The following systematic review and meta‐analysis summarize all available published scientific literature on the effects of wildfire on aspects of Spotted Owl demography (survival, recruitment, and reproduction), site occupancy, and habitat selection, from studies using empirical data to answer the question: How does fire, especially mixed‐severity fire with substantial patches of high‐severity fire within their home ranges, affect Spotted Owl demography, site occupancy, and habitat selection in the first few post‐fire years?

Research on Spotted Owl in fire‐affected landscapes did not begin until the early 2000s, and much of what scientists previously understood about habitat associations of Spotted Owl was derived from studies in forests that had generally not experienced recent fire, and where the non‐suitable owl habitat was a result of logging (Gutiérrez et al. 1992 , Franklin et al. 2000 , Seamans et al. 2002 , Blakesley et al. 2005 , Seamans and Gutiérrez 2007 , Forsman et al. 2011 , Tempel et al. 2014 ). Because Spotted Owls are associated with dense, late‐successional forests, it has often been assumed that fires that burn at high severity are analogous to clear‐cut logging and have a negative effect on population viability. It has become widely believed among wildlife management professionals that severe wildfire is a contributing cause of recent Spotted Owl population declines (USFWS 2011 , 2012 , 2017 ), and many land managers believe that forest fires currently pose the greatest risk to owl habitat and are a primary threat to population viability (Davis et al. 2016 , Gutiérrez et al. 2017 ). These beliefs result in fuel‐reduction logging projects in Spotted Owl habitat (USDA 2012 , 2018 ) which the USDA Forest Service and US Fish and Wildlife Service state are actions consistent with Spotted Owl recovery (USDA 2012 , 2018 , Gutiérrez et al. 2017 , USFWS 2017 ). Narrative literature reviews have attempted to summarize the effects of fire on Spotted Owl (Bond 2016 , Gutiérrez et al. 2017 ), but evidence‐based conservation decisions should be based upon systematic, transparent reviews of primary literature with quantitative meta‐analysis of effects (Sutherland et al. 2004 , Pullin and Stewart 2006 , Pullin and Knight 2009 , Koricheva et al. 2013 ).

Spotted Owls ( Strix occidentalis ) occur in western U.S. forests and have been intensively studied since the 1970s (Fig. 1 ). The species is strongly associated with mature and old‐growth (i.e., late‐successional) conifer and mixed conifer–hardwood forests with thick overhead canopy and many large live and dead trees and fallen logs (Gutiérrez et al. 1995 ). Its association with older forests has made the Spotted Owl an important umbrella indicator species for public lands management (Noon and Franklin 2002 ). The scientific literature has established that the optimal habitat for Spotted Owl nesting, roosting, and foraging is provided by conifer and mixed conifer–hardwood forests dominated by medium (30–60 cm) and large (>61 cm) trees with medium (50–70%) to high (>70%) canopy cover (Gutiérrez et al. 1995 ). The populations of all three subspecies have declined due to widespread historical and ongoing habitat loss, primarily from logging mature and old‐growth forests favored by the owls for nesting and roosting (Seamans et al. 2002 , Forsman et al. 2011 , USFWS 2011 , 2012 , Conner et al. 2013 , Tempel and Gutiérrez 2013 , Dugger et al. 2016 ).

Wildfires are major natural disturbances in forests of the western United States, and native plants and animals in this region have been coexisting with fire for thousands of years of their evolutionary history (Pierce et al. 2004 , Power et al. 2008 , Marlon et al. 2012 ). Western forest fires typically burn as mixed‐severity fires with each fire resulting in a mosaic of different vegetation burn severities, including substantial patches (range, 5–70% of burned area; mean, 22%) of high‐severity fire (Beaty and Taylor 2001 , Hessburg et al. 2007 , Whitlock et al. 2008 , Williams and Baker 2012 , Odion et al. 2014a , Baker 2015a ). High‐severity fire (high vegetation burn severity) kills most or all of the dominant vegetation in a stand (>75% mortality; Hanson et al. 2009 , Baker 2015a , b ) and creates complex early seral forests, where standing dead trees, fallen logs, shrubs, tree seedlings, and herbaceous plants comprise the structure (Swanson et al. 2011 , DellaSala et al. 2014 ). Post‐fire vegetation processes (i.e., succession) then commence according to the pre‐fire vegetation, local wildfire processes, propagules from outside the disturbance, and the dynamic biotic and abiotic conditions at the site (Gutsell and Johnson 2006 , Johnson and Miyanishi 2006 , Mori 2011 ).

I used all three methods at three levels: on all parameters, on three main groups of parameters (occupancy, foraging habitat selection, and demography), and on subgroups of habitat selection (for low‐, moderate‐, and high‐severity burned forest) and demography (survival, reproduction, and recruitment). In meta‐analyses, I used z tests to determine if effects were significantly different from zero (95% confidence interval excluded zero). In meta‐regression, z tests determined whether intercepts or slope coefficients were significantly different from zero. I quantified heterogeneity among effects as Cochran's Q (Hedges and Olkin 1985 ) and I 2 (Higgins and Thompson 2002 ). I used a funnel plot and the rank correlation test (Kendall's τ) to assess publication bias (Begg and Mazumdar 1994 ).

I used three quantitative methods for evaluating the evidence (Koricheva et al. 2013 ): a random‐effects meta‐analysis of mean effect sizes as the standardized difference in means (Hedge's d ; Hedges and Olkin 1985 ); multi‐level linear mixed‐effects models (hierarchical models) meta‐regression of time since fire and percent of high‐severity fire in the study area as covariates to explain heterogeneity in mean effect sizes (Hedges and Vevea 1998 , Nakagawa and Santos 2012 ); and a random‐effects meta‐analysis of variation to examine differences in parameter variances due to fire with effect sizes as the natural logarithm of the ratio between the coefficients of variation (lnCVR; Nakagawa et al. 2015 ). For analyses, I used the metafor package of R (Viechtbauer 2010 ) and used function metacont for random‐effects meta‐analyses, function rma.mv for multi‐level linear mixed‐effects model meta‐regression, and function rma for random‐effects meta‐analysis of variation (Viechtbauer 2010 ). Study within geographic area was included as multi‐level random effects to properly estimate study site‐ and region‐specific variation and to account for repeated measurements (pseudo‐replication) within a study or region. Regions were defined as Sierra Nevada, southern California, national parks, not California, and the Eldorado density study area (because several studies used data from there).

I conducted all analyses in R 3.3.1 ( www.r-project.org ). For meta‐analysis, I noted or calculated the mean, variance (SD), and sample size for burned (treatment) and unburned (control) groups. I calculated raw effect sizes as mean differences ( ) and signs (positive or negative) for all reported effects, regardless of their statistical significance. Most papers reported effect sizes as probabilities (occupancy, survival, and foraging habitat selection) so raw effect sizes were scaled between negative and positive one with a mean of zero, making comparison among studies easy. When papers reported multiple effects (e.g., occupancy and reproduction, or survival and recruitment), I recorded each effect individually. Where papers did not report any effect size for a parameter determined to have no significant effects from fire, I included a zero to represent the presence of no significant effect and to avoid a significance bias in the meta‐analysis. I stratified data by subspecies (California, Mexican, or northern) and parameter type according to whether the study estimated site occupancy, foraging habitat selection (substratified into selection for low‐, moderate‐, and high‐severity burned forest), and demographic rates (substratified into survival, reproduction, and recruitment). I performed meta‐analyses on parameters for which ≥4 estimates existed from ≥4 different fires.

I evaluated all final review papers and included all papers where effects of fire were reported and could be differentiated from other disturbances such as post‐fire logging. I extracted evidence by reading every paper and tabulating all quantified results from text, tables, and figures (Table 1 ). I noted the mean ( ) and variation (SD) of burned and unburned groups for all significant and non‐significant parameters, the parameters being estimated, sample sizes ( n = number of owl breeding sites in burned and unburned groups), amount of high‐severity fire in the total fire perimeter and/or within the owl territory core areas examined, time since fire (years), amount of post‐fire logging that occurred, subspecies (California = Strix occidentalis occidentalis , Mexican = Strix occidentalis lucida , or northern = Strix occidentalis caurina ), and whether the result was statistically significant (as defined in each paper).

Because post‐fire logging often occurred, I also recorded effects of this disturbance where they were reported. I believe all studies in the final review were generally comparable because time since fire and percent of high‐severity burn were similar among studies (Tables 1 , 2 ), and the high number of non‐significant results reported indicates little to no publication bias exists in this topic (Tables 1 , 2 ; Appendix S1 : Fig. S1). I considered the basic sampling unit of all studies to be the central core of the owl breeding‐season territory (~400 ha, or a circle with radius 1.1 km centered on the nest or roost stand) because this is the spatial and temporal scale for sampling used in almost all Spotted Owl studies. In contrast, Spotted Owl year‐round home ranges vary according to latitude and dominant vegetation, but range from 300 to 11,000 ha, or circles with radius 1.0–5.9 km (Zabel et al. 1992 ). I considered forest fires to affect the landscape scale (~10,000 ha/decade), but that fires would affect numerous individual owl breeding‐season territories (1200 ha) and year‐round home ranges (300–19,000 ha) in various ways.

I used a threefold filtering process for accepting studies into the final systematic review. Initially, I filtered all articles by title and removed any obviously irrelevant material from the list of articles found in the search. Subsequently, I examined the abstracts of the remaining studies with regard to possible relevance to the systematic review question, using inclusion criteria based on the subject matter and the presentation of empirical data. I accepted articles for viewing at full text if I determined that they may contain information pertinent to the review question or if the abstract was ambiguous and did not allow inferences to be drawn about the content of the article. Finally, I read all remaining studies at full text and either rejected or accepted into the final review based upon subject matter (Pullin and Stewart 2006 , Koricheva et al. 2013 ). Studies that only modeled effects of simulated fires on Spotted Owl habitat and demography were not considered here.

I conducted a systematic review of the primary scientific literature and used meta‐analyses and meta‐regression to examine the evidence for the direct effects of wildfire on Spotted Owl demography, site occupancy, and habitat selection. My subject was Spotted Owls; the intervention was wildfire; the outcomes were change or difference in estimates of demography, site occupancy, and habitat selection probabilities; and the comparator was pre‐fire estimates or control estimates from unburned areas (Pullin and Stewart 2006 ). I searched the following electronic databases on 1 April 2018: Agricola, BIOSIS Previews, ISI Web of Science, and Google Scholar. Search terms were as follows: spotted AND owl AND *fire, Strix AND occidentalis AND *fire. My search included papers published in any year.

Meta‐regression of foraging habitat selection parameters found a significant positive selection for low‐ and moderate‐severity burned forest, with high‐severity burned forest used in proportion to its availability, but not avoided (Fig. 5 , Table 4 ). Time since fire did not affect foraging habitat selection during the period covered by the studies I examined (up to 7 yr), and the amount of high‐severity fire did not affect habitat selection overall (Table 4 ).

Results of multi‐level linear mixed‐effects models (hierarchical models) meta‐regression of time since fire and percent of high‐severity fire in the study area as covariates to explain heterogeneity in effect sizes from mixed‐severity fire on Spotted Owl ( Strix occidentalis ) parameters of foraging habitat selection, recruitment, and reproduction. Significant effects included positive selection for low‐ and moderate‐severity burned forest for foraging, increased recruitment immediately post‐fire that diminished with increasing time since fire, and increased reproduction with a positive correlation with amount of high‐severity fire. In top two panels, all studies were California subspecies, and colors indicate forest in different burn severity categories: green, low severity; orange, moderate severity; red, high severity. In bottom four panels, symbols indicate subspecies: filled black circles, California; white circles with black outline, Mexican; light gray circles with black outline, northern; and dark gray circles, all three subspecies.

Meta‐regression of demographic parameters found a significant positive effect on recruitment immediately after the fire (intercept significantly different from zero), but the effect diminished with time since fire (Fig. 5 , Table 4 ). Reproduction intercept was not significantly different from recruitment (Table 4 ), and not significantly different from zero ( z = −0.218, P = 0.86), but reproduction was significantly positively correlated with the percent of high‐severity fire in owl territories (Fig. 5 , Table 4 ). Survival was significantly lower than recruitment (Table 4 ), but survival intercept was not significantly different from zero ( z = −0.052, P = 0.97). There were no significant survival effects of time since fire or percent of high‐severity fire (Table 4 ).

Results of multi‐level linear mixed‐effects models (hierarchical models) meta‐regression of time since fire and percent of high‐severity fire in the study area as covariates to explain heterogeneity in effect sizes from mixed‐severity fire on Spotted Owl ( Strix occidentalis ) parameters of breeding site occupancy and survival. The only significant effect was a reduction in occupancy with increasing time since fire, but the effect was sensitive to one study. Symbols indicate subspecies: filled black circles, California; white circles with black outline, Mexican; light gray circles with black outline, northern; and dark gray circles, all three subspecies.

Meta‐regression of occupancy probability found no significant immediate effect of fire on occupancy (intercept not significantly different from zero; Table 4 ). There was a significant negative effect of time since fire (Fig. 4 , Table 4 ), but no effect of percent high‐severity fire in study territories (Table 4 ). The negative effect of time since fire was sensitive to one study (Roberts et al. 2011 ), and when that study was omitted, the effect disappeared.

Meta‐regression of all standardized mean effects found significant effect of time since fire (Table 3 ), and a nearly significant effect of percent high‐severity burn in territory cores (Table 3 ), so those effects were included in parameter‐specific meta‐regressions. Subspecies was not a significant factor (Table 3 ), so effects from different subspecies were pooled in subsequent parameter‐specific analyses.

Variation was generally higher among parameter estimates from burned areas compared to estimates from unburned areas (mean CV burned − CV unburned = 23%; range 4–57%). The mixed‐effects meta‐analysis of variation in fire effects on Spotted Owl parameters (lnCVR) found mixed‐severity fire resulted in significantly higher variation in parameter estimates in all parameters and in occupancy, demography, and survival (Fig. 3 b). There was significantly lower variation in estimates of foraging habitat selection probability for low‐severity burned forest (Fig. 3 b).

The mixed‐effects model meta‐analysis of fire effects on Spotted Owl parameters grouped by type (occupancy, demography, and foraging habitat selection), and subtypes of demography (survival, reproduction, and recruitment) or foraging habitat selection (selection for low‐, moderate‐, and high‐severity burned forest), found mixed‐severity fire has generally no significant effect on Spotted Owls (Fig. 3 a). Mean overall raw effect size was positive (+0.001), but weighted mean Hedge's d from the random‐effects model was not significantly different from zero (Fig. 3 a, 95% confidence interval included zero). Mean raw effect sizes were negative for occupancy (−0.060), demography (−0.006), and survival (−0.095), but no Hedge's d value for these three negative effects was significantly different from zero (Fig. 3 a). Mean raw effect sizes were positive for reproduction (+0.047), recruitment (+0.073), foraging habitat selection (+0.083), selection of high‐severity (+0.004), moderate‐severity (+0.087), and low‐severity burned forest (+0.195), but Hedge's d values were not significantly different from zero for any of these positive effects, except for significant selection of low‐severity burned forest (Fig. 3 a).

Results of mixed‐effects meta‐analyses of mixed‐severity fire effects ( n = 50 effects from 21 studies) on Spotted Owl ( Strix occidentalis ) parameters grouped by type (occupancy, demography, and foraging habitat selection) and subtype of demography (survival, reproduction, and recruitment), or habitat selection (selection for low‐, moderate‐, and high‐severity burned forest). (a) Hedge's d is standardized mean effect size, and error bars are 95% confidence intervals. The only significant effect (95% confidence intervals excluded zero) was a positive effect of habitat selection for low‐severity burned forest. (b) lnCVR is the natural logarithm of the ratio between the coefficients of variation, a measure of differences in variation of parameter estimates between burned and unburned areas. Mixed‐severity fire resulted in significantly higher variation in parameter estimates in all parameters, occupancy, demography, and survival, and significantly lower variation in habitat selection for low‐severity burned forest.

Meta‐analysis of 50 reported effects on occupancy, foraging habitat selection, and demographic rates found effect sizes and signs were variable (Table 2 and Fig. 2 ), with high heterogeneity among effects ( Q = 1091, df = 51, P < 0.0001; I 2 = 95.3%). Funnel plot (Appendix S1 : Fig. S1) and rank correlation test (Kendall's τ = 0.108, P = 0.27) showed no publication bias or unusual heterogeneity. Sample sizes ( n = number of reported effects) were variable among parameter types (Fig. 3 ). The number of reported effects were occupancy = 20; demography = 14; and foraging habitat selection = 16. The number of reported effects by demography subtype were survival = 6; reproduction = 4; and recruitment = 4. The number of reported effects by habitat selection subtype were low‐severity burned forest = 4; moderate‐severity burned forest = 6; and high‐severity burned forest = 6.

Fifteen of the 18 papers in the meta‐analysis set reported evidence explicitly pertaining to mixed‐severity wildfires that burned during the past few decades and which included proportions of high‐severity burn characteristic of this fire regime, while three reported evidence from an undifferentiated mix of wildfire and prescribed fires. The studies reported varying amounts of high‐severity fire, a defining feature of mixed‐severity fires, and the burn severity type that is most responsible for vegetation changes in wildfires, with an overall mean percent of high‐severity fire of 26% (standard error [SE] = 3.6, range 6–64) within the study area. Because almost all the studies in this review reported on effects from recent wildfires (all fires burned in the past 30 yr, mean time since fire = 4 yr, SE = 1.1, range 1–26), the reported effects are representative of natural mixed‐severity fires as they burned through currently existing forest structure, fire regime, and climate conditions. Papers reported effects of fire on site occupancy (11), foraging habitat selection (4), reproduction (4), apparent survival (3), overwinter roosting habitat selection (2), site fidelity (1), mate fidelity (1), breeding‐season nesting and roosting habitat selection (1), home‐range size (1), and recruitment (1). Sample sizes measured as number of burned sites were variable among studies (demography CV = 122%, site occupancy CV = 56%, and habitat selection CV = 24%).

I found 21 papers reporting empirical evidence relevant to direct fire effects on owls (Table 1 ). Three papers presented data from a study area which was extensively logged post‐fire and results did not discriminate between effects of fire and post‐fire logging (Clark et al. 2011 , 2013 , Comfort et al. 2016 ), so these three papers were not included in meta‐analyses with the meta‐analysis set of papers that were not confounded by extensive post‐fire logging (Table 2 ). All 21 papers are summarized in Appendix S1 .

Discussion

This systematic review and summary of effects from the primary literature indicated Spotted Owls are usually not significantly affected by mixed‐severity fire as 83% of all studies and 60% of all effects found no significant impact of fire on owl parameters. Meta‐analysis of mean effects found no significant effects of fire on owls, except a positive effect on foraging habitat selection for low‐severity burned forest. Meta‐regression indicated significant positive effects in recruitment, reproduction, and foraging habitat selection for low‐ and moderate‐severity burned forest. Meta‐regression found a significant negative effect of time since fire on occupancy probability. Meta‐analysis of variation found mixed‐severity fire resulted in greater parameter variation overall, and specifically in occupancy, demography, and survival, and significantly less variation in foraging habitat selection for low‐severity burned forest.

These results represent Spotted Owl responses to mixed‐severity wildfires that burned within the past 30 yr with representative proportions of high‐severity fire in a landscape mosaic. Additionally, because most of the studies in this review reported on effects from wildfire, rather than prescribed fire, the fires and their effects are representative of wildfires as they burned through currently existing forest structure, fire regime, and climate conditions. Several studies have reported that fires during the past few decades have been larger and more severe than the historical mean (Miller and Safford 2012, 2017, Mallek et al. 2013, Steel et al. 2015), but others have disputed this point (Odion and Hanson 2006, Hanson et al. 2009, Odion et al. 2014a, Baker 2015a). Regardless of what is correct about trends in fire severity, Spotted Owls appear fairly resistant and/or resilient to effects from recent hot, large fires, wherever these fires fall in the long‐term range of variability for size and amount of high‐severity burn. This is corroborated by the meta‐regressions that explicitly quantified the relationship between amount of high‐severity fire and Spotted Owl parameters and found only a positive significant correlation (reproduction). My finding of no significant negative relationships between amount of high‐severity fire and Spotted Owl parameters demonstrates that large high‐severity fire patches, including territories that burn 100% at high severity as was seen in sites within several of the studies in this review, do not have unequivocally negative outcomes for Spotted Owls.

Contrary to current perceptions, recovery efforts, and forest management projects for the Spotted Owl (USFWS 2011, 2012, 2017, USDA 2012, 2018, Gutiérrez et al. 2017) mixed‐severity fire as it has been burning in recent decades does not appear to be an immediate, dire threat to owl populations that require landscape‐level fuel‐reduction treatments to mitigate fire severity. Empirical studies reviewed here demonstrated that wildfires can generally have no significant effect, but effects can include improved foraging habitat, reduced site occupancy, and improved demographic rates. Most territories occupied by reproductive Spotted Owl pairs that burn remain occupied and reproductive at the same rates as sites that did not experience recent fire, regardless of the amount of high‐severity fire in core nesting and roosting areas.

To place my results into perspective, mixed‐severity fire typically affects (≥50% vegetation basal area mortality) a very small portion (0.02–0.50%) of Spotted Owl nesting and roosting habitat per year (Odion et al. 2014b, Baker 2015b, Stephens et al. 2016). Breeding sites that experienced a typical mixed‐severity burn mosaic can be expected to have occupancy probability reduced by −0.06 on average. A 0.06 decline in occupancy is less than typical annual declines in occupancy rates observed in the Sierra Nevada in the absence of large fires (Jones et al. 2016: Fig. 3f). In comparison, post‐fire logging caused a mean occupancy probability reduction of −0.18.

Post‐fire logging is likely to be partially responsible for some of the negative effects attributed to high‐severity fire in the studies reviewed here (Tempel et al. 2014, Jones et al. 2016, Rockweit et al. 2017, Hanson et al. 2018). Because Spotted Owl studies typically characterize territory vegetation only in the breeding core area within 1.1 km of the nest, these studies ignore habitat changes and alterations in the year‐round home‐range area that can extend up to 5.9 km from the nest (Zabel et al. 1992). Spotted Owl habitat protections have generally not included areas beyond 1 km from the nest, a management policy that has not contributed to population recovery.

Complex early seral forests created by fire differ from post‐fire salvage‐logged forests in that dead trees remain on‐site, providing perching sites for hunting owls as well as food sources and shelter for numerous wildlife species (Hutto 2006, Swanson et al. 2011, DellaSala et al. 2014). Longitudinal studies also indicated that burned breeding sites where owls were not detected immediately after fire were often recolonized later (Lee et al. 2012, 2013, Tempel et al. 2016), and this review shows burned forest habitat is used for foraging, demonstrating the mistake of concluding severely burned sites or habitats are lost to Spotted Owls or require restoration (Davis et al. 2016). A recent global meta‐analysis found post‐fire logging is generally not consistent with ecological management objectives (Thorn et al. 2018).

This review on fire and Spotted Owls forms one portion of the evidence base for data‐driven forest management. A recent systematic review of thinning and fire found 56 studies addressing fuel treatment effectiveness in real (not simulated) wildfires from eight states in the western United States (Kalies and Kent 2016). There was general agreement that thin + burn treatments (thinning immediately followed by burning) had some positive effects in terms of reducing fire severity, while treatments by burning or thinning alone were less effective or ineffective (Kalies and Kent 2016). There is also evidence that doing nothing can achieve many forest restoration goals related to age structure and fuels’ density (Zachmann et al. 2018). Additional systematic reviews are needed to examine (1) the quantifiable risk of fire to Spotted Owl habitat, as there are disparate lines of evidence regarding whether fire is impeding the recovery of late‐seral‐stage forests; and (2) the impacts of fuel treatments on Spotted Owl demography and site occupancy. Thinning immediately followed by burning to reduce wildfire risk may or may not have adverse effects on Spotted Owls (Franklin et al. 2000, Dugger et al. 2005, Tempel et al. 2014, 2016, Odion et al. 2014b), but the evidence presented here indicates fire itself has arguably more benefits than costs to the species and thus suggests thinning is not necessary.

The results presented here should serve to guide management decisions, but also should be understood as limited by the available data. The sample sizes of number of estimated effects from mixed‐severity fire on survival and recruitment were small and limited mainly to the northern subspecies. There were also very few studies from the Mexican subspecies. A few studies presented effect sizes that were influential on results, especially meta‐regression results (Roberts et al. 2011), so studies examining longer times since fire are needed. We encourage future studies to increase sample sizes of each parameter and to provide a more balanced sample of studies from all subspecies, and over longer time frames.