Publication Summary

We sought to derive chemical criteria that could predict possible biological effects in sediments. To develop chemical-based criteria, data from several bioassays (Hyalella azteca, Microtoxâ Chironomus tentans, Daphnia magna, Ceriodaphnia dubia, and Hexagenia limbata) and chemical analyses (metals, Polycyclic Aromatic Hydrocarbons (PAH), pesticide/PCB, semivolatiles) were merged from 33 studies and 245 stations in Washington and Oregon into a single database.

We sought to derive chemical criteria that could predict possible biological effects in sediments. To develop chemical-based criteria, data from several bioassays (Hyalella azteca, Microtoxâ Chironomus tentans, Daphnia magna, Ceriodaphnia dubia, and Hexagenia limbata) and chemical analyses (metals, Polycyclic Aromatic Hydrocarbons (PAH), pesticide/PCB, semivolatiles) were merged from 33 studies and 245 stations in Washington and Oregon into a single database.

We tested the efficiency (correctly predicted/number predicted: 1 minus Type I error) and sensitivity (correctly predicted/impacted: 1 minus Type II error) that sediment quality values have in predicting biological effects. The values derived in this study were Apparent Effects Thresholds (AET) and Probable AET (PAET: 95th percentile of no effects stations) calculated from Hyalella azteca and Microtoxâ. The efficiency and sensitivity of other values including Ontario′s Severe Effect Level (SEL), Environment Canada′s Probable Effects Level (PEL) and Threshold Effect Level (TEL), EPA′s Equilibrium Partitioning (EQP), and Washington State Department of Ecology′s Marine Sediment Management Standards (SMS) were also tested and compared with values derived in this study.

For PAH, dry weight normalized values for AETs and PAETs were significantly more sensitive and efficient than organic carbon normalized values (p<0.05). TEL were always the most sensitive (fewest missed effects) and least efficient (most false alarms). The AET Hyalella were the reverse. In rough progression from most sensitive to least sensitive were TEL, SMS, PAET Microtox®, PEL, AET Microtox®, SEL, PAET Hyalella and AET Hyalella; from most efficient to least were AET Hyalella, SEL, AET Microtox®, PAET Hyalella, PAET Microtox®, SMS, PEL, TEL. With comparisons limited to the three PAH considered by EQP, the AET and PAET Hyalella and SEL errors were roughly equivalent to EQP; they were highly efficient but less sensitive than random selection.

We suggest a set of Freshwater Sediment Quality Values (FSQV) based on PAET Microtox® values for organics and SMS values for metals be considered as a threshold to detect biological effect. These FSQVs ranked second in sensitivity (80%) and fourth in efficiency (45%). Highly efficient AET Hyalella (96%) could provide a level above which detrimental biological effects are reasonably certain. The Lowest AET (LAET) between Hyalella and Microtoxâ could also be considered. Advantages of these values (LAET) are that its methods have been accepted and they provide slightly better efficiency than the FSQV above (46%). One major disadvantage over the FSQV is their reduced sensitivity (75%).