woulds et al. (2009). This
high contribution also translates into a much higher meiofaunal respiration at 21% of
total respiration in the upper section of the Nazaré canyon as compared to other open
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slopes that vary from 4 – 8% (Piepenburg et al., 1995; Heip et al., 2001; Soetaert et
al., 2009).
Rowe et al. (2008) and Bagulay et al. (2008) report even substantially higher
contributions ranging from ~20 up to 51% for the Northern Gulf of Mexico. Their
estimates are based on biomass-specific respiration rates of 0.04 to 0.11 d-1 at a
temperature of 4 – 5°C. Moodley et al. (2008) used a novel micro-respiration system
and reported specific rates of 0.021 to 0.032 d-1 for intertidal (20°C) Nematoda,
Ostracoda and Foraminifera over a biomass range of 0.7 to 5.2 μC ind-1. Nematodes
from the Gulf of Mexico are smaller (~0.1μC ind-1, Baguley et al., 2008), but specific
respiration rates are still fairly high as compared to these intertidal meiofauna. The
high meiofaunal contribution to total community respiration is therefore probably also
related to the comparatively high biomass-specific respiration rates that are estimated
for the Gulf of Mexico. Clearly more experimental work for especially small
nematodes at lower temperatures is needed to better constrain these respiration rates.
The carbon sources that are consumed by meiofauna to fuel these respiration
rates are detritus and prokaryotes (e.g., Rowe et al., 2008, this study). Stable isotope
tracer experiments allow direct quantification of labile food assimilation rates of
amongst others meiofauna. Intriguingly, these results typically show low biomass-
specific assimilation rates of <0.01 and mostly <0.001 d-1 ( Moens et al., 2007; Franco
et al., 2008; Ingels et al., 2011;), a limited (<5%) contribution to 13C uptake by
metazoan meiofauna on open slope (Moodley et al., 2002) and abyssal plain (Witte et
al., 2003) sediments and negligible bacterivory by nematodes in a slope sediment
(Guilini et al., 2010). Irrespective of the labeled substrate or setting, meiofauna
consistently show an uptake of labile 13C carbon that seems to be in imbalance with
carbon requirements as estimated from biomass-specific respiration rates. This is not
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in contrast with the meiofaunal diet composition as inferred for the Nazaré canyon
(Fig. 2), where semi-labile detritus (a carbon source not used in isotope tracer studies)
is the dominant component. This dominance of semi-labile detritus in their diet would
explain the low labeling of metazoan meiofauna (dominated by nematodes) in isotope
tracer studies. It also agrees with Soetaert et al. (1997), who found a strong positive
correlation between depth profiles of nematodes and organic N content and suggested
that the concentration of lower quality food primarily determines nematode depth
distribution.
The elevated OM input in the upper canyon section combined with
hydrodynamic conditions with current speeds of up to 30 – 40 cm s-1 appear to
particularly favor meiofauna, whereas macro- and megafauna have a lower
contribution to carbon processing as compared to open slope sediments. As a result,
meiofaunal biomass in the upper canyon section rank among the highest reported in
marine sediments (Rex et al., 2006), whereas macrofaunal biomass is comparatively
low.
Prokaryotes are responsible for the dominant part of carbon cycling and
respiration in the upper canyon section (Fig. 1 and Table 5). An important pathway,
also seen in the middle and lower canyon section, is deposition of semi-labile detritus,
dissolution to dissolved organic carbon, to prokaryotic uptake of this DOC and
subsequent prokaryote respiration. A dominance of prokaryotes in carbon cycling and
respiration is commonly found in continental shelf sediments (Canfield et al., 1993;
Piepenburg et al., 1995; Heip et al., 2001; Rowe et al., 2008). Hence, it appears that
hydrodynamic conditions in the upper canyon act predominantly on carbon
partitioning between faunal compartments rather than on the partitioning between pro-
and eukaryotes.
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4.2 Middle canyon section
Soft-sediment terraces in the middle section of the canyon experience high
sedimentation rates (de Stigter et al., 2007; Tyler et al., 2009; Masson et al., 2010),
which is accompanied by an input of organic matter of 9.30±0.71 mmol C m-2 d-1 that
is comparable to the upper canyon section. These high OM inputs clearly show that
the archetypical picture seen in open slope sediments that biomass, respiration and
carbon processing decreases with increasing water depth does not necessarily hold for
submarine canyons.
With respect to the carbon partitioning within the food web, the middle
canyon section seems to fall in the “metazoan-macrofaunal-uptake-dominated”
category, a category that is typically found in shelf and upper slopes, with a
comparatively high macrofaunal biomass (Woulds et al., 2009). An importanct
discrepancy with the categorization by Woulds et al. is that faunal carbon processing
in the middle canyon is not dominated by macrofauna, but by surface deposit-feeding
and deposit-feeding megafauna (i.e. the holothurians Ypsilothuria bitentaculata and
Molpadia musculus, respectively). The megafaunal importance is also apparent in
community respiration (57%) and export of secondary production from the food web
(79%).
De Leo et al. (2010) reported recently for the Kaikoura Canyon (New
Zealand) an extremely high biomass of 89±18 g C m-2 of megafauna (dominated by
M. musculus) in low relief, muddy and accreting sediments at 900 – 1100 m of water
depth. Megafaunal biomass in the middle section of the Nazaré canyon is about an
order of magnitude lower (6.2 g C m-2), but still 2 – 3 orders of magnitude higher than
found in open slopes at comparable depth (Rex et al., 2006).
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Amaro et al. (2010) conducted trophic studies on the holothurian M. musculus
and estimated removal rates of 0.5 gC of semi-labile detritus m-2 d-1. Our food web
analysis even suggests higher removal rates of 2.5 gC of semi-labile detritus m-2 d-1,
showing that this holothurian can have an important impact on the sedimentary food
web. Amaro et al. (2010) also inferred that prokaryotes delivered <0.1% of the
assimilated proteins and it was concluded that holothurians do not appear to rely on
microbes for direct nutrition. This is also supported by our diet reconstruction of
deposit-feeding megafauna (i.e., M. musculus), where prokaryotes play only a
marginal role (Fig. 2B).
Carbon partitioning with the food web of the middle canyon section at 2700 –
4000 m is comparable to much shallower shelf and upper-slope sediments, where also
an important faunal contribution is typically found. The large faunal contribution in
the middle canyon section is due to the comparatively high input of OM, which is
quantitatively comparable to the upper canyon section. It is however unclear why
canyon-specific conditions in the middle section are particularly beneficial for
(surface) deposit-feeding holothurians as compared to for example macrofaunal
polychaetes. The deposit-feeding megafauna consist predominantly of the holothurian
head-down feeder M. musculus and there was no evidence for a specialized
prokaryotic community in the guts of M. musculus that may aid in the hydrolyzation
of organic matter (Amaro et al., 2009). Other possible explanations for a strong
proliferation of M. musculus in soft accreting sediments within canyons may involve a
better adaptation to high sediment rates, enhanced trapping of the depositing organic
matter in their feeding pits and negative feedbacks on macrofauna through, for
example, predation or sediment disturbance.
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4.3 Lower canyon section
The food web structure in the lower canyon section is markedly distinct from
the upper and middle sections (Fig. 1). Not only is total carbon input (1.26±0.03
mmol C m-2 d-1) about an order of magnitude lower than in the upper and middle
sections, but also its partitioning within the food web differs considerably. OM input
in the lower section is lower, because OM delivery from the upper and middle canyon
section is less frequent, OM has been degraded during transport through the canyon
and the lower canyon begins where the V-shaped valley widens into a kilometers-
wide channel thereby lowering the OM input per surface area.
Respiration in the lower canyon section is strongly dominated by protozoa
(82% of total respiration) whereas the faunal compartments each respire <10%. These
characteristics place the lower canyon section in the “respiration-dominated”
category, in which most OM is respired by the prokaryotic community and the role of
benthic fauna in carbon cycling is low (Woulds et al., 2009). Other sites that fall in
this category are lower slope sediments and abyssal plains (Woulds et al., 2009),
suggesting that the benthic food of the lower canyon section resembles others sites at
similar depth . The lower canyon section seems to be less influenced by canyon
conditions as compared to the upper and middle section of the canyon.
4.4 Comparison of canyon sections with network indices
The lower carbon processing in the lower canyon is also evident in the index
total system throughput ( ), in which carbon flows are summed to obtain a measure
of total food web activity (Ulanowicz, 2004). Total system throughput does not differ
significantly between the upper and middle sections (medians of 41.1 and 39.7 mmol
C m-2 d-1, respectively), but is significantly lower in the lower canyon section (median
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of 6.7 mmol C m-2 d-1) (Table 6). Though community respiration and OM input is
higher for the middle canyon section, total system throughput is slightly elevated (not
significantly) in the upper canyon section. This reversal in activity measures is
probably linked to the low recycling within the food web of the middle canyon as
quantified with the Finn cycling index (Fig. 4B). This index summarizes the fraction
of total carbon cycling that is generated by recycling processes (Allesina and
Ulanowicz, 2004). Significant differences in recycling are found between the canyon
sections, with the most notable difference being low recycling in the middle canyon
section. One explanation relates to the viral shunt (Danovaro et al., 2008), in which
viral infection cause lysis of prokaryotes and the subsequent release of dissolved
organic matter that is again recycled by other heterotrophic prokaryotes (e.g., Van
Oevelen et al., 2006a). Prokaryotes dominate carbon flows in the lower section, but
this dominance is reduced in the upper and particularly the middle canyon section. If
the viral-mediated shunt significantly influences the FCI, this would explain the
decreasing FCI when going from the lower, upper to the middle canyon section. To
examine the impact of the viral shunt on the FCI, the viral shunt was eliminated from
the food web by only including the net flow from DOC to prokaryotes in the FCI
calculations. Though differences in FCI remain, the FCI of the upper and lower
sections drops to medians of 0.07 and 0.04, respectively, whereas the middle section
is much less affected with a drop to 0.03. This exercise clearly shows that the viral
shunt increases carbon recycling in benthic food webs rendering recycling to be
higher in prokaryote-dominated food webs as compared to faunal-dominated food
webs.
The index average mutual information (AMI) gauges the developmental status
of an ecosystem in the sense that while food webs develop, trophic specialization will
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result in higher values for AMI (Ulanowicz, 2004). The AMI is that part of the flow
diversity (i.e. the Shannon index applied to flow diversity, Ulanowicz, 2004) that
quantifies how orderly and coherently carbon flows are inter-connected. Since the
AMI is claimed to assess the developmental status of an ecosystems it is interesting to
assess whether differences in the food web structures are also reflected in the AMI
index. More specifically, we had expected the less-disturbed lower canyon section to
have highest AMI values with decreasing values going up-canyon. Differences in
AMI between the upper and middle canyon are non-significant (Table 6), though
large differences exist in environmental conditions and food web structure. The AMI
is significantly lower in the lower canyon section though this section is less impacted
by canyon conditions as compared to the other two sections. Tobor-Kaplon et al.
(2007) quantified the AMI of soil food webs that were exposed to different stress
levels (i.e. pH and copper) and concluded that AMI appeared useful as an indicator of
environmental stress at the ecosystem level. For the benthic food webs analyzed here
however, there does not seem to be a straightforward relation between AMI and
environmental stress. On the other hand, there is another important factor that
influences food web structure when going down-canyon, namely the reduced OM
input. To verify the usefulness of AMI as a stress indicator it is therefore necessary to
compare the AMI of marine benthic food webs at similar levels of OM input, but
different levels of environmental stress.
In conclusion, benthic food web structures in the upper, middle and lower
sections of the Nazaré canyon were shown to be influenced by the conditions in the
particular canyon section. The OM input in the upper and middle canyon sections is
elevated as compared to those of the surrounding open slope sediments and this
resulted in a higher contribution of fauna in carbon processing as compared to open
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slope sites at similar water depth. The compartments that were responsible for the
faunal processing were strongly influenced by conditions in the particular canyon
section. In the upper canyon section, a dominance of meiofauna in faunal carbon
processing was evident, whereas a high faunal contribution to carbon processing in
open slope sediments is typically dominated by macrofauna. It is proposed that
hydrodynamic disturbance and resulting sediment resuspension in the upper canyon
shifts the balance towards the meiofauna. In contrast, the food web of the accreting
sediments in the middle canyon showed a completely different pattern where carbon
processing was dominated by the megafaunal holothurians. Our study confirms that
accreting sediments in canyons can be hotspots of megafaunal biomass and
production and megafauna can greatly influence carbon processing. The food web
structure of the lower canyon section resembled that of lower slope and abyssal plain
sediment, where carbon processing is dominated by prokaryotes. The influence of the
canyon-specific processes seems to vanish in the deeper sections where the Nazaré
canyon widens and enters the abyssal plain. In all canyon sections, a dominance of
semi-labile detritus in the diet of (surface) deposit feeders is suggested. These results
are supported by stable isotope tracer (for meiofauna) and gut transformation
(holothurian M. musculus) studies. This study shows that elevated OM input in
canyons may favor the faunal contribution to carbon processing and creating hotspots
of faunal biomass and carbon processing along the continental shelf.
Acknowledgements
This research was supported by the HERMES project (contract
GOCE-CT-2005-511234), funded by the European Commission’s Sixth Framework
Programme under the priority “Sustainable Development, Global Change and
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Ecosystems”, and HERMIONE project (grant agreement n° 226354") funded by the
European Community's Seventh Framework Programme (FP7/2007-2013). This is
publication 5018 of the Netherlands Institute of Ecology (NIOO-KNAW), Yerseke.
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The response of Oneirophanta mutabilis (Holothuroidea) to the seasonal
deposition of phytopigments at the porcupine Abyssal Plain in the Northeast
Atlantic. Progress in Oceanography 50 (1-4), 423-441.
Witte, U., Wenzhofer, F., Sommer, S., Boetius, A., Heinz, P., Aberle, N., Sand, M.,
Cremer, A., Abraham, W.R., Jorgensen, B.B., Pfannkuche, O., 2003. In situ
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experimental evidence of the fate of a phytodetritus pulse at the abyssal sea floor.
Nature 424 (6950), 763-766.
Woulds, C., Andersson, J.H., Cowie, G.L., Middelburg, J.J., Levin, L.A., 2009. The
short-term fate of organic carbon in marine sediments: Comparing the Pakistan
margin to other regions. Deep-Sea Research Part II-Topical Studies in
Oceanography 56 (6-7), 393-402.
Woulds, C., Cowie, G.L., Levin, L.A., Andersson, J.H., Middelburg, J.J., Vandewiele,
S., Lamont, P.A., Larkin, K.E., Gooday, A.J., Schumacher, S., Whitcraft, C.,
Jeffreys, R.M., Schwartz, M., 2007. Oxygen as a control on seafloor biological
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Oceanography 52 (4), 1698-1709.
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Tables
Table 1. Standing stocks (in mmol C m-2 as mean ± standard deviation) of the food web compartments for the upper, middle and lower section of the
Nazaré canyon. See “Methods – Data availability for description. References are: 1) Garcia and Thomson (2008), 2) Pusceddu et al., In Press), 3)
Epping et al. (2002), 4) Danovaro (unpub. data), 5) biomass is Danovaro et al. (unpub. data), but biodiversity analysis in Danovaro et al. (2009),
6) Tyler et al. (2009) and 7) Cunha et al. (unpub. data).
Compartment Upper Middle Lower Ref
Labile detritus (lDet) 35.8 ± 19.8 46.9 ± 16.4 10.9 ± 6.7 1
Semi-labile detritus (sDet) 5393 ± 2419 5114 ± 2692 4761 ± 2384 2
Refractory detritus (rDet) 66137 66661 50211 3
Prokaryotes (Pro) 4.84 ± 0.08 3.14 ± 0.11 2.79 ± 0.09 4
Selective feeding meiofauna (MeiSF) 6.80 ± 1.98 2.32 ± 0.77 2.34 ± 2.00 5
Non-selective feeding meiofauna (MeiNF) 12.42 ± 3.62 2.46 ± 0.82 0.96 ± 0.83 5
Predatory+omnivore meiofauna (MeiPO) 2.42 ± 0.70 0.63 ± 0.21 0.34 ± 0.29 5
Surface deposit feeding macrofauna (MacSDF) 0.86 0.52 ± 0.56 0.40 ± 0.71 6, 7
Deposit feeding macrofauna (MacDF) 0.39 2.28 ± 0.82 0.32 ± 0.42 6, 7
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Suspension feeding macrofauna (MacSF) 0.04 0.73 ± 0.17 0.82 ± 1.01 6, 7
Predatory+scavenging macrofauna (MacPS) 17.6 1.02 ± 0.30 2.00 ± 3.57 6, 7
Surface deposit feeding megafauna (MegSDF) 21.35 ± 10.43 6, 7
Deposit feeding megafauna (MegDF) 494.7 ± 703.0 6, 7
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Table 2. Equality and inequality constraints on processes implemented for the food web models of Nazaré canyon. Values designated as single
number implies that the data are implemented as equality and values designated between “[,]” indicates [minimum value, maximum value] and
are implemented as inequalities. Value in italic implies it was modified to allow the model to be solved (see Results and Discussion)References
are: 1) Epping et al. (2002) and references therein, 2) Danovaro et al. (unpub. data),3) del Giorgio and Cole (1998), 4) Middelboe and Glud
(2006), 5) Danovaro et al. (2008), 6) Van Oevelen et al. (2006b) and references therein, 7) Hendriks (1999), 8) Tenore (1982), 9) Ruhl (2007),
11) Burdige et al. (1999).
Inequality description Upper Middle Lower Unit Reference
Temperature limitation (Tlim) 0.54 0.35 0.30 - See text
Degradation rate of lDet1 [2.74·10-3,3.29·10-2] [2.74·10-3,3.29·10-2] [2.74·10-3,3.29·10-2] d-1 1
Degradation rate of sDet1 [8.21·10-4, 1.51·10-2] [8.21·10-4, 1.51·10-2] [8.21·10-4, 1.51·10-2] d-1 1
Degradation rate of rDet1 [2.27·10-6, 8.22·10-4] [2.27·10-6, 8.22·10-4] [2.27·10-6, 8.22·10-4] d-1 1
Prokaryotic C production [1.44, 7.20] [0.25, 1.25] [0.49, 2.44] mmol C m-2 d-1 2
Prokaryotic growth efficiency2 [0.05, 0.45] [0.05, 0.45] [0.05, 0.45] - 3
Viral lysis of prokaryotic production [0.40, 1.00] [0.40, 1.00] [0.40, 1.00] - 4, 5
Faunal maintenance respiration Tlim·0.01·Stock Tlim·0.01·Stock Tlim·0.01·Stock mmol C m-2 d-1 6
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Assimilation efficiency of labile
sources Mei3
[0.57, 0.77] [0.57, 0.77] [0.57, 0.77] - 6, 7
Assimilation efficiency of semi-labile
detritus Mei3
[0.29, 0.39] [0.29, 0.39] [0.29, 0.39] - 6, 7
Net growth efficiency Mei4 [0.60, 0.90] [0.60, 0.90] [0.60, 0.90] - 7
Production rate Mei5 Tlim·[0.05, 0.20] Tlim·[0.05, 0.20] Tlim·[0.05, 0.20] d-1 7
Mortality rate Mei5 Tlim·[0, 0.20] d-1 7
Feeding preference MeiSF, MacSDF
and MegSDF6
[50, 100] [50, 100] [50, 100] - See text
Feeding preference MeiNSF, MacDF
and MegDF6
[1, 10] [1, 10] [1, 10] - See text
Feeding preference MeiPO, MacPS
and MegPS7
[0.75, 1.00] [0.75, 1.00] [0.75, 1.00] - See text
Assimilation efficiency of labile
sources of Mac and Meg3
[0.40, 0.75] [0.40, 0.75] [0.40, 0.75] - 6, 7
Assimilation efficiency of semi-labile [0.20, 0.38] [0.20, 0.38] [0.20, 0.38] - See text
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detritus of Mac and Meg3
Net growth efficiency Mac and Meg4 [0.50, 0.70] [0.50, 0.70] [0.50, 0.70] - 6, 7
Production rate Mac5 Tlim·[0.01, 0.05] Tlim·[0.01, 0.05] Tlim·[0.01, 0.05] d-1 7, 8
Mortality rate Mac5 Tlim·[0.0, 0.05] Tlim·[0.0, 0.05] Tlim·[0.0, 0.05] d-1 7, 8
Production rate Meg5 Tlim·[0.0027, 0.0137] Tlim·[0.0027, 0.0137] Tlim·[0.0027, 0.0137] d-1 9
Mortality rate Meg5 Tlim·[0.0, 0.0137] Tlim·[0.0, 0.0137] Tlim·[0.0, 0.0137] d-1 9
Prokaryotic respiration as fraction of
respiration by Bac, Mei and Mac
[0.60, 1.00] [0.60, 1.00] [0.30, 1.00] 1, see Text
Respiration of Bac, Mei and Mac [1.02, 4.91] [0.75, 2.3] [0.36, 0.90] mmol C m-2 d-1 1
Carbon deposition from lDet_w,
sDet_w, rDet_w and by MacSF
[0.96, 9.4] [0.64, 3.9] [0.31, 1.3] mmol C m-2 d-1 1
Burial efficiency [0.15, 0.48] [0.08, 0.43] [0.11, 0.36] - 1
DOC Efflux from sediment relative to
total POC input
[0, 0.10] [0, 0.10] [0, 0.10] - 11
1 Degradation rate is defined as outflows from detritus compartment divided its stock: .
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2 Prokaryotic growth efficiency is defined as fraction of prokaryotic carbon uptake used for production: .
3 Assimilation efficiency is defined as fraction of ingested carbon being assimilated: .
4 Net growth efficiency is defined as:
5 The mortality and production rates are biomass-specific.
6 Feeding preference is defined as and is 1 when food sources are consumed in their stock
proportion.
7 Feeding preference is defined as fraction of total ingested met by predation.
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Table 3. Nomenclature of symbols used in calculation of network indices.
Term Description
Number of internal compartments in the network, excluding 0 (zero), and
External source (i.e. detritus input)
Useable export from the food web (i.e. secondary production)
Unusable export from the food web (i.e. respiration and DOC efflux)
Flow from compartment to where represents the columns of the flow matrix
and the rows
Flow matrix, excluding flows to and from the externals
Total inflows to compartment
Total outflows from compartment
Total inflows to compartment , excluding inflow from external sources
Total outflows from compartment , excluding outflow to external sources
A negative state derivative, considered as a gain to the system pool of mobile
energy
A positive state derivative, considered as a loss from the system pool of mobile
energy
Flow into compartment from outside the network
Flow out of the network for compartment to compartments and ,
respectively
The number of species with which both and interact divided by the number of
species with which either or interact
Identity matrix
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Table 4. Algorithms for the calculation of the network indices; see Table 3 for symbols.Index name Code FormulaTotal System Throughput
T..
Total System Throughflow
TST
Total System cycled throughflow
cTST
Finn’s Cycling Index
FCI
Average Mutual Information
AMI
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Table 5. Model derived total respiration (mmol C m-2 d-1) and the biotic contributions (%) to total respiration in the food webs of the upper, middle and lower sections of the Nazaré canyon. See Table 1 for abbreviations.
Compartment Upper Middle LowerTotal respiration 4.52±0.28 5.06±0.30 0.86±0.02Bac 70.0 37.9 81.7MeiSF 6.1 1.0 8.2MeiNF 11.8 1.5 3.2MeiPO 2.6 0.4 1.1MacSDF 0.5 0.17 0.7MacDF 0.22 0.7 0.5MacSF 0.02 0.2 1.25MacPS 8.23 0.3 3.3MegSDF 2.89MegDF 54.5
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Table 6. Comparison of network indices calculated for the different sections of the Nazaré canyon. The numbers indicate the fraction of network values that are higher in one section as compared to another section based on a pair-wise comparison. Significant differences are in italic and highly significant differences are in bold. Network index upper > middle upper > lower middle > lower
0.62 1.00 1.00
1.00 0.03 0.00
0.43 0.93 0.95
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Figure legends
Fig. 1. Food webs picturing scaled carbon flows (mmol C m-2 d-1) in the upper, middle
and lower sections of the Nazaré canyon. All carbon flows are depicted in the
top row (A-C), carbon flows are truncated at a maximum value of 1.5 mmol C
m-2 d-1 in the middle row (D-F) and at 0.15 mmol C m-2 d-1 in the bottom row
(G-I). See Table 1 for abbreviations of food web compartments. Other
abbreviations are: DOC is dissolved organic carbon in the sediment, lDet_w,
sDet_w and rDet_w are labile, semi-labile and refractory detritus in the water
column, DOC_w is dissolved organic carbon in the water column and DIC is
dissolved inorganic carbon.
Fig. 2. Faunal diets in the upper (A), middle (B) and lower (C) sections of the Nazaré
canyon. See Table 1 and Fig. 1 for abbreviations.
Fig. 3. Fate of secondary production (%) of prokaryotes (A-C), meiofauna (D-F),
macrofauna (G-I) and megafauna (J). Absolute production (mmol C m-2 d-1) is
plotted above the compartment. The possible fates of this secondary production
are maintenance respiration (“maint”), mortality other than predation (“mort”),
export (“exp”) and predation by meiofauna (“mei”), macrofauna (“mac”) and
megafauna (“meg”).
Fig. 4. Box plots of the network indices total system throughput (A), Finn cycling
index (B) and average mutual information (C) of the upper, middle
and lower sections of the Nazaré canyon.
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Upper region
A
lDetsDet
rDet
DOC
Pro
MeiSF
MeiNF
MeiPOMacSDFMacDFMacSFMacPS
MegSDF
MegDF
lDet_w
sDet_w
rDet_w
DOC_w
DICBurial Export
150.00015
Middle region
B
lDetsDet
rDet
DOC
Pro
MeiSF
MeiNF
MeiPOMacSDFMacDFMacSFMacPS
MegSDF
MegDF
lDet_w
sDet_w
rDet_w
DOC_w
DICBurial Export
150.00015
Lower region
C
lDetsDet
rDet
DOC
Pro
MeiSF
MeiNF
MeiPOMacSDFMacDFMacSFMacPS
MegSDF
MegDF
lDet_w
sDet_w
rDet_w
DOC_w
DICBurial Export
150.00015
D
lDetsDet
rDet
DOC
Pro
MeiSF
MeiNF
MeiPOMacSDF
MacDFMacSFMacPS
MegSDF
MegDF
lDet_w
sDet_w
rDet_w
DOC_wDIC
Burial Export
1.50.00015
E
lDetsDet
rDet
DOC
Pro
MeiSF
MeiNF
MeiPOMacSDF
MacDFMacSFMacPS
MegSDF
MegDF
lDet_w
sDet_w
rDet_w
DOC_wDIC
Burial Export
1.50.00015
F
lDetsDet
rDet
DOC
Pro
MeiSF
MeiNF
MeiPOMacSDF
MacDFMacSFMacPS
MegSDF
MegDF
lDet_w
sDet_w
rDet_w
DOC_wDIC
Burial Export
1.50.00015
G
lDetsDet
rDet
DOC
Pro
MeiSF
MeiNF
MeiPOMacSDF
MacDFMacSFMacPS
MegSDF
MegDF
lDet_w
sDet_w
rDet_w
DOC_wDIC
Burial Export
0.150.00015
H
lDetsDet
rDet
DOC
Pro
MeiSF
MeiNF
MeiPOMacSDF
MacDFMacSFMacPS
MegSDF
MegDF
lDet_w
sDet_w
rDet_w
DOC_wDIC
Burial Export
0.150.00015
I
lDetsDet
rDet
DOC
Pro
MeiSF
MeiNF
MeiPOMacSDF
MacDFMacSFMacPS
MegSDF
MegDF
lDet_w
sDet_w
rDet_w
DOC_wDIC
Burial Export
0.150.00015
Figure 1
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Mei
SF
Mei
NF
Mei
PO
Mac
SD
F
Mac
DF
Mac
SF
Mac
PS
Meg
SD
F
Meg
DF
A) Upper region
Die
t con
tribu
tion
(-)
0.0
0.2
0.4
0.6
0.8
1.0sDet_wlDet_wMacSFMacDFMacSDFMeiPOMeiNFMeiSFProsDetlDet
Mei
SF
Mei
NF
Mei
PO
Mac
SD
F
Mac
DF
Mac
SF
Mac
PS
Meg
SD
F
Meg
DF
B) Middle region
Die
t con
tribu
tion
(-)
0.0
0.2
0.4
0.6
0.8
1.0sDet_wlDet_wMacSFMacDFMacSDFMeiPOMeiNFMeiSFProsDetlDet
Mei
SF
Mei
NF
Mei
PO
Mac
SD
F
Mac
DF
Mac
SF
Mac
PS
Meg
SD
F
Meg
DF
C) Lower region
Die
t con
tribu
tion
(-)
0.0
0.2
0.4
0.6
0.8
1.0sDet_wlDet_wMacSFMacDFMacSDFMeiPOMeiNFMeiSFProsDetlDet
Figure 2
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Upper region
65.130.9
4
pro
mort mei mac meg
1.95A
Middle region
51.711.5
1.2 35.6
pro
mort mei mac meg
1.04B
Lower region
88.210.5
1.3
pro
mort mei mac meg
0.53C
5.7 17.121.3
55.9
mei
maint mort mei mac meg
2.06D
5.6 18.322.5
17.6 36.1
mei
maint mort mei mac meg
0.34E
5.5 29.517.6
47.3
mei
maint mort mei mac meg
0.2F
24 31.82 42.2
mac
maint mort mac meg exp
0.424G
22 29.419.1 29.4
mac
maint mort mac meg exp
0.072H
22 33.811.2 33.1
mac
maint mort mac meg exp
0.048I
91.45.3
4.1
meg
maint mort meg exp
1.975J
Figure 3
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Upper Middle Low er
1020
3040
50
Tota
l sys
tem
thro
ughp
ut (m
mol
C m
2
d1
)A
Upper Middle Low er
0.05
0.10
0.15
0.20
Finn
cyc
ling
inde
x (-)
B
Upper Middle Low er
2.0
2.1
2.2
2.3
2.4
Ave
rage
mut
ual i
nfor
mat
ion
(-) C
Figure 4
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Web appendix
Mean and standard deviation of the food web flows (mmol C m-2 d-1) of the upper,
middle and lower areas of the Nazaré canyon. Empty cells indicate that the flow is not
present in the food web of the respective area.
Upper area Middle area Lower areaFlow Mean St. dev. Mean St. dev. Mean St. dev.lDet_w→lDet 3.88E-01 2.29E-01 8.10E-01 3.67E-01 5.88E-02 4.36E-02lDet_w→MacSF 1.60E-03 8.30E-04 1.97E-02 9.02E-03 1.80E-02 9.63E-03sDet_w→sDet 5.99E+00 7.90E-01 8.23E+00 8.44E-01 1.10E+00 3.48E-02sDet_w→MacSF 3.23E-03 1.66E-03 3.54E-02 1.64E-02 3.81E-02 2.07E-02rDet_w→rDet 1.58E+00 9.64E-01 2.02E-01 1.62E-01 5.01E-02 3.68E-02lDet→DOC 3.85E-01 2.47E-01 5.50E-01 3.61E-01 7.93E-02 5.22E-02sDet→DOC 1.16E+00 6.90E-01 5.15E-01 3.99E-01 5.09E-01 7.73E-02rDet→DOC 2.52E+00 6.34E-01 1.64E+00 3.23E-01 2.26E-01 6.99E-02lDet→MeiSF 2.83E-01 1.85E-01 9.08E-02 5.09E-02 4.25E-02 2.68E-02lDet→MeiNF 1.09E-01 7.60E-02 2.10E-02 1.39E-02 2.50E-03 1.68E-03lDet→MeiPO 2.62E-02 2.21E-02 4.71E-03 3.93E-03 2.10E-03 1.76E-03lDet→MacSDF 9.97E-03 8.45E-03 4.09E-03 3.40E-03 1.62E-03 1.36E-03lDet→MacDF 1.19E-03 1.01E-03 4.65E-03 3.93E-03 2.30E-04 1.90E-04lDet→MacPS 6.17E-02 5.15E-02 3.13E-03 2.67E-03 5.32E-03 4.41E-03lDet→MegSDF 8.82E-02 6.08E-02lDet→MegDF 2.31E-01 1.26E-01sDet→MeiSF 1.22E+00 2.22E-01 2.64E-01 6.10E-02 4.01E-01 4.31E-02sDet→MeiNF 4.43E+00 4.99E-01 5.89E-01 7.03E-02 2.28E-01 3.00E-02sDet→MeiPO 5.83E-02 3.14E-02 1.02E-02 5.40E-03 4.64E-03 2.46E-03sDet→MacSDF 5.68E-02 1.16E-02 2.33E-02 4.74E-03 2.51E-02 4.22E-03sDet→MacDF 6.10E-02 9.98E-03 2.35E-01 3.79E-02 3.36E-02 4.58E-03sDet→MacPS 1.71E-01 8.80E-02 6.74E-03 3.63E-03 1.33E-02 6.20E-03sDet→MegSDF 1.72E-01 6.78E-02sDet→MegDF 6.90E+00 6.68E-01rDet→Burial 3.05E+00 7.98E-01 3.85E+00 3.47E-01 3.35E-01 3.99E-02DOC→DOC_w 2.16E-01 1.23E-01 2.86E-01 1.48E-01 4.71E-02 2.30E-02DOC→Bac 5.14E+00 4.23E-01 2.96E+00 1.85E-01 1.23E+00 3.51E-02Bac→DIC 3.18E+00 3.16E-01 1.91E+00 1.03E-01 7.05E-01 2.56E-02Bac→DOC 1.28E+00 3.45E-01 5.38E-01 1.02E-01 4.65E-01 3.49E-02Bac→MeiSF 4.25E-01 1.89E-01 9.33E-02 5.08E-02 5.05E-02 2.44E-02Bac→MeiNF 1.42E-01 8.58E-02 2.13E-02 1.40E-02 2.55E-03 1.68E-03Bac→MeiPO 2.74E-02 2.26E-02 4.70E-03 3.92E-03 2.10E-03 1.78E-03Bac→MacSDF 1.04E-02 8.66E-03 4.12E-03 3.42E-03 1.62E-03 1.38E-03Bac→MacDF 1.21E-03 1.03E-03 4.63E-03 3.93E-03 2.30E-04 1.90E-04Bac→MacPS 6.40E-02 5.23E-02 3.04E-03 2.60E-03 5.19E-03 4.23E-03
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Bac→MegSDF 9.06E-02 6.11E-02Bac→MegDF 2.83E-01 9.85E-02MeiSF→DIC 2.77E-01 9.63E-02 7.19E-02 2.49E-02 7.07E-02 1.48E-02MeiSF→lDet 1.20E-01 9.33E-02 2.69E-02 2.15E-02 3.46E-02 1.47E-02MeiSF→sDet 2.42E-01 6.92E-02 6.38E-02 1.87E-02 3.18E-02 7.75E-03MeiSF→rDet 8.12E-01 1.57E-01 1.76E-01 4.34E-02 2.70E-01 3.28E-02MeiSF→MeiPO 1.71E-01 1.09E-01 3.51E-02 2.14E-02 2.07E-02 7.80E-03MeiSF→MacSDF 9.87E-03 8.27E-03 3.78E-03 3.21E-03 1.63E-03 1.38E-03MeiSF→MacDF 1.19E-03 1.02E-03 4.21E-03 3.63E-03 2.30E-04 1.90E-04MeiSF→MacPS 2.97E-01 1.65E-01 1.50E-02 1.07E-02 6.35E-02 1.12E-02MeiSF→MegSDF 2.46E-02 2.01E-02MeiSF→MegDF 2.69E-02 2.11E-02MeiNF→DIC 5.34E-01 1.87E-01 7.66E-02 2.21E-02 2.78E-02 7.16E-03MeiNF→lDet 1.36E-01 1.00E-01 2.78E-02 2.13E-02 1.62E-02 9.22E-03MeiNF→sDet 8.30E-02 2.92E-02 1.41E-02 4.95E-03 1.68E-03 5.90E-04MeiNF→rDet 2.93E+00 3.65E-01 3.94E-01 5.37E-02 1.55E-01 2.32E-02MeiNF→MeiPO 2.68E-01 1.12E-01 4.15E-02 2.19E-02 1.41E-02 7.36E-03MeiNF→MacSDF 1.01E-02 8.48E-03 3.80E-03 3.23E-03 1.59E-03 1.35E-03MeiNF→MacDF 1.20E-03 1.03E-03 4.25E-03 3.69E-03 2.30E-04 2.00E-04MeiNF→MacPS 7.15E-01 1.45E-01 1.59E-02 1.11E-02 1.71E-02 9.54E-03MeiNF→MegSDF 2.58E-02 2.05E-02MeiNF→MegDF 2.79E-02 2.15E-02MeiPO→DIC 1.18E-01 3.62E-02 2.07E-02 6.21E-03 9.50E-03 2.69E-03MeiPO→lDet 9.71E-02 6.21E-02 7.65E-03 6.17E-03 7.60E-03 4.54E-03MeiPO→sDet 1.77E-01 4.72E-02 3.07E-02 8.07E-03 1.42E-02 3.64E-03MeiPO→rDet 3.85E-02 2.09E-02 6.72E-03 3.58E-03 3.06E-03 1.63E-03MeiPO→MacSDF 9.68E-03 8.29E-03 2.99E-03 2.68E-03 1.53E-03 1.32E-03MeiPO→MacDF 1.19E-03 1.03E-03 3.15E-03 2.85E-03 2.20E-04 1.90E-04MeiPO→MacPS 1.10E-01 6.36E-02 6.75E-03 5.65E-03 7.54E-03 4.56E-03MeiPO→MegSDF 9.87E-03 7.07E-03MeiPO→MegDF 7.77E-03 6.32E-03MacSDF→DIC 2.21E-02 3.41E-03 8.63E-03 1.35E-03 5.75E-03 8.80E-04MacSDF→lDet 5.55E-03 3.97E-03 2.24E-03 1.59E-03 1.46E-03 1.04E-03MacSDF→sDet 2.58E-02 7.39E-03 9.61E-03 2.84E-03 3.93E-03 1.21E-03MacSDF→rDet 4.21E-02 1.00E-02 1.73E-02 4.08E-03 1.91E-02 3.77E-03MacSDF→MacPS 5.60E-03 4.02E-03 2.13E-03 1.56E-03 1.45E-03 1.04E-03MacSDF→Export 5.63E-03 4.01E-03 2.21E-03 1.59E-03 1.46E-03 1.05E-03MacDF→DIC 9.94E-03 1.52E-03 3.77E-02 5.83E-03 4.70E-03 6.70E-04MacDF→lDet 2.48E-03 1.79E-03 9.77E-03 6.91E-03 1.19E-03 8.40E-04MacDF→sDet 2.73E-03 9.30E-04 9.46E-03 3.23E-03 5.00E-04 1.60E-04MacDF→rDet 4.68E-02 9.03E-03 1.80E-01 3.42E-02 2.60E-02 4.13E-03MacDF→MacPS 2.57E-03 1.83E-03 8.86E-03 6.47E-03 1.17E-03 8.50E-04MacDF→Export 2.51E-03 1.81E-03 9.99E-03 6.95E-03 1.18E-03 8.50E-04MacSF→DIC 9.40E-04 1.80E-04 1.11E-02 2.06E-03 1.08E-02 1.97E-03MacSF→lDet 2.50E-04 1.80E-04 2.94E-03 2.16E-03 2.82E-03 2.04E-03MacSF→sDet 7.70E-04 4.80E-04 9.38E-03 5.37E-03 8.63E-03 5.52E-03
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MacSF→rDet 2.38E-03 1.30E-03 2.59E-02 1.27E-02 2.83E-02 1.63E-02MacSF→MacPS 2.50E-04 1.80E-04 2.84E-03 2.10E-03 2.78E-03 2.03E-03MacSF→Export 2.50E-04 1.80E-04 2.94E-03 2.13E-03 2.84E-03 2.06E-03MacPS→DIC 3.72E-01 6.33E-02 1.64E-02 2.67E-03 2.85E-02 3.83E-03MacPS→lDet 1.27E-01 7.52E-02 6.36E-03 3.72E-03 1.09E-02 5.78E-03MacPS→sDet 6.35E-01 1.31E-01 3.07E-02 8.29E-03 5.79E-02 9.04E-03MacPS→rDet 1.22E-01 6.39E-02 4.82E-03 2.65E-03 9.50E-03 4.53E-03MacPS→Export 1.71E-01 7.71E-02 6.17E-03 3.71E-03 1.05E-02 5.92E-03MegSDF→DIC 1.46E-01 1.56E-02MegSDF→lDet 1.41E-02 9.82E-03MegSDF→sDet 1.13E-01 4.10E-02MegSDF→rDet 1.24E-01 5.14E-02MegSDF→Export 1.42E-02 9.76E-03MegDF→DIC 2.75E+00 2.47E-01MegDF→lDet 9.07E-02 7.22E-02MegDF→sDet 2.07E-01 5.73E-02MegDF→rDet 4.36E+00 4.22E-01MegDF→Export 6.77E-02 5.22E-02
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