Sediment contaminants and biological effects in southern California: Use of a multivariate statistical approach to assess biological impact

Abstract

This study attempts to predict biological toxicity and benthic community impact in sediments collected from two southern California sites. Contaminant concentrations and grain size were evaluated as predictors using a two‐step multivariate approach. The first step used principal component analysis (PCA) to describe contamination type and magnitude present at each site. Four dominant PC vectors, explaining 88% of the total variance, each corresponded to a unique physical and/or chemical signature. The four PC vectors, in decreasing order of importance, were: (1) high molecular weight polynuclear aromatic hydrocarbons (PAH), most likely from combusted or weathered petroleum; (2) low molecular weight alkylated PAH, primarily from weathered fuel product; (3) low molecular weight nonalkylated PAH, indicating a fresh petroleum‐related origin; and (4) fine‐grained sediments and metals. The second step used stepwise regression analysis to predict individual biological effects (dependent) variables using the four PC vectors as independent variables. Results showed that sediment grain size alone was the best predictor of amphipod mortality. Contaminant vectors showed discrete depositional areas independent of grain size. Neither contaminant concentrations nor PCA vectors were good predictors of biological effects, most likely due to the low concentrations in sediments.

Prediction of ecotoxicity of hydrocarbon‐contaminated soils using physicochemical parameters

“…The use of multivariate methods in this study has helped elucidate and implicate possible relationships between soil properties and toxicity. Multivariate statistics have been increasingly used in recent years to relate sets of variables in environmental studies, particularly in studies to assess biological impact of contaminated sediments and studies in which the sediment quality triad approach was used [19–24]. Eriksson et al [14] also illustrated the utility of PLS analysis in modeling aquatic toxicity data.…”

Contribution of trace metals in structuring in situ macroinvertebrate community composition along a salinity gradient

“…Total metal concentrations are used in most sediment risk assessment procedures to evaluate the effects of trace metals on, e.g., macroinvertebrates [1,15,16]. However, it is well accepted that it is not total but rather bioavailable concentrations that cause the effects on the biota [17–20] and thus on the community.…”

Modification of an ecotoxicological rating to bioassess small acid mine drainage‐impacted watersheds exclusive of benthic macroinvertebrate analysis

“…Chapman [18,28] and Chapman et al [29] established that summary indices should be avoided when using sediment quality triad studies intended to rank impaired stations because summary indices do not effectively distinguish intermediate impacts [1,10]. Both the original ETR and METR constructed for Ely Crrek and Puckett's Creek differentiated reference (group 1) and recovery stations (group 5) from stations receiving both acutely toxic AMD inputs (group 3) and intermittently impacted stations (groups 2 and 4; Table 5).…”

“…Integrative bioassessment approaches that incorporate both field and laboratory techniques, such as the sediment quality triad, have become increasingly popular [7–12]; a number of researchers have conducted assessments of heavy metal‐impacted watersheds by comparing chemical, physical, and biological data to describe the environmental condition of the associated aquatic ecosystem [1,13–17]. Many of these studies used a sediment quality triad and weight‐of‐evidence approach to determine which stations were impacted and to provide insight toward causality of the observed impacts [18–20].…”