Estimating population size, age composition, and sex ratio of mule deer (Odocoileus hemionus) is important to conservation and managed hunting of this species in the western United States. Increasingly, wildlife agencies are estimating abundance of deer using fecal DNA (fDNA), especially in forested habitats where aerial surveys are not feasible. These same data can be used to estimate overall sex ratio but require additional data on age structure to quantify adult‐ and fawn‐specific sex ratios, which are expected to differ substantially. We demonstrate an integrated modeling approach to estimating population sizes of adult females, adult males, and fawns from 3 sources of data: fDNA, camera stations, and global positioning system (GPS) telemetry. We conducted the study on an 11,500‐km2 forested region in northern California, USA, corresponding to 3 hunt management zones. Within a Bayesian framework, we used spatial capture–recapture (SCR) modeling of fDNA samples and prior information on home range sizes from telemetry to estimate sex‐specific densities, and N‐mixture modeling of camera detections to separate adult and fawn densities. We estimated 29,317 adult females (90% CI = 24,550–34,592), 10,845 adult males (90% CI = 7,778–14,858), and 19,587 fawns (90% CI = 15,340–24,430) within the study area. The inclusion of telemetry increased precision of our results, and cameras provided comparable estimates of density when we calibrated them on the SCR results. Based on these results, we recommend a monitoring program of fDNA transects repeated once every 5 years, camera stations repeated at half of transects every year, and telemetry data from 1 deer for every 2 transects on average. We estimated an average annual cost of $1,316 (U.S.) per transect to sustain this endeavor. The integration of cameras with fDNA to combine age structure data with sex‐specific abundance data represents a novel and significant step forward in the capacity to estimate deer population parameters. © 2018 The Authors. Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.

Abstract. Estimating density and population size is often more challenging than measuring indices of abundance because of uncertainty about the effective area of surveys. We combined hierarchical modeling of detection/non-detection data from camera stations with auxiliary information on home range sizes to address this issue. We used this approach to estimate the total population size of fishers (Pekania pennanti) throughout the largest remaining native range (Northern California and Southern Oregon [NCSO], 48,760 km 2 ) of this species in the Pacific States of the United States. After controlling for various habitat, gender, and survey factors affecting detection probability, local abundance, and home range size, we estimated an average density of 6.6 fishers per 100 km 2 (95% confidence interval [CI]: 5.1-8.6) and a total of 3196 fishers (95% CI: 2507-4184). We mapped how fisher density varied throughout the range and demonstrated spatial autocorrelation in density at lag distances up to 40 km. These findings represent the first robust estimate of fisher population size for the range in NCSO. They are important for setting a baseline against which to monitor changes in population status and spatial distribution of fishers which are a species of conservation concern at federal and state levels. However, we note that our estimate of population size is very sensitive to assumptions about the effective area of camera surveys. Our methods could likely be applied to other forest carnivores and highlight the benefits of coordination between researchers to collect and share comparable survey and telemetry data.

Abundance of mule deer (Odocoileus hemionus) in western North America is often considered lower than desirable for hunting. Some coastal populations of Columbian black‐tailed deer (O. h. columbianus) in California, USA, near urban development, however, are perceived as a nuisance and may be overabundant. To determine the density of a potential nuisance population in Marin County, California, we used a combination of fecal DNA surveys, camera stations, and 2 sources of ancillary data on wildlife observations. We estimated an average density of 18.3 deer/km2 (90% CI = 15.8–20.7) throughout Marin County during late summer and early fall, 2015 and 2016. Within the county, areas with intermediate human density (885 people/km2, 90% CI = 125–1,646) were associated with the highest deer densities (25–44/km2). Our estimate of average deer density was 1.7–6.1 times higher than published density estimates for deer from elsewhere in California and on the low end of densities reported for mule and white‐tailed (O. virginianus) deer in regions where they routinely cause a nuisance to humans. High black‐tailed deer densities in Marin County may be partially attributed to a paucity of large predators, but more investigation is warranted to evaluate the effects of a recent increase in coyotes (Canis latrans) on the deer population. Analyses of highway road kill rates and citizen science surveys suggest that the deer population in Marin County has been stable over the past 10 years. Our results demonstrate how robust estimation of deer density can inform human–wildlife conflict issues, not just managed hunting. © 2020 The Authors. The Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.

Hermit Warblers (Setophaga occidentalis) sing a formulaic, type I song to attract mates, in contrast to a repertoire of more complex, type II songs to defend territories. A single, dominant type I song, or a low diversity of type I songs, often occur within a geographic area. We provide the first comprehensive description of Hermit Warbler type I song variants throughout California, USA. We recorded type I songs from 1,588 males across 101 study sites in the state from April through July 2009–2014. Using those locations and a pre-existing range map of the species, we created a maximum entropy-based breeding habitat suitability map and classified the songs into 35 variants using a typological rubric. We validated consistent classification of songs for 87.5% of the birds. We then modeled the effects of recent fire history at the local scale (10 yr, 315 km2), the amount of breeding habitat at the regional scale (8,000 km2), and the distance between territories to examine factors involved in song sameness at the local scale. We found that the probability of different birds singing the same form declined with the amount of local fire, regional habitat, and distance, and that these findings were robust to uncertainty in our song classification rubric. Using a longitudinal analysis including additional data from 10 study areas revisited in 2019, we showed that song structure within forms had drifted since our initial visits 5–10 yr earlier, and that the evenness (e.g., Simpson’s measure) of song forms increased at locations that had been burned by wildfire between visits. Taken together, the results suggest that wildfires and the mass effects of dispersal of birds singing rival song forms disrupt the uniformity of type I songs locally. The results demonstrate how species traits, such as birdsong, can be used to disentangle the ecological processes that regulate observed patterns in biodiversity. Further investigation is recommended to determine whether song pattern dynamics reflect underlying genetic differences and habitat specializations among subpopulations.

Historically, aerial surveys have been used widely to monitor abundance of large mammals in the western United States. In California, such surveys have typically served as minimum count indices rather than true abundance estimates. Here, we evaluated the utility of aerial multiple covariate distance sampling (MCDS) to estimate abundance of three populations of tule elk (Cervus canadensis nannodes) in northern California. We also compared estimates and costs with published results from a concurrent fecal DNA spatial capture-recapture (SCR) survey. During December 2018 and 2019, we flew line transects for distance sampling of tule elk in Colusa and Lake counties. We modeled detection functions and evaluated effects of group size, canopy cover, and survey year. We averaged the top models comprising ≥0.95 of Akaike Model Weight and estimated abundance of both total and discrete populations. Detection probability increased with increasing group size and decreasing canopy cover. We estimated a two-year average total population size of N̂ = 674 elk (90% CI = 501–907) in our survey area which was similar to N̂ = 653 elk (90% CI = 573–745) from SCR estimates. Overall precision was greater (CV = 0.08; range = 0.11–0.30 by population) for SCR than for MCDS (CV = 0.18; range = 0.22–0.43 by population). Although estimates differed somewhat between methods for the individual populations, the combined estimate across the study region compared favorably. Total cost of SCR and MCDS surveys was $98,326 and $147,324, respectively. While SCR efforts were more precise and less expensive overall, our MCDS approach reduced staff time by 64% (587 person-hours) and the number of survey days by 87% (64 days). Our results suggest MCDS methods can produce reliable abundance estimates across a gradient of canopy cover, particularly when observations can be pooled across populations to decrease variance. We recommend future research to assess use of hybrid models, such as mark-recapture distance sampling or hierarchical distance sampling, to improve precision and estimation of detection probability.