dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgement We acknowledge the "Ecole Doctorale ED305" from the University of Perpignan Via Domitia for funding the PhD grant of Mel Constant and the "Parc naturel marin du golfe du Lion" for the Master grant of Morgan Mino-Vercellio-Verollet. We thank Núria Ferrer from the "Centres Científics i Tecnològics" of the University of Barcelona for her technical support during FTIR analyses. We are also grateful to the "Centre d'études et d'expertise sur les risques, l'environnement, la mobilité et l'aménagement" (CEREMA) for providing us swell data, "Météo-France" for the access to weather data and the Banque Hydro hosted by the "French Ministère de l'Environnement et du Développement durable" for hydrological data. This research has also been supported by a Catalan Government Grups de Recerca Consolidats grant (2014 SGR 1068).
Recent progress on instance segmentation demonstrated by the Mask-RCNN method is very promising in the context of herbarium sheets, in particular for detecting with high precision different organs of interest on each specimen, including leaves, flowers, and fruits. However, like any deep learning approach, this method requires a significant number of labeled examples with fairly detailed outlines of individual organs. Creating such a training dataset can be very time-consuming and may be discouraging for researchers. We propose in this work to integrate the Mask-RCNN approach within a global system enabling an active learning mechanism (Sener and Savarese 2018) in order to minimize the number of outlines of organs that researchers must manually annotate. The principle is to alternate cycles of manual annotations and training updates of the deep learning model and predictions on the entire collection to process.
Discussion Previous surveys of floating macrophytes conducted close to our study sites showed that their maximum number was reached in early summer (May and June), with S. horneri as the most abundant species  36. Those findings correspond well with the results found for our bottom-trawl surveys, where S. horneri was the most frequently collected species among the macrophyte debris in spring (April) and summer (June, July). Additionally, in both     3 ) and (  4 ) are origins determined for 1-14 d, for 15-30 d, and for >30 d before the collection date of S. horneri debris, respectively. The maps were generated using Matlab R2011b (https://www. mathworks. com/ products/matlab). seasons, S. horneri dominated in the mass of macrophyte samples, but its maximum biomass was achieved in each of the three summers.
Authors confirmed that the two-way PTM provides estimates with higher reliability than other conventional numerical methods. Two components were required to use the two-way PTM origin estimation algorism: a particle tracking simulation code to simulate the floating macrophyte trajectory and a sea-surface velocity forcing data. We used a floating macrophyte particle tracking simulator developed by Filippi et al. 55. The basic attributes of this simulator are described in the Supplementary Information. We used the sea-surface velocity forcing data of the OFES (Ocean General Circulation Model for the earth simulator) calculated by JAMSTEC (the Japan Agency for Marine-Earth Science and Technology). The spatial resolution of the OFES velocity data was 0. 1° (zonal and meridian) with a temporal frequency of 3 days 56.
Acknowledgements We are extremely grateful to  Masaki Ito ,  Tsutomu Hattori , and  Yoji Narimatsu  of the  Japan Fisheries Research and Education Agency  to provide us the opportunity to take part in their bottom trawling research activities. We thank both ship crews that helped to collect the macrophyte samples. Our special thanks go to the  Japan Fisheries Information Service Center  ( Hideo Tameishi  and  Toshiyuki Kouguchi ) that provided the sea-surface temperature images, and to the  Earth Simulator Center of JAMSTEC (Yoshikazu Sasai ) that provided the OFES sea-surface velocity data. Financial support was obtained through a  Grant-in-Aid for Scientific Research , No. 12J06184 , No. 19405033 (B), and No. 22255010  (A), from the  Japan Society for the Promotion of Science.
Estimating gene flow requires the access to a random and representative sampling of the populations studied, with demographic units represented only once. Now, the delineation of what is a "demographic unit" depends on the path of sexual reproduction and on the independent or entangled fates of ramets. Once the colonies are discriminated and the level of clonality is assessed, one will engage in a population genetics analysis in a different way depending on the path of asexual reproduction. For most clonal plants including seagrasses, where modules -ramets-of the same genetic individual -genet-remain connected and potentially metabolically interdependent for some time  (Salzman and Parker 1985; Alpert 1996; Arnaud-Haond et al. 2012) , the choice of keeping or discarding replicates in the dataset before estimating population genetic structure can be debated.
Each of these choices implies underlying assumptions: the lack of a relationship between the reproductive success and the size (in terms of number of ramets) of genets, none of which are usually tested for the species and populations at stake. For corals, the question at hand is a little different: distinct colonies in the same area can be considered as independent metabolic and reproductive units, whether or not they share the same genotype, and thus be included for connectivity estimates. It is thus reasonable in most cases, provided sampled colonies were well discriminated in the field (see above), to engage into connectivity estimates based on the full dataset.
If signs of demographic expansions were also detected within M. oculata's dataset, this would support a recent population expansion/recolonisation in some reefs. The contrasting present-day genetic structure between L. pertusa and M. oculata and the polymorphism differentially shared among regions pleads for two different biogeographic scenarios: a clear support of a Mediterranean origin only for the first species, and a pattern calling for a more complex history for the other. The possibly large dispersal ability of L. pertusa larvae may have maintained genetic homogeneity in the recolonised area of the NE-Atlantic reefs analysed in this study during the last millennia  (Boavida et al. , under revision).
co/portal/es/parques-nacionales/parque-nacional-naturalcorales-de-profundidad). Specifically, results from studies on genetic connectivity of D. dianthus populations in the Mediterranean Sea contributed to the classification of a Natura 2000 Site of Community Interest (SCI), the centerpiece of the European Union's conservation policy, in the southern Tyrrhenian Sea. This SCI will be used to characterise and define the novel concept of cells of ecosystem functioning  (Boero 2015)  as conservation and management units, a key concept for the definition of networks of MPAs and for the identification of suitable areas for off-shore wind farms  (Costantini et al. 2017 ; see also www. coconet-fp7. eu, CoCoNet EU project).
Acknowledgements We wish to thank the following projects, which contributed through data production or thoughts to feed this synthesis chapter:  CoralFISH EU-FP7  project under Grant agreement no. 213144 , Atlas  H2020  under grant agreement No  678760 , the  Spanish Ministry of Science and Innovation  ( CGL2011-23306  and  CTM2014-57949R ) and  EU CoCoNET-"Towards COast  to  COast NETworks  of marine protected areas (from the shore to the high and deep-sea), coupled with sea-based wind energy potential"-from the  VII FP of the European Commission  under grant agreement n°  287844 , and the participants in the network on  Marine Connectivity MarCo  (wwz. ifremer. fr/gdrmarco/). Joana Boavida  is supported by an Ifremer post-doc fellowship. The work on M. oculata and L. pertusa corals was performed by  Ronan Becheler  during his PhD supported by an  Ifremer-Region Bretagne  grant, on corals collected during the BobEco (2011) and IceCTD ( 2012) cruises and on Mediterranean corals sampled thanks to colleagues including  Alessandra Savini ,  Marco Taviani  and  Franck Lagarde.
When researchers are not necessarily interested in appraising the extent of clonality but are just focused on basic genetic analysis to estimate genetic diversity and structure, they may favor a coarse sampling of ramets with a haphazard strategy, and exclude replicates of the same genotypes (i. e. belonging to the same genet) if still occurring in the final dataset. Making the a priori choice of ignoring clonality can be imposed by technical limitations when sampling, which are particularly acute in deep-sea research.
Since 2012, Local Climate Zones (LCZ) have been used for numerous studies related to urban environment. In 2015, this use amplified because a method to map urban areas in LCZs was introduced by the World Urban Database and Access Portal Tools (WUDAPT). However in 2017, the first HUMan INfluence EXperiment showed that these maps often have poor or low quality. Since the maps are used in different applications such as urban modelling and land use/land cover change studies, it is of the utmost importance to improve mapping accuracies and a second experiment was launched. In HUMINEX 2. 0, the focus lies on providing guidelines on the use of the mapping protocol based on the results of both HUMINEX 1. 0 and 2. 0. The results showed that: (1) it is important to follow the mapping protocol as strictly as possible, (2) a reasonable amount of time should be spent on the mapping procedure, (3) all users should perform a driving test, and (4) training area sets should be stored in the WUDAPT database for other users.
In 2015, a method  [4, 5]  was presented within the World Urban Database and Access Portal Tools (WUDAPT) initiative, to classify major urban areas into spatially explicit LCZ maps and gather information on the internal structure and texture of cities  [4, 6, 7]. The data gathering process is organized into a hierarchy based on the level of detail. The default WUDAPT level-0 fundamentally relies on supervised classification of Landsat satellite scenes into LCZ types based on training areas (TAs) that are created by urban experts who identify parts of the urban landscape that exemplify each type present in a city  [4]. Thus, WUDAPT is an example of crowd-sourcing geographic information, also referred to as volunteered geographic information  [8]  and citizen science, among other terms related to user-generated content  [9].
Layout of the Experiment The LCZ workflow  [2, 4, 23]  was provided online and consisted of a set of training materials that were used in guided student exercises. First, the students (in the remainder of the paper also referred to as participants) were introduced to the LCZ scheme and the WUDAPT framework  [4]. Subsequently, they were provided with the software and the workflow of the exercise. Each participant defined a TA set for Berlin according to the protocol developed by WUDAPT, i. e. , "to be of a size of approximately 1 km 2 ; to be as homogeneous as possible; to be compact in shape; and to have sufficient space along the borders with neighbouring LCZ areas"  [4]. Next to that, in the first round, the TA sets of each LCZ class had to include at least five to ten TA polygons in order to cover the internal variation within the different zones (e.
g. , for an urban LCZ class the internal variation due to different roof colours/materials). The experiment was set up as a joint effort of several universities who offered the online exercises to their students as part of a geographic information course. All participants were provided with the same training materials (Saga GIS software, website, and papers), which included the LCZ mapping workflow as described in  [23] , and were asked to perform a LCZ classification with at least three iterations. Next to the TA sets and LCZ maps, elaborate metadata was collected from each participant in the second phase of the experiment using an online questionnaire. Table  1  provides an overview of the collected metadata, ranging from basic information (e. g. , age and gender) to questions relating to human behaviour and personality.
Discussion The second experiment showed that it is not straightforward to deduce improved guidelines from the metadata and the training areas. As was shown in the results, no significant relation could be found between personality and dedication traits. This could mean that any individual, independently of their background could properly map Local Climate Zones after some training (e. g. , through multiple iterations or by using a 'driving test' previous to the mapping). However, the small size of the HUMINEX 2. 0 sample does not allow for drawing such conclusions. Experiments with more participants should be performed to get convincing results. Still, results indicate that pressuring participants decreases their ability to produce accurate maps. Encouragingly, the driving test results support that all WUDAPT contributors shall take the test in order to improve their capacity to locate and recognize representative TAs, and hence their mapping accuracies.
Literature selection For a systematic and reproducible literature review, we followed a four-step procedure (Collaboration for Environmental Evidence, 2013). Target literature was selected following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) framework: Identification, Screening, Eligibility, Inclusion  (Moher et al. , 2009)  (Supplementary Fig. SF1 ). Literature searches were conducted in the ISI Web of Knowledge core database targeting peerreviewed articles published online until April 30th, 2015 in two steps. In a first query, we tested it by including a specific management option such as 'irrigation' because water shortage is conceived as a potential threat to the Mediterranean agricultural system  (Fader et al. , 2016; Malek and Verburg, 2017). The search terms for the first query was thus ("agro*" OR "agri*" Or "farm*") AND (mediterranean*) AND (ecosystem*) AND (management*) AND (irrigat*) in the topic field.
This query yielded 45 papers. Then, we strove to capture the diversity of farming practices studied in case studies by not including any à priori restrictive search terms. This additional query was made with combinations of keywords including ("agro*" OR "agri*" Or "farm*") AND (mediterranean*) AND (management*) in the topic field. Similarly, we strove to include all papers that contained relevant information on ecosystem services, and a large number of indicators that were used in the literature to quantify the supply of those services. We therefore refrained from using 'ecosystem services' as a search term. Doing so helped to include relevant papers such as traditional agronomy research out of the domain of ecosystem services. The additional query returned data records for 1,881 peer-reviewed articles.
The first (n = 45) and the second query (n = 1,881) resulted in total 1,926 papers (Identification). After removing duplicate articles (n = 17) and adding one relevant article manually as suggested by a contacted author  (Roper et al. , 2013) , a total of 1,910 articles was used as the initial data base. From this initial database, we screened articles using title, abstract and full text (Supplementary Fig. SF1 , (Screening, Eligibility). We selected empirical case studies which measured ecosystem services-related properties both for conservation (treatment) and conventional (control) management options. This step excluded pure simulation modeling studies and reviews. We focused on papers reporting results from the Mediterranean Basin but included six well-designed papers (see the caption of Supplementary Fig.
Management types and options We considered six major management types (i) tillage, (ii) mulching, (iii) use of cover crops, (iv) fertilization, (v) weed management, and (vi) water management (Table  1 ), all of which had more than 10 case studies in our literature database. In the following, we describe shortly each management type and the corresponding pairwise conventional (control) and conservation (treatment) management options. Tillage. Conservative tillage aims to minimize soil disturbance. Tillage physically disturbs upper soil layers, thereby facilitating soil aeration, water infiltration as well as inhibiting weeds growth  (Phillips et al. , 1980). However, it is also known that tilling damages soil structure and harms soil organisms, which can lead to soil quality degradation  (Six et al.
From now on, the short names refer to the CICES 'group' level unless mentioned otherwise. For the detailed CICES classification, we refer readers to the Supplementary table  ST3. The mean, standard deviation, and sample size for indicators studied in each case study were extracted from texts, figures, and tables of the original literature. If a study presented the data only on the figures, we used WebPlotDigitizer  (Rohatgi, 2017)  to extract the data.
Acknowledgements This project was funded by the  EU   FP-7 project OPERAs  (grant number  308393 ). APGN, AB, WC and IRG contribute to the  Labex OT-Med  (no. ANR-11-LABEX-0061 ) funded by the  French government  through the A* MIDEX  project (no. ANR-11-IDEX-0001-02 ). We would like to thank  Bumsuk Seo  for his help with the analysis. We acknowledge the support of the  German Academic Exchange Service (DAAD)  in the form of an  International Travel Grant  which enabled H. L. to attend the Ecosystem Services Partnership 2018.
The power supply board was designed to operate off aircrafts' 28 V DC board with special care taken to stand reverse polarity and load dumps. The power supply can stand ±80 V overvoltages and features overcurrent protection (current limiting). A second board is used to control the current in the TECs with fast, high-power metal-oxide semiconductor field-effect transistors (MOSFETs) in a half bridge. Finally a sensor board with an 8-bit microcontroller measures pressure, temperature, flow rate, counts the pulses from the optics and generates 300 kHz waveforms to drive the TEC power supply MOSFETs. The system is controlled by a credit card sized computer board powered by an ARM processor. The operating system is a custom-made Linux system, built from scratch with the Buildroot framework. The computer runs advanced software algorithms  (Landau, 1993)  to achieve a tight control on the flow rate (±0.
02 L min -1 ) and temperature (±0. 1 • C). The B3010 features a TSI-compatible serial port command set, a BNC pulse output connector, data recording capability and a 9. 7 cm touchscreen. An Ethernet port allows remote access while the software is running, due to the multitasking nature of Linux. The software is written in C++ with the Qt open source library. 3 Calibration bench.
Methods: We combined genetic data and distribution databases to obtain information on biological traits and on the native/alien status of reptiles on >900 Mediterranean islands, and we gathered data on geographic and human features of islands. We then used spatially explicit generalized additive mixed models to identify the factors associated with the establishment of alien reptiles. Results: Alien reptile populations are more frequent on islands far from the native range and with large human population. Alien populations of reptiles that are able to feed on plants are particularly frequent. Traditional data sources underestimate the frequency of alien reptiles on Mediterranean islands, and using genetic evidence to assess the status of populations provided a more complete picture of the factors associated with the presence of alien populations.
e. , cryptic introduced species). Mediterranean reptiles have been the target of multiple phylogeographic studies that provide a rich dataset for addressing several unresolved questions on biological invasions and determining the currently unclear status of certain species. In this paper, we address the following questions: life history information to infer the status of island reptiles for which accurate information is available? To address these questions, we constructed a broad-scale, multispecies database with the verified status (native/alien) of island reptiles, with status ascertained via genetic and phylogeographic studies. We then assessed the relationships between status and (a) island, (b) human and (c) species characteristics, to identify the eco-geographic and human factors that increase the probability that a reptile species is alien on islands.
g. ,  Bellati et al. , 2011; Poulakakis et al. , 2013). In other cases, island populations were genetically similar to mainland populations but separated from them by hundreds or thousands of kilometres, indicating human-mediated colonization as the most likely process (e. g. ,  Carretero, Perera, Cascio, Corti, & Harris, 2009; Barbanera et al. , 2009). In a few cases, genetic data were inconclusive and the status of the population was considered uncertain. For our study, we relied on the conclusions stated by the papers reviewed. Studies that did not objectively confirm the alien status of a population but, relied on information from other authors' expertise or suppositions, were not considered to have ascertained the alien or native status of a population. We built two complementary datasets.
, 2005)  Distance to native continental range (km) Distance between the island and the nearest continental area where the species is native. Species that are far from the native range are more likely to be alien  portance (weight of evidence). All possible models were then ranked according to their Akaike's information criterion (AIC)  (Burnham & Anderson, 2002). To avoid collinearity, models that included variables with strong pairwise correlation (|r| > 0. 7) were excluded from the set of candidate models  (Dormann et al. , 2013). Island identity and taxonomy (family/genus/species) were included as random nested factors in all models, in order to take into account potential non-independence. Generalized Additive Mixed Models were fitted using a binomial error using the gamm four package  (Wood & Scheipl, 2016).
The independent variables were fitted as linear terms. Spatial autocorrelation might also bias the outcome of regressions in spatial data analyses. Therefore, we incorporated the island coordinates in GAMM as tensor product smooth terms, using thin plate regression splines  (Beale, Lennon, Yearsley, Brewer, & Elston, 2010). Simulations showed that this implementation of GAMM is able to estimate regression coefficients correctly in spatially structured datasets, with relatively good performance in the presence of violations of model assumptions, such as non-stationarity of autocorrelation  (Beale et al. , 2010). The importance of predictor variables was assessed by summing the AIC weights across all models in the set of models in which the variable occurs  (Burnham & Anderson, 2004; Giam & Olden, 2016).
The predictor variable with the largest predictor weight is estimated to be the most important, while the variable with the smallest weight is considered the least important. To confirm that our results are not biased by phylogenetic relationships, we used Pagel's lambda  (Pagel, 1999)  to assess whether the model residuals show significant phylogenetic signal. Phylogenetic analyses were performed using cape  (Tyler, Lu, Hendrick, Philip, & Carter, 2013)  based on the Pyron, Burbrink, and Wiens (2013) phylogeny. We tested the quality of the model by calculating the true skill statistics (TSS;  Allouche, Tsoar, & Kadmon, 2006)  on the confirmed dataset. A cross-validation approach was used to confirm the robustness of predictions, by randomly splitting the confirmed dataset into three sub-datasets (33% of data each) and then calculating TSS for each sub-dataset in which 75% of data was used to build the model and 25% to predict species status.