Limnology and Oceanography: Methods最新文献

{"title":"Impacts of counting protocols for light microscopy on estimates of biodiversity and algal density of phytoplankton","authors":"Pascalle Jacobs,&nbsp;Léon Serre-Fredj,&nbsp;Reinoud P. T. Koeman,&nbsp;Anneke van den Oever,&nbsp;Myron A. Peck,&nbsp;Catharina J. M. Philippart","doi":"10.1002/lom3.10651","DOIUrl":"10.1002/lom3.10651","url":null,"abstract":"<p>Knowledge on the biodiversity and abundance of phytoplankton is key for many ecological and societal (e.g., blue growth) questions. Gathering temporal variation and spatial patterns on key indicators requires reliable and standardized protocols on sampling, species identification and counting. Numerous methods are used but consequences for comparing the biodiversity and abundance of phytoplankton of these different techniques are not well known. We evaluated the consequences of different counting protocols using light microscopy (i.e., subsampling transects or wedges within counting chambers) for these indices using samples collected weekly to bi-weekly (<i>n</i> = 398, 2009–2018) from the Wadden Sea (southern North Sea). Phytoplankton cells were counted (by one person under similar conditions) in a fixed number of viewing fields (58, 70, and 29) at three respective magnifications (10 × 100, 10 × 40, and 10 × 10). Patterns in the spatial distribution of phytoplankton cells varied among species and clustering of cells occurred in more than one-fifth of the samples. This will induce error in the conversion from counts (per viewing field) to abundance (cells mL⁻¹). Our present effort resulted in a high accuracy (95%) in overall cell abundances. This was not the case for species richness, for example, capturing 90% of all species present in the sample would require an almost threefold increase in effort for the 10 × 40 and 10 × 10 magnifications. We recommend that counting methods be tailored to the main research objectives and that counting protocols should quantify uncertainty as well as potential bias to provide an estimation of the error in phytoplankton abundance and species composition.</p>","PeriodicalId":18145,"journal":{"name":"Limnology and Oceanography: Methods","volume":"22 12","pages":"930-942"},"PeriodicalIF":1.9,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lom3.10651","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond transfer learning: Leveraging ancillary images in automated classification of plankton","authors":"Jeffrey S. Ellen,&nbsp;Mark D. Ohman","doi":"10.1002/lom3.10648","DOIUrl":"10.1002/lom3.10648","url":null,"abstract":"<p>We assess whether a supervised machine learning algorithm, specifically a convolutional neural network (CNN), achieves higher accuracy on planktonic image classification when including non-plankton and ancillary plankton during the training procedure. We focus on the case of optimizing the CNN for a single planktonic image source, while considering ancillary images to be plankton images from other instruments. We conducted two sets of experiments with three different types of plankton images (from a <i>Zooglider</i>, Underwater Vision Profiler 5, and Zooscan), and our results held across all three image types. First, we considered whether single-stage transfer learning using non-plankton images was beneficial. For this assessment, we used ImageNet images and the 2015 ImageNet contest-winning model, ResNet-152. We found increased accuracy using a ResNet-152 model pretrained on ImageNet, provided the entire network was retrained rather than retraining only the fully connected layers. Next, we combined all three plankton image types into a single dataset with 3.3 million images (despite their differences in contrast, resolution, and pixel pitch) and conducted a multistage transfer learning assessment. We executed a transfer learning stage from ImageNet to the merged ancillary plankton dataset, then a second transfer learning stage from that merged plankton model to a single instrument dataset. We found that multistage transfer learning resulted in additional accuracy gains. These results should have generality for other image classification tasks.</p>","PeriodicalId":18145,"journal":{"name":"Limnology and Oceanography: Methods","volume":"22 12","pages":"943-952"},"PeriodicalIF":1.9,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lom3.10648","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-throughput determination of total lipids from North Pacific marine fishes via the sulfo-phospho-vanillin microplate assay","authors":"Cody Pinger,&nbsp;Drew Porter,&nbsp;Bryan Cormack,&nbsp;Corey Fugate,&nbsp;Matthew Rogers","doi":"10.1002/lom3.10649","DOIUrl":"10.1002/lom3.10649","url":null,"abstract":"<p>Total lipid content is a valuable indicator of fish health, prey quality, survival potential, stock health, and ecosystem status. Here, we demonstrate an accurate method for measuring total lipids in fish tissues using the spectrophotometric sulfo-phospho-vanillin (SPV) assay, adapted to a 96-well plate format. Samples of dried homogenate were cross-analyzed via the SPV assay and standard gravimetric lipid analysis. Initial measurements of whole fish homogenates analyzed include Pacific herring (<i>Clupea pallasii</i>), Pacific cod (<i>Gadus macrocephalus</i>), walleye pollock (<i>G. chalcogrammus</i>), Pacific capelin (<i>Mallotus villosus</i>), Chinook (<i>Oncorhynchus tshawytscha</i>), and coho (<i>O. kisutch</i>) salmon. Samples of muscle tissue were analyzed from Chinook, pink (<i>O. gorbuscha</i>), sockeye (<i>O. nerka</i>), and chum (<i>O. keta</i>) salmon. All SPV measurements were calibrated using menhaden oil. The mean absolute and relative difference between gravimetric and SPV analysis was 0.5 and ~ 16.4%, respectively (<i>n</i> = 121). To improve the accuracy of SPV assay results, linear calibration models specific to taxa and tissue matrix type were developed, enabling calculation of <i>corrected</i> SPV assay values. The accuracy of using these calibration models was tested by analyzing additional fish samples (<i>n</i> = 16). The results of the <i>corrected</i> SPV assay were not statistically different (<i>p</i> &gt; 0.05) from gravimetric analysis for any samples measured, and the mean absolute and relative difference between the two assays improved to 0.2% and 4.6%, respectively. The SPV assay provides a rapid (2 h), high-throughput (25 samples processed in triplicate), precise (interassay coefficient of variation = 5.6%), and accurate method for quantifying the total lipid content of homogenized fish tissue.</p>","PeriodicalId":18145,"journal":{"name":"Limnology and Oceanography: Methods","volume":"22 12","pages":"903-909"},"PeriodicalIF":1.9,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lom3.10649","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to “Estimating ethanol correction factors for δ13C and δ15N isotopic signatures of freshwater zooplankton from multiple lakes”","authors":"","doi":"10.1002/lom3.10647","DOIUrl":"10.1002/lom3.10647","url":null,"abstract":"<p>Blechinger, T., Link, D., Nelson, J.K.R. and Hansen, G.J.A. (2024), Estimating ethanol correction factors for δ¹³C and δ¹⁵N isotopic signatures of freshwater zooplankton from multiple lakes. Limnol Oceanogr Methods, <b>22</b>: 464–472. https://doi.org/10.1002/lom3.10623</p><p>In the author affiliation section, the correct affiliation for the co-author “Jenna K. R. Nelson” is: “Minnesota Department of Natural Resources, Saint Paul, Minnesota, USA.”</p><p>We apologize for this error.</p>","PeriodicalId":18145,"journal":{"name":"Limnology and Oceanography: Methods","volume":"22 10","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lom3.10647","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multivariate statistical “unmixing” of Indian and Pacific Ocean sediment provenance","authors":"Ann G. Dunlea,&nbsp;Kazutaka Yasukawa,&nbsp;Erika Tanaka,&nbsp;Ingrid L. Hendy","doi":"10.1002/lom3.10645","DOIUrl":"10.1002/lom3.10645","url":null,"abstract":"<p>The geochemistry of marine sediment is a massive archive of (paleo)oceanographic information. Accessing that information requires “unmixing” the various influences on marine sediment geochemistry to understand individual sources and marine geochemical processes. Q-mode factor analysis (QFA) and independent component analysis (ICA) are multivariate statistical techniques that have successfully been applied to large datasets of marine sediment element concentrations to identify the number and composition of marine sediment sources or end-members. In this study, we apply both techniques to two datasets of marine sediment geochemistry, compare the output, and discuss the advantages of each approach. In both datasets, ICA identified a mixing trend between carbonates and dust, whereas QFA represented the end-members as two separate factors. In the Pacific and Indian Oceans dataset, both techniques produced three factors or independent components involving rare earth elements, but two of the QFA factors explained a small, almost negligible, amount of the variability of the dataset. Also, QFA identified more aluminosilicate end-members (dust or volcanic ash) than ICA. In the Indian Ocean Sites 738 and 752 dataset, ICA identified two processes affecting Sr and Ba concentrations as separate independent components, while QFA created a factor representing the covariation of Sr and Ba over intervals of the site's paleoceanographic history. The results of this study exemplify that QFA identifies covariances and finds discrete end-members contributing to the bulk mass of sediment. ICA works best with non-Gaussian element distributions and finds geochemical signals and mixing trends that constitute the characteristic structure of the multielemental data.</p>","PeriodicalId":18145,"journal":{"name":"Limnology and Oceanography: Methods","volume":"22 11","pages":"823-839"},"PeriodicalIF":1.9,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lom3.10645","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of a pH optode for oceanographic moored and profiling applications","authors":"Taylor Wirth,&nbsp;Yuichiro Takeshita,&nbsp;Benjamin Davis,&nbsp;Ellen Park,&nbsp;Irene Hu,&nbsp;Christine L. Huffard,&nbsp;Kenneth S. Johnson,&nbsp;David Nicholson,&nbsp;Christoph Staudinger,&nbsp;Joseph K. Warren,&nbsp;Todd Martz","doi":"10.1002/lom3.10646","DOIUrl":"10.1002/lom3.10646","url":null,"abstract":"<p>As global ocean monitoring programs and marine carbon dioxide removal methods expand, so does the need for scalable biogeochemical sensors. Currently, pH sensors are widely used to measure the ocean carbonate system on a variety of autonomous platforms. This paper assesses a commercially available optical pH sensor (optode) distributed by PyroScience GmbH for oceanographic applications. Results from this study show that the small, solid-state pH optode demonstrates a precision of 0.001 pH and relative accuracy of 0.01 pH using an improved calibration routine outlined in the manuscript. A consistent pressure coefficient of 0.029 pH/1000 dbar is observed across multiple pH optodes tested in this study. The response time is investigated for standard and fast-response versions over a range of temperatures and flow rates. Field deployments include direct comparison to ISFET-based pH sensor packages for both moored and profiling platforms where the pH optodes experience sensor-specific drift rates up to 0.006 pH d⁻¹. In its current state, the pH optode potentially offers a viable and scalable option for short-term field deployments and laboratory mesocosm studies, but not for long term deployments with no possibility for recalibration like on profiling floats.</p>","PeriodicalId":18145,"journal":{"name":"Limnology and Oceanography: Methods","volume":"22 11","pages":"805-822"},"PeriodicalIF":1.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lom3.10646","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating O2 : Ar, N2 : Ar, and 29,30N2 using membrane inlet mass spectrometry configured to minimize oxygen interference","authors":"Ashlynn R. Boedecker,&nbsp;Jason M. Taylor,&nbsp;Tyler H. Tappenbeck,&nbsp;Robert O. Hall Jr.,&nbsp;Caleb J. Robbins,&nbsp;J. Thad Scott","doi":"10.1002/lom3.10644","DOIUrl":"10.1002/lom3.10644","url":null,"abstract":"<p>Membrane inlet mass spectrometry (MIMS) provides detailed measures of dissolved ^28,29,30N₂, O₂, and argon (Ar) for estimating important gas fluxes and concentrations in aquatic ecosystems. Previous studies demonstrated a large O₂ scavenging effect while using a MIMS, where varying concentrations of O₂ can affect measured N₂ : Ar because O₂ interacts with N₂ in the ion source to produce NO⁺ (<i>m</i>/<i>z</i> = 30), potentially decreasing the detected current for ^28,29N₂ and increasing the detected current for ³⁰N₂. A common solution is to use a muffle furnace heated to 600°C with a copper reduction column to reduce the concentration of O₂ to minimal levels and accurately measure ^28,29,30N₂. However, this solution eliminates the detection of O₂ in environmental samples, which is a major benefit of using a MIMS. We questioned whether the MIMS was sensitive enough to provide accurate O₂ estimates when using the furnace and whether the O₂ scavenging effect was real and consistent among MIMS. We conducted four separate experiments on three different MIMS to test the O₂ scavenging effect and the potential detection of O₂ when using a MIMS with furnace. The furnace removed ~ 99% of O₂, and O₂ scavenging had little to no detectable effect on N₂ : Ar and an unclear effect on ²⁹N₂ : ²⁸N₂, but increased ³⁰N₂ : ²⁸N₂. In most cases, accurate O₂ data could be retrieved despite using the furnace. The need for O₂ reduction may be limited to measuring accurate ³⁰N₂ : ²⁸N₂ in isotope pairing studies, but without substantial loss of MIMS measurements used to describe O₂ dynamics.</p>","PeriodicalId":18145,"journal":{"name":"Limnology and Oceanography: Methods","volume":"22 11","pages":"791-804"},"PeriodicalIF":1.9,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lom3.10644","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing observational arrays for biogeochemistry in the tropical Pacific by estimating correlation lengths","authors":"Winnie U. Chu,&nbsp;Matthew R. Mazloff,&nbsp;Ariane Verdy,&nbsp;Sarah G. Purkey,&nbsp;Bruce D. Cornuelle","doi":"10.1002/lom3.10641","DOIUrl":"10.1002/lom3.10641","url":null,"abstract":"<p>Global climate change has impacted ocean biogeochemistry and physical dynamics, causing increases in acidity and temperature, among other phenomena. These changes can lead to deleterious effects on marine ecosystems and communities that rely on these ecosystems for their livelihoods. To better quantify these changes, an array of floats fitted with biogeochemical sensors (BGC-Argo) is being deployed throughout the ocean. This paper presents an algorithm for deriving a deployment strategy that maximizes the information captured by each float. The process involves using a model solution as a proxy for the true ocean state and carrying out an iterative process to identify optimal float deployment locations for constraining the model variance. As an example, we use the algorithm to optimize the array for observing ocean surface dissolved carbon dioxide concentrations (pCO₂) in a region of strong air–sea gas exchange currently being targeted for BGC-Argo float deployment. We conclude that 54% of the pCO₂ variability in the analysis region could be sampled by an array of 50 Argo floats deployed in specified locations. This implies a relatively coarse average spacing, though we find the optimal spacing is nonuniform, with a denser sampling being required in the eastern equatorial Pacific. We also show that this method could be applied to determine the optimal float deployment along ship tracks, matching the logistics of real float deployment. We envision this software package to be a helpful resource in ocean observational design anywhere in the global oceans.</p>","PeriodicalId":18145,"journal":{"name":"Limnology and Oceanography: Methods","volume":"22 11","pages":"840-852"},"PeriodicalIF":1.9,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lom3.10641","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simultaneous onboard analysis of seawater dissolved inorganic carbon (DIC) concentration and stable isotope ratio (δ13C-DIC)","authors":"Zhentao Sun,&nbsp;Xinyu Li,&nbsp;Zhangxian Ouyang,&nbsp;Charles Featherstone,&nbsp;Eliot A. Atekwana,&nbsp;Najid Hussain,&nbsp;Wei-Jun Cai","doi":"10.1002/lom3.10642","DOIUrl":"10.1002/lom3.10642","url":null,"abstract":"<p>Dissolved inorganic carbon (DIC) and its stable carbon isotope (<i>δ</i>¹³C-DIC) are valuable parameters for studying the aquatic carbon cycle and quantifying ocean anthropogenic carbon accumulation rates. However, the potential of this coupled pair is underexploited as only 15% or less of cruise samples have been analyzed for <i>δ</i>¹³C-DIC because the traditional isotope analysis is labor-intensive and restricted to onshore laboratories. Here, we improved the analytical precision and reported the protocol of an automated, efficient, and high-precision method for ship-based DIC and <i>δ</i>¹³C-DIC analysis based on cavity ring-down spectroscopy (CRDS). We also introduced a set of stable in-house standards to ensure accurate and consistent DIC and <i>δ</i>¹³C-DIC measurements, especially on prolonged cruises. With this method, we analyzed over 1600 discrete seawater samples over a 40-d cruise along the North American eastern ocean margin in summer 2022, representing the first effort to collect a large dataset of <i>δ</i>¹³C-DIC onboard of any oceanographic expedition. We evaluated the method's uncertainty, which was 1.2 <i>μ</i>mol kg⁻¹ for the DIC concentration and 0.03‰ for the <i>δ</i>¹³C-DIC value (1<i>σ</i>). An interlaboratory comparison of onboard DIC concentration analysis revealed an average offset of 2.0 ± 3.8 <i>μ</i>mol kg⁻¹ between CRDS and the coulometry-based results. The cross-validation of <i>δ</i>¹³C-DIC in the deep-ocean data exhibited a mean difference of only −0.03‰ ± 0.07‰, emphasizing the consistency with historical data. Potential applications in aquatic biogeochemistry are discussed.</p>","PeriodicalId":18145,"journal":{"name":"Limnology and Oceanography: Methods","volume":"22 11","pages":"862-875"},"PeriodicalIF":1.9,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stabilization of nitrite in the presence of the nitrification inhibitor allylthiourea (ATU) in freshwater nitrification rate measurements","authors":"Jade Bosviel,&nbsp;Katharina Kitzinger,&nbsp;Michael Pester","doi":"10.1002/lom3.10643","DOIUrl":"10.1002/lom3.10643","url":null,"abstract":"<p>Nitrification rate measurements provide critical information on the performance of an environmental process central to the N cycle and are best studied using isotope labeling techniques. However, combining the high sensitivity of isotope labeling techniques with selected inhibition of nitrifiers as a whole or of specific nitrifier guilds has not been established in limnology. This can be achieved with different concentrations of the commonly used nitrification inhibitor allylthiourea (ATU). In the ¹⁵N-ammonium oxidation technique, the converted isotope label is typically captured in an excess pool of ¹⁴N-nitrite. Here, we assessed how different storage conditions affect the stability of the nitrite pool in freshwater samples treated with ATU. When stored frozen, the nitrite pool was rapidly destabilized to 25–31% after 7 d of storage and even to less than 5% after storage exceeding 90 d for samples treated with ATU, thus making them unusable for rate determinations in these cost and labor-intensive experiments. In comparison, this was not the case in marine samples or freshwater samples not treated with ATU, where the nitrite pool remained stable. Building on these results, we tested two options to stabilize nitrite during the storage of freshwater samples. The nitrite pool was stable if samples were stored at 4°C instead of freezing. We recommend this option for short-term storage. For long-term storage, samples should be supplemented with 0.5 mmol L⁻¹ NaCl to increase salinity before freezing. As in marine samples, this stabilized the nitrite pool. Our results provide important guidance for the storage of non-saline samples used for nitrification rate measurements in freshwater environments.</p>","PeriodicalId":18145,"journal":{"name":"Limnology and Oceanography: Methods","volume":"22 10","pages":"752-758"},"PeriodicalIF":1.9,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lom3.10643","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142181788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}