From sediment to tissue and tissue to sediment: An evaluation of statistical bioaccumulation models. (19th December 2013)

• Record Type: Journal Article
• Authors: Judd, Nancy; Tear, Lucinda; Toll, John
• Is Part Of: Integrated environmental assessment and management. Volume 10:Number 1(2014:Jan.)
• Page Start: 102
• Page End: 113
• Publication Date: 2013-12-19
• Subjects: Environmental management -- Periodicals; Pollution -- Periodicals; Environmental toxicology -- Periodicals; Environmental risk assessment -- Periodicals; Environmental impact analysis -- Periodicals; 628
• DOI: 10.1002/ieam.1484
• Languages: English
• ISSNs: 1551-3777

Abstract

<abstract abstract-type="main" xml:lang="en"> <title>ABSTRACT</title> <sec id="ieam1484-sec-0001" sec-type="section"> <p>Biota–sediment accumulation factors (BSAFs) and biota–sediment accumulation regressions (BSARs) are statistical models that may be used to estimate tissue chemical concentrations from sediment chemical concentrations or vice versa. Biota–sediment accumulation factors and BSARs are used to fill tissue concentration data gaps, set sediment preliminary remediation goals (PRGs), and make projections about the effectiveness of potential sediment cleanup projects in reducing tissue chemical concentrations. We explored field‐based, benthic invertebrate biota–sediment chemical concentration relationships using data from the US Environmental Protection Agency (USEPA) Mid‐Continent Ecology Division (MED) BSAF database. Approximately two thirds of the 262 relationships investigated were very poor (<italic>r</italic><sup><italic>2</italic></sup> < 0.3 or <italic>p</italic>‐value ≥ 0.05); for some of the biota–sediment relationships that did have a significant nonzero slope (<italic>p</italic>‐value < 0.05), lipid‐normalized tissue concentrations tended to decrease as the colocated organic carbon (OC)‐normalized sediment concentration increased. Biota–sediment relationships were further evaluated for 3 of the 262 datasets. Biota–sediment accumulation factors, linear regressions, model II regressions, illustrative sediment PRGs, and confidence intervals (CIs) were calculated for each of the three examples. These examples illustrate some basic but important statistical practices that should be followed before selecting a BSAR or BSAF or relying on these simple models of biota–sediment relationships to support consequential management decisions. These practices include the following: one should not assume that the relationship between chemical concentrations in tissue and sediment is necessarily linear, one should not assume the model intercept to be zero, and one should not place too much stock on models that are heavily influenced by one or a few high chemical concentration data points. People will continue to use statistical models of field‐based biota–sediment chemical concentration relationships to support sediment investigations and remedial action decisions. However, it should not be assumed that the models will be reliable. In developing and applying BSAFs and BSARs, it is essential that best practices are followed and model limitations and uncertainties are understood, acknowledged, and quantified as much as possible. <italic>Integr Environ Assess Manag</italic> 2014;10:102–113. © 2013 SETAC</p> </sec> </abstract>