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Lost in the river: the plastic vegetation index for detecting plastics within vegetation
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Plastics are a well-known problem that accumulates in the environment causing detrimental effects on ecosystems. Macroplastics in rivers are only recently studied, with most studies focusing on the transport of plastics to the sea. However, most plastics are retained in the fluvial system. To date, only abiotic factors have been considered in the transport process, but recently vegetation has proven to block plastics from having a pivotal role in influencing plastic riverine drift. Given that little is known on the biotic component affecting riverine plastic transport, we aimed at investigating further on (i) the three-dimensionality structure of riparian vegetation in trapping plastics along watercourses and (ii) to develop a vegetation index to describe vegetation structure and to understand the plastic entrapment service provided by plants. To do so, we sampled field data from central Italy rivers along the three riverine zones considering riparian vegetation in relation to river width. Data on plastics within vegetation has been recollected. Also, data on plant structures (i.e. the number of individuals and the number and height of branches per species) was sampled and then used to develop the 3D vegetation index (i.e. 3D Vegetation Index, 3DVI) considering the tridimensionality and diversity index. As result, plastics occurring in vegetation were significantly related to vegetation structure with the 3DVI correlated with the number of plastics (R2 = 0.36, p = 0.0086, Y = 0.007157*X + 2.562). Furthermore, the most dense and diverse community block more plastics. Considering different vegetation heights in all the rivers, there is a significant linear regression between the 3DVI in vegetation branches (0.5<r<2.0 m, and r>2.0 m, respectively R2 = 0.38, p = 0.007, Y = 0.007662*X + 2.711 and R2 = 0.45, p = 0.0023, Y = 0.2522*X + 2.696). With regards to the three riverine zones, only in the lower river zone there was a significant regression between 3DVI and plastics in vegetation (R2 = 0.94, p = 0.001, Y = 108.0*X-143.7). Biotic factors (i.e. vegetation structure) most correlate to the occurrence of plastics in vegetation driving the plastic entrapment process more than the environmental abiotic factors (i.e. hydrology). Overall, we developed for the first time a vegetation index to describe the structure and diversity of the plant community related to the plastic entrapment service. The higher the 3DVI value, the more complex the vegetation (i.e. characterised by a lot of individuals and branches). We emphasized that plant structures are important variables for understanding the entrapment efficiency of macrolitter, highlighting that the complexity of vegetation structure is key for the trapping net effect. As vegetation retain plastics efficiently in all the zones providing us the ecosystem service of trapping macrolitter, the 3DVI could be applied for future solution to plastic pollution – also detecting plastic hotspot areas for mitigation and clean-up activities.
Title: Lost in the river: the plastic vegetation index for detecting plastics within vegetation
Description:
Plastics are a well-known problem that accumulates in the environment causing detrimental effects on ecosystems.
Macroplastics in rivers are only recently studied, with most studies focusing on the transport of plastics to the sea.
However, most plastics are retained in the fluvial system.
To date, only abiotic factors have been considered in the transport process, but recently vegetation has proven to block plastics from having a pivotal role in influencing plastic riverine drift.
Given that little is known on the biotic component affecting riverine plastic transport, we aimed at investigating further on (i) the three-dimensionality structure of riparian vegetation in trapping plastics along watercourses and (ii) to develop a vegetation index to describe vegetation structure and to understand the plastic entrapment service provided by plants.
To do so, we sampled field data from central Italy rivers along the three riverine zones considering riparian vegetation in relation to river width.
Data on plastics within vegetation has been recollected.
Also, data on plant structures (i.
e.
the number of individuals and the number and height of branches per species) was sampled and then used to develop the 3D vegetation index (i.
e.
3D Vegetation Index, 3DVI) considering the tridimensionality and diversity index.
As result, plastics occurring in vegetation were significantly related to vegetation structure with the 3DVI correlated with the number of plastics (R2 = 0.
36, p = 0.
0086, Y = 0.
007157*X + 2.
562).
Furthermore, the most dense and diverse community block more plastics.
Considering different vegetation heights in all the rivers, there is a significant linear regression between the 3DVI in vegetation branches (0.
5<r<2.
0 m, and r>2.
0 m, respectively R2 = 0.
38, p = 0.
007, Y = 0.
007662*X + 2.
711 and R2 = 0.
45, p = 0.
0023, Y = 0.
2522*X + 2.
696).
With regards to the three riverine zones, only in the lower river zone there was a significant regression between 3DVI and plastics in vegetation (R2 = 0.
94, p = 0.
001, Y = 108.
0*X-143.
7).
Biotic factors (i.
e.
vegetation structure) most correlate to the occurrence of plastics in vegetation driving the plastic entrapment process more than the environmental abiotic factors (i.
e.
hydrology).
Overall, we developed for the first time a vegetation index to describe the structure and diversity of the plant community related to the plastic entrapment service.
The higher the 3DVI value, the more complex the vegetation (i.
e.
characterised by a lot of individuals and branches).
We emphasized that plant structures are important variables for understanding the entrapment efficiency of macrolitter, highlighting that the complexity of vegetation structure is key for the trapping net effect.
As vegetation retain plastics efficiently in all the zones providing us the ecosystem service of trapping macrolitter, the 3DVI could be applied for future solution to plastic pollution – also detecting plastic hotspot areas for mitigation and clean-up activities.
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