Correcting for Phylogenetic Autocorrelation in Species Sensitivity Distributions
Autor: | Richard A. Brain, Colleen D. Priest, Dwayne R. J. Moore, Sara I. Rodney, Nika Galic |
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Rok vydání: | 2020 |
Předmět: |
Independent and identically distributed random variables
Percentile Phylogenetic autocorrelation 010504 meteorology & atmospheric sciences Statistical assumption Geography Planning and Development 010501 environmental sciences Ecotoxicology Risk Assessment Sensitivity and Specificity 01 natural sciences Species Specificity Statistics Animals Phylogeny 0105 earth and related environmental sciences General Environmental Science Phylogenetic tree Cumulative distribution function Autocorrelation General Medicine Data set Sample size determination Species sensitivity distribution Atrazine Chlorpyrifos Water Pollutants Chemical Health & Ecological Risk Assessment |
Zdroj: | Integrated Environmental Assessment and Management |
ISSN: | 1551-3793 1551-3777 |
DOI: | 10.1002/ieam.4207 |
Popis: | A species sensitivity distribution (SSD) is a cumulative distribution function of toxicity endpoints for a receptor group. A key assumption when deriving an SSD is that the toxicity data points are independent and identically distributed (iid). This assumption is tenuous, however, because closely related species are more likely to have similar sensitivities than are distantly related species. When the response of 1 species can be partially predicted by the response of another species, there is a dependency or autocorrelation in the data set. To date, phylogenetic relationships and the resulting dependencies in input data sets have been ignored in deriving SSDs. In this paper, we explore the importance of the phylogenetic signal in deriving SSDs using a case studies approach. The case studies involved toxicity data sets for aquatic autotrophs exposed to atrazine and aquatic and avian species exposed to chlorpyrifos. Full and partial data sets were included to explore the influences of differing phylogenetic signal strength and sample size. The phylogenetic signal was significant for some toxicity data sets (i.e., most chlorpyrifos data sets) but not for others (i.e., the atrazine data sets, the chlorpyrifos data sets for all insects, crustaceans, and birds). When a significant phylogenetic signal did occur, effective sample size was reduced. The reduction was large when the signal was strong. In spite of the reduced effective sample sizes, significant phylogenetic signals had little impact on fitted SSDs, even in the tails (e.g., hazardous concentration for 5th percentile species [HC5]). The lack of a phylogenetic signal impact occurred even when we artificially reduced original sample size and increased strength of the phylogenetic signal. We conclude that it is good statistical practice to account for the phylogenetic signal when deriving SSDs because most toxicity data sets do not meet the independence assumption. That said, SSDs and HC5s are robust to deviations from the independence assumption. Integr Environ Assess Manag 2019;00:1–13. © 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC) KEY POINTS The assumption when deriving an SSD that toxicity data points are independent is tenuous because species sensitivity is correlated with taxonomic relatedness.We explored the importance of the phylogenetic signal in deriving SSDs using toxicity datasets for aquatic autotrophs exposed to atrazine and aquatic and avian species exposed to chlorpyrifos.A significant phylogenetic signal was observed in several of our chlorpyrifos toxicity datasets though not in our atrazine toxicity datasets.In spite of the reduced effective sample sizes, significant phylogenetic signals had little impact on fitted distributions (e.g., little change to HC5 values), indicating that SSDs are robust to deviations from the independence assumption. |
Databáze: | OpenAIRE |
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