Hi All,
This may be too long of an explanation, if so I am very sorry!
I am trying to create an ordination that shows one dot for every avian species and a vector for each vegetation character ( I have 32). Basically I want to view which species are most impacted by each veg characteristic as well as view which veg characters are most correlated ( I know I can do this in a simple correlation test but its more about the end product graph)
I believe I need to use an NMDS and the Vegan package to put my species in an ordination space and then later use a permutation test for the veg characters (I have not even gotten to the point of attempting this yet so explanation would be appreciated).
This is the code I have run on my species data
library(vegan)
SpeciesData <- Analyzable_veg_and_Bird_Abundance[2:26]
Species.mds <- metaMDS(SpeciesData, distance = "bray", autotransform = FALSE)
and I am getting this error. Do I need to get rid of the 197 rows in which no birds were counted? I hope not because my other analysis will be presence/absence .
Error in distfun(comm, method = distance, ...) :
missing values are not allowed with argument 'na.rm = FALSE'
I have attached a piece of my data, not all because it goes on for over 1000 rows. Any help at all would be appreciated. I need to know why I'm getting this error and if I am even headed in the right direction to get an ordination from this data. My problem is I am new enough to R that I can not figure out how to include all that my data encompasses in one ordination.
Point ID | BEVI | BEWR | BGGN | BHCO | BLGR | CACH | CASP | CARW | DICK | EAME | FISP | GRSP | INBU | LASP | MODO | NOBO | NOCA | NOMO | PABU | RCSP | STFL | TUTI | WEME | WEVI | YBCU | Max % Grass DF | Max % Forb DF | Max % Bare DF | Max % Litter DF | Max % Woody DF | Average % Grass DF | Average % Forb DF | Average % Bare DF | Average % Litter DF | Average % Woody DF | Max Height Grass DF | Max Height Forb DF | Max Height Litter DF | Max Height Woody DF | Avg Height Grass DF | Avg Height Forb DF | Avg Height Litter DF | Avg Height Woody DF | Avg Concealment Cover | Max Concealment Cover | Avg % Bare LI | Avg % Herb LI | Avg % Litter LI | Avg % Shrub LI | Max % Bare LI | Max % Herb LI | Max % Litter LI | Max % Shrub LI | % Canopy Cover | Average Extimated Height | Max Estimated Height | Average Shrubs per Hectare |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
18BR3015 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 63 | 85 | 3 | 63 | 0 | 21 | 50.25 | 0.75 | 27 | 0 | 0.48 | 0.83 | 0.39 | 0 | 0.335 | 0.7475 | 0.18 | 0 | 7 | 9 | 0 | 19.5 | 0 | 0.1 | 0 | 20 | 0 | 1 | 0.16 | 0.625 | 0.75 | 277.7777778 |
18BR3019 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 38 | 63 | 15 | 85 | 3 | 11 | 44.75 | 8.25 | 40.75 | 0.75 | 1 | 1 | 0.5 | 0.33 | 0.4725 | 0.775 | 0.2975 | 0.0825 | 8.75 | 11 | 0 | 13.45 | 0.9 | 1.13 | 0 | 14.8 | 1.1 | 7.2 | 0.16 | 0.875 | 1 | 17777.77778 |
18BR3043 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 38 | 63 | 85 | 15 | 0 | 14.75 | 29.75 | 27.25 | 12 | 0 | 0.5 | 0.52 | 0.01 | 0 | 0.305 | 0.37 | 0.0025 | 0 | 1.75 | 4 | 0 | 20 | 0 | 0 | 0 | 20 | 0 | 0 | 0.16 | 1.4375 | 2 | 3.844675125 |
18BR3051 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 63 | 63 | 38 | 15 | 0 | 29.75 | 56.75 | 20.75 | 5.25 | 0 | 0.36 | 0.61 | 0.16 | 0 | 0.295 | 0.5475 | 0.0575 | 0 | 4.25 | 8 | 1.35 | 16.55 | 0.65 | 0.29 | 1.6 | 17 | 1.3 | 1.5 | 0.16 | 0.6875 | 1 | 625 |
18BR3070 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 98 | 3 | 0 | 0 | 0 | 98 | 1.5 | 0 | 0 | 0 | 0.72 | 0.72 | 0 | 0 | 0.5425 | 0.18 | 0 | 0 | 3.25 | 4 | 0 | 20 | 0 | 0 | 0 | 20 | 0 | 0 | 0.16 | 1.75 | 3 | 22.67573696 |
Thank You!
Jennifer