Marine litter is one of the main sources of anthropogenic pollution in the marine ecosystem, with plastic representing a global threat. This paper aims to assess the spatial distribution of plastic macro-litter on the seafloor, identifying accumulation hotspots at a northern Mediterranean scale. Density indices (items km–2) from the MEDITS trawl surveys (years 2013-2015) were modelled by generalized additive models using a Delta-type approach and several covariates: latitude, longitude, depth, seafloor slope, surface oceanographic currents and distances from main ports. To set thresholds for the identification of accumulation areas, the percentiles (85th, 90th and 95th) of the plastic spatial density distribution were computed on the raster data. In the northern Mediterranean marine macro-litter was widespread (90.13% of the 1279 surveyed stations), with plastic by far the most recurrent category. The prediction map of the plastic density highlighted accumulation areas (85th, 90th and 95th percentiles of the distribution, respectively, corresponding to 147, 196 and 316 items km–2) in the Gulf of Lions, eastern Corsica, the eastern Adriatic Sea, the Argo-Saronic region and waters around southern Cyprus. Maximum densities were predicted in correspondence to the shallower depths and in proximity to populated areas (distance from the ports). Surface currents and local water circulation with cyclonic and anticyclonic eddies were identified as drivers likely facilitating the sinking to the bottoms of floating debris
La basura marina es una de las principales fuentes de contaminación antropogénica en el ecosistema marino representando el plástico una amenaza global. El objetivo de este trabajo es evaluar la distribución espacial de las macro-basuras plásticas en el fondo marino, identificando los hotspots de acumulación en el Mediterráneo norte. Los índices de densidad (ítems km–2), procedentes de las campañas de arrastre MEDITS (años: 2013-2015), fueron modelados mediante Modelos Aditivos Generalizados, utilizando un enfoque de tipo delta y varias covariables: latitud, longitud, profundidad, pendiente del fondo marino, corrientes marinas y distancias desde los principales puertos. Para establecer los umbrales para la identificación de áreas de acumulación, se calcularon los percentiles (85-90-95) de la distribución espacial de densidad de plásticos en los datos ráster. En el Mediterráneo norte, la macro-basura marina estaba muy extendida (90.13% de las 1279 estaciones muestreadas), siendo el plástico, con diferencia, la categoría más recurrente. El mapa de predicción de la densidad de plásticos resaltó las áreas de acumulación (percentiles 85, 90 y 95 de la distribución, respectivamente, correspondientes a: 147, 196 y 316 ítems km–2), localizadas en el Golfo de León, Córcega oriental, Mar Adriático oriental, región Argo-Saronic y aguas que rodean el sur de Chipre. Se predijeron las densidades máximas a menor profundidad y cercanas a zonas pobladas (distancia desde los puertos). Las corrientes superficiales y la circulación local del agua, con giros ciclónicos y anticiclónicos, se identificaron como factores que favorecen el hundimiento de las basuras flotantes.
Humans impact the marine environment in several ways, and marine litter has been considered one of the main issues of anthropogenic pollution in the marine ecosystem in the last few decades (
Waste production varies between countries and has been detected worldwide in all the marine habitats (
Marine litter is consequently becoming a primary political and societal concern in many countries worldwide, prompting several major policy actions by international organizations. In 2015 the leaders of G7 recognized that marine litter, in particular plastic, represents a global challenge and stressed the need to address the identification and assessment of land and sea-based sources, removal actions, and education and research development (
The Circular Economy Action Package (
The Convention of the United Nations on the Law of the Sea (UNCLOS) agreed upon the legal framework within which all activities in the oceans and seas must be carried out (
– the trend in the number/amount of marine litter deposited on the coast;
– the trend in the number/amount of marine litter on the water surface and the seafloor,
and one candidate indicator of marine litter impact,
– trends in the amount of litter ingested by or entangling marine organisms, especially marine mammals, birds, turtles and sharks (
The main purpose was to facilitate the implementation of the Barcelona Convention and monitor related provisions to assess GES. The Meeting of the Contracting Parties in 2012 adopted ecological objectives, describing the desired results to be pursued to reach GES. In 2016 the Regional Cooperation Platform on Marine Litter in the Mediterranean was established at the invitation of the UN Environment/Mediterranean Action Plan (MAP) -Barcelona Convention Secretariat (
Recently several papers have focused on a numerical circulation model at Mediterranean (
There is thus an increasing need to model the distribution of the marine macro-litter on the seafloor in order to provide information useful for identifying accumulation areas, and to prompt actions aimed at achieving effective management in an ecosystem conservation-oriented planning.
In the Mediterranean Sea only a few studies conducted in the northwestern basin have used explicit spatial model analysis to obtain distribution maps of marine litter on the seafloor (
This paper therefore aims to model the distribution of marine litter on the seafloor and to identify hotspots, particularly of plastic, through a spatial analysis at a northern Mediterranean scale, using generalized additive models (GAMs) applied to the data collected in 18 geographical sub-areas (GSA;
Covariates (geographical descriptors and potential sources of litter) were used to describe their effects on the distribution of marine litter on the seafloor and accumulation areas: latitude and longitude, depth, seafloor slope, surface oceanographic currents, marine traffic and distance from main rivers and ports.
Marine macro-litter data were collected from the MEDITS bottom trawl survey using a standardized common protocol (
A total of 1279 hauls carried out yearly were distributed over the depth range 10-800 m and allocated to five bathymetrical strata (details on the stratification scheme are in the
To obtain density indices (items km–2), the number of items collected per litter category was standardized to the km2 according to the swept area method. Given that the time series was still short, a mean value of the density indices per haul was calculated among the available years (2013-2015) for all the GSAs. From GSAs 1, 2 and 5 only mass data (kg km–2) were available and could not be used in the model, which was set using observations on the number of items, because the collection of this type of data has been mandatory since the beginning in the survey protocol. However, mass data of GSAs 1, 2 and 5 were used to describe the occurrence of litter categories.
An exploratory analysis was first conducted to assess the litter categories recurrent in the study areas. Hence, the frequency of occurrence of each litter category was computed. Considering the large dominance of plastic in marine macro-litters (see
To model the macro-litter distribution pattern, georeferenced informative layers were collated (
– Geographical and geomorphological characteristics (latitude, longitude, depth and bottom slope).
– Euclidean distance from the major harbours, as many studies report the highest litter densities close to the most important port cities (
– Euclidean distances from the most important river outlets, considering that considerable quantities of litter can be introduced in the marine environment by transportation from water courses (
– Ship traffic density (routes/23 km2/year) from the marine traffic portal, as marine traffic is also reported to be a mechanism likely linked to marine litter inputs (
– Mean annual surface current velocity, both northing (cury) and easting (curx) components of sea water velocity, as the current is an important driver influencing the movement and accumulation of floating debris (
Min. | 1st qu. | Median | Mean | 3rd qu. | Max. | |
---|---|---|---|---|---|---|
Longitude (degrees) | –0.99 | 12.57 | 15.63 | 16.69 | 24.12 | 34.86 |
Latitude (degrees) | 34.39 | 37.42 | 39.76 | 39.81 | 42.22 | 45.76 |
Depth (m) | 0.00 | 75.40 | 151.20 | 255.10 | 424.00 | 800.00 |
Slope (degrees) | 0 | 0.27 | 0.81 | 1.61 | 2.05 | 48.85 |
Traffic (routes/23 km2/year) | 0 | 0 | 13523.1 | 12663.5 | 14133.3 | 42400 |
Distance from the rivers (km) | 0 | 83.6 | 138.1 | 155.50 | 202.50 | 592.10 |
Distance from the ports (km) | 0 | 40.31 | 63.73 | 68.73 | 92.63 | 228.17 |
curx (m s–1) | –0.22 | –0.017 | –0.0006 | 0.003 | 0.02 | 0.87 |
cury (m s–1) | –0.29 | –0.03 | –0.006 | –0.01 | 0.01 | 0.24 |
Regarding geographical and geomorphological characteristics,
The main descriptive characteristics of the considered covariates are reported in
The marine macro-litter density data were firstly tested for normality of distribution using the Shapiro-Wilk normality test (
The multivariate analysis was based on the use of GAMs, a nonparametric extension of GLMs that includes smooth functions (a piecewise polynomial curve) of explanatory variables (
where
A step-wise procedure was used to generate GAMs, using a one-dimensional smoother for each covariate and two-dimensional smoothers for geographic coordinates and current components. Collinearity between the covariates was analysed by means of variance inflation factor (VIF) values (
In the forward inclusion approach (
GAMs were fitted using the mgcv package (
In the northern Mediterranean Sea marine macro-litter is widely distributed and was found at 90.13% of the 1279 surveyed stations. In the Gulf of Lions (GSA 7), eastern Corsica (GSA 8), the Ligurian and northern Tyrrhenian seas (GSA 9) and Crete (GSA 23), 100% of the hauls were positive to bottom macro-litter. Overall, plastic is by far the most recurrent macro-litter category, with a frequency of occurrence ranging from around 58% in Sardinian waters (GSA 11) to about 99% in the Gulf of Lions (GSA 7). In most of the GSAs the frequency of occurrence is higher than 90%. Secondarily, macro-litter categories such as metal (L3), clothes/natural fibres (L4) and glass/ceramic/concrete (L5) had a frequency of occurrence ranging from 20% to 30% (
Overall, density indices (
A bubble plot of the plastic density indices by haul (items km–2) is presented in
The main results of the tested models are reported in
log(μi)~ α +f1(Loni, Lati) + f2(curxi, curyi) + f3(depthi) + f4(slopei)+ f5(portsi) + ε | (1) |
logit(μi)~ β +g1(Loni, Lati) + g2(curxi, curyi) + g3(depthi) + g4(slopei) + g5(ports) + ε | (2) |
The binomial model (2) described 20.5% of the explained deviance in presence-absence data. All the variables used in the model had a significant effect on the probability of macro-litter presence (
N | Models | R2 | % dev. | GCV | AIC |
---|---|---|---|---|---|
1 | marine litter ~ s(X, Y) | 0.300 | 30.0% | 9910 | 13075 |
2 | marine litter ~ s(depth) | 0.001 | 0.1% | 13111 | 13404 |
3 | marine litter ~ s(slope) | 0.009 | 1.3% | 13085 | 13399 |
4 | marine litter ~ s(traffic) | 0.002 | 0.3% | 13105 | 13403 |
5 | marine litter ~ s(river) | 0.046 | 5.0% | 12603 | 13358 |
6 | marine litter ~ s(ports) | 0.000 | 0.0% | 13114 | 13405 |
7 | marine litter ~ s(curx, cury) | 0.071 | 8.7% | 12564 | 13343 |
8 | marine litter ~ s(X, Y)+s(curx, cury) | 0.440 | 45.0% | 8140 | 12845 |
9 | marine litter ~ s(X, Y)+s(depth) | 0.430 | 40.4% | 8599 | 12914 |
10 | marine litter ~ s(X, Y)+s(slope) | 0.339 | 32.8% | 9660 | 13042 |
11 | marine litter ~ s(X, Y)+s(river) | 0.310 | 32.4% | 9665 | 13044 |
12 | marine litter ~ s(X, Y)+s(traffic) | 0.284 | 28.2% | 10124 | 13099 |
13 | marine litter ~ s(X, Y)+s(ports) | 0.300 | 30.0% | 9910 | 13075 |
14 | marine litter ~ s(X, Y)+s(curx, cury)+s(depth) | 0.507 | 51.2% | 7393 | 12732 |
15 | marine litter ~ s(X, Y)+s(curx, cury)+s(slope) | 0.478 | 48.8% | 7758 | 12785 |
16 | marine litter ~ s(X, Y)+s(curx, cury)+s(traffic) | 0.456 | 46.8% | 8045 | 12825 |
17 | marine litter ~ s(X, Y)+s(curx, cury)+s(ports) | 0.440 | 45.0% | 8140 | 12845 |
18 | marine litter ~ s(X, Y)+s(curx, cury)+s(river) | 0.462 | 47.4% | 7950 | 12812 |
19 | marine litter ~ s(X, Y)+s(curx, cury)+s(depth)+s(slope) | 0.521 | 53.0% | 7270 | 12706 |
20 | marine litter ~ s(X, Y)+s(curx, cury)+s(depth)+s(river) | 0.520 | 52.9% | 7277 | 12707 |
21 | marine litter ~ s(X, Y)+s(curx, cury)+s(depth)+s(traffic) | 0.524 | 53.0% | 7289 | 12708 |
22 | marine litter ~ s(X, Y)+s(curx, cury)+s(depth)+s(ports) | 0.507 | 51.2% | 7393 | 12732 |
23 | marine litter ~ s(X, Y)+s(curx, cury)+s(depth)+s(slope)+s(ports) | 0.523 | 53.3% | 7266 | 12703 |
24 | marine litter ~ s(X, Y)+s(curx, cury)+s(depth)+s(slope)+s(traffic) | 0.519 | 52.6% | 7295 | 12711 |
25 | 0.516 | 52.3% | 7322 | 12717 | |
26 | 0.524 | 53.4% | 7248 | 12701 |
Smooth term prediction for each of the four smooth terms used in the GAM and in the presence-absence GAM are reported in
Min. | 1st qu. | Median | Mean | 3rd qu. | Max. | |
---|---|---|---|---|---|---|
observations | 0 | 21.48 | 45.58 | 79.19 | 92.89 | 1283.94 |
predictions | 1.75E-22 | 11.36 | 46.19 | 70.49 | 99.50 | 1110.37 |
residuals | –226.80 | –32.56 | 6.32 | 8.71 | 39.35 | 453.30 |
This study gives evidence of widespread presence of marine macro-litter at a northern Mediterranean geographical scale, occurring at 90% of the 1279 examined stations sampled yearly during the MEDITS survey in the period 2013-2015. This occurrence ranged from about 69% in Sardinian waters (GSA 11) to 100% in the Gulf of Lions, eastern Corsica, the Ligurian and northern Tyrrhenian seas, and waters around Crete (respectively GSAs 7, 8, 9 and 23). Plastic was the most abundant litter category sinking on the seafloor, as stressed in previous studies (e.g.
Among marine litter materials, plastic is surely the most resistant to biodegradation and the most easily transportable by wind and current. For the moment little or no information is available regarding the lifetime of the synthetic polymers in the environment, and only a few studies have examined the lifetime of plastic items lying on the seafloor of the Mediterranean (
On average, depths ranging from 50 m to approximately the border of the continental shelf (200 m) were the most affected by the presence of plastic, though exceptions were observed in deeper waters. For example, in eastern Corsica, values were higher on seafloors deeper than 200 m and especially between 500 and 800 m depth. This is not surprising given that the variability within a GSA was sometimes higher than that between GSAs, indicating a contagious distribution of plastic on the seafloor, but also the fact that several factors may affect this distribution (e.g.
The objective of identifying hotspots of plastic accumulation was achieved using GAM modelling and testing geographical, environmental and anthropogenic variables, to highlight the most important drivers influencing accumulation in the sinking areas. A wide range of mechanisms is potentially responsible for litter accumulation in the marine environment. Highly populated centres are the potential primary origin of marine macro-litter, as wastes are produced by direct disposal of domestic or tourism infrastructure activities to the sea (
However, the model proposed here recognizes that both bottom depth and slope are important drivers for the retention of plastic macro-litter. Looking at the density model smoothing terms, the depth effect shows the presence of four local maxima. The first corresponds to shallower waters, while the others are at aproximatively 200, 400 and 600 m depth. The maximum corresponding to the shallower depths is likely linked to the proximity to populated areas and human activities. This also appears quite evident from the effect of the distance from ports, which shows the highest levels of accumulation in the proximity of major port cities, where litter disposal very likely has the highest rates, such as in the areas of Valencia (GSA 6), Marseille (GSA 7) and the Argo-Saronic region, where the most important Greek port is located (
The slope has an interesting effect, and the accumulation is quite stable at lower slope steepness. However, when the slope increases and the litter cannot be retained by the seafloor, the accumulation is lower.
The association of topographic and hydrodynamics components is also a pivotal factor influencing the dispersion or accumulation of marine macro-litter. Weak currents, for example, may facilitate deposition on shores, bays and lagoons more than in the open ocean (e.g.
The GAM modelling highlighted the presence of hotspots of accumulation on the bottoms in the Strait of Gibraltar, the Gulf of Valencia, the Gulf of Lions, eastern Corsica, the eastern side of central-southern Adriatic Sea, the Argo-Saronic region, the eastern Aegean near the coasts of Asia Minor and the southern side of Cyprus. By analysing the geographic smooth term prediction of the model and mapping results, it is possible to identify the position of hotspots of plastic accumulation, mainly localized in the western and eastern parts of the Mediterranean, while the central part of the basin appears less affected. However, it should be considered that no data from the western part of the northern Adriatic Sea were available for the analysis.
The model proposed in this paper recognized the surface current effect as another relevant factor responsible for the dispersion of marine macro-litter in marine environments and influencing the formation of hotspots of plastic accumulation. The Atlantic current (AW) enters the Mediterranean Sea through the Strait of Gibraltar, also transporting floating plastic debris in the western Alborán following the Western Anticyclonic Gyre (
The main circulation in the Adriatic Sea is guaranted by the warm waters that move northward along the eastern coasts and the northern Adriatic current that moves in the opposite direction, conveying the fresh waters of the Po river towards the western-middle Adriatic current (
The topografy of the eastern basin of the Mediterranean Sea has a crucial role in influencing one of the most important components of the water movements in this area: the Mid-Mediterranean Jet (MMJ) of the Levantine basin (
Considering the floating macro-litter,
The most important risk linked to the presence of plastic for living organisms is that of physical injuries, especially caused by ingestion (
Policy strategies to contrast marine litter, such as incentivized responsible waste management, the Circular Economy Action Package, replacing non-biodegradable plastics with other biodegradable materials and schemes for cleaning, sustainable consumption and production, and extended producer responsibility need information on the characterization, quantification and location of existing amounts of plastic marine litter. These strategies also require regular monitoring of the marine environment against agreed threshold values (currently agreed in the Mediterranean in the framework of the Barcelona Convention, while a similar initiative is ongoing at a European Union level) to verify the effectiveness of the measures.
Regularly collecting data on the real presence and accumulation of macro-litter on the seafloor is a pivotal point. Different kinds of sampling methods have been reported in literature for the characterization and assessment of marine litter on the seafloor.
So far, modelling marine litter distribution and accumulation at a Mediterranean (
The GAM modelling approach used here allowed us to assess, through multiple predictors, the contemporary effects of explanatory variables on the spatial distribution of plastic macro-litter and to localize, for the first time at a wide geographical scale, hotspots of plastic accumulation associated with specific density values (items per km2). This use of GAM modelling is likely only the starting point for further studies aimed at giving insight to the distribution and accumulation of other litter categories and sub-categories.
The MEDITS surveys have been carried out within the Data Collection Framework. The European Commission and Member States of the Mediterranean countries are thankfully acknowledged. We are also grateful to all the colleagues who have spent effort and time collecting and classifying the macro-litter data during the MEDITS surveys.