Prioritizing conservation and monitoring areas in the Danube River basin: Insights from the DANUBE4all project

The Danube River basin currently lacks a comprehensive action plan for restoring its freshwater and transitional water ecosystems, despite some efforts to address continuum disruptions in upstream regions. The DANUBE4all project aims to address these challenges by identifying, selecting, and recommending implementation measures to increase the extent of free-flowing rivers throughout the entire basin. One of the specific objectives of the project involves identifying suitable habitats for both protected and invasive species, prioritizing conservation actions. To accomplish this, we initially modeled the habitat suitability of the fish species that inhabit the Danube basin. Fishes were chosen because they are good indicators for longitudinal connectivity. This modeling process involved spatially explicit species distribution models, which were trained using environmental data and information on species occurrences. Following the habitat suitability modeling, we conducted a spatial conservation planning analysis. This analysis aimed to pinpoint regions across the Danube River basin that are of high priority for future conservation and monitoring efforts. Priority areas were identified based on the presence of suitable habitats for fish species and the facilitation of longitudinal connectivity within the river system

hydrographr: An R package for scalable hydrographic data processing

1. Freshwater ecosystems are considered biodiversity hotspots, but assessing the spatial distribution of species remains challenging. One major obstacle lies in the complex geospatial processing of large amounts of data, such as stream network, sub-catchment and basin data, that are necessary for addressing the longitudinal connectivity among water bodies. Workflows thus need to be scalable, especially when working across large spatial extents and at high spatial resolution. This in turn requires advanced command-line GIS skills and programming language integration, which often poses a challenge for freshwater researchers. 2. To address this challenge, we developed the package hydrographr that provides scalable hydrographic data processing in R. The package contains functions for downloading data of the high-resolution Hydrography90m dataset, processing, reading and extracting information, as well as assessing network distances and connectivity. While the functions are, by default, tailored toward the Hydrography90m data, they can also be generalised toward other data and purposes, such as efficient cropping and merging of raster and vector data, point-raster extraction, raster reclassification and data aggregation. The package depends on the open-source software GDAL/OGR, GRASS-GIS and the AWK programming language in the Linux environment, allowing a seamless language integration. Since the data is processed outside R, hydrographr allows creating scalable geo-processing workflows. 3. We illustrate the hydrographr functions using two workflows that focus on (i) a freshwater species distribution modelling approach, and (ii) assessing stream connectivity given the fragmentation by dams. We also provide a detailed guide for the initial installation of the required software. Windows users need to first enable the Windows Subsystem for Linux (WSL) feature, and can then follow the same software installation as Linux users. hydrographr is maintained on GitHub at https://github.com/glowabio/hydrographr. 4. hydrographr provides a set of key functions for processing freshwater geospatial data. We expect that the package will support the freshwater-related research communities given the easy-to-use wrapper functions that allow capitalizing on powerful open-source command-line software, which may otherwise require a steep learning curve. Users can thus perform large-scale freshwater-specific longitudinal connectivity and network analyses across large geographic extents while staying within the R environment

GeoFRESH – an online platform for freshwater geospatial data processing

Freshwater ecosystems are characterized by their unique longitudinal and lateral habitat connectivity. As a result, spatial units in freshwater-specific analyses can often not be considered independent of each other. Accounting for this connectivity in modelling analyses requires advanced skills in Geographic Information Systems (GIS) for adequately processing and managing the data. To address this challenge, we developed the GeoFRESH online platform, which is available at https://geofresh.org. The platform provides a graphical, easy-to-use interface to create freshwater-specific analysis-ready data for any given location in the world, based on a high-resolution stream network (https://hydrography.org/hydrography90m/hydrography90m_layers). Users can (i) upload and visualize point coordinates, (ii) automatically assign points to the closest stream network segment, (iii) annotate the point data with a suite of 104 local and/or upstream-aggregated topographic, climatic, land-cover and soil variables, (iv) visualize summary plots, and (v) download the data in csv-format for further analyses. The platform can be expanded given its modular structure and it can serve as a key element to support freshwater science and management relying on high-resolution geospatial analyses. GeoFRESH provides a low-entry interface while being complementary to the hydrographr R-package, and contributes importantly to the re-usability of data as an important aspect of the FAIR principles

Dataset of freshwater macroinvertebrates of Cuba downloaded from GBIF

Dataset of freshwater macroinvertebrates of Cuba dowloaded from GBIF and modified. Cross-checked the georeference using the standard web client of the GEOLocate software (https://www.geo-locate.org/web/WebGeoref.aspx) and corrected when required. Coordinates were assigned when missing.  We checked the municipality and province names and updated these according to the last political-administrative organization of Cuba in 2011.</p

Hypolestes hatuey sp. nov.: a new species of the enigmatic genus Hypolestes (Odonata, Hypolestidae) from Hispaniola

Torres-Cambas, Yusdiel, Lorenzo-Carballa, M. Olalla, Ferreira, Sónia, Cordero-Rivera, Adolfo (2015): Hypolestes hatuey sp. nov.: a new species of the enigmatic genus Hypolestes (Odonata, Hypolestidae) from Hispaniola. Zootaxa 4000 (2): 207-226, DOI: 10.11646/zootaxa.4000.2.

An update on the distribution of threatened odonate species from the Greater Antilles

<div><p>The Antilles harbour several island endemic odonate species, including some palaeoendemics, within a relatively small and anthropized area. Such attributes give this archipelago a special significance for the conservation of Odonata in the Neotropics. However, despite the importance of these islands, inadequately surveyed regions persist, mainly in the Greater Antilles, and there is not enough information to set IUCN threat categories for eight species supposed to be at risk, which are currently classified as data deficient (DD). To update the distribution of endangered (EN), vulnerable (VU) and DD species, we conducted a series of field surveys in Dominican Republic, Jamaica and Cuba, and compiled data from literature, museum collections as well as personal communications. We sampled a total of 37 species, including <i>Microneura caligata, Phylolestes ethelae</i> and <i>Hypolestes clara</i> (EN); <i>H. trinitatis</i> (VU); and <i>Diceratobasis macrogaster, Neoneura maria</i> and <i>Protoneura capillaris</i> (DD). We provide new locality records for <i>M. caligata, N. carnatica</i> (DD), <i>N. maria</i> (DD), <i>P. capillaris, H. clara, H. trinitatis</i> and <i>Erythrodiplax bromeliicola</i> (DD). According to our results, we suggest changing the category of <i>D. macrogaster, D. melanogaster, N. carnatica, N. maria</i> and <i>P. capillaris</i> to VU.</p></div

hydrographr: An R package for scalable hydrographic data processing

Abstract Freshwater ecosystems are considered biodiversity hotspots, but assessing the spatial distribution of species remains challenging. One major obstacle lies in the complex geospatial processing of large amounts of data, such as stream network, sub‐catchment and basin data, that are necessary for addressing the longitudinal connectivity among water bodies. Workflows thus need to be scalable, especially when working across large spatial extents and at high spatial resolution. This in turn requires advanced command‐line GIS skills and programming language integration, which often poses a challenge for freshwater researchers. To address this challenge, we developed the package hydrographr that provides scalable hydrographic data processing in R. The package contains functions for downloading data of the high‐resolution Hydrography90m dataset, processing, reading and extracting information, as well as assessing network distances and connectivity. While the functions are, by default, tailored toward the Hydrography90m data, they can also be generalised toward other data and purposes, such as efficient cropping and merging of raster and vector data, point‐raster extraction, raster reclassification and data aggregation. The package depends on the open‐source software GDAL/OGR, GRASS‐GIS and the AWK programming language in the Linux environment, allowing a seamless language integration. Since the data is processed outside R, hydrographr allows creating scalable geo‐processing workflows. We illustrate the hydrographr functions using two workflows that focus on (i) a freshwater species distribution modelling approach, and (ii) assessing stream connectivity given the fragmentation by dams. We also provide a detailed guide for the initial installation of the required software. Windows users need to first enable the Windows Subsystem for Linux (WSL) feature, and can then follow the same software installation as Linux users. hydrographr is maintained on GitHub at https://github.com/glowabio/hydrographr. hydrographr provides a set of key functions for processing freshwater geospatial data. We expect that the package will support the freshwater‐related research communities given the easy‐to‐use wrapper functions that allow capitalizing on powerful open‐source command‐line software, which may otherwise require a steep learning curve. Users can thus perform large‐scale freshwater‐specific longitudinal connectivity and network analyses across large geographic extents while staying within the R environment

GeoFRESH – an online platform for freshwater geospatial data processing

Freshwater ecosystems are characterized by their unique longitudinal and lateral habitat connectivity. As a result, spatial units in freshwater-specific analyses can often not be considered independent of each other. Accounting for this connectivity in modelling analyses requires advanced skills in Geographic Information Systems (GIS) for adequately processing and managing the data. To address this challenge, we developed the GeoFRESH online platform, which is available at https://geofresh.org. The platform provides a graphical, easy-to-use interface to create freshwater-specific analysis-ready data for any given location in the world, based on a high-resolution stream network (https://hydrography.org/hydrography90m/hydrography90m_layers). Users can (i) upload and visualize point coordinates, (ii) automatically assign points to the closest stream network segment, (iii) annotate the point data with a suite of 104 local and/or upstream-aggregated topographic, climatic, land-cover and soil variables, (iv) visualize summary plots, and (v) download the data in csv-format for further analyses. The platform can be expanded given its modular structure and it can serve as a key element to support freshwater science and management relying on high-resolution geospatial analyses. GeoFRESH provides a low-entry interface while being complementary to the hydrographr R-package, and contributes importantly to the re-usability of data as an important aspect of the FAIR principles

The global EPTO database : Worldwide occurrences of aquatic insects

Motivation: Aquatic insects comprise 64% of freshwater animal diversity and are widely used as bioindicators to assess water quality impairment and freshwater ecosystem health, as well as to test ecological hypotheses. Despite their importance, a comprehensive, global database of aquatic insect occurrences for mapping freshwater biodiversity in macroecological studies and applied freshwater research is missing. We aim to fill this gap and present the Global EPTO Database, which includes worldwide geo-referenced aquatic insect occurrence records for four major taxa groups: Ephemeroptera, Plecoptera, Trichoptera and Odonata (EPTO).Main type of variables contained: A total of 8,368,467 occurrence records globally, of which 8,319,689 (99%) are publicly available. The records are attributed to the corresponding drainage basin and sub-catchment based on the Hydrography90m dataset and are accompanied by the elevation value, the freshwater ecoregion and the protection status of their location.Spatial location and grain: The database covers the global extent, with 86% of the observation records having coordinates with at least four decimal digits (11.1 m precision at the equator) in the World Geodetic System 1984 (WGS84) coordinate reference system.Time period and grain: Sampling years span from 1951 to 2021. Ninety-nine percent of the records have information on the year of the observation, 95% on the year and month, while 94% have a complete date. In the case of seven sub-datasets, exact dates can be retrieved upon communication with the data contributors.Major taxa and level of measurement: Ephemeroptera, Plecoptera, Trichoptera and Odonata, standardized at the genus taxonomic level. We provide species names for 7,727,980 (93%) records without further taxonomic verification.Software format: The entire tab-separated value (.csv) database can be downloaded and visualized at . Fifty individual datasets are also available at , while six datasets have restricted access. For the latter, we share metadata and the contact details of the authors.Peer reviewe

The global EPTO database:worldwide occurrences of aquatic insects

Abstract Motivation: Aquatic insects comprise 64% of freshwater animal diversity and are widely used as bioindicators to assess water quality impairment and freshwater ecosystem health, as well as to test ecological hypotheses. Despite their importance, a comprehensive, global database of aquatic insect occurrences for mapping freshwater biodiversity in macroecological studies and applied freshwater research is missing. We aim to fill this gap and present the Global EPTO Database, which includes worldwide geo-referenced aquatic insect occurrence records for four major taxa groups: Ephemeroptera, Plecoptera, Trichoptera and Odonata (EPTO). Main type of variables contained: A total of 8,368,467 occurrence records globally, of which 8,319,689 (99%) are publicly available. The records are attributed to the corresponding drainage basin and sub-catchment based on the Hydrography90m dataset and are accompanied by the elevation value, the freshwater ecoregion and the protection status of their location. Spatial location and grain: The database covers the global extent, with 86% of the observation records having coordinates with at least four decimal digits (11.1 m precision at the equator) in the World Geodetic System 1984 (WGS84) coordinate reference system. Time period and grain: Sampling years span from 1951 to 2021. Ninety-nine percent of the records have information on the year of the observation, 95% on the year and month, while 94% have a complete date. In the case of seven sub-datasets, exact dates can be retrieved upon communication with the data contributors. Major taxa and level of measurement: Ephemeroptera, Plecoptera, Trichoptera and Odonata, standardized at the genus taxonomic level. We provide species names for 7,727,980 (93%) records without further taxonomic verification. Software format: The entire tab-separated value (.csv) database can be downloaded and visualized at https://glowabio.org/project/epto_database/. Fifty individual datasets are also available at https://fred.igb-berlin.de, while six datasets have restricted access. For the latter, we share metadata and the contact details of the authors