Research in limnology is nurtured by the work of many fascinating and passionate women, who have contributed enormously to our understanding of inland waters. Female limnologists have promoted and established the bases of our knowledge about inland waters and fostered the need of protecting the values of those ecosystems. However, on numerous occasions, their contribution to the advancement of limnology has not been duly recognized. Here, we review the presence of women in limnology through the history of the discipline: from the pioneers who contributed to the origins to present day' developments. We aim at visibilizing those scientists and establish them as role models. We also analyze in a simple and illustrative way the current situation of women in limnology, the scientific barriers they must deal with, and their future prospects. Multiple aspects fostering the visibility of a scientist, such as their presence in conferences, awards, or representation in societal or editorial boards show a significant gap, with none of those aspects showing a similar visibility of women and men in limnology. This article raises awareness of the obstacles that women in limnology faced and still face, and encourages to embrace models of leadership, scientific management, and assessment of research performance far from those commonly established.
This article is categorized under:
Science of Water > Methods
Water and Life > Methods
Metabarcoding of bulk or environmental DNA has great potential for biomonitoring of freshwater environments. However, successful application of metabarcoding to biodiversity monitoring requires universal primers with high taxonomic coverage that amplify highly variable, short metabarcodes with high taxonomic resolution. Moreover, reliable and extensive reference databases are essential to match the outcome of metabarcoding analyses with available taxonomy and biomonitoring indices. Benthic invertebrates, particularly insects, are key taxa for freshwater bioassessment. Nevertheless, few studies have so far assessed markers for metabarcoding of freshwater macrobenthos. Here we combined in silico and laboratory analyses to test the performance of different markers amplifying regions in the 18S rDNA (Euka02), 16S rDNA (Inse01) and COI (BF1_BR2\uffe2\uff80\uff90COI) genes, and developed an extensive database of benthic macroinvertebrates of France and Europe, with a particular focus on key insect orders (Ephemeroptera, Plecoptera and Trichoptera). Analyses on 1,514 individuals representing different taxa of benthic macroinvertebrates showed very different amplification success across primer combinations. The Euka02 marker showed the highest universality, while the Inse01 marker showed excellent performance for the amplification of insects. BF1_BR2\uffe2\uff80\uff90COI showed the highest resolution, while the resolution of Euka02 was often limited. By combining our data with GenBank information, we developed a curated database including sequences representing 822 genera. The heterogeneous performance of the different primers highlights the complexity in identifying the best markers, and advocates for the integration of multiple metabarcodes for a more comprehensive and accurate understanding of ecological impacts on freshwater biodiversity.", "keywords": ["0106 biological sciences", "570", "amplification rate; biomonitoring; biotic indices; cytochrome c oxidase I; environmental DNA; freshwater biodiversity; macroinvertebrates; primer bias; taxonomic resolution; universality", "500", "Fresh Water", "Biodiversity", "15. Life on land", "01 natural sciences", "[SDE.BE] Environmental Sciences/Biodiversity and Ecology", "Europe", "Animals", "DNA Barcoding", " Taxonomic", "Humans", "France", "[SDE.BE]Environmental Sciences/Biodiversity and Ecology"]}, "links": [{"href": "https://air.unimi.it/bitstream/2434/791349/3/ficetola%20et%20al%202020%20Mol%20Ecol%20submitted.pdf"}, {"href": "https://air.unimi.it/bitstream/2434/791349/4/mec.15632.pdf"}, {"href": "https://onlinelibrary.wiley.com/doi/pdf/10.1111/mec.15632"}, {"href": "https://doi.org/10.1111/mec.15632"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Molecular%20Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/mec.15632", "name": "item", "description": "10.1111/mec.15632", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/mec.15632"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-09-28T00:00:00Z"}}, {"id": "10.3389/fsufs.2024.1410205", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:18:59Z", "type": "Journal Article", "created": "2024-08-26", "title": "Building a solid foundation: advancing evidence synthesis in agri-food systems science", "description": "Enhancing the reliability of literature reviews and evidence synthesis is crucial for advancing the transformation of agriculture and food (agri-food) systems as well as for informed decisions and policy making. In this perspective, we argue that evidence syntheses in the field of agri-food systems research often suffer from a suite of methodological limitations that substantially increase the risk of bias, i.e., publication and selection bias, resulting in unreliable and potentially flawed conclusions and, consequently, poor decisions (e.g., policy direction, investment, research foci). We assessed 926 articles from the Collaboration for Environmental Evidence Database of Evidence Reviews (CEEDER) and recent examples from agri-food systems research to support our reasoning. The analysis of articles from CEEDER (n\uffe2\uff80\uff89=\uffe2\uff80\uff89926) specifically indicates poor quality (Red) in measures to minimize subjectivity during critical appraisal (98% of all reviews), application of the eligibility criteria (97%), cross-checking of extracted data by more than one reviewer (97%), critical appraisal of studies (88%), establishment of an a priori method/protocol (86%), and transparent reporting of eligibility decisions (65%). Additionally, deficiencies (Amber) were found in most articles (>50%) regarding the investigation and discussion of variability in study findings (89%), comprehensiveness of the search (78%), definition of eligibility criteria (72%), search approach (64%), reporting of extracted data for each study (59%), consideration and discussion of the limitations of the synthesis (56%), documentation of data extraction (54%) and regarding the statistical approach (52%). To enhance the quality of evidence synthesis in agri-food science, review authors should use tried-and-tested methodologies and publish peer-reviewed a priori protocols. Training in evidence synthesis methods should be scaled, with universities playing a crucial role. It is the shared duty of research authors, training providers, supervisors, reviewers, and editors to ensure that rigorous and robust evidence syntheses are made available to decision-makers. We argue that all these actors should be cognizant of these common mistakes to avoid publishing unreliable syntheses. Only by thinking as a community can we ensure that reliable evidence is provided to support appropriate decision-making in agri-food systems science.Organization of the data The name of the files are domain-type.zip, where type is gridded (NetCDF) or point (csv). Each zip file contains multiple files, organized in subfolders: experiment/modelNumber/variable.nc for gridded and experiment/modelNumber/variable-pilotFieldNumber.txt for point data, where experiment is rcp26, rcp45 or rcp85. domain and pilotFieldNumber domain domain location (min and max. Longitude, min and max latitude) pilotFieldNumber pilot field location (longitude, latitude) case study number country Name (OPTAIN case study) 01 50.95 51.45 14.55 15.05 1 DEU Schoeps 02 46.35 47.05 6.55 7.15 2 46.816667 6.95 2 CHE Petite Glane 02_1 46.75 47.25 7.25 7.75 1 46.983333 7.466667 02_34 47.35 47.85 8.35 3 4 47.433333 8.516667 47.683333 8.616667 02_5 46.15 46.65 5.95 6.45 5 46.4 6.233333 03a 46.65 47.15 17.45 17.95 1 2 3 4 46.92649 17.68246 46.9166 17.68976 46.91283 17.69754 46.91283 17.69723 3a HUN Csorsza 03b 46.45 46.95 16.65 17.15 3b HUN Felso Valicka 04 52.35 52.85 18.45 18.95 1 52.597469 18.728617 4 POL Upper Zglowiaczka 05 46.35 46.85 15.35 15.85 5 SVN Pesnica 06 46.45 46.95 16.15 16.65 6 HUN/SVN Kebele/Kobiljski 07 49.85 50.35 4.75 5.25 7 BEL La Wimbe 08 55.15 55.75 23.55 24.05 1 2 55.522057 23.799235 55.42233194 23.82580339 8 LTU Dotnuvele 09 45.45 45.95 9.65 10.15 9 ITA Cherio 10 59.45 59.95 10.75 11.25 1 2 3 4 5 6 7 8 59.71949 10.83576 59.6833306 10.8833298 59.6833306 10.8833298 59.665 10.9475 59.665 10.9475 59.841012 10.903597 59.757631 11.072031 59.539623 10.856447 10 NOR Krogstad 11 46.45 46.95 17.55 18.05 1 2 46.658333 17.75583 46.656944 17.75833 11 HUN Tetves 12 49.35 49.85 14.75 15.25 1 49.616837 15.078266 12 CZE Cechticky 13 55.85 56.35 25.85 26.45 13 LVA Dviete 14 59.75 60.25 17.55 18.05 14 SWE Ingvastaan Lehstaan modelNumber modelNumber Driving Model (GCM) Ensemble RCM End date 1 EC-EARTH r12i1p1 CCLM4-8-17 31.12.2100 2 EC-EARTH r3i1p1 HIRHAM5 31.12.2100 3 HadGEM2-ES r1i1p1 HIRHAM5 30.12.2099 4 HadGEM2-ES r1i1p1 RACMO22E 30.12.2099 5 HadGEM2-ES r1i1p1 RCA4 30.12.2099 6 MPI-ESM-LR r2i1p1 REMO2009 31.12.2100 variable variable description Unit Tmean Mean temperature \ufffd\ufffdC Tmin Min temperature \ufffd\ufffdC Tmax Max temperature \ufffd\ufffdC prec Precipitation mm solarRad Solar radiation MJ/m2 windSpeed Wind speed at 2m m/s relHum Relative humidity % Methodolody Bias correction was done using non-parametric empirical quantile mapping with modified method from R package qmap. Parameters selected were: corrections for each day of the year using a moving windows for a 31 days; 100 quantiles; wet days corrections for precipitation. The reference period is 1981-2010. The interpolation of gridded bias-corrected climate model simulations to the location was made using universal kriging with R packages automap and gstat with (external) variables x, y, x2, y2, x*y, z, where x is latitude, y is longitude, and z is elevation. For Digital Elevation Model Shuttle Radar Topography Mission was used. If there was an error using above mentioned variables, the number of variables was reduced to x, y, x*y, z and if there was still an error to x, y, z. Funding This project has received funding from the European Union\ufffd\ufffd\ufffds Horizon 2020 research and innovation programme under grant agreement No 862756.", "keywords": ["CORDEX", "13. Climate action", "RCM", "ERA5-Land", "OPTAIN", "EURO-CORDEX", "bias correction"], "contacts": [{"organization": "Honzak, Luka", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.6202062"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.6202062", "name": "item", "description": "10.5281/zenodo.6202062", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.6202062"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-02-21T00:00:00Z"}}, {"id": "10.5281/zenodo.7050730", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:20:54Z", "type": "Report", "title": "Climate scenarios for integrated modelling. Deliverable D3.1 of the EU Horizon 2020 project OPTAIN.", "description": "Deliverable report D3.1 of the EU Horizon 2020 Project OPTAIN (Grant agreement No. 862756). This report describes the preparation of the bias-corrected RCM simulation data for all case studies as an input to the OPTAIN modeling approaches. Summary: The objective of OPTAINs task 3.2 was to provide bias-corrected regional climate model (RCM) simulation data for all case studies as input to the OPTAIN modelling approaches. For this purpose, we used a common climate database - RCM simulations from the EURO-CORDEX project and the Representative Concentration Pathway (RCP) scenarios 2.6, 4.5 and 8.5. Bias correction was done using ERA5-Land reanalysis data with non-parametric empirical quantile mapping. Moreover, for the field scale modelling the interpolation of gridded bias-corrected climate model simulations to the location of the modelling sites was made using universal kriging. This deliverable D3.1 of the OPTAIN project reports about the procedure of creating the bias-corrected RCM simulation data and provides all necessary background information. The report starts with an introduction, followed by a description of the materials and method, where the process of preparing bias-corrected RCM simulation data is explained in six subchapters, namely: (1) required variables, (2) selection of reference data for bias correction, (3) selection of domains, (4) selection of EURO-CORDEX RCM simulations, (5) bias correction and interpolation of climate simulations and (6) evaluation and analysis. Finally, the last chapter presents an analysis of the results of the bias-correction procedure and the ensemble of RCM simulations. Together with this report, the dataset on climate scenarios for integrated modelling of the OPTAIN case studies was made publicly accessible on ZENODO: [DOI LINK] as a part of the OPTAIN project repository: [ZENODO Community LINK].", "keywords": ["13. Climate action", "H2020", "RCM", "ERA5-Land", "OPTAIN", "EURO-CORDEX", "bias correction"], "contacts": [{"organization": "Honzak, Luka, Poga\u010dar, Tja\u0161a,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7050730"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7050730", "name": "item", "description": "10.5281/zenodo.7050730", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7050730"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-02-28T00:00:00Z"}}, {"id": "10.5281/zenodo.7050731", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:20:54Z", "type": "Report", "title": "Climate scenarios for integrated modelling. Deliverable D3.1 of the EU Horizon 2020 project OPTAIN.", "description": "Deliverable report D3.1 of the EU Horizon 2020 Project OPTAIN (Grant agreement No. 862756). This report describes the preparation of the bias-corrected RCM simulation data for all case studies as an input to the OPTAIN modeling approaches. Summary: The objective of OPTAINs task 3.2 was to provide bias-corrected regional climate model (RCM) simulation data for all case studies as input to the OPTAIN modelling approaches. For this purpose, we used a common climate database - RCM simulations from the EURO-CORDEX project and the Representative Concentration Pathway (RCP) scenarios 2.6, 4.5 and 8.5. Bias correction was done using ERA5-Land reanalysis data with non-parametric empirical quantile mapping. Moreover, for the field scale modelling the interpolation of gridded bias-corrected climate model simulations to the location of the modelling sites was made using universal kriging. This deliverable D3.1 of the OPTAIN project reports about the procedure of creating the bias-corrected RCM simulation data and provides all necessary background information. The report starts with an introduction, followed by a description of the materials and method, where the process of preparing bias-corrected RCM simulation data is explained in six subchapters, namely: (1) required variables, (2) selection of reference data for bias correction, (3) selection of domains, (4) selection of EURO-CORDEX RCM simulations, (5) bias correction and interpolation of climate simulations and (6) evaluation and analysis. Finally, the last chapter presents an analysis of the results of the bias-correction procedure and the ensemble of RCM simulations. Together with this report, the dataset on climate scenarios for integrated modelling of the OPTAIN case studies was made publicly accessible on ZENODO: [DOI LINK] as a part of the OPTAIN project repository: [ZENODO Community LINK].", "keywords": ["13. Climate action", "H2020", "RCM", "ERA5-Land", "OPTAIN", "EURO-CORDEX", "bias correction"], "contacts": [{"organization": "Honzak, Luka, Poga\u010dar, Tja\u0161a,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7050731"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7050731", "name": "item", "description": "10.5281/zenodo.7050731", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7050731"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-02-28T00:00:00Z"}}, {"id": "10261/375649", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:21:44Z", "type": "Journal Article", "created": "2024-08-26", "title": "Building a solid foundation: advancing evidence synthesis in agri-food systems science", "description": "
Enhancing the reliability of literature reviews and evidence synthesis is crucial for advancing the transformation of agriculture and food (agri-food) systems as well as for informed decisions and policy making. In this perspective, we argue that evidence syntheses in the field of agri-food systems research often suffer from a suite of methodological limitations that substantially increase the risk of bias, i.e., publication and selection bias, resulting in unreliable and potentially flawed conclusions and, consequently, poor decisions (e.g., policy direction, investment, research foci). We assessed 926 articles from the Collaboration for Environmental Evidence Database of Evidence Reviews (CEEDER) and recent examples from agri-food systems research to support our reasoning. The analysis of articles from CEEDER (n\uffe2\uff80\uff89=\uffe2\uff80\uff89926) specifically indicates poor quality (Red) in measures to minimize subjectivity during critical appraisal (98% of all reviews), application of the eligibility criteria (97%), cross-checking of extracted data by more than one reviewer (97%), critical appraisal of studies (88%), establishment of an a priori method/protocol (86%), and transparent reporting of eligibility decisions (65%). Additionally, deficiencies (Amber) were found in most articles (>50%) regarding the investigation and discussion of variability in study findings (89%), comprehensiveness of the search (78%), definition of eligibility criteria (72%), search approach (64%), reporting of extracted data for each study (59%), consideration and discussion of the limitations of the synthesis (56%), documentation of data extraction (54%) and regarding the statistical approach (52%). To enhance the quality of evidence synthesis in agri-food science, review authors should use tried-and-tested methodologies and publish peer-reviewed a priori protocols. Training in evidence synthesis methods should be scaled, with universities playing a crucial role. It is the shared duty of research authors, training providers, supervisors, reviewers, and editors to ensure that rigorous and robust evidence syntheses are made available to decision-makers. We argue that all these actors should be cognizant of these common mistakes to avoid publishing unreliable syntheses. Only by thinking as a community can we ensure that reliable evidence is provided to support appropriate decision-making in agri-food systems science.Research in limnology is nurtured by the work of many fascinating and passionate women, who have contributed enormously to our understanding of inland waters. Female limnologists have promoted and established the bases of our knowledge about inland waters and fostered the need of protecting the values of those ecosystems. However, on numerous occasions, their contribution to the advancement of limnology has not been duly recognized. Here, we review the presence of women in limnology through the history of the discipline: from the pioneers who contributed to the origins to present day' developments. We aim at visibilizing those scientists and establish them as role models. We also analyze in a simple and illustrative way the current situation of women in limnology, the scientific barriers they must deal with, and their future prospects. Multiple aspects fostering the visibility of a scientist, such as their presence in conferences, awards, or representation in societal or editorial boards show a significant gap, with none of those aspects showing a similar visibility of women and men in limnology. This article raises awareness of the obstacles that women in limnology faced and still face, and encourages to embrace models of leadership, scientific management, and assessment of research performance far from those commonly established.
This article is categorized under:
Science of Water > Methods
Water and Life > Methods
Research in limnology is nurtured by the work of many fascinating and passionate women, who have contributed enormously to our understanding of inland waters. Female limnologists have promoted and established the bases of our knowledge about inland waters and fostered the need of protecting the values of those ecosystems. However, on numerous occasions, their contribution to the advancement of limnology has not been duly recognized. Here, we review the presence of women in limnology through the history of the discipline: from the pioneers who contributed to the origins to present day' developments. We aim at visibilizing those scientists and establish them as role models. We also analyze in a simple and illustrative way the current situation of women in limnology, the scientific barriers they must deal with, and their future prospects. Multiple aspects fostering the visibility of a scientist, such as their presence in conferences, awards, or representation in societal or editorial boards show a significant gap, with none of those aspects showing a similar visibility of women and men in limnology. This article raises awareness of the obstacles that women in limnology faced and still face, and encourages to embrace models of leadership, scientific management, and assessment of research performance far from those commonly established.This article is categorized under:
Science of Water > Methods
Water and Life > Methods
Enhancing the reliability of literature reviews and evidence synthesis is crucial for advancing the transformation of agriculture and food (agri-food) systems as well as for informed decisions and policy making. In this perspective, we argue that evidence syntheses in the field of agri-food systems research often suffer from a suite of methodological limitations that substantially increase the risk of bias, i.e., publication and selection bias, resulting in unreliable and potentially flawed conclusions and, consequently, poor decisions (e.g., policy direction, investment, research foci). We assessed 926 articles from the Collaboration for Environmental Evidence Database of Evidence Reviews (CEEDER) and recent examples from agri-food systems research to support our reasoning. The analysis of articles from CEEDER (n\uffe2\uff80\uff89=\uffe2\uff80\uff89926) specifically indicates poor quality (Red) in measures to minimize subjectivity during critical appraisal (98% of all reviews), application of the eligibility criteria (97%), cross-checking of extracted data by more than one reviewer (97%), critical appraisal of studies (88%), establishment of an a priori method/protocol (86%), and transparent reporting of eligibility decisions (65%). Additionally, deficiencies (Amber) were found in most articles (>50%) regarding the investigation and discussion of variability in study findings (89%), comprehensiveness of the search (78%), definition of eligibility criteria (72%), search approach (64%), reporting of extracted data for each study (59%), consideration and discussion of the limitations of the synthesis (56%), documentation of data extraction (54%) and regarding the statistical approach (52%). To enhance the quality of evidence synthesis in agri-food science, review authors should use tried-and-tested methodologies and publish peer-reviewed a priori protocols. Training in evidence synthesis methods should be scaled, with universities playing a crucial role. It is the shared duty of research authors, training providers, supervisors, reviewers, and editors to ensure that rigorous and robust evidence syntheses are made available to decision-makers. We argue that all these actors should be cognizant of these common mistakes to avoid publishing unreliable syntheses. Only by thinking as a community can we ensure that reliable evidence is provided to support appropriate decision-making in agri-food systems science.