| Title: | Predict Vertebrate Home-Range Sizes Using Allometric Models |
| Version: | 0.1.0 |
| Description: | Provides empirically strong allometric predictions of the home-range size of most vertebrate species. Based on inputs of mean body size, taxonomic class, and optional classifications of environment and trophic level or foraging mode, 'HomeRangeR' predicts home-range size using the most appropriate model for the species selected from a collection of empirically derived vertebrate home-range allometries. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| LazyData: | true |
| Depends: | R (≥ 3.5) |
| RoxygenNote: | 7.3.3 |
| Imports: | dplyr |
| NeedsCompilation: | no |
| Packaged: | 2026-06-27 12:26:21 UTC; dalemoskoff |
| Author: | Dale Moskoff [aut, cre] |
| Maintainer: | Dale Moskoff <d.moskoff@mail.utoronto.ca> |
| Repository: | CRAN |
| Date/Publication: | 2026-07-03 12:00:21 UTC |
HomeRangeR home-range allometry database
Description
Allometric scaling relationships used by HomeRangeR to estimate vertebrate home-range size (Moskoff & Mandrak, 2026).
Format
A data frame with 17 variables:
- taxonomy
Taxonomic grouping
- environment
Environmental grouping
- trophic_level
Trophic guild or foraging mode
- slope
Allometric slope (b)
- slope_low
Lower 95 percent CI
- slope_high
Upper 95 percent CI
- intercept
Intercept (log10(a))
- intercept_low
Lower 95 percent CI
- intercept_high
Upper 95 percent CI
- r2_multiple
Multiple R-squared
- r2_adjusted
Adjusted R-squared
- p_value
Model p-value
- lambda
Phylogenetic signal
- lambda_low
Lower 95 percent CI
- lambda_high
Upper 95 percent CI
- n
Sample size
- response_unit
Units of home range
Source
Moskoff, D. R., & Mandrak, N. E. (2026). A database of vertebrate home-range allometries for conservation applications. Unpublished manuscript. Department of Physical and Environmental Sciences, University of Toronto Scarborough.
List supported environment inputs
Description
List supported environment inputs
Usage
environment_options()
Value
Character vector of supported environment type classifications.
Predict mean home-range size of vertebrate species
Description
Predicts mean home-range size of bird, mammal, fish, lizard, snake, and turtle species using allometric scaling relationships derived from empirical data (Moskoff & Mandrak, 2026). HomeRangeR contains a hierarchy of allometric models fitted within nested subsets of taxonomic class, environment type, and trophic guild or foraging mode. The function automatically selects the most appropriate model available for the supplied combination of taxonomy, environment, and trophic level or foraging mode. When a finer-scale subset is unavailable or was not retained because it did not explain significant variation in home-range scaling, the function falls back to the most appropriate coarser grouping and returns a note describing the decision. See Moskoff & Mandrak (2026) for methods.
Usage
predict_home_range(
body_mass_kg,
taxonomy,
environment = NA,
trophic_level = NA
)
Arguments
body_mass_kg |
Numeric. Mean body mass of the species in kilograms. Sex-weighted average preferred when species exhibits sexual size dimorphism. |
taxonomy |
Character string specifying the taxonomic class of the species. Supported values include:
Amphibians are not currently represented in HomeRangeR. |
environment |
Optional character string specifying the environment occupied by the species. Supported values vary among taxonomic groups and include:
|
trophic_level |
Optional trophic level or foraging mode classification. Snakes and turtles are classified by foraging strategy as:
All other taxa are classified by trophic guild as:
|
Details
Allometric formulae used by HomeRangeR were obtained using phylogenetic generalized least square (PGLS) regressions of species' mean home-range size by mean body size. PGLS regression is an extension of standard least squares estimation including a phylogenetic covariance matrix representing the expected covariance structure among the residuals of the regression model based on phylogeny (Freckleton et al., 2002). PGLS was chosen over other regression methods to account for phylogenetic nonindependence of data points (Garland & Adolph, 1994; Harvey & Pagel, 1991; Perry & Pianka, 1997; Rees, 1995). Formulae used by HomeRangeR follow the syntax:
\log_{10}(HRA) = \log_{10}(a) + b \times \log_{10}(M)
where:
-
HRAis home-range area; -
Mis body mass in kilograms; -
ais the taxonomically-specific, empirically-derived intercept; -
bis the taxonomically-specific, empirically-derived slope.
Predicted home-range size is returned on the original scale:
HRA = 10^{(\log_{10}(a) + b \log_{10}(M))}
Home-range estimates are reported in square kilometres (km^2)
except for river fishes, for which home-range length is reported in
linear kilometres (km). It is recommended that the home ranges of river
fishes be converted from length to area using the mean width of the relevant
occupied river estimated by the Stahler stream order, as per Cheng (2013).
The function returns both the estimated home-range area of the species and the metadata associated with the selected model, including confidence intervals, model fit statistics, phylogenetic signal estimates, size of species sample used to derive the home-range scaling relationship, and explanatory notes.
Value
A list containing:
estimated_home_range
response_unit
model_used
slope
intercept
slope_confidence_interval
intercept_confidence_interval
r2_multiple
r2_adjusted
p_value
lambda
lambda_confidence_interval
sample_size
note
References
Cheng, J. (2013). Spatial criteria used in IUCN assessment overestimate area of occupancy for freshwater taxa. Unpublished Master’s thesis. University of Toronto.
Freckleton, R.P., Harvey, P.H., & Pagel, M. (2002). Phylogenetic analysis and comparative data: A test and review of evidence. The American Naturalist, 160(6), 712–726. https://doi.org/10.1086/343873
Garland, T., & Adolph, S.C. (1994). Why not to do two-species comparative studies: Limitations on inferring adaptation. Physiological Zoology, 67, 797-828.
Harvey, P.H., & Pagel, M.D. (1991). The comparative method in evolutionary biology. Oxford University Press.
Moskoff, D.R., & Mandrak, N.E. (2026). A database of vertebrate home-range allometries for conservation applications. Unpublished manuscript. Department of Physical and Environmental Sciences, University of Toronto Scarborough.
Perry, G., & Pianka, E.R. (1997). Animal foraging: Past, present, and future. Trends in Ecology and Evolution, 12, 360-364.
Rees, M. (1995). EC-PC comparative analyses? Journal of Ecology, 83(5), 891-893. https://doi.org/10.2307/2261426
See Also
taxonomy_options,
environment_options,
trophic_level_options
Examples
# Marine mammal
predict_home_range(
body_mass_kg = 10,
taxonomy = "mammals",
environment = "marine"
)
# Herbivorous terrestrial mammal
predict_home_range(
body_mass_kg = 50,
taxonomy = "mammals",
environment = "terrestrial",
trophic_level = "herbivorous"
)
# Herbivorous terrestrial fish
predict_home_range(
body_mass_kg = 2,
taxonomy = "fishes",
environment = "marine",
trophic_level = "herbivorous"
)
# Freshwater fish
predict_home_range(
body_mass_kg = 1,
taxonomy = "fishes",
environment = "river"
)
# Display supported inputs
taxonomy_options()
environment_options()
trophic_level_options()
List supported taxonomy inputs
Description
List supported taxonomy inputs
Usage
taxonomy_options()
Value
Character vector of supported taxonomic groups.
List supported trophic guild / foraging strategy inputs
Description
List supported trophic guild / foraging strategy inputs
Usage
trophic_level_options()
Value
Character vector of supported trophic guild or foraging mode classifications.