Exploring the Input Data

glimpse(psp)

Rows: 14,845
Columns: 19
$ id             <chr> "PSP19.3_2014-04-01_mytilus", "PSP21.09_2014-04-01_myti…
$ location_id    <chr> "PSP19.3", "PSP21.09", "PSP21.2", "PSP25.17", "PSP26.07…
$ date           <date> 2014-04-01, 2014-04-01, 2014-04-01, 2014-04-02, 2014-0…
$ species        <chr> "mytilus", "mytilus", "mytilus", "mytilus", "mytilus", …
$ total_toxicity <dbl> 0.1561590, 0.2044939, 0.1933397, 0.1301325, 0.1859036, …
$ lat            <dbl> 44.22853, 44.23824, 44.29200, 44.61438, 44.65701, 44.53…
$ lon            <dbl> -68.53441, -68.34792, -68.23696, -67.43323, -67.20525, …
$ gtx4           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ gtx1           <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000…
$ dcgtx3         <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ gtx5           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ dcgtx2         <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ gtx3           <dbl> 0.1561590, 0.2044939, 0.1933397, 0.1301325, 0.1859036, …
$ gtx2           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ neo            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ dcstx          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ stx            <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000…
$ c1             <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ c2             <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…

The data set contains seasonal biotoxin measurements from 2014 until present

summary(psp$date)

        Min.      1st Qu.       Median         Mean      3rd Qu.         Max. 
"2014-04-01" "2015-07-15" "2017-07-10" "2018-03-19" "2020-05-20" "2025-04-02" 

There are >250 unique sampling locations along the Maine coast. Sites have been sampled between 1 and almost 300 times.

counts <- count(psp, location_id) |>
  arrange(desc(n))

counts

# A tibble: 383 × 2
   location_id     n
   <chr>       <int>
 1 PSP27.46      325
 2 PSP26.15      261
 3 PSP12.03      260
 4 PSP12.13      259
 5 PSP10.11      252
 6 PSP10.33      242
 7 PSP16.41      239
 8 PSP12.34      236
 9 PSP27.05      235
10 PSP12.01      230
# ℹ 373 more rows

hist(counts$n)

A map of all of the stations included in this tutorial

summary(psp$total_toxicity)

    Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
   0.000    0.000    1.119   16.489    8.911 3092.832 

hist(psp$total_toxicity, 100)

There are multiple shellfish species that are sampled. We’ll only use one since they take up and depurate the toxin at different rates.

Blue mussels (Mytilus edulis) are the most commonly sampled.

psp |>
  count(species) |>
  arrange(desc(n))

# A tibble: 12 × 2
   species         n
   <chr>       <int>
 1 mytilus     11695
 2 mya          1464
 3 arctica      1155
 4 spisula       260
 5 crassostrea    90
 6 ensis          70
 7 mercenaria     60
 8 ostrea         32
 9 placopecten    12
10 <NA>            5
11 9ROY            1
12 RMCP            1

The dynamics of a site during one season