Get annual medians of AMBI scores by bay segment

Get annual medians of AMBI scores by bay segment

Usage

anlz_ambimed(
  ambiscr,
  bay_segment = c("HB", "OTB", "MTB", "LTB", "TCB", "MR", "BCB", "All"),
  rev = FALSE,
  yrrng = c(1993, 2024),
  window = TRUE
)

Arguments

ambiscr

input data frame as returned by anlz_ambiscr; the AMBI variant (conventional or Tampa Bay-specific) is detected automatically from the column names

bay_segment

chr string for the bay segment, one to many of "HB", "OTB", "MTB", "LTB", "TCB", "MR", "BCB", "All"

rev

logical if factor levels for bay segments are reversed

yrrng

numeric indicating year ranges to evaluate

window

logical indicating whether to use a rolling 5-year window (default TRUE) or single year values (FALSE) for the bay segment categories, see details

Value

A data frame of annual percent composition by AMBI category and bay segment

Details

An additional summary is provided for the entire bay as an unweighted summary across categories ("All").

Only sampling funded by TBEP and as part of the routine EPC benthic monitoring program are included in the final categories.

The default behavior is to use a rolling five-year window to calculate the percent of sites in each AMBI category by bay segment. This applies only to years 2005 and later, where the counts from the current year and the prior four years are summed to calculate the percentages. This is intended to help smooth out inter-annual variability due to reduced sampling effort from 2005 to present. If window = FALSE, then only single year values are used.

The AMBI category column (AMBICat or TBAMBICat) is based on the adjusted AMBI score (0-10 scale) using the classification thresholds defined in anlz_ambiscr.

Examples

ambiscr <- anlz_ambiscr(benthicdata)
anlz_ambimed(ambiscr)
#> # A tibble: 254 × 7
#>    bay_segment    yr `Extremely Polluted` `Heavily Polluted` `Meanly Polluted`
#>    <fct>       <dbl>                <dbl>              <dbl>             <dbl>
#>  1 All          1993              0                   0                0      
#>  2 All          1994              0.0111              0                0.0444 
#>  3 All          1995              0.0448              0                0.00746
#>  4 All          1996              0.0152              0                0.00758
#>  5 All          1997              0.00813             0                0.00813
#>  6 All          1998              0.0167              0                0.0167 
#>  7 All          1999              0.00806             0                0.0161 
#>  8 All          2000              0                   0                0.0233 
#>  9 All          2001              0.025               0.0125           0.0125 
#> 10 All          2002              0.0120              0.0120           0.0361 
#> # ℹ 244 more rows
#> # ℹ 2 more variables: `Slightly Polluted` <dbl>, Unpolluted <dbl>