Quantifying microplastic pollution on sandy beaches: the conundrum of large sample variability and spatial heterogeneity

Despite the environmental risks posed by microplastic pollution, there are presently few standardized protocols for monitoring these materials within marine and coastal habitats. We provide a robust comparison of methods for sampling microplastics on sandy beaches using pellets as a model and attempt to define a framework for reliable standing stock estimation. We performed multiple comparisons to determine: (1) the optimal size of sampling equipment, (2) the depth to which samples should be obtained, (3) the optimal sample resolution for cross-shore transects, and (4) the number of transects required to yield reproducible along-shore estimates across the entire sections of a beach. Results affirmed that the use of a manual auger with a 20-cm diameter yielded the best compromise between reproducibility (i.e., standard deviation) and sampling/processing time. Secondly, we suggest that sediments should be profiled to a depth of at least 1 m to fully assess the depth distribution of pellets. Thirdly, although sample resolution did not have major consequence for overall density estimates, using 7-m intervals provides an optimal balance between precision (SD) and effort (total sampling time). Finally, and perhaps most importantly, comparing the minimum detectable difference yielded by different numbers of transects along a given section of beach suggests that estimating absolute particle density is probably unviable for most systems and that monitoring might be better accomplished through hierarchical or time series sampling efforts. Overall, while our study provides practical information that can improve sampling efforts, the heterogeneous nature of microplastic pollution poses a major conundrum to reproducible monitoring and management of this significant and growing problem.

Mara Fisner, Alessandra P. Majer, Danilo Balthazar-Silva, Daniel Gorman, Alexander Turra, Environmental Science and Pollution Research, pp 1–9, First online, 11 April 2017

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