Biology subjects

Cancellario, T.

Publications and source records attributed to Cancellario, T..

5 recordsLinked to original sources

bioRxiv2026

BiOS: An Open-Source Framework for the Integration of Heterogeneous Biodiversity Data

The era of Big Data has reshaped biodiversity research, yet the potential of this information is frequently constrained by data heterogeneity, incompatible schemas, and the fragmentation of resources. Whilst standards such as Darwin Core have improved interoperability, significant barriers persist in harmonising multi-typology datasets ranging from taxonomy and genetics to species distribution. Here, we present the Biodiversity Observatory System (BiOS), a comprehensive, open-source software stack designed to address these impediments through a modular, community-driven architecture. BiOS departs from monolithic database designs by decoupling the back-end data management from the front-end presentation layer. This architectural separation supports a dual-access model tailored to diverse stakeholder needs. For researchers and developers, the system offers a comprehensive Application Programming Interface (API) that exposes all back-end functionalities, enabling seamless programmatic access, automated data retrieval, and integration with external analytical workflows. Simultaneously, the platform features a user web interface designed to lower the technical barrier to entry. This interface facilitates intuitive data exploration through agile taxonomic navigation, advanced geospatial map viewers for species occurrence filtering, and dedicated dashboards for visualising genetic markers and legislative status. Strictly adhering to the FAIR principles (Findable, Accessible, Interoperable, Reusable), BiOS acts as a relational engine capable of integrating heterogeneous data streams. By providing a flexible, interoperable core that supports the "seven shortfalls" framework of biodiversity knowledge, BiOS offers a turnkey solution to overcome data fragmentation and enhance collaborative conservation efforts.

bioinformatics↗

bioRxiv2025

Specifind: A Natural Language Processing Tool for Automating Species Occurrence (Re-)Discovery from Scientific Literature

A vast amount of valuable information on species occurrences remains embedded within the unstructured and continuously expanding body of ecological literature written in natural language. When effectively extracted, such dispersed knowledge has the potential to significantly improve understanding of species distributions and ecological patterns, thereby enabling more targeted and informed conservation actions. To address this challenge, Specifind is introduced as a tool designed to facilitate the extraction of species occurrence data through the identification of scientific species names, geographic references, and the relationships between them while ensuring traceability. At its core lies a newly developed and expertly annotated dataset comprising over one thousand open-access abstracts drawn from five domains: biogeography, botany, entomology, mycology, and zoology. A suite of Natural Language Processing components has been integrated, including Document Layout Analysis, Optical Character Recognition, Named Entity Recognition, Coreference Resolution, and Relation Extraction. These components enable the accurate identification and contextual linking of species and geographic entities, even when references are distributed throughout the text. As a result, Specifind enhances the discoverability and usability of species occurrence information embedded within unstructured scientific texts. It is expected to reduce the substantial effort required for manual literature review, thereby supporting biodiversity research, informing conservation planning, and facilitating ecological analysis.

bioinformatics↗

bioRxiv2025

biodumpy: A Comprehensive Biological Data Downloader

In recent years, the expansion of public biodiversity platforms and associated datasets has greatly improved access to ecological and biological information. These resources now cover vast geographic areas, extended temporal scales, and diverse taxonomic groups, becoming essential for ecological studies by enabling more comprehensive analyses and novel hypotheses testing. Concurrently, the development of programming packages has facilitated data access and interaction, streamlining their retrieval processes. However, most existing tools are limited to specific databases, posing challenges for studies requiring seamless integration of data from multiple sources. The growing availability of biodiversity data highlights the urgent need for robust tools to efficiently process, analyse, and interpret ecological and biological information. To address this limitation, we introduce biodumpy, a new Python package developed for the retrieval, management, and integration of biological data from various public databases. biodumpy provides access to up-to-date and comprehensive datasets spanning genetic, distributional, taxonomic, and bibliographic sources. It includes specialized modules for efficient data retrieval across taxonomic lists, with the capability to process multiple modules simultaneously. By integrating diverse data sources, biodumpy enhances data acquisition, providing researchers with a powerful framework for comprehensive analyses and supporting ecological research to tackle complex environmental challenges.

ecology↗

bioRxiv2023

Drivers of species knowledge across the Tree of Life

Knowledge of biodiversity is unevenly distributed across the Tree of Life. In the long run, such disparity in awareness unbalances our understanding of life on Earth, influencing policy decisions and the allocation of research and conservation funding. We investigated how humans accumulate knowledge of biodiversity by searching for consistent relationships between scientific (number of publications) and societal (number of views in Wikipedia) interest, and species-level morphological, ecological and socio-cultural factors. Across a random selection of 3,019 species spanning 29 Phyla/Divisions, we show that socio-cultural factors are the most important correlates of scientific and societal interest in biodiversity, including the fact that a species is useful or harmful to humans, has a common name and is listed in the IUCN Red List. Furthermore, large-bodied, broadly distributed and taxonomically unique species receive more scientific and societal attention, whereas colorfulness and phylogenetic proximity to humans correlates exclusively with societal attention. These results highlight a favoritism towards limited branches of the Tree of Life, and that scientific and societal priorities in biodiversity research broadly align. This suggests that we may be missing out on key species in our research and conservation agenda simply because they are not on our cultural radar.

ecology↗

bioRxiv2022

Climate change will redefine taxonomic, functional, and phylogenetic diversity patterns of Odonata in space and time

Climate change is rearranging the mosaic of biodiversity on our planet. These broad-scale species re-distributions will affect the structure of communities across multiple biodiversity facets (taxonomic, phylogenetic, and functional diversity). The current challenges to understand such effects involve focusing on organisms other than vertebrates and considering the signature of species redistribution on phylogenetic and functional diversity in addition to species composition. Using European dragonflies and damselflies (Odonata), we asked: i) how climate change will redefine taxonomic, phylogenetic, and functional diversity at continental scales; ii) which traits will mediate species response to global change; and iii) whether this response will be conserved across the phylogeny. First, we constructed stacked species distribution models for 107 species of Odonata under current and future climate conditions. Then, we quantified the temporal variation of taxonomic, functional and phylogenetic components, forecasting alpha and beta diversity changes through our geographical grid. Lastly, we used phylogenetic comparative models to test the influence of phylogeny and traits on range shifts. We observed broad latitudinal and altitudinal rearrangements in community composition driven by climate change. Given the high dispersal ability of Odonata, changes are predicted to be rapid, especially in areas experiencing faster climate change rates. According to our predictions, changes in species composition cascade to affect functional and phylogenetic diversity, determining broad turnovers in traits and evolutionary lineages. There was no clear phylogenetic signal in the range-shift response of European Odonata to climate change. According to our phylogenetic regression models, only body size and flight period can be partly correlated with observed range shifts. By considering all three primary facets of biodiversity, our results support the design of inclusive management and conservation strategies, accounting not only for the diversity of species, but also the services they provide and the phylogenetic heritage they carry in a targeted ecosystem.

ecology↗