NMDS with vegan - How to modify insufficient data?

Hi there,
I have a dataset with 26 observations and 7039 variables each. The data looks like this

SampleID Time Prot1 Prot2 Prot3 Prot4 Prot5 Prot6
t0_2 Start 0.004898333 0.000986609 0 0 0.020992855 0
t0_3 Start 0.006429024 0 0 0 0.025716094 0
t0_5 Start 0.003940074 0.000925866 0.000990521 0 0.015760296 0.001959153

with Prot1 - Prot7039. Missing data has been replaced with 0. To visualize and test my data, I want to conduct a NMDS using the vegan package. However, when I run the NMDS I get an error saying

*** Solution reached
Warning message:
In metaMDS(data_1, distance = "bray", k = 2) :
stress is (nearly) zero: you may have insufficient data

The stress values is usually around 9.873474e-05. These are the commands I ran

#Load the data
Exp245 <- read.table("Exp245_NMDS_Input.txt", header = TRUE)

#Create subsets for the NMDS command
data_1 <- Exp245[,3:7039]
data_2 <- Exp245[,1:2]

#Load vegan

#Run the actual NMDS analysis
NMDS <- metaMDS(data_1, distance = "bray", k = 2)

I did this analysis with a similar dataset and it worked perfectly fine. I tried to transform the data hoping that this will change something but it didn't. Do you have a solution for this? Should I maybe try another distance matrix? Or is it because there are so many 0 in the dataset which makes the matrix rank insufficient?

Thank you all in advance!


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