About this document

The mission of the National Oceanic and Atmospheric Administration (NOAA) is to 

understand and predict changes in the Earth’s environment and to conserve and manage coastal 

and oceanic marine resources and habitats to help meet our Nation’s economic, social, and 

environmental needs. As a branch of NOAA, the National Marine Fisheries Service (NMFS) 

conducts or sponsors research and monitoring programs to improve the scientific basis for 

conservation and management decisions. NMFS strives to make information about the purpose, 

methods, and results of its scientific studies widely available.

NMFS’ Pacific Islands Fisheries Science Center (PIFSC) uses the NOAA Technical 

Memorandum NMFS series to achieve timely dissemination of scientific and technical 

information that is of high quality but inappropriate for publication in the formal peer-reviewed 

literature. The contents are of broad scope, including technical workshop proceedings, large data 

compilations, status reports and reviews, lengthy scientific or statistical monographs, and more. 

NOAA Technical Memoranda published by the PIFSC, although informal, are subjected to 

extensive review and editing and reflect sound professional work. Accordingly, they may be 

referenced in the formal scientific and technical literature.

A NOAA Technical Memorandum NMFS issued by the PIFSC may be cited using the 

following format:

Nadon, M. O. 

2017. Stock assessment of the coral reef fishes of Hawaii, 2016. U.S. 

Dep. Commer., NOAA Tech. Memo., NOAA-TM-NMFS-PIFSC-60, 212 

p. doi:10.7289/V5/TM-PIFSC-60.

Species photos for C. argus, P. insularis, M. vanicolensis, and C. melampygus were taken by

the author for NOAA-PIFSC. All other species photos are from Randall, J.E. 1997. Randall’s 

underwater photos. Collection of almost 2,000 underwater photos. Unpublished. Accessed 

through fishbase.org.

__________________________ 

For further information direct inquiries to

Chief, Science Operations Division

Pacific Islands Fisheries Science Center

National Marine Fisheries Service

National Oceanic and Atmospheric Administration

U.S. Department of Commerce 

1845 Wasp Boulevard 

Honolulu, Hawaii 96818 

Phone: 808-725-5331 

Fax: 808-725-5532 _______________________________________________________________________

Cover: Photograph taken by author for the Pacific Islands Fisheries Science Center. 

 National Marine Fisheries Service.
Pacific Islands Fisheries Science Center

National Marine Fisheries Service

National Oceanic and Atmospheric Administration

U.S. Department of Commerce

Stock Assessment of the Coral Reef Fishes of Hawaii, 2016 

1,2Marc O. Nadon

1

Joint Institute for Marine and Atmospheric Research

University of Hawaii

1000 Pope Road, Honolulu, Hawaii 96822

2

Pacific Islands Fisheries Science Center

National Marine Fisheries Service

1845 Wasp Boulevard

Honolulu, Hawaii 96818

NOAA Technical Memorandum NMFS-PIFSC-60 

February 2017

doi:10.7289/V5/TM-PIFSC-60
i 

ABSTRACT

This report contains single-species assessments of 27 reef-associated fish stocks around the 

main Hawaiian Islands using data from various sources collected during the 2003–2016 period. 

Previous management actions have set acceptable biological catches (ABCs) at the family level 

using either a percentile of historical catches or a catch-MSY approach. Here, we used fisheryindependent size composition and abundance data from diver surveys combined with fisherydependent catch estimates to calculate current fishing mortality rates (F), spawning potential 

ratios (SPR), SPR-based sustainable fishing rates (F30: F resulting in SPR = 30%), and catch 

levels corresponding to these sustainable rates (C30). We used a length-based model to obtain 

mortality rates and a relatively simple age-structured population model to obtain the various 

stock status metrics. C30 were obtained by combining F30 estimates with current population 

biomass estimates derived directly from diver surveys or indirectly from the total catch. The 

overfishing limits (OFL) corresponding to a 50% risk of overfishing was defined as the median 

of the C30 distribution. A novel data-poor approach was used to estimate life history parameters 

for 11 species with either no or inadequate published growth and maturity studies. We used 

Monte Carlo simulations to incorporate all sources of uncertainty (i.e., life history parameters, 

average length, abundance, and catch). Of the 27 assessed species, 11 had median F/F30 ratios 

greater than 1 and therefore median SPR values below the minimum overfished limit of 30%. 

Another two were close to this limit (30% ≤ SPR < 35%). This suggests some stocks may be 

experiencing overfishing and, if at equilibrium, may also be overfished. Surgeonfishes and 

parrotfishes were the families with the most species with low SPR values, while goatfishes 

generally had higher SPR values. Typically, species with low SPR were the ones with long 

lifespan (i.e., surgeonfishes) or highly targeted (i.e., jacks, snappers). Species with shorter 

lifespans (i.e., goatfishes) fared generally better. As a final step, overfishing probability 

distributions for a range of catch limits were generated for all 27 species.
ii
iii

CONTENTS

ABSTRACT ............................................................................................................................. i

INTRODUCTION ................................................................................................................... 1

Description of the Fisheries ................................................................................................. 2

METHODS .............................................................................................................................. 3

Stock Area ........................................................................................................................... 3

Size Selectivity in the Fishery ............................................................................................. 4

Data Sources ........................................................................................................................ 5

Total and Natural Mortality Models .................................................................................... 8

Population Simulation Model ............................................................................................ 10

Overfishing Limit Calculation ........................................................................................... 11

Decision Process for Multiple Data Sources ..................................................................... 12

Analyses Work Flow ......................................................................................................... 12

RESULTS SUMMARY ........................................................................................................ 14

DISCUSSION ........................................................................................................................ 15

ACKNOWLEDGEMENTS ................................................................................................... 18

REFERENCES ...................................................................................................................... 19

TABLES AND FIGURES ..................................................................................................... 25

SPECIES REPORTS ............................................................................................................. 35

Acanthurus blochii .............................................................................................................36

Acanthurus dussumieri.......................................................................................................42

Naso brevirostris ................................................................................................................49

Naso hexacanthus ..............................................................................................................55

Naso lituratus .....................................................................................................................62

Naso unicornis ...................................................................................................................69

Carangoides orthogrammus ..............................................................................................75

Caranx ignobilis.................................................................................................................81

Caranx melampygus...........................................................................................................88

Aprion virescens.................................................................................................................95

Lutjanus fulvus .................................................................................................................102

Lutjanus kasmira ..............................................................................................................109

Mulloidichthys flavolineatus ............................................................................................116

Mulloidichthys pfluegeri .................................................................................................123

Mulloidichthys vanicolensis .............................................................................................130
iv

Parupeneus cyclostomus ..................................................................................................136

Parupeneus insularis .......................................................................................................143

Parupeneus porphyreus ...................................................................................................150

Calotomus carolinus ........................................................................................................157

Chlorurus perspecillatus ..................................................................................................163

Chlorurus spilurus ...........................................................................................................169

Scarus dubius ...................................................................................................................175

Scarus psittacus ...............................................................................................................181

Scarus rubroviolaceus .....................................................................................................187

Cephalopholis argus ........................................................................................................193

Monotaxis grandoculis.....................................................................................................199

Myripristis berndti ...........................................................................................................206 
1 

INTRODUCTION

The 2006 re-authorization of the Magnuson-Stevens Fishery Conservation and Management 

Act calls for annual catch limits (ACLs) to be set for all exploited stocks in the United States and 

its territories in order to, among other goals, insure sustainable harvesting practices. In the U.S. 

Pacific, exploited stocks include a multitude of coral reef-associated finfish species inhabiting 

shallow-water areas around a large number of islands and atolls. The high species diversity, the 

mixture of commercial and recreational fishing effort, and the spatially diffused nature of the 

fisheries result in a comparatively data-poor situation for these stocks. This has led the Western 

Pacific Regional Fishery Management Council (WPRFMC) to set ACLs using basic analytical 

methods such as using the 75th percentile of historical catches or using catch-based methods 

applied at the family level (Sabater & Kleiber, 2013). However, recent efforts in fisheriesindependent surveys and life history research by the Pacific Islands Fisheries Science Center 

(PIFSC) have improved this situation to the point where simple age-based assessment 

approaches can now be applied to individual coral-reef fish stocks (Nadon et al., 2015). 

In this report, the status of 27 of the most commonly exploited coral-reef fish species of 

Hawaii was assessed using a length-based mortality model and a relatively simple numerical 

population model. Using this approach, we obtained estimates of fishing mortality (F) and

spawning potential ratio (SPR) over the recent time period, F at SPR = 30% (F30), catch 

associated with F30 (C30), and overfishing risk tables for a range of catch limits (including a 

proxy overfishing limit, OFL, defined as the C30 level that results in a 50% chance of 

overfishing; see Table 1 for the definition of all parameters). 

For the purposes of our SPR-based approach in this paper, we used a default definition of 

overfished and overfishing as recommended by Restrepo et al. (1998): 

• Overfished limit: SPR = 30%, with overfished defined as SPR < 30% 

• Overfishing limit: F at SPR = 30% (F30), with overfishing defined as F > F30 or 

F/F30 > 1.

It is important to note that since our analyses assumed populations were at equilibrium a 

stock that is experiencing overfishing was also considered overfished (and vice-versa). 

For this approach, we used fishery-independent size composition and abundance data 

provided by NOAA diver surveys as well as fishery-dependent data from the State of Hawaii 

commercial fishing database. These 27 species, from 8 different families, were selected based on 

the availability of length data from either data sources and the availability of reliable life history 

parameters related to growth, maturity, and longevity. In the situation where no published life 

history parameters where available, a new data-poor estimation approach developed at PIFSC 

and the University of Miami was implemented (Nadon & Ault, 2016). Additional species could 

not be assessed due to data limitations, but this situation may change as new data sources 

become available. Although most of these species’ depth range occurs within the 3 nautical mile 
2 

limit defining State waters, species inhabiting depths beyond 50 m have significant portions of 

their range (18–26%) in federal waters, mainly on Penguin Bank and in the channel waters 

between Maui, Molokai, and Lanai (see Table 3, Figure 2, and Figure 3). 

Description of the Fisheries

The Hawaiian Archipelago is a large island chain extending 2600 km along a SE-NW axis 

from 19°N, 155°W to 28°N, 178°W (Figure 1). The archipelago is composed of 18 islands and 

atolls which are typically divided into two broad regions: the inhabited main Hawaiian Islands

(MHI; 1.4 million individuals; dbedt.hawaii.gov/census) and the mostly un-inhabited 

Northwestern Hawaiian Islands (NWHI). The MHI consists of 8 geologically young, high (4,205 

m maximum elevation) volcanic islands while the NWHI have low elevation (275 m max 

elevation). The MHI were settled by people around AD 1250, and reef fish communities in the 

MHI have been exploited since that time (Kittinger et al., 2011). The NWHI were never 

permanently inhabited. However, they were the focus of commercial fishing, especially in the 

19th century (Kittinger et al., 2011). Presently, the coral reef ecosystem around the MHI are 

critical to both fishing and tourism activities (Cesar & Beukering, 2004). 

The coral reef fishery around the MHI involves near-shore recreational/subsistence fishing 

combined with a small commercial fishing sector. Almost a third of Hawaii households are 

involved in recreational-subsistence fishing (Hamnett et al., 2006), and their catches are 

estimated to exceed those of the commercial sector significantly (Friedlander & Parrish, 1997; 

Zeller et al., 2005; Williams & Ma, 2013). The recreational-subsistence sector is composed of 

(mostly) shore-based fishers using a variety of gears such as spears, hook-and-line, traps, and 

small gill and cast nets. The primary targeted families include larger jacks and snappers, and, to a 

lesser extent, smaller reef-associated families such as surgeonfish, goatfish, soldierfish, and 

parrotfish (Friedlander & Parrish, 1997). Commercial marine landings in Hawaii are mostly 

composed of coastal-pelagic species (> 80% of catches; DeMello, 2004), but also include the 

reef fishes targeted by the recreational-subsistence sector. The direct monetary value of the nearshore fishery is only 10–20% of the pelagic fishery (Gulko et al., 2002), but it is culturally and 

socially important to the local population. 
3 

METHODS

The general assessment approach used in the present document recognizes the relatively

data-poor status of most of the coral-reef fish stocks in Hawaii. We specifically focused on the 

best available data sources which are the ongoing NOAA-PIFSC diver surveys (2005–2016) and 

the recent commercial data from the State of Hawaii (2003–2015). Since these two data sources 

contain relatively short time-series, our assessment approach was limited to equilibrium models 

that assume relatively constant fishing mortality and recruitment. The validity of this assumption 

was investigated for each species by looking at temporal trends in average length in the catch and 

abundance index from diver surveys as illustrated in the Species Report section at the end of this 

document. Furthermore, the lack of stock-recruitment relationships meant that we had to rely on 

a biological reference point (BRP) based on per-recruit spawning stock biomass (SSBR) and the 

ratio of current SSBR to un-exploited SSBR (spawning potential ratio, SPR, a measure of the 

spawning potential of a stock). The general assessment approach consisted of three main steps: 

1) calculate current fishing mortality rates (F) using diver and commercial data derived average 

length estimates in a length-mortality model, 2) calculate SPR and F30 (the fishing mortality rate 

resulting in SPR = 30%) using published life history parameters in a population simulation 

model, and 3) calculate the catch limit associated with a given F30 (C30) by combining the F30

estimate with an estimate of current population biomass (derived directly from diver surveys or 

indirectly by relating the current total catch with the current F). A Monte Carlo procedure was 

used to integrate the uncertainty in each individual parameters related to length, population size, 

and life history. The median of the C30 distribution is the overfishing limit (OFL) value, by 

definition, since it corresponds to a 50% chance of overfishing. A schematic of these steps and 

decisions are presented in Figure 4. The following sections explain this approach in greater 

details and describe the various data sources.

Stock Area

The first step of any stock assessment is typically to define the geographical extent of the 

stocks being analyzed. It is still not entirely clear to what level the reef fish populations around 

the MHI are connected and if significant larval exchanges or adult movements exist between the 

different Hawaiian Islands, although it is generally accepted that fish populations between the 

MHI and NWHI are disconnected (see Discussion section for details). In this report, all 27 stocks 

were analyzed at the MHI scale (Figure 1) mainly due to data limitations, as well as to follow 

current management stock definitions. Further stock connectivity studies may suggest that future 

stock assessments be conducted at different spatial scales for certain species.

Another consideration for these assessments was the extent of each species’ geographical 

range that fell in federal vs. state waters. For each species, we obtained depth range estimates 

from Baited Remote Underwater Video (BRUV) and bottom-fish camera (BotCam) exploratory 

surveys conducted by PIFSC (J. Asher, pers. comm.) and the University of Hawaii (J. Drazen, 

pers. comm.). We also used the mesophotic deep diving exploratory work conducted by Pyle et 

al. (2016). We did not attempt to quantify abundance-at-depth given the limited coverage of 
4 

these surveys. We simply reported the maximum depth that individual species can inhabit, which 

may be fairly marginal in certain cases, and calculated the sea floor area to this depth. In the 

Species Report section, we provide both the maximum depth and the percentage of sea floor area 

in federal vs. state waters for all species (see Table 3, Figure 2, and Figure 3 for a summary). 

Size Selectivity in the Fishery

The State of Hawaii has minimum size regulations on some of the species included in this 

report. However, it is uncertain to what degree these are respected by fishermen. To infer on the 

selectivity pattern in the reef fish fishery, we used the indirect abundance-at-length data from the 

State commercial data set (see Data Source section below for details) and, to a lesser extent, the 

Hawaii Marine Recreational Fishing Survey (HMRFS). Fishing records were utilized from the 3 

main fishing gear types used in inshore areas: hook-and-line (44% of fishing reports for the 

species targeted in this study, DAR gear code: 1–6, 8–10, 61–63, 70, and 91–93), spearfishing 

(40%, gear code: 13 and 14), and various nets (15%, gear code: 20–23, 25-27, 30, 32, 33, 40, 41, 

and 45). Other gears, such as traps, represented less than 1% of reports for the species selected in 

the current study and data from these reports were not used. From what is known about the reef 

fish fishery and the size composition in the catch, it was clear that some form of logistic 

selectivity curve was most appropriate (i.e., there was no indication of reduced selectivity at 

larger sizes). We therefore used the following formulation of logistic selectivity:

















−

− −+

=

95 50

50 1 exp )19ln(

1

SS

S

LL

LL

S (1)

where L is the length at which selectivity is estimated, LS50 is the length at 50% selectivity, and 

LS95 is the length at 95% selectivity. To estimate these two parameters, we first searched for a 

discontinuous break in the size composition histogram obtained from the commercial data set

(and HMRFS data set, if it had sufficient observations) to obtain an initial estimate of LS95. We 

then looked at the smallest size bin in the size composition graph and split the difference 

between this size and LS95 to obtain an initial estimate of LS50. For example, the commercial 

catch size structure for Parupeneus porphyreus did not have individuals below 20 cm, had a few 

individuals in the 20–22 cm and 22–24 cm ranges (~ 50), and a significantly higher number of 

individuals in the 24–26 cm range (close to 200 fish). The number of fish in size bins above 24–

26 cm increased in a continuous manner. This discontinuous jump between 22–24 cm and 24–26 

cm appeared to be related to selectivity; consequently a first estimate of LS95 was set at 26 cm. 

The smallest size bin was 20–22 cm and we therefore set LS50 at 23 cm (i.e. the midpoint 

between 20 and 26 cm). To test the validity of the LS95 and LS50 parameters, we simulated a size 

structure using our population simulation model with these parameters (see Population 

Simulation section) and compared it to the actual size structure data. If the size structures did not 

agree, we adjusted the LS50 and LS95 parameters and ran further simulations. Typically, one or 

two runs were necessary to obtain an appropriate estimate of the selectivity parameters. For most 

species, sensitivity analyses were also used with different selectivity parameter pairs.
5 

Finally, the length-mortality model used to obtain an estimate of total mortality (see Total 

Mortality section below) requires an estimate of length at full selectivity (“LS100”). Since it is 

impossible to differentiate between LS95 and LS100, given their similarity and the limited 

resolution of our length data, we simply used LS95 as our estimate of length at full selectivity for 

the length-mortality model. This made our total mortality estimate slightly lower than if LS100

was known. 

Data Sources

Size composition, density, and total biomass from diver surveys

The main source of fisheries-independent data came from the diver surveys conducted by 

the Pacific Islands Fisheries Science Center’s Coral Reef Ecosystem Program (CREP). The diver 

surveys were used to obtain size structure data (from which average length in the exploited phase 

could be calculated - L ) and abundance data (from which population biomass estimates could be 

derived). Below is a brief description of the survey protocol. An in-depth description is available 

in Ayotte et al. (2015). 

Starting in 2005, trained divers from the NOAA Pacific Islands Fisheries Science Center 

(PIFSC) have been conducting visual surveys around the MHI. Survey sites were randomly 

selected within strata defined by depth-bins (shallow, 0–6 m; mid, 6–18 m; and deep, 18–30 m). 

All coastlines from all islands in the MHI were surveyed, except for the small, restricted island 

of Kaho'olawe. For practical and safety reasons, surveys were limited to depths above 30 m. 

During a typical CREP survey day, a NOAA ship deployed 3 to 4 small dive boats that sampled 

pre-assigned random sites along 10 to 12 miles of coastline. The daily starting location of the 

ship along different coastlines of the MHI was set in as systematic manner, with the goal of 

covering as much of the shoreline as possible. At each site, stationary point counts were 

implemented by two paired divers inside contiguous 15-m diameter cylinders that extended from 

the bottom to the surface (Brandt et al., 2009; Smith et al., 2011; Williams et al., 2011). Divers 

first listed all observed fish species during an initial 5-minute period. The divers then went

through this list, one species at the time, recording the number of individuals and estimating 

sizes of all fish seen within the cylinder. Fish sizes were recorded as total lengths to the nearest 

cm. Fishes from species not listed during the initial 5-minute period, but observed later in the 

survey, were also recorded but classified in a different data category (i.e., non-instantaneous 

count). Divers were continuously trained between cruises in size estimation using fish cut-outs of 

various sizes. Diver performance during research cruises was evaluated by comparing size and 

count estimates between paired divers. 

Average length in the exploited phase ( L ) was obtained from the abundance-at-size data by 

averaging all length observations (weighted by count) from 2005 to 2016 for a species inside 

each of the 4 subregions of the MHI (see Figure 1, Table 2 for subregion descriptions). Only 

lengths above size at full selectivity (LS95) were kept. The overall L was obtained by averaging 

all 4 sub-regional L weighted by the respective size of each subregion’s shallow reef area (Table 

2). This was done to account for differences in size composition due to uneven fishing pressure 
6 

(inferred from humans per reef area values—Table 2) and uneven sampling effort between 

regions. The standard deviations of L estimates were obtained by bootstrapping the diver survey 

data set by re-sampling survey sites within subregion (Figure 1) and applying the weighted mean 

procedure described above to generate a distribution of L . 

Numerical density estimates (fish per 100 m2) were obtained by dividing the fish counts in 

each survey by the area per survey (353 m2 from two 15-m diameter survey cylinders) and 

multiplying by 100 (an individual survey consisted of the combined fish counts from the two 

divers deployed at a random site). We calculated selectivity for each observation using the 

observed length and Eq. (1), and multiplied each fish count by this value. The overall average 

numerical density was obtained by (1) averaging site-level density estimates within a coastline 

sector (see Figure 5 for sector map) and by (2) averaging all sector-level density estimates 

together, weighted by the amount of reef area in each sector. It is important to note here that we 

did not use the higher spatial resolution sectors for the L bootstrapping procedure due to the 

relatively low length observation sample sizes (we use the subregions instead). The standard

deviations of overall mean density estimates were obtained by bootstrapping the diver survey 

data set by re-sampling survey sites within sector (Figure 5) and applying the weighted mean 

procedure described above to generate a distribution of mean numerical density. These density 

estimates are presented as time series graphs in the Species Report section. Finally, it is 

important to note that only instantaneous fish counts were kept for this calculation in order to get 

an abundance estimate close to “true” density. The implied assumption here is that the 

“catchability” (q) of an individual underwater survey is the fraction of the total hard-bottom 

population area (96,208 ha) covered by a single survey (353 m2; q = 3.67e-7). We used hardbottom area since all species in this report are heavily associated with this habitat type. Some 

species, like goatfishes, feed over soft-bottom areas but they are usually within range of hardbottom areas which they rely on for refuge. 

Biomass density estimates (kg per 100 m2

) were obtained by using the same approach as for 

numerical density, but by first converting each individual fish length into weight using published 

length-weight conversion parameters as provided in the Species Report section. Fish biomass 

density per sector was used to estimate fish biomass per sector by multiplying biomass density 

by the amount of hard-bottom area in each sector (obtained from CREP and bathymetric data 

compiled by the Hawaii Mapping Research Group). Total stock biomass was obtained by 

summing all sector biomass together. The standard deviations of biomass density and total fish 

biomass were obtained through bootstrapping in a similar fashion as for numerical density.

One limitation of this data set was the potential impact of fish behavior on the assumed

catchability coefficient (3.66e-7) for population biomass calculations. Cryptic behavior and diver 

avoidance (or attraction) will have an effect on this assumed value and this will differ between 

species. Although the biomass calculations for all species were done assuming this value, we 

discuss potential biomass estimate biases for certain species in the Species Report section. 

Another limitation of this data set is the potential mismatch between the survey domain 

(limited to 30-m depth) and the greater depth range of certain species. For species occurring at 

depths greater than 30 m, we did not attempt to assign a population abundance to the un-sampled 
7 

sea floor area, given our limited knowledge of the amount of suitable habitat at these depths. We 

do however discuss this potential bias and implications for the relevant species in the Species

Report section. 

Size composition and total catch from fishing report data 

We used the commercial fishing report data from the State of Hawaii’s Division of Aquatic 

Resources (DAR) to obtain an estimate of total commercial catch. Catch records for certain taxa 

that were not identified to the species level were not included in analyses that depended on this 

data set (all parrotfishes, the “kala” group of surgeonfishes composed of Naso unicornis, N. 

annulatus, and N. brevirostris, and the Acanthurus blochii/A. xanthopterus reporting group). We 

also used the Hawaii Marine Recreational Fishing Survey program (HMRFS) catch estimates 

provided by Williams and Ma (2013) to obtain an estimate of total recreational catch from 2004 

to 2015. For the commercial data, we simply summed the reported catch by weight by year from 

2003 to 2015 by species (for species reported at the species level). Given the uncertainty 

associated with both catch data sets, we assumed that annual total catch has been mostly stable 

from 2003 to 2015 and that the year to year variability is representative of the uncertainty around 

the total catch estimates. Thus it was not necessary that the time periods of commercial and 

recreational data sets matched perfectly. HMRFS data were not always available for every 

species in every year. Past reports (Williams & Ma, 2013) have shown that the nearshore fishery 

is dominated by recreational fishing, and there is no evidence that recreational fishing effort has 

been going dramatically up in recent years given that Hawaii’s human population is increasing at 

a fairly low rate (~ 1% per year). Plotting the catch data by year for these species revealed mostly 

year-to-year variability, although these estimates were generally fairly variable (see Species 

Report section). In order to come up with a total catch estimate, we fitted a lognormal 

distribution to both the commercial and recreational yearly catch estimates and summed these 

together using a Monte Carlo procedure by randomly sampling both distributions, adding those 

values together, and fitting a new lognormal distribution to the resulting data set. Of note, when 

summing lognormal distributions, the median value of the final distribution will be different than 

the sum of the two median values of the original distribution (see Species Report section).

We also used the commercial fishing report data to obtain a second source of size 

composition data for species that have individual species codes (note: the HMRFS data set did 

not have sufficient length observation to be used consistently). As discussed in the Selectivity 

section, all 3 main fishing gears (hook-and-line, spearfishing, and nets) had a similar selectivity 

pattern, as inferred from the similar size composition of their catch (i.e. similar logistic shape

with no indication of lower selectivity at larger sizes). We therefore combined catch records

from all 3 fishing gears, providing close to 100,000 individual reports. Unfortunately, directlength observations are not recorded in the commercial data set. However, each record report the 

total weight and the number of fish caught by species. It was possible to obtain an indirect 

measure of length by dividing the catch in weight by the number of fish caught to obtain average 

weight per individual report. Average weights per report were then converted to total lengths 

using published standard allometric weight (W)–length (L) relationships (see individual species 

tables in the Species Report section),
8 

β α ⋅= LW (2) 

which can be inverted to obtain 





 









 



 = β

α

1

W L (3) 

where α is a scaling and β is a volumetric model parameter. For each species, average length per 

report were combined across all years using numbers caught per report as a weighting variable, 

in a similar fashion as for diver-survey L . Converting average weight per report to average 

length per report can theoretically lead to a biased estimate of average length (Jensen’s inequality 

caused by the non-linear length-weight relationship; Ruel & Ayres, 1999). To test the degree to 

which this occurred, for each species, we compared the average length from catch records with 

only one recorded fish caught vs. the average calculated for all catch records regardless of how 

many fish per record were reported. We found minimal differences in average length between 

these two calculation methods. The resulting length observations for each report were checked 

and lengths that were greater than the maximum reported for each species were discarded. The 

standard deviations of the average length estimates derived from commercial report data were 

estimated by bootstrapping individual report data by subregion and running the above analyses. 

Life history parameter sources 

We reviewed the scientific literature for published life history parameters related to growth, 

longevity, and maturity. We did not restrict our search to local studies given the paucity of peerreviewed literature on coral reef fish biology. If multiple growth or maturity studies were 

available for a species, we prioritized local studies, followed by the most recent, in-depth studies 

(even if from a different geographical area). If no life history study was available, for certain 

species, we used the data-poor life history estimation approach described in Nadon and Ault 

(2016). In short, this approach uses a local estimate of maximum length to provide familyspecific probability distribution for all main life history parameters. The standard deviations of 

life history parameters were obtained by one of the following methods, presented in order of 

preference based on reliability: 1) bootstrapping the raw length, age, or maturity data, when 

available, 2) using the coefficient of variations at different sample sizes from Kritzer et al. (2001) 

for growth and Nadon (unpublished) for maturity (Table 4), or 3) from the stepwise approach 

itself, if it was used to generate life history parameters (Nadon and Ault, 2016). See Figure 4 for 

a summary of life history steps within this assessment framework. 

Total and Natural Mortality Models 

As mortality rates increase, the probability of a fish reaching larger sizes decreases, and thus 

the mean of the size frequency distribution ( L ) decreases accordingly. Theoretically, the 

average length L in the catch can be expressed as
9 

∫

∫ = λ

λ

a

a a

a

a aa

c

c

daN

daLN

L (4) 

where the exploitable phase is integrated from ac (age at first capture) to aλ (oldest age), Na is the 

abundance at age class a, and La is the expected length at age a. 

A formula for estimating mortality rates using estimates of L was derived from Eq. (4) by 

Ehrhardt and Ault (1992). The first step in this derivation was to substitute La in Eq. (1) with the 

von Bertalanffy growth function and Na with the exponential mortality model

aZ

aaa eNN ∆−

∆+ = (5) 

where Z is the total instantaneous mortality rate and Δa is the age interval, normally one year. 

Step two was to integrate and algebraically solve for Z, 

( ) ( )

( ) ( ) LLKLLZ

LLKLLZ

LL

LL S

KZ

S −+−

−+−  =



 





−

−

∞

∞

∞

∞

λ

λ 95

/

95

 (6)

where K and L∞ are parameters of the von Bertalanffy growth equation (assumed to be constant 

over time), LS95 is the size at full selectivity (see Selectivity section), and Lλ is the expected size 

at oldest known age, respectively. We selected Eq. (6) instead of the Beverton-Holt model 

(Beverton & Holt 1956) due to a reported bias in this model associated with the assumption of 

infinite longevity (Ehrhardt & Ault, 1992). It is important to note that Eq. (4) and (6) are valid in 

equilibrium conditions where fishing mortality has been relatively constant for a sufficient 

amount of time for the population to be in a stable state. For each individual species, we looked 

at temporal trends in average lengths and estimated population abundance to verify that this was 

the case (see the Species Report section for further details). Fishing mortality was obtained from 

F = Z – M, where M is the instantaneous natural mortality rate which was derived from longevity 

in our study (see paragraph below for more details). Estimates of total instantaneous mortality 

rates Z were computed from Eq. (6) using a numerical procedure. Values of Lλ (expected length 

at maximum age aλ) were estimated from the von Bertalanffy growth function using an observed 

maximum age.

To derive F from Z, as well as to parameterize our population simulation model, it is 

necessary to obtain an estimate of natural mortality (M). To do so, we used the procedure of 

Alagaraja (1984), similar to Hoenig (1983) and Hewitt and Hoenig (2005), which assumes that 

4% of a cohort survives to the observed maximum age (aλ): 

λ a

M − ln( )04.0 = (7) 
10 

We used the 4% cohort survivorship value based on the analyses of Nadon et al. (2015) 

which showed that this is an appropriate survivorship value for coral reef fishes. We did not have 

independent estimates of M per se and had to rely on this longevity-based approach. Although 

there are other data-poor methods for estimating natural mortality, involving other parameters 

(e.g., K, Linf, Lmat, water temperature), two recent scientific papers on the subject clearly suggest 

that longevity-only methods are better performing (Kenchington, 2014; Then et al., 2015). It is 

important to consider the potential difficulty in obtaining a representative longevity value in 

heavily exploited stocks. To reduce this concern as much as possible, we always selected the 

oldest recorded age, regardless of geographical location, as our measure of longevity. It was, 

unfortunately, impossible to only select longevity estimates from un-exploited stocks given that 

there are few life history studies on such stocks. The Species Report section provides details of 

parameters selected and their sources, and output parameter values and associated uncertainty. 

Population Simulation Model

We built a population model in order to calculate various stock metrics (SPR, F30, Lc30). For 

exploited fish populations, a biological reference point for sustainability risks (spawning 

potential ratio, SPR) was computed using a numerical model to simulate exploited fish 

populations. The computations were based on the mortality rates derived from L estimates and 

life history parameters synthesized from the literature. Numerical abundance at age a was 

estimated through use of an exponential mortality function (Eq. 9). Length-at-age was estimated 

from the von Bertalanffy growth equation, and converted to weight-at-age using the allometric

weight-length relationship (Eq. 1). 

The numerical model was used to obtain spawning stock biomass per recruit (SSBR), at 

given levels of fishing mortality by summing over individuals in the population between the age 

of sexual maturity (am; age where 50% of individuals are mature, with knife-edge assumption) 

and 1.5 times the oldest recorded age (aλ),

= ∑

aλ

a

aa

m

SSBR WN

5.1

 (8) 

Where Na is the mean abundance at age a and Wa is the mean weight of individuals at age a

(derived from the von Bertalanffy equation combined with length-weight equation). The model 

was run using weekly time steps. Average abundance at age was modeled using the following 

equation: 

aMFS

aaa eNN ∆+⋅−∆+ = )( (9) 

where F and M are fishing and natural mortality, respectively, and S is selectivity which was 

defined by a logistic curve with parameters LS50 and LS95 (see Selectivity section). SPR was 

computed as the ratio of the current SSB relative to that of an unexploited stock: 
11 

un loited

loited

SSB

SSB

SPR

exp

exp = (10) 

Estimated SPRs were compared to the recommended 30% SPR threshold below which a 

stock is likely no longer sustainable (i.e., is experiencing recruitment overfishing), a standard 

recommended for less well-known stocks (Gabriel et al., 1989; Restrepo et al., 1998; Clark, 

2002). Lc30, the size at first capture required to obtain an SPR = 30% was also estimated using 

this model. To do so, we used an iterative procedure which calculated SPR at incrementing Lc

values (keeping all other parameters fixed) until the SPR = 30% level was reached. An identical 

procedure was used to obtain F30. 

Calculated SPR, proportion of SPR iterations that resulted in SPR < 0.30, Lc30, F30, and 

F/F30 values are provided in the Species Report section. 

Overfishing Limit Calculation

The sections above presented the data sources and models used to obtain various population 

parameters (mortality rates, SPR, F30, Lc30). To calculate an overfishing limit (OFL) estimate 

(i.e. the catch that results in a 50% chance of overfishing), we first needed to obtain an estimate 

of standing population biomass (B). This could be obtained in up to two ways depending on data 

reliability and availability for each species: 1) extrapolating total biomass from the diver-survey 

biomass density estimates, as explained earlier, and 2) by using the estimates of total catch (C), 

natural mortality, and length-derived fishing mortality in the Baranov catch equation: 

( ))( 1 MF e

MF

F CB +− − +

÷= (11) 

From one or both of these estimates of current population biomass, we derived the catch 

level corresponding to F30 (C30) by using the Baranov equation and our estimates of sustainable 

fishing mortality rate (F30):

( ))(

30

30

30 30 1 MF e

MF

F BC +− − + ⋅= (12) 

The final distribution of C30 estimates and other derived values (e.g., SPR) were obtained by 

incorporating all sources of uncertainty (data and parameters) using a Monte Carlo approach. In 

short, we drew a random value from the probability distributions of each data source ( L , life 

history parameters, diver-derived population biomass, and total catch) and ran all the steps to 

calculate C30 using these random values (Figure 4). The Monte Carlo draws for parameters that 

could not be negative (e.g. catch, L ) were bounded at zero (if they were drawn from probability 

distributions that allowed negative values). The Monte Carlo procedure was repeated 6,000 times 

to generate distributions of C30 and other derived values. The median of the C30 distribution 

represented the catch level with a 50% chance of overfishing (OFL). 
12 

It is important to note that randomly drawn combinations of life history parameters could 

lead to a biologically impossible scenario where an L was larger than the pristine average length 

predicted by these parameters. For these random draws, F will be negative and SPR will go

above 1. This can be a fairly common situation for lightly fished stocks with L close to its 

pristine value and is not necessarily an indication of incorrect life history parameter distributions. 

Instead, it is the result of a lack of a proper a priori covariance structure between these 

parameters that should have limited certain parameter combinations. For example, a very high M

value, combined with a low K and low Linf values can lead to a pristine average length that is 

unrealistically low and below a randomly drawn L . To correct this issue, for a randomly drawn

L , we rejected life history parameter combinations that led to this situation and re-drew life 

history parameters until a realistic combination was sampled. 

Decision Process for Multiple Data Sources

Throughout the process used to generate OFL estimates (Figure 4), there were several steps 

where decisions had to be made regarding data sources. To reduce the subjectivity of these 

decisions, we created a decision table presented in Figure 4. In short, there were 4 main decision 

steps: 1) whether to combine the L estimates from diver and report data or keep only one 

source, 2) whether to use a local study, external study, or the Nadon and Ault (2016) approach as 

a source of life history parameters, 3) whether to use a bootstrap procedure on raw data or the 

meta-analysis of Kritzer et al. (2001) and Nadon (unpubl.) to generate uncertainty of life history 

parameters, and 4) whether to use C30 distribution generated from diver-survey biomass or from 

catch-based biomass to calculate an OFL (this final decision point is discussed for individual 

species in the Species Reports section but is ultimately left to managers). 

Analyses Work Flow 

The raw diver survey data were provided by CREP (file named “all_diver_rea.rdata”) and 

the raw commercial data were extracted directly from the PIFSC Oracle database where they are 

stored. Two R scripts were used to process these raw data sets (“process_uvc_data.r” and 

“process_dar_data.r”). Other R scripts were used to obtain various metrics and their associated 

distributions: average length (“get_lbar.r”), population biomass (“get_diver_biomass.r”), 

commercial and recreational catch (“get_catch.r”), and time series graphs 

(“get_abund_timeseries.r” and “get_lbar_timeseries.r”). 

The overall approach to generate population status metrics (F, F30, and SPR) and the C30

distributions (Figure 4) was implemented in a Java-language computer program developed 

specifically for this purpose. This tool requires inputs in the form of probability distribution 

parameters (e.g., mean, standard deviation) for 1) the life history parameters, 2) average length, 

3) total catch (if available), and 4) population biomass from surveys (if available). In the case of 

the stepwise approach (Nadon and Ault, 2016), this tool also requires parameters for an Lmax

distribution and a species’ family-level taxonomic group. Other required parameters are entered 

as fixed values: selectivity (LS50 and LS95), a0, length-weight parameters (alpha and beta), number 
13 

of Monte Carlo iterations, the assumed survivorship at maximum age value (S), and the 

spawning schedule (when spawning occurs throughout the year, set to monthly by default). 

Once launched, the program will draw random samples from the input distributions and run 

the calculations showed in Figure 4: 1) generate an estimate of Z from the length-mortality 

model, 2) calculate M from longevity (if necessary) and F, 3) calculate SPR and F30 using the 

population simulation model, and 4) calculate C30 from the diver surveys (if available) and from 

the catch data (if available). The program outputs a comma-separated data file (.CSV) containing 

parameter values for all Monte Carlo iterations. This CSV file is processed with an R script to 

generate the standard suite of figures and tables displayed in each species report

(“process_mast.r”). 
14 

RESULTS SUMMARY

It is beyond the scope of this summary section to discuss individual assessments of the 27 

reef fish species in this report. In-depth results, comments, and specific concerns can be found in 

the Species Reports section at the end of this manuscript. Here, we provide a brief overview of 

the state of reef fishes in Hawaii, as can be inferred from the species analyzed in this report. 

Table 5 presents a summary of selected stock status metrics for each species.

Out of the 27 species in this report, 25 had depth ranges extending significantly (21 to 26%) 

into federal waters (i.e., beyond the 3 nautical mile limit of state waters). Two parrotfish species 

appeared to have limited presence in federal waters (Chlorurus spilurus and Scarus psittacus). A 

significant portion (~ 40%) of federal reef fish seafloor habitat above 250 m occurred at depths 

between 40 and 70 m, mainly on Penguin Bank, off Molokai (Figure 2).

We found local life history parameters for only 11 species and had to use parameters from 

studies conducted elsewhere in the Indo-Pacific region for 5 species. The remaining 11 species 

had either no (9) or inadequate (2) published life history studies and we used the data-poor 

approach presented in Nadon & Ault (2016) to obtain estimates (Table 5). As expected, the 

assessments conducted with these estimates were more variable than those conducted with life 

history parameters from actual studies.

Of the 27 assessed species, 11 had median SPR values below the minimum 0.30, which is 

the recommended limit we used as the default metric for overfishing in the current report 

(Restrepo et al., 1998). By this metric, SPR values lower than 0.30 indicate a stock may be

experiencing overfishing (and due to the equilibrium assumption, may also be overfished). Two

species had a median SPR values close to this limit (< 0.35; Table 5). Surgeonfishes had the most 

species with low SPR values, while goatfishes generally had higher SPR values. Typically, 

species with low SPRs were the ones with long lifespan (i.e., surgeonfishes, large parrotfishes, A. 

virescens) or highly targeted (i.e., jacks). Species with shorter lifespans (i.e., goatfishes) fared 

generally better.

To generate C30 from estimates of F30 (fishing mortality at SPR = 0.3), we had to obtain 

estimates of current stock biomass, either directly from diver surveys or indirectly from dividing 

total catch by an estimate of current F. Biomass estimates derived from diver-survey biomass 

were usually much more precise than those obtained through the catch. Consequently, C30

distributions derived from diver-biomass were generally more precise as well. Table 5 presents 

both estimates of population biomass by species. For species where both biomass estimates were 

available, 6 out of 12 species had biomass estimates within an order of magnitude of each other

(Table 5). Almost all biomass estimates derived from the catch were lower than those derived 

from diver surveys, suggesting some measure of under-reporting in the commercial catch and/or 

some bias from the HMRFS recreational fishing survey. The only 2 species with greater catchderived biomass than diver-survey biomass were goatfish species, with a potential bias 

associated with an important fishery for juveniles (see Species Reports section).
15 

DISCUSSION

The assessment approach used in this report focused on fisheries-independent diver-survey 

data and recent estimates of both commercial and recreational catch. It used mortality and 

population models that are relatively simple, but well-tested and appropriate for the data-poor 

situation that characterize coral-reef fisheries (Ehrhardt & Ault, 1992; Ault et al., 2005; Hordyk 

et al., 2015; Nadon et al., 2015). Several assumptions and caveats apply to these models. 

First, we assumed the stocks analyzed in the current study were at equilibrium in terms of 

both mortality rates and recruitment (i.e., relatively constant over the last decade or so). Ault et 

al. (2005) showed that mortality rates derived from average length are fairly robust to even 

moderate levels of recruitment variation. In the case of an extreme recruitment event (e.g., an 

annual ten-fold increase in the background recruitment level), we would have expected average 

lengths to decrease dramatically for a few years followed by a quick upward rebound before a 

return to the long-term equilibrium. In the case of a long-term increasing trend in fishing 

mortality, we would have expected a slow, constant decline in average length. We did not 

observe such patterns in average length over time in our study and this suggests that potential 

fluctuations in recruitment levels over time were not significant enough to affect our average 

length estimates and that fishing mortality was more or less constant. Furthermore, the fish 

abundance time series from diver surveys did not reveal major trends, although these 

observations were fairly variable and only started in 2005. Despite these issues, these time series 

observations also support the general equilibrium assumption. It is worth noting again that 

because we assumed the populations were at equilibrium, a finding that a stock may be

experiencing overfishing also meant that the stock may be overfished (and vice versa).

A second key assumption was that size composition, abundance, and catch data were 

representative of the true population around the MHI. Both the underwater visual survey and 

commercial report data sets had strengths and weaknesses. The underwater surveys by scuba 

divers did not reach depths beyond 30 m due to safety and time constraints, thus underestimating 

total population size for species with depth range extending beyond this depth. However, diver 

surveys were able to sample remote and exposed areas of the MHI that are likely visited less 

frequently by fishers. The size composition and abundance data for the visual survey data set was 

thus more representative of nearshore (< 30-m deep) communities but encompassed the entire 

nearshore waters in the MHI, including remote, lightly-populated, and relatively inaccessible 

sections of coastlines. On the other hand, size composition data from commercial reports 

included information on deeper fish communities, but were less likely to be representative of 

inaccessible coastlines. Despite these potential biases, the size composition information from 

these two disparate data sets have been shown to be similar suggesting that the average lengths 

used in the current report were likely representative of the real values (Nadon et al., 2015). It is 

also important to note that the population abundance estimate from the diver surveys assumed a 

catchability coefficient equal to the area of a single survey divided by the total hard-bottom 

habitat area above 30 m. In other words, we did not assume any detectability bias which could 

have an impact on population biomass estimates for certain, more mobile species (jacks, 

snappers, larger parrotfishes). However, for more mobile species we did not use diver survey 
16 

abundance estimates for C30 and OFL estimation because of this potential bias, and instead used 

catch based abundance estimates. 

The total catch estimates used in this report came from the commercial reports and the 

HMRFS program for recreational catches (which are the vast majority of the total catch), both of 

which have issues. The commercial reports may under-estimate the catch given that it is selfreported. The HMRFS catches are based on an interpolation of total fishing effort from telephone 

surveys, combined with creel surveys, and suffer from low sampling effort. These issues reduced 

our confidence in catch-derived C30. However, for most species, diver-survey based C30 were 

also available, which helped verify catch-derived metrics.

Third, it is highly likely that segments of fish stocks located around more heavily populated 

islands (i.e., Oahu, Maui) face considerably higher fishing pressure than more isolated parts of 

the MHI. However, it is not entirely clear to what level reef fish populations are connected 

between islands, in terms of larval exchange and/or adult movement. For example, a tagging 

study failed to detect inter-island movements for tagged Caranx ignobilis, a large and highly 

mobile predator (Meyer et al., 2007). Conversely, a State of Hawaii tagging program did record a 

kahala jack (Seriola dumerili, amberjack) swimming hundreds of kilometers from the NWHI to 

the MHI in a 3-year timespan (Tagawa & Clayward, 2006). Genetic connectivity studies indicate 

that most reef fish species have no genetic structuring across the Hawaiian archipelago (Rivera et 

al., 2004; Craig et al., 2007; Gaither et al., 2010). However, the absence of genetic structure does 

not necessarily imply that stocks are well-connected at time scales relevant to population 

dynamic processes. More informatively, recent genetic parentage analyses of two coral reef fish 

species in Australia have found parent-offspring pairs at distances up to 250 km, with a median

dispersal distance of 110 km and 190 km (Williamson et al., 2016). As shown in Table 2, the 

longest distance between islands in the MHI is 116 km (Oahu – Kauai), with most islands 

separate by much shorter distances. Another parentage study conducted on Hawaii Island found 

yellow tang surgeonfish parent-offspring pairs separated by up to 184 km, although they did not 

attempt to find cross-channel pairs (Christie et al., 2010). Furthermore, a recent study of passive 

pelagic particle connectivity in the MHI, based on a pelagic larval duration of 45 days found a 

median distance for successful settlements around 100 km (Wren et al., 2016) and that crosschannel dispersal can be common. Population connectivity within the MHI is still an open 

question and will require further research attention, however, based on current research, it 

appears that our MHI-scale analyses are appropriate. As a side note, it is generally well-accepted 

that the MHI and NWHI reef fishes form different stocks, and that little larval or adult exchange 

exists between these two regions given the dominant current direction and the large distances 

involved, with the exception of the kahala example mentioned above (Toonen et al., 2011; Wren 

et al., 2016). 

Fourth, for many species, we had to use life history parameters from other Pacific areas. It is 

possible that these values change geographically and with environmental conditions (Choat & 

Robertson, 2002; Gust et al., 2002, although see Donovan et al., 2013). The availability of an

extensive underwater visual survey data set for the relatively pristine NWHI allowed Nadon et 

al. (2015) to evaluate the validity of the length-based mortality model used in the current report, 

as well as the validity of our life history information. Nadon et al. (2015) used independent 
17 

estimates of M from the NWHI (where Z derived from average length is assumed to be equal to 

M) to derive an estimate of average cohort survivorship (S) to maximum age (aλ). They obtained 

a value close to 0.04. The exact survivorship value is linked to the sampling effort in the data set

from which aλ is obtained (i.e., the larger the number of aged individuals, the greater the chance 

of finding extremely old individuals that are not representative of a 5% or even 1% cohort 

survivorship value; Kenchington, 2014). Since the aλ value for reef fishes generally comes from 

life history studies with less than 100 aged individuals, it is possible that these values represent 

cohort survivorship higher than 1.5%, which is what our analysis suggests. For species with no 

published life history parameters, we used the approach presented in Nadon & Ault (2016) to 

provide first-step estimates. This approach uses a local estimate of Lmax which may be biased 

downward in heavily fished stocks (and thus result in biased life history parameters). This is less 

of an issue in the current report given that length data in the pristine NWHI were available to 

generate Lmax estimates. 

Future directions 

The Pacific Islands Fisheries Science Center is conducting research on a wide variety of 

subjects that will help address some of the concerns mentioned above. The Coral Reef 

Ecosystem Program, with assistance from the Stock Assessment Program, will continue 

collecting fisheries-independent diver data. This data set, in conjunction with longer HMRFS and 

DAR catch data sets, will eventually have a time-series of sufficient length to run more 

advanced, non-equilibrium models. The continuing efforts in deep-water surveys using 

underwater cameras will also provide abundance and size composition data for a section of the 

reef fish populations that is not accessible by diver survey and may be significantly different. 

These camera system deployments are also generating deep-water habitat information. The Life 

History Program at PIFSC is continuing their work on growth, maturity, and longevity of local 

stocks in the U.S. Pacific which will lead to more appropriate life history parameters and will 

allow further assessment for data-less species. Finally, new population genetic work, mainly at

the University of Hawaii, can provide further information regarding the scale of reef fish 

population connectivity across the MHI and depending on the results may lead to future 

assessments being conducted at a different scale (e.g., island or smaller island group). 
18 

ACKNOWLEDGEMENTS

This technical memo was made possible by the work of a large number of people across 

multiple NOAA offices in Hawaii. The Coral Reef Ecosystem Program at PIFSC collected much 

of the diver survey data under the supervision of R. Brainard and I. Williams, with the assistance 

of the crew and officers of the NOAA Ship Hi’ialakai and Oscar Elton Sette. The Life History 

Program at PIFSC generated several of the maturity, growth, and longevity information used in 

this document (E. DeMartini, B. Taylor, A. Andrews, and J. O’Malley). The work contained in 

this document was also greatly improved by a number of reviewers (K. Stokes, G. Pilling, C. 

Dichmont, H. Choat, and A. Yau).
19 

REFERENCES

Alagaraja, K. 

1984. Simple methods for estimation of parameters for assessing exploited fish stocks.

 Indian Journal of Fisheries 31:177–208. 

Allen, G. R. 

1985. Snappers of the world: an annotated and illustrated catalogue of Lutjanid species 

known to date. Food and Agriculture Organization of the United Nations. 

Andrews, A. H., E. E. DeMartini, J. A. Eble, B. M. Taylor, D. C. Lou, and R. L. Humphreys. 

2016. Age and growth of bluespine unicornfish (Naso unicornis): a half-century life-span for 

 a keystone browser, with a novel approach to bomb radiocarbon dating in the Hawaiian 

 Islands. Canadian Journal of Fisheries and Aquatic Sciences 73:1575–1586. 

Ault, J. S., S. G. Smith, and J. A. Bohnsack. 

2005. Evaluation of average length as an estimator of exploitation status for the Florida 

coral-reef fish community. ICES Journal of Marine Science 62:417–423. 

Ayotte, P., K. McCoy, A. Heenan, I. Williams, and J. Zamzow. 

2015. Coral Reef Ecosystem Program Standard Operating Procedures: Data Collection for 

 Rapid Ecological Assessment Fish Surveys. Available from 

 http://www.pifsc.noaa.gov/library/pubs/admin/PIFSC_Admin_Rep_15-07.pdf. 

Beverton, R. J. H., and S. J. Holt. 

1956. A review of methods for estimating mortality rates in exploited fish populations, with 

special reference to sources of bias in catch sampling. Rapports et proces-verbaux des 

 reunions du Conseil International pour l’Exploration de la Mer 140:67–83.

Brandt, M. E. et al. 

2009. A cooperative multi-agency reef fish monitoring protocol for the Florida Keys coral 

reef ecosystem. Natural Resource Report NPS/SFCN/NRR - 2009/150, National Park 

Service, Fort Collins. 

Cesar, H. S. J., and P. van Beukering. 

2004. Economic valuation of the coral reefs of Hawai’i. Pacific Science 58:231–242. 

Choat, J. H., and L. M. Axe. 

1996. Growth and longevity in acanthurid fishes; an analysis of otolith increments. Marine 

 Ecology-Progress Series 134:15–26. 

Choat, J. H., and D. R. Robertson. 

2002. Age-based studies on coral reef fishes. Pages 57–80 Coral Reef Fishes: Dynamics and 

Diversity in a Complex Ecosystem. Academic Press, San Diego.
20 

Christie, M. R., B. N. Tissot, M. A. Albins, J. P. Beets, Y. Jia, D. M. Ortiz, S. E. Thompson, and 

M. A. Hixon. 

 2010. Larval Connectivity in an Effective Network of Marine Protected Areas. PLoS ONE 

5:e15715. 

Clark, W. G. 

2002. F35% Revisited Ten Years Later. North American Journal of Fisheries Management 

22:251–257. 

Cole, K. S. 

2009. Size-dependent and age-based female fecundity and reproductive output for three 

Hawaiian goatfish (Family Mullidae) species, Mulloidichthys flavolineatus (yellowstripe 

goatfish), M. vanicolensis (yellowfin goatfish), and Parupeneus porphyreus (whitesaddle 

goatfish). Report to the Division of Aquatic Resources Dingell-Johnson Sport Fish 

Restoration. 

Craig, M. T., J. A. Eble, B. W. Bowen, and D. R. Robertson. 

2007. High genetic connectivity across the Indian and Pacific Oceans in the reef fish 

Myripristis berndti (Holocentridae). Marine Ecology-Progress Series 334:245–254. 

Craig, M. T., and E. C. Franklin. 

2008. Life history of Hawaiian “redfish”: a survey of age and growth in “aweoweo 

 (Priacanthus meeki) and u”u (Myripristis berndti). Hawaii Institute of Marine Biology, 

Kaneohe, Hawaii.

DeMello, J. D. 

2004. Commercial marine landings from fisheries on the coral reef ecosystem of the 

Hawaiian Archipelago. Proceedings of the 2001 Fisheries Symposium of Hawai’i. 

American Fisheries Society - Hawaii Chapter, Honolulu. 

Donovan, M. K., A. M. Friedlander, E. E. DeMartini, M. J. Donahue, and I. D. Williams. 

2013. Demographic patterns in the peacock grouper (Cephalopholis argus), an introduced 

 Hawaiian reef fish. Environmental Biology of Fishes 96:981–994. 

Eble, J. A., R. Langston, and B. W. Bowen. 

2009. Growth and reproduction of Hawaiian Kala, Naso unicornis. Division of Aquatic 

 Resources report, Honolulu. 

Ehrhardt, N. M., and J. S. Ault. 

1992. Analysis of two length-based mortality models applied to bounded catch length 

frequencies. Transactions of the American Fisheries Society 121:115–122. 
21 

Everson, A. R., and A. Williams. 

1989. Maturation and Reproduction in Two Hawaiian Eteline Snappers, Uku, Aprion 

virescens, and Onaga, Etelis cormcans. Fishery Bulletin 87: 877–888. 

Friedlander, A. M., and J. D. Parrish. 

1997. Fisheries harvest and standing stock in a Hawaiian Bay. Fisheries Research 32:33–50. 

Gabriel, W. L., M. P. Sissenwine, and W. J. Overholtz. 

1989. Analysis of spawning stock biomass per recruit: an example for Georges Bank 

 haddock. North American Journal of Fisheries Management 9:383–391. 

Gaither, M. R., R. J. Toonen, D. R. Robertson, S. Planes, and B. W. Bowen. 

2010. Genetic evaluation of marine biogeographical barriers: perspectives from two 

widespread Indo-Pacific snappers (Lutjanus kasmira and Lutjanus fulvus). Journal of 

 Biogeography 37:133–147. 

Gulko, D., J. E. Maragos, A. M. Friedlander, and R. E. Brainard. 

2002. Status of coral reefs in the Hawaiian Archipelago. Pages 155–182 The state of coral 

reef ecosystems of the United States and Pacific Freely Associated States: 2002. National 

 Oceanic and Atmospheric Administration report, Silver Spring. 

Gust, G., J. H. Choat, and A. Ackerman. 

2002. Demographic plasticity in tropical reef fishes. Marine Biology 140:1039–1051. 

Hamnett, M., M. Lui, and D. Johnson. 

2006. Fishing, ocean recreation, and threats to Hawaii’s coral reefs. Hawaii Coral Reef 

 Initiative, Honolulu. 

Hewitt, D. A., and J. M. Hoenig. 

2005. Comparison of two approaches for estimating natural mortality based on longevity. 

Fishery Bulletin 103:433–437. 

Hoenig, J. M. 

1983. Empirical use of longevity data to estimate mortality rates. Fisheries Bulletin 82:898–

 903. 

Holland, K. N., J. D. Peterson, C. G. Lowe, and B. M. Wetherbee. 

1993. Movements, distribution and growth rates of the white goatfish Mulloidichthys 

 flavolineatus in a fisheries conservation zone. Bulletin of Marine Science 52:982–992. 

Hordyk, A., K. Ono, S. Valencia, N. Loneragan, and J. Prince. 

2015. A novel length-based empirical estimation method of spawning potential ratio (SPR), 

 and tests of its performance, for small-scale, data-poor fisheries. ICES Journal of Marine 

Science 72:217–231. 
22 

Howard, K. G. 

2008. Community structure, life history, and movement patterns of parrotfishes: large 

 protogynous fishery species. PhD. University of Hawaii at Manoa, Honolulu. 

Jehangeer, M. I. 

2003. Some population parameters of the goatfish, Mulloidichthys vanicolensis from the 

 lagoon of Mauritius. ACP-EU Fisheries Research Report (14).

Kenchington, T. J. 

2014. Natural mortality estimators for information-limited fisheries. Fish and Fisheries 

15:533–562. 

Kittinger, J. N., J. M. Pandolfi, J. H. Blodgett, T. L. Hunt, H. Jiang, K. Maly, L. E. 

McClenachan, J. K. Schultz, and B. A. Wilcox. 

2011. Historical reconstruction reveals recovery in Hawaiian coral reefs. PLoS ONE 

6:e25460. 

Kritzer, J. P., C. R. Davies, and B. D. Mapstone. 

2001. Characterizing fish populations: effects of sample size and population structure on the 

 precision of demographic parameter estimates. Canadian Journal of Fisheries and Aquatic 

Sciences 58:1557–1568. 

Kulbicki, M., N. Guillemot, and M. Amand. 

2005. A general approach to length-weight relationships for New Caledonian lagoon fishes. 

 Cybium 29:235–252. 

Meyer, C. G., K. N. Holland, and Y. P. Papastamatiou. 

2007. Seasonal and diel movements of giant trevally Caranx ignobilis at remote Hawaiian 

atolls: implications for the design of marine protected areas. Marine Ecology Progress 

Series 333:13–25. 

Moffitt, R. B. 

1979. Age, growth, and reproduction of the kumu, Parupeneus porphyreus. M.Sc. thesis. 

 University of Hawaii, Honolulu. 

Morales-Nin, B., and S. Ralston. 

1990. Age and growth of Lutjanus kasmira (Forskaal) in Hawaiian waters. Journal of Fish 

 Biology 36:191–203. 

Murty, V. S. 

2002. Marine Ornemental Fish Resources of Lakshadweep. CMFRI, Spl. Pub. 72: 134 pp. 
23 

Nadon, M. O., and J. S. Ault. 

2016. A stepwise stochastic simulation approach to estimate life history parameters for data-

 poor fisheries. Canadian Journal of Fisheries and Aquatic Sciences 73:1874–1884. 

Nadon, M. O., J. S. Ault, I. D. Williams, S. G. Smith, and G. T. DiNardo. 

2015. Length-based assessment of coral reef fish populations in the Main and Northwestern 

Hawaiian Islands. PLoS ONE 10:e0133960. 

Pyle, R. L. et al. 

2016. A comprehensive investigation of mesophotic coral ecosystems in the Hawaiian 

 Archipelago. PeerJ 4:e2475. 

Restrepo, V. R. et al. 

1998. Technical guidance on the use of precautionary approaches in implementing national 

 standard 1 of the Magnuson-Stevens Fishery Conservation and Management Act. NOAA 

Technical Memorandum NMFSF/ SPO-031, NOAA, USA: 54 pp. 

Rivera, M. A. J., C. D. Kelley, and G. K. Roderick. 

2004. Subtle population genetic structure in the Hawaiian grouper, Epinephelus quernus

(Serranidae) as revealed by mitochondrial DNA analyses. Biological Journal of the 

 Linnean Society 81:449–468. 

Ruel, J. J., and M. P. Ayres. 

1999. Jensen’s inequality predicts effects of environmental variation. Trends in Ecology & 

 Evolution 14:361–366. 

Sabater, M. G., and P. Kleiber. 

2013. Improving specification of acceptable biological catches of data-poor reef fish stocks 

 using a biomass-augmented catch-MSY approach. Page 24. Western Pacific Regional 

 Fishery Management Council, Honolulu, HI. 

Seki, M. P. 

1986. Carangidae. Pages 86–87 Fishery atlas of the Northwestern Hawaiian Islands. NOAA 

 Tech. Rep. NMFS 38. 

Smith, A., and P. Dalzell. 

1993. Fisheries resources and management investigations in Woleai Atoll, Yap State, 

 Federated States of Micronesia. Inshore Fish. Res. Proj., Tech. Doc., South Pacific 

 Commission. Noumea, New Caledonia. 

Smith, S. G., J. S. Ault, J. A. Bohnsack, D. E. Harper, J. Luo, and D. B. McClellan. 

2011. Multispecies survey design for assessing reef-fish stocks, spatially explicit 

 management performance, and ecosystem condition. Fisheries Research 109:25–41. 
24 

Sudekum, A. E., J. D. Parrish, R. L. Radtke, and S. Ralston. 

1991. Life history and ecology of large jacks in undisturbed, shallow, oceanic communities. 

Fishery Bulletin 89:493–513. 

Tagawa, A., and T. Clayward. 

2006. Hawaii’s ulua and papio tagging project 2000 to 2004. 06-01, DAR Technical Report. 

 Honolulu, HI. 

Then, A. Y., J. M. Hoenig, N. G. Hall, and D. A. Hewitt. 

2015. Evaluating the predictive performance of empirical estimators of natural mortality rate 

 using information on over 200 fish species. ICES Journal of Marine Science 72:82–92. 

Toonen, R. J. et al. 

2011. Defining boundaries for ecosystem-based management: a multispecies case study of 

 marine connectivity across the Hawaiian Archipelago. Journal of Marine Biology 

2011:1–13. 

Williams, I. D., B. L. Richards, S. A. Sandin, J. K. Baum, R. E. Schroeder, M. O. Nadon, B. 

Zgliczynski, P. Craig, J. L. McIlwain, and R. E. Brainard.

 2011. Differences in reef fish assemblages between populated and remote reefs spanning 

 multiple archipelagos across the central and western Pacific. Journal of Marine Biology 

2011:1–14. 

Williams, I., and H. Ma. 

2013. Estimating catch weight of reef fish species using estimation and intercept data from 

 the Hawaii Marine Recreational Fishing Survey. Page 61. Honolulu: NOAA Pacific 

Islands Fisheries Science Center Administrative Report H-13-04. 

Williamson, D. H. et al. 

2016. Large-scale, multidirectional larval connectivity among coral reef fish populations in 

the Great Barrier Reef Marine Park. Molecular Ecology 25: 6039-6054. 

Wren, J. L. K., D. R. Kobayashi, Y. Jia, and R. J. Toonen. 

2016. Modeled Population Connectivity across the Hawaiian Archipelago. PLOS ONE 

11:e0167626. 

Zeller, D., S. Booth, and D. Pauly. 

2005. Reconstruction of coral reef fisheries catches for US associated islands in the Western 

 Pacific Region, 1950 to 2002. Western Pacific Regional Fishery Management Council 

 report, Honolulu. 
25 

TABLES AND FIGURES

Table 1.--List of parameters used in the document. 

Parameter Definition

α, β Parameters of the length-weight relationship

aλ Oldest recorded age (i.e., longevity)

a0 Theoretical age at which length equals zero from the von Bertalanffy growth curve

B Total population biomass

C30 Catch limit resulting in SPR = 0.3 

F Instantaneous annual fishing mortality rate

F30 Instantaneous annual fishing mortality rate resulting in SPR = 0.3

K Brody growth coefficient of the von Bertalanffy growth curve

Lbar or L Average length in the exploited phase of a stock

Lc30 Size at first capture limit resulting in SPR = 0.3

Linf or L∞ Expected length at infinite age from the von Bertalanffy growth curve

Lλ Expected length at the oldest recorded age

Lmat Length at which 50% of females reach maturity

Lmax Longest length in a growth study or 99th percentile of lengths in a population survey

LS50 Length at 50% selectivity

LS95 Length at 95% selectivity

M Instantaneous annual natural mortality rate

OFL Overfishing limit, defined as the median of the C30 distribution

S Survivorship at maximum recorded age

SPR Spawning potential ratio

Z Instantaneous annual total mortality rate
26 

Table 2.-- Information summary of the two principal regions of the Hawaiian Islands, 

including the four subregions of the main Hawaiian Islands. Reef area is to 30-m depth and 

excludes soft bottom habitat. Source: CREP and Hawaii Mapping Research Group 

bathymetric synthesis data set. 

Region

Human 

population 

(2010)

Reef area

(km2)

Prop. of total 

reef in region

Pop. per 

reef area

(# km-2)

Channel 

width

(km)a

Main Hawaiian Is.

 Hawaii 185,079 168 0.18 1099 48

 Maui Nui 154,950 269 0.28 577 48-42

 Oahu 953,000 251 0.26 3794 42-116

 Kauai-Niihau 65,819 274 0.28 240 116-220 a Channel widths from east to west.

Table 3.-- Area of sea floor in the MHI by depth zones, in state and federal waters (soft 

and hard bottom). Depth range extends to 250 m which is close to the maximum recorded 

depths for the species included in this report. Source: CREP and Hawaii Mapping 

Research Group bathymetric synthesis data set. 

Depth (m) Hectares of sea floor Cumulative 

percent in 

fed. Waters Min Max State waters Federal waters Total

0 30 126,930 0 126,930 0

30 40 37,670 57 37,727 < 1

40 50 32,960 23,097 56,057 10

50 60 32,770 27,893 60,663 18

60 70 31,725 19,711 51,436 21

70 80 31,667 9,151 40,818 21

80 90 27,698 6,343 34,041 21

90 100 25,343 7,560 32,903 21

100 150 88,823 32,365 121,188 22

150 200 44,440 24,036 68,476 24

200 250 39,120 32,261 71,381 26
27 

Table 4.--Coefficient of variation of 4 life history parameters at various sample 

sizes. Linf, K, and amax from Kritzer et al. (2001), and Lmat from Nadon (unpubl.). 

Sample size CV Linf CV K CV Lmat CV amax

25 0.167 0.568 0.070 0.190

50 0.111 0.299 0.048 0.168

75 0.078 0.250 0.036 0.147

100 0.060 0.222 0.031 0.129

125 0.050 0.190 0.027 0.118

150 0.045 0.172 0.025 0.113

200 0.040 0.142 0.021 0.092

300 0.030 0.120 0.017 0.074

500 0.021 0.095 0.013 0.056
28 

Table 5.--Species summary of selected stock metrics. Bold text indicates stocks considered overfished

/overfishing according to the SPR = 30% based biological reference point. Overfishing is defined as F/F30

> 1 and overfished is defined as SPR < 0.30. 

Species

Man.

unit Group

LH 

source

Max 

depth 

(m)

Percent 

in fed. 

waters F/F30 SPR

Pop. from 

catch

(kg)

Pop. from 

survey

(kg)

Acanthuridae

Acanthurus blochii C Ac E 80 21 2.3 0.12 - 365,000

Acanthurus dussumieri C Ac E 131 22 0.8 0.36 356,000 719,000

Naso brevirostris C Ac E 122 22 1.9 0.14 - 132,000

Naso hexacanthus C Ac E 124 22 2.0 0.13 30,000 -

Naso lituratus C Ac E 93 21 1.3 0.25 30,000 452,000

Naso unicornis C Ac L 120 22 6.0 0.03 - 364,000

Carangidae

Carangoides orthogrammus C Ca S 235 26 0.7 0.41 123,000 - 

Caranx ignobilis B ND7 L 228 26 1.1 0.28 1,070,000 -

Caranx melampygus C Ca L 230 26 0.7 0.40 811,000 -

Lutjanidae 

Aprion virescens B ND7 L 203 24 0.9 0.33 758,000 434,000

Lutjanus fulvus C Lu S 128 22 0.9 0.33 48,000 180,000

Lutjanus kasmira B ND7 L 265 26 0.3 0.62 181,000 496,000

Mullidae

Mulloidichthys flavolineatus C Mu L 97 21 0.5 0.49 307,000 42,000

Mulloidichthys pflueregi C Mu S 242 26 0.7 0.41 21,000 -

Mulloidichthys vanicolensis C Mu L 132 22 0.4 0.55 139,000 35,000

Parupeneus cyclostomus C Mu S 113 21 1.3 0.24 12,000 77,000

Parupeneus insularis C Mu S 90 21 0.4 0.57 5,000 42,000

Parupeneus porphyreus C Mu L 140 22 1.9 0.15 15,000 14,000

Scaridae

Calotomus carolinus C Sc S 71 21 2.2 0.13 - 38,000

Chlorurus perspicillatus C Sc S 80 21 0.5 0.54 - 79,000

Chlorurus spilurus C Sc S 34 0 1.4 0.23 - 139,000

Scarus dubius C Sc S 80 21 0.6 0.45 - 33,000

Scarus psittacus C Sc S 48 10 0.7 0.41 - 130,000

Scarus rubroviolaceus C Sc L 68 21 1.2 0.26 - 624,000

Other families

Cephalopholis argus C Se L 80 21 0.1 0.80 232,000 777,000

Monotaxis grandoculis C Le S 101 22 0.8 0.38 29,000 232,000

Myripristis berndti C Ho L 159 22 0.4 0.59 - 260,000

Management units: C = Coral Reef Management Unit Species (CREMUS), B = Bottomfish Management Unit Species (BMUS)

Grouping: Ac = Acanthuridae, Ca = Carangidae, Ho = Holocentridae, Le = Lethrinidae, Lu = Lutjanidae, Mu = Mullidae, ND7 = 

Non-deep 7 bottomfish, Se = Serranidae, Sc = Scaridae.

Life history source: E = external (different geographic location), L = local (from Hawaii), S = stepwise approach (Nadon & Ault, 

2016).
29 

Figure 1.--Map of the Hawaiian Islands (including Northwestern Hawaiian Islands in inset), with 

the four subregions. Figure from Nadon et al. (2015). 
30 

Figure 2.--Map of the 8 main Hawaiian Islands with deep water depth zones (0-m to 

250-m depths). Black contour lines represent the 3 nautical mile State waters limit. Islands are 

not to scale. Data source: CREP and Hawaii Mapping Research Group. 


33 

Figure 5.--Survey sectors of the MHI (islands at different scales). These sectors were used when 

running bootstrap analyses for biomass density data from diver surveys. There are 3 habitat 

categories (simple, complex, and coral-dominated) and 3 fishing intensity category (green = low, 

yellow = moderate, and red = high). Habitat categories were derived from CREP habitat survey 

data and the fishing categories are based on accessibility and human population density. 
34 
35 

SPECIES REPORTS
36 

Acanthurus blochii

Ringtail surgeonfish, pualu 

Acanthuridae (surgeonfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 363 61 mm

K 0.25 0.14 yr 24 Mean: Choat & Robertson (2002), SD: Kritzer (2001) -1

a0 -0.38 - yr

Lmat 276 19 mm 24 Mean: 76% of Linf, SD: Nadon (unpublished)

Longevity 35 6.7 yr 24 Mean: Choat & Robertson (2002), SD: Kritzer (2001)

L-W α 1.87e-5 - - - Kulbicki (2005) L-W β 3.03

LS50 225 - mm - Estimated. LS95 250

L diver survey 299 3 mm 672 NOAA-CREP diver survey

L commercial - - mm - -

L combined - - mm - -

Max. depth 80 - m - Pyle et al. (2016)

Federal waters 21 - % - -

Stock status and other output parameters 

Parameter Median SD Unit

M 0.09 0.02 yr-1

F 0.27 0.21 yr-1

F30 0.12 0.03 yr-1

F/F30 2.3 1.7 -

SPR 0.12 0.17 -

SPR < 0.30 iterations 84 - %

Lc30 290 - mm

General comments

The DAR commercial reporting system combines A. xanthopterus with this species. The commercial catch for 

these two species is listed above, but as a reference only. In the HMRFS data set, the A. xanthopterus catch is 

4× larger than A. blochii. 

Population abundance has been slowly rising since 2007 while Lbar has remained fairly stable at around 30cm, 

suggesting a population near equilibrium. Selectivity had to be estimated from A. dussumieri, a similar species, 

given the absence of fishery data. A sensitivity run with LS50 at 250 and LS95 at 280 had little impact on the 

results (F: 0.28, SPR: 0.11). There were some concerns with the LH parameters, which came from an 

Australian study with a low sample size and we therefore ran extra analyses using the stepwise approach (Lmax: 

420 mm gave Linf: 390 mm, K:0.42, M: 0.1). The higher Linf value resulted in a much higher F (0.61) and lower 

SPR (0.03). However, the C30 was mostly unchanged (40,300 kg). 

The annual total catch estimate (5,668 kg) is fairly small compared to the OFL estimate (38,300 kg), even 

though it includes A. xanthopterus catches. This amount of catch is too small to explain the level of fishing 

mortality estimated from Lbar. However, the diver survey data for this species is fairly reliable (i.e., easily 

identifiable, common species, non-cryptic) and therefore the C30 estimates from these surveys should be 

reliable.

Parameter Median SD Unit

B from catch - - -

B from survey 365,392 48,886 kg

Commercial catch 3,604 1,362 kg

Recreational catch 1,394 4,005 kg

Total catch 5,668 3,042 kg

C30 from catch - - -

C30 from survey 38,300 9,000 kg
37 

Acanthurus blochii 

Life history parameter distributions.
38 

Acanthurus blochii 

Abundance index from UVS (blue circles, ±SE). 

Size structure and average length time series from UVS (±SE).
39 

Acanthurus blochii 

Stock status parameter distributions (SPR: small bar shows 0.30 level). 

C30 (left) and population size (right) distributions.
40 

Acanthurus blochii 

Overfishing probability for a range of C30 levels (UVS – blue dotted line). OFL is represented by 

a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from survey 

(1000 kg)

Overfishing 

probability

C30 from survey 

(1000 kg)

0.10 28.4 0.31 34.2

0.11 28.8 0.32 34.4

0.12 29.1 0.33 34.7

0.13 29.5 0.34 34.9

0.14 29.8 0.35 35.1

0.15 30.1 0.36 35.4

0.16 30.4 0.37 35.5

0.17 30.7 0.38 35.7

0.18 31.0 0.39 35.9

0.19 31.4 0.40 36.2

0.20 31.6 0.41 36.4

0.21 31.9 0.42 36.7

0.22 32.2 0.43 36.9

0.23 32.5 0.44 37.1

0.24 32.7 0.45 37.3

0.25 32.9 0.46 37.5

0.26 33.1 0.47 37.8

0.27 33.4 0.48 38.0

0.28 33.6 0.49 38.2

0.29 33.9 0.50 38.3

0.30 34.0
41 

Acanthurus blochii 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 364 0.31 324

0.11 362 0.32 322

0.12 358 0.33 320

0.13 356 0.34 317

0.14 353 0.35 315

0.15 351 0.36 315

0.16 349 0.37 313

0.17 349 0.38 310

0.18 346 0.39 308

0.19 344 0.40 306

0.20 342 0.41 306

0.21 340 0.42 304

0.22 338 0.43 302

0.23 335 0.44 299

0.24 335 0.45 299

0.25 333 0.46 297

0.26 331 0.47 295

0.27 331 0.48 295

0.28 328 0.49 292

0.29 326 0.50 290

0.30 324
42 

Acanthurus dussumieri

Eyestripe surgeonfish, palani 

Acanthuridae (surgeonfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 371 41 mm

K 0.296 0.089 yr 43 Mean: Choat & Robertson (2002), SD: Kritzer (2001) -1

a0 -0.29 - yr

Lmat 282 14 mm 50 Mean: Choat & Robertson (2002), SD: Nadon (unpublish.)

Longevity 28 4.7 yr 43 Mean: Choat & Robertson (2002), SD: Kritzer (2001)

L-W α 2.33e-5 - - - Kulbicki (2005) L-W β 3.03

LS50 230 - mm - DAR commercial data LS95 260

L diver survey 323 3 mm 1198 NOAA-CREP diver survey

L commercial 334 1 mm 6403 DAR commercial data

L combined 333 2 mm - -

Max. depth 131 - m - Pyle et al. (2016)

Federal waters 22 - % - -

Stock status and other output parameters 

Parameter Median SD Unit

M 0.11 0.02 yr-1

F 0.12 0.08 yr-1

F30 0.14 0.02 yr-1

F/F30 0.8 0.6 -

SPR 0.36 0.21 -

SPR < 0.30 iterations 37 - %

Lc30 129 - mm

General comments

Both population abundance and Lbar (UVS and commercial) time series were relatively stable suggesting a 

population mostly at equilibrium. Recreational catch did seem to be increasing, but the yearly estimates are 

fairly variable and this trend may have been spurious. Lbar estimates from the UVS and commercial data sets 

were almost identical. The LH parameters were obtained from an Australian study with a limited sample size. 

A sensitivity run using the stepwise approach gave the following results: Lmax: 428 mm, Linf: 399 mm, K: 0.40, 

M: 0.1, F30: 0.13. The higher Linf value resulted in a higher F (0.25) and lower SPR (0.14). The diver-survey

C30 was mostly unchanged (81,000 kg), but the C30 from catch was reduced to 24,000 kg due to the higher F. 

The population estimates derived from the catch was about half the size from the diver surveys. The lower 

population estimate from the catch data results in a lower catch-derived OFL estimate (44,900 kg vs. 90,100 

kg). Given the quality of the diver data (i.e., high observation count, appropriate sampling design) and the 

similarity in F30 estimates between the external LH parameters and the stepwise-derived LH parameters, the 

survey-derived C30 is likely more reliable. The true population size may be even larger than the diver estimate 

(718,622 kg) given that this species’ habitat extends far beyond diver survey depth (131 m vs. 30 m). 

Parameter Median SD Unit

B from catch 356,000 938,000 kg

B from survey 718,622 106,385 kg

Commercial catch 13,370 2,294 kg

Recreational catch 21,529 12,334 kg

Total catch 35,959 11,712 kg

C30 from catch 44,900 121,000 kg

C30 from survey 90,100 18,600 kg
43 

Acanthurus dussumieri

Life history parameter distributions.
44 

Acanthurus dussumieri 

Abundance index from UVS (blue circles, ±SE) and total catch time series from recreational

(green squares) and commercial (orange triangles) sectors. 

Size structure from commercial catch (top left) and UVS (top right). Average length time series 

(blue circles – UVS, orange triangles – commercial data, ±SE). 
45 

Acanthurus dussumieri 

Stock status parameter distributions (SPR: small bar shows 0.30 level).
46 

Acanthurus dussumieri 

C30 and current total catch (left) and population size (right) distributions.
47 

Acanthurus dussumieri 

Overfishing probability for a range of C30 levels (catch - orange dashed line, UVS – blue dotted 

line). OFLs are represented by small vertical bars. 

Probability of overfishing for various C30 levels. 

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from

survey (1000 kg)

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from survey 

(1000 kg)

0.10 20.4 68.4 0.31 32.2 81.2

0.11 21.1 69.2 0.32 32.8 81.7

0.12 21.8 70.1 0.33 33.4 82.3

0.13 22.4 71.0 0.34 33.9 82.7

0.14 23.0 71.7 0.35 34.6 83.1

0.15 23.6 72.4 0.36 35.1 83.6

0.16 24.2 73.2 0.37 35.7 84.0

0.17 24.8 73.9 0.38 36.3 84.6

0.18 25.3 74.5 0.39 36.9 85.1

0.19 25.8 75.0 0.40 37.6 85.6

0.20 26.3 75.6 0.41 38.3 86.0

0.21 26.9 76.1 0.42 38.9 86.5

0.22 27.4 76.7 0.43 39.7 86.9

0.23 28.0 77.3 0.44 40.2 87.3

0.24 28.6 77.8 0.45 41.0 87.7

0.25 29.1 78.4 0.46 41.7 88.2

0.26 29.7 78.9 0.47 42.6 88.7

0.27 30.2 79.3 0.48 43.3 89.1

0.28 30.7 79.7 0.49 44.1 89.6

0.29 31.2 80.3 0.50 44.9 90.1

0.30 31.7 80.8
48 

Acanthurus dussumieri 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 315 0.31 246

0.11 310 0.32 242

0.12 308 0.33 237

0.13 304 0.34 232

0.14 301 0.35 230

0.15 299 0.36 225

0.16 294 0.37 218

0.17 292 0.38 214

0.18 287 0.39 207

0.19 285 0.40 202

0.20 283 0.41 196

0.21 278 0.42 191

0.22 276 0.43 186

0.23 274 0.44 177

0.24 271 0.45 170

0.25 267 0.46 163

0.26 264 0.47 156

0.27 260 0.48 147

0.28 255 0.49 138

0.29 253 0.50 129

0.30 248
49 

Naso brevirostris

Paletail unicornfish, kala lolo

Acanthuridae (surgeonfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 327 16 mm

K 0.402 0.076 yr 120 Mean: Choat & Robertson (2002), SD: Kritzer (2001) -1

a0 -0.21 - yr

Lmat 269 7 mm 120 Mean: Choat & Robertson (2002), SD: Nadon (unpublish.)

Longevity 25 3.0 yr 120 Mean: Choat & Robertson (2002), SD: Kritzer (2001)

L-W α 6.09e-6 - - - Kulbicki (2005) L-W β 3.24

LS50 200 - mm - Best estimate based on similar surgeonfishes. LS95 220

L diver survey 271 7 mm 561 NOAA-CREP diver survey

L commercial - - mm - No species-specific catch data.

L combined - - mm - -

Max. depth 122 - m - Pyle et al. (2016)

Federal waters 22 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.13 0.02 yr-1

F 0.30 0.16 yr-1

F30 0.16 0.02 yr-1

F/F30 1.9 1.0 -

SPR 0.14 0.12 -

SPR < 0.30 iterations 88 - %

Lc30 264 - mm

General comments

The commercial catch data set for this species includes both N. unicornis and N. annulatus, and therefore 

could not be used to estimate Lbar. The HMRFS data was also fairly unreliable given that this species only had 1 

year with a recreational catch estimate.

Population abundance and Lbar appeared fairly stable, suggesting a population near equilibrium. Size 

selectivity had to be estimated, based on other surgeonfishes. A sensitivity run with LS50 at 225 and LS95 at 250 

had some moderate impact on the results (F = 0.23, SPR = 0.22), but did not change overall conclusions. The 

life history parameters are from a study in Australia, with a decent sample size. Using the stepwise approach to 

generate LH parameters, we obtained the following estimates: Lmax: 416 mm, Linf: 388 mm, K: 0.39, M: 0.10, 

F30: 0.12. Similarly to previous surgeonfishes, the Linf was much higher than the Australian study value. This led 

to a higher F (0.71) and lower SPR (0.02). F30 (0.12) and C30 (13,745 kg) where only slightly lower given the 

similarity in M estimates.

Given the quality of the diver data (i.e., high observation count, appropriate sampling design) and the 

similarity in F30 estimates between the external LH parameters and the stepwise-derived LH parameters, the 

survey-derived C30 is likely reasonable. The true population size may be even larger than the diver estimate 

(132,456 kg) given that this species’ habitat extends beyond diver survey depth (122 m vs. 30 m). 

Parameter Median SD Unit

B from catch - - kg

B from survey 132,456 31,857 kg

Commercial catch - - kg

Recreational catch - - kg

Total catch - - kg

C30 from catch - - kg

C30 from survey 17,800 4,680 kg
50 

Naso brevirostris

Life history parameter distributions.
51 

Naso brevirostris

Abundance index from UVS (blue circles, ±SE). 

Size structure and average length time series from UVS (±SE).
52 

Naso brevirostris

Stock status parameter distributions (SPR: small bar shows 0.30 level).

C30 (left) and population size (right) distributions.
53 

Naso brevirostris

Overfishing probability for a range of C30 levels (UVS – blue dotted line). OFL is represented by 

a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from survey 

(1000 kg)

Overfishing 

probability

C30 from survey 

(1000 kg)

0.10 12.0 0.31 15.6

0.11 12.3 0.32 15.7

0.12 12.5 0.33 15.9

0.13 12.7 0.34 16.0

0.14 12.9 0.35 16.1

0.15 13.1 0.36 16.2

0.16 13.3 0.37 16.3

0.17 13.5 0.38 16.4

0.18 13.7 0.39 16.6

0.19 13.9 0.40 16.7

0.20 14.1 0.41 16.8

0.21 14.2 0.42 16.9

0.22 14.4 0.43 17.0

0.23 14.5 0.44 17.2

0.24 14.7 0.45 17.3

0.25 14.8 0.46 17.4

0.26 14.9 0.47 17.5

0.27 15.1 0.48 17.6

0.28 15.2 0.49 17.7

0.29 15.3 0.50 17.8

0.30 15.5
54 

Naso brevirostris

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 302 0.31 282

0.11 300 0.32 282

0.12 300 0.33 280

0.13 300 0.34 280

0.14 298 0.35 280

0.15 296 0.36 278

0.16 296 0.37 278

0.17 294 0.38 276

0.18 294 0.39 276

0.19 292 0.40 274

0.20 292 0.41 274

0.21 292 0.42 272

0.22 290 0.43 272

0.23 290 0.44 270

0.24 288 0.45 270

0.25 288 0.46 268

0.26 286 0.47 268

0.27 286 0.48 266

0.28 286 0.49 266

0.29 284 0.50 264

0.30 284
55 

Naso hexacanthus

Sleek unicornfish, kala lolo 

Acanthuridae (surgeonfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 599 57 mm

K 0.221 0.061 yr 59 Mean: Choat & Robertson (2002), SD: Kritzer (2001) -1

a0 -0.22 - yr

Lmat 511 22 mm 59 Mean: Choat & Robertson (2002), SD: Nadon (unpub.)

Longevity 44 6.9 yr 59 Mean: Choat & Robertson (2002), SD: Kritzer (2001)

L-W α 4.12e-5 - - - Choat and Axe (1996) L-W β 2.85

LS50 350 - mm - DAR commercial data LS95 410

L diver survey - - mm - NOAA-CREP diver survey

L commercial 507 2 mm 1249 DAR commercial data

L combined - - mm - -

Max. depth 124 - m - BRFA BotCam project

Federal waters 22 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.07 0.01 yr-1

F 0.16 0.08 yr-1

F30 0.08 0.01 yr-1

F/F30 2.0 0.9 -

SPR 0.13 0.14 -

SPR < 0.30 iterations 88 - %

Lc30 497 - mm

General comments

The number of diver survey observations for this species was insufficient to generate reliable Lbar or 

population biomass estimates. The commercial catch increased from 2007 to 2013, but dropped back down to 

2003-2006 levels in the last few years. The recreational catch estimates were fairly variable, making it hard to 

discern any patterns. Lbar have been stable since 2003, which indicated a population near equilibrium. 

The life history parameters came from an Australian study with low sample size. We obtained the following 

parameters from the stepwise approach, which are fairly similar: Lmax: 642 mm, Linf: 614 mm, K: 0.28, M: 

0.10, F30: 0.11. F (0.20), SPR (0.15), and C30 (2,578 kg) were also close to the original results. We also tried 

reducing the survivorship estimate for the M calculation from 0.04 to 0.01. This increased M from 0.07 to 0.10 

and did not change the results significantly (F: 0.21, SPR: 0.15). 

Parameter Median SD Unit

B from catch 29,900 75,600 kg

B from survey - - kg

Commercial catch 1,361 1,434 kg

Recreational catch 2,279 3,884 kg

Total catch 4,185 3,664 kg

C30 from catch 2,260 5,170 kg

C30 from survey - - kg
56 

Naso hexacanthus 

Life history parameter distributions.
57 

Naso hexacanthus 

Total catch time series from recreational (green squares) and commercial (orange triangles) 

sectors. 

Size structure and average length time series from commercial data (±SE)
58 

Naso hexacanthus 

Stock status parameter distributions (SPR: small bar shows 0.30 level).
59 

Naso hexacanthus 

C30 and current total catch (left) and population size (right) distributions.
60 

Naso hexacanthus 

Overfishing probability for a range of C30 levels (commercial data – orange dashed line). OFL is

represented by a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from catch

(1000 kg)

Overfishing 

probability

C30 from catch

(1000 kg)

0.10 0.86 0.31 1.53

0.11 0.89 0.32 1.57

0.12 0.93 0.33 1.60

0.13 0.96 0.34 1.63

0.14 1.00 0.35 1.66

0.15 1.02 0.36 1.70

0.16 1.05 0.37 1.74

0.17 1.09 0.38 1.77

0.18 1.12 0.39 1.81

0.19 1.14 0.40 1.86

0.20 1.18 0.41 1.90

0.21 1.22 0.42 1.93

0.22 1.25 0.43 1.98

0.23 1.27 0.44 2.02

0.24 1.30 0.45 2.07

0.25 1.34 0.46 2.11

0.26 1.38 0.47 2.15

0.27 1.41 0.48 2.18

0.28 1.45 0.49 2.22

0.29 1.47 0.50 2.26

0.30 1.49
61 

Naso hexacanthus 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 578 0.31 536

0.11 574 0.32 532

0.12 572 0.33 532

0.13 570 0.34 528

0.14 567 0.35 528

0.15 567 0.36 525

0.16 564 0.37 525

0.17 564 0.38 522

0.18 560 0.39 522

0.19 556 0.40 518

0.20 556 0.41 514

0.21 556 0.42 514

0.22 553 0.43 511

0.23 550 0.44 511

0.24 550 0.45 508

0.25 546 0.46 508

0.26 546 0.47 504

0.27 542 0.48 500

0.28 539 0.49 500

0.29 539 0.50 497

0.30 536
62 

Naso lituratus

Orangespine unicornfish, umaumalei 

Acanthuridae (surgeonfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 322 36 mm

K 0.341 0.10 yr 58 Mean: Nadon (unpublished), SD: Kritzer (2001) -1

a0 -0.66 - yr

Lmat 250 37 mm 66 Mean: Nadon (unpublished) , SD: Nadon (unpublished)

Longevity 25 4.2 yr 58 Mean: Nadon (unpublished), SD: Kritzer (2001)

L-W α 7.20e-5 - - - Smith and Dalzell (1993) L-W β 2.84

LS50 215 - mm - DAR commercial data LS95 230

L diver survey 276 1 mm 1563 NOAA-CREP diver-survey data set

L commercial 287 2 mm 1098 DAR commercial data set

L combined 280 2 mm - -

Max. depth 93 - m - Pyle et al. (2016)

Federal waters 21 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.13 0.02 yr-1

F 0.21 0.13 yr-1

F30 0.17 0.04 yr-1

F/F30 1.3 0.9 -

SPR 0.25 0.20 -

SPR < 0.30 iterations 62 - %

Lc30 215 - mm

General comments

Population abundance appeared to be relatively stable, with a sharp increase in 2016 which may be spurious. 

Lbar from both data sets were similar and stable from 2003 to 2016, suggesting a population near equilibrium. 

The commercial catch increased slightly from 2008 to 2012, but appear to be declining in recent years. The 

recreational catch was too variable to infer on any temporal patterns.

The life history parameters for this species came from specimens collected in the Mariana islands by PIFSC, 

but they appeared appropriate for the Hawaii population. A sensitivity run using the stepwise approach gave 

nearly identical parameters: Lmax: 350 mm, Linf: 321 mm, K: 0.44, M: 0.1, F30: 0.15, and F: 0.25. 

There was a strong discrepancy between the population size estimates from the catch vs. those from diver 

surveys (30,000 kg vs. 451,619 kg). The catch estimates from both the HMRFS and commercial data sets 

seemed unrealistically low. The diver-derived population estimate should be fairly reliable given that this is a 

commonly encountered species that is easily identifiable and is not particularly afraid of divers. Therefore, the 

C30 from the survey data is likely more reliable than the C30 derived from the catch. The population estimate 

was likely negatively biased given that the population extends to 93 m, which is beyond the diver survey depth 

(30 m) from which the population size is derived. 

Parameter Median SD Unit

B from catch 30,000 205,000 kg

B from survey 451,619 37,121 kg

Commercial catch 544 1,934 kg

Recreational catch 3,730 7,888 kg

Total catch 4,924 7,317 kg

C30 from catch 4,390 27,000 kg

C30 from survey 66,200 15,400 kg
63 

Naso lituratus 

Life history parameter distributions.
64 

Naso lituratus 

Abundance index from UVS (blue circles, ±SE) and total catch time series from recreational

(green squares) and commercial (orange triangles) sectors. 

Size structure from commercial catch (top left) and UVS (top right). Average length time series 

(blue circles – UVS, orange triangles – commercial data, ±SE). 
65 

Naso lituratus 

Stock status parameter distributions (SPR: small bar shows 0.30 level). 
66 

Naso lituratus 

C30 and current total catch (left) and population size (right) distributions.
67 

Naso lituratus 

Overfishing probability for a range of C30 levels (catch - orange dashed line, UVS – blue dotted 

line). OFLs are represented by small vertical bars.

Probability of overfishing for various C30 levels. 

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from

survey (1000 kg)

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from survey 

(1000 kg)

0.10 1.18 48.4 0.31 2.62 59.1

0.11 1.24 49.1 0.32 2.70 59.4

0.12 1.30 49.8 0.33 2.78 59.8

0.13 1.36 50.4 0.34 2.85 60.2

0.14 1.43 51.0 0.35 2.92 60.6

0.15 1.50 51.7 0.36 3.01 61.0

0.16 1.58 52.3 0.37 3.08 61.4

0.17 1.65 52.8 0.38 3.17 61.7

0.18 1.72 53.4 0.39 3.25 62.2

0.19 1.78 53.9 0.40 3.35 62.6

0.20 1.86 54.5 0.41 3.44 62.9

0.21 1.93 54.9 0.42 3.51 63.4

0.22 1.99 55.4 0.43 3.63 63.7

0.23 2.06 55.8 0.44 3.73 64.1

0.24 2.13 56.3 0.45 3.82 64.5

0.25 2.19 56.8 0.46 3.92 64.8

0.26 2.26 57.1 0.47 4.02 65.1

0.27 2.32 57.5 0.48 4.14 65.5

0.28 2.40 57.9 0.49 4.27 65.9

0.29 2.48 58.2 0.50 4.39 66.2

0.30 2.55 58.7
68 

Naso lituratus 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 295 0.31 254

0.11 292 0.32 254

0.12 290 0.33 252

0.13 288 0.34 247

0.14 286 0.35 247

0.15 284 0.36 245

0.16 282 0.37 243

0.17 279 0.38 241

0.18 277 0.39 239

0.19 275 0.40 236

0.20 275 0.41 234

0.21 273 0.42 232

0.22 271 0.43 230

0.23 269 0.44 228

0.24 267 0.45 226

0.25 264 0.46 224

0.26 264 0.47 221

0.27 262 0.48 219

0.28 260 0.49 217

0.29 258 0.50 215

0.30 256
69 

Naso unicornis

Bluespine unicornfish, kala 

Acanthuridae (surgeonfishes) 

Life history and other input parameters 

Parameter Value SD Unit n Source

Linf 480 4 mm

K 0.44 0.02 yr 534 Mean and SD: Andrews et al. (2016) -1

a0 -0.12 - yr

Lmat 355 10 mm 295 Mean and SD: Eble (2009)

Longevity 50 5.4 yr 534 Mean and SD: Andrews et al. (2016)

L-W α 1.65e-5 - - - Kulbicki (2005) L-W β 3.035

LS50 230 - mm - Estimated from HMRFS data and other surgeonfishes. LS95 260

L diver survey 348 5 mm 522 NOAA-CREP diver survey

L commercial - - mm - DAR commercial data

L combined - - mm - -

Max. depth 120 - m - BRFA BotCam project

Federal waters 22 - % - -

Stock status and other output parameters 

Parameter Median SD Unit

M 0.06 0.01 yr-1

F 0.60 0.07 yr-1

F30 0.10 0.01 yr-1

F/F30 6.0 0.9 -

SPR 0.03 0.01 -

SPR < 0.30 iterations 100 - %

Lc30 467 - mm

General comments

The commercial data set could not be used to generate Lbar estimates given that N. annulatus and N. brevirostris are 

included with N. unicornis in the reporting system. The commercial catch for these 3 species is reported in the table 

above and in the graph further below as reference only.

Population abundance and Lbar were stable from 2005 to 2016, likely indicating a population near equilibrium. The 

recreational catch was fairly variable, but overall appeared stable as well. The LH parameters came from an in-depth 

study conducted locally and is likely highly reliable. There was some HMRFS data (n = 18) that could be used to help 

infer the selectivity parameters. A sensitivity run with LS50 at 200 and LS95 at 230 had little impact on the results (M: 0.11, 

F = 0.54, SPR = 0.05). 

The elevated F/F30 ratio and correspondingly low SPR estimate could not be explained by the relatively modest catch 

estimate, which was below the C30 estimate (20,197 kg vs. 33,100 kg). The reason for this may be the unusually high 

maximum age recorded for this species (50 year, from a bomb radio-carbon validated aged Oahu specimen). This high 

longevity leads to an extremely low M estimate, which in turn leads to a high F estimate and low SPR. The 50-year max 

age could be from an outlier individual, not representative of a 4% cohort survival rate (see equation 7). To test this 

scenario, we also ran the analyses using S = 1% and longevity at 40 years and obtained the following estimates: F: 0.54, 

SPR: 0.05.

Despite this discrepancy, the population estimate from diver surveys should be reliable given that this is a common 

species that is easily identifiable. The population estimate is likely biased downward given that this species has been 

recorded to 120-m depths and diver surveys only reach 30-m depths.

Parameter Median SD Unit

B from catch - - kg

B from survey 364,114 74,939 kg

Commercial catch 11,282 3,350 kg

Recreational catch 8,169 4,829 kg

Total catch 20,197 5,743 kg

C30 from catch - - kg

C30 from survey 33,200 7,270 kg
70 

Naso unicornis 

Life history parameter distributions.
71 

Naso unicornis 

Abundance index from UVS (blue circles, ±SE) and total catch time series 

from recreational (green squares) and commercial (orange triangles) sectors 

(presented as a reference, see comments section). 

Size structure and average length time series from UVS (±SE).
72 

Naso unicornis 

Stock status parameter distributions (SPR: small bar shows 0.30 level). 

C30 (left) and population size (right) distributions.
73 

Naso unicornis 

Overfishing probability for a range of C30 levels (UVS – blue dotted line). 

OFL is represented by a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from survey 

(1000 kg)

Overfishing 

probability

C30 from survey 

(1000 kg)

0.10 24.2 0.31 29.6

0.11 24.5 0.32 29.8

0.12 24.9 0.33 29.9

0.13 25.2 0.34 30.2

0.14 25.5 0.35 30.3

0.15 25.8 0.36 30.5

0.16 26.1 0.37 30.7

0.17 26.4 0.38 30.9

0.18 26.6 0.39 31.1

0.19 26.8 0.40 31.3

0.20 27.1 0.41 31.4

0.21 27.4 0.42 31.7

0.22 27.7 0.43 31.8

0.23 27.9 0.44 32.0

0.24 28.1 0.45 32.2

0.25 28.3 0.46 32.4

0.26 28.5 0.47 32.6

0.27 28.7 0.48 32.8

0.28 28.9 0.49 32.9

0.29 29.1 0.50 33.2

0.30 29.4
74 

Naso unicornis 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 474 0.31 469

0.11 474 0.32 469

0.12 474 0.33 469

0.13 474 0.34 469

0.14 471 0.35 469

0.15 471 0.36 469

0.16 471 0.37 469

0.17 471 0.38 469

0.18 471 0.39 469

0.19 471 0.40 469

0.20 471 0.41 469

0.21 471 0.42 469

0.22 471 0.43 467

0.23 471 0.44 467

0.24 471 0.45 467

0.25 471 0.46 467

0.26 471 0.47 467

0.27 469 0.48 467

0.28 469 0.49 467

0.29 469 0.50 467

0.30 469
75 

Carangoides orthogrammus

Island jack, ulua 

Carangidae (jacks) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 773 81 mm

- Mean and SD: Nadon & Ault (2016) 

Lmax: 685 (3) from DAR commercial data K 0.290 0.101 yr-1

a0 -0.6 - yr

Lmat 454 58 mm - Mean and SD: Nadon & Ault (2016)

Longevity 11 3.4 yr - Mean and SD: Nadon & Ault (2016)

L-W α 1.29e-5 - - - Kulbicki (2005) L-W β 2.994

LS50 325 - mm - DAR commercial data LS95 350

L diver survey - - mm - NOAA-CREP diver survey

L commercial 502 3 mm 3128 DAR commercial data

L combined - - mm - -

Max. depth 235 - m - BRFA BotCam project

Federal waters 26 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.27 0.08 yr-1

F 0.18 0.19 yr-1

F30 0.26 0.07 yr-1

F/F30 0.7 0.8 -

SPR 0.41 0.25 -

SPR < 0.30 iterations 36 - %

Lc30 0 - mm

General comments

There were insufficient UVS observations to generate population or Lbar estimates for this species. 

Commercial and recreational catches appeared relatively stable from 2003 to 2016, although the recreational 

catch estimates were highly variable. Lbar estimates from the commercial data set appeared to be slowly rising 

in the early year of the time series before slowly declining in recent years. 

No life history parameters exist for this species and we therefore used the stepwise approach to generate 

estimates. We used the Lmax estimate from the commercial data since the diver estimate was deemed unreliable

due to a low observation number. The estimate of Lmax for the NWHI from diver surveys was 700 mm (from 

95 UVS observations). A sensitivity run using an even larger Lmax (720 mm) generated the following LH 

parameters estimates: Linf: 798 mm, K: 0.27, M: 0.27, F: 0.18, F30: 0.25, SPR: 0.38, C30: 22,358 kg). These 

results were fairly similar to the original ones. 

Note that the estimated Linf parameter is higher than the Lmax due to the indeterminate growth curve typical of 

jacks (high M/K ratio).

Parameter Median SD Unit

B from catch 123,000 609,000 kg

B from survey - - kg

Commercial catch 2,686 1,098 kg

Recreational catch 13,162 16,036 kg

Total catch 16,714 14,139 kg

C30 from catch 24,300 134,000 kg

C30 from survey - - kg
76 

Carangoides orthogrammus 

Life history parameter distributions.
77 

Carangoides orthogrammus 

Total catch time series from recreational (green squares) and commercial (orange triangles) 

sectors. 

Size structure and average length time series from commercial data (±SE)
78 

Carangoides orthogrammus 

Stock status parameter distributions (SPR: small bar shows 0.30 level).

C30 and current total catch (left) and population size (right) distributions.
79 

Carangoides orthogrammus 

Overfishing probability for a range of C30 levels (commercial data – orange dashed line). 

OFL is represented by a small vertical bar. 

 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from catch

(1000 kg)

Overfishing 

probability

C30 from catch

(1000 kg)

0.10 7.0 0.31 14.5

0.11 7.4 0.32 14.8

0.12 7.8 0.33 15.1

0.13 8.1 0.34 15.5

0.14 8.4 0.35 16.0

0.15 8.8 0.36 16.4

0.16 9.1 0.37 16.9

0.17 9.4 0.38 17.5

0.18 9.8 0.39 17.9

0.19 10.2 0.40 18.3

0.20 10.5 0.41 18.9

0.21 10.9 0.42 19.3

0.22 11.2 0.43 19.9

0.23 11.6 0.44 20.4

0.24 11.9 0.45 21.0

0.25 12.2 0.46 21.6

0.26 12.4 0.47 22.3

0.27 12.9 0.48 22.9

0.28 13.2 0.49 23.6

0.29 13.7 0.50 24.3

0.30 14.1
80 

Carangoides orthogrammus 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 539 0.31 358

0.11 530 0.32 348

0.12 520 0.33 338

0.13 510 0.34 325

0.14 500 0.35 318

0.15 494 0.36 306

0.16 484 0.37 292

0.17 478 0.38 276

0.18 471 0.39 266

0.19 462 0.40 250

0.20 452 0.41 240

0.21 442 0.42 224

0.22 436 0.43 205

0.23 426 0.44 188

0.24 419 0.45 169

0.25 413 0.46 150

0.26 406 0.47 118

0.27 393 0.48 0

0.28 387 0.49 0

0.29 377 0.50 0

0.30 367
81 

Caranx ignobilis

Giant trevally, ulua aukea 

Carangidae (jacks) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 2170 310 mm

K 0.111 0.02 yr 10 Mean and SD: Sudekum (1991) -1

a0 0.097 - yr

Lmat 839 31 mm 10 Mean and SD: Sudekum (1991)

Longevity 11 3 yr 10 Mean and SD: Sudekum (1991)

L-W α 2.22e-5 - - - Seki (1986) L-W β 2.913

LS50 350 - mm - DAR commercial data LS95 430

L diver survey - - mm - -

L commercial 761 6 mm 5372 DAR commercial data

L combined - - mm - -

Max. depth 228 - m - BRFA BotCam project

Federal waters 26 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.26 0.05 yr-1

F 0.18 0.10 yr-1

F30 0.17 0.03 yr-1

F/F30 1.1 0.7 -

SPR 0.28 0.22 -

SPR < 0.30 iterations 54 - %

Lc30 430 - mm

General comments

There were insufficient diver observations in the MHI to generate a reliable Lbar estimate. The catch was 

dominated by the recreational sector and, although fairly variable from year to year, it appear to be mostly 

constant. Lbar from the commercial catch were also stable throughout the period under consideration, 

suggesting equilibrium conditions. 

The life history parameters for this species came from a local study with a very limited sample size. We also 

ran the analyses using the stepwise approach and generated the following values: Lmax: 1351 mm, Linf: 1679 

mm, K: 0.17, M: 0.21, F30: 0.15, F: 0.21, SPR: 0.19. These are fairly similar to the original analyses and did 

not change the conclusions. 

Parameter Median SD Unit

B from catch 1,070,000 3,930,000 kg

B from survey - - kg

Commercial catch 6,689 2,079 kg

Recreational catch 133,921 117,016 kg

Total catch 142,429 113,530 kg

C30 from catch 147,000 564,000 kg

C30 from survey - - kg
82 

Caranx ignobilis

Life history parameter distributions.
83 

Caranx ignobilis 

Total catch time series from recreational (green squares) and commercial (orange triangles) 

sectors. 

Size structure and average length time series from commercial data (±SE)
84 

Caranx ignobilis

Stock status parameter distributions (SPR: small bar shows 0.30 level).
85 

Caranx ignobilis

C30 and current total catch (left) and population size (right) distributions.
86 

Caranx ignobilis

Overfishing probability for a range of C30 levels (commercial data – orange dashed line). 

OFL is represented by a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from catch

(1000 kg)

Overfishing 

probability

C30 from catch

(1000 kg)

0.10 51.8 0.31 96.9

0.11 54.0 0.32 99.2

0.12 56.3 0.33 102.0

0.13 59.3 0.34 104.1

0.14 61.6 0.35 106.4

0.15 63.8 0.36 108.8

0.16 65.7 0.37 111.3

0.17 67.8 0.38 113.9

0.18 70.2 0.39 116.6

0.19 71.8 0.40 119.4

0.20 73.9 0.41 121.9

0.21 76.2 0.42 124.2

0.22 77.8 0.43 126.5

0.23 80.0 0.44 129.1

0.24 82.3 0.45 132.7

0.25 84.6 0.46 135.2

0.26 86.6 0.47 138.4

0.27 88.7 0.48 141.5

0.28 90.4 0.49 144.1

0.29 92.6 0.50 147.0

0.30 94.9
87 

Caranx ignobilis 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 959 0.31 710

0.11 945 0.32 696

0.12 931 0.33 686

0.13 917 0.34 679

0.14 906 0.35 668

0.15 892 0.36 654

0.16 878 0.37 640

0.17 864 0.38 626

0.18 858 0.39 616

0.19 844 0.40 602

0.20 833 0.41 584

0.21 819 0.42 570

0.22 808 0.43 556

0.23 798 0.44 536

0.24 788 0.45 518

0.25 777 0.46 504

0.26 763 0.47 486

0.27 752 0.48 466

0.28 742 0.49 452

0.29 732 0.50 430

0.30 721
88 

Caranx melampygus

Bluefin trevally, ‘omilu

Carangidae (jacks) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 1041 174 mm

K 0.233 0.13 yr 14 Mean: Sudekum (1991), SD: Kritzer (2001) -1

a0 -0.044 - yr

Lmat 476 33 mm 14 Mean: Sudekum (1991), SD: Nadon (unpublished)

Longevity 7 1.3 yr 14 Mean: Sudekum (1991), SD: Kritzer (2001)

L-W α 2.38e-5 - - - Seki (1986) L-W β 2.94

LS50 325 - mm - DAR commercial data LS95 370

L diver survey 465 9 mm 169 NOAA-CREP diver survey

L commercial 557 3 mm 4501 DAR commercial data

L combined 550 3 mm - -

Max. depth 230 - m - Pyle et al. (2016)

Federal waters 26 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.44 0.07 yr-1

F 0.27 0.21 yr-1

F30 0.37 0.06 yr-1

F/F30 0.7 0.6 -

SPR 0.40 0.23 -

SPR < 0.30 iterations 34 - %

Lc30 88 - mm

General comments

Population abundance appeared to be slowly increasing in recent years. There were enough diver 

observations to obtain an Lbar estimate, but the fast swimming behavior of this species made estimating 

population size unreliable. Lbar from the UVS were not abundant enough on a yearly basis to generate a long 

term pattern. Lbar from the commercial data appeared fairly stable, which suggested that the population was 

mostly at equilibrium. The recreational sector dominated the catch and appeared fairly constant, although 

variable from year to year.

As for C. ignobilis, the life history parameters for this species came from a local study with a limited sample 

size. We also ran the analyses using the stepwise approach and generated the following values: Lmax: 843 mm, 

Linf: 921 mm, K: 0.25, M: 0.26, F30: 0.22, F: 0.22, SPR: 0.32, C30: 141,420 kg. These were reasonably similar 

to the original analyses and did not change the conclusions. 

Parameter Median SD Unit

B from catch 811,000 3,500,000 kg

B from survey - - kg

Commercial catch 3,147 718 kg

Recreational catch 144,775 50,248 kg

Total catch 148,127 50,035 kg

C30 from catch 205,000 911,000 kg

C30 from survey - - kg
89 

Caranx melampygus 

Life history parameter distributions.
90 

Caranx melampygus 

Abundance index from UVS (blue circles, ±SE) and total catch time series from recreational

(green squares) and commercial (orange triangles) sectors. 

Size structure from commercial catch (top left) and UVS (top right). Average length time series 

(blue circles – UVS, orange triangles – commercial data, ±SE). 
91 

Caranx melampygus 

Stock status parameter distributions (SPR: small bar shows 0.30 level).
92 

Caranx melampygus 

C30 and current total catch (left) and population size (right) distributions.
93 

Caranx melampygus 

Overfishing probability for a range of C30 levels (commercial data – orange dashed line). 

OFL is represented by a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from catch

(1000 kg)

Overfishing 

probability

C30 from catch

(1000 kg)

0.10 92.1 0.31 143.7

0.11 95.6 0.32 146.4

0.12 98.2 0.33 149.0

0.13 100.4 0.34 151.5

0.14 102.5 0.35 153.8

0.15 104.9 0.36 156.7

0.16 107.5 0.37 159.6

0.17 110.4 0.38 162.7

0.18 112.7 0.39 165.0

0.19 115.4 0.40 167.7

0.20 117.5 0.41 170.9

0.21 119.4 0.42 174.2

0.22 121.6 0.43 177.2

0.23 123.6 0.44 181.3

0.24 126.0 0.45 185.4

0.25 128.4 0.46 188.6

0.26 130.7 0.47 192.7

0.27 132.7 0.48 196.5

0.28 135.6 0.49 200.0

0.29 138.1 0.50 205.3

0.30 141.4
94 

Caranx melampygus 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 536 0.31 354

0.11 526 0.32 344

0.12 517 0.33 332

0.13 507 0.34 325

0.14 500 0.35 315

0.15 491 0.36 302

0.16 484 0.37 292

0.17 474 0.38 280

0.18 465 0.39 267

0.19 458 0.40 254

0.20 452 0.41 240

0.21 445 0.42 224

0.22 436 0.43 211

0.23 426 0.44 198

0.24 416 0.45 182

0.25 410 0.46 166

0.26 400 0.47 146

0.27 393 0.48 130

0.28 384 0.49 107

0.29 374 0.50 88

0.30 364
95 

Aprion virescens

Green jobfish, uku

Lutjanidae (snappers) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 771 50 mm

K 0.372 0.021 yr 379 Mean and SD: O’Malley (unpubl.) -1

a0 -0.51 - yr

Lmat 489 16 mm 103 Mean: Everson (1989), SD: Nadon (unpublished)

Longevity 31 2.3 yr 379 Mean and SD: O’Malley (unpubl.)

L-W α 6.44e-4 - - - HMFRS data L-W β 2.404

LS50 425 - mm - DAR commercial data LS95 475

L diver survey 613 10 mm 278 NOAA-CREP diver survey

L commercial 665 1 mm 17634 DAR commercial data

L combined 664 1 mm - -

Max. depth 203 - m - BRFA BotCam project

Federal waters 24 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.10 0.01 yr-1

F 0.15 0.07 yr-1

F30 0.16 0.01 yr-1

F/F30 0.9 0.5 -

SPR 0.33 0.16 -

SPR < 0.30 iterations 42 - %

Lc30 349 - mm

General comments

Population abundance appeared to be increasing from 2003 to 2016. The commercial catch also appeared to 

be increasing although it has been flat in the last 2 years. Recreational catch, although fairly variable, appeared

to be relatively stable. Lbar from both the commercial and UVS data sets were similar and mostly stable, 

suggesting that the population was mostly at equilibrium.

The life history parameters for this species came from a local study conducted by the PIFSC life history 

group (J. O’Malley) with a fairly large sample size. Length at maturity came from a local study as well. Given 

the reliability of these sources, we did not deem it necessary to run the stepwise analyses for this species.

The diver Lbar was lower than the commercial one. A sensitivity run using this Lbar generated the following 

results: F: 0.33, F/F30: 2.1, SPR: 0.15. Another sensitivity run using selectivity parameters of 475 mm and 525 

mm resulted in the following values: F: 0.18, F/F30: 1.1, SPR: 0.30. 

There were also sufficient diver observations to obtain a population size estimate (434,419 kg) which was 

relatively close to the one derived from the total catch estimate (758,000 kg). The lower population estimate 

from diver surveys could be related to the depth limitation of these surveys compared to the full population 

range for this species (30 m vs. 203 m). 

Parameter Median SD Unit

B from catch 758,000 1,590,000 kg

B from survey 434,419 83,661 kg

Commercial catch 36,867 11,226 kg

Recreational catch 51,001 38,316 kg

Total catch 92,248 36,805 kg

C30 from catch 104,000 226,000 kg

C30 from survey 60,000 12,100 kg
96 

Aprion virescens

Life history parameter distributions.
97 

Aprion virescens

Abundance index from UVS (blue circles, ±SE) and total catch time series from recreational

(green squares) and commercial (orange triangles) sectors. 

Size structure from commercial catch (top left) and UVS (top right). Average length time series 

(blue circles – UVS, orange triangles – commercial data, ±SE). 
98 

Aprion virescens

Stock status parameter distributions (SPR: small bar shows 0.30 level).
99 

Aprion virescens

C30 and current total catch (left) and population size (right) distributions.
100 

Aprion virescens

Overfishing probability for a range of C30 levels (catch - orange dashed line, UVS – blue dotted 

line). OFLs are represented by small vertical bars.

Probability of overfishing for various C30 levels. 

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from

survey (1000 kg)

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from survey 

(1000 kg)

0.10 51.3 44.6 0.31 78.3 54.0

0.11 52.9 45.4 0.32 79.1 54.4

0.12 54.0 46.1 0.33 80.2 54.7

0.13 55.0 46.7 0.34 81.4 55.1

0.14 56.4 47.3 0.35 82.6 55.5

0.15 57.8 47.7 0.36 84.0 55.7

0.16 59.1 48.2 0.37 85.3 56.1

0.17 60.5 48.6 0.38 86.4 56.4

0.18 61.8 49.0 0.39 87.7 56.6

0.19 63.2 49.4 0.40 89.3 57.0

0.20 64.8 49.8 0.41 90.5 57.4

0.21 66.1 50.2 0.42 91.8 57.7

0.22 67.3 50.7 0.43 93.3 58.0

0.23 68.4 51.2 0.44 94.9 58.4

0.24 69.5 51.5 0.45 96.3 58.6

0.25 70.6 51.9 0.46 97.9 58.9

0.26 71.7 52.3 0.47 99.4 59.2

0.27 73.0 52.6 0.48 100.9 59.5

0.28 74.4 53.0 0.49 102.4 59.8

0.29 75.8 53.3 0.50 104.3 60.0

0.30 76.9 53.7
101 

Aprion virescens

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 625 0.31 502

0.11 616 0.32 497

0.12 608 0.33 489

0.13 604 0.34 480

0.14 595 0.35 476

0.15 591 0.36 468

0.16 586 0.37 463

0.17 582 0.38 455

0.18 574 0.39 446

0.19 570 0.40 438

0.20 565 0.41 429

0.21 557 0.42 425

0.22 552 0.43 421

0.23 548 0.44 408

0.24 540 0.45 404

0.25 536 0.46 391

0.26 531 0.47 378

0.27 523 0.48 370

0.28 518 0.49 357

0.29 514 0.50 348

0.30 506
102 

Lutjanus fulvus

Blacktail snapper, to’au 

Lutjanidae (snappers) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 342 19 mm

- Mean and SD: Nadon & Ault (2016) 

Lmax: 372 (7) from MHI diver data K 0.43 0.17 yr-1

a0 -0.6 - yr

Lmat 240 37 mm - Mean and SD: Nadon & Ault (2016)

Longevity 19 7 yr - Mean and SD: Nadon & Ault (2016)

L-W α 2.04e-5 - - - Kulbicki (2005) L-W β 2.97

LS50 210 - mm - DAR commercial data LS95 220

L diver survey 264 3 mm 471 NOAA-CREP diver survey

L commercial 295 2 mm 4771 DAR commercial data

L combined 283 2 mm - -

Max. depth 128 - m - Pyle et al. (2016)

Federal waters 22 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.17 0.07 yr-1

F 0.20 0.18 yr-1

F30 0.22 0.09 yr-1

F/F30 0.9 0.9 -

SPR 0.33 0.23 -

SPR < 0.30 iterations 45 - %

Lc30 132 - mm

General comments

Note: this species is non-native and considered invasive. It was introduced in 1956 from Tahiti. 

Population abundance for this species has been stable. The commercial Lbar have been stable as well, while 

the recreational Lbar have declined a bit from the early years. The recreational catch was much larger than the 

commercial one and both have been steady in recent years (with the recreational catch declining slightly in the

last 2 years).

There is no published life history parameters for this species. We therefore used the stepwise approach to 

generate estimates, using an Lmax value of 372 mm from diver survey data (from the MHI, since this species is 

not present in the NWHI). A sensitivity run with a higher Lmax (400 mm), generated the following estimates: 

Linf: 364 mm, K: 0.40, M: 0.17, F30: 0.21, F: 0.32, C30 survey: 32,359 kg).

The population size estimate derived from the catch was lower than the estimate from diver survey. This 

could be expected given the uncertainty in both the total catch estimate and the life history parameters. The 

population size estimate derived from the diver survey is likely more reliable given that this is a common 

species that is easily identifiable. Consequently, the C30 derived from the diver survey population estimate is 

likely more reliable.

Parameter Median SD Unit

B from catch 47,900 161,000 kg

B from survey 180,433 29,498 kg

Commercial catch 1,606 832 kg

Recreational catch 6,682 2,358 kg

Total catch 8,488 2,488 kg

C30 from catch 8,670 36,000 kg

C30 from survey 33,100 11,400 kg
103 

Lutjanus fulvus 

Life history parameter distributions.
104 

Lutjanus fulvus 

Abundance index from UVS (blue circles, ±SE) and total catch time series from recreational

(green squares) and commercial (orange triangles) sectors. 

Size structure from commercial catch (top left) and UVS (top right). Average length time series 

(blue circles – UVS, orange triangles – commercial data, ±SE). 
105 

Lutjanus fulvus 

Stock status parameter distributions (SPR: small bar shows 0.30 level).
106 

Lutjanus fulvus 

C30 and current total catch (left) and population size (right) distributions.
107 

Lutjanus fulvus 

Overfishing probability for a range of C30 levels (catch - orange dashed line, UVS – blue dotted 

line). OFLs are represented by small vertical bars. 

Probability of overfishing for various C30 levels. 

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from

survey (1000 kg)

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from survey 

(1000 kg)

0.10 3.5 21.3 0.31 5.9 28.0

0.11 3.6 21.7 0.32 6.0 28.2

0.12 3.7 22.1 0.33 6.1 28.5

0.13 3.8 22.5 0.34 6.2 28.8

0.14 3.9 22.8 0.35 6.4 29.0

0.15 4.0 23.2 0.36 6.5 29.3

0.16 4.1 23.6 0.37 6.6 29.6

0.17 4.2 24.0 0.38 6.8 29.8

0.18 4.3 24.3 0.39 6.9 30.2

0.19 4.4 24.6 0.40 7.1 30.5

0.20 4.5 24.9 0.41 7.3 30.8

0.21 4.6 25.2 0.42 7.4 31.1

0.22 4.8 25.5 0.43 7.5 31.3

0.23 4.9 25.8 0.44 7.7 31.6

0.24 5.0 26.0 0.45 7.8 31.9

0.25 5.2 26.3 0.46 8.0 32.2

0.26 5.3 26.5 0.47 8.1 32.5

0.27 5.4 26.8 0.48 8.3 32.8

0.28 5.5 27.0 0.49 8.5 33.0

0.29 5.6 27.4 0.50 8.7 33.3

0.30 5.7 27.7
108 

Lutjanus fulvus 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 294 0.31 231

0.11 290 0.32 229

0.12 288 0.33 225

0.13 284 0.34 220

0.14 281 0.35 218

0.15 279 0.36 216

0.16 275 0.37 210

0.17 273 0.38 208

0.18 271 0.39 202

0.19 268 0.40 197

0.20 265 0.41 193

0.21 263 0.42 187

0.22 260 0.43 181

0.23 258 0.44 174

0.24 254 0.45 168

0.25 250 0.46 162

0.26 248 0.47 156

0.27 246 0.48 147

0.28 242 0.49 141

0.29 239 0.50 132

0.30 235
109 

Lutjanus kasmira

Bluestripe snapper, ta’ape 

Lutjanidae (snappers) 

Life history and other input parameters 

Parameter Value SD Unit n Source

Linf 340 15 mm

K 0.29 0.05 yr 171 Mean: Morales-Nin and Ralston (1990), SD: Kritzer (2001) -1

a0 -1.37 - yr

Lmat 200 5 mm 100? Mean: Allen (1985), SD: Nadon (unpublished)

Longevity 8 1 yr 171 Mean: Loubens (1980), SD: Kritzer (2001)

L-W α 4.30e-6 - - - Kulbicki (2001) L-W β 3.25

LS50 220 - mm - DAR commercial data LS95 240

L diver survey 274 4 mm 1402 NOAA-CREP diver survey

L commercial 271 1 mm 7460 DAR commercial data

L combined 271 1 mm - -

Max. depth 265 - m - Pyle et al. (2016)

Federal waters 26 - % - -

Stock status and other output parameters 

Parameter Median SD Unit

M 0.39 0.04 yr-1

F 0.21 0.13 yr-1

F30 0.75 0.14 yr-1

F/F30 0.3 0.2 -

SPR 0.62 0.16 -

SPR < 0.30 iterations 0 - %

Lc30 0 - mm

General comments

Note: this species is non-native and considered invasive. It was introduced in 1956 from Tahiti. 

Population abundance appears to have declined from a peak in 2005. However, the survey effort in this early year 

had a limited sample size and this may simply be an outlier. Abundance appeared to be fairly stable for the rest of 

the time series. Lbar from both data sets were very similar and constant throughout the years, which suggest a 

population near equilibrium. The commercial catch has been declining in recent years while the recreational catch 

has remained highly variable but stable. 

The growth parameters for this species came from a local study with a proper sample size. However, the maturity 

parameter source was not ideal (i.e. a fish ID guide). The stepwise approach for this species provided the following 

results: Lmax: 340 mm, Linf: 316 mm, Lmat: 224, K: 0.45, M: 0.20, F: 0.37, F30: 0.30, SPR: 0.23, C30 survey: 118,185 

kg. The Lmat value obtained from the stepwise approach was close to the original one. The rest of the parameters 

were similar except for a higher longevity and thus higher M. The max age for this species is estimated at 8 years 

while snapper typically live longer (16 years). This lead to the higher F value and low SPR value.

The population size estimate derived from the catch was less than half the estimate from diver surveys. This can

be expected given the uncertainty in the total catch estimate. The population size estimate derived from the diver 

survey is likely more reliable given that this is a common species that is easily identifiable. The OFL derived from 

the diver survey population estimate is therefore likely more reliable.

Parameter Median SD Unit

B from catch 181,000 576,000 kg

B from survey 496,235 98,182 kg

Commercial catch 16,165 2,813 kg

Recreational catch 10,734 7,534 kg

Total catch 27,968 7,429 kg

C30 from catch 80,100 288,000 kg

C30 from survey 221,000 50,000 kg
110 

Lutjanus kasmira 

Life history parameter distributions.
111 

Lutjanus kasmira 

Abundance index from UVS (blue circles, ±SE) and total catch time series from recreational

(green squares) and commercial (orange triangles) sectors. 

 

Size structure from commercial catch (top left) and UVS (top right). Average length time series 

(blue circles – UVS, orange triangles – commercial data, ±SE). 
112 

Lutjanus kasmira 

Stock status parameter distributions (SPR: small bar shows 0.30 level). 

. 
113 

Lutjanus kasmira 

C30 and current total catch (left) and population size (right) distributions.
114 

Lutjanus kasmira 

Overfishing probability for a range of C30 levels (catch - orange dashed line, UVS – blue dotted 

line). OFLs are represented by small vertical bars. 

Probability of overfishing for various C30 levels. 

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from

survey (1000 kg)

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from survey 

(1000 kg)

0.10 36.6 161.4 0.31 57.2 197.0

0.11 37.7 163.5 0.32 58.1 198.0

0.12 38.8 165.5 0.33 59.1 199.6

0.13 39.9 167.3 0.34 60.0 200.8

0.14 41.1 169.1 0.35 61.1 202.2

0.15 42.3 171.2 0.36 62.1 203.4

0.16 43.3 173.7 0.37 63.0 204.5

0.17 44.1 175.5 0.38 64.1 205.6

0.18 45.0 177.2 0.39 65.0 206.8

0.19 45.9 179.1 0.40 66.2 208.5

0.20 46.7 180.9 0.41 67.3 209.7

0.21 47.6 182.5 0.42 68.4 210.9

0.22 48.4 184.0 0.43 69.8 212.1

0.23 49.5 185.8 0.44 71.1 213.4

0.24 50.6 187.2 0.45 72.3 214.6

0.25 51.5 188.7 0.46 73.7 215.7

0.26 52.4 190.2 0.47 75.4 216.9

0.27 53.4 191.5 0.48 77.1 218.2

0.28 54.3 193.0 0.49 78.6 219.4

0.29 55.2 194.2 0.50 80.1 220.5

0.30 56.3 195.7
115 

Lutjanus kasmira 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 172 0.31 0

0.11 169 0.32 0

0.12 167 0.33 0

0.13 163 0.34 0

0.14 161 0.35 0

0.15 158 0.36 0

0.16 156 0.37 0

0.17 152 0.38 0

0.18 150 0.39 0

0.19 146 0.40 0

0.20 143 0.41 0

0.21 141 0.42 0

0.22 136 0.43 0

0.23 134 0.44 0

0.24 130 0.45 0

0.25 128 0.46 0

0.26 123 0.47 0

0.27 119 0.48 0

0.28 112 0.49 0

0.29 0 0.50 0

0.30 0
116 

Mulloidichthys flavolineatus

Yellowstripe goatfish, weke’a

Mullidae (goatfishes)

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 371 41 mm

K 0.564 0.170 yr 50 Mean: Holland (1993), SD: Kritzer (2001) -1

a0 -0.36 - yr

Lmat 199 7 mm 95 Mean: Cole (2009), SD: Nadon (unpublished)

Longevity 6 2 yr - Mean: Estimated, SD: estimated

L-W α 4.12e-6 - - - Holland (1993) L-W β 3.21

LS50 215 - mm - DAR commercial data LS95 230

L diver survey 281 10 mm 414 NOAA-CREP diver survey

L commercial 293 5 mm 2035 DAR commercial data

L combined 291 6 mm - -

Max. depth 97 - m - Pyle et al. (2016)

Federal waters 21 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.46 0.12 yr-1

F 0.33 0.26 yr-1

F30 0.64 0.18 yr-1

F/F30 0.5 0.5 -

SPR 0.49 0.22 -

SPR < 0.30 iterations 18 - %

Lc30 0 - mm

General comments

Population abundance from UVS was fairly variable, but overall appeared constant. The commercial catch 

was relatively small and stable. The recreational catch was very high but this is likely an artefact of the 

HMRFS sampling protocol (see discussion below). Lbar from both data sets were similar and appear to be 

slightly increasing in recent years.

The growth parameters for this species came from a local mark-recapture study. There is, however, no 

estimate of maximum age. Longevity for this species is estimated at around 6 years, which is the average for 

the goatfish family. A sensitivity run with longevity set at the highest value recorded for goatfishes (11 years) 

gave the following estimates: M: 0.29, F30: 0.41, SPR: 0.30, C30 survey: 12,487 kg. 

The recreational catch for this species is 25× larger than the commercial catch, which is highly unusual (i.e., 

the next highest catch ratio for goatfishes is 5× for P. cyclostomus. There is a fishery for the juvenile of this 

species (called oama). It is very likely that HMRFS surveyors do not often measure lengths or weights when 

encountering oama (Hongguang Ma, pers. comm.), but still record counts. This likely biases the average

weight upward. Since average weight multiplied by number recorded is used to infer total catch by weight, the 

total recreational catch estimate is very likely positively biased. If we multiply the commercial catch by the 

(continued on next page) 

Parameter Median SD Unit

B from catch 307,000 1,840,000 kg

B from survey 42,455 14,919 kg

Commercial catch 2,152 843 kg

Recreational catch 61,857 68,173 kg

Total catch 64,806 65,901 kg

C30 from catch 118,000 787,000 kg

C30 from survey 16,300 6,260 kg
117 

(continued from previous page)

average recreational to commercial catch ratio for goatfishes (4), we get an estimated recreational catch of

8,608 kg, which, combined with the commercial catch, provides a population biomass estimate of 47,164 kg. 

This value is close to the population biomass estimate from diver surveys (42,455 kg). Given this issue, the 

diver survey C30 estimates should be used for this species. The “corrected” total catch estimate of 10,760 kg is 

significantly below the OFL value of 16,300 kg which is concordant with the SPR value of 0.49. 

Life history parameter distributions.
118 

Mulloidichthys flavolineatus 

Abundance index from UVS (blue circles, ±SE) and total catch time series from recreational

(green squares) and commercial (orange triangles) sectors. 

 

Size structure from commercial catch (top left) and UVS (top right). Average length time series 

(blue circles – UVS, orange triangles – commercial data, ±SE). 
119 

Mulloidichthys flavolineatus

Stock status parameter distributions (SPR: small bar shows 0.30 level). 
120 

Mulloidichthys flavolineatus 

C30 and current total catch (left) and population size (right) distributions.
121 

Mulloidichthys flavolineatus 

Overfishing probability for a range of C30 levels (catch - orange dashed line, UVS – blue dotted 

line). OFLs are represented by small vertical bars. 

Probability of overfishing for various C30 levels. 

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from

survey (1000 kg)

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from survey 

(1000 kg)

0.10 34.9 8.8 0.31 70.5 13.2

0.11 36.6 9.1 0.32 72.3 13.4

0.12 38.2 9.3 0.33 74.3 13.6

0.13 39.6 9.6 0.34 76.2 13.8

0.14 40.9 9.9 0.35 78.5 14.0

0.15 42.4 10.1 0.36 80.7 14.2

0.16 44.3 10.3 0.37 83.1 14.3

0.17 45.8 10.5 0.38 85.2 14.5

0.18 47.3 10.7 0.39 87.6 14.7

0.19 48.9 10.9 0.40 89.7 14.8

0.20 50.3 11.2 0.41 92.3 15.0

0.21 52.0 11.4 0.42 95.0 15.1

0.22 54.0 11.6 0.43 98.4 15.3

0.23 55.5 11.8 0.44 100.6 15.4

0.24 57.4 12.0 0.45 103.8 15.6

0.25 59.7 12.2 0.46 106.9 15.7

0.26 61.4 12.4 0.47 109.8 15.9

0.27 62.7 12.6 0.48 112.6 16.0

0.28 64.8 12.8 0.49 115.2 16.1

0.29 66.6 12.9 0.50 118.3 16.3

0.30 68.2 13.1
122 

Mulloidichthys flavolineatus 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 245 0.31 161

0.11 241 0.32 157

0.12 234 0.33 153

0.13 230 0.34 148

0.14 226 0.35 142

0.15 224 0.36 138

0.16 219 0.37 131

0.17 215 0.38 127

0.18 211 0.39 118

0.19 209 0.40 114

0.20 204 0.41 108

0.21 200 0.42 101

0.22 198 0.43 92

0.23 194 0.44 84

0.24 189 0.45 64

0.25 185 0.46 0

0.26 181 0.47 0

0.27 176 0.48 0

0.28 174 0.49 0

0.29 170 0.50 0

0.30 166
123 

Mulloidichthys pfluegeri

Pflueger’s goatfish, weke nono 

Mullidae (goatfishes) 

Life history and other input parameter

Parameter Value SD Unit n Source

Linf 557 26 mm

- Mean and SD: Nadon & Ault (2016) 

Lmax: 484 (1) from DAR data K 0.55 0.14 yr-1

a0 -0.6 - yr

Lmat 270 31 mm - Mean and SD: Nadon & Ault (2016)

Longevity 5.6 2.0 yr - Mean and SD: Nadon & Ault (2016)

L-W α 2.87e-6 - - - Kulbicki (2005) L-W β 3.29

LS50 300 - mm - DAR commercial data LS95 330

L diver survey - - mm - -

L commercial 401 1 mm 3541 DAR commercial data

L combined - - mm - -

Max. depth 242 - m - BRFA BotCam project

Federal waters 26 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.57 0.19 yr-1

F 0.53 0.37 yr-1

F30 0.81 0.33 yr-1

F/F30 0.7 0.7 -

SPR 0.41 0.23 -

SPR < 0.30 iterations 31 - %

Lc30 168 - mm

General comments

This species mostly occurs in deep water and therefore was not encountered during the diver surveys. The 

recreational and commercial catch were similar and relatively constant (except for a spike in 2004 from the 

recreational catch, which is likely spurious). The Lbar from the commercial data has been constant since 2003 

reflecting a population likely near equilibrium conditions. 

There were no published life history parameters for this species and we therefore used the stepwise

approach to generate estimates from an Lmax value of 484 mm. This Lmax value was close to the maximum 

length value reported on fishbase.org (480 mm) and no specimen were reported above 500 mm in the 

commercial data set. A sensitivity run with an Lmax of 520 mm generated the following estimates: Linf: 520 

mm, K: 0.52, M: 0.61, F30: 0.82, F: 0.73, SPR: 0.34, C30 catch: 6,923 kg. These values were reasonably 

similar to the original results and did not change the conclusion of our analyses for this species.

Parameter Median SD Unit

B from catch 21,100 167,000 kg

B from survey - - kg

Commercial catch 2,195 668 kg

Recreational catch 3,036 9,128 kg

Total catch 6,042 5,736 kg

C30 from catch 9,010 89,100 kg

C30 from survey - - kg
124 

Mulloidichthys pfluegeri 

Life history parameter distributions.
125 

Mulloidichthys pfluegeri 

Total catch time series from recreational (green squares) and commercial (orange triangles) 

sectors. 

Size structure and average length time series from commercial data (±SE). 
126 

Mulloidichthys pfluegeri 

Stock status parameter distributions (SPR: small bar shows 0.30 level).
127 

Mulloidichthys pfluegeri 

C30 and current total catch (left) and population size (right) distributions.
128 

Mulloidichthys pfluegeri 

Overfishing probability for a range of C30 levels (commercial data – orange dashed line). OFL is

represented by a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from catch

(1000 kg)

Overfishing 

probability

C30 from catch

(1000 kg)

0.10 2.80 0.31 5.64

0.11 2.94 0.32 5.80

0.12 3.07 0.33 5.95

0.13 3.18 0.34 6.12

0.14 3.31 0.35 6.27

0.15 3.42 0.36 6.40

0.16 3.55 0.37 6.55

0.17 3.67 0.38 6.70

0.18 3.82 0.39 6.87

0.19 3.95 0.40 7.05

0.20 4.08 0.41 7.24

0.21 4.20 0.42 7.42

0.22 4.30 0.43 7.59

0.23 4.42 0.44 7.74

0.24 4.56 0.45 7.91

0.25 4.72 0.46 8.13

0.26 4.88 0.47 8.31

0.27 5.04 0.48 8.54

0.28 5.20 0.49 8.78

0.29 5.35 0.50 9.01

0.30 5.50
129 

Mulloidichthys pfluegeri 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 372 0.31 279

0.11 366 0.32 276

0.12 360 0.33 270

0.13 354 0.34 267

0.14 351 0.35 261

0.15 345 0.36 258

0.16 342 0.37 252

0.17 336 0.38 249

0.18 333 0.39 243

0.19 330 0.40 237

0.20 324 0.41 231

0.21 321 0.42 225

0.22 315 0.43 222

0.23 312 0.44 215

0.24 306 0.45 207

0.25 303 0.46 201

0.26 297 0.47 192

0.27 294 0.48 186

0.28 291 0.49 180

0.29 288 0.50 168

0.30 282
130 

Mulloidichthys vanicolensis

Yellowtail goatfish, weke ‘ula 

Mullidae (goatfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 267 30 mm

K 1.3 0.39 yr 50 Mean: Cole (2009), SD: Kritzer (2001) -1

a0 -1.1 - yr

Lmat 206 6 mm 118 Mean: Cole (2009), SD: Nadon (unpublished)

Longevity 5 1 yr 50 Mean: Cole (2009), SD: Kritzer (2001)

L-W α 1.83e-5 - - - Jehangeer (2003) L-W β 2.96

LS50 200 - mm - DAR commercial data LS95 210

L diver survey 256 8 mm 595 NOAA-CREP diver survey

L commercial 278 2 mm 2175 DAR commercial data

L combined 276 3 mm - -

Max. depth 132 - m - BRFA BotCam project

Federal waters 22 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.61 0.12 yr-1

F 0.35 0.40 yr-1

F30 0.83 0.22 yr-1

F/F30 0.4 0.5 -

SPR 0.55 0.23 -

SPR < 0.30 iterations 15 - %

Lc30 - - mm

General comments

Population abundance appeared to be declining in the last year of the UVS surveys. Further surveys should clarify if 

this is a clear pattern or caused by an outlier data point. The catch from both sectors were similar and constant, except for

an anomalous jump in the recreational catch in 2015. This jump could be due to the same juvenile goatfish reporting issue 

as for M. flavolineatus (see discussion for this species). It is unlikely to reflect a real increase in recreational catch for this 

species. Commercial and recreational Lbar appeared relatively constant for this species, suggesting a population near

equilibrium. However, the commercial Lbar was higher than Linf for this species, which is problematic given the low M/K

ratio. We thus ran the analyses with the diver survey Lbar, given the high observation count.

The life history parameters for this species came from a local study with a limited sample size. Using the stepwise 

approach, we obtained the following results: Lmax: 325 mm, Linf: 377 mm, K: 0.59, M: 0.61, F30: 0.80, F: 0.70, SPR: 0.34, 

C30 survey: 13,890 kg. Note that goatfishes usually have indeterminate growth curves, resulting in a fairly high Linf value 

for the stepwise approach in this example.

Similarly to M. flavolineatus, there was a discrepancy between the population sizes estimated from the catch vs. diver 

surveys (139,000 kg vs. 34,896 kg). This lead to significant difference in C30 estimates from the catch vs. diver surveys as 

well. The smaller population estimate could be due to the depth limit associated with diver surveys (30 m) vs. the actual 

depth range of this species (132 m). Note that the catch-derived population size form the sensitivity run was much smaller 

(80,965 kg) given the much higher F value (0.70 vs. 0.35). The C30 from the diver survey is likely more reliable than the 

catch-derived estimates.

Parameter Median SD Unit

B from catch 139,000 897,000 kg

B from survey 34,896 17,672 kg

Commercial catch 14,267 4,772 kg

Recreational catch 9,875 38,536 kg

Total catch 28,511 22,058 kg

C30 from catch 61,600 402,000 kg

C30 from survey 15,500 7,710 kg
131 

Mulloidichthys vanicolensis 

Life history parameter distributions.
132 

Mulloidichthys vanicolensis 

Abundance index from UVS (blue circles, ±SE) and total catch time series from recreational

(green squares) and commercial (orange triangles) sectors. 

 

 

Size structure from commercial catch (top left) and UVS (top right). Average length time series 

(blue circles – UVS, orange triangles – commercial data, ±SE). 
133 

Mulloidichthys vanicolensis 

Stock status parameter distributions (SPR: small bar shows 0.30 level).
134 

Mulloidichthys vanicolensis 

C30 and current total catch (left) and population size (right) distributions.
135 

Mulloidichthys vanicolensis 

Overfishing probability for a range of C30 levels (catch - orange dashed line, UVS – blue dotted 

line). OFLs are represented by small vertical bars.

Probability of overfishing for various C30 levels. 

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from

survey (1000 kg)

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from survey 

(1000 kg)

0.10 18.7 6.4 0.31 37.0 11.7

0.11 19.6 6.7 0.32 38.2 11.9

0.12 20.4 7.0 0.33 39.2 12.1

0.13 21.3 7.3 0.34 40.3 12.3

0.14 22.0 7.6 0.35 41.3 12.5

0.15 22.9 7.9 0.36 42.3 12.8

0.16 23.6 8.2 0.37 43.5 13.0

0.17 24.4 8.4 0.38 44.7 13.2

0.18 25.5 8.7 0.39 45.9 13.4

0.19 26.4 9.0 0.40 46.9 13.6

0.20 27.2 9.2 0.41 48.0 13.8

0.21 28.1 9.5 0.42 49.5 14.0

0.22 28.9 9.7 0.43 50.8 14.1

0.23 29.6 10.0 0.44 52.3 14.3

0.24 30.3 10.2 0.45 53.7 14.5

0.25 31.2 10.4 0.46 55.3 14.7

0.26 31.8 10.6 0.47 56.5 14.9

0.27 33.1 10.9 0.48 58.1 15.1

0.28 34.0 11.1 0.49 60.1 15.2

0.29 35.0 11.3 0.50 61.6 15.5

0.30 35.9 11.5
136 

Parupeneus cyclostomus

Blue goatfish, moano hulu 

Mullidae (goatfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 565 30 mm

- Mean and SD: Nadon & Ault (2016) 

Lmax: 494 (10) from NWHI diver survey K 0.512 0.146 yr-1

a0 -0.6 - yr

Lmat 269 33 mm - Mean and SD: Nadon & Ault (2016)

Longevity 5.4 1.9 yr - Mean and SD: Nadon & Ault (2016)

L-W α 8.28e-6 - - - Kulbicki (2001) L-W β 3.13

LS50 225 - mm - DAR commercial data LS95 250

L diver survey 318 4 mm 362 NOAA-CREP diver survey

L commercial 342 2 mm 3070 DAR commercial data

L combined 336 3 mm - -

Max. depth 113 - m - Pyle et al. (2016)

Federal waters 21 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.60 0.18 yr-1

F 0.73 0.46 yr-1

F30 0.59 0.17 yr-1

F/F30 1.3 1.0 -

SPR 0.24 0.22 -

SPR < 0.30 iterations 61 - %

Lc30 263 - mm

General comments

Population abundance jumped unexpectedly in 2012 with no easy explanation for this pattern. Future surveys 

should reveal if this is a persistent pattern or simply an anomaly. The commercial catch appeared to be rising 

slightly from 2003 to 2014 but fell in 2016. The recreational catch was fairly variable but also appear to be 

rising slightly. The commercial and recreational Lbar were reasonably similar and mostly stable in recent years. 

There were no published life history parameters for this species and the stepwise approach was used to 

generate estimates. The Lmax used for this analysis was obtained from the pristine NWHI and was likely a 

fairly reasonable estimate. A sensitivity run with a larger Lmax (530 mm) generated the following estimates: 

Linf: 608 mm, K: 0.50, M: 0.63, F30: 0.57, F: 1.0, SPR: 0.16, C30 survey: 26,100 kg. 

The catch data for this species seemed unusually small (4,474 kg) compared to other species with similar 

abundance (M. vanicolensis, M. flavolineatus). There is little reason to doubt the diver surveys, given that this 

is a fairly common and easily identifiable species. The diver survey C30 is likely more reliable than the catchderived C30. 

Parameter Median SD Unit

B from catch 12,000 66,300 kg

B from survey 77,428 30,321 kg

Commercial catch 700 257 kg

Recreational catch 3,684 1,871 kg

Total catch 4,474 1,829 kg

C30 from catch 4,000 25,200 kg

C30 from survey 25,600 11,300 kg
137 

Parupeneus cyclostomus 

Life history parameter distributions.

139 

Parupeneus cyclostomus 

Stock status parameter distributions (SPR: small bar shows 0.30 level).
140 

Parupeneus cyclostomus 

C30 and current total catch (left) and population size (right) distributions.
141 

Parupeneus cyclostomus 

Overfishing probability for a range of C30 levels (catch - orange dashed line, UVS – blue dotted 

line). OFLs are represented by small vertical bars. 

Probability of overfishing for various C30 levels. 

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from

survey (1000 kg)

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from survey 

(1000 kg)

0.10 1.92 12.3 0.31 2.93 20.3

0.11 1.99 12.9 0.32 2.99 20.6

0.12 2.03 13.4 0.33 3.03 20.9

0.13 2.09 14.0 0.34 3.08 21.2

0.14 2.14 14.4 0.35 3.13 21.5

0.15 2.19 15.0 0.36 3.17 21.8

0.16 2.24 15.3 0.37 3.22 22.0

0.17 2.28 15.8 0.38 3.28 22.3

0.18 2.33 16.1 0.39 3.34 22.6

0.19 2.37 16.5 0.40 3.39 22.8

0.20 2.41 16.9 0.41 3.45 23.1

0.21 2.46 17.3 0.42 3.52 23.4

0.22 2.51 17.6 0.43 3.57 23.7

0.23 2.56 18.0 0.44 3.63 23.9

0.24 2.61 18.2 0.45 3.69 24.2

0.25 2.65 18.5 0.46 3.76 24.5

0.26 2.70 18.8 0.47 3.81 24.7

0.27 2.75 19.1 0.48 3.87 25.0

0.28 2.79 19.4 0.49 3.94 25.3

0.29 2.84 19.7 0.50 4.00 25.6

0.30 2.89 20.1
142 

Parupeneus cyclostomus 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 403 0.31 326

0.11 398 0.32 324

0.12 394 0.33 322

0.13 389 0.34 317

0.14 385 0.35 315

0.15 382 0.36 310

0.16 378 0.37 308

0.17 376 0.38 306

0.18 371 0.39 304

0.19 367 0.40 299

0.20 364 0.41 297

0.21 360 0.42 295

0.22 358 0.43 290

0.23 353 0.44 286

0.24 351 0.45 281

0.25 349 0.46 279

0.26 344 0.47 274

0.27 340 0.48 270

0.28 338 0.49 266

0.29 333 0.50 263

0.30 331
143 

Parupeneus insularis

Island goatfish, munu 

Mullidae (goatfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 376 17 mm

- Mean and SD: Nadon & Ault (2016) 

Lmax: 324 (4) from NWHI diver survey K 0.60 0.14 yr-1

a0 -0.6 - yr

Lmat 203 25 mm - Mean and SD: Nadon & Ault (2016)

Longevity 6.4 2.2 yr - Mean and SD: Nadon & Ault (2016)

L-W α 9.15e-6 - - - L-W β 3.13

LS50 220 - mm - DAR commercial data LS95 240

L diver survey 278 3 mm 179 NOAA-CREP diver survey

L commercial 305 2 mm 1598 DAR commercial data

L combined 296 2 mm - -

Max. depth 90 - m - Pyle et al. (2016)

Federal waters 21 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.50 0.16 yr-1

F 0.28 0.24 yr-1

F30 0.72 0.25 yr-1

F/F30 0.4 0.4 -

SPR 0.57 0.22 -

SPR < 0.30 iterations 12 - %

Lc30 0 - mm

General comments

Population abundance was stable from 2005 to 2016. The commercial catch increased in the early year 

before going down from 2013 to 2016. The recreational catch was elevated in the early years and lower in 

recent years, although it is not clear if this is a real pattern given the variability associated with this data set. 

Lbar from both data set appeared to be declining slightly.

There are no published life history parameters for this species and the stepwise approach was used to 

generate estimates using an Lmax from NWHI surveys. A sensitivity run with a Lmax of 360 mm generated the 

following results: Linf: 412 mm, K: 0.56, M: 0.57, F30: 0.73, F: 0.48, SPR: 0.42, C30 survey: 16,783 kg. 

Similarly to P. cyclostomus, The catch data for this species seemed unusually small (776 kg) compared to 

other species with similar abundance (M. vanicolensis, M. flavolineatus). There is no clear explanation for this 

observation. However, the diver survey data is likely more reliable to estimate population size and OFLs. 

Parameter Median SD Unit

B from catch 4,740 37,500 kg

B from survey 41,983 7,557 kg

Commercial catch 176 153 kg

Recreational catch 496 1,358 kg

Total catch 776 1,011 kg

C30 from catch 1,960 16,900 kg

C30 from survey 17,100 4,300 kg
144 

Parupeneus insularis 

Life history parameter distributions.
145 

Parupeneus insularis 

Abundance index from UVS (blue circles, ±SE) and total catch time series from recreational

(green squares) and commercial (orange triangles) sectors. 

 

Size structure from commercial catch (top left) and UVS (top right). Average length time series 

(blue circles – UVS, orange triangles – commercial data, ±SE). 
146 

Parupeneus insularis 

Stock status parameter distributions (SPR: small bar shows 0.30 level).
147 

Parupeneus insularis 

C30 and current total catch (left) and population size (right) distributions.
148 

Parupeneus insularis 

Overfishing probability for a range of C30 levels (catch - orange dashed line, UVS – blue dotted 

line). OFLs are represented by small vertical bars. 

Probability of overfishing for various C30 levels. 

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from

survey (1000 kg)

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from survey 

(1000 kg)

0.10 0.49 12.1 0.31 1.09 15.1

0.11 0.52 12.3 0.32 1.13 15.1

0.12 0.55 12.5 0.33 1.17 15.2

0.13 0.58 12.6 0.34 1.20 15.4

0.14 0.60 12.8 0.35 1.24 15.5

0.15 0.63 13.0 0.36 1.28 15.6

0.16 0.65 13.1 0.37 1.31 15.7

0.17 0.67 13.3 0.38 1.35 15.8

0.18 0.70 13.4 0.39 1.40 15.9

0.19 0.72 13.6 0.40 1.45 16.1

0.20 0.75 13.7 0.41 1.50 16.2

0.21 0.78 13.8 0.42 1.55 16.3

0.22 0.82 14.0 0.43 1.58 16.4

0.23 0.84 14.1 0.44 1.63 16.5

0.24 0.87 14.2 0.45 1.69 16.6

0.25 0.90 14.3 0.46 1.74 16.7

0.26 0.93 14.4 0.47 1.79 16.8

0.27 0.96 14.5 0.48 1.83 16.9

0.28 0.99 14.7 0.49 1.90 17.0

0.29 1.02 14.8 0.50 1.96 17.1

0.30 1.06 14.9
149 

Parupeneus insularis 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 216 0.31 0

0.11 209 0.32 0

0.12 205 0.33 0

0.13 200 0.34 0

0.14 196 0.35 0

0.15 189 0.36 0

0.16 183 0.37 0

0.17 178 0.38 0

0.18 172 0.39 0

0.19 165 0.40 0

0.20 158 0.41 0

0.21 152 0.42 0

0.22 145 0.43 0

0.23 136 0.44 0

0.24 128 0.45 0

0.25 117 0.46 0

0.26 91 0.47 0

0.27 0 0.48 0

0.28 0 0.49 0

0.29 0 0.50 0

0.30 0
150 

Parupeneus porphyreus

White-saddle goatfish, kumu

Mullidae (goatfishes)

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 547 76 mm

K 0.538 0.231 yr 36 Mean: Moffitt (1979), SD: Kritzer (2001) -1

a0 -0.446 - yr

Lmat 264 13 mm 36 Mean: Moffitt (1979), SD: Nadon (unpublished)

Longevity 6 1.1 yr 36 Mean: Moffitt (1979), SD: Kritzer (2001)

L-W α 6.99e-6 - - - Kulbicki (2005) - P. multifasciatus L-W β 3.211

LS50 225 - mm - DAR commercial data LS95 250

L diver survey 299 8 mm 179 NOAA-CREP diver survey

L commercial 323 1 mm 5074 DAR commercial data

L combined 323 2 mm - -

Max. depth 140 - m - Pyle et al. (2016)

Federal waters 22 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.53 0.11 yr-1

F 1.00 0.58 yr-1

F30 0.54 0.11 yr-1

F/F30 1.9 1.1 -

SPR 0.15 0.17 -

SPR < 0.30 iterations 80 - %

Lc30 317 - mm

General comments

Population abundance was highly variable due to the number of observations in individual years for this 

species being low. The commercial catch increased from 2008 to 2011 but has been going down since then. 

The recreational catch also appeared to be declining. The commercial Lbar has been steady (there were not 

enough observations per year to generate a Lbar time series from UVS).

The life history parameters for this species came from a local study with a limited sample size. The stepwise 

approach applied to this species generated the following estimates: Lmax: 435 mm, Linf: 496 mm, K: 0.54, M: 

0.59, F30: 0.63, F: 0.60, SPR: 0.32, C30 survey: 5,157 kg, C30 catch: 7,931 kg. The lower Linf estimate lead to a 

lower F and higher SPR. 

There was a good agreement between catch-derived and survey-derived population and C30 estimates. The 

survey-derived C30 had lower variability and is usually more reliable than catch-derived C30. 

Parameter Median SD Unit

B from catch 14,600 73,000 kg

B from survey 13,810 4,225 kg

Commercial catch 1,717 1,507 kg

Recreational catch 5,045 2,266 kg

Total catch 7,130 2,704 kg

C30 from catch 4,860 25,000 kg

C30 from survey 4,580 1,480 kg
151 

Parupeneus porphyreus 

Life history parameter distributions.
152 

Parupeneus porphyreus 

Abundance index from UVS (blue circles, ±SE) and total catch time series from recreational

(green squares) and commercial (orange triangles) sectors. 

 

Size structure from commercial catch (top left) and UVS (top right). Average length time series 

(blue circles – UVS, orange triangles – commercial data, ±SE). 
153 

Parupeneus porphyreus 

Stock status parameter distributions (SPR: small bar shows 0.30 level). 
154 

Parupeneus porphyreus 

C30 and current total catch (left) and population size (right) distributions.
155 

Parupeneus porphyreus 

Overfishing probability for a range of C30 levels (catch - orange dashed line, UVS – blue dotted 

line). OFLs are represented by small vertical bars. 

Probability of overfishing for various C30 levels. 

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from

survey (1000 kg)

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from survey 

(1000 kg)

0.10 2.64 2.73 0.31 3.80 3.84

0.11 2.70 2.80 0.32 3.86 3.88

0.12 2.77 2.86 0.33 3.90 3.92

0.13 2.83 2.93 0.34 3.95 3.96

0.14 2.89 3.00 0.35 4.00 4.00

0.15 2.95 3.05 0.36 4.06 4.05

0.16 3.01 3.11 0.37 4.10 4.09

0.17 3.07 3.17 0.38 4.16 4.14

0.18 3.12 3.23 0.39 4.22 4.18

0.19 3.18 3.30 0.40 4.27 4.22

0.20 3.23 3.34 0.41 4.33 4.25

0.21 3.28 3.39 0.42 4.39 4.28

0.22 3.33 3.44 0.43 4.44 4.32

0.23 3.39 3.49 0.44 4.49 4.36

0.24 3.44 3.54 0.45 4.54 4.39

0.25 3.50 3.59 0.46 4.61 4.42

0.26 3.56 3.64 0.47 4.67 4.47

0.27 3.60 3.68 0.48 4.73 4.50

0.28 3.66 3.72 0.49 4.80 4.54

0.29 3.70 3.77 0.50 4.86 4.58

0.30 3.75 3.80
156 

Parupeneus porphyreus 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 418 0.31 360

0.11 414 0.32 358

0.12 412 0.33 356

0.13 407 0.34 353

0.14 405 0.35 351

0.15 400 0.36 349

0.16 398 0.37 346

0.17 396 0.38 344

0.18 394 0.39 342

0.19 389 0.40 340

0.20 387 0.41 338

0.21 385 0.42 335

0.22 382 0.43 333

0.23 380 0.44 331

0.24 376 0.45 328

0.25 374 0.46 326

0.26 374 0.47 324

0.27 369 0.48 322

0.28 367 0.49 320

0.29 364 0.50 317

0.30 362
157 

Calotomus carolinus

Stareye parrotfish, ponuhunuhu 

Scaridae (parrotfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 366 25 mm

- Mean and SD: Nadon & Ault (2016) 

Lmax: 430 (11) from NWHI diver survey K 0.534 0.168 yr-1

a0 -0.6 - yr

Lmat 253 29 mm - Mean and SD: Nadon & Ault (2016)

Longevity 13 4.8 yr - Mean and SD: Nadon & Ault (2016)

L-W α 8.31e-6 - - - Smith & Dalzell (1993) L-W β 3.17

LS50 200 - mm - Estimated. LS95 220

L diver survey 275 4 mm 141 NOAA-CREP diver survey

L commercial - - mm - -

L combined - - mm - -

Max. depth 71 - m - Pyle et al. (2016)

Federal waters 21 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.24 0.08 yr-1

F 0.61 0.33 yr-1

F30 0.29 0.10 yr-1

F/F30 2.2 1.2 -

SPR 0.13 0.14 -

SPR < 0.30 iterations 87 - %

Lc30 276 - mm

General comments

Parrotfish catches are grouped at the family level and therefore there is no species-level commercial data.

Population abundance for this species appeared to be increasing significantly. There were not enough 

observation in individual years to generate a Lbar time series. 

There are currently no published life history parameters for this species. We used the stepwise approach to 

generate LH parameters, using a Lmax value of 430 mm from the pristine NWHI. Analyses using the lower 

Lmax value found in the MHI (410 mm) generated the following results: Linf: 349 mm, K: 0.57, M: 0.25, F30: 

0.32, F: 0.46, SPR: 0.20, C30 survey: 8,879 kg. Furthermore, selectivity for parrotfishes had to be estimated, 

given the absence of catch data. A sensitivity run with LS50 at 230 mm and LS95 at 260 mm had little impact on 

the results (F: 0.62, SPR: 0.16). 

The population biomass estimate may be biased downward given that this species’ range extends to 68 m 

depth, which is beyond the depth of the diver surveys (30 m). 

Parameter Median SD Unit

B from catch - - kg

B from survey 38,102 9,192 kg

Commercial catch - - kg

Recreational catch - - kg

Total catch - - kg

C30 from catch - - kg

C30 from survey 8,430 3,010 kg
158 

Calotomus carolinus 

Life history parameter distributions.
159 

Calotomus carolinus 

Abundance index from UVS (blue circles, ±SE). 

Size structure and average length time series from UVS (±SE).
160 

Calotomus carolinus 

Stock status parameter distributions (SPR: small bar shows 0.30 level). 

C30 (left) and population size (right) distributions.
161 

Calotomus carolinus 

Overfishing probability for a range of C30 levels (UVS – blue dotted line). OFL is represented by 

a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from survey 

(1000 kg)

Overfishing 

probability

C30 from survey 

(1000 kg)

0.10 5.12 0.31 6.99

0.11 5.24 0.32 7.07

0.12 5.34 0.33 7.15

0.13 5.46 0.34 7.23

0.14 5.58 0.35 7.32

0.15 5.66 0.36 7.39

0.16 5.74 0.37 7.46

0.17 5.85 0.38 7.51

0.18 5.94 0.39 7.58

0.19 6.03 0.40 7.64

0.20 6.13 0.41 7.73

0.21 6.22 0.42 7.81

0.22 6.29 0.43 7.90

0.23 6.37 0.44 7.97

0.24 6.45 0.45 8.04

0.25 6.53 0.46 8.13

0.26 6.63 0.47 8.22

0.27 6.70 0.48 8.29

0.28 6.77 0.49 8.35

0.29 6.84 0.50 8.43

0.30 6.92
162 

Calotomus carolinus 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 334 0.31 302

0.11 332 0.32 302

0.12 330 0.33 300

0.13 328 0.34 298

0.14 326 0.35 296

0.15 324 0.36 296

0.16 324 0.37 294

0.17 322 0.38 292

0.18 320 0.39 292

0.19 320 0.40 290

0.20 318 0.41 288

0.21 316 0.42 288

0.22 314 0.43 286

0.23 312 0.44 284

0.24 312 0.45 282

0.25 310 0.46 282

0.26 310 0.47 280

0.27 308 0.48 278

0.28 306 0.49 278

0.29 306 0.50 276

0.30 304
163 

Chlorurus perspecillatus

Spectacled parrotfish, uhu uliuli 

Scaridae (parrotfishes) 

Life history and other input parameters

Parameter Value SD Unit N Source

Linf 500 22 mm

- Mean and SD: Nadon & Ault (2016) 

Lmax: 574 (4) from NWHI diver survey K 0.377 0.135 yr-1

a0 -0.6 - yr

Lmat 348 28 mm - Mean and SD: Nadon & Ault (2016)

Longevity 19 6.5 yr - Mean and SD: Nadon & Ault (2016)

L-W α 1.06e-5 - - - Smith & Dalzell (1993) taken for S. rubroviolaceus L-W β 3.11

LS50 240 - mm - Estimated. LS95 260

L diver survey 404 13 mm 123 NOAA-CREP diver survey

L commercial - - mm - -

L combined - - mm - -

Max. depth 80 - m - Pyle et al. (2016)

Federal waters 21 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.17 0.06 yr-1

F 0.09 0.08 yr-1

F30 0.19 0.06 yr-1

F/F30 0.5 0.4 -

SPR 0.54 0.21 -

SPR < 0.30 iterations 13 - %

Lc30 0 - mm

General comments

Parrotfish catches are grouped at the family level and therefore there is no species-level commercial data.

Population abundance was fairly variable from year to year for this species, likely due to the relatively low 

observation counts. Similarly, there were not enough yearly observations to generate an Lbar time series. 

There are currently no published life history parameters for this species. We used the stepwise approach to 

generate LH parameters using an Lmax value (574 mm) from the NWHI, where this species is fairly abundant. 

Analyses using a higher Lmax estimate from the MHI (610 mm) generated the following results: Linf: 526 mm, 

K: 0.33, M: 0.17, F30: 0.17, F: 0.11, SPR: 0.45, C30 survey: 11,609 kg. Furthermore, selectivity for parrotfishes 

had to be estimated, given the absence of catch data. A sensitivity run with LS50 at 260 mm and LS95 at 300 mm

had little impact on the results (F: 0.09, SPR: 0.52). 

The population biomass estimate may be biased downward given that this species’ range extends to 68 m 

depth, which is beyond the depth of the diver surveys (30 m). 

Parameter Median SD Unit

B from catch - - kg

B from survey 78,752 22,829 kg

Commercial catch - - kg

Recreational catch - - kg

Total catch - - kg

C30 from catch - - kg

C30 from survey 12,400 5,050 kg
164 

Chlorurus perspicillatus

Life history parameter distributions.
165 

Chlorurus perspicillatus 

Abundance index from UVS (blue circles, ±SE). 

Size structure and average length time series from UVS (±SE).
166 

Chlorurus perspicillatus

Stock status parameter distributions (SPR: small bar shows 0.30 level).

C30 (left) and population size (right) distributions.
167 

Chlorurus perspicillatus

Overfishing probability for a range of C30 levels (UVS – blue dotted line). OFL is represented by 

a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from survey 

(1000 kg)

Overfishing 

probability

C30 from survey 

(1000 kg)

0.10 6.9 0.31 10.1

0.11 7.1 0.32 10.2

0.12 7.3 0.33 10.3

0.13 7.5 0.34 10.4

0.14 7.6 0.35 10.6

0.15 7.8 0.36 10.7

0.16 8.0 0.37 10.8

0.17 8.1 0.38 10.9

0.18 8.4 0.39 11.1

0.19 8.5 0.40 11.2

0.20 8.6 0.41 11.3

0.21 8.8 0.42 11.4

0.22 8.9 0.43 11.6

0.23 9.1 0.44 11.7

0.24 9.2 0.45 11.8

0.25 9.3 0.46 11.9

0.26 9.4 0.47 12.0

0.27 9.6 0.48 12.1

0.28 9.7 0.49 12.2

0.29 9.8 0.50 12.4

0.30 9.9
168 

Chlorurus perspicillatus

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 278 0.31 0

0.11 266 0.32 0

0.12 257 0.33 0

0.13 240 0.34 0

0.14 228 0.35 0

0.15 214 0.36 0

0.16 194 0.37 0

0.17 173 0.38 0

0.18 158 0.39 0

0.19 137 0.40 0

0.20 108 0.41 0

0.21 0 0.42 0

0.22 0 0.43 0

0.23 0 0.44 0

0.24 0 0.45 0

0.25 0 0.46 0

0.26 0 0.47 0

0.27 0 0.48 0

0.28 0 0.49 0

0.29 0 0.50 0

0.30 0
169 

Chlorurus spilurus

Bullethead parrotfish, uhu 

Scaridae (parrotfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 341 21 mm

- Mean and SD: Nadon & Ault (2016) 

Lmax: 397 (7) from NWHI diver survey K 0.59 0.22 yr-1

a0 -0.6 - yr

Lmat 235 37 mm - Mean and SD: Nadon & Ault (2016)

Longevity 13 4.2 yr - Mean and SD: Nadon & Ault (2016)

L-W α 2.61e-5 - - - Kulbicki (2005) L-W β 2.97

LS50 220 - mm - Estimated. LS95 240

L diver survey 283 3 mm 435 NOAA-CREP diver survey

L commercial - - mm - -

L combined - - mm - -

Max. depth 34 - m - NOAA-CREP BRUV survey

Federal waters 0 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.26 0.09 yr-1

F 0.50 0.36 yr-1

F30 0.37 0.15 yr-1

F/F30 1.4 1.1 -

SPR 0.23 0.20 -

SPR < 0.30 iterations 64 - %

Lc30 222 - mm

General comments

Parrotfish catches are grouped at the family level and therefore there is no species-level commercial data.

Population abundance has been rising steadily since 2008 while Lbar seemed to be slightly declining. 

Selectivity had to be estimated given the absence of fishery data. A sensitivity run with LS50 at 190 mm and LS95

at 220 mm had little impact on the results (F: 0.57, SPR: 0.16).

Life history parameters were available for this species from a study in American Samoa but the Linf 

parameter was too small (289 mm vs. an Lmax of 380 mm in the MHI). We therefore used the stepwise 

approach for this species. The American Samoa LH parameters generated the following estimates: F: 0.03, 

SPR: 0.88. The much lower F value (and higher SPR value) were expected given the unrealistically low Linf

estimate from this source. 

Note that the longevity estimate obtained through the stepwise approach was similar to the maximum 

recorded age for this species (13 yr vs. 10 yr). The NWHI Lmax is identical to the MHI estimate (397 mm), 

which suggested this number was appropriate.

The population biomass estimate should be reasonably accurate given that this species extends only slightly 

beyond the maximum diver survey depth (30 m). 

Parameter Median SD Unit

B from catch - - kg

B from survey 139,438 17,478 kg

Commercial catch - - kg

Recreational catch - - kg

Total catch - - kg

C30 from catch - - kg

C30 from survey 38,400 11,000 kg
170 

Chlorurus spilurus 

Life history parameter distributions.
171 

Chlorurus spilurus 

Abundance index from UVS (blue circles, ±SE). 

Size structure and average length time series from UVS (±SE).
172 

Chlorurus spilurus

Stock status parameter distributions (SPR: small bar shows 0.30 level). 

C30 (left) and population size (right) distributions.
173 

Chlorurus spilurus

Overfishing probability for a range of C30 levels (UVS – blue dotted line). OFL is represented by 

a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from survey 

(1000 kg)

Overfishing 

probability

C30 from survey 

(1000 kg)

0.10 26.6 0.31 33.3

0.11 26.9 0.32 33.7

0.12 27.4 0.33 33.9

0.13 27.8 0.34 34.2

0.14 28.2 0.35 34.4

0.15 28.6 0.36 34.7

0.16 29.0 0.37 35.0

0.17 29.3 0.38 35.1

0.18 29.6 0.39 35.4

0.19 29.9 0.40 35.8

0.20 30.3 0.41 36.1

0.21 30.5 0.42 36.3

0.22 30.9 0.43 36.5

0.23 31.1 0.44 36.8

0.24 31.4 0.45 37.1

0.25 31.7 0.46 37.3

0.26 32.0 0.47 37.6

0.27 32.3 0.48 37.8

0.28 32.6 0.49 38.1

0.29 32.8 0.50 38.4

0.30 33.1
174 

Chlorurus spilurus

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 301 0.31 264

0.11 299 0.32 262

0.12 297 0.33 260

0.13 295 0.34 257

0.14 293 0.35 257

0.15 290 0.36 255

0.16 288 0.37 253

0.17 286 0.38 251

0.18 284 0.39 249

0.19 284 0.40 246

0.20 282 0.41 244

0.21 279 0.42 242

0.22 277 0.43 240

0.23 275 0.44 238

0.24 273 0.45 235

0.25 273 0.46 233

0.26 271 0.47 231

0.27 268 0.48 229

0.28 266 0.49 227

0.29 264 0.50 224

0.30 301
175 

Scarus dubius

Regal parrotfish, lauia 

Scaridae (parrotfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 335 17 mm

- Mean and SD: Nadon & Ault (2016) 

Lmax: 375 (2) from NWHI diver survey

K 0.63 0.22 yr-1

a0 -0.6 - yr

Lmat 232 26 mm - Mean and SD: Nadon & Ault (2016)

Longevity 13 4.5 yr - Mean and SD: Nadon & Ault (2016)

L-W α 3.86e-7 - - - Froese (1998) L-W β 3.75

LS50 190 - mm - Estimated. LS95 220

L diver survey 287 5 mm 121 NOAA-CREP diver survey

L commercial - - mm - -

L combined - - mm - -

Max. depth 80 - m - Pyle et al. (2016)

Federal waters 21 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.26 0.09 yr-1

F 0.18 0.18 yr-1

F30 0.31 0.10 yr-1

F/F30 0.6 0.6 -

SPR 0.45 0.23 -

SPR < 0.30 iterations 26 - %

Lc30 0 - mm

General comments

Parrotfish catches are grouped at the family level and therefore there is no species-level commercial data.

Population abundance was fairly variable from year to year for this species, but appeared to be increasing 

from 2003 to 2015 before falling slightly in 2016. There was not enough yearly observation to generate a 

proper Lbar time series. 

There are currently no published life history parameters for this species. We used the stepwise approach to 

generate these parameters using an Lmax value (375 mm) from the NWHI. The Lmax estimate from the MHI was 

nearly identical (378 mm). Furthermore, selectivity for parrotfishes had to be estimated, given the absence of 

catch data. A sensitivity run with LS50 at 230 mm and LS95 at 250 mm had little impact on the results (F: 0.21, 

SPR: 0.43). 

The population biomass estimate may be biased downward given that this species’ range extends to 68 m 

depth, which is beyond the depth of the diver surveys (30 m). 

Parameter Median SD Unit

B from catch - - kg

B from survey 32,840 7,868 kg

Commercial catch - - kg

Recreational catch - - kg

Total catch - - kg

C30 from catch - - kg

C30 from survey 7,690 2,660 kg
176 

Scarus dubius 

Life history parameter distributions.
177 

Scarus dubius 

Abundance index from UVS (blue circles. 

Size structure and average length time series from UVS (±SE).
178 

Scarus dubius 

Stock status parameter distributions (SPR: small bar shows 0.30 level).

C30 (left) and population size (right) distributions.
179 

Scarus dubius 

Overfishing probability for a range of C30 levels (UVS – blue dotted line). OFL is represented by 

a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from survey 

(1000 kg)

Overfishing 

probability

C30 from survey 

(1000 kg)

0.10 4.7 0.31 6.4

0.11 4.8 0.32 6.5

0.12 4.9 0.33 6.5

0.13 5.0 0.34 6.6

0.14 5.1 0.35 6.7

0.15 5.2 0.36 6.7

0.16 5.3 0.37 6.8

0.17 5.4 0.38 6.9

0.18 5.4 0.39 7.0

0.19 5.5 0.40 7.0

0.20 5.6 0.41 7.1

0.21 5.7 0.42 7.2

0.22 5.8 0.43 7.2

0.23 5.8 0.44 7.3

0.24 5.9 0.45 7.4

0.25 6.0 0.46 7.4

0.26 6.0 0.47 7.5

0.27 6.1 0.48 7.6

0.28 6.2 0.49 7.6

0.29 6.3 0.50 7.7

0.30 6.3
180 

Scarus dubius 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 260 0.31 136

0.11 256 0.32 125

0.12 253 0.33 108

0.13 249 0.34 0

0.14 243 0.35 0

0.15 239 0.36 0

0.16 236 0.37 0

0.17 232 0.38 0

0.18 226 0.39 0

0.19 222 0.40 0

0.20 217 0.41 0

0.21 211 0.42 0

0.22 203 0.43 0

0.23 198 0.44 0

0.24 190 0.45 0

0.25 185 0.46 0

0.26 179 0.47 0

0.27 173 0.48 0

0.28 165 0.49 0

0.29 158 0.50 0

0.30 148
181 

Scarus psittacus

Palenose parrotfish, uhu 

Scaridae (parrotfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 291 16 mm

- Mean and SD: Nadon & Ault (2016) 

Lmax: 326 (2) from NWHI diver survey K 0.72 0.25 yr-1

a0 -0.6 - yr

Lmat 201 25 mm - Mean and SD: Nadon & Ault (2016)

Longevity 11 3 yr - Mean and SD: Nadon & Ault (2016)

L-W α 5.02e-6 - - - Kulbicki (2005) L-W β 3.32

LS50 200 - mm - Estimated LS95 210

L diver survey 254 2 mm 344 NOAA-CREP diver survey

L commercial - - mm - -

L combined - - mm - -

Max. depth 48 - m - NOAA-CREP BRUV survey

Federal waters 10 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.29 0.10 yr-1

F 0.31 0.29 yr-1

F30 0.45 0.16 yr-1

F/F30 0.7 0.7 -

SPR 0.41 0.23 -

SPR < 0.30 iterations 32 - %

Lc30 0 - Mm

General comments

Parrotfish catches are grouped at the family level and therefore there is no species-level commercial data.

Population abundance has been increasing since 2003, with a potential small decrease in 2016. Lbar has 

remained stable from 2008 to 2016. Selectivity had to be estimated given the lack of catch data. 

The life history parameters were available from a study conducted in American Samoa, but the Linf for this 

study was deemed too small compared to Lmax values in the NWHI (278 mm vs. 326 mm). This study also 

estimated a K parameter that seemed extreme for parrotfishes (1.65). The American Samoa LH parameters 

would have generated the following estimates: Linf: 278 mm, K: 1.65, Lmat: 196 mm, M: 0.50, F30: 0.82, F: 

0.87, SPR: 0.30, C30 survey: 57,913 kg. 

A sensitivity run with LS50 at 220 mm and LS95 at 240 mm had a slight impact on the results (F: 0.51, SPR: 

0.31). 

The population biomass estimate should be reasonably accurate given that this species extends only slightly 

beyond the maximum diver survey depth (30 m). 

Parameter Median SD Unit

B from catch - - kg

B from survey 130,295 41,926 kg

Commercial catch - - kg

Recreational catch - - kg

Total catch - - kg

C30 from catch - - kg

C30 from survey 39,900 16,300 kg
182 

Scarus psittacus 

Life history parameter distributions.
183 

Scarus psittacus 

Abundance index from UVS (blue circles). 

 

Size structure and average length time series from UVS (±SE).
184 

Scarus psittacus 

Stock status parameter distributions (SPR: small bar shows 0.30 level). 

C30 (left) and population size (right) distributions.
185 

Scarus psittacus 

Overfishing probability for a range of C30 levels (UVS – blue dotted line). OFL is represented by 

a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from survey 

(1000 kg)

Overfishing 

probability

C30 from survey 

(1000 kg)

0.10 22.0 0.31 32.4

0.11 22.7 0.32 32.8

0.12 23.4 0.33 33.2

0.13 23.9 0.34 33.6

0.14 24.4 0.35 34.0

0.15 24.9 0.36 34.4

0.16 25.4 0.37 34.8

0.17 26.0 0.38 35.2

0.18 26.5 0.39 35.7

0.19 27.0 0.40 36.0

0.20 27.5 0.41 36.3

0.21 28.0 0.42 36.7

0.22 28.4 0.43 37.0

0.23 28.9 0.44 37.4

0.24 29.5 0.45 37.8

0.25 29.9 0.46 38.3

0.26 30.4 0.47 38.7

0.27 30.8 0.48 39.2

0.28 31.1 0.49 39.5

0.29 31.6 0.50 39.9

0.30 31.9
186 

Scarus psittacus 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 240 0.31 180

0.11 236 0.32 174

0.12 234 0.33 170

0.13 230 0.34 168

0.14 228 0.35 162

0.15 226 0.36 158

0.16 222 0.37 154

0.17 220 0.38 146

0.18 218 0.39 140

0.19 214 0.40 132

0.20 212 0.41 124

0.21 208 0.42 118

0.22 206 0.43 106

0.23 204 0.44 88

0.24 200 0.45 0

0.25 198 0.46 0

0.26 196 0.47 0

0.27 194 0.48 0

0.28 190 0.49 0

0.29 186 0.50 0

0.30 182
187 

Scarus rubroviolaceus

Redlip parrotfish, uhu ‘ele’ele

Scaridae (parrotfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 563 23 mm

K 0.288 0.041 yr 182 Mean and SD: Howard (2008) -1

a0 -0.809 - yr

Lmat 374 9 mm 182 Mean and SD: Howard (2008)

Longevity 22 2 yr 182 Mean and SD: Howard (2008)

L-W α 7.89e-6 - - - Smith & Dalzell (1993) L-W β 3.11

LS50 240 - mm - Estimated. LS95 260

L diver survey 401 8 mm 1054 NOAA-CREP diver survey

L commercial - - mm - -

L combined - - mm - -

Max. depth 68 - m - Pyle et al. (2016)

Federal waters 21 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.15 0.01 yr-1

F 0.18 0.04 yr-1

F30 0.15 0.01 yr-1

F/F30 1.2 0.3 -

SPR 0.26 0.08 -

SPR < 0.30 iterations 68 - %

Lc30 302 - mm

General comments

Parrotfish catches are grouped at the family level and therefore there is no species-level commercial data.

Population abundance has been fluctuating between 2005 and 2016, with no clear temporal pattern. Lbar from 

UVS has also been fluctuating but has remained stable overall. As with other parrotfishes, selectivity had to be 

estimated given the lack of catch data. A sensitivity run with LS50 at 260 mm and LS95 at 300 mm had little 

impact on the results (F: 0.19, SPR: 0.25). 

The life history parameters for this species came from an in-depth local study and there was little reasons to 

doubt the validity of these parameters. As an exercise, the stepwise approach was used to generate alternate 

numbers (using an Lmax of 681 mm from the NWHI) and generated the following values: Linf: 580 mm, K: 0.26, 

M: 0.15, Lmat: 403 mm, F: 0.17, SPR: 0.24. C30 survey: 75,920 kg. These values are fairly close to the original 

analyses.

The population biomass estimate may be biased downward given that this species’ range extends to 68 m 

depth, which is beyond the depth of the diver surveys (30 m). 

Parameter Median SD Unit

B from catch - - kg

B from survey 623,532 80,385 kg

Commercial catch - - kg

Recreational catch - - kg

Total catch - - kg

C30 from catch - - kg

C30 from survey 82,500 11,900 kg
188 

Scarus rubroviolaceus 

Life history parameter distributions.
189 

Scarus rubroviolaceus 

Abundance index from UVS (blue circles, ±SE). 

Size structure and average length time series from UVS (±SE).
190 

Scarus rubroviolaceus 

Stock status parameter distributions (SPR: small bar shows 0.30 level). 

 

C30 (left) and population size (right) distributions.
191 

Scarus rubroviolaceus 

Overfishing probability for a range of C30 levels (UVS – blue dotted line). OFL is represented by 

a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from survey 

(1000 kg)

Overfishing 

probability

C30 from survey 

(1000 kg)

0.10 67.9 0.31 76.7

0.11 68.5 0.32 77.0

0.12 68.9 0.33 77.3

0.13 69.5 0.34 77.6

0.14 70.1 0.35 77.9

0.15 70.6 0.36 78.3

0.16 71.2 0.37 78.6

0.17 71.6 0.38 78.9

0.18 72.0 0.39 79.1

0.19 72.3 0.40 79.4

0.20 72.7 0.41 79.7

0.21 73.1 0.42 80.0

0.22 73.6 0.43 80.3

0.23 73.9 0.44 80.7

0.24 74.4 0.45 81.0

0.25 74.7 0.46 81.3

0.26 75.0 0.47 81.5

0.27 75.4 0.48 81.8

0.28 75.7 0.49 82.2

0.29 76.1 0.50 82.5

0.30 76.4
192 

Scarus rubroviolaceus 

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 386 0.31 355

0.11 384 0.32 353

0.12 382 0.33 353

0.13 379 0.34 350

0.14 379 0.35 348

0.15 377 0.36 348

0.16 374 0.37 346

0.17 372 0.38 343

0.18 370 0.39 341

0.19 370 0.40 338

0.20 367 0.41 338

0.21 365 0.42 336

0.22 362 0.43 334

0.23 360 0.44 334

0.24 360 0.45 331

0.25 358 0.46 329

0.26 355 0.47 326

0.27 353 0.48 324

0.28 350 0.49 324

0.29 350 0.50 322

0.30 348
193 

Cephalopholis argus

Peacock grouper, roi 

Serranidae (groupers) 

Life history and other input parameters

Parameter Value SD Unit N Source

Linf 506 11 mm

K 0.075 0.007 yr 590 Mean: Donovan (2013), SD: Kritzer (2001) -1

a0 -6.5 - yr

Lmat 268 8 mm 100? Mean: Myers (1999), SD: Nadon (unpublished)

Longevity 25 1.4 yr 590 Mean: Donovan (2013), SD: Kritzer (2001)

L-W α 2.05e-5 - - - Kulbicki (2005) L-W β 2.99

LS50 270 - mm - DAR commercial data LS95 310

L diver survey 373 4 mm 614 NOAA-CREP diver survey

L commercial 374 4 mm 2234 DAR commercial data

L combined 374 4 mm - -

Max. depth 80 - m - Pyle et al. (2016)

Federal waters 21 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.13 0.01 yr-1

F 0.02 0.02 yr-1

F30 0.16 0.01 yr-1

F/F30 0.1 0.1 -

SPR 0.80 0.11 -

SPR < 0.30 iterations 0 - %

Lc30 - - mm

General comments

Note: this species is non-native and considered invasive. It was introduced in 1956 from Tahiti. 

Population abundance has been stable for the last 10 years, except for a higher estimate in the first year. The 

commercial catch increased steadily from 2003 to 2011 before going back down. The recreational catch was too 

variable to infer on any temporal trends. The Lbar from the commercial and recreational sector were identical and 

stable.

The growth parameters for this species came from an in-depth local study. However, the maturity parameter came

from a less reliable source. Furthermore, the growth curve did not have juvenile age estimates which explains the 

highly negative a0 and the resulting low K value. We could not run the stepwise approach for this species given that 

the grouper family is not currently available for this method. 

Population estimate from the catch was about a third the size of the population estimate from diver surveys. This 

is not entirely surprising given that the catch estimate seemed low. For example, the average weight of this species 

is around 1 kg, which would suggest that only 3000 individuals are caught recreationally every year. This would 

mean only 8 individuals are caught on a daily basis across the entire island chain, which seems unlikely. The diver 

survey population should be fairly representative given that this is a commonly encountered species that is easily 

identified, although it is likely biased downward given that this species’ range extends beyond diver depths, to 80 

m. Note: no Lc30 could be generated given the very low fishing mortality rates.

Parameter Median SD Unit

B from catch 232,000 494,000 kg

B from survey 777,397 56,961 kg

Commercial catch 830 980 kg

Recreational catch 3,192 6,708 kg

Total catch 4,552 5,594 kg

C30 from catch 33,300 72,200 kg

C30 from survey 111,000 11,300 kg
194 

Cephalopholis argus 

Life history parameter distributions.
195 

Cephalopholis argus 

Abundance index from UVS (blue circles, ±SE) and total catch time series from recreational

(green squares) and commercial (orange triangles) sectors. 

 

Size structure from commercial catch (top left) and UVS (top right). Average length time series 

(blue circles – UVS, orange triangles – commercial data, ±SE). 
196 

Cephalopholis argus 

Stock status parameter distributions (SPR: small bar shows 0.30 level). 
197 

Cephalopholis argus 

C30 and current total catch (left) and population size (right) distributions.
198 

Cephalopholis argus 

Overfishing probability for a range of C30 levels (catch - orange dashed line, UVS – blue dotted 

line). OFLs are represented by small vertical bars. 

Probability of overfishing for various C30 levels. 

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from

survey (1000 kg)

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from survey 

(1000 kg)

0.10 8.9 97.1 0.31 19.8 105.4

0.11 9.3 97.6 0.32 20.4 105.7

0.12 9.7 98.1 0.33 21.0 106.0

0.13 10.3 98.6 0.34 21.7 106.2

0.14 10.8 99.2 0.35 22.3 106.5

0.15 11.3 99.7 0.36 22.9 106.8

0.16 11.8 100.1 0.37 23.5 107.1

0.17 12.2 100.4 0.38 24.2 107.4

0.18 12.7 100.9 0.39 24.8 107.7

0.19 13.2 101.2 0.40 25.5 108.0

0.20 13.6 101.6 0.41 26.2 108.3

0.21 14.1 101.9 0.42 26.9 108.6

0.22 14.5 102.4 0.43 27.8 108.9

0.23 15.2 102.7 0.44 28.6 109.2

0.24 15.7 103.2 0.45 29.3 109.4

0.25 16.3 103.5 0.46 30.0 109.7

0.26 16.8 103.9 0.47 30.7 110.0

0.27 17.4 104.1 0.48 31.4 110.4

0.28 17.9 104.5 0.49 32.3 110.7

0.29 18.6 104.8 0.50 33.3 110.9

0.30 19.0 105.1
199 

Monotaxis grandoculis

Bigeye bream, mu

Lethrinidae (emperors) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 527 22 mm

- Mean and SD: Nadon & Ault (2016) 

Lmax: 597 (19) from NWHI diver survey K 0.37 0.18 yr-1

a0 -0.5 - yr

Lmat 389 28 mm - Mean and SD: Nadon & Ault (2016)

Longevity 21 9 yr - Mean and SD: Nadon & Ault (2016)

L-W α 1.93e-5 - - - Smith & Dalzell (1993) L-W β 3.02

LS50 250 - mm - DAR commercial data LS95 300

L diver survey 359 7 mm 278 NOAA-CREP diver survey

L commercial 448 4 mm 1951 DAR commercial data

L combined 425 5 mm - -

Max. depth 101 - m - Pyle et al. (2016)

Federal waters 22 - % - -

Stock status and other output parameters Management information 

Parameter Median SD Unit

M 0.15 0.06 yr-1

F 0.12 0.12 yr-1

F30 0.16 0.07 yr-1

F/F30 0.8 0.6 -

SPR 0.38 0.22 -

SPR < 0.30 iterations 36 - %

Lc30 0 - Mm

General comments

The population abundance has been stable except for a drastic jump in the last survey year which was likely 

a statistical outlier. Commercial Lbar have been generally steady and higher than the UVS Lbar. It is not entirely 

clear why there is such a discrepancy between Lbar sources. The commercial catch increased drastically 

between 2008 and 2011 before falling quickly again to its original level. The recreational catch was too 

variable to infer on temporal trends. 

There are currently no published life history parameters for this species. We used the stepwise approach to 

generate LH parameters, using an Lmax value from NWHI diver surveys. A sensitivity run using an alternate 

Lmax value from the MHI UVS (556 mm) generated the following results: Linf: 493 mm, K: 0.45, M: 0.16, F30: 

0.18, F: 0.07, SPR: 0.59, C30 catch: 6,828 kg, C30 survey: 35,538 kg. 

The total catch estimate seemed fairly low for a relatively common and prized species. The population 

biomass estimate from diver surveys was much high than the catch-derived estimate. The diver survey 

biomass estimate, and the C30 generated from it, is likely more reliable than the catch data for this species.

Parameter Median SD Unit

B from catch 28,600 82,200 kg

B from survey 231,797 49,031 kg

Commercial catch 1,346 1,270 kg

Recreational catch 1,381 1,129 kg

Total catch 2,998 1,668 kg

C30 from catch 3,950 11,700 kg

C30 from survey 31,700 12,800 kg
200 

Monotaxis grandoculis 

Life history parameter distributions.
201 

Monotaxis grandoculis 

Abundance index from UVS (blue circles, ±SE) and total catch time series from recreational

(green squares) and commercial (orange triangles) sectors. 

 

Size structure from commercial catch (top left) and UVS (top right). Average length time series 

(blue circles – UVS, orange triangles – commercial data, ±SE). 
202 

Monotaxis grandoculis

Stock status parameter distributions (SPR: small bar shows 0.30 level).
203 

Monotaxis grandoculis 

C30 and current total catch (left) and population size (right) distributions.
204 

Monotaxis grandoculis

Overfishing probability for a range of C30 levels (catch - orange dashed line, UVS – blue dotted 

line). OFLs are represented by small vertical bars. 

Probability of overfishing for various C30 levels. 

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from

survey (1000 kg)

Overfish. 

probability

C30 from

catch (1000 kg)

C30 from survey 

(1000 kg)

0.10 1.50 18.7 0.31 2.62 26.0

0.11 1.55 19.2 0.32 2.67 26.3

0.12 1.60 19.7 0.33 2.72 26.6

0.13 1.65 20.2 0.34 2.79 26.9

0.14 1.71 20.5 0.35 2.85 27.2

0.15 1.76 20.9 0.36 2.90 27.5

0.16 1.82 21.3 0.37 2.98 27.8

0.17 1.87 21.6 0.38 3.05 28.2

0.18 1.92 21.9 0.39 3.11 28.5

0.19 1.97 22.2 0.40 3.16 28.7

0.20 2.04 22.6 0.41 3.23 29.1

0.21 2.09 22.9 0.42 3.32 29.4

0.22 2.14 23.3 0.43 3.39 29.7

0.23 2.18 23.6 0.44 3.49 30.0

0.24 2.24 23.9 0.45 3.58 30.2

0.25 2.28 24.2 0.46 3.64 30.5

0.26 2.34 24.5 0.47 3.72 30.8

0.27 2.39 24.9 0.48 3.79 31.0

0.28 2.45 25.1 0.49 3.86 31.3

0.29 2.51 25.4 0.50 3.95 31.7

0.30 2.56 25.7
205 

Monotaxis grandoculis

Probability of overfishing at various minimum sizes. 

Overfishing 

probability

Lc30

(mm)

Overfishing 

probability

Lc30

(mm)

0.10 415 0.31 288

0.11 410 0.32 278

0.12 405 0.33 265

0.13 400 0.34 255

0.14 398 0.35 250

0.15 390 0.36 238

0.16 385 0.37 225

0.17 380 0.38 215

0.18 372 0.39 205

0.19 368 0.40 190

0.20 360 0.41 175

0.21 355 0.42 160

0.22 350 0.43 140

0.23 345 0.44 122

0.24 340 0.45 85

0.25 332 0.46 0

0.26 325 0.47 0

0.27 320 0.48 0

0.28 312 0.49 0

0.29 302 0.50 0

0.30 295
206 

Myripristis berndti

Bigscale soldierfish, ’u’u 

Holocenridae (soldierfishes) 

Life history and other input parameters

Parameter Value SD Unit n Source

Linf 271 14 mm

K 0.148 0.028 yr 126 Mean: Craig & Franklin (2008), SD: Kritzer (2001) -1

a0 -4.48 - yr

Lmat 175 5 mm 100? Mean: Murty (2002) , SD: Nadon (unpublished)

Longevity 27 3.2 yr 126 Mean: Craig & Franklin (2008), SD: Kritzer (2001)

L-W α 2.14e-5 - - - Kulbicki (2005) L-W β 3.00

LS50 170 - mm - Estimated with some HMRFS data. LS95 180

L diver survey 224 4 mm 824 NOAA-CREP diver survey

L commercial - - mm - -

L combined - - mm - -

Max. depth 159 - m - Pyle et al. (2016)

Federal waters 22 - % - -

Stock status and other output parameters

Parameter Median SD Unit

M 0.12 0.01 yr-1

F 0.06 0.04 yr-1

F30 0.16 0.02 yr-1

F/F30 0.4 0.3 -

SPR 0.59 0.17 -

SPR < 0.30 iterations 3 - %

Lc30 - - mm

General comments

This species is reported with other soldierfishes in the commercial data set, preventing the use of catch data 

for the current analyses.

Population abundance for this species appear to have been relatively stable. Lbar were higher in the earlier 

survey years (2005–2008) but appear to have declined in 2009, staying relatively stable since then. Selectivity 

had to be estimated given the lack of catch data. However, there were some length estimates in the HMRFS 

recreational data set (n = 15) which provided some basis for our estimate. A sensitivity run with LS50 at 200 

mm and LS95 at 220 mm generated similar values (F: 0.07 and SPR: 0.63). 

The growth parameters came from a local study. However, the maturity parameter came from a study in 

India for a different species (M. murdjan). Further, the growth study lacked age estimates for juveniles 

resulting in a fairly negative a0 parameter and low K estimate. We could not run the stepwise approach for this 

species given that the soldierfish family is not currently available for this method.

This species occurs at depths much greater than the maximum diver survey depth (159 m vs. 30 m) and it is 

likely that the population size estimate is bias downward. 

Parameter Median SD Unit

B from catch - - kg

B from survey 260,111 47,848 kg

Commercial catch - - kg

Recreational catch - - kg

Total catch - - kg

C30 from catch - - kg

C30 from survey 36,100 7,700 kg
207 

Myripristis berndti

Life history parameter distributions.
208 

Myripristis berndti

Abundance index from UVS (blue circles, ±SE). 

Size structure and average length time series from UVS (±SE).
209 

Myripristis berndti

Stock status parameter distributions (SPR: small bar shows 0.30 level). 

C30 (left) and population size (right) distributions.
210 

Myripristis berndti

Overfishing probability for a range of C30 levels (UVS – blue dotted line). OFL is represented by 

a small vertical bar. 

Probability of overfishing for various C30 levels. 

Overfishing 

probability

C30 from survey 

(1000 kg)

Overfishing 

probability

C30 from survey 

(1000 kg)

0.10 26.7 0.31 32.4

0.11 27.1 0.32 32.6

0.12 27.5 0.33 32.8

0.13 27.9 0.34 33.0

0.14 28.2 0.35 33.2

0.15 28.5 0.36 33.4

0.16 28.8 0.37 33.6

0.17 29.1 0.38 33.8

0.18 29.4 0.39 34.0

0.19 29.7 0.40 34.2

0.20 29.9 0.41 34.4

0.21 30.2 0.42 34.6

0.22 30.4 0.43 34.8

0.23 30.6 0.44 35.1

0.24 30.8 0.45 35.2

0.25 31.1 0.46 35.4

0.26 31.3 0.47 35.5

0.27 31.6 0.48 35.8

0.28 31.8 0.49 35.9

0.29 32.0 0.50 36.1

0.30 32.2