Tag: species description

Two New Caddisfly Species Discovered from the Middle East and Caucasus

Two new caddisfly species have been described from Middle East and Caucasus ecoregions.

The newly described aquatic insects, belonging to the genus Hydropsyche, help close substantial knowledge gaps regarding the biodiversity of Azerbaijan, Iran, and Türkiye. Caddisflies (order Trichoptera) are vital components of freshwater ecosystems, and the Hydropsyche genus is among the most diverse and ecologically important, comprising more than 8% of all Trichoptera species recorded in the Western Palaearctic region.

The Two New Caddisfly Species

  • Caddisfly Hydropsyche fitesa
    Hydropsyche fitesa, credit to Dr. Halil Ibrahimi
  • caddisfly Hydropsyche hindrajab
    Hydropsyche hindrajab, credit to Dr. Halil Ibrahimi

Both new species were found in habitats characterized by stone, pebble, and fine sediments with sparse riparian vegetation. Hydropsyche fitesa was discovered in Iran, specifically near the Shalmash Waterfalls on the Chamyaman River, a tributary originating in the Zagros Mountains; the epithet fitesa honors the first author’s wife, in recognition of her lifelong support of caddisfly research. Hydropsyche hindrajab was found across multiple river localities in Azerbaijan, Iran, and Türkiye, and was named in honor of Hind Rajab, a five-year-old girl whose life was lost amid the Israeli-Palestinian conflict. 

The full species descriptions are available in the open-access Biodiversity Data Journal.

An Integrative Approach to Discovery

Authored by Halil Ibrahimi (University of Prishtina, Kosovo) and Dora Hlebec (University of Zagreb, Croatia), the study highlights the challenges of identifying morphologically similar species. Because both new insects belong to the Hydropsyche guttata species cluster, a group whose members look strikingly alike, the team employed an integrative taxonomic approach.

By combining traditional morphological examination with advanced DNA analysis (specifically, sequencing of the mitochondrial cytochrome c oxidase subunit I, or COI gene), the researchers confirmed that H. hindrajab represents a distinct evolutionary lineage. H. fitesa was distinguished based on unique morphological differences in its physical structure compared to its closest relatives.

Future Explorations

map of caddislies distribution

Distribution of Hydropsyche hindrajab sp. nov. (red squares), Hydropsyche fitesa sp. nov. (green square), Hydropsyche sciligra (yellow squares) and Hydropsyche tigrata (green squares), based on data used for the current study. Credit to Ibrahimi and Hlebec, 2026.

The discovery underscores how much of the region’s aquatic life remains undocumented. The authors note that the type localities in West Azerbaijan Province, Iran, are known for harboring rare aquatic insects, and they believe the area likely holds additional undescribed species yet to be found. Currently, 23 Hydropsyche species are known in Iran, 67 in Türkiye, and 12 in Azerbaijan, but the potential for new discoveries remains high.

Original study:

Ibrahimi H, Hlebec D (2026) Two new species of the genus Hydropsyche Pictet, 1834 (Trichoptera, Hydropsychidae) from the Middle East and Caucasus ecoregions. Biodiversity Data Journal 14: e191076. https://doi.org/10.3897/BDJ.14.e191076

Brand new computer language describes organismal traits to create computable species descriptions

Describing traits with Phenoscript is like programming a computer code for how an organism looks.

The beetle species Grebennikovius basilewskyi. Numbers next to arrows indicate patterns of phenotype statements explained in the section “Phenoscript: main patterns of phenotype statements”. Arrow numbers from T1 to T5 illustrate individual body parts. See more in the research study.

One of the most beautiful aspects of Nature is the endless variety of shapes, colours and behaviours exhibited by organisms. These traits help organisms survive and find mates, like how a male peacock’s colourful tail attracts females or his wings allow him to fly away from danger. Understanding traits is crucial for biologists, who study them to learn how organisms evolve and adapt to different environments.

To do this, scientists first need to describe these traits in words, like saying a peacock’s tail is “vibrant, iridescent, and ornate”. This approach works for small studies, but when looking at hundreds or even millions of different animals or plants, it’s impossible for the human brain to keep track of everything.

Computers could help, but not even the latest AI technology is able to grasp human language to the extent needed by biologists. This hampers research significantly because, although scientists can handle large volumes of DNA data, linking this information to physical traits is still very difficult.

To solve this problem, researchers from the Finnish Museum of Natural History, Giulio Montanaro and Sergei Tarasov, along with collaborators, have created a special language called Phenoscript. This language is designed to describe traits in a way that both humans and computers can understand. Describing traits with Phenoscript is like programming a computer code for how an organism looks.

Phenoscript uses something called semantic technology, which helps computers understand the meaning behind words, much like how modern search engines know the difference between the fruit “apple” and the tech company “Apple” based on the context of your search.

“This language is still being tested, but it shows a lot of promise. As more scientists start using Phenoscript, it will revolutionise biology by making vast amounts of trait data available for large-scale studies, boosting the emerging field of phenomics,”

explains Montanaro.

In their research article, newly published in the open-access, peer-reviewed Biodiversity Data Journal, the researchers make use of the new language for the first time, as they create semantic phenotypes for four species of dung beetles from the genus Grebennikovius. Then, to demonstrate the power of the semantic approach, they apply simple semantic queries to the generated phenotypic descriptions. 

Finally, the team takes a look yet further ahead into modernising the way scientists work with species information. Their next aim is to integrate semantic species descriptions with the concept of nanopublications, “which encapsulates discrete pieces of information into a comprehensive knowledge graph”. As a result, data that has become part of this graph can be queried directly, thereby ensuring that it remains Findable, Accessible, Interoperable and Reusable (FAIR) through a variety of semantic resources.

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Research paper:

Montanaro G, Balhoff JP, Girón JC, Söderholm M, Tarasov S (2024) Computable species descriptions and nanopublications: applying ontology-based technologies to dung beetles (Coleoptera, Scarabaeinae). Biodiversity Data Journal 12: e121562. https://doi.org/10.3897/BDJ.12.e121562

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The hereby study is the latest addition to the special topical collection: “Linking FAIR biodiversity data through publications: The BiCIKL approach”, launched and supported by the recently concluded Horizon 2020 project: Biodiversity Community Integrated Knowledge Library (BiCIKL). The collection aims to bring together scientific publications that demonstrate the advantages and novel approaches in accessing and (re-)using linked biodiversity data.

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What expert recommendations did the BiCIKL consortium give to policy makers and research funders to ensure that biodiversity data is FAIR, linked, open and, indeed, future-proof? Find out in the blog post summarising key lessons learnt from the Horizon 2020 project.

How to ensure biodiversity data are FAIR, linked, open and future-proof?

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