dataesr/scientific-paragraphs-categorization huggingface dataset:
The size of the genome is 4. 25 Mbp and its G + C content is 74. 8 mol%. The type strain Marseille-Q7820 T (= CSUR Q7820 = CECT 30716) was isolated from an endometrial sample taken from a 34-year-old woman suffering from recurrent early miscarriage and chronic endometritis. The 16S rRNA and genome sequences have been deposited in GenBank under accession numbers OX458243 and CATKPC000000000, respectively.
The identification of plants according to the Linnaean system of taxonomy is a cornerstone of ethnobotany, allowing the discipline to be a comparative science. To accomplish plant identification, ethnobotanists have long relied on the collection of voucher specimens and their deposition in herbaria. Here we critically analyze the role of botanical collecting in ethnobotany and bring attention to a range of issues that can complicate, and sometimes hamper, the practice. In lieu of traditional herbarium specimens, the collection of photographic vouchers and their deposition in digital repositories is proposed as an alternative method for ethnobotanical research. The ever-improving quality and ubiquity of smartphone cameras, photographic citizen science applications like Pl@ntnet and iNaturalist, and deep learning techniques of automated photo identification are discussed as elements that are contributing to a slow revolution in the role of digital data in the field sciences.
Online Platforms and Crowd-Sourced e-Identification The digital revolution and the consequent growth of online social networks have given a radical boost to the long tradition of citizen science, where non-professionals contribute to scientific data collection and research. Online platforms and later, smartphone-based applications of those platforms, have provided an incredible accessibility and interactability for citizen scientist networks (e. g. WEB sakana-zukan, a Japanese fish platform operating since 2002;  Miyazaki et al. 2014 ). These platforms fall into one of two categories, those that rely on photographs for data validation (photo vouchers), and those that do not require photographs (trusting observers with identification) and thus use other approaches to data validation. Examples of the latter include eBird, a global ornithological database with hundreds of thousands of observers and millions of observations  (Sullivan et al.
2014) , and FauneFrance, which collects data on a huge range of taxa throughout the French territories  (Zucca 2019). The premier photo-based online citizen science database is iNaturalist (https://www. inaturalist. org/), a global all-taxa platform where observers upload date-stamped and geo-located photo observations from smartphones. These photos are instantaneously run through a powerful automated identification tool, which suggests possible identifications. Observers can examine and compare their photos with suggestions or other taxa they manually search for before selecting an identification (at any taxonomic level they prefer). Once observations are uploaded, they are immediately accessible for other users to review and verify by confirming the original identification, refining it, or disagreeing and offering an alternative identification.
Observations that fulfill a set of criteria, including having multiple users agree on the identification, are classed as 'researchgrade'; others remain at 'needs ID' or 'casual'  (Horn et al. 2018). This powerful data proofing and verification process has made iNaturalist useful for research purposes. A study using iNaturalist with trained volunteers to survey amphibians found that 82% of observations could be verified to species level and 100% of research-grade observations were correct  (Wittmann, Girman and Crocker 2019). iNaturalist observations have led to the discovery of new insect taxa  (Winterton 2020) , and significantly contribute to mapping of threatened and endangered species  (Mesaglio and Callaghan 2021). Another series of other platforms focus specifically on plants, including the most well-known, Pl@ntNet (https://plantnet.
org/), as well as CONECTe (https://conecte. es/index. php/es/) for Spain (Reyes-García et al. 2021), PlantSnap (https://www. plantsnap. com/; Otter, Mayer and Tomaszewski 2021) and LeafSnap (http://leafsnap. com/; Bonnet and Frame 2015). Since 2011, the LifeCLEF project has brought together tens of research teams to regularly test and improve automated plant photo identification techniques using large datasets drawn from Pl@ntNet  (Bonnet et al. 2016; Goëau, Bonnet and Joly 2017). These photo voucher platforms, particularly iNaturalist and Pl@ntNet, are already being employed in botanical research. Research-grade iNaturalist observations have been incorporated into Global Biodiversity Information Facility (GBIF) since at least 2015  (Gardiner and Bachman 2016). Other uses include vegetation mapping  (Uyeda, Stow and Richart 2020) , for the development of the atlas of Russian flora (Seregin 2021), for invasive species distribution modeling (with Pl@ntNet,  Botella et al.
e-Deposition Although the use of photo vouchers is becoming more common in research, their deposition in permanent repositories is still fairly underdeveloped. Affouard et al. (2021)  lay out a process for using iNaturalist Projects to curate photo vouchers in specific data sets. Heberling and Isaac (2018) , in advocating for the use of photo vouchers alongside botanical specimens, go one step further by describing how photo vouchers organized in iNaturalist Projects can be associated with physical herbarium specimens by the use of QR codes printed on herbarium specimen labels. We are in the process of experimenting with iNaturalist Projects to store collections of photo vouchers for home garden surveys in the Hmong diaspora (Figure  3 ), and surveys of toxic plants in nurseries in French Guiana.
However, there is still no standard method for the deposition of photo vouchers that can integrate all platforms as well as researchers' offline photos  (Gómez-Bellver et al. 2019) , and the need for such a system is rapidly growing. To be ready for deposition, each photo voucher should be identified by a unique code similar to a botanical specimen number. These photo voucher codes can then be referenced in tables in publications, alongside or in lieu of specimen numbers. Observations in iNaturalist automatically receive such a code, and projects can be used to export these codes along with other metadata (location, date, etc. ). Additional data, including description, local names, and use, can be entered in a Description field for each observation. If photo vouchers are not managed through a platform like iNaturalist or Pl@ntnet, they should be assembled in photosets (.
As more and more botanical collections are decentralized rather than concentrated in the Global North, photo vouchers offer an important tool to verify published data across administrative and national borders. They also offer an excellent possibility for easy diffusion of results to study participants, as well as a method of collaborative research, as highlighted in recent ethnobotanical studies using photo vouchers created by Nahuatl  (Amith 2013)  and Taruma and Wapichan local partners  (Holt 2021). Ethnobotanists have a long tradition of close collaboration with taxonomic botanists, the expert knowledge holders who often ensure the accuracy of our results. Photo vouchers can increase the accessibility of ethnobotanical datasets far beyond a small team of herbarium curators to the global community of botanical experts.
Its definition is an open question and relies on an a priori knowledge of the fluctuating velocity field. Our strategy is to use few parameters, preferably with quantities available in standard simulation data or well documented in the literature. Moreover, we need to respect the ground hypothesis that the noise is decorrelated from resolved coherent field (at the large-scale characteristic time scale). We propose to set the variance tensor, a, defined in equation (  3 ), from root-mean-square (RMS) velocity profiles, and variances of velocity fluctuations, which are quantities often available in databases accompanying the mean flow profile: a(y) = τ s   ⟨u ′2 (y)⟩ ⟨u ′ (y)v ′ (y)⟩ 0 ⟨u ′ (y)v ′ (y)⟩ ⟨v ′2 (y)⟩ 0 0 0 ⟨w ′2 (y)⟩   , (14) where ⟨•⟩ denotes average in time and in the homogeneous directions.
IV. 1. Numerical simulation Databases of direct numerical simulation of turbulent channels were obtained with the pseudospectral code Channelflow 2. 0  [65]. Periodic boundary conditions are enforced in the streamwise (x) and spanwise (z) directions and Chebyshev polynomials are used in the wall-normal direction (y). Parameters are given in table I and additional numerical details, including validation results, can be found in Amaral et al. [24]. Mean flow profiles for the three Reynolds numbers and root-mean-square (RMS) profiles at Re τ = 1000 are presented in figure  1. Results are presented using non-dimensional quantities using viscous (wall) scaling, denoted with a + superscript. SPOD has been computed as a reference to which ν t -resolvent analysis and FSLM will be compared. They represent the most energetic structure for a given frequency-wavenumber combination, which can be meaningfully compared to most amplified responses of resolvent and FSLM.
Resolvent analysis with eddy viscosity leads to good predictions as it takes into account this non-linear forcing and incorporates eddy diffusion. These predictions are significantly enhanced by the stochastic model since it explicitly modifies lift-up by incoherent turbulent motions through three complementary terms: the transport by the noise, a diffusion tensor with non-zero off-diagonal terms and a drift velocity active in the buffer region  [41]. Profiles of power spectral density (PSD) of the three velocity components are shown in figure  4. They confirm that streamwise velocity (u) profiles are similarly captured by ν t -resolvent and by SLM. The agreement of FSLM with SPOD data is significantly improved. Moreover, the streamwise vortices signing on the (v, w) profiles are not captured by SLM but strongly intensified in FSLM.
Marine diazotrophs convert dinitrogen (N 2 ) gas into bioavailable nitrogen (N), supporting life in the global ocean. In 2012, the first version of the global oceanic diazotroph database (version 1) was published. Here, we present an updated version of the database (version 2), significantly increasing the number of in situ diazotrophic measurements from 13 565 to 55 286. Data points for N 2 fixation rates, diazotrophic cell abundance, and nifH gene copy abundance have increased by 184 %, 86 %, and 809 %, respectively. Version 2 includes two new data sheets for the nifH gene copy abundance of non-cyanobacterial diazotrophs and cell-specific N 2 fixation rates. The measurements of N 2 fixation rates approximately follow a log-normal distribution in both version 1 and version 2. However, version 2 considerably extends both the left and right tails of the distribution.
Non-cyanobacterial diazotrophs (NCDs) have also been widely detected in the ocean  (Bombar et al. , 2016; Delmont et al. , 2021; Moisander et al. , 2017). However, the contribution of NCDs to marine N 2 fixation has not been directly quantified, despite a few studies that have reported N 2 fixation by putative NCDs at the cellular level  (Harding et al. , 2022; Bentzon-Tilia et al. , 2015a). Diazotroph abundance has been estimated from nifH gene copies using qPCR assays  (Church et al. , 2005b)  or droplet digital PCR (ddPCR;  Gradoville et al. , 2017). The abundance of some cyanobacterial diazotrophs can also be obtained by counting them directly using microscopy-based techniques and in some cases flow cytometry. A recent work combined an image recognition pipeline with molecular mapping of the nifH gene to quantify diazotrophs in the Tara Oceans dataset https://doi.
" Both gene-based and microscopy cell counts have innate biases, which should be elucidated in future studies. Given the importance of N 2 fixation to ocean ecology and biogeochemistry, it is imperative that a database of up-todate N 2 fixation and diazotrophic abundance measurements be maintained. Currently, global estimates of marine fixed N inputs calculated via the N 2 fixation rate mostly range from 100 to 170 Tg N yr -1 (see summary in  Zhang et al. , 2020). This value, together with other bioavailable N sources to the ocean including riverine input and atmospheric deposition, is considerably lower than estimates of N losses from the ocean such as denitrification, anammox, and sediment burial  (Zhang et al. , 2020; Gruber, 2008; Zehr and Capone, 2021). While the overestimation of the N losses cannot be ruled out, one of possible reasons for this imbalance is the inaccurate estimation of global marine N 2 fixation due to limited spatiotemporal coverage of rate measurements and the different methods employed in N 2 fixation assays  (White et al.
Other studies have also suggested that NCDs may be significant contributors to marine N 2 fixation  (Shiozaki et al. , 2014b; Turk-Kubo et al. , 2022; Geisler et al. , 2020; Delmont et al. , 2021; Karlusich et al. , 2021; Bombar et al. , 2016; Moisander et al. , 2017)  and may occupy different niches than cyanobacterial diazotrophs  (Shao and Luo, 2022). Luo et al. (2012)  compiled the first global oceanic diazotrophic database including in situ measurements of N 2 fixation rates and cell-count-based and nifH-based diazotrophic abundance. Several years later, two studies supplemented the database with a collection of some newly reported diazotrophic data  (Tang and Cassar, 2019; Tang et al. , 2019) , although a substantial amount of additional data remained to be included. Here, we present an updated version of the global oceanic diazotrophic database with data not yet compiled.
We describe the database information, a summary of the data updates, measurement methods, and data distribution. Furthermore, we conduct a first-order estimation of the global oceanic N 2 fixation rate using the updated version of the database. In light of the aforementioned concerns of nifH : cell and various N 2 fixation methods (see Sect. 2. 3), we also discuss the significance of employing different methodological approaches to estimate N 2 fixation rates and abundance metrics. We use the data available in the database to analyze the discrepancies between N 2 fixation rates using 15 N 2 bubble and dissolution methods, and compare the observed ranges of nifH gene copies and diazotrophic cell abundance.
Database summary This study updated the original global oceanic diazotrophic database of  Luo et al. (2012; version 1 hereafter)  with new in situ measurements of N 2 fixation rates and abundances of diazotrophic cells and nifH gene copies. Together there were 55 286 diazotrophic data points in the updated database (version 2 hereafter; Tables  1 2 3 ), including 13 565 data points from version 1  (Luo et al. , 2012) , 6736 measured in 2012-2018 and compiled by two previous studies  (Tang et al. , 2019; Tang and Cassar, 2019 ), 26 597 data points measured in 1979 -2023 and compiled by this study, and 8388 NCD data mostly from Turk-Kubo et al. (2022; see below). In version 2, some errors in the datasets of  Tang et al. (2019) , mostly caused by unit conversions, were also corrected. Version 2 was composed of six main sub-databases: (1) 9231 volumetric N 2 fixation rates (5853 new data points; Tables  1  and 4 ); (2) 2590 depth-integrated N 2 fixation rates (1805 new data points; Tables  1  and 4 ); (3) 9040 volumetric cell abundances (4154 new data points; Tables  2  and 5 ); (4) 1784 depth-integrated cell abundances (859 new data points; Tables  2  and 5 ); (  5 ) 29 655 volumetric nifH gene copy abundances (26 506 new data points; Tables  3  and 6 ); and (6) 2986 depth-integrated nifH gene copy abundances (2544 new data points; Tables  3  and 6 ).
Please be aware that 2416 N 2 fixation rates were measured with incubation periods less than 24 h; they were listed in separate spreadsheets in the database for reasons discussed in Sect. 2. 3. Additionally, we included a compiled NCD dataset  (Turk-Kubo et al. , 2022)  in the database, which contained 7919 nifH gene copy abundances of primarily the most studied phylotype NCD Gamma A  (Shao and Luo, 2022; Langlois et al. , 2015) , also referred to as 24774A11  (Moisander et al. , 2012)  and UMB  (Bird et al. , 2005) , as well as other phylotypes, and updated the compilation with 469 additional nifH gene copy abundances of NCDs published more recently  (Turk-Kubo et al. , 2021; Sato et al. , 2022; Moore et al. , 2018; Reeder et al. , 2022; Wen et al. , 2022; Bonnet et al. , 2023). We also collected 468 cell-specific in situ N 2 fixation rates and added them to version 2 (Table  7 ).
Depth-integrated data were either provided directly in published papers or calculated as part of this study for those vertical profiles with at least three volumetric data points in each profile. The measurements within a profile were first interpolated linearly with depth, with the shallowest datum representing the level between the sea surface and the depth of that datum. The profile was then integrated from the sea surface to the deepest recorded measurement. Most vertical profiles of N 2 fixation rates were measured within the euphotic zone, with a few studies extending measurements to several hundred meters or deeper. In these cases, we only integrated to the deepest data point above 200 m, taking into account the scarcity of aphotic N 2 fixation measurements in the global ocean and their controversial contribution to the global budget  (Benavides et al.
The UCYN abundance data were further grouped into UCYN-A, UCYN-B, and UCYN-C. Four sublineages of UCYN-A, including UCYN-A1, UCYN-A2, UCYN-A3, and UCYN-A4, have been identified  (Thompson et al. , 2014; Farnelid et al. , 2016). UCYN-A1 and UCYN-A2 have significant distinctions in the sizes and species of their symbiotic hosts, with the former living in relatively smaller hosts  (Thompson et al. , 2014; Martínez-Pérez et al. , 2016; Cornejo-Castillo et al. , 2016). Hence, in addition to recording the total nifH gene copy abundance of UCYN-A in our database, the nifH gene copy abundances of its sublineages were also included if reported. Heterocystous cyanobacterial abundance was grouped into Richelia intracellularis (het-1 and het-2, associated with Hemiaulus and Rhizosolenia, respectively) and Richelia rhizosolenia (het-3, previously named Calothrix sp.
Quality control The data of N 2 fixation rates and diazotrophic abundance in the database spanned several orders of magnitude. Extremely high rates and abundance values of both usually occurred during algal blooms, and zero values indicated that diazotrophic activity was below detection or truly absent at the sampling time and stations. The positive-value data were first logarithmically transformed and then analyzed for outliers, considering that they were approximately log-normally distributed (Figs. S1-S5). For each parameter, we used Chauvenet's criterion to identify suspicious outliers whose probability of deviation from the means is lower than 1/2n, where n is the number of data points  (Glover et al. , 2011). Because N 2 fixation rates and diazotroph abundances in the ocean can be extremely low, this filtering only applied to data on the high side.
, 2020). Ultimately, White et al. (  2020 ) "advise employing either the dissolution or bubble release method, whichever is best suited to the specific research objectives and logistical constraints" with additional recommendations on the need for determination of detection limits for all rate measurements. We compared volumetric N 2 fixation rates in the upper 50 m and depth-integrated N 2 fixation rates in the database measured using acetylene reduction assays, the original 15 N 2 bubble method, and the 15 N 2 dissolution method and found that they span a similar range (Fig. 1 ). Meanwhile, in the analysis for volumetric N 2 fixation rates in the upper 50 m, the peak of the log-normal distributions of the measurements using the 15 N 2 dissolution method was approximately double that of the original 15 N 2 bubble method (Fig.
1a ). The measurements using the 15 N 2 bubble release method were limited to several study sites and their distribution was thus not presented in this study. A further analysis comparing the original 15 N 2 bubble method and the 15 N 2 dissolution method will be presented later (see Sect. 4. 1). The majority of N 2 fixation rates (9405) were measured with incubation periods of 24 h and were reported as daily rates. In contrast, 2416 samples were incubated for less than 24 h and hourly N 2 fixation rates were reported. Diel cycles of N 2 fixation vary among samples and/or diazotrophic groups, and substantial errors may be introduced when ex-Earth Syst. Sci. Data, 15, 3673-3709, 2023  https://doi. org/10. 5194/essd-15-3673-2023   7. Summary of data points of cell-specific N 2 fixation rates added to version 2 of the database.
The rates were measured either by using the combination of CARD-FISH and nanoscale secondary ion mass spectrometry (nanoSIMS; method A) or via the measurements of bulk N 2 fixation rates incubated with a known number of diazotrophic cells (method B; see Sect. 2. 3). Note that all the data were reported as N 2 fixation rates per cell, except for  Filella et al. (2022)  in which biomass-normalized rates in units of d -1 were reported. trapolating N 2 fixation rates incubated for less than 24 h to daily rates  (White et al. , 2020). Therefore, the N 2 fixation rates measured with incubation periods of less than 24 h were collected into separated data sheets in our database and were not used in further analysis within this study. Please note that the incubation periods of whole diurnal cycles (e.
g. , 24, 48, or 72 h) were used in  Konno et al. (2010). The incubation of samples in  Yogev et al. (2011)  lasted from 24 to 30 h. The reported daily N 2 fixation rates by these two studies were also included in the 24 h data sheets and were used in our estimation of the global marine N 2 fixation rate (see below). Cell-specific N 2 fixation rates of diazotrophs (or symbioses) were mostly measured using catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH) and nanoscale secondary ion mass spectrometry (nanoSIMS), in combination with 15 N 2 addition experiments  (Mills et al. , 2020; Berthelot et al. , 2019). Using specific oligonucleotide probes, CARD-FISH enables the visualization and location of the regions of interest in diazotrophs at a single-cell level using a epifluorescence microscope.
Estimation of the global marine N 2 fixation rate Using these data, we performed a first-order estimation of the global marine N 2 fixation rate. In a previous study  (Luo et al. , 2012) , version 1 was utilized to estimate the global marine N 2 fixation rate, which included all the depth-integrated N 2 fixation rates. However, in this study, we employed more rigorous criteria to estimate the global rate using both version 1 and version 2, taking into account the reliability of different N 2 fixation rate data discussed in the preceding section. Specifically, we exclusively used depth-integrated N 2 fixation rates that met the following criteria: (1) measurements were taken from whole seawater samples, (2) incubation periods of 24 h were used, and (3) the three 15 N 2 -based methods were employed, although we acknowledged that the rates obtained using the original 15 N 2 bubble method might be underestimated.