Dataset Information

A nationwide assessment of plastic pollution in the Danish realm using citizen science.

ABSTRACT: Plastic pollution is considered one of today's major environmental problems. Current land-based monitoring programs typically rely on beach litter data and seldom include plastic pollution further inland. We initiated a citizen science project known as the Mass Experiment inviting schools throughout The Danish Realm (Denmark, Greenland and the Faeroe Islands) to collect litter samples of and document plastic pollution in 8 different nature types. In total approximately 57,000 students (6-19 years) collected 374,082 plastic items in 94 out of 98 Danish municipalities over three weeks during fall 2019. The Mass Experiment was the first scientific survey of plastic litter to cover an entire country. Here we show how citizen science, conducted by students, can be used to fill important knowledge gaps in plastic pollution research, increase public awareness, establish large scale clean-up activities and subsequently provide information to political decision-makers aiming for a more sustainable future.

SUBMITTER: Syberg K

PROVIDER: S-EPMC7576202 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

A nationwide assessment of plastic pollution in the Danish realm using citizen science.

Syberg Kristian K Palmqvist Annemette A Khan Farhan R FR Strand Jakob J Vollertsen Jes J Clausen Lauge Peter Westergaard LPW Feld Louise L Hartmann Nanna B NB Oturai Nikoline N Møller Søren S Nielsen Torkel Gissel TG Shashoua Yvonne Y Hansen Steffen Foss SF

Scientific reports 20201020 1

Plastic pollution is considered one of today's major environmental problems. Current land-based monitoring programs typically rely on beach litter data and seldom include plastic pollution further inland. We initiated a citizen science project known as the Mass Experiment inviting schools throughout The Danish Realm (Denmark, Greenland and the Faeroe Islands) to collect litter samples of and document plastic pollution in 8 different nature types. In total approximately 57,000 students (6-19 year ...[more]

PMID: 33082484

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Project description:Species distribution models (SDM) have been increasingly developed in recent years, but their validity is questioned. Their assessment can be improved by the use of independent data, but this can be difficult to obtain and prohibitive to collect. Standardized data from citizen science may be used to establish external evaluation datasets and to improve SDM validation and applicability.We used opportunistic presence-only data along with presence-absence data from a standardized citizen science program to establish and assess habitat suitability maps for 9 species of amphibian in western France. We assessed Generalized Additive and Random Forest Models' performance by (1) cross-validation using 30% of the opportunistic dataset used to calibrate the model or (2) external validation using different independent datasets derived from citizen science monitoring. We tested the effects of applying different combinations of filters to the citizen data and of complementing it with additional standardized fieldwork.Cross-validation with an internal evaluation dataset resulted in higher AUC (Area Under the receiver operating Curve) than external evaluation causing overestimation of model accuracy and did not select the same models; models integrating sampling effort performed better with external validation. AUC, specificity, and sensitivity of models calculated with different filtered external datasets differed for some species. However, for most species, complementary fieldwork was not necessary to obtain coherent results, as long as the citizen science data were strongly filtered.Since external validation methods using independent data are considered more robust, filtering data from citizen sciences may make a valuable contribution to the assessment of SDM. Limited complementary fieldwork with volunteer's participation to complete ecological gradients may also possibly enhance citizen involvement and lead to better use of SDM in decision processes for nature conservation.

Dataset Information

A nationwide assessment of plastic pollution in the Danish realm using citizen science.

Publications

A nationwide assessment of plastic pollution in the Danish realm using citizen science.

Similar Datasets

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