evaluation of observer‐ and industry‐based catch data in a

126 | wileyonlinelibrary.com/journal/fme Fish Manag Ecol. 2017;24:126–138.© 2017 John Wiley & Sons Ltd

DOI: 10.1111/fme.12210

O R I G I N A L A R T I C L E

Evaluation of observer- and industry- based catch data in a recreational charter fishery

C. A. Gray1 | S. J. Kennelly2

1WildFish Research Consultancy, Grays Point, NSW, Australia2IC Independent Consulting, Cronulla, NSW, Australia

CorrespondenceCharles Gray, WildFish Research Consultancy, Grays Point, NSW, Australia.Email: [email protected]

Funding informationAustralian Fisheries Research and Development Corporation; NSW Recreational Fishing Trust; NSW Marine and Estuarine Recreational Charter Trust.

AbstractThere is international recognition for greater inclusion of recreational fisheries catch data in species, fisheries and ecosystem assessments. Recreational charter fisheries provide important social services and contribute to total species catches. This study compares and validates industry logbook catch and effort data (1,357 trips) against observer data (154 trips) across six ports in a recreational charter fishery in eastern Australia. The mean numbers of clients and fishing effort (hours) per trip varied incon-sistently between data sources and among ports. Logbooks did not adequately report released catches, and the mean number of species retained per trip was consistently underestimated in logbooks compared to observer data. For both data sources, catch rates of total individuals and key species displayed similar trends across different units of effort; catch per hour, client, client/hour and trip. The mean catch rates of total in-dividuals and most key species, except those retained for bait, were similar across data sources, as were estimates of total fleet harvests. The length compositions of retained catches of some key species displayed truncation of larger organisms in the observer data whereas other species did not. Despite the shortcomings of the logbook data, future fishery and species monitoring strategies could include industry and observer data sources.

K E Y W O R D S

fisheries management, fishery-dependent data, logbook, monitoring strategy, observer survey, recreational fishing

1 | INTRODUCTION

Recreational fisheries provide important social and economic contri-butions to many communities (Aas, Arlinghaus, Ditton, Policansky & Schramm, 2008; Barrella et al., 2016; Pitcher & Hollingworth, 2002; Solstrand, 2013), and there is growing acknowledgement that they are the major harvest sector of many organisms in freshwater and marine environments across various regions throughout the world (Arlinghaus et al., 2016; Coleman, Figueira, Ueland & Crowder, 2004; Cooke & Cowx, 2006; Ihde, Wilberg, Loewensteiner, Secor & Miller, 2011; McPhee, Leadbitter & Skilleter, 2002). Consequently, there is

now greater recognition of the real and potential impacts of recre-ational fishing on species and ecosystems (Font & Lloret, 2014; Ihde et al., 2011; Lewin, Arlinghaus & Mehner, 2006; McPhee et al., 2002; Post et al., 2002; Sheaves et al., 2016). As such, there is considerable awareness of the need for greater inclusion of data on recreational fisheries in species, fisheries and ecosystem assessments (Arlinghaus et al., 2016; Beard et al., 2011; Cooke & Cowx, 2006; Ihde et al., 2011).

Pay for hire recreational charter fisheries operate in most indus-trialised and many transitioning and developing countries and provide specific services to anglers, ranging from one- on- one guiding experi-ences to larger group fishing expeditions that can last from a couple of

mailto:[email protected]

| 127GRAY And KEnnELLY

hours to several days (McEachron & Matlock, 1983; Motta, Mendonca & Moro, 2016; Savolainen, Fannin & Caffey, 2014; Solstrand, 2013). Moreover, such operations can specifically target singular iconic species or a diverse range of species across a plethora of habitats (Motta et al., 2016; Pradervand & Van der Elst, 2008). Depending on fleet sizes, client numbers and local regulations, such enterprises can harvest significant quantities of species across a hierarchy of spatial scales (Dell’Apa et al., 2015; Greiner & Gregg, 2010; Lew & Larson, 2016; Pradervand & Van der Elst, 2008; Vølstad et al., 2011). Sampling strategies that deliver reliable, quantitative catch and socio- economic data are required for the management of viable, resilient and sustain-able charter fisheries.

Fishery- dependent data sources such as log books, interviews and questionnaires from operators are commonly used to obtain catch and economic information in charter fisheries (Dell’Apa et al., 2015; Lichtkoppler, O’Keefe, Lucente & Gabriel, 2015; Ryan, Trinnie, Jones, Hart & Wise, 2016). As in many commercial fisheries, these data are often used as the primary sources of information to monitor changes in catch compositions, rates (catch- per- unit- of- effort [CPUE]) and total harvests of species (Cotter & Pilling, 2007; Hilborn & Walters, 1992). Such data are often problematic and can be of limited value in assessments and management deliberations due to their often- prescribed limitations and biases (Cotter & Pilling, 2007; Rotherham, Underwood, Chapman & Gray, 2007). Moreover, some client groups often question the validity and reliability of industry- reported catch data in fisheries assessments and management (Hoare, Graham & Schon, 2011). As such, there is a need to validate such data using in-dependent sources, and one of the most pertinent and well- accepted ways to do this for logbook catch data is to use a scientific observer programme (Uhlmann et al., 2014).

In this study, the catch data obtained from industry logbooks and an independent observer programme in an Australian charter fish-ery are compared in terms of their value and cost- efficiencies for fu-ture population and fishery monitoring and assessment. Differences between data sources in species composition, and catch rates and length compositions of some key species are specifically exam-ined. This study serves as a model for the development of fishery- dependent data sampling strategies in other recreational charter fisheries.

2 | METHODS

2.1 | Fishery

The New South Wales (NSW; South- east Australia) coastal recrea-tional charter boat line fishery has 276 endorsements with registered vessels ranging between 10 and 30 m. Charter vessels operate out of 36 ports and typically carry between 8 and 15 fishing clients (the ac-tual maximum number of clients per individual boat is determined by survey regulations) and undertake day trips of up to 8- hr duration, but the actual times are dependent on client requirements, weather and fishing conditions. Vessels generally target demersal fish by drifting across fishing grounds between 10 and 130 m deep, but some vessels

anchor when targeting specific shallow reef locations. Substratum types vary from bare sand to complex reef and reef/gravel habitats and their combinations. The locations and habitats fished often vary within each trip. The fishing gears used by clients are mostly provided by the operators, with rod and non- electric reels combined with a Paternoster hook (maximum two hooks) and sinker rig most common. Bait usually consists a mixture of frozen squid, fish and shrimp but is often supplemented with fresh fish caught in situ. Operators often also tow surface lures to and from demersal fishing grounds targeting seasonal pelagic species.

Several “primary” fish species in this fishery have mandated min-imum legal lengths (MLL) that dictate whether each individual fish caught is retained or released. By contrast, many other secondary species have no length prescriptions so the choice of whether they are retained or released is determined by client and operator pref-erences—which can vary among individuals on a vessel and change throughout a trip. Several primary species also have maximum catch limits per trip, but each vessel has a total catch endorsement that cov-ers all clients.

2.2 | Data sources

The comparison of industry logbook and observer catch and effort data covered six ports (Wooli, Coffs Harbour, Sydney, Port Hacking, Kiama and Shoalhaven) for the period 1 December 2014 to 30 November 2015. For the logbook data, charter operators are man-dated to provide for each fishing trip the type and general location of fishing, the numbers of clients and hours fished, as well as the num-bers of each species (or species complex) retained (including those used for bait). Operators also have the option to record information on released catches if they desire. The logbook data were supplied by the NSW Department of Primary Industries and included catch and effort data for each trip (without vessel identification) per study port over the 1- year period. The corresponding independent catch and effort data were obtained by scientific observers who accompanied regular charter trips where they identified, counted and measured (nearest cm) each retained and released organism and recorded op-erational information including the number of clients, fishing times, depth, bottom topography (as determined by the operator), fishing gear, bait types, and general weather and sea conditions. Observed trips were selected at random among participating vessels and days within each port for each season.

Across the six ports, data from a total of 1,357 completed logbooks (individual trips) and 154 observed trips were available for comparison. As the logbook data only included information on released catches for 122 trips (Coffs Harbour—43, Sydney—56, Port Hacking—1, Kiama—3, Shoalhaven—19) that yielded 161 released individuals, the compara-tive analyses between the two data sources were only performed for the retained catch component. Industry- generated length compo-sition data of retained catches recorded on logbooks for the period 2001–2003 were used to compare with the retained catch length compositions from the observer data. Data across all ports were com-bined for these comparisons.

128 | GRAY And KEnnELLY

2.3 | Data analyses

Differences between the two data sources and across the six ports in the numbers of clients and fished hours, the catch rates (i.e. CPUE; number caught per unit of effort) of total species, total individuals and of key species, were examined using permutational analyses of variance (PERMANOVA; Anderson, Gorley & Clarke, 2008). In each analysis, the term data source (i.e. logbook vs. observer) was consid-ered a fixed factor and port a random factor. Each univariate (i.e. ef-fort and catch rates) analysis was based on the Euclidean distance measure with Type III (partial) sums- of- squares calculated using 9999 unrestricted permutations of the raw data (Anderson et al., 2008). Where appropriate, separate pairwise comparisons using the PERMANOVA interactive effects routine were subsequently used to determine across which ports the logbook and observer data signifi-cantly differed. All analyses were performed using the Primer 6 and Permanova+ programs (Anderson et al., 2008).

Estimated total annual harvests of total individuals and key species for the period 1 December 2014 to 30 November 2015 were deter-mined for each port for the logbook and observer data. For logbooks, this was performed by summing all submitted catches for the selected period, whereas for the observer data, the mean observed catch per trip data (+SE) for each port was appropriately scaled to the total num-ber of reported fishing trips for each port and across all ports com-bined for the selected annual period.

3 | RESULTS

3.1 | Fishing effort and client numbers

The mean number of clients and fished hours significantly differed according to the interaction of data source and port (df = 5, 1499; p < .001 in both cases). The pairwise comparisons identified that the mean number of clients per trip was significantly greater for the observer than the logbook data for Sydney, Port Hacking and Shoalhaven, but did not differ between data sources for the other three ports (Figure 1). By contrast, the mean hours fished per trip was greater for logbooks than observed trips across all ports, except Port Hacking (which did not differ between data sources; Figure 1). The mean observed total trip length differed significantly among ports and ranged from 1 to 3 hr greater than observed fishing time (Figure 1).

3.2 | Catch composition

A total of 109 taxonomic/species complexes were recorded as being retained in industry logbooks (n = 1,357 trips), and in comparison, ob-servers identified 85 retained species across the 154 trips (Table 1). Greater total numbers of species were reported in logbooks for Sydney, Port Hacking and Kiama, but the opposite was evident for the Shoalhaven. Similar total species numbers were reported across both data sources at Coffs Harbour. Differences between data sources in total species numbers were mostly attributable to spe-cies/groups that occurred in low numbers (i.e. infrequently caught).

Moreover, the logbook data included a number of “other” (e.g. flat-head [Platycephalidae] other, leatherjacket [Monacanthidae] other) and combined taxonomic/species groupings (e.g. tailor [Pomatomus saltatrix (L.)] and salmon [Arripis trutta (Forster)], yellowtail scad [T. novaezelandiae Richardson] and jack mackerel [Trachurus declivis (Jenyns)]) that did not exist in the observer data.

Six species—grey morwong, bluespot flathead, snapper, ocean leatherjacket, redfish and silver sweep—were the most commonly re-tained species across both the logbook and observer data, contrib-uting 67% and 61% to total logbook and observed retained catch. Similarly, the ten most numerous retained species contributed 79% and 76%, and the top twenty 91% and 89%, towards the total logbook and observed total retained catch, respectively (Table 2).

3.3 | Catch rates

For both data sources, the mean catch rates (i.e. catch- per- effort- unit) of total individuals and the three key species (snapper, grey morwong and bluespot flathead) displayed the same results across the four units of fishing effort (i.e. catch per: trip, client, hour and client/hour;

F IGURE 1 Mean (+SE) number of clients and fished hours per fishing trip for each port as determined from industry logbook and independent observer data sources

0

7

14

21

0

4

8

12

0

4

8

12

Clients

Fished hours

Trip length hours

Wooli

Coffs H

arbou

r

Sydne

y

Port H

ackin

gKiam

a

Shoalh

aven

Mea

n nu

mbe

r per

trip

(+SE

)

Logbook Observer


Table 3). Differences between ports in mean catch rates of total in-dividuals and the three key species were also similar across the four units of fishing effort (Figure 2). As these results indicated that all units of fishing effort displayed similar patterns, further analyses com-paring catch rates between data sources were performed at the catch per trip level.

Across all ports, mean catch rates per trip for some key species (snapper, grey morwong and bluespot flathead) did not differ signifi-cantly between the logbook and observer data (Table 4, Figure 3). For snapper and grey morwong, this trend was also consistent across seasons for the three ports examined (Table 5, Figure 4). By contrast, mean catch rates of blue mackerel were significantly greater for the observer than the logbook data across all ports, and similarly for ser-geant baker except for Wooli and Sydney where catches were very low.

Differences between data sources in mean catch rates for num-bers of total species and individuals and for some key species were not consistent across all ports (Table 4). Notably, the mean number of spe-cies retained was significantly greater for the observer than the log-book data for all ports except Sydney (where there was no difference). Similarly, the mean number of individuals retained per trip was greater for logbook data for Port Hacking and Shoalhaven, but the opposite was evident for Sydney and Kiama (Figure 3). Similar opposing trends in data sources were evident for bluespot flathead (Sydney vs. Port Hacking), ocean leatherjacket, redfish and tiger flathead (Port Hacking vs. Kiama; Figure 3).

Differences between data sources in mean catch rates of total species and individuals and for the three key species examined dis-played temporal consistency across each of the three ports examined (Table 5, Figure 4).

3.4 | Estimated total annual harvests

Summed across all six ports, a total of 49,028 individuals were re-ported as being retained in industry logbooks. In comparison, an es-timated scaled annual harvest of 48,337 individuals was obtained by scaling the observer data to total reported fishing effort (number of trips) for the same ports (Table 6). However, differences between data sources in reported and scaled total annual harvests were evident for individual ports. For example, the logbook and observer estimates of total individuals retained were similar for Wooli and Coffs Harbour, but were much greater for logbooks than for observer data for Sydney and Kiama, but the opposite pattern was evident for Port Hacking and Shoalhaven (Table 6).

Notable differences in reported and scaled total annual harvests of individual species were also evident across some ports; for exam-ple, (1) catches of most key species (except bluespot flathead, blue mackerel and silver trevally) were greater in logbooks than observer estimates for Sydney; (2) catches of several species including bluespot flathead, blue mackerel and silver trevally were much greater for ob-server estimates than reported in logbooks for Port Hacking; (3) total harvests of snapper were similar across all ports except Sydney, where 3× more were reported in logbooks than in observer estimates; (4) for T

ABLE 1

The

tota

l num

ber o

f log

book

and

obs

erve

d tr

ips,

tota

l num

ber o

f ret

aine

d sp

ecie

s an

d in

divi

dual

s an

d th

e av

erag

e nu

mbe

r of r

etai

ned

indi

vidu

als

per t

rip a

s re

port

ed in

indu

stry

lo

gboo

ks a

nd o

bser

ver d

ata

acro

ss e

ach

of th

e six

stu

dy p

orts

Logb

ook

Obs

erve

r

No.

trip

sTo

tal s

peci

esTo

tal i

ndiv

idua

lsIn

divi

dual

s per

trip

No.

Trip

sTo

tal s

peci

esTo

tal i

ndiv

idua

lsIn

divi

dual

s per

tr

ip

Woo

li12

643

4,42

935

.219

3560

531

.8

Coffs

Har

bour

151

304,

603

30.5

3129

933

30.1

Sydn

ey50

667

11,6

9523

.112

2315

713

.1

Port

Hac

king

296

6113

,005

43.9

4243

2,47

859

.0

Kiam

a18

343

11,0

9760

.637

361,

928

52.1

Shoa

lhav

en95

234,

199

44.2

1338

843

64.8

Tota

l1,

357

109

49,0

2836

.115

485

6,94

445

.1


TABLE 2

The

20 m

ost n

umer

ous

spec

ies

repo

rted

as

bein

g re

tain

ed in

indu

stry

logb

ooks

and

in o

bser

ved

catc

hes

and

thei

r per

cent

con

trib

ution

to th

e to

tal c

atch

of e

ach

data

sou

rce

Logb

ook

(n =

1,3

57)

Obs

erve

r (n

= 15

4)

Rank

Spec

ies

Tota

l num

ber

% T

otal

num

ber

Rank

Spec

ies

Tota

l num

ber

% T

otal

num

ber

1G

rey

mor

won

gN

emad

acty

lus d

ougl

asii

(Hec

tor)

7,70

015

.71

Oce

an le

athe

rjack

etN

elus

etta

ayra

ud92

713

.3

2Bl

uesp

ot fl

athe

adPl

atyc

epha

lus c

aeru

leop

unct

a-tu

s McC

ullo

ch6,

676

13.6

2Sn

appe

rPa

grus

aur

atus

897

12.9

3Sn

appe

rPa

grus

aur

atus

(For

ster

)6,

125

12.5

3G

rey

mor

won

gN

emad

acty

lus d

ougl

asii

718

10.3

4O

cean

leat

herja

cket

Nel

usett

a ay

raud

(Quo

y &

G

aim

ard)

5,67

211

.64

Blue

spot

flat

head

Plat

ycep

halu

s ca

erul

eopu

ncta

tus

679

9.8

5Re

dfish

Cent

robe

ryx

affini

s (G

ünth

er)

4,16

88.

55

Redfi

shCe

ntro

bery

x affi

nis

654

9.4

6Si

lver

sw

eep

Scor

pis l

ineo

lata

, Kne

r2,

401

4.9

6Si

lver

sw

eep

Scor

pis l

ineo

lata

375

5.4

7Ti

ger fl

athe

adPl

atyc

epha

lus r

icha

rdso

ni

Cast

elna

u2,

087

4.3

7Bl

ue m

acke

rel

Scom

ber a

ustr

alas

icus

361

5.2

8Ea

ster

n bl

acks

pot

pigfi

shBo

dian

us u

nim

acul

atus

(G

ünth

er)

1,42

32.

98

Oce

an p

erch

Hel

icol

enus

per

coid

es

(Ric

hard

son)

262

3.8

9So

uthe

rn fu

silie

rPa

raca

esio

xan

thur

a (B

leek

er)

1,19

12.

49

Serg

eant

bak

erH

ime

purp

uriss

atus

215

3.1

10Bl

ue m

acke

rel

Scom

ber a

ustr

alas

icus

Cuv

ier

1,13

12.

310

Tige

r flat

head

Plat

ycep

halu

s ric

hard

soni

203

2.9

11Ye

llow

tail

king

fish

Serio

la la

land

i Cuv

ier &

V

alen

cien

nes

1,04

12.

111

East

ern

blac

kspo

t pi

gfish

Bodi

anus

uni

mac

ulat

us18

32.

6

12Te

ragl

inAt

ract

osci

on a

equi

dens

(C

uvie

r)92

01.

912

Sout

hern

mao

ri w

rass

eO

phth

alm

olep

is lin

eola

tus

175

2.5

13Lo

ngfin

per

chCa

prod

on lo

ngim

anus

(G

ünth

er)

777

1.6

13Lo

ngfin

per

chCa

prod

on lo

ngim

anus

154

2.2

14So

uthe

rn m

aori

wra

sse

Oph

thal

mol

epis

lineo

latu

s (V

alen

cien

nes)

732

1.5

14Ye

llow

tail

scad

Trac

huru

s no

vaez

eala

ndia

e15

22.

2

15Se

rgea

nt b

aker

Him

e pu

rpur

issat

us

Rich

ards

on73

01.

515

Tera

glin

Atra

ctos

cion

aeq

uide

ns10

41.

5

16Si

lver

trev

ally

Pseu

doca

ranx

geo

rgia

nus

(Cuv

ier)

617

1.3

16Si

lver

trev

ally

Pseu

doca

ranx

geo

rgia

nus

991.

4

17O

rang

e pe

rch

Lepi

dope

rca

pulc

hella

(Wai

te)

362

0.7

17Ea

ster

n re

d sc

orpi

onfis

hSc

orpa

ena

jack

soni

ensis

St

eind

achn

er83

1.2

19D

olph

infis

hCo

ryph

aena

hip

puru

s (L

inna

eus)

345

0.7

18Lo

ngfin

sea

pik

eD

inol

este

s lew

ini

(Griffi

th)

781.

1

18Pe

arl p

erch

Gla

ucos

oma

scap

ular

e M

acle

ay33

10.

719

Barr

acou

taTh

yrsit

es a

tun

(Eup

hras

én)

600.

9

20So

uthe

rn s

and

flath

ead

Plat

ycep

halu

s bas

sens

is Cu

vier

329

0.7

20Pe

arl P

erch

Gla

ucas

oma

scap

ular

e57

0.8


bluespot flathead, total harvests were greater for logbooks for Port Hacking, but less in logbooks for Wooli, Sydney and Kiama; and sim-ilarly (5) total grey morwong harvests were greater for logbooks for Sydney and Kiama but not elsewhere (Table 6).

3.5 | Length compositions

The length compositions of retained catches of snapper, grey mor-wong, eastern red scorpionfish, sweep and ocean leatherjacket differed between data sources, with a greater proportion of larger in-dividuals recorded in logbooks (Figure 5). By contrast, the length com-positions of bluespot flathead, eastern blackspot pigfish, maori wrasse and teraglin were similar for both data sources (Figure 5). Notably, the sample sizes of measured fish were much greater for the logbook data.

4 | DISCUSSION

Comparative studies such as that performed here can help identify the suitability and cost- efficiencies of alternative data sources for de-veloping long- term fishery monitoring, assessment and management

strategies (Gray, 2016; Lunn & Dearden, 2006). In doing this particular study, several assumptions were required, which include the follow-ing: (1) the observed vessels and trips sampled were representative of the fleet in each port; and (2) operators did not change their habits of fishing and recording information on logbooks during the study period (Benoît & Allard, 2009; Faunce & Barbeaux, 2011; Liggins, Bradley & Kennelly, 1997).

The comparative analyses identified that the mean catch rates of total individuals and of most key species for the logbook and ob-server data were the same for each sampled port except Sydney—most likely due to the small number of observer trips available for this port. Moreover, both data sources revealed similar spatial differences among ports in total retained catch composition and catch rates of key species. These results suggest that industry logbook data could poten-tially be used as the primary source of longitudinal monitoring of catch rates (CPUE) of key species in this fishery. However, this study was performed only across one year and further examinations are required to assess interannual variability. Nevertheless, such data are commonly used in assessing and managing many commercial fisheries (Cotter & Pilling, 2007). This option would be a more cost- effective means of obtaining such data than utilising an ongoing large- scale, fleet- wide, observer programme. Moreover, data from only an appropriately strat-ified subset of reliable operators would be required for monitoring spatio- temporal trends in catch rates. Furthermore, such data would provide a means to incorporate industry- based recreational fisheries information in stock assessments of key harvested species, bearing in mind that the long- term provision of reliable industry- reported data depends on maintaining good industry- management relations. Development of a cooperative research programme in the fish-ery could help improve data quality and acceptance (Johnson & van Densen, 2007; Kaplan & McCay, 2004; Kraan, Uhlmann, Steenbergen, Van Helmond & Van Hoof, 2013).

For assessment purposes, it does not appear vital for either data source which unit of fishing effort (trip, client, hour) is used to deter-mine and examine trends in retained catch rates (CPUE) for key spe-cies. For most analyses, the coarsest unit of fishing effort was used (i.e. trip) as this was the least subjective (e.g. compared to reported num-bers of clients and hours fished—which differed inconsistently among ports for the two data sources). For example, the hours fished was cal-culated as that time between the start and end of fishing and included travel between different locations within this time band. Likewise, the number of clients that actually participated in fishing often varied throughout a trip as individuals had breaks, and often the number of clients actively fishing declined as the trip progressed. Moreover, such effort determinations do not account for each client’s fishing ability.

Total annual harvest determinations of total individuals and key species for each data source varied among ports. The precision of the scaled observer- based estimations was reliant on accurate and repre-sentative observed mean catch rates and reported total fishing effort data across the same unit of effort. Annual harvest determinations based solely on reported logbook data relied on the compliance of op-erators to supply both accurate catch and effort information. McIlgorm and Pepperell (2014) suggested that only about 50% of operators

TABLE 3 Summary of PERMANOVA’s comparing between data sources and among the six ports catch rates of the total numbers of retained individuals, snapper, grey morwong and bluespot flathead for each of the four units of effort (per trip, client, hour, client & hour)

Degrees of freedom

Data source (DS) Port (P) DS × P

1, 1499 5, 1499 5, 1499

Total individuals

Trip ns *** **

Client ns *** *

Hour * *** **

Client/hour ns *** ns

Grey morwong

Trip ns * ns

Client ns * ns

Hour ns * ns

Client/hour ns * ns

Snapper

Trip ns *** ns

Client ns *** ns

Hour ns *** ns

Client/hour ns *** ns

Bluespot flathead

Trip ns *** **

Client ns *** **

Hour ns *** **

Client/hour ns *** ***

*P < .05; **P < .01; ***P < .001; ns, P > .05.


comply with completing logbooks across the fishery and thus actual annual harvest levels could potentially be double that reported here. Increased compliance procedures and online reporting may facilitate greater uptake of completing logbooks.

The data presented provide evidence that large numbers of some species are harvested by the coastal charter boat fishery. Given that the study ports accounted for approximately a third of total fleet fishing effort, fleet- wide annual total catch estimates could poten-tially be triple that determined here; approximating 150,000 retained organisms. Whilst these quantities are considerably less than those taken in the coastal trailer boat fishery (West, Stark, Murphy, Lyle & Ochwada- Doyle, 2015), the charter fishery is an important contrib-uting component to total fishery harvests and mortality schedules of key species that needs to be monitored and reported (Wise, Telfer, Lai, Hall & Jackson, 2012).

Several aspects of the logbook programme require attention prior to its acceptance as a credible data collection strategy for fishery mon-itoring. Notably, the mean diversity of retained catches (i.e. mean num-ber of total retained species) was significantly less for the logbook than the observed data across all ports. This indicated that not all operators

F IGURE 2 Mean (+SE) catch of retained total individuals, grey morwong, snapper and bluespot flathead across different units of effort for each port as determined from industry logbook and independent observer data sources

0255075

05

1015

05

1015

05

1015

05

1015

05

1015

00.51.01.5

0123

0123

0123

0123

0123

0123

00.10.20.3

00.10.20.3

00.150.300.45

Total individuals Grey morwong Snapper Bluespot flathead

(b) Retained per client/trip

(c) Retained per fished hour/trip

(d) Retained per client/fished hour/trip

(a) Retained per trip

Logbook Observer

Wooli

Coffs H

arbou

r

Sydne

y

Port H

ackin

gKiam

a

Shoalh

aven

Wooli

Coffs H

arbou

r

Sydne

y

Port H

ackin

gKiam

a

Shoalh

aven

Wooli

Coffs H

arbou

r

Sydne

y

Port H

ackin

gKiam

a

Shoalh

aven

Wooli

Coffs H

arbou

r

Sydne

y

Port H

ackin

gKiam

a

Shoalh

aven

Mea

n ca

tch

rate

(+SE

)

TABLE 4 Summary of PERMANOVA’s comparing catch rates (per trip) of total numbers of retained species and individuals and the ten key species between data sources among the six ports

Degrees of freedom

Data source (DS) Port (P) DS × P

1, 1499 5, 1499 5, 1499

Total species *** *** ***

Total individuals ns *** **

Grey morwong ns * ns

Snapper ns *** ns

Bluespot flathead ns *** **

Ocean leatherjacket ns *** ***

Redfish ns *** ***

Silver sweep ns *** ns

Blue mackerel ** ** ns

Sergeant baker *** *** *

Tiger flathead ns *** ***

Eastern blackspot pigfish

ns *** ns

*P < .05; **P < .01; ***P < .001; ns, P > .05.


reported all species retained on each trip, most likely omitting those species deemed unimportant, and/or caught infrequently and in low numbers. This occurred even though total reported diversity of retained catches across the study was greater for the logbook than the observer data. This latter result was to be expected, given the far greater (×9) sample size of logbook trips compared with observer trips. Nevertheless, it is important for catch biodiversity monitoring that the numbers of all retained species be recorded for each trip. The current industry logbooks compound this situation due to the recording of

mixed species complexes and species amalgamations (as experienced in commercial fisheries—Uhlmann et al., 2014). Explaining the impor-tance of such information and the provision of species identification guides to operators could assist in rectifying this situation.

The mean catch rates of several important species, including those used for bait (e.g. blue mackerel and sergeant baker), were lower in log-books compared with the observer data. Organisms caught and used in situ as bait are an important component of retained catches (as in other recreational fisheries—West et al., 2015), and operators should

TABLE 5 Summary of PERMANOVA’s comparing catch rates (per trip) of total numbers of retained species and individuals and numbers of three key species between data sources across seasons and among three ports

df Total species Total individuals Snapper Bluespot flathead Grey morwong

Data source (DS) 1 *** ns ns ns ns

Port (P) 2 *** *** *** *** *

Season (S) 3 ns ns *** ** ns

DS × P 2 ns * ns * ns

DS × S 3 ns ns ns ns ns

P × S 6 ns * ns ** ns

DS × P × S 6 ns ns ns ns ns

Residual 716

df, degrees of freedom.*P < .05; **P < .01; ***P < .001; ns, P > .05.

F IGURE 3 Mean (+SE) catch of total species, total individuals and key individual species retained per fishing trip for each port as determined from industry logbook and independent observer data sources. Data pooled across all seasons

0

5

10

15

0

5

10

15

0

5

10

15

0

5

10

15

0

5

10

15

0

5

10

15

0

5

10

15

0

10

20

30

Total species

Ocean leatherjacket

Redfish

Silver sweep

Blue mackerel

Sergeant baker

Tiger flathead

Blackspot pigfish

Wooli

Coffs H

arbou

r

Sydne

y

Port H

ackin

gKiam

a

Shoalh

aven

Mea

n ca

tch

per t

rip (+SE

)

Wooli

Coffs H

arbou

r

Sydne

y

Port H

ackin

gKiam

a

Shoalh

aven

Logbook Observer


be encouraged to report their numbers accurately. For baitfish, this is potentially more difficult than for other retained organisms that can be counted at the end of the day’s fishing.

The logbook data are currently restricted to the numbers of each individual species/complex retained for each trip. If deemed neces-sary to monitor and report on released catches, there is the option to

either mandate that operators also record such information as part of the logbook programme, or use an independent observer programme (Gray & Kennelly, 2016). Whilst it would be cheaper to obtain such data directly from operators, it is probably an unrealistic and logisti-cally difficult task as it would need to be recorded ongoing throughout each fishing trip. In most circumstances, this would compromise the

F IGURE 4 Mean (+SE) catch of total species, total individuals and key individual species retained per fishing trip per season for three ports as determined from industry logbook and independent observer data sources. Su, summer; A, autumn; W, winter; Sp, spring

0

30

60

90

Su A W Sp Su A W Sp Su A W Sp

0

4

8

12


0

5

10

15


0

10

20

30


0

10

20

30


Total species

Total individuals

Snapper

Bluespot flathead

Grey morwong

Coffs Harbour Port Hacking Kiama

Logbook Observer

Mea

n ca

tch

per t

rip (+SE

)


TABLE 6

Repo

rted

logb

ook

and

scal

ed o

bser

ver e

stim

ated

tota

l ann

ual r

etai

ned

harv

ests

of k

ey s

peci

es a

cros

s ea

ch o

f the

six

por

ts fo

r the

per

iod

1 D

ecem

ber 2

014

to 3

0 N

ovem

ber 2

015

Woo

liCo

ffs H

arbo

urSy

dney

Port

Hac

king

Kiam

aSh

oalh

aven

Tota

l

Logb

ook

Obs

erve

rLo

gboo

kO

bser

ver

Logb

ook

Obs

erve

rLo

gboo

kO

bser

ver

Logb

ook

Obs

erve

rLo

gboo

kO

bser

ver

Logb

ook

Obs

erve

r

Tota

l ind

ivid

uals

4,42

94,

012

4,60

34,

545

11,6

956,

620

13,0

0517

,464

11,0

979,

536

4,19

96,

160

49,0

2848

,337

Gre

y m

orw

ong

7646

173

190

2,89

459

01,

922

1,87

52,

072

1,49

956

365

07,

700

4,85

0

Blue

spot

flat

head

1910

61,

754

1,79

71,

828

2,61

42,

129

402

166

406

780

680

6,67

66,

005

Snap

per

1,51

51,

592

1,31

51,

203

807

253

843

867

829

930

816

680

6,12

55,

524

Oce

an le

athe

rjack

et5

056

4483

242

2,86

15,

624

1,75

655

916

244

5,67

26,

313

Redfi

sh0

02

51,

024

169

1,27

52,

516

1,54

41,

266

323

263

4,16

84,

219

Swee

p17

925

915

569

533

710

110

689

293

051

990

62,

401

2,54

3

Tige

r flat

head

108

00

9779

142

545

1,07

864

312

90

222,

087

1,36

8

East

ern

blac

kspo

t pi

gfish

00

4168

284

8436

633

858

651

914

610

21,

423

1,11

2

Sout

hern

fusil

ier

1,19

129

80

00

00

00

00

01,

191

298

Blue

mac

kere

l2

4629

6342

295

513

853

457

608

8865

81,

131

2,52

4

Yello

wta

il ki

ngfis

h18

386

530

642

020

021

512

244

1,04

113

5

Tera

glin

352

6652

143

842

05

210

50

092

053

1

Long

fin p

erch

00

10

134

024

645

134

442

552

2977

790

6

Mao

ri w

rass

e0

01

011

916

914

049

266

351

206

680

732

1,24

9

Serg

eant

bak

er0

018

8316

30

252

662

271

401

2616

873

01,

314

Silv

er tr

eval

ly26

039

194

027

169

8342

2740

126

161

617

803

Oce

an p

erch

00

00

370

30

322

275

07

362

262

Dol

phin

fish

10

9512

724

50

47

00

07

345

141

Pear

l per

ch14

615

318

416

11

00

00

00

733

132

1

Sout

hern

san

d fla

thea

d0

00

00

070

025

90

00

329

0


primary duty of operators catering for their paying clients. This is an extra consideration not faced in self- sampling programmes in com-mercial fisheries (Hoare et al., 2011; Kraan et al., 2013; Lordan, Cuaig, Graham & Rihan, 2011).

Observers collected data on the lengths of retained and released species (Gray & Kennelly, 2016), which can be incorporated in species stock assessments. As part of the logbook programme, charter oper-ators previously recorded the lengths of some key retained species, which differed to the observer data for several of the species exam-ined. The reasons for these differences are not determinable, but could be due to a combination of fork and total length being measured by industry operators for some species, spatio- temporal variability, sys-tematic sampling biases (Hoare et al., 2011; Uhlmann, Bierman & van

Helmond, 2011) and length truncation among populations between the data collection periods (Stewart, 2011).

Whilst industry- recorded length data can be credible (Uhlmann et al., 2011), it may be difficult to reintroduce this data collection strategy in this fishery. Importantly, the collection of length data was abandoned in 2008 due to a combination of operator burden and management concerns that the data were not representative (although this was not actually tested). Whilst again it would be cheaper to obtain such data directly from oper-ators, it would probably prove to be a challenging management option with strong opposition from operators. Moreover, whilst these data could potentially be collected dockside upon completion of each trip, this again would generate opposition from operators as it would burden clients and mean they could not depart straight after disembarkation.

F IGURE 5 Length compositions of some key species as determined from industry logbook (2001–2003) and independent observer (2014–2015) data sources. nL, number measured logbook data; nO, number measured observer data

Eastern blackspot pigfish

Maori wrasse

Teraglin

Total length (cm)

Freq

uenc

y (%

)Ocean leatherjacket

nL = 25,891nO = 1157

nL = 17,325nO = 214

nL = 14,090nO = 168

nL = 7,389nO = 109

Bluespot flatheadnL = 32,889nO = 764

0

5

10

15

30 35 40 45 50 55 60 65

0

5

10

15

30 35 40 45 50 55 60 65 70 75

0

5

10

15

20 25 30 35 40 45 50

0

5

10

15

15 20 25 30 35 40 45 50

0

5

10

15

20 25 30 35 40 45 50 55 60

Sweep

Snapper

Grey morwong

Fork length (cm)

Freq

uenc

y (%

)

Eastern red scorpionfish

nL = 65,525nO = 1085

nL = 65,434nO = 862

nL = 3,993nO = 89

nL = 41,990nO = 425

0

5

10

15

20 25 30 35 40 45 50 55

0

5

10

15

15 20 25 30 35 40 45

0

10

20

30

15 20 25 30 35 40 45

0

5

10

15

20 25 30 35 40 45 50 55

Logbook Observer


The observer sampling also obtained additional finer detail infor-mation of catch, location, depth and habitat of each individual fishing event during each trip. Such information has important considerations for interpreting spatio- temporal variability in catches (Gray & Kennelly, 2016) and the spatial management of the marine ecosystem. Again, this type of information could be recorded by operators if required, but this would add another level of detail to logbooks that would most likely further overladen operators in data collection.

5 | CONCLUSIONS

This study identified that industry logbooks could be a credible source of information of obtaining total catches and catch rates (CPUE) of total individuals and key retained species for longitudinal monitoring and species assessments. Further research is required, however, to ascertain relationships between logbook CPUE and actual fish abun-dance. Nevertheless, the logbook data are problematic regarding di-versity of retained catches and appear to under report catch rates of species retained for bait. Whilst these issues can be rectified via edu-cation and changes to logbooks, it would be unrealistic for operators to collect additional data on the diversity and numbers of released catches as well as the lengths of fish.

There is a raft of options for the future monitoring and assessment of this fishery and harvested recreational species. These range in scale and costs from a large- scale, fishery- wide annual observer programme that reports on retained and released catches and demographics of species, to industry logbooks that report data on retained catches and effort. The overall strategy is dependent on the levels and frequen-cies of information needs to satisfy management and conservation objectives, costs and cost- efficiencies compared with alternative data sources (such as obtaining lengths and ages from other recreational and commercial fisheries).

It is most likely that a future monitoring and assessment strategy will include a combination of industry and observer data, ideally in-corporating a collaborative research partnership (Kraan et al., 2013; Lordan et al., 2011; Motta et al., 2016). For example, it could involve an ongoing industry logbook programme of retained catches and a pe-riodic (e.g. every 3–5 years) observer- based programme that collects quantitative data on the diversity and numbers of released catches, and the length compositions (and potentially age compositions) of retained and released species. This would pave the way for greater assessment and reporting of discarding and biodiversity impacts for ecosystem- based fishery management. Such a sampling programme would also prove vital in validating the ongoing industry logbook data and help mitigate any criticism regarding the reliability of industry- reported data for assessment and management purposes (Hoare et al., 2011; Kraan et al., 2013).

ACKNOWLEDGMENTS

This study was funded by the Australian and New South Wales Governments via the Australian Fisheries Research and Development

Corporation (Project 2014/036), the NSW Recreational Fishing Trust and the NSW Marine and Estuarine Recreational Charter Trust. We thank charter operators John Paton and Ann and Rodney Garard for their valuable advice concerning the charter fishery and observer sam-pling logistics; Geoff Barrett, John Stewart and Bryan van der Walt from NSW DPI for providing the industry logbook catch, effort and length data and for logistic assistance; the observers who collected the independent data—Jennifer Marshall, Toby Piddock, Ricky Tate, Derrick Cruz, Krystle Keller, Stephanie Brodie, Brendon Findlay, Kim Elder, Grant Clark, Sascha Schulz and Martin Hing—and the various charter boat operators (and their clients) that participated in the ob-server sampling.

CONFLICT OF INTEREST

The authors declare there was no conflict of interest in undertaking and reporting this study.

REFERENCES

Aas, Ø., Arlinghaus, R., Ditton, R. B., Policansky, D., & Schramm, H. L. Jr (2008). Global challenges in recreational fisheries (pp. 363). Oxford: Blackwell Science.

Anderson, M. J., Gorley, R. N., & Clarke, K. R. (2008). PERMANOVA+ for PRIMER: Guide to Software and Statistical Methods. Plymouth, UK: PRIMER-E.

Arlinghaus, R., Cooke, S. J., Sutton, S. G., Danylchuk, A. J., Potts, W., Freire, K. D. M. F., … van Anrooy, R. (2016). Recommendations for the future of recreational fisheries to prepare the social- ecological system to cope with change. Fisheries Management and Ecology, 23, 177–186.

Barrella, W., Ramires, M., Rotundo, M. M., Petrere, M. Jr, Clauzet, M., & Giordano, F. (2016). Biological and socio- economic aspects of the rec-reational fisheries and its implications to the management of coastal urban areas of southeastern Brazil. Fisheries Management and Ecology, 23, 303–314.

Beard, T. D., Arlinghaus, R., Cooke, S. J., McIntyre, P. B., De Silva, S., Bartley, D., & Cowx, I. G. (2011). Ecosystem approach to inland fish-eries: Research needs and implementation strategies. Biology Letters, 7, 481–483.

Benoît, H. P., & Allard, J. (2009). Can the data from at- sea observer sur-veys be used to make general inferences about catch composition and discards? Canadian Journal of Fisheries and Aquatic Sciences, 66, 2025–2039.

Coleman, F. C., Figueira, W. F., Ueland, J. S., & Crowder, L. B. (2004). The im-pact of United States recreational fisheries on marine fish populations. Science, 305, 1958–1960.

Cooke, S. J., & Cowx, I. G. (2006). Contrasting recreational and commer-cial fishing: Searching for common issues to promote unified con-servation of fisheries resources and aquatic environments. Biological Conservation, 128, 93–108.

Cotter, A. J. R., & Pilling, G. M. (2007). Landings, logbooks and observer sur-veys: Improving the protocols for sampling commercial fisheries. Fish & Fisheries, 8, 123–152.

Dell’Apa, A., Knight, E., Overton, A. S., Landry, C. E., Dumas, C. F., Whitehead, J. C., & Herstine, J. H. (2015). The North Carolina charter boat fishery changing with the times: A comparative analysis of the catch composition (1978 and 2007–2008). Fisheries, 40, 222–233.

Faunce, C. H., & Barbeaux, S. J. (2011). The frequency and quantity of Alaskan groundfish catcher- vessel landings made with and without an observer. ICES Journal of Marine Science, 68, 1757–1763.


Font, T., & Lloret, J. (2014). Biological and ecological impacts derived from recreational fishing in Mediterranean coastal areas. Reviews in Fisheries Science and Aquaculture, 22, 73–85.

Gray, C. A. (2016). Evaluation of fishery- dependent sampling strategies for monitoring a small- scale beach clam fishery. Fisheries Research, 177, 24–30.

Gray, C. A., & Kennelly, S. J. (2016). First implementation of an indepen-dent observer program for the Charter Boat Industry of NSW: data for industry-driven resource sustainability. Fisheries Research and Development Corporation Project 2014/036 Final Report. WildFish Research, ISBN 978-0-9941504-9-3. 71 pp.

Greiner, R., & Gregg, D. (2010). Considering recreational catch and harvest in fisheries management at the bio- regional scale. Fisheries Management and Ecology, 17, 336–345.

Hilborn, R., & Walters, C. (1992). Quantitative fisheries stock assessment: Choice, dynamics and uncertainty (pp. 570). New York: Chapman & Hall.

Hoare, D., Graham, N., & Schon, P. (2011). The Irish Sea data- enhancement project: Comparison of self- sampling and national data- collection pro-grammes – results and experiences. ICES Journal of Marine Science, 68, 1778–1784.

Ihde, T. F., Wilberg, M. J., Loewensteiner, D. A., Secor, D. H., & Miller, T. J. (2011). The increasing importance of marine recreational fishing in the US: Challenges for management. Fisheries Research, 108, 268–276.

Johnson, T. R., & van Densen, W. L. T. (2007). The benefits and organiza-tion of cooperative research for fisheries management. ICES Journal of Marine Science, 64, 834–840.

Kaplan, I. M., & McCay, B. J. (2004). Cooperative research, co- management and the social dimension of fisheries science and management. Marine Policy, 28, 257–258.

Kraan, M., Uhlmann, S., Steenbergen, J., Van Helmond, A. T. M., & Van Hoof, L. (2013). The optimal process of self- sampling in fisheries: Lessons learned in the Netherlands. Journal of Fish Biology, 83, 963–973.

Lew, D. K., & Larson, D. M. (2016). Stated preferences for size and bag lim-its of Alaska charter boat anglers. Marine Policy, 61, 66–76.

Lewin, W. C., Arlinghaus, R., & Mehner, T. (2006). Documented and poten-tial biological impacts of recreational fishing: Insights for management and conservation. Reviews in Fisheries Science, 14, 305–367.

Lichtkoppler, F., O’Keefe, D. M., Lucente, J., & Gabriel, T. (2015). The great lakes charter fishing industry: 2002 to 2011. Fisheries, 40, 200–212.

Liggins, G. W., Bradley, M. J., & Kennelly, S. J. (1997). Detection of bias in observer- based estimates of retained and discarded catches from a multi species trawl fishery. Fisheries Research, 32, 133–147.

Lordan, C., Cuaig, M. O., Graham, N., & Rihan, D. (2011). The ups and downs of working with industry to collect fishery- dependent data: The Irish experience. ICES Journal of Marine Science, 68, 1670–1678.

Lunn, K. E., & Dearden, P. (2006). Monitoring small- scale marine fisheries: An example from Thialand’s Ko Chang archipelago. Fisheries Research, 77, 60–71.

McEachron, L. W., & Matlock, G. C. (1983). An estimate of harvest by the Texas charter boat fishery. Marine Fisheries Review, 45, 11–17.

McIlgorm, A., & Pepperell, J. (2014). An economic survey of the recreational fishing charter boat industry in NSW. A report to the NSW Department of Primary Industries by Dominion Consulting Pty Ltd, 31 pp.

McPhee, D. P., Leadbitter, D., & Skilleter, G. A. (2002). Swallowing the bait: Is recreational fishing ecologically sustainable? Pacific Conservation Biology, 8, 40–51.

Motta, F. S., Mendonca, J. T., & Moro, P. S. (2016). Collaborative assessment of recreational fishing in a subtropical estuarine system: A case study

with fishing guides from Southeastern Brazil. Fisheries Management and Ecology, 23, 291–302.

Pitcher, T., & Hollingworth, C. (2002). Recreational fisheries: Ecological, eco-nomic and social evaluation (pp. 271). Oxford: Blackwell Science.

Post, J. R., Sullivan, M., Cox, S., Lester, N. P., Walters, C. J., Parkinson, E. A., … Shuter, B. J. (2002). Canada’s recreational fisheries: The invisible collapse? Fisheries, 27, 6–15.

Pradervand, P., & Van der Elst, R. (2008). Assessment of the charter- boat fishery in KwaZulu- Natal, South Africa. African Journal of Marine Science, 30, 101–112.

Rotherham, D., Underwood, A. J., Chapman, M. G., & Gray, C. A. (2007). A strategy for developing scientific sampling tools for fishery- independent surveys of estuarine fish in New South Wales, Australia. ICES Journal of Marine Science, 64, 1512–1516.

Ryan, K. L., Trinnie, F. I., Jones, R., Hart, A. M., & Wise, B. S. (2016). Recreational fisheries data requirements for monitoring catch shares. Fisheries Management and Ecology, 23, 218–233.

Savolainen, M. A., Fannin, J. M., & Caffey, R. H. (2014). Economic impacts of the U.S. Gulf of Mexico recreational for- hire fishing industry. Human Dimensions of Wildlife, 19, 72–87.

Sheaves, M., Baker, R., McLeod, I., Abrantes, K., Wani, J., & Barnett, A. (2016). The conservation status of Niugini black bass: A world- renowned sport fish with an uncertain future. Fisheries Management and Ecology, 23, 243–252.

Solstrand, M. V. (2013). Marine angling tourism in Norway and Iceland: Finding balance in management policy for sustainability. Natural Resource Forum, 37, 113–126.

Stewart, J. (2011). Evidence of age- class truncation in some exploited ma-rine fish populations in New South Wales, Australia. Fisheries Research, 108, 209–213.

Uhlmann, S. S., Bierman, S. M., & van Helmond, A. T. M. (2011). A method of detecting patterns in mean lengths of samples of discarded fish, applied to the self- sampling programme of the Dutch bottom- trawl fishery. ICES Journal of Marine Science, 68, 1712–1718.

Uhlmann, S. S., van Helmond, A. T., Stefánsdóttir, E. K., Sigurðardóttir, S., Haralabous, J., Bellido, J. M., … Rochet, M. (2014). Discarded fish in European waters: General patterns and contrasts. ICES Journal of Marine Science, 71, 1235–1245.

Vølstad, J. H., Korsbrekke, K., Nedreaas, K. H., Nilsen, M., Nilsson, G. N., Pennington, M., … Wienerroither, R. (2011). Probability- based surveying using self- sampling to estimate catch and effort in Norway’s coastal tourist fishery. ICES Journal of Marine Science, 68, 1785–1791.

West, L. D., Stark, K. E., Murphy, J. J., Lyle, J. M., & Ochwada- Doyle, F. A. (2015). Survey of recreational fishing in New South Wales and the ACT, 2013/14. Fisheries Final Report Series No. 149, 150 pp.

Wise, B. S., Telfer, C. F., Lai, E. K. M., Hall, N. G., & Jackson, G. (2012). Long- term monitoring of boat- based recreational fishing in Shark Bay, Western Australia: Providing scientific advice for sustainable management in a World Heritage Area. Marine and Freshwater Research, 63, 1129–1141.

How to cite this article: Gray CA, and Kennelly SJ. Evaluation of observer- and industry- based catch data in a recreational charter fishery. Fish Manag Ecol. 2017;24:126–138. https://doi.org/10.1111/fme.12210

https://doi.org/10.1111/fme.12210

https://doi.org/10.1111/fme.12210

evaluation of observer‐ and industry‐based catch data in a

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