DOI: 10.5061/dryad.v9s4mw71b
title: Is green the new black? Black-backed Woodpecker vital rates do not differ between unburned and burned forests within a pyrodiverse landscape

description: Woodpeckers can reflect rapid changes to forest health and often serve as
 indicator species to help guide forest management decisions. The
 Black-backed Woodpecker (Picoides arcticus) is known for its strong
 association with recently burned forests and is a species of conservation
 concern due to habitat loss stemming from post-fire management of burned
 forest. Recently, several studies have found the Black-backed Woodpecker
 occupying extensive areas of unburned (i.e., green) forests in the western
 part of its range during the breeding season, raising questions about
 whether green forests can support viable nesting populations in this
 region. We studied breeding Black-backed Woodpeckers in southern Oregon,
 USA to evaluate whether two vital rates critical to population recruitment
 – nest survival and post-fledging survival – differed between green and
 burned forests. During 2018, 2019, and 2021, we monitored 91 Black-backed
 Woodpecker nests (n = 34 in green forest, n = 57 in burned forest) and
 found that neither daily nest survival rate nor reproductive output (i.e.,
 the number of fledglings per successful nest) differed between nests
 located in green and burned forest; however, nestling body condition was
 slightly enhanced in green forest. We also quantified survival of recently
 fledged individuals using VHF radio telemetry and found that the survival
 rate of birds in green forest was nearly identical to those in burned
 forest, with most mortalities occurring within 4 weeks of fledging. Taken
 together, our results indicate that Black-backed Woodpeckers in green
 forests were equally successful at breeding as conspecifics in recently
 burned forest, although nesting densities in the green forest we studied
 were lower than those in burned forest. Our findings indicate certain
 types of green forest, particularly mature lodgepole pine, can support
 viable populations of the Black-backed Woodpecker in the western portion
 of its range. This finding has conservation implications given that green
 forest occupies the majority of the forested landscape in this region and
 is often juxtaposed to areas subjected to high-severity fire. Therefore,
 practices that promote pyrodiversity – landscape-level spatial and
 temporal variability in fire effects – as well as connectivity between
 green and burned forest within fire-prone landscapes are likely to provide
 the greatest conservation benefit for this species.  
description: <strong>Study Area</strong> We
 studied Black-backed Woodpeckers during the 2018, 2019, and 2021 breeding
 seasons (May–August) within a ca. 165,000 ha study area in the Klamath
 Basin of southern Oregon covering public lands that included the Klamath,
 Coquille, and Chemult Ranger Districts of the Fremont-Winema National
 Forest, the Diamond Lake Ranger District on the Umpqua National Forest,
 and the Sun Pass State Forest. Our study sites ranged from 1280–1950
 meters above sea level (m.a.s.l.) in forests comprised of lodgepole pine,
 ponderosa pine, mixed conifer, and mixed pine. We defined mixed conifer
 stands as those containing white fir (<em>Abies</em>
 <em>concolor</em>), red fir (<em>Abies</em>
 <em>magnifica</em>), grand fir (<em>Abies</em>
 <em>grandis</em>), Douglas-fir
 (<em>Pseudotsuga</em> <em>menziesii</em>),
 Engelmann spruce (<em>Picea</em>
 <em>engelmannii</em>), and/or mountain hemlock
 (<em>Tsuga</em> <em>mertensiana</em>), and mixed
 pine stands as those containing lodgepole pine, ponderosa pine, western
 white pine (<em>Pinus</em> <em>monticola</em>),
 and/or sugar pine (<em>Pinus</em>
 <em>lambertiana</em>). Lower elevation sites were typically
 drier and characterized by increased abundance of lodgepole pine on coarse
 pumice soils, whereas higher elevations had more moisture and harbored
 more ponderosa pine, mixed pine, and mixed conifer (Hagmann et al. 2019).
 Historically, this region experienced frequent, widespread wildfire
 accompanied by low mortality rates of trees, with fire return intervals
 averaging 13 y (range: 7–25 y) until fire exclusion began in approximately
 1918 (Hagmann et al. 2019). Average temperatures during the Black-backed
 Woodpecker breeding season in our study area averaged 10–12°C with a range
 of -6°C (2018) to 34°C (2021), with precipitation ranging from 30 mm
 (2021) to 224 mm (2019) (SNOTEL weather station, Sun Pass, Oregon, 1646
 m.a.s.l.). Contemporary forest management in our study area is conducted
 in collaboration with the Klamath Tribes with the goals of reducing
 hazardous fuel loads, improving habitat quality for species of
 conservation interest, and undertaking sustainable timber production that
 enhances older age classes of ponderosa pine (Charnley et al. 2017).
 Nearly all harvesting operations on the Fremont-Winema National Forest
 portion of our study area take place via thinning of trees between 18–76
 cm diameter at breast height (DBH) depending on the species and averaging
 approximately 4,200 ha treated annually (Charnley et al. 2017). On the Sun
 Pass State Forest, group selection cuts of 0.2–2 ha are implemented at a
 target of 14,000–28,000 m<sup>3</sup>/y and lodgepole pine is
 clearcut in 8.1–20.2 ha sized blocks on 80-year rotations (Charnley et al.
 2017). <strong>Nest Searching and
 Monitoring</strong> During each year of the
 study, we searched for Black-backed Woodpecker nests starting the first
 week of May and continuing until mid-July. To cover the range of green
 forest used by Black-backed Woodpeckers in the broader landscape we
 targeted our searches to green forest that was classified as one of the
 four composition types described above (i.e., lodgepole pine, ponderosa
 pine, mixed conifer, and mixed pine), and contained potential nest trees
 of a minimum of 15 cm DBH (Verschuyl et al. 2021). The green forest areas
 we targeted for nest-searching were generally absent of major disturbance,
 differentiating our study from prior research in green forest dominated by
 beetle-killed trees (Bonnot et al. 2008, Rota et al. 2014, Matseur et al.
 2018, Tingley et al. 2020). We also searched for nests in recently burned
 conifer forest in areas that were interspersed with green forest
 throughout our focal landscape, including the 2017 North Pelican Fire
 (1,452 ha), the 2017 Blanket Creek Fire (13,484 ha), the 2018 Timber
 Crater 6 Fire (1,265 ha), the 2020 Thielsen Fire (4,037 ha), and the 2020
 Two Four Two Fire (5,857 ha). We based fire severity measurements off of
 the 4-class Composite Burn Index (CBI-4) provided by the USDA Forest
 Service Rapid Assessment of Vegetation Condition After Wildfire (RAVG)
 program (Key and Benson 2006, U.S. Forest Service 2022). Our initial
 nest-searching efforts revealed that (1) Black-backed Woodpecker nests in
 green forests were most likely to occur in lodgepole stands, (2)
 Black-backed Woodpeckers were most likely to be found nesting in recently
 burned areas that experienced moderate- to high-severity fire, and (3)
 Black-backed Woodpecker nesting densities were greater in recently burned
 forest relative to green forest. To maximize our sample sizes, we
 therefore undertook greater cumulative search effort in lodgepole pine
 relative to other green forest types, greater cumulative search effort in
 moderate- to high-severity burned areas relative to low-severity burned
 areas, and greater cumulative search effort in green forest relative to
 burned forest. Importantly, our primary goal was to obtain a
 representative sample of nests in both green and burned forests, and we
 have no reason to believe this nest-searching approach would have resulted
 in any biases when estimating vital rates. Additionally, we note that
 although we refer to unburned lodgepole pine forest as “green” forest and
 forest recently disturbed by high-severity fire as “burned” forest, we
 recognize these coarse descriptions may not be suitable for characterizing
 the full spectrum of forest types that the Black-backed Woodpecker may use
 in other parts of its range (Trembley et al. 2020).  
 To locate nests, we used a combination of systematically targeted
 and opportunistic ground-based surveys dispersed across our study area.
 Our surveys included passive searches in potential nesting habitat for
 Black-backed Woodpecker activity, as well as active surveys where we used
 a game caller (FOXPRO NX4, FOXPRO Inc, Lewistown, PA, USA) to broadcast
 vocalizations and drumming sounds recorded in the Pacific Northwest
 (Macaulay Library of Natural Sounds, Cornell Laboratory of Ornithology,
 Ithaca, NY, USA) to locate territorial individuals. Our broadcasted
 recordings were audible to a human observer 500 m distant within open
 forest (authors, personal observation), so we assumed that woodpeckers
 could detect recorded vocalizations at least 500 m distant from our
 broadcasting locations. Once a Black-backed Woodpecker was detected, we
 followed it for up to 2 hr to determine whether the bird was paired and
 showed signs of nesting behavior or appeared to be unpaired and was not
 nesting. We located nests by following adults to their nest sites,
 observing adult activity at the nest tree (e.g., excavating, nestling
 provisioning), or by detecting nesting begging calls emanating from nest
 trees. After we located nests, we re-visited them approximately every 4
 days (range: 1–8 days) to monitor their status and determine their fate.
 During our visits we visually checked nests using a wireless cavity
 inspection camera (www.ibwo.org; Little
 Rock, AR) that was mounted on a telescoping pole and allowed us to view
 the contents of nest cavities as small as 3.8 cm in diameter and up to 14
 m in height; this allowed us to obtain a visual record of the nest
 contents during the majority of our nest checks (i.e., 84% of
 <em>n</em> = 728 cumulative visits). We
 assigned the nest initiation date to each nest as the day the first egg
 was laid, either through direct observation or by back-dating using photos
 of nestlings taken by our inspection camera in known-age nests from our
 study area. For back-dated nests, we estimated nest initiation date based
 on the observed number of unique offspring (i.e., eggs or nestlings)
 observed in the nest together, and we assumed an incubation period of 13
 days (Stillman et al. 2019a) that commenced on the day the penultimate egg
 in the clutch was laid. When clutch sizes were unknown, we assumed a
 clutch size of 4 eggs, the average clutch size across the Black-backed
 Woodpecker’s geographic range (Tremblay et al. 2020) which was the typical
 clutch size in our study in nests for which we had complete laying data
 (authors, unpublished data). We considered a nest to be successful if it
 fledged at least one nestling, which was based on observations of tagged
 fledglings outside of the nest cavity, or nests that were no longer active
 on the expected fledge date with no signs of predation. We considered
 unsuccessful nests as those found empty prior to the expected fledge date,
 had clear evidence of predation (e.g., eggshell fragments), or contained a
 brood in which all nestlings had died. We calculated reproductive output
 as the number of young considered to have fledged from each nest based on
 its individual history. After nests fledged, we
 quantified vegetation around nest sites to determine whether nest-site
 conditions influenced nest survival. We measured nest vegetation in 10-m
 radius plots centered on each nest tree, and within each plot, we counted
 the number of small (10–30 cm DBH), medium (30–60 cm DBH) and large
 (&gt;60 cm) live trees and standing dead trees (i.e., snags). We also
 quantified basal area of all trees and snags using variable-radius plots
 centered on the nest tree. We quantified additional characteristics of
 nest trees that included species, DBH, tree height, cavity height
 (measured from cavity center), cavity orientation, tree decay class (1 =
 live; 2 = live but declining; 3 = recently dead; 4 = snag with loose bark;
 5 = snag with no bark; 6 = broken snag with no bark, top, or branches; or
 7 = decomposing snag; Maser et al. 1979), and the average canopy cover
 taken over the four cardinal directions from the base of the nest
 tree. <strong>Measuring and Tagging
 Nestlings</strong> When nestlings were ~20 days
 old (± 2 days) we returned to nests to band them, measure their body
 condition, and, to a subset of the brood, attach a VHF radio telemetry tag
 to assess post-fledging survival. For nest trees we deemed safe for
 climbing, we accessed nest cavities using aluminum sectional ladders that
 were secured directly to the bole, allowing us to access nest cavities up
 to 19 m high. For nests that were unsafe for direct climbing, we erected a
 free-standing 12 m extension ladder that was secured with 4 opposingly
 anchored static climbing ropes that allowed access to nest cavities
 (Rohwer 1988). Once at the nest cavity, we used a hole saw to remove a
 wooden plug from the outside wall of the tree below the cavity entrance to
 create an access hole that allowed for safe extraction of nestlings
 (Ibarzabal and Tremblay 2006). Of note, we did not penetrate the inner
 wall of the cavity with the hole saw; instead, we used a chisel to
 manually remove the wooden plug that was created by the hole saw to access
 the nest. Once nestlings were extracted (<em>n</em> = 133), we
 banded them with an aluminum U.S. Geological Survey leg band and 1–3
 colored plastic leg bands (Avinet Research Supplies, Portland, ME, USA) to
 allow for individual identification after release, and then measured body
 mass and right tarsus length to calculate an index of size-corrected body
 condition. Finally, we attached a VHF telemetry tag to a subset of
 nestlings (n = 69), randomly selecting at least one nestling per brood for
 tagging that was of sufficient size based on research permit guidelines.
 To attach tags, we used the leg-loop method of Rappole and Tipton (1991)
 with beaded elastic cord to allow for flexion, and each individual
 received either a standard beeper tag (model Ag393, Lotek Wireless,
 Newmarket, ON) or a similarly constructed tag whose activity periods could
 be programmed prior to attachment (model CTx Ag393, Lotek Wireless,
 Newmarket, ON). All tags weighed 2.8–4.0% of each individual’s body mass
 and were within permit guidelines. After tagging, we immediately returned
 nestlings to their nest, wrapped the outside edge of the wooden plug with
 duct tape to account for kerf caused by removal, placed it back into the
 hole from which it was removed, and then secured it in place with two wood
 screws. Our nestling removal approach provided a safe and efficient method
 for removing nestlings from the nest, with no instances of subsequent nest
 abandonment in our study. Indeed, we documented several instances of nests
 from which we removed nestlings being used by secondary cavity nesting
 species in subsequent years, indicating that the cavities retained their
 integrity and remained suitable for nesting and roosting after being
 modified (see Ibarzabal and Tremblay 2006).
 <strong>Post-Fledging Survival  </strong>
 After we returned nestlings to their nest cavity, we continued to
 monitor nests until they fledged after which we attempted to relocate them
 using the homing method every 3–5 days until approximately the first week
 of September. Individuals that survived until the end of our tracking
 period were 41–84 days old, which extended beyond the period when
 fledgling Black-backed Woodpeckers become independent from their parents
 (~35 days; Stillman et al. 2019b). During each relocation, we recorded an
 individual’s status (i.e., alive/dead) and their location using a handheld
 GPS unit. When individuals were not relocated during a scheduled search,
 we attempted at least three additional relocations in the vicinity of
 their last known location, after which we periodically checked for
 telemetry signals of missing birds throughout the rest of the season.
 Additionally, we attempted to relocate all missing individuals during
 mid-August of each year by conducting aerial telemetry flights over the
 study area using fixed-wing aircraft. If an individual was not detected
 after ≥ 3 regular consecutive searches nor during our aerial telemetry
 searches, we assumed it dispersed from the study area and was
 right-censored in our analysis, along with individuals known to be alive
 during their last encounters. We considered a tagged bird to have
 undergone mortality when we recovered a tag that was severely damaged
 without a carcass, was tracked to raptor nests or roost sites, or was
 found with considerable quantities of feathers near the tag.
 <strong>Statistical Analyses</strong>
 We performed all analyses using the R statistical environment (R
 Core Team, 2021; v4.1.2). Given our stated objectives, we constructed two
 separate types of models: (1) design-based models that we initially used
 to quantify how the four primary responses variables we measured (i.e.,
 daily nest survival, reproductive output, body condition, and
 post-fledging survival) differed between green and burned forests, and (2)
 covariate-based models that we assessed within a model selection framework
 (Burnham and Anderson 2002) to explore which covariate(s) had the
 strongest effect on the primary response variables (see Rivers et al.
 2019). All design-based models were constructed similarly in that they
 included one of the four primary response variables with forest type (2
 levels: green forest, burned forest) as a fixed effect. For
 covariate-based models, we tested a priori hypotheses that were based on
 biological processes and varied among the different response variables,
 and we used the <em>AICcmodavg</em> package (Mazerolle 2020)
 to calculate Akaike’s Information Criterion corrected for small sample
 size (AICc) for selecting the top model from each candidate set (Burnham
 and Anderson 2002). To model daily nest survival, we
 used the <em>RMark</em> (Laake 2013) package to construct
 logistic exposure models that incorporate exposure time and can account
 for nests that were discovered at different ages after initiation (Shaffer
 2004). For the design-based model for daily nest survival, we constructed
 a logistic exposure model with forest type as a fixed effect. For the
 covariate-based models of daily nest survival, we assembled a set of 14
 candidate models that included forest type, as well as temporal,
 nest-tree, and nest-site habitat variables. We did not include nest age in
 daily nest survival models because predation events were uncommon and
 occurred throughout both incubation and nestling stages. To calculate the
 probability of nest success, we raised the estimated daily survival rate
 to the 40<sup>th</sup> power because the Black-backed
 Woodpecker nestling period is ~40 days (Tremblay et al. 2020).
 To model reproductive output, we constructed a general linear
 model that assumed a Poisson distribution and had forest type (2 levels)
 as a fixed effect for the designed-based model. For the covariate models,
 we assessed 9 additional models that included forest type and a suite of
 nest-site and temporal covariates. Because clutch size, egg hatchability
 (i.e., the proportion of eggs in a clutch that hatched), and nestling
 survival (i.e., proportion of nestlings that fledged relative to those
 that hatch) each has the potential to drive differences in nest survival
 and reproductive output, we also tested whether these secondary response
 variables varied between forest type. To do this, we constructed separate
 general linear models for each response variable with forest type as a
 fixed effect.   To evaluate nestling body condition, we
 constructed two separate general linear models – one for each sex because
 of size-based sexual dimorphism (Tremblay et al. 2020) – whereby we
 log-transformed body mass and regressed it on log-transformed right tarsus
 length (Labarbera 1989, Jakob et al. 1996, Schrader et al. 2003), with
 nest identity as a random effect to account for non-independence of
 nestlings reared in the same nest. We then took the residual from this
 regression as a size-corrected, unitless measure of body condition that
 allowed us to compare relative size of individuals against the population
 mean. As described above, we constructed a general linear model for our
 design-based model with forest type as a fixed effect. For covariate
 models, we developed a set of 13 models based on 5 potential covariates
 that related to a priori hypotheses, including forest type.
 Finally, to assess post-fledging survival we constructed Cox
 Proportional Hazard (CPH) models (Sara et al. 2012, Fox and Weisberg 2018)
 using the <em>survminer</em> (Kassambara et al. 2021) and
 <em>survival</em> packages (Therneau 2021). For our
 design-based model, we modeled the number of days of exposure with forest
 type as a fixed effect; for our covariate models we developed a set of 12
 candidate models covering six potential covariates, including forest type.
 For all CPH models, we included nest identity as a random effect in all
 models to account for non-independence between tagged fledglings
 originating from the same nest. Assumptions were upheld for all
 statistical models. <strong>Methods
 References:</strong> Bonnot, T. W.,
 M. A. Rumble, and J. J. Millspaugh (2008). Nest success of Black-backed
 Woodpeckers in forests with mountain pine beetle outbreaks in the Black
 Hills, South Dakota. The Condor 110:450–457. Burnham,
 K. P., and D. R. Anderson. 2002. Model Selection and Multimodel Inference:
 A Practical Information-Theoretic Approach. Springer-Verlag: New
 York. Charnley, S., T. A. Spies, A. M. G. Barros, E.
 M. White, and K. A. Olsen (2017). Diversity in forest management to reduce
 wildfire losses: Implications for resilience. Ecology and Society
 22:22. Fox, J., and S. Weisberg (2018). Cox
 Proportional-Hazards Regression for Survival Data in R.
 Hagmann, R. K., A. G. Merschel, and M. J. Reilly (2019).
 Historical patterns of fire severity and forest structure and composition
 in a landscape structured by frequent large fires: Pumice Plateau
 ecoregion, Oregon, USA. Landscape Ecology 34:551–568.
 Ibarzabal, J., and J. A. Tremblay (2006). The hole saw method
 for accessing woodpecker nestlings during developmental studies. Annales
 Zoologici Fennici 43:235–238. Jakob, E. M., S. D.
 Marshall, and G. W. Uetz (1996). Estimating Fitness: A Comparison of Body
 Condition Indices. Oikos 77:61–67. Kassambara, A., M.
 Kosinski, and P. Biecek (2021). Survminer: Drawing Survival Curves using
 “ggplot2.” R package  version 0.4.9. Https://CRAN.R-project.org/package=survminer.       Key, Carl H., and Nathan C. Benson (2006). FIREMON – Landscape Assessment. In FIREMON: Fire Effects Monitoring and Inventory System (D. C. Lutes, R. E. Keane II, J. F. Caratti, C. H. Key, N. C. Benson, S. Sutherland, L. J. Gangi, Editors). Technical Report RMRS-GTR-164-CD. USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO. Laake, J. L. (2013). Rmark: An R Interface for Analysis of Capture-Recapture Data with MARK. FSC Processed Rep. 2013-01, Alaska Fish. Sci. Cent., NOAA, National Marine Fisheries Service, Seattle, WA. https://apps-afsc.fisheries.noaa.gov/Publications/ProcRpt/PR2013-01.pdf. Labarbera, M. (1989). Analyzing Body Size as a Factor in Ecology and Evolution. Annual Review of Ecology and Systematics 20:97–117. Matseur, E. A., F. R. Thompson, B. E. Dickerson, M. A. Rumble, and J. J. Millspaugh (2018). Black-backed Woodpecker abundance in the Black Hills. Journal of Wildlife Management 82:1039–1048. Maser, C., R. G. Anderson, and K. Cromack, Jr. (1979). Dead and down woody material. In Wildlife Habitats in Managed Forests: The Blue Mountains of Oregon and Washington (J. W. Thomas, Editor). USDA Forest Service Agricultural Handbook 553:78. Mazerolle, M. J. (2020). Aiccmodavg: Model selection and multimodel inference based on (Q)AIC(c). R package version 2.3-1. Https://cran.r-project.org/package=aiccmodavg. R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. Rappole, J. H., and A. R. Tipton (1991). New harness design for attachment of radio transmitters to small passerines. Journal of Field Ornithology 62:335–337. Rivers, J. W., J. Verschuyl, C. J. Schwarz, A. J. Kroll, and M. G. Betts (2019). No evidence of a demographic response to experimental herbicide treatments by the White-crowned Sparrow, an early successional forest songbird. Condor 121(2):duz004.  Rohwer, S. (1988). Guyed Extension Ladder for Access to High Nests. Journal of Field Ornithology 59:262–265. Rota, C. T., J. J. Millspaugh, M. A. Rumble, C. P. Lehman, and D. C. Kesler (2014). The Role of Wildfire, Prescribed Fire, and Mountain Pine Beetle Infestations on the Population Dynamics of Black-Backed Woodpeckers in the Black Hills, South Dakota. PLOS One 9:e94700. Sarà, M., D. Campobello, and L. Zanca (2012). Effects of nest and colony features on Lesser Kestrel (<em>Falco</em> <em>naumanni</em>) reproductive success. Avian Biology Research 5:209–217. Shaffer, T. L. (2004). A Unified Approach to Analyzing Nest Success. The Auk 121:526–540. Schrader, M. S., E. L. Walters, James, Frances C, Greiner, and Ellis C (2003). Seasonal prevalence of a hematozoan parasite of Red-Bellied Woodpeckers (<em>Melanerpes</em> <em>carolinus</em>) and its association with host condition and overwinter survival. The Auk 120:130–137. Stillman, A. N., R. B. Siegel, R. L. Wilkerson, M. Johnson, C. A. Howell, and M. W. Tingley (2019a). Nest site selection and nest survival of Black-backed Woodpeckers after wildfire. The Condor 121:1–13. Stillman, A. N., R. B. Siegel, R. L. Wilkerson, M. Johnson, and M. W. Tingley (2019b). Age-dependent habitat relationships of a burned forest specialist emphasize the role of pyrodiversity in fire management. Journal of Applied Ecology 56:880-890. Therneau, T. M. (2021). A Package for Survival Analysis in R. R package version 3.2-13, https://CRAN.R-project.org/package=survival. Tingley, M. W., A. N. Stillman, R. L. Wilkerson, S. C. Sawyer, and R. B. Siegel (2020). Black-backed woodpecker occupancy in burned and beetle-killed forests: Disturbance agent matters. Forest Ecology and Management 455:117694. Tremblay, J. A., R. D. Dixon, V. A. Saab, P. Pyle, and M. A. Patten (2020). Black-backed Woodpecker (<em>Picoides</em> <em>arcticus</em>), version 1.0. In Birds of the World (P. G. Rodewald, Editor). Cornell Lab of Ornithology, Ithaca, NY, USA. https://doi.org/10.2173/bow.bkbwoo.01 U.S. Forest Service (2022). RAVG Thematic Percent Change in Composite Burn Index (CBI-4). Raster Dataset, https://data.fs.usda.gov/geodata/rastergateway/ravg/index.php. Verschuyl, J., J. L. Stephens, A. J. Kroll, K. E. Halstead, and D. Rock (2021). Black-backed Woodpecker occupancy is extensive in green conifer forests of the southern cascade mountains, Oregon. Avian Conservation and Ecology 16:1–8.
description: R statistical environment. See the methods above for packages and
 usage.