DOI: 10.5061/dryad.k98sf7mjw
title: Understanding <em>Picoides articus</em> (Black-backed Woodpecker) occupancy in fire-suppressed forests of the Northern Blue Mountains, USA

description: Fire is a significant disturbance agent, impacting forest structure and
 composition. In fire-adapted forests, fire can foster biodiversity by
 resetting successional processes and increasing habitat heterogeneity.
 However, fire suppression practices have altered historical fire regimes
 and left fire-adapted ecosystems largely unburned and the use of unburned
 forests by post-fire habitat specialists is understudied. Picoides
 arcticus (Black-backed Woodpecker) is a post-fire specialist that thrives
 in recently burned coniferous forests by exploiting heterogeneous patches
 of live and dead trees. Despite being a regional species of conservation
 concern, its occurrence and habitat use remains poorly understood in the
 managed forests of the northern Blue Mountains of Washington and Oregon,
 USA. Here, we combine passive acoustic monitoring and Bayesian occupancy
 modeling to understand Picoides arcticus occurrence across two National
 Forests during the breeding season. We examined how the prevalence of
 prominent tree species, attributes of forest structure, and fire history
 relate to occurrence. We found the odds of Picoides arcticus occupancy was
 3.67 times larger for every 2.88 m2/ha increase in Pinus contorta basal
 area and 2.16 times higher with every 5.04 m2/ha increase in Pinus
 ponderosa basal area. The small number of survey stations classified as
 burned limited our ability to identify an effect of fire history. Our
 findings provide insight into how a fire-adapted species is using largely
 unburned forest. We also fill important knowledge gaps for a priority
 species of conservation concern by creating a species distribution map.
 Collectively, this information can inform active forest management and
 conservation decisions.
description: # Dryad dataset Dataset DOI:
 [10.5061/dryad.k98sf7mjw](10.5061/dryad.k98sf7mjw) ## Description of the
 data and file structure Audio recordings were collected using automated
 recordings units randomly dispersed across the Umatilla and
 Wallowa-Whitman National Forests in 2022 and 2023. Audio recordings were
 processed using BirdNET v2.4. Detection/Non-detection data were collected
 for each week of recording by manually reviewing Black-backed Woodpecker
 detections using a top-down listening approach wherein detections were
 sorted in descending order by BirdNET confidence scores before manual
 review. Habitat covariates were generated using remotely-sensed datasets
 (LEMMA and LANDFIRE) and averaging or classifying values for each site
 using a 200m radius, circular buffer centered on each sampling site.
 Bayesian occupancy models and slab/spike priors were used to estimate and
 identify covariates relevant to Black-backed Woodpecker occurrence. See
 Method's section of manuscript for more details. ### Files and
 variables #### File: bbwo_site_covariates.csv **Description:**  #####
 Variables * station: location recordings were collected, first five
 numerical characters denote hexagon * fire_one_year: binary variable
 denoting if the site burned in the last 1 year * fire_two_five_year:
 binary variable denoting if the site burned in the last 2 to 5 years *
 fire_six_ten_year: binary variable denoting if the site burned in the last
 6 to 10 years * med_snag_biomass: biomass of snags with a DBH of 25-50 cm,
 measured in kg/ha * lrg_snag_biomass: biomass of snags between 50-75 cm
 DBH, measured in kg/ha * med_downed_wood: biomass of downed wood with a
 DBH of 50-75 cm DBH, measured in kg/ha * lrg_downed_wood: number of pixels
 within the 200m radius, circular buffer with a non-zero biomass of downed
 wood with a DBH &gt; 100 cm * grand_fir_BA: basal area of grand fir,
 measured in m^2^/ha * can_cov: average canopy cover within the 200m
 radius, circular buffer, measured in percantage * larch_BA: basal area of
 larch, measured in m^2^/ha * lodgepole_BA: basal area of lodgepole pine,
 measured in m^2^/ha * spruce_BA: basal area of spruce, measured in m^2^/ha
 * ponderosa_BA: basal area of ponderosa pine, measured in m^2^/ha *
 douglas_fir_BA: basal area of douglas fir, measured in m^2^/ha *
 elevation: average elevation of each station, measured in meters ####
 File: bbwo_detection_data_090425.csv **Description:** Black-backed
 Woodpecker (BBWO) occupancy data and monitoring meta data used in
 occupancy analysis ##### Variables * year: year station was monitored
 (2022 or 2023) * station: identifier of location samples were collected,
 first 5 numerical characters refer to the hexagon ID and the leter denotes
 the station ID within a given hexagon. * week: week of sampling within the
 survey period of a given station. First week of sampling denoted by 1,
 second week of sampling denoted by 2, etc. * total_monitoring_time: number
 of hours of audio recording collected during a given sampling period *
 min_date: date that the corresponding survey period began on * bbwo_state:
 binary variable denoting if a BBWO was detected or undetected within a
 given survey period * jday: day of the year a station's survey period
 began, denoted by the julian day value of min_date #### File:
 BBWO_Occupancy_Model_Script_102125.R **Description:** R script containing
 code used to fit Bayesian occupancy models, conduct the indicator analysis
 using spike and slab priors, and plot results. #### File:
 BBWO_data_code_for_submission.Rproj **Description:** .Rproj file used to
 increase the reproducibility of the analysis. This file should be opened
 before using the provided R script. #### File:
 BBWO_occupancy_probability_102925.tif **Description:** This raster depicts
 spatially continuous estimates of Black-backed Woodpecker (*Picoides
 arcticus*) occupancy probability across the study region. Each pixel value
 represents the posterior mean probability of occupancy predicted from a
 Bayesian occupancy model. **Format:** GeoTIFF (single-band raster)
 **Coordinate reference system:** NAD83 / Conus Albers (EPSG:5070)
 **Spatial resolution:** 30 × 30 meters **Number of Layers:** 1 **Value
 type:** Continuous **Value range:** 0.196–0.999 **Interpretation:** Pixel
 values represent the estimated probability that a site is occupied by
 Black-backed Woodpeckers. Higher values indicate greater predicted
 occupancy probability. ## Code/software ### Occupancy Analysis **R version
 4.2.0 (2022-04-22)** **Platform:** x86_64-apple-darwin17.0 (64-bit)
 **Running under:** macOS Monterey 12.3.1 **Matrix products:** default
 **LAPACK:**
 /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib **locale:** \[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 **attached base packages:** \[1] stats graphics grDevices utils datasets methods base other attached packages: \[1] cowplot_1.1.3 tidyr_1.3.1 ggplot2_3.5.1 dplyr_1.1.4 reshape2_1.4.4 jagsUI_1.6.2 R2jags_0.8-9 \[8] rjags_4-16 coda_0.19-4.1 **loaded via a namespace (and not attached):** \[1] Rcpp_1.0.12 pillar_1.9.0 compiler_4.2.0 plyr_1.8.9 tools_4.2.0 boot_1.3-30 \[7] lifecycle_1.0.4 tibble_3.2.1 gtable_0.3.5 lattice_0.22-6 pkgconfig_2.0.3 rlang_1.1.3 \[13] cli_3.6.2 rstudioapi_0.16.0 parallel_4.2.0 withr_3.0.0 stringr_1.5.1 generics_0.1.3 \[19] vctrs_0.6.5 grid_4.2.0 tidyselect_1.2.1 glue_1.7.0 R6_2.5.1 fansi_1.0.6 \[25] purrr_1.0.2 magrittr_2.0.3 scales_1.3.0 R2WinBUGS_2.1-22.1 abind_1.4-5 colorspace_2.1-0 \[31] utf8_1.2.4 stringi_1.8.4 munsell_0.5.1 **Maps and Species Distribution Map** **R version 4.2.0 (2022-04-22)** **Platform:** x86_64-apple-darwin17.0 (64-bit) **Running under:** macOS Monterey 12.3.1 **Matrix products:** default **LAPACK:** /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib **locale:** \[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 **attached base packages:** \[1] tools stats graphics grDevices utils datasets methods base **other attached packages:** \[1] viridis_0.6.5 viridisLite_0.4.2 purrr_1.0.2 dplyr_1.1.4 terra_1.7-46 sf_1.0-12 **loaded via a namespace (and not attached):** \[1] Rcpp_1.0.12 rstudioapi_0.16.0 magrittr_2.0.3 units_0.8-5 munsell_0.5.1 tidyselect_1.2.1 \[7] colorspace_2.1-0 R6_2.5.1 rlang_1.1.3 fansi_1.0.6 grid_4.2.0 gtable_0.3.5 \[13] KernSmooth_2.23-22 utf8_1.2.4 cli_3.6.2 e1071_1.7-14 DBI_1.2.3 class_7.3-22 \[19] tibble_3.2.1 lifecycle_1.0.4 gridExtra_2.3 ggplot2_3.5.1 codetools_0.2-20 vctrs_0.6.5 \[25] glue_1.7.0 proxy_0.4-27 compiler_4.2.0 pillar_1.9.0 scales_1.3.0 generics_0.1.3 \[31] classInt_0.4-10 pkgconfig_2.0.3 | QGIS version | 3.32.3-Lima | QGIS code revision | [67d46100b5b](https://github.com/qgis/QGIS/commit/67d46100b5b) | | :----------------------------- | :------------------- | :----------------- | :------------------------------------------------------------- | | Qt version | 5.15.2 | 
 
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 | | Python version | 3.9.5 | 
 
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 | | GDAL/OGR version | 3.3.2 | 
 
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 | | PROJ version | 8.1.1 | 
 
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 | | EPSG Registry database version | v10.028 (2021-07-07) | 
 
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 | | GEOS version | 3.9.1-CAPI-1.14.2 | 
 
 | 
 
 | | SQLite version | 3.35.2 | 
 
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 | | PDAL version | 2.3.0 | 
 
 | 
 
 | | PostgreSQL client version | unknown | 
 
 | 
 
 | | SpatiaLite version | 5.0.1 | 
 
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 | | QWT version | 6.1.6 | 
 
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 | | QScintilla2 version | 2.11.5 | 
 
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 | | OS version | macOS 12.3 | 
 
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 | ## Access information Other publicly accessible locations of the data:
 * LANDFIRE and LEMMA were used or remotely sensed habitat covariates Data
 was derived from the following sources: *
 [https://www.landfire.gov/data](https://www.landfire.gov/data) *
 [https://lemma.forestry.oregonstate.edu/data/structure-maps](https://lemma.forestry.oregonstate.edu/data/structure-maps)