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The methods followed in the creation of the dataset, including description of field, laboratory and processing steps, and quality control procedures
No methods recorded for this dataset
Detailed documentation of the fields comprising the dataset, including the type of measurement, units where applicable, and any controlled vocabularies or code lists present in the data
Equipment and software used to collect data, including how that equipment was used.
No sampling equipment recorded for this dataset
The spatial extent of the dataset site coverage, and descriptions of the spatial extent and context for the data collection
- Site Description
Minimum Altitude: 20 meters
Notes describing any special conditions or considerations for understanding the quality and consistency of the data
|Phytoplankton were assigned to morpho-functional group (MFG; Salmaso et al. 2015) and CSR (Reynolds 1988). Species with functional trait data in Rimet et al. (2019) were classified using criteria in Salmaso et al. (2015). Unclassified species were assigned to MFG based on library of species- and genus-level classifications derived from online trait databases and published literature. Library is available in the algaeClassify R package. CSR classifications were assigned based on Reynolds et al. (1988) where surface area (SA), volume (VOL), and linear dimension (LD) were available. SA and VOL refer to the biological unit (single cell for unicellular species, colony dimensions for a colonial species). If only LD and cell/colony geometries were available, SA and VOL calculations were calculated from Hillebrand et al. (1999). When relevant trait values were not available, CSR groups were assigned based on MFG classifications and a cross-mapping between functional traits associated with MFG and CSR groups, which was derived by the GEISHA group (Stockwell et al. 2020). All methods can be implemented in algaeClassify R package. Classifications reflect typical morphological characteristics of phytoplankton species under the conditions of common study. However, classifications are based on plastic traits that can vary among systems, seasons, and environmental change. We encourage users to derive functional classifications based on site- and time-specific trait data when possible.