Next Article in Journal
Optimizing AUV Navigation Using Factor Graphs with Side-Scan Sonar Integration
Previous Article in Journal
Wave Height and Period Estimation from X-Band Marine Radar Images Using Convolutional Neural Network
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JMSE
Volume 12
Issue 2
10.3390/jmse12020312
jmse-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Biometry, Growth, and Recruitment Pattern of a Commercially Important Nereid polychaete, Namalycastis fauveli, from the East Coast of Bangladesh

by
Md. Jahangir Sarker
1,*,
Pallab Kumer Sarker
2,
Md. Ariful Islam
3,
Nazmun Naher Rima
1,
Thadickal Viswanathan Joydas
4,
Nahid Sultana
1,
Md. Monirul Islam
5,
Md. Yeamin Hossain
6 and
Mohammad Belal Hossain
1,7,*
1
Department of Fisheries and Marine Science, Noakhali Science and Technology University, Noakhali 3814, Bangladesh
2
Environmental Studies Department, University of California, Santacruz, CA 94720, USA
3
Department of Biology, University of Louisiana at Lafayette, Lafayette, LA 70504, USA
4
Center for Environment and Marine Studies, King Fahd University of Petroleum & Minerals, Dhahran 31261, Dammam, Saudi Arabia
5
National Agriculture Technology Program, Bangladesh Agricultural Research Council, Dhaka 1215, Bangladesh
6
Department of Fisheries, Faculty of Fisheries, University of Rajshahi, Rajshahi 6205, Bangladesh
7
School of engineering and Built Environment, Griffith University, Nathan, QLD 4111, Australia
*
Authors to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2024, 12(2), 312; https://doi.org/10.3390/jmse12020312
Submission received: 23 November 2023 / Revised: 27 January 2024 / Accepted: 5 February 2024 / Published: 10 February 2024
(This article belongs to the Section Marine Biology)
Browse Figures
Versions Notes

Abstract

:
Certain benthic polychaetes, such as species within the genus Namalycastis, are employed in the diet of gravid shrimps in aquaculture due to their amino acids and highly unsaturated fatty acid content, enhancing the quality of gravid shrimp. Despite its importance in the rapidly developing shrimp culture industry, the population parameters of this economically valuable species are unknown. Therefore, the present study examines the population parameters of Namalycastis fauveli to assess its occurrence, growth, recruitment, exploitation level, and stock status in Bangladesh. Monthly samplings of N. fauveli and environmental variables were collected from five sites of the Cox’s Bazar coast using a square-shaped mud corer with a 0.093 m2 (or 1.0 ft2) mouth opening from August 2020 to July 2021 to measure or estimate. Within the 8.0–30.0 cm depth range of the intertidal zone, polychaete samples were collected from the sediment. The results showed negative allometric growth (b < 3), but there was a significant L–W relationship (p < 0.05, r2 = 0.43 to 0.94). The estimated L∝, K, and ϕ were 22.05 cm, 0.99 year−1, and 2.69, respectively, while total mortality (Z) was 4.56 year−1. It was calculated that the fishing mortality and capture probability proportionally increased with the total length at a certain age. Recruitment mostly occurred in October and March, and temperature had a greater impact than salinity. The evaluated exploitation level (E = 0.57) indicated that the stock was overexploited. Thus, the above results provide some valuable information for shrimp farmers and stakeholders, as well as for policymakers in the move towards restoration, species conservation, and efficient management of N. fauveli natural stocks.

1. Introduction

Polychaetes play a crucial role in estuarine and marine ecosystems by serving as a food source for higher-trophic-level marine animals such as shrimp, fish, birds, crabs, and mammals [1,2,3]. Beyond their ecological significance, certain polychaete species have gained recognition for their potential use in aquaculture as feed ingredients. This is attributed to their outstanding nutritional content, which is particularly rich in highly unsaturated fatty acids and amino acids [4,5]. These worms are commonly employed as food for brood stock shrimp, contributing to the enhancement of the quality of gamete cells in gravid or brood shrimps [6,7]. Whether supplied in a fresh state or as pellets, polychaetes have been shown to promote the growth and survival of shrimp in aquaculture settings. Moreover, they are utilized as effective fishing bait [8,9].
Namalycastis fauveli belong to Nereididaeis, a dominant benthic polychaete species in the coastal area of Bangladesh, especially on the southeastern coast. It is typical of marine, estuarine, and supralittoral (splash zone) coastal environments [10,11,12,13]. The coastal people of the southeastern region, Cox’s Bazar, exploit wild N. fauveli as fishing bait and as feed for gravid shrimp (Penaeus monodon) or brood shrimp, i.e., female shrimps carrying eggs. Currently, >53 shrimp hatcheries produce commercial P. monodon post-larvae (PL) in the Cox’s Bazar region [14]. Most hatcheries rely on N. fauveli wild stock to feed the brood stock shrimp since there are no hatcheries that commercially produce polychaetes in Bangladesh (personal observation). Despite the ecological and economic significance of this species, the existing literature lacks details on population dynamics parameters, such as growth, recruitment patterns, mortality, and exploitation (E) for N. fauveli. A comprehensive understanding of these aspects, including exploitation levels, is crucial in ensuring the effective management and sustainable harvesting of N. fauveli. The abundance and diversity of polychaetes in coastal habitats widely depend on their species composition [15,16,17], the physicochemical parameters of the habitat, the sediment characteristics [15], and hydrographic factors [16]. The excess nutrient load and the alteration of sediment properties may cause short- or long-term shifts in polychaete abundance and diversity [17].
Various methods exist for assessing the population dynamics and levels of exploitation of a stock. However, among the approaches, the FAO-ICLARM Stock Assessment Tools (FiSAT) have been the most widely applied for evaluating the population characteristics of polychaetes; these tools require length–frequency data [18,19,20,21,22]. Studies showed that size-based assessments might quickly reveal any community structure and function [23,24,25]. The length–weight (L–W) data of polychaetes worms can be used to estimate biomass, population density, growth, and evolution [26]. Moreover, this fundamental model determines secondary productivity and trophic potentiality [27]. The L–W relationship is ascertained using the following methods: the ash-free dry weight of recently captured polychaetes, the direct measurement of worm weight, and L–W regression data obtained by weighing all the preserved (through mediums such as formalin or ethanol) worms. [28]. Because of their accessibility and computerized methods, researchers commonly employ simple L–W regression assessments to estimate the linear dimensions of polychaetes [29].
The relationship between shrimp culture and polychaetes in terms of food and feeding highlights the interdependence of aquaculture practices and the diverse marine life that plays a crucial role in their success. Therefore, use of Nereid polychaete in shrimp diet can reduce the cost of feed and enhance the quality of shrimp product and sustainability. To date, no studies have been conducted on the population parameters and stock of Nereid polychaete, N. fauveli from the east coast of Bangladesh. Thus, this study is the first to examine the biometric measurements, growth, and recruitment of N. fauveli (Nereididae, Polychaeta) on the east coast of Bangladesh. The findings helped us answering the following questions: (i) What are the biometric measurements of N. fauveli (Nereididae, Polychaeta) on the east coast of Bangladesh? (ii) How does the growth pattern of N. fauveli vary in the studied area on the east coast of Bangladesh? (iii) What insights can be gained into the recruitment dynamics of N. fauveli in the context of the east coast of Bangladesh? (iv) How does the biometric variability of N. fauveli contribute to our understanding of its population characteristics in the specific geographic region? The results presented here can be viewed as an invitation for further research on the biological traits and composition of this species in the future, aiming to enable its large-scale production for aquaculture.

2. Materials and Methods

2.1. Study Area

Polychaetes were collected randomly from five sampling stations situated in the Bakkahli River and Maheshkahli Channel within the Cox’s Bazar district (Figure 1). The Bakkhali River is a major transitional route for Maheskhali channel. The sediments of this River (Site 1 and 2) reach a depth of 90 cm (Figure 1). The Charpara site (S 3) is positioned near the mouth of the Bay of Bengal, featuring silt–sand and silt–clay sediments with depths ranging from 7 to 20 cm. Sites 4 and 5 were chosen within the mangrove canal of the Maheshkahli channel, characterized by sediment depths ranging from 45 to 92 cm (Figure 1). The Bakkhali estuary serves as a crucial economic zone in the Cox’s Bazar district, featuring a seaport and playing a significant role in the local fishery. At its broadest section, the estuary spans approximately 0.5 km in width and maintains a depth exceeding 10 m, exhibiting semi-diurnal tide patterns [14]. This estuary area is distinguished by a large intertidal mudflat (2.0–10.0 m width) connected to the Bay of Bengal, with a spring tide amplitude of 3.0 m. Furthermore, Maheshkhali Island is surrounded by numerous mangrove channels incorporating the Bakkhali estuary. The intertidal regions host diverse mangrove vegetation, including species such as Avicennia alba, A. marina, and Acanthus ilicifolius. Additionally, macroalgae like Ulva intestinalis, U. lactuca, Gracilaria spp., cord grass (Porteresia sp.), and seagrass (Halophila beccarii) contribute to the ecological richness of these areas [30]. The mean yearly temperature and rainfall were 25.6 °C and 3770 mm, respectively, for the study year [31]. The climate is classified as Am (tropical climate) by the Koppen–Geiger system [31]. Then, we selected five identical stations from the same region. Thus, we did not consider the station-wise variation of the species, although stations differ slightly in sediment quality and depth.

2.2. Polychaetes Sample Collection and Identification

All the sampling stations in this study remained within <10.0 km with nearly a similar abiotic feature. Thus, the sampling was performed monthly during low tide from August 2020 to July 2021 using a square-shaped mud corer with a 0.093 m2 (or 1.0 ft2) mouth opening from the selected stations. In each case, 3 replicate samples were collected. Sediment samples were collected from depths of 8.0–30.0 cm, depending on where the intertidal zone was located (typically middle to lower middle). Sediment samples underwent sieving with a 0.5 mm mesh size, and the collected polychaete specimens were carefully separated and placed in a pre-prepared bucket (with a 3.0 cm sand bed and natural seawater) Monthly water temperature and salinity data were collected using a multiparameter sonde (HANNA, model: HI9829, Cluj, Romania). The collected polychaete samples were transported to the Cox’s Bazar Marine Research Station, where they were acclimated for 24 h to facilitate the emptying of their digestive tracts. Subsequently, the samples underwent thorough washing with fresh water, and a subset of the specimens was preserved in 70.0% ethanol for later examination. [32]. Then, the specimens were counted and measured. Only complete specimens were considered for the L–W data. Throughout the study duration, a total of 2094 polychaete specimens were gathered, and measurements for length (L) and width (W) were conducted on 1300 of these specimens (n). The worm is known to exhibit epitoky as part of its reproductive strategy. During length measurement, we could not include them in that stage of the life cycle of N. fauveli. A simple centimeter (cm) scale and a digital precision weighing scale (Model: PS. P3.310, P-Scale, Taiwan, China) were used to take L–W data of the individuals. Measurements of length were taken on the dorsal view of specimens, extending from the prostomium to the posterior end of the worm, with the anal cirri excluded. The specimens were dried for 1 min on absorbent paper before being weighed on a precision balance to obtain the individual wet weight (WW). The precision level was to the nearest milligram (0.001 g). The specimens were identified as N. fauveli in collaboration with Laboratório de Biodiversidade de Annelida (LaBiAnne), Departamento de Invertebrados, Universidade Federal do Rio de Janeiro (UFRJ), Brasil, based on the morphological features and taxonomic keys provided in [11,13,33,34].

2.3. Estimation of Population Parameters

Length, weight, growth, recruitment, mortality, and exploitation rate were estimated using the pooled data and established models (Equations (1)–(6)). Data were pooled because of the interconnectedness among site populations resulting from the dispersal of early planktonic stages. In its early life, this polychaete undergoes the epitoky stage, which can have a profound impact on the metapopulation structure within the region. The epitoky stage, characterized by the transformation of certain organs for reproduction, facilitates increased reproductive success and dispersal, influencing connectivity and genetic diversity among local populations. This adaptive strategy may enhance the species’ ability to colonize new habitats, respond to environmental changes, and maintain a dynamic metapopulation structure within the defined region. Again, pooling the data from the samples collected across the sites was performed to enhance the robustness and representativeness of the findings. This approach allows for a more generalized and ecologically relevant perspective, enabling researchers to draw more reliable conclusions. Additionally, pooling data from multiple locations facilitates the identification of commonalities and differences, providing a basis for comprehensive comparisons and contributing to a more holistic understanding of the studied polychaete communities.
For determining L–W relationship, the following equation was applied for polychaetes [29,32]:
W = aLb
where W = body weight in g of N. fauveli, a = intercept, b = slope, and L = total length of N. fauveli in cm.
If b > 3, then positive allometric growth is indicated; b = 3 denotes isometric growth, which means a perfect cubic relationship between length and mass. Moreover, b < 3 indicates negative allometric growth of N. fauveli.
The recorded data were analyzed using the FiSAT-II (FAO-ICLARM Stock Assessment Tools) following the revised version explained by Gayanilo et al. [30]. The asymptotic total length (L∝) and growth coefficient (K) of the von Bertalanffy equation for growth, considering the L of an N. individual, was estimated by ELEFAN-I (Electronic Length Frequency Analysis), implemented in the FiSAT-II software (v.1.2). The L∝ and K parameters were estimated using the following Formula (3):
Lt = L∝ (1 − e−K(t−t0))
where t denotes the age of the N. fauveli (year), L is the mean total length at age t (cm), t0 is the hypothetical age when L was zero (egg development before hatching), and K represents a growth coefficient (year–1).
The growth performance index (ϕ) of N. fauveli was estimated from the following Equation (4) [35] using the K and L∝ values:
ϕ′ = log K + 2 log L∝
The Beverton [36] length-converted catch curve method was applied to calculate the total mortality (Z) using the average annual habitat temperature, 28.58 °C, measured during the sampling period.
Natural mortality (M) was calculated by applying the empirical relationship of Pauly as follows [37]:
log10 M = −0.0066 − 0.279 log10 L∞ + 0.6543 log10 K + 0.4634 log10 T
where L∝ = asymptotic length; K = growth coefficient; T = 28.58 °C (average annual temperature of the habitat). Once Z and M were estimated, fishing mortality (F) was obtained using Equation (6), as follows:
F = Z − M
The exploitation level (E) was determined by Equation (6), developed by Gulland, as follows [38]:
E = F/Z
The recruitment pattern was estimated by the backward-projection method on the L axis of a L-frequency dataset, as explained in the FiSAT-II. The “probability of capture” routine was applied to calculate the possibility of N.s fauveli capture, and the FiSAT-II analyzer was applied to estimate the approximate L structured virtual population.

2.4. Statistical Analysis

The revised version of FAO-ICLARM Stock Assessment Tools II (FiSAT II) [30] was applied for the population dynamics (length, weight, growth, recruitment, mortality, and exploitation rate) of N. fauveli. In addition, several regression models were created using Microsoft Excel (version 2016).

3. Results

3.1. Length–Weight (L–W) Relationship of N. fauveli

The length–weight relationship of N. fauveli, including coefficients of determination (r2), regression coefficients/slopes (b), standard errors (SE), and other relevant parameters, is presented in Table 1. The length of individuals ranged from 4.3 to 22.05 cm and weight ranged from 0.100 to 1.980 g. A highly significant (p < 0.001) length–weight relationship was observed for N. fauveli across the annual samples from August 2020 to July 2021 (n = 1300, r2 = 0.73). However, the estimated regression coefficient (b) for N. fauveli was less than 3, indicating negative allometric growth (t-test value = 9.78). The highest b value, measured at 2.12, occurred in March (n = 104), while the lowest b value was 1.18 in June (n = 129). The linear (l), power (pw), and polynomial (p) models exhibited the highest r2 = 0.94 in April 2021 (n = 104), whereas no correlations were found in logarithmic (log) (r2 = 0.12), linear (l) (r2 = 0.19), power (pw) (r2 = 0.20), or exponential (e) (r2 = 0.37) models. A moderate correlation was observed in the polynomial (p) model (r2 = 0.59) in June 2021 (Table 1). Furthermore, the curvilinear polynomial and exponential models demonstrated a better fit compared to others. The estimated intercepts (a) in this study are >0, indicating that individuals hatch at their actual size, while an intercept ≤ 0 is biologically meaningless [32]. The estimated b value remained <3, generally indicating a negative allometric growth of N. fauveli. The estimated average b = 1.65 in this study of N. fauveli closely approximates 2, suggesting a more two-dimensional matrix of the species, with no significant changes in height.

3.2. Population Dynamics of N. fauveli

3.2.1. Growth Parameters

The estimated asymptotic length (L∞) of the von Bertalanffy growth function (VBGF) was 22.05 cm, and the growth coefficient (K) was 0.99 year−1 for N. fauveli. The growth curve derived from these parameters is illustrated over the restructured length distributions in Figure 2.
The best estimated value of K and growth performance index (ϕ) were 0.99 year−1 and 2.69, respectively (Figure 3). The growth parameter (L∝) value of 22.05 cm indicates that N. fauveli can grow up to 22.05 cm unless any fishing mortality occurs. Five cohorts or size groups in the N. fauveli population have been observed through the indicator of five growth curves (Figure 2).

3.2.2. Mortality and Exploitation of the Species

Figure 4 represents the catch curve utilized in the estimation of total mortality (Z) and exploitation rate (E). The shaded circles were employed to compute Z using the least square linear regression, while the empty circles depict points that are not yet fully recruited. Length converted catch curve analysis produced total mortality estimated value for N. fauveli was Z = 4.56 year−1 (Figure 4). The estimated natural mortality (M) and fishing mortality (F) were 1.96 year−1 and 2.60 year−1, respectively. According to Gulland [39], when the F and M are equal, the yield is optimized; however, the stock would be overexploited when E is >0.5. This study estimated the exploitation level (E) at 0.57 for N. fauveli.

3.2.3. Recruitment Pattern

The recruitment pattern of N. fauveli exhibited continuous activity throughout the year, with two prominent peaks observed in October–November and February–April. (Figure 5). During October–November, the peak pulse accounted for approximately 16.0% of the observed recruitment, while in February–April, it constituted around 13.0% during the study period (Figure 5).

3.2.4. Virtual Population Analysis (VPA)

The length-structured VPA serves as a robust tool for stock assessment, estimating the size of each cohort and annual mortality due to fishing. The results of the length-based VPA analysis depicted fishing mortality concerning mean length (Figure 6). The VPA outcomes suggest higher fishing pressure in the 10.0–18.0 cm length range, with fishing mortality ranging approximately from 2.0 to 3.7 across the 10.0−16.0 cm length groups. Fishing mortality demonstrated a proportional increase with the body size of N. fauveli up to 12.0 cm in length, while it fluctuated for individuals larger than 13.0 cm in total length.

3.2.5. Probability of Capture (P-Cap)

The P-cap is applied to assess the vulnerability of various sizes in a particular area at a certain time [40]. The P-cap of 0.25, indicated that 25.0% of the N. fauveli population, was subject to capture at 9.0 cm body length (Figure 7). In addition, 50.0 to 75.0% of the N. fauveli populations were captured at 10.1 to 11.4 cm length classes (Figure 7).

4. Discussion

The biometric data obtained from our study reveal key insights into the size, weight, growth, etc., within the polychaete population. Comparisons with the existing literature and the incorporation of a comparative table elucidate patterns and variations in the biometric parameters, offering a comprehensive view of the N. fauveli species. Furthermore, the study also delves into the potential ecological implications of observed biometric trends, such as adaptations to specific environmental conditions or life history strategies [29]. As no studies have been reported on the L–W relationship and population dynamics of N. fauveli to date, this study provides the first report comparing it and other Nereididae species. Several considerations should be cautiously made when comparing population parameters. For example, the study area, habitat, season, etc., play pivotal roles in determining population. Due to higher temperatures and a greater abundance of food sources, northern hemisphere species usually have reproductive seasons limited to the spring and/or summer and, most crucially, show seasonal maturation, with substantially varied growth rates throughout the life cycle [40,41,42,43,44,45,46,47]. Seasonal growing peaks, shown in temperate species, may still not appear in tropical and subtropical environments, and breeding may occur year-round [48,49]. Importantly, N. fauveli, a type of polychaete worm, is known to exhibit epitoky as part of its reproductive strategy. In this stage, the worm undergoes morphological changes to become a reproductive form (the epitoke) for the purpose of reproduction. The epitoke typically has modifications such as enlarged eyes, modified parapodia, and other features suited for swimming and mating. The epitokous individuals are adapted for a pelagic, reproductive lifestyle [2,3]. This adaptation is often triggered by environmental cues, such as changes in temperature, lunar cycles, or other factors. The epitokes are capable of swimming and migrating to the water’s surface, where mating takes place, and they release gametes into the water for fertilization. Moreover, population studies of polychaetes are often interrupted due to a lack of hard structures, body flexibility, and susceptibility [18].
In contrast to other research conducted worldwide, polynomial and exponential models of this study are better fitted than others. For instance, for Armandia maculata (Opheliidae) and Aglaophamus macroura (Nephtyidae) specimens obtained in the Otago shelf, New Zealand, the curvilinear regressions (e.g., p, pw, e) were better fitted than the linear model [32]. The estimated intercept (a) reflects the individuals hatch at their real size, whereas an intercept of zero has no biological significance [32]. The estimated b value for N. fauveli showed negative allometric growth. Thus, the rate of increase in weight decelerated with increasing length, implying that the worms became more attenuated as they grew. Nereididae, Phyllodocida (r2 = 0.54, n = 5), and Hediste diversicolor (Nereididae) (r2 = 0.90, n = 207), respectively, in the Mediterranean and Black Sea, were exhibited at b = 1.11 and 2.20. Although the b-value was less than 3 in numerous studies [5,19,22] of polychaetes conducted around the world, b reached 3.52 in Armandia maculata (Opheliidae), 4.27 in Bithynia tentaculata (Bithyniidae), and 2.36 in Naticidae mesogastropod species [29]. In addition, the mud crab (Scylla olivacea), found in Bangladesh’s Sundarbans mangrove, has b-values of 3.05 and 2.61 [40].
The asymptotic length (L∞) and peak recruitment were noted in October 2020 (Figure 2 and Figure 5), coinciding with temperature and salinity measurements of 30.30 °C and 12.71 PSU, respectively. The first recruitment peak took place in October and November, with average temperatures and salinities of 28.15 °C and 15.25 PSU, respectively. Additionally, a second recruitment peak was observed in March 2021 (Figure 5), aligning with mean temperatures and salinities of 28.93 °C and 29.75 PSU, respectively. Thus, the recruitment highly relied on temperature fluctuations. The recruitment and growth of N. fauveli are probably less dependent on salinity due to its euryhaline (0.5 to 73.0 PSU) nature [43,44]. However, tolerance is greater during the pre-recruitment period [44]. There was a significant decline in larger size classes of Namalycastis sp. between December 2020 and January 2021, which could be associated with the end of reproductive peaks. Like other Nereididae species, they may be semelparous [45], dying after releasing of gametes [47]. Likewise, the larger-sized N. fauveli sharply declined from May to July 2021. During the reproductive peaks, growth largely decreased because most nutrients and energy are diverted to gametes maturation and growth of epitokal modifications [41,50,51]. This decrease could also be due to the fishing mortality, as the larger individuals (10.0 to 11.0 cm) showed a higher probability of capture (50.0 to 75.0%) (Figure 7). Similarly, sudden decreases in Perinereis cultrifera and Nereis falsa were reported in other studies [25,52], respectively, in the Northern hemisphere.
Environmental factors such as food availability [53], competitive interactions among species [54], and pollution [55] are reported to favor variation in individual body size and characteristics influencing population size distributions (e.g., L–W). However, L–W relationships are or should be resilient to these sources of variation, especially when ecological variations are minor, because the populations belong to the same ecosystem group.
In our study, the estimated growth coefficient (K), growth performance index (ϕ), and total mortality (Z) were 0.99 year−1, 2.69, and 4.56 year−1, respectively. Estimated fishing mortality (F) was higher than natural mortality (M), and the population was overexploited (Figure 4). In addition to overfishing, this wild population might be affected by habitat disturbances, seasonality, and other environmental factors [56,57]. Overall, the K and ϕ were similar to values for Nereididae reported in other studies from tropical–subtropical regions. For example, K and ϕ ranged from 1.4–2.2 and 0.485–0.872 in Laeonereis acuta on Brazil’s southeast coast, respectively [18]. In addition, the K and ϕ values were 1.68–2.72 and 2.86 in Alitta succinea in Brazil’s tropical estuary, respectively [51]. Furthermore, the K, ϕ, and Z values were estimated to be at 2.36 year−1, 1.83, and 9.99 year−1, respectively, in Perinereis anderssoni in a subtropical Atlantic beach of Southeast Brazil [42]. These comparative values vary among different regions, species, and conditions that influence growth and survival seasonally, like photoperiod and temperature [41].

5. Conclusions

This study represents the first report on the population parameters of N. fauveli; the report has provided valuable insights into the growth, recruitment pattern, probability of capture, mortality, and stock size of a commercially important polychaete species, N. fauveli. The findings revealed a negative allometric growth (b < 3) despite a significant length–weight relationship. The analysis demonstrated a proportional increase in both fishing mortality and capture probability with the total length at a specific age. Notably, recruitment predominantly occurred in October and March, with temperature exerting a more pronounced influence than salinity. Evaluation of the exploitation level strongly suggested that the stock is currently experiencing overexploitation, emphasizing the need for conservation and management measures. Cultures of the studied species could help reduce the overexploitation pressure on N. fauveli, permitting its service to the ecosystem to flourish. Towards this goal, future research should focus on supplementing information on reproduction, suitable culture conditions of brood stock, oogenesis, in vitro fertilization, embryonic development, and larval rearing of N. Fauveli. Again, in this study, species-level identification was performed based on morphological characteristics; there is a possibility of a mix of more than one species of genera Namalycastis in the studied specimens. Further studies involving DNA barcoding are required to confirm species identification.

Author Contributions

Conceptualization, funding acquisition, and supervision, M.J.S.; methodology, formal analysis and investigation, writing—original draft preparation, M.J.S., M.A.I. and M.B.H.; writing—review and editing, M.J.S., M.B.H., P.K.S., T.V.J., N.N.R., M.Y.H., N.S. and M.M.I. All authors have read and agreed to the published version of the manuscript.

Funding

The research was carried out from the Program Based Research Grant (PBRG) funded jointly by the Project Implementation Unit (PIU)—Bangladesh Agricultural Research Council (BARC) and the World Bank (Grant no. PBRG-155) under the National Agriculture Technology Project (NATP), Bangladesh, Phase 2.

Institutional Review Board Statement

Not applicable for studies not involving humans or animals.

Data Availability Statement

Data will be available upon request.

Acknowledgments

The authors are deeply grateful to Joana Zanol Professora Associada, Laboratório de Biodiversidade de Annelida (LaBiAnne), Departamento de Invertebrados, Museu Nacional, Universidade Federal do Rio de Janeiro (UFRJ), Horto Botânico, Quinta da Boa Vista s/n, São Cristóvão, 20940-040, Rio de Janeiro, RJ, Brasil for her identification of the N. fauveli We also acknowledge Harunur Rashid, Director, PIU-BARC for his scholastic monitoring the project work and guidance. We would like to greatly thank Saleh Uddin Ahmed, Consultant, PIU-BARC for his suggestions for our fieldwork.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Hutchings, P. Biodiversity and functioning of polychaetes in benthic sediments. Biodivers. Conserv. 1998, 7, 1133–1145. [Google Scholar] [CrossRef]
  2. Jumars, P.A.; Dorgan, K.M.; Lindsay, S.M. Diet of worms emended: An update of polychaete feeding guilds. Annu. Rev. Mar. Sci. 2015, 7, 497–520. [Google Scholar] [CrossRef]
  3. Martins, A.D.; Barros, F. Ecological Functions of Polychaetes Along Estuarine Gradients. Front. Mar. Sci. 2022, 9, 780318. [Google Scholar] [CrossRef]
  4. Pauls, L.D. Optimization of Rearing Techniques for Cultured Marine Polychaetes (Nereis virens) Using Sustainably Sourced Ingredients. Ph.D. Thesis, University of Wales, Cardiff, UK, 2009. Available online: http://cronfa.swan.ac.uk/Record/cronfa42755 (accessed on 4 January 2020).
  5. Wang, H.; Seekamp, I.; Malzahn, A.; Hagemann, A.; Carvajal, A.K.; Slizyte, R.; Standal, I.B.; Handå, A.; Reitan, K.I. Growth and nutritional composition of the polychaete Hediste diversicolor (OF Müller, 1776) cultivated on waste from land-based salmon smolt aquaculture. Aquaculture 2019, 502, 232–241. [Google Scholar] [CrossRef]
  6. Yuwono, E.; Haryadi, B.; Susilo, U.; Siregar, A.; Sugiharto, S. Fertilization and Maintenance of Larvae and Juveniles as Efforts to Develop Lur Worm Cultivation Techniques. Majalah Ilmiah Biologi BIOSFERA. 2002, 9, 1–8. [Google Scholar]
  7. Chung, M.Y.; Liu, C.H.; Chen, Y.N.; Cheng, W. Enhancing the reproductive performance of tiger shrimp, Penaeus monodon, by incorporating sodium alginate in the broodstock and larval diets. Aquaculture 2011, 312, 180–184. [Google Scholar] [CrossRef]
  8. Yuwono, E. Kebutuhan Nutrisi Crustacea dan Potensi Cacing Lur (Nereis sp., Polychaeta) Untuk Pakan Udang. J. Pemb. Pedesaan 2005, 5, 42–49. [Google Scholar]
  9. Cole, V.J.; Chick, R.C.; Hutchings, P.A. A review of global fisheries for Polychaeta worms as a resource for recreational fishers: Diversity, sustainability and research needs. Rev. Fish Bio. Fish. 2018, 28, 543–565. [Google Scholar] [CrossRef]
  10. Górska, B.; Gromisz, S.; Włodarska-Kowalczuk, M. Size assessment in polychaetes worms—Application of morphometric correlations for common North Atlantic taxa Barbara. Limnol. Oceanogr. Methods 2019, 17, 254–265. [Google Scholar] [CrossRef]
  11. Glasby, C.J. The Namanereidinae (Polychaeta: Nereididae). Part 1, Taxonomy and Phylogeny Records of the Australian Museum. In Records of the Australian Museum; Supplement 25; 1999; Available online: https://journals.australian.museum/glasby-1999-rec-aust-mus-suppl-25-1129/ (accessed on 4 January 2020).
  12. Glasby, C.J.; Timm, T. Global diversity of polychaetes (Polychaeta; Annelida) in freshwater. Hydrobiologia 2008, 595, 107–115. [Google Scholar] [CrossRef]
  13. Conde-vela, V.M. The troglomorphic adaptations of Namanereidinae (Annelida, Nereididae) revisited, including a redescription of Namanereis cavernicola (Solís-Weiss & Espinasa, 1991), and a new Caribbean species of Namanereis Chamberlin, 1919. Subterr. Biol. 2017, 23, 19–46. [Google Scholar] [CrossRef]
  14. Raknuzzaman, M.; Ahmed, M.K.; Islam, M.S.; Habibullah-Al-Mamun, M.; Tokumura, M.; Sekine, M.; Masunaga, S. Assessment of Trace Metals in Surface Water and Sediment Collected from Polluted Coastal Areas of Bangladesh. J. Wat. Environ. Technol. 2016, 14, 247–259. [Google Scholar] [CrossRef]
  15. Hena, M.K.A.; Kohinoor, S.M.S.; Siddique, M.A.M.; Ismail, J.; Idris, M.H.; Amin, S.M.N. Composition of Macrobenthos in the Bakkhali Channel System, Cox’s Bazar with Notes on the Soil Parameter. Pak. J. Biol. Sci. 2012, 15, 641–646. [Google Scholar] [CrossRef]
  16. Islam, M.S.; Sikder, M.N.A.; Al-Imran, M.; Hossain, M.B.; Mallick, D.; Morshed, M.M. Intertidal Macrobenthic Fauna of the Karnafuli Estuary: Relations with Environmental Variables. Wor. Appl. Scis. J. 2013, 21, 1366–1373. [Google Scholar]
  17. Aura, C.M.; Raburu, P.O.; Herrmann, J. Macro invertebrate’s community structure in Rivers Kipkaren and Sosiani, River Nzoia Basin, Kenya. J. Ecol. Nat. Environ. 2011, 3, 39–46. Available online: http://www.academicjournals.org/jene (accessed on 4 January 2020).
  18. Omena, E.P.; Amaral, A.C.Z. Population dynamics and production of Laeonereis acuta. Bull. Mar. Sci. 2000, 67, 421–431. Available online: https://www.researchgate.net/publication/233675884_Population_dynamics_and_secondary_production_of_Laeonereis_acuta_Treadwell_1923_Nereididae_Polychaeta (accessed on 4 January 2020).
  19. Pagliosa, P.R.; Lana, P.C. Population dynamics and secondary production of Nereis oligohalina (Nereididae: Polychaeta) from a subtropical marsh in southeast Brazil. Bull. Mar. Sci. 2000, 67, 259–268. Available online: https://www.researchgate.net/publication/298293084_Population_dynamics_and_secondary_production_of_Nereis_oligohalina_Nereididae_Polychaeta_from_a_subtropical_marsh_in_Southeast_Brazil (accessed on 14 January 2020).
  20. Daas, T.; Younsi, M.; Daas-Maamcha, Q.; Gillet, P.; Scaps, P. Reproduction, population dynamics and production of Nereis falsa (Nereididae: Polychaeta) on the rocky coast of El Kala National Park, Algeria. Helgol. Mar. Res. 2011, 65, 165–173. [Google Scholar] [CrossRef]
  21. Otegui, M.B.P.; Blankensteyn, A.; Pagliosa, P.R. Population structure, growth and production of Thoracophelia furcifera (Polychaeta: Opheliidae) on a sandy beach in Southern Brazil. Helgol. Mar. Res. 2012, 66, 479–488. [Google Scholar] [CrossRef]
  22. Peixoto, A.J.M.; Costa, T.D.M.M.; Santos, C.S.G. Population structure and dynamics of Perinereis anderssoni (Polychaeta: Nereididae) in a subtropical Atlantic Beach. Pan-Am. J. Aquat. Sci. 2018, 13, 188–199. [Google Scholar]
  23. Robinson, L.A.; Greenstreet, S.P.R.; Reiss, H.; Callaway, R.; Craeymeersch, J.; De Boois, I.; Degraer, S.; Ehrich, S.; Fraser, H.M.; Goffin, A.; et al. Length–weight relationships of 216 North Sea benthic Invertebrates and fish. J. Mar. Biol. Assoc. 2010, 90, 95–104. [Google Scholar] [CrossRef]
  24. Hua, E.; Zhang, Z.; Warwick, R.M.; Deng, K.; Lin, K.; Wang, R.; Yu, Z. Pattern of benthic biomass size spectra from shallow waters in the East China seas. Mar. Biol. 2013, 160, 1723–1736. [Google Scholar] [CrossRef]
  25. Górska, B.; Włodarska-Kowalczuk, M. Food and disturbance effects on Arctic benthic biomass and production size spectra. Prog. Oceanogr. 2017, 152, 50–61. [Google Scholar] [CrossRef]
  26. Costa-Paiva, E.M.; Paiva, P.C. A morphometric analysis of Eunice Cuvier (Annelida, Polychaeta) species. Rev. Bras. Zool. 2007, 24, 353–358. [Google Scholar] [CrossRef]
  27. Mistri, M.; Fano, E.A.; Rossi, R. Macrofaunal secondary production in a lagoon of the Po River Delta: An evaluation of estimation methods. Ital. J. Zool. 2001, 68, 147–151. [Google Scholar] [CrossRef]
  28. Benke, A.C.; Huryn, A.D.; Smock, L.A.; Wallace, J.B. Length-mass relationships for freshwater macroinvertebrates in North America with particular reference to the south-eastern United States. J. N. Am. Benthol. Soc. 1999, 18, 308–343. [Google Scholar] [CrossRef]
  29. Rosati, I.; Barbone, E.; Basset, A. Length-mass relationships for transitional water benthic macroinvertebrates in Mediterranean and Black Sea ecosystems. Estuar. Coas. Shelf Sci. 2012, 113, 231–239. [Google Scholar] [CrossRef]
  30. Gayanilo, F.C., Jr.; Sparre, P.; Pauly, D. FAO-ICLARM Stock Assessment Tools II (FiSAT II). Revised version. In User’s Guide, FAO Computerized Information Series (Fisheries). No. 8, Revised version; FAO: Rome, Italy, 2005; 168p, Available online: https://www.fao.org/3/y5997e/y5997e.pdf (accessed on 14 January 2020).
  31. Hossain, M.B.; Banik, P.; Nur, A.U.; Rahman, T. Abundance and characteristics of microplastics in sediments from the world’s longest natural beach, Cox’s Bazar, Bangladesh. Mar. Poll. Bull. 2021, 163, 111956. [Google Scholar] [CrossRef] [PubMed]
  32. Paavo, B.; Ziegelmeyer, A.; Lavric, E.; Probert, P.K. Morphometric correlations and body mass regressions for Armandiam aculata, Aglaophamus macroura (Polychaeta), and Zethalia zelandica (Gastropoda), New Zealand. J. Mar. Freshwat. Res. 2008, 42, 85–91. [Google Scholar] [CrossRef]
  33. Pramanik, M.N.; Chowdhury, S.H.; Kabir, S.M.H. Annelida. In Encyclopedia of Flora and Fauna of Bangladesh; Ahmad, M., Ahmed, A.T.A., Rahman, A.K.A., Ahmed, Z.U., Begum, Z.N.T., Hassan, M.A., Khondker, M., Eds.; Annelida, Echinodermata, Acanthocephala and Minor Phyla; Asiat. Society of Bangladesh: Dhaka, Bengal, 2009; Volume 16, pp. 1–91. [Google Scholar]
  34. Muir, A.I.; Hossain, M.M.M. The intertidal polychaete (Annelida) fauna of the Sitakunda coast (Chittagong, Bangladesh), with notes on the Capitellidae, Glyceridae, Lumbrineridae, Nephtyidae, Nereididae and Phyllodocidae of the “Northern Bay of Bengal Ecoregion”. ZooKeys 2014, 419, 1–27. [Google Scholar] [CrossRef]
  35. Pauly, D.; Munro, J.L. Once more on the comparison of growth in fish and invertebrates. Fishbyte 1984, 2, 1–21. Available online: http://pubs.iclarm.net/Naga/na_1951.pdf (accessed on 24 January 2020).
  36. Beverton, R.J.H. A review of methods for estimating mortality rates in fish populations, with special reference to sources of bias in catch sampling. Rapp. Procès-Verbaux Reun. 1956, 140, 67–83. Available online: https://www.scienceopen.com/document?vid=5ce3b272-dd06-4925-94ab-41995bbd5d47 (accessed on 14 January 2020).
  37. Pauly, D. On the interrelationships between natural mortality, growth parameters, and mean environmental temperature in 175 fish stocks. J. Mar. Sci. 1980, 39, 175–192. [Google Scholar] [CrossRef]
  38. Gulland, J.A. The fish resources of the Ocean West poly fleet, survey fishing news (Books) Ltd. FAO Tech. Pap. 1971, 97, 428. Available online: https://www.fao.org/3/al937e/al937e.pdf (accessed on 4 January 2020).
  39. Gulland, J.A. Estimation of mortality rates. In Annex to Arctic Fisheries Working Group Report (Meeting in Hamburg, January 1965); ICES, C.M.: Copenhagen, Denmark, 1965; Doc. No. 3 (mimeographed); Available online: https://www.ices.dk/sites/pub/CM%20Doccuments/1965/1965_3A%20-%20Annex%20-%20Estimation%20of%20Mortality%20Rates.pdf (accessed on 14 January 2020).
  40. Sakib, M.H.; Ahmmed, S.; Washim, M.R.; Islam, M.L.; Chowdhury, P. Population dynamics of mud crab, Scylla olivacea (Herbst, 1796) from the Sundarbans of Bangladesh. Aquac. Fish Fish. 2022, 2, 224–232. [Google Scholar] [CrossRef]
  41. Fischer, A. Reproductive and developmental phenomena in annelids: A source of exemplary research problems. Hydrobiologia 1999, 402, 1–20. [Google Scholar] [CrossRef]
  42. Hossain, M.B.; Hutchings, P. Nephtys bangladeshi n. sp., a new species of Nephtyidae (Annelida: Phyllodocida) from Bangladesh coastal waters. Zootaxa 2016, 4079, 41–52. [Google Scholar] [CrossRef]
  43. Komendantov, A.Y.; Aladin, N.V.; Ezhova, E.E. Environmental dependence of osmoregulation in Lycastopsis augeneri polychaeta nereidae. Zool. Žurnal 1989, 68, 137–140. Available online: https://eurekamag.com/research/007/305/007305572.php (accessed on 4 January 2020).
  44. Ezhova, E.E. Spawning and Early Ontogenesis of the Littoral Polychaete Namanereis littoralis (Grube, 1876) (Nereididae, Namanereidinae). Russi. J. Develop. Biol. 2011, 42, 159–166. [Google Scholar] [CrossRef]
  45. Wilson, R.S. Nerididae. In Fauna of Australia Volume 4A Polychaetes & Allies Polychaeta, Myzostomida, Pogonophora, Echiura, Sipuncula Subtitle (1–30); Beesley, P.L., Ed.; Australian Biological Resources Study/CSIRO Publishing: Sydney, Australia, 2000. [Google Scholar]
  46. Fischer, A.; Dorresteijn, A. The polychaete Platynereis dumerilii (Annelida): A laboratory animal with spiralian cleavage, lifelong segment proliferation and a mixed benthic/pelagic life cycle. BioEssays 2004, 26, 314–325. [Google Scholar] [CrossRef]
  47. Johnston, T.A.; Cunjak, R.A. Dry mass-length relationships for benthic insects: A review with new data from Catamaran Brook, New Brunswick, Canada. Freshwat. Biol. 1999, 41, 653–674. [Google Scholar] [CrossRef]
  48. Wenzel, E.; Meyer, E.; Schwoerbel, J. Morphology and biomass determination of dominan mayfly larvae (Ephemeroptera) in running waters. Arch. Hydrobiol. 1990, 118, 31–46. [Google Scholar] [CrossRef]
  49. Towers, D.J.; Henderson, I.M.; Veltman, C.J. Predicting dry weight of New Zealand aquatic macroinvertebrates from linear dimensions. N. Z. J. Mar. Freshwat. Res. 1994, 28, 159–166. [Google Scholar] [CrossRef]
  50. Sette, C.S.C.; Shinozaki-Mendes, R.A.; Barros, T.L.; Souza, J.R.B. Age and growth of Alitta succinea (Polychaeta; Nereididae) in a tropical estuary of Brazil. J. Mar. Biol. Assoc. 2013, 93, 2123–2128. [Google Scholar] [CrossRef]
  51. Olive, P.J.W.; Lewis, C.; Beardall, V. Fitness components of seasonal reproduction: An analysis using Nereis virens as a life history model. Oceano. Acta 2000, 23, 377–389. [Google Scholar] [CrossRef]
  52. Scaps, P.; Rouabah, A.; Leprêtre, A. Morphological and biochemical evidence that Perinereis cultrifera (Polychaeta: Annelida) is a complex of species. J. Mar. Biol. Assoc. 2000, 80, 735–736. [Google Scholar] [CrossRef]
  53. Basset, A.; Glazier, D.S. Resource limitation and intraspecific patterns of weight length variation among spring detritivores. Hydrobiologia 1995, 316, 127–137. Available online: https://link.springer.com/article/10.1007/BF00016894 (accessed on 4 January 2020). [CrossRef]
  54. Basset, A.; Rossi, L. Competitive trophic niche modifications in three populations of detritivores. Functional Ecol. 1990, 4, 685–694. [Google Scholar] [CrossRef]
  55. Basset, A. Resource-mediated effects of stream pollution on food absorption of Asellus aquaticus (L.) populations. Oecologia 1993, 93, 315–321. Available online: https://link.springer.com/article/10.1007/BF00317872 (accessed on 4 January 2020). [CrossRef]
  56. Scaps, P. The exploitation and aquaculture of marine polychaetes. Bull. Soc. Zool. Fr. 2003, 128, 21–33. Available online: https://www.researchgate.net/publication/286049351_The_exploitation_and_aquaculture_of_marine_polychaetes (accessed on 4 January 2020).
  57. Garcia-Alonso, J.; Muller, C.T.; Hardege, J.D. Influence of food regimes and seasonality on fatty acid composition in the ragworm. Aqua. Biol. 2008, 4, 7–13. [Google Scholar] [CrossRef]
Jmse 12 00312 g001
Figure 1. Map showing the Cox’s Bazar district and the sampling stations (red circled).
Figure 1. Map showing the Cox’s Bazar district and the sampling stations (red circled).
Jmse 12 00312 g001
Jmse 12 00312 g002
Figure 2. Von Bertalanffy growth curves of N. fauveli drawn over their restructured length–frequency distribution using ELEFAN-1 (L∞ = 22.05 cm; K = 0.99 year−1).
Figure 2. Von Bertalanffy growth curves of N. fauveli drawn over their restructured length–frequency distribution using ELEFAN-1 (L∞ = 22.05 cm; K = 0.99 year−1).
Jmse 12 00312 g002
Jmse 12 00312 g003
Figure 3. Estimation of growth coefficient (K) and growth performance index (ϕ) for N. fauveli in the Cox’s Bazar coast. Best growth performances are predicted employing growth parameters such as asymptotic length, growth coefficient, and age at zero length.
Figure 3. Estimation of growth coefficient (K) and growth performance index (ϕ) for N. fauveli in the Cox’s Bazar coast. Best growth performances are predicted employing growth parameters such as asymptotic length, growth coefficient, and age at zero length.
Jmse 12 00312 g003
Jmse 12 00312 g004
Figure 4. Length-converted catch curves for N. fauveli at Cox’s Bazar coast in Bangladesh.
Figure 4. Length-converted catch curves for N. fauveli at Cox’s Bazar coast in Bangladesh.
Jmse 12 00312 g004
Jmse 12 00312 g005
Figure 5. Annual recruitment pattern of N. fauveli sampled from the Cox’s Bazar coast.
Figure 5. Annual recruitment pattern of N. fauveli sampled from the Cox’s Bazar coast.
Jmse 12 00312 g005
Jmse 12 00312 g006
Figure 6. Virtual population analysis (VPA) for N. fauveli collected from Cox’s Bazar coast of Bangladesh.
Figure 6. Virtual population analysis (VPA) for N. fauveli collected from Cox’s Bazar coast of Bangladesh.
Jmse 12 00312 g006
Jmse 12 00312 g007
Figure 7. Probability of capture (P-cap) based on the total length (L) of N. fauveli in the Cox’s Bazar coast of Bangladesh.
Figure 7. Probability of capture (P-cap) based on the total length (L) of N. fauveli in the Cox’s Bazar coast of Bangladesh.
Jmse 12 00312 g007
Table 1. L–W relationship of N. fauveli in the present study compared with other species of polychaetes in other study areas.
Table 1. L–W relationship of N. fauveli in the present study compared with other species of polychaetes in other study areas.
ReferencesGroupsMonthsEquationnIntercept (a)Slope (b)SEp-Valuelog r21 r2pw r2e r2p r2
Present StudyN. fauveli, NereididaeAugust, 2020W = aL1.50870.7411.500.047<0.0010.820.890.900.920.92
September, 2020W = aL1.53770.7321.530.068<0.0010.790.800.820.800.80
October, 2020W = aL1.361220.8201.360.148<0.0010.430.440.480.470.45
November, 2020W = aL1.801090.5991.800.086<0.0010.700.750.760.770.77
December, 2020W = aL1.721110.7791.720.254<0.0010.690.640.690.700.66
January, 2021W = aL1.521300.7421.520.062<0.0010.700.780.850.880.87
February, 2021W = aL1.631050.8241.630.058<0.0010.740.830.860.890.89
March, 2021W = aL2.121040.7202.120.039<0.0010.880.870.900.870.87
April, 2021W = aL2.031040.6982.030.030<0.0010.930.940.940.920.94
May, 2021W = aL1.531060.7151.530.890<0.0010.800.870.900.900.91
June, 2021W = aL1.181290.3721.180.740<0.0010.120.190.200.370.59
July, 2021W = aL1.721010.6571.720.103<0.0010.800.810.820.810.82
OverallW = aL1.6513000.721.650.138<0.0010.630.700.720.710.73
[32]Armandia maculata OpheliidaeMarch, 2003eFW = L3.52690.00143.52−<0.050.690.770.880.800.79
March, 2003DW = L3.24690.00063.24−<0.050.690.770.880.800.79
March, 2003AFW = W2.39580.31022.39−<0.050.550.600.760.730.61
[32]Aglaophamus macroura, NephtyidaeMarch, 2003W7 = e0.04L560.28670.04−<0.050.620.780.700.770.82
March, 2003eFW = e0.16L560.18710.16−<0.050.500.730.890.900.92
March, 2003DW= e0.15L560.03590.15−<0.050.500.720.900.910.90
March, 2003AFW = e0.14L 0.03120.14−<0.050.480.690.870.910.86
March, 2003eFW = TA1.5 0.18471.5−<0.050.600.930.970.750.97
[29]Phyllodocida, NereididaeNovember, 2004 and May 2005W = aL1.1150.08411.11−−−0.54−−−
[32]Hediste diversicolor, NereididaeNovember, 2004 and May, 2005W = aL2.202070.00232.20−−−0.90−−−
L = total length; W = wet weight; FW = estimated fresh weight; DW = dry weight; AFW = ash-free weight; A = area; TA = total area; n = total number; SE = standard error; r2 = correlation coefficient; linear (1), logarithmic (log), polynomial (p), power (pw), and exponential (e) regressions. ‘−’ = not found.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Sarker, M.J.; Sarker, P.K.; Islam, M.A.; Rima, N.N.; Joydas, T.V.; Sultana, N.; Islam, M.M.; Hossain, M.Y.; Hossain, M.B. Biometry, Growth, and Recruitment Pattern of a Commercially Important Nereid polychaete, Namalycastis fauveli, from the East Coast of Bangladesh. J. Mar. Sci. Eng. 2024, 12, 312. https://doi.org/10.3390/jmse12020312

AMA Style

Sarker MJ, Sarker PK, Islam MA, Rima NN, Joydas TV, Sultana N, Islam MM, Hossain MY, Hossain MB. Biometry, Growth, and Recruitment Pattern of a Commercially Important Nereid polychaete, Namalycastis fauveli, from the East Coast of Bangladesh. Journal of Marine Science and Engineering. 2024; 12(2):312. https://doi.org/10.3390/jmse12020312

Chicago/Turabian Style

Sarker, Md. Jahangir, Pallab Kumer Sarker, Md. Ariful Islam, Nazmun Naher Rima, Thadickal Viswanathan Joydas, Nahid Sultana, Md. Monirul Islam, Md. Yeamin Hossain, and Mohammad Belal Hossain. 2024. "Biometry, Growth, and Recruitment Pattern of a Commercially Important Nereid polychaete, Namalycastis fauveli, from the East Coast of Bangladesh" Journal of Marine Science and Engineering 12, no. 2: 312. https://doi.org/10.3390/jmse12020312

APA Style

Sarker, M. J., Sarker, P. K., Islam, M. A., Rima, N. N., Joydas, T. V., Sultana, N., Islam, M. M., Hossain, M. Y., & Hossain, M. B. (2024). Biometry, Growth, and Recruitment Pattern of a Commercially Important Nereid polychaete, Namalycastis fauveli, from the East Coast of Bangladesh. Journal of Marine Science and Engineering, 12(2), 312. https://doi.org/10.3390/jmse12020312

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop