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Determination of catchability-at-age for the Mexican Pacific shrimp fishery in the southern Gulf of California
Journal Pre-proof Determination of catchability-at-age for the Mexican Pacific shrimp fishery in the southern Gulf of California Fernando Aranceta-Garza, Francisco Arreguín-Sánchez, Juan Carlos Seijo, Germán Ponce-Díaz, Daniel Lluch-Cota, Pablo del Monte-Luna
PII: DOI: Reference:
S2352-4855(19)30141-0 https://doi.org/10.1016/j.rsma.2019.100967 RSMA 100967
To appear in:
Regional Studies in Marine Science
Received date : 26 February 2019 Revised date : 12 November 2019 Accepted date : 19 November 2019 Please cite this article as: F. Aranceta-Garza, F. Arreguín-Sánchez, J.C. Seijo et al., Determination of catchability-at-age for the Mexican Pacific shrimp fishery in the southern Gulf of California. Regional Studies in Marine Science (2019), doi: https://doi.org/10.1016/j.rsma.2019.100967. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
© 2019 Published by Elsevier B.V.
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Title: Determination of catchability-at-age for the Mexican Pacific shrimp fishery in the southern
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Gulf of California
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Aranceta-Garza, Fernando1; Arreguín-Sánchez, Francisco2,*; Seijo, Juan Carlos3; Ponce-Díaz,
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Germán2; Lluch-Cota, Daniel1; del Monte-Luna, Pablo 2
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1
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COMITAN" La Paz, BCS 23201, México.
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2
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592, La Paz, 23000, Baja California Sur, México
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3
pro of
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Centro de Investigaciones Biológicas del Noroeste, Km. 1 Carretera a San Juan de La Costa "EL
Instituto Politécnico Nacional, Centro Interdisciplinario de Ciencias Marinas, Apartado Postal
Universidad Marista de Mérida, Periférico Norte Tablaje 13941 Carretera Mérida-Progreso,
Mérida 97300, Yucatán, México.
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* Corresponding author: [email protected] / Fax (52±612) 122-53-22.
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ORCID:
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Aranceta-Garza, Fernando, https://orcid.org/0000-0003-1298-1814
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Arreguín-Sánchez, Francisco, https://orcid.org/0000-0002-0143-6629
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Seijo, Juan Carlos, https://orcid.org/0000-0003-2064-8894
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Ponce-Díaz, Germán, https://orcid.org/0000-0002-7409-6880
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Lluch-Cota, Daniel https://orcid.org/0000-0002-9045-9821
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del Monte-Luna, Pablo https://orcid.org/0000-0002-9526-0846
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Summary: One of the main problems in the sequential Mexican-shrimp fisheries is the use of a
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constant catchability coefficient for fleets exploiting different population components implying a
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constant vulnerability in the population structure over time and age which denies important
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population processes and causes bias in fishery model outputs. The purpose of this study was to
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determine the catchability-at-age 𝑞
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,
coefficients in time and across ages the sequential shrimp
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fishery fleets exploiting white, blue and brown shrimp in the southern Gulf of California. The
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𝑞
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denoting important population processes (e.g. migration, recruitment and reproduction) per
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species. The 𝑞
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the offshore fleet in the white shrimp, showing an increase in the inshore fishing vulnerability
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which is associated to subadult migrations. The 𝑞
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similar magnitude among species with the highest observed values in the brown shrimp. However,
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their patterns showed differential peaks of recruitment to the marine fishery and reproductive
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aggregations. For the blue and brown species, the increment in their vulnerability could be
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associated to the offshore fishery recruitment and the reproductive aggregations, observing an
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increase in the 𝑞
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over time and across ages into the Mexican management of the shrimp fishery could improve the
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harvest rates and aid to reduce the growth and/or recruitment overfishing for the southern Gulf of
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California.
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Running title: Catchability-at-age for the shrimp fishery in the Gulf of California
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Keywords: Catchability, sequential fisheries, penaeid shrimp, Gulf of California, bioeconomic
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parameters
values were able to identify the catchability patterns in time and across ages for each fleet,
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for the offshore fleets were found to be of
values in relation to the first maturity ages. The integration of the 𝑞
,
variability
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values of the inshore fleet were three orders of magnitude lower than those from
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,
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1 Introduction
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The catchability coefficient (q) has an important role in establishing fisheries’ management
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policies, that aim to control fishing mortality (F) through fishing effort (Arreguín-Sánchez 1996,
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Mackinson et al. 1997). This coefficient is estimated as the proportion of fish in the population
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being caught per unit effort and reflects the fishing efficiency whilst relating the stock availability
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with fishing yields under the continuous population distribution assumption (Seijo et al. 1998).
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Current fisheries management usually target the adult population by applying a constant value of
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q to approach the average pattern of the variation of catchability reasonably well (Arreguín-
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Sánchez 1996). In contrast, in sequential fisheries (i.e. multifleets exploiting different population
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components in specific habitats and with diverse fishing gears; e.g. shrimp, groupers and squids
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fisheries), the q varies in time and across ages due to several factors; spatial age distribution (e.g.
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juveniles and preadults are present in the inshore habitat and adults in the offshore habitat);
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changes in stock availability between ontogenetic habitats produce by population processes such
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as recruitment, migrations and reproductive-protective aggregations, which increases fishing
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vulnerability (Martínez-Aguilar et al., 1996); and density-dependent population effects (e.g.
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hyperstability or density dependent catchability in Martínez-Aguilar et al. 2009). Also, other
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important sources of variability in q are caused by different fishing power between fleets (e.g.
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industrial trawlers and artisanal boats) and the environmental conditions (e.g. shrimp: García and
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Le Reste 1986, Zhou et al. 2007; small pelagics: Martínez-Aguilar et al. 1996, Mackinson et al.
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1997; red grouper: Arreguin-Sánchez 1996, López-Rocha and Arreguín-Sánchez 2008; red
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octopus: Velázquez-Abunader et al. 2013).
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In México, the most important fishery is the Pacific sequential shrimp fishery (i.e. in value,
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infrastructure and volume: CONAPESCA 2015). In the southern Gulf of California, this fishery
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is composed by two fleets mainly exploiting three commercial species: 1) brown,
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Farfantepenaeus californiensis; 2) blue, Litopenaeus stylirostris; and 3) white shrimps,
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Litopenaeus vannamei. The inshore fleet captures mostly juveniles of white shrimp using casting
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nets, canoes and seasonal channel blockades to shrimp migrations called “tapos”. The industrial
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or offshore fleet is comprised of fishing trawlers that target the adults of the three species in the
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marine grounds using trawling nets.
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The penaeid annual life cycle starts in the marine bottom grounds where mature adults mate,
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fertilize the eggs and produce the pelagic larvae (García and Le Reste 1986). The larvae then
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develop for relatively 20 days until recruiting in the shallow-protected coastal waters, then
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becoming a benthonic postlarvae (20mm of total length “TL”). The postlarvae grow until the pre-
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adult phase (90-150mm TL), and then begin a migration into deep marine waters for the marine
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recruitment and successive reproductive aggregation (210-240mm TL), afterwards, they disperse
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whilst some migrate to deeper waters (Lluch 1977). These population processes increase
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temporarily the shrimp densities, whilst increasing the stock vulnerability to fishing effort
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(Gracia 1996). Most penaeid shrimp present an annual lifespan, although, their maximum
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longevity is about 2-3 years (Garcia 1988). The penaid reproduction cycle varies among the
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species. The blue and white shrimps present the main reproduction peaks in spring and summer
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for the, while for the brown shrimp it is present all year long (Lluch 1977; Aragón -Noriega and
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Alcántara-Razo 2005).
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Shrimp fishery in México is regulated by the Mexican Official Norm (NOM-002-SAG/PEC-
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2013) and currently presents no official management plan (SAGARPA 2018). The current
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management strategy is to maintain a minimal spawning biomass size at the end of the fishing
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season (SAGARPA 2018). This is based on instruments such as fishing permits, fishing gear
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regulations, annual closed seasons and spatial segregation of fleets’ fishing grounds (SAGARPA
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2018). There are no explicit calculations for fishing mortality coefficients or harvest rates. The
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general stock status is categorized as maximally sustainably fished (SAGARPA 2018), however,
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some stocks are reported under deterioration and overexploitation status, such as white and blue
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shrimp in Sinaloa (INP 2004, Madrid-Vera et al. 2012). This status is mainly attributed to growth
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overfishing by inshore fishermen (i.e. mesh size below legal size), and illegal fishing operation
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during the reproductive season closure causing recruitment overfishing. This has been further
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reported in other marine regions of Mexico (e.g. Gulf of Tehuantepec: Cervantes et al. 2006;
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Ramos et al. 2006; Gulf of Mexico: Gracia 1996; Cervantes-Hernández and Gracia 2011).
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The current Mexican shrimp management still uses a constant q in time and/or across ages in
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their stock assessments (e.g. INP 2003; García-Juárez et al. 2009; Cervantes-Hernández et al.
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2010, Meraz-Sánchez et al. 2013). This creates and introduces a bias by the assignation of same
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probabilities of the catch and fishing vulnerabilities to all the population, thereby excluding
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important population processes (i.e. recruitment, migration and reproductive aggregations). This
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management bias is thought to have detrimental consequences applied in deteriorated shrimp
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stocks (Madrid-Vera et al. 2012).
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Current approaches estimating catchability-at-age (𝑞 , ) in other sequential fisheries have
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demonstrated to be useful for fisheries management. In the pacific sardine (Martínez-Aguilar et
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al. 2009) the variability in q-at-length estimates represented a pattern of hyperstability (i.e.
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density-dependent catchability) suggesting a management strategy of a low constant harvest rate.
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For the red grouper fishery (López-Rocha and Arreguín-Sánchez 2008) the q-at-length
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differences suggest an application of spatial management policies for stock recovery. For these
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reasons, the main objective of this study is to determine the catchability-at-age (𝑞 , ) values in the
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shrimp sequential fishery, describing their variability across ages and stock vulnerability patterns
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in a temporal and spatial scale in relation with the shrimp biology in the southern Gulf of
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California. This study aims to improve the management of the shrimp fishery, through the
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knowledge of a variable catchability-per-fleet that impacts harvest rate whilst preventing
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overfishing in this sequential fishery.
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2 Material and methods
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Information used to estimate catchability-at-age (𝑞 , ) was comprised of inshore and offshore data
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from the shrimp fishery fleets from Mazatlán to Escuinapa (southern of Sinaloa, México) during
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the 2014-2015 fishing season (from September 2014 to March 2015) (Figure 1).
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2.1. Fleet effort and catch estimation
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2.1.1 Inshore effort
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The inshore fishing effort was estimated in cast net throws per month (from September to
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December 2014). For each month only the effective fishing days were accounted. The effort was
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estimated as follows:
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a) The reported fishing effort (i.e. number of fishermen per season) and their respective effective
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fishing days were obtained from the SAGARPA-CONAPESCA database using the local fishery
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offices in Mazatlán, Rosario and Escuinapa (Table1a-b). The seasonal fishing dynamics reported
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by local fishermen established a maximum effort during the first month following by a drastically
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decrease towards December associated to early shrimp migration during the fishing season;
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b) The total monthly throws were estimated in the study site from the cast net samplings during the
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fishing season reported by Muñoz-Rubi et al. (2012) using the equation:
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𝑐 𝑒
𝐶 ∴ 𝐸 𝐸
𝐶 𝑒 𝑐
Eq. 1
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Where 𝑐 is sampling catch in kg per month, 𝑒 is the sampling number of cast net throws per
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month, 𝐶 is monthly SAGARPA inshore catch (2014) and 𝐸 is total estimated monthly throws;
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c) The total estimated fishermen per day were obtained dividing estimated monthly throws by the
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product of daily throws by fisherman and effective fishing days;
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d) The estimated fleet monthly fishing days was calculated as the product of the estimated
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fishermen and the fisherman effective fishing days.
pro of
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The fishing power among the inshore fishing effort is assumed as relative constant, comprising a
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canoe with paddles or small outside motor (15-20 HP) with two casting nets.
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2.1.2 Inshore fleet catch estimation
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The inshore fleet catch estimation targeted exclusively the white shrimp. The reported commercial
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catch per month (September to December 2014) was obtained from the SAGARPA-CONAPESCA
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database for the local fishery offices in Mazatlán, Rosario and Escuinapa. The monthly catch per
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cast net throw was the ratio of Muñoz-Rubi et al. (2012) catch in tons and number of cast net throws
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(Table 1h). The catch per fisherman was estimated as the product of total estimated monthly throws
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and the catch per cast net throw in tons (Table 1i).
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The cast net samplings of Muñoz-Rubi et al. (2012) during the fishing season were used to estimate
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the catch in numbers per cast net throw per month, with the assumption that the sampling and
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commercial catch used the same fishing gear and are equivalent. Each sampling presented a catch
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length structure (5mm length class intervals) in numbers (individuals) and in biomass (kg). The
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estimation of the sampling catch structure relative frequencies (in kg) per month was multiplied by
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the total commercial catch (in kg) per month. The catch database, in kilograms, was converted to
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catch in individuals per length using the length/age keys in section 2.3 and obtaining the catch in
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individuals per cast net throws per month.
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2.2.1 Offshore effort
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The offshore fishing effort was estimated in boats (i.e. trawlers) per month. For each month only
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the effective fishing days were accounted. The total boats per month in the study area were obtained
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from the SAGARPA-CONAPESCA satellite database. The fishing power among the offshore
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fishing effort was assumed relatively constant and even conformed a statically Representative
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Production Units (RPU) for Mazatlán (Almendarez-Hernández et al. 2015).
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2.2.2 Offshore fleet catch estimation
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The commercial catch database (from October 2014 to March 2015) for the offshore fleet targeted
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white, blue and brown shrimps and were obtained from the SAGARPA-CONAPESCA satellite
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database. The catch length-structure per month was obtained from a report from a shrimp packing
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plant enterprise, “Mexican Shrimp Paradise”, located in Mazatlán port. They pack for the 55% of
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the total port shrimp trawlers (380 trawlers), therefore, the observed catch length-structure was
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assumed to represent the offshore fishery in the southern Gulf of California.
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Total commercial catch was corrected to only include the observed fishing boats in the study site
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during the fishing season using a rule of three in the equivalence sampling catch/sampling effort =
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total catch/total effort and solving for the sampling catch. Same as in the inshore catch estimation,
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for each species per month, the catch structure relative frequencies per length (class intervals of
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5mm) from the shrimp packing plant (in kg) was estimated and multiplied by its monthly
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commercial catch (in kg). The conversion to catch in individuals per month was made using the
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length/age keys in section 2.3.
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2.3 Age/length key estimation
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The total catch per species was transformed to catch in number of individuals using the age/length
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keys following the methodology on penaeid shrimp in López-Martínez (2000). Only the brown
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shrimp already had an age/length key (López-Martínez 2000). Briefly, a) for the white and blue
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specie s a length frequency dataset was constructed using the total season catch length frequencies
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and previous studies on the study area (inshore length frequencies in the white shrimp: Gutiérrez
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(1980) and Muñoz-Rubi et al. (2012); offshore length frequencies in the white shrimp: Chávez
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(1973) and Mexican Shrimp Paradise 2014-2015 season dataset; blue shrimp: Castro-Ortiz and
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Sánchez-Rojas (1976), National Fisheries Bureau (INP 1974 a-d, 1975a-g) and Mexican Shrimp
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Paradise 2014-2015 season dataset); b) following a), the mean and standard deviation (sd) were
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then calculated for the length frequency database using Bhattacharya (1967) in software FISAT II
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- FAO-ICLARM Stock Assessment (v.1.2.2); c) each mean and sd per species database were fitted
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to a quadratic function; d) a mean total length was then estimated for each relative age in months
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(ranging from 1 – 24 months) using the von Bertalanffy equations per specie (for the white shrimp:
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Aranceta-Garza et al. 2016; blue shrimp: Sáenz-Martínez and Lluch-Belda 1990; and brown
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shrimp: López-Martínez 2000), and assigning for each modal length class its corresponding sd
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estimated from the quadratic function equation; e) the construction of the age/length key was based
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on the normal distribution of each mean length and sd per species. This allowed to assign a
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probability that an individual of length L belongs to one or several ages.
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The age structure was obtained as follows:
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𝐿 𝑃
𝐸 (Eq. 2)
where:
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𝐿 is the transposed vector of the length frequencies;
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𝑃 is the age/length key matrix; and
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𝐸 is the age structure vector.
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2.3.1 Catch-per-unit of effort per fleet
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Catch-per-unit of effort (CPUE) was estimated for the inshore fleet as the catch in numbers per
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cast-net throw per month. The CPUE for the offshore fleet was estimated as catch in numbers per
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boat per month.
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2.4 Catchability-at-age estimation
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Catchability-at-age (𝑞 , ) was estimated following Arreguín-Sánchez (1996) and Arreguín-
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Sánchez and Pitcher (1999), and used the computation algorithm by Martínez-Aguilar et al. (1999).
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The method computes the catchability-at-length (𝑞 , ) based on the transition matrix (Shepherd
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1987, Caswell 1989), as follows: 𝐴
,
,
𝑁
,
Eq. 3
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𝑁
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pro of
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213
where:
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𝑘 and 𝑙 are successive length classes;
215
𝑁
216
𝐴 is the transition matrix, which depends on growth and mortality probabilities calculated by:
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is the number of individuals of length 𝑙 at time t; and
,
𝐴
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𝐺
,
,
𝑆
Eq. 4
,
where:
219
𝐺
220
growth probabilities to each length class interval; and
221
𝑆
,
,
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represents the elements of the growth matrix estimated following Shepard (1987) to assign
represents elements of the survival matrix (following Caswell 1989), which are defined by: ,
𝑒
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𝑆
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,
𝑒
,
Eq. 5
223
where:
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𝑍 𝑘 is the instantaneous rate of total mortality for the 𝑘-length at time 𝑡;
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𝑀 is the instantaneous rate of natural mortality, assumed constant for all length classes, and
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estimated from Aranceta et al. (2016);
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𝑠
is the probability of gear selection for length 𝑘 (assumed to be 𝑠
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and per fleet because of the absence of data); and
229
𝐸
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trawlers per month.
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From substituting Eq. 4 and 5 in Eq. 2 we obtain:
1 for all length classes
𝑁
232
𝐺
,
,
𝑒
,
pro of
is the fishing effort at time t given as cast-net throws per month for the inshore fleet and
𝑁
Eq. 6
,
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Following Arreguín-Sánchez and Pitcher (1999), to solve Eq. 6, 𝑁
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using the CPUE (𝑈 ,
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biomass in the fishery. Then, since all the remaining variables are known, 𝑞
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The 𝑞 , model assumes that catchability 1) is length dependant; 2) depends on fish behaviour; 3)
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is density dependent; 4) the units of effort have static properties or have consistent fishing power
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over time; 5) the fishing fleets present differences in fish-length/age catchability patterns implying
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differences in vulnerability due to differences in fishing strategies, fishing areas, available
240
population structure and fish behaviour; 6) because the model (Eq.6) considered a constant growth,
241
constant natural mortality and no variation in effort, the main source of variability is the
242
survivorship (𝑆
243
(Arreguín-Sánchez 1996; Arreguín-Sánchez and Pitcher 1999).
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Following the pattern of 𝑞 , with age, a logistic function represented as:
values were approached
,
can be estimated.
,
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by the assumption that the CPUE is an acceptable proxy to the available
) related to the fishing mortality and consequently to the catchability-at-age
246
where:
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𝑞,
245
247
,
𝑞𝑚𝑎𝑥 ,
1
𝑒𝑥𝑝
Eq. 7
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𝑙 is length class; 𝑡 is a unit of time, in our case month; 𝑞 , represents the catchability-at-length
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per time; 𝑞𝑚𝑎𝑥 , represents the maximum 𝑞 , for each species, at time 𝑡; 𝑏 is
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the change of catchability-at-length with change in length class; 𝑐 is a fitting parameter.
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Global catchability pattern per species was estimated including all the 𝑞 , values per fishing
252
season in a single function. Once the pattern of catchability-at-length class was estimated with
253
equation 7, the catchability-at-age was computed according with the corresponding mid length
254
for each age.
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Based on the observed data, this model was deemed appropriate as the assumption of catchability
256
increased with length until a certain length limit was achieved and no further increase was
257
observed. The function was empirically fitted per fleet and species to obtain a model describing
258
catchability-at-length; and the form of the function described the data and the species’ biology.
259
3 Results
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Monthly estimates of fishing effort for inshore and offshore fleets are shown in Table 1 and Table
261
2, respectively. The CPUE per fleet and per species is shown in Figure 2, where higher values
262
tended to appear in September, declining afterwards for all but the brown shrimp. The maximum
263
CPUE for the brown shrimp was found in December.
264
The monthly averaged (𝑞 , ± sd) in the white shrimp for the inshore fleet was (7.44×10-07±
265
8.14×10-07). For the offshore fleet, the monthly average for white was (2.13×10-04 2.10×10-04); for
266
blue (2.11×10-04±1.01×10-04); and (1.41×10-04 9.73×10-05) for the brown shrimp. Each monthly
267
𝑞
268
the white shrimp (Figure 3A) showed the aggregation of migrating ages into the “tapos” overtime.
269
The offshore 𝑞
270
recruitment to the marine fishing grounds (ages 4-5 months) or the reproductive aggregations (<9
, representing
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,
pattern presented high variability among all species (Figure 3). The inshore 𝑞
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,
,
,
pattern for
patterns (Figure 3B-D) for the three species showed monthly increments in either
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271
months). Only the white shrimp presented 𝑞
272
species of the inshore lagoon in southern Sinaloa. The 𝑞
273
fishery (Figure 3B-D). Global 𝑞
,
patterns, involving all species, ages and fleets, is represented in
274
Figure 4. The white shrimp 𝑞
,
pattern showed increases with age until an asymptotic trend
275
towards older ages. On the other hand, the blue shrimp 𝑞
276
ages, which remained constant and further increased for older ages. Finally, the brown shrimp
277
𝑞
278
As shown in Figure 5, the increments in the monthly 𝑞
279
vulnerability. For the white shrimp in the inshore grounds, the high slope value in November could
280
be associated to the pre-adult migration (Figure 5A) and, for the three species in the offshore
281
grounds, the high slope values were associated to marine recruitment (i.e. first maturity ages) and
282
reproductive aggregations (Figure 5B-D).
283
4 Discussion
284
Based on the results obtained, we successfully demonstrate the catchability-at-age (𝑞
285
the sequential shrimp fishery for the 2014-2015 season in the Mexican Pacific. The 𝑞
286
varied in time and across ages per fleet and per species. The vulnerability of each species to the
287
fishery could be related with the recognized aggregations of individuals in response to their
288
population processes: recruitment, migration, reproduction.
289
This study successfully showed high fluctuations in the fleets 𝑞
290
responded to several variability factors. Shrimp population processes associated to age behaviour,
291
(e.g. recruitment, migration, and reproduction in García (1988)), were observed in the 𝑞
292
(as shown in Figure 3) showing vulnerability increases (Figure 5). This is due to individual
293
aggregation (i.e. density effects) and fishing gear efficiency (Arreguín-Sánchez 1996). These
for both fleets (Figure 3A,B) being the dominant values were higher for the offshore
pro of
,
,
appeared to be relatively high in early
appeared to have a gradual increase with age, but with a high uncertainty.
slope per species denoted the fishing
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,
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,
,
,
values for ,
patterns
values (Figures 3 and 4) which
,
patterns
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density effects in 𝑞 have been reported for other shrimp fisheries (Australian banana prawns,
295
Penaeus semisulcatus: Zhou et al. 2007), and in other sequential fisheries on other species such as
296
red grouper (López-Rocha et al. 2008) and pacific sardine (Martínez-Aguilar et al. 2009). Other
297
possible variation factors for 𝑞
298
habitat along ontogeny of species (Caddy 1975); changes of fishing power related to fishing gear
299
or operations between fleets (Arreguín-Sánchez 1996); responses to environment changes (Castro-
300
Aguirre and Lluch-Belda 2008, López-Martínez et al. 2008, Aragón Noriega et al. 2012) and
301
fishermen behaviour, where at the beginning of the fishing season the CPUE was concentrated in
302
the blue shrimp (Figure 2C) (i.e. bigger size, better profits), amongst many others.
303
The offshore fleet 𝑞
304
1.41×10-04 9.73×10-05 were in accordance with the magnitude of independent catchability values
305
(𝑞) estimated for the Mexican shrimp fishery in the Gulf of California (3.30×10-04 to 1.74×10-04,
306
Morales-Bojórquez et al. 2001, García-Juárez et al. 2009, Meraz-Sánchez et al. 2013) and even
307
with q values of other regions like Australian banana prawn fishery (6.15×10-04 to 1.09×10-04 in
308
Zhou et al. 2011). Of importance, these constant seasonal values cannot give any further
309
information about the resource vulnerability-at-age patterns, which may underestimate the fishing
310
mortality values.
311
Other studies showing inshore fleet q values were very scarce in Mexican shrimp fishery. This
312
study used several information sources from the fishery office, including field fisher’s logs, in order
313
to estimate robust inshore 𝑞
314
7.44×10-07 8.14×10-07. Other studies assessing the inshore fleet fishery in Oaxaca ( 1,600km
315
away from study site) do not explicitly present any q values methodology, however, they are
316
implicitly estimated by biomass models assuming constant values (Rivera-Velázquez et al. 2009,
values in the shrimp sequential fishery, are those associated to
pro of
,
re-
average values for the three shrimp species (2.13×10-04 2.10×10-04 to
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,
,
values (observed in Figures 3 and 4), with an average value of
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Cervantes-Hernández et al. 2012). Only one study assessing the white shrimp inshore fishery in
318
Chiapas (≈1,750km away from study site) presented q value of 6.3×10-04 (Ramos-Cruz 2013) using
319
similar fishing gear (i.e. cast nets). According to our findings, Ramos-Cruz (2013) q value was
320
three orders of magnitude larger than the values found for our inshore fleet and ranged with the
321
trawlers q values, which may suggest a possible overestimation. In this case, caution must be taken
322
when assessing sequential inshore fisheries using inflated q values because it will overestimate the
323
fishing mortality values for the inshore fleet and consequently, its management may cause a growth
324
overfishing in the shrimp fishery.
325
The global 𝑞
326
fleet associated to the migration ages (Figure 4A). This increment was also associated in the
327
offshore fleet with the first maturity ages and observing the highest values over the older ages
328
(Figure 4 A,B,C) probably because the reproductive aggregations. This pattern has been observed
329
in other fisheries with aggregating behaviour (Sardinops caeruleus, in the Gulf of California,
330
Martínez-Aguilar et al. 2009; Epinephelus morio, Campeche Banks, López-Rocha and Arreguín-
331
Sánchez 2008).
332
Particularly for the white shrimp, 𝑞
333
(Figure 4A). Most young shrimps are exposed to fishing gear at inshore water mostly from
334
September to November and is reflected by high values of catchability and vulnerability (Figure
335
5A) with a rapid decrease afterwards. Catchability was also found to increase rapidly at offshore
336
waters from November to December due to the migration to offshore waters (Figure 5B). Once
337
migration was completed, the catchability decreased at offshore waters following the stock
338
decrement.
log function (Figure 4) indicated an increment in the vulnerability for the inshore
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,
pro of
317
,
values at inshore waters tended to increase as shrimps grow
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The blue shrimp showed a constant catchability for pre-adults increasing for older ages and over
340
time (Figure 4B and 5C). This pattern was found to be congruent with their biology and fishing
341
operations. At the beginning of the season (Figure 5C: October), most fishing occurs with blue
342
shrimp in shallow coastal waters as they reach higher market prices. Even when the CPUE
343
decreases over time, shrimps tend to move into deeper waters and aggregate for reproduction. This
344
allowed to reach a maximum catchability and vulnerability value prior to the end of fishery seasons
345
designated to prevent recruitment overfishing (Figure 5C: Jan-Feb).
346
The catchability behaviour for the brown shrimp appears to depend on both, the reproductive adult
347
aggregations (e.g. October, December and February in Figure 3D) and the recruitment to the fishery
348
(e.g. November, January, March in Figure 3D), which can be explained because it is an all-year-
349
round reproductive period in southern Sinaloa (Aragón-Noriega and Alcántara-Razo 2005). Even
350
when catchability-at-age is the most uncertain pattern, it suggests that catchability tends to increase
351
with age (Figure 4C), which is probably associated with reproductive aggregation ages. However,
352
changes in catchability tend to decrease with time along the fishing season (Figure 5D), which,
353
according to our assumption in equation 6, also coincides with the decrease of the stock availability,
354
probably due to the stock depletion at the end of the season. The proportionality between the stock
355
availability and CPUE does not imply linearity and could be reflecting a density-dependent
356
catchability or hyperstability, as demonstrated previously in the pacific sardine (Martínez-Aguilar
357
et al. 2009).
358
Following Caddy (1979), catchability relates available stock, or individuals removed, by a fishing
359
effort unit which, at the same time, depends of the stock distribution and behaviour. In this sense,
360
and regarding its management, further research is warranted. the next step of research, once
361
catchability is known, will be to relate the CPUE with the real stock abundance measures.
362
5 Conclusion
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339
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The management efficiency of any fishery can be increased using fishing effort as a control variable
364
coupled with knowledge of catchability patterns. Estimated patterns of catchability-at-age over
365
time and across ages appear to offer an opportunity to evaluate potential success of management
366
for the three main shrimp species in the southern Gulf of California. Additionally, such patterns
367
provide specific information on how fishing could be applied in a sequential fishery. In the case of
368
the white shrimp, it can offer realistic fishing mortality estimates for an adequate management to
369
aid restoring the already deteriorated stocks. For blue and brown shrimp, catchability patterns can
370
offer more detailed information on fishing mortality related to reproductive aggregation and, in the
371
case of Mexico, help increase the confidence in defining seasonal fishing closures. Finally, even
372
when estimated catchability-at-age patterns can be taken as global patterns for each species, the
373
relative catchability values also depend on other factors affecting shrimp behaviour such as changes
374
in habitats, climate, and distribution of individuals. To improve management practices that
375
anticipate natural or induced changes, we strongly suggest reinforcing the monitoring programme
376
year to year in order to adapt management as required.
377
ACKNOWLEDGEMENTS
378
FAG thanks CONACyT, IPN-BEIFI and COFAA for the grants received. A Special thanks to Raul
379
Villaseñor (CONAPESCA), Jesús Ortiz (industrial fleet leader) and Miguel Rose (Mexican Shrimp
380
Paradise). FAS, GPD and PDM thank Instituto Politécnico Nacional support through EDI and
381
COFAA programs. Authors acknowledge the support through projects CONACYT (221705), SIP-
382
IPN (20172122, 20180929).
383
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384
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523
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524 525
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521
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TABLES
528
Table 1. Inshore fishing effort and observed catch of white shrimp during the 2014-15 fishing
529
season in southern Gulf of California. Sep a. Reported inshore fishing effort (total fishermen) b. Fisherman effective monthly fishing days c. Total throws per fisherman
25
25
25
150.96
67.14
73.56
re-
Dec
1,978,337
733,818
681,259
2,529
524
437
370
58,155
13,105
10,930
9,261
424.53
183.48
40.99
30.29
0.0073
0.0140
0.0038
0.0033
1.48E-04
9.30E-05
5.60E-05
4.4E-05
f. Estimated fleet effective monthly
h. Catch per fisherman (t day-1)b
urn a
(t day-1)b
Nov
2,873,546
e. Estimated fishermen (day) b
i. Catch per cast net throw
Oct
lP
d. Total estimated monthly throws b
g. Reported monthly catch (t)a
23
49.41
(day)b
fishing days
4000
pro of
526 527
a
531
from local fishing offices and surveys in southern Sinaloa.
532 533
SAGARPA-CONAPESCA 2014 database; b Muñoz et al. (2012); observed data were obtained
Jo
530
Journal Pre-proof
534
Table 2. Offshore fishing effort and observed catch of white shrimp (Litopenaeus vannamei);
536
blue shrimp (L. stylirostris) and brown shrimp (Farfantepenaeus californiensis) during the 2014-
537
15 fishing season in the southern Gulf of California. Observed satellite tracking Oct
Nov
Dec
189
95
140
Number of shrimp trawlers Effective fishing days per boat 17.69
21.02
27.25
White shrimp
17.6
22.19
27.81
Brown shrimp
17.71
19.75
Mean±sd
17.67±0.06 20.99±1.22
27.51
27.52±0.17
lP
Effective fishing days per fleet
Jan
Feb
Mar
165
203
135
22.61
31.35
21.28
23.72
30.84
24
44.1
31.58
20.95
re-
Blue shrimp
pro of
535
30.14±10.42 31.26±0.37 22.08±1.54
Blue shrimp
3343
1996
3815
3731
6364
2873
White shrimp
3326
2108
3894
3914
6261
3240
Brown shrimp
3348
1876
3851
3777
6410
2828
3348
2108
3894
3914
6410
3240
582
195
274
92
178
104
69
24
25
35
63
12
437
340
890
348
909
299
1088
559
1189
475
1150
414
effective fishing days
urn a
Maximum
Observed catch (t) Blue shrimp White shrimp Total 538 539 540
Jo
Brown shrimp
Journal Pre-proof
Table 3. Catchability-at-age logistic function parameters for commercial shrimps in the 2014-15
542
fishing season in the southern Gulf of California.
543
White shrimp (Litopenaeus vannamei) a b c 7.4E-06 0.038 -7.420 3.9E-06 0.029 -5.790 1.6E-06 0.285 -28.913 8.1E-07 -0.140 18.877 White shrimp (L. vannamei) F(x) parameters Log (a) Log (b) Log (c) October -3.845 -0.054 13.562 -3.793 -0.108 25.240 November December -4.219 0.159 -21.968 January -4.744 -0.032 8.077 February -143.943 0.004 -4.313 1.00E-04 -0.093 18.706 March Fishery (Log) -8.046 -0.017 3.325 Blue shrimp (L. stylirostris) F(x) parameters a b c October 0.369 0.019 -11.036 November 3.00E-04 -0.040 7.326 December 4.00E-04 -0.013 3.104 January 5.00E-04 0.035 -7.153 1.00E-04 0.041 -7.042 February March 7.00E-05 -0.323 68.426 Fishery (Log) -3.73461 -0.118 27.849 Brown shrimp (Farfantepenaeus californiensis) F(x) parameters a b c October 2.35 E-04 0.0862 -14.089 November 3.54 E-04 -0.069 10.000 December 2.84 E-04 0.047 -6.127 January 2.48 E-04 0.024 -3.782 February 5.60 E-04 -0.200 29.793 March 1.20 E-04 -0.084 12.672 -3.95796 -0.049 12.103 Fishery (Log) *a is 𝑞𝑚𝑎𝑥 , ; 𝑏 is Δ𝑞 , ⁄Δ𝑙 ; 𝑐 is a fitting parameter.
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F(x) parameters September October November December
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Offshore fleet
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R 0.897 0.785 0.654 0.825 R 0.926 0.574 0.588 0.688 0.709 0.693 0.812 R 0.860 0.601 0.524 0.586 0.467 0.381 0.368 R 0.970 0.902 0.490 0.446 0.946 0.999 0.295
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FIGURES
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Figure 1 - Study regions for the shrimp fishery in southern Gulf of California.
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*Inshore fleet surveys applied in: Huizache; Chametla; Teacapán lagoon; Palmilla; and
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Teacapán marine area in Sinaloa.
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Figure 2 – Catch-per-unit-effort (CPUE) of A) white shrimp (Litopenaeus vannamei) as number of individuals per cast net throws per
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the offshore fleet.
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California. The season length was from September to December (2014) for inshore fleet and from October (2014) to March (2015) for
(Farfantepenaeus californiensis) as number of individuals per trawler per month for the offshore fleet (2) in southern Gulf of
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and from October (2014) to March (2015) for the offshore fleet.
for the offshore fleet (2) in southern Gulf of California. The season length was from September to December (2014) for inshore fleet
fleet (1); and of B) white shrimp (L. vannamei); C) blue shrimp (L. stylirostris) and D) brown shrimp (Farfantepenaeus californiensis)
Figure 3 – Catchability-at-age and log function estimation (dashed line) of A) white shrimp (Litopenaeus vannamei) for the inshore
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A) White Shrimp
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(L. stylirostris) and C) brown shrimp (Farfantepenaeus californiensis) in southern Gulf of California.
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A)
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Figure 5 - Slope of catchability-at-age pattern (Table 3) showing the change of catchability pattern with time: A) white shrimp (Litopenaeus vannamei) – inshore fleet; B) white shrimp (L. vannamei) – offshore fleet; C) blue shrimp (L. stylirostris) – offshore fleet; D) brown shrimp (Farfantepenaues californiensis) – offshore fleet, during the 2014-15 season in southern Gulf of California.
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La Paz, Baja California Sur, Mexico, September 27th, 2019.
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Dr. Gunnar Lauenstein Regional Studies in Marine Science Editor
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Regarding the manuscript titled “Determination of catchability‐at‐age for the Mexican Pacific shrimp fishery in the southern Gulf of California”, authored by Aranceta‐Garza F., Arreguín‐Sánchez F., Seijo JC., Ponce‐Díaz G., Lluch‐Cota D., del Monte‐Luna P.; we declare that there is not any conflict of interest regarding use of data. Also, we declare that the described has not been published previously, that it is not under consideration for publication elsewhere, and that it was approved by all authors and tacitly by the responsible authorities of my institution
With no other thing to declare, I appreciate very much your kind attention
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Sincerely yours
Dr. Francisco Arreguín Sánchez
PII: DOI: Reference:
S2352-4855(19)30141-0 https://doi.org/10.1016/j.rsma.2019.100967 RSMA 100967
To appear in:
Regional Studies in Marine Science
Received date : 26 February 2019 Revised date : 12 November 2019 Accepted date : 19 November 2019 Please cite this article as: F. Aranceta-Garza, F. Arreguín-Sánchez, J.C. Seijo et al., Determination of catchability-at-age for the Mexican Pacific shrimp fishery in the southern Gulf of California. Regional Studies in Marine Science (2019), doi: https://doi.org/10.1016/j.rsma.2019.100967. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
© 2019 Published by Elsevier B.V.
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Title: Determination of catchability-at-age for the Mexican Pacific shrimp fishery in the southern
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Gulf of California
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Aranceta-Garza, Fernando1; Arreguín-Sánchez, Francisco2,*; Seijo, Juan Carlos3; Ponce-Díaz,
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Germán2; Lluch-Cota, Daniel1; del Monte-Luna, Pablo 2
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1
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COMITAN" La Paz, BCS 23201, México.
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2
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592, La Paz, 23000, Baja California Sur, México
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Centro de Investigaciones Biológicas del Noroeste, Km. 1 Carretera a San Juan de La Costa "EL
Instituto Politécnico Nacional, Centro Interdisciplinario de Ciencias Marinas, Apartado Postal
Universidad Marista de Mérida, Periférico Norte Tablaje 13941 Carretera Mérida-Progreso,
Mérida 97300, Yucatán, México.
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* Corresponding author: [email protected] / Fax (52±612) 122-53-22.
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ORCID:
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Aranceta-Garza, Fernando, https://orcid.org/0000-0003-1298-1814
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Arreguín-Sánchez, Francisco, https://orcid.org/0000-0002-0143-6629
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Seijo, Juan Carlos, https://orcid.org/0000-0003-2064-8894
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Ponce-Díaz, Germán, https://orcid.org/0000-0002-7409-6880
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Lluch-Cota, Daniel https://orcid.org/0000-0002-9045-9821
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del Monte-Luna, Pablo https://orcid.org/0000-0002-9526-0846
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Summary: One of the main problems in the sequential Mexican-shrimp fisheries is the use of a
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constant catchability coefficient for fleets exploiting different population components implying a
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constant vulnerability in the population structure over time and age which denies important
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population processes and causes bias in fishery model outputs. The purpose of this study was to
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determine the catchability-at-age 𝑞
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,
coefficients in time and across ages the sequential shrimp
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fishery fleets exploiting white, blue and brown shrimp in the southern Gulf of California. The
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𝑞
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denoting important population processes (e.g. migration, recruitment and reproduction) per
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species. The 𝑞
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the offshore fleet in the white shrimp, showing an increase in the inshore fishing vulnerability
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which is associated to subadult migrations. The 𝑞
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similar magnitude among species with the highest observed values in the brown shrimp. However,
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their patterns showed differential peaks of recruitment to the marine fishery and reproductive
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aggregations. For the blue and brown species, the increment in their vulnerability could be
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associated to the offshore fishery recruitment and the reproductive aggregations, observing an
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increase in the 𝑞
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over time and across ages into the Mexican management of the shrimp fishery could improve the
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harvest rates and aid to reduce the growth and/or recruitment overfishing for the southern Gulf of
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California.
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Running title: Catchability-at-age for the shrimp fishery in the Gulf of California
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Keywords: Catchability, sequential fisheries, penaeid shrimp, Gulf of California, bioeconomic
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parameters
values were able to identify the catchability patterns in time and across ages for each fleet,
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for the offshore fleets were found to be of
values in relation to the first maturity ages. The integration of the 𝑞
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variability
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values of the inshore fleet were three orders of magnitude lower than those from
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1 Introduction
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The catchability coefficient (q) has an important role in establishing fisheries’ management
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policies, that aim to control fishing mortality (F) through fishing effort (Arreguín-Sánchez 1996,
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Mackinson et al. 1997). This coefficient is estimated as the proportion of fish in the population
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being caught per unit effort and reflects the fishing efficiency whilst relating the stock availability
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with fishing yields under the continuous population distribution assumption (Seijo et al. 1998).
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Current fisheries management usually target the adult population by applying a constant value of
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q to approach the average pattern of the variation of catchability reasonably well (Arreguín-
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Sánchez 1996). In contrast, in sequential fisheries (i.e. multifleets exploiting different population
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components in specific habitats and with diverse fishing gears; e.g. shrimp, groupers and squids
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fisheries), the q varies in time and across ages due to several factors; spatial age distribution (e.g.
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juveniles and preadults are present in the inshore habitat and adults in the offshore habitat);
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changes in stock availability between ontogenetic habitats produce by population processes such
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as recruitment, migrations and reproductive-protective aggregations, which increases fishing
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vulnerability (Martínez-Aguilar et al., 1996); and density-dependent population effects (e.g.
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hyperstability or density dependent catchability in Martínez-Aguilar et al. 2009). Also, other
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important sources of variability in q are caused by different fishing power between fleets (e.g.
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industrial trawlers and artisanal boats) and the environmental conditions (e.g. shrimp: García and
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Le Reste 1986, Zhou et al. 2007; small pelagics: Martínez-Aguilar et al. 1996, Mackinson et al.
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1997; red grouper: Arreguin-Sánchez 1996, López-Rocha and Arreguín-Sánchez 2008; red
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octopus: Velázquez-Abunader et al. 2013).
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In México, the most important fishery is the Pacific sequential shrimp fishery (i.e. in value,
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infrastructure and volume: CONAPESCA 2015). In the southern Gulf of California, this fishery
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is composed by two fleets mainly exploiting three commercial species: 1) brown,
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Farfantepenaeus californiensis; 2) blue, Litopenaeus stylirostris; and 3) white shrimps,
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Litopenaeus vannamei. The inshore fleet captures mostly juveniles of white shrimp using casting
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nets, canoes and seasonal channel blockades to shrimp migrations called “tapos”. The industrial
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or offshore fleet is comprised of fishing trawlers that target the adults of the three species in the
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marine grounds using trawling nets.
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The penaeid annual life cycle starts in the marine bottom grounds where mature adults mate,
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fertilize the eggs and produce the pelagic larvae (García and Le Reste 1986). The larvae then
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develop for relatively 20 days until recruiting in the shallow-protected coastal waters, then
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becoming a benthonic postlarvae (20mm of total length “TL”). The postlarvae grow until the pre-
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adult phase (90-150mm TL), and then begin a migration into deep marine waters for the marine
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recruitment and successive reproductive aggregation (210-240mm TL), afterwards, they disperse
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whilst some migrate to deeper waters (Lluch 1977). These population processes increase
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temporarily the shrimp densities, whilst increasing the stock vulnerability to fishing effort
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(Gracia 1996). Most penaeid shrimp present an annual lifespan, although, their maximum
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longevity is about 2-3 years (Garcia 1988). The penaid reproduction cycle varies among the
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species. The blue and white shrimps present the main reproduction peaks in spring and summer
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for the, while for the brown shrimp it is present all year long (Lluch 1977; Aragón -Noriega and
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Alcántara-Razo 2005).
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Shrimp fishery in México is regulated by the Mexican Official Norm (NOM-002-SAG/PEC-
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2013) and currently presents no official management plan (SAGARPA 2018). The current
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management strategy is to maintain a minimal spawning biomass size at the end of the fishing
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season (SAGARPA 2018). This is based on instruments such as fishing permits, fishing gear
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regulations, annual closed seasons and spatial segregation of fleets’ fishing grounds (SAGARPA
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2018). There are no explicit calculations for fishing mortality coefficients or harvest rates. The
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general stock status is categorized as maximally sustainably fished (SAGARPA 2018), however,
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some stocks are reported under deterioration and overexploitation status, such as white and blue
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shrimp in Sinaloa (INP 2004, Madrid-Vera et al. 2012). This status is mainly attributed to growth
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overfishing by inshore fishermen (i.e. mesh size below legal size), and illegal fishing operation
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during the reproductive season closure causing recruitment overfishing. This has been further
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reported in other marine regions of Mexico (e.g. Gulf of Tehuantepec: Cervantes et al. 2006;
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Ramos et al. 2006; Gulf of Mexico: Gracia 1996; Cervantes-Hernández and Gracia 2011).
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The current Mexican shrimp management still uses a constant q in time and/or across ages in
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their stock assessments (e.g. INP 2003; García-Juárez et al. 2009; Cervantes-Hernández et al.
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2010, Meraz-Sánchez et al. 2013). This creates and introduces a bias by the assignation of same
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probabilities of the catch and fishing vulnerabilities to all the population, thereby excluding
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important population processes (i.e. recruitment, migration and reproductive aggregations). This
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management bias is thought to have detrimental consequences applied in deteriorated shrimp
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stocks (Madrid-Vera et al. 2012).
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Current approaches estimating catchability-at-age (𝑞 , ) in other sequential fisheries have
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demonstrated to be useful for fisheries management. In the pacific sardine (Martínez-Aguilar et
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al. 2009) the variability in q-at-length estimates represented a pattern of hyperstability (i.e.
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density-dependent catchability) suggesting a management strategy of a low constant harvest rate.
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For the red grouper fishery (López-Rocha and Arreguín-Sánchez 2008) the q-at-length
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differences suggest an application of spatial management policies for stock recovery. For these
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reasons, the main objective of this study is to determine the catchability-at-age (𝑞 , ) values in the
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shrimp sequential fishery, describing their variability across ages and stock vulnerability patterns
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in a temporal and spatial scale in relation with the shrimp biology in the southern Gulf of
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California. This study aims to improve the management of the shrimp fishery, through the
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knowledge of a variable catchability-per-fleet that impacts harvest rate whilst preventing
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overfishing in this sequential fishery.
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2 Material and methods
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Information used to estimate catchability-at-age (𝑞 , ) was comprised of inshore and offshore data
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from the shrimp fishery fleets from Mazatlán to Escuinapa (southern of Sinaloa, México) during
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the 2014-2015 fishing season (from September 2014 to March 2015) (Figure 1).
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2.1. Fleet effort and catch estimation
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2.1.1 Inshore effort
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The inshore fishing effort was estimated in cast net throws per month (from September to
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December 2014). For each month only the effective fishing days were accounted. The effort was
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estimated as follows:
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a) The reported fishing effort (i.e. number of fishermen per season) and their respective effective
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fishing days were obtained from the SAGARPA-CONAPESCA database using the local fishery
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offices in Mazatlán, Rosario and Escuinapa (Table1a-b). The seasonal fishing dynamics reported
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by local fishermen established a maximum effort during the first month following by a drastically
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decrease towards December associated to early shrimp migration during the fishing season;
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b) The total monthly throws were estimated in the study site from the cast net samplings during the
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fishing season reported by Muñoz-Rubi et al. (2012) using the equation:
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𝑐 𝑒
𝐶 ∴ 𝐸 𝐸
𝐶 𝑒 𝑐
Eq. 1
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Where 𝑐 is sampling catch in kg per month, 𝑒 is the sampling number of cast net throws per
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month, 𝐶 is monthly SAGARPA inshore catch (2014) and 𝐸 is total estimated monthly throws;
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c) The total estimated fishermen per day were obtained dividing estimated monthly throws by the
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product of daily throws by fisherman and effective fishing days;
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d) The estimated fleet monthly fishing days was calculated as the product of the estimated
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fishermen and the fisherman effective fishing days.
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The fishing power among the inshore fishing effort is assumed as relative constant, comprising a
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canoe with paddles or small outside motor (15-20 HP) with two casting nets.
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2.1.2 Inshore fleet catch estimation
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The inshore fleet catch estimation targeted exclusively the white shrimp. The reported commercial
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catch per month (September to December 2014) was obtained from the SAGARPA-CONAPESCA
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database for the local fishery offices in Mazatlán, Rosario and Escuinapa. The monthly catch per
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cast net throw was the ratio of Muñoz-Rubi et al. (2012) catch in tons and number of cast net throws
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(Table 1h). The catch per fisherman was estimated as the product of total estimated monthly throws
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and the catch per cast net throw in tons (Table 1i).
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The cast net samplings of Muñoz-Rubi et al. (2012) during the fishing season were used to estimate
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the catch in numbers per cast net throw per month, with the assumption that the sampling and
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commercial catch used the same fishing gear and are equivalent. Each sampling presented a catch
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length structure (5mm length class intervals) in numbers (individuals) and in biomass (kg). The
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estimation of the sampling catch structure relative frequencies (in kg) per month was multiplied by
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the total commercial catch (in kg) per month. The catch database, in kilograms, was converted to
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catch in individuals per length using the length/age keys in section 2.3 and obtaining the catch in
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individuals per cast net throws per month.
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2.2.1 Offshore effort
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The offshore fishing effort was estimated in boats (i.e. trawlers) per month. For each month only
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the effective fishing days were accounted. The total boats per month in the study area were obtained
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from the SAGARPA-CONAPESCA satellite database. The fishing power among the offshore
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fishing effort was assumed relatively constant and even conformed a statically Representative
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Production Units (RPU) for Mazatlán (Almendarez-Hernández et al. 2015).
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2.2.2 Offshore fleet catch estimation
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The commercial catch database (from October 2014 to March 2015) for the offshore fleet targeted
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white, blue and brown shrimps and were obtained from the SAGARPA-CONAPESCA satellite
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database. The catch length-structure per month was obtained from a report from a shrimp packing
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plant enterprise, “Mexican Shrimp Paradise”, located in Mazatlán port. They pack for the 55% of
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the total port shrimp trawlers (380 trawlers), therefore, the observed catch length-structure was
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assumed to represent the offshore fishery in the southern Gulf of California.
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Total commercial catch was corrected to only include the observed fishing boats in the study site
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during the fishing season using a rule of three in the equivalence sampling catch/sampling effort =
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total catch/total effort and solving for the sampling catch. Same as in the inshore catch estimation,
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for each species per month, the catch structure relative frequencies per length (class intervals of
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5mm) from the shrimp packing plant (in kg) was estimated and multiplied by its monthly
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commercial catch (in kg). The conversion to catch in individuals per month was made using the
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length/age keys in section 2.3.
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2.3 Age/length key estimation
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The total catch per species was transformed to catch in number of individuals using the age/length
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keys following the methodology on penaeid shrimp in López-Martínez (2000). Only the brown
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shrimp already had an age/length key (López-Martínez 2000). Briefly, a) for the white and blue
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specie s a length frequency dataset was constructed using the total season catch length frequencies
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and previous studies on the study area (inshore length frequencies in the white shrimp: Gutiérrez
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(1980) and Muñoz-Rubi et al. (2012); offshore length frequencies in the white shrimp: Chávez
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(1973) and Mexican Shrimp Paradise 2014-2015 season dataset; blue shrimp: Castro-Ortiz and
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Sánchez-Rojas (1976), National Fisheries Bureau (INP 1974 a-d, 1975a-g) and Mexican Shrimp
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Paradise 2014-2015 season dataset); b) following a), the mean and standard deviation (sd) were
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then calculated for the length frequency database using Bhattacharya (1967) in software FISAT II
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- FAO-ICLARM Stock Assessment (v.1.2.2); c) each mean and sd per species database were fitted
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to a quadratic function; d) a mean total length was then estimated for each relative age in months
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(ranging from 1 – 24 months) using the von Bertalanffy equations per specie (for the white shrimp:
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Aranceta-Garza et al. 2016; blue shrimp: Sáenz-Martínez and Lluch-Belda 1990; and brown
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shrimp: López-Martínez 2000), and assigning for each modal length class its corresponding sd
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estimated from the quadratic function equation; e) the construction of the age/length key was based
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on the normal distribution of each mean length and sd per species. This allowed to assign a
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probability that an individual of length L belongs to one or several ages.
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The age structure was obtained as follows:
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𝐿 𝑃
𝐸 (Eq. 2)
where:
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𝐿 is the transposed vector of the length frequencies;
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𝑃 is the age/length key matrix; and
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𝐸 is the age structure vector.
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2.3.1 Catch-per-unit of effort per fleet
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Catch-per-unit of effort (CPUE) was estimated for the inshore fleet as the catch in numbers per
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cast-net throw per month. The CPUE for the offshore fleet was estimated as catch in numbers per
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boat per month.
207
2.4 Catchability-at-age estimation
208
Catchability-at-age (𝑞 , ) was estimated following Arreguín-Sánchez (1996) and Arreguín-
209
Sánchez and Pitcher (1999), and used the computation algorithm by Martínez-Aguilar et al. (1999).
210
The method computes the catchability-at-length (𝑞 , ) based on the transition matrix (Shepherd
211
1987, Caswell 1989), as follows: 𝐴
,
,
𝑁
,
Eq. 3
re-
𝑁
212
pro of
204
213
where:
214
𝑘 and 𝑙 are successive length classes;
215
𝑁
216
𝐴 is the transition matrix, which depends on growth and mortality probabilities calculated by:
lP
is the number of individuals of length 𝑙 at time t; and
,
𝐴
217
𝐺
,
,
𝑆
Eq. 4
,
where:
219
𝐺
220
growth probabilities to each length class interval; and
221
𝑆
,
,
urn a
218
represents the elements of the growth matrix estimated following Shepard (1987) to assign
represents elements of the survival matrix (following Caswell 1989), which are defined by: ,
𝑒
Jo
𝑆
222
,
𝑒
,
Eq. 5
223
where:
224
𝑍 𝑘 is the instantaneous rate of total mortality for the 𝑘-length at time 𝑡;
225
𝑀 is the instantaneous rate of natural mortality, assumed constant for all length classes, and
226
estimated from Aranceta et al. (2016);
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227
𝑠
is the probability of gear selection for length 𝑘 (assumed to be 𝑠
228
and per fleet because of the absence of data); and
229
𝐸
230
trawlers per month.
231
From substituting Eq. 4 and 5 in Eq. 2 we obtain:
1 for all length classes
𝑁
232
𝐺
,
,
𝑒
,
pro of
is the fishing effort at time t given as cast-net throws per month for the inshore fleet and
𝑁
Eq. 6
,
233
Following Arreguín-Sánchez and Pitcher (1999), to solve Eq. 6, 𝑁
234
using the CPUE (𝑈 ,
235
biomass in the fishery. Then, since all the remaining variables are known, 𝑞
236
The 𝑞 , model assumes that catchability 1) is length dependant; 2) depends on fish behaviour; 3)
237
is density dependent; 4) the units of effort have static properties or have consistent fishing power
238
over time; 5) the fishing fleets present differences in fish-length/age catchability patterns implying
239
differences in vulnerability due to differences in fishing strategies, fishing areas, available
240
population structure and fish behaviour; 6) because the model (Eq.6) considered a constant growth,
241
constant natural mortality and no variation in effort, the main source of variability is the
242
survivorship (𝑆
243
(Arreguín-Sánchez 1996; Arreguín-Sánchez and Pitcher 1999).
244
Following the pattern of 𝑞 , with age, a logistic function represented as:
values were approached
,
can be estimated.
,
urn a
lP
re-
by the assumption that the CPUE is an acceptable proxy to the available
) related to the fishing mortality and consequently to the catchability-at-age
246
where:
Jo
𝑞,
245
247
,
𝑞𝑚𝑎𝑥 ,
1
𝑒𝑥𝑝
Eq. 7
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248
𝑙 is length class; 𝑡 is a unit of time, in our case month; 𝑞 , represents the catchability-at-length
249
per time; 𝑞𝑚𝑎𝑥 , represents the maximum 𝑞 , for each species, at time 𝑡; 𝑏 is
250
the change of catchability-at-length with change in length class; 𝑐 is a fitting parameter.
251
Global catchability pattern per species was estimated including all the 𝑞 , values per fishing
252
season in a single function. Once the pattern of catchability-at-length class was estimated with
253
equation 7, the catchability-at-age was computed according with the corresponding mid length
254
for each age.
255
Based on the observed data, this model was deemed appropriate as the assumption of catchability
256
increased with length until a certain length limit was achieved and no further increase was
257
observed. The function was empirically fitted per fleet and species to obtain a model describing
258
catchability-at-length; and the form of the function described the data and the species’ biology.
259
3 Results
260
Monthly estimates of fishing effort for inshore and offshore fleets are shown in Table 1 and Table
261
2, respectively. The CPUE per fleet and per species is shown in Figure 2, where higher values
262
tended to appear in September, declining afterwards for all but the brown shrimp. The maximum
263
CPUE for the brown shrimp was found in December.
264
The monthly averaged (𝑞 , ± sd) in the white shrimp for the inshore fleet was (7.44×10-07±
265
8.14×10-07). For the offshore fleet, the monthly average for white was (2.13×10-04 2.10×10-04); for
266
blue (2.11×10-04±1.01×10-04); and (1.41×10-04 9.73×10-05) for the brown shrimp. Each monthly
267
𝑞
268
the white shrimp (Figure 3A) showed the aggregation of migrating ages into the “tapos” overtime.
269
The offshore 𝑞
270
recruitment to the marine fishing grounds (ages 4-5 months) or the reproductive aggregations (<9
, representing
urn a
lP
re-
pro of
,
pattern presented high variability among all species (Figure 3). The inshore 𝑞
Jo
,
,
,
pattern for
patterns (Figure 3B-D) for the three species showed monthly increments in either
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271
months). Only the white shrimp presented 𝑞
272
species of the inshore lagoon in southern Sinaloa. The 𝑞
273
fishery (Figure 3B-D). Global 𝑞
,
patterns, involving all species, ages and fleets, is represented in
274
Figure 4. The white shrimp 𝑞
,
pattern showed increases with age until an asymptotic trend
275
towards older ages. On the other hand, the blue shrimp 𝑞
276
ages, which remained constant and further increased for older ages. Finally, the brown shrimp
277
𝑞
278
As shown in Figure 5, the increments in the monthly 𝑞
279
vulnerability. For the white shrimp in the inshore grounds, the high slope value in November could
280
be associated to the pre-adult migration (Figure 5A) and, for the three species in the offshore
281
grounds, the high slope values were associated to marine recruitment (i.e. first maturity ages) and
282
reproductive aggregations (Figure 5B-D).
283
4 Discussion
284
Based on the results obtained, we successfully demonstrate the catchability-at-age (𝑞
285
the sequential shrimp fishery for the 2014-2015 season in the Mexican Pacific. The 𝑞
286
varied in time and across ages per fleet and per species. The vulnerability of each species to the
287
fishery could be related with the recognized aggregations of individuals in response to their
288
population processes: recruitment, migration, reproduction.
289
This study successfully showed high fluctuations in the fleets 𝑞
290
responded to several variability factors. Shrimp population processes associated to age behaviour,
291
(e.g. recruitment, migration, and reproduction in García (1988)), were observed in the 𝑞
292
(as shown in Figure 3) showing vulnerability increases (Figure 5). This is due to individual
293
aggregation (i.e. density effects) and fishing gear efficiency (Arreguín-Sánchez 1996). These
for both fleets (Figure 3A,B) being the dominant values were higher for the offshore
pro of
,
,
appeared to be relatively high in early
appeared to have a gradual increase with age, but with a high uncertainty.
slope per species denoted the fishing
re-
,
lP
Jo
urn a
,
,
,
,
values for ,
patterns
values (Figures 3 and 4) which
,
patterns
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294
density effects in 𝑞 have been reported for other shrimp fisheries (Australian banana prawns,
295
Penaeus semisulcatus: Zhou et al. 2007), and in other sequential fisheries on other species such as
296
red grouper (López-Rocha et al. 2008) and pacific sardine (Martínez-Aguilar et al. 2009). Other
297
possible variation factors for 𝑞
298
habitat along ontogeny of species (Caddy 1975); changes of fishing power related to fishing gear
299
or operations between fleets (Arreguín-Sánchez 1996); responses to environment changes (Castro-
300
Aguirre and Lluch-Belda 2008, López-Martínez et al. 2008, Aragón Noriega et al. 2012) and
301
fishermen behaviour, where at the beginning of the fishing season the CPUE was concentrated in
302
the blue shrimp (Figure 2C) (i.e. bigger size, better profits), amongst many others.
303
The offshore fleet 𝑞
304
1.41×10-04 9.73×10-05 were in accordance with the magnitude of independent catchability values
305
(𝑞) estimated for the Mexican shrimp fishery in the Gulf of California (3.30×10-04 to 1.74×10-04,
306
Morales-Bojórquez et al. 2001, García-Juárez et al. 2009, Meraz-Sánchez et al. 2013) and even
307
with q values of other regions like Australian banana prawn fishery (6.15×10-04 to 1.09×10-04 in
308
Zhou et al. 2011). Of importance, these constant seasonal values cannot give any further
309
information about the resource vulnerability-at-age patterns, which may underestimate the fishing
310
mortality values.
311
Other studies showing inshore fleet q values were very scarce in Mexican shrimp fishery. This
312
study used several information sources from the fishery office, including field fisher’s logs, in order
313
to estimate robust inshore 𝑞
314
7.44×10-07 8.14×10-07. Other studies assessing the inshore fleet fishery in Oaxaca ( 1,600km
315
away from study site) do not explicitly present any q values methodology, however, they are
316
implicitly estimated by biomass models assuming constant values (Rivera-Velázquez et al. 2009,
values in the shrimp sequential fishery, are those associated to
pro of
,
re-
average values for the three shrimp species (2.13×10-04 2.10×10-04 to
Jo
urn a
lP
,
,
values (observed in Figures 3 and 4), with an average value of
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Cervantes-Hernández et al. 2012). Only one study assessing the white shrimp inshore fishery in
318
Chiapas (≈1,750km away from study site) presented q value of 6.3×10-04 (Ramos-Cruz 2013) using
319
similar fishing gear (i.e. cast nets). According to our findings, Ramos-Cruz (2013) q value was
320
three orders of magnitude larger than the values found for our inshore fleet and ranged with the
321
trawlers q values, which may suggest a possible overestimation. In this case, caution must be taken
322
when assessing sequential inshore fisheries using inflated q values because it will overestimate the
323
fishing mortality values for the inshore fleet and consequently, its management may cause a growth
324
overfishing in the shrimp fishery.
325
The global 𝑞
326
fleet associated to the migration ages (Figure 4A). This increment was also associated in the
327
offshore fleet with the first maturity ages and observing the highest values over the older ages
328
(Figure 4 A,B,C) probably because the reproductive aggregations. This pattern has been observed
329
in other fisheries with aggregating behaviour (Sardinops caeruleus, in the Gulf of California,
330
Martínez-Aguilar et al. 2009; Epinephelus morio, Campeche Banks, López-Rocha and Arreguín-
331
Sánchez 2008).
332
Particularly for the white shrimp, 𝑞
333
(Figure 4A). Most young shrimps are exposed to fishing gear at inshore water mostly from
334
September to November and is reflected by high values of catchability and vulnerability (Figure
335
5A) with a rapid decrease afterwards. Catchability was also found to increase rapidly at offshore
336
waters from November to December due to the migration to offshore waters (Figure 5B). Once
337
migration was completed, the catchability decreased at offshore waters following the stock
338
decrement.
log function (Figure 4) indicated an increment in the vulnerability for the inshore
Jo
urn a
lP
re-
,
pro of
317
,
values at inshore waters tended to increase as shrimps grow
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The blue shrimp showed a constant catchability for pre-adults increasing for older ages and over
340
time (Figure 4B and 5C). This pattern was found to be congruent with their biology and fishing
341
operations. At the beginning of the season (Figure 5C: October), most fishing occurs with blue
342
shrimp in shallow coastal waters as they reach higher market prices. Even when the CPUE
343
decreases over time, shrimps tend to move into deeper waters and aggregate for reproduction. This
344
allowed to reach a maximum catchability and vulnerability value prior to the end of fishery seasons
345
designated to prevent recruitment overfishing (Figure 5C: Jan-Feb).
346
The catchability behaviour for the brown shrimp appears to depend on both, the reproductive adult
347
aggregations (e.g. October, December and February in Figure 3D) and the recruitment to the fishery
348
(e.g. November, January, March in Figure 3D), which can be explained because it is an all-year-
349
round reproductive period in southern Sinaloa (Aragón-Noriega and Alcántara-Razo 2005). Even
350
when catchability-at-age is the most uncertain pattern, it suggests that catchability tends to increase
351
with age (Figure 4C), which is probably associated with reproductive aggregation ages. However,
352
changes in catchability tend to decrease with time along the fishing season (Figure 5D), which,
353
according to our assumption in equation 6, also coincides with the decrease of the stock availability,
354
probably due to the stock depletion at the end of the season. The proportionality between the stock
355
availability and CPUE does not imply linearity and could be reflecting a density-dependent
356
catchability or hyperstability, as demonstrated previously in the pacific sardine (Martínez-Aguilar
357
et al. 2009).
358
Following Caddy (1979), catchability relates available stock, or individuals removed, by a fishing
359
effort unit which, at the same time, depends of the stock distribution and behaviour. In this sense,
360
and regarding its management, further research is warranted. the next step of research, once
361
catchability is known, will be to relate the CPUE with the real stock abundance measures.
362
5 Conclusion
Jo
urn a
lP
re-
pro of
339
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The management efficiency of any fishery can be increased using fishing effort as a control variable
364
coupled with knowledge of catchability patterns. Estimated patterns of catchability-at-age over
365
time and across ages appear to offer an opportunity to evaluate potential success of management
366
for the three main shrimp species in the southern Gulf of California. Additionally, such patterns
367
provide specific information on how fishing could be applied in a sequential fishery. In the case of
368
the white shrimp, it can offer realistic fishing mortality estimates for an adequate management to
369
aid restoring the already deteriorated stocks. For blue and brown shrimp, catchability patterns can
370
offer more detailed information on fishing mortality related to reproductive aggregation and, in the
371
case of Mexico, help increase the confidence in defining seasonal fishing closures. Finally, even
372
when estimated catchability-at-age patterns can be taken as global patterns for each species, the
373
relative catchability values also depend on other factors affecting shrimp behaviour such as changes
374
in habitats, climate, and distribution of individuals. To improve management practices that
375
anticipate natural or induced changes, we strongly suggest reinforcing the monitoring programme
376
year to year in order to adapt management as required.
377
ACKNOWLEDGEMENTS
378
FAG thanks CONACyT, IPN-BEIFI and COFAA for the grants received. A Special thanks to Raul
379
Villaseñor (CONAPESCA), Jesús Ortiz (industrial fleet leader) and Miguel Rose (Mexican Shrimp
380
Paradise). FAS, GPD and PDM thank Instituto Politécnico Nacional support through EDI and
381
COFAA programs. Authors acknowledge the support through projects CONACYT (221705), SIP-
382
IPN (20172122, 20180929).
383
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Morales-Bojórquez, E., López-Martínez, J., Hernández-Vázquez, S. 2001. Dynamic catch-effort
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model for brown shrimp Farfantepenaeus californiensis (Holmes) from the Gulf of California,
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Mexico. Cienc. Mar. 27, 105-124.
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Muñoz-Rubí, H.A., Chávez-Herrera, D., Villegas-Hernández, F. 2012. Evaluación de las
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poblaciones de Litopenaeus vannamei, L. stylirostris y Farfantepenaeus californiensis en el
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sistema lagunar Huizache-Caimanero, Sinaloa, en 2011. SAGARPA, Mazatlán, 23 pp.
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Norma Oficial Mexicana-002-SAG/PESC-2013. Para ordenar el aprovechamiento de las especies
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de camarón en aguas de jurisdicción federal de los Estados Unidos Mexicanos:
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http://www.dof.gob.mx/nota_detalle_popup.php?codigo=5306294 Ramos-Cruz, S., Sánchez-Meraz, B., Carrasco-Ayuso, F., Cervantes-Hernández, P. 2006.
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Estimación de la tasa de mortalidad natural de Farfantepenaeus californiensis (Holmes, 1900)
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y Litopenaeus vannamei (Boone, 1931) en la zona costera del Golfo de Tehuantepec, México.
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Rev Biol Mar Oceanogr. 41(2), 221-229.
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Ramos-Cruz, S. 2013. Evaluación de la pesquería artesanal de camarón en el sistema lagunar La Pampita-Joya-Buenavista, Chiapas, México. Cien. Pesq. 21, 5-11. Rivera-Velázquez, G., Soto, L.A., Ugarte, I.H.S., Naranjo, E.J. 2009. Assessment of an artisanal
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shrimp fishery of Litopenaeus vannamei in a lagoon-estuarine system based on the concept of
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maximum sustainable yield. Rev. Biol. Mar. Oceanogr. 44, 635-646.
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Sáenz-Martínez, P.G., Lluch-Belda, D. 1990. Análisis de una temporada de pesca de camarón azul en alta mar. Secretaria de Pesca, México, 20 pp.
SAGARPA. 2018. ACUERDO por el que se da a conocer la actualización de la Carta Nacional Pesquera. DOF, México, 69 pp.
Seijo, J.C., Defeo, O., Salas, S. 1998. Fisheries bioeconomics: theory, modelling and management.
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FAO Fisheries Technical Paper. No. 368. Rome, FAO. 108p. Shepherd, J.G. 1987. Towards a method for short-term forecasting of catch rates based on length
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composition. In: Pauly D., Morgan G.R. (eds.), Length-based methods in fisheries research.
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ICLARM Conf. Proc, Manila, pp. 167-176.
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Velázquez-Abunader, I., Salas, S., Cabrera, M.A. 2013. Differential catchability by zone, fleet,
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and size: the case of the red octopus (Octopus maya) and common octopus (Octopus vulgaris)
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fishery in Yucatan, Mexico. J. Shellfish Res. 32, 845-854.
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Zhou, S., Dichmont, C., Burridge, C.Y., Venables, W.N., Toscas, P.J., Vance, D. 2007. Is catchability density-dependent for schooling prawns?. Fish. Res. 85, 23-36. Zhou, S., Punt, A.E., Deng, R., Bishop, J. 2011. Estimating multifleet catchability coefficients and
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natural mortality from fishery catch and effort data: comparison of Bayesian state–space and
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observation error models. Can. J. Fish. Aquat. Sci. 68, 1171-1181.
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TABLES
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Table 1. Inshore fishing effort and observed catch of white shrimp during the 2014-15 fishing
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season in southern Gulf of California. Sep a. Reported inshore fishing effort (total fishermen) b. Fisherman effective monthly fishing days c. Total throws per fisherman
25
25
25
150.96
67.14
73.56
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Dec
1,978,337
733,818
681,259
2,529
524
437
370
58,155
13,105
10,930
9,261
424.53
183.48
40.99
30.29
0.0073
0.0140
0.0038
0.0033
1.48E-04
9.30E-05
5.60E-05
4.4E-05
f. Estimated fleet effective monthly
h. Catch per fisherman (t day-1)b
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(t day-1)b
Nov
2,873,546
e. Estimated fishermen (day) b
i. Catch per cast net throw
Oct
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d. Total estimated monthly throws b
g. Reported monthly catch (t)a
23
49.41
(day)b
fishing days
4000
pro of
526 527
a
531
from local fishing offices and surveys in southern Sinaloa.
532 533
SAGARPA-CONAPESCA 2014 database; b Muñoz et al. (2012); observed data were obtained
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Table 2. Offshore fishing effort and observed catch of white shrimp (Litopenaeus vannamei);
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blue shrimp (L. stylirostris) and brown shrimp (Farfantepenaeus californiensis) during the 2014-
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15 fishing season in the southern Gulf of California. Observed satellite tracking Oct
Nov
Dec
189
95
140
Number of shrimp trawlers Effective fishing days per boat 17.69
21.02
27.25
White shrimp
17.6
22.19
27.81
Brown shrimp
17.71
19.75
Mean±sd
17.67±0.06 20.99±1.22
27.51
27.52±0.17
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Effective fishing days per fleet
Jan
Feb
Mar
165
203
135
22.61
31.35
21.28
23.72
30.84
24
44.1
31.58
20.95
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Blue shrimp
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30.14±10.42 31.26±0.37 22.08±1.54
Blue shrimp
3343
1996
3815
3731
6364
2873
White shrimp
3326
2108
3894
3914
6261
3240
Brown shrimp
3348
1876
3851
3777
6410
2828
3348
2108
3894
3914
6410
3240
582
195
274
92
178
104
69
24
25
35
63
12
437
340
890
348
909
299
1088
559
1189
475
1150
414
effective fishing days
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Observed catch (t) Blue shrimp White shrimp Total 538 539 540
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Brown shrimp
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Table 3. Catchability-at-age logistic function parameters for commercial shrimps in the 2014-15
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fishing season in the southern Gulf of California.
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White shrimp (Litopenaeus vannamei) a b c 7.4E-06 0.038 -7.420 3.9E-06 0.029 -5.790 1.6E-06 0.285 -28.913 8.1E-07 -0.140 18.877 White shrimp (L. vannamei) F(x) parameters Log (a) Log (b) Log (c) October -3.845 -0.054 13.562 -3.793 -0.108 25.240 November December -4.219 0.159 -21.968 January -4.744 -0.032 8.077 February -143.943 0.004 -4.313 1.00E-04 -0.093 18.706 March Fishery (Log) -8.046 -0.017 3.325 Blue shrimp (L. stylirostris) F(x) parameters a b c October 0.369 0.019 -11.036 November 3.00E-04 -0.040 7.326 December 4.00E-04 -0.013 3.104 January 5.00E-04 0.035 -7.153 1.00E-04 0.041 -7.042 February March 7.00E-05 -0.323 68.426 Fishery (Log) -3.73461 -0.118 27.849 Brown shrimp (Farfantepenaeus californiensis) F(x) parameters a b c October 2.35 E-04 0.0862 -14.089 November 3.54 E-04 -0.069 10.000 December 2.84 E-04 0.047 -6.127 January 2.48 E-04 0.024 -3.782 February 5.60 E-04 -0.200 29.793 March 1.20 E-04 -0.084 12.672 -3.95796 -0.049 12.103 Fishery (Log) *a is 𝑞𝑚𝑎𝑥 , ; 𝑏 is Δ𝑞 , ⁄Δ𝑙 ; 𝑐 is a fitting parameter.
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F(x) parameters September October November December
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Offshore fleet
Inshore fleet
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R 0.897 0.785 0.654 0.825 R 0.926 0.574 0.588 0.688 0.709 0.693 0.812 R 0.860 0.601 0.524 0.586 0.467 0.381 0.368 R 0.970 0.902 0.490 0.446 0.946 0.999 0.295
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FIGURES
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Figure 1 - Study regions for the shrimp fishery in southern Gulf of California.
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*Inshore fleet surveys applied in: Huizache; Chametla; Teacapán lagoon; Palmilla; and
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Teacapán marine area in Sinaloa.
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pro of
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Age (months)
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1
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re8
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January
4
4
4
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March
12
12
12
14
14
14
month for the inshore fleet (1); and CPUE of B) white shrimp (L. vannamei); C) blue shrimp (L. stylirostris) and D) brown shrimp
Figure 2 – Catch-per-unit-effort (CPUE) of A) white shrimp (Litopenaeus vannamei) as number of individuals per cast net throws per
12
0 10
0 8
1
1
6
2
2
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D) Brown shrimp
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B) White shrimp
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October
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2) Offshore fleet
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A) White shrimp
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CPUE (X104)
CPUE (X103)
1) Inshore fleet C September
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the offshore fleet.
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California. The season length was from September to December (2014) for inshore fleet and from October (2014) to March (2015) for
(Farfantepenaeus californiensis) as number of individuals per trawler per month for the offshore fleet (2) in southern Gulf of
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and from October (2014) to March (2015) for the offshore fleet.
for the offshore fleet (2) in southern Gulf of California. The season length was from September to December (2014) for inshore fleet
fleet (1); and of B) white shrimp (L. vannamei); C) blue shrimp (L. stylirostris) and D) brown shrimp (Farfantepenaeus californiensis)
Figure 3 – Catchability-at-age and log function estimation (dashed line) of A) white shrimp (Litopenaeus vannamei) for the inshore
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A) White Shrimp
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Inshore Offshore
-7.0
Global tendency
-9.0 0
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B) Blue shrimp
-3.5 -3.8 -4.1
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2 C) Brown shrimp
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Log q(a,t)
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Log q(a,t)
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Log q(a,t)
-3.0
4
6 8 Age (months)
Figure 4 - Catchability-at-age pattern for A) white shrimp (Litopenaeus vannamei); B) blue shrimp
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(L. stylirostris) and C) brown shrimp (Farfantepenaeus californiensis) in southern Gulf of California.
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A)
0.200 0.100 0.000 Sep
Oct
Nov
-0.100 -0.200
0.100 0.000 Sep
Oct
-0.100 -0.200 0.05 0.025 0 Sep -0.025
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Catchability-at-age slope pattern
Nov
Jan
Feb
Dec
Jan
Feb
Mar
B)
Mar
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Catchability-at-age slope pattern
0.200
Dec
pro of
Catchability-at-age slope pattern
0.300
Nov
Dec
C)
Jan
Feb
Mar
Catchability-at-age slope pattern
0.150
D)
0.050 -0.050
Sep
Oct
Nov
Dec
Jan
Feb
Mar
-0.150
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Figure 5 - Slope of catchability-at-age pattern (Table 3) showing the change of catchability pattern with time: A) white shrimp (Litopenaeus vannamei) – inshore fleet; B) white shrimp (L. vannamei) – offshore fleet; C) blue shrimp (L. stylirostris) – offshore fleet; D) brown shrimp (Farfantepenaues californiensis) – offshore fleet, during the 2014-15 season in southern Gulf of California.
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La Paz, Baja California Sur, Mexico, September 27th, 2019.
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Dr. Gunnar Lauenstein Regional Studies in Marine Science Editor
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Regarding the manuscript titled “Determination of catchability‐at‐age for the Mexican Pacific shrimp fishery in the southern Gulf of California”, authored by Aranceta‐Garza F., Arreguín‐Sánchez F., Seijo JC., Ponce‐Díaz G., Lluch‐Cota D., del Monte‐Luna P.; we declare that there is not any conflict of interest regarding use of data. Also, we declare that the described has not been published previously, that it is not under consideration for publication elsewhere, and that it was approved by all authors and tacitly by the responsible authorities of my institution
With no other thing to declare, I appreciate very much your kind attention
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Sincerely yours
Dr. Francisco Arreguín Sánchez