We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Akaike Information Criterion on small sample size (AICc) for competing models ranked from most to least parsimonious with area, site, and mesh size as independent variables to explain the sum of microplastic particles combined and subsetted for fiber and fragments.
AI summary Read the abstract
Researchers used Akaike Information Criterion corrected for small sample size (AICc) to rank competing statistical models explaining total microplastic counts, fiber counts, and fragment counts in the St. Lawrence River and Estuary, with area, site, and mesh size as independent variables. This model comparison framework identified the most parsimonious predictors of microplastic abundance across 61 sampling sites.
Akaike Information Criterion on small sample size (AICc) for competing models ranked from most to least parsimonious with area, site, and mesh size as independent variables to explain the sum of microplastic particles combined and subsetted for fiber and fragments.
More Papers Like This
S2 Table - Surface Water Microplastics in the St. Lawrence River and Estuary in Canada
AI summary Read the abstract
Researchers calculated Shannon and Simpson diversity indices for microplastic assemblages at 61 sites across the St. Lawrence River and Estuary using the vegan package, applying permutational ANOVA to assess variation by site and area using two net mesh sizes. This supplementary dataset supports broader analysis of microplastic community composition across fluvial and estuarine zones in Canada.
Proportion of microplastics by polymer name for A.
AI summary Read the abstract
Researchers characterized the proportional composition of microplastics by polymer type across 11 sites in the St. Lawrence River and Estuary using two net mesh sizes (300 µm and 100 µm), sampling from upstream to downstream locations. This dataset reveals site-specific and mesh-size-dependent variation in the polymer makeup of surface water microplastics.
Size and shape matter: A preliminary analysis of microplastic sampling technique in seawater studies with implications for ecological risk assessment
AI summary Read the abstract
This study showed that sampling with coarse-mesh towed nets significantly underestimates microplastic concentrations in seawater, particularly for fibrous particles, raising concerns about the accuracy of published abundance estimates.
Influential factors on microplastics occurrence in river sediments
AI summary Read the abstract
A Bayesian network analysis of river sediment data found that microplastic type is more strongly influenced by catchment land use and population than by sediment particle size, while microplastic concentration showed a positive relationship with clay content. The study improves understanding of which landscape factors drive microplastic accumulation in river sediments.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.