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Spatial verbs for ForestGEO-style stem maps

stems_spatial.Rd

Stems in forest dynamics plots (ForestGEO / CTFS) are mapped in local metre coordinates (gx, gy). These verbs are the spatial part of a stem workflow:

  • stems_quadrat() assigns each stem to a square quadrat (ForestGEO default 20 m) and adds quadrat, quadrat_x, quadrat_y, quadrat_col and quadrat_row.

  • stems_habitat() joins quadrat-level habitat or topography by quadrat or by quadrat_x/quadrat_y.

  • stems_neighbours() counts neighbours within radius metres of each stem, either all stems or conspecifics only.

Census summaries (stems_abundance(), stems_basal_area(), stems_demography(), stems_as_community()) live in tidydiversity. Map stems with plot_topo() and test habitat associations with stems_habitat_test().

Usage

stems_quadrat(data, grid = 20, gx = gx, gy = gy)

stems_habitat(data, habitat, grid = 20)

stems_neighbours(
  data,
  radius = 10,
  conspecific = TRUE,
  alive_only = TRUE,
  alive = "A"
)

Arguments

data

A ForestGEO-like stem or tree table with species and local coordinates (gx/gy or x/y).

grid

Quadrat size in metres (ForestGEO default 20).

gx, gy

Bare column names for local metre coordinates.

habitat

A data frame of quadrat-level habitat or topography (quadrat, or quadrat_x/quadrat_y, plus covariates).

radius

Neighbourhood radius in metres.

conspecific

Count only neighbours of the same species (TRUE) or all neighbours (FALSE).

alive_only

Keep only stems whose status is in alive?

alive

Character codes of status that mean alive (default "A").

Value

A tibble: data with the new quadrat, habitat or neighbour columns.

References

Condit, R. (1998). Tropical Forest Census Plots. Springer. Anderson-Teixeira, K. J. et al. (2015). CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change. Global Change Biology, 21, 528-549. doi:10.1111/gcb.12712 .

Examples

stems <- geo_example_stems()
q <- stems_quadrat(stems, grid = 20)
head(q[c("gx", "gy", "quadrat", "quadrat_col", "quadrat_row")])
#> # A tibble: 6 × 5
#>      gx    gy quadrat quadrat_col quadrat_row
#>   <dbl> <dbl> <chr>         <int>       <int>
#> 1  27.5  97.2 20_80             1           4
#> 2  37.7  49.6 20_40             1           2
#> 3  57.0  48.5 40_40             2           2
#> 4  89.2  18.7 80_0              4           0
#> 5  21.4  74.5 20_60             1           3
#> 6  88.2  45.6 80_40             4           2

hab <- unique(q[c("quadrat", "quadrat_x", "quadrat_y")])
hab$elev <- hab$quadrat_x + hab$quadrat_y
head(stems_habitat(stems, hab))
#> # A tibble: 6 × 16
#>   plot    treeID stemID    gx    gy   dbh species status quadrat_x.x quadrat_y.x
#>   <chr>    <int>  <int> <dbl> <dbl> <dbl> <chr>   <chr>        <dbl>       <dbl>
#> 1 demo100      1      1  27.5  97.2   6.8 Homala… A               20          80
#> 2 demo100      2      2  37.7  49.6  18.9 Pometi… A               20          40
#> 3 demo100      3      3  57.0  48.5   8   Homala… A               40          40
#> 4 demo100      4      4  89.2  18.7   8.2 Ficus_… A               80           0
#> 5 demo100      5      5  21.4  74.5   8.5 Pteroc… A               20          60
#> 6 demo100      6      6  88.2  45.6  13.4 Intsia… D               80          40
#> # ℹ 6 more variables: quadrat <chr>, quadrat_col <int>, quadrat_row <int>,
#> #   quadrat_x.y <dbl>, quadrat_y.y <dbl>, elev <dbl>

head(stems_neighbours(stems, radius = 10))
#> # A tibble: 6 × 11
#>   plot    treeID stemID    gx    gy   dbh species            status n_neighbours
#>   <chr>    <int>  <int> <dbl> <dbl> <dbl> <chr>              <chr>         <int>
#> 1 demo100      1      1  27.5  97.2   6.8 Homalanthus_novog… A                 0
#> 2 demo100      2      2  37.7  49.6  18.9 Pometia_pinnata    A                 0
#> 3 demo100      3      3  57.0  48.5   8   Homalanthus_novog… A                 0
#> 4 demo100      4      4  89.2  18.7   8.2 Ficus_sp           A                 0
#> 5 demo100      5      5  21.4  74.5   8.5 Pterocarpus_indic… A                 0
#> 6 demo100      7      7  92.7  51.1   8.7 Pometia_pinnata    A                 0
#> # ℹ 2 more variables: neighbour_radius <dbl>, conspecific <lgl>