diff --git a/src/model_fitting/abundance_model.R b/src/model_fitting/abundance_model.R
index cbb71191f168b932ad014acb481406fff1624168..8590860b9d69583c6a59022457994f4c16b74284 100644
--- a/src/model_fitting/abundance_model.R
+++ b/src/model_fitting/abundance_model.R
@@ -262,7 +262,7 @@ model_terms <- names(glm.nb(as.formula(paste("nr_nests~", paste(m_terms,
                                              "+ offset(offset_term)",
                                              sep = "")),
                               data = predictors_obs,
-                            control = glm.control(maxit = 500))$coefficients)
+                            control = glm.control(maxit = 250))$coefficients)
 # prediction estimates
 intercept <- rep(1, nrow(predictors_obs))
 predictor_estimates <- cbind( intercept,
@@ -286,7 +286,7 @@ model <- as.formula(
   paste("nr_nests ~", full_model, "+ offset(offset_term)"))
 
 res_full <- glm.nb(model, data = predictors_obs,
-                   control = glm.control(maxit = 500))
+                   control = glm.control(maxit = 250))
 
 # HERE I CAN NOW USE THE OTHER FUNCTION
 dfbeta_frame <- data.frame(slope=res_full$coefficients, res_full$coefficients+
@@ -329,7 +329,7 @@ results_res <- foreach(i = 1:nrow(all_model_terms),
 	    paste(m_terms[all_model_terms[i, ] == 1], collapse = "+"),
             "+ offset(offset_term)"))
             res <- glm.nb(model, data = predictors_obs,
-                          control = glm.control(maxit = 500))
+                          control = glm.control(maxit = 250))
 
 
 # model