Restoration of anthropogenically altered habitats has often focused on management for umbrella species—vulnerable species whose conservation is thought to benefit co-occurring species. Woody plant encroachment is a form of habitat alteration occurring in grasslands and shrublands around the globe, driven by anthropogenic shifts in disturbance regimes. One pervasive threat to historically widespread sagebrush communities is conifer expansion, which outcompetes sagebrush and can negatively affect sagebrush-obligate animal species. Degradation and loss of sagebrush plant communities in western North America have been associated with drastic declines in wildlife populations. The imperiled Greater Sage-Grouse is assumed to be an umbrella species for the sagebrush community, so habitat restoration, including removal of encroaching conifers, is commonly targeted toward sage-grouse. How this conservation action affects the demography of species other than age grouse is largely unknown. We quantified the demographic effects of landscape-level restoration of sagebrush communities through conifer removal on an assemblage of sagebrush-obligate, shrubland generalist, and woodland-associated songbirds. We compared songbird density and reproduction between adjacent restored and uncut conifer-encroached sagebrush plots in southwest Montana. We found and monitored nests to record nest fate and number of offspring produced. We found demographic benefits for sagebrush-obligate species in restored areas. Sage Thrashers colonized restored areas. Brewer’s Sparrow density was 39% higher and nest success was 63% higher in removal treatments, resulting in 119% higher fledgling production compared with uncut areas. The density of Vesper Sparrows, a shrubland generalist, was 308% higher, and fledgling production was 660% higher in restored areas. Another shrubland generalist, the White-crowned Sparrow, experienced 55% lower density and 37% lower fledgling production in conifer removal areas. Two woodland-associated species, Chipping Sparrows and Dark-eyed Juncos were nearly extirpated following conifer removal. A third woodland-associated species, the Green-tailed Towhee, experienced 57% lower density and 69% lower fledgling production in removal than in non-removal areas.

Synthesis and applications: Our study demonstrates the benefits of conifer removal for sagebrush-obligate species while highlighting species that may be sensitive. Umbrella species management can benefit co-occurring species with similar habitat associations, but demographic analyses for all impacted species are essential for effective conservation.

Density

To understand how treatment impacted breeding pair density, we used spot-mapping to create territory maps in each year of the study (Chalfoun & Martin, 2007; Ralph et al., 1993). We surveyed all plots 3-5 times throughout the breeding season and mapped every bird seen and heard. The 50m grid of points was used to assist with the accurate identification of bird locations using a GPS unit and visual distance estimation. We paid attention to males that were counter-singing to determine territory boundaries. Using the spot-mapping observations and nest locations, we created a territory map for each species each year of the study. We assumed that every territory held a pair of birds and if a territory overlapped the plot boundary, then it was considered half of a territory. We used the final territory maps to estimate the number of pairs of each species on each plot and divided by plot area to calculate density.

Nest success and offspring production

To estimate reproductive success and offspring production between treatments, we located nests by observing parental behavior and following individuals to their nests, as well as systematic searching (Martin & Geupel, 1993). Once nests were found, we monitored them every 1-3 days, recording nest contents at each visit. Nests were considered failed if the nest was empty two or more days before the end of the mean nestling period and no evidence of fledglings was detected. Nests were considered successful if at least one nestling fledged. We recorded the egg number when the final clutch size was confirmed on two or more consecutive visits. We recorded the number of eggs hatched only if all young were accounted for and none disappeared at hatch. We recorded the number of fledglings based on nestling count in the nest within two days of average fledging age and evidence of fledging was observed (i.e., fledglings seen or heard, adults carrying food in the vicinity, or nest edge flattened).

To determine whether more nesting attempts were possible in one of the treatment types due to a longer active breeding period, we calculated the mean season length for each species. We took the average of the earliest and the latest three Julian initiation dates for each species in each year to account for outliers and subtracted them to calculate season length. Finally, to understand how removal treatments may impact population dynamics and impact declining species, we calculated the number of fledglings produced per hectare.

Statistical analysis

We used species-specific mixed effects models to assess the effect of treatment on various dependent variables, including density, nest success, season length, number of eggs laid, number of eggs hatched, nestlings fledged, and fledglings produced per hectare. Each model included treatment as the only fixed effect. We used linear models to test for a treatment effect so we could account for temporal and spatial variation using random effects of year and plot. Species abundance varied between years (Table 1) and was measured at the plot level, so models of species density included only year as a random effect. For analyzing nest success, we used a logistic-exposure analysis with nest fate as the dependent variable (1 = success, 0 = fail) and exposure days accounted for in the logistic-exposure link function (Shaffer, 2004). We expected that varying species abundance between years and spatial autocorrelation may impact nest success, so we tested random effects of year and plot. We used AIC to select the top model and calculated daily nest success by taking the inverse logit of beta estimates from the models. For the remaining models of offspring number, we assumed similar spatial and temporal impacts and used the same random effects structure as used in nest success models. For all mixed models, we calculated degrees of freedom using the Satterthwaite method (Satterthwaite, 1941) in the jtools package (Long, 2022).

Finally, to estimate the number of fledglings produced per hectare, we first calculated entire-period nest success by raising daily nest success to the power of the average length of the entire period of each nest (Mayfield, 1961) for each species in both treatments. To capture the variability of fledglings per hectare, we bootstrapped 1000 iterations of the density dataset in each treatment for each species and took their means. Then, we multiplied density, entire-period nest success, and number of fledglings per successful nest to calculate the number of fledglings produced per hectare. Finally, we ran linear models with treatment as a fixed effects and the same random effects as nest success models.