Environmental Risk Assessments Case Studies

Environmental Risk Assessments 10 Case Studies Kenneth M. Brooks his chapter discusses the results of evaluating physi- downcurrent vector and at a reference location displaced cochemical and biological responses in freshwater upcurrent by >50 m. Tand marine environments to the presence of pressure- In some cases, such as in the Wildwood Wetland treated wood structures. In general, these projects were Boardwalk Study (Brooks 2000b), the Sooke Basin Creosote chosen to be representative of worst cases where adverse evaluation (Goyette and Brooks 1998, 2000; Brooks et al. effects could be anticipated or where the study was re- 2006), and the Railway Tie Study (Brooks 2004b), the hybrid quired by a court in support of permits. statistical approach was used in a before-after-control- treatment (BACT) design with two levels of control. The 10.1 EXPERIMENTAL DESIGN first level of control was an open reference location and the second level was termed a “mechanical control” (MC), 10.1.1 ANOVA design and hybrid which was a structure identical to the treatment structure(s), regression but constructed of untreated wood. The purpose of the All of the assessments of contaminants in the water column MC was to assess the environmental response to the pres- and studies required by a court are based on a replicated ence of the structure, absent any contamination from the analysis of variance (ANOVA) design. In these studies, wood preservative. samples were collected within half a meter of the structures and at a local reference station sharing the same physico- 10.1.2 Why was the hybrid study chemical characteristics (percent silt and clay in sediments, design chosen? water depth, etc.). The benefits of hybrid approaches to environmental sam- Most of the studies discussed in this chapter are based pling have been described by Liber et al. (1992), Prairie on a hybrid regression combined with replicated (ANOVA) (1996), and Neter et al. (1985). The following comments designs. In all cases, the designs are based on anticipated are intended to extend that discussion. The contamination worst cases. In other words, in environments with steady- of sediments has spatial and temporal dimensions. state currents, replicated treatment samples (N = 3) were Underwood (1996) discusses the importance of time in collected at 0.25 to 0.5 m from the structure. Single samples sampling designs for detecting environmental distur- were then collected at varying intervals along the down- bances. The ANOVA approach is useful for determining current vector to a distance at which no further significant whether or not contaminants at a point in time are statisti- contamination was anticipated (usually 20+ m from the cally significantly different at a treatment station in com- structure). In steady-state current regimes, replicated parison with a control station. However, the ANOVA samples (N = 3) were collected at a reference station hav- approach tells us little or nothing about the spatial distri- ing the same general properties (water depth, current bution of contaminants associated with a source. This is speed, substrate composition) as the treatment stations, readily apparent when reviewing the history of environ- but located >20 m upstream. In tidally driven environmental studies undertaken to monitor and manage inten- ments, treatment stations were located on the dominantly sive aquaculture. Prior to 2001, studies relied solely on an ANOVA approach. In large part, this was because regula- The author is Environmental Consultant with Aquatic Environmental tory agencies preferred tests that gave a “yes” (in compli- Sciences, Port Townsend, WA 98368. ance) or a “no” (not in compliance) answer. Most sampling 309 310 Managing Treated Wood in Aquatic Environments programs required replicate samples collected on the High concentrations of free sediment sulfide on the net perimeter of net pens for comparison with three to five pen perimeter were the result of the anaerobic breakdown samples collected at one or two local reference locations. of farm waste. At this site, sulfides increased quickly at Reference locations were frequently located 15 to 60 m distances <65 m. However, the graph suggests that small from the perimeter of intensive aquaculture sites, and the sulfide effects (a significant coefficient on distance) were literature notes that effects appeared to be confined to present to 165 m. Redox potential was low on the perimeter areas within a few tens of meters of the operation. Brooks of the farm and increased almost linearly to a distance of (2001) undertook studies at seven salmon farms in support 150 m, where it became highly variable. Canister studies of British Columbia’s Technical Advisory Group’s efforts to and same-sample concentrations of sediment total volatile develop a better waste regulation for managing salmon solids (TVS) demonstrated that waste deposition declined farming in the province. Preliminary monitoring examined exponentially with distance from the net pens. These re- sediments on four orthogonal transects originating at the sults are internally consistent in that it is the catabolism middle of each side of the net pens. The results indicated of labile salmon feces and waste feed that creates low that organic waste from the farms was distributed primarily redox potentials leading to anaerobic catabolism (strip- along the upcurrent and downcurrent transects, with ping of oxygen from sulfate), leaving sulfide as a waste much less waste distributed orthogonal to the currents. product. At this farm, dramatic sediment physicochemical A one-year study using a hybrid regression-ANOVA ap- effects were seen to a distance of 65 m, and subtle effects proach was then undertaken, with periodic sampling extended to 145 m. The macrofaunal inventories con- taking place from early spring to late fall. The results pre- ducted on the same samples from which the data in Figure sented in Brooks (2001), Brooks et al. (2003, 2004a), and 10.1 was developed confirmed these effects. Figure 10.2 other peer-reviewed publications demonstrated that sig- describes the number of species observed in the 0.1 m2 nificant effects extended to >100 m from the farms; that van Veen grab samples (Log10(Taxa+1)). Prarie (1996) noted benthic effects associated with organic enrichment were that the power of regression to predict relationships be- in evidence shortly after feeding began at a farm; and that tween dependent and independent variables can be as- physicochemical and biological remediation of the benthos sessed through the coefficient of determination (R2). He was frequently complete within 6 mo post harvest. demonstrated exponentially increasing power when R2 Figure 10.1 describes the sediment’s physicochemical values exceeded 0.65 or (65% of the variation). Obtaining response to organic enrichment at one of the seven farms. the best “fit” between dependent and independent vari- 4000 100 3500 75 50 3000 25 2500 0 2000 -25 -50 1500 -75 1000 -100 SULFIDE(L) Redox Potential (mV) -125 500 ORP(R) -150 Free sediment sulfide (micromolar) 0 -175 -500 -200 0 50 100 150 200 250 300 350 Distance (m) Figure 10.1 Free sediment sulfide (µM) given by the solid line and left ordinate andredox potential (mV) given on the right ordinate and by the dashed line versus distance from salmon farm netpens (Brooks, 2001). Data for the reference location is plotted at 300 m.SULFIDE = Distance Weighted Least Squares. ORP = Distance Weighted Least Squares. Chapter 10. Environmental Risk Assessments – Case Studies Kenneth M. Brooks 311 ables in a dataset depends on protocols based on a good 2.0 understanding of the basic relationships involved, good ) experimental designs, and the skill of the analyst. The 2 1.8 simplest description of the R2 statistic is that it defines the 1.6 proportion of the variance in relationships that is explained by the fitted regression line. Many biologists are familiar 1.4 with linear regression. It is less common to see non-linear 1.2 regression analysis used to predict responses. Note that (number of taxa/0.1 m in Figure 10.1, there was more variability in the redox 10 1.0 2 potential data (dashed line), resulting in a lower R value Log than was observed in the sulfide data, which has a much 0.8 2 higher R value. 0.6 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Another advantage of regression analysis is that good Log (free sediment sulfides in micromoles) experimental designs will provide responses across a range 10 2 of independent variables, which, as noted by Liber et al. Figure 10.2 Log10(Taxa + 1) observed in 0.1-m modified van Veen (1992), allows for determination of no-effect thresholds grab samples along a 225-m long transect originating on the perimeter of a salmon farm and proceeding down current for 225 m. for toxicants. Brooks et al. (2004a) produced the graph and Data for the reference location is plotted at 300 m. Log(taxa + 1) linear regression given in Figure 10.3 describing the versus distance at Focused Study Farm FLog(Taxa + 1) = 0.51 + 1.20*(1-exp(-0.029*distance)) R2 = 0.90. Log10(Taxa+1) response to increasing sulfide concentrations between free sediment sulfide concentrations of 8 and 7,950 µM. The coefficient of determination for this regression was 0.69. A 50% reduction in the number of taxa at this site occurred at 447 µM free sediment sulfide 2.0 (S=). C:398 1.8 C:393 C:395 C:396 C:399 The author believes that the hybrid ANOVA-regression C:392 C:4 C:391 C:394 C:397 C:4 approach used in these risk assessments is superior to a 1.6 C:390 C:4 C:389 simple ANOVA study design because it provides informa- 1.4 C:388 tion describing the spatial extent of effects, as well as the 1.2 degree of the contamination.

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