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1
Canyon conditions impact carbon flows in food webs
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of three sections of the Nazaré canyon
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Dick van Oevelen1,*, Karline Soetaert1, Rosa García Novoa2,3, Henko de Stigter4,
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Marina da Cunha5, Antonio Pusceddu6, Roberto Danovaro6
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Centre for Estuarine and Marine Ecology, Netherlands Institute of Ecology (NIOOKNAW), POB 140, 4400 AC Yerseke, The Netherlands
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2
Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany
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3
Department of Global Change Research, IMEDEA (CSIC-UIB) Instituto
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Mediterráneo de Estudios Avanzados, Miquel Marqués 21, 07190 Esporles, Spain
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Texel, The Netherlands
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Royal Netherlands Institute for Sea Research (NIOZ), POB 59, 1790 AB Den Burg -
Centro de Estudos do Ambiente e do Mar (CESAM) & Departamento de Biologia,
Universidade de Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal
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Department of Marine Science, Polytechnic University of Marche, Via Brecce
Bianche, 60131 Ancona, Italy
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*
corresponding author: d.vanoevelen@nioo.knaw.nl
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Abstract
Submarine canyons directly transport large amounts of sediment and organic
3
matter (OM) from the continental shelf to the abyssal plain. Three carbon-based food
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web models were constructed for the upper (300 – 750 m water depth), middle (2700
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– 3500 m) and lower section (4000 – 5000 m) of the Nazaré canyon (eastern Atlantic
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Ocean) using linear inverse modeling to examine how the food web is influenced by
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the characteristics of the respective canyon section. The models were based on an
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empirical dataset consisting of biomass and carbon processing data, and general
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physiological data constraints from the literature. Environmental conditions, most
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notably organic matter (OM) input and hydrodynamic activity, differed between the
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canyon sections and strongly affected the benthic food web structure. Despite the
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large difference in depth, the OM inputs into the food webs of the upper and middle
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sections were of similar magnitude (7.98±0.84 and 9.30±0.71 mmol C m-2 d-1,
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respectively). OM input to the lower section was however almost 6-7 times lower
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(1.26±0.03 mmol C m-2 d-1). Canyon conditions greatly influenced OM processing
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within the food web. Carbon processing in the upper section was dominated by
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prokaryotes (70% of total respiration), though there was a significant meiofaunal
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(21%) and smaller macrofaunal (9%) contribution. The high total faunal contribution
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to carbon processing resembles that found in shallower continental shelves and upper
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slopes, although the meiofaunal contribution is surprisingly high and suggest that high
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current speeds and sediment resuspension in the upper canyon favor the role of the
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meiofauna. The high OC input and conditions in the accreting sediments of the middle
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canyon section were more beneficial for megafauna (holothurians), than for the other
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food web compartments. The high megafaunal biomass (516 mmol C m-2), their large
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contribution to respiration (56% of total respiration) and secondary production (0.08
3
1
mmol C m-2 d-1) shows that these accreting sediments in canyons are megafaunal
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hotspots in the deep-sea. Conversely, carbon cycling in the lower canyon section was
3
strongly dominated by prokaryotes (86% of respiration) and the food web structure
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therefore resembled that of lower slope and abyssal plain sediments. This study shows
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that elevated OM input in canyons may favor the faunal contribution to carbon
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processing and create hotspots of faunal biomass and carbon processing along the
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continental shelf.
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1
2
Introduction
Submarine canyons are incisions of the continental margin and directly link
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the continental shelf with deep-sea plains by transporting large amounts of sediment
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(Canals et al., 2006; de Stigter et al., 2007) and OM (Epping et al., 2002; Vetter and
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Dayton, 1999). The comparatively rapid transport in active canyons results in the
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sedimentary OM being also of higher quality as compared to slope sediments at
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similar water depth (Garcia et al., 2007; Pusceddu et al., 2010; Vetter and Dayton,
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1999). The high quantity and quality of the OM in canyon sediments results in carbon
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oxidation rates (Epping et al., 2002; Rabouille et al., 2009) and benthic standing
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stocks of nematodes (Ingels et al., 2009) and deposit feeding holothurians (Amaro et
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al., 2009; De Leo et al., 2010; Vetter and Dayton, 1999) that are higher as compared
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to adjacent open slopes and indicate extensive carbon cycling in the benthic food web.
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These latter studies focus on individual components of the benthic food web
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and suggest that different benthic components may benefit from the enhanced influx
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of OM into canyons. These comparisons are, however, based on single biomass-to-
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biomass or process-by-process comparisons. It is unclear how the structure of the
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whole food web and carbon partitioning within the food web is affected by canyon
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conditions. Moreover, it is unclear whether and how emerging properties at the whole
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food web level are impacted by canyon conditions. Network analysis has been
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developed to condense information contained in complex networks, such as food
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webs, into interpretable indices (Fath and Patten, 1999; Ulanowicz, 2004). The index
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total system throughput (
23
of total food web activity. The Finn cycling index summarizes the fraction of total
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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
) sums carbon flows in the food web to obtain a measure
5
1
mutual information (AMI), that gauges how orderly and coherently flows are inter-
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connected (Ulanowicz, 2004 and references therein). It is claimed that AMI is
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indicative of the developmental status of an ecosystem and that while a food web
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develops specialization results in higher values of AMI.
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The Nazaré canyon intersects the Portuguese continental shelf and extends
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from a water depth of 50 m near the coast down to 5000 m at the abyssal plain and
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presents an interesting case study because of the varying conditions within the
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canyon. The upper canyon section (50 – 2700 m water depth) is characterized by a V-
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shaped valley that is deeply incised in the continental shelf. The middle canyon (2700
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– 4000 m) is a broad meandering valley with terraced slopes that may experience high
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rates of particle and organic matter sedimentation (Masson et al., this issue). The
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upper and middle canyon sections capture suspended particulate matter from the
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adjacent shelf and are affected by internal tide circulation of water with high bottom
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current speeds, thereby imposing physical disturbance on the sedimentary
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environment (de Stigter et al., 2007). Finally, the lower canyon is a kilometers-wide
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flat-floored valley that gently descends from 4000 to 5000 m depth (de Stigter et al.,
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2007; Masson et al., this issue).
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The physical disturbance of sediments is especially strong in the narrow V-
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shaped valley of the upper canyon section and this may impose constraints on the
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development of the food web. Especially large and longer-lived components of the
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food web may be affected and carbon cycling may be shifted towards microbes as
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compared to sediments with similar OM input that are less frequently disturbed (Aller
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and Aller, 2004). Carbon recycling, quantified with the Finn cycling index, may
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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
6
1
index AMI, is expected to be lower as compared to the middle and lower canyon
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sections.
3
The terraced slopes of the middle canyon section experience high rates of
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sedimentation and associated organic matter input. Transport of (semi)-labile OM to
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these greater depths in the canyon may imply a deviation from the archetypical
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relation between water depth and sediment oxygen consumption (SOC). The SOC and
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the network index “total system throughput” is expected to be comparatively elevated
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in the middle section of the canyon due to the enhanced OM input as compared to
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open slope sediments at similar water depth. The enhanced input OM may not be
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partitioned equally among the food web compartments and may be influenced by the
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environmental conditions in the respective canyon. De Leo et al. (2010) for example,
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reported extremely high biomass levels of particularly deposit-feeding holothurians in
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a low relief muddy sediment at 900 – 1100 m in the Kaikoura Canyon (New Zealand).
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The conditions in the Kaikoura canyon are reported to be similar to the middle section
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of the Nazaré canyon and indeed high holothurian abundances are found there too
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(Amaro et al., 2009). With a whole food web approach as followed here it will be
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possible to study quantitatively whether different food web compartments take
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proportional advantage of the enhanced OM input in this section of the Nazaré
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canyon.
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The deeper canyon section is where the canyon widens into a kilometres-broad
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channel in the abyssal plain (de Stigter et al., 2007). This deep canyon section, which
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only intermittently receives material derived from up-canyon sections via sediment
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gravity flows, better resembles regular abyssal plain conditions with an associated
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lower OM input. Under these lower OM inputs, lower faunal contributions to carbon
7
1
cycling are expected and the more steady conditions may imply a higher food web
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maturity and higher recycling within the food web.
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Verifying how specific conditions in the three canyon sections impose on the
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benthic food web requires an analysis of the trophic structure of the complete benthic
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food web. The quantification of complete food webs is however a data-demanding
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effort and canyon data sets are typically incomplete and limited in scope. To
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overcome these limitations and maximize the amount of information gained from the
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available data, so-called linear inverse models (LIM) have been developed. LIM
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allow quantifying biological interactions in a complex food web from an incomplete
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and uncertain data set such as encountered in the deep-sea (Soetaert and Van Oevelen,
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2009). For example, Van Oevelen et al. (2009) using linear inverse modeling to
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quantify the interactions in the complex food web of a cold-water coral community at
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Rockall Bank and provided evidence that coral communities are hot-spots of biomass
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and carbon cycling along continental margins.
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Here we develop linear inverse models (LIM) to quantify carbon flows in the
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complex food webs characterizing upper, middle and lower sections of the Nazaré
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canyon. The observed food web structures and selected network indices are examined
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as a function of the characteristics of the respective canyon section.
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Methods
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2.1 Nazaré canyon characteristics
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The Nazaré canyon, one of the largest submarine canyons in Europe, intersects
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the Portuguese continental shelf and has been intensively studied in the framework of
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different European projects such as OMEX-II, EUROSTRATAFORM and HERMES.
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Expeditions carried out within these projects have resulted in comparatively high data
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1
availability on different physical, chemical and biological aspects of the canyon
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system. De Stigter et al. (2007) proposed a division of the canyon into three sections
3
based on hydrographic and physical characteristics. The upper canyon is characterized
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by a V-shaped valley that is deeply incised in the continental shelf and starts at 50 m
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water depth and runs down to a depth of 2700 m. The middle canyon (2700 – 4000 m)
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is a broad meandering valley with terraced slopes and the lower canyon is a flat
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floored valley that gently descends from 4000 to 5000 m depth. The water column
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along the Western Iberian Margin is stratified, with relatively warm (14 to 18ºC) and
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saline (35.4 to 35.8) water at the surface (North Atlantic Central Water) to cold (2ºC)
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and less saline (34.8) water at 5000 m depth (North Atlantic Deep Water). The upper
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and middle canyon sections capture suspended particulate matter from the adjacent
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shelf and are affected by internal tide circulation of water with high bottom current
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speeds (de Stigter et al., 2007).
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The seabed of the Nazaré canyon is heterogeneous and consists of a highly
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dynamic thalweg filled with coarse sandy and gravelly deposits, steep sloping canyon
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walls with rocky outcrops, and terraces with thick accumulations of soft muddy
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sediments (Tyler et al., 2009). The hard substrata in the thalweg and on steep walls
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and outcrops are covered in places with a thin, centimeter-thick drape of soft mud,
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where it is impossible to sample with box- or multicorer to estimate biomass.
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Moreover, to avoid large heterogeneity in the data set due to seabed differences, the
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focus of this manuscript is on soft-sediments outside the thalweg, which were split
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into the three sections as described above. The depth range of the upper section was
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here limited to 300 – 700 m.
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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
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et al., 2002), prokaryotic heterotrophic carbon production (Danovaro, unpub. data),
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nematode trophic structure (Danovaro et al., 2009) and the macro- and megafaunal
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community structure (Cunha et al., this issue and unpub. data). Such data on biotic
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and abiotic carbon stocks and transformation rates are perfectly suited to quantify
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food webs of the three sections of the Nazaré canyon using linear inverse modeling.
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2.2 Linear inverse models
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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
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compartments and flows between them are fixed a priori (see ‘Food web structure’
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below). The flow magnitudes are constrained within the boundaries that are defined
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by the inclusion of empirical data on standing stocks, flux data and physiology into
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the model. The food web topology and empirical data are included in a matrix
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equation with equalities and in a matrix equation with inequalities. These matrix
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equations are solved simultaneously to recover quantitative values for the flow values,
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such that the flow values in a model solution are within the boundaries defined by the
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matrix equations. The model was run 10,000 times and each time a different solution
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is generated to allow estimating the mean and standard deviation of each unknown
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flow. It is important to note that by running the model 10,000 times, the uncertainty in
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the empirical data (see ‘Data availability’ below) is propagated onto an uncertainty
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estimate of the carbon flows as indicated by its standard deviation. Convergence of
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the mean and standard deviation of the flows was used to verify whether the set of
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10,000 model solutions was sufficiently large.
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25
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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1
Van Oevelen, 2009; Van Oevelen et al., 2010). These reviews contain simple models
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to exemplify the setup and solution of linear inverse food web models using the
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software packages LIM (Soetaert and Van Oevelen, 2008; Van Oevelen et al., 2010)
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and limSolve (Soetaert et al., 2008) that run in the R software (R Development Core
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Team, 2008). The Nazaré food web models are made publically available in the LIM
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package.
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2.3 Food web structure
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The compartments in the food web models were chosen based on the classical
size distribution of prokaryotes (Pro), meiofauna (Mei), macrofauna (Mac) and
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megafauna (Meg). The faunal compartments were further subdivided based on the
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feeding classification for nematodes (Wieser, 1953) and feeding types for macro- and
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megafauna were surface deposit-feeder (SDF), deposit-feeder (DF), suspension feeder
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(SF) and predator+scavenger (PS) (see below). The sedimentary organic matter was
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divided into dissolved organic carbon (DOC) and labile (lDet), semi-labile (sDet) and
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refractory detritus (rDet).
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Inputs to the food web are deposition and/or suspension feeding of suspended
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labile (lDet_w), semi-labile (sDet_w) and refractory detritus (rDet_w). Outputs from
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the food web are respiration to dissolved inorganic carbon (DIC), burial of rDet, DOC
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efflux to the water column and export by the macro- and megafaunal compartments
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(e.g. consumption by fish).
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The detritus pools in the sediment can be hydrolyzed to DOC and the labile
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and semi-labile detritus pools are grazed upon by meiofauna and MacSDF, MacDF,
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MacPS, MegSDF and MegDF. DOC is taken up by prokaryotes or fluxes out of the
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sediment to the water column. Predatory feeding links are primarily defined based on
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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
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non-suspension feeding macro- and megafaunal compartments, the macrofaunal
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compartments MacSDF, MacDF and MacSF are preyed upon by MacPS.
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Part of the ingested matter by the faunal compartments is not assimilated but
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instead expelled as feces, the non-assimilated labile (e.g. labile detritus, prokaryotes
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and faunal compartments) and semi-labile (semi-labile detritus) carbon, flows into
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semi-labile and refractory detritus, respectively. Respiration by faunal compartments
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is defined as the sum of maintenance respiration (biomass-specific respiration) and
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growth respiration (overhead on new biomass production). Prokaryotic mortality is
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represented here as a flux to DOC and faunal mortality is defined as a flux to labile
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detritus.
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2.4 Data availability
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The Nazaré canyon is one of the best studied canyons in Europe, with studies
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on sediment transport and/or fate of organic matter (e.g. de Stigter et al., 2007; Epping
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et al., 2002; García et al., 2008), concentration of total carbohydrates, lipids and
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proteins in the sediment (Pusceddu et al., 2010) heterotrophic prokaryotic C
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production (Danovaro unpub. data), nematode community structure (Garcia et al.,
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2007; Danovaro et al., 2009; Ingels et al., 2009), meiofaunal abundance (Bianchelli et
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al., 2010), macro- and megafaunal community structure (Tyler et al., 2009, Cunha et
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al., this issue and unpub. data). As stated above, empirical data were only included if
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they were collected from the soft-sediments of the upper, middle or lower section of
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the canyon.
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Detritus stocks were delineated as follows (Table 1): the stock of labile
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detritus was defined as all carbon associated with chlorophyll a. Chlorophyll a
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concentrations were taken from the top 5 cm in sediments of the off-thalweg stations
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1
(Garcia and Thomsen, 2008), which were converted to carbon units by assuming a
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carbon to chl a ratio of 40. Semi-labile detritus was defined as the sum of the
3
carbohydrates, lipids and proteins (i.e. biopolymeric carbon) that were converted to
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carbon equivalents (Pusceddu et al., 2010). Biopolymeric carbon concentrations were
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measured only in the top 1 cm and were linearly extrapolated to 5 cm depth under the
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assumption that all semi-labile detritus is degraded in the top 5 cm. The latter
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assumption is supported by Epping et al. (2002) who showed that carbon degradation
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occurs primarily in the top 5 cm of the sediment. Refractory detritus was defined as
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the degradable fraction of the particulate organic carbon in the top 5 cm of the
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sediment (derived from organic carbon content profiles in Epping et al., 2002), minus
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the labile and semi-labile detritus pools.
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Biomass data were available for prokaryotes and all faunal compartments (i.e.,
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meiofaunal, macrofauna and megafauna; Table 1). Nematodes dominated the
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metazoan meiofauna (on average 90% of total abundance) and the Wieser feeding
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classification based on nematode mouth morphology was used to designate biomass
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to selective feeding (Wieser type 1A + 2A), non-selective feeding (Wieser type 1B)
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and omnivore/predatory (Wieser type 1B). Polychaetes dominated the macrofaunal
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compartments and these were grouped into surface-deposit, deposit, suspension and
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predatory+scavenging feeding compartment based on standard feeding type
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classification from Fauchald and Jumars (1979). Biomass-dominant polychaete
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families in the upper section are Onuphidae (57%) and Sigalionidae (36%), in the
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middle section Spionidae (61%), Fauveliopsidae (9%) and Ampharetidae (8%), and in
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the lower section Spionidae (40%), Goniadidae (15%) and Siboglinidae (12%). Other
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contributions to the macrofaunal biomass from Mollusca, Bivalvia and Crustacea are
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low (< 3%) in the upper section, higher in the middle section with 48%, 14% and
13
1
19%, and negligible in the lower section (<1%), respectively. Finally, the megafaunal
2
surface-deposit feeding community consists of Ypsilothuria bitentaculata
3
(Holothuroidea) and deposit feeding community of Molpadia musculus
4
(Holothuroidea).
5
Since there were no data available on the temporal variability in benthic
6
biomass, these were neglected and it was assumed that the mass balances of all
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compartments are in steady-state, i.e.,
8
limited bias in the model solution (Vézina and Pahlow, 2003), primarily because net
9
biomass increases (e.g. for the fauna and bacteria) are small as compared to the other
10
. This assumption introduces only
flows in the food web.
11
In addition to the standing stock measurements, a variety of data on process
12
rates were available for the different sections of the Nazaré canyon (Table 2). These
13
data were implemented as inequalities by setting the minimum and maximum value
14
found in each section as lower and upper bounds, respectively.
15
The determination of prokaryotic C production in sediment samples was
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carried out according to the procedure described for marine sediments by Danovaro et
17
al. (2002). Sediment subsamples from the top 1 cm were mixed with a solution of 3H-
18
leucine (final concentration 0.2 mmol L-1), were incubated at in situ temperature for 1
19
hour in the dark. After incubation, samples were supplemented with ethanol (80%)
20
and processed according to Van Duyl and Kop (1994) before scintillation counting.
21
Sediment blanks were made adding ethanol immediately after 3H-leucine addition.
22
The incorporated radioactivity in all samples was measured by a liquid scintillation
23
counter. The following equation was used for calculating prokaryotic C production:
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PCP ~ LI · 131.2 · (%Leu) – 1 · (C: protein) · ID
14
1
where PCP is prokaryotic C production, LI is the leucine incorporation rate
2
(mol ml-1 h-1), 131.2 is the molecular weight of leucine, %Leu is the fraction of
3
leucine in protein (0.073), C:protein is the ratio of cellular carbon to protein (0.86),
4
and ID is the isotope dilution assuming a value of 2.
5
The prokaryotic C production was determined in the top 1 cm and this value was
6
taken as lower bound on prokaryotic production (Table 2). Prokaryote production
7
typically decreases with depth in the sediment due to reduced availability of
8
degradable detritus and electron acceptors (e.g. Nodder et al., 2003; Glud and
9
Middelboe, 2004). The upper bound on prokaryotic C production for the top 5 cm was
10
set to five times the prokaryotic C production of the top 1 cm. As such, we impose
11
that the integrated prokaryotic C production does not increase within the top 5 cm of
12
the sediment, because the model solution is found between the lower bound
13
(production in top 1 cm layer) and the upper bound (5 times the production in the top
14
1 cm layer). Carbon burial rates, total respiration rates, total carbon deposition and
15
burial efficiencies for each section were taken from the diagenetic modeling work of
16
Epping et al. (2002) (Table 2). We imposed that total respiration and carbon
17
deposition in Epping et al. (2002) did not include the respiration and uptake by
18
megafauna, respectively, because the activity of these large burrowing or surface-
19
dwelling organisms is missed in a diagenetic modeling approach that is based on
20
small cores incubations and oxygen profiles in the sediment.
21
An additional number of general inequality constraints were taken from the
22
literature to constrain degradation rates of the labile, semi-labile and refractory
23
detritus pools, prokaryote growth efficiency, release of DOC from the sediment,
24
assimilation efficiency of all faunal compartments, net growth efficiency of all faunal
25
compartments, production and mortality rates of all faunal compartments (Table 2).
15
1
Since measurements of assimilation and growth efficiencies of deep-sea benthos are
2
very rare, we decided to use an extensive literature review (Van Oevelen et al.,
3
2006b) of temperate benthos as basis for these constraints. Biomass-specific
4
maintenance respiration of all faunal compartments was defined as 0.01 d-1 at 20°C
5
(see references in Van Oevelen et al., 2006b) and is corrected with Q10 of 2, giving a
6
temperature-correction factor (Tlim) for each canyon section (Table 2).
7
Benthic organisms do not feed indiscriminately on the available food sources.
8
Both surface-deposit and deposit-feeding holothurians and echinoderms ingest
9
organic matter with higher than ambient chlorophyll a and total hydrolysable amino
10
acid concentrations (Ginger et al., 2001; Witbaard et al., 2001; Amaro et al., 2010),
11
though selectivity differs between feeding modes with surface-deposit feeders
12
typically exhibiting stronger selectivity than deposit feeders (Wigham et al., 2003).
13
Selectivity between labile detritus and semi-labile detritus for megafauna was defined
14
as the ratio of chlorophyll a concentrations in the gut with respect to the ambient
15
surface sediment. The level of selectivity varies from 1 to 10 for deposit feeding
16
holothurians to >500 for the surface deposit feeding holothurians Amperima rosea
17
(Porcupine Abyssal Plain, Wigham et al., 2003). Selectivity at the Antarctic Peninsula
18
was less evident (selectivity of 2 to 7), possibly because of the existence of a food
19
bank, but there was a clear separation between deposit and surface deposit feeders
20
(Wigham et al., 2008). Therefore, no to moderate selectivity of 1 to 10 for deposit
21
feeders and strong selectivity (50 to 100) for surface-deposit feeders was assumed in
22
the model (Table 2). Since no comparable data are available for macrofauna, similar
23
selectivity ranges were defined for these compartments (Table 2). Finally, few
24
organisms in benthic food webs can be considered as sole predators (Fauchald and
25
Jumars, 1979), therefore the predatory meio-, macro- and megafaunal compartments
16
1
were assumed rely between 75% and 100% through predatory feeding to account for
2
this (Table 2).
3
2.5 Network indices
4
The network indices
,
and
were directly calculated from the
5
output of the sampling algorithm in R using the newly developed R-package
6
NetIndices (Kones et al., 2009). Details on the calculation of the indices can be found
7
in Ulanowicz (2004) and Kones et al. (2009), but a summary of the nomenclature
8
(Table 3) and calculation algorithms (Table 4) are included in this manuscript.
9
Network indices were calculated for the complete set of food web solutions
10
(10,000 for each section). The network indices were compared between canyon
11
sections by calculating the fraction of which the randomized set of indices of one
12
canyon section is larger than that of another section. For example, when this fraction
13
is 0.90, this implies that 90% of the values of section 1 are larger than the ones of
14
section 2 (and consequently 10% of the values are lower). We define differences of
15
>90% and <10% as significant difference and >95% and <5% as highly significant
16
difference.
17
Results
18
3.1 Food web structure
19
The models of the upper and middle canyon could be solved with the default
20
equality and inequality constraints. However, the first attempt to solve the model of
21
the lower section with the default set of constraints was unsuccessful, which indicates
22
that some of the data embedded in the linear inverse model are in conflict with each
23
other. Subsequent analysis showed that the minimum degradation of semi-labile
17
1
detritus (4761 · 8.21·10-4 = 3.9 mmol C m-2 d-1, Table 1 & 2) was higher than the
2
maximum rates of total carbon oxidation and carbon deposition (0.90 and 1.3 mmol C
3
m-2 d-1, respectively). Since the latter two data are site-specific field data, it was
4
decided to modify the literature bound on the minimum rate of semi-labile
5
degradation through pre-multiplication with the temperature limitation factor (Tlim =
6
0.30, Table 2). This allowed the model to be solved and its implications will be
7
discussed below.
8
9
10
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
11
Variation (CoV), which is the standard deviation of a flow divided by the mean flow
12
value. As such, the CoV provides an indication for the residual uncertainty in the
13
solution, where flows with a relatively large residual uncertainty have a comparatively
14
high CoV and flows with a relatively small residual uncertainty have a comparatively
15
low CoV. All flows in all three canyon sections had a CoV that was smaller than 1.
16
Maximum CoV were 0.86, 0.90 and 0.86 for the upper, middle and lower canyon
17
section, respectively and were associated with transfer of one the nematode
18
compartments to the (surface) deposit-feeding macrobenthos. The CoV was smaller
19
than 0.75 for 81%, 73% and 82% of the flows of the upper, middle and lower canyon
20
section, respectively, and the CoV was smaller than 0.50 for 40%, 40% and 45% of
21
the flows.
22
Total carbon input (mmol C m-2 d-1) to the different food webs was 7.98±0.84
23
(5% labile, 75% semi-labile and 20% refractory detritus), 9.30±0.71 (9% labile, 89%
24
semi-labile and 2% refractory detritus) and 1.26±0.03 (6% labile, 90% semi-labile and
25
4% refractory detritus) for the upper, middle and lower canyon section, respectively.
18
1
Total respiration was 4.52±0.28, 5.06±0.30 and 0.86±0.02 mmol C m-2 d-1 and organic
2
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,
3
middle and lower canyon section, respectively. Prokaryotes dominated carbon
4
respiration in the upper (70%) and lower (82%) section, but their contribution to total
5
respiration is lower (38%) than the total megafaunal respiration in the middle section
6
(57%) (Table 5). Summed meiofaunal respiration contributes 21% tot total respiration
7
in the upper, 3% in the middle and 13% in the lower canyon section, whereas summed
8
macrofaunal respiration contributes 8% in the upper, 1% in the middle and 5% in the
9
lower section. Summed export fluxes (i.e. secondary production not consumed within
10
the food web) differed between the sections with 0.18±0.08, 0.10±0.05 and
11
0.02±0.006 mmol C m-2 d-1 for the upper, middle and lower section, respectively.
12
The structural differences between the food webs become apparent when
13
flows are plotted as mean net values in a circular food web structure (Fig. 1). The
14
main differences between the upper and lower section are the more important role of
15
the non-selective feeding meiofauna compartment (Fig. 1A vs. 1C) and MacPS
16
compartment (Fig. 1D vs 1F) in carbon cycling in the upper canyon section. Of
17
similar importance, however, is the pathway of deposition of semi-labile, dissolution
18
to dissolved organic carbon, prokaryotic uptake of this DOC and prokaryotic
19
respiration in the upper and lower sections (Fig. 1A vs. 1C). Consistent with their
20
comparatively low contribution to total respiration, the carbon flows related to the
21
macrofaunal compartments are small, except for the MacPS compartment in the upper
22
canyon section that show up mostly in the lower row of Fig.1. The food web structure
23
of the middle canyon section stands out primarily because of the dominant role of the
24
MegDF and, to a lesser extent, MegSDF compartments (Fig. 1B and 1H). Moreover,
19
1
carbon cycling by the macrobenthic compartments, especially MacPS, is less
2
important as compared to the upper and lower canyon section.
3
There is a dominance of semi-labile detritus in the diets of most faunal
4
compartments in the upper section of the Nazaré canyon, with semi-labile detritus
5
supplying between 53% and 95% of carbon of the non-predatory compartments and
6
11-12% of the predatory compartments MeiPS and MacPS, respectively (Fig. 2A).
7
Labile detritus (2 – 15%) and prokaryotes (2 – 22%) supply a comparable lower
8
fraction of carbon to the non-predatory compartments and 4 – 5% to the predatory
9
compartments. Non-predatory meiofaunal compartments fuels the meiofaunal and
10
macrofaunal predatory compartments in similar amounts (21 – 50%). Faunal diets of
11
the non-predatory compartments in the middle section are comparable to the upper
12
section, with a dominance of semi-labile detritus (42 – 93%) and labile (2 – 21%)
13
detritus (Fig. 2B). The diet contribution of prokaryotes to non-predatory faunal
14
compartments varies between 2 and 21%. Dependence on selective and non-selective
15
feeding meiofaunal compartments is highest for predatory meiofauna (80%), followed
16
by predatory macrofauna (48%) and <10% for the other macrofaunal and megafaunal
17
compartments. The diet of the predatory/scavenging macrofaunal compartment is
18
diverse, with no clear dominance of any resource (3 – 25%).
19
The diet compositions in the lower section of the Nazaré canyon resemble
20
overall those of the upper section (Fig. 2A vs. 2C). Again, semi-labile detritus is most
21
important (between 76 – 98%) in the diets of non-predatory faunal compartments.
22
Diet contributions of labile detritus and prokaryotes are similar for selective feeding
23
meiofauna (9-10%), non-selective meiofauna (each 1%), predatory/omnivore
24
meiofaunal (each 5%), surface-deposit feeding macrofauna (each 5%), deposit-
25
feeding macrofauna (each 1%) and predatory/scavenging macrofauna (4-5%) (Fig.
20
1
2C). The meiofaunal compartments MeiSF + MeiNF are important resources for the
2
meiofaunal predators/omnivores (together 80% of the diet) and predatory (69%)
3
macrofauna, but are of lesser importance for surface-deposit (10%), deposit feeding
4
(1%). The diet composition of predatory/scavenging macrofauna is diverse though
5
with a high importance of selective feeding meiofauna (54%) and lower contributions
6
ranging from 1 - 11% from other resources.
7
The diet of suspension-feeding macrofauna is similar among the canyon
8
sections and is partitioned among labile (32 – 36%) and semi-labile (64 – 68%)
9
detritus from the water column.
10
The dominant fate of prokaryotic production in all three sections is mortality
11
(52 – 88%) and grazing by meiofauna in the upper canyon section (31%) and by
12
megafauna in the middle section (36%) (Fig. 3A-C). The majority of the meiofaunal
13
secondary production is grazed by macrofauna in the upper (56%) and lower (47%)
14
canyon section, while megafaunal grazing is important in the middle section (36%)
15
and grazing by meiofauna (MeiPO) is important with a consistent contribution of 18 –
16
23% in the three sections (Fig. 3D-F). The fate of macrofaunal production is
17
partitioned similarly in all three canyon sections with maintenance representing 22 –
18
24%, mortality 29 – 34%, predation by macrofauna (MacPS) 2 – 20% and export 29 –
19
42% (Fig. 3G-I). The fate of megafauna is dominated by maintenance respiration
20
(91%) and with limited contributions of mortality (5%) and export (4%) (Fig. 3J).
21
3.2 Network indices
22
The network indices total system throughput (
23
and average mutual information (
24
and compared (Table 6). The
), Finn cycling index (
)
) were calculated for the three sections (Fig. 4)
does not differ significantly between the upper and
21
1
middle sections with median values of 41.1 and 39.7 mmol C m-2 d-1, respectively, but
2
is significantly lower in the lower section with a median of 6.7 mmol C m-2 d-1
3
(Table 6). Differences in
are highly significant between canyon sections (Table
4
6) and median values are 0.13, 0.06 and 0.17 for the upper, middle and lower section,
5
respectively.
6
and middle (2.22) canyon section, but significantly lower for the lower section (2.12).
is not significantly different between the upper (median of 2.21)
22
1
2
Discussion
In this paper, we present the first quantitative analysis of carbon flows within
3
food webs of different sections of a submarine canyon. This provides a unique
4
opportunity to study how different characteristics within a canyon influence food web
5
structure and attributes such as total system throughput, recycling within the food web
6
and food web maturity. The modeled food webs of the upper, mid and lower canyon
7
sections are based on a large variety of site-specific biological and biogeochemical
8
data and are combined with physiological constraints and empirical relations from the
9
literature. Despite the large amount of data that are implemented, this is insufficient to
10
uniquely quantify all carbon flows (Van Oevelen et al., 2010). This implies that a
11
“solution space” exists, within which an infinite number of solutions are present that
12
are consistent with the data (Soetaert and Van Oevelen, 2009). Conventional single-
13
solution modeling approaches typically find a final solution at or close to boundaries
14
of the solution space, making the final solution sensitive to the exact boundaries of the
15
solution space ( Vézina et al., 2004; Kones et al., 2006; Van Oevelen et al., 2010).
16
The multi-solution approach followed here, samples the solution space (Van den
17
Meersche et al., 2009) such that the mean of this sampled set represents the best
18
central flow value that is less sensitive to the boundaries of the solution space (Van
19
Oevelen et al., 2010). Moreover, the standard deviation on each carbon flow indicates
20
how the uncertainty in the data set propagates to an uncertainty on its value (Van
21
Oevelen et al., 2010). The Coefficient of Variation (CoV) was smaller than 0.75 for
22
73 – 82% flows in the three sections (Web appendix), which indicates that the
23
residual uncertainty on the flows is comparatively low and that the food web is well-
24
constrained. The lowest CoVs are associated with the respiration flows of the biotic
25
compartments, whereas highest CoVs are predominantly associated with carbon flows
23
1
that exist between biotic compartments. This directly relates to the data availability.
2
The carbon requirement of faunal compartments is constrained primarily by the
3
available biomass data. There are however few data that constrain the origin of this
4
carbon, such that the residual uncertainty on diet contributions and fates of secondary
5
production are comparatively high. Perhaps even more important than the residual
6
uncertainty on the flows, are the limitations and uncertainties with respect to the
7
assumptions that were needed to setup the model. These sources of uncertainty mainly
8
concern substrate heterogeneity and combining different data sets and will be
9
discussed now.
10
The seafloor in the Nazaré canyon is heterogeneous and consists of rocks,
11
boulders, coarse gravel sediments, steep walls, a highly dynamic thalweg and terraces
12
consisting of soft-sediments. The hard substrata may be draped with a thin soft muddy
13
layer. Not surprisingly, also the associated fauna changes with substratum type and
14
condition. Rocky surfaces for example are dominated by suspension feeders such as
15
hard and soft corals, gorgonians, anemones, sea pens and crinoids (Tyler et al., 2009).
16
In thalweg sediments, the biomass of nematodes (Garcia et al., 2007) is about one
17
order of magnitude lower than in soft-sediment terraces (Ingels et al., 2009), which is
18
attributed to repeated sediment disturbance of thalweg sediments that prevents the
19
development of a mature nematode community (Garcia et al., 2007). In addition,
20
megafauna and the giant epifaunal protozoans (xenophyophores) were not observed in
21
the thalweg (Tyler et al., 2009) but are found outside the thalweg. Up to now, there
22
are no quantitative data available on the biomass and activity of the filter-feeding
23
community in the Nazaré canyon on rocky substrata. Moreover, quantitative data on
24
the faunal community in the thalweg is only sparsely available and its food web
25
structure is not representative for that of large sections of the canyon. Hence, in this
24
1
study we restricted our analysis to the soft-sediments of the terraces adjacent to the
2
thalweg and excluded other substrate types. This implies for example that we may
3
miss the potentially high carbon processing activity associated with the canyon walls.
4
In terms of areal coverage however, these soft-sediments with net mud deposition
5
represent an appreciable ~70% of the total surface area of the canyon (Masson et al.,
6
2010), such that a significantly large part of the Nazaré canyon is addressed here.
7
One compartment that is not included in the food web is Foraminifera, which
8
are protozoans that are typically of meiofaunal size but can occur as giant epifauna
9
(xenophyophores). Meiofaunal foraminifera (Koho et al., 2008) and epifaunal
10
xenophyophores (Tyler et al., 2009) have a high abundance in especially the muddy
11
terraces with stable redox conditions and low disturbance. Foraminifera have been
12
shown to play an important role in the initial processing of fresh phytodetritus under
13
deep-sea conditions (Moodley et al., 2002) although their contribution may also be
14
more limited (Woulds et al., 2007). Moreover, their contribution to total respiration in
15
continental shelf sediments was recently found to be limited to <3% (Geslin et al.,
16
2010). Unfortunately, the available abundance data could not be converted to biomass
17
with reasonable accuracy, and since biomass is essential to constrain their activity in
18
the food web we therefore decided to omit this compartment in this analysis.
19
The site-specific data that we include in this study were lumped into the three
20
canyon sections (Table 1 and 2). However, since deep-sea research is time
21
consuming, conducted over large spatial areas and depends on ship time availability
22
and meteorological/sea conditions, the data were not collected synoptically.
23
Inevitably, this data ‘lumping’ into canyon sections will introduce errors in the food
24
web analysis linked to the spatial and temporal variability of the data collected.
25
Nevertheless, the Nazaré canyon is comparatively well-studied and one of the
25
1
strengths of linear inverse modeling is that datasets are merged and tested for internal
2
consistency (Van Oevelen et al., 2010). Given the amount of data in the models
3
(Table 1 and 2), the inverse model analysis at least showed that the different data sets
4
are consistent. The only exception was that the minimum degradation rate of semi-
5
labile detritus in the lower canyon section was higher than the maximum rates of
6
carbon oxidation and total carbon deposition. The carbon oxidation and deposition
7
data are site-specific data and were therefore maintained. Instead, the minimum bound
8
on semi-labile degradation was reduced by multiplication with the temperature
9
limitation factor, which allowed solving the food web model. Several explanations
10
may apply here. First, water temperature in the deep canyon section is about 2.5°C
11
and lowest of the three sections. This low temperature may cause degradation to
12
proceed slower than in the higher sections of the canyon with comparatively higher
13
water temperatures. Moreover, the quality of the semi-labile detritus may have
14
decreased during transport through the canyon and this may also lower the
15
degradation rates further. Despite this minor adaptation that was needed, the results
16
from the present analysis serve as a significant first step in gaining insight in the food
17
web structure of submarine canyons.
18
4.1 Upper canyon section
19
The dynamic upper canyon receives about 8±0.84 mmol C m-2 d-1, which is
20
lower than the 15 – 23 mmol C m-2 d-1 that is predicted using an empirical relation for
21
continental shelf sediments (i.e. summed burial and mineralization rates at 700 and
22
300 m, respectively, Middelburg et al., 1997). However, carbon inputs at the open
23
slope sediments of the adjacent Iberian margin are substantially lower than predicted
24
by the empirical relation by Middelburg et al. (1997) and are between 2.3 and 4.3
25
mmol C m-2 d-1 (Epping et al., 2002). Thus, carbon inputs to the upper canyon section
26
1
is higher those of adjacent slopes, but not extremely high as compared to other slope
2
sediments. Burial rates in the upper and middle canyon are substantial flows in the
3
food web (Fig. 1A, B), but burial efficiencies are comparable to Iberian open slopes
4
and relate to sediment accumulations rates (Epping et al., 2002). Hence, the efficiency
5
with which the food web processes organic carbon is similar to open slope sediments.
6
The model results allow detailed deciphering of the biotic compartments that
7
are responsible for carbon processing within the canyon. Woulds et al. (2009) used
8
the results of isotope tracer experiments from different slope sediments to define
9
different categories of biological C-processing. In this categorization, the “active-
10
faunal-uptake” category contains mostly shallow (<300 m) slope sediments and is
11
characterized by 10 – 25% metazoan uptake. This category matches best with the
12
upper canyon section that has a faunal contribution of ~40% and bacterial
13
contribution of 60% to total carbon assimilation.
14
The faunal contribution to total respiration and carbon processing typically
15
decreases with increasing water depth and associated decrease in carbon input (Heip
16
et al., 2001; Rowe et al., 2008; Woulds et al., 2009). Henceforth, the high faunal
17
contribution in the upper canyon section is probably related to the higher OM content
18
and quality as compared to slope sediments at comparable water depth (Garcia et al.,
19
2007; Garcia and Thomsen, 2008; Pusceddu et al., 2010). One striking difference
20
however is that meiofauna dominated faunal processing and contributed around 33%
21
of the total carbon assimilation in the upper canyon section, which is much higher
22
than in open slopes sediments included in the overview of Woulds et al. (2009). This
23
high contribution also translates into a much higher meiofaunal respiration at 21% of
24
total respiration in the upper section of the Nazaré canyon as compared to other open
27
1
slopes that vary from 4 – 8% (Piepenburg et al., 1995; Heip et al., 2001; Soetaert et
2
al., 2009).
3
Rowe et al. (2008) and Bagulay et al. (2008) report even substantially higher
4
contributions ranging from ~20 up to 51% for the Northern Gulf of Mexico. Their
5
estimates are based on biomass-specific respiration rates of 0.04 to 0.11 d-1 at a
6
temperature of 4 – 5°C. Moodley et al. (2008) used a novel micro-respiration system
7
and reported specific rates of 0.021 to 0.032 d-1 for intertidal (20°C) Nematoda,
8
Ostracoda and Foraminifera over a biomass range of 0.7 to 5.2 μC ind-1. Nematodes
9
from the Gulf of Mexico are smaller (~0.1μC ind-1, Baguley et al., 2008), but specific
10
respiration rates are still fairly high as compared to these intertidal meiofauna. The
11
high meiofaunal contribution to total community respiration is therefore probably also
12
related to the comparatively high biomass-specific respiration rates that are estimated
13
for the Gulf of Mexico. Clearly more experimental work for especially small
14
nematodes at lower temperatures is needed to better constrain these respiration rates.
15
The carbon sources that are consumed by meiofauna to fuel these respiration
16
rates are detritus and prokaryotes (e.g., Rowe et al., 2008, this study). Stable isotope
17
tracer experiments allow direct quantification of labile food assimilation rates of
18
amongst others meiofauna. Intriguingly, these results typically show low biomass-
19
specific assimilation rates of <0.01 and mostly <0.001 d-1 ( Moens et al., 2007; Franco
20
et al., 2008; Ingels et al., 2011;), a limited (<5%) contribution to 13C uptake by
21
metazoan meiofauna on open slope (Moodley et al., 2002) and abyssal plain (Witte et
22
al., 2003) sediments and negligible bacterivory by nematodes in a slope sediment
23
(Guilini et al., 2010). Irrespective of the labeled substrate or setting, meiofauna
24
consistently show an uptake of labile 13C carbon that seems to be in imbalance with
25
carbon requirements as estimated from biomass-specific respiration rates. This is not
28
1
in contrast with the meiofaunal diet composition as inferred for the Nazaré canyon
2
(Fig. 2), where semi-labile detritus (a carbon source not used in isotope tracer studies)
3
is the dominant component. This dominance of semi-labile detritus in their diet would
4
explain the low labeling of metazoan meiofauna (dominated by nematodes) in isotope
5
tracer studies. It also agrees with Soetaert et al. (1997), who found a strong positive
6
correlation between depth profiles of nematodes and organic N content and suggested
7
that the concentration of lower quality food primarily determines nematode depth
8
distribution.
9
The elevated OM input in the upper canyon section combined with
10
hydrodynamic conditions with current speeds of up to 30 – 40 cm s-1 appear to
11
particularly favor meiofauna, whereas macro- and megafauna have a lower
12
contribution to carbon processing as compared to open slope sediments. As a result,
13
meiofaunal biomass in the upper canyon section rank among the highest reported in
14
marine sediments (Rex et al., 2006), whereas macrofaunal biomass is comparatively
15
low.
16
Prokaryotes are responsible for the dominant part of carbon cycling and
17
respiration in the upper canyon section (Fig. 1 and Table 5). An important pathway,
18
also seen in the middle and lower canyon section, is deposition of semi-labile detritus,
19
dissolution to dissolved organic carbon, to prokaryotic uptake of this DOC and
20
subsequent prokaryote respiration. A dominance of prokaryotes in carbon cycling and
21
respiration is commonly found in continental shelf sediments (Canfield et al., 1993;
22
Piepenburg et al., 1995; Heip et al., 2001; Rowe et al., 2008). Hence, it appears that
23
hydrodynamic conditions in the upper canyon act predominantly on carbon
24
partitioning between faunal compartments rather than on the partitioning between pro-
25
and eukaryotes.
29
1
4.2 Middle canyon section
2
Soft-sediment terraces in the middle section of the canyon experience high
3
sedimentation rates (de Stigter et al., 2007; Tyler et al., 2009; Masson et al., 2010),
4
which is accompanied by an input of organic matter of 9.30±0.71 mmol C m-2 d-1 that
5
is comparable to the upper canyon section. These high OM inputs clearly show that
6
the archetypical picture seen in open slope sediments that biomass, respiration and
7
carbon processing decreases with increasing water depth does not necessarily hold for
8
submarine canyons.
9
With respect to the carbon partitioning within the food web, the middle
10
canyon section seems to fall in the “metazoan-macrofaunal-uptake-dominated”
11
category, a category that is typically found in shelf and upper slopes, with a
12
comparatively high macrofaunal biomass (Woulds et al., 2009). An importanct
13
discrepancy with the categorization by Woulds et al. is that faunal carbon processing
14
in the middle canyon is not dominated by macrofauna, but by surface deposit-feeding
15
and deposit-feeding megafauna (i.e. the holothurians Ypsilothuria bitentaculata and
16
Molpadia musculus, respectively). The megafaunal importance is also apparent in
17
community respiration (57%) and export of secondary production from the food web
18
(79%).
19
De Leo et al. (2010) reported recently for the Kaikoura Canyon (New
20
Zealand) an extremely high biomass of 89±18 g C m-2 of megafauna (dominated by
21
M. musculus) in low relief, muddy and accreting sediments at 900 – 1100 m of water
22
depth. Megafaunal biomass in the middle section of the Nazaré canyon is about an
23
order of magnitude lower (6.2 g C m-2), but still 2 – 3 orders of magnitude higher than
24
found in open slopes at comparable depth (Rex et al., 2006).
30
1
Amaro et al. (2010) conducted trophic studies on the holothurian M. musculus
2
and estimated removal rates of 0.5 gC of semi-labile detritus m-2 d-1. Our food web
3
analysis even suggests higher removal rates of 2.5 gC of semi-labile detritus m-2 d-1,
4
showing that this holothurian can have an important impact on the sedimentary food
5
web. Amaro et al. (2010) also inferred that prokaryotes delivered <0.1% of the
6
assimilated proteins and it was concluded that holothurians do not appear to rely on
7
microbes for direct nutrition. This is also supported by our diet reconstruction of
8
deposit-feeding megafauna (i.e., M. musculus), where prokaryotes play only a
9
marginal role (Fig. 2B).
10
Carbon partitioning with the food web of the middle canyon section at 2700 –
11
4000 m is comparable to much shallower shelf and upper-slope sediments, where also
12
an important faunal contribution is typically found. The large faunal contribution in
13
the middle canyon section is due to the comparatively high input of OM, which is
14
quantitatively comparable to the upper canyon section. It is however unclear why
15
canyon-specific conditions in the middle section are particularly beneficial for
16
(surface) deposit-feeding holothurians as compared to for example macrofaunal
17
polychaetes. The deposit-feeding megafauna consist predominantly of the holothurian
18
head-down feeder M. musculus and there was no evidence for a specialized
19
prokaryotic community in the guts of M. musculus that may aid in the hydrolyzation
20
of organic matter (Amaro et al., 2009). Other possible explanations for a strong
21
proliferation of M. musculus in soft accreting sediments within canyons may involve a
22
better adaptation to high sediment rates, enhanced trapping of the depositing organic
23
matter in their feeding pits and negative feedbacks on macrofauna through, for
24
example, predation or sediment disturbance.
31
1
2
4.3 Lower canyon section
The food web structure in the lower canyon section is markedly distinct from
3
the upper and middle sections (Fig. 1). Not only is total carbon input (1.26±0.03
4
mmol C m-2 d-1) about an order of magnitude lower than in the upper and middle
5
sections, but also its partitioning within the food web differs considerably. OM input
6
in the lower section is lower, because OM delivery from the upper and middle canyon
7
section is less frequent, OM has been degraded during transport through the canyon
8
and the lower canyon begins where the V-shaped valley widens into a kilometers-
9
wide channel thereby lowering the OM input per surface area.
10
Respiration in the lower canyon section is strongly dominated by protozoa
11
(82% of total respiration) whereas the faunal compartments each respire <10%. These
12
characteristics place the lower canyon section in the “respiration-dominated”
13
category, in which most OM is respired by the prokaryotic community and the role of
14
benthic fauna in carbon cycling is low (Woulds et al., 2009). Other sites that fall in
15
this category are lower slope sediments and abyssal plains (Woulds et al., 2009),
16
suggesting that the benthic food of the lower canyon section resembles others sites at
17
similar depth . The lower canyon section seems to be less influenced by canyon
18
conditions as compared to the upper and middle section of the canyon.
19
4.4 Comparison of canyon sections with network indices
20
The lower carbon processing in the lower canyon is also evident in the index
21
total system throughput (
), in which carbon flows are summed to obtain a measure
22
of total food web activity (Ulanowicz, 2004). Total system throughput does not differ
23
significantly between the upper and middle sections (medians of 41.1 and 39.7 mmol
24
C m-2 d-1, respectively), but is significantly lower in the lower canyon section (median
32
1
of 6.7 mmol C m-2 d-1) (Table 6). Though community respiration and OM input is
2
higher for the middle canyon section, total system throughput is slightly elevated (not
3
significantly) in the upper canyon section. This reversal in activity measures is
4
probably linked to the low recycling within the food web of the middle canyon as
5
quantified with the Finn cycling index (Fig. 4B). This index summarizes the fraction
6
of total carbon cycling that is generated by recycling processes (Allesina and
7
Ulanowicz, 2004). Significant differences in recycling are found between the canyon
8
sections, with the most notable difference being low recycling in the middle canyon
9
section. One explanation relates to the viral shunt (Danovaro et al., 2008), in which
10
viral infection cause lysis of prokaryotes and the subsequent release of dissolved
11
organic matter that is again recycled by other heterotrophic prokaryotes (e.g., Van
12
Oevelen et al., 2006a). Prokaryotes dominate carbon flows in the lower section, but
13
this dominance is reduced in the upper and particularly the middle canyon section. If
14
the viral-mediated shunt significantly influences the FCI, this would explain the
15
decreasing FCI when going from the lower, upper to the middle canyon section. To
16
examine the impact of the viral shunt on the FCI, the viral shunt was eliminated from
17
the food web by only including the net flow from DOC to prokaryotes in the FCI
18
calculations. Though differences in FCI remain, the FCI of the upper and lower
19
sections drops to medians of 0.07 and 0.04, respectively, whereas the middle section
20
is much less affected with a drop to 0.03. This exercise clearly shows that the viral
21
shunt increases carbon recycling in benthic food webs rendering recycling to be
22
higher in prokaryote-dominated food webs as compared to faunal-dominated food
23
webs.
24
The index average mutual information (AMI) gauges the developmental status
25
of an ecosystem in the sense that while food webs develop, trophic specialization will
33
1
result in higher values for AMI (Ulanowicz, 2004). The AMI is that part of the flow
2
diversity (i.e. the Shannon index applied to flow diversity, Ulanowicz, 2004) that
3
quantifies how orderly and coherently carbon flows are inter-connected. Since the
4
AMI is claimed to assess the developmental status of an ecosystems it is interesting to
5
assess whether differences in the food web structures are also reflected in the AMI
6
index. More specifically, we had expected the less-disturbed lower canyon section to
7
have highest AMI values with decreasing values going up-canyon. Differences in
8
AMI between the upper and middle canyon are non-significant (Table 6), though
9
large differences exist in environmental conditions and food web structure. The AMI
10
is significantly lower in the lower canyon section though this section is less impacted
11
by canyon conditions as compared to the other two sections. Tobor-Kaplon et al.
12
(2007) quantified the AMI of soil food webs that were exposed to different stress
13
levels (i.e. pH and copper) and concluded that AMI appeared useful as an indicator of
14
environmental stress at the ecosystem level. For the benthic food webs analyzed here
15
however, there does not seem to be a straightforward relation between AMI and
16
environmental stress. On the other hand, there is another important factor that
17
influences food web structure when going down-canyon, namely the reduced OM
18
input. To verify the usefulness of AMI as a stress indicator it is therefore necessary to
19
compare the AMI of marine benthic food webs at similar levels of OM input, but
20
different levels of environmental stress.
21
In conclusion, benthic food web structures in the upper, middle and lower
22
sections of the Nazaré canyon were shown to be influenced by the conditions in the
23
particular canyon section. The OM input in the upper and middle canyon sections is
24
elevated as compared to those of the surrounding open slope sediments and this
25
resulted in a higher contribution of fauna in carbon processing as compared to open
34
1
slope sites at similar water depth. The compartments that were responsible for the
2
faunal processing were strongly influenced by conditions in the particular canyon
3
section. In the upper canyon section, a dominance of meiofauna in faunal carbon
4
processing was evident, whereas a high faunal contribution to carbon processing in
5
open slope sediments is typically dominated by macrofauna. It is proposed that
6
hydrodynamic disturbance and resulting sediment resuspension in the upper canyon
7
shifts the balance towards the meiofauna. In contrast, the food web of the accreting
8
sediments in the middle canyon showed a completely different pattern where carbon
9
processing was dominated by the megafaunal holothurians. Our study confirms that
10
accreting sediments in canyons can be hotspots of megafaunal biomass and
11
production and megafauna can greatly influence carbon processing. The food web
12
structure of the lower canyon section resembled that of lower slope and abyssal plain
13
sediment, where carbon processing is dominated by prokaryotes. The influence of the
14
canyon-specific processes seems to vanish in the deeper sections where the Nazaré
15
canyon widens and enters the abyssal plain. In all canyon sections, a dominance of
16
semi-labile detritus in the diet of (surface) deposit feeders is suggested. These results
17
are supported by stable isotope tracer (for meiofauna) and gut transformation
18
(holothurian M. musculus) studies. This study shows that elevated OM input in
19
canyons may favor the faunal contribution to carbon processing and creating hotspots
20
of faunal biomass and carbon processing along the continental shelf.
21
Acknowledgements
22
This research was supported by the HERMES project (contract
23
GOCE-CT-2005-511234), funded by the European Commission’s Sixth Framework
24
Programme under the priority “Sustainable Development, Global Change and
35
1
Ecosystems”, and HERMIONE project (grant agreement n° 226354") funded by the
2
European Community's Seventh Framework Programme (FP7/2007-2013). This is
3
publication 5018 of the Netherlands Institute of Ecology (NIOO-KNAW), Yerseke.
36
1
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Cremer, A., Abraham, W.R., Jorgensen, B.B., Pfannkuche, O., 2003. In situ
20
experimental evidence of the fate of a phytodetritus pulse at the abyssal sea floor.
21
Nature 424 (6950), 763-766.
22
Woulds, C., Andersson, J.H., Cowie, G.L., Middelburg, J.J., Levin, L.A., 2009. The
23
short-term fate of organic carbon in marine sediments: Comparing the Pakistan
24
margin to other regions. Deep-Sea Research Part II-Topical Studies in
25
Oceanography 56 (6-7), 393-402.
46
1
Woulds, C., Cowie, G.L., Levin, L.A., Andersson, J.H., Middelburg, J.J., Vandewiele,
2
S., Lamont, P.A., Larkin, K.E., Gooday, A.J., Schumacher, S., Whitcraft, C.,
3
Jeffreys, R.M., Schwartz, M., 2007. Oxygen as a control on seafloor biological
4
communities and their roles in sedimentary carbon cycling. Limnology and
5
Oceanography 52 (4), 1698-1709.
6
7
47
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
48
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
49
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
50
Assimilation efficiency of labile
[0.57, 0.77]
[0.57, 0.77]
[0.57, 0.77]
-
6, 7
[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
[50, 100]
[50, 100]
[50, 100]
-
See text
[1, 10]
[1, 10]
[1, 10]
-
See text
[0.75, 1.00]
[0.75, 1.00]
[0.75, 1.00]
-
See text
[0.40, 0.75]
[0.40, 0.75]
[0.40, 0.75]
-
6, 7
[0.20, 0.38]
[0.20, 0.38]
[0.20, 0.38]
-
See text
sources Mei3
Assimilation efficiency of semi-labile
detritus Mei3
and MegSDF6
Feeding preference MeiNSF, MacDF
and MegDF6
Feeding preference MeiPO, MacPS
and MegPS7
Assimilation efficiency of labile
sources of Mac and Meg3
Assimilation efficiency of semi-labile
51
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
[0.60, 1.00]
[0.60, 1.00]
[0.30, 1.00]
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,
[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
[0, 0.10]
[0, 0.10]
[0, 0.10]
-
11
1, see Text
respiration by Bac, Mei and Mac
sDet_w, rDet_w and by MacSF
total POC input
1
Degradation rate is defined as outflows from detritus compartment
divided its stock:
.
52
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
proportion.
7
Feeding preference is defined as fraction of total ingested met by predation.
.
.
and is 1 when food sources are consumed in their stock
53
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
and
to
where
represents the columns of the flow matrix
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
species with which either
Identity matrix
or
interact
and
interact divided by the number of
54
Table 4. Algorithms for the calculation of the network indices; see Table 3 for
symbols.
Index name
Total System
Throughput
Code
T..
Total System
Throughflow
TST
Total System cycled
throughflow
TSTc
Finn’s Cycling Index
FCI
Average Mutual
Information
AMI
Formula
55
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
Total respiration
Bac
MeiSF
MeiNF
MeiPO
MacSDF
MacDF
MacSF
MacPS
MegSDF
MegDF
Upper
4.52±0.28
70.0
6.1
11.8
2.6
0.5
0.22
0.02
8.23
Middle
5.06±0.30
37.9
1.0
1.5
0.4
0.17
0.7
0.2
0.3
2.89
54.5
Lower
0.86±0.02
81.7
8.2
3.2
1.1
0.7
0.5
1.25
3.3
56
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
57
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
index
(B) and average mutual information
and lower sections of the Nazaré canyon.
(A), Finn cycling
(C) of the upper, middle
58
Figure 1
Uppe r re gion
Burial Export lDet
DIC
sDet
DOC_w
rDet
rDet_w
MeiPO
MacSDF
MacDF
rDet
A
B
Burial Export lDet
DIC
sDet
Burial Ex port lDet
DIC
sDet
DOC_w
rDet
rDet_w
DOC_w
DOC
sDet_w
lDet_w
MegSDF
MacPS
MacSF
MeiPO
MacSDF
MacDF
Burial Export lDet
DIC
sDet
DOC_w
rDet
rDet_w
sDet_w
MeiSF
MegDF
MegSDF
MacPS
MacSF
MeiPO
MacSDF
MacDF
G
lDet_w
MeiSF
MegDF
1.5
0.00015
MeiNF
MegSDF
MacPS
MacSF
MeiPO
MacSDF
MacDF
Burial Export lDet
DIC
sDet
rDet
DOC_w
DOC
MeiSF
MegSDF
MacPS
MacSF
MeiPO
MacSDF
Mac DF
H
DOC
sDet_w
Pro
lDet_w
MeiNF
MeiSF
MegDF
0.15
0.00015
1.5
0.00015
rDet
rDet_w
Pro
MegDF
0.15
0.00015
Pro
Burial Ex port lDet
DIC
sDet
lDet_w
MeiNF
DOC
sDet_w
F
sDet_w
15
0.00015
rDet
E
rDet_w
Pro
lDet_w
MeiPO
MacSDF
Mac DF
DOC_w
DOC
DOC_w
MeiSF
D
MeiPO
MacSDF
MacDF
rDet_w
MeiNF
MegSDF
MacPS
MacSF
MeiNF
MegSDF
MacPS
MacSF
Burial Export lDet
DIC
sDet
Pro
MegDF
1.5
0.00015
15
0.00015
DOC
lDet_w
MeiNF
MegDF
rDet
sDet_w
MeiSF
MegDF
MeiSF
C
rDet_w
Pro
Pro
lDet_w
MeiNF
MeiPO
MacSDF
Mac DF
DOC
sDet_w
MeiSF
MegSDF
MacPS
MacSF
rDet
rDet_w
Pro
MegDF
15
0.00015
DOC_w
DOC
lDet_w
MeiNF
MegSDF
MacPS
MacSF
Burial Export lDet
DIC
sDet
sDet_w
MeiSF
MegDF
Burial Ex port lDet
DIC
sDet
rDet_w
Pro
lDet_w
Lowe r re gion
DOC_w
DOC
sDet_w
Middle re gion
MeiNF
MegSDF
MacPS
MacSF
MeiPO
MacSDF
MacDF
I
0.15
0.00015
59
Figure 2
Diet cont ri buti on (-)
A) Uppe r re gion
1.0
0.8
0.6
MegDF
Mac PS
MegSDF
Mac SF
Mac DF
Mei PO
Mac SDF
0.0
Mei SF
0.2
Mei NF
0.4
s Det_w
lDet_w
Mac SF
Mac DF
Mac SDF
MeiPO
MeiNF
MeiSF
Pro
s Det
lDet
Diet cont ri buti on (-)
B) Middle re gion
1.0
0.8
0.6
MegDF
Mac PS
MegSDF
Mac SF
Mac DF
Mei PO
Mac SDF
0.0
Mei SF
0.2
Mei NF
0.4
s Det_w
lDet_w
Mac SF
Mac DF
Mac SDF
MeiPO
MeiNF
MeiSF
Pro
s Det
lDet
1.0
0.8
0.6
MegDF
Mac PS
MegSDF
Mac SF
Mac DF
0.0
Mei PO
Mac SDF
0.2
Mei NF
0.4
Mei SF
Diet cont ri buti on (-)
C) Lowe r re gion
s Det_w
lDet_w
Mac SF
Mac DF
Mac SDF
MeiPO
MeiNF
MeiSF
Pro
s Det
lDet
60
Figure 3
Uppe r re gion
Middle re gion
1.95
1.04
A
B
pro
mei
mac
meg
11.5
mort
2.06
D
mei
17.1
maint
mort
5.6
maint
mac
meg
maint
mort
42.2
36.1
mac
5.5
meg
29.5
maint
0.072
mort
meg
exp
mort
mac
29.4
meg
22
exp
1.975
J
meg
91.4
maint
4.1
5.3
mort
17.6
47.3
mei
mac
meg
mac
29.4
maint
meg
0.048
I
19.1
22
mac
0.2
mac
2
mac
mei
mei
mei
H
31.8
mort
mort
F
22.5
17.6
18.3
mac
24
meg
10.5
mei
0.424
G
1.3
88.2
0.34
E
21.3
55.9
mei
35.6
mac
mei
5.7
pro
1.2
51.7
30.9
mort
0.53
C
pro
4
65.1
Lowe r re gion
meg
ex p
maint
11.2
33.1
33.8
mort
mac
meg
exp
2. 0
2. 1
2. 2
2. 3
Average m utual i nformat ion (-)
2. 4
0. 05
0. 10
0. 15
Fi nn cycli ng i ndex (-)
0. 20
2 1
10
20
30
40
50
Tot al syst em throughput (m mol C m d )
61
Figure 4
A
Upper
Upper
Upper
Middle
Middle
Middle
Low er
B
Low er
C
Low er
62
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
Flow
Middle area
Mean
St. dev.
Mean
Mean
St. dev.
3.88E-01
2.29E-01
8.10E-01
3.67E-01
5.88E-02
4.36E-02
lDet_w→MacSF
1.60E-03
8.30E-04
1.97E-02
sDet_w→sDet
5.99E+00
7.90E-01
8.23E+00
9.02E-03
1.80E-02
9.63E-03
8.44E-01
1.10E+00
3.48E-02
sDet_w→MacSF
3.23E-03
1.66E-03
3.54E-02
1.64E-02
3.81E-02
2.07E-02
rDet_w→rDet
1.58E+00
9.64E-01
2.02E-01
1.62E-01
5.01E-02
3.68E-02
lDet→DOC
sDet→DOC
3.85E-01
2.47E-01
5.50E-01
3.61E-01
7.93E-02
5.22E-02
1.16E+00
6.90E-01
5.15E-01
3.99E-01
5.09E-01
7.73E-02
rDet→DOC
2.52E+00
6.34E-01
1.64E+00
3.23E-01
2.26E-01
6.99E-02
lDet→MeiSF
2.83E-01
1.85E-01
9.08E-02
5.09E-02
4.25E-02
2.68E-02
lDet→MeiNF
1.09E-01
7.60E-02
2.10E-02
1.39E-02
2.50E-03
1.68E-03
lDet→MeiPO
2.62E-02
2.21E-02
4.71E-03
3.93E-03
2.10E-03
1.76E-03
lDet→MacSDF
9.97E-03
8.45E-03
4.09E-03
3.40E-03
1.62E-03
1.36E-03
lDet→MacDF
1.19E-03
1.01E-03
4.65E-03
3.93E-03
2.30E-04
1.90E-04
lDet→MacPS
6.17E-02
5.15E-02
5.32E-03
4.41E-03
lDet_w→lDet
St. dev.
Lower area
3.13E-03
2.67E-03
lDet→MegSDF
8.82E-02
6.08E-02
lDet→MegDF
2.31E-01
1.26E-01
sDet→MeiSF
1.22E+00
2.22E-01
2.64E-01
6.10E-02
4.01E-01
4.31E-02
sDet→MeiNF
4.43E+00
4.99E-01
5.89E-01
7.03E-02
2.28E-01
3.00E-02
sDet→MeiPO
5.83E-02
3.14E-02
1.02E-02
5.40E-03
4.64E-03
2.46E-03
sDet→MacSDF
5.68E-02
1.16E-02
2.33E-02
4.74E-03
2.51E-02
4.22E-03
sDet→MacDF
6.10E-02
9.98E-03
2.35E-01
3.79E-02
3.36E-02
4.58E-03
sDet→MacPS
1.71E-01
8.80E-02
1.33E-02
6.20E-03
3.35E-01
3.99E-02
6.74E-03
3.63E-03
sDet→MegSDF
1.72E-01
6.78E-02
sDet→MegDF
6.90E+00
6.68E-01
3.85E+00
3.47E-01
rDet→Burial
3.05E+00
7.98E-01
DOC→DOC_w
2.16E-01
1.23E-01
2.86E-01
1.48E-01
4.71E-02
2.30E-02
DOC→Bac
5.14E+00
4.23E-01
2.96E+00
1.85E-01
1.23E+00
3.51E-02
Bac→DIC
3.18E+00
3.16E-01
1.91E+00
1.03E-01
7.05E-01
2.56E-02
Bac→DOC
1.28E+00
3.45E-01
5.38E-01
1.02E-01
4.65E-01
3.49E-02
Bac→MeiSF
4.25E-01
1.89E-01
9.33E-02
5.08E-02
5.05E-02
2.44E-02
Bac→MeiNF
1.42E-01
8.58E-02
2.13E-02
1.40E-02
2.55E-03
1.68E-03
Bac→MeiPO
2.74E-02
2.26E-02
4.70E-03
3.92E-03
2.10E-03
1.78E-03
Bac→MacSDF
1.04E-02
8.66E-03
4.12E-03
3.42E-03
1.62E-03
1.38E-03
Bac→MacDF
1.21E-03
1.03E-03
4.63E-03
3.93E-03
2.30E-04
1.90E-04
Bac→MacPS
6.40E-02
5.23E-02
3.04E-03
2.60E-03
5.19E-03
4.23E-03
9.06E-02
6.11E-02
Bac→MegSDF
63
Bac→MegDF
2.83E-01
9.85E-02
MeiSF→DIC
2.77E-01
9.63E-02
7.19E-02
2.49E-02
7.07E-02
1.48E-02
MeiSF→lDet
1.20E-01
9.33E-02
2.69E-02
2.15E-02
3.46E-02
1.47E-02
MeiSF→sDet
2.42E-01
6.92E-02
6.38E-02
1.87E-02
3.18E-02
7.75E-03
MeiSF→rDet
8.12E-01
1.57E-01
1.76E-01
4.34E-02
2.70E-01
3.28E-02
MeiSF→MeiPO
1.71E-01
1.09E-01
3.51E-02
2.14E-02
2.07E-02
7.80E-03
MeiSF→MacSDF
9.87E-03
8.27E-03
3.78E-03
3.21E-03
1.63E-03
1.38E-03
MeiSF→MacDF
1.19E-03
1.02E-03
4.21E-03
3.63E-03
2.30E-04
1.90E-04
MeiSF→MacPS
2.97E-01
1.65E-01
1.50E-02
1.07E-02
6.35E-02
1.12E-02
MeiSF→MegSDF
2.46E-02
2.01E-02
MeiSF→MegDF
2.69E-02
2.11E-02
MeiNF→DIC
5.34E-01
1.87E-01
7.66E-02
2.21E-02
2.78E-02
7.16E-03
MeiNF→lDet
1.36E-01
1.00E-01
2.78E-02
2.13E-02
1.62E-02
9.22E-03
MeiNF→sDet
8.30E-02
2.92E-02
1.41E-02
4.95E-03
1.68E-03
5.90E-04
MeiNF→rDet
2.93E+00
3.65E-01
3.94E-01
5.37E-02
1.55E-01
2.32E-02
MeiNF→MeiPO
2.68E-01
1.12E-01
4.15E-02
2.19E-02
1.41E-02
7.36E-03
MeiNF→MacSDF
1.01E-02
8.48E-03
3.80E-03
3.23E-03
1.59E-03
1.35E-03
MeiNF→MacDF
1.20E-03
1.03E-03
4.25E-03
3.69E-03
2.30E-04
2.00E-04
MeiNF→MacPS
7.15E-01
1.45E-01
1.59E-02
1.11E-02
1.71E-02
9.54E-03
MeiNF→MegSDF
2.58E-02
2.05E-02
MeiNF→MegDF
2.79E-02
2.15E-02
MeiPO→DIC
1.18E-01
3.62E-02
2.07E-02
6.21E-03
9.50E-03
2.69E-03
MeiPO→lDet
9.71E-02
6.21E-02
7.65E-03
6.17E-03
7.60E-03
4.54E-03
MeiPO→sDet
1.77E-01
4.72E-02
3.07E-02
8.07E-03
1.42E-02
3.64E-03
MeiPO→rDet
3.85E-02
2.09E-02
6.72E-03
3.58E-03
3.06E-03
1.63E-03
MeiPO→MacSDF
9.68E-03
8.29E-03
2.99E-03
2.68E-03
1.53E-03
1.32E-03
MeiPO→MacDF
1.19E-03
1.03E-03
3.15E-03
2.85E-03
2.20E-04
1.90E-04
MeiPO→MacPS
1.10E-01
6.36E-02
7.54E-03
4.56E-03
6.75E-03
5.65E-03
MeiPO→MegSDF
9.87E-03
7.07E-03
MeiPO→MegDF
7.77E-03
6.32E-03
MacSDF→DIC
2.21E-02
3.41E-03
8.63E-03
1.35E-03
5.75E-03
8.80E-04
MacSDF→lDet
5.55E-03
3.97E-03
2.24E-03
1.59E-03
1.46E-03
1.04E-03
MacSDF→sDet
2.58E-02
7.39E-03
9.61E-03
2.84E-03
3.93E-03
1.21E-03
MacSDF→rDet
4.21E-02
1.00E-02
1.73E-02
4.08E-03
1.91E-02
3.77E-03
MacSDF→MacPS
5.60E-03
4.02E-03
2.13E-03
1.56E-03
1.45E-03
1.04E-03
MacSDF→Export
5.63E-03
4.01E-03
2.21E-03
1.59E-03
1.46E-03
1.05E-03
MacDF→DIC
9.94E-03
1.52E-03
3.77E-02
5.83E-03
4.70E-03
6.70E-04
MacDF→lDet
2.48E-03
1.79E-03
9.77E-03
6.91E-03
1.19E-03
8.40E-04
MacDF→sDet
2.73E-03
9.30E-04
9.46E-03
3.23E-03
5.00E-04
1.60E-04
MacDF→rDet
4.68E-02
9.03E-03
1.80E-01
3.42E-02
2.60E-02
4.13E-03
MacDF→MacPS
2.57E-03
1.83E-03
8.86E-03
6.47E-03
1.17E-03
8.50E-04
MacDF→Export
2.51E-03
1.81E-03
9.99E-03
6.95E-03
1.18E-03
8.50E-04
MacSF→DIC
9.40E-04
1.80E-04
1.11E-02
2.06E-03
1.08E-02
1.97E-03
MacSF→lDet
2.50E-04
1.80E-04
2.94E-03
2.16E-03
2.82E-03
2.04E-03
MacSF→sDet
7.70E-04
4.80E-04
9.38E-03
5.37E-03
8.63E-03
5.52E-03
MacSF→rDet
2.38E-03
1.30E-03
2.59E-02
1.27E-02
2.83E-02
1.63E-02
64
MacSF→MacPS
2.50E-04
1.80E-04
2.84E-03
2.10E-03
2.78E-03
2.03E-03
MacSF→Export
2.50E-04
1.80E-04
2.94E-03
2.13E-03
2.84E-03
2.06E-03
MacPS→DIC
3.72E-01
6.33E-02
1.64E-02
2.67E-03
2.85E-02
3.83E-03
MacPS→lDet
1.27E-01
7.52E-02
6.36E-03
3.72E-03
1.09E-02
5.78E-03
MacPS→sDet
6.35E-01
1.31E-01
3.07E-02
8.29E-03
5.79E-02
9.04E-03
MacPS→rDet
1.22E-01
6.39E-02
4.82E-03
2.65E-03
9.50E-03
4.53E-03
MacPS→Export
1.71E-01
7.71E-02
6.17E-03
3.71E-03
1.05E-02
5.92E-03
MegSDF→DIC
1.46E-01
1.56E-02
MegSDF→lDet
1.41E-02
9.82E-03
MegSDF→sDet
1.13E-01
4.10E-02
MegSDF→rDet
1.24E-01
5.14E-02
MegSDF→Export
1.42E-02
9.76E-03
MegDF→DIC
2.75E+00
2.47E-01
MegDF→lDet
9.07E-02
7.22E-02
MegDF→sDet
2.07E-01
5.73E-02
MegDF→rDet
4.36E+00
4.22E-01
MegDF→Export
6.77E-02
5.22E-02