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Collectomics in plant biodiversity research - looking into the past to understand the present and shape the future
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Abstract
Global biodiversity is changing at unprecedented rates during the Anthropocene. Whereas current biodiversity patterns can be observed directly, information from the recent past is far less easily retrieved yet urgently needed to understand present observations and predict future developments. For plants, herbaria offer such a unique glimpse into the past. Evaluation of plant specimens allows determining a wide range of attributes like species identity, morphological and phenological traits and even signs of biotic interactions. Specimen’s labels convey data such as species identity (and identification history), date and locality of collection, as well as the surrounding biotic and abiotic environment. Current methodological developments in sensor technology and computer vision increasingly enable us to extract this information in a high throughput and automated way. Equally vast developments in data science allow to integrate data from other sources for much more comprehensive analyses than before. With millions of specimens already digitized and digitization schemes running in many institutions, we will be increasingly able to determine characteristics of species and link them via distribution records to large-scale climate change scenarios. This allows us to better predict species’ threat levels, and to develop scenarios on the consequences of biodiversity change for ecosystem functioning. The present contribution reviews recent herbaria research and describes potential avenues with respect to Museomics and the Extended Specimen concept, and we propose Collectomics as a new framework to unravel, understand, and cope with the Anthropocene biodiversity change.
DOI
https://doi.org/10.32942/X21S8W
Subjects
Life Sciences
Keywords
Anthropocene Biodiversity loss; Computer vision: Herbaria; Extended Specimen; Natural history collection, Antropocene Biodiversity loss, computer vision, herbaria, Exetended Specimen, Natural histoty collection
Dates
Published: 2025-05-27 18:29
Last Updated: 2025-05-27 18:29
License
CC-BY Attribution-NonCommercial-ShareAlike 4.0 International
Additional Metadata
Conflict of interest statement:
None
Data and Code Availability Statement:
The dataset consisting of 100 annotated, digitized herbarium specimens, which is referenced in section 4, is available as an RO-Crate under a Creative Commons license and openly published un-der https://doi.org/10.12761/w2c1-x551.
Language:
English
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