dataesr/scientific-paragraphs-categorization huggingface dataset:
officinalis was hydrically stressed tends to make it more flammable. Alkane emissions of well-watered and water-deficit R. officinalis monitored at the plant scale Values are taken from safety data sheets except for LFL and Emission Factors. using SPEE showed similar distribution to those observed at the leaf scale. Results of the composition of emissions at plant scale were in agreement with the ones at leaf scale. This work showed that plant species do not react equally with hydric stress or with combined hydric and thermal stresses. Several experiments were conducted in order to improve emission sampling with SPEE method in the compartment configuration. The active sampling from the outside of the compartment gave the best results. Concerning the influence of combined hydric and thermal stresses on fire propagation, these results suggest that both a lower content of water and a higher content of monoterpenes and fatty acids could induce an increase in plant flammability.
Acknowledgements. The authors would like to thank  Vincent Lebeurre  for plant production. We also acknowledge  Khaled Chetehouna  from  PRISME laboratory (Bourges-France ) for the loan of the heating compartment equipped with a radiant panel. Finally, we acknowledge Masters students  Kenza Ait Ali Yahia  and  Axel Rigoulet  for their participation in this project as part of their internships.
Estimating of soil sorptivity (S) and saturated hydraulic conductivity (K s ) parameters by field infiltration tests are widespread due to the ease of the experimental protocol and data treatment. The analytical equation proposed by  Haverkamp et al. (1994)  allows the modelling of the cumulative infiltration process, from which the hydraulic parameters can be estimated. This model depends on both initial and final values of the soil hydraulic conductivity, initial soil sorptivity, the volumetric water content increase (Δθ) and two infiltration constants, the so-called β and γ parameters. However, to reduce the number of unknown variables when inverting experimental data, constant parameters such as β and γ are usually prefixed to 0. 6 and 0. 75, respectively. In this study, the values of these constants are investigated using numerical infiltration curves for different soil types and initial soil water contents for the van Genuchten-Mualem (vGM) soil hydraulic model.
Our new approach considers the long-time expansions of the Haverkamp model, the exact soil properties such as S, K s and initial soil moisture to derive the value of the β and γ parameters for each specific case. We then generated numerically cumulative infiltration curves using Hydrus-3D software and fitted the long-time expansions to derive the value of the β and γ parameters. The results show that these parameters are influenced by the initial soil water content and the soil type. However, for initially dry soil conditions, some prefixed values can be proposed instead of the currently used values. If an accurate estimate of S and K s is the case, then for coarsetextured soils such as sand and loamy sand, we propose the use of 0. 9 for both constants. For the remaining soils, the value of 0.
This approach differs from the others since it does not constrain the optimized couplet to 1D flow estimation. For this purpose, numerical cumulative infiltration curves corresponding to six different synthetic soils from the database of and with contrasting hydraulic behaviours are considered. Hydrus-3D software was used to model cumulative infiltration corresponding to a zero water pressure head at the surface, considering the vGM model for describing the soil hydraulic functions and several initial water contents. The long-time expansion of QEI formulation was used to retrieve the couplet of unknown β and γ for each synthetic soil. Then, the variation of both parameters is discussed in the function of the synthetic soils and initial soil water conditions.
| Synthetic data from Hydrus-3D software Cumulative Beerkan infiltrations were simulated using HYDRUS-2D/3D software  ( Šimu ˚nek et al. , 2008) , which solves Richards' equation governing the flow by applying the finite element method. The numerical domain was configured as a cylinder of 40 cm radius and 40 cm height, representing a volume of 200 dm 3 , large enough to contain the wetting front below the ring infiltration device during the whole infiltration process until the attainment of steady-state. Finite elements of 2 mm were used to discretize the numerical domain  (Lassabatere et al. , 2009). The upper boundary condition was set to saturated water content for the ring section, while the lower boundary limit was set to free drainage condition, and zero flux boundary conditions were applied elsewhere.
, 2009) , which in Medes Islands tends to pulse between 10 and 25 m  (Bensoussan et al. , 2010). During the study period (2016 to 2021), the Medes MR was subjected to a similar number of total dives for the first 4 years (Fig. 1 ), with around 60,000 dives/yr, dropped by half in 2020 due to the COVID-19 pandemic, and mostly recovered pre-pandemic levels in 2021. To explore the site's exposure to MHWs, we analyzed hourly in-situ temperature measured during the last 20 years in the Medes Islands, obtained from the collaborative T-MEDNet initiative (www. t-mednet. org). We used  Hobday's et al. (2016)  definition for MHWs: prolonged discrete anomalously warm water events that last at least 5 days and have temperatures above the 90th percentile of the in-situ climatology. Considering the available data, we defined the climatology as the temperature data before the study and explored MHWs for the studied period.
Data analysis A total of 659 colonies were monitored, obtaining data for the following descriptors: density, as the number of colonies/m 2 ; mean height and size frequency within size-classes; biomass (g/m 2 ), and partial mortality. Biomass was estimated by using a previously adjusted relationship (B = 0. 002H 2. 61 ; relating maximum height (cm) and biomass (g of dry weight);  Coma et al. , 1998) , corrected for the percentage of surface that presented injury  (Linares et al. , 2008). Partial mortality was estimated in two ways: i) as the percentage of injured colonies, those with 10 % or more injured surface  (Linares et al. , 2008) , and ii) as the mean extent of injury, for which we differentiated recent injury (denuded axis) from overall partial mortality. Given that some locations had <100 colonies (with a minimum of 40) and that preliminary analysis showed similar demographic patterns, we performed the analysis by pooling the data for all sites.
Modelling We examined the long-term viability of P. clavata while considering different management schemes on diving frequentation and different frequencies of climate-driven MME through a size-structured matrix population model  (Lefkovitch, 1965). For the model, we implemented 7 size classes based on the life cycle of the species (see supplementary Fig. A2 ), as defined in previous studies  (Linares et al. , 2007). We computed the annual matrices by estimating survival, growth, shrinkage, and fecundity rates for each size class (see Appendix A1 for the detailed methodology), and used the R package "popbio"  (Stubben and Milligan, 2007)  to perform sensitivity and elasticity analyses, to estimate deterministic yearly lambdas (λ), as a measurement of longterm annual growth rates, together with a stochastic lambda (λs), estimated as the average growth rate in a varying environment  (Morris and Doak, 2002).
Acknowledgements We acknowledge the support of the  Ramon Alturro  and all the staff of  Parc Natural of Montgrí ,  Illes Medes  and  Baix Ter  and  Judith Ahuffinger  from the  Generatitat de Catalunya. This work was supported by the longterm monitoring programme of the  Natural Park of Montgrí, Medes Islands  and  Baix Ter  protected areas funded by  Departament de Territori i Sostenibilitat of the Generalitat de Catalunya  public agreements  PTOP-2017-130  and  PTOP-2021-3. This work was also financially supported by  MCIU/AEI/FEDER  [ RTI2018-095346-BI00 ;  HEATMED  and  TED2021-131622B-I00 ,  CORFUN ] and the  European Union 's  Horizon 2020 research and innovation programme  [grant  SEP-210597628-FutureMARES. Yanis Zentner  was supported by an  FPU grant  [ FPU20/03574 ]. C. L acknowledges the support by  ICREA Academia.
Laboratory analyses Sediment core sections were analyzed with an Avaatech X-Ray Fluorescence core scanner (XRF) available at the Laboratoire des Sciences du Climat et de l'Environnement (Gif-sur-Yvette, France) to obtain high resolution (0. 5 cm) and semi-quantitative (cps) values of chemical elements along the core. These data were used for characterizing potential changes in sediment sources throughout time associated with land cover and climate changes across the basin. Titanium (Ti), potassium (K), strontium (Sr), rubidium (Rb) and the titanium/calcium ratio (Ca/Ti) were used for identifying potential changes in detritical material contributions along the sequence  (Croudace and Rothwell, 2015). Particle size analysis was performed using a Malvern Mastersizer 3000 allowing to measure the grain size distribution between 10 nm and 3.
5 mm. Particle size was measured on the coarser layers identified along the core (n=19) and on randomly selected samples along the sequence (n=10). Grain size parameters such as d10, d50, d90 and raw data were extracted for characterizing these properties. Non-calibrated sediment density was recorded every 0. 6 mm along the sediment sequence using Computer Tomography scanner (CT-Scan) images obtained using the equipment (GE Discovery CT750 HD) available at the DOSEO platform (Université Paris-Saclay, CEA, List). Image reconstruction and relative density values (CT-number) were extracted from the scanner images using the free software ImageJ  (Schneider et al. , 2012)  following the procedure described in  Foucher et al. (2020). Energy dispersive X-ray fluorescence (ED-XRF) measurements (Epsilon 3, Malvern Panalytical) were conducted on selected samples along the sediment cores to obtain concentrations in major elements and calibrate the relative concentrations obtained with the semi-continuous XRF analyses.
ED-XRF measurements were conducted on 0. 5g of crushed sediment. Calibration was performed using the free software package XELERATE (http://www. ascar. nl/). In addition to the analyses performed on the sediment core, ED-XRF measurements were also conducted on the 17 source samples. The R package FingerPro was used for estimating the sediment contributions supplied by the potential sources (dry forest vs Andean area) in the sediment accumulated in the reservoir based on the ED-XRF and calibrated XRF records from the sediment sequence. This model un-mixed the sediment sources after a three-step statistical tracer selection procedure described in  Lizaga et al. (2020). imageries. Correlation between these temporal series was performed using the updated version of the free software Analyseries  (Paillard et al.
Acknowledgements The authors are grateful to the  DOSEO platform (Université Paris-Saclay, CEA , List) and especially to  Anne-Catherine Simon  and  Mathieu Agelou  for performing the tomography scanner measurements on the core sections. This work was supported by  ANR PIA  (funding  ANR-20-IDEES-0002 ) and by  ProCiencia  (https://prociencia. gob. pe) through the project " Implementación del sistema de Monitoreo de los Sedimentos Ante los Riesgos y Desastres ", contract  N°011-2018-FONDECYT/BM- Mejoramiento de infraestructura  para la investigación, as well as the  FONDES  project through the " Fortalecimiento de la red de monitoreo de  sedimentos y la sedimentación en los embalses de Poechos y Gallito Ciego" and the Technical Cooperation https://doi. org/10. 5194/egusphere-2022-1233 Preprint.
Motivation: Aquatic insects comprise 64% of freshwater animal diversity and are widely used as bioindicators to assess water quality impairment and freshwater ecosystem health, as well as to test ecological hypotheses. Despite their importance, a comprehensive, global database of aquatic insect occurrences for mapping freshwater biodiversity in macroecological studies and applied freshwater research is missing. We aim to fill this gap and present the Global EPTO Database, which includes worldwide geo-referenced aquatic insect occurrence records for four major taxa groups: Ephemeroptera, Plecoptera, Trichoptera and Odonata (EPTO).
Spatial location and grain: The database covers the global extent, with 86% of the observation records having coordinates with at least four decimal digits (11. 1 m precision at the equator) in the World Geodetic System 1984 (WGS84) coordinate reference system. Time period and grain: Sampling years span from 1951 to 2021. Ninety-nine percent of the records have information on the year of the observation, 95% on the year and month, while 94% have a complete date. In the case of seven sub-datasets, exact dates can be retrieved upon communication with the data contributors.
, 2018; Schmidt-Kloiber et al. , 2017) , the CONUS database for the contiguous United States  (Twardochleb et al. , 2021)  and Macro-MED for macroinvertebrates of mediterranean countries  (Blanco-Garrido et al. , 2013) , as well as online repositories such as Odonata Central (https://www. odona tacen tral. org/;  Abbott, 2018)  the Atlas of Living Australia (ALA; http://www. ala. org. au) and the Global Biodiversity Information Facility (GBIF. org, 2020). However, these are either focused on one taxonomic order (e. g. , DAET for caddisflies, Odonata Central for dragon-and damselflies) or cover subcontinental and continental scales (e. g. , DAET in Europe, CONUS in the USA, ALA in Australia). The majority of studies on the macroecology of freshwater insects has focused on regional or continental scales  (Altermatt et al.
Software format: The entire tab-separated value (. csv) database can be downloaded and visualized at https://glowa bio. org/proje ct/epto_datab ase/. Fifty individual datasets are also available at https://fred. igb-berlin. de, while six datasets have restricted access. For the latter, we share metadata and the contact details of the authors. K E Y W O R D S aquatic insects, biodiversity, Ephemeroptera, freshwater ecosystems, global dataset, observation records, Odonata, Plecoptera, species distributions, Trichoptera distributions  (Collen et al. , 2014; Vinson & Hawkins, 2003). Species distribution models are now increasingly used to predict aquatic macroinvertebrate distributions at regional scales  (Bush et al. , 2014; Dias-Silva et al. , 2021; Domisch et al. , 2013; Kaelin & Altermatt, 2016; Nieto et al.
, 2017). These could greatly benefit from more occurrence records and larger-scale data, as manifested in  Sánchez-Fernández et al. (2011)  over a decade ago, not least to decrease geographic and environmental sampling biases. Overall, the Global EPTO Database aims to fill these gaps, assisting future studies to disentangle broad-scale spatial patterns and determinants of insect distributions and detect biodiversity hot-and coldspots across the world.
| Data acquisition The Global EPTO Database is a comprehensive compilation of heterogeneous data sources. As well as the 93 co-authors who contributed with occurrence records via personal communication up to the end of 2021, our database has also been supported by many researchers and taxonomists who contributed to parts of databases, such as the DAET  (Neu et al. , 2018; Schmidt-Kloiber et al. , 2017) , the CONUS database covering the contiguous USA  (Twardochleb et al. , 2021) , Mayflies of South America (Dos  Santos et al. , 2018; Molineri et al. , 2020) , and Macro-MED  (Blanco-Garrido et al. , 2013) , as well as the public databases GBIF (2020) and ALA (http://www. ala. org. au). Overall, we collated an initial number of 10,069,801 occurrence records, comprising any georeferenced data on EPTO records that had been made available until December 2021.
| Taxonomy We standardized the database at the genus level. We validated and complemented the taxonomic classification of the occurrence records using the package "taxize" v. 0. 9. 99 in R (R Core Team, 2020), which interacts with the Integrated Taxonomic Information System (ITIS) and the National Center for Biotechnology Information (NCBI) databases to verify genus names and correct spelling, as well as to obtain taxonomic hierarchies  (Chamberlain & Szöcs, 2013). For cases in which names were not found in these databases because of misspellings or database deficiencies, we manually verified them through online sources, such as the Catalogue of Life  (Bánki et al. , 2022) , Zootaxa (http://www. biota xa. org), the Encyclopedia of Life (https://eol. org/), and primary publications. We also provide the binomial nomenclature regarding species names, available for 7,727,980 (93%) records, without further taxonomic verification because of heterogenous country-level checklists.
| Dates We included records taken between 1951 and 2021 in the database and harmonized the sampling dates to the yyyymmdd format in R, split into separate columns of year, month and day. We removed records with a date format that impeded the differentiation between month and day (e. g. , 03082000) or with a year later than 2021. Additionally, we removed records lacking year information, with the exception of the dataset "Mayflies of South America"  (Nieto et al. , 2022) , for which we kept the year range 1970-2019. In total, we discarded 331,585 records with inconsistent date information.
| Coordinate treatment We transformed all coordinates to the World Geodetic System 1984 (WGS84) coordinate reference system using the package "sp" in R  (Bivand et al. , 2013). We approximated the spatial precision of records using the number of decimal digits of the coordinates. We counted the decimal digits using the function "format. info" in R, taking 10 digits into account. Subsequently, we evaluated the validity of the records' coordinates through the package "CoordinateCleaner" by using geographic gazetteers to identify possibly erroneous sets of coordinates or imprecise records, which are common in biological collections  (Zizka et al. , 2019). We discarded records with zero or equal latitude and longitude coordinate attributes and coordinates assigned to the location of biodiversity institutions or universities, instead of exact sampling locations.
| Integration with the Hydrography90m dataset We attributed the EPTO occurrence records to their corresponding hydrographic units at two spatial scales, namely the drainage basin and sub-catchment, as delineated in the Hydrography90m dataset (https://hydro graphy. org/hydro graph y90m/hydro graph y90m_layer s/;  Amatulli et al. , 2022). In Hydrography90m, a drainage basin is defined as any area of land where precipitation is collected and drained into a common outlet, either into the sea or into an inland depression. Further, every basin is divided into smaller sub-catchments, each of them representing the land area between two stream segment nodes that contributes to the local flow accumulation of a given stream segment  (Amatulli et al. , 2022). (Yamazaki et al. , 2019). For cases in which sea coordinates were located within a 10-km radius off the coast or of an island, we attributed/snapped them to the closest sub-catchment using the function "r.
| Integration with the Freshwater Ecoregions of the World and the World Protected Areas datasets We assigned the ID of the corresponding freshwater ecoregion to each record using the Freshwater Ecoregions of the World dataset (FEOW,  Abell et al. , 2008) , after rasterizing the layer to a 90-m resolution using the function "gdal_rasterize" (GDAL/OGR Contributors, 2021). This allows quick filtering of the records based on the biogeographic realm. We included the IDs of all the freshwater ecoregions present in each dataset in its metadata file. Measures (WD-OECM), UNEP-WCMC and IUCN, 2022]. We downloaded the layer using the "wdpa_fetch" function of the "wdpar" package in R  (Hanson, 2022)  and filtered the global file based on the protection status, using the function "ogr2ogr" (GDAL/OGR contributors, 2021).
| Database formatting The database comprises the entire table including 8,319,689 publicly available WGS84 geo-referenced records of EPTO genera globally, from 50 individual datasets, for download at https://doi. org/10. 18728/ igb-fred-811. 0 and https://glowa bio. org/proje ct/ epto_datab ase/. In addition, we provide the metadata and authors' contact details for six datasets that have restricted access, comprising 48,728 records, which can be found in the metadata file (Supporting Information Table  S1 ). All data are organized in tables (i. e. , tab separated. csv format; see Supporting Information Table  S1  for the URLs to the individual datasets). Within the dataset tables, each row corresponds to one observation record defined as the presence of an individual of a given genus observed at a particular location on a given date, while the 28 columns include a variety of taxonomic, geographic and additional site-specific information (Table  1 ).
| Spatial coverage and precision The Global EPTO Database includes 8,368,467 occurrence records, covering 1,505,302 unique locations worldwide and 39,584 out of 1. 6 million drainage basins of the Hydrography90m dataset (Table  2 ;  Amatulli et al. , 2022). The records are spread across 417 out of 426 Freshwater Ecoregions of the World (FEOW,  Abell et al. , 2008) , while 20% of them occur in protected areas. We mapped the number of observations of the whole database on a 10-km regular grid and per drainage basin (Figure  1a, c , respectively) and the numbers of observation records of each order individually per drainage basin (Figure  1e ). The spatial patterns arising from the maps of Figure  1a  and the respective strong peaks in the marginal plots reveal a major sampling bias towards North America, central Europe, and Oceania.
| Taxonomic representation The observation records include 1,473 genera and 142 families (Table  2 ). Sixty-two percent of all occurrence records correspond to observations of Odonata, which is probably related to their being considered as charismatic, not least because their specimens are easily observable due to their size, colour patterns, and flying style  (Vorster et al. , 2020). The database includes more than 15 records for most genera of each order for which we have occurrence data Unique ID of the sub-catchment where the record is located, based on the Hydrography90m dataset  (Amatulli et al. , 2022)  basin_ID Unique ID of the drainage basin where the record is located, based on the Hydrography90m dataset  (Amatulli et al. , 2022)  elevation Elevation of the point of the record, in metres, based on the MERIT Hydro DEM  (Yamazaki et al.
, 2019)  WDPA_protection_status Status of the record's location based on the Protected Planet WDPA WD-OECM dataset, updated in November 2022 (UNEP-WCMC and IUCN, 2022). If "0", the record was not located in a protected area. If "1", the record was in a protected site. If "2", the record's location was protected on a date following the observation required for building robust predictive models, such as species distribution models (SDMs), may vary depending on the prevalence and spatial representativeness of each taxon  (van Proosdij et al. , 2016) , it has been proposed that 15 presence observations may be enough to capture the general response of species to important environmental gradients  (Mateo et al. , 2010; Støa et al. , 2019). Following this guideline, the Global EPTO Database provides enough occurrences for modelling spatial patterns and their underlying mechanisms of most EPTO genera.