BSA
AI CRAB R RATIIONA
ALIZA
ATION ED
DR AUDIT
U
S REPPORT PREPAR
RED FO
OR PACIFIC ST
TATES MARINE FISH
HERIES
S COMM
MISSION 20111 Calen
ndar Yeear Da
ata December 20012 TABLE OF CONTENTS Introductio
on ........................................................... ......................................................... 1 M
Methodolo
ogy ......................................................... ......................................................... 3 S
Support Classes ..................................................... ......................................................... 5 C
Catcher Ve
essel Auditt Code Anaalysis ...................... ......................................................... 6 P
Processor A
Audit Code Analysis .............................. ......................................................... 8 O
Outlier Aud
dit Code A
Analysis ................................... ......................................................... 9 A
Audit Variaable Analyysis .......................................... ....................................................... 10 B
Burden Ho
our Estimatte ............................................ ....................................................... 11 C
Commendation ...................................................... ....................................................... 13 C
Conclusion
n ............................................................. ....................................................... 14 A
Appendix A
A ............................................................ ....................................................... 15 A
Appendix B
B ............................................................ ....................................................... 17 INTRO
ODUCTION B
Backgro
ound
T
The Bering Sea S and Aleutian Islands (BSAI) (
Crab Rationalization Program was develop
ped to createe a quota ssystem that g
grants exclusive harvesting
g and processsing rights too crab harvestters, processors, and com
mmunities. T
The rationalized fishery began in fall 2005, with
h quota alloccated to harrvesters and processors based on h
historical participation in the fishery. Because of the expectted impact o
on the industtry, an econo
omic data ccollection pro
ogram was de
eveloped to better understtand the econnomic impactts on the indu
ustry. E
Economic datta reports (EDRs) were de
eveloped to o
obtain inform
mation aboutt the crab op
perations of h
harvesters aand processors to help mo
onitor how co
osts and economic returnns of various stakeholderss in BSAI crab
b fisheries aare affected by rationalizzation. In orrder to ensurre that the d
data submitteed by respon
ndents in thee EDRs is aaccurate, Con
ngress and th
he North Paccific Fishery Management
M
t Council specified that EDR data be ssubject to m
mandatory au
udits conducted by the th
hird party co
ollection agennt, Pacific States Marine Fisheries Commission (PSMFC). PS
SMFC contraccted AKT to develop and
d implement an EDR review and veriffication systeem, which involves revie
ewing the data contained
d within subm
mitted EDRs, conducting verification aaudits for those EDRs ccontaining daata values outside of the e
expected range, and cond
ducting rando
om audits for a certain peercentage o
of submitted EDRs. T
The EDRs we
ere developed
d to help dettermine the e
effects of thee rationalization program,, including ch
hanges to tthe costs of production p
an
nd the effectt of consolidaation. Natio nal Marine FFisheries Servvice (NMFS) ssought to u
understand th
he general trrends over th
he years and the effects oof rationalizaation to transslate to otherr fisheries tthat are begin
nning similar programs. T
This validation process is a
a continuation of similar w
work done in years 2006 to
o 2010. Priorr years’ data is audited in the currentt year; for exaample the 20110 data was a
audited in 20111. In summary, t
the purpose o
of the econom
mic data repo
ort and data v
validation is t
o: 11)
Aid the Council and N
NMFS in asse
essing the succcess of the P
Program; 22)
Understtand the econ
nomic perform
mance of crab
b fisherman; 33)
Understtand how the economic pe
erformance h
has changed a
after rationalization; 44)
Isolate t
the effects atttributable to the crab ratio
onalization pprogram; 55)
Assess t
the validity off data reporte
ed in submitted EDRs; and
d 66)
Provide guidance on improvemen
nts in the EDR
R process to i mprove the v
validity of futture data repo
orting. K
Key Participantts and Roles
R
T
The key particcipants in the
e project inclu
ude: 
National Marine Fisheeries Service (NMFS) – initiator of thee audit processs and end‐user of the infformation contained
d in the EDRs. 
Pacific States
S
Marine Fisheries Commission
C
(PSMFC) – collector and manager o
of the data collected through t
he EDRs. 1 
AKT LLP
P – independ
dent accounttants and co
onsultants seelected to auudit and valiidate the infformation collected in the EDRs. 
Participan
nts in the crab
b rationalizattion program. S
Scope off Work
T
The following
g procedures w
were requestted to be perfformed in thee scope of wo
ork for this project: 11)
Random
m Audits – Review R
and verification v
off a subset off data valuess reported in
n a randomlyy selected sample of EDRs. 22)
Outlier Audits – Revview and veriification of data values reeported in ED
DRs that conttained multip
ple outlier variable
es. These outliers were ide
entified throu
ugh an analyssis performed
d by NMFS. Analysis is cconducted as needed, based on prior year au
udit results an
nd statistical a
analysis. 33)
For Cau
use Audits – R
Review and v
verification o
of data valuess reported in EDRs that w
were non‐com
mpliant or that failed the audit process in the
e previous ED
DR calendar y
year. T
The methodo
ology to addre
ess the proce
edures above is outlined laater in this rep
port. B
Based upon o
our conversations with NM
MFS and PSMFC, the key oobjectives of t
the audit werre outlined ass follows: 
Validate k
key data. 
Identify p
problems with
h the data or EDR instructiions and makke suggestion
ns for future r
reporting. 
Promote compliance w
with timely an
nd accurate d
data reportingg requiremen
nts. 
Identify appropriate ch
hanges to datta when misssing or incorreect. 
Characterrize, and in so
ome cases qu
uantify, the level of accura cy associated
d with particu
ular data elem
ments. K
Key Info
ormation
n
T
The current aanalysis is bassed on the daata collected from partici pants of the BSAI crab raationalization
n program ffor the year 2
2011. A statisstical sample was determined based uupon a total s
submitted po
opulation of 1
111, which w
was comprise
ed of all unique submitterrs of informaation. The saample was deetermined baased upon acchieving a 9
95% confiden
nce level with a precision le
evel of 15% in
n terms of as sessing the a
accuracy of th
he submitted data (see A
Appendix A for detailed discussion of t
the statisticaal basis of thee sample). The following table summaarizes the n
number of ED
DRs submitted
d by type and
d the resulting
g sample sizee.
2 METHODOLOGY A
AKT, PSMFC, and NMFS w
worked together to determ
mine the bestt process to analyze data s
submitted through the E
EDR process and to deterrmine the methodology to t sample annd audit the data submittted in the ED
DRs. The p
process was b
based on prior year experie
ence with improvements m
made to beneefit the particcipants. The following iss a summary of the steps t
taken throughout the aud
dit process. 11)
Determine appropriiate variablees to validatte. The sig nificance of the data fo
or random au
udits and ence is consid
dered when d
determining the appropriate variabless to validate. This is a available audit evide
collaborrative processs between PS
SMFC, NMFS,, and AKT. 22)
Determine populatio
on subject to
o random aud
dit. The sam
mple size is deetermined using a statisticcal model with a 9
95% confiden
nce level and a 15% precission level. Seee Appendix A for a discu
ussion of the statistical basis used for selection. 33)
Determine outlier audit
a
populattion. Based upon its anaalysis of the EDR data without vessel identity, NMFS id
dentifies the population t
hat it desiress to validate t
through an o
outlier audit. These auditss focus on EDRs th
hat have a siignificant number of outlliers identifieed through aanalytical revview. Once aa vessel is identifie
ed has an outtlier, it is subjject to validaation for onlyy those variab
bles for which
h an outlier status was identifie
ed. Nine vessels and six processors were w
identifieed as having outlier variab
bles for the 2
2011 EDR data yeaar. 44)
Determining for‐cau
use audits. Vessels selecte
ed for for‐cauuse audits aree those that d
did not comply with an equest in the previous yeaar. Four vesssels were seleected for aud
dit in the 20111 EDR data year as a audit re
result off a failed audit in the prior year. 55)
Gather and crossch
heck EDR da
ata to be audited. EDR data pertain
ning to the variables selected for auditing
g are transferred to AKT from PSMFC
C. AKT usess a standard auditing anaalysis spreadssheet and imports data from PS
SMFC into th
his format. EDR data is veerified against the selected
d vessels’ orig
ginal EDR submisssions for accu
uracy. 66)
Requestt information
n subject to audit for ran
ndom, outlieer and for‐ca
ause audits. Selected veessels and processo
ors are asked
d to provide s
supporting infformation fo r the variablees selected fo
or validation. They are given on
ne month to c
comply with t
the request, t
though extennsions are graanted on an a
as‐needed baasis. If the selected
d vessels and
d processors do not comp
ply within onne month, they are individually contacted, and addition
nal contact effforts are maade as needed to ensure t
that each sellected vessel and processsor has an opportu
unity to respo
ond in a timelyy manner. 77)
Validatee information by comparring with sup
pporting docuumentation. This processs involves a review of the supporting docu
umentation submitted agaainst the origginal EDR daata submissio
on for each vvessel and variable
e selected. De
etailed notes related to th
he basis and q
quality of info
ormation are maintained i n order to evaluate
e the validityy of selected
d data. The vessels or pprocessors are contacted
d as need fo
or further clarifications and add
ditional suppo
orting docum
ments. 88)
Summarize the resu
ults of the audit
a
verifica
ation processs. Each audited variablee is classified
d within a support category, wh
hich classify a
and summariize the validitty of the aud
dit evidence r
eceived, allow
wing AKT to bette
er perform overall analysiss. 3 99)
Compilee a burden ho
our estimatee. Selected vvessels and p rocessors aree asked to esstimate the aamount of time de
edicated to compiling c
th
heir EDR sub
bmissions. T
The resulting
g responses are summarrized into estimated burden ho
ours by respondent type. A
Audit Methodol
M
logy
A
AKT selects vessels v
or processors for random aud
dit based upoon the statisstical sample outlined in Appendix A
A. AKT workss with NMFS and PSMFC t
to determine the appropriiate variabless to validate. FFor each datta variable re
equested, AK
KT critically evaluates th e support prrovided by tthe selected vessel or p
processor. In
nformation iss evaluated against a
third party suppoort, such as iinvoices or ffish tickets; internally‐
g
generated infformation, such as crew
w settlement sheets, gen eral ledger d
details, invoiices, detailed
d internal rreports, or fiinancial state
ements; and estimates made, m
includ
ding an asseessment of the reasonab
bleness of aassumptions. Supporting documentattion for intern
nally‐generatted spreadsh
heets is requeested on a judgmental b
basis. AKT also notes whe
en no supportt is available t
to evaluate thhe informatio
on.
M
Many of the r
records provided to AKT a
are unique, specifically fo r the vessels. The processsor reporting
g tends to b
be more form
mal and stan
ndardized, re
eflecting the large compaany nature o
of those opeerations. Beccause the m
material provvided is so unique, the au
udit process begins with a detailed rreview of eacch informatio
on packet rreceived whille comparing
g totals for each e
variable
e to the origiinal EDR enttry. Each supporting doccument is aassessed for a
accuracy and depth of sup
pport. Estimaates are acceppted as long a
as a reasonab
ble explanation and/or ccalculation arre also provid
ded. Handwritten stateme
ents are also considered a
adequate, bu
ut only after d
discussion w
with the EDR preparer and
d requests forr additional su
upport. A
AKT places phone p
calls to
o all submitte
ers with estim
mates and haand written sstatements. AKT also validates all vvariables thatt are reported
d with no valu
ue (blank) or a
a zero value. If discrepanccies are found
d between th
he original E
EDR submissiion and the supporting do
ocumentation
n, AKT contaccts the vessel owner and/o
or preparer to
o validate tthe correct re
eported value
e. Many time
es this leads to receiving further docuumentation ffrom the vesssel and/or ffurther explan
nation as to t
he methodology used to r
report EDR vaalues. ort is missing for a Iff the initially provided doccumentation is determined to be insuffficient support, or if suppo
ccertain variab
ble, AKT contacts vessels t
to ask for furtther documenntation. Once documentaation is receivved, it is aassessed and validated viaa the process described above. 4 SUPPO
ORT CLASSE
L
ES A
AKT worked j ointly with PSMFC and NM
MFS to develop the follow
wing classificaations to desccribe audit evvaluations aand summarizze the resultss of the audite
ed values. Validation Code
e ‐ Is original va
alue Is audited value Original Value
e substantiatted? substantia
ated?
Correction
Valida
ation Code ‐ Aud
dit Value
1
Yes
Yes (sam
me)
Natu
ure of Reporting
g Error
s clearly No error; reported value is
substantiated by complete records
No
1
1T
Yes
yes (sam
me)
Original v
value is blank, or N/A
No
1
2
Yes
Yes (sam
me)
Calculatio
on error
Yes
1
2T
Yes
Yes(sam
me)
Typograp
phical Error
Yes
1
3
Yes
Yes
1
4
Yes
Yes
4
5
Yes
No
5
6
Yes
Yes
1
7
No
No
7
8
No
Misinterpretation of questtion
nal Estimate is based on origin
documen
ntation but flawed assumptio
on/logic
Yes (sam
me)
Data cann
not be reported p
precisely as specified in EDR form and
d must be estimated
d; estimate is based on appropriaate documentatio
on and sound asssumptions/logic and is considereed validated Yes (sam
me)
value was reporteed correctly Original v
based on original documeentation, but corrected based on up
pdated ntation
Yes (updaated) documen
Reported value is "best gu
uess"; value is not derived from record
ds
No
Original v
value is unsubstantiated; correction
n based on new documen
ntation
Yes (new
w)
Yes
1
Yes (sam
me)
9
No
No
No data r
eported
10
No
No
Item "Nott Applicable" to v
vessel
5 Yes ‐ "Corrected Vallue is ‐9"
9
Yess ‐ "Corrected Value is ‐7"
10
CATCH
HER VE
ESSEL ‐ AUDITT CODEE ANA
ALYSIS T
The records o
of 21 catcher vessels were
e requested, and 19 were received. Tw
wo catcher vvessels were g
granted a rreprieve due t
to the medicaal hardship of the EDR pre
eparer. In thee current yeaar, four vessels selected fo
or random aaudit did not require follow
w‐up informaation requestss. All other caatcher vessells complied w
with AKT’s req
quests for aadditional sup
pport.
A
AKT analyzed
d the audit co
odes assigned
d to each of the vessels in
n order to do
ocument consistent errorss for each vvariable, along with the reasoning behind the error.
T
The total num
mber of audiit codes posssible was dettermined by the numberr of EDR variiables requessted from sselected vesssels. 19 catcher vessels submitted information for 8 itemss, totaling 1152 audit codes. The d
distribution o
of those auditt codes is sum
mmarized bellow. Where a
appropriate, examples of situations caausing the rreporting erro
ors are included. 6 Non‐Error Audit Codes
Of the twelve possible audit codes, four do not represent actual errors. These codes are:
 1‐1  5‐5  1T‐1  10‐10 The four non‐error audit codes comprise 72.4% of all catcher vessel audit codes used, with 1‐1, 1T‐1 and 5‐5 claiming 59.87%, 8.55%, and 3.95% respectively. Audit code 1T‐1 was used most frequently in EDR Section 5.1 – Cost for BSAI Crab Fishing Only when vessels did not purchase any line and other gear, bait, or pay crab harvest cooperative fees throughout the year. Audit code 5‐5 was used most commonly in reference to fuel purchases reported in Section 5.1 – Cost for BSAI Crab Fishing Only. These vessels typically track either fuel cost or fuel gallons, and arrive at the other measure using an average fuel cost per gallon.
Audit code 10‐10 was not used.
Error Audit Codes AKT analyzed the following results for the remaining audit codes, which are used to categorize errors:  2‐1  6‐1 
2T‐1 
7‐7 
3‐1 
8‐1 
4‐4 
9‐9 Audit code 3‐1 was documented 9.21% of the time. The most common sources of misunderstanding the question related to:
 Section 4.1 – Crab Harvesting Labor Costs. Vessels reported earnings before crew‐related expenses, rather than net of food and other shared expenses as instructed in the EDR.  Section 6.0 – Labor Costs. Vessels were unclear on what figure should be reported here, resulting in the reporting of only BSAI labor or all labor other than BSAI labor. Additionally, vessels were unsure of whether to deduct food and other crew‐related expenses from the amount reported (see note on Section 4.1 – Crab Harvesting Labor Costs above). Audit code 8‐1 was the error code used most frequently at 15.13%. This audit code was documented across all variables and indicates that the vessel’s original submission was incorrect, but that adequate documentation was provided to support the revised value. In some instances the vessels acknowledged the original error, and in others AKT determined the existence of the error based upon the audit information provided and conversations with the vessels. Anecdotal evidence suggests that vessels do not always thoroughly review their records to report an accurate EDR number initially, and only revise the figures when forced to look more closely at their own data to produce auditable support for AKT.
Four additional audit codes appeared in a fraction of the catcher vessels: calculation errors (2‐1) at 0.66%, typographical errors (2T‐1) at 1.32%, values updated for new information (6‐1) at 0.66%, and “best guesses” not derived from records (7‐7) at 0.66%.
Audit codes 4‐4 and 9‐9 were not used. 7 PROCEESSOR
R AUDIIT COD
DE ANA
ALYSIS
S T
The records of ten proce
essors were requested, and a
ten packkets were reeceived. In tthe current yyear, two p
processors se
elected for raandom auditt did not req
quire follow‐uup informatio
on requests. All other p
processors ccomplied with
h AKT’s reque
ests for additional supportt. A
AKT analyzed
d the audit co
odes it assign
ned to each o
of the proces sors in orderr to documen
nt consistent errors for eeach variable,, along with t
the reasoning
g behind the e
error.
T
The total num
mber of audiit codes posssible was dettermined by the numberr of EDR variiables requessted from sselected proccessors. Nine
e shoreside/ffloating proce
essors subm itted informaation for 3 ittems and one catcher p
processor sub
bmitted inforrmation for 8
8 items, totaling 35 audit codes. The d
distribution o
of those audit codes is ssummarized b
below. A
Audit code 1‐1 was used m
most extensivvely, accountting for 80.000% of variables tested. Th
his high rate attests to tthe quality of o data subm
mitted by the
e processorss and is an iindication off the larger operations aand more ssophisticated record‐keeping practicess of processorrs as compareed to catcher r vessels. A
Audit code 5‐5 5 appeared
d 8.57% of th
he time, mosst often in reelation to the Total Processing Labor r Payment vvariable in Seection 3.1 – Crrab Processin
ng Labor Costts. Because t
the same stafff perform prrocessing acttivities for m
many types o
of products, t
these processsors use alloccation bases,, such as dayys processing or percent o
of pounds p
processed, to estimate lab
bor costs for e
each fishery. A
Audit codes 1
1T‐1, 3‐1, and
d 7‐7 also app
peared, accou
unting for 5.771%, 2.86%, a
and 2.86% respectively. In total, non‐e
error audit co
odes (1‐1, 1T‐11, 5‐5, and 10
0‐10) compris ed 94.3% of p
processor aud
dit codes useed. 8 OUTLIIER AUDIT U
CODE ANALYYSIS N
Nine vessels a
and six processors were se
elected for ou
utlier audits t
through the N
NMFS analysis process described in tthe Methodology section of the reportt. AKT receivved support f
for the uniquue variables id
dentified by NMFS for eeach of the 15 1 vessels/pro
ocessors sele
ected. In the
e current yeaar, nine vessels and/or prrocessors sellected for o
outlier audit d
did not require additional requests. All other outlieers complied with AKT’s r
requests for a
additional ssupport.
A
AKT analyzed
d the audit co
odes it assigned to each off the outliers in order to document con
nsistent errors for each vvariable, along with the reasoning behind the error.
T
The total num
mber of auditt codes possib
ble was determined by thhe number off EDR variablees requested from the o
outliers, totaling 23. The d
distribution of those audit codes is sum
mmarized belo
ow. A
Audit code 1‐1 was used s
slightly more
e than half of the time, at 52.17%, with
h overall non‐‐error codes (
(1‐1, 1T‐1, 55‐5, and 10‐10
0) totaling 56
6.5%. This we
ell‐supported
d rate is signifficantly less t
han that of v
vessels and prrocessors, aat 73.0% and 94.3% respectively. Give
en that outlier selections a
are based up
pon submissio
ons identified
d as being aanomalous, th
he decreased
d rate of support is reasonaable.
A
Audit code 2T
T‐1, accounted for 21.74%
% of codes ussed, and was used most frrequently in E
EDR Section 5
5.1 – Cost ffor BSAI Crabb Fishing Onlyy. Most of th
hese errors arrose from thrree vessels ow
wned by the same compaany, all of w
which mistakenly recorded
d Crab Landin
ng Taxes and Fees in the fieeld for Crab H
Harvest Coopeerative Fees.
A
Audit code 8‐1 was used 113.04% of the
e time, and sp
pans a varietyy of variabless. The audit c
code indicatees that the vvessel’s origin
nal submissio
on was incorrect, but that adequate documentattion was pro
ovided to sup
pport the rrevised value. In many insstances this a
audit code is indicative of carelessnesss by the subm
mitters when preparing tthe initial EDR
R. A
Audit codes 2
2‐1, 3‐1, and 5‐5 appeared
d in a fraction
n of outliers, a
at 4.35% each
h.
9 AUDITT VARIABLE ANALY
YSIS In addition to
o assessing th
he distributio
on and use of o the variouss audit codess, AKT analyzzed the EDR variables w
which were m
most frequenttly not suppo
orted by direcct documentaary evidence. This lack of support inclu
udes both eerrors and the
e necessary use of estimattes. C
Catcherr Vesselss
A
AKT identified three variables v
wh
hich received
d unsupportted audit ccodes in grreater than 30% of instances. Vessels were unable to substantiate s
these variab
bles resulting in either errors or th
he use of eestimates. A summary of those variables is provided
d below. N
Nearly one‐third of vesse
els received an unsupported audit coode for Total Labor Paym
ment to Harvvest Crew (Section 4.1). This rate of unsubstantiaation owes prrimarily to a m
misunderstan
nding of the q
question; nam
mely, that vvessels are no
ot reporting c
crew labor paayments net of food and o
other shared crew expensses. Placing a
additional eemphasis on t
this point in t
the EDR instructions may be valuable i n the reduction of future e
errors for thiss variable.
T
The variable f
for Fuel, Lubrrication, and Fluids Used i
in BSAI Crab Fishery (Secttion 5.1) elicitted unsupporrted audit ccodes for 47%
% of vessels. Five of these
e unsupported
d codes relatte to reasonable estimates. The estimates used ttook a couple
e of different forms; two v
vessels had to
o estimate thhe number of f gallons used
d in the fisherry, usually b
by dividing th
he total fuel cost as reco
orded in their accountingg system by the market price per galllon. This p
practice suggests that vessels are failing to retain ap
pplicable fuell invoices, and
d are thus forrced to rely exclusively o
on their accou
unting record
ds, which do n
not always include detail r
regarding galllons purchassed. Two other vessels eestimated the
e cost of fuel used in the f
fishery by mu
ultiplying the amount of fuuel used, as m
measured by the crew, b
by the market price of fue
el. The fifth v
vessel relying on estimate s for this variable estimatted the amou
unt of fuel u
used in non‐ccrab activitie
es and subtraacted that am
mount from the annual ffuel cost to aarrive at the reported aamount. Ove
erall, vessels had difficultty determinin
ng exactly h ow much fuel was consu
umed in each fishery, leeading to the
e extensive usse of estimate
es and numerous errors.
FFinally, the To
otal Labor Co
osts (Section 6
6.0) variable w
was unsuppoorted in 58% of instances.. In many casses, these eerrors were the result of vessels misunderstan
m
nding what labor costs should be reported under this vvariable. Som
me vessels reported only B
BSAI crab fishing labor coosts, while otthers reporteed all labor co
osts other tthan those fo
or BSAI fishing. Whether o
or not to included shared crew expensses like food, which are exxcluded in S
Section 4.1, was w also identified as a source of co
onfusion. Fu rther clarification of the data needed for this vvariable migh
ht prove ben
neficial. Additionally, ane
ecdotal evideence derived
d from conveersations witth vessels indicates thatt the annual totals requirred in this secction are diffficult to com
mpile, thus contributing to
o the high eerror rate.
C
Catcher/
r/Shoresside/Floa
ating Prrocessorrs
A
As noted in th
he Processor Audit Code A
Analysis section, the qual ity of submisssions was very high, with 80.0% of vvariables rece
eiving a 1‐1 au
udit code. Acccordingly, an
nalysis of freqquent errors i s not materiaal to the processors. 10 BURDEEN HOUR O
ESTIMAT
S
TE A
As a result off its analysis a
and contact w
with the vesssels and proc essors selectted for audit, AKT asked a
all vessels den hours) to
aand processors to provide information regarding th
he time comm
mitment (burd
o prepare orig
ginal EDR ssubmissions f
for PSMFC an
nd to prepare submissions for AKT. C
Catcherr Vesselss
A
A summary off the burden hours estimaated by the re
esponsive vesssels is included below. No
ote that 17 veessels p
provided estim
mates as to t
he amount off time taken t
to prepare thhe initial EDR,, while 13 pro
ovided estimaates for tthe time spen
nt preparing s
supporting materials for vaalidation. E
Estimates reg
garding the time required for catcher vessels to com
mplete the oriiginal EDR su
ubmission ran
nged from ttwo hours to one month, with 53.3% placing the burden b
at or below 20 ho
ours and 46.77% at greateer than 20 h
hours. E
Estimates reg
garding the amount a
of tim
me needed to t compile doocumentation for AKT affter being sellected for aaudit ranged from one ho
our to a weekk and a half, with 84.6% of vessels sp
pending less tthan ten hou
urs on the p
process and 1
15.4% spendin
ng more.
A
Additional co
omments pro
ovided by vessels expresssed general d
dissatisfactio
on with the w
workload and
d level of d
detail required by the EDR
R. Specificallly, vessels exxpressed thatt the annual t
totals requireed by Table 6
6 – Annual T
Totals for All F
Fisheries are t
the most tim
me‐consuming
g and difficultt figures to compile. Furtthermore, theey believe tthe questionss in this table are unduly in
nvasive in that they are no t directly relaated to crab a
activity.
C
Catcher/
r/Shoresside/Floa
ating Prrocessorrs
A
A summary of o the burden
n hours estim
mated by the
e responsive processors iis included b
below. Note that nine p
processors prrovided estim
mates as to th
he amount off time taken t
to prepare th
he initial EDR
R, while eightt provided eestimates for the time spent preparing supporting m
materials for v
validation.
E
Estimates reg
garding the tiime required for processo
ors to compleete the original EDR subm
mission ranged
d from six h
hours to 40 hours, with the distribution
n of processo
ors taking lesss than and m
more than 20 hours resembling that o
of vessels, at 55.6% and 44
4.4% respectively.
11 Estimates regarding the amount of time needed to compile documentation for AKT after being selected for audit ranged from a half‐hour to eight hours, with 75.0% of processors spending five hours or less.
The processors also included comments emphasizing that in addition to the time directly spent preparing the EDR, 50 to 60 hours are required throughout the year to maintain systems and files solely for EDR reporting purposes.
See Appendix B for detailed results of burden hour inquiries.
12 COMM
MENDA
ATION A
AKT worked c
collaboratively with memb
bers of the PS
SMFC and NM
MFS staff and
d would like t
to thank them
m for their ccommitment and time. Name
N
Organizatiion
Dave Colpo D
Pacificc States Marinne Fisheries C
Commission Geana Tyler G
Pacificc States Marinne Fisheries C
Commission Brian Garber
B
r‐Yonts Nation
nal Marine Fissheries Servicce Audit particip
A
pants Individ
dual vessels a
and/or processsors 13 CONCLLUSION T
The 2011 ED
DR yielded a high respon
nse rate from
m all catcherr vessels and
d catcher, flo
oating, and shoreside p
processors. T
The vessels that contained errors on t
their submisssions were co
orrected easily by contactt with the d. vvessel or by th
he addition of new information to subsstantiate the data reported
A
AKT appreciates the opportunity to wo
ork with PSMFC and NMFS
S staff. This collaborativee relationship
p is critical tto AKT’s success in comple
eting this yeaarly audit. 14 APPEN
NDIX A A
S
Statisticcal Sam
mple
In order to determine an appropriate sample size as the basiss of selection
n for the random audits, the main ccriteria to con
nsider are the
e level of preccision desired
d, the level of f confidence o
or risk, and th
he degree of v
variability in the attributtes being meaasured. Thesse elements a
are defined ass follows: 
Level of Precision – A
P
lso referred t
to as the margin of error, t
this is the ran
nge in which t
the true poin
nt value of the population is estim
mated to be. T
This is expresssed as a perccentage ± thee true value (ee.g., ± 5%). Th
hus, if it is found fro
om the samp
ple that on average 15%
% of the fishherman did n
not submit d
data then is could be concluded
d, that for the
e total populaation, betwee
en 10% and 220% of the fisherman havee not submittted data. 
Confidence Level – Th
he degree to which we are
e certain thatt a result, or estimate, ob
btained from the study includes t
the true popu
ulation percentage, when the precisionn is taken intto account. In
n a normal distribution 95% of th
he sample vaalues are with
hin two stand
dard deviatioons of the truue population value. If 10
00 vessels were sam
mpled 95 woulld have the trrue population values withhin the range specified. 
Degree of
o Variability
y – This me
easures the variability w
within the p
population (ee.g. Catcherr Vessels, Catcher/P
Processor Ve
essels, Shorre/Floating Processors, P
Large Vesssels, Small Vessels). The more heterogen
neous a popu
ulation, the larger the sam
mple size reqquired to obttain a given llevel of preciision. The more hom
mogenous a population the t smaller the t sample s ize required.. A variabilityy of 50% signifies the greatest v
variability. D
Due to the vaariability within the industry and the vaariability of thhe data being
g analyzed, th
here is not on
ne specific vvariable that can be used t
to create a sttatistical mod
del that woulld enable AKT to calculatee a standard deviation aand regressio
on analysis fo
or the projecct. This fact places p
the prroject in a sim
milar category as a questionnaire, p
political poll, surveys, and extension program impaccts. W
While there are no statisstical analyse
es that can be applied d
directly, therre are similar projects th
hat derive sstatistical sam
mpling metho
ods relating t
to extension program imppact. In thesee projects the samples arre used to eevaluate a chaange made to
o the extensio
on programs. T
The sampling
g formulas derived for such
h projects and to ensure a
a statistical baasis for the saamples choseen are the ffollowing: n
Z  p q  n 
n 

n  1
1
e 2
N
2
0
0
0
n0 = Sample size n = Sample
e size with fin
nite populatio
on correctionn for proportio
ons Z = The nu
umber of stan
ndard deviatio
ons a point x is from the m
mean; is a scaled value p = Populaation variability q = 1 – p e = The de
esired level off precision N = Total p
population FFor this projecct p (variability) equals .5 t
to account fo
or maximum v
variability in t
the populatio
on. 15 This type of sampling methodology takes into account errors and missing information in the data. The precision level quantifies the tolerable level of error based on the sample size. This error level is then projected to the total population. The samples were stratified based on the proportion of the group versus the total population. The reasoning behind this is that by sampling each individual population there would be no statistical basis for both the Catcher/Processor and Stationary/Floater Processors. The only way to have a statistical basis for this population would be to census the population. Because this is not a reasonable approach, AKT suggested that the population include all groups and then additional random audits be performed for the Catcher/Processor and Stationary/Floater Processor populations. The sample population was ultimately chosen based upon a 95% confidence level with 15% precision and variability of 50% (due to the variability of the information requested). This method ensures the data are correct (outlier audits) and provides a process to measure the quality of data (random audits). This sampling method provides a statistical basis for future studies and gives the agencies a basis to measure the accuracy of the population data. 16 APPEN
NDIX B B
T
Time Bu
urden Esstimatess
T
Time burden estimates forr each respon
ndent are sum
mmarized below:
17