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    Neofunctionalization of an ancient domain allows parasites to avoid intraspecific competition by manipulating host behaviour

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    The influence of a lost society, the Sadlermiut, on the environment in the Canadian Arctic

    Understanding the ‘push’ and ‘pull’ influence of environment on the migration and sustainability of peoples in northern North America over the last millennia is arguably one of the most important elements of understanding how recent climate change may affect society and lead to genetic adaptations1,2. The timing of migration has often been associated with paleo- temperature reconstructions that link evidence of distinctive material culture3 as well as the impact of subsistence practices in areas where hunting camps were established4 with shifting conditions. For the Dorset people, who were reliant on ice-dependent species such as walrus5, climate may have served as a “push” factor that served as a mechanism for northern migration during periods of time such as the Medieval Climate Anomaly (MCA). Conversely, the Thule were able to take advantage of increased activity of belugas and narwhals during longer open-water seasons, and migrations associated with the Thule expansion (circa 1250 CE) may have followed this transition until cooling associated with the Little Ice Age in the fifteenth century3,6. The Sadlermiut of Southampton Island (Nunavut, Arctic Canada) have often been referred to as descendants of the Dorset culture7,8 even though recent genetic evidence suggests they were a long isolated Thule population9,10. Archaeological evidence of stone-carved tools for walrus hunting, which is much more related to Dorset cultural practices than Thule4,5, is a prominent feature of winter hunting camps concentrated on the eastern side of Southampton Island in proximity to polynyas and ample walrus hunting grounds. Small, shallow ponds that are widespread in this area were used as staging grounds for the cleaning and preparation of subsistence harvest, and serve as sedimentary archives of the past presence and influence of the Sadlermiut, and their cultural practices, on the landscape.High latitude freshwater ecosystems are often referred to as sentinels of environmental changes caused by climate variability and human activity11. Small and shallow lakes and ponds that characterize Arctic landscapes have a low resilience to buffer environmental change12,13,14, as well as catchment disturbances induced by prehistoric Inuit whalers15. Likewise, diffuse and point source disturbances can have disproportional effects due to the suboptimal environmental thresholds characteristic of biological communities of northern aquatic ecosystems16. Here, we show that a small subarctic pond in proximity of the archaeological site “Native Point” on Southampton Island evolved atypically after human activities initiated almost 800 years ago when Sadlermiut settled in the area. Our multi-proxy paleolimnological investigation uses geochemical and biological indicators to infer direct and indirect anthropogenic impacts. The lacustrine sediments collected from this site are highly sensitive environmental recorders that also allow us to pinpoint the first arrival of Sadlermiut culture, define their dietary shifts, and summarize the legacy of anthropogenic activities at “Native Point” since their first arrival.The legacy of the Sadlermiut on the environmentOne of the richest archaeological sites found in the Canadian Arctic, the “Native Point” site was occupied by the Sadlermiut ca. 1250–1325 CE until decimated by disease introduced by European whalers in 19033,4,5. The Sadlermiut village, referred to as the Tunermiut site4, consisted of numerous sod and winter houses that bordered a small shallow freshwater body (c. 20,000 m2), “Bung Stick Pond”. This site (Fig. 1A–C), and others in the well-known archaeological area of Native Point, offer a fascinating glimpse of an isolated society that evolved independently of modern-day Inuit and incorporated cultural elements of the Dorset peoples that vacated the area prior to the Thule migration10.Figure 1Bung Stick Pond and its catchment at Native Point, Southampton Island, Nunavut; (A) Aerial photo of Native Point (Orthoimage GéoBase, Natural Resources Canada), yellow circle—Bung Stick Pond; contains information licensed under the Open Government Licence—Canada; (B) Simplified geological map of Southampton Island17 and location of nine reference lakes and ponds; (Source: Geological Survey of Canada, “A” Series Map 1404A, 1977, 1 sheet, https://doi.org/10.4095/108900; contains information licensed under the Open Government Licence—Canada; georeferenced with Grass GIS 7.8.3; https://grass.osgeo.org/) (C) Photo of Bung Stick Pond facing northward, note scattered bones and antler fragments and partly paleozoic limestone gravel, informed consent for the publication of image has been obtained from Gabriel Bruce.Full size imageThe heavy influence of Sadlermiut families processing food and leaving the remains of butchered carcasses to degrade in the pond is both visible and likely the main contributing factor for the difference in water chemistry that persists until today (Fig. 2). Southampton Island is characterized by a short vegetation period, ultra-oligotrophic freshwater ecosystems, and low sedimentation rates18,19. As such, the lakes and ponds of the area have low nutrient concentrations (i.e. total N and P; see Fig. 2), and the concentration of ions is dependent on soluble bedrock geology in their catchment, basin evolution since the last glaciation, distance to shore, and inputs from wildlife14,18,20,21,22. Here, the water chemistry of our study site, Bung Stick Pond, is an order or magnitude higher in concentrations of nutrients and organic carbon than in other lakes and ponds investigated on Southampton Island during the sampling period (Fig. 2). The only other eutrophic systems known in the region are those affected by waterfowl colonies18. Furthermore, the pond is characterized by an unusual high alkalinity caused by the catchment’s surface geology, which consists of Paleozoic limestone.Figure 2Box and whiskers diagram of water chemistry of nine lakes and ponds sampled on Southampton Island compared to Bung Stick Pond (red circle) (see Fig. 1). Nutrient indicators (top row) and major ion concentrations (bottom row) in mg L−1.Full size imageThe arrival and harvesting practices of the SadlermiutThe sediment history collected from Bung Stick Pond offers the possibility to track the aquatic system’s evolution since the arrival of the Sadlermiut when the site was used by the community for butchering of the collected harvest (Fig. 3). There is little archaeological evidence to suggest that the diet of Sadlermiut contained fish or any plants4,5, and the pond’s littoral zone is littered with skulls/skeletons at the bottom (see Fig. 1C). The predominant role of marine resources in Sadlermiut culture is also mirrored by the stable isotope signal in their adult bone collagen measured from burials23,24,25 (Fig. 4). Similarly, the surplus of organic material from the decaying process of carcasses in or around Bung Stick Pond carried the species specific isotope signal in the sediment. In general, heavier isotopes of nitrogen are enriched in predators relative to its food, which leads to high values in top predators of a food web26,27,28,29,30. Carbon isotope ratios usually show much less trophic enrichment, however a secondary fractionation process causes a positive offset in bone collagen in relation to soft tissue26,27,28,29,30 and apparently sediment samples.Figure 3Nitrogen isotope analysis from paleo-Inuit harvesting sites and distinguishable phases at Bung Stick Pond cores. Inferred August air temperature based on chironomid remains from Southampton Island19. Earlier pronounced stable δ15N isotope record from sediment core tracingprehistoric Inuit whalers on Somerset Island15. Stable δ15N isotope record and TOC:TN-ratio from bulk sediment samples of core NP-3; iron (Fe) record from bulk sediment samples of core NP-2; selected relative abundance of chironomids of core NP-2, with Tanytarsus gracilentus (pale blue) and sum percentage of Paratanytarsus (dark blue); enumerated Daphnia ephippia (resting eggs) and Fabaeformiscandona harmsworthi (Ostracoda) valves of core NP-2 in individuals per cm3 with; adults (dark green), juveniles (pale green); interpreted activity phases I–IV at Native Point; sediment colors of age-corrected core NP-1.Full size imageFigure 4Relationship of δ13C and δ15N in organic material of sediment core NP-3 and bone collagen of the Sadlermiut and their potential diet. Circles indicate isotope excursion in organic material (sediment) in different time intervals; green (Phase 1):  1767 CE; triangles show isotope data from human skeletal remains (bone collagen) in Sadlermiut burials from Coltrain (up)23, (down)24,25; whisker plots indicate modern range of isotope composition in muscle and blubber tissue of mammals supposedly included in the Sadlermiut diet from Hudson Bay or the Canadian Arctic/reports26,27,28,29,30.Full size imageThe stratigraphic analysis of biological and geochemical indicators revealed four distinguishable phases that are attributable to the arrival and cultural practices of the Sadlermiut (Fig. 3). The reference condition of the pristine environment prior to Sadlermiut settlement (Phase 1; Fig. 3) is inferred by the low abundance of aquatic organisms (e.g., chironomids, cladocerans ephippia, ostracods) and δ15N values of around 8‰ at the base of the sediment core. During this time, the carbon:nitrogen ratio (TOC:TN) indicated mostly allochthonous inputs from the terrestrial environment31. An abrupt shift in geochemical indicators (Phase 2) suggests that the arrival of the Sadlermiut occurred between 1250 and 1300 CE. This period leads the earliest radiocarbon dated materials (1325 CE) found at the Sadlermiut heritage site4. Isotope analyses show a substantial increase in δ15N from about + 8 to + 19‰ (Fig. 3) and depletion of δ13C from about − 18 to − 21‰ (Fig.S2). Likewise, a decline in TOC:TN from 13 to 9 in bulk sediments indicates a large difference in the source of materials entering the lake and a sharp increase in aquatic production during this period32. Abnormally high iron concentrations were also observed starting from 1250 CE, potentially from blood washed into the system from butchered marine harvest.The onset of Phase 3 (~ 1400 CE) suggests that settlement of the Sadlermiut camp supplied less external materials to the lake basin and a shift in the harvest of the Sadlermiut from a diet primarily comprised of marine mammals (e.g., seals, whales), which are characterized by the heavier δ15N and depleted δ13C (see Figs. 3 & S2), to one dominated by a more terrestrial origin (i.e., caribou). The shift in isotopic indicators, including the decrease of TOC:TN, during Phase 3 is concurrent with loss of macrophyte habitat as inferred from the chironomid data, notably the reduction of Paratanytarsus from 35 to  2 (Table S5). The sediment concentrations of each of the metals showed major increases from pre-industrial (~ 1850) to modern times consistent with industrial air-borne pollution (Fig. 5). Ag and Zn increased beginning ~ 1750–1800, while Bi, Pb, Sb and Sn showed increases occurring after 1900. The most striking EF was for tin (Sn), which had a rapid rise in concentrations from about 1900 (Fig. 5) and an EF of 72. Other trace elements including As, Cd, Cu, and Se showed modest enrichment (EFs 1.6–1.9) in post-1900 horizons (Table S5). So far, there is only one reference in subarctic Hudson Bay region that significant anthropogenic enrichment of Pb in post-1900 horizons (EFs 2–5×) has occurred38. Enrichment of metals is better known from ice cores from the Devon Ice cap (Devon Island Nunavut, Arctic Canada), which are in good agreement or show higher EFs than observations in the NP2 core. Noteworthy are anthropogenic enrichment of As and Bi39, Sb40, Pb41, Ag and Thallium (Tl)42, which originate from urban and industrial areas and linked to coal combustion and metal smelting. The overall comparison of ice cap ice cores and NP-2 EFs suggests that the inputs of Ag, Bi, Pb, Sb, and Ag are influenced by long-range transport from Eurasian sources40,42. Historical profiles are not available for Sn in Arctic sediment, peat, or ice core archives. Elsewhere, peat cores in the UK record deposition of Sn from regional tin mining and smelting43.Figure 5Metal concentrations of industrial air-borne pollution in sediment core NP-2; concentrations in ppm; interpreted activity phases I–IV at Native Point; sediment colors of age-corrected core NP-1.Full size imageIn concert with recent anthropogenic deposition of contaminants, an eutrophication trend can be inferred from more abundant remains of aquatic microfauna (i.e., chironomids, cladocerans, and ostracods) in the uppermost lake sediments (Fig. 3). Likewise, the sediments are composed of highly organic material (mean 15 wt%), which accumulates toward the core top exceeding 30 wt% (Fig. 3).All these data indicate the extreme vulnerability and low resilience of small Arctic ponds as the effects of human activities at this site are still prevalent after more than 750 years. The sediment archive ipso facto records the influence of the Sadlermiut on the environment since their arrival and until the last of their population succumbed to disease in 1903. Furthermore, the continued contamination by airborne metal pollutants of remote Arctic landscapes since industrialisation is evident. More

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    First tracks of newborn straight-tusked elephants (Palaeoloxodon antiquus)

    The MTS proboscidean tracks and trackmakersRounded-to-elliptical tracks, with an axial length range from 9.6 to 54.5 cm (pes), were found mostly isolated and as manus-pes couples, or associated forming at least eight short trackways (see Table 1). They reveal good preservation in one 6-footprint trackway (see below), two converging trackways and some couples, showing anteriorly directed, wide, short and blunt toe impressions (Figs. 2, 3 and 4). Toe impressions are not commonly visible in elephant footprints9,13, (but see27), which attests to cases of exceptional preservation in Matalascañas tracks. Preservation as true tracks is identified through expulsion marginal rims (e.g., Fig. 4a, g) and possible ejecta (Fig. 3b,e). Large and flat sole surfaces sometimes show evidence of pockmarks23 (Fig. 4f).Table 1 Measurements of Proboscipeda tracks, ordered from smallest to largest in length.Full size tableFigure 2Proboscidean tracks (Proboscipeda panfamilia) attributed in the MTS to straight-tusked elephants. (a–h) Morphological features of small-sized tracks produced by calves and juveniles. Examples of manus impressions in (a) PAT/MTS/011a, (b) PAT/MTS/016 and (f) PAT/MTS/015x, and for further interpretation of (a) see Fig. 3; the latter two with drag marks made during the foot-off event. (c) and (g) PAT/MTS/002a,b: Manus-pes couple found isolated showing heteropody and different number of toe impressions (interpretation as left-side tracks by peak pressure deformation in the left side of the track according to27); interpretation in (c). (d) PAT/MTS/014 and (e) PAT/MTS/007a: Calf-sized pes with three toe impressions. (h) PAT/MTS/011 h: Badly preserved manus of a calf. Scale bar = 5 cm.Full size imageFigure 3Photograph, outline, high-resolution 3D and false-coloured 3D images of the PAT/MTS/0011a track representing the best preserved manus of a juvenile-sized Proboscipeda track. (a) and (c) From the photograph and high-resolution images, five toe impressions in the anterior part of the rounded track are clear (especially toes I–IV). (b) and (f) The false coloured images in orthogonal (b) and oblique angle views (f) highlight the deepening of the track fore- and outwards, thus revealing a peak pressure pattern typical of left forefoot (toes III–IV), as well as a possible ejecta mound in front of the track. The poorly evident and narrow expulsion rim developed around the track is the result of the high cohesiveness and plasticity of the clayey fine-sand substrate. (d) Contour map supporting previous interpretation. (e) The cross-section of the track details the anterior migration of the foot pressure during its rotation, creating a peak pressure in the foot-off event that is represented in the deepest part of the track. Scale bars are 10 cm.Full size imageFigure 4Large-sized Proboscipeda tracks attributed to P. antiquus adults. (a) to (d) PAT/MTS/001: Right manus showing clearly 5 toe impressions and the frontal and lateral displacement rims (morphological interpretation based on the orthogonal (b) and oblique (d) depth and contour (c) maps). (e) and (f) PAT/MTS/010e: Deeper manus with pockmarks; toe pad impressions indicated (I–III). (g) PAT/MTS/004a,b: large manus-pes couple where the hind foot deformed the fore foot during overstepping, and revealing a typical elephantine gait; the toe impressions in both tracks indicate the direction of movement. Scale bar = 10 cm.Full size imageIrrespective of the track size, pes are elliptical to sub-rounded, with the length axis larger than the width and manus are circular or elliptical, with the width axis larger than the length (Figs. 2c and 4d, g for small and large size tracks, respectively). The safest way to differentiate between pes and manus is through the orientation of the track provided by the toe impressions, or by the orientation of the longer axis in trackways. When arranged in trackways, manus-pes couples show the typical elephantine gait, showing a short pace resulting from the fore- and hind feet on the same side swinging forward simultaneously below the body, as it is known from modern elephant gait28. In some cases, the partial impression of a pes overstepping the proximal part of a manus can be seen (Fig. 2c, g). Based on similar preservational style and opposing directions of movement without overlapping at the meeting point, a converging pair of trackways was apparently produced contemporaneously by an adult and a rather small juvenile. Sharp edges of the toe impressions indicate the presence of nails. These are found mostly in well preserved, smaller-sized tracks (Fig. 2a, d, e) because nails are commonly worn down in adult elephants and not always shown in their tracks13. These morphological features allow us to attribute the MTS trackways to the ichnospecies Proboscipeda panfamilia used previously for describing, among other tracksites, those tracks attributed confidently to the straight-tusked elephant Palaeoloxodon antiquus in the paleogeographical context of southern Europe11,14 (see supplementary Table S1).Manus-pes couples, when showing overstepping, were not considered in Table 1 (Fig. 2c, g). Overstepping depends on the speed of walking; at faster speeds the overstepping is only partial or there is no overstepping; elephants maintain the footfall pattern at all speeds, shifting toward a calculated 25% phase offset between limbs as they increase speed28 (Fig. 2g). The smallest tracks usually do not show overstepping possibly because of the greater activity, with longer pace and stride lengths, demonstrated by calves and juveniles when compared to adults. Manus or pes showing a large width-length ratio (below 0.80–0.96 sensu25) were not considered for the estimates since they represent slippage.Younger elephants have more pliable skin and musculature than adults. Also, the greater expansion and distribution of the weight in heavier adult animals is enough to reduce or negate toe impressions in some types of sediments, such as compacted substrates24,29. Interpreting the sedimentological data for the paleosol where MTS was developed15,17,30, suggests a drying clayey-sandy substrate14 that was still plastic enough to absorb the impact of the limbs during the locomotion of the elephants (presence of expulsion rims and absence of radial pressure cracks), and preserving, in many cases, the morphological details of the feet in good condition (Figs. 2a, 3, 4a; see Fig. 2h for a badly preserved example).Ichnological inference about the height, body mass and age of Palaeoloxodon antiquus in the MTSSeveral methods have been proposed for estimating the height at the shoulders for proboscideans, and the relationship between body mass and age with shoulder height 1,31,32. A linear relationship between foot length and shoulder height was confirmed by Lee and Moss33 from extant elephants and compared with fossil examples by Pasenko24. Pes length has been especially used in studies as an indicator of shoulder height21,34,35,36. Among Asian elephants, manus circumference has been shown to have a similar predictive relationship with shoulder height33. These parameters were determined for each isolated track (or representative track in a trackway), including manus and pes (Table 1), using equations previously proposed31,33 (see Methods). A similar approach has been applied to mammoth track studies in North America21,27, where modern ontogenetic and body-mass data has been used to provide age and size estimates from fossil tracks.From the skeletal record, sexual dimorphism of P. antiquus was observed to be more accentuated than in extant elephants, especially in terms of size differences1. During the first 10 years of life, both male and female African bush elephant foot lengths increase rapidly, with the fastest growth shown in the first two years for calves33,37. In P. antiquus, males would have continued to grow until their fifties according to bone data1, while females would have been much smaller as result of energy expenditure with reproduction, flattening the growth curve just after puberty. That is why the equations of Lee and Moss33 that discriminates the shoulder height from tracks for males and females have been applied. However, by comparison with the study of Marano and Palombo32 (based on the progress of eruption and degree of wear of teeth compared to extant elephants), and the body mass correlation of Larramendi et al.1 for calculating the age of P. antiquus, our MTS ages obtained from the application of the regression curve of Lee and Moss33 are underestimated and must be analysed as minimum age approximations for track lengths corresponding to adolescent and adult animals, especially for males. The obtained estimations from tracks are subject to a level of uncertainty related to biotic and abiotic factors that can distort the data (i.e., taphonomy) as it happens also with the calculations taken from skeletal proportions. Therefore, McNeil et al.21 even included data from frozen mammoth carcasses on the growth curve of Lee and Moss33 for correcting size discrepancies along ontogeny. For P. antiquus, our best data for comparison comes, however, from the flesh reconstructions1.Ontogenetic implicationsBased on the best fossil site found for this species in Europe, corresponding to 70 individual Palaeoloxodon antiquus specimens recovered in Geiseltal, Germany, Larramendi et al.1 developed the best reconstruction, so far, of the life appearance of this species and discussed size, body mass, ontogeny and sexual dimorphism. The Neumark-Nord bone site may be contemporary or slightly older than MTS, corresponding to late Middle Pleistocene-to-Eemian interglacial period1. The authors found that the body mass of P. antiquus males was up to three times more that of male Asian elephants and twice that of extant male African bush elephants. The large size determined for straight-tusked elephants (with an estimated  > 400 cm shoulder height in the flesh and body mass of 13 tonnes) and a later complete epiphyseal-diaphyseal fusion of limb bones (not yet totally fused at an estimated age of 47 years), in comparison with extant elephants, suggests that this species had a longer lifespan of 80 years or more1. Sexual dimorphism of P. antiquus was observed to be more accentuated than in extant elephants, with females generally not exceeding 300 cm at the shoulders with an estimated weight of not more than 5.5 tonnes, while males continued to grow until their fifties1. Males in extant elephant species grow more rapidly than females after puberty (i.e., around 7 years in age), which are affected by a trade-off between growth and reproduction. Under normal nutritional conditions, the growth rate is generally higher in males than females leading to a marked difference in size between sexes at already around 10 years in age33,37,38,39.The ontogenetic variation in growth projected for the MTS, when compared to what we known from extant proboscideans, is expressed in the track size distribution plot, with the definition of five age classes (Fig. 5; see also Table 1): calves under 2 years in age (when extant elephants experience fastest growth rates in both sexes), juveniles between 2 and 7 years in age (up to when elephant females reach their sexual maturity and therefore experience a strong reduction of growth rate in comparison to males), 7–15 years in age which include pre-puberty males and young female adults, over 15 years in age and  More

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    The biogeographic differentiation of algal microbiomes in the upper ocean from pole to pole

    Research cruisesThis dataset consists of sequence data from 4 separate cruises: ARK-XXVII/1 (PS80)—17th June to 9th July 2012; Stratiphyt-II— April to May 2011; ANT-XXIX/1 (PS81)—1st to 24th November 2012 and ANT-XXXII/2 (PS103)—16th December 2016 to 3rd February 2017 and covers a transect of the Atlantic Ocean from Greenland to the Weddell Sea (71.36°S to 79.09°N) (Supplementary Table 1). In order to study the composition, distribution and activity of microbial communities in the upper ocean across the broadest latitudinal ranges possible, samples have been collected during four field campaigns as shown in Fig. 1A. The first collection of samples was collected in the North Atlantic Ocean from April to May 2011 by Dr. Willem van de Poll of the University of Groningen, Netherlands and Dr. Klaas Timmermans of the Royal Netherlands Institute for Sea Research. The second set of samples was collected in the Arctic Ocean from June to July 2012, and the third set of samples was collected in the South Atlantic Ocean from October to November 2012. Both of which were collected by Dr. Katrin Schmidt of the University of East Anglia. The final set of samples was collected in the Antarctic Ocean from December 2016 to January 2017 by Dr. Allison Fong of the Alfred-Wegener Institute for Polar and Marine Research, Bremerhaven, Germany.SamplingWater samples from the Arctic Ocean and South Atlantic Ocean expeditions were collected using 12 L Niskin bottles (Rosette sampler with an attached Sonde (CTD, conductivity, temperature, depth) either at the chlorophyll maximum (10–110 m) and/or upper of the ocean (0–10 m). As soon as the rosette sampler was back on board, water samples were immediately transferred into plastic containers and transported to the laboratory. All samples were accompanied by measurements on salinity, temperature, sampling depth and silicate, nitrate, phosphate concentration (Supplementary Table 1). Water samples were pre-filtered with a 100 μm mesh to remove larger organisms and subsequently filtered onto 1.2 μm polycarbonate filters (Isopore membrane, Millipore, MA, USA). All filters were snap frozen in liquid nitrogen and stored at −80 °C until further analysis.Water samples from the North Atlantic Ocean cruise were also taken with 12 L Niskin bottles attached to a Rosette sampler with a Sonde. However, these samples were filtered onto 0.2 μm polycarbonate filters (Isopore membrane, Millipore, MA, USA) without pre-filtration but snap frozen in liquid nitrogen and stored at −80 °C as the other samples.Water samples from the Southern Ocean cruise were taken with 12 L Niskin bottles attached to an SBE911plus CTD system equipped with 24 Niskin samplers. These samples were filtered onto 1.2 μm polycarbonate membrane filters (Merck Millipore, Germany) in a container cooled to 4 °C and snap frozen in liquid nitrogen and stored at −80 °C as the other samples. Environmental data recorded at the time of sampling can be found in Supplementary Table 1.DNA extractions: Arctic Ocean and South Atlantic Ocean samplesDNA was extracted with the EasyDNA Kit (Invitrogen, Carlsbad, CA, USA) with modification to optimise DNA quantity and quality. Briefly, cells were washed off the filter with pre-heated (65 °C) Solution A and the supernatant was transferred into a new tube with one small spoon of glass beads (425–600 μm, acid washed) (Sigma-Aldrich, St. Louis, MO, USA). Samples were vortexed three times in intervals of 3 s to break the cells. RNase A was added to the samples and incubated for 30 min at 65 °C. The supernatant was transferred into a new tube and Solution B was added followed by a chloroform phase separation and an ethanol precipitation step. DNA was pelleted by centrifugation and washed several times with isopropanol, air dried and suspended in 100 μL TE buffer (10 mM Tris-HCl, pH 7.5, 1 mM EDTA, pH 8.0). Samples were snap frozen in liquid nitrogen and stored at −80 °C until sequencing.DNA extractions: North Atlantic Ocean samplesNorth Atlantic Ocean samples were extracted with the ZR-Duet™DNA/RNA MiniPrep kit (Zymo Research, Irvine, USA) allowing simultaneous extraction of DNA and RNA from one sample filter. Briefly, cells were washed from the filters with DNA/RNA Lysis Buffer and one spoon of glass beads (425–600 μm, Sigma-Aldrich, MO, USA) was added. Samples were vortexed quickly and loaded onto Zymno-Spin™IIIC columns. The columns were washed several times and DNA was eluted in 60 μmL, DNase-free water. Samples were snap frozen in liquid nitrogen and stored at −80 °C until sequencing.DNA extractions: Southern Ocean samplesDNA from the Southern Ocean samples was extracted with the NucleoSpin Soil DNA extraction kit (Macherey‐Nagel) following the manufacturer’s instructions. Briefly, cells were washed from the filters with DNA Lysis Buffer and into a lysis tube containing glass beads was added. Samples were disrupted by bead beating for 2 × 30 s interrupted by 1 min cooling on ice and loaded onto the NucleoSpin columns. The columns were washed three times and DNA was eluted in 50 μL, DNase-free water. Samples were stored at −20 °C until further processing.Amplicon sequencing of 16S and 18S rDNAAll extracted DNA samples were sequenced and pre-processed by the Joint Genome Institute (JGI) (Department of Energy, Berkeley, CA, USA). iTAG amplicon sequencing was performed at JGI with primers for the V4 region of the 16S (FW(515F): GTGCCAGCMGCCGCGGTAA; RV(806R): GGACTACNVGGGTWTCTAAT)49 and 18S (FW(565F): CCAGCASCYGCGGTAATTCC; RV(948R): ACTTTCGTTCTTGATYRA)50. (Supplementary Table 6) rRNA gene (on an Illumina MiSeq instrument with a 2 × 300 base pairs (bp) read configuration51. 18S sequences were pre-processed, this consisted of scanning for contamination with the tool Duk (US Department of Energy Joint Genome Institute (JGI), 2017,a) and quality trimming of reads with cutadapt52. Paired end reads were merged using FLASH53 with a max mismatch set to 0.3 and min overlap set to 20. A total of 54 18S samples passed quality control after sequencing. After read trimming, there was an average of 142,693 read pairs per 18S sample with an average length of 367 bp and 2.8 Gb of data over all samples.16S sequences were pre-processed, this consisted of merging the overlapping read pairs using USEARCH’s merge pairs54 with the parameter minimum number of differences (merge max diff pct) set to 15.0 into unpaired consensus sequences. Any reads that could not be merged are discarded. JGI then applied the tool USEARCH’s search oligodb tool with the parameters mean length (len mean) set to 292, length standard deviation (len stdev) set to 20, primer trimmed max difference (primer trim max diffs) set to 3, a list of primers and length filter max difference (len filter max diffs) set to 2.5 to ensure the Polymerase Chain Reaction (PCR) primers were located with the correct direction and inside the expected spacing. Reads that did not pass this quality control step were discarded. With a max expected error rate (max exp err rate) set to 0.02, JGI evaluated the quality score of the reads and those with too many expected errors were discarded. Any identical sequence was de-duplicated. These are then counted and sorted alphabetically for merging with other such files later. A total of 57 × 16S samples passed quality control after sequencing. There was an average 393,247 read pairs per sample and an average base length of 253 bp for each sequence with a total of 5.6 Gb.RNA extractions: Arctic Ocean and Atlantic samplesRNA from the Arctic and Atlantic Ocean samples was extracted using the Direct-zol RNA Miniprep Kit (Zymo Research, USA). Briefly, cells were washed off the filters with Trizol into a tube with one spoon of glass beads (425–600 μm, Sigma-Aldrich, MO, USA). Filters were removed and tubes bead beaten for 3 min. An equal volume of 95% ethanol was added, and the solution was transferred onto Zymo-Spin™ IICR Column and the manufacturer instructions were followed. Samples were treated with DNAse to remove DNA impurities, snap frozen in liquid nitrogen and stored at −80 °C until sequencing.RNA extractions: Southern OceanRNA from the Southern Ocean samples was extracted using the QIAGEN RNeasy Plant Mini Kit (QIAGEN, Germany) following the manufacturer’s instructions with on-column DNA digestion. Cells were broken by bead beating like for the DNA extractions before loading samples onto the columns. Elution was performed with 30 µm RNase-free water. Extracted samples were snap frozen in liquid nitrogen and stored at −80 °C until sequencing.Metatranscriptome sequencingAll samples were sequenced and pre-processed by the U.S. Department of Energy Joint Genome Institute (JGI). Metatranscriptome sequencing was performed on an Illumina HiSeq-2000 instrument27. A total of 79 samples passed quality control after sequencing with 19.87 Gb of sequence read data over all samples for analysis. This comprised a total of 34,241,890 contigs, with an average length of 503 and an average GC% of 51%. This resulted in 36354419 of non-redundant genes detected.JGI employed their suite of tools called BBTools55 for preprocessing the sequences. First, the sequences were cleaned using Duk a tool in the BBTools suite that performs various data quality procedures such as quality trimming and filtering by kmer matching. In our dataset, Duk identified and removed adaptor sequences, and also quality trimmed the raw reads to a phred score of Q10. In Duk the parameters were; kmer-trim (ktrim) was set to r, kmer (k) was set to 25, shorter kmers (mink) set to 12, quality trimming (qtrim) was set to r, trimming phred (trimq) set to 10, average quality below (maq) set to 10, maximum Ns (maxns) set to 3, minimum read length (minlen) set to 50, the flag “tpe” was set to t, so both reads are trimmed to the same length and the “tbo” flag was set to t, so to trim adaptors based on pair overlap detection. The reads were further filtered to remove process artefacts also using Duk with the kmer (k) parameter set to 16.BBMap55 is another a tool in the BBTools suite, that performs mapping of DNA and RNA reads to a database. BBMap aligns the reads by using a multi-kmer-seed-and-extend approach. To remove ribosomal RNA reads, the reads were aligned against a trimmed version of the SILVA database using BBMap with parameters set to; minratio (minid) set to 0.90, local alignment converter flag (local) set to t and fast flag (fast) set to t. Also, any human reads identified were removed using BBMap.BBmerge56 is a tool in the BBTools suite that performs the merging of overlapping paired end reads (Bushnell, 2017). For assembling the metatranscriptome, the reads were first merged with the tool BBmerge, and then BBNorm was used to normalise the coverage so as to generate a flat coverage distribution. This type of operation can speed up assembly and can even result in an improved assembly quality.Rnnotator52 was employed for assembling the metatranscriptome samples 1–68. Rnnotator assembles the transcripts by using a de novo assembly approach of RNA-Seq data and it accomplishes this without a reference genome52. MEGAHIT57 was employed for assembling the metatranscriptome samples 69–82. The tool BBMap was used for reference mapping, the cleaned reads were mapped to metagenome/isolate reference(s) and the metatranscriptome assembly.Metatranscriptome analysisJGI performed the functional analysis on the metatranscriptomic dataset. JGI’s annotation system is called the Metagenome Annotation Pipeline (MAP) (v4.15.2)27. JGI used HMMER 3.1b258 and the Pfam v3059 database for the functional analysis of our metatranscriptomic dataset. This resulted in 11,205,641 genes assigned to one or more Pfam domain. This resulted in 8379 Pfam functional assignments and their gene counts across the 79 samples. The files were further normalised by applying hits per million.18S rDNA analysisA reference dataset of 18S rRNA gene sequences that represent algae taxa was compiled for the construction of the phylogenetic tree by retrieving sequences of algae and outgroups taxa from the SILVA database (SSUREF 115)60 and Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP) database61. The algae reference database consists of 1636 species from the following groups: Opisthokonta, Cryptophyta, Glaucocystophyceae, Rhizaria, Stramenopiles, Haptophyceae, Viridiplantae, Alveolata, Amoebozoa and Rhodophyta. A diagram of the 18S classification pipeline can be found in Supplementary Fig. 1. In order to construct the algae 18S reference database, we first retrieved all eukaryotic species from the SILVA database with a sequence length of  > = 1500 base pairs (bp) and converted all base letters of U to T. Under each genus, we took the first species to represent that genus. Using a custom written script (https://github.com/SeaOfChange/SOC/blob/master/get_ref_seqs.pl), the species of interest (as stated above) were selected from the SILVA database, classified with NCBI taxa IDs and a sequence information file produced that describes each of the algae sequences by their sequence ID and NCBI species ID. Taxonomy from the NCBI database, eukaryote sequences from the SILVA database and a list of algal taxa including outgroups were used as input for the script. This information was combined with the MMETSP database excluding duplications.The algae reference database was clustered to remove closely related sequences with CD-HIT (4.6.1)62 using a similarity threshold of 97%. Using ClustalW (2.1)63 we aligned the reference sequences with the addition of the parameter iteration numbers set to 5. The alignment was examined by colour coding each species to their groups and visualising in iTOL64. It was observed that a few species were misaligning to other groups and these were then deleted using Jalview65. The resulting alignment was tidied up with TrimAL (1.1)66 by applying parameters to delete any positions in the alignment that have gaps in 10% or more of the sequence, except if this results in less than 60% of the sequence remaining. A maximum likelihood phylogenetic reference tree and statistics file based on our algae reference alignment was constructed by employing RaxML (8.0.20)67 with a general time reversible model of nucleotide substitution along with the GAMMA model of rate heterogeneity. For a description of the lineages of all species back to the root in the algae reference database, the taxa IDs were submitted for each species to extract a subset of the NCBI taxonomy with the NCBI taxtastic tool (0.8.4)68 Based on the algae reference multiple sequence alignment, with HMMER3 (3.1B1)69 a Profile HMM was created. A pplacer reference package using taxtastic was generated, which produced an organized collection of all the files and taxonomic information into one directory. With the reference package, a SQLite database was created using pplacer’s Reference Package PReparer (rppr). With hmmalign, the query sequences were aligned to the reference set and created a combined Stockholm format alignment. Pplacer (re-aligned to the reference set and created a combined Stockholm format alignment. Pplacer (1.1)70 was used to place the query sequences on the phylogenetic reference tree by means of the reference alignment according to a maximum likelihood model70 The place files were converted to CSV with pplacer’s guppy tool; in order to easily take those with a maximum likelihood score of  > = 0.5 and counted the number of reads assigned to each classification. This resulted in 6,053,291 reads that were taxonomically assigned being taken for analysis.Normalisation of 18S rDNA gene copy number18S rDNA gene copy number vary widely among eukaryotes. In order to create an estimate of abundances of the species in the samples the data had to be normalised. Previous work has explored the link between copy number and genome size71. However, there is not a single database of 18S rDNA gene copy numbers for eukaryote species. In order to address this, gene copy number and related genome sizes of 185 species across the eukaryote tree was investigated and plotted (Supplementary Fig. 2, Supplementary Table 4)68,71,72,73,74,75,76,77,78,79. Based on the log transformed data, a significant correlation with a R2 of 0.55 with a p-value  More