Research Article |
Corresponding author: Murat Dağtekin ( muratdagtekin998@gmail.com ) Academic editor: Adnan Tokaç
© 2023 Murat Dağtekin.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Dağtekin M (2023) The invasive mollusk Rapana venosa (Mollusca: Neogastropoda: Muricidae) in the mid-southern Black Sea: Distribution, growth, and stock structure. Acta Ichthyologica et Piscatoria 53: 191-199. https://doi.org/10.3897/aiep.53.113745
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The rapa whelk, Rapana venosa (Valenciennes, 1846), known also as the veined rapa whelk or the Asian rapa whelk, settled in the Black Sea in 1940 and within the past 30 years has become an important economic contribution to local fishers along the coastline. This study examines the annual change in biomass, population structure, and interaction of the species with the ecosystem of rapa whelk in the mid-southern Black Sea. The samples were collected monthly in 2011 and 2012 by hydraulic dredge at different sites. Stock biomass was estimated at five different subregions and along four depth contours. In 2012 the biomass of rapa whelk increased significantly in in all subregions compared with the previous year sampling. Food availability is the main factor for species distribution, and in parallel, striped Venus clams, Chamelea gallina (Linnaeus, 1758), the main food source for rapa whelks, was significantly concentrated in the study area. The von Bertalanffy growth parameters (VBGP) were expressed as Lt = 121.78(1 − e−0.246(t + 0.33)). As a fisheries management point, our results highlight the overpopulation of rapa whelk in the region.
alien species, biomass, Black Sea, Rapana venosa, spatial distribution, VBGP
One of the biggest challenges to biodiversity and community structure is the encroachment of non-indigenous species into ecosystems (
Rapa whelks caused serious destruction to the benthic life of the Black Sea (
Despite its negative environmental effects, R. venosa is a commercially important whelk in the Turkish Black Sea. Since the early 1980s, it has been intensively fished by beam trawls and divers in the southeastern Black Sea. Landings have decreased in recent years after showing a great increase (Fig.
The presently reported study was intended to determine the growth characteristics, distribution pattern, and stock structure of R. venosa in the mid-southern Black Sea. Despite its commercial importance, information on the life history, distribution, and status of rapa whelk is scarce in the Black Sea. Therefore, growth parameters, length–weight relations, mortality, and exploitation rates were estimated to contribute to its population status. The difference in its distribution and estimated biomass was considered within the area colonized by the striped Venus clam (C. gallina) beds is an essential commercial bivalve species in Turkish fisheries. Exploitation rate and stock distribution results were considered for better management actions in the fishing areas.
Sampling. The presently reported study was carried out in the western Black Sea, especially in the important region where the sandy substrate is dense and baby clam beds can be found. This study was carried out considering the reproduction season of Rapana venosa, because during the reproduction period, this species migrates toward the coasts (
Estimation of growth parameters and mortality rates. The estimation of length–weight relations (LWRs) was calculated according to the
W = aLb
This formula can be expressed in the linearized form as
log W = log a + b log L
where W is the total body weight in grams, L is the total body length in cm, b is the slope, and a is the intercept. The growth parameters of von Bertalanffy were estimated according to
Lt = L∞(1 − e−K (t − t0))
where Lt is the length at time t, L∞ is the theoretical asymptotic length, K is the growth coefficient and t0 is the theoretical age at length zero. The values of L∞ and K were calculated in the ELEFAN in the TropFishR version 1.6.3 (
Log (−t0) = −0.3922 − 0.2752 log (L∞) − 1.038 log (K)
Natural mortality (M) was calculated using Then’s growth formula empirical equation (
M = 4.118K0.73 L∞−0.33
where M is natural mortality, L∞ and K parameters of von Bertalanffy equation.
Total mortality (Z) was estimated utilizing a catch curve. Fishing mortality (F) was determined as
Z = F + M
while exploitation rate (E) was calculated as suggested by
E = F × Z–1
Estimation of stock size. The swept area method was used to estimate rapa whelk stock size in the whole study region and separately for individual sub-regions. In this study, data were collected annually from the same 174 stations, selected to best represent the continental shelf of the western region of Türkiye (Table
Area covered by the beds of Rapana venosa in the mid-southern part of the Black Sea, according to sub-areas and number of hauls.
Sub-area | Depth [m] | Number of hauls | Area [km2] |
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Cide | 15–20 | 13 | 13.75 |
10–15 | 13 | 13.09 | |
5–10 | 12 | 17.29 | |
0–5 | 11 | 8.94 | |
Inebolu | 15–20 | 15 | 24.24 |
10–15 | 12 | 25.42 | |
5–10 | 9 | 56.65 | |
0–5 | 5 | 21.5 | |
Türkeli | 15–20 | 12 | 35.44 |
10–15 | 13 | 28.26 | |
5–10 | 10 | 16.15 | |
0–5 | 11 | 12.97 | |
Ayancık | 15–20 | 6 | 15.44 |
10–15 | 6 | 10.96 | |
5–10 | 8 | 7.22 | |
0–5 | 6 | 6.62 | |
Sarıkum | 15–20 | 3 | 2.25 |
10–15 | 3 | 1.91 | |
5–10 | 3 | 1.16 | |
0–5 | 3 | 0.82 |
The swept area formula proposed by
A S = D × LHR × X2
where: AS is the swept area [km2], X2 is a fraction expressing the width of the swept area, D = towing distance, and LHR is the length of the head rope. The towing distance (D) was estimated in units of km2 (1 nautical mile = 1.852 km), by
Lat1 is the latitude at the start of the haul (degrees) and Lat2 is the latitude at the end of the haul (degrees). Similarly, Lon1 is the longitude at the start of the haul (degrees) and Lon2 is the longitude at the end of the haul (degrees).
The catch per unit area (CA) [kg ∙ km−2] was determined as
where CW is the weight of rapa whelk collected in one sampling and AS is the area swept in one haul [km2].
The mean biomass per unit area (B̅) [kg ∙ km−2], was estimated as follows.
where X1 is the coefficient of catch. The hydraulic dredge coefficient of fishing has been accepted as “1”. This reflects the dredge efficiency and is considered to have collected all samples during towing.
The total biomass (BT) [kg ∙ km−2] was estimated as
where AT is km2 total size of area under investigation.
Analysis of Variance (ANOVA) was used to test differences for estimated stock sizes among sub-regions, depths, and years. ArcGIS software package was used for rapa whelk distribution biomass. Data were analyzed in R (
Growth and mortality. The mean TL of rapa whelk, Rapana venosa, in 2011 was 47.43 ± 0.36 mm and the mean TW was 24.20 ± 0.66 g (Figs
The results of growth parameter analysis showed that rapa whelk can reach an asymptotic length (L∞) of 121.78 mm, with a mean K of 0.246 per year and the age of t0 at −0.33 years. Lt can be estimated by obtaining the parameter values of K, L∞, and t0 (Fig.
Uploaded raw (A) and restructured (B) length-frequency data of Rapana venosa from the mid-southern part of the Black Sea with overlaid von Bertalanffy growth (VBG) curves fitted by ELEFAN with a genetic algorithm. Ideally, the growth curves overlay with length bins with a high count or high positive value (blue shading) for raw (A) and restructured (B) data, respectively.
The logarithm of catch per length interval of Rapana venosa from the mid-southern part of the Black Sea against relative age. Blue points correspond to points used in the regression analysis (blue line) of the catch curve for the estimation of total mortality (Z), which corresponds to the slope of the displayed regression line. C is the number of specimens caught within a length class, dt is time needed by rapa whelk to grow through a length class].
Stock distribution and structure. Results showed that R. venosa biomass increased threefold from 2011 to 2012 and reached 1062.41 tonnes during the sampling period. In 2011, the highest stock size was estimated in Inebolu, while the lowest was in Sarıkum. In 2012, it was determined that the biomass was higher in the Cide region (Table
Estimated biomass of Rapana venosa from the mid-southern part of the Black Sea.
Year | Sub-area | Biomass [tonnes] | Confidence interval [tonnes] |
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2011 | Cide | 76.24 | ±73.55 |
2011 | Inebolu | 134.24 | ±203.02 |
2011 | Türkeli | 98.58 | ±58.67 |
2011 | Ayancık | 37.66 | ±37.16 |
2011 | Sarıkum | 17.18 | ±22.99 |
Total | 363.92 | ±395.39 | |
2012 | Cide | 330.62 | ±31.83 |
2012 | Inebolu | 140.89 | ±65.79 |
2012 | Türkeli | 268.89 | ±230.46 |
2012 | Ayancık | 301.64 | ±332.23 |
2012 | Sarıkum | 20.36 | ±37.73 |
Total | 1062.41 | ±984.51 |
Estimated biomass values showed significant differences between the years. However, no significant differences were found among sub-regions and depths for overall results (Table
Box plots of estimated stock size of Rapana venosa with 95% CI according to sub-region, and years in the mid-southern part of the Black Sea. Horizontal lines in the boxes represent the mean values, and whiskers represent the standard deviations. Error bars represent 95% confidence intervals.
ANOVA table for differences in estimated stock biomass of Rapana venosa from the mid-southern part of the Black Sea among sub-regions, depth, and years.
Factor | Df | SS | MS | F | P |
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All | |||||
Sub-region | 4 | 10743.98 | 2685.99 | 2.09 | 0.11 |
Depth | 3 | 3039.35 | 1013.12 | 0.79 | 0.51 |
Year | 1 | 12201.05 | 12201.05 | 10.84 | 0.00 |
2011 | |||||
Sub-region | 4 | 2197.34 | 549.34 | 1.61 | 0.22 |
Depth | 3 | 254.05 | 84.68 | 0.19 | 0.90 |
2012 | |||||
Sub-region | 4 | 16775.73 | 4193.93 | 3.37 | 0.04 |
Depth | 3 | 4646.76 | 1548.92 | 0.80 | 0.51 |
LWR changes depending on many factors such as access to food, nutritional habits, season, gonad development, and reproduction time (
Comparison of length–weight relations of Rapana venosa from various studies carried out in the Black Sea.
Region | a | b | R 2 | Year | Reference |
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East Black Sea | 0.0004 | 2.798 | 1991 |
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Bulgaria | 0.0005 | 2.813 |
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East Black Sea | 0.0001 | 3.146 | Sağlam, unpublished | ||
Romania | 0.0002 | 2.568 | Micu et al. 2008 | ||
East Black Sea | 0.0006 | 2.712 | 2007 | Saglam et al. 2008 | |
East Black Sea | 0.00009 | 3.145 |
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Trabzon (EBS) | 0.0004 | 2.826 | 0.89 | 2007 |
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Terme (EBS) | 0.0006 | 2.735 | 0.84 | 2007 |
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Samsun (EBS) | 0.0011 | 2.556 | 0.85 | 2007 |
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Yakakent (EBS) | 0.0076 | 2.728 | 0.91 | 2015 |
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Türkiye | 0.0002 | 2.876 | 0.98 | 2016 |
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Türkiye | 0.0002 | 2.9868 | 2017 |
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Türkiye | 0.0001 | 3.085 | 2018 |
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Türkiye | 0.0001 | 3.104 | 2019 |
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Türkiye | 0.0002 | 2.949 | 2020 |
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Türkiye | 0.0002 | 2.981 | 2021 |
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Türkiye | 0.0002 | 2.921 | 2022 |
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Ukraine | 0.334 | 2.725 | 2017 |
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Ukraine | 0.4304 | 2.533 | 2018 |
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Ukraine | 0.2328 | 2.893 | 2019 |
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Ukraine | 0.469 | 2.568 | 2020 |
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Ukraine | 0.309 | 2.756 | 2021 |
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Bulgaria | 0.16 | 2.99 | 2017 |
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Bulgaria | 0.1642 | 2.99 | 2018 |
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Bulgaria | 0.0005 | 2.726 | 2021 |
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Bulgaria | 0.00024 | 2.915 | 2022 |
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West Black Sea | 0.0004 | 2.824 | 0.89 | 2011 | Presently reported study |
West Black Sea | 0.0001 | 3.089 | 0.94 | 2012 | Presently reported study |
The b value of R. venosa in 2012 was 3.08. These findings are similar to the values found by
Considering sub-regions, the R. venosa population in Cide, Türkeli, and Ayancık increased significantly in one year, related to the increase in C. gallina in abundance. Inebolu sub-region was an important distribution area of R. venosa, and estimated stock sizes are the highest. Additionally, the amount of C. gallina, its main prey, was high (62 000 tonnes) in this area (
In conclusion, many studies on the Rapana venosa stocks have settled along the Black Sea coastline and become an important economic contribution for fishers over the past 30 years. Some researchers have suggested that this species should be removed entirely owing to its substantial harmful effects (
Additionally, the rapa whelk has become a component of the Black Sea ecosystem. Therefore, there is a need for clear outcomes to be discussed and actions to be implemented to monitor the fisheries of this species. This includes creating and monitoring management scenarios or taking the necessary measures to eliminate this species from the ecosystem owing to the damage it causes to the habitat.
This study was supported by the General Directorate of Agricultural Research and Policies (GDAR), Ankara, Türkiye (Project no:TAGEM/HAYSÜD/2011/09/02/05). This study was carried out within the Central Fisheries Research Institute.