Probabilistic risk assessment of mine-derived copper in the Ok Tedi/Fly River, Papua New Guinea.

The Ok Tedi mine discharges waste rock and tailings into the Ok Tedi River in Papua New Guinea. This has resulted in elevated copper concentrations throughout the Ok Tedi/Fly River system, which can potentially impact aquatic biota. Ten years of measured copper and toxicity monitoring data were used to assess the risk of chronic effects from the mine-derived copper. Cumulative probability plots of dissolved and labile copper were compared to a species sensitivity distribution (SSD) of published copper toxicity data for four regions of the river. The Cu-SSD was used to estimate the risk of chronic effects to aquatic organisms in the Ok Tedi/Fly River at a range of potential copper exposure scenarios. The risk to species at the median labile copper concentration for each region showed a gradient effect with distance downstream from the mine and only the most sensitive (0.2-11%) species were at risk. There were copper exceedances of the region-specific guideline values (GV) and default guideline value (DGV) 88% and 74% of the time, respectively, in the Ok Tedi region (closest to the mine) and this is considered a high risk of chronic effects. Measured copper concentrations in the middle Fly River, lower Fly River (farthest downstream of the mine) and the river at Kiunga (reference site) exceeded the region-specific GVs and DGVs less frequently to rarely and present a lower risk of chronic effects from copper. The risk was supported using toxicity tests with the local microalgal species Chlorella sp. Comparison of recent (2010-2020) and historical (1996-2004) copper monitoring data from the Ok Tedi/Fly River indicates a decrease in the labile copper concentrations (30-76%) at key sites from impacted regions and a subsequent decrease in risk. This coincides with improved mining practices aimed at reducing the copper load into the Ok Tedi/Fly River.

Use of scanning and image recognition technology to semi-automate larval development assessment in toxicity tests with a tropical copepod.

There is a high demand for the development of reliable chronic toxicity tests using tropical marine species for subsequent use in tropical risk assessment. However, many chronic test endpoints can be laborious and time-consuming to assess, particularly if the endpoints require measurements of individuals (e.g. growth, size) or advanced taxonomic expertise (e.g. differentiating between larval development stages). In this study, we used scanning and image recognition (SIR) technology to develop and validate a chronic toxicity test with larvae of the tropical euryhaline copepod, Acartia sinjiensis. Optimisation steps are described, and included egg age, and effect of algal food type and salinity on toxicity. Comparisons were made between traditional endpoints measured using microscopy and those measured using SIR. Traditional endpoints of larval development ratio (LDR) and survival achieved using microscope examination and SIR were almost identical (R2 = 0.96-0.97). Additional endpoints made possible by SIR included larval development index (LDI; based on the number of animals at different stages of development), and a range of size measurements (e.g. surface area, perimeter and length) for individual animals and for total populations (i.e. a proxy for biomass). The SIR-derived endpoints were based on measurements that had concentration-dependant responses to tested toxicants (copper, nickel, ammonia), and were a sub-set of the full range of metrics provided by the software. Toxicity values based on SIR-measurements were similar to or more sensitive than the traditional LDR endpoint. SIR technology provides a major opportunity to improve and modernise larval development tests for a range for species, but comes at a cost of increased data size and complexity. Therefore, as a research tool, SIR has significant advantages over traditional microscope methods, but for routine toxicity testing, SIR incorporation into invertebrate toxicity testing will benefit from further improvements to the associated software and data management systems.