Calculate Basal Area with Decay Function

Description

This function calculates the basal area across a given set of trees, applying a decay effect based on distance and species identity for each tree within a given radius.

Usage

ba_decay(
  mu_values,
  sp,
  gx,
  gy,
  ba,
  r,
  exponential_normal = FALSE,
  edge_correction = c("none", "safe"),
  bounds = NULL
)

Arguments

Details

The function applies an exponential decay model where the basal area contribution diminishes with distance from the focal tree:

\text{decayed basal area} = \text{ba} \cdot \exp\left(-\frac{\text{dist}}{\mu}\right)

where 'mu' is the decay parameter, 'ba' is the basal area, and 'dist' is the Euclidean distance between trees.

Value

A list with two matrices:

'con_ba_matrix'

A numeric matrix of basal areas with decay applied for conspecific (same species) trees.

'total_ba_matrix'

A numeric matrix of basal areas with decay applied for all trees (conspecific + heterospecific).

Examples

# Generate a sample dataset
set.seed(42)
sample_data <- data.frame(
  latin = sample(letters[1:4], 100, replace = TRUE),
  gx = runif(100, 0, 10),
  gy = runif(100, 0, 10),
  ba = runif(100, 10, 30)
)
mu_values <- c(1, 3, 5, 7)
ba_decay(
  mu_values = mu_values,
  sp = sample_data$latin,
  gx = sample_data$gx,
  gy = sample_data$gy,
  ba = sample_data$ba,
  r = 3,
  exponential_normal = FALSE
)

Long-format decay table

Description

Transform the matrices returned by 'ba_decay' into a tidy table that can be joined with other data or mapped with 'ggplot2'.

Usage

ba_decay_long(
  mu_values,
  sp,
  gx,
  gy,
  ba,
  r,
  exponential_normal = FALSE,
  edge_correction = c("none", "safe"),
  bounds = NULL
)

Arguments

Value

A data frame with 'tree_id', 'species', 'mu', 'con_ba', and 'total_ba'.

Calculate Simple Basal Area

Description

This function calculates the total basal area (conspecific + heterospecific) for a given set of tree data, focusing on the number of focal trees and a radius parameter. The basal area represents the cumulative cross-sectional area of tree trunks, either unadjusted or adjusted for a simple distance-weighted decay model.

Usage

ba_simple(
  sp,
  gx,
  gy,
  ba,
  r,
  dist_weighted = FALSE,
  edge_correction = c("none", "safe"),
  bounds = NULL
)

Arguments

Details

The function either: - Calculates the unadjusted basal area if 'dist_weighted = FALSE'. - Applies a simple distance-weighted approach ('ba / dist') if 'dist_weighted = TRUE'.

Value

A list with two numeric vectors:

'con_ba'

A numeric vector representing the cumulative basal area of conspecific trees within the radius.

'total_ba'

A numeric vector representing the cumulative basal area of all trees (conspecific + heterospecific) within the radius.

Examples

# Generate a sample dataset
set.seed(42)  # For reproducibility
sample_data <- data.frame(
  latin = sample(letters[1:4], 100, replace = TRUE),
  gx = runif(100, 0, 10),  # Spatial coordinates between 0 and 10
  gy = runif(100, 0, 10),
  ba = runif(100, 10, 30)  # Basal area between 10 and 30
)

# Calculate with distance weighting
ba_simple(
  sp = sample_data$latin,
  gx = sample_data$gx,
  gy = sample_data$gy,
  ba = sample_data$ba,
  r = 3,  # Radius within the spatial scale
  dist_weighted = TRUE
)

# Calculate without distance weighting
ba_simple(
  sp = sample_data$latin,
  gx = sample_data$gx,
  gy = sample_data$gy,
  ba = sample_data$ba,
  r = 3,
  dist_weighted = FALSE
)

Count Conspecific Trees

Description

This function counts the number of conspecific trees within a given radius for each focal tree.

Usage

count_con(sp, gx, gy, r, edge_correction = c("none", "safe"), bounds = NULL)

Arguments

Value

A numeric vector containing the count of conspecific trees within the radius for each focal tree.

Examples

sample_data <- data.frame(
  latin = sample(letters[1:4], 100, replace = TRUE),
  gx = runif(100, 0, 10),
  gy = runif(100, 0, 10)
)
count_con(
  sp = sample_data$latin,
  gx = sample_data$gx,
  gy = sample_data$gy,
  r = 3
)

Count Total Trees

Description

This function counts the total number of trees within a given radius for each focal tree.

Usage

count_total(gx, gy, r, edge_correction = c("none", "safe"), bounds = NULL)

Arguments

Value

A numeric vector containing the count of all trees within the radius for each focal tree.

Examples

sample_data <- data.frame(
  gx = runif(100, 0, 10),
  gy = runif(100, 0, 10)
)
count_total(
  gx = sample_data$gx,
  gy = sample_data$gy,
  r = 3
)

Neighborhood summaries for basal area and counts

Description

Provide a tidy summary of pairwise neighborhood basal area and counts, optionally including decay results for a vector of decay parameters.

Usage

neigh_ba(
  sp,
  gx,
  gy,
  ba,
  r,
  mu_values = NULL,
  dist_weighted = FALSE,
  exponential_normal = FALSE,
  edge_correction = c("none", "safe"),
  bounds = NULL
)

Arguments

Value

A list with * 'summary': data frame with 'tree_id', 'species', 'con_ba', 'total_ba', 'con_count', 'total_count'. * 'decay': ('NULL' or) long data frame with 'tree_id', 'species', 'mu', 'con_ba', 'total_ba'.

The 'summary' component also includes derived columns: 'prop_con_ba', 'het_ba', 'het_count', and 'competition_index'.

Examples

sample_data <- data.frame(
  latin = sample(letters[1:4], 10, replace = TRUE),
  gx = runif(10, 0, 10),
  gy = runif(10, 0, 10),
  ba = runif(10, 10, 30)
)
neigh_ba(
  sp = sample_data$latin,
  gx = sample_data$gx,
  gy = sample_data$gy,
  ba = sample_data$ba,
  r = 3,
  mu_values = c(1, 3)
)

Neighborhood metrics across multiple radii

Description

Compute basal area sums and counts for each tree across multiple radii in one pass.

Usage

neigh_multi_r(
  sp,
  gx,
  gy,
  ba,
  r_values,
  dist_weighted = FALSE,
  edge_correction = c("none", "safe"),
  bounds = NULL
)

Arguments

Value

A tidy tibble with 'tree_id', 'species', 'radius', 'con_ba', 'total_ba', 'con_count', 'total_count', 'prop_con_ba', 'het_ba', 'het_count', and 'competition_index'.

Examples

sample_data <- data.frame(
  latin = sample(letters[1:4], 10, replace = TRUE),
  gx = runif(10, 0, 10),
  gy = runif(10, 0, 10),
  ba = runif(10, 10, 30)
)
neigh_multi_r(
  sp = sample_data$latin,
  gx = sample_data$gx,
  gy = sample_data$gy,
  ba = sample_data$ba,
  r_values = c(3, 5)
)