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Fibre-Sensitive Uncertainty Shifts Microplastic Monitoring Priorities in Tropical Aquaculture Ponds
Summary
Researchers checked fish ponds in Indonesia for tiny plastic particles (microplastics) and found them in every pond, mostly tiny fibers likely from clothing or fishing nets—but without proper contamination controls, they can't be 100% sure those fibers came from the ponds and not the lab air. The bigger takeaway: when scientists only count total particles to decide which ponds are "most polluted," they can get misleading answers, so this study suggests smarter ways to identify true hotspots before doing more rigorous testing (including checking if fish are absorbing these particles into their gills and guts, which matters since we eat farm
Brackish aquaculture ponds can retain plastic-derived particles, but early monitoring in tropical pond systems is often constrained by visual identification, incomplete contamination controls, and limited access to particle-level polymer confirmation. This study develops an uncertainty-aware interpretation of a replicated pond-water dataset from five traditional milkfish ponds in Tarakan, North Kalimantan, Indonesia. Three 20 L water replicates were collected at each station, yielding 300 L overall. Across all samples, 319 suspected microplastic-like particles were recovered. Pooled station abundance ranged from 0.60 to 1.37 particles L−1. Fibre-like particles dominated the recovered material (250 of 319 particles; 78.4%); because field and airborne blanks were unavailable, this pattern is interpreted as a contamination-sensitive signal rather than definitive environmental fibre dominance. Morphology-sensitive analysis changed the monitoring priority: Mamburungan ranked first by total abundance, whereas Islamic Center and Tenguyun ranked first and second when non-fibre particles were prioritised. Organ-level FTIR peak regions from milkfish intestine and gill samples were retained only as boundary-setting observations, not polymer confirmation. This study shows that abundance-only hotspot narratives can be unstable in fibre-dominated exploratory datasets and that morphology-sensitive uncertainty analysis can support transparent site selection for future blank-corrected, polymer-confirmed aquaculture monitoring.