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This content will become publicly available on January 18, 2025

Title: What is an Herbarium and How Does it Help Us Protect Biodiversity?

When scientists study plants, they often collect, preserve, and store parts of the plants in a big collection called an herbarium. These plant specimens serve as proof that a species was growing in a certain place at a certain time. Herbaria (“herbaria” is the plural of herbarium) are where scientists describe new plant species and study how different species are related. Herbaria also contain lots of information about where certain plant species grow, what type of habitats species like, and at what time of year plants bloom and make fruits. Finally, herbaria are powerful tools for helping us understand how plants are affected by disturbances like habitat destruction and climate change. For all of these reasons, herbaria allow us to better understand and protect plant species all over the world. To continue benefitting from herbaria, we need to keep collecting plants and make these collections accessible to the world.

 
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Award ID(s):
1936971 1754664
PAR ID:
10486462
Author(s) / Creator(s):
; ;
Publisher / Repository:
Frontiers Media
Date Published:
Journal Name:
Frontiers for Young Minds
Volume:
11
ISSN:
2296-6846
Page Range / eLocation ID:
1170456
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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    With digitization and data sharing initiatives underway over the last 15 years, an important need has been prioritizing specimens to digitize. Because duplicate specimens are shared among herbaria in exchange and gift programs, we investigated the extent to which unique biogeographic data are held in small herbaria vs. these data being redundant with those held by larger institutions. We evaluated the unique specimen contributions that small herbaria make to biogeographic understanding at county, locality, and temporal scales.

    Methods

    We sampled herbarium specimens of 40 plant taxa from each of eight states of the United States of America in four broad status categories: extremely rare, very rare, common native, and introduced. We gathered geographic information from specimens held by large (≥100,000 specimens) and small (<100,000 specimens) herbaria. We built generalized linear mixed models to assess which features of the collections may best predict unique contributions of herbaria and used an Akaike information criterion‐based information‐theoretic approach for our model selection to choose the best model for each scale.

    Results

    Small herbaria contributed unique specimens at all scales in proportion with their contribution of specimens to our data set. The best models for all scales were the full models that included the factors of species status and herbarium size when accounting for state as a random variable.

    Conclusions

    We demonstrated that small herbaria contribute unique information for research. It is clear that unique contributions cannot be predicted based on herbarium size alone. We must prioritize digitization and data sharing from herbaria of all sizes.

     
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  4. Premise

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    To encourage the development of an automatic species identification algorithm, we submitted our Herbarium 2019 data set to the Fine‐Grained Visual Categorization sub‐competition (FGVC6) hosted on the Kaggle platform. We chose to focus on the flowering plant family Melastomataceae because we have a large collection of imaged herbarium specimens (46,469 specimens representing 683 species) and taxonomic expertise in the family. As is common for herbarium collections, some species in this data set are represented by few specimens and others by many.

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    In less than three months, the FGVC6 Herbarium 2019 Challenge drew 22 teams who entered 254 models for Melastomataceae species identification. The four best algorithms identified species with >88% accuracy.

    Discussion

    The FGVC competitions provide a unique opportunity for computer vision and machine learning experts to address difficult species‐recognition problems. The Herbarium 2019 Challenge brought together a novel combination of collections resources, taxonomic expertise, and collaboration between botanists and computer scientists.

     
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