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Assessment of Indian Ocean Narrow-Barred Spanish Mackerel (Scomberomorus Commerson) Using Data

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Assessment of Indian Ocean Narrow-Barred Spanish Mackerel (Scomberomorus Commerson) Using Data IOTC–2017–WPNT07–17 Rev_1 Assessment of Indian Ocean narrow-barred Spanish mackerel (Scomberomorus commerson) using data limited catch-based methods June 2017 IOTC Secretariat1 Introduction ......................................................................................................................................... 2 Basic biology .................................................................................................................................. 2 Fisheries and Catch Trends ............................................................................................................. 2 Methods .............................................................................................................................................. 6 1) C-MSY method ....................................................................................................................... 6 2) Optimised Catch Only Method (OCOM) ................................................................................ 8 Results ................................................................................................................................................. 9 Catch-MSY method ........................................................................................................................ 9 OCOM method .............................................................................................................................. 14 Discussion ......................................................................................................................................... 22 References ......................................................................................................................................... 23 1 [email protected]; [email protected] Page 1 of 24 IOTC–2017–WPNT07–17 Rev_1 Introduction Assessing the status of the stocks of neritic tuna species in the Indian Ocean is fairly challenging due to the data limitations. There is limited information available on stock structure, a lack of standardised (or nominal) CPUE series and biological information is also sparse. Since 2014, data-poor approaches using basic catch information have been used to assess the status of Indian Ocean narrow-barred Spanish mackerel (Scomberomorus commerson) (Zhou and Sharma, 2014; Martin and Sharma 2015; Martin and Robinson, 2016). These assessments are updated in this paper based on the latest catch information. Two methods are used to assess the status of S. commerson: (i) an updated Catch-MSY method (Kimura and Tagart 1982; Walters et. al. 2006; Martell and Froese 2012; Froese et al. 2016) and (ii) an Optimised Catch-Only Method OCOM (Zhou et al., 2013; Zhou et al., 2016). The other neritic species investigated in 2017, as requested by the Scientific Committee, using the same methods was longtail tuna (Thunnus tonggol) (Fu and Martin, 2017). Basic biology The narrow-barred Spanish mackerel (Scomberomorus commerson) (Lacépѐde, 1800) is part of the Scombridae family. It is an epipelagic predator which is distributed widely in the Indo-Pacific region from shallow coastal waters to the edge of the continental shelf where it is found from depths of 10- 70 m (McPherson 1985). It is relatively large for a neritic species with a maximum fork length of 240 cm. Narrow-barred Spanish mackerel is primarily caught by gillnet fleets operating in coastal waters with the highest reported catches form Indonesia, India and I.R. Iran (Geehan et al., 2017). Most research has been focussed in these areas where there are important fisheries for the species, with the most common methods used to estimate growth being through length-frequency studies, although a number of otolith ageing studies have also been undertaken. Estimates of growth parameters for S. commerson, using either length or age-based information, vary between geographic locations. Estimates of the growth parameter K of the von Bertalanffy equation are variable for the Indian Ocean, ranging from 0.12 (Edwards et al. 1985) to 0.78 (Pillai et al. 1993), however, the majority of studies suggest relatively rapid growth of juveniles (IOTC, 2015). Fisheries and Catch Trends Disaggregated nominal catch data were extracted from the IOTC Secretariat database for the period 1950 - 2015, given that records for 2016 were still incomplete at the time of writing. Gillnet fleets are responsible for the majority of reported catches of S. commerson followed by line and purse seine gear, with the majority of catches taken by coastal country fleets (Figure 1). Indonesia, India and I.r.Iran together account for 65% of catches. Figure 2 shows the total catch of narrow-barred Spanish mackerel since 1950, which increased to 2007 and has remained relatively stable since with the most recent catches in 2015 estimated at approximately 150,000 t ( Page 2 of 24 IOTC–2017–WPNT07–17 Rev_1 Table 1). Very few revisions have been made to the nominal catch series since the last assessment was conducted in 2016 (Figure 3). There is a relatively high uncertainty associated with the catch data for the neritic tuna species due to the difficulties in differentiating amongst the different species resulting in reported data in highly aggregate form, often as seerfishes or other groupings. The IOTC Secretariat uses methods of disaggregating these catches by species for assessment purposes. Figure 4 shows the relationship between the catches over time of each of the six neritic tunas. The high level of correlation amongst the species is likely to be because they are often caught together, due to difficulty with species identification and also because of the estimation procedures used to assign proportions of catch amongst the various species. Species-specific reporting has improved over time, leading to a lower level of correlation in more recent years. Figure 1. Average catches in the Indian Ocean over the period 2012-2015, by country. The red line indicates the (cumulative) proportion of catches of Spanish mackerel by country. Table 1. Catch data for S. commerson in the Indian Ocean, 1950-2015 (source IOTC Database) Year Catch (t) Year Catch (t) 1950 9,188 1983 57,647 1951 9,827 1984 64,550 1952 9,707 1985 79,184 1953 9,687 1986 87,184 Page 3 of 24 IOTC–2017–WPNT07–17 Rev_1 1954 11,055 1987 93,123 1955 10,060 1988 100,023 1956 14,291 1989 83,801 1957 13,740 1990 74,451 1958 12,553 1991 76,693 1959 13,076 1992 83,324 1960 13,262 1993 81,509 1961 15,325 1994 87,213 1962 17,040 1995 97,745 1963 17,600 1996 88,404 1964 19,766 1997 95,755 1965 19,618 1998 101,600 1966 23,354 1999 100,019 1967 25,327 2000 104,708 1968 26,430 2001 97,295 1969 25,043 2002 100,544 1970 23,470 2003 103,474 1971 25,387 2004 103,551 1972 30,455 2005 103,404 1973 27,370 2006 117,609 1974 36,180 2007 124,914 1975 36,269 2008 123,297 1976 41,451 2009 135,028 1977 49,986 2010 137,148 1978 49,528 2011 144,523 1979 55,831 2012 157,636 1980 53,927 2013 148,988 1981 56,937 2014 152,187 1982 65,724 2015 154,177 Page 4 of 24 IOTC–2017–WPNT07–17 Rev_1 Figure 2. Total nominal catch of Spanish mackerel by gear, 1950-2015 (IOTC Nominal Catch database) Figure 3. Revisions to the S. commerson nominal catch time series since 2014 Page 5 of 24 IOTC–2017–WPNT07–17 Rev_1 Figure 4. Correlation in catch trends across IOTC neritic tuna species Methods 1) C-MSY method We applied the C-MSY method of Froese et al. (2016) to estimate reference points from catch, resilience and qualitative stock status information for longtail. The C-MSY method represents a further development of the Catch-MSY method of Martell and Froese (2012), with a number of improvements to reduce potential bias. Similar to the Catch-MSY method, The C-MSY relies on only a catch time series dataset, which was available from 1950 – 2015, prior ranges of r and K, and possible ranges of stock sizes in the first and final years of the time series. The Graham-Shaefer surplus production model (Shaefer 1954) is used (equation 1), but it is combined with a simple recruitment model to account for the reduced recruitment at severely depleted stock sizes Page 6 of 24 IOTC–2017–WPNT07–17 Rev_1 (equation 2), where Bt is the biomass in time step t, r is the population growth rate, B0 is the virgin biomass equal to carrying capacity, K, and Ct is the known catch at time t. Annual biomass quantities can then be calculated for every year based on a given set of r and K parameters. Bt B if t (1) Bt1 B r1 Bt Ct 0.25 K K Bt Bt B if t (2) Bt1 B 4 r1 Bt Ct 0.25 K K K A reasonably wide prior range was set for r based on the known level of resilience of the stock as proposed by Martell and Froese (2012) where stocks with a very low resiliency are allocated an r value from 0.015 - 0.1, low resiliency 0.05 - 0.5, medium resiliency 0.2 – 1 and high resiliency 0.6 – 1.5. Based on the FishBase classification, all of the neritic species assessed have a high level of resilience and so a range of 0.6 - 1.5 was used. The prior range of K was determined as maxCt 4maxCt klow ,khigh (3) r high r low Where klow and khigh are the lower and upper lower bound of the range of k, max(C) is the maximum catch in the time series, and rlow and rhigh are lower and upper bound of the range of r values. The ranges for starting and final depletion levels were assumed to be one of possible three biomass ranges: 0.01–0.4 (low), 0.2–0.6 (medium), and high (0.5–0.9), using a set of rules based on the trend of the catch series (see Froese et al. (2016) for details). With this approach, the prior range for
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