Canyon conditions impact carbon flows in food webs of three sections of the Nazaré canyon

Deep-Sea Research II 58 (2011) 2461–2476

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Canyon conditions impact carbon flows in food webs of three sections of the Nazare´ canyon Dick van Oevelen a,n, Karline Soetaert a, R. Garcia b,c, Henko C. de Stigter d, Marina R. Cunha e, Antonio Pusceddu f, Roberto Danovaro f a

Centre for Estuarine and Marine Ecology, Netherlands Institute of Ecology (NIOO-KNAW), PO Box 140, 4400 AC Yerseke, The Netherlands Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany c ´neo de Estudios Avanzados, Miquel Marque´s 21, 07190 Esporles, Spain Department of Global Change Research, IMEDEA (CSIC-UIB) Instituto Mediterra d Royal Netherlands Institute for Sea Research (NIOZ), PO Box 59, 1790 AB Den Burg, Texel, The Netherlands e Centro de Estudos do Ambiente e do Mar (CESAM), Departamento de Biologia, Universidade de Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal f Department of Marine Science, Polytechnic University of Marche, Via Brecce Bianche, 60131 Ancona, Italy b

a r t i c l e i n f o

abstract

Available online 16 April 2011

Submarine canyons 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 Nazare´ 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 7 0.84 and 9.30 7 0.71 mmol C m  2 d  1, respectively). OM input to the lower section was however almost 6–7 times lower (1.26 7 0.03 mmol C m  2 d  1). 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 OM 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 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. & 2011 Elsevier Ltd. All rights reserved.

Keywords: Food web Linear inverse model Organic matter Carbon processing Respiration Benthos Nazare´ canyon Atlantic Ocean

1. 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;

n

Corresponding author. E-mail address: [email protected] (D. van Oevelen).

0967-0645/$ - see front matter & 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.dsr2.2011.04.009

de Stigter et al., 2007) and organic matter (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), benthic standing stocks of nematodes (Ingels et al., 2009) and deposit feeding holothurians

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(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 (Ty) 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, 2004). An index that is claimed to be related to food web maturity is average mutual information (AMI) that gauges how orderly and coherently flows are interconnected (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 Nazare´ 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., 2011). 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 flatfloored valley that gently descends from 4000 to 5000 m depth (de Stigter et al., 2007; Masson et al., 2011). 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 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 Nazare´ 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 Nazare´ canyon. The deeper canyon section is where the canyon widens into a kilometers-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 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 Nazare´ canyon. The observed food web structures and selected network indices are examined as a function of the characteristics of the respective canyon section.

2. Methods ´ canyon characteristics 2.1. Nazare The Nazare´ 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 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 (14–18 1C) and saline (35.4–35.8) water at the surface (North Atlantic Central Water) to cold (2 1C) 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

D. van Oevelen et al. / Deep-Sea Research II 58 (2011) 2461–2476

internal tide circulation of water with high bottom current speeds (de Stigter et al., 2007). The seabed of the Nazare´ 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, centimeterthick 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 however limited to 300–750 m. Chemical and biological data were available on the concentration of total carbohydrates, lipids and proteins in the sediment (Pusceddu et al., 2010), sedimentary chl a content (Garcia and Thomsen, 2008), sediment diagenesis (Epping et al., 2002), prokaryotic heterotrophic carbon production (Danovaro, unpublished), nematode trophic structure (Danovaro et al., 2009) and the macro- and megafaunal community structure (Cunha, unpublished; Cunha et al., 2011). Such data on biotic and abiotic carbon stocks and transformation rates are perfectly suited to quantify food webs of the three sections of the Nazare´ canyon using linear inverse modeling. 2.2. Linear inverse models The food web models developed for the Nazare´ 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 Section 2.4) 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 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 Nazare´ 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

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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 predatorþscavenger (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 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 semilabile 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 Nazare´ 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; Garcı´a et al., 2008), concentration of total carbohydrates, lipids and proteins in the sediment (Pusceddu et al., 2010) heterotrophic prokaryotic C production (Danovaro, unpublished), 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., unpublished). 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 (Garcia and Thomsen, 2008), which were converted to carbon units by assuming a carbon to chlorophyll 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 semilabile 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

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Table 1 Standing stocks (in mmol C m  2 as mean 7 standard deviation) of the food web compartments for the upper, middle and lower section of the Nazare´ canyon. See Section 2.4 for description. References are as follows: (1) Garcia and Thomsen (2008), (2) Pusceddu et al. (2010), (3) Epping et al. (2002), (4) Danovaro (unpublished), (5) biomass is Danovaro et al. (unpublished), but biodiversity analysis by Danovaro et al. (2009), (6) Tyler et al. (2009) and (7) Cunha et al. (unpublished). Compartment

Upper

Middle

Lower

Ref.

Labile detritus (lDet) Semi-labile detritus (sDet) Refractory detritus (rDet) Prokaryotes (Pro) Selective feeding meiofauna (MeiSF) Non-selective feeding meiofauna (MeiNF) Predatory þomnivore meiofauna (MeiPO) Surface deposit feeding macrofauna (MacSDF) Deposit feeding macrofauna (MacDF) Suspension feeding macrofauna (MacSF) Predatory þscavenging macrofauna (MacPS) Surface deposit feeding megafauna (MegSDF) Deposit feeding megafauna (MegDF)

35.8 7 19.8 5393 7 2419 66,137 4.84 7 0.08 6.80 71.98 12.42 7 3.62 2.42 7 0.70 0.86 0.39 0.04 17.6

46.9 716.4 5114 72692 66,661 3.14 70.11 2.32 70.77 2.46 70.82 0.637 0.21 0.527 0.56 2.28 70.82 0.737 0.17 1.027 0.30 21.35 710.43 494.7 7703.0

10.9 76.7 4761 7 2384 50,211 2.79 7 0.09 2.34 7 2.00 0.96 70.83 0.34 70.29 0.40 70.71 0.32 70.42 0.82 71.01 2.00 73.57

1 2 3 4 5 5 5 6, 6, 6, 6, 6, 6,

(derived from organic carbon content profiles by 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 1Aþ2A), 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 predatoryþ 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 (o 3%) in the upper section, higher in the middle section with 48%, 14% and 19%, and negligible in the lower section (o1%), 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., dX/ dt¼0. This assumption introduces only limited bias in the model solution (Ve´zina 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 Nazare´ 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 3 H-leucine (final concentration 0.2 mmol L  1), were incubated at in situ temperature for 1 h 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.

7 7 7 7 7 7

The following equation was used for calculating prokaryotic C production: PCP LI 131.2 (%Leu)—1 (C:protein) ID where PCP is the 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 reported by 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). 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 1C (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

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Table 2 Equality and inequality constraints on processes implemented for the food web models of Nazare´ 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 Sections 3 and 4) References are as follows: (1) Epping et al. (2002) and references therein, (2) Danovaro et al. (unpublished), (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) and (11) Burdige et al. (1999). Inequality description

Upper

Middle

Lower

Unit

Ref.

Temperature limitation (Tlim) Degradation rate of lDeta

0.54 [2.74  10  3, 3.29  10  2] [8.21  10  4, 1.51  10  2] [2.27  10  6, 8.22  10  4] [1.44, 7.20] [0.05, 0.45] [0.40, 1.00] Tlim  0.01  Stock

0.35 [2.74  10  3, 3.29  10  2] [8.21  10  4, 1.51  10  2] [2.27  10  6, 8.22  10  4] [0.25, 1.25] [0.05, 0.45] [0.40, 1.00] Tlim  0.01  Stock

0.30 [2.74  10  3, 3.29  10  2] [8.21  10  4, 1.51  10  2] [2.27  10  6, 8.22  10  4] [0.49, 2.44] [0.05, 0.45] [0.40, 1.00] Tlim  0.01  Stock

– d1

See text 1

d1

1

[0.57, 0.77] [0.29, 0.39] [0.60, 0.90] Tlim  [0.05, 0.20] Tlim  [0, 0.20] [50, 100] [1, 10] [0.75, 1.00] [0.40, 0.75] [0.20, 0.38]

[0.57, 0.77] [0.29, 0.39] [0.60, 0.90] Tlim  [0.05, 0.20]

[0.57, 0.77] [0.29, 0.39] [0.60, 0.90] Tlim  [0.05, 0.20]

[50, 100] [1, 10] [0.75, 1.00] [0.40, 0.75] [0.20, 0.38]

[50, 100] [1, 10] [0.75, 1.00] [0.40, 0.75] [0.20, 0.38]

[0.50, 0.70] Tlim  [0.01, 0.05] Tlim  [0.0, 0.05] Tlim  [0.0027, 0.0137] Tlim  [0.0, 0.0137] [0.60, 1.00]

[0.50, 0.70] Tlim  [0.01, 0.05] Tlim  [0.0, 0.05] Tlim  [0.0027, 0.0137] Tlim  [0.0, 0.0137] [0.60, 1.00]

[1.02, 4.91] [0.96, 9.4] [0.15, 0.48] [0, 0.10]

Degradation rate of sDeta Degradation rate of rDeta Prokaryotic C production Prokaryotic growth efficiencyb Viral lysis of prokaryotic production Faunal maintenance respiration Assimilation efficiency of labile sources Meic Assimilation efficiency of semi-labile detritus Meic Net growth efficiency Meid Production rate Meie Mortality rate Meie Feeding preference MeiSF, MacSDF and MegSDFf Feeding preference MeiNSF, MacDF and MegDFf Feeding preference MeiPO, MacPS and MegPSg Assimilation efficiency of labile sources of Mac and Megc Assimilation efficiency of semi-labile detritus of Mac and Megc Net growth efficiency Mac and Megd Production rate Mace Mortality rate Mace Production rate Mege Mortality rate Mege Prokaryotic respiration as fraction of respiration by Bac, Mei and Mac Respiration of Bac, Mei and Mac Carbon deposition from lDet_w, sDet_w, rDet_w and by MacSF Burial efficiency DOC Efflux from sediment relative to total POC input

d1

1 2

1

mmol C m d – – mmol C m  2 d  1 mmol C m  2 d  1 – – d1 d1 – – – – –

2 3 4, 5 6

[0.50, 0.70] Tlim  [0.01, 0.05] Tlim  [0.0, 0.05] Tlim  [0.0027, 0.0137] Tlim  [0.0, 0.0137] [0.30, 1.00]

– d1 d1 d1 d1

[0.75, 2.3] [0.64, 3.9]

[0.36, 0.90] [0.31, 1.3]

mmol C m  2 d  1 mmol C m  2 d  1

6, 7 7, 8 7, 8 9 9 1, see text 1 1

[0.08, 0.43] [0, 0.10]

[0.11, 0.36] [0, 0.10]

– –

1 11

6, 7 6, 7 7 7 7 See text See text See text 6, 7 See text

a

Degradation rate is defined as outflows from detritus compartment j divided its stock: Sk xj-k =Stockj . Prokaryotic growth efficiency is defined as fraction of prokaryotic carbon uptake used for production: xDOC-PRO xPRO-DIC =xDOC-PRO . c Assimilation efficiency is defined as fraction of ingested carbon being assimilated: Si xj-k xj-detritus =Si xj-k . d Net growth efficiency is defined as Si xj-k xj-detritus ðxj-DIC maintenance respirationÞ=Si xj-k xj-detritus e The mortality and production rates are biomass-specific. f Feeding preference is defined as ðingested labile carbon=total labile carbonÞ=ðSlabile carbon stocks=S carbon stocks) and is 1 when food sources are consumed in their stock proportion. g Feeding preference is defined as fraction of total ingested met by predation. b

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 surfacedeposit 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 4500 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 2–7), 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 1–10 for deposit feeders and strong selectivity (50–100) 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 were assumed rely between 75% and 100% through predatory feeding to account for this (Table 2). 2.5. Network indices The network indices Ty, FCI and AMI 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 by 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

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section 1 are larger than the ones of section 2 (and consequently 10% of the values are lower). We define differences of 490% and o10% as significant difference and 495% and o5% as highly significant difference.

3. 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 detritus (4761  8.21  10  4 ¼3.9 mmol C m  2 d  1, Tables 1 and 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

Table 3 Nomenclature of symbols used in calculation of network indices. Term

Description

n

Number of internal compartments in the network, excluding 0 (zero), n þ1 and nþ 2 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 j Q to i where j represents the columns of the flow matrix and i the rows Flow matrix, excluding flows to and from the externals

j ¼0 j ¼nþ 1 j ¼nþ 2 Tij Tij Ti. T.j Ti Tj ðx_ i Þ ðx_ i Þ þ zi0 yn þ 1, yn þ 2,j cij l

Total inflows to compartment j Total outflows from compartment j Total inflows to compartment i excluding inflow from external sources Total outflows from compartment j 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 i E from outside the network Flow out of the network for compartment j to compartments nþ 1 and nþ 2 respectively The number of species with which both i j interact divided by the number of species with which either i j interact Identity matrix

temperature limitation factor (Tlim¼0.30, 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 Nazare´ canyon are reported in 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 7.9870.84 (5% labile, 75% semi-labile and 20% refractory detritus), 9.3070.71 (9% labile, 89% semi-labile and 2% refractory detritus) and 1.2670.03 (6% labile, 90% semi-labile and 4% refractory detritus) for the upper, middle and lower canyon section, respectively. Total respiration was 4.5270.28, 5.0670.30 and 0.8670.02 mmol C m  2 d  1 and organic carbon burial was 3.0570.80, 3.8570.35 and 0.3470.04 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 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 Nazare´ canyon. See Table 1 for abbreviations. Compartment

Upper

Middle

Lower

Total respiration Bac MeiSF MeiNF MeiPO MacSDF MacDF MacSF MacPS MegSDF MegDF

4.52 70.28 70.0 6.1 11.8 2.6 0.5 0.22 0.02 8.23

5.06 70.30 37.9 1.0 1.5 0.4 0.17 0.7 0.2 0.3 2.89 54.5

0.86 70.02 81.7 8.2 3.2 1.1 0.7 0.5 1.25 3.3

Table 4 Algorithms for the calculation of the network indices; see Table 3 for symbols. Index name

Code

Formula

Total system Throughput

T..

nP þ2

n P

Tij

i¼1j¼0

Total system throughflow

TST

n P n P

½Tij þ zi0 ðx_ i Þ  ¼

i¼1j¼1

Total system cycled throughflow

TSTc

Finn’s cycling index

FCI

Average mutual information

AMI

 n  P 1 q1ij Tj

n P

i¼1j¼0

Tij T::

½Tij þ y0i ðx_ i Þ þ 

where Q ¼ ðIG0 Þ1

j¼1 TSTc TST nP þ2

n P n P

i¼1j¼1

T T

log2 Tiji: T:j::

h i where G0 ¼ Tij =maxðTi ,Tj Þ

D. van Oevelen et al. / Deep-Sea Research II 58 (2011) 2461–2476

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 0.1870.08, 0.1070.05 and 0.0270.006 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 nonselective feeding meiofauna compartment (Fig. 1A vs. 1C) and MacPS compartment (Fig. 1D vs. F) 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 H). Moreover, carbon cycling by the

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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 Nazare´ 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 fuel 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 semilabile 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 o10% 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%).

Upper region

Middle region

Lower region

Burial Export lDet DIC sDet

Burial Export lDet DIC sDet

Burial Export lDet DIC sDet

DOC_w

rDet

rDet_w

DOC_w

DOC

sDet_w

Pro

lDet_w

MeiNF

MegSDF MacPS MacSF

MeiPO MacSDF MacDF

lDet_w

DOC_w

DOC_w

sDet_w

MeiSF

MegDF

MeiPO MacSDF MacDF

lDet_w

1.5 0.00015

Burial Export lDet DIC sDet DOC_w rDet_w sDet_w lDet_w MegDF MegSDF MacPS MacSF

MegSDF MacPS MacSF

DOC_w

MeiSF

DOC_w rDet_w

DOC

sDet_w

Pro MeiSF

MegDF

MeiNF MeiPO MacSDF MacDF

lDet_w

0.15 0.00015

MegSDF MacPS MacSF

15 0.00015

MeiPO MacSDF MacDF

rDet DOC

sDet_w

Pro MeiSF

lDet_w MegDF

1.5 0.00015

MeiNF

MegSDF MacPS MacSF

Burial Export lDet DIC sDet

rDet

MeiPO MacSDF MacDF

rDet_w

MeiNF

MegSDF MacPS MacSF

MeiSF MeiNF

Burial Export lDet DIC sDet

Pro

MegDF

MeiNF

MegSDF MacPS MacSF

15 0.00015

DOC

sDet_w

Pro

Pro

MegDF

rDet

rDet_w

DOC

DOC

lDet_w

Burial Export lDet sDet DIC

rDet

lDet_w

MeiSF

MeiPO MacSDF MacDF

rDet

sDet_w

MeiNF

MegSDF MacPS MacSF

Burial Export lDet DIC sDet

rDet_w

Pro

MegDF 15 0.00015

DOC_w rDet_w

DOC

sDet_w

MeiSF

MegDF

rDet

rDet_w

MeiPO MacSDF MacDF

1.5 0.00015

Burial Export lDet sDet DIC

rDet

DOC_w

DOC

rDet_w

Pro

sDet_w

MeiSF MeiNF MeiPO MacSDF MacDF

lDet_w MegDF

0.15 0.00015

MegSDF MacPS MacSF

rDet DOC Pro MeiSF MeiNF MeiPO MacSDF MacDF

0.15 0.00015

Fig. 1. Food webs picturing scaled carbon flows (mmol C m  2 d  1) in the upper, middle and lower sections of the Nazare´ 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: DOC is dissolved organic carbon in the sediment, lDet_w, sDet_w and rDet_w are labile, semilabile and refractory detritus in the water column, DOC_w is dissolved organic carbon in the water column and DIC is dissolved inorganic carbon.

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D. van Oevelen et al. / Deep-Sea Research II 58 (2011) 2461–2476

Diet contribution (−)

1.0 sDet_w lDet_w MacSF MacDF MacSDF MeiPO MeiNF MeiSF Pro sDet lDet

0.8 0.6 0.4 0.2

M

ei S M F ei N M F ei PO M ac SD M F ac D M F ac S M F ac M PS eg S M DF eg D F

0.0

Diet contribution (−)

1.0 sDet_w lDet_w MacSF MacDF MacSDF MeiPO MeiNF MeiSF Pro sDet lDet

0.8 0.6 0.4 0.2

M

ei S M F ei N M F ei PO M ac SD M F ac D M F ac S M F ac M PS eg S M DF eg D F

0.0

Diet contribution (−)

1.0 sDet_w lDet_w MacSF MacDF MacSDF MeiPO MeiNF MeiSF Pro sDet lDet

0.8 0.6 0.4 0.2

M

ei

SF

M ei N M F ei PO M ac SD M F ac D M F ac S M F ac M PS eg S M DF eg D F

0.0

Fig. 2. Faunal diets in the upper (A), middle (B) and lower (C) sections of the Nazare´ canyon. See Table 1 and Fig. 1 for abbreviations.

The diet compositions in the lower section of the Nazare´ canyon resemble overall those of the upper section (Fig. 2 A vs. 2C). Again, semi-labile detritus is most important (between 76% and 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%), surfacedeposit feeding macrofauna (each 5%), deposit-feeding macrofauna (each 1%) and predatory/scavenging macrofauna (4–5%) (Fig. 2C). The meiofaunal compartments MeiSFþMeiNF 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% to 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 (Ty), Finn cycling index (FCI) and average mutual information (AMI) were calculated for the three sections (Fig. 4) and compared (Table 6). The Ty does not differ significantly between the upper and middle sections with median values of 41.1 and 39.7 mmol C m  2 d  1, respectively, but Ty is significantly lower in the lower section with a median of 6.7 mmol C m  2 d  1 (Table 6). Differences in FCI 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. AMI 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).

4. 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 (Ve´zina 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

D. van Oevelen et al. / Deep-Sea Research II 58 (2011) 2461–2476

Upper region

Middle region

Lower region

1.95

1.04

0.53

pro

pro

pro

4

65.1

5.7 maint

24 maint

mei

17.1 mort

31.8 mort

1.2

51.7

30.9

mort

2469

mac

meg

11.5

mort

mei

mac

1.3

88.2

35.6 meg

10.5

mort

mei

mac

2.06

0.34

0.2

mei

mei

mei

21.3 55.9 mei

mac

5.6 meg

22.5 17.6

18.3

maint

mort

mei

5.5

36.1

mac

meg

maint

29.5 mort

17.6 47.3 mei

0.424

0.072

0.048

mac

mac

mac

2 mac

22

42.2 meg

exp

19.1

29.4

maint

mort

mac

22

29.4 meg

exp

maint

33.8 mort

meg

mac

11.2 mac

meg

33.1 meg

exp

1.975 meg

91.4 maint

4.1

5.3 mort

meg

exp

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’’).

sections (Appendix 1), 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 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 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 Nazare´ 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 Nazare´ canyon on rocky substrata. Moreover, quantitative data on the faunal community in the thalweg is only sparsely available and its food web 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 softsediments 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 Nazare´ 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).

D. van Oevelen et al. / Deep-Sea Research II 58 (2011) 2461–2476

Total system throughput (mmol C m−2d−1)

2470

Table 6 Comparison of network indices calculated for the different sections of the Nazare´ canyon. The numbers indicate the fraction of network values that are higher in one section as compared to another section based on a pairwise comparison. Significant differences are in italic and highly significant differences are in bold.

50

40

30

Finn cycling index (-)

>Upper 4middle

>Upper 4lower

>Middle4lower

Ty FCI AMI

0.62 1.00 0.43

1.00 0.03 0.93

1.00 0.00 0.95

20

10

Upper

Middle

Lower

Upper

Middle

Lower

0.20

0.15

0.10

0.05

2.4 Average mutual information (-)

Network index

2.3

2.2

2.1

shelf sediments was recently found to be limited to o3% (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 (Tables 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. Nevertheless, the Nazare´ 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 (Tables 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 1C 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

2.0 Upper

Middle

Lower

Fig. 4. Box plots of the network indices total system throughput Ty (A), Finn cycling index FCI (B) and average mutual information AMI (C) of the upper, middle and lower sections of the Nazare´ canyon.

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

The dynamic upper canyon receives about 870.84 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 mmol C m  2 d  1 (Epping et al., 2002). Thus, carbon inputs to the upper canyon section is higher than 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 and B), but burial efficiencies are comparable to Iberian open slopes and relate to sediment accumulations rates (Epping et al., 2002). Hence, the efficiency with

D. van Oevelen et al. / Deep-Sea Research II 58 (2011) 2461–2476

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 ( o300 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 Nazare´ canyon as compared to other open slopes that vary from 4% to 8% (Piepenburg et al., 1995; Heip et al., 2001; Soetaert et al., 2009). Rowe et al. (2008) and Baguley 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 0.04–0.11 d  1 at a temperature of 4–5 1C. Moodley et al. (2008) used a novel micro-respiration system and reported specific rates of 0.021–0.032 d  1 for intertidal (20 1C) Nematoda, Ostracoda and Foraminifera over a biomass range of 0.7–5.2 mC ind  1. Nematodes from the Gulf of Mexico are smaller (  0.1 mC 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 among others meiofauna. Intriguingly, these results typically show low biomass-specific assimilation rates of o0.01 and mostly o0.001 d  1 (Moens et al., 2007; Franco et al., 2008; Ingels et al., 2011), a limited (o5%) 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, nematodes 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 in contrast with the meiofaunal diet composition as inferred for the Nazare´ 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),

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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 ranks 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.

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 9.3070.71 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 ‘‘metazoanmacrofaunal-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 important difference 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 Y. 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 89718 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 Nazare´ 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). Amaro et al. (2010) conducted trophic studies on the holothurian M. musculus and estimated removal rates of 0.5 g C of semilabile detritus m  2 d  1. Our food web analysis even suggests higher removal rates of 2.5 g C 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 o0.1% 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

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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. 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 (1.2670.03 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 o10%. 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 (Ty), 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 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 viralmediated 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 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. ToborKaplon 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 Nazare´ 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 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

D. van Oevelen et al. / Deep-Sea Research II 58 (2011) 2461–2476

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 Nazare´ 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.

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Acknowledgments This research was supported by the HERMES project (Contract no. GOCE-CT-2005-511234), funded by the European Commission’s Sixth Framework Program under the priority ‘‘Sustainable Development, Global Change and Ecosystems’’, and HERMIONE project (Grant agreement no. 226354) funded by the European Community’s Seventh Framework Program (FP7/2007-2013). This is publication 5018 of the Netherlands Institute of Ecology (NIOO-KNAW), Yerseke.

Appendix 1 The mean flow values and standard deviations for the three sections of the Nazare´ canyon are shown in Table A1.

Table A1 Mean and standard deviation of the food web flows (mmol C m  2 d  1) of the upper, middle and lower sections of the Nazare´ canyon. Empty cells indicate that the flow is not present in the food web of the respective area. Flow

lDet_w-lDet lDet_w-MacSF sDet_w-sDet sDet_w-MacSF rDet_w-rDet lDet-DOC sDet-DOC rDet-DOC lDet-MeiSF lDet-MeiNF lDet-MeiPO lDet-MacSDF lDet-MacDF lDet-MacPS lDet-MegSDF lDet-MegDF sDet-MeiSF sDet-MeiNF sDet-MeiPO sDet-MacSDF sDet-MacDF sDet-MacPS sDet-MegSDF sDet-MegDF rDet-Burial DOC-DOC_w DOC-Bac Bac-DIC Bac-DOC Bac-MeiSF Bac-MeiNF Bac-MeiPO Bac-MacSDF Bac-MacDF Bac-MacPS Bac-MegSDF Bac-MegDF MeiSF-DIC MeiSF-lDet MeiSF-sDet MeiSF-rDet MeiSF-MeiPO MeiSF-MacSDF MeiSF-MacDF MeiSF-MacPS MeiSF-MegSDF MeiSF-MegDF MeiNF-DIC MeiNF-lDet MeiNF-sDet

Upper area

Middle area

Lower area

Mean

St. dev.

Mean

St. dev.

Mean

St. dev.

3.88E  01 1.60E  03 5.99E þ00 3.23E  -03 1.58E þ00 3.85E  01 1.16E þ00 2.52E þ00 2.83E  01 1.09E  01 2.62E  02 9.97E  03 1.19E  03 6.17E  02

2.29E  01 8.30E  04 7.90E  01 1.66E  03 9.64E  01 2.47E  01 6.90E  01 6.34E  01 1.85E  01 7.60E  02 2.21E  02 8.45E  03 1.01E  03 5.15E  02

4.36E  02 9.63E  03 3.48E  02 2.07E  02 3.68E  02 5.22E  02 7.73E  02 6.99E  02 2.68E  02 1.68E  03 1.76E  03 1.36E  03 1.90E  04 4.41E  03

2.22E  01 4.99E  01 3.14E  02 1.16E  02 9.98E  03 8.80E  02

4.01E  01 2.28E  01 4.64E  03 2.51E  02 3.36E  02 1.33E  02

4.31E  02 3.00E  02 2.46E  03 4.22E  03 4.58E  03 6.20E  03

3.05Eþ 00 2.16E  01 5.14E þ00 3.18E þ00 1.28E þ00 4.25E  01 1.42E  01 2.74E  02 1.04E  02 1.21E  03 6.40E  02

7.98E  01 1.23E  01 4.23E  01 3.16E  01 3.45E  01 1.89E  01 8.58E  02 2.26E  02 8.66E  03 1.03E  03 5.23E  02

3.35E  01 4.71E  02 1.23E þ00 7.05E  01 4.65E  01 5.05E  02 2.55E  03 2.10E  03 1.62E  03 2.30E  04 5.19E  03

3.99E  02 2.30E  02 3.51E  02 2.56E  02 3.49E  02 2.44E  02 1.68E  03 1.78E  03 1.38E  03 1.90E  04 4.23E  03

2.77E  01 1.20E  01 2.42E  01 8.12E  01 1.71E  01 9.87E  03 1.19E  03 2.97E  01

9.63E  02 9.33E  02 6.92E  02 1.57E  01 1.09E  01 8.27E  03 1.02E  03 1.65E  01

7.07E  02 3.46E  02 3.18E  02 2.70E  01 2.07E  02 1.63E  03 2.30E  04 6.35E  02

1.48E  02 1.47E  02 7.75E  03 3.28E  02 7.80E  03 1.38E  03 1.90E  04 1.12E  02

5.34E  01 1.36E  01 8.30E  02

1.87E  01 1.00E  01 2.92E  02

3.67E  01 9.02E 03 8.44E  01 1.64E  02 1.62E  01 3.61E  01 3.99E  01 3.23E  01 5.09E 02 1.39E  02 3.93E  03 3.40E 03 3.93E  03 2.67E  03 6.08E 02 1.26E  01 6.10E 02 7.03E 02 5.40E 03 4.74E  03 3.79E  02 3.63E  03 6.78E  02 6.68E  01 3.47E  01 1.48E  01 1.85E  01 1.03E 01 1.02E 01 5.08E 02 1.40E 02 3.92E  03 3.42E  03 3.93E  03 2.60E 03 6.11E  02 9.85E  02 2.49E  02 2.15E  02 1.87E  02 4.34E  02 2.14E  02 3.21E  03 3.63E  03 1.07E 02 2.01E 02 2.11E  02 2.21E  02 2.13E  02 4.95E  03

5.88E  02 1.80E  02 1.10Eþ 00 3.81E  02 5.01E  02 7.93E  02 5.09E  01 2.26E  01 4.25E  02 2.50E  03 2.10E  03 1.62E  03 2.30E  04 5.32E  03

1.22E þ00 4.43E þ00 5.83E  02 5.68E  02 6.10E  02 1.71E  01

8.10E  01 1.97E  02 8.23E þ00 3.54E  02 2.02E  01 5.50E  01 5.15E  01 1.64E þ00 9.08E  02 2.10E  02 4.71E  03 4.09E  03 4.65E  03 3.13E  03 8.82E  02 2.31E  01 2.64E  01 5.89E  01 1.02E  02 2.33E  02 2.35E  01 6.74E  03 1.72E  01 6.90E þ00 3.85E þ00 2.86E  01 2.96E þ00 1.91E þ00 5.38E  01 9.33E  02 2.13E  02 4.70E  03 4.12E  03 4.63E  03 3.04E  03 9.06E  02 2.83E  01 7.19E  02 2.69E  02 6.38E  02 1.76E–01 3.51E  02 3.78E  03 4.21E  03 1.50E  02 2.46E  02 2.69E  02 7.66E  02 2.78E  02 1.41E  02

2.78E  02 1.62E  02 1.68E  03

7.16E  03 9.22E  03 5.90E  04

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Table A1 (continued ) Flow

MeiNF-rDet MeiNF-MeiPO MeiNF-MacSDF MeiNF-MacDF MeiNF-MacPS MeiNF-MegSDF MeiNF-MegDF MeiPO-DIC MeiPO-lDet MeiPO-sDet MeiPO-rDet MeiPO-MacSDF MeiPO-MacDF MeiPO-MacPS MeiPO-MegSDF MeiPO-MegDF MacSDF-DIC MacSDF-lDet MacSDF-sDet MacSDF-rDet MacSDF-MacPS MacSDF-Export MacDF-DIC MacDF-lDet MacDF-sDet MacDF-rDet MacDF-MacPS MacDF-Export MacSF-DIC MacSF-lDet MacSF-sDet MacSF-rDet MacSF-MacPS MacSF-Export MacPS-DIC MacPS-lDet MacPS-sDet MacPS-rDet MacPS-Export MegSDF-DIC MegSDF-lDet MegSDF-sDet MegSDF-rDet MegSDF-Export MegDF-DIC MegDF-lDet MegDF-sDet MegDF-rDet MegDF-Export

Upper area

Middle area

Lower area

Mean

St. dev.

Mean

St. dev.

Mean

St. dev.

2.93Eþ 00 2.68E  01 1.01E  02 1.20E  03 7.15E  01

3.65E  01 1.12E  01 8.48E  03 1.03E  03 1.45E  01

2.32E  02 7.36E  03 1.35E  03 2.00E  04 9.54E  03

3.62E  02 6.21E  02 4.72E  02 2.09E  02 8.29E  03 1.03E  03 6.36E  02

9.50E  03 7.60E  03 1.42E  02 3.06E  03 1.53E  03 2.20E  04 7.54E  03

2.69E  03 4.54E  03 3.64E  03 1.63E  03 1.32E  03 1.90E  04 4.56E  03

2.21E  02 5.55E  03 2.58E  02 4.21E  02 5.60E  03 5.63E  03 9.94E  03 2.48E  03 2.73E  03 4.68E  02 2.57E  03 2.51E  03 9.40E  04 2.50E  04 7.70E  04 2.38E  03 2.50E  04 2.50E  04 3.72E  01 1.27E  01 6.35E  01 1.22E  01 1.71E  01

3.41E  03 3.97E  03 7.39E  03 1.00E  02 4.02E  03 4.01E  03 1.52E  03 1.79E  03 9.30E  04 9.03E  03 1.83E  03 1.81E  03 1.80E  04 1.80E  04 4.80E  04 1.30E  03 1.80E  04 1.80E  04 6.33E  02 7.52E  02 1.31E  01 6.39E  02 7.71E  02

5.37E  02 2.19E  02 3.23E  03 3.69E  03 1.11E  02 2.05E 02 2.15E  02 6.21E  03 6.17E  03 8.07E 03 3.58E  03 2.68E  03 2.85E  03 5.65E  03 7.07E 03 6.32E  03 1.35E  03 1.59E  03 2.84E  03 4.08E 03 1.56E  03 1.59E  03 5.83E  03 6.91E  03 3.23E  03 3.42E  02 6.47E  03 6.95E  03 2.06E 03 2.16E  03 5.37E  03 1.27E  02 2.10E 03 2.13E  03 2.67E  03 3.72E  03 8.29E  03 2.65E  03 3.71E  03 1.56E  02 9.82E  03 4.10E 02 5.14E  02 9.76E  03 2.47E  01 7.22E  02 5.73E  02 4.22E  01 5.22E  02

1.55E  01 1.41E  02 1.59E  03 2.30E  04 1.71E  02

1.18E  01 9.71E  02 1.77E  01 3.85E  02 9.68E  03 1.19E  03 1.10E  01

3.94E  01 4.15E  02 3.80E  03 4.25E  03 1.59E  02 2.58E  02 2.79E  02 2.07E  02 7.65E  03 3.07E  02 6.72E  03 2.99E  03 3.15E  03 6.75E  03 9.87E  03 7.77E  03 8.63E  03 2.24E  03 9.61E  03 1.73E  02 2.13E  03 2.21E  03 3.77E  02 9.77E  03 9.46E  03 1.80E  01 8.86E  03 9.99E  03 1.11E  02 2.94E  03 9.38E  03 2.59E  02 2.84E  03 2.94E  03 1.64E  02 6.36E  03 3.07E  02 4.82E  03 6.17E  03 1.46E  01 1.41E  02 1.13E  01 1.24E  01 1.42E  02 2.75E þ00 9.07E  02 2.07E  01 4.36E þ00 6.77E  02

5.75E  03 1.46E  03 3.93E  03 1.91E  02 1.45E  03 1.46E  03 4.70E  03 1.19E  03 5.00E  04 2.60E  02 1.17E  3 1.18E  03 1.08E  02 2.82E  03 8.63E  03 2.83E  02 2.78E  03 2.84E-03 2.85E  02 1.09E  02 5.79E  02 9.50E  03 1.05E  02

8.80E  04 1.04E  03 1.21E  03 3.77E  03 1.04E  03 1.05E  03 6.70E  04 8.40E  04 1.60E  04 4.13E  03 8.50E  04 8.50E  04 1.97E  03 2.04E  03 5.52E  03 1.63E  02 2.03E  03 2.06E  03 3.83E  03 5.78E  03 9.04E  03 4.53E  03 5.92E  03

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