Euxinic conditions and altered biogeochemical cycles in a Patagonian fjord influenced by tectonic activity

Euxinic conditions and altered biogeochemical cycles in a Patagonian fjord influenced by tectonic activity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Euxinic conditions and altered biogeochemical cycles in a Patagonian fjord influenced by tectonic activity Iván Pérez-Santos, Paulina Montero, Marcelo H. Gutiérrez, Gerdhard L. Jessen, and 19 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8735657/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Fjords in Chilean Patagonia are highly dynamic systems shaped by land-derived inputs, oceanic exchange, and tectonic activity. Prior to the elaboration of the present article, no in-depth investigation had been undertaken into the anoxic or euxinic conditions of fjords in this region. Consequently, the present research represents an interdisciplinary oceanographic approach to studying Quitralco Fjord (45.6° S, 73.1° W; 2022–2025) and provides the first evidence of a volcanically influenced euxinic fjord in Chilean Patagonia. A subsurface anoxic layer, beginning between 90 and 120 m and extending to the basin floor (~ 160 m), was shown to exhibit elevated temperatures and high concentrations of H 2 S, consistent with inputs of volcanically derived fluids. A bubble-like acoustic scattering and the detection of CH 4 within this layer suggest an external input of the gas into the water column. Although largely stagnant, this layer shifted vertically over time, likely driven by interannual deep-water renewal. Within the euxinic layer, nitrate was completely depleted, while high phosphate (20 µM) and ammonium (25 µM) concentrations indicated an active sulfur cycle. A pronounced deep fluorescence maximum was also detected in the dark, anoxic basin, attributed to fluorescent dissolved organic matter (fDOM) dominated by two humic-like components (C1 245(350)-440 and C3 270(400)-505 ) with high aromaticity. Microbial community composition changed markedly across the redox gradient, while geochemical and microbiological fingerprints exhibited shifts in metabolic potential through the water column. The geological emissions of H 2 S from the seabed likely enhance and sustain the euxinic conditions, thereby strongly influencing the biogeochemical cycles of the basin. Overall, the present study reveals a previously unrecognized link between volcanic activity and fjord biogeochemistry, documenting for the first time the development of euxinic conditions in a Patagonian fjord in Chile. Earth and environmental sciences/Biogeochemistry Earth and environmental sciences/Climate sciences Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Ocean sciences Earth and environmental sciences/Solid earth sciences Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Fjord ecosystems constitute key transition zones in aquatic systems 1 and further investigation into the natural and anthropogenic physical, biological, and chemical processes that govern their functioning are therefore warranted. One recently discovered process affecting Patagonian fjords is the deoxygenation of deep water 2 , primarily due to the advection of low-oxygen water from the equatorial region. While hypoxic conditions have been reported 3, 4, 5, 6 in certain areas, such as the Puyuhuapi Fjord, anoxia has never previously been recorded due to the occurrence of deep water ventilation 7, 8 . Accordingly, residence-time mapping has revealed values of 100 to 250 days in Patagonian fjords that were previously reported to exhibit hypoxic waters with particularly low levels of dissolved oxygen 6 . Furthermore, anoxic conditions have been recorded in recent years at the head of Quitralco Fjord, located in the northern Patagonian fjord system (Fig. 1 b-c), where marine current velocities are close to 0 cms − 1 and residence times exceed 200 days (Fig. 1 e-f). The present article is motivated by the occurrence of anoxic waters and the processes that underlie the development of euxinic conditions, as indicated by elevated hydrogen sulfide concentrations at depth. Quitralco Fjord is located 45.7° South and 73.4° West in the northern Patagonian fjord system. It is ~ 50 km in length and 3 km wide and its orientation is northeast toward the Andes (Fig. 1 d). It is located in an active volcanic region 9, 10 and a new active volcano was recently discovered in this area, the Mate Grande Volcano, located just 7 km from the head of the fjord (Fig. 1 c). The Hudson Volcano (previous eruption 2011) is located 30 km south of the fjord, while the Maca and Cay volcanoes lie 60 km to the north 10 . In the research conducted by De Pascale, the Liquiñe-Ofqui fault zone (LOFZ) was found to extend north of the Patagonian region, traversing the underwater area of the head of Quitralco Fjord. However, faults could not be readily detected using remote sensing techniques 10 . From an oceanographic perspective 6 , reported low dissolved oxygen water (LDOW) (30 − 60% saturation) and hypoxic conditions (less than 30% saturation, 2 mL − 1 L 6 , 2.8 mg L − 1 , 89.3 mM) in Quitralco Fjord in November 2020. The LDOW readings were taken from waters between the mid-point of the fjord and the head, at a depth of 20 m, while hypoxia was observed in waters near the head and from a depth of between 150 m to the seabed (250 m). Four primary mechanisms were proposed as contributing to deep-water hypoxia in Quitralco Fjord: (1) weak deep-water circulation (Fig. 1 e); (2) shorter residence times (Fig. 1 f); (3) elevated dissolved oxygen (DO) consumption driven by community respiration; and (4) increased inputs of allochthonous organic matter associated with river discharges. Subsequent recent investigations have focused on the fjord head and have revealed a previously unreported feature of the Patagonian fjord system: deep-water anoxia extending from 100 m depth to the seabed (160 m), accompanied by hydrogen sulfide accumulation, likely driven by emissions from the basin floor into the water column. It should be noted that an environment is classified as euxinic when anoxic conditions coincide with sulfide concentration levels exceeding 0.1 µM 11 . The mechanisms driving the euxinic conditions observed in Quitralco Fjord remain unresolved, thus motivating the present investigation to be conducted into a unique ecosystem in which tectonic and anthropogenic activities, including salmon aquaculture, converge. Euxinic conditions have been present during key periods of Earth’s history, when the deep ocean became anoxic and hydrogen sulfide accumulated to toxic levels 12 . Although the cause of prolonged euxinia in the past has been debated, the general underlying mechanism is attributed to the predominance of anaerobic oxidative metabolism in the absence of DO and an abundance of organic matter. Under such conditions, microbial metabolism shifts to sulphate reduction, producing hydrogen sulfide as a metabolic end product 13 . Although scarce in the ocean today, permanent euxinic environments do exist under particular conditions in certain seas 11 , with the most notable example being the Black Sea 14 . In this particular environment, anoxic conditions result from a combination of strong stratification and low ventilation linked to high oxygen consumption, which are, in turn, associated with elevated rates of primary productivity 12 . Euxinic conditions can also be transient and in several marine basins they follow seasonal productive cycles. However, persistent anoxic and euxinic environments can be found in bodies of water in which there is restricted ventilation, such as silled basins, including certain fjords 15, 16 . Once oxygen and nitrate are depleted during organic matter oxidation, microbial sulfate reduction becomes the dominant remineralization pathway in suboxic and anoxic bottom waters, leading to hydrogen sulfide accumulation. Accordingly, phosphate and sulfide concentrations are expected to covary during organic matter decomposition (Shen et al., 2002), while ammonium accumulates as a product of remineralization. This coupling reflects the tight linkage between nutrient regeneration and redox dynamics in poorly ventilated fjord systems, where nutrient trapping and high primary productivity sustain intense oxygen consumption in deep waters, potentially triggering euxinic conditions. Additionally, groundwater discharge or tectonic activity may result in the introduction of additional sulfur, often in the form of sulfate and sulfide, into fjords, allowing H₂S accumulation independently of organic matter decomposition 12 . Fjords are generally well ventilated. However, the bathymetry and occurrence of high productivity in certain basins contribute to the development of deep-water oxygen-deficiency. Anoxia has also been documented in fjord systems; for example 15 , reported persistent anoxia in Nitinat Lake (48.7°N, 124.75°W) in British Columbia, Canada. In general, an active population of sulfur bacteria can be observed in these and other oxygen-deficient environments 17, 18, 19 . Certain Patagonian fjords have exhibited tectonic inputs of reduced fluids (CH₄, H₂S). In Chile, Comau Fjord hosts shallow cold vents and chemosynthetic communities, evincing strong reductant supply 20 . In contrast, the Almirante Montt Gulf (51.8° S/72.8° W) exhibits a pockmarked seabed and gas flares near the fjord entrance, where biogenic methane is released from gas-rich sediments, consistent with active sedimentary methanogenesis and seepage 21 . Across such systems, CH₄, H₂S and other reductant inputs may fuel vigorous chemoautotrophic oxidation (methanotrophy, sulfur oxidation, and in places Fe/Mn cycling), creating “oxidative filters” in redox transition zones that consume additional DO 22 . These oxidative filters are modulated by stratification, residence time, and the supply of electron acceptors (O₂, NO₃⁻/NO₂⁻, SO₄²⁻, resulting in steep redox gradients consistent with observations from Canadian and Scandinavian fjords 23, 22, 24, 16 . As a previously unexplored system, Quitralco Fjord affords researchers a new area in which to investigate the influence of tectonic activity on oceanographic-biogeochemical processes and, as such, prompts the following research questions: (1) Do sulfur-oxidizing or sulfate-reducing bacteria that support anoxygenic chemosynthesis occur in the deep water column? (2) Which species of sulfur bacteria are present in the anoxygenic layer? (3) Are the anoxic/euxinic conditions exhibited in Quitralco Fjord driven primarily by natural processes or anthropogenic forcing? (4) On what timescales do anoxic conditions develop and persist? (5) To what extent does the euxinic condition influence biogeochemical cycling? The primary objective of the present article is to elucidate the mechanisms that contribute to the anoxic and euxinic conditions in Quitralco Fjord and their impact on biogeochemistry. To answer these questions, in situ measurements of CTDO, trace oxygen concentrations using microsensors, biogeochemical parameters, and microbial community composition were collected along the fjord between2022 and 2025. 2. Results 2.1. Hydrographic conditions. Hydrographic measurements taken along the fjord revealed well-oxygenated waters in the surface layer (0–50 m) throughout Quitralco Fjord (Fig. S2a-g), and similarly ventilated conditions at the fjord mouth. In the subsurface layer, oxygenated waters increased toward the fjord head along the 180 µM isoline, contributing to deep-water ventilation, particularly during the 2024 seasonal expeditions (Fig. S2d-g). Nevertheless, persistent anoxic conditions were observed year-round in the fjord head (station E8), with the upper limit varying between sampling periods (Fig. 2 e). While surface water temperatures responded to the seasonal solar radiation cycle, colder waters were observed in the subsurface layer from the fjord head to the mid-fjord area, coinciding with ventilation events that occurred during 2024 (Fig. S2h-n). In contrast, the highest temperatures were observed in the anoxic deep basin (station E8), while cooler deep waters were confined to the mid-fjord and the head regions (Fig. 2 b). Seasonal hydrographic profiles of DO, fluorescence, and water turbidity collected between August 2022 and July 2025 revealed significant features of the anoxic basin in the fjord (Fig. 2 ): (1) Deep-water temperatures (down to 100 m) exceeded those of the inner-subsurface layers (Fig. 2 a) by ~ 0.5°C, with values of ~ 11°C near the seabed (Fig. 2 b). (2) Salinity and density ranged from 21 to 31 and 18−24.5 kg m -3 , respectively, indicating the dominance of a single water mass type: estuarine water mass (Fig. 2 c and 2 d). (3) A peak of fluorescence and turbidity was observed at the anoxic basin (Fig. 2 g), while the position of the deep-oxycline modulated the dynamics of the deep fluorescence and turbidity records across seasonal expeditions (Fig. 2 g and 2 h). Dissolved oxygen was measured using a conductivity, temperature and depth oxygen (CTDO) optical sensor, revealing minimum DO values of 0.5 µM (0.018 mg L -1 , 0.012 ml L -1 ) and 0.2% saturation at a depth greater than 90 m. The position of the anoxic boundary layer (oxycline) in the water column varied over time, registering a vertical displacement of up to 36 m. The absolute minimum and maximum depth of oxycline were observed in June and August 2023, at 92 m and 126 m, respectively (Fig. 2 d). (4). Because standard optical oxygen sensors are limited to concentrations above 1 µM (e.g., Fig. 2 e), a trace oxygen profiler instrument (uTail model) was used to measure oxygen values in the anoxic layer at depths of 120 − 160 m |(Fig. 2 f). Results from the uTail readings revealed a sharp decrease in oxygen concentrations between 118.1 m and 121.8 m (Fig. S1 ). Below these depths, oxygen levels dropped to < 10 nM at ~ 140 m and continued dropping to approximately 5 nM at 160 m. Overall, average oxygen concentrations of 8.19 ± 2.48 nM were observed in the anoxic layer, with minimum and maximum values of 4.94 nM and 11.44 nM, respectively (Fig. 2 f and Fig. S1 ). A deep fluorescence maximum (~ 4 ppb) was detected in the anoxic layer, comparable in magnitude to the surface-layer fluorescence (Fig. 2 g). (5) A deep-turbidity peak coincided with the deep-oxicline position and the deep fluorescence maximum at all times (Fig. 2 h). 2.2. Acoustic records. The backscattering acoustic signal in the anoxic basin revealed the strongest signal at a depth of approximately 60 − 80 m during daytime (Fig. S3a). This signal ascended at 18:00 h (local time), reached the surface layer between 21:00 and 06:00 h, and exhibited a diel vertical migration (DVM) pattern characteristic of zooplankton. A strong second signal was observed at 120 m, particularly during daylight hours, with a portion of it ascending to ~ 60 m at night, prior to continuing its upward migration until 06:00 h. In addition, a third acoustic signal was detected within the anoxic-euxinic layer, appearing as an intermittent, upward-moving event that resembled gas emissions from the seabed up to a depth of ~ 120 m, between 03:00 and 08:00 h (Fig. S3a); this phenomenon is discussed further in section 4. In-situ macrozooplankton sampling at differing depth strata corroborated the acoustic observations, revealing a pronounced concentration between 100 m and 120 m depth during nighttime (22:00 − 23:00 h), with lower concentrations in shallower layers. The sampled community was dominated by copepods, siphonophores, and euphausiids (Fig. S3b). A similar pattern emerged when zooplankton was grouped by size (> 5 mm, corresponding to the particle size detected by the 300 kHz ADCP used in the present study), with chaetognatha, total euphausiids, siphonophores, and mysidacea being the most abundant (Fig. S3c). Macrozooplankton groups were also present in the anoxic layer, although the anoxic boundary layer at 126 m in October 2024, which may have influenced the zooplankton samples. When the ADCP was redeployed at the same location in December 2024, the DVM pattern remained consistent, although the new dataset revealed multiple gas-emission events (Fig. S3d). 2.3. Evidence of tectonic activity. Surface-sediment analyses showed the highest heavy-metal concentrations at the head of the fjord (stations E7 and E8), particularly in the anoxic basin (Fig. S4, station E8). In this area, heavy metals typically associated with tectonic activity, such as Fe, Mg, Cr, and Cu, were found at elevated levels, with median values of 88.70, 11.14, 1.07, and 0.70 µg kg − 1 , respectively (Fig. S4a-d). These concentrations were approximately four orders of magnitude higher than those in the remainder of the study area, for example, median values of 22.40, 2.81, 0.09, and 0.17 µg kg − 1 for Fe, Mg, Cr, and Cu were observed, respectively (Fig. S4). 2.4. Biogeochemical parameters. Biogeochemical parameters were measured throughout the water column with high vertical resolution (every 10 m) across the anoxic layer (Fig. 3 a). Hydrogen sulfide (∑H 2 S) concentrations were extremely elevated below 120 m, increasing from 35 to 112.9 µM, (maximum value) at 150 m in October 2024 (Fig. 3 b). In contrast, concentrations of nitrate < 11 µM, nitrite < 1 µM, and phosphate < 2 µM were primarily confined to the upper 15 m of the water column at both sampling stations (E7 and E8) (Fig. 3 c- 3 e). Below this layer, at depths of between 25 and 100 m, nitrate concentrations fluctuated between 14 and 25 µM (Fig. 3 c and 3 d), while phosphate concentrations ranged between 2 and 3 µM (Fig. 3 e). In deep waters (100 − 150 m) at station E8 (anoxic basin), nitrate decreased to below detection limits (ca. 0 µM), whereas nitrite levels increased, particularly in December 2024, at which point they reached ~ 1.4 µM. Phosphate levels also ​​rose in this layer to 20 µM. This pattern was not observed at the control station E7, where nitrate ranged from between 15 and 18 µM, nitrite from between 0.1 and 0.5 µM, and phosphate remained constant at approximately 2 µM, with values distributed homogeneously throughout the water column. Silicate concentrations at station E7 were relatively uniform throughout the water column (11 − 23 𝜇M), with a minimum of 4 µM at 5 m depth (Fig. 3 f). At station E8, silicate concentrations were observed at < 12 µM mainly within the upper 25 m, with a minimum of 1 µM at 5 m. However, between 50 and 150 m depth, silicate concentrations ​​increased progressively from 24 to 102 µM (Fig. 3 f). At station E8, ammonium concentrations were low (0.5 to 0.9 µM) from the surface to 100 m, increasing below this depth up to 25 µM at 150 m (Fig. 3 g). The nitrogen deficit (N*) exhibited a vertical pattern similar to that of nitrate, reaching extreme maximum values exceeding − 200 µM in the deep anoxic zone (Fig. 3 h). Dissolved organic carbon (DOC) concentrations in surface waters (0 − 5 m) exceeded 140 µM in both sampling stations (E7 and E8). Between 10 and 100 m depth, DOC ranged from 85 to 110 µM at station E7 and from 80 to 130 µM at station E8. In contrast, in deep waters (120 − 150 m) DOC increased from 120 to 185 µM at E8, while values decreased considerably at E7 (Fig. 3 i). Chlorophyll-a concentrations at both stations were high (0.8 − 2.7 mg L -1 ) in the surface layer (0 − 10 m) and low (< 0.6 mg L -1 ) at depths of 15 − 150 m. Maximum concentrations of 2.7 and 1.6 mg L -1 were observed at a 5 m depth in both sampling stations (Fig. 3 j), coinciding with minimum silicate values. In Quitralco Fjord, the N₂O profile (Fig. 3 k) shows equilibrium surface N 2 O values (~ 12–14 nmol L⁻¹) that increase sharply at intermediate depths, peaking at ~ 49.5 nmol L⁻¹ at approximately 100 m, where nitrate consumption begins. Below 120 m, concentrations decreased rapidly and reached near-zero at 150 m, indicating complete denitrification to N₂. It should be noted that no nitrite accumulation was observed, underscoring complete NO 3 - reduction to N 2 , as well as the efficiency of the redox transition, in addition to marking the establishment of anoxic–euxinic conditions. Dissolved CH 4 concentrations exhibited a pronounced vertical gradient (Fig. 3 l), from 10 nmol L -1 in surface waters to approximately 19.200 nM at 150 m. 2.5. Optical properties of dissolved organic matter. Figure 4 shows the absorption spectra obtained at stations E7 and E8. At E8, absorption coefficients were higher, between 130 and 150 m, than at the surface layer (Fig. 4 a). In contrast, at E7, higher values were obtained at the surface layer (0 − 5 m) (Fig. 4 b). CDOM 325 exhibited elevated values (2 − 4 m − 1 ) in the upper 5 m of the water column at both sampling stations (Fig. 4 c). Below this depth, values ​​ranged between 0.8 and 1.5 m − 1 , except at station E8 at depths of 120 − 150 m, where they ​​increased from 3 to 8 m − 1 (Fig. 4 c). The SUVA 254 values exhibited a pattern similar to that of CDOM 325 at both sampling stations, with increased values of 3 to 5 mg C L − 1 m − 1 in surface waters (0 − 5 m) and lower levels (< 3 mg C L − 1 m − 1 ) throughout the remainder of the sampling depths. An exception was observed at station E8, where elevated values from 5 to 9 mg C L − 1 m − 1 were recorded in deep waters (120 − 150 m) (Fig. 4 d). Fluorescence intensity was higher at station E8 than at E7, particularly in deep waters. At E8, values ranged from 0.1 to 8.4 RU, while at E7 they varied between 0.1 and 3.1 RU throughout the water column (Fig. 4 e and 4 f). The highest fluorescence values ​​were recorded by component C1 and the lowest by component C4 at both sampling stations. Fluorescence intensity profiles were similar between the surface layer and 120 m at E7 and E8, except at 100 m, where component C4 at station E8 reached a maximum of 4.4 RU (Fig. 4 e). Below 120 m, fluorescence intensities of components C1, C2, and C3 revealed values that ​​exceeded 2 RU at station E8. In contrast, values < 2 RU were recorded at E7 (Fig. 4 e and 4 f). The Parallel Factor (PARAFAC) analysis identified four fluorescent dissolved organic matter (fDOM) components (C1, C2, C3, and C4) in the study area, explaining 96.9% of the variance in the dataset (Fig. S5). Based on findings from peak locations and literature comparisons, fDOM components were classified as follows: two humic-like (C1 and C3), one marine humic-like (C2), and one protein-like (C4) components (Table 1 ). The first (C1, Ex/Em = 245(330)/440 nm) and third (C3, Ex/Em = 270(400)/505 nm) humic-like components exhibited two fluorescence peaks (Table 1 , Fig. S5), characteristic of allochthonous terrestrial material, likely derived from terrestrial plants. The second component (C2), classified as marine humic-like, also exhibited two fluorescence peaks (Ex/Em = 245(330)/440 nm) and is most likely associated with an autochthonous microbial source. Finally, component C4 (Ex/Em = 275/302 nm) showed a protein-like (tyrosine-like) fluorescence peak, characteristic of a soluble autochthonous source produced in an aquatic environment (Fig. S5). Table 1 PARAFAC analysis. The reference peak component from 25, 26 . PARAFAC Type Name double peak Excitation (range Ex) maximum Emission (range Em) maximum Region (Chen et al., 2003) Source Component 1 UV humic-like First peak (A) (245 − 250) 245 (430 − 460) 440 III fulvic Terrestrial allochthonous Visible humic-like Second peak (C) (310 − 350) 330 (430 − 460) 440 V humic Component 2 UV humic-like First peak (A) (245 − 250) 245 (370 − 395) 382,5 III fulvic Microbial autochthonous Visible marine humic-like Second peak (M) (280 − 315) 290 (370 − 395) 382,5 V humic Component 3 UV humic-like First peak (A) (260 − 280) 270 (485 − 520) 505 V humic Terrestrial allochthonous Visible humic-like Second peak (C+) (380 − 415) 400 (485 − 520) 505 V humic Component 4 Tyrosine-like, Protein-like peak (B) (270 − 280) 275 (295 − 305) 302,5 IV soluble microbial Autochthonous 2.6. Microbial community structure and composition. Prokaryote abundance ranged from 149,590 ± 43,956 to 550,714 ± 63,372 cells mL − 1 . Maximum abundances were observed in surface waters, decreasing to minimal values between 120 and 130 m (< 250,000 cells mL − 1 ), and increasing once more to approximately 300,000 cells mL − 1 in anoxic waters below 140 m (Fig. 5 a). Regarding prokaryote community diversity, a total of 2,075,016 16S rRNA gene sequences, produced by Illumina sequencing, were analyzed following resampling by rarefaction, corresponding to 3,241 and 13,396 amplicon sequence variants (ASVs) for archaea and bacteria, respectively. Rarefaction curves indicated that the sampling effort exceeded the curvilinear phase, with all samples reaching a plateau (Supplementary Fig. 6). Alpha diversity at station E8 ranged from 679 to 3,548, with the highest ASV richness (> 1,700) observed in anoxic waters (> 120 m; Fig. 5 a). At the order level, between 44 and ~ 60% of the prokaryote community in anoxic waters comprised bacterial groups, including Bacteroidetes, Arcobacteraceae, Latescibacterota, Desulfobacterales, Brocadiales, and Desulfatiglandales as well as the archaean domine of Nanoarchaeota, grouped in Woesearchaeales (Supplementary Fig. 7). In oxic waters, bacteria of the orders Flavobacteriales, the SAR11 clade, and Thiomicrospirales, in conjunction with archaea belonging to Nitrosopumilales and Marine Group II accounted for more than 45% of the prokaryote community in waters between 0 and 110 m (Supplementary Fig. 7). At the ASV level, members of the VC2.1 clade of Bacteroidetes, Acrobacteracea, Latescibacterota, SUP05, the Candidatus Scalindua, and two members of the genus Desulfatiglans were the most abundant bacterial taxa in anoxic waters (Fig. 5 b). Regarding archaea, representative ASVs were more abundant in oxic (10 − 110 m) than in anoxic waters, with a predominance of Candidatus Nitrosopumilus, Candidatus Nitrosopelagicus, and Marine Group II (Fig. 5 c). In anoxic waters, representative archaeal taxa included two members of Candidatus Nitrosopumilus and a member of the Woesearchaeales and Bathyarchaeia groups (Fig. 5 c). Analysis of full-length 16S sequences revealed differences in bacterial community composition between the anoxic waters of station E8 and the deep oxic waters of control station E7 (Fig. 5 D). In the anoxic waters of station E8, the most abundant and distinctive bacterial taxa related to members of the genera Desulfobacula , Desulfatiglans , Desulfotignum , Desulfobacter , Arcobacter , and Malaciobacter , together accounting for more than 70% of the representative sequences (Fig. 5 d). 3. Discussion Quitralco Fjord has been reported as one of the areas within the Patagonian fjord system experiencing hypoxic conditions, primarily due to prolonged water residence time (Fig. 1 f) and the dominance of community respiration, which promotes a decrease in dissolved oxygen concentrations6. Moreover, during oceanographic expeditions that covered the entire fjord, anoxic conditions were observed in the deep layer at the fjord head (90 − 160 m), exhibiting oxygen concentrations of approximately 10 nM (Fig. 2 ). This trace oxygen level is considered anoxic according to 27 . As noted in the Introduction section, Quitralco Fjord is influenced by tectonic activity associated with the Liquiñe-Ofqui fault line that lies underneath the fjord head and is bounded by the surrounding volcanoes (Fig. 1 ). Elevated deep-water temperatures (~ 11° C, Fig. 2 a-b), high H 2 S concentrations (~ 100 µM, Fig. 3 b), and gas bubble emissions detected acoustically (Fig. S3) provide evidence of tectonic activity in the anoxic-euxinic Quitralco basin. Furthermore, elevated concentrations of heavy metals in surface sediments (for example, Fe, Mg, and Cu; Fig. S4) support the hypothesis of the influence caused by tectonic activity on the study area. However, the principal results of the present study stem from the detection of a deep fluorescence maximum (DFM) in a dark environment, as well as the influence of tectonic activity on biogeochemical cycles and the microbial community (Fig. 6 ), which are discussed in the following section. 3.1. Deep fluorescence maximum (DFM) . A DFM was consistently detected using a vertical microprofiler in the dark, deep anoxic basin of Quitralco Fjord, with a magnitude comparable to that measured at the photic surface layer (Fig. 2 g). The DFM exhibited vertical displacement in synchrony with the anoxic boundary layer, where turbidity also displayed a deep maximum (Fig. 2 e, 2 g, and 2 h). The surface fluorescence maximum recorded in October 2024 can be attributed to elevated surface Chl-a or fDOM concentrations. However, Chl-a concentrations (close to 0 mg L − 1 ) do not account for the deep fluorescence profile behaviour (Fig. 3 j). Rather, fDOM values with humic-like components (C1, C2 and C3) revealed maximum fluorescence within the anoxic layer, while the protein-like component (C4) peaked at 100 m. C4 maximum is likely associated with fresh, autochthonous (aquatic) and microbially-derived DOM material, as indicated by high biological fluorescence index (BIX) values (> 1, data not shown). In contrast, components C1, C2 and C3 are primarily associated with humic material and weak recent autochthonous inputs, as shown by the humification (HIX) index values (6 − 13, data not shown). DOM is one of the Earth’s major carbon reservoirs 28 . The fraction of DOM that absorbs light, known as chromophoric DOM (CDOM), and its fluorescent sub-fraction (fDOM) are ubiquitous constituents of the aquatic DOM pool, strongly influencing the optical properties of the water column 29 . In coastal environments, CDOM and fDOM typically exhibit profiles with high surface concentrations that decrease rapidly with depth 30 . This vertical pattern reflects the primary sources of DOM, i.e., photosynthesis from the surface layers and terrestrial inputs from rivers. Although a portion of this organic material is labile and rapidly degraded or photodegraded, a significant proportion is refractory and resistant to decomposition. In Quitralco Fjord, measurements from control station E7 exhibited findings with a vertical profile consistent with that described above, with elevated concentrations of CDOM 325 (2 − 4 m − 1 ), SUVA 254 (3 − 5 mg L −1 m − 1 ), fDOM (0.15 − 3 RU) and absorption 250−350 (5 − 10 m − 1 ) within the upper 5 m. These patterns indicate that DOM is of primarily terrestrial origin, characterized by high molecular weight, a high aromaticity and elevated concentrations of allochthonous humic compounds (C1 and C3). This suggests an active transformation of DOM within the water column by means of the actions of the bacterial community (C2). At station E8, similar surface values of CDOM 325 (2 − 3 m − 1 ), SUVA 254 (3 − 4 mg L − 1 m − 1 ), fDOM (0.15 − 3 RU), absorption 250−350 (5 − 8 m − 1 ) in addition to the same terrestrial characteristics of DOM were observed. However, all variables reached their maxima in deep anoxic waters, with a CDOM 325 of 4 − 8 m − 1 , a SUVA 254 of 4 − 9 mg L −1 m − 1 , an fDOM of 1.5 − 8 RU, and an absorption 250−350 of 15 − 18 m − 1 . These values ​​constitute the highest reported to date for deep waters in the Chilean fjord system. No previous information has been published with regards to optical properties of Quitralco Fjord. 31 reported CDOM 325 values for Puyuhuapi Fjord ​​within a similar range and vertical pattern to those observed in the present study at station E7. Additional measurements from Puyuhuapi Fjord and the Caleta Tortel area (unpublished data) also exhibit ranges and profiles comparable to those described for station E7. The maximum fDOM values ​​observed, particularly with regards to components C1 and C3 at E8, suggest that the anoxic waters of Quitralco Fjord contain substantial concentrations of highly refractory humic organic material capable of generating a DFM. Anomalies from the classical pattern of optical properties in the water column have been recorded in different aquatic ecosystems, including coastal and oceanic environments in the Northern Hemisphere, where elevated CDOM and fDOM levels have been observed in greater detail 32, 33, 34, 35 . These observations suggest that within these deep waters there may be: i) local DOM production through mineralization of organic matter; ii) accumulation of refractory DOM; and iii) upward diffusion of DOM. Indeed, marine sediments are considered an important source of DOM to overlying seawater, comparable in magnitude to riverine input 36 . In Quitralco Fjord, all these processes may contribute to the anomalous distribution of CDOM and fDOM in the water column, particularly given the euxinic characteristics of the basin. Such characteristics may result from microbial mineralization of DOM in deep waters, which consumes oxygen (leading to hypoxia/anoxia conditions) and releases hydrogen sulfide as a metabolic by-product 37 . In addition, the presence of sulfate-reducing bacteria (Fig. 5 d) also plays an important role in the formation of humic-like substances 34 , ultimately leading to substantial alterations in DOM composition 38 . 3.2. Biogeochemical conditions and microbial community structure, and their association with tectonic activity. The high concentrations of H 2 S detected in the deep anoxic layer (120 − 150 m) of Quitralco Fjord reveal a previously unrecognized euxinic ecosystem that should be considered in the global distribution of such environments 11 . This system is an ideal area in which to improve understanding around the microbial community structures and biogeochemistry (BGC) in fjord systems associated with tectonic activity (Fig. 3 ). The Black Sea remains the region with the highest reported H 2 S concentrations (200 − 400 𝜇M), largely driven by sulfate-reducing bacteria activity 39 . However, H 2 S concentrations recorded at between 50 − 100 𝜇M in the deep anoxic basin of Quitralco Fjord (Fig. 3 b) exceed the values observed in the Baltic Sea (7 − 23 𝜇M; 40 ) as well as the By Fjord (10 𝜇M) in the western Sweden 41 . While the origin of these reduced sulfate compounds (∑H 2 S) appears to be primarily linked to tectonic activity, the presence of sulfate-reducing communities likely also contributes to the substantial accumulation of H 2 S. Nitrous oxide (N₂O) is a sensitive tracer of suboxic and anoxic processes, as it accumulates during nitrification–denitrification coupling but is consumed when complete denitrification to N₂ prevails. N 2 O is also a potent greenhouse gas and an ozone depleting agent, and its net production or consumption is strongly modulated by temporal and vertical oxygen gradients and the availability of nitrogen species 42 . For example, in Saanich Inlet, British Columbia, Canada, one of the most intensively studied seasonally anoxic fjords in the world; seasonal deep-water oxygenation alters the mechanisms of N₂O production. During oxic phases, ammonium oxidation dominates N 2 O production, whereas under anoxic conditions, N₂O is reduced or consumed through complete denitrification 43 . Steep O 2 gradients are known hotspots of intensive microbial activity, as described in the present study. Accordingly, the elevated N 2 O concentrations detected in this particular part of the oxycline (Fig. 3 k) may result from multiple nitrogen transformation processes, including ammonia oxidation, nitrifier denitrification, and incomplete denitrification. These processes are accompanied by high biodiversity and abundance of chemolithoautotrophic nitrate-reducing, sulfur-oxidizing γ-proteobacteria (SUP05 cluster) observed in the present study (Fig. 5 ). It should be noted that the maximum and minimum N 2 O concentrations in Quitralco Fjord were both higher and lower, respectively, than those reported in relation to other anoxic fjords 43, 44 . Extreme N 2 O concentrations such as these may be attributable to the presence of nitrate-rich waters below the surface layer, in conjunction with the presence of electron donor compounds, such as organic matter and additional reductants including CH₄, H₂S or reduced metals (Fe²⁺, Mn²⁺). These inputs enhance DO demand, intensify anoxia and promote complete denitrification to N 2 . Elevated microbial stimulation occurs when alternative substrates, such as CH₄ and H₂S sustain chemoautotrophic communities, thereby altering the oxidant/reductant balance and nitrogen transformation pathways 42, 45 . In Quitralco Fjord, intense organic matter supply combined with tectonic seepage, likely involving CH₄ and H₂S, may enhance reducing conditions, stimulating partial denitrification and generating a pronounced N₂O maximum (~ 45 nM), while denitrification also proceeds to completion, driving N₂O concentrations to zero. 46 investigated the activity and abundance of denitrifying bacteria in the subsurface biosphere associated with diffuse hydrothermal vents on the Juan de Fuca Ridge. These bacteria perform denitrification, a crucial process in the nitrogen cycle, by converting nitrogen oxides into nitrogen gas by means of chemosynthetic chemical energy sources. Their research helped to improve understanding around the role and function of these microorganisms in deep-sea ecosystems fueled by chemical energy rather than sunlight. The large-scale methane accumulation could indicate intense benthic methane release due to in situ methanogenesis; although under euxinic conditions methanogenesis is usually inhibited 47 . The extreme CH 4 accumulation in the euxinic bottom waters of Quitralco reaffirms negligible oxidation due to the absence of oxygen and nitrate. In contrast, along the oxycline (redoxcline), dissolved methane and sulfide are largely removed by strong aerobic and anaerobic oxidation. Critically, inputs of CH₄, H₂S and other reductants can stimulate intense chemoautotrophic activity, methanotrophy, sulfur oxidation and even ammonium oxidation which consumes available oxidants and supports in situ primary production, thereby reshaping carbon and nitrogen cycling. In addition, nutrient distributions revealed a particular pattern, with nitrate exhibiting a clear oxic, suboxic and anoxic sequence. The presence of Subantarctic Water (SAAW) explains the relatively high NO₃⁻ concentrations above 100 m 2 , but the depressed N:P and N:Si ratios, in conjunction with peaks in P and Si, may indicate other sources than aerobic or anaerobic organic matter mineralization. For example, phosphate concentrations near 6 µM (and up to 20 µM at 150 m) are well above typical SAAW end-member values (Linford et al., 2024). If these nutrients were derived solely from aerobic organic-matter remineralization, N and P would accumulate in near-Redfield proportions, which is not observed (N:P ≪ 16). The co-occurrence of near-zero nitrate, very high CH₄, and elevated silicate concentrations indicates the presence of strongly reducing conditions with internal P release, likely driven by reductive dissolution of Fe-bound P and benthic diffusive fluxes 48, 49,50 . In addition, tectonic seepage or cold-vent inputs are a plausible external source of P- and Si-rich reduced fluids; prolonged residence times would then allow the accumulation thereof at depth. Discriminating between sedimentary and tectonic sources could be achieved using tracers (for example, dissolved Fe/Mn, ³He, Ra isotopes) and combined pore water-water-column flux measurements. The plasticity of the prokaryotic community structure (i.e., composition and function) is widely documented across extreme gradients in a varied array of environments. In the case of the anoxic basin (Station E8), a clear shift is observed in microbial community composition throughout the water column, particularly in oxic, hypoxic and euxinic waters. In addition, several geochemical fingerprints indicate changes in potential microbial metabolic functions throughout the redox gradient of the water column. Thus, heterotrophic bacteria, primarily related to the Flavobacteriales and SAR11 groups, modulate carbon cycling in oxic waters 51, 52 while chemolithoautotrophic nitrifying archaea, such as Nitrosopumilales, regulate ammonium oxidation across the oxycline (20 − 50 m depth) and in hypoxic waters (50 − 100 m depth). This process likely explains the accumulation of nitrate and the absence of ammonium 53, 54 observed directly above the anoxic layer. Additional archaeal organisms abundant in the oxygenated waters were associated with Marine Group II, which are organisms characterized by their metabolic potential for obligate aerobic heterotrophs, many of which are capable of harnessing solar energy through proteorhodopsins 55 . In contrast, across the deep-oxycline (100 − 120 m depth) and throughout the anoxic environment (below 100 m depth), the large estimated nitrogen deficit indicates substantial nitrate consumption, with nitrate acting as an electron acceptor in the absence of oxygen 56 to sustain primary chemical production or organic matter respiration. The microbial decomposition of organic matter in this layer may be further supported by the pronounced accumulation of ammonium, possibly derived from remineralization (Fig. 3 g). In this regard, the abundance of heterotrophic bacterial groups, such as Bacteroidetes (VC2.1) and Latescibacterota in the euxinic zone, which are characterized by their ability to tolerate or even thrive in the absence of oxygen 57, 58, 59 , is likely a contributory factor to this nitrogen deficit, primarily by means of nitrate consumption. These groups are capable of oxidizing complex organic compounds in order to obtain energy. In particular, Bacteroidetes can do so by reducing NO/N 2 O and polysulfides 59 , while Latescibacterota do so via dissimilatory nitrate reduction, specifically by reducing nitrate to nitrite (for example 57 and references therein). The accumulation of nitrite, particularly evident during December 2024 (Fig. 3 d), indicates a decoupling between the reduction rates of the different steps of the denitrification pathway, namely from nitrate reduction to nitrite relative to the subsequent reduction of nitrite to nitric oxide/nitrous oxide. Additionally, given that the oxidation of reduced sulfur compounds represents an important source of inorganic chemical energy for inorganic carbon fixation 60, 62 ,the increasing accumulation of hydrogen sulfide (∑H 2 S) recorded across the deepest layer (> 120 m depth) indicates the potential of this system to support chemolithoautotrophy through the coupling of the sulfur, carbon and nitrogen cycles. Arcobacteraceae, for example, a ubiquitous mixotrophic bacteria and the second most abundant sequence found under euxinic conditions, can fix carbon from sulfur oxidation and nitrate reduction 62 . Similarly, the SUP05 clade of Gammaproteobacteria (Thioglobaceae) use sulfide and other reduced forms of inorganic sulfur to obtain energy with which to fix inorganic carbon, while reducing nitrate, nitrite, nitric oxide, or nitrous oxide via the autotrophic denitrification pathway 60,63,64 . Furthermore, several members of the Desulfatiglans genus were among the most abundant taxa identified (Fig. 5 ). Members of this group belong to the deltaproteobacterial family, Desulfobacteraceae, and are dissimilatory sulfate reducers often found in anoxic marine environments, primarily in surface sediments with limited sulfate and organic carbon. As such, they are capable of using aromatic compounds as energy sources 65, 66 . The presence of this group is of particular interest because sulfate reduction leads to the formation of H 2 S, therefore raising concerns about the relevance of biological-mediated processes versus tectonic inputs in the production of H 2 S in the fjord. In addition, the detection of the predominant marine anammox bacterium Candidatus Scalindua 67, 68 as one of the relatively well-represented sequences in the euxinic layer is intriguing, since this ammonium-based metabolism is inhibited even at low H 2 S concentrations 69,70 . Such inhibition may help to explain the large-scale accumulation of ammonium observed. Collectively, these results reopen the debate on the metabolic potential of organisms identified from DNA samples, underscoring the need for targeted experimental approaches in order to quantify the magnitude of the processes in which these organisms are putatively involved. 3.3. Mechanism-driven anoxic and euxinic conditions. The results detailed in the present study suggest the existence of two new major mechanisms driving anoxia and euxinic conditions in Quitralco Fjord. 1) From the physical oceanography perspective, Quitralco Fjord has been identified as one of the fjords in the northern Patagonian with the longest water residence times 71, 6 (Fig. 1 f). This characteristic is primarily associated with the irregular topography of the fjord, particularly the presence of a numerous sills that reduce marine current velocity and, therefore, contribute directly to the establishment of anoxic conditions in the waters (Fig. 1 e). Moreover, recent measurements of hydrographic conditions (temperature and salinity) and DO throughout the fjord from March 2023 to December 2024 revealed the entrance of cold-oxygenated waters into the fjord from the subsurface layer, which subsequently spread across the entire deep fjord basin (Fig. S2). A ventilation event observed in 2024 resulted in a downward displacement of the anoxic boundary layer by approximately 30 m (from 90 m to 120 m, see Fig. 2 e). This highlights the key role of ventilation events in modulating the vertical displacement of the anoxic layer. Nevertheless, the physical drivers involved in the interannual variability of deep ventilation observed in Quitralco Fjord warrant further investigation. 2) A second mechanism driving the anoxic conditions in the fjord arises from the geochemical oxygen consumption arising from reactions with H 2 S, ammonium and methane (Fig. 3 ). The geochemical production of H 2 S resulting from tectonic activity underneath Quitralco Fjord generates a toxic environment similar to the ancient anoxic Proterozoic oceans 72 . These conditions appear to support the colonization of abundant marine microbial organisms, dominated primarily by bacteria and, to a lesser extent, archaea (Fig. 5 ). Taken in conjunction, the aforementioned drivers ensure that the fjord provides researchers with a unique destination in which to further general understanding of the complex biological and biogeochemical processes occurring in the current Holocene era. 4. Conclusion The Patagonian fjords comprise an extensive system of not only fjords, but also channels, sounds, and bays that interact constantly with the adjacent eastern South Pacific Ocean waters. They are also subject to continuous natural and anthropogenic pressures. Over the past decade, oceanographic expeditions have investigated water mass variability, generally revealing a predominance of oxygenated waters. Nevertheless, hypoxic conditions have been observed in subsurface layers of certain fjords since the earliest research expeditions. Notably, the present study identifies the first anoxic and euxinic area reported in northern Patagonia, at the deep fjord head (90 − 160 m depth) of Quitralco Fjord. This finding provides a modern analogue of ancient anoxic-euxinic oceans and the fjord waters represent a natural laboratory in which to test CH₄--S-Nox redox coupling and chemosynthetic pathways under contemporary deoxygenation. Indeed, elevated concentrations of H 2 S (50 − 100 µM) and CH 4 (up to 19,000nM) were identified in the bottom waters. The co-occurrence of a deep fluorescence maximum, elevated DOC, and a modest increase in prokaryotic cells is consistent with the presence of chemolithotrophic prokaryotes (for example, S-, ammonium and methane-oxidizers). Coupled with long water-residence times and physical characteristics, these conditions help sustain anoxia/euxinia and favour the accumulation of reduced compounds in bottom waters, which are then rapidly oxidized across the oxycline, forming an effective oxidative filter. Concurrently, vertical profiles of reductant compounds closely matched the microbial community composition, including an abundance of sulfate reducers ( Desulfobacula, Desulfatiglans, Desulfotignum, Desulfobacter ) and sulfur oxidizers (Arcobacteraceae/Malaciobacter, SUP05), as well as anammox ( Ca. Scalindua) and VC2.1. In contrast, oxic layers (10–110 m) were enriched in ammonia-oxidizing archaea ( Ca. Nitrosopumilus, Ca. * Nitrosopelagicus ) and Marine Group II. This community pattern is consistent with observed biogeochemistry, and helps to explain the accumulation of H₂S/CH₄ and the depressed N:P and N:Si, which are partially explained by fixed-N loss through denitrification (observed as complete N 2 O consumption) and anammox, followed by re-oxidation across the oxycline. 5. Methods 5.1. Oceanographic data. A total of 77 profiles of temperature, salinity, dissolved oxygen, fluorescence, and turbidity (Table 2 ) were collected using a vertical microprofiler model VMP250 RDL from Rockland Scientific ( https://rocklandscientific.com/products/profilers/vmp-250 ). This instrument collected data at a sampling rate of 64 Hz and can be used at depths of up to 500 m, with an optimal vertical free-fall velocity of ~ 70 cms − 1 . In addition, the VMP250 RDL features a high-response RINKO dissolved oxygen (DO) sensor (63% response in less than 1 second in water) with an initial accuracy of ± 2.0 µM, as well as fluorescence and turbidity sensors provided by JFE Advantech from Japan. Table 2 Chronology of oceanographic expeditions and sampling activities in Quitralco Fjord. Expeditions (Austral seasons) Date (mm, yyyy) CTDO stations Water sampling stations Analysis of water samples PN-Winter August 2022 13 - - PN-Summer March 2023 8 - - PN-Autumn June 2023 8 - - PN-Winter August 2023 8 - - PN- Autumn June 2024 8 - - PN-Winter August 2024 8 1 Ammonium Inorganic nutrients FONDECYT-Spring October 2024 8 2 H 2 S Inorganic nutrients Biogeochemical parameters PN-Spring December 2024 8 1 H 2 S, ammonium Inorganic nutrients PN-Winter July 2025 8 1 Gases (N 2 O and CH 4 ) 5.2. Trace oxygen profilers. Oxygen measurements within the anoxic layer were conducted using a uTail+ instrument, which enables detection of ultralow oxygen concentrations (< 1µM). The uTail + is an upgraded version of the Trace Oxygen Profiler (TOP) instrument described in 73 . Both instruments share the same fundamental operational principles and methodologies. Data was calibrated using the provided zero-point calibration, in-house laboratory-based multipoint calibrations, and corrections for temperature and pressure. The instrument was mounted on an RBR CONCERTO CTD frame and deployed at the same location where CTDO and biogeochemical data were collected (Table 1 ). Upcast profiles from uTail+ were prioritized because the ascent speed is generally higher than the descent speed, resulting in an increased flow around the sensor/CTD package. Furthermore, a significant amount of oxygen appears to be released from the CTD unit itself, a process that is likely time-dependent. Consequently, the upcast should minimize contamination and provide more representative oxygen readings in hypoxic environments. 5.3. Acoustic data. Backscatter or echo intensity (Fig. 4 ) was measured from the surface to the bottom at a 1 min temporal resolution using a 307.7 kHz Teledyne RDI Workhorse Acoustic Doppler Current Profiler (ADCP). The downward-facing sensor was deployed during the October 2024 expeditions, collecting data at 1 m vertical resolution over a 24-hour sampling period. Echo intensity indicates the strength of the ADCP acoustic signal (“ping”) reflected by suspended particulates in the water column. Following corrections for signal attenuation, water velocity, and instrument-specific factors, echo intensity was converted to volume backscatter ( Sv ). This parameter serves as a proxy for zooplankton biomass, pycnocline depth, and suspended sediment abundance, which typically accumulate at density interfaces between water masses 74, 75 . The ADCP echo intensity was converted to volume backscatter ( Sv , dB re 1 m − 1 ) using the following conversion formula: $$\:{\:\:\:\:\:\:S}_{v}=C+10log\left[\left(Tx+273.16\right){R}^{2}\right]-{L}_{DBW}-{P}_{DBW}+2\alpha\:R+{K}_{c}\left(E-{E}_{r}\right)$$ 1 In this equation, C is a sonar-configuration scaling factor (-148.2 dB) specific to the RDI Workhorse Sentinel ADCP, Tx is the temperature at the transducer (°C), L is log10 (transmit-pulse length, L = 8.13 m), PDBW is log10 (output power, 15.5 W), α is the absorption coefficient (dB m − 1 ), Kc is a beam-specific sensitivity coefficient (provided by the manufacturer as 0.45), E is the recorded automatic gain control (AGC), and Er is the minimum AGC recorded (40 dB). The beam average of the AGC for the 4 ADCP transducer heads was used to obtain optimal results, following the procedure outlined in 76 . Finally, R is the slant range to the sample bin (m), which is corrected using the depth 77 . Therefore, R is expressed as: $$\:R=\frac{b+\frac{L+d}{2}+\left(\left(n-1\right)d\right)+\left(\frac{d}{4}\right)}{cos\zeta\:}\frac{c¯}{{c}_{I}}$$ 2 where b is the blanking distance (3.23 m), L is the transmit pulse length (same as above), d is the depth cell size (1 m), n is the depth cell number of the particular scattering layer being measured, ζ is the beam angle (20°), C − is the average sound speed from the transducer to the depth cell (1,453 m s − 1 ), and C I is the nominal sound speed used by the instrument (1,454 m s − 1 ). 5.4. Zooplankton sampling. Stratified mesozooplankton samples were collected on 9 October 2024 using a WP2 net (300 µm mesh, 50 cm mouth diameter, equipped with a flowmeter) during a single vertical nighttime tow (22:00 local time). Sampling spanned four depth strata: 0 − 50 m, 50 − 100 m, 100 − 120 m, and 120 − 150 m. Discrete stratum sampling was achieved using a double-release trigger system (Puget Sound Workshop dba Research Nets). Samples were preserved on board in 5% formaldehyde. Laboratory processing included the sorting of functional zooplankton groups, measuring individual lengths, and classifying organisms into three size categories ( 5 mm). Abundance was standardized as individuals per cubic meter (ind/m 3 ). 5.5. Sediment sampling and heavy metal analysis. At each station, sediments were collected using a 0.1 m² Van Veen grab for the quantification of heavy metals (HM). Three undisturbed sub-samples were extracted from the upper 3 cm of each grab using a dark plastic corer (8 cm in length × 6 cm in diameter), transferred to a 60 mL plastic flask wrapped in aluminium foil, and preserved at − 20°C until HM analysis. Heavy metal processing took place in line with the protocol described by 78 , using the EPA method 3050B 79 . Sediments were dried at 60°C and sieved through a 60 µm mesh. One gram of the < 60 µm sediment fraction was subjected to acidic digestion using nitric and hydrochloric acid to extract metals. Digestion was completed with 10 mL of 1:1 hydrogen peroxide at 95 ° ± 5°C. The remaining solution was analyzed via atomic absorption spectrophotometry (PERKIN ELMER Inc, ANALYST 200, Waltham, MA, USA) for Cu, Cd, Cr, Pb, Zn, Mn, Ni, Mg, and Fe concentrations (µg kg − 1 , triplicate measurements). 5.6. Hydrogen sulfide concentration. The concentrations of aqueous hydrogen sulfide species (∑H 2 S) were determined following Jessen et al. (2022). Briefly, water samples were collected directly into glass cells from Niskin bottles. Immediately after collection, reagents were added to fix the ∑H 2 S, and the concentration was analyzed using the methylene blue method directly on board using a HACH portable colorimeter (Hach DR900, HACH Company, Loveland, CO, USA). 5.7. Dissolved organic carbon, inorganic nutrients, and chlorophyll-a. Dissolved organic carbon (DOC) concentrations were determined from 60 mL water samples collected at each sampling depth and filtered through pre-combusted 25 mm Whatman GF/F filters (450°C for four h) and stored in plastic sampling containers (HDPE) at -20°C until analysis. Prior to analysis, samples were acidified with 40 µL of phosphoric acid. DOC concentrations were measured as non-purgeable organic carbon (NPOC) using a TOC-L CPH high temperature analyzer (Shimadzu TOC-LCPH FA, J100), equipped with a high-sensitivity catalyst. Each individual DOC concentration value obtained represents the average of two to three sample injections. Prior to analyses and between batches, deep seawater reference samples (provided by the University of Miami) were analysed to verify analytical accuracy and stability over time. Water samples of 500 mL from each sampling depth were collected for inorganic nutrient analyses (nitrate, nitrite, phosphate, and silicate). Samples were filtered through Whatman GF/F filters and filtrates were stored in plastic containers (HDPE). Samples were frozen at -20°C until laboratory analysis. Concentrations of inorganic nutrients were determined spectrophotometrically according to standard methods (Strickland and Parsons, 1968). Water samples of 125 mL were collected from each sampling depth to determine ammonium concentrations. These samples did not undergo filtering and a phenol solution (4 mL) was immediately added. Ammonium concentrations were calculated in the laboratory in line with the method proposed by Solorzano (1969). N deficit (N*) was calculated following the method proposed by Gruber and Sarmiento (1997), based on the relationship between fixed inorganic N species (nitrate, nitrite and ammonium) and phosphate concentrations. For total chlorophyll-a (Chl-a), two 1,000-mL water samples from each sampling depth were filtered through Whatman GF/F filters. Filters were immediately frozen at -20°C until subsequent analysis by fluorometry. Pigments were extracted with 90% v/v acetone, as per standard procedures (Parsons et al., 1984). 5.8. N 2 O and CH 4 analysis . Dissolved CH₄ and N₂O were sampled in triplicate at the same depths as nutrient samples. Subsamples were transferred into 20 mL glass vials and preserved with 0.05 µL of saturated HgCl₂, to inhibit microbial activity, following the recommendations of 80 . Gas concentrations were determined using the headspace equilibration technique. A 5 mL volume of ultra-pure helium was added to each vial to create the headspace, which was equilibrated at 30°C under constant agitation. Subsequently, 500 µL of the headspace were manually injected into two gas chromatographs: one Agilent 7697A, equipped with a flame ionization detector (FID) for CH₄, and one Shimadzu 17A, fitted with an electron capture detector (ECD) for N₂O. Both systems were operated at 30°C with ultra-pure N₂ as the carrier gas (flow rate: 2.6 mL min⁻¹), using an Rt-QS-BOND capillary column (30 m × 0.53 mm ID × 20 µm). Calibration curves consisted of six points prepared from certified standards (Air Liquide Company), balanced with helium. CH₄ standards ranged from 1 to 20 ppm (1, 2.5, 5, 10, 20 ppm), and N₂O standards from 0.25 to 2 ppm (0.25, 0.35, 0.50, 1, 2 ppm). Zero points were obtained with ultra-pure helium. Both detectors exhibited linear responses (R² = 0.999). Analytical precision was ~ 5% and samples with coefficients of variation > 10% were discarded. Samples exceeding the calibration range, such as those found in bottom waters, were diluted with 5 µL aliquots, and concentrations were corrected for the corresponding dilution factor. Dissolved gas concentrations (C_gas, nmol L⁻¹) were calculated as: C Gas [nmol L − 1 ] = ( β x P V wp + ( x P / R T) V hs ), (3) where β is the solubility constant of the gas in water, x is the mole fraction measured by gas chromatography, P is the atmospheric pressure (atm), V_wp is the water phase volume (L), V_hs is the headspace volume (L), R is the universal gas constant (0.08205 L atm K⁻¹ mol⁻¹), and T is the absolute temperature (K). Solubility corrections were applied in line with the recommendations of 81 for CH₄ and 82 for N₂O. 5.9. Optical properties of dissolved organic matter. The optical properties of DOM, including CDOM and fDOM were analysed to study its distribution and infer its composition and source. Water samples for CDOM and fDOM were filtered through pre-combusted 25 mm GF/F filters (Whatman) and stored in 60 mL plastic bottles (HDPE). Samples were frozen at -20°C until subsequent laboratory analysis. DOM optical properties were determined using a spectrofluorometer (Aqualog, Horiba, UV-800-C) with a 1 cm quartz cuvette. CDOM concentrations were measured using the absorption spectra at 325 nm as a proxy (Nelson et al., 2007). Spectral scans were acquired between the 200 and 700 nm wavelength range, using ultrapure water as a blank. Absorption coefficients (a λ ) of CDOM (m − 1 ) were calculated according to the equation: a( λ ) = 2.303 * Abs (λ) /l (4) where Abs (λ) is the absorbance at λ wavelength (after subtraction of the average absorbance between 600 and 700 nm), l is the optical path length (m), and 2.303 is the factor to convert base-10 to a natural logarithm (Aiken 2014). Specific UV absorbance at 254 nm (SUVA 254 ) was calculated by dividing CDOM absorbance at 255 nm by the DOC concentration 30 . For fDOM measurements, emission scans were acquired from 250 to 800 nm at 2.5-nm intervals, with excitation wavelengths ranging from 200 to 700 nm at 5-nm intervals. Fluorescence spectra were scanned with an integration time of 2 seconds, a pixel increment of 4, and a medium gain setting. Corrections for the inner filter effect and Rayleigh masking were applied using predefined tools in Aqualog software. All fluorescence data are reported in Raman units (RU) after normalization to the integrated Raman area (excitation at 350 nm). The data obtained from the scans were consolidated into an excitation-emission matrix (EEM) and subsequently analysed using PARAFAC, which enables the identification of DOM fluorescent components based on their Ex/Em peaks 24, 25 . PARAFAC analysis was performed using the Eigenvector Inc. Solo package (V9.2). 5.10. Microbial community structure and composition. Prokaryote abundance (bacteria and archaea) was determined using a flow cytometer (InFlux®) equipped with a 488 nm laser in the Flow Cytometry Laboratory of the Millennium Institute of Oceanography, University of Concepción, Chile. Aliquots of 1,350 µL of seawater, collected directly from Niskin bottles, were fixed with 0.1% glutaraldehyde flash-frozen in liquid nitrogen and stored in cryovials. At the laboratory, samples were thawed at room temperature and stained with SYBR-Green I for 15 min. Heterotrophic [MC1] prokaryotes were detected using a 530 nm filter, and the intersections of SybrGreen versus forward scatter (FSC) and SybrGreen versus Chlorophyll signals were used to differentiate prokaryotes from other small fluorescent organisms. For microbial diversity and community composition analysis, two liters of seawater from selected depths were filtered through 0.22 µm sterile membrane filters (Millipore) and stored in cryotubes with 300 µL of RNA at -20°C. DNA was extracted using a Power Water DNA Isolation Kit (MOBIO Laboratories), following manufacturer instructions. Prokaryote 16S rRNA genes were amplified using the universal primer set 515F (GTGYCAGCMGCCGCGGTA) and 806R (GGACTACNVGGGTWTCTAAT) and sequenced on an Illumina MiSeq platform in the Austral-Omics Laboratory of the Universidad Austral de Chile. The complete MiSeq data set is available at the National Center for Biotechnology Information Sequence Read Archive. Paired Illumina demultiplexed reads were processed using QIIME2 version 2024.2 (Boylen et al., 2019) and the DADA2 package for quality filtering, denoising, and chimera removal. Amplicon Sequence Variants (ASVs) taxonomy was assigned using the classify-sklearn function and a Naïve Bayes classifier trained on the Silva 138 (99%) reference sequences 83, 84, 85 . Rarefaction curves for each prokaryote community were generated from the means of ten randomized data sets in QIIME2. Analysis of beta and alpha diversity (measured as ASV abundance) was estimated following the removal of sequences identified as Chloroplasts and subsequent to resampling via the rarefaction method, using a minimum of 172,918 sequences per sample. In addition, full-length 16S rRNA gene sequences were obtained from samples taken from the anoxic layer at station 8 and from the same depths at control station E7 using Oxford Nanopore Technologies. DNA libraries were prepared from 10 ng of genomic DNA per sample using the Oxford Nanopore 16S Barcoding Kit 24 V14 (SQK-16S114.24), following the manufacturer guidelines ( https://nanoporetech.com/document/rapid-sequencing-DNA-16s-barcoding-kit-v14-sqk-16114-24 ). Briefly, the 16S rRNA gene regions were amplified by PCR using LongAmp Hot Start Taq 2× Master Mix (New England Biolabs). Barcoded amplicons were purified with AMPure XP beads (Beckman Coulter), eluted in 15 µL of molecular-grade water, and quantified using a Qubit dsDNA HS assay (Thermo Fisher Scientific). Adapter ligation was performed by incubating 50 fmol of the pooled library with the Rapid Adapter for 5 min at room temperature. Sequencing was conducted on a MinION MK-1C equipped with FLO-MIN114 flow cells using the Fast Basecalling mode. Following basecalling with the default 16S barcoding parameters, reads were filtered to a minimum quality score of 8, resulting in 4.39 GB of data (N50 = 1.57 kb). Demultiplexing and taxonomic profiling were performed using the cloud-based EPI2ME 16S workflow ( https://github.com/epi2me-labs/wf-16s ) and independently verified using Kraken2 (v2.1.2) (Wood et al., 2019) against the SILVA 138 database, in order to generate high-resolution genus- and species-level abundance tables. Vertical profiles of community composition and ASVs heatmaps were generated in R version 4.2.0 (R Core Team 2019) and Orange3 software (Demsar et al., 2013) for the representative ASVs, which were defined as the top 25 ASVs from Illumina sequencing and those exceeding over 5,000 reads for full-length 16S rRNA gene sequences. Declarations Data availability statement Data and metadata are available at: https://doi.org/10.5281/zenodo.18422011 Acknowledgements We thank the chemical and microbiological laboratories of the Patagonia Ecosystem Research Center (CIEP) and the University of Concepción for the biogeochemical analyses presented in this manuscript. Special thanks to the crews of the Jürgen Winter, Antiqua, and Don Felipe III vessels for supporting data collection in the Quitralco Fjord. Funding Iván Pérez-Santos was funded by FONDECYT 1211037, 1251038, COPAS COASTAL FB210021, and CIEP R20F002. Alexander Galán has been partially supported by ANID, Concurso de Fortalecimiento al Desarrollo Científico de Centros Regionales 2020 CLAP-R20F0008. Paulina Montero was funded by FONDECYT 11230763, COPAS COASTAL FB210021, and PATSER R20F002. Marcelo Gutiérrez was funded by COPAS COASTAL FB210021. Laura Farias would like to thank the Instituto Milenios Secos ICM 2019–015, CR2 FONDAP-ANID 1522A0001, and FONDECYT 1250210. Author contributions statement IPS: led study design, collection and analysis of physical oceanographic and acoustic data, and manuscript leader. PM, MG, GL: collection and analysis of microbiological and biogeochemical data, and manuscript revision. AG, LF: analysis of biogeochemical data, and manuscript revision. LC: analysis of zooplankton data and manuscript revision. CRV: analysis of surface sediment data and design of the conceptual model. PD, CA: study design, collection and analysis of physical oceanographic data, and manuscript revision. 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Supplementary Files SuplemmentarymaterialtoEuxinicconditionsandalteredbiogeochemicalcyclesinaPatagonianfjordinfluencedbytectonicactivity29.1.2026.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 13 Apr, 2026 Reviews received at journal 12 Apr, 2026 Reviewers agreed at journal 31 Mar, 2026 Reviews received at journal 04 Mar, 2026 Reviewers agreed at journal 19 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers invited by journal 08 Feb, 2026 Editor invited by journal 05 Feb, 2026 Editor assigned by journal 03 Feb, 2026 Submission checks completed at journal 03 Feb, 2026 First submitted to journal 29 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Jessen","email":"","orcid":"","institution":"Austral University of Chile","correspondingAuthor":false,"prefix":"","firstName":"Gerdhard","middleName":"L.","lastName":"Jessen","suffix":""},{"id":589905818,"identity":"aa92919d-19df-4be5-81c0-2ee94e2e358a","order_by":4,"name":"Alexander Galán","email":"","orcid":"","institution":"Catholic University of the Maule","correspondingAuthor":false,"prefix":"","firstName":"Alexander","middleName":"","lastName":"Galán","suffix":""},{"id":589905822,"identity":"f5d74e61-3e98-42f5-8c8e-129f64a69bae","order_by":5,"name":"Laura Farías","email":"","orcid":"","institution":"University of Concepción","correspondingAuthor":false,"prefix":"","firstName":"Laura","middleName":"","lastName":"Farías","suffix":""},{"id":589905824,"identity":"3e3769bb-9c03-41fd-9523-ca0608d5696f","order_by":6,"name":"Leonardo Castro","email":"","orcid":"","institution":"University of Concepción","correspondingAuthor":false,"prefix":"","firstName":"Leonardo","middleName":"","lastName":"Castro","suffix":""},{"id":589905825,"identity":"155b8ed6-5fdf-4cf1-b914-61deedec76b9","order_by":7,"name":"Camilo Rodriguéz-Villegas","email":"","orcid":"","institution":"University of Los Lagos","correspondingAuthor":false,"prefix":"","firstName":"Camilo","middleName":"","lastName":"Rodriguéz-Villegas","suffix":""},{"id":589905828,"identity":"1d4443ed-341c-4913-86c3-701ab277b331","order_by":8,"name":"Patricio Díaz","email":"","orcid":"","institution":"University of Los Lagos","correspondingAuthor":false,"prefix":"","firstName":"Patricio","middleName":"","lastName":"Díaz","suffix":""},{"id":589905830,"identity":"b6f1432d-e2f6-44eb-afc0-8eeb06c1251d","order_by":9,"name":"Claudia Aracena","email":"","orcid":"","institution":"Universidad Bernardo O'Higgins","correspondingAuthor":false,"prefix":"","firstName":"Claudia","middleName":"","lastName":"Aracena","suffix":""},{"id":589905831,"identity":"53a724b1-844a-46ce-81d3-884b8a32871d","order_by":10,"name":"Elías Pinilla","email":"","orcid":"","institution":"University of Maine System","correspondingAuthor":false,"prefix":"","firstName":"Elías","middleName":"","lastName":"Pinilla","suffix":""},{"id":589905832,"identity":"ba32e6fb-210f-4133-b16d-143adedd31ca","order_by":11,"name":"Karen Sanzana","email":"","orcid":"","institution":"University of Concepción","correspondingAuthor":false,"prefix":"","firstName":"Karen","middleName":"","lastName":"Sanzana","suffix":""},{"id":589905833,"identity":"fa29cf97-ad61-4e2b-8982-40fff9446939","order_by":12,"name":"Aranza L. 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Bristow","email":"","orcid":"","institution":"University of Gothenburg","correspondingAuthor":false,"prefix":"","firstName":"Laura","middleName":"A.","lastName":"Bristow","suffix":""},{"id":589905846,"identity":"99af9674-95f4-4d10-a80f-22224e7a2131","order_by":21,"name":"Morten Larsen","email":"","orcid":"","institution":"University of Southern Denmark","correspondingAuthor":false,"prefix":"","firstName":"Morten","middleName":"","lastName":"Larsen","suffix":""},{"id":589905848,"identity":"08e17250-a168-430d-8f89-781f6d118ded","order_by":22,"name":"Osvaldo Ulloa","email":"","orcid":"","institution":"University of Concepción","correspondingAuthor":false,"prefix":"","firstName":"Osvaldo","middleName":"","lastName":"Ulloa","suffix":""}],"badges":[],"createdAt":"2026-01-29 23:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8735657/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8735657/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102747085,"identity":"cd1d08fc-b027-4f29-88f8-5fe57afadede","added_by":"auto","created_at":"2026-02-16 09:03:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2589826,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003ea\u003c/strong\u003e) Study area outlined denoted by red rectangle in South America; (\u003cstrong\u003eb\u003c/strong\u003e) map of Patagonian fjords region, highlighting key geographical features and red rectangle denoting study area; (\u003cstrong\u003ec\u003c/strong\u003e) distribution of sampling stations along the fjord, including the recently discovered active volcano, Mate Grande, and the Hudson Volcano. Colours indicate bathymetry and land topography; (\u003cstrong\u003ed\u003c/strong\u003e) fjord bathymetry; (\u003cstrong\u003ee\u003c/strong\u003e) results of the net velocity and; (\u003cstrong\u003ef\u003c/strong\u003e) mean water age derived from the validated numerical model\u003ca href=\"#_References\"\u003e\u003csup\u003e6\u003c/sup\u003e\u003c/a\u003e.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8735657/v1/1861fe099880d002e1e51d49.png"},{"id":102747084,"identity":"ac58318c-cce3-4c8f-a504-aed22fd90946","added_by":"auto","created_at":"2026-02-16 09:03:47","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":766967,"visible":true,"origin":"","legend":"\u003cp\u003eProfiles of: (a) water column temperature; (b) deep water temperature; (c-h) salinity, density, dissolved oxygen, fluorescence, and turbidity. Profiles obtained in the anoxic basin (station E8) arecolour-coded according to sampling periods, while those recorded within the fjord but outside the anoxic basin (stations E1 to E7, during 2024) are shown in grey. Oxygen data were obtained using a RINKO sensor (e) and, in the anoxic basin, a uTail oxygen sensor (f).\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8735657/v1/25ea20e2cf017051967e341f.jpeg"},{"id":102538777,"identity":"2d170a08-92e1-4b17-ae24-0c5ff73f7db9","added_by":"auto","created_at":"2026-02-12 18:13:52","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":692819,"visible":true,"origin":"","legend":"\u003cp\u003eProfiles of:\u003cstrong\u003e (a) \u003c/strong\u003edissolved oxygen; \u003cstrong\u003e(b) \u003c/strong\u003ehydrogen sulfide; \u003cstrong\u003e(c) \u003c/strong\u003enitrate;\u003cstrong\u003e(d) \u003c/strong\u003enitrite;\u003cstrong\u003e (e) \u003c/strong\u003ephosphate;\u003cstrong\u003e (f) \u003c/strong\u003esilicate;\u003cstrong\u003e (g) \u003c/strong\u003eammonium; \u003cstrong\u003e(h) \u003c/strong\u003enitrogen deficit (N*); \u003cstrong\u003e(i) \u003c/strong\u003edissolved organic carbon (DOC); (\u003cstrong\u003ej\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003echlorophyll-a (Chl-a); (\u003cstrong\u003ek\u003c/strong\u003e) nitrous oxide; and (\u003cstrong\u003el\u003c/strong\u003e) methane; all obtained from a sampling station in the anoxic basin (E8, green, magenta, and blue lines) and a control station (E7, black line).\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8735657/v1/c381bc98a20953fc3987ea80.jpeg"},{"id":102538776,"identity":"b286930a-8eec-4d6f-a62e-b016de8cea85","added_by":"auto","created_at":"2026-02-12 18:13:52","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":439315,"visible":true,"origin":"","legend":"\u003cp\u003eProfiles of: (\u003cstrong\u003ea, b\u003c/strong\u003e) all absorption spectra; (\u003cstrong\u003ec)\u003c/strong\u003e absorption spectra at 325 nm (aCDOM-325); (\u003cstrong\u003ed\u003c/strong\u003e) SUVA at 255 nm (SUVA 254); and (\u003cstrong\u003ee, f\u003c/strong\u003e) DOM fluorescence (fDOM) obtained for stations in anoxic basin (E8) and control station (E7) in October 2024.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8735657/v1/70854068cf75f62777c5fa2b.jpeg"},{"id":102538778,"identity":"eeeed1db-c2b0-4c95-94aa-42ceff05a49f","added_by":"auto","created_at":"2026-02-12 18:13:52","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":359436,"visible":true,"origin":"","legend":"\u003cp\u003eVertical profiles of: (\u003cstrong\u003ea\u003c/strong\u003e) prokaryote abundance and ASV richness; (\u003cstrong\u003eb\u003c/strong\u003e) abundance of representative bacteria; and (\u003cstrong\u003ec\u003c/strong\u003e) archaea ASVs from station E8, from Illumina sequencing. (\u003cstrong\u003ed\u003c/strong\u003e) Heatmap of abundance (log scale) of representative taxa from full-length 16S sequences from deep waters from control station E sampling station E8, under anoxic conditions.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8735657/v1/ea1016d9661d5e1af635a974.jpeg"},{"id":102538780,"identity":"8d31f048-6f95-430c-848f-52e8dfc5566a","added_by":"auto","created_at":"2026-02-12 18:13:52","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":933243,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual model depicting the biogeochemical processes occurring within the anoxic-euxinic zones of Quitralco Fjord, northern Patagonian fjord system.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8735657/v1/be7cf5c791f3049a8c7d5060.jpeg"},{"id":102750750,"identity":"4609e3da-3aaf-444f-ba6b-b60b2501fe14","added_by":"auto","created_at":"2026-02-16 09:21:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6986278,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8735657/v1/c9f64d6e-485b-4ee0-8d31-56a388c2147c.pdf"},{"id":102746943,"identity":"a25c608d-4bc1-440b-b95c-b0334acbe009","added_by":"auto","created_at":"2026-02-16 09:03:03","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2788548,"visible":true,"origin":"","legend":"","description":"","filename":"SuplemmentarymaterialtoEuxinicconditionsandalteredbiogeochemicalcyclesinaPatagonianfjordinfluencedbytectonicactivity29.1.2026.docx","url":"https://assets-eu.researchsquare.com/files/rs-8735657/v1/fb5940530cf3b577eee4e615.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Euxinic conditions and altered biogeochemical cycles in a Patagonian fjord influenced by tectonic activity","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eFjord ecosystems constitute key transition zones in aquatic systems\u003csup\u003e1\u003c/sup\u003e and further investigation into the natural and anthropogenic physical, biological, and chemical processes that govern their functioning are therefore warranted. One recently discovered process affecting Patagonian fjords is the deoxygenation of deep water\u003csup\u003e2\u003c/sup\u003e, primarily due to the advection of low-oxygen water from the equatorial region. While hypoxic conditions have been reported\u003csup\u003e3, 4, 5, 6\u003c/sup\u003e in certain areas, such as the Puyuhuapi Fjord, anoxia has never previously been recorded due to the occurrence of deep water ventilation\u003csup\u003e7, 8\u003c/sup\u003e. Accordingly, residence-time mapping has revealed values of 100 to 250 days in Patagonian fjords that were previously reported to exhibit hypoxic waters with particularly low levels of dissolved oxygen\u003csup\u003e6\u003c/sup\u003e. Furthermore, anoxic conditions have been recorded in recent years at the head of Quitralco Fjord, located in the northern Patagonian fjord system (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb-c), where marine current velocities are close to 0 cms\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and residence times exceed 200 days (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee-f). The present article is motivated by the occurrence of anoxic waters and the processes that underlie the development of euxinic conditions, as indicated by elevated hydrogen sulfide concentrations at depth.\u003c/p\u003e \u003cp\u003eQuitralco Fjord is located 45.7\u0026deg; South and 73.4\u0026deg; West in the northern Patagonian fjord system. It is ~\u0026thinsp;50 km in length and 3 km wide and its orientation is northeast toward the Andes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). It is located in an active volcanic region\u003csup\u003e9, 10\u003c/sup\u003e and a new active volcano was recently discovered in this area, the Mate Grande Volcano, located just 7 km from the head of the fjord (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). The Hudson Volcano (previous eruption 2011) is located 30 km south of the fjord, while the Maca and Cay volcanoes lie 60 km to the north\u003csup\u003e10\u003c/sup\u003e. In the research conducted by De Pascale, the Liqui\u0026ntilde;e-Ofqui fault zone (LOFZ) was found to extend north of the Patagonian region, traversing the underwater area of the head of Quitralco Fjord. However, faults could not be readily detected using remote sensing techniques\u003csup\u003e10\u003c/sup\u003e. From an oceanographic perspective\u003csup\u003e6\u003c/sup\u003e, reported low dissolved oxygen water (LDOW) (30\u0026thinsp;\u0026minus;\u0026thinsp;60% saturation) and hypoxic conditions (less than 30% saturation, 2 mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e L\u003csup\u003e6\u003c/sup\u003e, 2.8 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 89.3 mM) in Quitralco Fjord in November 2020. The LDOW readings were taken from waters between the mid-point of the fjord and the head, at a depth of 20 m, while hypoxia was observed in waters near the head and from a depth of between 150 m to the seabed (250 m). Four primary mechanisms were proposed as contributing to deep-water hypoxia in Quitralco Fjord: (1) weak deep-water circulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee); (2) shorter residence times (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef); (3) elevated dissolved oxygen (DO) consumption driven by community respiration; and (4) increased inputs of allochthonous organic matter associated with river discharges. Subsequent recent investigations have focused on the fjord head and have revealed a previously unreported feature of the Patagonian fjord system: deep-water anoxia extending from 100 m depth to the seabed (160 m), accompanied by hydrogen sulfide accumulation, likely driven by emissions from the basin floor into the water column. It should be noted that an environment is classified as euxinic when anoxic conditions coincide with sulfide concentration levels exceeding 0.1 \u0026micro;M\u003csup\u003e11\u003c/sup\u003e. The mechanisms driving the euxinic conditions observed in Quitralco Fjord remain unresolved, thus motivating the present investigation to be conducted into a unique ecosystem in which tectonic and anthropogenic activities, including salmon aquaculture, converge.\u003c/p\u003e \u003cp\u003eEuxinic conditions have been present during key periods of Earth\u0026rsquo;s history, when the deep ocean became anoxic and hydrogen sulfide accumulated to toxic levels\u003csup\u003e12\u003c/sup\u003e. Although the cause of prolonged euxinia in the past has been debated, the general underlying mechanism is attributed to the predominance of anaerobic oxidative metabolism in the absence of DO and an abundance of organic matter. Under such conditions, microbial metabolism shifts to sulphate reduction, producing hydrogen sulfide as a metabolic end product\u003csup\u003e13\u003c/sup\u003e. Although scarce in the ocean today, permanent euxinic environments do exist under particular conditions in certain seas\u003csup\u003e11\u003c/sup\u003e, with the most notable example being the Black Sea\u003csup\u003e14\u003c/sup\u003e. In this particular environment, anoxic conditions result from a combination of strong stratification and low ventilation linked to high oxygen consumption, which are, in turn, associated with elevated rates of primary productivity\u003csup\u003e12\u003c/sup\u003e. Euxinic conditions can also be transient and in several marine basins they follow seasonal productive cycles. However, persistent anoxic and euxinic environments can be found in bodies of water in which there is restricted ventilation, such as silled basins, including certain fjords\u003csup\u003e15, 16\u003c/sup\u003e. Once oxygen and nitrate are depleted during organic matter oxidation, microbial sulfate reduction becomes the dominant remineralization pathway in suboxic and anoxic bottom waters, leading to hydrogen sulfide accumulation. Accordingly, phosphate and sulfide concentrations are expected to covary during organic matter decomposition (Shen et al., 2002), while ammonium accumulates as a product of remineralization. This coupling reflects the tight linkage between nutrient regeneration and redox dynamics in poorly ventilated fjord systems, where nutrient trapping and high primary productivity sustain intense oxygen consumption in deep waters, potentially triggering euxinic conditions. Additionally, groundwater discharge or tectonic activity may result in the introduction of additional sulfur, often in the form of sulfate and sulfide, into fjords, allowing H₂S accumulation independently of organic matter decomposition\u003csup\u003e12\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFjords are generally well ventilated. However, the bathymetry and occurrence of high productivity in certain basins contribute to the development of deep-water oxygen-deficiency. Anoxia has also been documented in fjord systems; for example\u003csup\u003e15\u003c/sup\u003e, reported persistent anoxia in Nitinat Lake (48.7\u0026deg;N, 124.75\u0026deg;W) in British Columbia, Canada. In general, an active population of sulfur bacteria can be observed in these and other oxygen-deficient environments \u003csup\u003e17, 18, 19\u003c/sup\u003e. Certain Patagonian fjords have exhibited tectonic inputs of reduced fluids (CH₄, H₂S). In Chile, Comau Fjord hosts shallow cold vents and chemosynthetic communities, evincing strong reductant supply\u003csup\u003e20\u003c/sup\u003e. In contrast, the Almirante Montt Gulf (51.8\u0026deg; S/72.8\u0026deg; W) exhibits a pockmarked seabed and gas flares near the fjord entrance, where biogenic methane is released from gas-rich sediments, consistent with active sedimentary methanogenesis and seepage\u003csup\u003e21\u003c/sup\u003e. Across such systems, CH₄, H₂S and other reductant inputs may fuel vigorous chemoautotrophic oxidation (methanotrophy, sulfur oxidation, and in places Fe/Mn cycling), creating \u0026ldquo;oxidative filters\u0026rdquo; in redox transition zones that consume additional DO\u003csup\u003e22\u003c/sup\u003e. These oxidative filters are modulated by stratification, residence time, and the supply of electron acceptors (O₂, NO₃⁻/NO₂⁻, SO₄\u0026sup2;⁻, resulting in steep redox gradients consistent with observations from Canadian and Scandinavian fjords\u003csup\u003e23, 22, 24, 16\u003c/sup\u003e. As a previously unexplored system, Quitralco Fjord affords researchers a new area in which to investigate the influence of tectonic activity on oceanographic-biogeochemical processes and, as such, prompts the following research questions: (1) Do sulfur-oxidizing or sulfate-reducing bacteria that support anoxygenic chemosynthesis occur in the deep water column? (2) Which species of sulfur bacteria are present in the anoxygenic layer? (3) Are the anoxic/euxinic conditions exhibited in Quitralco Fjord driven primarily by natural processes or anthropogenic forcing? (4) On what timescales do anoxic conditions develop and persist? (5) To what extent does the euxinic condition influence biogeochemical cycling?\u003c/p\u003e \u003cp\u003eThe primary objective of the present article is to elucidate the mechanisms that contribute to the anoxic and euxinic conditions in Quitralco Fjord and their impact on biogeochemistry. To answer these questions, in situ measurements of CTDO, trace oxygen concentrations using microsensors, biogeochemical parameters, and microbial community composition were collected along the fjord between2022 and 2025.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2. Results","content":"\u003cp\u003e \u003cb\u003e2.1. Hydrographic conditions.\u003c/b\u003e Hydrographic measurements taken along the fjord revealed well-oxygenated waters in the surface layer (0\u0026ndash;50 m) throughout Quitralco Fjord (Fig. S2a-g), and similarly ventilated conditions at the fjord mouth. In the subsurface layer, oxygenated waters increased toward the fjord head along the 180 \u0026micro;M isoline, contributing to deep-water ventilation, particularly during the 2024 seasonal expeditions (Fig. S2d-g). Nevertheless, persistent anoxic conditions were observed year-round in the fjord head (station E8), with the upper limit varying between sampling periods (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). While surface water temperatures responded to the seasonal solar radiation cycle, colder waters were observed in the subsurface layer from the fjord head to the mid-fjord area, coinciding with ventilation events that occurred during 2024 (Fig. S2h-n). In contrast, the highest temperatures were observed in the anoxic deep basin (station E8), while cooler deep waters were confined to the mid-fjord and the head regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Seasonal hydrographic profiles of DO, fluorescence, and water turbidity collected between August 2022 and July 2025 revealed significant features of the anoxic basin in the fjord (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e): (1) Deep-water temperatures (down to 100 m) exceeded those of the inner-subsurface layers (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea) by ~\u0026thinsp;0.5\u0026deg;C, with values of ~\u0026thinsp;11\u0026deg;C near the seabed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). (2) Salinity and density ranged from 21 to 31 and 18\u0026minus;24.5 kg m\u003csup\u003e-3\u003c/sup\u003e, respectively, indicating the dominance of a single water mass type: estuarine water mass (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). (3) A peak of fluorescence and turbidity was observed at the anoxic basin (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg), while the position of the deep-oxycline modulated the dynamics of the deep fluorescence and turbidity records across seasonal expeditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eh).\u003c/p\u003e \u003cp\u003eDissolved oxygen was measured using a conductivity, temperature and depth oxygen (CTDO) optical sensor, revealing minimum DO values of 0.5 \u0026micro;M (0.018 mg L\u003csup\u003e-1\u003c/sup\u003e, 0.012 ml L\u003csup\u003e-1\u003c/sup\u003e) and 0.2% saturation at a depth greater than 90 m. The position of the anoxic boundary layer (oxycline) in the water column varied over time, registering a vertical displacement of up to 36 m. The absolute minimum and maximum depth of oxycline were observed in June and August 2023, at 92 m and 126 m, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). (4). Because standard optical oxygen sensors are limited to concentrations above 1 \u0026micro;M (e.g., Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee), a trace oxygen profiler instrument (uTail model) was used to measure oxygen values in the anoxic layer at depths of 120\u0026thinsp;\u0026minus;\u0026thinsp;160 m |(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef). Results from the uTail readings revealed a sharp decrease in oxygen concentrations between 118.1 m and 121.8 m (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Below these depths, oxygen levels dropped to \u0026lt;\u0026thinsp;10 nM at ~\u0026thinsp;140 m and continued dropping to approximately 5 nM at 160 m. Overall, average oxygen concentrations of 8.19\u0026thinsp;\u0026plusmn;\u0026thinsp;2.48 nM were observed in the anoxic layer, with minimum and maximum values of 4.94 nM and 11.44 nM, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef and Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). A deep fluorescence maximum (~\u0026thinsp;4 ppb) was detected in the anoxic layer, comparable in magnitude to the surface-layer fluorescence (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg). (5) A deep-turbidity peak coincided with the deep-oxicline position and the deep fluorescence maximum at all times (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eh).\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.2. Acoustic records.\u003c/b\u003e The backscattering acoustic signal in the anoxic basin revealed the strongest signal at a depth of approximately 60\u0026thinsp;\u0026minus;\u0026thinsp;80 m during daytime (Fig. S3a). This signal ascended at 18:00 h (local time), reached the surface layer between 21:00 and 06:00 h, and exhibited a diel vertical migration (DVM) pattern characteristic of zooplankton. A strong second signal was observed at 120 m, particularly during daylight hours, with a portion of it ascending to ~\u0026thinsp;60 m at night, prior to continuing its upward migration until 06:00 h. In addition, a third acoustic signal was detected within the anoxic-euxinic layer, appearing as an intermittent, upward-moving event that resembled gas emissions from the seabed up to a depth of ~\u0026thinsp;120 m, between 03:00 and 08:00 h (Fig. S3a); this phenomenon is discussed further in section 4. In-situ macrozooplankton sampling at differing depth strata corroborated the acoustic observations, revealing a pronounced concentration between 100 m and 120 m depth during nighttime (22:00\u0026thinsp;\u0026minus;\u0026thinsp;23:00 h), with lower concentrations in shallower layers. The sampled community was dominated by copepods, siphonophores, and euphausiids (Fig. S3b). A similar pattern emerged when zooplankton was grouped by size (\u0026gt;\u0026thinsp;5 mm, corresponding to the particle size detected by the 300 kHz ADCP used in the present study), with chaetognatha, total euphausiids, siphonophores, and mysidacea being the most abundant (Fig. S3c). Macrozooplankton groups were also present in the anoxic layer, although the anoxic boundary layer at 126 m in October 2024, which may have influenced the zooplankton samples. When the ADCP was redeployed at the same location in December 2024, the DVM pattern remained consistent, although the new dataset revealed multiple gas-emission events (Fig. S3d).\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.3. Evidence of tectonic activity.\u003c/b\u003e Surface-sediment analyses showed the highest heavy-metal concentrations at the head of the fjord (stations E7 and E8), particularly in the anoxic basin (Fig. S4, station E8). In this area, heavy metals typically associated with tectonic activity, such as Fe, Mg, Cr, and Cu, were found at elevated levels, with median values of 88.70, 11.14, 1.07, and 0.70 \u0026micro;g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, respectively (Fig. S4a-d). These concentrations were approximately four orders of magnitude higher than those in the remainder of the study area, for example, median values of 22.40, 2.81, 0.09, and 0.17 \u0026micro;g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for Fe, Mg, Cr, and Cu were observed, respectively (Fig. S4).\u003c/p\u003e\u003cp\u003e \u003cb\u003e2.4. Biogeochemical parameters.\u003c/b\u003e Biogeochemical parameters were measured throughout the water column with high vertical resolution (every 10 m) across the anoxic layer (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Hydrogen sulfide (\u0026sum;H\u003csub\u003e2\u003c/sub\u003eS) concentrations were extremely elevated below 120 m, increasing from 35 to 112.9 \u0026micro;M, (maximum value) at 150 m in October 2024 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). In contrast, concentrations of nitrate\u0026thinsp;\u0026lt;\u0026thinsp;11 \u0026micro;M, nitrite\u0026thinsp;\u0026lt;\u0026thinsp;1 \u0026micro;M, and phosphate\u0026thinsp;\u0026lt;\u0026thinsp;2 \u0026micro;M were primarily confined to the upper 15 m of the water column at both sampling stations (E7 and E8) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec-\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee). Below this layer, at depths of between 25 and 100 m, nitrate concentrations fluctuated between 14 and 25 \u0026micro;M (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed), while phosphate concentrations ranged between 2 and 3 \u0026micro;M (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee). In deep waters (100\u0026thinsp;\u0026minus;\u0026thinsp;150 m) at station E8 (anoxic basin), nitrate decreased to below detection limits (ca. 0 \u0026micro;M), whereas nitrite levels increased, particularly in December 2024, at which point they reached\u0026thinsp;~\u0026thinsp;1.4 \u0026micro;M. Phosphate levels also ​​rose in this layer to 20 \u0026micro;M. This pattern was not observed at the control station E7, where nitrate ranged from between 15 and 18 \u0026micro;M, nitrite from between 0.1 and 0.5 \u0026micro;M, and phosphate remained constant at approximately 2 \u0026micro;M, with values distributed homogeneously throughout the water column. Silicate concentrations at station E7 were relatively uniform throughout the water column (11\u0026thinsp;\u0026minus;\u0026thinsp;23 \u0026#120583;M), with a minimum of 4 \u0026micro;M at 5 m depth (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef). At station E8, silicate concentrations were observed at \u0026lt;\u0026thinsp;12 \u0026micro;M mainly within the upper 25 m, with a minimum of 1 \u0026micro;M at 5 m. However, between 50 and 150 m depth, silicate concentrations ​​increased progressively from 24 to 102 \u0026micro;M (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef). At station E8, ammonium concentrations were low (0.5 to 0.9 \u0026micro;M) from the surface to 100 m, increasing below this depth up to 25 \u0026micro;M at 150 m (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg). The nitrogen deficit (N*) exhibited a vertical pattern similar to that of nitrate, reaching extreme maximum values exceeding\u0026thinsp;\u0026minus;\u0026thinsp;200 \u0026micro;M in the deep anoxic zone (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eh). Dissolved organic carbon (DOC) concentrations in surface waters (0\u0026thinsp;\u0026minus;\u0026thinsp;5 m) exceeded 140 \u0026micro;M in both sampling stations (E7 and E8). Between 10 and 100 m depth, DOC ranged from 85 to 110 \u0026micro;M at station E7 and from 80 to 130 \u0026micro;M at station E8. In contrast, in deep waters (120\u0026thinsp;\u0026minus;\u0026thinsp;150 m) DOC increased from 120 to 185 \u0026micro;M at E8, while values decreased considerably at E7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ei). Chlorophyll-a concentrations at both stations were high (0.8\u0026thinsp;\u0026minus;\u0026thinsp;2.7 mg L\u003csup\u003e-1\u003c/sup\u003e) in the surface layer (0\u0026thinsp;\u0026minus;\u0026thinsp;10 m) and low (\u0026lt;\u0026thinsp;0.6 mg L\u003csup\u003e-1\u003c/sup\u003e) at depths of 15\u0026thinsp;\u0026minus;\u0026thinsp;150 m. Maximum concentrations of 2.7 and 1.6 mg L\u003csup\u003e-1\u003c/sup\u003e were observed at a 5 m depth in both sampling stations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ej), coinciding with minimum silicate values.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eIn Quitralco Fjord, the N₂O profile (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ek) shows equilibrium surface N\u003csub\u003e2\u003c/sub\u003eO values (~\u0026thinsp;12\u0026ndash;14 nmol L⁻\u0026sup1;) that increase sharply at intermediate depths, peaking at ~\u0026thinsp;49.5 nmol L⁻\u0026sup1; at approximately 100 m, where nitrate consumption begins. Below 120 m, concentrations decreased rapidly and reached near-zero at 150 m, indicating complete denitrification to N₂. It should be noted that no nitrite accumulation was observed, underscoring complete NO\u003csub\u003e3\u003c/sub\u003e- reduction to N\u003csub\u003e2\u003c/sub\u003e, as well as the efficiency of the redox transition, in addition to marking the establishment of anoxic\u0026ndash;euxinic conditions. Dissolved CH\u003csub\u003e4\u003c/sub\u003e concentrations exhibited a pronounced vertical gradient (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003el), from 10 nmol L\u003csup\u003e-1\u003c/sup\u003e in surface waters to approximately 19.200 nM at 150 m.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.5. Optical properties of dissolved organic matter.\u003c/b\u003e Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the absorption spectra obtained at stations E7 and E8. At E8, absorption coefficients were higher, between 130 and 150 m, than at the surface layer (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). In contrast, at E7, higher values were obtained at the surface layer (0\u0026thinsp;\u0026minus;\u0026thinsp;5 m) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). CDOM\u003csub\u003e325\u003c/sub\u003e exhibited elevated values (2\u0026thinsp;\u0026minus;\u0026thinsp;4 m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) in the upper 5 m of the water column at both sampling stations (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). Below this depth, values ​​ranged between 0.8 and 1.5 m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, except at station E8 at depths of 120\u0026thinsp;\u0026minus;\u0026thinsp;150 m, where they ​​increased from 3 to 8 m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). The SUVA\u003csub\u003e254\u003c/sub\u003e values exhibited a pattern similar to that of CDOM\u003csub\u003e325\u003c/sub\u003e at both sampling stations, with increased values of 3 to 5 mg C L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in surface waters (0\u0026thinsp;\u0026minus;\u0026thinsp;5 m) and lower levels (\u0026lt;\u0026thinsp;3 mg C L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) throughout the remainder of the sampling depths. An exception was observed at station E8, where elevated values from 5 to 9 mg C L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e were recorded in deep waters (120\u0026thinsp;\u0026minus;\u0026thinsp;150 m) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). Fluorescence intensity was higher at station E8 than at E7, particularly in deep waters. At E8, values ranged from 0.1 to 8.4 RU, while at E7 they varied between 0.1 and 3.1 RU throughout the water column (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef). The highest fluorescence values ​​were recorded by component C1 and the lowest by component C4 at both sampling stations. Fluorescence intensity profiles were similar between the surface layer and 120 m at E7 and E8, except at 100 m, where component C4 at station E8 reached a maximum of 4.4 RU (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee). Below 120 m, fluorescence intensities of components C1, C2, and C3 revealed values that ​​exceeded 2 RU at station E8. In contrast, values\u0026thinsp;\u0026lt;\u0026thinsp;2 RU were recorded at E7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef).\u003c/p\u003e \u003cp\u003eThe Parallel Factor (PARAFAC) analysis identified four fluorescent dissolved organic matter (fDOM) components (C1, C2, C3, and C4) in the study area, explaining 96.9% of the variance in the dataset (Fig. S5). Based on findings from peak locations and literature comparisons, fDOM components were classified as follows: two humic-like (C1 and C3), one marine humic-like (C2), and one protein-like (C4) components (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The first (C1, Ex/Em\u0026thinsp;=\u0026thinsp;245(330)/440 nm) and third (C3, Ex/Em\u0026thinsp;=\u0026thinsp;270(400)/505 nm) humic-like components exhibited two fluorescence peaks (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig. S5), characteristic of allochthonous terrestrial material, likely derived from terrestrial plants. The second component (C2), classified as marine humic-like, also exhibited two fluorescence peaks (Ex/Em\u0026thinsp;=\u0026thinsp;245(330)/440 nm) and is most likely associated with an autochthonous microbial source. Finally, component C4 (Ex/Em\u0026thinsp;=\u0026thinsp;275/302 nm) showed a protein-like (tyrosine-like) fluorescence peak, characteristic of a soluble autochthonous source produced in an aquatic environment (Fig. S5).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePARAFAC analysis. The reference peak component from \u003csup\u003e25, 26\u003c/sup\u003e .\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePARAFAC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eName double peak\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExcitation (range Ex) maximum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEmission (range Em) maximum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRegion (Chen et al., 2003)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComponent 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUV humic-like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirst peak (A)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c4\"\u003e \u003cp\u003e(245\u0026thinsp;\u0026minus;\u0026thinsp;250) 245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e(430\u0026thinsp;\u0026minus;\u0026thinsp;460) 440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII fulvic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTerrestrial allochthonous\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVisible humic-like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSecond peak (C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c4\"\u003e \u003cp\u003e(310\u0026thinsp;\u0026minus;\u0026thinsp;350) 330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e(430\u0026thinsp;\u0026minus;\u0026thinsp;460) 440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV humic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComponent 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUV humic-like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirst peak (A)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c4\"\u003e \u003cp\u003e(245\u0026thinsp;\u0026minus;\u0026thinsp;250) 245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e(370\u0026thinsp;\u0026minus;\u0026thinsp;395) 382,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII fulvic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMicrobial autochthonous\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVisible marine humic-like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSecond peak (M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c4\"\u003e \u003cp\u003e(280\u0026thinsp;\u0026minus;\u0026thinsp;315) 290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e(370\u0026thinsp;\u0026minus;\u0026thinsp;395) 382,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV humic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComponent 3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUV humic-like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirst peak (A)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c4\"\u003e \u003cp\u003e(260\u0026thinsp;\u0026minus;\u0026thinsp;280) 270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e(485\u0026thinsp;\u0026minus;\u0026thinsp;520) 505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV humic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTerrestrial allochthonous\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVisible humic-like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSecond peak (C+)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c4\"\u003e \u003cp\u003e(380\u0026thinsp;\u0026minus;\u0026thinsp;415) 400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e(485\u0026thinsp;\u0026minus;\u0026thinsp;520) 505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV humic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComponent 4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTyrosine-like, Protein-like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epeak (B)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c4\"\u003e \u003cp\u003e(270\u0026thinsp;\u0026minus;\u0026thinsp;280) 275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c5\"\u003e \u003cp\u003e(295\u0026thinsp;\u0026minus;\u0026thinsp;305) 302,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIV soluble microbial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAutochthonous\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e2.6. Microbial community structure and composition.\u003c/b\u003e Prokaryote abundance ranged from 149,590\u0026thinsp;\u0026plusmn;\u0026thinsp;43,956 to 550,714\u0026thinsp;\u0026plusmn;\u0026thinsp;63,372 cells mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Maximum abundances were observed in surface waters, decreasing to minimal values between 120 and 130 m (\u0026lt;\u0026thinsp;250,000 cells mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and increasing once more to approximately 300,000 cells mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in anoxic waters below 140 m (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Regarding prokaryote community diversity, a total of 2,075,016 16S rRNA gene sequences, produced by Illumina sequencing, were analyzed following resampling by rarefaction, corresponding to 3,241 and 13,396 amplicon sequence variants (ASVs) for archaea and bacteria, respectively. Rarefaction curves indicated that the sampling effort exceeded the curvilinear phase, with all samples reaching a plateau (Supplementary Fig.\u0026nbsp;6). Alpha diversity at station E8 ranged from 679 to 3,548, with the highest ASV richness (\u0026gt;\u0026thinsp;1,700) observed in anoxic waters (\u0026gt;\u0026thinsp;120 m; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). At the order level, between 44 and ~\u0026thinsp;60% of the prokaryote community in anoxic waters comprised bacterial groups, including Bacteroidetes, Arcobacteraceae, Latescibacterota, Desulfobacterales, Brocadiales, and Desulfatiglandales as well as the archaean domine of Nanoarchaeota, grouped in Woesearchaeales (Supplementary Fig.\u0026nbsp;7). In oxic waters, bacteria of the orders Flavobacteriales, the SAR11 clade, and Thiomicrospirales, in conjunction with archaea belonging to Nitrosopumilales and Marine Group II accounted for more than 45% of the prokaryote community in waters between 0 and 110 m (Supplementary Fig.\u0026nbsp;7). At the ASV level, members of the VC2.1 clade of Bacteroidetes, Acrobacteracea, Latescibacterota, SUP05, the \u003cem\u003eCandidatus\u003c/em\u003e Scalindua, and two members of the genus \u003cem\u003eDesulfatiglans\u003c/em\u003e were the most abundant bacterial taxa in anoxic waters (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Regarding archaea, representative ASVs were more abundant in oxic (10\u0026thinsp;\u0026minus;\u0026thinsp;110 m) than in anoxic waters, with a predominance of \u003cem\u003eCandidatus\u003c/em\u003e Nitrosopumilus, \u003cem\u003eCandidatus\u003c/em\u003e Nitrosopelagicus, and Marine Group II (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). In anoxic waters, representative archaeal taxa included two members of \u003cem\u003eCandidatus\u003c/em\u003e Nitrosopumilus and a member of the Woesearchaeales and Bathyarchaeia groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). Analysis of full-length 16S sequences revealed differences in bacterial community composition between the anoxic waters of station E8 and the deep oxic waters of control station E7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). In the anoxic waters of station E8, the most abundant and distinctive bacterial taxa related to members of the genera \u003cem\u003eDesulfobacula\u003c/em\u003e, \u003cem\u003eDesulfatiglans\u003c/em\u003e, \u003cem\u003eDesulfotignum\u003c/em\u003e, \u003cem\u003eDesulfobacter\u003c/em\u003e, \u003cem\u003eArcobacter\u003c/em\u003e, and \u003cem\u003eMalaciobacter\u003c/em\u003e, together accounting for more than 70% of the representative sequences (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed).\u003c/p\u003e "},{"header":"3. Discussion","content":"\u003cp\u003e Quitralco Fjord has been reported as one of the areas within the Patagonian fjord system experiencing hypoxic conditions, primarily due to prolonged water residence time (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef) and the dominance of community respiration, which promotes a decrease in dissolved oxygen concentrations6. Moreover, during oceanographic expeditions that covered the entire fjord, anoxic conditions were observed in the deep layer at the fjord head (90\u0026thinsp;\u003cb\u003e\u0026minus;\u003c/b\u003e\u0026thinsp;160 m), exhibiting oxygen concentrations of approximately 10 nM (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This trace oxygen level is considered anoxic according to \u003csup\u003e27\u003c/sup\u003e. As noted in the Introduction section, Quitralco Fjord is influenced by tectonic activity associated with the Liqui\u0026ntilde;e-Ofqui fault line that lies underneath the fjord head and is bounded by the surrounding volcanoes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Elevated deep-water temperatures (~\u0026thinsp;11\u0026deg; C, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-b), high H\u003csub\u003e2\u003c/sub\u003eS concentrations (~\u0026thinsp;100 \u0026micro;M, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb), and gas bubble emissions detected acoustically (Fig. S3) provide evidence of tectonic activity in the anoxic-euxinic Quitralco basin. Furthermore, elevated concentrations of heavy metals in surface sediments (for example, Fe, Mg, and Cu; Fig. S4) support the hypothesis of the influence caused by tectonic activity on the study area. However, the principal results of the present study stem from the detection of a deep fluorescence maximum (DFM) in a dark environment, as well as the influence of tectonic activity on biogeochemical cycles and the microbial community (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), which are discussed in the following section.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.1. Deep fluorescence maximum (DFM)\u003c/b\u003e. A DFM was consistently detected using a vertical microprofiler in the dark, deep anoxic basin of Quitralco Fjord, with a magnitude comparable to that measured at the photic surface layer (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg). The DFM exhibited vertical displacement in synchrony with the anoxic boundary layer, where turbidity also displayed a deep maximum (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg, and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eh). The surface fluorescence maximum recorded in October 2024 can be attributed to elevated surface Chl-a or fDOM concentrations. However, Chl-a concentrations (close to 0 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) do not account for the deep fluorescence profile behaviour (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ej). Rather, fDOM values with humic-like components (C1, C2 and C3) revealed maximum fluorescence within the anoxic layer, while the protein-like component (C4) peaked at 100 m. C4 maximum is likely associated with fresh, autochthonous (aquatic) and microbially-derived DOM material, as indicated by high biological fluorescence index (BIX) values (\u0026gt;\u0026thinsp;1, data not shown). In contrast, components C1, C2 and C3 are primarily associated with humic material and weak recent autochthonous inputs, as shown by the humification (HIX) index values (6\u0026thinsp;\u0026minus;\u0026thinsp;13, data not shown).\u003c/p\u003e \u003cp\u003eDOM is one of the Earth\u0026rsquo;s major carbon reservoirs \u003csup\u003e28\u003c/sup\u003e. The fraction of DOM that absorbs light, known as chromophoric DOM (CDOM), and its fluorescent sub-fraction (fDOM) are ubiquitous constituents of the aquatic DOM pool, strongly influencing the optical properties of the water column \u003csup\u003e29\u003c/sup\u003e. In coastal environments, CDOM and fDOM typically exhibit profiles with high surface concentrations that decrease rapidly with depth \u003csup\u003e30\u003c/sup\u003e. This vertical pattern reflects the primary sources of DOM, i.e., photosynthesis from the surface layers and terrestrial inputs from rivers. Although a portion of this organic material is labile and rapidly degraded or photodegraded, a significant proportion is refractory and resistant to decomposition.\u003c/p\u003e \u003cp\u003eIn Quitralco Fjord, measurements from control station E7 exhibited findings with a vertical profile consistent with that described above, with elevated concentrations of CDOM\u003csub\u003e325\u003c/sub\u003e (2\u0026thinsp;\u0026minus;\u0026thinsp;4 m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), SUVA\u003csub\u003e254\u003c/sub\u003e (3\u0026thinsp;\u0026minus;\u0026thinsp;5 mg L\u003csup\u003e\u0026minus;1\u003c/sup\u003em\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), fDOM (0.15\u0026thinsp;\u0026minus;\u0026thinsp;3 RU) and absorption\u003csub\u003e250\u0026minus;350\u003c/sub\u003e (5\u0026thinsp;\u0026minus;\u0026thinsp;10 m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) within the upper 5 m. These patterns indicate that DOM is of primarily terrestrial origin, characterized by high molecular weight, a high aromaticity and elevated concentrations of allochthonous humic compounds (C1 and C3). This suggests an active transformation of DOM within the water column by means of the actions of the bacterial community (C2). At station E8, similar surface values of CDOM\u003csub\u003e325\u003c/sub\u003e (2\u0026thinsp;\u0026minus;\u0026thinsp;3 m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), SUVA\u003csub\u003e254\u003c/sub\u003e (3\u0026thinsp;\u0026minus;\u0026thinsp;4 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), fDOM (0.15\u0026thinsp;\u0026minus;\u0026thinsp;3 RU), absorption\u003csub\u003e250\u0026minus;350\u003c/sub\u003e (5\u0026thinsp;\u0026minus;\u0026thinsp;8 m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) in addition to the same terrestrial characteristics of DOM were observed. However, all variables reached their maxima in deep anoxic waters, with a CDOM\u003csub\u003e325\u003c/sub\u003e of 4\u0026thinsp;\u0026minus;\u0026thinsp;8 m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, a SUVA\u003csub\u003e254\u003c/sub\u003e of 4\u0026thinsp;\u0026minus;\u0026thinsp;9 mg L\u003csup\u003e\u0026minus;1\u003c/sup\u003em\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, an fDOM of 1.5\u0026thinsp;\u0026minus;\u0026thinsp;8 RU, and an absorption\u003csub\u003e250\u0026minus;350\u003c/sub\u003e of 15\u0026thinsp;\u0026minus;\u0026thinsp;18 m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. These values ​​constitute the highest reported to date for deep waters in the Chilean fjord system. No previous information has been published with regards to optical properties of Quitralco Fjord. \u003csup\u003e31\u003c/sup\u003ereported CDOM\u003csub\u003e325\u003c/sub\u003e values for Puyuhuapi Fjord ​​within a similar range and vertical pattern to those observed in the present study at station E7. Additional measurements from Puyuhuapi Fjord and the Caleta Tortel area (unpublished data) also exhibit ranges and profiles comparable to those described for station E7. The maximum fDOM values ​​observed, particularly with regards to components C1 and C3 at E8, suggest that the anoxic waters of Quitralco Fjord contain substantial concentrations of highly refractory humic organic material capable of generating a DFM.\u003c/p\u003e \u003cp\u003eAnomalies from the classical pattern of optical properties in the water column have been recorded in different aquatic ecosystems, including coastal and oceanic environments in the Northern Hemisphere, where elevated CDOM and fDOM levels have been observed in greater detail\u003csup\u003e32, 33, 34, 35\u003c/sup\u003e. These observations suggest that within these deep waters there may be: i) local DOM production through mineralization of organic matter; ii) accumulation of refractory DOM; and iii) upward diffusion of DOM. Indeed, marine sediments are considered an important source of DOM to overlying seawater, comparable in magnitude to riverine input\u003csup\u003e36\u003c/sup\u003e. In Quitralco Fjord, all these processes may contribute to the anomalous distribution of CDOM and fDOM in the water column, particularly given the euxinic characteristics of the basin. Such characteristics may result from microbial mineralization of DOM in deep waters, which consumes oxygen (leading to hypoxia/anoxia conditions) and releases hydrogen sulfide as a metabolic by-product\u003csup\u003e37\u003c/sup\u003e. In addition, the presence of sulfate-reducing bacteria (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed) also plays an important role in the formation of humic-like substances\u003csup\u003e34\u003c/sup\u003e, ultimately leading to substantial alterations in DOM composition\u003csup\u003e38\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.2. Biogeochemical conditions and microbial community structure, and their association with tectonic activity.\u003c/b\u003e The high concentrations of H\u003csub\u003e2\u003c/sub\u003eS detected in the deep anoxic layer (120\u0026thinsp;\u0026minus;\u0026thinsp;150 m) of Quitralco Fjord reveal a previously unrecognized euxinic ecosystem that should be considered in the global distribution of such environments\u003csup\u003e11\u003c/sup\u003e. This system is an ideal area in which to improve understanding around the microbial community structures and biogeochemistry (BGC) in fjord systems associated with tectonic activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The Black Sea remains the region with the highest reported H\u003csub\u003e2\u003c/sub\u003eS concentrations (200\u0026thinsp;\u0026minus;\u0026thinsp;400 \u0026#120583;M), largely driven by sulfate-reducing bacteria activity\u003csup\u003e39\u003c/sup\u003e. However, H\u003csub\u003e2\u003c/sub\u003eS concentrations recorded at between 50\u0026thinsp;\u0026minus;\u0026thinsp;100 \u0026#120583;M in the deep anoxic basin of Quitralco Fjord (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb) exceed the values observed in the Baltic Sea (7\u0026thinsp;\u0026minus;\u0026thinsp;23 \u0026#120583;M;\u003csup\u003e40\u003c/sup\u003e) as well as the By Fjord (10 \u0026#120583;M) in the western Sweden\u003csup\u003e41\u003c/sup\u003e. While the origin of these reduced sulfate compounds (\u0026sum;H\u003csub\u003e2\u003c/sub\u003eS) appears to be primarily linked to tectonic activity, the presence of sulfate-reducing communities likely also contributes to the substantial accumulation of H\u003csub\u003e2\u003c/sub\u003eS.\u003c/p\u003e \u003cp\u003eNitrous oxide (N₂O) is a sensitive tracer of suboxic and anoxic processes, as it accumulates during nitrification\u0026ndash;denitrification coupling but is consumed when complete denitrification to N₂ prevails. N\u003csub\u003e2\u003c/sub\u003eO is also a potent greenhouse gas and an ozone depleting agent, and its net production or consumption is strongly modulated by temporal and vertical oxygen gradients and the availability of nitrogen species\u003csup\u003e42\u003c/sup\u003e. For example, in Saanich Inlet, British Columbia, Canada, one of the most intensively studied seasonally anoxic fjords in the world; seasonal deep-water oxygenation alters the mechanisms of N₂O production. During oxic phases, ammonium oxidation dominates N\u003csub\u003e2\u003c/sub\u003eO production, whereas under anoxic conditions, N₂O is reduced or consumed through complete denitrification\u003csup\u003e43\u003c/sup\u003e. Steep O\u003csub\u003e2\u003c/sub\u003e gradients are known hotspots of intensive microbial activity, as described in the present study. Accordingly, the elevated N\u003csub\u003e2\u003c/sub\u003eO concentrations detected in this particular part of the oxycline (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ek) may result from multiple nitrogen transformation processes, including ammonia oxidation, nitrifier denitrification, and incomplete denitrification. These processes are accompanied by high biodiversity and abundance of chemolithoautotrophic nitrate-reducing, sulfur-oxidizing γ-proteobacteria (SUP05 cluster) observed in the present study (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). It should be noted that the maximum and minimum N\u003csub\u003e2\u003c/sub\u003eO concentrations in Quitralco Fjord were both higher and lower, respectively, than those reported in relation to other anoxic fjords\u003csup\u003e43, 44\u003c/sup\u003e. Extreme N\u003csub\u003e2\u003c/sub\u003eO concentrations such as these may be attributable to the presence of nitrate-rich waters below the surface layer, in conjunction with the presence of electron donor compounds, such as organic matter and additional reductants including CH₄, H₂S or reduced metals (Fe\u0026sup2;⁺, Mn\u0026sup2;⁺). These inputs enhance DO demand, intensify anoxia and promote complete denitrification to N\u003csub\u003e2\u003c/sub\u003e. Elevated microbial stimulation occurs when alternative substrates, such as CH₄ and H₂S sustain chemoautotrophic communities, thereby altering the oxidant/reductant balance and nitrogen transformation pathways\u003csup\u003e42, 45\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn Quitralco Fjord, intense organic matter supply combined with tectonic seepage, likely involving CH₄ and H₂S, may enhance reducing conditions, stimulating partial denitrification and generating a pronounced N₂O maximum (~\u0026thinsp;45 nM), while denitrification also proceeds to completion, driving N₂O concentrations to zero. \u003csup\u003e46\u003c/sup\u003einvestigated the activity and abundance of denitrifying bacteria in the subsurface biosphere associated with diffuse hydrothermal vents on the Juan de Fuca Ridge. These bacteria perform denitrification, a crucial process in the nitrogen cycle, by converting nitrogen oxides into nitrogen gas by means of chemosynthetic chemical energy sources. Their research helped to improve understanding around the role and function of these microorganisms in deep-sea ecosystems fueled by chemical energy rather than sunlight.\u003c/p\u003e \u003cp\u003eThe large-scale methane accumulation could indicate intense benthic methane release due to in situ methanogenesis; although under euxinic conditions methanogenesis is usually inhibited\u003csup\u003e47\u003c/sup\u003e. The extreme CH\u003csub\u003e4\u003c/sub\u003e accumulation in the euxinic bottom waters of Quitralco reaffirms negligible oxidation due to the absence of oxygen and nitrate. In contrast, along the oxycline (redoxcline), dissolved methane and sulfide are largely removed by strong aerobic and anaerobic oxidation. Critically, inputs of CH₄, H₂S and other reductants can stimulate intense chemoautotrophic activity, methanotrophy, sulfur oxidation and even ammonium oxidation which consumes available oxidants and supports in situ primary production, thereby reshaping carbon and nitrogen cycling.\u003c/p\u003e \u003cp\u003eIn addition, nutrient distributions revealed a particular pattern, with nitrate exhibiting a clear oxic, suboxic and anoxic sequence. The presence of Subantarctic Water (SAAW) explains the relatively high NO₃⁻ concentrations above 100 m\u003csup\u003e2\u003c/sup\u003e, but the depressed N:P and N:Si ratios, in conjunction with peaks in P and Si, may indicate other sources than aerobic or anaerobic organic matter mineralization. For example, phosphate concentrations near 6 \u0026micro;M (and up to 20 \u0026micro;M at 150 m) are well above typical SAAW end-member values (Linford et al., 2024). If these nutrients were derived solely from aerobic organic-matter remineralization, N and P would accumulate in near-Redfield proportions, which is not observed (N:P ≪ 16). The co-occurrence of near-zero nitrate, very high CH₄, and elevated silicate concentrations indicates the presence of strongly reducing conditions with internal P release, likely driven by reductive dissolution of Fe-bound P and benthic diffusive fluxes\u003csup\u003e48, 49,50\u003c/sup\u003e. In addition, tectonic seepage or cold-vent inputs are a plausible external source of P- and Si-rich reduced fluids; prolonged residence times would then allow the accumulation thereof at depth. Discriminating between sedimentary and tectonic sources could be achieved using tracers (for example, dissolved Fe/Mn, \u0026sup3;He, Ra isotopes) and combined pore water-water-column flux measurements.\u003c/p\u003e \u003cp\u003eThe plasticity of the prokaryotic community structure (i.e., composition and function) is widely documented across extreme gradients in a varied array of environments. In the case of the anoxic basin (Station E8), a clear shift is observed in microbial community composition throughout the water column, particularly in oxic, hypoxic and euxinic waters. In addition, several geochemical fingerprints indicate changes in potential microbial metabolic functions throughout the redox gradient of the water column. Thus, heterotrophic bacteria, primarily related to the Flavobacteriales and SAR11 groups, modulate carbon cycling in oxic waters\u003csup\u003e51, 52\u003c/sup\u003e while chemolithoautotrophic nitrifying archaea, such as Nitrosopumilales, regulate ammonium oxidation across the oxycline (20\u0026thinsp;\u0026minus;\u0026thinsp;50 m depth) and in hypoxic waters (50\u0026thinsp;\u0026minus;\u0026thinsp;100 m depth). This process likely explains the accumulation of nitrate and the absence of ammonium\u003csup\u003e53, 54\u003c/sup\u003e observed directly above the anoxic layer. Additional archaeal organisms abundant in the oxygenated waters were associated with Marine Group II, which are organisms characterized by their metabolic potential for obligate aerobic heterotrophs, many of which are capable of harnessing solar energy through proteorhodopsins\u003csup\u003e55\u003c/sup\u003e. In contrast, across the deep-oxycline (100\u0026thinsp;\u0026minus;\u0026thinsp;120 m depth) and throughout the anoxic environment (below 100 m depth), the large estimated nitrogen deficit indicates substantial nitrate consumption, with nitrate acting as an electron acceptor in the absence of oxygen\u003csup\u003e56\u003c/sup\u003e to sustain primary chemical production or organic matter respiration. The microbial decomposition of organic matter in this layer may be further supported by the pronounced accumulation of ammonium, possibly derived from remineralization (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg). In this regard, the abundance of heterotrophic bacterial groups, such as Bacteroidetes (VC2.1) and Latescibacterota in the euxinic zone, which are characterized by their ability to tolerate or even thrive in the absence of oxygen\u003csup\u003e57, 58, 59\u003c/sup\u003e, is likely a contributory factor to this nitrogen deficit, primarily by means of nitrate consumption. These groups are capable of oxidizing complex organic compounds in order to obtain energy. In particular, Bacteroidetes can do so by reducing NO/N\u003csub\u003e2\u003c/sub\u003eO and polysulfides\u003csup\u003e59\u003c/sup\u003e, while Latescibacterota do so via dissimilatory nitrate reduction, specifically by reducing nitrate to nitrite (for example\u003csup\u003e57\u003c/sup\u003e and references therein).\u003c/p\u003e \u003cp\u003eThe accumulation of nitrite, particularly evident during December 2024 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed), indicates a decoupling between the reduction rates of the different steps of the denitrification pathway, namely from nitrate reduction to nitrite relative to the subsequent reduction of nitrite to nitric oxide/nitrous oxide. Additionally, given that the oxidation of reduced sulfur compounds represents an important source of inorganic chemical energy for inorganic carbon fixation\u003csup\u003e60, 62\u003c/sup\u003e,the increasing accumulation of hydrogen sulfide (\u0026sum;H \u003csub\u003e2\u003c/sub\u003eS) recorded across the deepest layer (\u0026gt;\u0026thinsp;120 m depth) indicates the potential of this system to support chemolithoautotrophy through the coupling of the sulfur, carbon and nitrogen cycles. Arcobacteraceae, for example, a ubiquitous mixotrophic bacteria and the second most abundant sequence found under euxinic conditions, can fix carbon from sulfur oxidation and nitrate reduction\u003csup\u003e62\u003c/sup\u003e. Similarly, the SUP05 clade of Gammaproteobacteria (Thioglobaceae) use sulfide and other reduced forms of inorganic sulfur to obtain energy with which to fix inorganic carbon, while reducing nitrate, nitrite, nitric oxide, or nitrous oxide via the autotrophic denitrification pathway \u003csup\u003e60,63,64\u003c/sup\u003e. Furthermore, several members of the \u003cem\u003eDesulfatiglans\u003c/em\u003e genus were among the most abundant taxa identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Members of this group belong to the deltaproteobacterial family, Desulfobacteraceae, and are dissimilatory sulfate reducers often found in anoxic marine environments, primarily in surface sediments with limited sulfate and organic carbon. As such, they are capable of using aromatic compounds as energy sources \u003csup\u003e65, 66\u003c/sup\u003e. The presence of this group is of particular interest because sulfate reduction leads to the formation of H\u003csub\u003e2\u003c/sub\u003eS, therefore raising concerns about the relevance of biological-mediated processes versus tectonic inputs in the production of H\u003csub\u003e2\u003c/sub\u003eS in the fjord. In addition, the detection of the predominant marine anammox bacterium \u003cem\u003eCandidatus Scalindua\u003c/em\u003e \u003csup\u003e67, 68\u003c/sup\u003e as one of the relatively well-represented sequences in the euxinic layer is intriguing, since this ammonium-based metabolism is inhibited even at low H\u003csub\u003e2\u003c/sub\u003eS concentrations \u003csup\u003e69,70\u003c/sup\u003e. Such inhibition may help to explain the large-scale accumulation of ammonium observed. Collectively, these results reopen the debate on the metabolic potential of organisms identified from DNA samples, underscoring the need for targeted experimental approaches in order to quantify the magnitude of the processes in which these organisms are putatively involved.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.3. Mechanism-driven anoxic and euxinic conditions.\u003c/b\u003e The results detailed in the present study suggest the existence of two new major mechanisms driving anoxia and euxinic conditions in Quitralco Fjord. 1) From the physical oceanography perspective, Quitralco Fjord has been identified as one of the fjords in the northern Patagonian with the longest water residence times\u003csup\u003e71, 6\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef). This characteristic is primarily associated with the irregular topography of the fjord, particularly the presence of a numerous sills that reduce marine current velocity and, therefore, contribute directly to the establishment of anoxic conditions in the waters (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). Moreover, recent measurements of hydrographic conditions (temperature and salinity) and DO throughout the fjord from March 2023 to December 2024 revealed the entrance of cold-oxygenated waters into the fjord from the subsurface layer, which subsequently spread across the entire deep fjord basin (Fig. S2). A ventilation event observed in 2024 resulted in a downward displacement of the anoxic boundary layer by approximately 30 m (from 90 m to 120 m, see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). This highlights the key role of ventilation events in modulating the vertical displacement of the anoxic layer. Nevertheless, the physical drivers involved in the interannual variability of deep ventilation observed in Quitralco Fjord warrant further investigation. 2) A second mechanism driving the anoxic conditions in the fjord arises from the geochemical oxygen consumption arising from reactions with H\u003csub\u003e2\u003c/sub\u003eS, ammonium and methane (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The geochemical production of H\u003csub\u003e2\u003c/sub\u003eS resulting from tectonic activity underneath Quitralco Fjord generates a toxic environment similar to the ancient anoxic Proterozoic oceans\u003csup\u003e72\u003c/sup\u003e. These conditions appear to support the colonization of abundant marine microbial organisms, dominated primarily by bacteria and, to a lesser extent, archaea (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Taken in conjunction, the aforementioned drivers ensure that the fjord provides researchers with a unique destination in which to further general understanding of the complex biological and biogeochemical processes occurring in the current Holocene era.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThe Patagonian fjords comprise an extensive system of not only fjords, but also channels, sounds, and bays that interact constantly with the adjacent eastern South Pacific Ocean waters. They are also subject to continuous natural and anthropogenic pressures. Over the past decade, oceanographic expeditions have investigated water mass variability, generally revealing a predominance of oxygenated waters. Nevertheless, hypoxic conditions have been observed in subsurface layers of certain fjords since the earliest research expeditions. Notably, the present study identifies the first anoxic and euxinic area reported in northern Patagonia, at the deep fjord head (90\u0026thinsp;\u003cb\u003e\u0026minus;\u003c/b\u003e\u0026thinsp;160 m depth) of Quitralco Fjord. This finding provides a modern analogue of ancient anoxic-euxinic oceans and the fjord waters represent a natural laboratory in which to test CH₄--S-Nox redox coupling and chemosynthetic pathways under contemporary deoxygenation. Indeed, elevated concentrations of H\u003csub\u003e2\u003c/sub\u003eS (50\u0026thinsp;\u003cb\u003e\u0026minus;\u003c/b\u003e\u0026thinsp;100 \u0026micro;M) and CH\u003csub\u003e4\u003c/sub\u003e (up to 19,000nM) were identified in the bottom waters. The co-occurrence of a deep fluorescence maximum, elevated DOC, and a modest increase in prokaryotic cells is consistent with the presence of chemolithotrophic prokaryotes (for example, S-, ammonium and methane-oxidizers). Coupled with long water-residence times and physical characteristics, these conditions help sustain anoxia/euxinia and favour the accumulation of reduced compounds in bottom waters, which are then rapidly oxidized across the oxycline, forming an effective oxidative filter. Concurrently, vertical profiles of reductant compounds closely matched the microbial community composition, including an abundance of sulfate reducers (\u003cem\u003eDesulfobacula, Desulfatiglans, Desulfotignum, Desulfobacter\u003c/em\u003e) and sulfur oxidizers (Arcobacteraceae/Malaciobacter, SUP05), as well as anammox (\u003cem\u003eCa.\u003c/em\u003e Scalindua) and VC2.1. In contrast, oxic layers (10\u0026ndash;110 m) were enriched in ammonia-oxidizing archaea (\u003cem\u003eCa.\u003c/em\u003e Nitrosopumilus, \u003cem\u003eCa.\u003c/em\u003e *\u003cem\u003eNitrosopelagicus\u003c/em\u003e) and Marine Group II. This community pattern is consistent with observed biogeochemistry, and helps to explain the accumulation of H₂S/CH₄ and the depressed N:P and N:Si, which are partially explained by fixed-N loss through denitrification (observed as complete N\u003csub\u003e2\u003c/sub\u003eO consumption) and anammox, followed by re-oxidation across the oxycline.\u003c/p\u003e "},{"header":"5. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003cp\u003e \u003cb\u003e5.1. Oceanographic data.\u003c/b\u003e A total of 77 profiles of temperature, salinity, dissolved oxygen, fluorescence, and turbidity (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) were collected using a vertical microprofiler model VMP250 RDL from Rockland Scientific \u003cb\u003e(\u003c/b\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://rocklandscientific.com/products/profilers/vmp-250\u003c/span\u003e\u003cspan address=\"https://rocklandscientific.com/products/profilers/vmp-250\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e This instrument collected data at a sampling rate of 64 Hz and can be used at depths of up to 500 m, with an optimal vertical free-fall velocity of ~\u0026thinsp;70 cms\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. In addition, the VMP250 RDL features a high-response RINKO dissolved oxygen (DO) sensor (63% response in less than 1 second in water) with an initial accuracy of \u0026plusmn;\u0026thinsp;2.0 \u0026micro;M, as well as fluorescence and turbidity sensors provided by JFE Advantech from Japan.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChronology of oceanographic expeditions and sampling activities in Quitralco Fjord.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExpeditions\u003c/p\u003e \u003cp\u003e(Austral seasons)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDate\u003c/p\u003e \u003cp\u003e(mm, yyyy)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTDO\u003c/p\u003e \u003cp\u003estations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWater sampling\u003c/p\u003e \u003cp\u003estations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAnalysis of water samples\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePN-Winter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAugust 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePN-Summer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarch 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePN-Autumn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJune 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePN-Winter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAugust 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePN- Autumn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJune 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePN-Winter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAugust 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAmmonium\u003c/p\u003e \u003cp\u003eInorganic nutrients\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFONDECYT-Spring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOctober 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eH\u003csub\u003e2\u003c/sub\u003eS\u003c/p\u003e \u003cp\u003eInorganic nutrients\u003c/p\u003e \u003cp\u003eBiogeochemical parameters\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePN-Spring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecember 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eH\u003csub\u003e2\u003c/sub\u003eS, ammonium\u003c/p\u003e \u003cp\u003eInorganic nutrients\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePN-Winter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJuly 2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGases (N\u003csub\u003e2\u003c/sub\u003eO and CH\u003csub\u003e4\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e5.2. Trace oxygen profilers.\u003c/b\u003e Oxygen measurements within the anoxic layer were conducted using a uTail+ instrument, which enables detection of ultralow oxygen concentrations (\u0026lt;\u0026thinsp;1\u0026micro;M). The uTail\u0026thinsp;+\u0026thinsp;is an upgraded version of the Trace Oxygen Profiler (TOP) instrument described in \u003csup\u003e73\u003c/sup\u003e. Both instruments share the same fundamental operational principles and methodologies. Data was calibrated using the provided zero-point calibration, in-house laboratory-based multipoint calibrations, and corrections for temperature and pressure. The instrument was mounted on an RBR CONCERTO CTD frame and deployed at the same location where CTDO and biogeochemical data were collected (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Upcast profiles from uTail+ were prioritized because the ascent speed is generally higher than the descent speed, resulting in an increased flow around the sensor/CTD package. Furthermore, a significant amount of oxygen appears to be released from the CTD unit itself, a process that is likely time-dependent. Consequently, the upcast should minimize contamination and provide more representative oxygen readings in hypoxic environments.\u003c/p\u003e \u003cp\u003e \u003cb\u003e5.3. Acoustic data.\u003c/b\u003e Backscatter or echo intensity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) was measured from the surface to the bottom at a 1 min temporal resolution using a 307.7 kHz Teledyne RDI Workhorse Acoustic Doppler Current Profiler (ADCP). The downward-facing sensor was deployed during the October 2024 expeditions, collecting data at 1 m vertical resolution over a 24-hour sampling period. Echo intensity indicates the strength of the ADCP acoustic signal (\u0026ldquo;ping\u0026rdquo;) reflected by suspended particulates in the water column. Following corrections for signal attenuation, water velocity, and instrument-specific factors, echo intensity was converted to volume backscatter (\u003cem\u003eSv\u003c/em\u003e). This parameter serves as a proxy for zooplankton biomass, pycnocline depth, and suspended sediment abundance, which typically accumulate at density interfaces between water masses \u003csup\u003e74, 75\u003c/sup\u003e. The ADCP echo intensity was converted to volume backscatter (\u003cem\u003eSv\u003c/em\u003e, dB re 1 m\u003csup\u003e\u003cem\u003e\u0026minus;\u003c/em\u003e\u0026thinsp;1\u003c/sup\u003e) using the following conversion formula:\u003c/p\u003e \u003cdiv id=\"Equ1\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:{\\:\\:\\:\\:\\:\\:S}_{v}=C+10log\\left[\\left(Tx+273.16\\right){R}^{2}\\right]-{L}_{DBW}-{P}_{DBW}+2\\alpha\\:R+{K}_{c}\\left(E-{E}_{r}\\right)$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn this equation, \u003cem\u003eC\u003c/em\u003e is a sonar-configuration scaling factor (-148.2 dB) specific to the RDI Workhorse Sentinel ADCP, \u003cem\u003eTx\u003c/em\u003e is the temperature at the transducer (\u0026deg;C), \u003cem\u003eL\u003c/em\u003e is log10 (transmit-pulse length, L\u0026thinsp;=\u0026thinsp;8.13 m), \u003cem\u003ePDBW\u003c/em\u003e is log10 (output power, 15.5 W), \u003cem\u003eα\u003c/em\u003e is the absorption coefficient (dB m\u003csup\u003e\u003cem\u003e\u0026minus;\u003c/em\u003e\u0026thinsp;1\u003c/sup\u003e), \u003cem\u003eKc\u003c/em\u003e is a beam-specific sensitivity coefficient (provided by the manufacturer as 0.45), \u003cem\u003eE\u003c/em\u003e is the recorded automatic gain control (AGC), and \u003cem\u003eEr\u003c/em\u003e is the minimum AGC recorded (40 dB). The beam average of the AGC for the 4 ADCP transducer heads was used to obtain optimal results, following the procedure outlined in\u003csup\u003e76\u003c/sup\u003e. Finally, \u003cem\u003eR\u003c/em\u003e is the slant range to the sample bin (m), which is corrected using the depth\u003csup\u003e77\u003c/sup\u003e. Therefore, \u003cem\u003eR\u003c/em\u003e is expressed as:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:R=\\frac{b+\\frac{L+d}{2}+\\left(\\left(n-1\\right)d\\right)+\\left(\\frac{d}{4}\\right)}{cos\\zeta\\:}\\frac{c\u0026macr;}{{c}_{I}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003eb\u003c/em\u003e is the blanking distance (3.23 m), \u003cem\u003eL\u003c/em\u003e is the transmit pulse length (same as above), \u003cem\u003ed\u003c/em\u003e is the depth cell size (1 m), \u003cem\u003en\u003c/em\u003e is the depth cell number of the particular scattering layer being measured, \u003cem\u003eζ\u003c/em\u003e is the beam angle (20\u0026deg;), \u003cem\u003eC\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u0026minus;\u003c/em\u003e\u003c/sup\u003e is the average sound speed from the transducer to the depth cell (1,453 m s\u003csup\u003e\u003cem\u003e\u0026minus;\u003c/em\u003e\u0026thinsp;1\u003c/sup\u003e), and \u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003eI\u003c/em\u003e\u003c/sub\u003e is the nominal sound speed used by the instrument (1,454 m s\u003csup\u003e\u003cem\u003e\u0026minus;\u003c/em\u003e\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003e5.4. Zooplankton sampling.\u003c/b\u003e Stratified mesozooplankton samples were collected on 9 October 2024 using a WP2 net (300 \u0026micro;m mesh, 50 cm mouth diameter, equipped with a flowmeter) during a single vertical nighttime tow (22:00 local time). Sampling spanned four depth strata: 0\u0026thinsp;\u0026minus;\u0026thinsp;50 m, 50\u0026thinsp;\u0026minus;\u0026thinsp;100 m, 100\u0026thinsp;\u0026minus;\u0026thinsp;120 m, and 120\u0026thinsp;\u0026minus;\u0026thinsp;150 m. Discrete stratum sampling was achieved using a double-release trigger system (Puget Sound Workshop dba Research Nets). Samples were preserved on board in 5% formaldehyde. Laboratory processing included the sorting of functional zooplankton groups, measuring individual lengths, and classifying organisms into three size categories (\u0026lt;\u0026thinsp;1 mm, 1\u0026thinsp;\u0026minus;\u0026thinsp;5 mm, \u0026gt;\u0026thinsp;5 mm). Abundance was standardized as individuals per cubic meter (ind/m\u003csup\u003e3\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003e5.5. Sediment sampling and heavy metal analysis.\u003c/b\u003e At each station, sediments were collected using a 0.1 m\u0026sup2; Van Veen grab for the quantification of heavy metals (HM). Three undisturbed sub-samples were extracted from the upper 3 cm of each grab using a dark plastic corer (8 cm in length \u003cem\u003e\u0026times;\u003c/em\u003e 6 cm in diameter), transferred to a 60 mL plastic flask wrapped in aluminium foil, and preserved at \u0026minus;\u0026thinsp;20\u0026deg;C until HM analysis. Heavy metal processing took place in line with the protocol described by \u003csup\u003e78\u003c/sup\u003e, using the EPA method 3050B \u003csup\u003e79\u003c/sup\u003e. Sediments were dried at 60\u0026deg;C and sieved through a 60 \u0026micro;m mesh. One gram of the \u0026lt;\u0026thinsp;60 \u0026micro;m sediment fraction was subjected to acidic digestion using nitric and hydrochloric acid to extract metals. Digestion was completed with 10 mL of 1:1 hydrogen peroxide at 95 \u0026deg; \u003cem\u003e\u0026plusmn;\u003c/em\u003e 5\u0026deg;C. The remaining solution was analyzed via atomic absorption spectrophotometry (PERKIN ELMER Inc, ANALYST 200, Waltham, MA, USA) for Cu, Cd, Cr, Pb, Zn, Mn, Ni, Mg, and Fe concentrations (\u0026micro;g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, triplicate measurements).\u003c/p\u003e \u003cp\u003e \u003cb\u003e5.6. Hydrogen sulfide concentration.\u003c/b\u003e The concentrations of aqueous hydrogen sulfide species (\u0026sum;H\u003csub\u003e2\u003c/sub\u003eS) were determined following Jessen et al. (2022). Briefly, water samples were collected directly into glass cells from Niskin bottles. Immediately after collection, reagents were added to fix the \u0026sum;H\u003csub\u003e2\u003c/sub\u003eS, and the concentration was analyzed using the methylene blue method directly on board using a HACH portable colorimeter (Hach DR900, HACH Company, Loveland, CO, USA).\u003c/p\u003e \u003cp\u003e \u003cb\u003e5.7. Dissolved organic carbon, inorganic nutrients, and chlorophyll-a.\u003c/b\u003e Dissolved organic carbon (DOC) concentrations were determined from 60 mL water samples collected at each sampling depth and filtered through pre-combusted 25 mm Whatman GF/F filters (450\u0026deg;C for four h) and stored in plastic sampling containers (HDPE) at -20\u0026deg;C until analysis. Prior to analysis, samples were acidified with 40 \u0026micro;L of phosphoric acid. DOC concentrations were measured as non-purgeable organic carbon (NPOC) using a TOC-L\u003csub\u003eCPH\u003c/sub\u003e high temperature analyzer (Shimadzu TOC-LCPH FA, J100), equipped with a high-sensitivity catalyst. Each individual DOC concentration value obtained represents the average of two to three sample injections. Prior to analyses and between batches, deep seawater reference samples (provided by the University of Miami) were analysed to verify analytical accuracy and stability over time. Water samples of 500 mL from each sampling depth were collected for inorganic nutrient analyses (nitrate, nitrite, phosphate, and silicate). Samples were filtered through Whatman GF/F filters and filtrates were stored in plastic containers (HDPE). Samples were frozen at -20\u0026deg;C until laboratory analysis. Concentrations of inorganic nutrients were determined spectrophotometrically according to standard methods (Strickland and Parsons, 1968). Water samples of 125 mL were collected from each sampling depth to determine ammonium concentrations. These samples did not undergo filtering and a phenol solution (4 mL) was immediately added. Ammonium concentrations were calculated in the laboratory in line with the method proposed by Solorzano (1969). N deficit (N*) was calculated following the method proposed by Gruber and Sarmiento (1997), based on the relationship between fixed inorganic N species (nitrate, nitrite and ammonium) and phosphate concentrations. For total chlorophyll-a (Chl-a), two 1,000-mL water samples from each sampling depth were filtered through Whatman GF/F filters. Filters were immediately frozen at -20\u0026deg;C until subsequent analysis by fluorometry. Pigments were extracted with 90% v/v acetone, as per standard procedures (Parsons et al., 1984).\u003c/p\u003e \u003cp\u003e \u003cb\u003e5.8. N\u003c/b\u003e \u003csub\u003e \u003cb\u003e2\u003c/b\u003e \u003c/sub\u003e \u003cb\u003eO and CH\u003c/b\u003e \u003csub\u003e \u003cb\u003e4\u003c/b\u003e \u003c/sub\u003e \u003cb\u003eanalysis\u003c/b\u003e. Dissolved CH₄ and N₂O were sampled in triplicate at the same depths as nutrient samples. Subsamples were transferred into 20 mL glass vials and preserved with 0.05 \u0026micro;L of saturated HgCl₂, to inhibit microbial activity, following the recommendations of \u003csup\u003e80\u003c/sup\u003e. Gas concentrations were determined using the headspace equilibration technique. A 5 mL volume of ultra-pure helium was added to each vial to create the headspace, which was equilibrated at 30\u0026deg;C under constant agitation. Subsequently, 500 \u0026micro;L of the headspace were manually injected into two gas chromatographs: one Agilent 7697A, equipped with a flame ionization detector (FID) for CH₄, and one Shimadzu 17A, fitted with an electron capture detector (ECD) for N₂O. Both systems were operated at 30\u0026deg;C with ultra-pure N₂ as the carrier gas (flow rate: 2.6 mL min⁻\u0026sup1;), using an Rt-QS-BOND capillary column (30 m \u0026times; 0.53 mm ID \u0026times; 20 \u0026micro;m). Calibration curves consisted of six points prepared from certified standards (Air Liquide Company), balanced with helium. CH₄ standards ranged from 1 to 20 ppm (1, 2.5, 5, 10, 20 ppm), and N₂O standards from 0.25 to 2 ppm (0.25, 0.35, 0.50, 1, 2 ppm). Zero points were obtained with ultra-pure helium. Both detectors exhibited linear responses (R\u0026sup2; = 0.999). Analytical precision was ~\u0026thinsp;5% and samples with coefficients of variation\u0026thinsp;\u0026gt;\u0026thinsp;10% were discarded. Samples exceeding the calibration range, such as those found in bottom waters, were diluted with 5 \u0026micro;L aliquots, and concentrations were corrected for the corresponding dilution factor. Dissolved gas concentrations (C_gas, nmol L⁻\u0026sup1;) were calculated as:\u003c/p\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eC\u003csub\u003e\u003cem\u003eGas\u003c/em\u003e\u003c/sub\u003e [nmol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e] = ( β \u003cem\u003ex\u003c/em\u003e P V\u003csub\u003ewp\u003c/sub\u003e + (\u003cem\u003ex\u003c/em\u003e P / R T) V\u003csub\u003ehs\u003c/sub\u003e ), (3)\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003ewhere β is the solubility constant of the gas in water, x is the mole fraction measured by gas chromatography, P is the atmospheric pressure (atm), V_wp is the water phase volume (L), V_hs is the headspace volume (L), R is the universal gas constant (0.08205 L atm K⁻\u0026sup1; mol⁻\u0026sup1;), and T is the absolute temperature (K). Solubility corrections were applied in line with the recommendations of \u003csup\u003e81\u003c/sup\u003e for CH₄ and \u003csup\u003e82\u003c/sup\u003e for N₂O.\u003c/p\u003e \u003cp\u003e \u003cb\u003e5.9. Optical properties of dissolved organic matter.\u003c/b\u003e The optical properties of DOM, including CDOM and fDOM were analysed to study its distribution and infer its composition and source. Water samples for CDOM and fDOM were filtered through pre-combusted 25 mm GF/F filters (Whatman) and stored in 60 mL plastic bottles (HDPE). Samples were frozen at -20\u0026deg;C until subsequent laboratory analysis. DOM optical properties were determined using a spectrofluorometer (Aqualog, Horiba, UV-800-C) with a 1 cm quartz cuvette. CDOM concentrations were measured using the absorption spectra at 325 nm as a proxy (Nelson et al., 2007). Spectral scans were acquired between the 200 and 700 nm wavelength range, using ultrapure water as a blank. Absorption coefficients (a\u003csub\u003eλ\u003c/sub\u003e) of CDOM (m\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) were calculated according to the equation:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003ea(\u003csub\u003eλ\u003c/sub\u003e)\u0026thinsp;=\u0026thinsp;2.303 * Abs\u003csub\u003e(λ)\u003c/sub\u003e/l (4)\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere Abs\u003csub\u003e(λ)\u003c/sub\u003e is the absorbance at λ wavelength (after subtraction of the average absorbance between 600 and 700 nm), l is the optical path length (m), and 2.303 is the factor to convert base-10 to a natural logarithm (Aiken 2014). Specific UV absorbance at 254 nm (SUVA\u003csub\u003e254\u003c/sub\u003e) was calculated by dividing CDOM absorbance at 255 nm by the DOC concentration \u003csup\u003e30\u003c/sup\u003e. For fDOM measurements, emission scans were acquired from 250 to 800 nm at 2.5-nm intervals, with excitation wavelengths ranging from 200 to 700 nm at 5-nm intervals. Fluorescence spectra were scanned with an integration time of 2 seconds, a pixel increment of 4, and a medium gain setting. Corrections for the inner filter effect and Rayleigh masking were applied using predefined tools in Aqualog software. All fluorescence data are reported in Raman units (RU) after normalization to the integrated Raman area (excitation at 350 nm). The data obtained from the scans were consolidated into an excitation-emission matrix (EEM) and subsequently analysed using PARAFAC, which enables the identification of DOM fluorescent components based on their Ex/Em peaks \u003csup\u003e24, 25\u003c/sup\u003e. PARAFAC analysis was performed using the Eigenvector Inc. Solo package (V9.2).\u003c/p\u003e \u003cp\u003e \u003cb\u003e5.10. Microbial community structure and composition.\u003c/b\u003e Prokaryote abundance (bacteria and archaea) was determined using a flow cytometer (InFlux\u0026reg;) equipped with a 488 nm laser in the Flow Cytometry Laboratory of the Millennium Institute of Oceanography, University of Concepci\u0026oacute;n, Chile. Aliquots of 1,350 \u0026micro;L of seawater, collected directly from Niskin bottles, were fixed with 0.1% glutaraldehyde flash-frozen in liquid nitrogen and stored in cryovials. At the laboratory, samples were thawed at room temperature and stained with SYBR-Green I for 15 min. Heterotrophic [MC1] prokaryotes were detected using a 530 nm filter, and the intersections of SybrGreen versus forward scatter (FSC) and SybrGreen versus Chlorophyll signals were used to differentiate prokaryotes from other small fluorescent organisms. For microbial diversity and community composition analysis, two liters of seawater from selected depths were filtered through 0.22 \u0026micro;m sterile membrane filters (Millipore) and stored in cryotubes with 300 \u0026micro;L of RNA at -20\u0026deg;C. DNA was extracted using a Power Water DNA Isolation Kit (MOBIO Laboratories), following manufacturer instructions. Prokaryote 16S rRNA genes were amplified using the universal primer set 515F (GTGYCAGCMGCCGCGGTA) and 806R (GGACTACNVGGGTWTCTAAT) and sequenced on an Illumina MiSeq platform in the Austral-Omics Laboratory of the Universidad Austral de Chile. The complete MiSeq data set is available at the National Center for Biotechnology Information Sequence Read Archive. Paired Illumina demultiplexed reads were processed using QIIME2 version 2024.2 (Boylen et al., 2019) and the DADA2 package for quality filtering, denoising, and chimera removal. Amplicon Sequence Variants (ASVs) taxonomy was assigned using the classify-sklearn function and a Na\u0026iuml;ve Bayes classifier trained on the Silva 138 (99%) reference sequences \u003csup\u003e83, 84, 85\u003c/sup\u003e. Rarefaction curves for each prokaryote community were generated from the means of ten randomized data sets in QIIME2. Analysis of beta and alpha diversity (measured as ASV abundance) was estimated following the removal of sequences identified as Chloroplasts and subsequent to resampling via the rarefaction method, using a minimum of 172,918 sequences per sample. In addition, full-length 16S rRNA gene sequences were obtained from samples taken from the anoxic layer at station 8 and from the same depths at control station E7 using Oxford Nanopore Technologies. DNA libraries were prepared from 10 ng of genomic DNA per sample using the Oxford Nanopore 16S Barcoding Kit 24 V14 (SQK-16S114.24), following the manufacturer guidelines (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://nanoporetech.com/document/rapid-sequencing-DNA-16s-barcoding-kit-v14-sqk-16114-24\u003c/span\u003e\u003cspan address=\"https://nanoporetech.com/document/rapid-sequencing-DNA-16s-barcoding-kit-v14-sqk-16114-24\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Briefly, the 16S rRNA gene regions were amplified by PCR using LongAmp Hot Start Taq 2\u0026times; Master Mix (New England Biolabs). Barcoded amplicons were purified with AMPure XP beads (Beckman Coulter), eluted in 15 \u0026micro;L of molecular-grade water, and quantified using a Qubit dsDNA HS assay (Thermo Fisher Scientific). Adapter ligation was performed by incubating 50 fmol of the pooled library with the Rapid Adapter for 5 min at room temperature. Sequencing was conducted on a MinION MK-1C equipped with FLO-MIN114 flow cells using the Fast Basecalling mode. Following basecalling with the default 16S barcoding parameters, reads were filtered to a minimum quality score of 8, resulting in 4.39 GB of data (N50\u0026thinsp;=\u0026thinsp;1.57 kb). Demultiplexing and taxonomic profiling were performed using the cloud-based EPI2ME 16S workflow (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/epi2me-labs/wf-16s\u003c/span\u003e\u003cspan address=\"https://github.com/epi2me-labs/wf-16s\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e and independently verified using Kraken2 (v2.1.2) (Wood et al., 2019) against the SILVA 138 database, in order to generate high-resolution genus- and species-level abundance tables. Vertical profiles of community composition and ASVs heatmaps were generated in R version 4.2.0 (R Core Team 2019) and Orange3 software (Demsar et al., 2013) for the representative ASVs, which were defined as the top 25 ASVs from Illumina sequencing and those exceeding over 5,000 reads for full-length 16S rRNA gene sequences.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData and metadata are available at: https://doi.org/10.5281/zenodo.18422011\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the chemical and microbiological laboratories of the Patagonia Ecosystem Research Center (CIEP) and the University of Concepci\u0026oacute;n for the biogeochemical analyses presented in this manuscript. Special thanks to the crews of the J\u0026uuml;rgen Winter, Antiqua, and Don Felipe III vessels for supporting data collection in the Quitralco Fjord.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIv\u0026aacute;n P\u0026eacute;rez-Santos was funded by FONDECYT 1211037, 1251038, COPAS COASTAL FB210021, and CIEP R20F002. Alexander Gal\u0026aacute;n has been partially supported by ANID, Concurso de Fortalecimiento al Desarrollo Cient\u0026iacute;fico de Centros Regionales 2020 CLAP-R20F0008. Paulina Montero was funded by FONDECYT 11230763, COPAS COASTAL FB210021, and PATSER R20F002. Marcelo Guti\u0026eacute;rrez was funded by COPAS COASTAL FB210021. Laura Farias would like to thank the Instituto Milenios Secos ICM 2019\u0026ndash;015, CR2 FONDAP-ANID 1522A0001, and FONDECYT 1250210.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIPS: led study design, collection and analysis of physical oceanographic and acoustic data, and manuscript leader. PM, MG, GL: collection and analysis of microbiological and biogeochemical data, and manuscript revision. AG, LF: analysis of biogeochemical data, and manuscript revision. LC: analysis of zooplankton data and manuscript revision. CRV: analysis of surface sediment data and design of the conceptual model. PD, CA: study design, collection and analysis of physical oceanographic data, and manuscript revision. EP: development and analysis of numerical models. KS, AP, KF, CA, GM, GS: collection and analysis of physical and biogeochemical data though fieldwork and in the laboratory. CU, CN: analysis of surface sediment samples. MC: analysis of microbial community samples. OU: study design and manuscript revision. All authors contributed to the writing of the present manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompetition interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBianchi, T.S., DiMarco, S.F., Cowan, J.H., Hetland, R.D., Chapman, P., Day, \u0026amp; Allison, J.W.: The science of hypoxia in the Northern Gulf of Mexico: A review, Science of The Total Environment, 408, 7, 1471\u0026ndash;1484, https://doi.org/10.1016/j.scitotenv.2009.11.047, (2010).\u003c/li\u003e\n\u003cli\u003eLinford, P., P\u0026eacute;rez-Santos, I., Montes, I., Dewitte, B., Buchan, S., Narv\u0026aacute;ez, D., et al. 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Acids Res. 41, Article D590-D596, (2013).\u003c/li\u003e\n\u003cli\u003eYilmaz, P., Parfrey, L. W., Yarza, P., Gerken, J., Pruesse, E., Quast, C., et al. The SILVA and \u0026quot;All-species Living Tree Project (LTP)\u0026quot; taxonomic frameworks. Nucl. Acids Res. 42, D643-D648, (2014).\u003c/li\u003e\n\u003cli\u003eBokulich, N. A., Kaehler, B. D., Rideout, J. R., Dillon, M., Bolyen, E., Knight, R., et al. Optimizing taxonomic classification of marker‐gene amplicon sequences with QIIME 2\u0026rsquo;s q2‐feature‐classifier plugin. Microbiome 6, Article 90. doi.org/10.1186/s40168-018-0470-z\u003cu\u003e, \u003c/u\u003e(2018).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8735657/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8735657/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFjords in Chilean Patagonia are highly dynamic systems shaped by land-derived inputs, oceanic exchange, and tectonic activity. Prior to the elaboration of the present article, no in-depth investigation had been undertaken into the anoxic or euxinic conditions of fjords in this region. Consequently, the present research represents an interdisciplinary oceanographic approach to studying Quitralco Fjord (45.6\u0026deg; S, 73.1\u0026deg; W; 2022\u0026ndash;2025) and provides the first evidence of a volcanically influenced euxinic fjord in Chilean Patagonia. A subsurface anoxic layer, beginning between 90 and 120 m and extending to the basin floor (~\u0026thinsp;160 m), was shown to exhibit elevated temperatures and high concentrations of H\u003csub\u003e2\u003c/sub\u003eS, consistent with inputs of volcanically derived fluids. A bubble-like acoustic scattering and the detection of CH\u003csub\u003e4\u003c/sub\u003e within this layer suggest an external input of the gas into the water column. Although largely stagnant, this layer shifted vertically over time, likely driven by interannual deep-water renewal. Within the euxinic layer, nitrate was completely depleted, while high phosphate (20 \u0026micro;M) and ammonium (25 \u0026micro;M) concentrations indicated an active sulfur cycle. A pronounced deep fluorescence maximum was also detected in the dark, anoxic basin, attributed to fluorescent dissolved organic matter (fDOM) dominated by two humic-like components (C1\u003csub\u003e245(350)-440\u003c/sub\u003e and C3\u003csub\u003e270(400)-505\u003c/sub\u003e) with high aromaticity. Microbial community composition changed markedly across the redox gradient, while geochemical and microbiological fingerprints exhibited shifts in metabolic potential through the water column. The geological emissions of H\u003csub\u003e2\u003c/sub\u003eS from the seabed likely enhance and sustain the euxinic conditions, thereby strongly influencing the biogeochemical cycles of the basin. Overall, the present study reveals a previously unrecognized link between volcanic activity and fjord biogeochemistry, documenting for the first time the development of euxinic conditions in a Patagonian fjord in Chile.\u003c/p\u003e","manuscriptTitle":"Euxinic conditions and altered biogeochemical cycles in a Patagonian fjord influenced by tectonic activity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-12 18:13:47","doi":"10.21203/rs.3.rs-8735657/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-13T09:21:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-13T01:58:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"327273476036447961256332537526130582","date":"2026-03-31T05:25:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-04T17:16:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"12621154664679551903167360425334196263","date":"2026-02-19T09:28:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"11068981462801511164864265286248554692","date":"2026-02-11T11:40:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-09T00:35:53+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-05T09:54:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-03T06:42:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-03T06:41:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-01-29T23:46:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"780c85cd-19e1-4c39-9dbc-1559e1b070d3","owner":[],"postedDate":"February 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":62771484,"name":"Earth and environmental sciences/Biogeochemistry"},{"id":62771485,"name":"Earth and environmental sciences/Climate sciences"},{"id":62771486,"name":"Biological sciences/Ecology"},{"id":62771487,"name":"Earth and environmental sciences/Ecology"},{"id":62771488,"name":"Earth and environmental sciences/Environmental sciences"},{"id":62771489,"name":"Earth and environmental sciences/Ocean sciences"},{"id":62771490,"name":"Earth and environmental sciences/Solid earth sciences"}],"tags":[],"updatedAt":"2026-05-14T11:09:50+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-12 18:13:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8735657","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8735657","identity":"rs-8735657","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}