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.  

Study Area

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 (Abies concolor), red fir (Abies magnifica), grand fir (Abies grandis), Douglas-fir (Pseudotsuga menziesii), Engelmann spruce (Picea engelmannii), and/or mountain hemlock (Tsuga mertensiana), and mixed pine stands as those containing lodgepole pine, ponderosa pine, western white pine (Pinus monticola), and/or sugar pine (Pinus lambertiana). 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 m³/y and lodgepole pine is clearcut in 8.1–20.2 ha sized blocks on 80-year rotations (Charnley et al. 2017).

Nest Searching and Monitoring

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 n = 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 (>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.

Measuring and Tagging Nestlings

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 (n = 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).

Post-Fledging Survival 

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.

Statistical Analyses

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 AICcmodavg 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 RMark (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^th 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 survminer (Kassambara et al. 2021) and survival 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.

Methods References:

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R statistical environment. See the methods above for packages and usage.