Description: During Sonne cruise SO242-2 six enclosure corrals (30*30 cm) were deployed in undisturbed sediment at the southern reference site of the DISCOL experimental area using ROV Kiel 6000 (GEOMAR). Artificial sediment was incubated at 2°C in filtered seawater (sediment effect) or in filtered seawater spiked with copper (copper effect; 1, 5, 10, or 20 mg Cu L-1) for 72 h prior to deployment and subsequently added on top of the deep-sea sediment inside the corrals. After approx. 94h of in-situ incubation, push cores (7.4 cm inner diameter) were taken inside the corrals and sliced in different depth layers (artificial sediment layer, 0-1 cm, 1-2 cm and 2-5 cm). Samples were fixed in formaldehyde and meiofauna was analysed in the lab of the Marine Biology group at Ghent university.

Description: During Sonne cruise SO242-2 six steel rings were inserted into undisturbed sediment at the southern reference site of the DISCOL experimental area using ROV Kiel 6000 (GEOMAR). Subsequently, on three of these steel rings a sediment dispenser was deployed to distribute 250 mL of crushed nodule substrate onto the ring surface area resulting in an added layer of approximately 2 cm. The sediment dispensers were left on the steel rings for one night to allow settlement of all particles. After the incubation time of eleven days each steel ring was subsampled with push cores (7.4 cm inner diameter) and those were sliced in different depth layers (added substrate layer, 0-1 cm,1-2 cm and 2-5 cm sediment depth). Samples were fixed in formaldehyde and meiofauna was analysed in the lab of the Marine Biology group at Ghent university.

Description: Between September and October 2017, MUC cores were deployed at various locations across the Northeast Greenland (NEG) shelf with R/V Polarstern during PS109. Samples for meiofauna were collected with a cut-off 10 ml syringe (area 1.89 m²) that was inserted to 5 cm depth sediment depth in the MUC core, and subsequently sliced in 5 horizons of 1 cm. Afterwards, meiofauna were extracted from the samples by triple density centrifugation with the colloidal silica polymer LUDOX TM 40 (Heip et al., 1985) and rinsed with freshwater on stacked 1 mm and 32 µm mesh sieves. The fraction retained on the 32 µm mesh sieve was preserved in 4 % Li2CO3-buffered formalin and stained with Rose Bengal. Nematodes of each sample were handpicked with a fine needle, transferred to glycerine (De Grisse I, II and III) (Seinhorst, 1959) , mounted on glass slides, identified to genus level and allocated to functional feeding groups based on Wieser, 1953 (as selective deposit feeders - 1A, non-selective deposit feeders - 1B, epistratum feeders - 2A and predators/scavengers - 2B).

Description: Between September and October 2017, MUC cores were deployed at various locations across the Northeast Greenland (NEG) shelf with R/V Polarstern during PS109. Samples for meiofauna were collected with a cut-off 10 ml syringe (area 1.89 m²) that was inserted to 5 cm depth sediment depth in the MUC core, and subsequently sliced in 5 horizons of 1 cm. Afterwards, meiofauna were extracted from the samples by triple density centrifugation with the colloidal silica polymer LUDOX TM 40 (Heip et al., 1985) and rinsed with freshwater on stacked 1 mm and 32 µm mesh sieves. The fraction retained on the 32 µm mesh sieve was preserved in 4 % Li2CO3-buffered formalin and stained with Rose Bengal. All metazoan meiobenthic organisms were classified at higher taxonomic levels and counted under a stereoscopic microscope (Leica MZ 8, 16x5x).

Description: Between September and October 2017, MUC cores were deployed at various locations across the Northeast Greenland (NEG) shelf with R/V Polarstern during PS109. Samples for meiofauna were collected with a cut-off 10 ml syringe (area 1.89 m²) that was inserted to 5 cm depth sediment depth in the MUC core, and subsequently sliced in 5 horizons of 1 cm. Afterwards, meiofauna were extracted from the samples by triple density centrifugation with the colloidal silica polymer LUDOX TM 40 (Heip et al., 1985) and rinsed with freshwater on stacked 1 mm and 32 µm mesh sieves. The fraction retained on the 32 µm mesh sieve was preserved in 4 % Li2CO3-buffered formalin and stained with Rose Bengal. All metazoan meiobenthic organisms were classified at higher taxonomic levels and counted under a stereoscopic microscope (Leica MZ 8, 16x5x). All Nematodes of each sample were handpicked with a fine needle, transferred to glycerine (De Grisse I, II and III) (Seinhorst, 1959) , mounted on glass slides, identified to genus level and allocated to functional feeding groups based on Wieser, 1953 (as selective deposit feeders - 1A, non-selective deposit feeders - 1B, epistratum feeders - 2A and predators/scavengers - 2B).

Description: Future deep-sea mining for polymetallic nodules in abyssal plains will negatively impact the benthic ecosystem, but it is largely unclear whether this ecosystem will be able to recover from mining disturbance and if so, to what extent and at what timescale. During the "DISturbance and reCOLonization" (DISCOL) experiment, a total of 22% of the seafloor within a 10.8km2 circular area of the nodule-rich seafloor in the Peru Basin (SE Pacific) was ploughed in 1989 to bury nodules and mix the surface sediment. This area was revisited 0.1, 0.5, 3, 7, and 26 years after the disturbance to assess macrofauna, invertebrate megafauna and fish density and diversity. We used this unique abyssal faunal time series to develop carbon-based food web models for each point in the time series using the linear inverse modeling approach for sediments subjected to two disturbance levels: (1) outside the plough tracks; not directly disturbed by plough, but probably suffered from additional sedimentation; and (2) inside the plough tracks. Total faunal carbon stock was always higher outside plough tracks compared with inside plough tracks. After 26 years, the carbon stock inside the plough tracks was 54% of the carbon stock outside plough tracks. Deposit feeders were least affected by the disturbance, with modeled respiration, external predation, and excretion rates being reduced by only 2.6% inside plough tracks compared with outside plough tracks after 26 years. In contrast, the respiration rate of filter and suspension feeders was 79.5% lower in the plough tracks after 26 years. The "total system throughput" (T..), i.e., the total sum of modeled carbon flows in the food web, was higher throughout the time series outside plough tracks compared with the corresponding inside plough tracks area and was lowest inside plough tracks directly after the disturbance (8.63 × 10−3±1.58 × 10−5mmolCm−2d−1). Even 26 years after the DISCOL disturbance, the discrepancy of T.. between outside and inside plough tracks was still 56%. Hence, C cycling within the faunal compartments of an abyssal plain ecosystem remains reduced 26 years after physical disturbance, and a longer period is required for the system to recover from such a small-scale sediment disturbance experiment.

Description: With the mining of polymetallic nodules from the deep-sea seafloor once more evoking commercial interest, decisions must be taken on how to most efficiently regulate and monitor physical and community disturbance in these remote ecosystems. Image-based approaches allow non-destructive assessment of the abundance of larger fauna to be derived from survey data, with repeat surveys of areas possible to allow time series data collection. At the time of writing, key underwater imaging platforms commonly used to map seafloor fauna abundances are autonomous underwater vehicles (AUVs), remotely operated vehicles (ROVs) and towed camera “ocean floor observation systems” (OFOSs). These systems are highly customisable, with cameras, illumination sources and deployment protocols changing rapidly, even during a survey cruise. In this study, eight image datasets were collected from a discrete area of polymetallic-nodule-rich seafloor by an AUV and several OFOSs deployed at various altitudes above the seafloor. A fauna identification catalogue was used by five annotators to estimate the abundances of 20 fauna categories from the different datasets. Results show that, for many categories of megafauna, differences in image resolution greatly influenced the estimations of fauna abundance determined by the annotators. This is an important finding for the development of future monitoring legislation for these areas. When and if commercial exploitation of these marine resources commences, robust and verifiable standards which incorporate developing technological advances in camera-based monitoring surveys should be key to developing appropriate management regulations for these regions.