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Split livestock excretion across manure-management systems.

Source: R/manure_management.R
split_manure_management.Rd

Splits the excreted nitrogen, carbon and volatile solids from estimate_n_excretion() across manure-management systems (MMS), separating the in-situ grazing stream (pasture/range/paddock, deposited where it falls) from the collected/housed streams routed to storage. The split conserves mass: the per-species MMS shares sum to one.

Usage

split_manure_management(excretion, options = list())

Arguments

excretion

A tibble from estimate_n_excretion() with year, territory (a stringified area_code, see estimate_n_excretion()), sub_territory, livestock_category, n_excretion, c_excretion and vs_excretion.

options

A named list. mms_source selects how the MMS shares in regional_mms_distribution are read:

  • "regional_default" (default): every territory takes the table's region == "Global" rows, the IPCC/GLEAM global default.

  • "region_specific": each territory takes the rows of the region it resolves to, and the Global rows when its region has none. Only four (region, species) pairs carry region-specific rows (North America cattle and swine, Western Europe cattle, Latin America cattle), so every other row is unchanged.

Value

A tibble with one row per year x territory x sub_territory x livestock_category x mms_type, plus species_gen, loss_category, stream ("grazing" or "collected"), n_stream, c_stream, vs_stream and method_mms.

Examples

excretion <- tibble::tribble(
  ~year, ~territory, ~sub_territory, ~livestock_category,
  ~n_excretion, ~c_excretion, ~vs_excretion,
  2020L, "203", NA, "Cattle_milk", 100, 1900, 60,
  2020L, "203", NA, "Pigs", 30, 270, 20
)
split_manure_management(excretion)
#> # A tibble: 7 × 13
#>    year territory sub_territory livestock_category species_gen loss_category
#>   <int> <chr>     <lgl>         <chr>              <chr>       <chr>        
#> 1  2020 203       NA            Cattle_milk        Cattle      Dairy Cattle 
#> 2  2020 203       NA            Cattle_milk        Cattle      Dairy Cattle 
#> 3  2020 203       NA            Cattle_milk        Cattle      Dairy Cattle 
#> 4  2020 203       NA            Cattle_milk        Cattle      Dairy Cattle 
#> 5  2020 203       NA            Pigs               Swine       Swine        
#> 6  2020 203       NA            Pigs               Swine       Swine        
#> 7  2020 203       NA            Pigs               Swine       Swine        
#> # ℹ 7 more variables: cn_species <chr>, mms_type <chr>, stream <chr>,
#> #   n_stream <dbl>, c_stream <dbl>, vs_stream <dbl>, method_mms <chr>