A Model to Evaluate Recreational Management Measures Objective I – Stock Assessment Analysis Create a model to distribute estimated landings (A + B1 fish) by size class. Create a model to distribute estimated catch (A + B1 +B2 fish) by size class

A Model to Evaluate Recreational Management Measures Objective II – Estimates of landings and catch for different proposed recreational fishery regulations Size limits Possession limits Abundance

Summer Flounder Size Class 2011

I. Logistic Analysis The logit model where multiple possible outcomes exist can be extended to a multinomial model referred to as a generalized or baseline-category logit model of the form (McFadden, 1974): Log(Pr(Y=i|x)/Pr(Y=k+1|x)) = α i + β’ i xi = 1,....,k α i = the intercept parameters, and β i = the vector of the slope parameters.

Analysis of Maximum Likelihood Estimates for the Probability that a Fish will be Landed in a Given Size Category Extra-Fishery Variables Parameter DF Estimate Standard Wald Error Chi-Square Pr > ChiSq sfldp <.0001 FPPI <.0001 pr <.0001 NP E E NPd <.0001 omega <.0001

Analysis of Maximum Likelihood Estimates for the Probability that a Fish will be Landed in a Given Size Category Recreational Fishing Experience Variables Parameter DF Estimate Standard Wald Error Chi-Square Pr > ChiSq Weight <.0001 TotSFL E <.0001 SSB E E <.0001 PARTY <.0001

Analysis of Maximum Likelihood Estimates for the Probability that a Fish will be Landed in a Given Size Category Regulatory Variables Parameter DF Estimate Standard Wald Error Chi-Square Pr > ChiSq minsLm minslmi <.0001 PosLmt ARecTrgt <.0001

Numbers of Summer Flounder Landed Minimum Size = 16 Possession Limit = 3 StATotnszclnszcl11nszcl12nszcl13nszcl14nszcl15nszcl16nszcl17nszcl18nszcl19nszcl20nszcl21nszcl22nszcl23nszcl24nszcl25 CT DE MA MD NC NJ NY RI VA Coastwi de Total

II. Quick Assessment Method The first model (m1) predicts the number of fish landed (Type A + B1 fish) in a state that have been intercepted, identified, measured, and in some cases weighted by observers (TotSFLnmbr). The second model (m2) predicts the total number of fish (Type A+B1+B2 fish) reported to observers by anglers who did not necessarily allow them to be identified, measured, and weighted by observers (TotSFLnd).

M1: Parameters of Interest Variable Parameter EstimateStandard ErrorF ValuePr > F Offshore Minimum Size limit <.0001 Inshore Minimum Size Limit <.0001 Possession Limit Offshore <.0001 Possession Limit Inshore <.0001 Open Season <.0001

QAM: Scatter Plot Two scatter plots at the end of the program provide a comparison of the actual and predicted values of these two dependent variables. These plots indicate that most predicted values fall within narrow bands around the actual values of the variables; this reflects the coefficient of determination of 76.7 and 76.8 percent, respectively.

Summer flounder recreational management measures by state, 2012.

Estimated Landed and Caught StateLandedCaught MA RI CT NY NJ DE MD VA NC Coast Wide

Fluke MRIP 2012 Number of Fish STATE Grand TotalSum W1-4 % W1-4 from 2011Proj Total MASSACHUSETTS , %134,981 RHODE ISLAND , %109,727 CONNECTICUT , %61,056 NEW YORK , %526,319 NEW JERSEY , %951,286 DELAWARE , %43,404 MARYLAND , %26,806 VIRGINIA , %266,473 NORTH CAROLINA , %48,039 1,995,794 2,168,092 2,168

Proposed Regulations Season length = 153 days Abundance = Possession Limit = 3, 4, and 5 fish Minimum Size Limit = 16 and 17 inches Landed = A + B1 fish Caught = A + B1 + B2 fish Inshore Regulations = Offshore Regulations

Numbers of Coast Wide Fish Landed (A + B1) and Caught (A + B1 + B2) (000 of fish) Minimum Size Possession LimitNumbers LandedNumbers Caught (inches)(number of fish) (Type A+B1)(Type A+B1+B2)

Summary This model is a simple application of time proven methods of dealing with imperfect information in a marketplace or natural environment. While the concepts are simple, their actual application is complex. A step by step user guide is provided in the appendix attached. The programs in steps I to VII are used if the existing data set is to be modified for another species of recreationally harvested fish. These steps will update the database needed to estimate a new sets of coefficients for use in a policy analysis of any existing or proposed fishery management regulations.