diff --git a/README.Rmd b/README.Rmd
index d1e5ff79..85ba70b6 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -143,9 +143,10 @@ run_SSMSE(scen_name_vec = c("H-ctl", "H-1"), # name of the scenario
           use_SS_boot_vec = c(TRUE, TRUE), # use the SS bootstrap module for sampling
           nyrs_vec = c(6, 6),        # Years to project OM forward
           nyrs_assess_vec = c(3, 3), # Years between assessments
-          rec_dev_pattern = c("none", "none"), # Don't use recruitment deviations
-          impl_error_pattern = c("none", "none"), # Don't use implementation error
-          sample_struct_list = sample_struct_list) # How to sample data for running the EM.
+          rec_dev_pattern = c("none"), # Don't use recruitment deviations
+          impl_error_pattern = c("none"), # Don't use implementation error
+          sample_struct_list = sample_struct_list, # How to sample data for running the EM.
+          seed = 12345) #Set a fixed integer seed that allows replication 
 ```
 
 The function `SSMSE_summary_all` can be used to summarize the model results in a list of dataframes. Note that if you have issues, try reinstalling SSMSE using `remotes::install_github("nmfs-fish-tools/SSMSE")` and restarting your R session. Also, make sure you are using the development branch versions of [r4ss](https://github.com/r4ss/r4ss) and [ss3sim](https://github.com/ss3sim/ss3sim) (by installing `remotes::install_github("r4ss/r4ss@development")` and `remotes::install_github("ss3sim/ss3sim@development")`. These versions should be installed automatically when SSMSE is downloaded.
diff --git a/README.md b/README.md
index 9ccae99a..a378f5db 100644
--- a/README.md
+++ b/README.md
@@ -93,6 +93,7 @@ library(r4ss) #install using remotes::install_github("r4ss/r4ss@development)
 # Create a folder for the output in the working directory.
 run_SSMSE_dir <- file.path("run_SSMSE-ex")
 dir.create(run_SSMSE_dir)
+## Warning in dir.create(run_SSMSE_dir): 'run_SSMSE-ex' already exists
 ```
 
 The cod model with H = 0.65 is included as external package data.
@@ -105,7 +106,10 @@ cod_mod_path <- system.file("extdata", "models", "cod", package = "SSMSE")
 file.copy(from = cod_mod_path, to = run_SSMSE_dir, recursive = TRUE)
 ## [1] TRUE
 file.rename(from = file.path(run_SSMSE_dir, "cod"), to = file.path(run_SSMSE_dir, "cod-1"))
-## [1] TRUE
+## Warning in file.rename(from = file.path(run_SSMSE_dir, "cod"), to =
+## file.path(run_SSMSE_dir, : cannot rename file 'run_SSMSE-ex/cod' to 'run_SSMSE-
+## ex/cod-1', reason 'Access is denied'
+## [1] FALSE
 cod_1_path <- file.path(run_SSMSE_dir, "cod-1")
 # make model read initial values from control file and not ss.par
 start <- r4ss::SS_readstarter(file = file.path(cod_1_path, "starter.ss"), verbose = FALSE)
@@ -118,14 +122,14 @@ r4ss::SS_changepars(dir = cod_1_path, ctlfile = "control.ss_new",
 ## [1] "SR_BH_steep"
 ## These are the ctl file lines as they currently exist:
 ##      LO HI INIT PRIOR PR_SD PR_type PHASE env_var&link dev_link dev_minyr
-## 107 0.2  1 0.65   0.7  0.05       0    -4            0        0         0
+## 107 0.2  1    1   0.7  0.05       0    -4            0        0         0
 ##     dev_maxyr dev_PH Block Block_Fxn       Label Linenum
 ## 107         0      0     0         0 SR_BH_steep     107
 ## line numbers in control file (n=1):
 ## 107
 ## wrote new file to control_modified.ss with the following changes:
 ##   oldvals newvals oldphase newphase oldlos newlos oldhis newhis oldprior
-## 1    0.65       1       -4       -4    0.2    0.2      1      1      0.7
+## 1       1       1       -4       -4    0.2    0.2      1      1      0.7
 ##   newprior oldprsd newprsd oldprtype newprtype       comment
 ## 1      0.7    0.05    0.05         0         0 # SR_BH_steep
 # remove files with M = 0.2
@@ -221,9 +225,10 @@ run_SSMSE(scen_name_vec = c("H-ctl", "H-1"), # name of the scenario
           use_SS_boot_vec = c(TRUE, TRUE), # use the SS bootstrap module for sampling
           nyrs_vec = c(6, 6),        # Years to project OM forward
           nyrs_assess_vec = c(3, 3), # Years between assessments
-          rec_dev_pattern = c("none", "none"), # Don't use recruitment deviations
-          impl_error_pattern = c("none", "none"), # Don't use implementation error
-          sample_struct_list = sample_struct_list) # How to sample data for running the EM.
+          rec_dev_pattern = c("none"), # Don't use recruitment deviations
+          impl_error_pattern = c("none"), # Don't use implementation error
+          sample_struct_list = sample_struct_list, # How to sample data for running the EM.
+          seed = 12345) #Set a fixed integer seed that allows replication 
 ```
 
 The function `SSMSE_summary_all` can be used to summarize the model
@@ -241,8 +246,12 @@ should be installed automatically when SSMSE is downloaded.
 # Summarize 1 iteration of output
 summary <- SSMSE_summary_all(normalizePath(run_res_path))
 ## Extracting results from 2 scenarios
-## Starting H-1 with 5 iterations
-## Starting H-ctl with 5 iterations
+## Warning in ss3sim::get_results_all(directory = dir, user_scenarios = scenarios):
+## ss3sim_scalar.csv already exists and overwrite_files = FALSE, so a new file was
+## not written
+## Warning in ss3sim::get_results_all(directory = dir, user_scenarios = scenarios):
+## ss3sim_ts.csv already exists and overwrite_files = FALSE, so a new file was not
+## written
 ```
 
 Plotting and data manipulation can then be done with these summaries.
@@ -254,6 +263,7 @@ in year 103 (cod\_EM\_103), and the EM run with last year of data in 106
 
 ``` r
 library(ggplot2) # use install.packages("ggplot2") to install package if needed
+## Warning: package 'ggplot2' was built under R version 4.0.2
 library(tidyr) # use install.packages("tidyr") to install package if needed
 ## 
 ## Attaching package: 'tidyr'