dataesr/scientific-paragraphs-categorization huggingface dataset:
Unfortunately, there are not long term observations of wind waves in the upper and intermediate RDP to verify that hypothesis with a climatology, but simultaneous wind, wind waves and turbidity observations were collected at the oceanographic buoy and Pilote Norden and Torre Oyarvide during a few months during the FREPLATA/FFEM Experiment. Those data are presented in Fig. 12 , showing a clear connection between stronger winds, higher waves and increased turbidity, which supports our hypothesis. To further analyze the above mentioned connection, a multi channel singular spectral analysis (MSSA) was applied to the normalized series of the wind burst measured at Pontón Recalada and the wave height and turbidity gathered at Torre Oyarvide between October 26th and December 17th, 2010 (53 days).
Summary of conclusions In this paper we analyze SM observations in the RDP estuary with the aim of characterizing the annual mean values and the seasonal cycle and to identify the involved physical mechanisms. We used in-situ data collected during the FREPLATA/FFEM Experiment. It included six oceanographic cruises performed every approximately two months, between November, 2009 and December, 2010, which provided quasi synoptic fields and profiles of salinity, temperature and turbidity in the entire estuary. During the cruises, water samples were also collected, which were analyzed for SM concentration and turbidity. Additionally, we used time series gathered at three fixed points of the RDP, providing high temporal resolution observations of waves, winds and turbidity. We complement the study with ten years of 1 km-resolution MODIS-Aqua ocean color observations in the RDP and the adjacent shelf, processed for surface SM concentration with the IFREMER algorithm for coastal turbid waters.
Acknowledgments This study was funded by the  FFEM (Fonds Français pour l'Environnement Mondial of France)  in the frame of the  PNUD/ GEF RLA/99/G31   FREPLATA  Project, the  ANPCyT (National Agency for Scientific and Technological Research of Argentina)   PICT 2010-1831  and the  CONICET (National Council for Scientific and Technological Research of Argentina)   PIP 112 201101 00176  Projects. Diego Moreira 's and  Moira Luz Clara 's participation were also allowed by  UBA  and  CONICET Ph. D. fellowships, respectively.
Background Molecular analysis of gut or feces contents using polymerase chain reaction-based techniques (PCR) has the potential to characterize predator diets and unveil the complexity of food webs  [1] [2] [3]. Prey-specific DNA fragments can be detected from unidentifiable prey items, even after several hours of digestion  [4] [5] [6]. Amplified sequences are then compared against existing prey sequence databases to provide a qualitative dietary analysis of any vertebrate or invertebrate predator  [7]. The success of molecular analyses of animal gut contents primarily depends on the ability to detect the range of prey consumed via PCR amplification. Gut contents may contain undigested (recently consumed) or indigestible individual prey items which can be individually dissected and from which a target gene can be amplified and sequenced to supplement morphological identification  [8] [9] [10].
These primers are particularly useful when either predators have a diet restricted to one or a few taxonomic groups (i. e. bats feeding on insects  [14, 24, 25] ), or the aim of the study is to detect specific food items (i. e. detect consumption of invasive species by generalist predators  [15, 16] ). On the other hand, using multiple sets of species or group-specific primers to screen the gut or feces contents of generalist predators for food web studies will be costly, time consuming and might produce false negatives as sequence datasets used to design primers are often incomplete  [17]. In this case, versatile PCR primer sets (also referred to as universal or general primers), designed to bind to a highly conserved region across taxa, will be more powerful to establish an exhaustive list of prey consumed.
This preliminary COI database was used to (1) provide guidelines for the choice of a restriction enzyme and the design of predator specific blocking primers that would minimize loss of prey (false negatives), and (2) identify prey to provide a preliminary assessment of the feeding ecology of two predatory fish species. We believe that the methodological guidelines presented in this study are applicable for dietary analyses of any generalist predator and will ultimately encourage further research into food web dynamics in both marine and terrestrial ecosystems.
Guidelines for developing two predator DNA removal techniques Restriction enzymes. We evaluated the cutting frequency of commercially available enzymes among taxa, by mapping the presence of restriction sites within the COI barcoding region of three diverse groups found within the Moorea reef ecosystem that are represented in the BIOCODE sequence database: <330 decapod morpho-species (947 sequences), <380 ray-finned fish morpho-species (758 sequences) and <170 gastropod morphospecies (271 sequences) using the program Cleaver  [30]. We provide approximate numbers of morpho-species in each group because a number of specimens remain unidentified to the species level or belong to undescribed species  [8]. Enzymes with an effective recognition sequence length ranging between 6 and 15 base pairs which include either specified base pairs only (i.
COI fragments were similarly gel excised, purified, cloned and sequenced to enable data comparison between the sets of COI amplicons obtained after the removal of predator DNA using restriction enzymes. We examined differences in the detection of prey template (number of species amplified) between treatments. For prey detection in the gut contents of P. arcatus, a repeated measures ANOVA design was used to examine the main effect of predator removal, the main effect of primer set and the interaction between the two factors. Paired t-tests were then computed to determine the directionality of the effects and interpret the interaction. Since no predator DNA removal method was needed for prey amplification in the gut contents of N. armatus with the ''COI'' primer set, we only tested whether the mean number of prey detected using the ''dgCOI'' primer sets was higher using the blocking primer than the restriction enzyme.
Sequence dissimilarity threshold for prey species delineation The evaluation of taxonomic diversity from clone libraries obtained from gut contents requires clustering sequences into Operational Taxonomic Units (OTU). Each OTU is then assumed to represent an evolutionary distinct lineage. We used COI sequence datasets from the Moorea BIOCODE project to determine the optimal sequence dissimilarity threshold for species delineation among decapods, ray-finned fish and gastropods. Uncorrected pairwise genetic distances were calculated between aligned sequences and the furthest neighbor algorithm, with 1% to 15% dissimilarity thresholds, was employed for sequence clustering. We ran a step function analysis (as in  [35] [36] [37] ) to determine the threshold upon which the number of OTUs becomes stable: that is the threshold where intra-and inter-specific variability do not affect diversity estimations.
Taxonomic assignment of prey Sequences obtained from clone libraries were edited, trimmed and translated into amino acids for alignment using ClustalW  [39]  implemented in Geneious Pro 5. 0. 3  [40]. Sequences with anomalies (stops or frame shifts) in amino acid translation were considered non-functional mitochondrial COI (e. g. pseudogenes) and removed. Chimeric sequences were identified using the program Bellerophon  [41]  and discarded. In order to cluster remaining sequences into OTUs, pairwise genetic distances were calculated and sequences were clustered in OTUs as previously detailed. To facilitate data handling, a single sequence per OTU exhibiting a minimum distance from the other sequences was chosen. ''Representative sequences'' were then identified based on their similarity to GenBank and BIOCODE sequence libraries using BLAST  [42]  searches implemented in Geneious  [40].
Sequences matching bacteria were removed from the prey dataset. The remaining COI sequences could then be assigned to species if the BLASTN similarity was $98%  [43]. Whenever species level assignment could not be achieved, we used the Statistical Assignment Package (SAP  [44] ) which uses a Bayesian approach to calculate the probability that a sequence belongs to a higher taxonomic group to that represented in reference databases. We used a posterior probability above 0. 95 to confidently assign a sequence to a taxonomic group. We tested whether the number of fish collected was sufficient to describe the diet of the two predator species. Expected species accumulation curves with 95% confidence intervals were computed using the program EstimateS  [45, 46].
Identification of undigested and indigestible items Dissection of the digestive system of ten P. arcatus revealed very few visually distinguishable prey items. Only two nearly undigested specimens of the decapods Trapezia tigrina and Galathea mauritiana, as well as appendages of two brachyuran, one anomoura and one caridean shrimp were found in the stomach of five different fish. A gastropod shell (Homalopoma) was also recovered from one intestine. Even fewer items were gathered from the ten N. armatus digestive tracts: a chelae of a brachyura in one stomach, as well as a bivalve (juvenile Pectinidae) and a gastropod (Rissoidae) from one intestine. COI amplification and sequencing of DNA extracted from decapod appendages enabled molecular identification to the species-level. A BLAST search in the BIOCODE database provided species level identifications (.
Consequently, a total of 2390 clones were successfully sequenced from semi-digested prey homogenates of both fish species to compare the performance of predator DNA removal strategies for the detection of prey. Prey sequences represented 55 to 86% of the total number of sequences in the unfiltered dataset for the different treatments (Table  2 ). Among the sequences extraneous to predator dietary analysis, bacterial genes accounted for between 12 to 42% of the total number of sequences. Pseudogenes were not as dominant in the clone libraries (2 to 7%) and chimeric sequences were rare (,0. 01% -not reported in Table  2 ). Using BIOCODE sequence libraries, we found that there was steep decrease in the number of OTUs from 1% to 3% before reaching an inflexion point at 4% (Fig. 3A ) which corresponds to a limit where intra-specific variation becomes negligible.
The curve stabilizes from 4 to 10% before decreasing more sharply. There was a more distinct pattern for prey sequences recovered from hawkfish gut contents (clone libraries) where the total number of OTUs was constant from 5% to 10% sequence dissimilarity (Fig. 3B ). Within this range, 24 and 32 prey OTUs were found in P. arcatus and N. armatus's guts respectively (Fig. 4  and 5 ). Fifty percent of all unique prey OTUs were identifiable to the species level while an additional 29. 7% was identifiable to a higher taxonomic level. Only 20. 3% of recovered dietary items could not be confidently assigned to any taxonomic level. A representative sequence of each OTU was deposited in GenBank (accession numbers JF905638 to JF905693). In terms of the diversity of prey recovered from P. arcatus gut contents, there was a significant interaction between removal strategy and primer set (Repeated-measures ANOVA: F 1,5 = 6.
Taxonomic identification of prey gives preliminary insights into the feeding ecology of hawkfish Sequence dissimilarity thresholds ranging from 5% to 10% identified a total of 24 and 32 prey species in the gut contents of P. arcatus and N. armatus respectively. This threshold is in accordance with previous studies targeting COI which used 5% for species delineation  [35] [36] [37]. Species level matches with BIOCODE reference specimens were achieved for larger prey species (macrobiota) collected and identified at their adult benthic stage, whereas small bodied taxonomic groups such as copepods and amphipods are less represented in the database. Rarefaction curves indicate that additional specimens should be collected to better characterize the diet of these hawkfish species (Figure  S2 ). Nevertheless, species-level prey identification provided interesting new information on the feeding strategies of these fish.
The name of the taxon is underlined when it was also identified using DNA barcoding of undigested remains. The BIOCODE number of the reference specimen to which an OTU match is given when the BLASTN similarity was greater than 98%. Pictures and sampling details of each reference specimen are available at http://mooreabiocode. org/. Whenever species level identification could not be achieved, we indicate the higher taxonomic group to which each prey sequence belongs (statistical assignment package -see methods). If not assigned to species-level, taxonomic rank is shown within parentheses (p: phylum, c: class; o: order, f: family, g: genus). Mismatches between the binding site of the predator specific blocking primer and amplified templates (positions 640 to 658 at the 39end of the COI region) are presented.
The future of COI in molecular analyses of predation The ability to accurately identify detected prey by matching unknown sequences to sequences of described taxa will also determine the quality of dietary analyses. The choice of the target gene will therefore be dependent upon both the availability of databases for matching with potential prey consumed, but also upon the level of taxonomic resolution required for prey characterization. The COI gene enables species level discrimination for most metazoan groups and ever since it was proposed as an appropriate 'taxon barcode' for animals  [62] , large COI sequence libraries have become available for ecologists  [63, 64]. In order to maximize the chances of prey identification, the COI gene is likely to become a preferential target in most ecological studies.
Acknowledgments We thank BIOCODE teams who collected marine invertebrates and fish specimens,  M. Parker ,  J. Hunt ,  G. Johnson  and  R. Turner  for assistance in the laboratory, the  Centre de Recherche Insulaire et Observatoire de l9Environnement (CRIOBE) of Moorea  and the Richard B. Gump field station in Moorea for logistical support. This project was part of  M. Leray 's  PhD research program  at  UniversitePierre et Marie Curie (Paris VI ) and  Ecole Pratique des Hautes Etudes.
Background: Over the last 30 years, the Asian tiger mosquito, Aedes albopictus, has rapidly spread around the world. The European distribution comprises the Mediterranean basin with a first appearance in Switzerland in 2003. Early identification of the most suitable areas in Switzerland allowing progressive invasion by this species is considered crucial to suggest adequate surveillance and control plans. Methodology/Principal Findings: We identified the most suitable areas for invasion and establishment of Ae. albopictus in Switzerland. The potential distribution areas linked to the current climatic suitability were assessed using remotely sensed land surface temperature data recorded by the MODIS satellite sensors. Suitable areas for adult survival and overwintering of diapausing eggs were also identified for future climatic conditions, considering two different climate change scenarios (A1B, A2) for the periods 2020-2049 and 2045-2074.
As shown previously  [13, 16, 17] , January mean temperature can be used as a threshold to estimate the survival chances of overwintering diapausing eggs, whereas the annual mean temperature can be used as a threshold to estimate population stability. The suitability of an area to the survival of Ae. albopictus populations can also be determined by growing degree days (GDD) derived from temperature time series  [16]. Growing degree days are defined as the degrees exceeding a given threshold (11uC for Ae. albopictus) accumulated for all days in a given year  [14]. Furthermore, Ae. albopictus can not survive in arid areas; 500 mm precipitation per annum is considered the minimum threshold value  [18, 19]. Many areas in Europe receive sufficient precipitation for Ae. albopictus to survive, including Switzerland, with mean annual precipitation ranging from 840 mm to 1,900 mm (European Climate Assessment and Dataset (ECA&D, http://www.
Data Sources for Current Conditions A general problem in spatial modeling with environmental and meteorological variables is the uneven distribution of meteorological stations, which is particularly problematic for a complex terrain such as that characteristic for Switzerland. An alternative to meteorological stations is remote sensing which can obtain temperature time series with a high spatial resolution. A sensor especially designed for this kind of environmental monitoring is MODIS (Moderate Resolution Imaging Spectroradiometer) on board the satellites Terra and Aqua  [16]. For MODIS on Terra, data are available from March 2000 onwards; for MODIS on Aqua, data are available from July 2002 onwards. Land Surface Temperature (LST) from MODIS is captured with four records per day, at approximately 1:30 am, 10:30 am, 1:30 pm, and 10:30 pm local time (Greenwich Mean Time +1:00).
After a short processing time of one week after image acquisition, the MODIS products are provided to the public free of charge. The spatial resolution of the MODIS LST products is 1,000 m, allowing for a detailed analysis on national and regional level. With a temporal resolution of 4 values per day and spatial resolution of 1000 m, this dataset is well suited for a spatialized risk assessment of Ae. albopictus. Gridded datasets derived from meteorological station records are usually only provided with a spatial resolution of 20 km or coarser  [23, 20] ; this spatial resolution is not adequate for topographically complex terrain such as found in Switzerland. With regard to temporal resolution, certain environmental indicators such as growing degree days can only be calculated with at least one data point per day.
Since land surface temperature data obtained with remote sensing can contain gaps due to cloud cover, these gaps needed to be filled by reconstructing any missing LST values before environmental indicators can be derived from these data. LST reconstruction was achieved with a combination of statistical (principal component analysis, multiple regression analysis) and spline-based surface interpolation methods including auxiliary parameters related to land surface temperature (method based on  [24] ). For validation, LST values were compared with records from 1,487 meteorological stations (GSOD) for 240 days. The correlation between the LST values and the station record was very good with R 2 = 0. 78 averaged over all days. We also calculated the differences in monthly average temperature between GSOD records and MODIS LST data for the months January, April, July, October in the years 2003 and 2010.
The spatial averages for Switzerland of the monthly differences ranged from 23. 12uC to 3. 78uC. The inclusion of elevation as one of the auxiliary parameters allowed an increase in the spatial resolution to 250 m. The final data set used in this study consists of four temperature maps per day from July 8, 2002 onward until end of 2012. Average annual precipitation was calculated from the European Climate Assessment and Dataset (ECA&D, http://www. ecad. eu/, [20] ) using the time series aggregation functions of GRASS GIS  [25]. The original data resolution is 0. 25 degrees. The ECA&D data show a current minimum annual precipitation of 840 mm/ year (the lower boundary of the range obtained from long-term average annual precipitation within Switzerland) for the territory of Switzerland, which is higher than the minimum needed for the establishment of the tiger mosquito (i.
Data Sources for Future Conditions Data on projected future temperature and precipitation regimes for Switzerland were obtained from the Swiss Climate Change Scenarios CH2011 (http://data. c2sm. ethz. ch/dataset/ch2011/ seasonal_regional/download. html) [22, 26]. This data set is delivered as comma separated values (CSV) files with regional estimates (three regions: northeastern Switzerland (CHNE), western Switzerland (CHW), and Switzerland south of the Alps (CHS)) for projected future change for winter (DJF: December-February), spring (MAM: March-May), summer (JJA: June-August), and autumn (SON: September-November). The CH2011 data set consists of three parts: lower, medium and upper estimates of changes in temperature and precipitation relative to the reference period 1980-2009. Future conditions are available for three scenario periods (2020-2049, 2045-2074, 2070-2099), and the A1B, A2, and RCP3-PD emission scenarios.
2-4. 8uC by the end of the century (period 2070-2099) and a reduction in summer mean precipitations by 21-28%, depending on region. In contrast to A1B and A2 scenarios, the RCP3-PD emission scenario (peak and decline, also referred to as RCP2. 6) presupposes the implementation of mitigation measures aiming at reducing the anthropogenic greenhouse gas emissions in the next decades, with a likely stabilization at an annual mean warming of 1. 2-1. 8uC and a summer drying of 8-10% by the end of the century (period 2070-2099)  [22]. In this study, we focused on the well known A1B and A2 scenarios and did not consider the more aggressive mitigation scenario RCP3-PD following  [27, 28]. In the present study, future suitable areas for Ae. albopictus adult survival and overwintering of diapausing eggs were assessed considering the A1B and A2 climate change scenarios for the period 2020-2049 (denoted by the corresponding central year 2035) and the period 2045-2074 (denoted by the corresponding central year 2060), using the seasonal and regional data tables for north-eastern, western, and southern Switzerland, respectively, following the spatial division of the Swiss Climate Change Scenarios (CH2011).
Acknowledgments We gratefully acknowledge  N. Patocchi  from the '' Fondazione Bolle di Magadino '',  Switzerland, PD Dr. O. Petrini  for scientific support, and the '' Centro Sistemi Informativi '',  Canton Tessin , for providing Swiss altimetry data. We thank  Dr. Heidi C. Hauffe  for her valuable comments on an earlier version of the manuscript. We are grateful to the  NASA Land Processes Distributed Active Archive Center (LP DAAC)  for making the MODIS LST data available. We acknowledge the E-OBS dataset from the  EU-FP6  project  ENSEMBLES  (http://ensembles-eu. metoffice. com) and the data providers in the  ECA&D  project (http://www. ecad. eu).
This study was financially supported by the  Swiss Federal Office for the Environment  (FOEN, http://www. bafu. admin. ch,Bern, Switzerland). It was also partially funded by the  Autonomous Province of Trento (Italy) ,  Research funds for Grandi Progetti ,  Project LExEM  ( Laboratory of  excellence for epidemiology and modeling, http://www. lexem. eu). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Validating Mutational Signatures Validating a mutational signature requires ensuring that a large set of somatic mutations attributed to this signature is genuine in at least one sample. Validation is complicated as multiple mutational processes are usually operative in most cancer samples, and thus every individual somatic mutation can be probabilistically assigned to several mutational signatures. To overcome this limitation, we examined our dataset for samples that are predominantly generated by one mutational signature (i. e. , more than 50% of the somatic mutations in the sample belong to an individual mutational signature) and/or for samples in which all operative mutational processes have mutually exclusive patterns of mutations (e. g. , a sample with mutations only from Signature 1B, which is predominantly C>T substitutions, and Signature 18, which is predominantly C>A substitutions).