dataesr/scientific-paragraphs-categorization huggingface dataset:
Sediment core collection and scanning Composite sediment cores including the intact sediment-water interface were recovered from near the depositional center of lakes Teli, Agouta, and Edem in October 2016, using gravity and push-rod operated piston corers from an anchored platform and applying state-of-the-art field curating techniques  (65). Computed tomography (CT) images were obtained with a medical x-ray CT scanner (Siemens, SOMATOM Definition Flash) at Ghent University Hospital. After splitting, the cores were photographed and scanned using a Geotek Multi-Sensor Core Logger, followed by lithostratigraphic description. Successive core sections were cross-correlated to produce a single composite "OUNIS16" sequence for each lake, using volume-specific MS (MS) data collected with a Bartington MS2E point sensor (2-mm resolution).
The elemental profiles were determined with an Itrax XRF scanner (Cox Analytical Systems) with a Mo tube and operated at 30 kV, 45 mA, and 15-s exposure. XRF data obtained at 0. 2-mm resolution from the upper 2. 3 m of finely laminated mud in the Teli record was here reduced to 0. 8-mm resolution to obtain a uniform data series for the entire OUNIS16-1P sequence. The nonlaminated sediment sequences from Edem (OUNIS16-2P) and Agouta (OUNIS16-3P) were XRF-scanned at 2-mm resolution.
Acknowledgments: We thank all contributors to the  Grands Ecosystèmes Lacustres de Tchad (GELT)  project, with special thanks to  K. Nkouka  for hands-on coordination. We thank the national and regional authorities in Chad for welcoming this research. D. Borschneck ,  D. Delanghe ,  M. Garcia-Molina ,  E. Ryken , and  Y. Torsy  provided laboratory assistance. We further thank the editor and three anonymous reviewers for constructive comments that helped to improve this paper. Funding: GELT was funded by the  French Ministry of Foreign Affairs  as an  FSP  project ( Fonds de Solidarité Prioritaire ) and supported by the  Ministry of Higher Education, Research and Innovation of Chad , the  National Centre for Research and Development in Chad (CNRD) , the  Chadian universities , and the  Service for Cooperation  and.
Results Modeling wetland δ 13 C-CH 4 dynamics. TEM simulates CH 4 production, oxidation, and transport between soils and the atmosphere (Eqs. 3-10)  24, 25, 27, 28. A carbon isotope-enabled module is incorporated into TEM, referred to as isoTEM, which explicitly considers carbon isotopic fractionation processes in wetlands (Fig. 1 ). The isotopic fractionation factor (α) for each process is defined in Eq. 2  20  , where α is larger than 1 when the product is isotopically more depleted than the reactant. δ  13  C-POM is determined by the global C 3 and C 4 plant distribution (Supplementary Fig. 1 )  29  , where C 4 vegetation is isotopically enriched due to its photosynthetic pathway  30. We incorporated observed long-term trends of atmospheric δ 13 C-CO 2 into soil δ  13  C-POM (Supplementary Fig.
21,  22), that are calculated as a function of soil CH 4 production and the resultant CH 4 concentration changes (C M in Eqs. 6-10). When CH 4 production increases due to input changes, CH 4 oxidation and transport increase simultaneously, causing minor variation in the fraction of oxidation and transport (Supplementary Fig. 16 ). Inundation datasets also alter wetland δ 13 C-CH 4 by changing the areas where wetland emissions occur (±2‰) (Supplementary Table  7  and Supplementary Figs. 6, 7 ).
01 h -1 , vegetation type, root density, vegetation growth, and soil CH 4 concentrations (K p , TR veg , f ROOT , f GROW , and C M , respectively) (Eq. 10)  68. R p depends on ecosystem-specific plant functional types and increases in a warmer soil due to the increase in vegetation growth. In TEM model, the soil profile was divided into 1-cm layers, and soil temperature, moisture, and CH 4 dynamics of TEM were simulated at an hourly time step  24, 27. F D z; t ð Þ ¼ ÀD z ð Þ ∂C M z; t ð Þ ∂t ð8Þ R E z; t ð Þ ¼ K e f C M z; t ð Þ À Á ð9Þ R P z; t ð Þ ¼ K P TR veg f ROOT z ð Þf GROW t ð ÞC M z; t ð Þ ð10Þ Methane stable carbon isotope module in TEM (isoTEM). IsoTEM explicitly considers carbon isotopic fractionation processes for precursor organic matter (POM) and CH 4 during production, oxidation, and transport process.
Besides the observed meteorology from field sites, we also used CRU time-series version 4. 01 to fill missing meteorological inputs  76. We then used the Shuffled Complex Evolution Approach in R language (SCE-UA-R) to minimize the difference between simulated and observed δ 13 C-CH 4  77. For each site, 20 ensembles were run using SCE-UA-R with 10,000 maximum loops per parameter ensemble, and all of them reached steady state before the end of the loops. Our optimization results show that isoTEM captures the magnitude and seasonality of observed soil CH 4 fluxes and δ 13 C-CH 4 (Supplementary Fig. 4 ). Simulation setup. To estimate spatially-and temporally-varying δ 13 C-CH 4 from global wetlands, we used spatially explicit data of land cover, soil pH and textures, meteorology and leaf area index (LAI)  24, 27.
Model-data comparison Site level. We compared our model results with previously published data from 58 in situ measurements compiled by Holmes et al. 19  and 66 in situ measurements by Sherwood et al. 13. Holmes et al. 19  compiled latitude, fraction of HM and AM, pH, vegetation, and δ 13 C-CH 4 to understand factors affecting the methanogenic pathway in global wetlands. The wetland database of Sherwood et al. 13  includes literature reference, latitude, wetland types, and measurement methods. After combining overlapped data of Holmes et al. 19  and Sherwood et al. 13  and excluding data that we used for our model optimization  35, 37, 38  , 70 sites remained for site-level validation (Supplementary Fig. 11  and Supplementary Data 1). Due to a possible mismatch of soil and vegetation properties, and wetland distribution of grid cells between model and observation, we compared observed δ 13 C-CH 4 with simulated δ 13 C-CH 4 of the sampling year within two adjacent grid cells (1°× 1°) of the observation.
Regional level. We used aircraft air samples from 3 regions in Alaska from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE)  83, 84. From 2012 to 2015, CARVE collected airborne measurements of atmospheric chemical components and relevant land surface parameters in the Alaskan Arctic to provide insights into Arctic carbon cycling. During the flights, flask-air samples were collected then sent to NOAA GML for measurements of 50 trace gases including CO 2 , CH 4 , CO, OCS, NMHCs, and then sent to INSTAAR for and the isotopic composition of CO 2 and CH 4. After excluding airborne data with flags, there are 1476 measurements during the sampling period. In situ flux observations collected across Alaskan wetlands show an average of -65‰ but a large 9‰ variation, due to the complex vegetation and soil properties  40.
To compare the spatial variability of wetland δ 13 C-CH 4 , we divided the Alaskan continent into three regions: North Slope, interior, and southwest Alaska based on latitude (62-68 °N, 52-62 °N and 140-155 °W, and 52-62 °N and 155-170 °W for North Slope, interior, and southwest Alaska, respectively). We used Miller-Tans plots to identify the source signatures of δ 13 C-CH 4 from wetlands using the airborne measurements  39. To identify wetland isotopic signatures, we removed measurements that may have effects from fossil fuel emission (C 3 H 8 < 300 ppt), biomass burning (CO < 300 ppb), and transport influence (Altitude < 1500 m), and we set the background altitude to >5000 m. After plotting the data, 2014 was excluded due to limited data and small R 2 (Supplementary Table  5 ).
Sensitivity test with meteorological and substrate inputs, f HM , and inundation. We conducted 8 sensitivity tests of meteorology and substrate inputs. Specifically, we altered air temperature by ±3 °C, precipitation by ±30%, and atmospheric CH 4 abundance by ±30%, and NPP by ±30%, uniformly for each grid cell, while maintaining all other variables at their default isoTEM values. We also varied parameters for f HM based on the uncertainty range from MCMC (Supplementary Table  1 ). We further varied a wetland inundation using satellite-driven Surface WAter Microwave Product Series-Global Lakes and Wetlands Database (SWAMPS-GLWD)  48. Forward modeling using TM5 atmospheric model Global mass balance for bottom-up inventory. We adjusted global long-term mean fossil fluxes to match the simulated growth rate of CH 4 during 1984-2016 and the 1998-2016 mean of δ 13 C-CH 4 with observation (Table  1  and Supplementary Table  11 ).
35  (Fukasawa et al. , 2015) ; and WolfPSort  (Horton et al. , 2006) , using the consensus prediction of animal, fungi and plant models. Homologue localizations were divided into mitochondrial (M), plastid (P), plasma membrane or endoplasmic reticulum (PM/ER), and homologues with unclear localizations (e. g. , N-incomplete gene annotations) were listed as undefined (U). The localizations of A. thaliana homologues of P. tricornutum plastid transporters, as inferred by BLASTp, were based on experimental data (https://suba. plantenergy. uwa. edu. au/; https://www. rostlab. org/services/locDB/) (Rastogi and Rost, 2011; Hooper et al. , 2017) , and when not available inferred from WolfPSORT (https://wolfpsort. hgc. jp/) using a plant reference dataset  (Horton et al. , 2006). Localizations were sorted as mitochondria (M), plastid (C), Vacuole (V), Golgi (G) and plasma membrane (PM).
, 2019) , with only genes that showed the same pattern of origin as the query gene (i. e. , earliest ochrophyte common ancestor for which the presence of gene homologues could be inferred) or loss (i. e. , monophyletic ochrophyte clades descended from the inferred common ancestor of the given gene in which the gene was not detected) scored as +1. Genes in the P. tricornutum genome for which a composite score of at least three was calculated were deemed to be associated to each query transporter (Supplementary Table  S3 ). Plastid metabolic pathways were annotated from previously constructed datasets  (Nonoyama et al. , 2019; Ait-Mohamed et al. , 2020) , PFAM, KEGG and KOG. Pathways for which more than three genes recovered a score ≥ +3 to a given transporter were considered to show a functional association with the transporter gene.
, 2020)  due to the exclusion of mitochondrial transcripts from polyA-selected RNA libraries; or from Thalassiosira equivalents of Phaeodactylum genes due to the absence of generated mitochondrial microarray probes for this species  (Ashworth et al. , 2016). Evolutionary conservation of P. tricornutum plastid transporters 70 plastid transporters were searched by RbH against 287 genomes and transcriptomes belonging to 11 taxonomic groups across the stramenopiles (diatoms, ochrophytes, and aplastidic groups), cryptomonads and haptophytes (Supplementary Table  S4 ), with threshold E-value< 1e-05 and percentage identity ≥ 30%. In silico targeting predictions were performed for each transporter using ASAFind, HECTAR and MitoFates as defined above. The deeper evolutionary history of each transporter was summarized from previously published data  (Dorrell et al.
Calculation of environmental expression trends associated with P. tricornutum plastid transporters The relationships between P. tricornutum plastid transporters and environmental factors were analyzed by correlating the relative abundances of transporter homologous sequences to environmental factors from Tara Oceans Version 1  (Carradec et al. , 2018)  on the Ocean Gene Atlas (OGA) website (http://tara-oceans. mio. osupytheas. fr/ocean-gene-atlas/) (Villar et al. , 2018). The FASTA-formatted protein sequence of each plastid transporter was searched on the OGA portal by BLASTp with threshold E-value 1x10 -05. Gene abundance estimates were calculated from the meta-genomes (MetaG) database, and transcript abundance estimates were calculated from the meta-transcriptomes (MetaT) database. Complete details of homologue sequences, taxonomic annotations, and environmental distributions of each diatom transporter metagene, as inferred by Ocean Gene Atlas website, are provided in the linked osf.
io repository https://osf. io/89vm3/ in the folder "Transporters" The resulting raw homologues downloaded from OGA website were filtered to only retrieve those homologue sequences to diatom plastid-targeted transporters. First, a reference dataset was constructed for each gene from all plastid-targeted transporters identified in stramenopile, haptophyte and cryptomonad libraries as defined above, and the best-matching sequence identified from 151 non-redundant taxonomic categories from a previously constructed whole-tree of life dataset  (Dorrell et al. , 2021) , inferred by BLASTp using the query with threshold e-value 10 -05. The Tara Oceans sequences were searched against the reference dataset by BLASTp with the -max_target_seqs 1 threshold applied, and only sequences with diatom plastid-targeted best hits were retained.
A second BLASTp was performed against the complete protein sequence annotation models from the P. tricornutum genome using the same criteria, and only sequences that obtained best hits with the specific queried gene ID were retained. The intersection of each set of retained genes were selected and combined with the reference dataset, and aligned using MAFFT  (Katoh et al. , 2002)  with the -auto setting. Poorly aligned sequences were manually removed, defined visually by <50% overlap with the conserved domain region of the query transporter, and a guide phylogenetic tree was generated for each curated alignment using the NJ tree-building function in Geneious v 10. 0. 9  (Kearse et al. , 2012)  and 100 replicates. Finally, Tara metagenes corresponding to diatom plastid transporters in the NJ tree topology, to the exclusion of all other cultured homologues, were extracted for 65 plastid transporter families, and used for quantitative analysis (Supplementary Table  S5 ).
Complete fasta files of Tara Oceans homologues for each transporter, along with raw and curated alignments and tree topologies are provided in the linked osf supporting database https://osf. io/89vm3/ in the folder "Transporters". MetaT and MetaG abundances of verified transporter homologues were calculated for all stations, all size fragments  (0. 8-5, 5-20, 20-180 and 180-2000mm)  and different depths (DCM: deep chlorophyll maximum layer; SRF: upper layer zone). Absolute correlation coefficients were calculated by Pearson correlation analysis between the sum MetaT total relative abundance, the sum MetaG total relative abundance (with the exception of transporter J12788, for which no MetaG data were available), and measured environmental factors for each station, following data from PANGAEA  (Pesant et al.
, 2009; Puissant et al. , 2021) ; and net primary production, particulate inorganic, organic and total carbon, previously used as metrics for modeling carbon export from the ocean surface layer, were merged together as primary production-related categories  (Guidi et al. , 2016; Leblanc et al. , 2018). A threshold of significant (P< 0. 05) correlations in ≥ 3 depth and size fractions combinations for ≥ 8 of the ten selected parameters across this merged dataset was deemed to correspond to a significant relationship with primary production.
thaliana plastid envelope  (Thuswaldner et al. , 2007; Gigolashvili et al. , 2012) , were only predicted to be localized to the P. tricornutum PM/ER (Figure  1C ). At least some of these transporters may localize to the P. tricornutum cERM and therefore still be implicated in metabolite exchange with the P. tricornutum plastid. In the case of the P. tricornutum PAPS transporter, a complete plastid cysteine synthesis pathway from PAPS reductase to cysteine synthase is known for diatoms, but no plastid-targeted adenosine sulphate kinase is known, indicating PAPS is likely to be imported from the cytoplasm across the cERM  (Dorrell et al. , 2017). Finally, we note that one putative phosphate permease (J23830) in our dataset has previously been GFP localized to the P. tricornutum cERM, and not the plastid  (Dell'Aquila et al.
Identification of diatom-specific plastid transporters from multispecies sequence datasets Given the limited conservation observed with A. thaliana, we wished to understand the deeper evolutionary conservation and gene transfer events underpinning the origins of P. tricornutum plastid transporters. First, to assess the immediate evolutionary conservation of each transporter, we identified homologous sequences of all 70 P. tricornutum plastid transporters by RbH amongst a previously assembled composite library of more than two hundred species  (Nonoyama et al. , 2019; Dorrell et al. , 2021)  sampled from across stramenopiles, the broader group of organisms including diatoms. The composite library was further divided into three groups: diatoms (106 species), other members of the ochrophytes that contain plastids (94 species) and are predominantly photosynthetic, and aplastidic groups (23 species) that lack functional plastids.
tricornutum plastid transporters that retrieved RbH over at least two species from 11 taxonomic groups (Materials and Methods; Supplementary Table  S4 ). Taxonomic categories are grouped as diatoms (blue); other ochrophytes (yellow/orange); aplastidic stramenopiles (grey) or other lineages with secondary red plastids surrounded by four membranes (purple). Transporter genes inferred to be conserved across diatoms (present in >1 species in all diatom taxonomic categories considered) but not found elsewhere (present in < 4 non-diatom species, and no more than two in any one non-diatom taxonomic category) are labelled with red rectangles. (B) Phylogram of P. tricornutum transporters based on single-gene trees for each transporter with a taxonomically exhaustive reference dataset, per a prior phylogenomic study  (Dorrell et al.
g. , through the phenotyping of mutant lines in transformable model species such as Phaeodactylum. Relationships between abundance of diatom plastid transporters and environmental parameters. (A) Heatmap showing relationships of environmental factors with 65 P. tricornutum transporter homologues in Tara Oceans meta-genome (MetaG) and meta-transcriptome (MetaT) datasets. The calculations for each transporter were performed using data from all Tara Oceans sampling stations in version 1; with independent calculations for each combination of size fractions (0. 8 to 5, 5 to 20, 20 to 180, 180 to to 2000; and 0. 8 to 2000 mm) and depths (DCM, deep chlorophyll maximum layer; SRF, upper layer zone) performed. Heatmap rows correspond to transporter gene IDs in P. tricornutum, columns represent different environmental parameters.
Discussion Although plastid transporters play important roles in energy supply and many other physiological and biochemical reactions in eukaryotic photosynthetic organisms, existing research has largely focused on those found in higher plants, while comprehensive analyses of plastid transporters in eukaryotic algae are still relatively rare  (Marchand et al. , 2018; Marchand et al. , 2020). Here, we profile diverse bioinformatic datasets constructed around the model diatom P. tricornutum, alongside environmental sequence data from Tara Oceans, to close the knowledge gap concerning the plastid transporters associated with diatoms, and other related algal groups with four-membranes surrounded plastids derived from the secondary endosymbiosis of red algae (e. g. , stramenopiles, cryptomonads, and haptophytes).
, 2017; Wright et al. , 2018; Nielsen et al. , 2019). Alongside this, we identify clear differences in plant and diatom plastid transporter architecture, including at least six unique to diatoms and not found in other stramenopile, cryptomonad or haptophyte groups (Figure  4 ). The exact evolutionary origins of these diatom-specific plastid transporters will be best revealed by detailed phylogenies of each protein, incorporating densely sampled phylogenetic reference datasets and in silico localization predictions, to identify their probable histories of gene transfer, duplication and relocalization within the diatom cell. The transporter architecture of the diatom plastid may underpin its unique metabolic potential  (Prihoda et al. , 2012; Marchand et al. , 2018; Nonoyama et al. , 2019 ).
Acknowledgments SL acknowledges a  Chinese Scholarship Council PhD student  (awarded 2019-2023, scholarship fi le No. 201904910555 ). RD acknowledges a  CNRS Momentum Fellowship  (awarded  2019-2021 ) and an  ANR t-ERC (ChloroMosaic). MS and GF acknowledge the support by the  European Research Council (ERC). CB  acknowledges an  ANR collaborative grant  ( Browncut, Grant  No. ANR-19-CE20-0020 ). The authors thank  Morgane Roquais  and  Juan Pierella Karlusich  ( IBENS ) for assistance in the retrieval of Tara Oceans homologues for Phatr3_J43171. This is article # ABCDEF in the Tara Oceans series.
Funding This work was supported by grants from the  Chinese Scholarship Council  (awarded 2019-2023, scholarship file No. 201904910555 ) to SL, a  CNRS Momentum Fellowship  (awarded  2019-2021 ), and an  ANR JCJC  ( ANR-21-CE02-0014-01 ) to RGD, an  ANR   Collaborative grant  ( ANR-19-CE20-0020 ) of France to CB, and a  European Research Council Advanced Grant (Chloro-mito , Grant No. 833184 ) to GF.
Introduction In subduction zones, Global Positioning System (GPS) data have been used to demonstrate inter-seismic locked patches to correlate well with regions of high co-seismic slip  (Bilek & Lay, 2018). Although major earthquakes may alter the inter-plate coupling over a decadal-scale  (Philibosian et al. , 2014) , in many locations, subduction earthquakes have repeatedly ruptured the same fault segment as exemplified in Ecuador over the past 110 years Abstract We investigate the relationship between the long-term (Quaternary) interplate coupling and the short-term geodetically derived interseismic coupling at the Central Ecuador subduction zone. At this nonaccretionary margin, the Cabo Pasado shelf promontory and coastal area are associated with two inter-plate geodetically locked patches.
The deepest patch ruptured co-seismically during the Mw7. 8-2016 Pedernales earthquake, while the shallowest underwent dominantly after-slip. Marine geophysical and chronostratigraphic data allow reconstructing the Quaternary tectonic evolution of the shelf promontory and substantiating variation of the long-term inter-plate coupling that led to the geodetically locked patches. Prior to ∼1. 8 Ma, the outer-wedge inter-plate coupling was strong enough to activate trench-subparallel strike-slip faults. Then, between ∼1. 8 and 0. 79 Ma, shortening and uplift affected the shelf promontory, implying a locally increased inter-plate coupling. After a short, post-0. 79 Ma period of subsidence, shortening and uplift resumed denoting a high inter-plate coupling that endured up to the present. The synchronicity of the structural evolution of the shelf promontory with the subduction chronology of two reliefs of the Carnegie Ridge crest suggests that the locked patches are caused by a geometrical resistance to subduction that propagates landward causing permanent deformation.
Multibeam Bathymetric Data The bathymetric map (Figure  1c ) is a compilation of swath bathymetry data collected during the 2005 Amadeus and Esmeraldas cruises (RV L'Atalante), using a SIMRAD EM12D multibeam system (13 kHz, 162 beams)  (Collot et al. , 2005). This data set was completed by higher-resolution multibeam swath data collected on the shelf using SIMRAD EM122 (12 kHz, 288 beams) and EM710 (100 kHz, 256 beams) echosounders during the 2012 Atacames cruise (RV L'Atalante)  (Michaud et al. , 2015). The RV L'Atalante bathymetric data were processed using the CARAIBES software (IFREMER). The whole data set allowed constructing a uniform digital elevation model with a 30-m grid spacing, using the nearest neighbor algorithm of the GMT software  (Wessel & Smith, 1998).