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This is the first comparative study of commercial scallop species in the Pacific coast of the MP combining morphological and molecular characters. Our phylogenetic analyses highlight the association between A. natans and Ad. colbecki; two members of monospecific tribes and last extant representatives of their Southern Ocean-restricted genera.These results confirm the presence of both Magallanes scallops in the MP, as well as the so-far unsuspected presence of mixed “banks” where both species occur in sympatry. The BND/VH ratio helps discriminate between two distinct entities that belong to the genetic lineage of Z. patagonica and to a different lineage, highly divergent from the former, which corresponds to A. natans. A. natans is the only species of a whole lineage with a particular phylogenetic value, therefore having developed and tested an accurate identification criterion for both scallops will allow efficient fishery management in the future.Here we discuss the phylogenetic position and the taxonomic status of both Magallanes scallops, as well as the implications of these results for the future management and conservation of Z. patagonica and A. natans in the Magallanes Region. Despite the numerous classifications built on morphological, ecological or molecular data, the relationships among pectinids are still under constant modification depending on the number of taxa, loci, length of the sequence and the selected outgroups1,4. The work of Alejandrino et al.7 is the most inclusive so far in terms of taxon sampling, with 81 species. Although Scherrat et al.25 included 143 species, the node supports of the phylogenetic trees are not provided, making it difficult to assess the robustness of this large phylogeny. In order to define the phylogenetic position of Zygochlamys patagonica and Austrochlamys natans, we included 93 pectinid taxa (43 genera) representative of tribes Chlamydini, Crassadomini, Fortipectini, Palliolini, Aequipectinini, Pectinini and Amussini. Comparing to Waller’s5 and Dijkstra’s15 classifications, only the subfamily Camptonectinae and the tribe Mesoplepini are missing. We used three ribosomal regions (one nuclear and two mitochondrial). Compared to Alejandrino et al.7, histone H3 is missing here, however this locus is among the least informative4. The family Pectinidae appears to be monophyletic with high support values (Fig. 5, S2), as previously demonstrated4,7,26,27,28. According to Dijkstra15 there are currently five subfamilies of Pectinidae, two of which are absent from our analysis: Camptonectinae and Pedinae. This topology supports the classifications of Waller5 and Dijkstra15, except for the position of the tribe Austrochlamydini.Our Magallanes scallops separated into two very divergent clades: Z. patagonica is associated with its conspecifics and congenerics in a single lineage (Fig. 5), which also contains species of Veprichlamys and Talochlamys. This lineage already appeared well supported as the sister clade to Palliolinae and Pectininae in Alejandrino7. For the first time, Talochlamys dichroa and T. gemmulata are nested with high support values into the Zygochlamys clade, making this latter genus paraphyletic (Fig. 5). These taxa are all restricted to high latitudes of the Southern Ocean. Due to phylogenetic and geographic affinities, we suggest that these three genera may constitute a tribe separate from Chlamydini. Since Dijkstra15 moved the two Atlantic ‘Crassadoma’ into the genus Talochlamys, the affinities among Talochlamys spp. had not been explored until now. Talochlamys species rather associate according to geographic affinities, splitting the genus into two highly divergent entities corresponding to European and New Zealand Talochlamys. A systematic revision of these four species would be useful.Austrochlamys natans associated with the Palliolinae, which was elevated to a subfamily rank by Waller5. Of the three extant tribes that compose this group, Mesopleplini are missing from our phylogenetic analyses. We included 4 genera (8 species) of the remaining two tribes: Adamussium (Adamussini) and Palliolum, Pseudamussium, Placopecten (Palliolini). The present sampling of Palliolini is the most inclusive to date and led to the monophyly and full support of the tribe Palliolini. Our phylogenetic results do not support any of the previous classifications of the tribe Austrochlamydini1,5,9,13,15, and introduce this monospecific tribe as a new member of the subfamily Palliolinae. Indeed, Austrochlamys natans clusters together with Adamussium colbecki, both in a sister clade to Palliolini. The first molecular characterization of Ad. colbecki did not lead to a clear classification due to the low polymorphism of the 18S26. Later, Ad. colbecki appears either as sister species to Chlamydinae or to Palliolini, depending on tribe sampling and the choice of outgroup and loci4,10,11. However, in the most recent and inclusive studies of taxon sampling7 (present study) or genomic cover29, Ad. colbecki is the sister group of the tribe Palliolini, as in the present phylogeny.The subfamily Palliolinae originated from a Chlamydinine ancestor in the Cretaceous and subsequently underwent diversification in the Northern Hemisphere1 and in the Southern Hemisphere, where the extinct genus Lentipecten spread in the Paleocene–Eocene Thermal Maximum30. The genus Adamussium derived from Lentipecten and appeared in the early Oligocene; it comprises 5 endemic Antarctic species; Ad. colbecki is the only one extant13,31,32. The genus Austrochlamys also appeared in the Oligocene and was first restricted to King George Island (South Shetlands), then spread around the north of the Antarctic Peninsula and achieved a circum-Antarctic distribution until the Pliocene13,33,34. Austrochlamys persisted during the progressive cooling of the Antarctic Continent from the Paleocene to the Pliocene, dominating the coastal areas, while Adamussium occupied the deep seas and continental platform33. The opening and deepening of the Drake Passage and the intensification of the Antarctic Circumpolar Current during the Pliocene provoked a drastic cooling and the extension of sea ice over the coastal habitat, which caused the northward movement of Austrochlamys and its subsequent disappearance from Antarctica, along with the circumpolar expansion of Ad. colbecki in Antarctic shallow waters33. The colonization of the coastal habitat has been related to the sea ice extent that provided a more stable environment and low-energy fine-grained sediment with which Adamussium was associated in the deep waters. Austrochlamys fossils appear in the Subantarctic Heard Island in late Pliocene layers (3.62–2.5 Ma35). Today Ad. colbecki is a circum-Antarctic and eurybathic species that reaches high local density in protected locations13,36, while all Austrochlamys became extinct except for A. natans, which is restricted to southern South America33. The phylogenetic affinity highlighted here between A. natans and Ad. colbecki has its origins in the Southern Ocean; the deep divergence between the lineages of these monospecific tribes attests to the long time since their common origin in the Paleogene. These results point out both species as relevant biogeographic models to address longstanding questions regarding the origin of marine biota from Southern Ocean.The nomenclature, taxonomy and ecology of both A. natans and Z. patagonica have been problematic for almost 200 years. Since its original description37, Z. patagonica, a.k.a. the “Ostión Patagónico” has been named with more than 10 synonyms, probably due to the great intra-specific morphological variability throughout its distribution19,38 (see the nomenclatural history in Supplementary Table S1). In contrast, there are very few records in the scientific literature and no genetic data on A. natans, a.k.a. the “Ostión del Sur”13,14,17,19, and some problems of nomenclature and establishing diagnostic characters persist since its description13,39. Many of the current junior synonyms of both species were described from small and juvenile specimens (under 52 mm VH39,40,41). Indeed, all deposited type material of A. natans ranges from 23.5 to 52 mm VH; the latter is half of the maximum size39. The criteria most commonly used for the identification of both scallops were number of radial primary ribs, maximum size, shell colour and presence of laminated concentric lines (Supplementary Table S1). Specimens with marked primary and secondary radial ribs alternated regularly and more whitish colouring of the right shell were attributed to Z. patagonica, while those with weaker and less markedly coloured radial ribs and the maximum size were considered as A. natans42. However, the number of radial ribs overlaps between Z. patagonica (26–4212,43) and A. natans (22–5017,19). These characters also have high variability across different environments and during ontogeny13,17. Thus the use of a taxonomy based on environment-sensitive and allometric characters has led to confusion in the morphological identification of these species13,38. The criterion used in the present study, the BND/VH ratio established by Jonkers13, discriminates the species efficiently. As attested by the narrow dispersal cluster in Fig. 3, this character has low intra-population variability13. In some cases a level of intraspecific variation can be detected, and this is mainly due to the environments where the scallop populations inhabit19 (e.g. exposed, protected, substrate type, fjord, oceanic). However, although there may be some intraspecific variability between populations, this variability does not generate problems for the identification of the two species. Individuals of A. natans generally presented a significantly greater BND/VH ratio than those of Z. patagonica. However, it is important to consider that, given that this character varies during ontogeny, it is more accurate in individuals over 25 mm VH13. Only the molecular identification was able to discriminate juvenile scallops of both species accurately.According to the literature, A. natans is restricted to interior waters of channels and is associated with kelp forests of M. pyrifera (Supplementary Table S1). Z. patagonica inhabits a wider range of environments such as bottoms of shells, sand, mud and gravel in protected and exposed areas, between 2 and 300 m depth (Supplementary Table S1), but is also associated with kelp forests in fjords with different degrees of glacial retreat12,16,44. The juveniles of both scallops recruit in kelp forests44,45. According to the local artisanal fishermen, adults of “Ostión del Sur” (A. natans) occur in fjords with glaciers (orange circles in Fig. 123). We included two sampling locations near glaciers (in Pia and Montañas fjords), where large individuals (between 46 and 86 mm) of A. natans and Z. patagonica occur in sympatry. This sympatry was previously reported in Silva Palma Fjord between 5 and 25 m depth16. In conclusion, scallop banks are not monospecific but rather mixed and Z. patagonica occurs in the interior waters of the channels and fjords. Consequently, these two species have overlapping ecology (recruiting zone and glacial affinity) in the channels and fjords, overturning a long-held view that these scallops have marked habitat segregation.The fishery for both species was established in the 1990s in the political-administrative Region of Magallanes16, despite the complexity of the morphological recognition of scallops. The distinction between species was based on shell colour and radial ribs42, two characters that, given the results of this study, do not have this diagnostic capacity. Consequently, the scallop fisheries in the Magallanes Region are currently based on inaccurately discriminative characters. Scallop banks in MP have always been considered as monospecific16,47. A great part of scallop landing has always been attributed to A. natans47, about which the scientific literature is scarce (Supplementary Table S1). Conversely, Z. patagonica, which was erroneously considered as the commercial species of southern Chile, has more scientific research (Supplementary Table S1).The difficulty to discriminate A. natans and Z. patagonica morphologically may lead to incorrect fishery statistics and uncertain conservation status of A. natans. Incorrect fishery statistics could overestimate the abundance of banks of A. natans compared to Z. patagonica. If the minimum catch size is reduced23 in the context of the fishing overuse of the last decade, A. natans may suffer a reduction of its maximum size48. Therefore, an identification criterion between species is a need to improve fishery management. We showcased a quantified criterion that is useful to identify both species. In the short-term, this method can be used, but it is difficult to enforce in practical ways. We suggest to train fishing inspectors, following three guidelines. First, the identification should consider only the right valve (RV) for species identification, since the left valve is not taxonomically informative. Second, for visual classification, check the outline of the BN, mainly because the individuals of Z. patagonica have a more arcute BN. Third, a reliable identification has to measure the depth of the byssal notch (BND) and shell height (VH) ratio. Lastly, future research and fishery monitoring should follow these criteria to carry out a correct identification and subsequently better landings statistics.Molecular tools allowed evaluating the phylogenetic relationships of scallops globally or regionally and incorporating parameters that can be used for the management and conservation of species of commercial interest49. For example, in the last few decades metrics have been developed to address conservation problems that give us a measure of the current state of particular taxa. These conservation priorities are often seen as measures for threatened species categorized by the IUCN Red List (World Conservation Union, 1980), one of the most widely and recognized systems. Although this prioritization metric incorporates phylogenetic distinctiveness (PD), this factor has been updated due to the importance of quantifying the loss of evolutionary diversity that would be implied by the extinction of a species50. The magnitude of the PD loss from any species will depend (but not exclusively) on the fate of its close relatives51. The “Ostión del Sur”, Austrochlamys natans is the last representative of its tribe (Austrochlamydini) in the Southern Ocean. Its phylogenetic position and the long branch length (i.e. the length of the branch from the tip to where it joins the tree), which represents an important amount of evolutionary change, highlights the degree of isolation of A. natans and calls attention to the possible loss of a unique genetic lineage. There is currently no conservation value for this relict species; we sought to alert the current fishery management that the “Ostión del Sur” is a distinct taxon and provide integrative evidence for further conservation studies.Finally, regarding the overlapping niche of these scallops and the conservation importance of the clade of A. natans, we propose three key recommendations for the future scallop fishery policies in the sub-Antarctic channels. First, it is necessary to assess the proportion of both species per bank and landing to generate a distribution map through the sub-Antarctic channels. For this assessment, the byssal notch depth is the most appropriate morphological character. Second, we recommend reassessments of biological and ecological parameters (e.g. size at first maturity) for A. natans across the glacial fjords, which are the most relevant fishing sites. As a final point, today there is a complete lack of knowledge of the genetic connectivity along the Subantarctic Channels. Thus we should generate more research about spatial population genetics at different temporal scales. The integration of genomic approaches (e.g. SNPs) with macro- and micro-environmental modelling approaches provide enormous opportunity to establish a new regional zoning for fishery management and conservation scallop strategy. More

Most problematic fishing methods based on ALDFG relative risksThis study presents the first quantitative assessment of gear-specific relative risks from ALDFG. Findings accounted for the: (a) derelict gear leakage rate; (b) fishing gear quantity indicators of catch and area of fishing grounds; and (c) adverse consequences from ALDFG. Maximum global conservation gains can be achieved through focusing ALDFG mitigation efforts on the fishing gears with the highest overall relative risk. Set and fixed gillnets and trammel nets, drift gillnets, gears using drifting and anchored FADs (tuna purse seines and pole-and-lines), and bottom trawls were the five most problematic gears on a global scale. This was followed by traps (fyke nets, pots, barriers, fences, weirs, corrals and pound nets).The overall RR score indicates a fishing gear’s relative degree of total adverse effects from ALDFG, accounting for the quantity of ALDFG produced by that gear (estimated from the ALDFG leakage rate and indices of fishing gear quantity of catch and area of fishing grounds), and the adverse consequences that result from ALDFG from that gear type relative to other gears. Globally, gillnets have the highest risks from ALDFG, while hand dredges and harpoons were least problematic.The focus of local management interventions to address problematic derelict fishing gear will be dictated by the specific context. Locally, adopting ALDFG controls following a sequential mitigation hierarchy and implementing effective monitoring, surveillance and enforcement systems are needed to curb derelict gear from these most problematic fisheries. This includes accounting for which fishing gears are predominant and the existing fisheries management framework. For example, a site may have pot and tuna purse seine anchored FAD fisheries. The purse seine fishery has a higher relative risk globally. However, a fisheries management system may have effective ALDFG preventive methods in place for this fishery, such as a high rate of detection and recovery of anchored FADs when they break from moorings, and minimization methods, such as prescribing the use of only non-entangling and biodegradable FAD designs to minimize adverse effects from derelict FADs35, 36. But there may be minimal measures in place to monitor and manage ALDFG from pots. In this hypothetical example, it would be a higher priority locally to improve ALDFG management for the pot fishery.Priority data quality improvementsThere are several priorities for data quality improvement to increase the certainty of future assessments. Given substantial deficits both in estimates of gear-specific quantity/effort and ALDFG rates, it is not yet possible to produce a robust contemporary estimate to replace the ca. five decades-old crude estimate of the magnitude of the annual quantity of leaked ALDFG4, 30. More robust estimates of ALDFG rates are needed for all gear types. Gear-specific estimates have low certainty due to small numbers of studies and sample sizes. Many compiled records estimate only one ALDFG component, typically only loss rates, and therefore may substantially underestimate total ALDFG rates. Most records are dated and may not accurately characterize contemporary rates. There is geographical sampling bias with estimates being primarily derived from the northern hemisphere. Furthermore, many estimates were derived from expert surveys (Supplementary Material Table S1), which have a higher risk of error and bias than approaches higher on the evidence hierarchy37. Substantially more primary studies with robust designs are needed.An expanded meta-analysis on gear-specific ALDFG rates is an additional priority, once sufficient sample sizes of robust studies accumulate. The statistical modeling approach used by Richardson et al.34 could be readily improved by using (1) a random-effects instead of a fixed effects structure to account for study-specific heterogeneity, and (2) a more appropriate model likelihood, such as zero-inflated Beta likelihood, to account for the zero values in the dataset38. Due to larger sample sizes and the number of independent studies, meta-analyses can produce estimates with increased accuracy, with increased statistical power to detect real effects. By synthesizing estimates from an assortment of independent, small and context-specific studies, pooled estimates from random-effects meta-analyses are generalizable and therefore relevant over diverse settings39. The strength of conclusions of hypotheses based on a single study can vary. This is because a single study can be context-specific, where true results may be affected by conditions specific to that single study, such as the species involved and environmental conditions, that cause the results from the single study to not be applicable under different conditions. A single study may also fail to find a meaningful result due to small sample sizes and low power. However, robust synthesis research, including meta-analysis, is more precise and powerful once a sufficient number of similar studies have accumulated, and therefore investing in more primary ALDFG studies is a high priority.For some gear types and fisheries, estimated ALDFG rates may overestimate adverse effects when gear that is abandoned, lost or even discarded does not become derelict because another fishing vessel continues to use the gear. For example, gear that is lost by theft remains in use. Macfadyen et al.4 explained that theft was likely a minor contribution to ALDFG, occurring, for instance, in inshore fishing grounds where static commercial fishing gear and recreational marine activities conflict. However, fishing gear theft may be prevalent in some developing country fisheries (e.g., Cambodian crab traps40). And, there is one gear type where theft has become a globally prevalent, routine and largely accepted practice: Tuna purse seine vessels routinely exchange satellite buoys attached to drifting FADs that they encounter at sea. The stolen FAD, lost by the previous vessel that had been tracking its position, remains in-use and not derelict, although it may eventually become derelict41, 42. Furthermore, because ALDFG leakage rates may be highest in illegal and unregulated fisheries4, if only legal fisheries are sampled, then this may produce underestimates. Thus, accounting for theft and illegal and unregulated fishing would increase the certainty of estimates of ALDFG leakage rates for some fishing gear types.The 20% ALDFG global production rate value used for anchored FADs by pole-and-line fisheries was likely an underestimate. We relied on a single value from the contemporary Maldives pole-and-line fishery’s government-owned and -managed network of anchored FADs. This fishery underwent a substantial reduction in anchored FAD loss rate, from 82 to 20%, by improving designs and a government incentive program that pays fishers to retrieve FADs when they break from their moorings35, 43. For comparison, describing Indonesia’s pole-and-line fishery’s anchored FADs, Widodo et al.44 stated: “Inaccuracy of number and position of FADs in the fishing ground are the outstanding issue facing by fisheries manager…This was largely the result of the current lack of effective systems of FAD registration and monitoring, and also because of the desire of fishing companies and vessel skippers to keep FADs position information confidential. [sic]”.Proctor et al.45, who estimated that between 5000 and 10,000 anchored FADs are used in Indonesian tuna fisheries, also reported a lack of accurate estimates of the numbers and locations of anchored FADs due to ineffective implementation of the government registration system and to high loss rates, including from storms, strong currents, vandalism, vessel collisions and wear and degradation of the FADs. Using the estimated rates of (1) Shainee and Leira43 that 82% of anchored FADs were lost per year prior to the Maldivian government’s incentives program, which might accurately characterize the Indonesian and other anchored FAD networks used by pole-and-line fisheries, and (2) the 20% loss rate value from Adam et al.35, the posterior mean = 0.506 (95% HDI: 0.15–0.84). Thus, 51% might have been a more appropriate estimate for a global ALDFG production rate for pole-and-line anchored FADs. The Maldivian and Indonesian pole-and-line fisheries, which combined supply over half of global pole-and-line catch, rely heavily on anchored FADs, as do several other smaller pole-and-line fisheries (e.g., Solomon Islands, segments of the Japanese pole-and-line fleet)35, 45,46,47,48.Units for ALDFG rates are highly variable. Records using different rates cannot be pooled for synthesis research29, 34. For example, some records reported rates of the percent of number of panels (sheets) or fleets (strings) of gillnets that were lost, while others reported the percent of the length or area of gillnets that were lost29. Similarly, for longline gear, some studies reported the percent of the length of the mainline, while others reported the percent of the number of branchlines/snoods that were lost34. Employment of agreed harmonized units for ALDFG rates are needed.Future assessments could use a ratio of ALDFG risk-to-seafood production to assess gear-specific relative risks locally and globally, similar to assessments of vulnerable fisheries bycatch by using bycatch-to-target catch ratios49. This would enable the assessment of risk from ALDFG to be balanced against meeting objectives of food security and nutritional health.Relationship between alternative indices with the quantity of fishing gearWe used gear-specific annual catch and area of fishing grounds as indicators of the relative global amount of each gear that is used annually as two terms in the model to assess gear-specific relative risks from ALDFG. However, the assumption of a linear relationship between these indices and gear quantity is questionable for similar reasons that have been raised with the relationship between various indices of effort (number of fishing hours, number of vessels, engine power, vessel length, gross tonnage, gear size, hold capacity, as well as kWh) and catch. For example, the ratio of catch from one set by an anchoveta purse seiner to the volume or weight of the gear is likely substantially different than for pots or driftnets. Not only is the relationship between catch and amount of gear variable by gear type and target species, there is also high variability within gear types—by fishery and within fisheries—due to the broad range of factors that significantly explain fishing efficiency per unit of nominal effort50, 51. Similarly, the relationship between catch weight and number of fishing operations varies substantially across gear types. For example, an industrial tropical tuna purse seine vessel might have a total catch of about 37 t per set on a drifting FAD27 while a tuna pole-and-line vessel catches about 1 t per fishing day52.Similarly, the relationship between the area of fishing grounds and amount of gear may vary substantially between gear types. A small number of vessels using a relatively small magnitude of active, mobile gear may have a much larger area of fishing grounds than a large number of vessels and shore-based fishers using a large amount of passive and static gears. For example, about 686 large-scale tuna purse seine vessels fish across the tropics53, while gillnets, which may be the most globally prevalent gear type, are used predominantly within 20 nm (37 km) of shore, most intensively in southeast Asia and the northwest Pacific54.Fishing effort has also been estimated using engine power as well as by using energy expended, such as in kilowatt-hours (kWh), the product of the fishing time and engine power of a fishing vessel, including non-motorized vessels55,56,57. We did not use these metrics for effort because the correlation between rate of production of ALDFG and vessel engine power or kWh, including of non-motorized vessels (1.70 million of the estimated global 4.56 million fishing vessels21), has not been explored. In general, vessel power and power per unit of fishing period largely distinguishes between mobile and passive gears, where the former (e.g., trawls, dredges), use substantially more vessel power per weight of catch than passive gears (traps, gillnets). Also, estimates using these fishing effort metrics used a small number of aggregated gear categories and extrapolated estimates primarily from sampled developed world fisheries (however, see56). These effort indices would also prevent inclusion of shore-based fishing methods.There have been recent gear specific estimates of effort, in units of time spent fishing and the estimated energy expended (fishing power * fishing time), using Automated Identification Systems (AIS) data, which are available for industrial fishing vessels, primarily using longlines, trawls and pelagic purse seines6, 58. AIS data provide coverage of the majority of large fishing vessels ≥ 24 m in overall length58. However, this accounts for only about 2% of the number of global fishing vessels (of an estimated 4.56 million global fishing vessels, about 67,800 are ≥ 24 m in length21).ALDFG monitoring, management and performance assessmentsA sequential mitigation hierarchy of avoidance, minimization, remediation and offsets can be applied to manage ALDFG29, 59. Referring to the three components of relative risk assessed by this study, avoidance and minimization of risks from ALDFG is achieved by reducing the ALDFG leakage rate, fishing effort, and/or adverse consequences from derelict gear. Remedial methods reduce adverse effects, such as reducing ghost fishing by reducing the duration that ALDFG remains in the marine environment1, 29, 60. In general, preventative methods are more cost effective than remedial methods—it is less expensive to prevent gear abandonment, loss and discarding than it is, for example, to detect and then disable or remove derelict gear61. Methods to prevent ALDFG include, for instance, spatially and temporally separating passive and mobile fishing gears, having bottom trawlers avoid features that could snag the net such as by using high-resolution seabed maps, tracking the real-time position of unattended fishing gears using various electronic technologies, and using gear marking to identify the owner and increase the visibility of passive gears. Furthermore, because some remedial methods, such as using less durable materials for fishing gear components, can reduce economic viability and practicality, preventative methods and remediation through quick recovery of ALDFG may be more effective as well as elicit broader stakeholder support29, 62.To assess the performance of global ALDFG management interventions against this study’s quantitative benchmark, substantial deficits in monitoring and surveillance of fisheries’ waste management practices must first be addressed1. Of 68 fisheries that catch marine resources managed by regional fisheries management organizations, 47 lack any observer coverage, half do not collect monitoring data on ALDFG, and surveillance and enforcement systems are rudimentary or nonexistent in many fisheries1, 63.Findings from this quantitative, global assessment of ALDFG risks guide the allocation of resources to achieve the largest improvements from preventing and remediating derelict gear from the world’s 4.6 million fishing vessels. With improved data quality and governance frameworks for fishing vessel waste management, including ALDFG, we can expect reductions in ecological and socioeconomic risks from derelict gear. More

pH distributions within sediment microcosms showed distinct spatial and temporal patterns. For the January 2019 experiment series, the strong pH maximum bands developed in the oxic surface sediment after 20 ~ 22 days of incubation. Development was not spatially uniform. Sediment surface pH maxima started to develop from isolated points covering horizontal lengths of 0.6–1 cm at the times of imaging (Fig. 1). Within a week, the pH maximum bands expanded laterally, covering the entire 6 cm long monitoring panel, and were sustained until the end of the experiment (106 days, data not shown). The pH maximum bands were about 2 mm in vertical extent with average pH ~ 8.5. Even after the electrogenic colonization was laterally complete (day 27), the activity intensities of cable bacteria, or the impacts of their activity as reflected by the magnitudes of pH elevations and associated reactions, were still spatially heterogeneous (Fig. 1C). pH values in the underlying anoxic sediment decreased from 7.0 to 6.5 gradually as surface pH maxima formed. However, in the experiment with the sediment collected in August 2019, sediment surface pH maxima started appearing on day 39 and expanded much more slowly, with only a 2.4 cm-long lateral coverage after a week of growth in one of the duplicate microcosms and no development at all in the other (Fig. 2A,B). At the same time, where pH maxima were present, a pH minimum band developed in the anodic zone ( > 2 mm depth) just below sediment surface pH maxima and expanded over time (Fig. 2A).Figure 12D pH distribution dynamics of duplicate microcosms starting from day 20 (January 2019 sediment). (A,B) For duplicate microcosms, sediment surface pH maximum bands started from isolated hotspots and quickly spread across the whole surface area with spreading speed ~ 1.2 cm/day. Anoxic sediment pH decreased from day 20–26. (C) The horizontal pH variations within the surficial pH maximum band on day 27 (microcosm B; vertical width ~ 1 mm). The pH ± standard deviations within the band are indicated by the blue dots.Full size imageFigure 22D pH and H2S distribution dynamics within microcosms during colonization. (A) 2D pH distribution dynamics starting from day 39 (August 2019 sediment) and corresponding 1D pH profiles. The sediment surface pH maximum band started from isolated hotspots and spread across sediment surface with an average rate of 0.3 cm/day, which is much slower compared with January 2019 sediment (1.2 cm/day). The pH in the cable bacteria anodic zone is lower (blue line, A2) compared with un-colonized sediment side (black line, A1) in the pH profile panel insert. (B) The duplicate microcosm (August 2019 sediment) did not show sediment surface pH maxima during the same time window. (C) 2D pH distribution dynamics starting from day 46 (October 2020 sediment). Both surface pH maxima and deep minima expand during electrogenic colonization. The pH minima (white arrows) are evident first on day 46 and 64. (D) Sediment 2D H2S distribution on day 71 (October 2020 sediment) with upper boundary showing the sediment water interface. The H2S distributions are consistent with pH patterns, but the sediment H2S concentrations are generally lower compared with other experiment series (Fig. 4).Full size imageThe October 2020 results (Fig. 2C) further resolved the cathodic and anodic zone development patterns. During colonization, the anoxic zone pH minima were evident earlier (day 46 and 64) and were distinctly wider than the sediment surface pH maxima (day 46–71). These differences in cathode and anode detection sensitivity might be caused by more rapid diffusion at the sediment–water boundary (free solution) and rapid neutralization by seawater CO2. They may also be related to the mode of colonization as discussed below. In addition to pH heterogeneity, the electrogenic activity also resulted in complex topographies of H2S distributions (Fig. 2D). In the locations where pH hotspots were found, the depths of detectable H2S are deeper compared with anywhere else, consistent with ongoing electrogenic sulfide oxidation metabolic activity. These data suggest that cable bacteria dynamics can be distinctly different in otherwise similar sediment (e.g. similar concentrations of dissolved H2S at depth), with variable development controlled by unknown factors.High resolution cable bacteria abundance data are not available in this study because of the design of the experiment. However, the vertical cable bacteria abundance dynamics, which were retrieved from random locations in the January 2019 microcosms during incubation from day 20 to 43, show that cable bacteria cell abundance in the oxic zone of the sediment did not vary significantly during the primary colonization period. In contrast, one of the microcosm series (Fig. 3B) showed a distinct trend of subsurface, anodic region (0.5–1.5 cm depth) enrichment of filament cells, and importantly, both microcosm series had similar terminal distributions when electrogenic activity had expanded across the entire surface (day 43) (Fig. 3). The first time sample in series A (day 20) (Fig. 3A) is similar in abundance distribution as at day 43. It is possible that the first sample taken in series A was located in an electrogenic colonization patch, that is, locally comparable to what would become the pattern across the entire surface at day 43. These abundance data together with the high resolution pH patterns allow inference of the colonization strategy of cable bacteria, as outlined subsequently.Figure 3Cable bacteria cell abundance dynamics in the duplicate January 2019 sediment microcosms. (A) and (B) represent duplication microcosms. From day 20 to 43, cable bacteria can be detected throughout the top 5 cm sediment with heterogeneous abundance patterns. There were depth intervals (e.g. B 2.5–3 cm) with cable bacteria cell abundance below the detection limit of the enumeration method. The sediment surface ( More

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Collection of marine organismsMarine invertebrates such as Corallium rubrum are ideal organisms to perform controlled experiments and to gather useful information on a variety of environmental conditions74. This species, whose diet is based on small zooplankton captured with the polyp tentacles, has been already used in long-term experiments74,75,76. Coral specimens were collected in March 2017 at ca. 35-m depth in the Marine Protected Area of Portofino (Punta del Faro, 44°17′41.02 N; 9°13′31.30 E) in the Ligurian Sea (North-Western Mediterranean Sea) by scuba divers (using TRIMIX blending).Experimental designAfter recovery, the coral specimens were brought to the laboratory and maintained in a tank (30 L) at in situ temperature (13 ± 0.8 °C) and subjected to the continuous flux of natural seawater filtered onto 0.7-µm pore-size membranes (micro-glass fibre paper, Munktell) by using two submersible pumps (Euronatale, 203 V, 50 Hz, 4 Watt).Sixty coral branches obtained from different colonies, with similar morphology, and a surface of ~2 cm2 each, were distributed among 12 experimental tanks, in order to have 5 coral branches per tank (12 L glass tanks, containing on average, 274 ± 26.4 coral polyps each). The corals were acclimatised for 20 days in a temperature-controlled room, and dim light conditions, before starting experiments. Each tank, filled with natural seawater, was equipped with a prefiltered (0.2 µm) channelled aeration system combined with motor-driven paddles in order to create convective currents, which allowed the resuspension of the microplastic mixture, thus ensuring as much as possible a homogeneous distribution of the polymers. This experimental system was designed and set up according to Sutherland et al.77. To assess the potential effects of increasing microplastic  microparticles L−1 (here defined as low, medium and high concentrations of microplastic particles). We also quantified the exact amount of particles actually interacting with the corals, by discounting the fractions loss due to experimental manipulations (see details in Supplementary Methods). According to the results reported in the Supplementary Results, the systems were responsible for the loss of ca. 40% of the microplastic particles, thus the corals in experimental systems were actually exposed to 60, 300 and 600 microplastic particles per litre (to which we referred the low, medium and high concentrations).The highest concentrations of microplastics (up to 600 microplastic particles per litre) can reflect future contamination on the basis of estimates obtained by numerical models9, whereas the low and medium concentrations have been selected to represent highly-contaminated marine habitats, including the areas where the corals were collected (Ligurian Sea)78,79. In particular, for the Ligurian Sea, we estimated an average value of 94 microplastic particles L−1, based on the concentrations of microplastic particles ( >200 µm) determined by Fossi et al.78,79, and the most cautionary correction factor (105) calculated by Brandon et al.10 for the unaccounted smaller fraction of microplastics (25–75% of the fragments falling approximately in the 20–100 µm dimensional class with median range: 59–116).Microplastic mixtures were also prepared considering the concentration and composition of dominant polymers in different coastal marine environments, especially in hot spots of microplastic contamination5,7,8.The microplastic mixture added to the tanks was composed of 76.6% polyethylene, 10.9% polypropylene, 7.3% polystyrene, 3.3% polyvinylchloride and 1.8% polyethylene terephthalate particles. These particles were obtained by milling plastic objects from everyday life (i.e., containers, bottles, cups, pipes) according to Paul-Pont et al.8 (Supplementary Table 5). Plastic milling was carried out under a laminar flow hood in chilled sterilized and 0.02 µm prefiltered milliQ water. All the tools used for handling plastics were pre-treated with 1% sodium hypochlorite in water and rinsed 10 times with sterilized and 0.02 µm prefiltered milliQ water, and then dried under laminar flow hood. Details on the preparation of microplastic mixtures are reported in the Supplementary Methods.The low, medium and high concentrations of microplastics were added in triplicate tanks (n = 3 for each concentration). Additional systems containing seawater and coral branches without microplastics (n = 3, here defined Controls), and seawater added with microplastics (at the highest concentration) without red corals (n = 3, here define CTRL MPs) were used as controls. Overall, the experimental setup comprised 15 tanks.The experiments for assessing the impact of microplastics on red corals started immediately after the microplastic mixture addition (time 0). During the experiment, seawater temperature (range: 13.10 ± 0.01–13.13 ± 0.05 °C), salinity (range: 38.35 ± 0.18–38.65 ± 0.18) and oxygen levels (7.10 ± 0.08–7.36 ± 0.2 mg L−1) were monitored daily in all tanks using a probe (YSI Professional Plus, USA) and corals were fed three times a week with 103 Artemia salina nauplii L−1.After ten days the condition of corals that were exposed to microplastics was deteriorating, so we collected one coral branch from each tank for molecular analyses (i.e., associated microbiome, gene expression and DNA damage). After 14 days, the experiment was stopped because the coral branches that were exposed to the medium and high microplastic particle concentrations were completely wrapped in mucus, with a large portion of damaged tissue and without polyp activity, therefore corals were defined dead (overall 12 branches, see ‘Results’ section for details). Coral branches in the controls showed no visible signs of necrosis or other macroscopic stress. The tissue remained intact, and the colour unchanged until the end of the experiment.Effects of microplastic ingestionCoral feeding activityTo assess the impact of microplastics on feeding activity of C. rubrum, analyses based on the use of Artemia salina were performed after 2 and 10 days from the start of the experiment (t0) in replicate systems (n = 3 for each treatment, n = 3 for the controls) according to standard international protocols80. The nauplii of Artemia salina were reared in the laboratory, incubating 0.5 g of cysts (Ocean Nutrition) in 1 L of seawater filtered onto 0.2-µm filter in a separatory funnel, 2 days before the analysis of feeding rate. At hatching, nauplii were counted and maintained in vials to obtain the concentration of 1000 nauplii L−1. To avoid stress, corals (one branch for each tank) were transferred underwater to beakers along with 1 L seawater of each tank. After addition of live A. salina nauplii (1000 nauplii L−1) to the 1 L beakers containing the coral branches and to the controls, three aliquots of 10 ml seawater were collected after ~30 s from the start of the experiment (t0) and after 2 and 4 h. The remaining nauplii present in each seawater aliquot were counted under a stereomicroscope at ×3.2 magnification (Zeiss Stami 2000). Mean ingestion rates (nauplii removed h−1) were determined by linear regression analysis.Accumulation of microplastics by C. rubrum
To investigate the accumulation of plastic polymers by C. rubrum polyps, the number of microplastic particles ingested by coral polyps was evaluated after 14 days of exposure to microplastic mixture, by dissolving polyps and skeleton of the corals (one for each tank at the concentration of 1000 microplastic particles L−1) using an acid/base digestion protocol36 with some modifications.To exclude biases on the estimate of the number of microplastic particles actually accumulated within the polyps, coral branches were accurately rinsed with milliQ water and checked under stereomicroscope (at ×50 magnification) for the potential presence of microplastic particles adherent to the coral tissue. Coral branches were then soaked in 5 ml of 4.5% sodium hypochlorite (NaClO) for 24 h and dissolved in 5 ml of 37% HCl for 30 min. Particulate material was retained on a 0.2-μm filter in a vacuum filtration system, and microplastic particles were counted under a stereomicroscope at ×50 magnification. The chemical composition of the polymers ingested by corals was confirmed by FT-IR analyses (Perkin Elmer, software Packages Spectrum 5.3.1). To evaluate possible damage to plastic polymers due to the use of acid/base solutions, we exposed polypropylene, polyethylene, polystyrene, polyvinylchloride and polyethylene terephthalate at the same volume and concentration of NaClO and HCl during digestion of the coral.Potential transfer of microplastics by zooplanktonWhile testing the exposure of the red corals to microplastics, we also determined the rate of microplastic ingestion by A. salina nauplii used to feed the red corals, in order to assess their role as potential vectors of microplastics. To do this, additional tanks (n = 3) were added with 0.2 µm prefiltered 12 L natural seawater, 1000 nauplii L−1 of A. salina and the same microplastic mixture used for the experiment on the red corals (at the highest concentration). Three other tanks were used as controls containing 0.2 µm prefiltered 12 L natural seawater and 1000 nauplii L−1 of A. salina.Microplastic ingestion by A. salina was determined after 2 and 10 days of experiment following the enzymatic digestion protocol previously developed81 with some modifications. Such a procedure degrades biological tissues without affecting shape, colour and composition of plastic fragments. Gut contents of 100 individuals of A. salina (n = 5) were assessed under a stereomicroscope (Leica MZ125) and light microscope (Zeiss Axiovert 200) and photographed with a Zeiss Axiocam digital camera. Afterwards, nauplii were processed immediately according to the modified enzymatic digestion protocol. Nauplii were dried in an oven for 3 h at 60 °C, transferred to glass jars containing a buffer homogenizing solution (400 mM Tris-HCl pH 8, 60 mM EDTA pH 8, 5 M NaCl, SDS 1%) incubated at 50 °C for 15 min and exposed to Proteinase K (1 mg ml−1). Then, samples were dried for 2 h at 50 °C, homogenized and re-incubated at 60 °C for 20 min and sonicated on ice (1–2 min) three times. After digestion, the microplastic-containing suspensions were placed in Utermöhl chambers and the microplastics were examined at the inverted light microscope (Leica DMI3000-Bat ×200 magnification) and counted. Microplastics obtained from nauplii digested after 10 days of incubation were also measured and categorized by colours and shape to evaluate the numbers and the size spectra of microplastics ingested by A. salina during the experiment.Physical impact on coral coenenchymaScanning electron microscopy (SEM) analysesTo investigate the physical damage of the microplastic mixture on the coral tissues, samples (one branch from each tank including the control) were collected before the start of the experiment (t0), after 7 days and at the end of the experiment and prepared for SEM analyses according to standard protocols82 with some modifications. Coral branches were stored in 0.7 µm prefiltered seawater with 4% buffered formalin. After 24 h, samples were washed with 0.7 µm prefiltered seawater and dehydrated for 3 h in 20% ethanol. After 3 h they were washed in the same way and dehydrated in ethanol 50%. After 3 h, samples were stored in 70% ethanol. Samples were stored at +4 °C. We dehydrated samples using different gradients of ethanol solutions (70–80%, 80–90%, 90–95%, 95–99% in 2 days)82. Then, samples were dried using HMDS (Hexamethyldisilazane, Aldrich 440191)83. Dried samples were mounted on aluminium stubs using Leit-C glue (conductive carbon cement, Neubauer Chemikalien) and sputter-coated with gold. Samples were examined with a Scanning Electron Microscope (Zeiss SUPRA 40). In addition, the tissue damage percentage was assessed on SEM micrographs at ×200 of magnification by using PhotoQuad v1.4 software84. Such a software for advanced image processing of 2D photographic quadrat samples, dedicated to ecological applications, was used for the analysis of three randomly selected areas from the apex to the base of each coral rotating it on three sides (n = 9). Additional analyses through random SEM observations (n = 20) at 3.00KX to 17.00KX of magnification were carried out to determine prokaryotic cell abundances around lesions of corals (n = 3) exposed to high concentrations of microplastic particles. Data were standardised to the coral surface analysed.Mucus release and trapped microplastics and prokaryotic cellsTo evaluate the first symptoms of coral stress, a photographic report was conducted daily. The abundance of microplastic particles trapped in coral mucus was estimated using an enzymatic digestion protocol81 with some modifications. Mucus produced by corals exposed to higher microplastics concentrations was dried in oven at 60 °C for 12 h. After 12 h, five ml of homogenizing solution was added to the samples and incubated at 50 °C for 15 min. Proteinase K (1 mg mL−1) was added to the samples, which subsequently were incubated at 50 °C for 2 h. Then, samples were homogenized and incubated again at 60 °C for 20 min, after that samples were sonicated three times (three 1-min treatments using a Branson Sonifier 2200; 60 W). After digestion, microplastics-containing suspension was filtered on 0.2-μm filters in a vacuum filtration system (Whatman, Nuclepore). Filters were analysed at stereomicroscope at ×50 magnification (Zeiss Stemi 2000).Stress signals at the molecular levelRNA extraction, cDNA synthesis and gene expression level by qPCRTo assess potential changes in the gene expression pattern of C. rubrum due to microplastics, total RNA was extracted from ca. 20 mg of tissue (wet weight) from one coral branch randomly collected from each treatment (n = 3) and control (n = 3) after 10 days of experiment by using Quick-RNA™ MiniPrep (Zymo Research, Freiburg, Germany) according to the manufacturer’s instructions. Total RNA was also extracted from additional samples of coral branches collected randomly at the beginning of the experiment. Once scraped by surgical disposable scalpels (Braun), coral tissues were placed in new 2 ml sterile tubes and washed three times with phosphate-buffered saline (PBS 1×). Samples were centrifuged at 1800 rpm for 10 min in an Eppendorf® 5810r refrigerated centrifuge using a swing-out rotor at 4 °C and, after removing the supernatant, were homogenized for 5 min with a RNase-free sterile glass stick in RNA lysis buffer. Contaminating DNA was degraded by treating each sample with DNase dissolved in RNase-free water included in the kit. For each sample, 250 ng of total RNA extracted was retrotranscribed with an iScript™ cDNA Synthesis kit (Bio-Rad, Milan, Italy), following the manufacturer’s instructions. The reaction was performed on the Veriti™ 96-Well Thermal Cycler (Applied Biosystem, Monza, Italy). To evaluate the efficiency of cDNA synthesis, a PCR was performed with primers of the reference gene, cytochrome oxidase I (COI, Supplementary Table 6). The reaction was carried out using MyTaq™ HS DNA Polymerase (Bioline, Luckenwalde, Germany) on the Veriti™ 96-Well Thermal Cycler (Applied Biosystem, Monza, Italy). The PCR programme consisted of a denaturation step at 95 °C for 1 min, 35 cycles at 95 °C for 45 s, 60 °C for 45 s, and 72 °C for 45 s and a final extension step at 72 °C for 10 min.The expression levels of the six genes of hsp70, hsp60, MnSOD, mtMutS, EF1 and cytb, involved in a broad range of functional responses, such as stress, detoxification processes, and DNA repair, were followed by real-time qPCR to identify potential stress of corals exposed to microplastics61. For the cytb, target-specific primer pairs were designed with the Primer 3 software (http://primer3.ut.ee85) using nucleotide sequences retrieved from the GenBank database for C. rubrum as template (https://www.ncbi.nlm.nih.gov/genbank/; Supplementary Table 6). SensiFAST™ SYBR® & Fluorescein mix (Bioline, Luckenwalde, Germany) were used for measuring the levels of mRNAs on CFX Connect™ Real-Time PCR detection system (Biorad, Milan, Italy). Fluorescence was measured using CFX Manager™ software (Biorad, Milan, Italy). All genes tested by qPCR in this study were amplified with primers purchased from Life Technologies/Thermo Fisher Scientific (Milan, Italy). The fold change in target gene mRNA expression of corals exposed to microplastics compared with the control was calculated using the comparative CT method using the 2−ΔΔCt equation86. COI was used as reference gene for normalising the gene expression analyses.DNA oxidative damageFor evaluating oxidative DNA damage potentially due to microplastic exposure on C. rubrum, the content of 8-hydroxydeoxyguanosine (8-OHdG) was analysed. DNA was extracted from 20 mg (wet weight) of tissue randomly collected from one coral branch for each treatment (n = 3) and control (n = 3) after 10 days of experiment using DNeasy Blood & Tissue Kits (Qiagen, Valencia, CA) and following the manufacturer’s protocol. Finally, samples were kept at −20 °C before subsequent analyses. Nucleic acids extracted (2 μg) were transferred into new 2-ml tubes and incubated for 5 min at 95 °C, then rapidly chilled on ice. Samples were digested to nucleosides by incubating the denatured DNA in sodium acetate 20 mM, pH 5.2 with 2 μl of nuclease P1 (6 U/μl; Merck KGaA, Darmstadt, Germany) for 2 h at 37 °C. Each sample was then incubated with 5 μl alkaline phosphatase (1 U/μl; Roche, Mannheim, Germany) in Tris-HCl 100 mM, pH 7.5 for 1 h at 37 °C. The reaction mixtures were then centrifuged for 5 min at 6000 × g and the supernatants tested for DNA oxidation with an OxiSelect™ Oxidative DNA Damage ELISA Kit (8-OHdG Quantitation; Cell Biolabs, CA, USA). As positive control, Escherichia coli genomic DNA (2 μg) was incubated in a final concentration of 50 and 100 mM H2O2 overnight at 37 °C, and subsequently tested.Prokaryotic abundance in coral mucus and surrounding seawaterTo highlight possible effects in terms of prokaryotic contamination associated with the exposure of the corals to microplastics, we determined prokaryotic abundances in the mucus released by C. rubrum and the surrounding seawater.Prokaryotic abundances in the coral mucus collected from each tank (except for the control where coral mucus was not released) after 14 days of the experiment, were analysed by epifluorescence microscopy. The extraction of prokaryotic cells from the mucus (ca. 1 mL for each tank) was performed using pyrophosphate (final concentration, 5 mM) and ultrasound treatment (three 1-min treatments using a Branson Sonifier 2200; 60 W)87. Then, samples were diluted from 50- to 100-fold with sterile water filtered onto 0.2-μm pore-size filters (Anodisc filters; black-stained polycarbonate). The filters were stained using SYBR Green I (10,000× in anhydrous dimethyl sulfoxide, Molecular Probes-Invitrogen) diluted 1:20 in prefiltered TE buffer (pH 7.5) and incubated in the dark for 20 min; a drop (20 µl) of antifade solution (composed of 50% 6.7 mmol L−1 phosphate buffer at pH 7.8 and 50% glycerol with the addition of 0.5% ascorbic acid) was laid both on a glass slide and on the filter mounted on it. Prokaryotic counts were performed under epifluorescence microscopy (magnification, ×1000; Zeiss filter set #09, 488009-9901-000, excitation BP 450–490 nm, beam splitter FT 515, emission LP 520), by examining at least 20 fields per slide and counting at least 400 cells per filter.For the determination of prokaryote abundance in seawater surrounding corals, three replicates of 10 ml of seawater were collected from each tank. Total prokaryotic abundance was determined according to Danovaro87. Samples were filtered onto 0.2-μm pore-size filters (Anodisc black-stained polycarbonate filters, Whatman) into a funnel with vacuum pressure no greater than 20 kPa (or 150 mmHg) to avoid cell damage. When the sample had passed through, filters were stained with 20 µl of SYBR Green I (10,000× in anhydrous dimethyl sulfoxide, Molecular Probes-Invitrogen) diluted 1:20 in prefiltered TE buffer (pH 7.5) and incubated in the dark for 20 min. Then, to remove the excess stain, filters were washed three times using 3 ml of Milli-Q water; a drop (20 µl) of antifading solution (composed of 50% 6.7 mmol L−1 phosphate buffer at pH 7.8 and 50% glycerol with the addition of 0.5% ascorbic acid) was laid both on a glass slide and on the filter mounted on it. Prokaryotic counts were carried out as described above.Microbiome of corals exposed to microplasticsThe coral microbiome was analysed immediately before the start of the experiment (before the addition of microplastics) and after 10 days of the experiment, both in replicated coral branches exposed to microplastics and in unexposed corals (Control t10). For the analysis of the microbiome, ca. 20 mg of tissue (wet weight) from one coral branch randomly collected from two tanks of each treatment and control was scraped from the skeleton by using surgical disposable scalpels (Braun) and DNA extraction was performed using the QIAGEN DNeasy Blood & Tissue Kit. Briefly, samples were digested with proteinase K at 56 °C overnight or until the tissue was completely lysed, then samples were processed following the manufacturer’s protocol. Finally, samples were held at −20 °C before PCR amplification and sequencing. The molecular size of the DNA extracts was analysed by agarose gel electrophoresis (1%) and the amount and purity of DNA were determined by Nanodrop spectrophotometer (ND-1000). For PCR amplification of the 16S V3 region, the Bacteria-specific primer pair 805R/341F was chosen with Illumina-specific adapters and barcodes. Sequencing was performed on an Illumina MiSeq platform by LGC Genomics GmbH (Berlin, Germany).Raw sequencing paired-end reads were first joined using the bbmerge tool from the BBMap suite88 in a two-step process: reads that did not merge in a first step were quality-trimmed to remove low-quality bases (Q  More