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Aquatic Plant, Bryophyte, and Macroalgae Collection (Herbarium Vouchers [Standard Sampling]) (NEON-APLC-HVSS)

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This collections contains aquatic plant, bryophyte, and macroalgae specimens collected as vouchers during standard sampling (NEON sample class: apc_voucher_in.sampleID). These samples are archived dry in herbarium voucher packets. See related links below for protocols and NEON related data products.

Aquatic herbarium voucher

Contacts: NEON Biorepository, biorepo@asu.edu
Collection Manager: Laura Steger, lsteger@asu.edu (ORCID #: 0000-0002-0878-4132)
Specimen Imaging (2021-2022): Christopher Livingston, calivin3@asu.edu (ORCID #: 0000-0001-8676-0817)
Voucher Mounting (2021-2022): Annessa Lyle, amfoss1@asu.edu (ORCID #: 0000-0001-9632-9721)
Mounting and Imaging (2024): Ava Claus, alclaus@asu.edu (ORCID #: 0009-0003-4944-688X)
Aquatic plant, bryophyte, lichen, and macroalgae point counts in wadeable streams data product: https://data.neonscience.org/data-products/DP1.20072.001
Sampling Protocol: https://data.neonscience.org/documents/10179/1883159/NEON.DOC.003039vG/a86b8479-28ad-d285-77a3-ec1597c12734
Collection Type: Preserved Specimens
Management: Live Data managed directly within data portal
Global Unique Identifier: f2d646d3-c30d-419a-b9a7-a4551fe59742
DwC-Archive Access Point: https://biorepo.neonscience.org/portal/content/dwca/NEON-APLC-HVSS_DwC-A.zip
Digital Metadata: EML File
Usage Rights: CC BY-NC (Attribution-Non-Commercial)
GBIF Dataset page: http://www.gbif.org/dataset/dd1b2dbc-1a38-4212-a3d9-893a160da252
Cite this collection:
NEON Biorepository Data Portal (2024). NEON Biorepository Aquatic Plant, Bryophyte, Lichen and Macroalgae Collection (Herbarium Vouchers [Standard Sampling]). Occurrence dataset https://doi.org/10.15468/bmmdp5 accessed via the NEON Biorepository Data Portal, https://biorepo.neonscience.org/ on 2024-10-14.
Address:
Arizona State University
Biodiversity Knowledge Integration Center
734 W. Alameda Drive Suite 158
Tempe, AZ   85282
Collection Statistics
  • 62 specimen records
  • 62 (100%) georeferenced
  • 35 (56%) with images (35 total images)
  • 48 (77%) identified to species
  • 28 families
  • 38 genera
  • 43 species
  • 43 total taxa (including subsp. and var.)
Extra Statistics
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