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Journal of Marine Science and Engineering
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  • Review
  • Open Access

2 September 2025

Review of Age Estimation Techniques and Growth Models for Shelled Organisms in Marine Animal Forests

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1
Sürmene Faculty of Marine Science, Karadeniz Technical University, 61530 Trabzon, Türkiye
2
Mediterranean Fisheries Research Production and Training Institute, 07001 Antalya, Türkiye
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Department of Water Quality, Institute of Marine Biology of National Academy of Sciences of Ukraine, 65076 Odesa, Ukraine
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Department of Ecology and Vertabrate Zoology, University of Lodz, 90-136 Lodz, Poland
J. Mar. Sci. Eng.2025, 13(9), 1693;https://doi.org/10.3390/jmse13091693
This article belongs to the Section Marine Biology
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Abstract

Marine shelled organisms exhibit diverse growth strategies shaped by species-specific traits and environmental conditions that critically influence their ecological roles, particularly within Marine Animal Forests (MAF), which are structurally complex habitats and biodiversity-rich habitats. This review compiles and compares empirical growth data for 16 bivalve and gastropod species across seven families, classified as full MAF contributors (Pinna nobilis, Flexopecten glaber, Pecten maximus, and Placopecten magellanicus), partial MAF contributors (Cerastoderma edule, C. glaucum, Chamelea gallina, Ruditapes philippinarum, Mercenaria mercenaria, Panopea generosa, Anadara kagoshimensis, A. inaequivalvis, and Tegillarca granosa), and ecologically relevant non-MAF species (Buccinum undatum, Hexaplex trunculus, and Rapana venosa). Age estimation methods included direct techniques, such as shell growth ring and opercular annulus analysis, alongside indirect approaches, such as length-frequency analysis, stable isotope profiling, and mark–recapture studies. Growth trajectories were modelled using von Bertalanffy growth function (VBGF) parameters to estimate the shell size from ages 1 to 4. Based on these estimates, species were categorised into slow, moderate, fast, and exceptional growth groups. These classifications were further explored through hierarchical clustering that grouped species according to their VBGF-derived growth values, revealing consistent and contrasting life history strategies. This comparative analysis should enhance the understanding of molluscan growth dynamics and support the conservation and management of MAF-associated ecosystems by informing restoration planning, guiding species selection, and contributing to evidence-based policy development.

1. Introduction

Marine Animal Forests (MAFs) represent some of the most dynamic and biodiverse marine ecosystems. They are characterised by the dense aggregation of organisms that form, maintain, or inhabit complex three-dimensional habitats [,]. Shelled organisms, including bivalves and gastropods, are both structural and functional components of these ecosystems [,]. Species such as Anadara inaequivalvis, Cerastoderma edule, Ruditapes philippinarum, and Pinna nobilis enhance ecosystem stability by improving water quality and nutrient cycling [,]. Conversely, predatory species, such as Rapana venosa and Hexaplex trunculus, regulate prey populations, contributing to trophic balance [,]. These species are ecologically significant and serve as biological indicators of environmental conditions through their growth- and age-related traits [,,].
Understanding the growth dynamics of shelled organisms is crucial for understanding their ecological roles and ensuring MAF ecosystem sustainability [,]. The ability of these organisms to respond to environmental changes and anthropogenic pressures is influenced by growth rates, age structures, and life history traits [,]. However, comprehensive insights into these aspects require robust methodologies for age determination and growth modelling [,]. Techniques such as shell increment analysis, isotopic composition studies, advanced imaging, and shape-based approaches like elliptic Fourier analysis have proven instrumental in assessing age, growth, and site-specific morphological variation across diverse biological systems [,,]. Coupled with growth models, such as the von Bertalanffy equation, these approaches provide critical data on species-specific growth trajectories and their adaptability to environmental gradients [,,].
This review aimed to summarise and compare the current state of knowledge on age determination methods and growth modelling for key marine shelled organisms, including those fully, partially and not associated with MAFs. Particular emphasis was placed on the comparison of growth rates across species, highlighting interspecies variability and its ecological implications.

2. Materials and Methods

2.1. Literature Search Strategy

A targeted literature review was conducted to identify peer-reviewed studies focusing on age determination techniques, growth modelling approaches, and MAF-associated interspecific growth comparisons of marine shelled organisms. Google Scholar was used to conduct the search to ensure comprehensive coverage of scientific literature [].
The search strategy was designed to capture a broad spectrum of methodologies and taxa. Boolean operators were used to combine the following thematic keyword groups:
  • Age determination: “age reading,” “growth increments,” “shell analysis,” “sclerochronology,” “isotope analysis,” “microstructure,” and “increment formation”
  • Growth modelling: “growth rate,” “growth modelling,” “von Bertalanffy,” “length-at-age,” “size-frequency analysis,” “growth curves”
  • Organism and ecosystem context: “bivalves,” “gastropods,” “shelled organisms,” “Marine animal forests,” “ecosystem engineers”
The search was restricted to studies that provided empirical data on growth or age estimation for species known to contribute to MAF structure and function. Both full and partial MAF contributors and ecologically relevant non-MAF species were included for comparative purposes.

2.2. Data Extraction and Classification

From the selected studies, data were systematically extracted and categorised into three primary domains:
  • Age determination methods: including direct techniques (e.g., shell increment analysis and operculum examination), indirect methods (e.g., length-frequency analysis), and advanced approaches (e.g., stable isotope analysis, mark–recapture, and laboratory-based validation).
  • Growth models: with emphasis on the use of the von Bertalanffy growth function (VBGF) and other length-at-age modelling frameworks. Parameters, such as asymptotic length (L∞), growth coefficient (K), and theoretical age at zero length (t0), were recorded where available.
  • Species-specific growth rates: including raw and modelled shell length data across age classes, with intra- and interspecific variability considered.
Each study was further classified by species, taxonomic family, geographic region, and methodological approach.

2.3. Statistical Analysis

Quantitative data on shell length at age were synthesised to evaluate growth patterns across species. Shell lengths at specific age classes (1, 1.5, 2, 2.5, 3, 3.5, and 4 years) were estimated for each species using VBGF parameters reported in the literature. These estimates enabled standardised comparisons of growth trajectories across species, regardless of the original study design or sampling approach.
To assess growth performance, the cumulative size gain was calculated as the difference between the estimated shell length at 4 years of age and that at 1 year of age (i.e., size at 4 years minus size at 1 year). This metric reflects net growth over a three-year interval, was selected to minimise early-life variability, and thus serves as a practical proxy for growth performance. The theoretical age at zero length (t0) in the VBGF may vary across studies and species, and in some cases, it may exceed age 1 (e.g., Panopea generosa in Cruz-Vásquez et al. [], with t0 = 2.26). However, our method relies on predicted lengths at fixed age points derived from published VBGF parameters, allowing consistent interspecies comparisons. Confidence intervals were also calculated to reflect variability in growth estimates across studies.
Species-specific growth trajectories were visualised using locally estimated scatterplot smoothing (LOESS), a non-parametric regression technique that fits simple models to localised subsets of the data to reveal underlying trends without assuming a global functional form []. Shell size estimates were extracted for each species, reshaped into a long format, and plotted to display individual study estimates (grey lines), a smoothed LOESS trend (black line), and the associated 95% confidence interval (red band). Axis limits were adjusted to accommodate species-specific size ranges, ensuring consistent visual interpretation across taxa.
Hierarchical clustering analysis was also performed using average cumulative shell size gain values for each species. Euclidean distance was used to measure species dissimilarity based on these growth metrics, and complete linkage was applied to form clusters by maximising the distance between the most dissimilar members within each group. This method was chosen to ensure clear separation between growth categories and to reflect biologically meaningful differences in growth trajectories. The resulting dendrogram grouped species into clusters representing slow, moderate, fast, and exceptional growth strategies.
All statistical analyses and visualisations were conducted in R (version 4.5.0) [] using RStudio (version 2025.5.0.496) [] as the integrated development environment, with packages including stats [], ggplot2 [], and dendextend [].

3. Results

3.1. Synthesis of Species and Methodological Scope

This review summarises findings from an extensive collection of studies focusing on the growth dynamics of 16 key marine shelled species. These species represent seven families across the Bivalvia and Gastropoda classes: Arcidae, Cardiidae, Hiatellidae, Pectinidae, Veneridae, Buccinidae, and Muricidae. Figure 1 illustrates the geographical distribution of these studies.
Figure 1. Distribution, species, and age estimation methods in marine shelled organisms.
Our analysis encompasses species integral to MAF formation, such as the noble pen shell (P. nobilis), the smooth scallop (Flexopecten glaber), the great scallop (Pecten maximus), and the Atlantic Sea scallop (Placopecten magellanicus). We also include species that partially contribute to MAF ecosystems, such as the common cockle (C. edule), the lagoon cockle (Cerastoderma glaucum), the striped venus (Chamelea gallina), the Manila clam (R. philippinarum), the hard clam (Mercenaria mercenaria), the geoduck (P. generosa), and the blood clams (Anadara kagoshimensis, A. inaequivalvis, and Tegillarca granosa). Non-MAF predatory gastropods, including the common whelk (Buccinum undatum), the banded dye-murex (Hexaplex trunculus), and the veined rapa whelk (R. venosa), were also examined to provide a broader ecological context. Table 1 presents a summary of these species, including their habitats, feeding biology, and representative images.
Table 1. Summary of species characteristics, including habitat and feeding biology (from SeaLifeBase []), and shell images accessed via World Register of Marine Species (WoRMS) [], hosted externally by Kapeller [] and Trausel and Slieker [].
The reviewed literature, comprising 42 studies, yielded a substantial dataset with numerous records for each species. Among the bivalves, P. nobilis was the most extensively documented, followed by P. maximus, C. edule, R. philippinarum, and P. generosa. In contrast, species such as T. granosa, A. inaequivalvis, A. kagoshimensis, and F. glaber were less frequently the focus of research. B. undatum was the most prominently studied gastropod species, with R. venosa and H. trunculus also receiving significant attention.
The methodologies for age determination varied considerably across the literature surveyed (Figure 1). A clear majority of studies favoured direct methods, primarily through the analysis of growth rings on the shells of both bivalves and some gastropods. For certain gastropod species, such as B. undatum and R. venosa, operculum analysis served as a reliable alternative for age estimation. Indirect approaches, such as length-frequency analysis, were also employed, although less commonly. A smaller subset of studies used alternative techniques, including stable isotope analysis, mark–recapture experiments, and laboratory-based growth trials, to ascertain the age and growth patterns of the rats.

3.2. Comparison of Growth Strategies Across Families

To investigate the diverse growth strategies among these species, we utilised the VBGF parameters derived from the literature (Table 2). By estimating shell lengths at sequential ages, we calculated the increase in cumulative shell size between the first and fourth years of life. This metric, along with its 95% confidence intervals, allowed for a standardised comparison of growth performance. The species were classified into four distinct growth categories based on this analysis, revealing a spectrum of life history strategies (Figure 2):
Table 2. Overview of age determination methods, and von Bertalanffy growth function (VBGF) parameters. The growth coefficient (K) is expressed in year−1, and the theoretical age at zero length (t0) is given in years.
Figure 2. Shell size gain was estimated using the von Bertalanffy growth function parameters from Table 2. Error bars represent 95% confidence intervals (CIs). Based on cumulative size gain over three years, species are grouped into four growth categories—Slow (8–13 mm), Moderate (16–21 mm), Fast (25–66 mm), and Exceptional (>150). These categories are used only for visualisation purposes and do not imply strict biological thresholds.
  • Slow Growers: A. inaequivalvis, C. glaucum, C. gallina, C. edule, and H. trunculus
  • Moderate Growers: T. granosa, M. mercenaria, R. philippinarum, and F. glaber
  • Fast Growers: P. magellanicus, P. maximus, A. kagoshimensis, R. venosa, P. generosa, and B. undatum
  • Exceptional Grower: P. nobilis
Figure 2 visually depicts the mean cumulative size gain and associated confidence intervals for each species, providing a clear depiction of these interspecific growth disparities.

3.2.1. Arcidae

Divergent growth patterns were evident within the Arcidae. A. kagoshimensis demonstrated rapid and sustained growth, achieving a considerable size by year four. In contrast, A. inaequivalvis exhibited more modest growth. Both species exhibited an initial burst of growth within the first 1.5 years. T. granosa exhibited a moderate growth rate with high individual variability, suggesting a plastic response to environmental conditions (Figure 3).
Figure 3. Shell size estimates across various ages for 16 mollusc species, derived from von Bertalanffy growth function parameters detailed in Table 2. Grey lines represent individual study estimates, the black line shows the LOESS trend, and the red band indicates the 95% confidence interval.

3.2.2. Buccinidae

B. undatum exhibited substantial intraspecific variability. Although the average growth was fast, shell sizes varied widely at each age class. The most significant increase occurred between years 1 and 2.5, after which growth decelerated (Figure 3).

3.2.3. Cardiidae

The two cockle species displayed distinct growth dynamics. C. edule had a pronounced early growth phase, reaching a large portion of its adult size within the first few years. C. glaucum followed a slower, more uniform growth trajectory (Figure 3).

3.2.4. Hiatellidae

P. generosa exhibited substantial and continuous growth, which is consistent with its long-lived life history. The shell size significantly increased each year, reaching large dimensions by year four (Figure 3).

3.2.5. Muricidae

The predatory gastropods showed contrasting strategies. H. trunculus grew slowly and steadily, with gradual increases in shell size. Conversely, R. venosa exhibited moderate to fast growth and high variability across populations (Figure 3).

3.2.6. Pectinidae

P. maximus and P. magellanicus were characterised by rapid early growth, reaching substantial sizes by year 4. F. glaber showed moderate, stable growth. P. nobilis stood out with exceptional growth and high variability, reaching sizes far beyond those of other species (Figure 3).

3.2.7. Veneridae

Species in this family generally exhibited moderate growth. R. philippinarum, M. mercenaria, and C. gallina all showed strong early growth, particularly between years 1 and 2.5, followed by a tapering growth rate (Figure 3).

3.3. Hierarchical Clustering of Growth Strategies

A hierarchical clustering analysis was conducted based on average cumulative shell size gain to further elucidate relationships in growth dynamics. The resulting dendrogram visually confirms the four distinct growth strategy clusters: Slow, Moderate, Fast, and Exceptional (Figure 4). The primary division in the dendrogram isolates P. nobilis, underscoring its unique high growth rate. The remaining species form two main clades. The first category includes both slow and moderate growers. Slow growers (H. trunculus, C. glaucum, C. gallina, C. edule, and A. inaequivalvis) are clearly separated from moderate growers (F. glaber, R. philippinarum, M. mercenaria, and T. granosa). The second major clade consists exclusively of fast growers. One sub-cluster groups the gastropods B. undatum and R. venosa with the bivalves A. kagoshimensis and P. generosa. The other subcluster includes the scallops P. maximus and P. magellanicus, indicating a shared rapid growth trajectory.
Figure 4. Hierarchical clustering of 16 marine shelled species based on estimated shell length growth data at age intervals of 1, 1.5, 2, 2.5, 3, 3.5, and 4 years, calculated using species-specific von Bertalanffy growth function parameters from Table 2. The y-axis represents Euclidean distance, indicating dissimilarity in growth trajectories among species.

4. Discussion

This review summarises the substantial variability in growth dynamics among 16 marine shelled mollusc species, distributed across seven families within the classes Bivalvia and Gastropoda. These differences reflect a continuum of life history strategies shaped by evolutionary adaptations, ecological roles, and environmental conditions [,,,]. The consistent application of the VBGF across studies—regardless of whether age estimation was direct (e.g., shell rings, opercula) or indirect (e.g., length-frequency analysis)—enabled standardised comparisons and robust classification of growth strategies [,].
Hierarchical clustering of cumulative shell growth revealed four distinct categories: slow, moderate, fast, and exceptional growers (Figure 2 and Figure 4). Slow-growing species, such as C. edule, C. gallina, and H. trunculus, exhibit gradual, uniform growth, often associated with long lifespans and resilience in stable or low-productivity environments [,,]. These species typically contribute to habitat stability and are more vulnerable to overexploitation due to slower recovery rates [,]. In contrast, fast-growing species—including R. venosa, B. undatum, P. generosa, and A. kagoshimensis—demonstrated rapid early growth, particularly within the first 2.5 years. This strategy is likely to enhance survival in dynamic or disturbed habitats by maximising early fecundity and resource acquisition [,,,]. Notably, P. nobilis emerged as an exceptional grower, showing remarkable shell size gains and high variability, with estimated sizes at age four ranging from 221 to 750 mm (Figure 3). As the largest bivalve in the Mediterranean—reaching up to 1200 mm, although typically ranging from 200 to 400 mm—it can live up to 27 years [,], underscoring its ecological importance as a keystone species in Mediterranean assemblages.
The observed decline in growth rates after 2.5 years across most species reflects energy trade-offs associated with maturation, reproduction, and shell maintenance [,]. These patterns align with ecological theory on fast–slow life history trade-offs, where fast growers prioritise early reproduction at the cost of longevity, whereas slow growers invest in long-term survival and structural contributions to ecosystems [,]. Understanding these growth dynamics is essential for conservation and aquaculture. During juvenile stages, fast-growing species may benefit from protective measures, such as seasonal closures or nursery habitat preservation [,]. Conversely, long-lived, slow-growing species may require long-term conservation strategies, including habitat restoration, stricter harvest regulations, and climate-resilient management approaches [,].
The ecological roles of these species are closely related to their growth strategies. Fast growers significantly contribute to biomass turnover and fisheries productivity, supporting the blue economy [,]. In contrast, slow-growing bivalves act as ecosystem engineers in MAFs, enhancing habitat complexity, biodiversity, and water quality [,,]. This functional diversity enhances the resilience of the ecosystem: long-lived engineers maintain structural integrity, while opportunistic species facilitate recovery after disturbance []. Future research should integrate physiological processes, such as energy assimilation, metabolic costs, and phenotypic plasticity, into growth models, while also considering empirical factors that influence digestion and nutrient utilisation [,,,,,]. Incorporating these factors, along with genomic tools and dynamic energy budget models, will improve species responses to environmental change and inform climate-smart aquaculture and conservation strategies [,].
Notably, a recent study provided the first direct ageing data for R. venosa in the Turkish Black Sea using statoliths—a method not previously applied in the region []. As this study was published after the completion of our analysis, it is not incorporated into the current dataset. However, it represents a significant advancement in gastropod age validation and offers valuable insights for future growth modelling and regional stock assessments.

5. Conclusions

Marine shelled organisms exhibit various growth strategies that reflect their ecological roles and evolutionary adaptations. This review highlights the importance of growth variability in shaping population dynamics and ecosystem functions. The consistent use of the VBGF across studies enabled meaningful comparisons and revealed distinct growth patterns across families. Rapid early growth in species such as R. venosa, B. undatum, and T. granosa suggests adaptive responses to predation and competition, whereas slower-growing species such as H. trunculus and P. nobilis contribute to long-term habitat stability. These findings underscore the need for tailored conservation strategies to account for species-specific growth dynamics.
When integrated with growth models, direct and indirect age estimation methods offer powerful tools for sustainable marine resource management. Future research should focus on refining these methodologies, incorporating environmental variables, and leveraging emerging technologies, such as remote sensing and molecular tools. Such efforts are critical for conserving MAF and ensuring marine ecosystems’ resilience despite accelerating anthropogenic change.
Nonetheless, the heterogeneity and geographic unevenness of the available literature constrained this review, which may affect the robustness of interspecific comparisons. Additionally, the targeted search strategy may have excluded some relevant or unpublished studies, potentially leading to the underrepresentation of certain taxa or regions. Despite these limitations, this review should serve as a valuable synthesis of growth dynamics in marine shelled organisms and provide a foundation for species-specific, adaptive conservation and management strategies.

Author Contributions

Conceptualisation, K.S. and Ö.D.; methodology, Ö.D. and K.S.; data curation, Ö.D., K.S., Ç.C.C., H.G., E.Ö., M.V. and G.B.; writing—original draft preparation, Ö.D. and K.S.; validation, Ç.C.C., H.G., E.Ö., M.V. and G.B.; supervision, K.S. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the European Cooperation in Science and Technology (COST) under COST Action CA20102, Marine Animal Forests of the World (MAF-WORLD). Additional support was provided by the Italian Ministry of University and Research’s project funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4–Call for Tender No. 3138 of 16 December 2021, rectified by Decree No. 3175 of 18 December 2021, and co-funded by the European Union–NextGeneration EU. Award Number: Project Code CN_00000033, Concession Decree No. 1034 of 17 June 2022, adopted by the Italian Ministry of University and Research, CUP D33C22000960007. Project Title: National Biodiversity Future Centre–NBFC. This additional support relates specifically to Genuario Belmonte.

Data Availability Statement

All data presented in this study are available through the references listed in Table 2.

Acknowledgments

This work is based on the MAF-WORLD Training Workshop, “Changes in the Marine Biota (MAF) of the Black Sea,” held at Karadeniz Technical University, Trabzon, Türkiye, from 18 to 21 October 2023. The workshop was supported by COST Action CA20102, Marine Animal Forests of the World (MAF-WORLD).

Conflicts of Interest

The authors have no conflicts of interest to declare.

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