Introduction
Abyssal plains cover approximately 50 % of the world's surface and
75 % of the seafloor (Ramírez-Llodrà et al., 2010). The abyssal
seafloor is primarily composed of soft sediments consisting of fine-grained
erosional detritus and biogenic particles (Smith et al., 2008). Occasionally,
hard substrate occurs in the form of clinker from steam ships, glacial drop
stones, outcrops of basaltic rock, whale carcasses, and marine litter (Amon
et al., 2017; Kidd and Huggett, 1981; Radziejewska, 2014;
Ramírez-Llodrà et al., 2011; Ruhl et al., 2008). In some
soft-sediment regions, islands of hard substrate are provided by polymetallic
nodules, authigenically formed deposits of metals, that grow at approximately
2 to 20 mm per million years (Guichard et al., 1978; Kuhn et al., 2017).
These nodules have shapes and sizes of cauliflower florets, cannon balls, or
potatoes, and are found on the sediment surface and in the sediment at water
depths between 4000 and 6000 m in areas of the Pacific, Atlantic, and Indian
Ocean (Devey et al., 2018; Kuhn et al., 2017).
(a) Location of the DISCOL experimental area (DEA) in the
Peru Basin (SE Pacific; red square), (b) detailed map of the DEA
indicated by the white circle, (c) location of all plough tracks
(black lines) that were observed by the “AUV Abyss” (Geomar Kiel) after
26 year during the R/V Sonne cruise SO242-1 (Greinert, 2015).
Polymetallic nodules are rich in metals, such as nickel, copper, cobalt,
molybdenum, zirconium, lithium, and rare-earth elements (Hein et al., 2013),
and occur in sufficient densities for potential exploitation by commercial
mining in the Clarion-Clipperton Fracture Zone (CCFZ; equatorial Pacific),
around the Cook Islands (equatorial Pacific), in the Peru Basin (E Pacific)
and in the central Indian Ocean basin (Kuhn et al., 2017). Extracting these
polymetallic nodules during deep-sea mining operations will have severe
impacts on the benthic ecosystem, such as the removal of hard substrate
(i.e., nodules) and the food-rich surface sediments from the seafloor,
physically causing the mortality of organisms within the mining tracks and
resettlement of resuspended particles (Levin et al., 2016; Thiel and
Forschungsverbund Tiefsee-Umweltschutz, 2001). Choosing appropriate
regulations on deep-sea mining requires knowledge of ecosystem recovery from
these activities, but to date information on these rates is not extensive,
especially on the recovery of ecosystem functions, such as food-web structure
and carbon (C) cycling (Gollner et al., 2017; Jones et al., 2017; Stratmann
et al., 2018a, b; Vanreusel et al., 2016).
In the Peru Basin (SE Pacific), a small-scale sediment disturbance experiment
was conducted during the “DISturbance and reCOLonization” experiment
(DISCOL) in 1989, which was aimed at mimicking deep-sea mining. A
10.8 km2 circular area (Fig. 1) was ploughed diametrically 78 times
with an 8 m wide plough-harrow; a treatment which did not remove nodules,
but disturbed the surface sediment, buried nodules into the sediment and
created a sediment plume (Thiel et al., 1989). This experimental disturbance
resulted in a heavily disturbed center and a less affected periphery of the
DISCOL area (Bluhm, 2001; Foell et al., 1990, 1992). Over 26 years, the
region was revisited five times to assess the post-disturbance (PD)
situation: directly after the disturbance event, March 1989: (hereafter
referred to as “PD0.1”); half a year later, September 1989:
“PD0.5”; 3 years later, January 1992: “PD3”; 7 years
later, February 1996: “PD7”; and 26 years later, September 2015:
“PD26”. During subsequent visits, densities of macrofauna and
invertebrate megafauna were assessed, but data on meiofaunal and microbial
communities were collected only sparsely. Therefore, the food-web models
presented in this work cover post-disturbance 1989 (no adequate
pre-disturbance sampling took place in 1989) to 2015, and contain only
macrofauna, invertebrate megafauna and fish data.
Linear inverse modeling is an approach that has been developed to
disentangle carbon flows between food-web compartments for data-sparse
systems (Klepper and Van De Kamer, 1987; Vézina and Platt, 1988). It has
been applied to assess differences in carbon and nitrogen (N) cycling in
various ecosystems, including the abyssal-plain food web at Station M (NE
Pacific) under various particulate organic carbon (POC) flux regimes (Dunlop
et al., 2016), and a comparison of food-web flows between abyssal hills and
plains at the Porcupine Abyssal Plain (PAP) in the north-eastern Atlantic
(Durden et al., 2017).
The aim of this study was (I) to assess whether faunal carbon stock and
trophic composition of the food webs varied and/or converged over the time
series between outside and inside plough tracks at DISCOL; (II) to compare
our model outcomes with the conceptual and qualitative predictions on benthic
community recovery from polymetallic nodule mining published by Jumars (1981)
and (III) to infer the recovery rate of C cycling following from a deep-sea
sediment disturbance experiment using the network index “total system
throughput” ΔT.., i.e., the sum of all C flows in the food web
(Kones et al., 2009), developed over time.
Methods
Linear inverse model
Linear inverse modeling is based on the principle of mass balance and
various data sources (Vézina and Platt, 1988), i.e., faunal carbon stock
and physiological constraints, that are implemented in the model, either as
equalities or inequalities, and they are solved simultaneously. A food-web
model with all compartments present in the food web, e.g., the PD26 food
web model outside plough tracks, consisted of 147 carbon flows with 14 mass
balances, i.e., food-web compartments, and 76 data inequalities leading to a
mathematically under-determined model (14 equalities vs. 147 unknown flows).
Therefore, the linear inverse models (LIMs) were solved with the R package
“LIM” (van Oevelen et al., 2010) in R (R-Core Team, 2017) following the
likelihood approach (van Oevelen et al., 2010) to quantify means and standard
deviations of each of the carbon flows from a set of 100 000 solutions. This
set was sufficient to guarantee convergence of means and standard deviations
within a 2.5 % deviation.
Number of box cores (nbox cores) taken for macrofauna
sampling outside plough tracks (outside PT) and inside plough tracks (inside
PT) directly after the disturbance event in March 1989 (PD0.1), 0.5-year
post-disturbance (September 1989, PD0.5), 3-year post-disturbance
(January 1992, PD3), 7-year post-disturbance (February 1996, PD7),
and 26-year post-disturbance events (September 2015, PD26). Number of “OFOS”
tracks (“ocean floor observatory system”; nOFOS tracks) analyzed
to estimate invertebrate megafauna and fish density and total area of
seafloor (m2) that was surveyed during each sampling event outside and
inside plough tracks. References: 1 Borowski and Thiel (1998),
2 Borowski (2001), 3 this study, 4 Bluhm (2001).
Macrofauna
Invertebrate megafauna and fish
nbox cores
Ref.
nOFOS tracks
Total area surveyed (m2)
Ref.
Outside PT
Inside PT
Outside PT
Inside PT
Outside PT
Inside PT
PD0.1
21
7
1,2
4
5
76 120
15 639
4
PD0.5
22
8
1,2
4
3
53 542
11 708
4
PD3
20
9
1,2
4
4
32 457
6673
4
PD7
8
8
2
4
4
64 536
16 013
4
PD26*
7
3
3
1420
1441
3
* During PD26, the densities of invertebrate megafauna
and fish were estimated using 300 pictures from outside plough tracks and 300
pictures from inside plough tracks that were randomly selected from a 21 OFOS
tracks (Boetius, 2015).
Food-web models from different sites and/or points in time were compared
quantitatively by calculating T.. with the R package “NetIndices” (Kones
et al., 2009) for each of the 100 000 model solutions and subsequently
summarized as mean ± standard deviation. A decrease in the difference
of T.. between the food webs from outside and inside plough tracks (ΔT..) over time was taken as a sign of ecosystem recovery following
disturbance.
Data availability
Macrofauna, invertebrate megafauna, and fish density data
(mean ± SD; ind. m-2) for the first four
cruises (PD0.1 to PD7) were extracted from the original papers
(Borowski and Thiel, 1998; Bluhm, 2001 annex 2.8; Borowski, 2001), and methodological details can be found in
those papers. In brief, macrofaunal samples (> 500 µm size
fraction) were collected with a 0.25 m-2 box corer (number of samples
is reported in Table 1), and densities of invertebrate megafauna and fish
were assessed on still photos and videos taken with a towed “Ocean Floor
Observation System” (OFOS) underwater camera system (extent of total
surveyed area is reported in Table 1). During the PD26 cruise (R/V
Sonne cruise SO242-2; Boetius, 2015), macrofauna were collected with
a square 50 × 50 × 60 cm box corer (outside plough tracks:
n=7; inside plough tracks: n=3), and the upper 5 cm of sediment were
sieved on a 500 µm sieve (Greinert, 2015). All organisms retained
on the sieve were preserved in 96 % un-denatured
ethanol on board (Greinert, 2015)
and were sorted and identified ashore under a stereomicroscope to the same
taxonomic level as the previous cruises. Invertebrate megafauna and fish
density during the PD26 cruise were acquired by deploying the OFOS
(Boetius, 2015). Every 20 s, the OFOS automatically took a picture from
approximately 1.5 m above the seafloor (Boetius, 2015; Stratmann et al.,
2018b) resulting in 1740 images of plough marks (inside plough tracks) and
6624 images from outside plough tracks (Boetius, 2015). A subset of
300 pictures from inside plough tracks (surface area: 1441 m2) and
300 pictures from the outside plough tracks (surface area: 1420 m2)
were randomly selected from the original set of pictures and annotated using
the open-source annotation software PAPARA(ZZ)I (Marcon and Purser, 2017).
Invertebrate megafauna were identified to the same taxonomic levels as for
the previous megafauna studies conducted within the DISCOL experimental area
(DEA; Bluhm, 2001), whereas fishes were identified to genus using the
Clarion-Clipperton Zone (CCZ) species atlas (http://www.ccfzatlas.com,
last access: 14 February 2018).
The above-mentioned density data collected for macrofauna, invertebrate
megafauna and fish were used to build food-web models to resolve carbon
fluxes; hence, all faunal density data required conversion into carbon units
before they could be used in the food-web model. Converting density data to
carbon stocks was challenging in the current study, as few to no conversion
factors for deep-sea fauna are available in the literature. Below, we
describe the approach that we used to tackle this problem for macrofauna,
invertebrate megafauna, and fish.
Taxon-specific biomass per individual (mmol C ind-1) for
macrofauna and invertebrate megafauna including the specific feeding types.
Macrofaunal biomass data are based on macrofaunal specimens collected in the
abyssal plains of the Clarion-Clipperton Zone (NE Pacific; Sweetman et al.,
2018). In contrast, invertebrate megafaunal biomass was estimated by
converting size measurements of specific body parts of organisms from DEA
that were acquired using photo-annotation into preserved wet weight per
organism using the relationships presented in Durden et al. (2016).
Subsequently the preserved wet weight was converted into fresh wet weight and
biomass following the conversions presented in Durden et al. (2016) and
Rowe (1983). Whenever no conversion factors for a specific taxon were
reported in Durden et al. (2016) mean taxon-specific biomass data per
individual were extracted from Tilot (1992) for the CCZ. The “n” refers to
the number of individuals used to estimate taxon-specific biomasses. A
detailed list with exact conversion factors for invertebrate megafauna is
presented in Supplement 1. The abbreviation are the following: C = carnivores,
DF = deposit feeders, FSF = filter/suspension feeders,
O = omnivores, PolC = carnivorous polychaetes, PolOF = omnivorous
polychaetes, PolSF = suspension-feeding polychaetes, PolSDF = surface
deposit-feeding polychaetes, PolSSDF = subsurface deposit-feeding
polychaetes, S = scavengers. References: 1 Fox et al. (2003),
2 Menzies (1962), 3 McClain et al. (2004), 4 Smith and
Stockley (2005), 5 Gage and Tyler (1991), 7 Jumars et al. (2015),
8 Bluhm (2001), 9 Drazen and Sutton (2017).
Size class
Taxon
Feeding type
n
Biomass (mmol C ind-1) (Mean ± SE)
Macro-fauna
Bivalviaa
FSF1
7
1.4 × 10-3 ± 3.1 × 10-4
Cumaceaa
DF1
2
3.1 × 10-3 ± 4.4 × 10-4
Echinoideab
85 % O, 15 % DF4
64
9.7 × 10-3 ± 3.6 × 10-3
Gastropodaa
90 % DF, 10 % C3
2
8.6 × 10-2 ± 2.8 × 10-2
Isopodaa
93 % DF, 7 % C2
4
1.3 × 10-3 ± 5.3 × 10-4
Ophiuroideab
C1
64
9.7 × 10-3 ± 3.6 × 10-3
Polychaetaa
PolSF, PolSDF, PolSSDF,PolC, PolOF7
26
1.3 × 10-2 ± 7.2 × 10-3
Scaphopodab
C1
64
9.7 × 10-3 ± 3.6 × 10-3
Tanaidaceaa
DF1
5
5.5 × 10-3 ± 4.7 × 10-3
Mega-fauna
Actiniaria
FSF1
301
3.0 × 10-1 ± 5.0 × 10-2
Alcyonacead
FSF1
2.2 × 101
Antipatharia
FSF1
3
1.8 × 102 ± 3.9 × 101
Ascidiacead
FSF1
8.3 × 10-1
Asteroidea
C1
53
1.4 × 102 ± 6.0
Cephalopoda
C1
7
4.7 × 101 ± 1.1 × 101
Cerianthariad
FSF1
1.9 × 103
Cnidariac
FSF1
2.4 × 10-1
Crinoidead
FSF1
5.3
Crustacea
C1,8
541
2.6 ± 4.3 × 10-1
Echinoidead
15 % DF, 85 % OF4
5.9 × 101
Hemichordatag
DF5,8
2.2 × 101
Holothuroideae
DF1
450
1.5 × 101 ± 1.6 × 101
Ophiuroidea
C1
527
1.6 × 101 ± 4.4 × 10-1
Pennatulariad
FSF1
2.2 × 101
Polychaeta
PolSF, PolSDF, PolSSDF,PolC, PolOF7
62
5.3 × 10-1 ± 1.5 × 10-3
Poriferac
FSF1
6.7
Fish
Osteichthyesf
S, C9
10
7.3 × 101 ± 1.3 × 101
a Taxon-specific individual biomass;
b Individual biomass calculated based on all other macrofauna data;
c Median taxon-specific individual biomass for individuals from the
Porcupine Abyssal Plain where Durden et al. (2016) did not have reliable
dimension measurements; d Mean taxon-specific biomass data per
individual were extracted from Tilot (1992) for the CCZ;
e Individual biomass of Benthodytes sp., one of the most
abundant holothurian morphotype at the DISCOL site (Stratmann et al., 2018b);
f Individual biomass of Ipnops sp., the most abundant
deep-sea fish at the PD26 outside plough tracks; g Individual
biomass calculated for mean benthic invertebrate megafauna at 4100 m depth
based on the biomass-bathymetry and abundance-bathymetry relationships
presented in Rex et al. (2006).
Mean carbon stocks (mmol C m-2) of the food-web compartments
for outside (outside PT) and inside (inside PT) the plough tracks at the
DISCOL experimental area (Peru Basin, SE Pacific) 0.1 year post-disturbance
(PD0.1), for 0.5-year post-disturbance (PD0.5), for 3-year post-disturbance
(PD3), for 7-year post-disturbance (PD7), and for
26-year post-disturbance events (PD26). For visibility reasons, no error bars
are plotted, but mean ± standard deviations of each food-web
compartment are presented in Supplement 2. The abbreviation are the following:
MacC = macrofauna carnivores, MacDF = macrofauna deposit feeders,
MacFSF = macrofauna filter/suspension feeders, MacO = macrofauna
omnivores, MegC = invertebrate megafauna carnivores,
MegDF = invertebrate megafauna deposit feeders, MegFSF = invertebrate
megafauna filter/suspension feeders, MegOF = invertebrate megafauna
omnivores, PolC = polychaete carnivores, PolOF = polychaete
omnivores, PolSDF = polychaete surface deposit feeders,
PolSF = polychaete suspension feeders, PolSSDF = polychaete
subsurface deposit feeders.
Measuring the carbon content of a macrofaunal specimen requires its complete
combustion, which means that the specimen cannot be kept as a voucher.
Macrofaunal samples collected for this study are part of the Biological
Research Collection of Marine Invertebrates (Department of Biology &
Centre for Environmental and Marine Studies, University of Aveiro, Portugal)
and were therefore not sacrificed. Instead, we used the C conversion factors
of macrofaunal specimens previously collected within the framework of a
pulse-chase experiment in the CCZ (NE Pacific), in
which a deep-sea benthic lander (3 incubation chambers,
20 × 20 × 20 cm each) was deployed at water depths between 4050
and 4200 m (Sweetman et al., 2018). The upper 5 cm of the sediment of the
incubation chambers were sieved on a 500 µm sieve and preserved in
4 % buffered formaldehyde. Ashore, the samples were sorted and identified
under a dissecting microscope, and the carbon content of individual
freeze-dried, acidified specimens was determined with a Thermo Flash EA 1112
elemental analyzer (EA; Thermo Fisher Scientific, USA) to give the individual
biomass in mmol C ind-1. Macrofaunal density data (ind. m-2) from
all cruises were converted to macrofaunal carbon stocks (mmol C m-2)
by multiplying each taxon-specific density (ind. m-2) with the mean,
taxon-specific, individual biomass value for macrofauna (mmol C ind-1;
Table 2). Subsequently, the carbon stock data of all taxa with the same
feeding type (Table 2) were summed to calculate the carbon stock of each
macrofaunal compartment (mmol C m-2; Supplement 2, Fig. 2).
The invertebrate megafaunal density data (ind. m-2) of the time series
was converted to carbon stocks (mmol C m-2) by multiplying the
taxon-specific density with a taxon-specific mean biomass per invertebrate
megafaunal specimen (mmol C ind-1; Table 2). To determine this
taxon-specific biomass per invertebrate megafaunal specimen, size
measurements were used as follows. The “AUV Abyss” (Geomar Kiel) equipped
with a Canon EOS 6D camera system with 8–15 mm f4 fisheye zoom lens and
24 LED arrays for lightning (Kwasnitschka et al., 2016) flew approximately
4.5 m above the seafloor at a speed of 1.5 m s-1 and took one picture
every second (Greinert, 2015). Machine-vision processing was used to generate
a photomosaic (Kwasnitschka et al., 2016). A subsample covering an area of
16 206 m2 of the mosaic was annotated using the web-based annotation
software “BIIGLE 2.0” (Langenkämper et al., 2017). Lengths of all
invertebrate megafaunal taxa for which data were available from previous
cruises were measured using the approach presented in Durden et al. (2016).
Briefly, depending on the taxon, either body length, the diameter of the
disk, or the length of an arm was measured on the photo mosaic and converted
into biomass per individual (g ind-1) using the relationship between
measured body dimensions (mm) and preserved wet weight (g ind-1)
(Durden et al., 2016). Subsequently, the preserved wet weight (g ind-1)
was converted to fresh wet weight (g ind-1) using conversion factors
from Durden et al. (2016) and to organic carbon (g C ind-1 and
mmol C ind-1) using the taxon-specific conversion factors presented in
Rowe (1983) (a detailed list with all conversion factors is presented in
Supplement 2). For the taxa Cnidaria and Porifera, no conversion factors were
available. Therefore, taxon-specific individual biomass values were extracted
from a study from the CCZ (Tilot, 1992). The individual biomass of
Hemichordata was calculated as the average biomass of an individual deep-sea
invertebrate megafaunal organism (B, mmol C ind-1) at 4100 m depth
following from the ratio of the regression for total biomass and abundance by
Rex et al. (2006):
B=10-0.734-0.00039×depth10-0.245-0.00037×depth.
Following the approach applied to the macrofauna dataset, individual carbon
stocks of taxa with similar feeding types (Table 2) were summed to determine
carbon stocks of invertebrate megafauna food-web compartments
(mmol C m-2; Supplement 1; Fig. 2).
Individual biomass of fish was calculated using the allometric relationship
for Ipnops agassizii:
wet weight=a×lengthb,
where a=0.0049 and b=3.03 (Froese et al., 2014; Froese and Pauly, 2017),
as Ipnops sp. was the most abundant fish observed at the DEA
(60 % of total fish density outside plough tracks and 40 % of total
fish density inside plough tracks). The length (mm) of all Ipnops
sp. specimens was measured on the annotated 600 pictures (300 pictures from
outside plough tracks, 300 pictures from inside plough tracks) in PAPARA(ZZ)I
(Marcon and Purser, 2017) using three laser points captured in each image
(distance between laser points: 0.5 m; Boetius, 2015). The wet weight (g)
was converted to dry weight and subsequently to carbon content
(mmol C ind-1) using the taxon-specific conversion factors presented
in Brey et al. (2010).
Food-web structure
Faunal carbon stocks were further divided into feeding guilds in order to
define food-web compartments of the model. Fish (Osteichthyes) were
classified as scavenger/predator and macrofauna and invertebrate megafauna
were divided into filter/suspension feeders (FSF), deposit feeders (DF),
carnivores (C), and omnivores (OF) (Fig. 3; Table 2). Since feeding types are
well described for polychaetes (Jumars et al., 2015), we made a further
detailed classification of the macrofaunal polychaetes into suspension
feeders (PolSF), surface deposit feeders (PolSDF), subsurface deposit feeders
(PolSSDF), carnivores (PolC), and omnivores (PolOF).
Simplified schematic representation of the food web structure that
forms the basis of the linear inverse model (LIM). All compartments inside
the box were part of the food web model, whereas compartments outside the
black box were only considered as carbon influx or efflux, but were not
directly modeled. In order to simplify the graph, for macrofauna,
polychaetes, and invertebrate megafauna, only feeding types were presented
and no size classes. Solid black arrows represent the carbon flux between
food-web compartments and black dashed arrows represent the influx of carbon
to the model. Blue-dotted arrows show the loss of carbon from the food web
via respiration to DIC. The red dashed arrows indicate the loss of carbon
from the food web as feces and as predation by pelagic/benthopelagic fish.
External carbon sources that were considered in the model included suspended
detritus in the water column (Det_w), labile (lDet_s), and semi-labile
detritus (sDet_s) in the sediment. Suspended detritus was considered a
food source for polychaete, macrofaunal, and invertebrate megafaunal
suspension feeders. Labile and semi-labile sedimentary detritus was a source
for deposit-feeding and omnivorous polychaetes, macrofauna, and invertebrate
megafauna. Omnivores and carnivores of each size class preyed upon organisms
of the same and smaller size classes, i.e., MegC and MegOF preyed upon MegDF,
MegFSF, MacFSF, MacDF, MacC, MacOF, PolSDF, PolSSDF, PolSF, PolOF, and PolC.
Furthermore, MacC, PolC, MacOF, and PolOF preyed upon MacFSF, MacDF, PolSDF,
PolSSDF, and PolSF. Fish preyed upon all fauna and the carcass pool. This
carcass pool consisted of all fauna (macrofauna, invertebrate megafauna, and
fish) that died in the food web and was also a food source of omnivores.
Carbon losses from the food web were respiration to dissolved inorganic
carbon (DIC), predation on macrofauna, invertebrate megafauna, and fish by
pelagic/benthopelagic fishes, scavenging on carcasses by
pelagic/benthopelagic scavengers and feces production by all faunal
compartments.
Literature constraints
Carbon flows between faunal compartments are constrained in all models by
various minimum and maximum process rates and conversion efficiencies.
Assimilation efficiency (AE) is calculated as
AE=(I-F)/I,
where I is the ingested food and F is the feces (Crisp, 1971). The
min-max range was set from 0.62 to 0.87 for macrofauna, including polychaetes
(Stratmann et al., 2018c), from 0.48 to 0.80 for invertebrate megafauna
(Stratmann et al., 2018c) and from 0.84 to 0.87 for fish (Drazen et al.,
2007).
Net growth efficiency (NGE) is defined as
NGE=P/(P+R),
with P being secondary production and R being respiration (Clausen and
Riisgård, 1996). The min–max ranges are set to 0.60 to 0.72 for
macrofauna, including polychaetes (Clausen and Riisgård, 1996; Navarro et
al., 1994; Nielsen et al., 1995), from 0.48 to 0.60 for invertebrate
megafauna (Koopmans et al., 2010; Mondal, 2006; Nielsen et al., 1995) and
from 0.37 to 0.71 for fish (Childress et al., 1980). The secondary production
P (mmol C m-2) is calculated as
P=P/Bratio×carbon stock
with the P / B ratios for macrofauna, including polychaetes
(8.49 × 10-4 to 4.77 × 10-3 d-1; Stratmann
et al., 2018c), invertebrate megafauna (2.74 × 10-4 to
1.42 × 10-2 d-1; Stratmann et al., 2018c), and fish
(6.30 × 10-4 d-1; Collins et al., 2005; Randall, 2002).
The respiration rate R (mmol C m-2) was calculated as
R=bsFR×carbon stock,
where bsFR is the biomass-specific faunal respiration rate (d-1), and
ranges were fixed between 7.12 × 10-5 and
2.28 × 10-2 d-1 for macrofauna, including polychaetes
(Stratmann et al., 2018c), 2.74 × 10-4 and
1.42 × 10-2 d-1 for invertebrate megafauna (Stratmann et
al., 2018c), and 2.3 × 10-4 and 3.6 × 10-4 d-1 for fishes (Mahaut et al., 1995; Smith and Hessler,
1974).
Proportional contribution (in %) of the feeding types
C = carnivores, DF = deposit feeders, FSF = filter and suspension
feeders, and OF = omnivores to the total carbon stocks outside and inside
plough tracks in the DISCOL experimental area (Peru Basin, SE Pacific)
0.1-year post-disturbance (PD0.1), for 0.5-year post-disturbance
(PD0.5), for 3-year post-disturbance (PD3), for 7-year post-disturbance
(PD7), and for 26-year post-disturbance events (PD26).
Statistical analysis
Statistical differences between individual compartment carbon stocks from
outside vs. inside plough tracks for the same sampling event (PD0.1,
PD0.5, PD3, PD7, and PD26) were omitted because of a lack
of invertebrate megafaunal replicates) were assessed by calculating Hedges'
d (Hedges and Olkin, 1985a), which is especially suitable for small sample
sizes (Koricheva et al., 2013):
d=Y‾E-Y‾C/(nE-1)(sE)2+(nC-1)(sC)2/(nE+nC-2)0.5×JwithJ=1-(3/(4(nE+nC-2)-1)),
where Y‾E is the mean of the experimental group (i.e.,
carbon stock from inside plough tracks of a particular year),
Y‾C is the mean of the control group (i.e., carbon
stock from inside plough tracks of the respective year), sE and
sC are the standard deviations with corresponding groups,
nE and nC are the sample sizes of the corresponding
groups. The variance in Hedges' dσd2 (Koricheva et al., 2013) is estimated as
σd2=(nE+nC)/(nEnC)+d2/(2(nE+nC)).
The weighted Hedges' d and estimated variances (Hedges and Olkin, 1985b) of
the sum of all carbon stocks of the same sampling event were calculated as
d+=sum(di/σdi2)/sum(1/σdi2),
with σd+2=1/sum(1/σdi2).
Following Cohen's (1988) rule of thumb for effect sizes, Hedges' d=|0.2|
signifies a small experimental effect, implying that the carbon stocks of the
food-web compartments are similar between outside and inside plough tracks.
When Hedges' d=|0.5|, the effect size is medium, hence there is a moderate
difference, and when Hedges' d=|0.8|, the effect size is large, i.e.,
there is a large difference between carbon stocks of compartments from
outside and inside plough tracks.
(a) Mean faunal carbon ingestion
(mmol C m-2 d-1) as suspended detritus, sedimentary labile and
sedimentary semi-labile detritus outside and inside plough tracks 0.1-year
post-disturbance (PD0.1), 0.5-year post-disturbance (PD0.5), 3-year
post-disturbance (PD3), 7-year post-disturbance (PD7), and 26-year
post-disturbance events (PD26). (b) Mean carbon losses
(mmol C m-2 d-1) from the food webs as predation, feces,
scavenging on the carcass, and faunal respiration outside and inside plough
tracks during PD0.1, PD0.5, PD3, PD7, and PD26. In
both figures, the error bars represent 1 standard deviation.
The network index T.. was compared between the outside and inside plough
tracks of the same sampling event by assessing the fraction of the T..
values of the 100 000 model solutions of the outside plough track food web
that were larger than the T.. values of the 100 000 model solutions of the
outside plough track food web. When this fraction is > 0.95, the
difference in “total system throughput” between the two food webs from the
same sampling event is considered significantly different (van Oevelen et
al., 2011), indicating that carbon flows in the food web from that specific
sampling event have not recovered from the experimental disturbance.
Results
Food-web structure and trophic composition
Total faunal carbon stocks were always higher outside plough tracks as
compared to inside plough tracks during the same sampling year (Fig. 2,
Supplement 1), and ranged from a minimum of
5.5 ± 1.3 mmol C m-2 (PD0.1) to a maximum
22.3 ± 3.4 mmol C m-2 (PD3) outside plough tracks and from
a minimum of 1.4 ± 1.2 mmol C m-2 (PD0.1) to a maximum
15.8 ± 2.0 mmol C m-2 (PD3) inside plough tracks. During
PD0.1, the total faunal carbon stock inside plough tracks was only
25 % of the total faunal carbon stock outside plough tracks, whereas
during PD3 the total faunal carbon stock inside plough tracks was
71 % of the total faunal carbon stock outside plough tracks. During
PD26, the faunal carbon stock inside plough tracks was 54% of the
carbon stock outside plough tracks. The absolute weighted Hedges' d|d+|
of all faunal compartment carbon stocks for PD0.1 to PD7 ranged
from 0.53 ± 0.02 during PD0.5 to 0.75 ± 0.02 during PD3
(Supplement 3), indicating a moderate experimental effect and therefore that
carbon stocks of all faunal compartments failed to recover over the period
analyzed (PD0.1 to PD7).
The faunal carbon stocks outside and inside plough tracks from PD0.1 to
PD7 were dominated by deposit feeders (from 63 % outside plough
tracks to 83 % inside plough tracks during PD0.5 and inside plough
tracks during PD3) (Fig. 4). In contrast, outside plough tracks during
PD26, filter- and suspension feeders had the largest contribution to
total faunal carbon stock (44 %), whereas deposit feeders only
contributed 35 %. Inside plough tracks during PD26, deposit feeders
had the highest carbon stock (61 %), followed by carnivores (19 %)
and filter and suspension feeders (14 %).
Faunal respiration rate (mmol C m-2 d-1) and
contribution (%) of the size classes macrofauna, polychaetes, invertebrate
megafauna, and fish to the respiration outside plough tracks (outside PT) and
inside plough tracks (inside PT) directly after the disturbance event in
March 1989 (PD0.1), 0.5-year post-disturbance (September 1989,
PD0.5), 3-year post-disturbance (January 1992, PD3), 7-year
post-disturbance (February 1996, PD7), and 26-year post-disturbance
events (September 2015, PD26).
PD0.1, outside PT
PD0.1, inside PT
PD0.5, outside PT
PD0.5, inside PT
PD3, outside PT
PD3, inside PT
PD7, outside PT
PD7, inside PT
PD26, outside PT
PD26, inside PT
Faunal respiration
1.0 × 10-2
2.7 × 10-3
1.1 × 10-2
6.0 × 10-3
3.9 × 10-2
3.0 × 10-2
2.1 × 10-2
1.5 × 10-2
2.0 × 10-2
1.1 × 10-2
± 1.2 × 10-4
± 5.2 × 10-6
± 5.7 × 10-5
± 6.8 × 10-5
± 3.7 × 10-4
± 2.3 × 10-4
± 2.5 × 10-4
± 1.5 × 10-4
± 1.5 × 10-4
± 1.0 × 10-4
Macrofauna
8.6
7.3
9.7
14.4
50.0
58.4
6.5
4.5
2.6
1.2
Polychaeta
61.6
77.8
62.7
77.6
27.1
30.0
67.1
83.5
18.5
32.4
Invertebrate megafauna
29.5
14.9
27.1
8.0
22.3
11.5
25.8
11.6
78.7
65.0
Fish
3.0 × 10-1
0.00
5.3 × 10-1
0.00
6.4 × 10-1
7.8 × 10-2
6.6 × 10-1
3.5 × 10-1
1.7 × 10-1
1.4
Carbon flows
Total faunal C ingestion (mmol C m-2 d-1) ranged from
8.6 × 10-3 ± 1.6 × 10-5 inside plough
tracks during PD0.1 to
1.5 × 10-1 ± 8.6 × 10-4 outside plough
tracks during PD3 and was always lower inside plough tracks compared to
outside plough tracks (Fig. 5a; Supplement 4). The ingestion consisted mainly
of sedimentary detritus (labile and semi-labile) that contributed between
57 % (outside plough tracks, PD26) and 100 % (inside plough
tracks, PD0.1) to the total carbon ingestion.
Faunal respiration (mmol C m-2 d-1) ranged from
6.0 × 10-3 ± 6.8 × 10-5 (inside plough
tracks, PD0.5) to 3.9 × 10-2 ± 3.7 × 10-4 (outside plough tracks, PD3). During the
26 years after the DISCOL experiment, modeled faunal respiration was always
higher outside plough tracks than inside plough tracks (Table 3, Fig. 5b).
Over time, non-polychaete macrofauna contributed least to total faunal
respiration (Table 3), except inside plough tracks during PD0.5 and at
both sites during PD3. During this PD3 sampling campaign,
macrofauna contributed 50 % outside plough tracks and 58 % inside
plough tracks to total faunal respiration. Polychaetes respired between
19 % of the total fauna respiration outside plough tracks during
PD26 and 78 % of total faunal respiration inside plough tracks
during PD0.5. Invertebrate megafaunal contribution to respiration was
highest during PD26, when they respired 65 % of the total faunal
respiration inside plough tracks and 79 % of the total faunal respiration
outside plough tracks. The contribution of fish to total faunal respiration
was always < 2 %. Besides respiration, feces production contributed
between 20 % inside plough tracks during PD3 and 35 % outside
plough tracks during PD0.1 to total carbon outflow from the food web
(Fig. 5). The contribution of the combined outflow of predation by external
predators and scavengers on carcasses to the total C loss from the food web
ranged from 50 % inside plough tracks during PD7 to 65 % inside
plough tracks during PD0.1.
The fraction of T.. values that were larger for the food webs outside
plough tracks than inside plough tracks during the same sampling event was
1.0 at PD0.1, PD0.5, PD3, PD7, and PD26. No
decreasing trend in ΔT.. over time was visible (Fig. 6); in fact, the
largest ΔT.. values were calculated for PD3 (7.9 × 10-2 ± 2.0 × 10-3 mmol C m-2 d-1)
and PD26
(7.7 × 10-2 ± 9.41 × 10-4 mmol C m-2 d-1).
Development of ΔT.. (mmol C m-2 d-1), i.e., the
difference in “total system throughput” T.. outside plough tracks
compared to inside plough tracks, over time. PD0.1 corresponds to
0.1-year post-disturbance, PD0.5 is 0.5-year post-disturbance, PD3
is 3-year post-disturbance, PD7 is 7-year post-disturbance, and PD26
is 26-year post-disturbance event.
Discussion
This study assessed the change over time of food-web structure and the
ecosystem function “faunal C cycling” in an abyssal, nodule-rich,
soft-sediment ecosystem after an experimental sediment disturbance. From the
26-year time series, we show that total faunal carbon stock inside plough
tracks was still only about half of total faunal carbon stock outside plough
tracks. Furthermore, the role of the various feeding types in the carbon
cycling differed by feeding type. In all, the “total system throughput”
T.., i.e., the sum of all carbon flows in the food web, was still
significantly lower inside plough tracks as compared to outside plough tracks
26 years after the experimental mining disturbance.
Model limitations
Our results are unique, as they allowed us, for the first time, to assess
recovery of C cycling in benthic deep-sea food webs from a small-scale
sediment disturbance in polymetallic nodule-rich areas. However, the models
proposed here come with limitations. Pre-disturbance samples and samples from
reference sites were not collected for all food-web compartments. A notable
omission is the lack of data for microbes and meiofauna throughout the times
series, hence our C cycling models only resolve C cycling by macro- and
megafaunal compartments. Another omission is the lack of a baseline to which
the “outside plough track” food web at PD0.1 could be compared to
assess the impact that the disturbance effect had on sites outside the plough
tracks. Hence, we cannot determine whether the high biomass and carbon flows
at PD3 were due to the onset of the positive (La Niña) phase of the
El Niño Southern Oscillation (Trenberth, 1997), a phenomenon which is
known to lead to a comparatively high POC export flux in the Pacific Ocean
(e.g., Station M; Ruhl et al., 2008).
Standard procedures to assess invertebrate megafaunal and fish densities have
evolved during the 26 years of post-disturbance monitoring. The OFOS system
used 26 years after the initial DISCOL experiment took pictures automatically
every 20 s from a distance of 1.5 m above the seafloor (Boetius, 2015;
Stratmann et al., 2018b). By contrast, the OFOS system used in former cruises
was towed approximately 3 m above the seafloor, and pictures were taken
selectively by the operating scientists (Bluhm and Gebruk, 1999). Therefore,
the procedure used in the former cruises very likely overestimated rare and
charismatic invertebrate megafauna, and probably underestimated dominant
fauna and organisms of small size (< 3 cm) for PD0.1 to PD7, as
compared to PD26.
Previous cruises to the DEA focused on monitoring changes in faunal density
and diversity, but not on changes in carbon stock. Hence, a major task in
this study was to find appropriate conversion factors to convert density into
carbon stocks. However, no individual biomass data for macrofaunal taxa were
available for the Peru Basin, so we used data from sampling stations of
similar water depths in the eastern CCZ (NE Pacific;
Sweetman et al., 2018). As organisms in deep-sea regions with higher organic
carbon input are larger than their counterparts from areas with lower organic
carbon input (McClain et al., 2012), using individual biomass data from the
CCZ, a more oligotrophic region than the Peru Basin (Haeckel et al., 2001;
Vanreusel et al., 2016), might have underestimated carbon stocks for
macrofauna. However, this potential bias has likely limited the impact on the
interpretation of the comparative results within the time series, because the
same methodology was applied throughout. Moreover, the determination of
invertebrate megafaunal carbon stocks was also difficult, as no size
measurements were taken from invertebrate megafaunal individuals during the
PD0.1 to PD7 cruises. Consequently, it was not possible to detect
differences in size classes between inside and outside plough tracks or
recruitment events in, e.g., echinoderms (Ruhl, 2007) following the DISCOL
experiment. Instead, we used fixed conversion factors for the different taxa
for the entire time series.
Feeding-type specific differences in recovery
Eight years before the experimental disturbance experiment was conducted at
the DISCOL area, Jumars (1981) qualitatively predicted the response of
different feeding types in the benthic community to polymetallic nodule
removal. Although several seabed test mining or mining simulations were
performed since then (Jones et al., 2017), no study compared or verified
these conceptual predictions on feeding-type specific
differences in recovery from deep-sea mining. As few comparative studies
are available, we compare here our food-web model results with those of the
conceptual model predictions for scavengers, surface and subsurface deposit
feeders, and suspension feeders by Jumars (1981).
Jumars (1981) predicted that organisms inside the mining tracks would be
killed either by the fluid shear of the dredge/plough or by abrasion and
increased temperatures inside the rising pipe with a mortality rate of
> 95 %. In contrast, the impact on mobile and sessile organisms in the
vicinity of the tracks would depend on their feeding type (Jumars, 1981).
The author also predicted that the density of mobile scavengers, such as fish
and lysianassid amphipods, would rise shortly after the disturbance in
response to the increased abundance of dying or dead organisms within the
mining tracks. In fact, experiments with baits at PAP and the Porcupine
Seabight (NE Atlantic) showed that the scavenging deep-sea fish
Coryphaenoides armatus intercept bait within 30 min (Collins et
al., 1999) and stayed at the food fall for 114 ± 55 min (Collins et
al., 1998). Therefore, the absence of fish inside plough tracks during
PD0.1 and PD0.5 could be related to a lack of prey in a potential
predator–prey relationship (Bailey et al., 2006). However, because of the
relatively small area of plough tracks (only 22 % of the 10.8 km2
of sediment were ploughed; Thiel et al., 1989), the low density of deep-sea
fish (e.g., between 7.5 and 32 ind. ha-1 of the dominant fish genus
Coryphaenoides sp. at Station M; Bailey et al.,
2006) and the high motility of
fish, this observation is likely coincidental.
Jumars (1981) predicted that, on a short term, subsurface deposit feeders
outside the mining tracks would be the least impacted feeding type, because
of their relative isolation from the re-settled sediment, and their relative
independence of organic matter on the sediment surface, whereas subsurface
deposit feeders inside the mining tracks would experience high mortality. For
the long-term recovery, the author pointed to the dependence of subsurface
deposit feeders on bacterial production in the sediment covered with
re-settled sediment. Moreover, this newly settling sediment would alter both
sediment composition and food concentration in the sediment. As the total
rate of sediment deposition would increase both inside and beyond mining
tracks, Jumars (1981) anticipated that surface deposit feeders would endure
stronger impacts from deep-sea mining activities compared with subsurface
deposit feeders.
In our food-web model, subsurface and surface deposit feeders were grouped
into the deposit feeder category, except for polychaetes, for which we kept
the surface–subsurface distinction. The carbon stock of PolSSDF fluctuated by
1 order of magnitude over the 26 year time series and had high carbon stock
values outside plough tracks during PD0.1, inside plough tracks during
PD3, and inside and outside plough tracks during PD7. Hence,
predictions by Jumars (1981) for subsurface deposit feeders are difficult to
test, but Hedges' d for PolSSDF was |1.47| at PD0.1 and decreased
steadily to |0.66| at PD7 (Supplement 3), indicating a very strong
experimental effect after the disturbance event and a logarithmic recovery
over time. In comparison, the recovery of surface deposit feeders might be
delayed, owing to potential unfavorable food conditions as Stratmann et
al. (2018b) hypothesized in a study about holothurian densities at the DISCOL
experimental area.
Jumars (1981) expected that the suspension feeders outside the mining tracks
would be negatively affected during the presence of the sediment plumes
and/or as long as their filtration apparatus was clogged by sediment. This
“clogging” hypothesis could not be tested here, because the models did not
resolve these unknown changes in faunal physiology, so we could only assess
carbon cycling differences associated with differences in carbon stocks.
Furthermore, Jumars (1981) anticipated that the recovery of nodule-associated
organisms, such as filter and suspension feeding Porifera, Antipatharia or
Ascidiacea (Vanreusel et al., 2016) would require more than 10 000 years,
owing to the slow growth rate of polymetallic nodules (Guichard et al., 1978;
Kuhn et al., 2017) and the removal and/or burial of the nodules. This
hypothesis could not be tested directly, because nodules were not removed in
this experiment, but only ploughed into the sediment. However, the
disappearance of nodules from the sediment surface will likely have the same
effect on sessile epifauna that depend on nodules as hard substrate
independently of the method by which the nodules disappeared. Immediately
after the initial DISCOL disturbance event, the respiration rate of filter
and suspension feeders inside plough tracks was only 1 % of the
respiration rate of this feeding type outside plough tracks. After 26 years,
the total respiration rate of filter and suspension feeders inside plough
tracks was still 80 % lower than in outside plough tracks. Part of
this difference at PD26 resulted from the presence of a single specimen
of Alcyonacea with a biomass of 4.71 mmol C m-2 outside plough
tracks. Even if we ignore this Alcyonacea specimen in the model, the
respiration of suspension and filter feeding inside plough tracks would still
be 71 % lower compared to outside plough tracks, indicating a slow
recovery of this feeding group.