dataesr/scientific-paragraphs-categorization huggingface dataset:
According to fossil data the wood mouse arrived in North Africa 7,500 ya, while it was present in Europe since early Pleistocene. Previous molecular studies suggested that its introduction in North Africa probably occurred via the Strait of Gibraltar more than 0. 4 Mya ago. In this study, we widely sampled wood mice in order to get a better understanding of the geographic and demographic history of this species in North Africa, and possibly to help resolving the discrepancy between genetic and paleontological data. Specifically we wanted to answer the following questions: (1) when and how did the wood mouse arrive in North Africa? and (2) What is its demographic and geographic history in North Africa since its colonization? We collected in the field 438 new individuals and used both mtDNA and six microsatellite markers to answer these questions.
Our results confirm that North African wood mice have a southwestern European origin and colonized the Maghreb through the Gibraltar strait probably during the Mesolithic or slightly after. They first colonized the Tingitane peninsula and then expanded throughout North Africa. Our genetic data suggest that the ancestral population size comprised numerous individuals reinforcing the idea that wood mice did not colonize Morocco accidentally through rafting of a few individuals, but via recurrent/multiple anthropogenic translocations. No spatial structuring of the genetic variability was recorded in North Africa, from Morocco to Tunisia.
Mitochondrial DNA amplification and sequencing The cytb gene was amplified for 375 individuals using polymerase chain reaction (PCR) primers L14723, H15915  (Ducroz et al. 2001 ), ApoIntL2 (CTGGATCWAAYAACCCAACA) or ApoIntH1 (GTGGGGTRTTWAGTGGGT; this study). The internal primers designed in this study were used to amplify the DNA of the Iberian specimens, for which DNA was degraded. PCR conditions and sequencing followed  Nicolas et al. (2014). The presence of cytb pseudogenes is well documented in Apodemus  (Dubey et al. 2009). Pseudogenes are usually characterized by the presence of indels, stop codons, frame-shift mutations and amplification of heterozygotes  (Frezal and Leblois 2008; Trian and DeWoody 2002). We have not observed any of these indications in our dataset. Moreover the base composition per codon was not significantly different between individuals.
Phylogenetic analysis In our phylogenetic analyses we included all the newly sequenced specimens and all specimens available in the Genbank database for which the cytb gene was sequenced, except those considered as pseudogenes by  Dubey et al. (2009). This represents 545 individuals (Supplementary Table  S1 : 375 newly sequenced specimens and 170 specimens from Genbank). Phylogenetic relationships between haplotypes were inferred by constructing a network using the median-joining (MJ) method available in NETWORK v4. 500  (Bandelt et al. 1999). This method accounts for the coexistence of ancestral and descendent haplotypes, multifurcations, and reticulate relationships  (Posada and Crandall 2001)  and it is therefore suitable for studying intraspecific relationships. We used the MP post-processing option, which removes all superfluous median vectors and links that are not contained in the shortest trees of the network.
5 year in Morocco and Algeria  (Harich and Benazzou 1990). Demographic history was also explored using the MIGRAINE software and the newly developed model of a single population with past variations in population size  (Leblois et al. 2014). The model of past change in population size implemented in MIGRAINE is similar to that used in the mismatch analysis except that past variation in population size is exponential and not discrete/sudden. MIGRAINE was used to estimate ancestral theta (θ anc =2N anc µ, where N anc is the ancestral haploid population size and µ the mutation rate of the whole sequence), current theta (θ=2Nµ, where N is the current population size) and D, the time of occurrence of the demographic change scaled by population size (i. e. D=T/2NG, where T is expressed in years and G is the generation time).
Because MIGRAINE is based on the infinite sites model (ISM) for analysis of sequence data, two datasets were produced for the mtDNA cytb region to fit this model. For one data set, we chose to systematically remove incompatible sites for all individuals, for the second, we chose to remove haplotypes with incompatible sites. For all analyses, we pooled all individuals from Morocco because of the clear lack of genetic structure observed in F o r R e v i e w O n l y our sample. All runs with MIGRAINE were done using 1,000,000 trees, 2400 points and two iterations. To get an inference of the time of occurrence of the past expansion, we need to compute the unscaled parameter T from the scaled time parameters inferred by the different methods using a given mutation rate and a generation time. However an accurate estimation of the mutation rate is usually difficult to obtain.
Thus we decided to infer a specific mutation rate using cytb data, from the third codon position only, for the genera Apodemus and two calibration points derived from paleontological data. The divergence time between A. mystacinus (Danford and Alston 1877) and A. flavicollis/A. sylvaticus was estimated to be approximately 7 My old, and the divergence between A. sylvaticus and A. flavicollis to be approximately 4 My old  (Michaux et al. 2004; Michaux et al. 2003). All cytb sequences of 864 bp of A. mystacinus and A. flavicollis available in the Genbank database were included in our analyses (i. e. 1 and 34 sequences respectively), and considering the third codon positions only results in a data set containing 288 bp per individual sequence. The mean number of substitutions between A. mystacinus and A.
Genetic diversity Genetic variability of the microsatellite markers was measured for each locus by the number of alleles (N a ), gene diversity (H e , expected heterozygosity), and observed heterozygosity (H o ) using R package adegenet v1. 2-7  (Jombart 2008). Allelic richness, tests for Hardy-Weinberg equilibrium (HWE) and linkage disequilibrium were conducted according  Lalis et al. (2012). We then used the software FREENA  (Chapuis and Estoup 2007)  to estimate null allele frequencies (a) for each population and locus following  Dempster et al. (1977).
Population structure We applied STRUCTURE v2. 3. 3  (Pritchard et al. 2000)  to the data with K varying from 1 to 6, with 5 runs for each K value. The number of contributing populations was statistically tested using the ad-hoc Evanno statistic DK  (Evanno et al. 2005). This procedure is sensitive to pronounced changes in mean log likelihood values between successive K values and the degree of variance of any given mean. We also analyzed the spatial genetic structure with the software GENELAND v2. 5. 0  (Guillot et al. 2005)  which uses geographic information to identify spatial discontinuities in the genetic structure of the sample. We first performed a preliminary analysis with 10 runs of 1 000 000 iterations with a thinning of 500 and a burn-in of 50%, considering values for K from 1 to 6 with a starting value of 2, to infer the number of populations K maximizing the posterior probability of the data.
Demographic history The MIGRAINE software was also used on the microsatellite data set to infer past changes in population sizes. All MIGRAINE runs for microsatellites used 20,000 to 200,000 trees, 2,400 points and 3 iterations. To convert our estimates of scaled parameters into unscaled demographic parameters we considered a fixed value of 5 10 -4 mutation per locus per generation for all microsatellite loci  (Dib et al. 1996; Ellegren 2000; Sun et al. 2012).
2010; Souville 1998). Human genetic data also indicates that crossing of the strait of Gibraltar occurred for humans about 9,000 ya  (Achilli et al. 2005; Semino et al. 2004 ). Divergence values between European and Moroccan wood mice are too small to be consistent with dispersal during the Early Pleistocene. The time of divergence obtained between European and North African population (85,000-165,000 ya) is greater than the point estimates obtained for the time of expansion in North Africa according to mismatch mtDNA analyses  (between 7, 319 and 30, 259] ) and MIGRAINE microsatellites analyses (135 ya [CI: 1-344,000])). MIGRAINE mtDNA point estimates tended to be higher (125,000 ya [CI: 22,000-340,000]), but with a low precision. It is very difficult to obtain robust age estimates for recent divergent events and for the start of a past expansion for several reasons: 1) the difficulty to robustly estimate mutation rate; 2) large confidence intervals are obtained with MIGRAINE for the dating of the expansion.
Those large confidence intervals are partly due to the lack of information in the data but also to the model of continuous exponential increase. Contrarily to sudden expansions, two exponentially growing populations with an expansion starting at different moments but with a similar change in effective population sizes will lead to very similar patterns of polymorphism because of the shape of the exponential. For example,  Leblois et al. (2014)  showed that the precision of the inference of the timing of such past progressive expansion is very limited compared to other parameters and to other demographic scenarios. Confidence intervals obtained from mismatch curves are much narrower than for MIGRAINE, probably because of both the sudden expansion model and the statistical method used. Beside these methodological arguments explaining the lack of precision in the dating, the discrepancy between divergence and expansion time estimates can be explained by two biological hypotheses: 1) A recent expansion from a small area of original 'inoculation', in which the inoculation occurred 85,000-165,000 ya.
Acknowledgments This study was supported by the  ANR call "6 ème extinction" project  " ANR-09-PEXT-004  and the project  CMEP TASSILI MDU 09MDU755. RL and CRB have been partially funded by  ANR  projects  EMILE 09-blan-0145-01  and  IM-Model@CORAL. FISH 2010-BLAN-1726-01 , and by the Project  INRA Starting Group "IGGiPop ". Molecular analyses were supported by the  ATM "Taxonomie moléculaire, DNA Barcode et Gestion Durable des Collections" , the  Service de Systématique Moléculaire of the MNHN (UMS 2700, Paris, France)  and the  network "Bibliothèque du Vivant " funded by  CNRS ,  MNHN ,  INRA  and  CEA (Genoscope). Part of this work was carried out by using the resources from the  MNHN UMS 2700 , INRA GENOTOUL and MIGALE bioinformatics platforms and the computing grid of the CBGP lab. We are grateful to all collectors, particularly  E.
Isotypematched antibodies were used as controls. After staining, the samples were fixed with 0. 2% formaldehyde for 2 hours and then analyzed by flow cytometry (EPICS XL, Beckman Coulter, Fullerton, CA, USA). We settled on the appropriate gate for mononuclear cells and used EXPO32 ADC software (Beckman Coulter) to identify triple-positively-stained cells. We expressed our results as the proportion of positive cells for the three markers in relation to the total number of gated cells. Typically, 300. 000 total events were acquired to determinate the percentage of the CD34+/ CD133+/KDR+ subpopulation in the gate.
Clinical data Patients were followed-up every 3 months during a mean follow-up of 29. 3 ± 16 months. The occurrence of vascular events was recorded. Most patients were interviewed face to face, but with patients who could not attend the scheduled visits, the required information was obtained by telephone from either the patient or a well-informed relative. A physician expert in stroke collected the data; if a stroke recurrence, a vascular event or death occurred outside of our center, medical records were obtained when possible (examination of hospital records and medical files of the patients' family doctor). During follow-up, secondary prevention measures followed the guidelines of the Cerebrovascular Group from the Spanish Neurological Society  [12, 13]. Investigators blinded to the EPC level of the patients did all of the data analyses and event adjudication.
Selection results: SCIAMACHY and GOSAT XCO 2 Within GHG-CCI, two SCIAMACHY and two TANSO XCO 2 algorithms have been further developed and the corresponding data products have been inter-compared. They have also been compared with three other TANSO XCO 2 data products generated outside of this project: with the two TANSO XCO 2 products generated at NIES, Japan, (i. e. , the operational TANSO product  (Yoshida et al. , 2011)  and the scientific PPDF product  (Oshchepkov et al. , 2011) ) and with the NASA ACOS team product  (O'Dell et al. , 2012 , Crisp et al. , 2012). Analysis of all seven products indicates that the precision requirement has been met, but not the very demanding bias requirement of less than 0. 5 ppm (approximately 1 ppm has been achieved at TCCON sites). Clearly, more work on the individual retrieval algorithms is required to achieve this goal and it has been decided to continue with all algorithms.
A possible exception is the fast SCIAMACHY XCO 2 WFMD algorithm, which shows a reduced data quality in terms of precision and biases compared to the computationally much more demanding BESD algorithm. On the other hand the WFMD product has significantly (3-4 times) more data points compared to BESD and therefore much better coverage compared to any of the other data products including BESD. GHG-CCI aims at taking advantage of the fact that an ensemble of state-ofthe-art data products exists which can be exploited. To this end, the EnseMble Median Algorithm (EMMA) has been developed  (Reuter et al. , 2013). EMMA generates a Level 2 XCO 2 product using the median of the individual data products thereby largely eliminating outliers of the data products generated with the individual algorithms.
Selection results: SCIAMACHY XCH 4 Data products generated with two algorithms have been assessed: WFMD  (Schneising et al. , 2011 (Schneising et al. , , 2012) )  and IMAP  (Frankenberg et al. , 2011). Comparison with ground-based TCCON observations revealed that both data products are very similar with respect to biases. This is also true for the estimated single measurement precisions for the time period 2003-2005, when the SCIAMACHY detector did not yet suffer from major degradation in the spectral region needed for methane retrieval. After 2005, the WFMD methane shows a larger scatter (~80 ppb) compared to IMAP (~50 ppb). Both data products have to be used with care for the time after 2005 due to potential bias issues related to detector degradation as indicated by the TCCON comparison at southern hemisphere TCCON sites, where both data products show a low bias of 20-30 ppb depending on FTS site.
Selection results: TANSO XCH 4 Four algorithms and their corresponding data products have been evaluated: OCFP and OCPR  (Parker et al. , 2011)  and SRFP and SRPR  (Butz et al. , 2011). All data products show very similar biases and scatter when compared with ground-based TCCON observations. The number of data points is however significantly higher for the "Proxy" (PR) algorithms compared to the "Full Physics"  (FP)  algorithms and the agreement between the two PR data products is better than for the FP products, indicating a higher level of maturity of the (simpler) PR algorithms. Note that the SCIAMACHY XCH 4 algorithms, WFMD and IMAP, are also PR algorithms and that the FP algorithms are relatively new and currently in their early stages of development. Overall, the OCPR algorithm shows a slightly better performance compared to SRPR (primarily in terms of number of data points at TCCON sites).
It has therefore been decided to continue with OCPR within GHG-CCI. The PR XCH 4 algorithms depend on a CO 2 correction using model data. The long-term goal of GHG-CCI is to use a FP algorithm that is independent of a CO 2 model. Because the SRFP algorithm shows a somewhat better performance compared to the OCFP algorithm (e. g. , lower station-to-station biases at TCCON sites), it has been decided to continue with the SRFP algorithm, despite the lower number of data points compared to OCFP. In summary, four TANSO XCH 4 algorithms have been evaluated as part of the GHG-CCI RR and two of these algorithms have been selected for further use within GHG-CCI: OCPR and SRFP.
Additional Constraints Algorithms (ACAs) The Additional Constraints Algorithms (ACAs) are algorithms to retrieve CO 2 and/or CH 4 information for layers above the planetary boundary layer. ACAs are applied to several satellite instruments. An overview of the ACAs used within GHG-CCI is given in Table  3. As the ACAs are not the focus of this manuscript the reader is referred to the references listed in Table  3  (including caption) for details on each of these algorithms and corresponding data products. For ACAs only one algorithm per data product has been considered within GHG-CCI, i. e. , ACAs are also being further developed but not in competition and not by covering all aspects (e. g. , no dedicated validation). For ACAs a number of criteria have been defined which need to be fulfilled to contribute to the CRDP but detailed user requirements have not been formulated.
Only a limited assessment of the data products generated with ACAs has been conducted during the initial phase of GHG-CCI described in this manuscript because the focus was on ECAs. However, for each of the ACAs listed in Table  3  it has been determined if the selection criteria specified in the Round Robin Evaluation Procedure (RREP,  Buchwitz et al. , 2011b)  have been met. The RREP defines 11 criteria for ACAs which need to be fulfilled for a given ACA to contribute to the CRDP. The criteria are mostly qualitative and refer to a required minimum level of documentation, error analysis and related auxiliary information. All ACA products are potentially useful for GHG-CCI climate applications as they deliver additional information on CO 2 and/or CH 4 thereby providing potentially important constraints when used, for example, within an appropriate inverse modeling framework to derive regional surface fluxes from the satellite observations.
Climate Research Data Package (CRDP) The goal of the GHG-CCI RR was to decide which algorithms to use to generate the CRDP. It is planned to generate the CRDP during September 2012 to March 2013. Table  6  presents an overview of the planned content of the CRDP in terms of data products and their spatio-temporal coverage. The CRDP will contain all relevant information needed for inverse modeling such as single observation uncertainties, a priori profiles and averaging kernels. The CRDP will be validated during March-May 2013 and subsequently evaluated by the GHG-CCI users (June-August 2013). By the end of August, the CRDP along with the corresponding documentation will be made publicly available via the GHG-CCI website.
Summary and conclusions An overview of the main activities and results achieved during the first two years of the GHG-CCI project of ESA's Climate Change Initiative (CCI) has been presented, focusing on the CCI "Round Robin" (RR) exercise. The goal of CCI is to generate a number of Essential Climate Variables (ECVs) in-line with GCOS (Global Climate Observing System) requirements and guidelines using European Earth observation data and data from ESA Third Party Missions (TPM) such as GOSAT. To achieve this, several existing state-of-the-art retrieval algorithms for retrieving XCO 2 and XCH 4 from SCIAMACHY/ENVISAT and TANSO/GOSAT nadir radiance spectra have been further improved in order to meet challenging requirements for the targeted regional CO 2 and CH 4 surface flux (source/sink) application as defined by the GHG-CCI Climate Research Group (CRG).
The ultimate goal of the RR was to identify and select the best algorithms to be used for generating the Climate Research Data Package (CRDP), which will essentially be the first version of the CCI ECV GHG data base. In addition, retrieval algorithms for a number of other satellite instruments such as IASI and MIPAS have also been further developed, but not in competition. Substantial progress has been made during the first two years (September 2010 -August 2012) of the GHG-CCI project. For example, longer XCO 2 and XCH 4 time series have been generated from SCIAMACHY with improved data quality and better error characterization  (Reuter et al. , 2011 , Frankenberg et al. , 2011 , Schneising et al. , 2011 , 2012 , Heymann et al. , 2012a , 2012b). The same is true for TANSO  (Butz et al. , 2011 , Parker et al.
, 2011 , Schepers et al. , 2012 , Cogan et al. , 2012). Several retrieval algorithms have been further developed in competition during the GHG-CCI RR and used to generate global multi-year data sets of XCO 2 and XCH 4 from SCIAMACHY and TANSO. The data products have been evaluated by comparison with ground-based TCCON observations, by inter-comparisons of the data products generated with the different candidate algorithms, and by comparisons with other data sets including global models. Due to the sparseness of the TCCON network it was not planned to base the algorithm selection decision only on satellite -TCCON comparisons. It has been found that nearly all candidate algorithms produce data with very similar quality at TCCON sites, i. e. , show similar satellite -TCCON differences. Significant differences have however been found remote from TCCON when comparing the global data sets, e.
g. , when comparing global maps. Depending on region and time, it has been found that the differences may exceed the systematic error requirements of less than 0. 5 ppm for XCO 2 and 10 ppb for XCH 4. It has been identified that more research is needed in order to understand the differences between the various data sets. It was therefore not possible for all products to clearly identify which of the candidate algorithms performs best. The goal of the RR was to identify which of the competing algorithms to use for the CRDP. The selected algorithms are listed in Table  6. A summary of the RR algorithm selection decision and justification is given in Section 5. 6 for the GHG-CCI ECV core data products and in Section 6 for additional products generated with algorithms not in competition during the RR phase.
The climate and inverse modeling community requires long-term datasets of near-surface-sensitive CO 2 and CH 4 observations that are as accurate and precise as possible. The goal of GHG-CCI is to build up such a time series starting with SCIAMACHY/ENVISAT (March 2002 -April 2012) and being continued with GOSAT (launch 2009) and future GHG satellite missions such as OCO-2  (Boesch et al. , 2011) , Sentinel-5-Precursor  (Butz et al. , 2012)  and potentially CarbonSat  (Bovensmann et al. , 2010). As shown in this manuscript, significant progress has been made to achieve this goal, but more work is needed in order to meet the demanding user requirements for as many conditions as possible. Table 1:  GHG-CCI XCO 2 and XCH 4 random and systematic uncertainty requirements for measurements over land.
The percentages of "Potential Outliers" (right) have been calculated using the same method except that all voxels have been counted where the differences to the median are larger than 2 ppm. As can be seen from the left figure, the data product which agrees best with the median is the ACOS product (v2. 9, 21% agreement) followed by the similar OCFP algorithm (19% agreement). The largest number of potential outliers have the data products generated with the two very fast algorithms WFMD (32%) and PPDF (16%). For a color version of this figure please have a look at the on-line version of this publication.