Microbial community structure in contrasting Hawaiian coastal sediments

Microbial community structure in contrasting Hawaiian coastal sediments | 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 Research Article Microbial community structure in contrasting Hawaiian coastal sediments Benjamin Van Heurck, Diana Vasquez Cardenas, Astrid Hylén, Emilia Jankowska, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5932099/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 May, 2025 Read the published version in Microbial Ecology → Version 1 posted 10 You are reading this latest preprint version Abstract Microbe-mineral interactions play a fundamental role in marine sediments and global biogeochemical cycles. Here, we investigated the sediment microbial communities in two contrasting field sites on Big Island, Hawaii (USA), that differ in their bay morphology and sediment grain size distributions: Papakōlea Beach (exposed, finer sediment) and Richardson Ocean Park (sheltered, coarser sediment). We selected three stations within each bay and characterized the mineral and chemical composition of the sediment and porewater, and used 16S rRNA amplicon sequencing of the V4V5 hypervariable region to investigate the naturally occurring microbial communities. Microbial community structure differed significantly between the two bays, rather than within each bay, whereby microbial diversity was markedly lower at Papakōlea compared to Richardson. We correlated environmental variables to microbial community structure in order to identify the key drivers of community differences between and within the two bays. Our study suggests that differing physico-chemical properties of the sediment and porewater, resulting from the contrasting bay morphologies and geophysical drivers, are the main factors influencing microbial community structure in these two bays. Papakōlea Beach is a naturally occurring ‘green sand’ beach, due to its high olivine content. This site was selected in the broader context of a field campaign investigating olivine as a source mineral for ocean alkalinity enhancement (OAE), a carbon dioxide removal technology. Our results highlight the complexity of marine sediment environments, with implications for the monitoring, reporting and verification of future field trials involving olivine addition for ocean alkalinity enhancement. Microbial communities sediment geochemistry coastal sediments 16S rRNA amplicon sequencing olivine coastal enhanced weathering Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Big Island (Hawaii, USA) consists of five distinct volcanoes [ 1 ]. Therefore, the island contains large quantities of basalt rock and olivine, which physically weather and contribute to beach sediments. Likewise, calcifying organisms (e.g. corals and calcareous algae), are abundant in the coastal waters surrounding Big Island, thus contributing to the formation of carbonate sand [ 2 ]. Consequently, beaches on the island vary substantially in their mineralogical composition and consist either predominantly of silicate sand, carbonate sand, or a mix of the two. Microbe-mineral interactions are fundamental to marine sediments and play an important role in global biogeochemical cycling [ 3 , 4 ]. Microorganisms alter the physical structure, geochemistry and stability of the sediment matrix through degradation of organic matter, biofilm formation, release of cellular exudates, and the precipitation and dissolution of minerals [ 5 – 7 ]. Conversely, differences in sediment properties such as grain size also shape microbial communities by determining the permeability of the sediment, and thus the availability of metabolic substrates (e.g. organic carbon and oxygen) through porewater irrigation [ 4 , 8 , 9 ]. Permeable, sandy sediments are formed in areas with strong hydrodynamic disturbance and are characterized by strong advective porewater flushing and high bed shear stress [ 10 , 11 ]. This results in deep oxygen penetration which fosters the development of a uniform microbial community with sediment depth, and the prevalence of aerobic metabolisms [ 12 – 15 ]. Increased bed shear stress additionally prevents the formation of benthic biofilms [ 16 ]. Consequently, coastal permeable sediments with similar grain size, organic carbon content and wave exposure tend to display similar microbial communities in the top centimeters [ 17 ]. The chemical composition of minerals and differences in their grain surface roughness can also impact the microbial community structure. Silicate minerals typically have a lower affinity for bacterial colonization compared to carbonate substrates, primarily due to their negatively charged surfaces that repel the negatively charged cell walls of bacteria [ 18 ]. Grain topography is additionally important, whereby rougher grains (more indents and grooves) are more densely populated and display more diverse communities compared to smooth, convex grains [ 9 ]. Co-occurrence of different sand types may therefore cause high levels of community heterogeneity and increase the availability of microbial niches [ 19 ]. Here we study the microbial community in two separate bays on Big Island, Hawaii: Papakōlea Beach is a naturally occurring olivine ‘green sand’ beach located in the southernmost part of Big Island and is exposed to the open Pacific Ocean, consequently experiencing strong hydrodynamic disturbance. Richardson Ocean Park is a contrasting field site, located on the eastern side of Big Island, in a bay sheltered from high hydrodynamic disturbance by lava rock beds that present sizeable coral reefs. As a result, the sand consists of basalt, olivine and carbonates, but with an expected lower olivine content compared to Papakōlea. We compare microbial communities in these two contrasting bays and assess the impact of sediment mineralogy, grain size and porewater geochemistry on microbial community structure, providing insight into the environmental factors that drive microbial diversity in permeable coastal sediments. This study is part of a broader field campaign investigating Papakōlea Beach as a natural analogue for ocean alkalinity enhancement (OAE) via coastal enhanced weathering (CEW) of olivine. This technique aims to remove atmospheric carbon dioxide (CO 2 ) through the deposition of finely pulverized silicate minerals, such as olivine, in coastal environments. Chemical weathering of these minerals generates alkalinity, which increases the CO 2 storage capacity of the coastal ocean [ 20 , 21 ]. Olivine content at Papakōlea can reach up to 70% in some areas [ 22 ]. Although our study does not focus exclusively on olivine, Papakōlea Beach provides a unique opportunity to investigate microbial communities in a naturally occurring olivine-rich environment, which is otherwise rare in coastal settings because of olivine’s high weathering rate. 2. Methods 2.1. Sample collection, physical and geochemical characterization Three stations were selected randomly in each bay, where water depth, salinity and temperature were measured, and a visual description of the sediment was recorded (Fig. 1 a, b, c; Table 1 ). At Papakōlea, cores were collected from the middle of the bay (Pap B, Pap C), and in the opening of the bay (Pap D). At Richardson, cores were collected from the northern part of the embayment (Ric B, Ric C and Ric D), whereby station C was located closest to the coral reef. In July and August 2022, sediment cores (inner diameter 4 cm) were collected manually by SCUBA divers at each station. Sediment cores were always collected in the troughs of sediment ripples. For chlorophyll- a analysis, three separate cores were collected per station, and the first 5 cm were placed in aluminum foil covered plastic bags to prevent exposure to sunlight, before storage at -20°C. Chlorophyll- a content was determined by fluorescence (EPA Method 445.0) [ 23 ] at the University of Hawai’i, Hilo (Hawaii, USA) [ 24 ]. A fourth core was taken to sample a deep sediment layer (9–15 cm at Pap B, 15–21 cm at Pap C-D, and 9–12 cm at all Richardson stations) for physical characterization of the sediment. The deeper sediment layers were used to evaluate the grain size distribution by sequential sieving of wet sediment (wt.%; 1 mm), and the mineralogical composition (wt.%) determined by X-ray diffraction (XRD) (QMineral, Leuven, Belgium). Triplicate porewater samples were collected by SCUBA divers using carbon fiber sippers (MHE products, East Tawas, MI, USA) attached to plastic syringes sealed with a Luer stopcock. Carbon fiber sippers were inserted at 2, 5, 10, 15, 20 and 25 cm depth (Fig. S1 ) and moved 1 m between replicate porewater profiles. Dissolved oxygen was measured immediately in the field using a PyroScience FireSting®-GO2 meter (PyroScience GmbH, Aachen, Germany) and probe calibrated using ambient air and an Oakton Zero Oxygen Calibration standard (Environmental Express, Charleston, SC, USA). The remaining porewater was filtered through a 0.45 µm Supor™ filter and preserved by freezing at -20°C for nutrient analysis. Nutrient samples were analyzed within 1 week at the University of Hawai’i, Hilo Analytical Laboratory using a Lachat Quikchem 8500 Series II Flow Injection Analyzer (Hach Co., Loveland, CO, USA) optimized for seawater nutrient analysis. For microbial analysis, a fifth sediment core per station was sectioned at 2 cm resolution for the first 6 cm and at 3 cm resolution for the remaining depth (max. 21 cm, Table S1 ). All equipment was sterilized with 70% ethanol between slices. Sediment slices were homogenized and triplicate subsamples of ~ 1 mL sediment were collected in sterile 2 mL Eppendorf® tubes. At Ric D, only one sample was collected per sediment slice. Samples were kept in the dark and cooled in the field, frozen at -20°C within 6 hours, shipped on dry ice (1 month after collection) and stored at -80°C until further processing. Table 1 Water depth, sediment description, temperature, salinity and location of all sampled stations Site Station Water depth (m) Sediment description Temperature (°C) Salinity Latitude, Longitude (°) Papakōlea (Pap) B 5.8 Silicate dominant (mostly green sand) Coarse(r) grains 26 33 18° 56' 07.40", -155° 38' 45.15" C 5.2 Silicate / carbonate mix Fine grains 27 33 18° 56' 07.82", -155° 38' 44.33" D 7.4 Silicate / carbonate mix Fine grains 27 34 18°56'05.17", -155°38'42.84" Richardson (Ric) B 3.0 Silicate / carbonate mix Coarse grains 27 33 19°44'11.5103", -155°00'50.07" C 2.8 Carbonate dominant (mostly white sand) Coarse grains 26 34 19°44'12.34", -155°00'50.07" D 3.0 Silicate / carbonate mix Coarse grains 28 33 19°44'10.86", -155°00'50.85" 2.2. DNA extraction and amplicon sequencing DNA was isolated from one replicate sediment sample (~ 0.5 g) per depth layer using the DNeasy® PowerSoil® Pro Kit (Qiagen, Hilden, Germany). The V4V5 hypervariable region of the 16S rRNA gene was PCR amplified using universal bacterial primers 515F-Y (5′-GTGYCAGCMGCCGCGGTAA) and 926R (5′-CCGYCAATTYMTTTRAGTTT) [ 24 ]. PCR was run on a Bio-Rad T100™ Thermal Cycler (Bio-Rad Laboratories, Hercules, CA, USA). Samples were sequenced using an Illumina MiSeq sequencer (Eurofins Genomics, Konstantinz, Germany), generating 2x 300 bp paired-end reads. Raw sequencing data were uploaded to the NCBI SRA Bioproject PRJNA1217334. More details on microbial sample processing are provided in the supplementary methods (Online Resource). 2.3. Microbial community analysis The DADA2 pipeline (version 1.26.0; [ 25 ]) was implemented to process the obtained Illumina sequences reads (mean sequencing depth 78,818 ± 19,527 reads; table S1 ), resulting in an amplicon sequencing variant (ASV) table. Taxonomy was assigned against the SILVA reference database (version 138; [ 26 ]) using the built-in naïve Bayesian classifier method [ 27 ]. Chloroplast sequences in the microbial dataset, with a relative abundance greater than 0.1%, were identified using BLASTn. The diversity of microbial communities was quantified using the Shannon diversity index (R microbiome package version 1.20.0; [ 28 ]) and the difference in diversity between sites was assessed using a Wilcoxon rank sum test. Community similarity was analyzed with non-metric multidimensional scaling (NMDS) using Bray-Curtis dissimilarity (R phyloseq package, version 1.42.0; [ 29 ]). Environmental variables were fitted to the NMDS using ‘envfit’ (R vegan package; version 2.6-4; [ 30 ]). Prior to running ‘envfit’, a log(x + 1) transformation was applied to the nutrient and chlorophyll- a data and a centered log-ratio (CLR) transformation to the grain size and mineralogy data. Then, porewater data (DO, nutrients) were binned to the corresponding microbial sample depths, and mineralogical, grain size and chlorophyll- a data were extrapolated to match all microbial sampling depths (Table S1 ). Differences in community structure between the two bays and between the surface (0–6 cm) and deeper layers (> 6 cm) within each bay were statistically tested using analysis of similarities (ANOSIM) (R vegan package; version 2.6-4; [ 30 ]). Functional Annotation of Prokaryotic Taxa (FAPROTAX, version 1.2.7; [ 31 ]) was used to identify the putative metabolic functional potential of the microbial communities. FAPROTAX assigns prokaryotic taxonomy to putative metabolic functions based on current literature on cultured strains. It is important to note that taxa can be assigned to multiple putative metabolic functions, and these functions can be nested within each other (e.g. aerobic chemoheterotrophy nested in chemoheterotrophy). More detailed information on data processing is provided in the supplementary methods (Online Resource). 3. Results 3.1. Sediment characterization Clear differences were observed between the two bays with regard to chlorophyll- a content, grain size distribution and mineralogy. Average chlorophyll- a content across stations was an order of magnitude lower at Papakōlea than at Richardson (0.4 ± 0.3 versus 3.7 ± 0.7 µg g − 1 , respectively; Fig. 2 a, Table S2 ). Grain size analysis showed a smaller large fraction (> 1 mm) at Papakōlea (0.1–10 wt.%) compared to Richardson (29–65 wt.%; Fig. 2 b, Table S2 ). The mineralogical analysis of sediments from both bays showed a varying mixture of olivine, basalt and carbonate sands across all stations (Fig. 2 c). Noteworthy were the high olivine content of station Pap B (64 wt.%) and the high carbonate content of station Ric C (75 wt.%). Furthermore, stations Pap C and D showed a higher carbonate content (55 and 57 wt.%) compared to stations Ric B and D (25 and 31 wt.%). Conversely, the olivine content at stations Pap C and D (6 and 10 wt.%) was lower than at stations Ric B and D (22 and 23 wt.%). Large calcareous fragments were observed at all Richardson stations, but were absent at Papakōlea (Fig. 1 c, Fig. S2 ). Plagioclase (8–22 wt.%), clinopyroxene (8–20 wt.%) and orthopyroxene (2–7 wt.%) are the silicate mineral components of basalt rock and were therefore combined into one fraction (Fig. 2 c, Table S2 ). Basalt was present in similar proportions at Papakōlea (21–24 wt.%), whereas at Richardson the sediment content of basalt was more variable (22–49 wt.%). Minor silicate mineral components across both bays were amorphous volcanic glass (0–14 wt.%) and quartz (0.5–1 wt.%). At Papakōlea, higher fractions of amorphous volcanic glass (7–14 wt.%) were found, which were mostly absent at Richardson (0–2.9 wt.%). The carbonate fractions consisted of magnesium calcite and aragonite (4–75 wt.% combined; Fig. 2 c, Table S2 ). Presence of halite was a sampling artefact caused by the drying of samples containing residual seawater and was removed from plots (Table S2 ). 3.2. Chemical characterization In both bays, oxygen was present throughout the sediment, suggesting strong and deep physical irrigation of the permeable deposits. At stations Pap C and D, the oxygen saturation declined within the top 5 cm, then remained constant at ~ 50% (5–25 cm). At Pap B, where the sediment contained a larger coarse fraction, oxygen remained fully saturated within the top 5 cm, declining more gradually, reaching ~ 50% at 20–25 cm depth. At Ric D, the oxygen saturation stayed consistently near 100% across the whole sediment profile. At Ric B, the oxygen saturation varied between replicates and depths but remained within the 50–100% range throughout the sediment. At Ric C, variation was large between replicates, with R1 & R2 declining rapidly in the top 5 cm, then remaining stable at ~ 50% (5–25 cm), whereas in R3, oxygen saturation remained ~ 100% across the whole sediment depth (Fig. 3 ; Table S3 ). Dissolved silica (H 4 SiO 4 ) concentrations in the porewater increased with depth at all stations and were double at Papakōlea (max. 88–130 µmol L − 1 ) compared to Richardson (max. 43–65 µmol L − 1 ) (Fig. 3 ; Table S3 ). Ammonium accumulated with depth at Pap C and D, reaching up to ~ 60 µmol L − 1 , though with considerable variation between replicates, particularly at deeper depths. At Pap B, ammonium (NH 4 + ) remained low within the top 15–20 cm, and then slowly increased to reach ~ 20 µmol L − 1 . At Richardson, the porewater was consistently depleted of ammonium, which did not exceed 5 µmol L − 1 at any of the stations (Fig. 3 ; Table S3 ). The nitrate/nitrite (NO x − ) concentration profiles did not exhibit a clear trend with depth and were comparable between the two bays. At Papakōlea, the maximum concentrations recorded were 8–25 µmol L − 1 , though with noticeable variation between replicates. At Richardson, the maximum concentrations remained within the 12–19 µmol L − 1 range (Fig. 3 ; Table S3 ). Phosphate (PO 4 3− ) was present across all Papakōlea stations (max. 15–56 µmol L − 1 ), though variability between replicates was considerable, especially at Pap D. In contrast, at Richardson, phosphate was depleted (similar to ammonium), not exceeding 1 µmol L − 1 at Ric B and C and reaching a maximum of 7 µmol L − 1 at Ric D (Fig. 3 ; Table S3 ). 3.3. Microbial characterization The DADA2 pipeline resulted in a total of 20,254 unique ASVs after singleton removal, across the whole dataset. Sample Pap C 6–9 cm had the lowest number of ASVs (326) and sample Pap C 0–2 cm the highest (2,568 ASVs; Table S1 ). The microbial communities differed significantly between the two bays, both with regard to their Shannon diversity and taxonomic composition. The Shannon diversity index was half at Papakōlea (3.8 ± 1.4) compared to Richardson (6.6 ± 0.7; p < 1e-07, Fig. 4 a; Table S1 ). ANOSIM analysis further supports the clear separation of microbial community structure between the two bays (R = 0.99, p 6 cm) sediment layers was observed at Papakōlea (R = 0.022, p = 0.31), thus suggesting a homogenous distribution of microbes in the surface layer (up to 20 cm). In contrast, at Richardson, microbial communities differed moderately between the surface and deeper layer (R = 0.37, p < 0.004). NMDS scaling further supports a clear separation of microbial communities based on site, along the first axis, whereas the second axis separates Richardson samples by station, an effect that is not apparent at Papakōlea (Fig. 4 b). The incorporation of environmental variables via ‘envfit’ provides additional insight into the factors that correlate with microbial community structure, between and within each site. For Papakōlea and Richardson combined, the highest significant correlations were observed for chlorophyll- a (R 2 = 0.96, p = 0.001), medium grain (R 2 = 0.90, p = 0.001), and large grain (R 2 = 0.65, p = 0.001). These correlations explain the separation of Papakōlea and Richardson along the NMDS1 axis and highlight the observed differences in chlorophyll- a content and grain size (Fig. 2 a, b) as potential drivers of microbial community structure between the two bays. At Papakōlea, no clear clustering of samples was observed (Fig. 4 c) and only weak (R 2 < 0.5) correlations were found for some mineralogical components (olivine, ca-carbonate, quartz, amorphous volcanic glass), dissolved oxygen, ammonia and silica (Table S4 ). In contrast, the NMDS of Richardson (Fig. 4 d) further explains the observed separation along the NMDS2 axis of the combined ordination (Fig. 4 b). The NMDS1 axis separated samples by station, with strong correlations (R 2 > 0.5) for mineralogical components (olivine, basalt, quartz, amorphous volcanic glass), grain size (fine grain, medium grain), chlorophyll- a , and ammonia (Table S4 ). The NMDS2 axis correlates strongly with depth (R 2 = 0.8, p = 0.001), indicating that microbial community structure at Richardson is influenced by spatial variation in sediment mineralogy and grain size, as well as depth. Although the dominant groups at phylum level were similar between both bays (Acidobacteriota, Cyanobacteria, Bacteroidota, Firmicutes, Planctomycetota and Proteobacteria; Fig. 5 a), clear differences were observed in their relative abundances. Notably, the average relative abundances of Cyanobacteria and Planctomycetota were 10 and 4 times lower at Papakōlea (0.03 ± 0.06% and 7 ± 7%, respectively) than at Richardson (4 ± 3% and 30 ± 7%, respectively). Likewise, the average relative abundance of Firmicutes also differed one order of magnitude between the two bays (Papakōlea: 44 ± 20%, Richardson: 5 ± 2%). At Papakōlea, four genera ( Alteromonas , Ascidiaceihabitans, Bacillus , and Limimaricola) made up approximately 80% of the microbial community in most samples, with approximately 50% of the community consisting of Bacillus (phylum Firmicutes), whereas no single genus dominated the community at Richardson, consistent with the higher Shannon diversity observed (Fig. 4 a, 5 b). Additionally, the relative abundance of eukaryotic chloroplast sequences was markedly lower at Papakōlea (0.1 ± 0.2%) compared to Richardson (5 ± 2%). A BLAST search of chloroplast sequences from Richardson with relative abundance > 0.1% ( N = 15, representing 70% of Richardson chloroplast sequences), revealed a diverse phototroph community, including foraminifera, diatoms, and brown algae (Table S5 ). Using FAPROTAX, putative metabolic functions were assigned to 4,564 ASVs (23% of total ASVs) represented by 969,392 reads (49% of total reads). Chemoheterotrophy was the most prominent function identified across all samples (39% of all reads assigned to a function) with the majority of these reads identified as aerobic (Fig. 6 ). Fermentation was assigned in all samples, representing 2% of the reads assigned. Functions related to phototrophy (including eukaryote chloroplast sequences) represented 0.8% of the total read count for Papakōlea samples, whereas their contribution to the total Richardson read count was more than 30 times higher (28%). Putative metabolic potential for nitrification also differed between the two bays and was consistently low at Papakōlea (up to 0.3% of the total assigned read count) and 9 times higher at Richardson (2.7% of the total read count). Four samples showed a strongly deviating microbial community structure compared to other samples from the same bay. At Pap C, three sediment depths (0–2, 2–4, and 12–15 cm) displayed a community that was more diverse and differed from other Papakōlea samples (Fig. 5 a, b). In one Ric C sediment layer (6–9 cm), Psychrobacter represented a relative abundance of 46%, while this genus was below 2% in all other samples (Fig. 5 b). While the appearance of Psychrobacter in sample Ric C (6–9 cm) with such unusually high relative abundance is peculiar, this genus does occur in Pacific Ocean sediments [ 32 ]. Given the unmeasurable DNA concentrations in the extraction blanks (Table S1 ) and no visual bands for PCR blanks after gel-electrophoresis, we state that contamination of samples is an unlikely source for these deviations. In the Papakōlea NMDS, the three deviating samples are separated from others along the NMDS1 axis (Fig. 4 c). However, no environmental variable vectors align clearly with this axis and thus none of our measured variables provide an explanation for this deviation. 4. Discussion The sediment mineralogy of the two bays investigated differed from our initial expectations. Papakōlea was expected to have a high olivine content (up to 70 wt.%) due to its location within a collapsed cinder cone[ 22 ] and it being a well-known ‘green sand’ beach. In contrast, Richardson was expected to have a higher contribution of carbonates because of the adjacent coral reef [ 2 ]. However, apart from the olivine-rich station Pap B (64 wt.%; Fig. 2 c) and the carbonate-rich station Ric C (75 wt.%; Fig. 2 c), the stations featured a mixture of carbonate, and volcanic-derived basalt and olivine, likely caused by along-shore sediment transport and mixing. Still, we found clear differences in the microbial community structure between the two bays, however these differences could not be directly related to the sediment mineralogy (Fig. 4 b). Overall, sediment mineralogy does not appear to have a strong effect on the observed differences in microbial community structure between the two bays nor within the bay of Papakōlea (Fig. 4 c). However, in the bay of Richardson, a moderate effect of mineralogy is apparent that separates the carbonate-rich station Ric C from the more olivine- and basalt-rich stations (Fig. 4 d). These variations in community structure between the stations of Richardson could be driven by differences in affinity for bacterial colonization of different mineral substrates [ 18 ]. Additionally, the increased large-grain fraction (> 1 mm) at station Ric C (Fig. 2 b) could lead to differences in sediment grain topography and therefore cause variation in the available microbial niches [ 9 ]. While mineralogy may influence microbial communities at finer spatial scale, broader patterns in community structure appear to be shaped more by other environmental factors. Rather than mineralogy, the specific geomorphology and the associated differences in hydrodynamic disturbance could be responsible for the observed differences in microbial community structure. Papakōlea is completely exposed to the open Pacific Ocean, and the waves entering the bay cause bedload transport that was observed during the diving operations in our field campaign. Additionally, our campaign took place after a tropical storm period, having caused strong oceanic swell from the South. In contrast, Richardson is sheltered by lava rock beds and a coral reef (Fig. 1 b) and the wave energy acting on the seabed there is much lower compared to Papakōlea. High shear stress resulting from strong hydrodynamic forces, like in Papakōlea, can prevent biofilm formation or cause detachment of existing biofilms [ 33 , 34 ], thus counteracting benthic phototrophic ecosystems. In contrast, lower bed shear stress, as in Richardson, favors the stabilization of microbial communities and biofilm formation, which typically harbor a complex consortium of aerobes and photoautotrophs [ 33 ]. During field sampling, a brown cover was observed on the sediment surface in Richardson, suggesting the presence of phototrophic biofilms. This observation is supported by higher chlorophyll- a content, which showed the highest correlation with microbial community structure in the combined NMDS ordination (Fig. 2 c, 4 b). Further support is granted by the abundance of Cyanobacteria and phototrophic putative metabolic functional groups, and the presence of eukaryotic chloroplasts from diverse taxa found in Richardson (Fig. 5 a, 6 , Table S5 ). Additionally, Planctomycetes were a prominent group at Richardson; they are often found in marine biofilms and less disturbed reef sediments [ 33 , 35 , 36 ]. Lastly, the observed bedload transport at Papakōlea potentially lead to increased shear stress and therefore abrasion of sediment grains, whereas in the sheltered bay of Richardson, the observed sediment was of a coarser nature (Fig. 1 c; Fig. S2 ). Cracks and dents in sediment grains serve as attachment sites and habitats that can increase microbial community diversity [ 9 ]. The higher Shannon diversity at Richardson (Fig. 4 a) could therefore result from an elevated availability of microniches in the sediment. The intense wave action at Papakōlea, as well as the coarse sediment at Richardson, are strongly associated with a high degree of advective porewater flushing, resulting in deep oxygen penetration into the sediment [ 11 , 12 ]. Additionally, sampling always occurred in the troughs of sediment ripples, where oxygen concentrations are generally higher due to intrusion of oxygenated water [ 15 ]. Consequently, oxygen profiles in both bays showed oxygen saturation levels that remained > 50% throughout the top 20–25 cm of the sediment (Fig. 3 ). This deep oxygen availability can support the aerobic chemoheterotrophs that we identified in both bays, at all sediment depths (Fig. 6 ). Active primary production within the top layer by phototrophs may explain why oxygen saturation remained higher throughout the sediment at Richardson (Fig. 3 ) [ 11 , 12 ], while these phototrophs were largely absent at Papakōlea (Fig. 2 a, 6 ). While an oxic-anoxic interface in the sediment typically gives a clear change in the microbial community [ 13 , 37 ], this feature was not seen in our data. At Papakōlea, the microbial community structure did not vary significantly with sediment depth (down to 20 cm; Fig. 5 a, b), while at Richardson, ANOSIM analysis showed a moderate difference between the surface and deeper layer. However, the predominant phyla (Proteobacteria, Bacteroidota, Plactomycetota, Firmicutes, Actinobacteriota, and Cyanobacteria) did not show large shifts along the depth profile and are all typically encountered in oxic, marine surface sediments [ 14 , 35 ]. Some anaerobic micro-niches might have still been present in the interstitial spaces between sediment particles, as fermentation was also part of the predicted putative metabolic functional potential in both bays (Fig. 6 ). At Richardson, ammonium was depleted in the porewater (Fig. 3 ), despite significant algal biomass input compared to Papakōlea (Fig. 2 a). In aerobic sediments, ammonium released during organic matter degradation is rapidly nitrified [ 11 , 38 ]. In Richardson, 2% of the sequence reads were associated with nitrification, compared to only 0.2% at Papakōlea (Fig. 6 ), suggesting a higher nitrification potential at Richardson. However, this potential was not reflected in the porewater NO x − concentrations, which were largely comparable between bays (Fig. 3 ). This discrepancy may be due to the higher presence of phototrophs at Richardson, as benthic primary producers are known to take up both ammonium and nitrite/nitrate [ 11 , 38 ]. Coupled nitrification-denitrification is generally suppressed in settings with benthic microalgae, due to substrate competition and increased oxygen levels, which reduces nitrogen removal through denitrification [ 39 ]. This is supported by the high oxygen levels and low potential for nitrate reduction (Fig. 3 , 6 ), making denitrification an unlikely sink for NO x − at Richardson. Additionally, benthic primary producers rapidly take up phosphate [ 40 ], which could explain its depletion in the porewater at Richardson, in addition to physical porewater flushing of the coarse sediment [ 11 ]. Although we did not observe high olivine concentrations in 2/3 of the selected stations at Papakōlea (Fig. 2 c), the olivine content is known to reach up to 70 wt.% in some areas of the bay [ 22 ]. Given the strong hydrodynamic transport within this bay, the higher silica concentrations observed at Papakōlea could be a consequence of olivine dissolution occurring [ 41 ]. Furthermore, diatoms were present at Richardson (Table S5 ) and use dissolved silica as a key nutrient, incorporating it in their cell walls [ 42 ]. Thus, benthic primary production at Richardson likely also contributed to the observed differences in silica concentrations (Fig. 3 ). In summary, the interplay between organic matter input, nitrification and benthic primary production at Richardson likely explains the observed differences in porewater nutrient concentrations compared to Papakōlea. Interestingly, the dominant genus present in all Papakōlea samples was Bacillus (Fig. 5 b), which has been associated with enhanced dissolution of olivine in terrestrial ecosystems [ 43 , 44 ]. Certain Bacillus species can release organic ligands (e.g., siderophores) that target the iron or magnesium ions incorporated in the silicate mineral structure, thereby drastically enhancing weathering rates [ 7 , 44 , 45 ]. A link between microbial activity and weathering of silicate minerals is documented in terrestrial ecosystems [ 46 ]. However, so far, evidence for such a link in coastal systems is lacking [ 47 ], as no specific research efforts have been devoted to this subject. Future microbial field studies providing higher taxonomic resolution could focus on whether the Bacillus species found at Papakōlea are related to those involved in terrestrial silicate solubilization. To conclude, the microbial communities differed significantly between Papakōlea and Richardson with regards to taxonomy, and to a lesser degree, in terms of their putative metabolic functional potential. While the putative metabolic functional potential assigned by FAPROTAX provides valuable insights, it is based on the assumption that uncultured strains share identical metabolic traits with their cultured counterparts in the database [ 48 ]. Additionally, only ~ 50% of reads in our dataset were assigned to a putative metabolic function. Nevertheless, the correspondence between FAPROTAX, taxonomic and geochemical data revealed meaningful patterns in our study. The main difference in community structure between the two bays lies in the higher prevalence of phototrophic organisms at Richardson, which we ascribe to a substantially lower degree of hydrodynamic disturbance and bed shear stress. The variations in community structure between the two bays are thus likely driven by differences in bay morphology and orientation relative to prevailing wind and wave conditions. The consequent differences in sediment disturbance then generate sorting effects and differences in grain size distribution, ultimately providing variation in microbial niches. While mineralogy did correlate to microbial community structure in Richardson, no such link was apparent between the two bays, suggesting that mineralogy can play a role in shaping microbial communities at finer spatial scale, but that its impact is of lesser importance when comparing different geographic locations, in which environmental factors such as wave exposure, organic matter input, and grain size are of greater importance for shaping microbial community structure [ 17 ]. Lastly, our results highlight the complexity of marine sediment environments, which poses a significant challenge for monitoring, reporting and verification (MRV) of field studies on olivine-based ocean alkalinity enhancement. The inherent heterogeneity of marine sediment environments complicates the identification of suitable study and control sites for field trials, emphasizing the need for careful site selection. Declarations Acknowledgements: We thank Jeanine Geelhoed (UAntwerpen) for advice on sediment sampling and microbial community analysis. The field work in Hawai’i was conducted in accordance with a Special Activity Permit (SAP 2023-15) issued by the Department of Land and Natural Resources. Funding: BVH was supported by a DocPro PhD fellowship from the University of Antwerp. Research Foundation Flanders (FWO) supported AH through a junior Postdoc fellowship (grant 1241724N), DVC through a senior Postdoc fellowship (grant 1275822N), and FJRM and MK through a SBO project grant (S008718N). FJRM received additional support from the Blue Cluster project Blue Alkalinity (HBC.2023.0496). The sampling campaign was organized and financially supported by Vesta PBC (SJR, FM, EJ, DBC). Competing interests: The authors declare no competing interests. Author contributions: Conceptualization: FJRM, FM, SJR Methodology: BVH, DVC, EJ, FM, MK Investigation: AH, EJ, MK, BVH, FM, SJR, DBC Funding acquisition: FJRM, AH, DVC Coordination: FJRM, FM Data analysis: BVH Writing – original draft: BVH, DVC Writing – review & editing: all authors Data availability: All sample metadata, mineralogy, grain size, porewater, Shannon diversity and BLASTn data are available in the supplementary tables (Online Resource). Sequencing data were uploaded to the NCBI SRA Bioproject PRJNA1217334. 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Supplementary Files MicrobialcommunitiesatPapakoleaBeachsupplementaryinformation.docx MicrobialcommunitiesatPapakoleaBeachTableS1.csv MicrobialcommunitiesatPapakoleaBeachTableS2.csv MicrobialcommunitiesatPapakoleaBeachTableS3.csv MicrobialcommunitiesatPapakoleaBeachTableS4.csv MicrobialcommunitiesatPapakoleaBeachTableS5.csv Cite Share Download PDF Status: Published Journal Publication published 23 May, 2025 Read the published version in Microbial Ecology → Version 1 posted Editorial decision: Revision requested 01 May, 2025 Reviews received at journal 01 May, 2025 Reviews received at journal 14 Apr, 2025 Reviews received at journal 11 Apr, 2025 Reviewers agreed at journal 10 Apr, 2025 Reviewers agreed at journal 04 Apr, 2025 Reviewers agreed at journal 04 Apr, 2025 Reviewers invited by journal 04 Apr, 2025 Submission checks completed at journal 04 Apr, 2025 First submitted to journal 04 Apr, 2025 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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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5932099","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":438566785,"identity":"d6c4e6c6-b420-4932-ac39-af88ce1fac92","order_by":0,"name":"Benjamin Van Heurck","email":"data:image/png;base64,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","orcid":"","institution":"University of Antwerp","correspondingAuthor":true,"prefix":"","firstName":"Benjamin","middleName":"Van","lastName":"Heurck","suffix":""},{"id":438566786,"identity":"f6532e5a-098d-423a-82cd-c814b93ab877","order_by":1,"name":"Diana Vasquez Cardenas","email":"","orcid":"","institution":"University of Antwerp","correspondingAuthor":false,"prefix":"","firstName":"Diana","middleName":"Vasquez","lastName":"Cardenas","suffix":""},{"id":438566787,"identity":"2c6592e5-d98b-48e2-9a0e-04cab18df4e0","order_by":2,"name":"Astrid Hylén","email":"","orcid":"","institution":"University of Antwerp","correspondingAuthor":false,"prefix":"","firstName":"Astrid","middleName":"","lastName":"Hylén","suffix":""},{"id":438566788,"identity":"9c22ec0a-2c3e-4f1c-8195-afc33a42c146","order_by":3,"name":"Emilia Jankowska","email":"","orcid":"","institution":"Vesta PBC","correspondingAuthor":false,"prefix":"","firstName":"Emilia","middleName":"","lastName":"Jankowska","suffix":""},{"id":438566789,"identity":"1de917ab-ff16-4f5e-96e4-3a69a5218a43","order_by":4,"name":"Devon B. 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R.","lastName":"Meysman","suffix":""}],"badges":[],"createdAt":"2025-01-30 18:23:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5932099/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5932099/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00248-025-02548-7","type":"published","date":"2025-05-23T15:57:53+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80229281,"identity":"59f0906a-f929-462a-9a47-b9808794ef3c","added_by":"auto","created_at":"2025-04-09 12:22:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":516472,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e Outline of Big Island, Hawaii (USA) with indication of field sites: Papakōlea (Pap) and Richardson (Ric). \u003cstrong\u003e(b)\u003c/strong\u003eOverview of each bay. In the top panels, the red square indicates the location of the sampled stations. At Richardson, yellow lines indicate rock beds sheltering the bay and green areas indicate coral reefs. Bottom panels show a close up of each bay, red diamonds indicate the three stations where sediment was sampled (B, C and D). \u003cstrong\u003e(c) \u003c/strong\u003ePictures of representative sediment from stations Pap B and Ric C. The outline map was made with the R \u003cem\u003emaps \u003c/em\u003epackage (version 3.4.2); map images modified from Google Earth pro (version 7.3.6.9796)\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5932099/v1/9bdec46732a85dbd9f6fcca8.png"},{"id":80228932,"identity":"271d01c3-0b9d-427f-acb9-05acde014d84","added_by":"auto","created_at":"2025-04-09 12:14:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":356380,"visible":true,"origin":"","legend":"\u003cp\u003eSediment chlorophyll-\u003cem\u003ea\u003c/em\u003e content (µg g\u003csup\u003e-1\u003c/sup\u003e) \u003cstrong\u003e(a)\u003c/strong\u003e, grain size distribution (wt.%) \u003cstrong\u003e(b)\u003c/strong\u003e, and mineralogical composition (wt.%) \u003cstrong\u003e(c)\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eof sampled stations in Papakōlea and Richardson bays. Sample labels on X-axis indicate the site (Pap or Ric) and station (B, C, or D). X in panel a indicates the mean chlorophyll-\u003cem\u003ea­ \u003c/em\u003econtent (µg g\u003csup\u003e-1\u003c/sup\u003e) per station and D (6 and 10 wt.%) was lower than at stations Ric B and D (22 and 23 wt.%). Large calcareous fragments were observed at all Richardson stations, but were absent at Papakōlea (Fig. 1c, Fig. S2).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5932099/v1/1a851ba96fe09f1ee6433b0c.png"},{"id":80228934,"identity":"b817db0b-3411-4364-91b6-2abdcd6d52d3","added_by":"auto","created_at":"2025-04-09 12:14:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":256871,"visible":true,"origin":"","legend":"\u003cp\u003ePorewater profiles for oxygen and nutrients at Papakōlea and Richardson. From left to right: oxygen (O\u003csub\u003e2\u003c/sub\u003e), dissolved silica (H\u003csub\u003e4\u003c/sub\u003eSiO\u003csub\u003e4\u003c/sub\u003e), ammonium (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e), nitrate + nitrite (NO\u003csub\u003ex\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e) and phosphate (PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3-\u003c/sup\u003e). The Y-axis displays the depth (in cm), the X-axis displays concentration values (% saturation for O\u003csub\u003e2\u003c/sub\u003e, µmol L\u003csup\u003e-1\u003c/sup\u003e for nutrients), colors and shapes indicate triplicate depth profiles.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5932099/v1/2e5c280a8ea33c754295ecd8.png"},{"id":80229288,"identity":"0ba84785-11b4-4307-b504-cca17cd6845b","added_by":"auto","created_at":"2025-04-09 12:22:55","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":244736,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eBoxplot displaying Shannon diversity at Papakōlea and Richardson. Closed circles indicate outliers, X indicates the mean Shannon diversity per site.\u003cem\u003e \u003c/em\u003e\u003cstrong\u003e(b, c, d) \u003c/strong\u003eNMDS ordination plots of sediment microbial communities, based on Bray Curtis dissimilarity: (b) Papakōlea and Richardson combined, (c) Papakōlea, and (d) Richardson. Stress values for the NMDS plots are 0.04, 0.05 and 0.11, respectively. In (b), colors indicate sampling sites; in (c) and (d), colors represent depth. Markers indicate sampling stations. Vectors in the ordination plots indicate significant correlations with environmental variables (p \u0026lt; 0.05), with arrow length representing the strength of the correlation.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5932099/v1/6a696f4b33c1acf7f212e948.png"},{"id":80228938,"identity":"042fb666-460b-419a-ad9e-deee7c41fec2","added_by":"auto","created_at":"2025-04-09 12:14:55","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":536929,"visible":true,"origin":"","legend":"\u003cp\u003eDepth profiles of the 20 most abundant microbial taxa at \u003cstrong\u003e(a)\u003c/strong\u003ephylum, and \u003cstrong\u003e(b)\u003c/strong\u003e genus level for Papakōlea (Pap) and Richardson (Ric). Sites (Pap or Ric), stations (B, C, or D), and sediment depths in cm (e.g. 0-2, 2-4) are indicated in sample labels. The black line separates the two sites.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-5932099/v1/04762d86aba118979235e602.png"},{"id":80229287,"identity":"b5b7e510-83e5-4cce-903e-413e6def8d13","added_by":"auto","created_at":"2025-04-09 12:22:55","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":234133,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap displaying the log-transformed read counts of the top 20 putative metabolic functions (\u0026gt; 3000 total reads) identified via FAPROTAX. The black line separates Papakōlea (Pap) and Richardson (Ric). Sample labels indicate site (Pap or Ric), station (B, C, or D) and sediment depth in cm (e.g. 0-2, 2-4).\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-5932099/v1/b0d420b5597ebc879ffc142a.png"},{"id":83460048,"identity":"d00732c2-174b-4da5-aa80-3caff9eb6025","added_by":"auto","created_at":"2025-05-26 16:09:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2900542,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5932099/v1/5f6cab59-3358-441a-bef1-49b23d9ae2db.pdf"},{"id":80228948,"identity":"ff43b914-1a80-4377-9200-e7c377ac3cc0","added_by":"auto","created_at":"2025-04-09 12:14:55","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":6777731,"visible":true,"origin":"","legend":"","description":"","filename":"MicrobialcommunitiesatPapakoleaBeachsupplementaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-5932099/v1/2deea9c6c8b5f3f3e3a2b8a1.docx"},{"id":80231050,"identity":"6f8d84f0-29e5-414e-8272-a889df8a417e","added_by":"auto","created_at":"2025-04-09 12:38:55","extension":"csv","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":7590,"visible":true,"origin":"","legend":"","description":"","filename":"MicrobialcommunitiesatPapakoleaBeachTableS1.csv","url":"https://assets-eu.researchsquare.com/files/rs-5932099/v1/bb996f76b40049f6d900898e.csv"},{"id":80228936,"identity":"914e7f69-5194-4cd6-a04d-43353e8b2995","added_by":"auto","created_at":"2025-04-09 12:14:55","extension":"csv","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":816,"visible":true,"origin":"","legend":"","description":"","filename":"MicrobialcommunitiesatPapakoleaBeachTableS2.csv","url":"https://assets-eu.researchsquare.com/files/rs-5932099/v1/c7d6ec160e91e3135fc1d1fe.csv"},{"id":80228939,"identity":"80befe5f-fd47-4f63-8781-415479cb5093","added_by":"auto","created_at":"2025-04-09 12:14:55","extension":"csv","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":7926,"visible":true,"origin":"","legend":"","description":"","filename":"MicrobialcommunitiesatPapakoleaBeachTableS3.csv","url":"https://assets-eu.researchsquare.com/files/rs-5932099/v1/045132ad54d251e1ec03e842.csv"},{"id":80228942,"identity":"e2ca6477-b7ba-4a5f-a28a-65743deccced","added_by":"auto","created_at":"2025-04-09 12:14:55","extension":"csv","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":804,"visible":true,"origin":"","legend":"","description":"","filename":"MicrobialcommunitiesatPapakoleaBeachTableS4.csv","url":"https://assets-eu.researchsquare.com/files/rs-5932099/v1/cf0e5eae54395beef2c5fe53.csv"},{"id":80228951,"identity":"22174bca-b73d-4969-8df3-e5a1eaf3583a","added_by":"auto","created_at":"2025-04-09 12:14:55","extension":"csv","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":6805,"visible":true,"origin":"","legend":"","description":"","filename":"MicrobialcommunitiesatPapakoleaBeachTableS5.csv","url":"https://assets-eu.researchsquare.com/files/rs-5932099/v1/1291b2ad6c669a6670330c24.csv"}],"financialInterests":"No competing interests reported.","formattedTitle":"Microbial community structure in contrasting Hawaiian coastal sediments","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eBig Island (Hawaii, USA) consists of five distinct volcanoes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Therefore, the island contains large quantities of basalt rock and olivine, which physically weather and contribute to beach sediments. Likewise, calcifying organisms (e.g. corals and calcareous algae), are abundant in the coastal waters surrounding Big Island, thus contributing to the formation of carbonate sand [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Consequently, beaches on the island vary substantially in their mineralogical composition and consist either predominantly of silicate sand, carbonate sand, or a mix of the two.\u003c/p\u003e \u003cp\u003eMicrobe-mineral interactions are fundamental to marine sediments and play an important role in global biogeochemical cycling [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Microorganisms alter the physical structure, geochemistry and stability of the sediment matrix through degradation of organic matter, biofilm formation, release of cellular exudates, and the precipitation and dissolution of minerals [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Conversely, differences in sediment properties such as grain size also shape microbial communities by determining the permeability of the sediment, and thus the availability of metabolic substrates (e.g. organic carbon and oxygen) through porewater irrigation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePermeable, sandy sediments are formed in areas with strong hydrodynamic disturbance and are characterized by strong advective porewater flushing and high bed shear stress [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This results in deep oxygen penetration which fosters the development of a uniform microbial community with sediment depth, and the prevalence of aerobic metabolisms [\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Increased bed shear stress additionally prevents the formation of benthic biofilms [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Consequently, coastal permeable sediments with similar grain size, organic carbon content and wave exposure tend to display similar microbial communities in the top centimeters [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe chemical composition of minerals and differences in their grain surface roughness can also impact the microbial community structure. Silicate minerals typically have a lower affinity for bacterial colonization compared to carbonate substrates, primarily due to their negatively charged surfaces that repel the negatively charged cell walls of bacteria [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Grain topography is additionally important, whereby rougher grains (more indents and grooves) are more densely populated and display more diverse communities compared to smooth, convex grains [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Co-occurrence of different sand types may therefore cause high levels of community heterogeneity and increase the availability of microbial niches [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHere we study the microbial community in two separate bays on Big Island, Hawaii: Papakōlea Beach is a naturally occurring olivine \u0026lsquo;green sand\u0026rsquo; beach located in the southernmost part of Big Island and is exposed to the open Pacific Ocean, consequently experiencing strong hydrodynamic disturbance. Richardson Ocean Park is a contrasting field site, located on the eastern side of Big Island, in a bay sheltered from high hydrodynamic disturbance by lava rock beds that present sizeable coral reefs. As a result, the sand consists of basalt, olivine and carbonates, but with an expected lower olivine content compared to Papakōlea. We compare microbial communities in these two contrasting bays and assess the impact of sediment mineralogy, grain size and porewater geochemistry on microbial community structure, providing insight into the environmental factors that drive microbial diversity in permeable coastal sediments.\u003c/p\u003e \u003cp\u003eThis study is part of a broader field campaign investigating Papakōlea Beach as a natural analogue for ocean alkalinity enhancement (OAE) via coastal enhanced weathering (CEW) of olivine. This technique aims to remove atmospheric carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) through the deposition of finely pulverized silicate minerals, such as olivine, in coastal environments. Chemical weathering of these minerals generates alkalinity, which increases the CO\u003csub\u003e2\u003c/sub\u003e storage capacity of the coastal ocean [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Olivine content at Papakōlea can reach up to 70% in some areas [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Although our study does not focus exclusively on olivine, Papakōlea Beach provides a unique opportunity to investigate microbial communities in a naturally occurring olivine-rich environment, which is otherwise rare in coastal settings because of olivine\u0026rsquo;s high weathering rate.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Sample collection, physical and geochemical characterization\u003c/h2\u003e \u003cp\u003eThree stations were selected randomly in each bay, where water depth, salinity and temperature were measured, and a visual description of the sediment was recorded (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, b, c; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). At Papakōlea, cores were collected from the middle of the bay (Pap B, Pap C), and in the opening of the bay (Pap D). At Richardson, cores were collected from the northern part of the embayment (Ric B, Ric C and Ric D), whereby station C was located closest to the coral reef.\u003c/p\u003e \u003cp\u003eIn July and August 2022, sediment cores (inner diameter 4 cm) were collected manually by SCUBA divers at each station. Sediment cores were always collected in the troughs of sediment ripples. For chlorophyll-\u003cem\u003ea\u003c/em\u003e analysis, three separate cores were collected per station, and the first 5 cm were placed in aluminum foil covered plastic bags to prevent exposure to sunlight, before storage at -20\u0026deg;C. Chlorophyll-\u003cem\u003ea\u003c/em\u003e content was determined by fluorescence (EPA Method 445.0) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] at the University of Hawai\u0026rsquo;i, Hilo (Hawaii, USA) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. A fourth core was taken to sample a deep sediment layer (9\u0026ndash;15 cm at Pap B, 15\u0026ndash;21 cm at Pap C-D, and 9\u0026ndash;12 cm at all Richardson stations) for physical characterization of the sediment. The deeper sediment layers were used to evaluate the grain size distribution by sequential sieving of wet sediment (wt.%; \u0026lt;63 \u0026micro;m, 63 \u0026micro;m \u0026ndash; 1 mm and \u0026gt;\u0026thinsp;1 mm), and the mineralogical composition (wt.%) determined by X-ray diffraction (XRD) (QMineral, Leuven, Belgium).\u003c/p\u003e \u003cp\u003eTriplicate porewater samples were collected by SCUBA divers using carbon fiber sippers (MHE products, East Tawas, MI, USA) attached to plastic syringes sealed with a Luer stopcock. Carbon fiber sippers were inserted at 2, 5, 10, 15, 20 and 25 cm depth (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) and moved 1 m between replicate porewater profiles. Dissolved oxygen was measured immediately in the field using a PyroScience\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFireSting\u0026reg;-GO2 meter (PyroScience GmbH, Aachen, Germany) and probe calibrated using ambient air and an Oakton Zero Oxygen Calibration standard (Environmental Express, Charleston, SC, USA). The remaining porewater was filtered through a 0.45 \u0026micro;m Supor\u0026trade; filter and preserved by freezing at -20\u0026deg;C for nutrient analysis. Nutrient samples were analyzed within 1 week at the University of Hawai\u0026rsquo;i, Hilo Analytical Laboratory using a Lachat Quikchem 8500 Series II Flow Injection Analyzer (Hach Co., Loveland, CO, USA) optimized for seawater nutrient analysis.\u003c/p\u003e \u003cp\u003eFor microbial analysis, a fifth sediment core per station was sectioned at 2 cm resolution for the first 6 cm and at 3 cm resolution for the remaining depth (max. 21 cm, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). All equipment was sterilized with 70% ethanol between slices. Sediment slices were homogenized and triplicate subsamples of ~\u0026thinsp;1 mL sediment were collected in sterile 2 mL Eppendorf\u0026reg; tubes. At Ric D, only one sample was collected per sediment slice. Samples were kept in the dark and cooled in the field, frozen at -20\u0026deg;C within 6 hours, shipped on dry ice (1 month after collection) and stored at -80\u0026deg;C until further processing.\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\u003eWater depth, sediment description, temperature, salinity and location of all sampled stations\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=\"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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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\u003eSite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWater depth (m)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSediment description\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTemperature\u003c/p\u003e \u003cp\u003e(\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSalinity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLatitude,\u003c/p\u003e \u003cp\u003eLongitude \u003c/p\u003e \u003cp\u003e(\u0026deg;)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePapakōlea\u003c/p\u003e \u003cp\u003e(Pap)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSilicate dominant (mostly green sand)\u003c/p\u003e \u003cp\u003eCoarse(r) grains\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18\u0026deg; 56' 07.40\", \u003c/p\u003e \u003cp\u003e-155\u0026deg; 38' 45.15\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSilicate / carbonate mix\u003c/p\u003e \u003cp\u003eFine grains\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18\u0026deg; 56' 07.82\", \u003c/p\u003e \u003cp\u003e-155\u0026deg; 38' 44.33\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSilicate / carbonate mix\u003c/p\u003e \u003cp\u003eFine grains\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18\u0026deg;56'05.17\", \u003c/p\u003e \u003cp\u003e-155\u0026deg;38'42.84\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRichardson\u003c/p\u003e \u003cp\u003e(Ric)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSilicate / carbonate mix\u003c/p\u003e \u003cp\u003eCoarse grains\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19\u0026deg;44'11.5103\", \u003c/p\u003e \u003cp\u003e-155\u0026deg;00'50.07\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCarbonate dominant (mostly white sand)\u003c/p\u003e \u003cp\u003eCoarse grains\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19\u0026deg;44'12.34\", \u003c/p\u003e \u003cp\u003e-155\u0026deg;00'50.07\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSilicate / carbonate mix\u003c/p\u003e \u003cp\u003eCoarse grains\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19\u0026deg;44'10.86\", \u003c/p\u003e \u003cp\u003e-155\u0026deg;00'50.85\"\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. DNA extraction and amplicon sequencing\u003c/h2\u003e \u003cp\u003eDNA was isolated from one replicate sediment sample (~\u0026thinsp;0.5 g) per depth layer using the DNeasy\u0026reg; PowerSoil\u0026reg; Pro Kit (Qiagen, Hilden, Germany). The V4V5 hypervariable region of the 16S rRNA gene was PCR amplified using universal bacterial primers 515F-Y (5\u0026prime;-GTGYCAGCMGCCGCGGTAA) and 926R (5\u0026prime;-CCGYCAATTYMTTTRAGTTT) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. PCR was run on a Bio-Rad T100\u0026trade; Thermal Cycler (Bio-Rad Laboratories, Hercules, CA, USA). Samples were sequenced using an Illumina MiSeq sequencer (Eurofins Genomics, Konstantinz, Germany), generating 2x 300 bp paired-end reads. Raw sequencing data were uploaded to the NCBI SRA Bioproject PRJNA1217334. More details on microbial sample processing are provided in the supplementary methods (Online Resource).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Microbial community analysis\u003c/h2\u003e \u003cp\u003eThe DADA2 pipeline (version 1.26.0; [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]) was implemented to process the obtained Illumina sequences reads (mean sequencing depth 78,818\u0026thinsp;\u0026plusmn;\u0026thinsp;19,527 reads; table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), resulting in an amplicon sequencing variant (ASV) table. Taxonomy was assigned against the SILVA reference database (version 138; [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]) using the built-in na\u0026iuml;ve Bayesian classifier method [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Chloroplast sequences in the microbial dataset, with a relative abundance greater than 0.1%, were identified using BLASTn. The diversity of microbial communities was quantified using the Shannon diversity index (R \u003cem\u003emicrobiome\u003c/em\u003e package version 1.20.0; [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]) and the difference in diversity between sites was assessed using a Wilcoxon rank sum test. Community similarity was analyzed with non-metric multidimensional scaling (NMDS) using Bray-Curtis dissimilarity (R \u003cem\u003ephyloseq\u003c/em\u003e package, version 1.42.0; [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]). Environmental variables were fitted to the NMDS using \u0026lsquo;envfit\u0026rsquo; (R \u003cem\u003evegan\u003c/em\u003e package; version 2.6-4; [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]). Prior to running \u0026lsquo;envfit\u0026rsquo;, a log(x\u0026thinsp;+\u0026thinsp;1) transformation was applied to the nutrient and chlorophyll-\u003cem\u003ea\u003c/em\u003e data and a centered log-ratio (CLR) transformation to the grain size and mineralogy data. Then, porewater data (DO, nutrients) were binned to the corresponding microbial sample depths, and mineralogical, grain size and chlorophyll-\u003cem\u003ea\u003c/em\u003e data were extrapolated to match all microbial sampling depths (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Differences in community structure between the two bays and between the surface (0\u0026ndash;6 cm) and deeper layers (\u0026gt;\u0026thinsp;6 cm) within each bay were statistically tested using analysis of similarities (ANOSIM) (R \u003cem\u003evegan\u003c/em\u003e package; version 2.6-4; [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]). Functional Annotation of Prokaryotic Taxa (FAPROTAX, version 1.2.7; [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]) was used to identify the putative metabolic functional potential of the microbial communities. FAPROTAX assigns prokaryotic taxonomy to putative metabolic functions based on current literature on cultured strains. It is important to note that taxa can be assigned to multiple putative metabolic functions, and these functions can be nested within each other (e.g. aerobic chemoheterotrophy nested in chemoheterotrophy). More detailed information on data processing is provided in the supplementary methods (Online Resource).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Sediment characterization\u003c/h2\u003e \u003cp\u003eClear differences were observed between the two bays with regard to chlorophyll-\u003cem\u003ea\u003c/em\u003e content, grain size distribution and mineralogy. Average chlorophyll-\u003cem\u003ea\u003c/em\u003e content across stations was an order of magnitude lower at Papakōlea than at Richardson (0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 versus 3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 \u0026micro;g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, respectively; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Grain size analysis showed a smaller large fraction (\u0026gt;\u0026thinsp;1 mm) at Papakōlea (0.1\u0026ndash;10 wt.%) compared to Richardson (29\u0026ndash;65 wt.%; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). The mineralogical analysis of sediments from both bays showed a varying mixture of olivine, basalt and carbonate sands across all stations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Noteworthy were the high olivine content of station Pap B (64 wt.%) and the high carbonate content of station Ric C (75 wt.%). Furthermore, stations Pap C and D showed a higher carbonate content (55 and 57 wt.%) compared to stations Ric B and D (25 and 31 wt.%). Conversely, the olivine content at stations Pap C\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eand D (6 and 10 wt.%) was lower than at stations Ric B and D (22 and 23 wt.%). Large calcareous fragments were observed at all Richardson stations, but were absent at Papakōlea (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec, Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePlagioclase (8\u0026ndash;22 wt.%), clinopyroxene (8\u0026ndash;20 wt.%) and orthopyroxene (2\u0026ndash;7 wt.%) are the silicate mineral components of basalt rock and were therefore combined into one fraction (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Basalt was present in similar proportions at Papakōlea (21\u0026ndash;24 wt.%), whereas at Richardson the sediment content of basalt was more variable (22\u0026ndash;49 wt.%). Minor silicate mineral components across both bays were amorphous volcanic glass (0\u0026ndash;14 wt.%) and quartz (0.5\u0026ndash;1 wt.%). At Papakōlea, higher fractions of amorphous volcanic glass (7\u0026ndash;14 wt.%) were found, which were mostly absent at Richardson (0\u0026ndash;2.9 wt.%). The carbonate fractions consisted of magnesium calcite and aragonite (4\u0026ndash;75 wt.% combined; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Presence of halite was a sampling artefact caused by the drying of samples containing residual seawater and was removed from plots (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Chemical characterization\u003c/h2\u003e \u003cp\u003eIn both bays, oxygen was present throughout the sediment, suggesting strong and deep physical irrigation of the permeable deposits. At stations Pap C and D, the oxygen saturation declined within the top 5 cm, then remained constant at ~\u0026thinsp;50% (5\u0026ndash;25 cm). At Pap B, where the sediment contained a larger coarse fraction, oxygen remained fully saturated within the top 5 cm, declining more gradually, reaching\u0026thinsp;~\u0026thinsp;50% at 20\u0026ndash;25 cm depth. At Ric D, the oxygen saturation stayed consistently near 100% across the whole sediment profile. At Ric B, the oxygen saturation varied between replicates and depths but remained within the 50\u0026ndash;100% range throughout the sediment. At Ric C, variation was large between replicates, with R1 \u0026amp; R2 declining rapidly in the top 5 cm, then remaining stable at ~\u0026thinsp;50% (5\u0026ndash;25 cm), whereas in R3, oxygen saturation remained\u0026thinsp;~\u0026thinsp;100% across the whole sediment depth (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDissolved silica (H\u003csub\u003e4\u003c/sub\u003eSiO\u003csub\u003e4\u003c/sub\u003e) concentrations in the porewater increased with depth at all stations and were double at Papakōlea (max. 88\u0026ndash;130 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) compared to Richardson (max. 43\u0026ndash;65 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). Ammonium accumulated with depth at Pap C and D, reaching up to ~\u0026thinsp;60 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, though with considerable variation between replicates, particularly at deeper depths. At Pap B, ammonium (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e) remained low within the top 15\u0026ndash;20 cm, and then slowly increased to reach\u0026thinsp;~\u0026thinsp;20 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. At Richardson, the porewater was consistently depleted of ammonium, which did not exceed 5 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at any of the stations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). The nitrate/nitrite (NO\u003csub\u003ex\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e) concentration profiles did not exhibit a clear trend with depth and were comparable between the two bays. At Papakōlea, the maximum concentrations recorded were 8\u0026ndash;25 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, though with noticeable variation between replicates. At Richardson, the maximum concentrations remained within the 12\u0026ndash;19 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e range (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). Phosphate (PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u0026minus;\u003c/sup\u003e) was present across all Papakōlea stations (max. 15\u0026ndash;56 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), though variability between replicates was considerable, especially at Pap D. In contrast, at Richardson, phosphate was depleted (similar to ammonium), not exceeding 1 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at Ric B and C and reaching a maximum of 7 \u0026micro;mol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at Ric D (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Microbial characterization\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe DADA2 pipeline resulted in a total of 20,254 unique ASVs after singleton removal, across the whole dataset. Sample Pap C 6\u0026ndash;9 cm had the lowest number of ASVs (326) and sample Pap C 0\u0026ndash;2 cm the highest (2,568 ASVs; Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe microbial communities differed significantly between the two bays, both with regard to their Shannon diversity and taxonomic composition. The Shannon diversity index was half at Papakōlea (3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4) compared to Richardson (6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7; p\u0026thinsp;\u0026lt;\u0026thinsp;1e-07, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea; Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). ANOSIM analysis further supports the clear separation of microbial community structure between the two bays (R\u0026thinsp;=\u0026thinsp;0.99, p\u0026thinsp;\u0026lt;\u0026thinsp;1e-04). No significant difference in community structure between the surface (0\u0026ndash;6 cm) and deeper (\u0026gt;\u0026thinsp;6 cm) sediment layers was observed at Papakōlea (R\u0026thinsp;=\u0026thinsp;0.022, p\u0026thinsp;=\u0026thinsp;0.31), thus suggesting a homogenous distribution of microbes in the surface layer (up to 20 cm). In contrast, at Richardson, microbial communities differed moderately between the surface and deeper layer (R\u0026thinsp;=\u0026thinsp;0.37, p\u0026thinsp;\u0026lt;\u0026thinsp;0.004).\u003c/p\u003e \u003cp\u003eNMDS scaling further supports a clear separation of microbial communities based on site, along the first axis, whereas the second axis separates Richardson samples by station, an effect that is not apparent at Papakōlea (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). The incorporation of environmental variables via \u0026lsquo;envfit\u0026rsquo; provides additional insight into the factors that correlate with microbial community structure, between and within each site. For Papakōlea and Richardson combined, the highest significant correlations were observed for chlorophyll-\u003cem\u003ea\u003c/em\u003e (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.96, p\u0026thinsp;=\u0026thinsp;0.001), medium grain (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.90, p\u0026thinsp;=\u0026thinsp;0.001), and large grain (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.65, p\u0026thinsp;=\u0026thinsp;0.001). These correlations explain the separation of Papakōlea and Richardson along the NMDS1 axis and highlight the observed differences in chlorophyll-\u003cem\u003ea\u003c/em\u003e content and grain size (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, b) as potential drivers of microbial community structure between the two bays.\u003c/p\u003e \u003cp\u003eAt Papakōlea, no clear clustering of samples was observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec) and only weak (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.5) correlations were found for some mineralogical components (olivine, ca-carbonate, quartz, amorphous volcanic glass), dissolved oxygen, ammonia and silica (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). In contrast, the NMDS of Richardson (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed) further explains the observed separation along the NMDS2 axis of the combined ordination (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). The NMDS1 axis separated samples by station, with strong correlations (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.5) for mineralogical components (olivine, basalt, quartz, amorphous volcanic glass), grain size (fine grain, medium grain), chlorophyll-\u003cem\u003ea\u003c/em\u003e, and ammonia (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). The NMDS2 axis correlates strongly with depth (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.8, p\u0026thinsp;=\u0026thinsp;0.001), indicating that microbial community structure at Richardson is influenced by spatial variation in sediment mineralogy and grain size, as well as depth.\u003c/p\u003e \u003cp\u003eAlthough the dominant groups at phylum level were similar between both bays (Acidobacteriota, Cyanobacteria, Bacteroidota, Firmicutes, Planctomycetota and Proteobacteria; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea), clear differences were observed in their relative abundances. Notably, the average relative abundances of Cyanobacteria and Planctomycetota were 10 and 4 times lower at Papakōlea (0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06% and 7\u0026thinsp;\u0026plusmn;\u0026thinsp;7%, respectively) than at Richardson (4\u0026thinsp;\u0026plusmn;\u0026thinsp;3% and 30\u0026thinsp;\u0026plusmn;\u0026thinsp;7%, respectively). Likewise, the average relative abundance of Firmicutes also differed one order of magnitude between the two bays (Papakōlea: 44\u0026thinsp;\u0026plusmn;\u0026thinsp;20%, Richardson: 5\u0026thinsp;\u0026plusmn;\u0026thinsp;2%). At Papakōlea, four genera (\u003cem\u003eAlteromonas\u003c/em\u003e, \u003cem\u003eAscidiaceihabitans, Bacillus\u003c/em\u003e, and \u003cem\u003eLimimaricola)\u003c/em\u003e made up approximately 80% of the microbial community in most samples, with approximately 50% of the community consisting of \u003cem\u003eBacillus\u003c/em\u003e (phylum Firmicutes), whereas no single genus dominated the community at Richardson, consistent with the higher Shannon diversity observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Additionally, the relative abundance of eukaryotic chloroplast sequences was markedly lower at Papakōlea (0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2%) compared to Richardson (5\u0026thinsp;\u0026plusmn;\u0026thinsp;2%). A BLAST search of chloroplast sequences from Richardson with relative abundance\u0026thinsp;\u0026gt;\u0026thinsp;0.1% (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;15, representing 70% of Richardson chloroplast sequences), revealed a diverse phototroph community, including foraminifera, diatoms, and brown algae (Table \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eUsing FAPROTAX, putative metabolic functions were assigned to 4,564 ASVs (23% of total ASVs) represented by 969,392 reads (49% of total reads). Chemoheterotrophy was the most prominent function identified across all samples (39% of all reads assigned to a function) with the majority of these reads identified as aerobic (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Fermentation was assigned in all samples, representing 2% of the reads assigned. Functions related to phototrophy (including eukaryote chloroplast sequences) represented 0.8% of the total read count for Papakōlea samples, whereas their contribution to the total Richardson read count was more than 30 times higher (28%). Putative metabolic potential for nitrification also differed between the two bays and was consistently low at Papakōlea (up to 0.3% of the total assigned read count) and 9 times higher at Richardson (2.7% of the total read count).\u003c/p\u003e \u003cp\u003eFour samples showed a strongly deviating microbial community structure compared to other samples from the same bay. At Pap C, three sediment depths (0\u0026ndash;2, 2\u0026ndash;4, and 12\u0026ndash;15 cm) displayed a community that was more diverse and differed from other Papakōlea samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea, b). In one Ric C sediment layer (6\u0026ndash;9 cm), \u003cem\u003ePsychrobacter\u003c/em\u003e represented a relative abundance of 46%, while this genus was below 2% in all other samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). While the appearance of \u003cem\u003ePsychrobacter\u003c/em\u003e in sample Ric C (6\u0026ndash;9 cm) with such unusually high relative abundance is peculiar, this genus does occur in Pacific Ocean sediments [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Given the unmeasurable DNA concentrations in the extraction blanks (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) and no visual bands for PCR blanks after gel-electrophoresis, we state that contamination of samples is an unlikely source for these deviations. In the Papakōlea NMDS, the three deviating samples are separated from others along the NMDS1 axis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). However, no environmental variable vectors align clearly with this axis and thus none of our measured variables provide an explanation for this deviation.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe sediment mineralogy of the two bays investigated differed from our initial expectations. Papakōlea was expected to have a high olivine content (up to 70 wt.%) due to its location within a collapsed cinder cone[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and it being a well-known \u0026lsquo;green sand\u0026rsquo; beach. In contrast, Richardson was expected to have a higher contribution of carbonates because of the adjacent coral reef [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, apart from the olivine-rich station Pap B (64 wt.%; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec) and the carbonate-rich station Ric C (75 wt.%; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec), the stations featured a mixture of carbonate, and volcanic-derived basalt and olivine, likely caused by along-shore sediment transport and mixing. Still, we found clear differences in the microbial community structure between the two bays, however these differences could not be directly related to the sediment mineralogy (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Overall, sediment mineralogy does not appear to have a strong effect on the observed differences in microbial community structure between the two bays nor within the bay of Papakōlea (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). However, in the bay of Richardson, a moderate effect of mineralogy is apparent that separates the carbonate-rich station Ric C from the more olivine- and basalt-rich stations (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). These variations in community structure between the stations of Richardson could be driven by differences in affinity for bacterial colonization of different mineral substrates [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Additionally, the increased large-grain fraction (\u0026gt;\u0026thinsp;1 mm) at station Ric C (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb) could lead to differences in sediment grain topography and therefore cause variation in the available microbial niches [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. While mineralogy may influence microbial communities at finer spatial scale, broader patterns in community structure appear to be shaped more by other environmental factors.\u003c/p\u003e \u003cp\u003eRather than mineralogy, the specific geomorphology and the associated differences in hydrodynamic disturbance could be responsible for the observed differences in microbial community structure. Papakōlea is completely exposed to the open Pacific Ocean, and the waves entering the bay cause bedload transport that was observed during the diving operations in our field campaign. Additionally, our campaign took place after a tropical storm period, having caused strong oceanic swell from the South. In contrast, Richardson is sheltered by lava rock beds and a coral reef (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) and the wave energy acting on the seabed there is much lower compared to Papakōlea. High shear stress resulting from strong hydrodynamic forces, like in Papakōlea, can prevent biofilm formation or cause detachment of existing biofilms [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], thus counteracting benthic phototrophic ecosystems. In contrast, lower bed shear stress, as in Richardson, favors the stabilization of microbial communities and biofilm formation, which typically harbor a complex consortium of aerobes and photoautotrophs [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. During field sampling, a brown cover was observed on the sediment surface in Richardson, suggesting the presence of phototrophic biofilms. This observation is supported by higher chlorophyll-\u003cem\u003ea\u003c/em\u003e content, which showed the highest correlation with microbial community structure in the combined NMDS ordination (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Further support is granted by the abundance of Cyanobacteria and phototrophic putative metabolic functional groups, and the presence of eukaryotic chloroplasts from diverse taxa found in Richardson (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea, \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Table \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e). Additionally, Planctomycetes were a prominent group at Richardson; they are often found in marine biofilms and less disturbed reef sediments [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Lastly, the observed bedload transport at Papakōlea potentially lead to increased shear stress and therefore abrasion of sediment grains, whereas in the sheltered bay of Richardson, the observed sediment was of a coarser nature (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec; Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Cracks and dents in sediment grains serve as attachment sites and habitats that can increase microbial community diversity [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The higher Shannon diversity at Richardson (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea) could therefore result from an elevated availability of microniches in the sediment.\u003c/p\u003e \u003cp\u003eThe intense wave action at Papakōlea, as well as the coarse sediment at Richardson, are strongly associated with a high degree of advective porewater flushing, resulting in deep oxygen penetration into the sediment [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Additionally, sampling always occurred in the troughs of sediment ripples, where oxygen concentrations are generally higher due to intrusion of oxygenated water [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Consequently, oxygen profiles in both bays showed oxygen saturation levels that remained\u0026thinsp;\u0026gt;\u0026thinsp;50% throughout the top 20\u0026ndash;25 cm of the sediment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This deep oxygen availability can support the aerobic chemoheterotrophs that we identified in both bays, at all sediment depths (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Active primary production within the top layer by phototrophs may explain why oxygen saturation remained higher throughout the sediment at Richardson (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], while these phototrophs were largely absent at Papakōlea (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). While an oxic-anoxic interface in the sediment typically gives a clear change in the microbial community [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], this feature was not seen in our data. At Papakōlea, the microbial community structure did not vary significantly with sediment depth (down to 20 cm; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea, b), while at Richardson, ANOSIM analysis showed a moderate difference between the surface and deeper layer. However, the predominant phyla (Proteobacteria, Bacteroidota, Plactomycetota, Firmicutes, Actinobacteriota, and Cyanobacteria) did not show large shifts along the depth profile and are all typically encountered in oxic, marine surface sediments [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Some anaerobic micro-niches might have still been present in the interstitial spaces between sediment particles, as fermentation was also part of the predicted putative metabolic functional potential in both bays (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt Richardson, ammonium was depleted in the porewater (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), despite significant algal biomass input compared to Papakōlea (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). In aerobic sediments, ammonium released during organic matter degradation is rapidly nitrified [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In Richardson, 2% of the sequence reads were associated with nitrification, compared to only 0.2% at Papakōlea (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), suggesting a higher nitrification potential at Richardson. However, this potential was not reflected in the porewater NO\u003csub\u003ex\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e concentrations, which were largely comparable between bays (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This discrepancy may be due to the higher presence of phototrophs at Richardson, as benthic primary producers are known to take up both ammonium and nitrite/nitrate [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Coupled nitrification-denitrification is generally suppressed in settings with benthic microalgae, due to substrate competition and increased oxygen levels, which reduces nitrogen removal through denitrification [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. This is supported by the high oxygen levels and low potential for nitrate reduction (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), making denitrification an unlikely sink for NO\u003csub\u003ex\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e at Richardson. Additionally, benthic primary producers rapidly take up phosphate [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], which could explain its depletion in the porewater at Richardson, in addition to physical porewater flushing of the coarse sediment [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although we did not observe high olivine concentrations in 2/3 of the selected stations at Papakōlea (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec), the olivine content is known to reach up to 70 wt.% in some areas of the bay [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Given the strong hydrodynamic transport within this bay, the higher silica concentrations observed at Papakōlea could be a consequence of olivine dissolution occurring [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Furthermore, diatoms were present at Richardson (Table \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e) and use dissolved silica as a key nutrient, incorporating it in their cell walls [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Thus, benthic primary production at Richardson likely also contributed to the observed differences in silica concentrations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In summary, the interplay between organic matter input, nitrification and benthic primary production at Richardson likely explains the observed differences in porewater nutrient concentrations compared to Papakōlea.\u003c/p\u003e \u003cp\u003eInterestingly, the dominant genus present in all Papakōlea samples was \u003cem\u003eBacillus\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb), which has been associated with enhanced dissolution of olivine in terrestrial ecosystems [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Certain \u003cem\u003eBacillus\u003c/em\u003e species can release organic ligands (e.g., siderophores) that target the iron or magnesium ions incorporated in the silicate mineral structure, thereby drastically enhancing weathering rates [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. A link between microbial activity and weathering of silicate minerals is documented in terrestrial ecosystems [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. However, so far, evidence for such a link in coastal systems is lacking [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], as no specific research efforts have been devoted to this subject. Future microbial field studies providing higher taxonomic resolution could focus on whether the \u003cem\u003eBacillus\u003c/em\u003e species found at Papakōlea are related to those involved in terrestrial silicate solubilization.\u003c/p\u003e \u003cp\u003eTo conclude, the microbial communities differed significantly between Papakōlea and Richardson with regards to taxonomy, and to a lesser degree, in terms of their putative metabolic functional potential. While the putative metabolic functional potential assigned by FAPROTAX provides valuable insights, it is based on the assumption that uncultured strains share identical metabolic traits with their cultured counterparts in the database [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Additionally, only\u0026thinsp;~\u0026thinsp;50% of reads in our dataset were assigned to a putative metabolic function. Nevertheless, the correspondence between FAPROTAX, taxonomic and geochemical data revealed meaningful patterns in our study. The main difference in community structure between the two bays lies in the higher prevalence of phototrophic organisms at Richardson, which we ascribe to a substantially lower degree of hydrodynamic disturbance and bed shear stress. The variations in community structure between the two bays are thus likely driven by differences in bay morphology and orientation relative to prevailing wind and wave conditions. The consequent differences in sediment disturbance then generate sorting effects and differences in grain size distribution, ultimately providing variation in microbial niches. While mineralogy did correlate to microbial community structure in Richardson, no such link was apparent between the two bays, suggesting that mineralogy can play a role in shaping microbial communities at finer spatial scale, but that its impact is of lesser importance when comparing different geographic locations, in which environmental factors such as wave exposure, organic matter input, and grain size are of greater importance for shaping microbial community structure [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Lastly, our results highlight the complexity of marine sediment environments, which poses a significant challenge for monitoring, reporting and verification (MRV) of field studies on olivine-based ocean alkalinity enhancement. The inherent heterogeneity of marine sediment environments complicates the identification of suitable study and control sites for field trials, emphasizing the need for careful site selection.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Jeanine Geelhoed (UAntwerpen) for advice on sediment sampling and microbial community analysis. The field work in Hawai\u0026rsquo;i was conducted in accordance with a Special Activity Permit (SAP 2023-15) issued by the Department of Land and Natural Resources.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBVH was supported by a DocPro PhD fellowship from the University of Antwerp. Research Foundation Flanders (FWO) supported AH through a junior Postdoc fellowship (grant 1241724N), DVC through a senior Postdoc fellowship (grant 1275822N), and FJRM and MK through a SBO project grant (S008718N). FJRM received additional support from the Blue Cluster project Blue Alkalinity (HBC.2023.0496). The sampling campaign was organized and financially supported by Vesta PBC (SJR, FM, EJ, DBC).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: FJRM, FM, SJR\u003c/p\u003e\n\u003cp\u003eMethodology: BVH, DVC, EJ, FM, MK\u003c/p\u003e\n\u003cp\u003eInvestigation: AH, EJ, MK, BVH, FM, SJR, DBC\u003c/p\u003e\n\u003cp\u003eFunding acquisition: FJRM, AH, DVC\u003c/p\u003e\n\u003cp\u003eCoordination: FJRM, FM\u003c/p\u003e\n\u003cp\u003eData analysis: BVH\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; original draft: BVH, DVC\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; review \u0026amp; editing: all authors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll sample metadata, mineralogy, grain size, porewater, Shannon diversity and BLASTn data are available in the supplementary tables (Online Resource). 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Gigascience 11:. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/gigascience/giab090\u003c/span\u003e\u003cspan address=\"10.1093/gigascience/giab090\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"microbial-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meco","sideBox":"Learn more about [Microbial Ecology](https://www.springer.com/journal/248)","snPcode":"248","submissionUrl":"https://submission.nature.com/new-submission/248/3","title":"Microbial Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Microbial communities, sediment geochemistry, coastal sediments, 16S rRNA amplicon sequencing, olivine, coastal enhanced weathering","lastPublishedDoi":"10.21203/rs.3.rs-5932099/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5932099/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMicrobe-mineral interactions play a fundamental role in marine sediments and global biogeochemical cycles. Here, we investigated the sediment microbial communities in two contrasting field sites on Big Island, Hawaii (USA), that differ in their bay morphology and sediment grain size distributions: Papakōlea Beach (exposed, finer sediment) and Richardson Ocean Park (sheltered, coarser sediment). We selected three stations within each bay and characterized the mineral and chemical composition of the sediment and porewater, and used 16S rRNA amplicon sequencing of the V4V5 hypervariable region to investigate the naturally occurring microbial communities. Microbial community structure differed significantly between the two bays, rather than within each bay, whereby microbial diversity was markedly lower at Papakōlea compared to Richardson. We correlated environmental variables to microbial community structure in order to identify the key drivers of community differences between and within the two bays. Our study suggests that differing physico-chemical properties of the sediment and porewater, resulting from the contrasting bay morphologies and geophysical drivers, are the main factors influencing microbial community structure in these two bays. Papakōlea Beach is a naturally occurring \u0026lsquo;green sand\u0026rsquo; beach, due to its high olivine content. This site was selected in the broader context of a field campaign investigating olivine as a source mineral for ocean alkalinity enhancement (OAE), a carbon dioxide removal technology. Our results highlight the complexity of marine sediment environments, with implications for the monitoring, reporting and verification of future field trials involving olivine addition for ocean alkalinity enhancement.\u003c/p\u003e","manuscriptTitle":"Microbial community structure in contrasting Hawaiian coastal sediments","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-09 12:14:50","doi":"10.21203/rs.3.rs-5932099/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-01T11:58:45+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-01T10:52:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-14T21:41:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-11T23:12:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"333959754130607217208683745776906702036","date":"2025-04-10T17:55:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"75800438563034488485500531070147624655","date":"2025-04-04T16:10:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"220420335021990459912067303556013486186","date":"2025-04-04T16:06:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-04T16:01:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-04T09:40:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Microbial Ecology","date":"2025-04-04T08:40:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"microbial-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meco","sideBox":"Learn more about [Microbial Ecology](https://www.springer.com/journal/248)","snPcode":"248","submissionUrl":"https://submission.nature.com/new-submission/248/3","title":"Microbial Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5d613be2-bd26-440f-9a03-5d07ba0cba14","owner":[],"postedDate":"April 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-26T16:02:16+00:00","versionOfRecord":{"articleIdentity":"rs-5932099","link":"https://doi.org/10.1007/s00248-025-02548-7","journal":{"identity":"microbial-ecology","isVorOnly":false,"title":"Microbial Ecology"},"publishedOn":"2025-05-23 15:57:53","publishedOnDateReadable":"May 23rd, 2025"},"versionCreatedAt":"2025-04-09 12:14:50","video":"","vorDoi":"10.1007/s00248-025-02548-7","vorDoiUrl":"https://doi.org/10.1007/s00248-025-02548-7","workflowStages":[]},"version":"v1","identity":"rs-5932099","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5932099","identity":"rs-5932099","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}