DOI: 10.5061/dryad.zcrjdfns6
title: Quantifying microhabitat selection of snowshoe hares using forest metrics from UAS-based LiDAR

description: This dataset and code was used to evaluate the influence of forest
 structure (mapped using high-resolution light detection and ranging
 [LiDAR] data, collected on unoccupied aerial systems [UAS]) on snowshoe
 hare (Lepus americanus) microhabitat use within the temperate-boreal
 forests of northern New England. We mapped 14 forested stands (each 20 ha)
 using UAS-LiDAR (&gt;300 returns/m2) and conducted fecal pellet
 surveys to estimate snowshoe hare microhabitat selection during the
 leaf-off and leaf-on seasons of 2022. We used the LiDAR point cloud data
 to generate traditional forest metrics (canopy closure, sapling
 prevalence, and shrub prevalence) that are often used in snowshoe hare
 habitat studies and three-dimensional metrics that we hypothesized to
 represent predator exposure (viewshed and lacunarity) and food
 availability (lacunarity). The data and code herein was used to evaluate
 which of these most influenced snowshoe hare microhabitat use during the
 leaf-off and leaf-on seasons.
description: See materials and methods in 10.1002/wlb3.01529.
description: # Quantifying microhabitat selection of snowshoe hares using forest
 metrics from UAS-based LiDAR Dataset DOI:
 [10.5061/dryad.zcrjdfns6](https://doi.org/10.5061/dryad.zcrjdfns6) ##
 Description of the data and file structure For a complete description of
 the experimental efforts for which the data was collected,
 see: 10.1002/wlb3.01529. ### Files and variables The code
 `WLB-2025-01529.R2.Rmd` does not contain external data (see below). The
 empirical snowshoe hare data `pellets.csv` file is a data.frame that
 contains 1,389 observations of the pellet count response data and
 covariates to model snowshoe hare (*Lepus americanus*) microhabitat use.
 Below is a description of these data: *Response, spatial (study, x_scal,
 y_scal), temporal (season), offset, and random variables** * count: Counts
 of snowshoe hare pellets from 1 m^2^ circular plots * study: fixed effect
 factor variable with two levels ("NB", "WMNF") to
 account for density differences between study regions * x_scal: scaled
 easting (UTM) values * y_scal: scaled northing (UTM) values * yr_season:
 2022spring is the leaf-off season and 2022fall is the leaf-on season *
 days: Number of days that elapsed since the last plot counts were
 conducted. This was used as an offset in models to account for differences
 in accumulation that would vary by differing count dates * stand_id:
 Identification name of the forested stand where pellets were counted.
 stand_id was used as a random effect to account for potential
 autocorrelation of counts of plots that were nested within stands.
 *Traditional forest metric predictors** * shrubs_8.5: prevalence of shrubs
 within 8.5-m radius plot * shrubs_17: prevalence of shrubs within 17-m
 radius plot * saplings_8.5: prevalence of saplings within 8.5-m radius
 plot * saplings_17: prevalence of saplings within 17-m radius plot *
 closure_8.5: canopy closure of 8.5-m radius plot * closure_17: canopy
 closure of 17-m radius plot *Three-dimensional viewshed metric
 predictors** * mean_count_8.5: average number of filled voxels between the
 center of a plot and the plot extent along observation angles within a
 8.5-m radius plot * mean_count_17: average number of filled voxels between
 the center of a plot and the plot extent along observation angles within a
 17-m radius plot * mean_distance_8.5: average unoccluded distance from
 plot center for all observation angles within a 8.5-m radius plot *
 mean_distance_17: average unoccluded distance from plot center for all
 observation angles within a 17-m radius plot * mean_proportion_8.5:
 proportion of unoccluded observation angles in a hemispherical viewshed
 within a 8.5-m radius plot * mean_proportion_17: proportion of unoccluded
 observation angles in a hemispherical viewshed within a 17-m radius plot
 *Three-dimensional lacunarity metric predictors** * L1: distribution of
 window size 3x3x3; 0.42 m^3^ * L3: distribution of window size 7x7x7; 5.36
 m^3^ * L5: distribution of window size 11x11x11; 20.80 m^3^ * L7:
 distribution of window size 15x15x15; 52.73 m^3^ * L11: distribution of
 window size 23x23x23; 190.11 m^3^ * L15: distribution of window size
 31x31x31; 465.48 m^3^ * L17: distribution of window size 35x35x35; 669.92
 m^3^ * L27: distribution of window size 55x55x55; 2599.61 m^3^ * L51:
 distribution of window size 103x103x103; 17073.86 m^3^ ## Code/software
 The file `WLB-2025-01529.R2.Rmd` contains code to analyze data using the
 `pellets.csv` data described above. ## Access information Data and R code
 used in this study are available at Dryad (Sirén et al. 2025):
 [[10.5061/dryad.zcrjdfns6](https://doi.org/10.5061/dryad.zcrjdfns6)]([10.5061/dryad.zcrjdfns6](https://doi.org/10.5061/dryad.zcrjdfns6)). **We politely request to be contacted by parties interested in data reuse from the empirical hare study to discuss collaboration**.