glmmADMB warning: 'sigma' and 'rdig' arguments are present for compatibility only: ignored

[dalalhanna]

Using a glmmADMB negative binomial model I'm getting the warning message:
"Warning message: In .local(x, sigma, ...) : 'sigma' and 'rdig' arguments are present for compatibility only: ignored".
This made me wonder if there was a problem with the model, although it is apparently a harmless (see https://stackoverflow.com/questions/40703179/recurring-but-probably-erroneous-error-message-in-glmmadmb-package, and personal communications with Ben Bolker).
I am proving a reproducible example so that this warning can be further investigated and removed if it is indeed a harmless problem that does not indicate a problem with this type of model. (Note that I am not 100% certain this model is actually doing a good job at meeting its assumptions... I am just learning how to use glmms and could be using the wrong approach using a negative binomial model for this data)

Reproducible code:
#Create dataframe
RecreationalTrails<-c(5, 0, 0, 4, 7, 0, 0, 0, 6, 5, 0, 6, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0,4, 6, 8, 0, 0, 7)
LandUse<-c("Protected", "Agricultural", "Forestry", "Unprotected Forest", "Protected", "Agricultural", "Forestry", "Unprotected Forest",
"Protected", "Agricultural", "Forestry", "Unprotected Forest","Protected", "Agricultural", "Forestry", "Unprotected Forest",
"Protected", "Agricultural", "Forestry", "Unprotected Forest","Protected", "Agricultural", "Forestry", "Unprotected Forest",
"Protected", "Agricultural", "Forestry", "Unprotected Forest")
Parc<-c("Monts Valin", "Monts Valin", "Monts Valin", "Monts Valin", "Fjords du Saguenay", "Fjords du Saguenay","Fjords du Saguenay",
"Fjords du Saguenay", "Hautes Gorges", "Hautes Gorges","Hautes Gorges","Hautes Gorges", "Grands Jardins", "Grands Jardins",
"Grands Jardins", "Grands Jardins", "Mont Tremblant", "Mont Tremblant", "Mont Tremblant", "Mont Tremblant", "Mauricie",
"Mauricie", "Mauricie", "Mauricie", "Jacques Cartier", "Jacques Cartier", "Jacques Cartier", "Jacques Cartier")
ESCombinedDataRE<-data.frame(c("LandUse", "Parc", "RecreationalTrails"))
ESCombinedDataRE <- data.frame(LandUse, Parc, RecreationalTrails)
names(ESCombinedDataRE) <- c("LandUse", "Parc", "RecreationalTrails")
ESCombinedDataRE

#Run glmer negative binomial model
R_glmer <- glmmadmb(RecreationalTrails ~ LandUse+ (1|Parc), data=ESCombinedDataRE, family= "nbinom")

#Validate model
#look at homogeneity
ResidR<-resid(R_glmer)
qqnorm(ResidR)
qqline(ResidR, col=2)

#Model output (where the error is)
summary(R_glmer)