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"La evaluación de poblaciones de la almeja de sifón Panopea globosa en México se ha basado en estimaciones de densidad promedio. Este método no considera los rasgos biológicos de las especies, promoviendo una evaluación de datos pobres y un esquema de manejo pasivo, sin puntos de referencia biológicos para la captura y aprovechamiento del recurso. En este estudio, un modelo dinámico estructurado por tallas (MDET) fue desarrollado para analizar la dinámica de la población y cantidades relevantes para el manejo pesquero de P. globosa, incluyendo reclutamiento, selectividad, mortalidad por pesca, crecimiento individual, supervivencia, tasa de explotación, biomasa total y vulnerable a la longitud. Los cambios en la dinámica de la población fueron analizados mediante dos enfoques. Primero, cuatro matrices de crecimiento estocástico fueron integradas dentro de MDET (von Bertalanffy, Gompertz, Logístico y Schnute) asumiendo diferentes patrones de crecimiento y fue analizado su efecto sobre la dinámica de la población. Un criterio de información Akaike corregido fue usado para seleccionar el mejor rendimiento entre los cuatro MDETs. Segundo, la matriz con el mayor rendimiento fue usada para analizar el efecto de la pesca sobre la dinámica poblacional de 2010 a 2012 y de 2014 a 2016. Los resultados indicaron que el MDET asociado con la matriz de von Bertalanffy fue el mejor para describir la dinámica poblacional de P. globosa, proporcionando estimaciones conservadoras sobre la condición del stock. Por el contrario, la matriz logística mostró bajo rendimiento, exhibiendo las más altas estimaciones para todos los componentes de dinámica poblacional, tal como un incremento de 75.3% en el reclutamiento y 58.5% en la abundancia total con respecto a la matriz de con Bertalanffy. Adicionalmente, un efecto de sobrepesca fue identificado en la población de almeja de sifón; la tasa de explotación excedió los límites legales establecidos para la pesquería de 0.5% y 1%, incluso fueron capturados individuos menores a la talla mínima legal (130 mm de longitud de concha). De 2010 a 2012 se observó una disminución en la biomasa total (de 3,262 a 1,130 t) y el reclutamiento (representando una disminución del 86%). Posteriormente, de 2014 a 2016 se observó un incremento en el reclutamiento y biomasa total; sin embargo, este fue debido a la reubicación espacial de la mortalidad por pesca, promoviendo un mecanismo de agotamiento en serie en la pesquería." "Stock assessment of the geoduck clam Panopea globosa in Mexico has been based on average density estimates. This method do not consider the biological traits of the species, promoting a data-poor assessment and a passive management scheme without biological reference points for the harvest and conservation of the resource. In this study, a size-structured dynamic model (MDET) was developed to analyze the population dynamics and quantities relevant to fishery management of P. globosa, including recruitment, selectivity, fishing mortality, individual growth, survival, harvest rate, total and vulnerable biomass-at-length. The changes in the population dynamics were analyzed through two approaches. First, four stochastic growth matrices were integrated within MDET (von Bertalanffy, Gompertz, Logistic, and Schnute) assuming different growth patterns and their effect on the population dynamics was analyzed. A corrected Akaike information criterion was used to select the best performance among the four MDETs. Second, the matrix with the highest performance was used to analyze the effect of fishing on the population dynamics from 2010 to 2012 and 2014 to 2016. The results indicated that the MDET associated with the von Bertalanffy matrix was the best for describing the population dynamics of P. globosa, providing conservative estimates on the condition of the stock. Conversely, the Logistic matrix showed low performance, exhibiting the highest estimates for all the components of population dynamics, such as an increase of 75.3% in the recruitment and 58.5% in the total abundance with regard to the von Bertalanffy matrix. Additionally, an effect of overfishing was identified in the geoduck clam population; the harvest rate exceeded the legal limits established for the fishery of 0.5% and 1%, even the individuals smaller than the minimum legal size (130 mm) were harvested. Declines in the total biomass (from 3,262 to 1,130 t) and recruitment (representing an 86% decrease) were observed from 2010 to 2012. Subsequently, an increase occurred in recruitment and total biomass from 2014 to 2016; however, this was due to the spatial relocation of fishing mortality, promoting a serial depletion mechanism in the geoduck fishery."

Stock assessment of the geoduck clam Panopea globosa in Mexico has been based on data-poor without consideration of the biological traits of the species, promoting a passive management strategy without biological reference points for its harvest and conservation, which results in limited advice regarding the sustainability of the fishery. The stock assessment was supported on an integrated catch-at-size assessment model. The model described the population changes, including recruitment, selectivity, fishing mortality, individual growth patterns and survival over time, providing management quantities for the geoduck clam fishery, such as biomass-at-length (total and vulnerable) and harvest rate-at-length. The results indicated overfishing of the geoduck clam population; the harvest rate exceeded the management tactics established for this fishery, even the individuals smaller than the minimum legal size (130 mm) were harvested. Thus, declines in the total biomass (from 3,262 to 1,130 t) and recruitment (representing an 86% decrease) were observed from 2010 to 2012. Although the results showed a recovery trend in recruitment and total biomass from 2014 to 2016, this trend may have been due to the spatial relocation of fishing mortality.

Growth variability has been a common feature within different Panopea species, affecting the accurate estimation of growth parameters and their theoretical trajectories. Recently, the interest in solving this problem has increased; however, the methods used for individual growth modeling of Panopea spp. have not been effective in identifying the variability within the shell length-at-age composition. In the current study, a novel approach is proposed to analyze the effect of shell length-at-age variability on the individual growth and growth parameters of Panopea globosa. The shell length-at-age data were fitted to six candidate growth models: von Bertalanffy, Gompertz, Johnson, Logistic, Generalized von Bertalanffy growth model (GVBGM), and Richards using a negative log-likelihood function. The variance for each age observed () in the population was estimated for each growth model. The best candidate growth model was selected based on corrected Akaike information criterion (AICc). The results in...

In size-based stock assessment models, the stochastic growth of individuals is expressed through a transition matrix representing the growth variability as probability of shift from one length class to another during a time period. This process is important because it describes the changes in population size structure brought about by the increase in length or weight of organisms over time. In this study, four stochastic growth matrices were developed within an integrated catch-at-length assessment model (ICLAM), and the changes in the population dynamics and quantities relevant to fishery management of Panopea globosa were analyzed. The growth increments were estimated through von Bertalanffy, Gompertz, Logistic, and Schnute models using a gamma probabilistic density function. A corrected Akaike information criterion was used to select the best performance among the four ICLAMs. The ICLAM associated with the von Bertalanffy matrix was the best for describing the catch-at-length data, providing conservative estimates on the condition of the stock; while the ICLAM for the Logistic matrix showed low performance, exhibiting the highest estimates for all the components of population dynamics, such as an increase of 75.3% in the recruitment and 58.5% in the total abundance with regard to the von Bertalanffy matrix. These differences emphasize the importance of determining a suitable stochastic growth matrix because it has serious implications in biasing stock assessments, resulting in inadequate management strategies.

In this study, a length-structured population model was implemented to describe changes in the abundance of Panopea globosa over time, given parameters for growth and natural mortality rate. The following modules described population dynamics: stochastic individual model growth, survival, selectivity, recruitment, and estimates of initial numbers. In addition, the harvest rate, total biomass, and vulnerable biomass (VB) were calculated to advise management quantities. Spatial serial depletion patterns were detected for P. globosa and evident from the expansion of the fishing grounds over time. These patterns of geographic expansion are common in developing fisheries and are a problem for stock assessment. The densest patches available are usually harvested or even depleted, with fishers switching to new beds and potentially rotating back over time. If the changes in the harvestable area are ignored, the increases in VB and recruitment may mask the population dynamics of several beds, including those that are depleted and have low yield.

La variabilidad individual en el crecimiento ha sido una característica común en diferentes especies del género Panopea, si este aspecto no es considerado en el análisis de crecimiento puede conducir a sobreestimaciones o subestimaciones de los parámetros y trayectorias teóricas. Sin embargo, los métodos usados tradicionalmente para modelar el crecimiento individual no han sido efectivos en identificar la variabilidad dentro de la composición de longitud de concha a la edad. Bajo este contexto, en estudios de edad y crecimiento es importante analizar dos hipótesis: si la variabilidad en la longitud de concha a la edad disminuye con el tiempo o la edad el fenómeno es conocido como crecimiento compensatorio; por el contrario, si la variabilidad incrementa con la edad, se denomina crecimiento depensatorio. En el presente estudio, un nuevo enfoque para analizar la variabilidad fenotípica individual en el crecimiento de Panopea globosa fue desarrollado, suponiendo que un efecto depensatorio influye sobre la población de Bahía Magdalena. El análisis incorporó datos de distribución de frecuencias de longitud de estadios tempranos y datos de longitud de concha a la edad de individuos adultos, mediante una función negativa de verosimilitud conjunta. Ambos tipos de datos fueron ajustados a seis modelos de crecimiento candidatos: von Bertalanffy, Gompertz, Johnson, Logístico, generalizado de von Bertalanffy y Richards, los cuales incluyeron una estimación de varianza para cada edad observada en la población. El mejor modelo de crecimiento candidato fue seleccionado usando una corrección del criterio de información Akaike (AICc) para muestras pequeñas. La modelación de crecimiento incorporando dos tipos de datos mostró mejores estimaciones del parámetro t0 y mayor exactitud en el ajuste de las trayectorias de crecimiento al origen (edad 0) en comparación con los métodos convencionales. Los modelos de crecimiento candidatos incluyendo varianza a la edad evidenciaron un patrón de crecimiento depensatorio, sus trayectorias fueron similares, con excepción del modelo de von Bertalanffy que exhibió una mayor variabilidad, demostrando no ser el más adecuado para representar a la población de Bahía Magdalena. El AICc indicó que el modelo de crecimiento de Johnson fue el más adecuado para describir ambos tipos de datos. Individual growth variability has been a common feature within different Panopea species; if this aspect is not incorporate in the growth analysis it can lead to overestimates and underestimates of the parameters and theoretical trajectories. However, the methods used traditionally to modeling the individual growth have not been effective for identified the variability within of the shell length at age composition. Thus, for age and growth studies, is important analyze two hypotheses: if the length-at-age variability decreases with time or age the phenomena is known as growth compensation, in contrast if length-at-age variability increases with age it is called growth depensation. In this study, a new approach to analyze the individual phenotypic variability in growth of Panopea globosa was development, assuming that a depensation effect influeces in the population of Bahia Magdalena. The analysis incorporated shell length frequency distribution of early stages and shell length-at-age for adult individuals data, through a joint negative log likelihood function. Both data sets were fitted to six candidate growth models: von Bertalanffy, Gompertz, Johnson, Logistic, Generalize von Bertalanffy and Richards, they incorporated an estimation of variance for each age observed in the population. The best candidate growth model was selected using a corrected Akaike information criterion (AICc) for small samples. Growth modeling incorporating two data sets showed better estimates of t0 parameter and higher accuracy for fit the growth trajectories to origin (age zero) in contrast to conventional methods. Candidate growth models including variance-at-age, showed a growth depensation pattern, their trajectories were similar except von Bertalanffy growth model that exhibited greater variability, showing not be the most suitable to represent the population from Bahia Magdalena. The AICc indicated that the Johnson growth model was the most suitable to describe both data set.