Effects of biological and environmental factors on the variability of Paralonchurus brasiliensis (Sciaenidae) density: An GAMLSS application

Costa, EudrianoF.S.; Teixeira, Gustavo Monteiro; Freire, Fúlvio Aurélio de Morais; Dias, June Ferraz; Fransozo, Adílson

doi:10.1016/j.seares.2022.102203

Cited by 3 publications

(3 citation statements)

References 46 publications

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“…According to (Hong et al, 2023), the dynamics of marine waters will cause a shift in fish abundance over a certain period in a water area which has an impact on the state of a fishery. Fish tend to be located or concentrated in environmental conditions according to activity, where fish environmental factors are related to biological and physical factors (Costa et al, 2022). The peak production of flying fish eggs in the east season and transition season II in the waters of the Kei Islands shows that there is a positive response of flying fish to the characteristics of seawater conditions, thereby encouraging flying fish to carry out optimal spawning.…”

Section: The Relationship Between Sst and Chlorophyll-a With The Dist...mentioning

confidence: 99%

Analysis of Sea Surface Temperature and Chlorophyll-A and Its Relationship with Catch Results Flying Fish Eggs in the Waters of the Kei Islands

Retraubun,

Tubalawony,

Masrikat

et al. 2023

jppipa, pendidikan ipa, fisika, biologi, kimia

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The Kei Islands water area is quite productive in fisheries management. Environmental characteristics and oceanographic factors in a body of water will determine the potential of fisheries resources in a water body, and influence fish movement patterns and the formation of fishing areas for flying fish eggs. This research aims to examine the distribution of sea surface temperature and chlorophyll-a concentrations and analyze the relationship between sea surface temperature and chlorophyll-a concentrations with catches of flying fish eggs. The research focused on the waters of the Kei Islands, Southeast Maluku, which is an area for catching flying fish eggs. The research data was studied in the period December 2014 – November 2017. SPL and Chlorophyll-a data were downloaded from Citra MODIS-Aqua, while data on flying fish egg production was obtained from PPN Tual. The research results show that the monthly average SST distribution is between 25.03-30.42ºC, and the monthly average of chlorophyll-a varies quite widely with a range of 0.05-3.09 mg/m3. The number of flying fish egg production fluctuates every year with a production range of 36.28-81.905 kg. The peak of catching flying fish eggs occurs in June-September (eastern season and transition season II). The results of the analysis show that the correlation between SST and chlorophyll-a variables has a very dominant influence on the abundance of flying fish eggs.

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Section: The Relationship Between Sst and Chlorophyll-a With The Dist...mentioning

confidence: 99%

Analysis of Sea Surface Temperature and Chlorophyll-A and Its Relationship with Catch Results Flying Fish Eggs in the Waters of the Kei Islands

Retraubun,

Tubalawony,

Masrikat

et al. 2023

jppipa, pendidikan ipa, fisika, biologi, kimia

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“…The study also demonstrated that using physical parameters (such as rainfall) as covariates to model the distribution's parameters yielded more reliable results than solely relying on time as a covariate. Furthermore, GAMLSSs have been employed to study the impacts of fires in Portugal [12] and to investigate the variability or changes in fish species due to biological or environmental factors [13,14].…”

Section: Introductionmentioning

confidence: 99%

Modelling and Clustering Sea Conditions: Bivariate FiniteMixtures of Generalized Additive Models for Location, Shape, and Scale Applied to the Analysis of Meteorological Tides and Wave Heights

Ricciotti,

Picone,

Pollice

et al. 2024

JMSE

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Modelling sea conditions is a complex task that requires a comprehensive analysis, considering various influencing factors. Observed and unobserved factors jointly play a role in the definition of sea conditions. Here, we consider finite mixtures of generalized linear additive models for location scale, and shape (GAMLSSs) to capture the effects of both environmental variables and omitted variables, whose effects are summarized using latent variables. The GAMLSS approach is flexible enough to allow for different data features such as non-normality, skewness, heavy tails, etc., and for the definition of a regression model not only for the expected values of the observed process but also for all the other distribution parameters, e.g., the variance. We collected data on multiple sea-related and environmental variables in Ancona (Italy) from two Italian networks: the Sea Level Measurement Network (Rete Mareografica Nazionale, RMN) and the Sea Waves Measurement Network (Rete Ondametrica Nazionale, RON). Our main outcomes were the meteorological tides (often also referred to as “residuals”) and the significant wave height. Atmospheric pressure and wind speed were considered as main drivers of the sea conditions, as well as the fetch associated with wind direction, linking these variables to the outcomes through the definition of multiple linear predictors in a regression framework. Our results confirm the importance of accounting for environmental variables and reveal that their effect is heterogeneous, where heterogeneity is modelled by three distinct mixture components, each capturing different sea conditions. These findings contribute to a deeper understanding of sea state dynamics and provide evidence of a clustering structure characterizing different sea conditions.

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“…Fish populations can be distributed over extensive geographical areas characterized by distinctive environmental characteristics (e.g., temperature, salinity, depth, habitat and currents), which together with the challenges related to food availability and predators can exert influence over significant demographic aspects, thereby affecting the dynamics of the populations including reproductive patterns, fecundity and lifespan [1][2][3]. In addition, other factors, such as fishing pressure, anthropic pollution, habitat destruction and climate change, can also affect the abundance and distribution of fish species and consequently fish stocks dynamics [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Chelidonichthys lucerna (Linnaeus, 1758) Population Structure in the Northeast Atlantic Inferred from Landmark-Based Body Morphometry

Ferreira,

Schroeder,

Mugerza

et al. 2023

Biology

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The study of geometric morphometrics among stocks has proven to be a valuable tool in delineating fish spatial distributions and discriminating distinct population units. Variations in fish body morphology can be linked to genetic factors or to phenotypic adaptability in response to environmental variables. The tub gurnard (Chelidonichthys lucerna) is a demersal species that usually lives in the bottom of the continental shelf, being widely distributed along the northeast Atlantic, Mediterranean and Black seas. Worldwide interest in the species has increased since 2006, when ICES recognized its potential for commercial exploitation. However, despite its broad geographic occurrence, to date, research on C. lucerna population structure at large spatial scales is still lacking. In this paper, body geometric morphometrics, using a landmark-based truss network, was applied in order to discriminate C. lucerna populations caught in three different fishery grounds areas along the northeast Atlantic: Conwy Bay (United Kingdom), Biscay Bay (Spain) and Matosinhos (Portugal). The results obtained in this study revealed a high overall relocation success (95%) of samples to their original locations, thus demonstrating the existence of significant regional differences and indicating that we are dealing with different fish population units. Moreover, the data revealed a partial overlap between individuals from Spain and United Kingdom, suggesting that in geographically distant areas these populations may inhabit similar environments. However, to corroborate these findings, future works using a holistic approach with alternative and complimentary stock assessment tools (e.g., genetic and phenotypic natural tags) are highly recommended.

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Effects of biological and environmental factors on the variability of Paralonchurus brasiliensis (Sciaenidae) density: An GAMLSS application

Cited by 3 publications

References 46 publications

Analysis of Sea Surface Temperature and Chlorophyll-A and Its Relationship with Catch Results Flying Fish Eggs in the Waters of the Kei Islands

Analysis of Sea Surface Temperature and Chlorophyll-A and Its Relationship with Catch Results Flying Fish Eggs in the Waters of the Kei Islands

Modelling and Clustering Sea Conditions: Bivariate FiniteMixtures of Generalized Additive Models for Location, Shape, and Scale Applied to the Analysis of Meteorological Tides and Wave Heights

Chelidonichthys lucerna (Linnaeus, 1758) Population Structure in the Northeast Atlantic Inferred from Landmark-Based Body Morphometry

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