• Address:
  705 Spear Street
  South Burlington, Vermont 05403
  United States of America
  
  Phone: (802) 391-4135
  Email: femc@uvm.edu
  Website: www.uvm.edu/femc

The Global Evaluation of the Impacts of Storms on freshwater Habitat and Structure of phytoplankton Assemblages (GEISHA) project is using long-term monitoring datasets and high-frequency data available through international networks to address questions about the impacts of storms on phytoplankton community in over 40 lakes across the globe. GEISHA has been developed within the context of the Global Lake Ecological Observatory Network (GLEON) initiative called “Storm-blitz”. “Storm-blitz” assembles an international group of investigators interested in contributing to theoretical discussions and sharing data to answer questions about the impacts of extreme events on phytoplankton communities. Although climate change is expected to cause more intense and frequent extreme weather events, we only have a basic understanding of how these events might alter freshwater phytoplankton communities. The storm-blitz group was created in 2016 and gathers 17 researchers with diverse skillsets and experiences to focus on data compilation and analysis (https://www.geisha-stormblitz.fr/).

• dataset_eml_attributelistlabel: lake

• dataset_eml_attributelistdescription: Lake Name

• dataset_eml_attributeliststoragetype: text

• dataset_eml_attributelistmeasurementtype: nominal

• dataset_eml_attributelistlabel: stationid

• dataset_eml_attributelistdescription: Unique ID for location of sampling; could be more than one per lake

• dataset_eml_attributeliststoragetype: text

• dataset_eml_attributelistmeasurementtype: nominal

• dataset_eml_attributelistlabel: device

• dataset_eml_attributelistdescription: Device used to collect phytoplankton samples

• dataset_eml_attributeliststoragetype: text

• dataset_eml_attributelistmeasurementtype: nominal

• dataset_eml_attributelistlabel: mesh_um

• dataset_eml_attributelistdescription: mesh size in microns; use NaN if device is not net

• dataset_eml_attributeliststoragetype: int

• dataset_eml_attributelistmeasurementtype: interval
• Unit: micron
• dataset_eml_attributelistnumbertype: integer
• dataset_eml_attributelistbounds:
• dataset_eml_attributelistboundsminimum: 1
• dataset_eml_attributelistboumdsmaximum:

• dataset_eml_attributelistlabel: integrated_y_n

• dataset_eml_attributelistdescription: is the sample integrated over depth range? yes or no

• dataset_eml_attributeliststoragetype: text

• dataset_eml_attributelistmeasurementtype: nominal

• dataset_eml_attributelistlabel: min_depth_m

• dataset_eml_attributelistdescription: Minimum depth of integrated sample (in most cases this is 0); if sample is from a single depth put this depth here and also as max_depth_m

• dataset_eml_attributeliststoragetype: decimal

• dataset_eml_attributelistmeasurementtype: ratio
• Unit: meter
• dataset_eml_attributelistnumbertype: real

• dataset_eml_attributelistlabel: max_depth_m

• dataset_eml_attributelistdescription: Maximum depth of integrated sample; if sample is from a single depth put this depth here and also as min_depth_m

• dataset_eml_attributeliststoragetype: decimal

• dataset_eml_attributelistmeasurementtype: ratio
• Unit: meter
• dataset_eml_attributelistnumbertype: real

• dataset_eml_attributelistlabel: date_dd_mm_yyyy

• dataset_eml_attributelistdescription: Date

• dataset_eml_attributeliststoragetype: date

• dataset_eml_attributelistmeasurementtype: datetime
• dataset_eml_attributelistformatstring: DD-MM-YYYY

• dataset_eml_attributelistlabel: phyto_name

• dataset_eml_attributelistdescription: Name of phytoplankton genus and species, or other taxonomic classification

• dataset_eml_attributeliststoragetype: text

• dataset_eml_attributelistmeasurementtype: nominal

• dataset_eml_attributelistlabel: cell_colony_density_ind_l

• dataset_eml_attributelistdescription: cells or colonies per liter; use of cell or colony density will depend on sampling program or taxa

• dataset_eml_attributeliststoragetype: decimal

• dataset_eml_attributelistmeasurementtype: ratio
• Unit: individuals per liter
• dataset_eml_attributelistnumbertype: real

• dataset_eml_attributelistlabel: biovol_um3_ml

• dataset_eml_attributelistdescription: Phytoplankton biovolume in cubic micrometers per milliliter

• dataset_eml_attributeliststoragetype: decimal

• dataset_eml_attributelistmeasurementtype: ratio
• Unit: cubic micrometer per milliliter
• dataset_eml_attributelistnumbertype: real

• dataset_eml_attributelistlabel: biomass_ug_l

• dataset_eml_attributelistdescription: Phytoplankton biomass in micrograms per liter

• dataset_eml_attributeliststoragetype: decimal

• dataset_eml_attributelistmeasurementtype: ratio
• Unit: micrograms per liter
• dataset_eml_attributelistnumbertype: real

• dataset_eml_attributelistlabel: genus

• dataset_eml_attributelistdescription: genus of phyto_name; if not applicable, use NaN

• dataset_eml_attributeliststoragetype: text

• dataset_eml_attributelistmeasurementtype: nominal

• dataset_eml_attributelistlabel: MFG

• dataset_eml_attributelistdescription: morpho-functional group classification

• dataset_eml_attributeliststoragetype: text

• dataset_eml_attributelistmeasurementtype: nominal

• dataset_eml_attributelistlabel: CSR

• dataset_eml_attributelistdescription: competitive, stress-tolerant, or ruderal strategist classification

• dataset_eml_attributeliststoragetype: text

• dataset_eml_attributelistmeasurementtype: nominal

• algaeClassify
  • dataset_eml_methoddescription: R package to convert phytoplankton genera or species to morpho-functional trait or CSR (competitive, stress-tolerant, ruderal) trait classifications. Citation is: Vijay Patil, Torsten Seltmann, Nico Salmaso, Orlane Anneville, Marc Lajeunesse and Dietmar Straile (2019). algaeClassify: Determine Phytoplankton Functional Groups Based on Functional Traits. R package version 1.2.0. https://CRAN.R-project.org/package=algaeClassify
  dataset_eml_methodsSoftware: https://CRAN.R-project.org/package=algaeClassify