dataesr/scientific-paragraphs-categorization huggingface dataset:
Concentrations of CH 4 become very small downstream of 3,750 (January) or 3,000 (August) meters. The furthest upstream (at the flow divide) CH 4 and DIC concentrations in August were substantially higher than those observed in January. 𝐴𝐴 𝐴𝐴 13 C of DIC decreases (becomes isotopically depleted) in the downstream direction in both datasets except for the sample at the flow divide in January 2020. 𝐴𝐴 𝐴𝐴 13 C of CH 4 initially increases to a maximum around 2200 (January) or 1,200 (August) m downstream then decreases. The January canal data for 𝐴𝐴 𝐴𝐴 13 C-CH 4 shows a smoother trend than the August data. Where CH concentrations are very low, small methane inputs will have a strong impact on the overall CH 4 isotopic signature which may explain the anomalously low 𝐴𝐴 𝐴𝐴 13 C of CH 4 observed at 5,070 (January) and 4,880 (August).
Fitted Model Indicates Spatial Patterns in Canal Methane Oxidation and Degassing The model was fit simultaneously to observed concentrations and 𝐴𝐴 𝐴𝐴 13 C of CH 4 and DIC (Figure  5 ) to estimate the parameters and their uncertainties (Table  1 ). We omitted 2 canal data points as outliers for the January data (x = 0 and 5,070 m) and one point for the August data (x = 4,880 m) because they showed markedly different values than the general trends. The root mean square error (RMSE) for modeled CH 4 concentration in January (and August) was 0. 0100 mM (0. 00858 mM) and 2. 98‰ (5. 25‰) for 𝐴𝐴 𝐴𝐴 13 C-CH 4. The RMSE for the modeled CO 2 concentration in January (and August) was 0. 0382 mM (0. 153 mM) and 0. 414‰ (1. 09‰) for 𝐴𝐴 𝐴𝐴 13 C-CO 2. Fitted values of the parameter that describes the distribution of porewater velocity with depth, D Jan and D Aug , are almost identical, with standard deviations of uncertainty that overlap, indicating that the vertical distribution of porewater flow to the canal remains the same in low and moderate flow conditions with shallow (<1 m deep) porewater contributing most of water discharge.
This represents a higher rate of greenhouse gas emission than methane (in CO 2 equivalents) from the canal. However, the contribution of DOC oxidation to the canal CO 2 budget remains uncertain as indicated by the wide 95% confidence interval (Figure  6 , Table  S1  in Supporting Information S1). As a rough check on the DOC oxidation rate, we compare it to the rate of total organic carbon fluvial export from drainage canals in Malaysia  (Cook et al. , 2018)  and find that our DOC oxidation rates fall on the same order of magnitude and below (9%-65%) TOC export from that study. We can also compare to a metadata analysis on peatland DOC export by  Rosset et al. (2022)  and find our DOC oxidation rate is on the same order of magnitude as the median tropical DOC export rate. Furthermore, our results indicate a substantial difference in the rate of DOC oxidation between January and August 2020.
The uncertainty is shown by the error bars and error envelopes in Figures  5  and 7 , and Table  1 , that represent the 95% confidence intervals. Our model is fit to eight datasets (corresponding to the panels in Figure  5 ) instead of one. This is why more than 5% of the observed datapoints can fall outside the 95% confidence envelope. In our data, local heterogeneities seemed to be most obvious in the 𝐴𝐴 𝐴𝐴 13 C-CH 4 data that was collected in August 2020, which does not follow a monotonic trend. When 𝐴𝐴 𝐴𝐴 13 C-CH 4 cannot be well matched by the model, parameter uncertainties become larger and our ability to differentiate between methane oxidation and degassing is reduced. 𝐴𝐴 𝐴𝐴 13 C-CO 2 observations should provide an additional constraint on methane oxidation rates because lighter methane is preferentially oxidized to create lighter CO 2.
Conclusions We developed an isotope-enabled CO 2 and CH 4 mass-balance model for tropical peatland drainage canals and applied it to two datasets from the Badas Canal in Brunei Darussalam. Our results inform our conceptual model of methane dynamics in tropical peatland drainage canals (Figure  1 ). Shallow porewater dominates groundwater inflow to the canal given the higher hydraulic conductivity of the shallow peat. Deeper porewater also flows toward the canal and upwells near the canal but contributes little to canal flow. In the canal, the majority of the incoming methane is oxidized to CO 2 by microbes (70%). A smaller, but still substantial amount of methane is degassed to the atmosphere at the canal surface (26%) and a small amount remains dissolved in the canal where it exits the peatland (4%).
Acknowledgments The authors thank  Jeffery Muli anak Incham ,  Ramasamy anak Zulkiflee ,  Haji Bohari  bin  Haji Idi  and  Surin Kumar Thamilselvam  for field assistance;  Jonathan Davies ,  Shuhei Ono  and  Richard Doucett  for helpful discussions and technical guidance; the  Brunei Forestry Department  for permission to conduct research at Badas (JPH/UND/17) and export permits;  Brunei Shell Petroleum Co Sdn Bhd  for site access and discussions;  Frédéric Julien  at the PAPC platform for major elements analysis (EcoLab Laboratory). This research was supported by the  National Research Foundation Singapore  under Grant  NRF2016-IT-COO1-021 , the  US National Science Foundation  under Grant  1923491 , and the  Natural Science and Engineering Research Council of Canada.
Data Availability Statement Field data and Matlab model codes  (Somers et al. , 2023)  for this study are available without registration from the HydroShare repository at https://doi. org/10. 4211/hs. 3953b24e0238467980a226c72cfc360e. Matlab model files  (Somers et al. , 2022)  are also available without registration from GitHub at https://github. com/Lauren-Somers/ Badas_Methane.
General description Purpose: One of the objectives of the programme is to make the information available to a wide public and to ensure it is always accessible and evolving. Experience from other AFTBIs shows that data management is often underestimated and information loss is a common issue  (Langdon et al. 2006 , Deharveng et al. 2015 , Ichter et al. 2022). Although the quality of the information was an important issue since the beginning of the project, the partners identified the need to allow extra resources for data quality and dissemination. All data and metadata are now structured according to the standards of the national information system for biodiversity (SINP) and the Global Biodiversity Information Facility (GBIF). Additional information: Before the publication of the datasets, we performed a quantitative and qualitative assessment of all data (see Quality control), an update of metadata and harmonisation of the information and we invited experts to pass on new species identification and relevant information.
Project description Personnel: About 92 people actively participated in the project, mostly field biologists, but also taxonomists in their laboratories in France and abroad (see Acknowledgements). As part of the partnership, a full-time project manager was recruited by the MNHN to coordinate the various studies and the fieldwork, exchange with the stakeholders including the partners, manage the data and write the scientific and technical reports. A professional entomologist was tasked with sorting the material from continuous sampling methods (i. e. entomological traps) and sending specimens to the specialists. The preparation of the data paper was an opportunity for a qualitative and quantitive update of the different datasets involving staff from PatriNat and an independent consultant.
A combination of standardised (i. e. trapping campaign) and opportunistic surveys is considered one of the most efficient methods to assess flying insect diversity  (Deharveng et al. 2015 ). An ecological assessment method, the Ecological Quality Index, was also used. As shown by the dataset, seven studies were performed from 2012 to 2021 on different parts of the Bois de Bouis to gather information for management and decision-making  (Delzons and Rault 2013a , Delzons and Rault 2013b , Rault and Delzons 2014 , Gourdain et al. 2017 , Roquinarc'h et al. 2022 ). The protocol is a transect survey of reptiles, butterflies, birds, amphibians, dragonflies, vascular flora and natural habitats across the natural habitats of the site. One study involved 6 days of fieldwork over four campaigns (including two dawns and one evening) from early spring to late summer in a year.
Sampling methods Sampling description: Sampling methods and techniques are varied and depend on the target and the type of habitat (Fig. 3 ). The most frequent techniques for collecting biodiversity data involves visual and auditive contact (e. g. 10 birds count or Orthoptera inventories using transects  (Lacoeuilhe et al. 2020) ). The invertebrates provide the most diverse sampling techniques: entomological net, light traps, sieving of litter, mowing of vegetation, the beating of trees and passive interception traps. Two malaise tents were placed between 28 April and 30 June 2014 and from 08 April to 20 July 2015. The first trap was set in an open area on the golf course and the second in undergrowth in the eastern part of the Bois de Bouis estate. Samples were preserved in alcohol to facilitate their management and their sending to specialists.
Some specimens were identified by DNA barcoding. Around 28,000 specimens were collected and sorted. Others specific methods were employed, such as plankton nets and sampling bottles for algae, ultrasonic bat detectors and recorder (SM2, SM4BAT and Audiomoth; Defrancq (2020), Defrancq and Lacoeuilhe (2020)), capture-recapture sampling of Hermann's tortoise  (Boitier and Teynié 2007 , Boitier 2008 , Boitier 2010 , Rault 2015) , soil sampling and then laboratory study of Nematodes (Sager 2019) and vegetation monitoring plots. The habitat map was produced using vegetation surveys and a GIS software (QGIS). The sampling methods are included in the datasets' metada using the national protocols and methods repository CAMPANULE  (Ichter et al. 2014b).
Quality control: The ATBI Bois de Bouis database is managed by PatriNat in the framework of the National Inventory of Natural Heritage (INPN). This information system guarantees the traceability of data and authorship and normalised standards of data and metadata. A high level of data quality was expected at all stages of the programme, especially in terms of accuracy and precision (Chapman 2005). The species have been directly identified by experts or the data have been checked by experts, which guarantees a good level of reliability of the identifications. Before data publication, two types of controls were performed. The first category of control is compliance with SINP standard formats. The data must be compliant with both physical and conceptual aspects: mandatory fields, required formats, repositories (including geographical and taxonomical, see Taxonomic coverage), classifications and lists of values.
Usage licence Usage licence: Creative Commons Public Domain Waiver (CC-Zero) nameAccordingTo The reference to the source in which the specific taxon concept circumscription is defined or implied -traditionally signified by the Latin "sensu" or "sec. " (from secundum, meaning "according to"). For taxa that result from identifications, a reference to the keys, monographs, experts and other sources should be given. dateIdentified The date on which the subject was determined as representing the Taxon. (83). This dataset corresponds to species data from the Ecological Quality Index (EQI) expertise in the eastern part of the estate. Provence-Alpes Côte d'Azur region, 457 species and 15 subspecies new for the Var Departement and 1618 species and 58 subspecies new for the Vidauban commune.
We argue that the work carried out on the Bois de Bouis estate responds to the abovementioned criteria and can be considered an All taxa biodiversity inventory. The main arguments are: 1) significant sampling efforts over a large period (most groups have been sampled at least twice), 2) a wide variety of taxonomic groups (including cryptic groups such as Algae, Lichens, Nematodes, Aranea or Hymenoptera), 3) a high level of data quality and dissemination and 4) significant scientific results  (Rault et al. 2015 , Kehlmaier et al. 2019 , Tillier 2019). However, the biodiversity inventory is far from being comprehensive, especially for lesserknown groups like Flies, Worms or Moths. Most Fungi (except Lichens) were not surveyed during the project. In 2009, a first study on the habitats of the Bois de Bouis estate was carried out (Baret 2009).
Acknowledgements The authors wish to thank all the participants involved in the  Bois de Bouis ATBI  during field surveys and species identification:  Pascal Auda ,  Philippe Bachelard ,  Jean-Philippe Barbarin ,  Julien Baret ,  Anne Bedos ,  Emmanuel Boitier ,  Michel Brulin ,  Stephen Byrne ,  Antoine Catard ,  Marion Charles ,  Cyprien Comoy ,  Elfie Corfa ,  Alain Couté ,  Xavier Cucherat ,  Christophe Daugeron ,  Jean-Christophe De Massary ,  Théo Defrancq ,  Louis Deharveng ,  Olivier Delzons ,  Camille Desjonqueres ,  Frédéric Durand ,  François Dusoulier ,  Olivier Escuder ,  Laëtitia Farsac ,  Laurent Fauvre ,  Colin Fleming ,  Catherine Fournil ,  Christophe Galkowski ,  Olivier Gargominy ,  David Genoud ,  Jean-Jacques Geoffroy ,  Dominique Guicheteau ,  Eric Guilbert ,  Patrick Haffner ,  Christophe Hervé ,  Michael Hilti ,  Arnaud Horellou ,  Horst Bohn ,  Christophe Jassaud ,  Mark Judson ,  Jean-François Julien ,  Julien Laignel ,  Michaël Latocha ,  Manon Latour ,  Lilian Leonard ,  Patrice Leraut ,  Sébastien Lesne ,  Sylvia Lochon-Menseau ,  Lise Maciejewski ,  Armand Matocq ,  Margaux Mistarz ,  Thierry Noblecourt ,  Pierre Noël ,  Benoît Nusillard ,  Benoît Offerhaus ,  Massimo Olmi ,  Yann Pastor ,  Christian Perez ,  Mitchell Pete ,  Dominique Pluot-Sigwalt ,  Rémy Poncet ,  Yoann Prioul ,  Renaud Puissauve ,  Clovis Quindroit ,  Philippe Reisdorf ,  Philippe Reynaud ,  Quentin Rome ,  Pascal Rousse ,  Amélie Roux ,  Manon Sager ,  Laura Savio ,  N.
Column description idem as "Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données algues d'eau douce 2018-2019" idem as "Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données algues d'eau douce 2018-2019". Data set name: Données espèces-Expertise Indice de Qualité Ecologique (IQE) Golf de Vidauban 2021/Ecological Quality Index Vidauban Golf 2021. Download URL: https://doi. org/10. 15468/7ugtew Data format: Darwin Core Archive Description: This dataset was acquired as part of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (MNHN -OFB -CNRS). The Bois de Bouis estate is a private property of 870 ha in the heart of the Plaine des Maures in the town of Vidauban in the Var Department (83).
This dataset corresponds to species data from the Ecological Quality Index (EQI) expertise on the golf course in 2021. Column label Column description idem as "Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données algues d'eau douce 2018-2019" idem as "Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données algues d'eau douce 2018-2019". Data set name: Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois deBouis -Données mollusques continentaux/All Taxa Biodiversity Inventory (ATBI) ofBois de Bouis estate -Continental mollusc data. Download URL: https://doi. org/10. 15468/y3q4ua Data format: darwin core Description: This dataset was acquired in the framework of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (Muséum national d'Histoire naturelle/Office français de la biodiversité/Centre national de la recherche scientifique) as part of an All Taxa Biodiversity Inventory (ATBI) of a biodiversity-rich private golf estate in south-eastern France (Vidauban, Var).
This dataset contains mollusc data acquired between 2018 and 2019. Inventaire général de la biodiversité (IGB/ ATBI) Domaine Bois de Bouis -Données algues d'eau douce 2018-2019" idem as "Inventaire général de la biodiversité (IGB/ ATBI)Domaine Bois de Bouis -Données algues d'eau douce2018-2019". Data set name: Habitat mapping Bois de Bouis estate. Data format: geospatial vector data Description: This habitat dataset was acquired as part of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (MNHN -OFB -CNRS). The Bois de Bouis estate is a private property of 870 hectares in the heart of the Plaine des Maures in the town of Vidauban in the Var Department (83). Habitat survey was carried out between 2014 and 2021 for the whole site at a scale of 1:5000 using EUNIS typology.
Used to indicate whether the habitat or habitat complex observed is stationary (it is present on the whole of the geographical object) or inventory (it is found on a given part of the geographical object without further precision). type_geom Type of geometry of the habitat observation event. id_sinp_jdd Permanent and unique identifier of the dataset metadata record in the SINP to which the observation data belongs. id_jddid_jdd Another unique identifier of the metadata record of the dataset in the SINP to which the observation data belongs. id_obs_habitat Unique identifier of the habitat observation. id_sinp_habitat Unique identifier of the observed habitat. It takes the form of a UUID (Universally unique identifier). id_origine_habitat Unique identifier of the observation in the producer database where the original data are stored and initially managed.
nom_cite Name of the habitat originally cited by the observer. code_hab_cite Code of the habitat originally cited by the observer or by the determiner (when it is not the same person). Code assigned to the habitat unit in the typology used by the data producer to describe the habitat observation and recorded in the source database. It should not be confused with the cdHab, which is the unique identifier of the habitat unit in the HABREF repository (when this habitat unit is included). nom_typo Typology to which the habitat unit is attached. This information is particularly useful in the case where the typology does not appear in the national reference system. (HABREF). cd_hab Unique identifier of the housing unit within the HABREF repository. This identifier is named CD_HAB in the HABREF repository.
The horizontal distance (in metres) from the given decimalLatitude and decimalLongitude describing the smallest circle containing the whole of the Location. Leave the value empty if the uncertainty is unknown, cannot be estimated or is not applicable (because there are no coordinates). Zero is not a valid value for this term. Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données bryophytes/All Taxa Biodiversity Inventory (ATBI) of Bois de Bouis estate -Bryophyte data. This dataset was acquired in the framework of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (Muséum national d'Histoire naturelle/Office français de la biodiversité/Centre national de la recherche scientifique) as part of an All Taxa Biodiversity Inventory (ATBI) of a biodiversity-rich private golf estate in south-eastern France(Vidauban, Var).
This dataset contains bryophyte data acquired in 2016. This dataset was acquired in the framework of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (Muséum national d'Histoire naturelle/Office français de la biodiversité/Centre national de la recherche scientifique) as part of an All Taxa Biodiversity Inventory (ATBI) of a biodiversity-rich private golf estate in south-eastern France(Vidauban, Var). This dataset contains monitoring data for Hermann's Tortoise (Testudo hermanni). Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données étude chiropteres 2020/All Taxa Biodiversity Inventory (ATBI) of Bois de Bouis estate -Chiroptera data 2020. This dataset was acquired in the framework of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (Muséum national d'Histoire naturelle/Office français de la biodiversité/Centre national de la recherche scientifique) as part of an All Taxa Biodiversity Inventory (ATBI) of a biodiversity-rich private golf estate in south-eastern France (Vidauban, Var).
The dataset contains bat (chiroptera) data acquired in 2020. This dataset was acquired in the framework of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (Muséum national d'Histoire naturelle/Office français de la biodiversité/Centre national de la recherche scientifique) as part of an All Taxa Biodiversity Inventory (ATBI) of a biodiversity-rich private golf estate in south-eastern France (Vidauban, Var). Inventaire général de la biodiversité (IGB/ATBI) Domaine Bois de Bouis -Données flore/All Taxa Biodiversity Inventory (ATBI) of Bois de Bouis estate -Floristic data. This dataset was acquired in the framework of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE), PatriNat (Muséum national d'Histoire naturelle/Office français de la biodiversité/Centre national de la recherche scientifique) and the Conservatoire Botanique National Méditerranéen (CBNMed) as part of an All Taxa Biodiversity Inventory (ATBI) of a biodiversity-rich private golf estate in south-eastern France (Vidauban, Var).
The dataset contains floristic data acquired between 2018 and 2019. This dataset was acquired in the framework of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (Muséum national d'Histoire naturelle/Office français de la biodiversité/Centre national de la recherche scientifique) as part of an All Taxa Biodiversity Inventory (ATBI) of a biodiversity-rich private golf estate in south-eastern France (Vidauban, Var). The dataset contains nematode data acquired between 2018 and 2019. ATBI) of a biodiversity-rich private golf estate in south-eastern France (Vidauban, Var). The present dataset contains insect data acquired between 2013 and 2015 from flight interception traps. This dataset was acquired as part of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (MNHN -OFB -CNRS).
The Bois de Bouis estate is a private property of 870 ha in the heart of the Plaine des Maures in the town of Vidauban in the Var Department (83). This dataset corresponds to species data from the Ecological Potential Index (EPI) expertise in the Bois de Bouis in 2015. This dataset was acquired as part of the partnership between the Fondation d'Entreprise du Golf de Vidauban pour l'Environnement (FEGVE) and PatriNat (MNHN -OFB -CNRS). The Bois de Bouis estate is a private property of 870 ha in the heart of the Plaine des Maures in the town of Vidauban in the Var Department (83). This dataset corresponds to species data from the Ecological Quality Index (EQI) expertise in the Bois de Bouis in 2012. Données espèces-Expertise Indice de Qualité Ecologique (IQE) Golf de Vidauban 2012/Ecological Quality Index Vidauban Golf course 2012.