The rising presence of wildfires in western US landscapes necessitates a better understanding of how wildlife respond to these disturbances both immediately and as scorched habitats recover. Managing for species, such as deer, requires an understanding of which forage items sustain them over different post-fire phases. We used molecular genetic analysis of feces (metabarcoding) to document changes in deer diet during springs of 2017–2021, spanning before and after a large wildfire (Ranch Fire of 2018) in Northern California. We used 707 pellet samples collected both on and off the burn area throughout the 5 years, providing pre-fire (2 yrs), post-fire (1 yr), and recovery (2 yrs) periods, each with burn and control comparisons. We predicted that dietary diversity would decrease post-fire in the burn area as herbaceous and shrub layers were reduced, and increase during the recovery period as pioneer species began to recover. We extracted DNA from fecal pellets and sequenced a trnL gene region of the chloroplast genome on a high-throughput platform. We identified 90 plant taxa from an average of ~7,000 sequencing reads per fecal sample. Diet diversity was high in pre-fire and recovery periods in all sites but significantly reduced post-fire in burn sites only (P < 0.001), with diet dominated by a single forage item, oak (Quercus spp). Diet diversity was dominated by shrub taxa pre-fire but composed proportionally more of herbaceous taxa during recovery. Thus, oak species played a central role in buffering the deer population from immediate impacts of wildfire.

Direct or indirect contact between domestic populations of animals and wildlife carries an inherent risk for transmission of pathogens that cause infectious disease. In Humboldt and Del Norte counties of northern California, ongoing conflict between ranchers and Roosevelt elk groups results from elk use of ranching pastures and pastures on private land. Fecal samples from elk in association with cattle, cattle, and from elk not in known association with cattle were assessed for the presence of bacteria Salmonella enterica and pathogenic Escherichia coli to assess whether association with cattle increases risk of infection for elk. Group identity (one of the elk groups or cattle group) was the leading parameter in infection likelihood models, and elk in association with cattle were over nine times more likely to have pathogenic non-O157:H7 E. coli isolated from their feces than elk that were not in association with cattle.

Population monitoring of game species is essential for supporting regulated hunting programs and for guiding effective conservation of these species in response to climate change, altered land use, and other potential stressors. However, indirect measures of population trend are the best available monitoring data in many situations. We used a 20-year timeseries of indices computed from three independent sources of data (e.g., hunter encounter surveys, harvest records, and citizen science observations) as proxies for the mule deer (Odocoileus hemionus) population status within a 26,400 km2 region of northeastern California. Results suggest that the deer population has steadily increased at an average rate of 1–2% annually, with adult male deer increasing at a faster rate. Periodic oscillations in population were strongly associated with winter severity. Populations appear to respond negatively in the two years following years of heavy snowfall, and the effects of climate change on snowfall may explain the overall increasing population trend. The stability of these apparent patterns is uncertain, and it is unclear whether the trend could be an ecological trap. Efforts underway to apply more robust monitoring methods (e.g., models using data from fecal DNA and aerial surveys) are expected to help answer these questions.

Noninvasive fecal DNA (fDNA)-based spatially explicit capture-recapture (SCR) approaches have proven valuable for estimating abundance of deer (Odocoileus spp) and other wildlife. The utility of SCR approaches for more gregarious species, such as elk (Cervus canadensis), is less clear because grouping behavior formally violates assumptions of statistical independence. We sought to understand the extent of spatial clustering in tule elk (C. c. nannodes) and to assess robustness of SCR estimates to such spatial dependence. Using GPS telemetry of 32 male and 34 female tule elk from 3 northern California populations during Jun–Aug 2017–19, we found strong clustering of female elk, but no detectable clustering by males. Concurrently, we conducted fDNA sampling, obtaining >1,000 genotypes of 425 sex-typed individuals, which we used for conventional CR analysis of the 66 physically captured individuals and for SCR based solely on the fDNA samples. Estimates of abundance from these approaches incorporating both sexes were statistically equivalent, although precision was considerably higher for SCR. Single-sex SCR estimates agreed with these estimates in 2 of the populations but differed in one population for which female spatial clustering was most extreme: in that case, the estimate of female abundance was much higher than in the two-sex model, the conventional CR model, and in an independent study of that population later that same year. We conclude that SCR of both sexes was robust to gregariousness in elk because inclusion of males was sufficient to offset spatial dependence stemming from aggregation of females.

In northern California, Roosevelt (Cervus canadensis roosevelti) and Rocky Mountain (C. c. nelsoni) elk occupy a wide variety of habitats over a large extent, including the Marble Mountains Elk Management Unit (MM EMU) within the Klamath Mountains. Dense forest canopy and steep, mountainous terrain present significant challenges for monitoring elk populations using traditional aerial and ground-based methods. These constraints have resulted in inadequate spatial and temporal research and monitoring. To address the need for comprehensive and reliable elk abundance estimates, we implemented a landscape-level remote camera study within the MM EMU. We deployed 180 remote cameras and applied a time-to-event model to estimate elk abundance. This method utilizes the movement rate, area in front of each camera, and leverages the latency time to detection for a given species. Here, we present the use of a recently developed method to non-invasively estimate the abundance of unmarked elk at the landscape-level in northern California. Implementation of this method can provide reliable information to aid management decisions for the continued recreational, ecological, and economic benefits of elk specifically and wildlife in general.