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R package to generate download and compile data from EPA ECOTOX database

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wqbench

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This package contains the functions and tools to generate aquatic life water quality benchmarks.

Installation

# install.packages("devtools")
devtools::install_github("bcgov/wqbench")

Workflow

library(wqbench)

Create Data Set for App

The wqb_create_data_set() function will download the US EPA ECOTOX1 database, create a local .sqlite database, add other data sources and filter conditions, clean and process the data, classify the duration, standardize the effect and output the completed data set needed for the shinywqbench app. The function will create an RDS file of the data set as well. It takes a few minutes to download and create the data set.

The default argument for:

  • file_path will save the raw text files at "~/Ecotoxicology/ecotox".
  • folder_path will save the .sqlite database and RDS file is at "~/Ecotoxicology/ecotox_db/".
  • version will download the most recent version of the data set available on the website.
data_set <- wqb_create_data_set()

The data set can be read in after it has been created.

data_set <- readRDS("~/Ecotoxicology/ecotox_db/ecotox_ascii_03_15_2023.rds")

Generate Benchmark

Deterministic Example

data <- wqb_filter_chemical(wqbenchdata::aquatic_data, "100016")
data <- wqb_benchmark_method(data)

data_agg <- wqb_aggregate(data)
data_agg <- wqb_af(data_agg)

ctv <- wqb_generate_ctv(data_agg)
ctv
## # A tibble: 1 × 3
##   ctv_est_mg.L ctv_lcl_mg.L ctv_ucl_mg.L
##          <dbl>        <dbl>        <dbl>
## 1          2.5           NA           NA

To calculate the benchmark for the chemical, divide the critical toxicity value (ctv) by the assessment factors.

benchmark <- ctv / (data_agg$af_bc_species * data_agg$af_salmon * data_agg$af_planktonic * data_agg$af_variation)
benchmark
##   ctv_est_mg.L ctv_lcl_mg.L ctv_ucl_mg.L
## 1   0.04166667           NA           NA

Deterministic method only generates an estimate, the lcl and ucl columns will always be blank .

# Plot data set
wqb_plot(data)

# Plot the results
wqb_plot_det(data_agg)

SSD Example

data <- wqb_filter_chemical(wqbenchdata::aquatic_data, "1071836")
data <- wqb_benchmark_method(data)

data_agg <- wqb_aggregate(data)
data_agg <- wqb_af(data_agg)

ctv <- wqb_generate_ctv(data_agg)
## Warning in checkMatrixPackageVersion(): Package version inconsistency detected.
## TMB was built with Matrix version 1.5.4
## Current Matrix version is 1.6.0
## Please re-install 'TMB' from source using install.packages('TMB', type = 'source') or ask CRAN for a binary version of 'TMB' matching CRAN's 'Matrix' package
ctv
## # A tibble: 1 × 3
##   ctv_est_mg.L ctv_lcl_mg.L ctv_ucl_mg.L
##          <dbl>        <dbl>        <dbl>
## 1       0.0101      0.00198       0.0583

To calculate the benchmark for the chemical, divide the critical toxicity value (ctv) by the assessment factors.

benchmark <- ctv / (data_agg$af_bc_species * data_agg$af_salmon * data_agg$af_planktonic * data_agg$af_variation)
benchmark
##   ctv_est_mg.L ctv_lcl_mg.L ctv_ucl_mg.L
## 1   0.01014924  0.001981239   0.05834417

SSD method can generate a lower and upper confidence interval.

# Plot data set
wqb_plot(data)

# Plot the results
fit <- wqb_ssd_fit(data_agg)
wqb_plot_ssd(data_agg, fit)

Summary Tables

wqb_summary_trophic_species(data_agg)
## # A tibble: 5 × 2
##   `Trophic Group` `Number of Species`
##   <fct>                         <int>
## 1 Algae                             6
## 2 Amphibian                         4
## 3 Fish                             11
## 4 Invertebrate                     12
## 5 Plant                             8
wqb_summary_trophic_groups(data_agg)
## # A tibble: 4 × 2
##   Consideration           Result                                                
##   <chr>                   <chr>                                                 
## 1 Trophic group(s)        Algae, Amphibian, Fish, Invertebrate, Plant           
## 2 Salmonid(s)             Oncorhynchus kisutch, Oncorhynchus mykiss, Oncorhynch…
## 3 Planktonic Invertebrate Artemia franciscana                                   
## 4 B.C. species            Cyprinus carpio, Lemna minor, Myriophyllum aquaticum,…
wqb_summary_af(data_agg)
## # A tibble: 3 × 3
##   Consideration                `Assessment Factor` Description                  
##   <chr>                                      <int> <chr>                        
## 1 Species variation factor                       1 Accounts for uncertainty due…
## 2 Ecological assessment factor                   1 Accounts for uncertainty whe…
## 3 B.C. species                                   1 Accounts for uncertainty of …

Getting Help or Reporting an Issue

To report issues, bugs or enhancements, please file an issue. Check out the support for more info.

Code of Conduct

Please note that the shinywqbench project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

The code is released under the Apache License 2.0

Copyright 2023 Province of British Columbia

Licensed under the Apache License, Version 2.0 (the “License”); you may not use this file except in compliance with the License. You may obtain a copy of the License at

https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Reference

  1. Olker, J. H., Elonen, C. M., Pilli, A., Anderson, A., Kinziger, B., Erickson, S., Skopinski, M., Pomplun, A., LaLone, C. A., Russom, C. L., & Hoff, D. (2022). The ECOTOXicology Knowledgebase: A Curated Database of Ecologically Relevant Toxicity Tests to Support Environmental Research and Risk Assessment. Environmental Toxicology and Chemistry, 41(6):1520-1539. https://doi.org/10.1002/etc.5324

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R package to generate download and compile data from EPA ECOTOX database

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