Here I will conduct exploratory analysis of 2018 eelgrass community data
Load biomass/abundace data, stable isotope, and fatty acid data
Biomass and oceanography
Stable Isotope - preliminary
Fatty Acid
Biomarker metadata
Merge all the different biomass data types into one data frame
## Warning: Removed 5 rows containing missing values (geom_errorbar).
summaries by site
## Warning: Removed 1 rows containing missing values (geom_errorbar).
## Warning: Removed 1 rows containing missing values (geom_errorbar).
Merge species with si values
## Warning: Removed 23 rows containing missing values (geom_point).
## Warning: Removed 23 rows containing missing values (geom_point).
The ultimate goal will be to look at some basic nmds plots of all species. Then overlay some depended variables like site and sea otter treatment.
What FAs do we have here.
## [1] "a.C17.0" "a.C18.0" "a.C19.0" "C14.0" "C15.0" "C16.0" "C16.1w"
## [8] "C16.1w5" "C16.1w7" "C16.1w9" "C16.2w" "C16.2w3" "C16.2w6" "C16.3w3"
## [15] "C16.4w" "C16.4w3" "C17.0" "C17.1w" "C17.1w9" "C18.0" "C18.1w"
## [22] "C18.1w7" "C18.1w9" "C18.2w" "C18.2w3" "C18.2w6" "C18.3w" "C18.3w3"
## [29] "C18.3w6" "C18.4w" "C18.4w2" "C18.4w3" "C19.1w" "C20.0" "C20.1w"
## [36] "C20.1w7" "C20.1w9" "C20.2w" "C20.2w3" "C20.2w6" "C20.3w3" "C20.3w6"
## [43] "C20.4w" "C20.4w3" "C20.4w6" "C20.5w3" "C21.0" "C22.0" "C22.1w"
## [50] "C22.1w9" "C22.2w" "C22.2w2" "C22.2w3" "C22.2w6" "C22.3w" "C22.4w3"
## [57] "C22.4w6" "C22.5w3" "C22.6w3" "C23.0" "C24.0" "i.C15.0" "i.C16.0"
## [64] "i.C17.0" "i.C18.0"
First will will have to prep that data with some manipulations and transformations and standardizations.
Subsets
I will use and arcsine sqrt transformation
NMDS calculations
FA vectors
Data prep. Build dataframe from metaMDS output fo easy plotting
Plots