Hello, this is Joaqu?n Aldabe from Uruguay. I?m trying to model shorebird counts (Buff breasted Sandpiper, BBSA) with glmm (using lme4 package), using continuous variables (grass height, field area, forest cover) and one factor variable (presence/absence of other shorebird species: American Golden Plover, AMGP). I sampled 19 fields during three years in December. I?m interested in identifying predictors correlated with BBSA counts. I used Year as a random effect as I?m not interested in Year as a fix effect and because fields were counted three times (pseudoreplication). The model doesn?t converge, and the output showed that the factorial variable has not a significant effect. This is weird as in every field I observed the Buff breasted Sandpiper I also observed the other species. When I take AMGP out, the model runs ok. This is the model I?m trying to run: mysub3.3<-glmer(BBSA~Grass_height+Field_area+Field_enclosure_700m+Grass_height*Field_enclosure_700m+fAMGP+(1|fYear),family="poisson", data=mysub3.2) continuous variables were scaled. I can send de data frame if somebody is interested. Thanks in advanced for helping me on my master thesis. Cheers, Joaqu?n.
*Joaqu?n Aldabe* *Grupo Biodiversidad, Ambiente y Sociedad* Centro Universitario de la Regi?n Este, Universidad de la Rep?blica Ruta 15 (y Ruta 9), Km 28.500, Departamento de Rocha *Departamento de Conservaci?n* Aves Uruguay BirdLife International Canelones 1164, Montevideo https://sites.google.com/site/joaquin.aldabe <https://sites.google.com/site/perfilprofesionaljoaquinaldabe>