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README.md
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- **Language(s):** English; Latin
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- **Homepage:**
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- **Repository:**
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- **Paper:** [Coming Soon!]() <!-- Add arXiv link once up -->
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## Dataset Description
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- For ecological analyses, it is essential to link specimen-level traits to NEON environmental data using identifiers such as `plotID` and `collectDate`. This enables spatially and temporally explicit studies on trait–environment relationships, including responses to climate gradients, habitat conditions, or ecological disturbances.
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- Researchers should avoid drawing continental-scale ecological or evolutionary inferences based solely on this dataset, as it represents a single tropical site. Broader-scale interpretations require supplementary datasets that capture geographic and taxonomic variation. As noted above, be sure to align the taxonomic naming from disparate sources (e.g., with [TaxonoPy](https://github.com/Imageomics/TaxonoPy)). Moreover, users are encouraged to consider the ethical implications of AI deployment in biodiversity monitoring and conservation, ensuring that research derived from this dataset aligns with its intended purpose of advancing ecological understanding and supporting conservation outcomes.
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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## Licensing Information
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Images and associated metadata: [Creative Commons Attribution 4.0](https://creativecommons.org/licenses/by/4.0/).
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- **Language(s):** English; Latin
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<!--
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- **Homepage:**
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- **Repository:** [Carabidae Beetle Processing](https://github.com/Imageomics/carabidae_beetle_processing)
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- **Paper:** [Coming Soon!]() <!-- Add arXiv link once up -->
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## Dataset Description
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- For ecological analyses, it is essential to link specimen-level traits to NEON environmental data using identifiers such as `plotID` and `collectDate`. This enables spatially and temporally explicit studies on trait–environment relationships, including responses to climate gradients, habitat conditions, or ecological disturbances.
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- Researchers should avoid drawing continental-scale ecological or evolutionary inferences based solely on this dataset, as it represents a single tropical site. Broader-scale interpretations require supplementary datasets that capture geographic and taxonomic variation. As noted above, be sure to align the taxonomic naming from disparate sources (e.g., with [TaxonoPy](https://github.com/Imageomics/TaxonoPy)). Moreover, users are encouraged to consider the ethical implications of AI deployment in biodiversity monitoring and conservation, ensuring that research derived from this dataset aligns with its intended purpose of advancing ecological understanding and supporting conservation outcomes.
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## Licensing Information
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Images and associated metadata: [Creative Commons Attribution 4.0](https://creativecommons.org/licenses/by/4.0/).
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