diff --git a/9control.tex b/9control.tex
index e09dcae2..1b8a66c0 100644
--- a/9control.tex
+++ b/9control.tex
@@ -1039,6 +1039,7 @@ \subsubsection{Predator Fleet Mortality}
 	\hline
 \end{longtable}
 
+\hypertarget{EquilRecr}{}
 \myparagraph{Equilibrium Recruitment}
 In principle, steepness should always be used when calculating equilibrium recruitment. This was not the default in early versions of Stock Synthesis, so has not come into common practice. The original logic, from early 1990s version of Stock Synthesis for long-lived U.S. west coast groundfish, was that fishing had not yet gone on long enough to have reduced spawning biomass enough to reduce expected recruitment noticeably for the chosen initial equilibrium year.
 
@@ -1406,6 +1407,8 @@ \subsubsection{Predator Fleet Mortality}
 	\item With F\_Method 4, fleets with low $F$ can apply $F_{hyb}$ across all model phases and high $F$ fleets can switch to $F_{par}$ during later phases.
 	\item It is always advisable to allow the model to start with good starting values for parameters. This can be done by specifying a later phase (> 1) under the conditional input for F\_Method = 2 where early phases will use the hybrid method, then switch to $F$ as parameter in later phases and transfer the hybrid $F$ values to the parameter initial values. Same advice for using the F\_Method = 4. However, bycatch fleets do not have retained catch, so cannot use the hybrid method. They must use $F_{par}$ with user-specified starting value starting in phase 1.
 	\item Tests have demonstrated that the $F$ approach has negligible impact on the variance of derived quantities, such as spawning biomass in the final year.
+	\item It is possible to estimate $F_{par}$ for a particular fleet $\times$ time even if it has an unknown catch observation (for example, if you have years of catch data followed by a gap and then catch data again, can you estimate the missing catch data in SS3). This certainly is true if there is a discard observation for that fleet $\times$ time, but the effect of the $F_{par}$ on the population age composition and trends also allows the survey and composition data to influence the estimates of the $F_{par}$s. A catch observation must exist in order to trigger SS3 to estimate a $F_{par}$ for that fleet $\times$ time, so enter a dummy (but reasonable) value for the catch observation and give it a very large \gls{se} so that the deviations from the input catch observations will only be slightly penalized. Make sure that you use F\_Method = 4 so that the parameter approach will be used for that fleet. If the $F$ values for those years fluctuate dramatically, you can stabilize those $F$ values by adding a dummy effort (survey type = 2) time series. For example, if you are missing catch for 2012--2014, enter an effort value of 1.0 for those years and at least one adjacent year for which SS3 is already able to estimate $F$. This will stabilize the missing year $F$s to be similar to the $F$s for the adjacent years.
+
 \end{itemize}
 
 \begin{longtable}{p{1cm} p{3cm} p{11cm}}
@@ -1485,6 +1488,8 @@ \subsubsection{Predator Fleet Mortality}
 
 If there is catch, then give a starting value greater than zero, and it generally is best to estimate the parameter in phase 1. The initial $F$ parameter lines are ordered as shown in the example below - by season, then within a season, by fleet.
 
+If the initial equilibrium catch is near \gls{msy}, than a logical inconsistency may occur as documented in the \hyperlink{EquilRecr}{Equilibrium Recruitment section}. 
+
 It is possible to use the initial $F$ method to achieve an estimate of the initial equilibrium $Z$ in cases where the initial equilibrium catch is unknown. To do this requires 2 changes to the input files:
 \begin{enumerate}
 	\item Data File: Include a positive value for the initial equilibrium catch for at least one fleet, often with a higher standard error depending upon the situation.