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Climate velocity: geographically nearest climate analogs

Source: R/analog_velocity.R
analog_velocity.Rd

Computes, for each focal location, the geographic nearest neighbor(s) in a reference dataset that satisfy a specified maximum climate distance threshold. This implements analog-based climate velocity (Hamann et al. 2015; Dobrowski and Parks 2016).

Usage

analog_velocity(
  x,
  pool,
  x_cov = NULL,
  values = NULL,
  coord_type = "auto",
  max_clim,
  max_geog = NULL,
  k = 1,
  index_res = "auto",
  n_threads = NULL,
  downsample = 1,
  seed = NULL,
  progress = FALSE
)

Arguments

x

Focal locations for which analogs will be found. Should be a matrix/data.frame with columns x, y, and climate variables, or a SpatRaster with climate variable layers.

pool

The reference dataset to search for analogs. Either:

  • Matrix/data.frame with columns x, y, and climate variables, or SpatRaster with climate variable layers, OR

  • An analog_index object created by build_analog_index() (for repeated queries).

x_cov

Optional focal-specific covariance matrices for Mahalanobis distance calculations. Should be a matrix or data.frame with one row per focal location and one column per unique covariance component, or a SpatRaster with a layer for each component. For n climate variables, there are n*(n+1)/2 unique components, ordered as: variances first (diagonals), then covariances (upper triangle by row).

values

Optional user-defined variables for each reference location in pool to aggregate across selected analogs. Can be a numeric vector (single variable), matrix or data.frame with numeric columns (multiple variables), or a SpatRaster with one or more numeic layers. Must have exactly the same number of reference locations as pool.

When provided, enables value-based aggregation stats "sum", "mean", "weighted_sum", and "weighted_mean". For stat = NULL/"none" (pairs mode), value columns are included in output for each analog pair.

coord_type

Coordinate system type:

  • "auto" (default): Automatically detect from coordinate ranges.

  • "lonlat": Unprojected lon/lat coordinates (uses great-circle distance; assumes max_geog is in km).

  • "projected": Projected XY coordinates (uses planar distance; assumes max_geog is in projection units).

max_clim

Maximum climate distance constraint (default: NULL = no climate constraint). Can be either:

  • A scalar: Euclidean radius in climate space (e.g., 0.5)

  • A vector: Per-variable absolute differences (length must equal number of climate variables)

Only reference locations within this climate distance are considered. When x_cov is provided, scalar thresholds are interpreted in Mahalanobis distance units.

max_geog

Maximum geographic distance constraint (default: NULL = no geographic constraint). When specified, only reference locations within this distance are considered. Radius units should be specified in kilometers if coord_type = "lonlat", or in projected coordinate units if coord_type = "projected".

k

Number of nearest analogs to return per focal location for kNN selection modes. Required when select is "knn_geog" or "knn_clim"; must be NULL for select = "all".

index_res

Tuning parameter giving the number of bins per dimension of the internally-used lattice search index. Either:

  • A positive integer.

  • "auto" (the default): Automatically tune the index resolution by optimizing compute time on a subsample of focal points. If focal has relatively few rows, auto-tuning is skipped and a default resolution of 16 is used.

Ignored if pool is an analog_index (uses index's resolution).

n_threads

Optional integer number of threads to use for the computation. If NULL (default), the global RcppParallel setting is used (see RcppParallel::setThreadOptions).

downsample

Optional downsampling rate (0-1) for the reference pool, indicating the proportion of points to retain. Values < 1 reduce memory and improve speed at some cost to precision. Default is 1.0 (no downsampling). Ignored if pool is a pre-built index.

seed

Optional random seed for reproducible downsampling. If NULL (default), uses current R random state. Ignored if pool is a pre-built index or downsample = 1.

progress

Logical; if TRUE, display a progress bar during computation. Progress tracking works by splitting the focal dataset into chunks and processing them sequentially. Useful for large datasets. Default is FALSE.

Value

Return type depends on input format and query mode.

Returns a data.frame, unless x is a SpatRaster and results have exactly one record per input cell (aggregation mode, or pairwise with k = 1), in which case returns a SpatRaster with one layer per output variable.

Pairwise mode (stat = NULL or "none") returns one row per focal-analog pair, with the following variables:

  • index, x, y: Focal location (1-based index and coordinates) corresponding to input x

  • analog_index, analog_x, analog_y: Analog location corresponding to input pool

  • clim_dist: Climate distance (Euclidean or Mahalanobis)

  • geog_dist: Geographic distance (km for lonlat, projection units otherwise)

  • Value columns (if values provided): one per variable

Aggregation mode (one or more stat values) returns one row per focal location, with the following variables:

  • index, x, y: Focal location

  • One column per requested statistic. For stat with single values variable: column named by stat (e.g., sum, mean). For stat with multiple values variables: columns named {stat}_{varname} (e.g., sum_biomass, mean_richness)

All results include metadata attributes (select, stat, weight, etc.). Use analog_summary() to view a formatted summary.

Details

This function is a wrapper that calls analog_search() using select = "knn_geog". and is used for estimating analog-based climate velocity.

References

Hamann A, Roberts DR, Barber QE, Carroll C, Nielsen SE (2015). "Velocity of climate change algorithms for guiding conservation and management." Global Change Biology, 21(2), 997-1004. doi:10.1111/gcb.12736

Dobrowski SZ, Parks SA (2016). "Climate change velocity underestimates climate change exposure in mountainous regions." Nature Communications, 7, 12349. doi:10.1038/ncomms12349

See also

analog_search() for the underlying flexible analog search function; tiled_analog_search() for memory-safe searches on large raster datasets.

Examples

if (FALSE) { # \dontrun{
# One-shot query
v <- analog_velocity(
  x = clim$clim1,
  pool = clim$clim2,
  max_clim = 0.5,
  k = 1
)

# With pre-built index (for repeated queries)
index <- build_analog_index(clim$clim2)
v1 <- analog_velocity(x = sites1, pool = index, max_clim = 0.5, k = 1)
v2 <- analog_velocity(x = sites2, pool = index, max_clim = 0.3, k = 1)

# With focal-specific covariance matrices
v_mahal <- analog_velocity(
  x = clim$clim1,
  pool = clim$clim2,
  x_cov = baseline_covariances,
  max_clim = 2,  # In Mahalanobis distance units
  k = 1
)
} # }