dataesr/scientific-paragraphs-categorization huggingface dataset:
This kind of processes cannot been properly assessed in regional climate models using monthly aerosol optical depth climatologies. Nabat et al. (2015b)  have shown that during summer 2012 the use of interactive aerosols instead of AOD climatologies could lead to differences in surface radiation of about 5 W m -2 and in near-surface temperature of about 0. 4 • C over the Mediterranean region. We could presume that a regional climate model with only monthly AOD climatology, as many of them exist in the Euro-CORDEX and Med-CORDEX programmes, for instance, could underestimate or overestimate the effects of aerosols in several weather regimes. Since cloud and aerosol variations are not uncorrelated, the frequency of clear-sky days with averaged and relatively high AOD could be, for example, overestimated in the event of using a monthly AOD data set.
Code and data availability. The code of the regional climate model CNRM-ALADIN63 is available as follows: the SUR-FEX code is accessible using a CECILL-C licence (http://cecill. info/licences/Licence_CeCILL-C_V1-en. txt, last access: 16 July 2020) at http://www. umr-cnrm. fr/surfex (CNRM, 2020); OASIS3-MCT is available at https://portal. enes. org/oasis/download (CER-FACS, 2020); XIOS is available at https://forge. ipsl. jussieu. fr/ ioserver (IPSL, 2020); and the rest of the CNRM-ALADIN63 code is available upon request to the authors. The two climate simulations used in this study are also available by contacting the authors. All the other data sets used in this study (satellite and ground-based observations) for the evaluation of the model are available at the following websites: the LAADS website for MODIS data (https://ladsweb.
modaps. eosdis. nasa. gov/missions-and-measurements/science-domain/aerosol, NASA, 2020a), the NASA EarthData website for MISR data (https:// eosweb. larc. nasa. gov/project/misr/mil3mae_table, NASA, 2020b), CERES data (https://ceres. larc. nasa. gov/data/, NASA, 2020c) and QuikSCAT data (https://podaac. jpl. nasa. gov/dataset/QSCAT_ L3_SFC_EASTWARD_WIND_1DEG_1MO, NASA, 2020d), the CloudSAT data processing center for the CALIOP CPR and CloudSAT Geoprof data sets (http://www. cloudsat. cira. colostate. edu/order-data, CloudSat DPC, 2020), the EUMETSAT CM-SAF website for the SARAH data set (https://wui. cmsaf. eu/safira/action/ viewDoiDetails?acronym=SARAH_V002, EUMETSAT, 2020), the CRU website for the CRU temperature and precipitation data set (http://www. cru. uea. ac. uk/data, Climate Research Unit, 2020), the AERONET website for AERONET AOD data (https://aeronet.
gsfc. nasa. gov/, NASA, 2020e), the BSRN website for BSRN data (https: //bsrn. awi. de/?id=393, WRMC-BSRN, 2020) and the NOAA website for the NOA indices (https://www. cpc. ncep. noaa. gov/products/ precip/CWlink/pna/nao. shtml, NOAA, 2020). Supplement. The supplement related to this article is available online at: https://doi. org/10. 5194/acp-20-8315-2020-supplement. Author contributions. PN designed and carried out the simulations, and led the writing of the paper. PN, SS, CC, MMa, MMi and DB contributed to the evaluation and the analysis of the simulations, while PN, MMa, MMi, BD, TD, RR and DSM contributed to the development of the model. https://doi. org/10. 5194/acp-20-8315-2020 Atmos. Chem. Phys. , 20, 8315-8349, 2020.
Acknowledgements. We are grateful for the support of the whole team in charge of the CNRM climate models and especially that of  Antoinette Alias  and  Stéphane Sénési  for their technical assistance. Supercomputing time and financial support of this publication was provided by  Météo-France. We thank  Julien Cattiaux  for his advice on the use of NAO data sets. We acknowledge all the PI investigators of the AERONET stations and their staff for establishing and maintaining the 72 sites used in the present work. We are also grateful to the  BSRN network  for providing radiation data in the 10 stations used here. We would like also to thank the  NASA Langley Research Center Atmospheric Science Data Center , the  National Center for Atmospheric Research and the Climate Research Unit  for providing the data sets used to evaluate our climate simulations.
This work is part of the  Med-CORDEX initiative  (http://www. medcordex. eu,last access:  16 July 2020 ) and a contribution to the  CORDEX Flagship Pilot Study  (FPS) on aerosols. It also provides a contribution to the ChArMEx programme, part of the  French multidisciplinary programme MISTRALS (Mediterranean Integrated Studies aT Regional And Local Scales ). Financial support. This research has been supported by  Météo-France. Review statement. This paper was edited by  Pedro Jimenez-Guerrero  and reviewed by two anonymous referees.
Methods: We conducted a systematic literature survey using two online publication databases, three search engines, specialist websites, and by sending a call for literature to subject experts. We successively screened the articles for relevance on titles, abstracts and full texts using criteria detailed in an a priori protocol. We then used six specific questions to categorize the retained studies and to critically appraise them. These questions encompassed the potential of verges as habitats and corridors for vertebrates, and the effects of landscape and management on these potentialities. We critically appraised all studies to assess their risk of bias and created a database of the studies with low and medium risk of bias. We synthesized results for each specific question in narrative syntheses.
Search strings The review team identified English search terms to be combined in search strings. For all keywords listed wildcards may be used to allow the use of derivations of the word's root and to account for the possibility of finding a word in various spellings (English from Great Britain or from the United States) and with various endings (singular or plural). We tested a first search string combining some of the search terms with Boolean operators of Web Of Science Core Collection (with search on "Topic"). To assess the comprehensiveness of the search string, we compared the search hits to the articles of the test list indexed in the database (see Additional file 2 for the list of articles of the test list and how it was constituted). Then, we modified the search string by removing some of the search terms and including new ones, to increase the number of articles of the test list retrieved  [21].
Publication databases We first listed the databases to which the members of our review team had access. The database selection was then based on three criteria  [21] : • Topic: the database(s) had to cover ecology; • Accessibility/reproducibility/sustainability: the database(s) had to be accessible by the whole review team, and by researchers all over the world (as a guarantee of reproducibility and further reviewing); out of the 102 articles). Searches on these two databases were made on "Topic".
Search engines We performed additional searches using three search engines: • Google Scholar (https ://schol ar. googl e. fr/); • BASE (Bielefeld Academic Search Engine, https :// www. base-searc h. net/); • CORE (https ://core. ac. uk/). Because these search engines could only handle a limited number of search terms and did not allow the use of all wildcards, the search strings used for publication databases were simplified. We thus developed a search string for each of the five LTIs (Additional file 3). In Google Scholar, results were sorted by relevance, with the boxes "include patents" and "include citations" unchecked. In BASE, results were sorted by relevance, with the box "boost open access documents" unchecked and the box "Verbatim search" checked. For each of the five search strings, we retrieved the first 20 hits.
Screening process The articles collected from online publication databases were screened by several members of the review team for eligibility (according to the criteria described in the next section) through three successive stages: first on titles (performed by AJ, EG, ELM, MV, RS, SV and VR), second on abstracts (performed by AC, AJ, EG, ELM, MV, RS, SV, VR and YB) and third on full-texts. The screening is conservative at each stage, i. e. in cases of doubt, articles proceed to the next stage for further assessment. The agreement between screeners was assessed before beginning the screening on titles and abstracts by computing a Randolph's Kappa coefficient  [21]  on a number of references randomly sampled among the sets of articles about waterways and other LTIs (200/62,940 titles and 20/23,588 abstracts), and screened by each of the reviewers independently of each other.
Study validity assessment We conducted a critical appraisal of the studies and assigned them a low, medium or high risk of bias. To define the criteria of this appraisal, eight external experts in landscape connectivity and transportation ecology were gathered and consulted during a 1-day workshop with seven scientists of our review team  [21]. During the workshop, we discussed about the gold standard protocol of an ideal study answering our primary question with unlimited resources (unlimited money, time, workforce, etc. ). We considered that a study was unreliable because of a high risk of bias, and therefore excluded it from the review, if there was/were: • A total absence of replications; • An inadequate methodology (for example for question Q4 on the role of corridor of verges, a statistical analysis of movement data that did not allow to distinguish LTI verges from other habitats); • A method description strongly insufficient (i.
Extraction of data for narrative syntheses For all specific questions, we first extracted into tables the statistically tested results of all studies with low and medium bias. For each species or group of species we extracted the effects of exposure/intervention and categorized them as positive, negative or neutral. Neutral effects referred to comparison between control and treatment that were statistically not significant (i. e. no statistically significant difference between the two, α = 0. 05). Where necessary, we assessed whether the differences were statistically significant using the confidence intervals reported by the authors. Data extraction was performed by one reviewer (DYO) and a second reviewer (AC) checked all the studies related to the specific questions Q1, Q4, and Q5.
Extraction of data for meta-analyses For each primary study, and for both LTI verges and control sites away from LTIs, sample sizes, outcome means, and measures of variation (standard deviation, standard error, or confidence interval) were extracted from tables, text, published raw data (e. g. in appendices), and graphics using WebPlotDigitizer version 4. 2 (https ://autom eris. io/WebPl otDig itize r, accessed 17 June 2019). When outcome means or measures of variation could not be directly extracted from the published data, the sample size and any other measure that enable further imputation according to Lajeunesse  [27]  (e. g. upper-and lower inter-quartile ranges, statistical tests parameters) were extracted. In case of uncertainty of the measure of variation reported (i. e. when it was impossible to know whether it was the standard deviation or the standard error that was reported), authors were directly contacted to recover missing information.
g. abundance of several species or group of species). In the models each effect size was weighted based on the precision of its estimate, with more precise estimates receiving greater weights. Weights w i were computed as w i = 1/ var i + τ 2 with τ 2 the among-study variance estimated during the meta-analysis. For each response variable (i. e. abundance and species richness), we first computed the grand mean effect size combining all studies (mixed model without moderators with cases nested within studies as random effects). We analysed the datasets for publication bias (i. e. when the published literature reports results that systematically differ from those of all studies conducted) using funnel plots, Pearson's correlation coefficient between effect size and publication year, cumulative meta-analysis by publication year, and Rosenberg's fail-safe number  [43].
Data extraction: • For readability, the coding variables "Publication year", "Authors", "Title", and "Publisher" were aggregated into a single column "Reference". For better referencing of the studies, the variable "DOI" was extracted. The unique identifier of the publication, the source of the publication, and the specific question (Q1-Q6) addressed by the study were also indicated in the final table of included studies, as well as whether the study is included in the narrative synthesis and in the meta-analyses. The implications of these deviations are considered in the review limitations section.
Literature searches and screening Searches returned 61,412 from Web Of Science Core Collection, and 21,160 from Zoological Records publication databases. We found 83 of the 84 articles of our test list indexed in Web Of Science core collection, and 49 of the 51 articles of our test list indexed in Zoological Records (Additional file 2). Combining the two databases, only one (out of 102) article of our test list was indexed in the databases but not found by our searches. The other searches gave 200 records from Google Scholar, 100 from BASE, 100 from CORE, 98 from specialist websites, and 495 from the 52 persons who answered the call for grey literature. Eventually, all the searches gave a total of 83,565 individual records which resulted in 62,940 articles after duplicate removal (Fig. 1 ).
Study validity assessment Because an article can answer to more than one of our specific questions, the 204 articles included in the review were split into 221 different studies that underwent critical appraisal. At this stage, 93 studies were excluded from further synthesis (Additional file 6, list of the studies included in the review with study validity assessment) because they showed a high risk of bias (but one study was excluded because data was redundant with another study). The reasons for a high risk of bias were the presence of a major confounding factor (53 studies), a strongly insufficient description of the method (30 studies), and an absence of replication (9 studies, Fig. 1 ). Finally, a total of 128 studies corresponding to 119 articles were retained after critical appraisal (Additional file 7, list of the studies included in the review with coded metadata).
Data synthesis: quantitative syntheses Description of the data We extracted quantitative data from 35 studies among the 82 with low or medium risk of bias addressing the specific question Q2 (Is biodiversity in LTI verges equal to, higher, or lower than in similar habitats away from LTIs?). Among the 136 cases extracted from these 35 studies, 99 cases in 31 studies referred to species or group abundance, and 37 cases in 14 studies referred to species richness (Additional file 9). We estimated the variance of cases with data imputation (i. e. filling missing variance by using the available data from the other studies) for two cases (1. 5% of the total data). When several cases were extracted from the same study, this was because there was data for several species or group of species (eight studies), for several sites (eight studies) or for several years or seasons (three studies).
Reasons for heterogeneity Highway verges may be a refuge for small mammals but seem detrimental to passerines Studies providing information on the role of road verges as habitats (question Q2) revealed contrasted patterns between birds (mostly passerines) and small mammals. Small mammal abundance was higher in highway verges than away from highways and bird species richness and abundance was lower in highway verges than away from highways (Figs. 7  and 9 , we did not analyse the response of small mammal species richness with a meta-analysis because of the lack of available cases). Fig. 6  Summary flow chart of the meta-analyses and results addressing our specific question Q2 (Is biodiversity in LTI verges equal to, higher, or lower than in similar habitats away from LTIs?). For abundance, data were analysed for each LTI separately (five subsets of data), and for species richness data were analysed for birds only.
Review limitations First, some biases in our review may arise from several decisions taken during the review process. On one hand, potential biases may arise because, due to time constraints, we excluded the articles that did not provide any abstract (N = 1235, Additional file 11), which is not consistent with the guidelines of the Collaboration of Environmental Evidence, which recommend directly allocating them to full-text screening. These articles mainly came from the Zoological Records database (93% of them). This may explain why our review contained few articles from the Zoological Records database (21 out of 119 articles). Nevertheless, most of the articles for which we did not find the full text were also from the Zoological Records database (169 out of the 209 articles with missing full text), suggesting that many of these excluded references could not have been included in the review in the end.
We however made the list of these excluded articles easily accessible for possible further use (Additional file 11). We also recommend that managers of publication databases pay attention to this issue of lacking abstract because it can interfere with the proper conduct of systematic reviews as searching for full-text and full-text screening are time-consuming steps. On the other hand, although it is a good practice, we were unable to test the consistency of screeners' decisions at full-text screening due to logistical constraints and time limitation. Clarifications and adjustments between screeners were made before the full-text assessment, and a retrospective check of a random sample of 10% of the articles rejected was done. This check revealed that it seems unlikely that some articles were missed because of inconsistency between screeners' decisions.
In addition, as we included only articles with full-text written in English or French, included studies are biased towards English and French speaking countries. The list of articles rejected because of language is nevertheless easily accessible for possible further use in Additional file 5. Last, our searches for grey literature were not consistent between the beginning of the review (call for grey literature) and the update for literature (searches on specialist websites and on BASE and CORE search engines). The call for literature made at the beginning of the review was very time-consuming for few included studies, which is why we changed search strategy to update the grey literature. Second, there is a set of limitations linked to the experimental design of the studies included in our review.
g. a small mammal). Third, the conclusions about waterways may be limited due to the difficulty in assessing waterway navigability. Indeed, the navigability of waterways is rarely reported by the authors and there is no international database that refers to this information. Thus, we included articles with Strahler  [26]  stream order above three, canals and rivers (Table  5 ) because these criteria sound relevant to restrict included articles to major waterways, implicitly assuming that they might be navigable. We are aware that this solution is not perfect: some articles about navigable waterways could have been rejected and others about non-navigable waterways could have been included. Fourth, we limited our narrative syntheses to the comparisons that were statistically tested. This resulted in the exclusion of 37 studies, often because they compared more than two categories and did not provide results for each comparison (e.
Acknowledgements We thank the CILB, the  French Ministry of Ecology  and the  ADEME  for funding this research project, the  ITTECOP research incentive program  for their logistical help and the  FRB  for their methodological support on systematic reviews and the organization of the steering committee meetings. We thank  Barbara Livoreil  ( FRB ) who contributed to the validation of the control list, the database selection, the search terms brainstorming and the external experts' workshop for critical appraisal;  Patrick Pacevicius (Cerema)  for his contribution to the screening of articles from the call to subject experts and  Google Scholar ;  Véronique Roy  (MNHN),  Nadine Deniaud  (MNHN), and  Emmanuel Jaslier  ( Université Paris 6 Pierre et Marie Curie ) for their contribution to the selection of databases and search equation and support for the bibliographical stage of the study; and  Magali Chao  ( MNHN ) for her help in searching the full text of articles.
Funding The project was supported by the CILB, the French Ministry of Ecology, the ADEME and the FRB. It was funded by the CILB, which is composed of the following LTI managing organizations: Réseau Ferré de France (now named SNCF Réseau), Voies Navigables de France, Réseau de Transport d'Électricité, GRT Gaz, Transport et Infrastructures Gaz France and Électricité Réseau Distribution France (now ENEDIS), EIFFAGE and Association des Sociétés Françaises d' Autoroutes. Besides, the French Ministry of Ecology and the ADEME supported the project through the ITTECOP program which constituted a framework for the project, offered a partial financial contribution to the project and provided funding through the Cerema participation. Finally, the FRB gave the research team methodological support for the realization of the systematic review.
2015). In the southern peripheral Arctic charr lakes of Europe, spawning typically occurs in late autumn and winter and requires stone and gravel substrate, which is frequently restricted to specific depth zones in each lake  (Gillet 1991; Low et al. 2011; Miller et al. 2015; Gerdeaux 2011). The STOREFISH database  (Teletchea et al. 2007 ), a repository of reproductive traits of freshwater teleosts based on published literature, provides data for the upper thermal tolerance of Arctic charr eggs. Multiple studies concur that egg mortality increases abruptly at water temperatures > 8-9 °C, and these studies encompass a range of freshwater populations from different geographic regions across the southern distribution limit of charr including Britain  (Swift 1965) , Central European alpine lakes  (Jungwirth and Winkler 1984; Humpesch 1985; Crisp 1996; Mari et al.
The aim of this study was to characterise changes in the contemporary and future thermal regimes during the winter spawning season of four peripheral European charr populations. These were chosen to represent different Arctic charr lake types at the southernmost distribution of the species' range-two peri-alpine lakes (Lakes Bourget and Geneva) from Central Europe and two lakes from Ireland and Britain (Lough Bunaveela and Windermere) (Fig. 1 ). Accurate assessment of temperature dynamics of the depth zones where spawning occurs and not just near the lake surface was crucial. Firstly, we used a hydrodynamic model and gridded climate reanalysis datasets to evaluate whether lake thermal dynamics have already been modified by contemporary climate change over the past four decades and whether temperature increases have encroached upon the thermal tolerance of Arctic charr.
To assess contemporary lake thermal dynamics, hourly timeseries of meteorological variables were extracted from the 0. 25°by 0. 25°grid containing each lake from the global ERA5 climate reanalysis dataset  (Hersbach et al. 2020 ) and used as model boundary conditions. In order to maximise model simulation fidelity to observed in-lake conditions, an auto-calibration routine was carried out which allows adjustment of model input parameters in order to minimise error between modelled and observed temperatures. This allows fine-tuning of specific model drivers that may not be fully realistic representations of local meteorological variables at the lake site (e. g. discrepancies between the gridded ERA5 data and actual abovelake meteorological conditions). Model performance was assessed by pairwise comparison between simulated temperatures and measured temperatures at each depth for which observations were available.