Estimation of Persistent Organic Pollutants (POPs) in Fish Collected at Sapelo Island, GA: Statistical Methods Using Left Censored Data translation missing: zh.hyrax.visibility.files_restricted.text

Mateja, Allyson (Spring 2019)

Permanent URL: https://etd.library.emory.edu/concern/etds/h702q748h?locale=zh
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Abstract

Background: Persistent organic pollutants (POPs) are resistant to degradation and bioaccumulate in food webs. Although many have been banned, they arestill pervasive threats to marine animal health. Dolphins in the Turtle/Brunswick River Estuary (TBRE), a nationally designated Superfund site, were exposed to very high levels of polychlorinated biphenyls (PCBs). Sapelo Island, GA has minimal urbanization, so was used as a control for the TBRE. However, research shows dolphins at Sapelo Island also have elevated PCB levels. 

Objective:We were interested in examining whether there is a difference in analyte levels between fish at four different sites at Sapelo Island and in three different species for different chemical classes. The majority of chemical concentration measurements were below a limit of detection (left-censored). 

Methods: The mean for each site/species/analyte combination was estimated using a maximum likelihood approach and a two-way ANOVA (model [1]). This model was simplified to assume no interaction between site and species (model [2]), and to a one-way ANOVA to compare only between species (model [3]).     

Results: Sea trout have lower summed mean concentrations across all chemical classes compared to mullet and silver perch, with the exception of Aroclor 1268, for which mullet have the lowest concentrations. Mullet and silver perch have similar summed mean concentrations across chemical classes, with mullet higher for DDTs and metals and silver perch higher for pesticides and PCBs. We found statistically significant differences between species for all chemical classes except polybrominated diphenyl ethers (PBDEs)in model [2]. Only pesticides were significantly different across species in model [1]. Aroclor 1268 was significantly different between sites in model [2], after removal of outliers. Otherwise, we found no significant differences between sites. 

Conclusion: Our results are limited due to large amounts of left-censored data and large variances of estimates. Even after removing outliers, most analytes did not have maximum likelihood estimates with stable standard errors. The small number of fish and large number of left-censored measurements create statistical challenges for accurate estimation and must be considered when interpreting results. We recommend future studies include larger sample sizes or focus on analytes present at higher concentrations. 

Table of Contents

1. Introduction ............................................................................................................................. 1

2. Background ............................................................................................................................. 2

Study site ..................................................................................................................................... 4

Sample collection and processing ............................................................................................... 6

Data Description ......................................................................................................................... 8

Approaches for handling left-censored data ............................................................................... 8

3. Methods................................................................................................................................. 13

Maximum Likelihood Estimation ............................................................................................. 15

Extreme Observations ............................................................................................................... 25

4. Results ................................................................................................................................... 26

DDTs ......................................................................................................................................... 27

PCBs ......................................................................................................................................... 39

PBDEs ....................................................................................................................................... 44

Metals ........................................................................................................................................ 46

Pesticides ................................................................................................................................... 51

5. Discussion ............................................................................................................................. 53

Limitations ................................................................................................................................ 56

Future Work .............................................................................................................................. 58

Conclusions ............................................................................................................................... 60

6. References ............................................................................................................................. 64

7. Appendix ............................................................................................................................... 67

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