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: d.vanoevelen@nioo.knaw.nl

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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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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

communities and their roles in sedimentary carbon cycling. Limnology and

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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6

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

50

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

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1.0sDet_wlDet_wMacSFMacDFMacSDFMeiPOMeiNFMeiSFProsDetlDet

Mei

SF

Mei

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SD

F

Mac

DF

Mac

SF

Mac

PS

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SD

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DF

C) Lower region

Die

t con

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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

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(-) 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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3

4

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

63

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

64

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