PROGRAM MANAGE
 
C ***** GLOBAL INPUT PARAMETERS
 
      COMMON /MANPAR/ PPROB,PYMAX,PNYSTP,PKSTEP,PDSTEP,PNBSTP,PBMIN,
     1     PBMAX,PSCALE,PHASET,PHASEP,PCYCLE,PLEVEL,PSLOPE,PYMIN
      REAL PPROB, PYMAX, PNYSTP, PKSTEP, PDSTEP, PNBSTP, PBMIN, PBMAX,
     1     PSCALE, PHASET, PHASEP, PCYCLE, PLEVEL, PSLOPE,PYMIN
 
      COMMON /MANDAT/ ISTART, IYEAR, NS, NZ, RKLO, RKHI
      INTEGER ISTART, IYEAR, NS, NZ
      REAL RKLO, RKHI
 
      PARAMETER (MAXYR = 200, MAXEST = 100)
      PARAMETER (MSIZE = (MAXEST * (MAXEST + 1) / 2))
      REAL CATCH(0:MAXYR), SIGHT(0:MAXEST), FMATRX(0:MSIZE),
     1     ZMULT(0:MAXEST), POP(0:MAXYR), G(0:MAXYR), RAWCL, CL
      INTEGER ISYR(0:MAXEST), IZYR(0:MAXEST), POUT
 
C ***** LOCAL VARIABLES
 
      CHARACTER STOCK*30, FORMT*50
      INTEGER IY, INITYR, I, IS, IYRCL, ILAST, N, IN, IOUT
 
C ***** Read in the data required for application of the CLA
 
      DATA IN/2/, IOUT/3/
      OPEN (IN, FILE = 'CLC.DAT')
      OPEN (IOUT, FILE = 'CLC.OUT')
 
      CALL RDPARS
      READ (IN, '(A30/)') STOCK
      WRITE (IOUT, '(A30/)') STOCK
 
C      Read the year of the first catch, the first year for which catch
C      limits are to be set & the phaseout option
 
      READ (IN, '(T30,I4)') INITYR
      WRITE (IOUT, '(A,T30,I4)') 'Year of first input data', INITYR
      READ (IN, '(T30,I4)') IYRCL
      WRITE (IOUT, '(A, T30, I4)') 'Year of first catch limit', IYRCL
      READ (IN, '(T30, I4)') POUT
      IF (POUT .EQ. 1) THEN
        WRITE (IOUT, '(A, T30,A4)') 'Apply phaseout if necessary', 'YES'
      ELSE
        WRITE (IOUT, '(A, T30,A4)') 'Apply phaseout', 'No'
      ENDIF
 
C     Re-scale IYRCL such that 0 is the year prior to the first input data
 
      ISTART = 0
      IYEAR = IYRCL - INITYR
      IF (IYEAR .LE. 0 .OR. IYEAR .GT. MAXYR) STOP 'INVALID YEAR'
 
C     Initialize the catch array
 
      DO 10 I = 0, MAXYR
        CATCH(I) = 0
 10   CONTINUE
 
C     Read in the catch data, scaling each year to the initial year
 
      READ (IN, '(// A)') FORMT
      WRITE (IOUT, '(/A)') 'Historic catches:'
      TOTALC = 0
      DO 20 I = 0, MAXYR
        READ (IN, FORMT) IY, C 
        IF (IY .LT. 0) GO TO 25
        WRITE (IOUT, FORMT) IY, C
        IY = IY - INITYR
        IF (IY .LT. 0 .OR. IY .GE. IYEAR) STOP 
        CATCH(IY) = C
        TOTALC = TOTALC + C
 20   CONTINUE
 
 25   IF (TOTALC .LT. 0) STOP ' ERROR: No historic catch input'
 
C     Read in the non-zero sightings estimates and information matrix
 
      READ (IN, '(//T30, I4 / A)') NS, FORMT
      WRITE (IOUT, '(/A)') 'Abundance estimates:'
      IF (NS .GT. MAXEST) STOP 'ERROR: Abundance year out of range'
      DO 30 N=0,NS-1
        N1 = (N * (N + 1)) / 2
        READ (IN, FORMT) ISYR(N), SIGHT(N), (FMATRX(N1 + J), J = 0, N)
        WRITE (IOUT, FORMT) ISYR(N), SIGHT(N), 
     1                           (FMATRX (N1 + J), j = 0, N)
        ISYR(N) = ISYR(N) - INITYR
        IF (ISYR(N) .LT. 0 .OR. ISYR(N) .GE. IYEAR) STOP 
     1                         'ERROR: Sight year out of range'
        IF (SIGHT(N) .LE. 0.0) STOP ' ERROR: Estimate not positive'
 30   CONTINUE
 
C     Read in the Poisson multipliers for any zero sightings estimates
 
      READ (IN, '(/T30, I3, /A)') NZ, FORMAT
      IF (NZ .GT. 0) WRITE (IOUT, '(/A)') 'Zero abundance estimates:'
      IF (NZ .GT. MAXEST) STOP ' ERROR: Zero estimate array too small'
      DO 40 N = 0, NZ - 1
        N1 = (N * (N + 1)) / 2
        READ (IN, FORMT) IZYR(N), ZMULT(N)
        WRITE (IOUT, FORMT) IZYR(N), ZMULT(N)
        IZYR(N) = IZYR(N) - INITYR
        IF (IZYR(N) .LT. 0 .OR. IZYR(N) .GE. IYEAR) STOP 
     1                                    ' Sight year out of range'
        IF (ZMULT(N) .LE. 0.0) STOP ' ERROR: Multiplier not positive'
 40   CONTINUE
      WRITE (IOUT, '()')
 
C     Bound the range for the integration over K
 
      RKHI = 1.E7
      RKLO = 0.0
 
C ******
C ****** Run the CLA to obtain the nominal catch limit
C ******
 
      RAWCL = CLIMIT (CATCH, SIGHT, FMATRX, ISYR, IZYR, ZMULT, POP, G)
 
C     Set the catch limits for PCYCLE years. If the catch limit may be
C     subject to phaseout, call POUT to apply the phaseout rule.
 
C     First set ILAST = year of the most recent abundance estimate
 
      IF (NS .GT. 0) ILAST = ISYR(NS - 1)
      IF (NZ .GT. 0) ILAST = MAX(IS, IZYR(NZ - 1))
 
      DO 100 IY = IYEAR, IYEAR + PCYCLE - 1
        IF (POUT .EQ. 1) THEN
          CALL PHOUT (CL, RAWCL, ILAST, IY)
        ELSE
          CL = RAWCL
        ENDIF
        WRITE (IOUT, '(A6, I5, A17, I6)') 'Year:', IY + INITYR,
     1                                         'Catch limit:', NINT(CL)
 100  CONTINUE
 
      STOP
      END
 
C **************************************************************************************
C **************************************************************************************
C
C     CLC version 6
C
C **************************************************************************************
C
C     31 January 1994
C
C **************************************************************************************
 
      SUBROUTINE RDPARS
 
C     Read the file of input parameters
 
      COMMON /MANPAR/ PPROB,PYMAX,PNYSTP,PKSTEP,PDSTEP,PNBSTP,PBMIN,
     1     PBMAX,PSCALE,PHASET,PHASEP,PCYCLE,PLEVEL,PSLOPE,PYMIN
      REAL PPROB, PYMAX, PNYSTP, PKSTEP, PDSTEP, PNBSTP, PBMIN, PBMAX,
     1     PSCALE, PHASET, PHASEP, PCYCLE, PLEVEL, PSLOPE,PYMIN
      DATA IFILE /21/
C
C     Open the input file (only read once)
C
      OPEN (UNIT = IFILE, FILE = 'CLC.PAR')
C
      READ (IFILE, '(T30, F10.0)') PPROB,PYMAX,PYMIN,PNYSTP,PKSTEP,
     1     PDSTEP, PBMIN,  PBMAX,  PNBSTP, PSCALE, PHASET,
     1     PHASEP, PCYCLE, PLEVEL, PSLOPE
      CLOSE (IFILE)
      RETURN
      END
C
C
C **************************************************************************************
C **************************************************************************************
C
      SUBROUTINE PHOUT (CL, RAWCL, ILAST, IY)
C
      COMMON /MANPAR/ PPROB,PYMAX,PNYSTP,PKSTEP,PDSTEP,PBMIN,PBMAX,
     1     PNBSTP,PSACLE,PHASET,PHASEP,PCYCLE,PLEVEL,PSLOPE,PYMIN
      REAL PPROB, YMAX,PNYSTP,PKSTEP,PDSTEP,PBMIN,PBMAX,PNBSTP,PSACLE,
     1     PHASET, PHASEP, PCYCLE, PLEVEL, PSLOPE,PYMIN
C     PHASET Number of years without surveys before phaseout invoked
C     PHASEP Phaseout annual reduction proportion
C
      REAL CL, RAWCL
      INTEGER ILAST, IY
C
C     Phaseout: Reduce catch limit if there is no survey data in the
C     last PHASET years
      IF (IY .GE. ILAST + PHASET) THEN
        CL = RAWCL * (1.0 - PHASEP * (IY - ILAST - PHASET))
        IF (CL .LT. 0.0) CL = 0.0
      ELSE
        CL = RAWCL
      ENDIF
C
      RETURN
      END
 
C ***************************************************************************************
 
      REAL FUNCTION CLIMIT (CATCH,SIGHT,FMATRX,ISYR,IZYR,ZMULT,POP,G)
 
C     Run the CLA to obtain to nominal catch limit
C
      PARAMETER (MAXSIM = 600000, MAXSTP = 500)
      REAL PRES(0:MAXSIM), QRES(0:MAXSIM), SS0, SS1, SS2, SS3
C
      COMMON /MANPAR/ PPROB,PYMAX,PNYSTP,PKSTEP,PDSTEP,PNBSTP,PBMIN,
     1         PBMAX,PSCALE,PHASET,PHASEP,PCYCLE,PLEVEL,PSLOPE,PYMIN
      REAL PPROB,PYMAX,PNYSTP,PKSTEP,PDSTEP,PNBSTP,PBMIN, PBMAX,
     1         PSCALE,PHASET,PHASEP,PCYCLE,PLEVEL,PSLOPE,PYMIN
C
      COMMON /MANDAT/ ISTART, IYEAR, NS, NZ, RKLO, RKHI
      INTEGER ISTART, IYEAR, NS, NZ
      REAL    RKLO, RKHI
C
      REAL CATCH(0:*),SIGHT(0:*),FMATRX(0:*),ZMULT(0:*),POP(0:*),G(0:*)
      INTEGER ISYR(0:*), IZYR(0:*)
C
C     Local variables:
 
      REAL SF, Y(0:MAXSTP), B(0:MAXSTP), RLGB(0:MAXSTP)
      INTEGER NB, NR
 
C     NB        Number of bias steps
C     NR        Number of steps for Y (the productivity parameter)
C     SF        Deviance scale factor (SF = .5 / PSCALE**2)
C
      CLIMIT = 0.
      IF (NS .LE. 0) RETURN
C
C     Set deviance scale factor S = 1/PSCALE**2
      SF = 0.5 / (PSCALE * PSCALE)
C
C     Check the sizes of the Y and B arrays are large enough
      IF (PNBSTP .GT. MAXSTP .OR. PNYSTP .GT. MAXSTP) STOP
     1                             'Y &/or b array sizes too small'
 
C     Set sightings bias step sizes & their log values. BINC = Bias increment
      NB = PNBSTP
      BINC = (PBMAX - PBMIN) / NB
      DO 10 I = 0, NB - 1
        B(I) = PBMIN + (I + 0.5) * BINC
        RLGB(I) = -ALOG(B(I))
 10   CONTINUE
C
C     Set productivity parameter step sizes (midpoints)
      NR = PNYSTP
      YINC = (PYMAX - PYMIN) / NR
      DO 20 I = 0, NR - 1
        Y(I) = (I + 0.5) * YINC + PYMIN
 20   CONTINUE
C
 
      PTOT = 0
      N = 0
      DO 50 I = 0, NR - 1
 
C     Set R from the productivity parameter, Y
        R = 1.4184 * Y(I)
 
C     Step size for K
        DK = PKSTEP
        D = 1.
        RK = RKHI
 
C     Use function STKSIM to set up the Nth population trajectory
C     i.e. set up the pop array
 30     IF (RK .LE. RKLO .OR. STKSIM (RK, R, POP, CATCH) .LE. 0.)
     1                                                     GOTO 40
      IF (N .GE. MAXSIM) STOP 'ERROR: TOO MANY SIMULATIONS'
 
C     How much depletion covered?
          DD = D - POP(IYEAR) / RK
          D = POP(IYEAR) / RK
          P = 0.0
 
          IF (DD .GT. 0.) THEN
 
C     Compute the internal catch limit corresponding to D and Y(I)
            QRES(N) = CONTRL (D, Y(I), PLEVEL, PSLOPE) * POP(IYEAR)
 
C     Calculate deviance
            CALL DEVIAN (SS0, SS1, SS2, SS3, SIGHT, FMATRX, ISYR,
     1                                            IZYR, ZMULT, POP, G)
 
C     Scale likelihood and integrate over values for the bias parameter
            DO 35 J = 0, NB - 1
              P = P + EXP(-SF * (SS0 + RLGB(J) * (SS1 + RLGB(J) * SS2)
     1                                              + SS3 * B(J)))
 35         CONTINUE
 
C     Calculate the weight for this point (& total area under likelihood)
            PRES(N) = P * DD
            PTOT = PTOT + PRES(N)
 
C     Update counter
            N = N + 1
 
C     Find the next K
            DK = DK * PDSTEP / DD
            IF (DK .GT. PKSTEP) DK = PKSTEP
 
          ELSE
C     IF DD = 0 change the step size only 
            DK = PKSTEP
          ENDIF
 
C     Set the new value of K
          RK = RK / (1. + DK)
 
        GOTO 30
 40     CONTINUE
 50   CONTINUE
 
 
      IF (PTOT .LE. 0.) STOP 'ERROR: PROB INTEGRATES TO ZERO'
 
C     Sort the QRES and PRES arrays in ascending order of QRES
      N2 = N
      CALL SORT (QRES, PRES, N2)
 
C     Normalize the relative likelihoods
      DO 60 I = 0, N - 1
        PRES(I) = PRES(I) / PTOT
 60   CONTINUE
 
C     Extract the desired probability level: the nominal catch limit (NCL)
C     is the lower PROB% of the distribution.
C     First calculate PRES(I), the probability that the NCL is between
C     QRES(I) & QRES(I + 1).
      P = 0
      DO 70 I = 0, N - 1
        P = P + PRES (I)
        IF (P .GT. PPROB) GOTO 80
 70   CONTINUE
 
C     Interpolate to set the nominal catch limit
 80   IF (I .GE. N - 1) THEN
        Q = QRES (N - 1)
      ELSE
        Q = (QRES (I + 1) * (PPROB - P + PRES(I)) + QRES(I) *
     1                                    (P - PPROB)) / PRES(I)
      ENDIF
 
      CLIMIT = Q
 
      RETURN
      END
 
C ***********************************************************************************
 
      FUNCTION CONTRL (D, Y, PLEVEL, PSLOPE)
 
C     Catch control law
 
      IF (D .LT. PLEVEL) THEN
        CONTRL = 0.
      ELSEIF (D .LT. 1.) THEN
        CONTRL = PSLOPE * Y * (D - PLEVEL)
      ELSE
        CONTRL = PSLOPE * Y * (1.0 - PLEVEL)
      ENDIF
 
      END
 
C **********************************************************************************
 
      SUBROUTINE DEVIAN (SS0, SS1, SS2, SS3, SIGHT, FMATRX, ISYR,
     1                                         IZYR, ZMULT, POP, G)
 
C     Calculate deviance (-2 log likelihood) in terms of coefficients for 
C     the bias and log bias parameters
 
      COMMON /MANDAT/ ISTART, IYEAR, NS, NZ, RKLO, RKHI
      INTEGER ISTART, IYAER, NS, NZ
      REAL    RKLO, RKHI
 
      REAL SS0,SS1,SS2,SIGHT(0:*),FMATRX(0:*),ZMULT(0:*),POP(0:*),G(0:*)
      INTEGER ISYR(0:*), IZYR(0:*)
 
      SS0 = 0
      SS1 = 0
      SS2 = 0
      SS3 = 0
 
      DO 100 N = 0, NS - 1
 
        G(N) = ALOG (SIGHT(N) / POP(ISYR(N)))
        K = N * (N + 1) / 2
        DO 10 J = 0, N - 1
C     1st add non diagonal contributions (which are doubled up)
          SS0 = SS0 + 2. * G(J) * G(N) * FMATRX(K)
          SS1 = SS1 + 2. * (G(J) + G(N)) * FMATRX(K)
          SS2 = SS2 + FMATRX(K) + FMATRX(K)
          K = K + 1
 10     CONTINUE
C     Now add diagnoal contribution
        SS0 = SS0 + G(N) * G(N) * FMATRX(K)
        SS1 = SS1 + 2. * G(N) * FMATRX(K)
        SS2 = SS2 + FMATRX(K)
 100  CONTINUE
 
C     Now do the zero estimates
      DO 200 N = 0, NZ - 1
        SS3 = SS3 + 2.0 * POP(IZYR(N)) / ZMULT(N)
 200  CONTINUE
 
      RETURN
      END
 
C *********************************************************************************
 
      FUNCTION STKSIM (RK, R, POP, CATCH)
 
C     Calculate the stock trajectory with parameter RK and R: return
C     the current stock size
C     RK = notional carrying capacity; R = productivity parameter * 1.4184
 
      COMMON /MANDAT/ ISTART, IYEAR, NS, NZ, RKLO, RKHI
      INTEGER ISTART, IYEAR, NS, NZ
      REAL    RKLO, RKHI
 
      REAL CATCH(0:*), POP(0:*)
 
      POP(ISTART) = RK
      DO 10 I = ISTART + 1, IYEAR
        D = POP(I - 1) / RK
        POP(I) = POP (I - 1) * (1. + R * (1. - D * D)) - CATCH(I-1)
        IF (POP(I) .LE. 0) GOTO 20
 10   CONTINUE
      STKSIM = POP(IYEAR)
      RETURN
 
 20   STKSIM = 0.
 
      END
 
C *********************************************************************************
 
      SUBROUTINE SORT (ARRAY, ARRAY2, N)
 
C     SORT sorts a pair of arrays in ascending order of the first array
C     (using the heapsort algorithm)
 
      REAL ARRAY(0:*), ARRAY2(0:*), TEMP, TEMP2
      INTEGER N, K, IR, I, J
      IF (N .LT. 2) RETURN
      K = N / 2
      IR = N - 1
 10   IF (K .NE. 0) THEN
        K = K - 1
        TEMP = ARRAY(K)
        TEMP2 = ARRAY2(K)
      ELSE
        TEMP = ARRAY(IR)
        TEMP2 = ARRAY2(IR)
        ARRAY(IR) = ARRAY(0)
        ARRAY2(IR) = ARRAY2(0)
        IR = IR - 1
        IF (IR .EQ. 0) THEN
          ARRAY(0) = TEMP
          ARRAY2(0) = TEMP2
          RETURN
        ENDIF
      ENDIF
      I = K
      J = K + K + 1
 20   IF (J .LE. IR) THEN
        IF (J .LT. IR .AND. ARRAY(J) .LT. ARRAY(J + 1)) J = J + 1
        IF (TEMP .LT. ARRAY(J)) THEN
          ARRAY(I) = ARRAY(J)
          ARRAY2(I) = ARRAY2(J)
          I = J
          J = J + I + 1
        ELSE
          J = IR + 1
        ENDIF
        GOTO 20
      ENDIF
      ARRAY(I) = TEMP
      ARRAY2(I) = TEMP2
      GOTO 10
 
      END
 
				      PROGRAM MANAGE

C ***** GLOBAL INPUT PARAMETERS

      COMMON /MANPAR/ PPROB,PYMAX,PNYSTP,PKSTEP,PDSTEP,PNBSTP,PBMIN,
     1     PBMAX,PSCALE,PHASET,PHASEP,PCYCLE,PLEVEL,PSLOPE,PYMIN
      REAL PPROB, PYMAX, PNYSTP, PKSTEP, PDSTEP, PNBSTP, PBMIN, PBMAX,
     1     PSCALE, PHASET, PHASEP, PCYCLE, PLEVEL, PSLOPE,PYMIN

      COMMON /MANDAT/ ISTART, IYEAR, NS, NZ, RKLO, RKHI
      INTEGER ISTART, IYEAR, NS, NZ
      REAL RKLO, RKHI

      PARAMETER (MAXYR = 200, MAXEST = 100)
      PARAMETER (MSIZE = (MAXEST * (MAXEST + 1) / 2))
      REAL CATCH(0:MAXYR), SIGHT(0:MAXEST), FMATRX(0:MSIZE),
     1     ZMULT(0:MAXEST), POP(0:MAXYR), G(0:MAXYR), RAWCL, CL
      INTEGER ISYR(0:MAXEST), IZYR(0:MAXEST), POUT

C ***** LOCAL VARIABLES

      CHARACTER STOCK*30, FORMT*50
      INTEGER IY, INITYR, I, IS, IYRCL, ILAST, N, IN, IOUT

C ***** Read in the data required for application of the CLA

      DATA IN/2/, IOUT/3/
      OPEN (IN, FILE = 'CLC.DAT')
      OPEN (IOUT, FILE = 'CLC.OUT')

      CALL RDPARS
      READ (IN, '(A30/)') STOCK
      WRITE (IOUT, '(A30/)') STOCK

C      Read the year of the first catch, the first year for which catch
C      limits are to be set & the phaseout option

      READ (IN, '(T30,I4)') INITYR
      WRITE (IOUT, '(A,T30,I4)') 'Year of first input data', INITYR
      READ (IN, '(T30,I4)') IYRCL
      WRITE (IOUT, '(A, T30, I4)') 'Year of first catch limit', IYRCL
      READ (IN, '(T30, I4)') POUT
      IF (POUT .EQ. 1) THEN
        WRITE (IOUT, '(A, T30,A4)') 'Apply phaseout if necessary', 'YES'
      ELSE
        WRITE (IOUT, '(A, T30,A4)') 'Apply phaseout', 'No'
      ENDIF

C     Re-scale IYRCL such that 0 is the year prior to the first input data

      ISTART = 0
      IYEAR = IYRCL - INITYR
      IF (IYEAR .LE. 0 .OR. IYEAR .GT. MAXYR) STOP 'INVALID YEAR'

C     Initialize the catch array

      DO 10 I = 0, MAXYR
        CATCH(I) = 0
 10   CONTINUE

C     Read in the catch data, scaling each year to the initial year

      READ (IN, '(// A)') FORMT
      WRITE (IOUT, '(/A)') 'Historic catches:'
      TOTALC = 0
      DO 20 I = 0, MAXYR
        READ (IN, FORMT) IY, C 
        IF (IY .LT. 0) GO TO 25
        WRITE (IOUT, FORMT) IY, C
        IY = IY - INITYR
        IF (IY .LT. 0 .OR. IY .GE. IYEAR) STOP 
        CATCH(IY) = C
        TOTALC = TOTALC + C
 20   CONTINUE

 25   IF (TOTALC .LT. 0) STOP ' ERROR: No historic catch input'

C     Read in the non-zero sightings estimates and information matrix

      READ (IN, '(//T30, I4 / A)') NS, FORMT
      WRITE (IOUT, '(/A)') 'Abundance estimates:'
      IF (NS .GT. MAXEST) STOP 'ERROR: Abundance year out of range'
      DO 30 N=0,NS-1
        N1 = (N * (N + 1)) / 2
        READ (IN, FORMT) ISYR(N), SIGHT(N), (FMATRX(N1 + J), J = 0, N)
        WRITE (IOUT, FORMT) ISYR(N), SIGHT(N), 
     1                           (FMATRX (N1 + J), j = 0, N)
        ISYR(N) = ISYR(N) - INITYR
        IF (ISYR(N) .LT. 0 .OR. ISYR(N) .GE. IYEAR) STOP 
     1                         'ERROR: Sight year out of range'
        IF (SIGHT(N) .LE. 0.0) STOP ' ERROR: Estimate not positive'
 30   CONTINUE

C     Read in the Poisson multipliers for any zero sightings estimates

      READ (IN, '(/T30, I3, /A)') NZ, FORMAT
      IF (NZ .GT. 0) WRITE (IOUT, '(/A)') 'Zero abundance estimates:'
      IF (NZ .GT. MAXEST) STOP ' ERROR: Zero estimate array too small'
      DO 40 N = 0, NZ - 1
        N1 = (N * (N + 1)) / 2
        READ (IN, FORMT) IZYR(N), ZMULT(N)
        WRITE (IOUT, FORMT) IZYR(N), ZMULT(N)
        IZYR(N) = IZYR(N) - INITYR
        IF (IZYR(N) .LT. 0 .OR. IZYR(N) .GE. IYEAR) STOP 
     1                                    ' Sight year out of range'
        IF (ZMULT(N) .LE. 0.0) STOP ' ERROR: Multiplier not positive'
 40   CONTINUE
      WRITE (IOUT, '()')

C     Bound the range for the integration over K

      RKHI = 1.E7
      RKLO = 0.0

C ******
C ****** Run the CLA to obtain the nominal catch limit
C ******

      RAWCL = CLIMIT (CATCH, SIGHT, FMATRX, ISYR, IZYR, ZMULT, POP, G)

C     Set the catch limits for PCYCLE years. If the catch limit may be
C     subject to phaseout, call POUT to apply the phaseout rule.

C     First set ILAST = year of the most recent abundance estimate

      IF (NS .GT. 0) ILAST = ISYR(NS - 1)
      IF (NZ .GT. 0) ILAST = MAX(IS, IZYR(NZ - 1))

      DO 100 IY = IYEAR, IYEAR + PCYCLE - 1
        IF (POUT .EQ. 1) THEN
          CALL PHOUT (CL, RAWCL, ILAST, IY)
        ELSE
          CL = RAWCL
        ENDIF
        WRITE (IOUT, '(A6, I5, A17, I6)') 'Year:', IY + INITYR,
     1                                         'Catch limit:', NINT(CL)
 100  CONTINUE

      STOP
      END

C **************************************************************************************
C **************************************************************************************
C
C     CLC version 6
C
C **************************************************************************************
C
C     31 January 1994
C
C **************************************************************************************

      SUBROUTINE RDPARS

C     Read the file of input parameters

      COMMON /MANPAR/ PPROB,PYMAX,PNYSTP,PKSTEP,PDSTEP,PNBSTP,PBMIN,
     1     PBMAX,PSCALE,PHASET,PHASEP,PCYCLE,PLEVEL,PSLOPE,PYMIN
      REAL PPROB, PYMAX, PNYSTP, PKSTEP, PDSTEP, PNBSTP, PBMIN, PBMAX,
     1     PSCALE, PHASET, PHASEP, PCYCLE, PLEVEL, PSLOPE,PYMIN
      DATA IFILE /21/
C
C     Open the input file (only read once)
C
      OPEN (UNIT = IFILE, FILE = 'CLC.PAR')
C
      READ (IFILE, '(T30, F10.0)') PPROB,PYMAX,PYMIN,PNYSTP,PKSTEP,
     1     PDSTEP, PBMIN,  PBMAX,  PNBSTP, PSCALE, PHASET,
     1     PHASEP, PCYCLE, PLEVEL, PSLOPE
      CLOSE (IFILE)
      RETURN
      END
C
C
C **************************************************************************************
C **************************************************************************************
C
      SUBROUTINE PHOUT (CL, RAWCL, ILAST, IY)
C
      COMMON /MANPAR/ PPROB,PYMAX,PNYSTP,PKSTEP,PDSTEP,PBMIN,PBMAX,
     1     PNBSTP,PSACLE,PHASET,PHASEP,PCYCLE,PLEVEL,PSLOPE,PYMIN
      REAL PPROB, YMAX,PNYSTP,PKSTEP,PDSTEP,PBMIN,PBMAX,PNBSTP,PSACLE,
     1     PHASET, PHASEP, PCYCLE, PLEVEL, PSLOPE,PYMIN
C     PHASET Number of years without surveys before phaseout invoked
C     PHASEP Phaseout annual reduction proportion
C
      REAL CL, RAWCL
      INTEGER ILAST, IY
C
C     Phaseout: Reduce catch limit if there is no survey data in the
C     last PHASET years
      IF (IY .GE. ILAST + PHASET) THEN
        CL = RAWCL * (1.0 - PHASEP * (IY - ILAST - PHASET))
        IF (CL .LT. 0.0) CL = 0.0
      ELSE
        CL = RAWCL
      ENDIF
C
      RETURN
      END

C ***************************************************************************************

      REAL FUNCTION CLIMIT (CATCH,SIGHT,FMATRX,ISYR,IZYR,ZMULT,POP,G)

C     Run the CLA to obtain to nominal catch limit
C
      PARAMETER (MAXSIM = 600000, MAXSTP = 500)
      REAL PRES(0:MAXSIM), QRES(0:MAXSIM), SS0, SS1, SS2, SS3
C
      COMMON /MANPAR/ PPROB,PYMAX,PNYSTP,PKSTEP,PDSTEP,PNBSTP,PBMIN,
     1         PBMAX,PSCALE,PHASET,PHASEP,PCYCLE,PLEVEL,PSLOPE,PYMIN
      REAL PPROB,PYMAX,PNYSTP,PKSTEP,PDSTEP,PNBSTP,PBMIN, PBMAX,
     1         PSCALE,PHASET,PHASEP,PCYCLE,PLEVEL,PSLOPE,PYMIN
C
      COMMON /MANDAT/ ISTART, IYEAR, NS, NZ, RKLO, RKHI
      INTEGER ISTART, IYEAR, NS, NZ
      REAL    RKLO, RKHI
C
      REAL CATCH(0:*),SIGHT(0:*),FMATRX(0:*),ZMULT(0:*),POP(0:*),G(0:*)
      INTEGER ISYR(0:*), IZYR(0:*)
C
C     Local variables:

      REAL SF, Y(0:MAXSTP), B(0:MAXSTP), RLGB(0:MAXSTP)
      INTEGER NB, NR

C     NB        Number of bias steps
C     NR        Number of steps for Y (the productivity parameter)
C     SF        Deviance scale factor (SF = .5 / PSCALE**2)
C
      CLIMIT = 0.
      IF (NS .LE. 0) RETURN
C
C     Set deviance scale factor S = 1/PSCALE**2
      SF = 0.5 / (PSCALE * PSCALE)
C
C     Check the sizes of the Y and B arrays are large enough
      IF (PNBSTP .GT. MAXSTP .OR. PNYSTP .GT. MAXSTP) STOP
     1                             'Y &/or b array sizes too small'

C     Set sightings bias step sizes & their log values. BINC = Bias increment
      NB = PNBSTP
      BINC = (PBMAX - PBMIN) / NB
      DO 10 I = 0, NB - 1
        B(I) = PBMIN + (I + 0.5) * BINC
        RLGB(I) = -ALOG(B(I))
 10   CONTINUE
C
C     Set productivity parameter step sizes (midpoints)
      NR = PNYSTP
      YINC = (PYMAX - PYMIN) / NR
      DO 20 I = 0, NR - 1
        Y(I) = (I + 0.5) * YINC + PYMIN
 20   CONTINUE
C

      PTOT = 0
      N = 0
      DO 50 I = 0, NR - 1

C     Set R from the productivity parameter, Y
        R = 1.4184 * Y(I)

C     Step size for K
        DK = PKSTEP
        D = 1.
        RK = RKHI

C     Use function STKSIM to set up the Nth population trajectory
C     i.e. set up the pop array
 30     IF (RK .LE. RKLO .OR. STKSIM (RK, R, POP, CATCH) .LE. 0.)
     1                                                     GOTO 40
      IF (N .GE. MAXSIM) STOP 'ERROR: TOO MANY SIMULATIONS'

C     How much depletion covered?
          DD = D - POP(IYEAR) / RK
          D = POP(IYEAR) / RK
          P = 0.0

          IF (DD .GT. 0.) THEN

C     Compute the internal catch limit corresponding to D and Y(I)
            QRES(N) = CONTRL (D, Y(I), PLEVEL, PSLOPE) * POP(IYEAR)

C     Calculate deviance
            CALL DEVIAN (SS0, SS1, SS2, SS3, SIGHT, FMATRX, ISYR,
     1                                            IZYR, ZMULT, POP, G)

C     Scale likelihood and integrate over values for the bias parameter
            DO 35 J = 0, NB - 1
              P = P + EXP(-SF * (SS0 + RLGB(J) * (SS1 + RLGB(J) * SS2)
     1                                              + SS3 * B(J)))
 35         CONTINUE

C     Calculate the weight for this point (& total area under likelihood)
            PRES(N) = P * DD
            PTOT = PTOT + PRES(N)

C     Update counter
            N = N + 1

C     Find the next K
            DK = DK * PDSTEP / DD
            IF (DK .GT. PKSTEP) DK = PKSTEP

          ELSE
C     IF DD = 0 change the step size only 
            DK = PKSTEP
          ENDIF

C     Set the new value of K
          RK = RK / (1. + DK)

        GOTO 30
 40     CONTINUE
 50   CONTINUE


      IF (PTOT .LE. 0.) STOP 'ERROR: PROB INTEGRATES TO ZERO'

C     Sort the QRES and PRES arrays in ascending order of QRES
      N2 = N
      CALL SORT (QRES, PRES, N2)

C     Normalize the relative likelihoods
      DO 60 I = 0, N - 1
        PRES(I) = PRES(I) / PTOT
 60   CONTINUE

C     Extract the desired probability level: the nominal catch limit (NCL)
C     is the lower PROB% of the distribution.
C     First calculate PRES(I), the probability that the NCL is between
C     QRES(I) & QRES(I + 1).
      P = 0
      DO 70 I = 0, N - 1
        P = P + PRES (I)
        IF (P .GT. PPROB) GOTO 80
 70   CONTINUE

C     Interpolate to set the nominal catch limit
 80   IF (I .GE. N - 1) THEN
        Q = QRES (N - 1)
      ELSE
        Q = (QRES (I + 1) * (PPROB - P + PRES(I)) + QRES(I) *
     1                                    (P - PPROB)) / PRES(I)
      ENDIF

      CLIMIT = Q

      RETURN
      END

C ***********************************************************************************

      FUNCTION CONTRL (D, Y, PLEVEL, PSLOPE)

C     Catch control law

      IF (D .LT. PLEVEL) THEN
        CONTRL = 0.
      ELSEIF (D .LT. 1.) THEN
        CONTRL = PSLOPE * Y * (D - PLEVEL)
      ELSE
        CONTRL = PSLOPE * Y * (1.0 - PLEVEL)
      ENDIF

      END

C **********************************************************************************

      SUBROUTINE DEVIAN (SS0, SS1, SS2, SS3, SIGHT, FMATRX, ISYR,
     1                                         IZYR, ZMULT, POP, G)

C     Calculate deviance (-2 log likelihood) in terms of coefficients for 
C     the bias and log bias parameters

      COMMON /MANDAT/ ISTART, IYEAR, NS, NZ, RKLO, RKHI
      INTEGER ISTART, IYAER, NS, NZ
      REAL    RKLO, RKHI

      REAL SS0,SS1,SS2,SIGHT(0:*),FMATRX(0:*),ZMULT(0:*),POP(0:*),G(0:*)
      INTEGER ISYR(0:*), IZYR(0:*)

      SS0 = 0
      SS1 = 0
      SS2 = 0
      SS3 = 0

      DO 100 N = 0, NS - 1

        G(N) = ALOG (SIGHT(N) / POP(ISYR(N)))
        K = N * (N + 1) / 2
        DO 10 J = 0, N - 1
C     1st add non diagonal contributions (which are doubled up)
          SS0 = SS0 + 2. * G(J) * G(N) * FMATRX(K)
          SS1 = SS1 + 2. * (G(J) + G(N)) * FMATRX(K)
          SS2 = SS2 + FMATRX(K) + FMATRX(K)
          K = K + 1
 10     CONTINUE
C     Now add diagnoal contribution
        SS0 = SS0 + G(N) * G(N) * FMATRX(K)
        SS1 = SS1 + 2. * G(N) * FMATRX(K)
        SS2 = SS2 + FMATRX(K)
 100  CONTINUE

C     Now do the zero estimates
      DO 200 N = 0, NZ - 1
        SS3 = SS3 + 2.0 * POP(IZYR(N)) / ZMULT(N)
 200  CONTINUE

      RETURN
      END

C *********************************************************************************

      FUNCTION STKSIM (RK, R, POP, CATCH)

C     Calculate the stock trajectory with parameter RK and R: return
C     the current stock size
C     RK = notional carrying capacity; R = productivity parameter * 1.4184

      COMMON /MANDAT/ ISTART, IYEAR, NS, NZ, RKLO, RKHI
      INTEGER ISTART, IYEAR, NS, NZ
      REAL    RKLO, RKHI

      REAL CATCH(0:*), POP(0:*)

      POP(ISTART) = RK
      DO 10 I = ISTART + 1, IYEAR
        D = POP(I - 1) / RK
        POP(I) = POP (I - 1) * (1. + R * (1. - D * D)) - CATCH(I-1)
        IF (POP(I) .LE. 0) GOTO 20
 10   CONTINUE
      STKSIM = POP(IYEAR)
      RETURN

 20   STKSIM = 0.

      END

C *********************************************************************************

      SUBROUTINE SORT (ARRAY, ARRAY2, N)

C     SORT sorts a pair of arrays in ascending order of the first array
C     (using the heapsort algorithm)

      REAL ARRAY(0:*), ARRAY2(0:*), TEMP, TEMP2
      INTEGER N, K, IR, I, J
      IF (N .LT. 2) RETURN
      K = N / 2
      IR = N - 1
 10   IF (K .NE. 0) THEN
        K = K - 1
        TEMP = ARRAY(K)
        TEMP2 = ARRAY2(K)
      ELSE
        TEMP = ARRAY(IR)
        TEMP2 = ARRAY2(IR)
        ARRAY(IR) = ARRAY(0)
        ARRAY2(IR) = ARRAY2(0)
        IR = IR - 1
        IF (IR .EQ. 0) THEN
          ARRAY(0) = TEMP
          ARRAY2(0) = TEMP2
          RETURN
        ENDIF
      ENDIF
      I = K
      J = K + K + 1
 20   IF (J .LE. IR) THEN
        IF (J .LT. IR .AND. ARRAY(J) .LT. ARRAY(J + 1)) J = J + 1
        IF (TEMP .LT. ARRAY(J)) THEN
          ARRAY(I) = ARRAY(J)
          ARRAY2(I) = ARRAY2(J)
          I = J
          J = J + I + 1
        ELSE
          J = IR + 1
        ENDIF
        GOTO 20
      ENDIF
      ARRAY(I) = TEMP
      ARRAY2(I) = TEMP2
      GOTO 10

      END
