© D. Mameri et al., Published by EDP Sciences 2025

1 Introduction

Rivers are among the most biodiverse ecosystems worldwide, harbouring one-quarter of all known vertebrate species (Dudgeon et al., 2006; Reid et al., 2019). Among vertebrates, fish are the most representative group, with nearly 17,800 species described so far, and a high proportion of endangered species (Collen et al., 2014; Tedesco et al., 2012). Particularly in Europe, over 500 native freshwater-dependent fish species have been reported to occur in rivers (Freyhof and Brooks, 2011), and currently, over a third of these taxa raise some level of conservation concern (IUCN, 2024).

The high degree of imperilment of European fish species is coupled with the current threats that freshwater ecosystems are facing, including the presence of barriers, water management, droughts, and the introduction and spread of alien species (Costa et al., 2021). To develop effective strategies for freshwater ecosystem management and fish conservation, the nested and hierarchical nature of rivers must be taken into consideration. As river basins function independently from each other, acting as “islands” for the biological instream communities they host, these can be regarded as the main units for freshwater conservation and management.

As fish are confined in river basins, it is fundamental to ensure that spatial data on species occurrence is correct. Imprecisions in spatial references may lead to an allocation of a species to a basin where it does not occur. Specifically in the case of species assessed by the IUCN, the distribution maps available for each species are often built based on convex hulls − the smallest convex set joining the occurrence data (Burgman and Fox, 2003). While this method fulfils the purpose of standardizing the resolution of the distribution maps for all species assessed by the IUCN, it may not reflect the real occurrences of freshwater fish.

Another issue related to spatial data on species occurrence is the taxonomic change that species undergo throughout time. A species that was recorded in a certain river basin may have had its scientific name changed, or it may have split into two species, and the previously recorded names are now misused (synonyms). If the link between the synonym and the current species name is not established, the time and spatial information may be lost. Hence, a correspondence between species synonyms and their current scientific name is essential to maximize data usage and adequately reflect species occurrence. FishBase, an online information system containing data on all described fish species and which feeds the fish data in Catalogue of Life (Bánki et al., 2024), presents a list of synonyms for each accepted scientific name (Froese and Pauly, 2024a). However, an association at the river basin level is required, as the geographical description for each species (e.g. “Adriatic basin”) does not allow a systematic allocation of each species to river basins.

Hence, the goal of the RivFISH database is to compile presence records, per river basin, of freshwater-dependent fish species, using all the recorded species names up to date, while also linking this information to data with conservation relevance, such as the IUCN Red List Categories. The RivFISH database is structured to account for updates, including the addition of new taxa (both synonyms and new species), but also new records of species occurrences in river basins.

2 Materials and methods

2.1 Data collection

Data was acquired for native freshwater-dependent fish species (resident and obligatory migrants) currently occurring in European river basins. The Ural and Caucasus Mountains were defined as the geographical boundaries for including river basins in Europe, plus Turkey (delimited on the south by the Orontes river basin), to account for diadromous species (that migrate between fresh waters and sea) that also occur in European river basins draining to the Mediterranean Sea, Black Sea and Caspian Sea.

The list of recorded species names associated with spatial data was elaborated by consulting existing data sources and literature, from a total of 68 references, including the IUCN Red List (IUCN, 2024) and the Freshwater Fish Ecology & Distribution (FFED) database (Tedesco et al., 2017). The majority of the presence records were obtained from the FFED database (38.0%), followed by the datasets compiled under the BioFresh project (Schmidt et al., 2019), published through the Global Information Biodiversity Platform (GBIF, 22.0%), scientific articles (13.0%), the IUCN Red List (11.1%), Kottelat and Freyhof's European Handbook of Freshwater Fish Species (9.8%), and other data sources including books, project reports and other datasets (6.1%).

2.2 Data validation and standardization

Following the inventory of fish presence per river basin, each species name was confronted with the accepted and synonym species names lists from FishBase, thus ensuring the correspondence of the recorded species name with spatial data and its current validated names. All species names were verified in October 2024 using the Checklist Bank portal, selecting the FishBase dataset (Froese and Pauly, 2024a). For presence records, data was retrieved from the sources listed in the Table “References” of the RivFISH database (Tab. 1).

The bibliographic reference used to confirm the presence of a species in each river basin was also included in the database, in the table “Species_basins” (Tab. 1). Spatial data for native fish species presence available at both the IUCN Red List and FFED is based on the watershed boundaries represented in HydroBASINS, derived from the HydroSHEDS database, at a 15-second resolution (Lehner & Grill, 2013). While the data retrieved from FFED comes in a tabular format (csv files) with the name of the main river basins in HydroBASINS, species occurrence in the IUCN may be provided through polygon layers based on the convex hull of HydroSHEDS level 8 units, whenever fish distribution cannot be allocated to the individual HydroSHEDS units. This may result in overestimating species presence in river basins if the spatial data is not previously processed. Hence, spatial data retrieved from the IUCN Red List was intersected with a vectorized river basins layer, and the presence of each species per basin was verified in the literature.

The spatial reference for the sea outlet river basins was taken from the Catchment Characterisation and Modelling (CCM2) − River and Catchment Database v2.1 (de Jager and Vogt, 2007). Overall, the CCM2 layer of river basins (where each basin has a unique ID − “WSO_ID”) presents a better adjustment to European basins and enables interoperability with other datasets requiring river representations at finer scales (e.g., river instream barriers). It should be noted that, for the RivFISH database, only CCM2 river basins with maximum Strahler stream order above 2 were considered (representing 95.8% of the study area), as these have been identified as thresholds for freshwater biodiversity (Vorste et al., 2017).

The RivFISH database seeks to increase interoperability with reference datasets, by adopting their persistent identifiers. This is possible for basin data (CCM2 and HydroSHEDS), and for the IUCN status, but not for FishBase, as this database actively decided to not adopt persistent identifiers (Froese and Pauly 2024b). To ensure interoperability with the retrieved data on species presence from the IUCN Red List and FFED, an association between the two catchment datasets was established. Each HydroSHEDS level 8 unit (for the spatial data retrieved in the IUCN Red List) corresponds to a sub-basin linked to a main river basin with a unique identifier, which was used to establish an association with the CCM river basins. Complementarily, the similarity of the main basin name (available in FFED) in both catchment models was used to match the basins. Finally, a spatial overlap between the CCM and HydroSHEDS basins was performed to link the remaining basins and validate species presence. This match allowed correcting species presence, by excluding polygons in vector layers that fell into adjacent river basins due to the changes in spatial resolution, and that are not supported by consulted datasets and literature (table “References”, see Tab. 1). All spatial analyses were conducted in ArcGIS Pro (version 3.2.2), using the coordinate reference system ETRS89-extended/LAEA Europe (EPSG: 3035).

2.3 Data structure and fields

The RivFISH database is organized into six tables, reflecting the taxonomic, spatial and conservation status data on all native freshwater-dependent fish species occurring in Europe, including Turkey. The database architecture implemented a normalized relational model, implemented in SQL. A short description of each table is presented in Table 1. A complete metadata file, following the DarwinCore biodiversity standard and including each field's description, is also provided in the Supplementary Information. These tables are linked through primary and foreign keys, based on unique identifiers (IDs), including an ID for each recorded species name (“TaxonID”), current accepted scientific name (“accepted_name_ID”), and CCM basin ID (“WSO_ID”), as depicted in Figure 1.

The interoperability to other databases is ensured by the fields and links listed in Table 2.

For user convenience, a denormalised flat table named “RivFISH_denormalised” was also included, containing all fields of the related tables.

Fig. 1 Entity-relationship diagram for the RivFISH database. Each table contains one primary key (PK), with unique values that may link to other tables through a foreign key (FK). RivFISH includes a total of six tables, covering species' taxonomy (“Current_species”, “Species_names”), spatial data (“CCM_sea_outlets” and “Species_basins”, with the last associated to the references from the literature) and IUCN information (“IUCN_assessments”).

3 Using the database

A total of 707 recorded taxa names, including 667 currently accepted scientific names, were included in the RivFISH database for Europe, including Turkey. All 667 species have spatial data associated with the CCM2 river basin resolution (1554 basins with maximum Strahler above 2, covering 95.8% of the total drainage area within the study area covered by RivFISH).

Regarding the conservation status in the IUCN, 633 freshwater-dependent fish species have a risk category assigned (94.9% of the currently accepted species included in RivFISH). Figure 2 provides a usage example that allows visualizing freshwater-dependent fish species richness per basin across Europe and where communities are most threatened, according to the IUCN. Southern Europe, including the Iberian, Adriatic and Balkan peninsulas, as well as southern European Turkey, stand out as the areas where there is a higher proportion of endangered species, given the higher levels of threatedness and lower species richness (Fig. 2).

Figure 3 shows another usage example of the database, displaying a positive association between species richness and basin area (R² = 0.542). Scale dependence and positive species-area relationship (SAR) is a well-known pattern in ecology (Lomolino, 2001), which also applies to stream fishes (Angermeier and Schlosser, 1989; Oberdorff et al., 2011). It should be noted, however, that the SAR may be diluted due to their environmental condition, such as habitat complexity and environmental variation (Oberdorff et al., 2011).

The Danube River basin (basin area of 800,000 km², the uppermost point of Fig. 3), for instance, presents a high heterogeneity across its sub-basins, with a total of 122 freshwater fish-dependent species, including several endemic species, thus standing out from the SAR pattern evidenced in Figure 3. The delimitation of the Danube drainage in the CCM2 layer also incorporates karstic (sinking) freshwater systems, including the Jadova and Lika rivers in the Western Balkans, where endemic species such as Cobitis jadovensis occur (Mustafic et al., 2008), contributing to the high biodiversity found in the Danube. Contrastingly, the biggest river basin (1,400,000 km²) in Europe, the Volga (the rightmost point of Fig. 3), harbours 79 freshwater-dependent fish species.

Fig. 2 Map representing species richness versus the ratio of threatened species (listed as “Vulnerable”, “Endangered” or “Critically Endangered”) per river basin, considering the risk category in the IUCN (International Union for Conservation of Nature) Red List. The map was produced in ArcGIS Pro (version 3.2.2) with the European sea outlet basins layer from the Catchment Characterisation and Modelling 2 (CCM2) dataset (de Jager and Vogt, 2007). All basins with a maximum Strahler above 2 and harbouring more than 2 native species were considered for this analysis, including 756 river basins, representing 90.9% of RivFISH study area.

Fig. 3 Species-area relationship (SAR), based on the log-transformed basin area. A multi-model inference approach was followed to determine a multi-model averaged curve with the best fit to the data (green curve, R2 = 0.542). Grey boundaries represent the bootstrap 95% confidence interval of the multi-model averaged curve. The SAR plot was produced in R, version 4.1.0 (R Core Team, 2021), using the “sars” package, version 1.3.6 (Matthews, Triantis, Whittaker, and Guilhaumon, 2019). All basins with a maximum Strahler above 2 were considered for this analysis, including 1554 river basins, representing 95.8% of RivFISH study area.

4 Discussion

The RivFISH database aggregates the available data on freshwater-dependent fish presence in Europe, validated at the river basin level and considering taxonomical synonyms for species names. This allows for a maximization of data usage and robustness. Having a correct species presence per basin enables an accurate starting point for proper management and conservation actions to be planned at a finer scale, namely at the sub-basin and river segment scale. It is, as far as the authors know, the most up-to-date and comprehensive database on the presence of freshwater-dependent fish species in European river basins, with the inclusion of 1554 river basins and 667 freshwater-dependent fish species. This represents an increase of over 120 species described in Europe since the publication of the Handbook of European Freshwater Fishes, which reported a total of 546 species by 2011 (Freyhof & Brooks, 2011).

RivFISH can be further used to investigate species occurrence, fish biodiversity and community vulnerability at the European extent, by crossing the taxonomic and spatial layers of information with other available datasets, such as climate data and anthropogenic pressures. The structure of the database is also prepared to deal with future alterations in species taxonomy, as well as new records of species occurrence in river basins, including recently described species (2023 and 2024) that are yet to be included and validated in both FishBase and the Catalogue of Life (e.g. (Doadrio, Sousa-Santos, Robalo, & Perea, 2024).

Acknowledgments

The authors would like to thank Iro Sipsa, Miguel Silva and Juliana Sêco for their contribution to data collection. This study was funded by the project “Dammed Fish − Impact of structural and functional river network connectivity losses on fish biodiversity − Optimizing management solutions” (PTDC/CTA-AMB/4086/2021, DOI: 10.54499/PTDC/CTA-AMB/4086/2021), from Fundação para a Ciência e Tecnologia, I.P. (FCT). DM and GD have been financed by FCT within the Dammed Fish project. PB was financed by national funds via FCT (LA/P/0092/2020). Forest Research Centre (CEF) is a research unit funded by FCT through project reference UID/00239: Centro de Estudos Florestais, DOI 10.54499/UIDB/00239/2020. The Associate Laboratory TERRA (LA/P/0092/2020, DOI: 10.54499/LA/P/0092/2020) is also funded by FCT.

Data availability statement

The RivFISH database (version 1.2) is published in tabular format (csv files) in the public repository Zenodo (https://doi.org/10.5281/zenodo.13848976), with the corresponding metadata, according to the EML 2.1.1 standard, in xml format. A shapefile containing the data on the presence of fish species included in the database (‘rivfish_shapefile’) is also made available. All files are compressed in a single zipped folder.

Supplementary Material

The Supplementary Material is available at https://www.kmae-journal.org/10.1051/kmae/2025002/olm. Access here

References

All Tables

All Figures

Fig. 1 Entity-relationship diagram for the RivFISH database. Each table contains one primary key (PK), with unique values that may link to other tables through a foreign key (FK). RivFISH includes a total of six tables, covering species' taxonomy (“Current_species”, “Species_names”), spatial data (“CCM_sea_outlets” and “Species_basins”, with the last associated to the references from the literature) and IUCN information (“IUCN_assessments”).

In the text

Fig. 2 Map representing species richness versus the ratio of threatened species (listed as “Vulnerable”, “Endangered” or “Critically Endangered”) per river basin, considering the risk category in the IUCN (International Union for Conservation of Nature) Red List. The map was produced in ArcGIS Pro (version 3.2.2) with the European sea outlet basins layer from the Catchment Characterisation and Modelling 2 (CCM2) dataset (de Jager and Vogt, 2007). All basins with a maximum Strahler above 2 and harbouring more than 2 native species were considered for this analysis, including 756 river basins, representing 90.9% of RivFISH study area.

In the text

Fig. 3 Species-area relationship (SAR), based on the log-transformed basin area. A multi-model inference approach was followed to determine a multi-model averaged curve with the best fit to the data (green curve, R2 = 0.542). Grey boundaries represent the bootstrap 95% confidence interval of the multi-model averaged curve. The SAR plot was produced in R, version 4.1.0 (R Core Team, 2021), using the “sars” package, version 1.3.6 (Matthews, Triantis, Whittaker, and Guilhaumon, 2019). All basins with a maximum Strahler above 2 were considered for this analysis, including 1554 river basins, representing 95.8% of RivFISH study area.

In the text