The secretive nature of the Mountain Quail (Oreortyx pictus) makes it a difficult species to study. Consequently, many aspects of Mountain Quail biology remain poorly known, including population dynamics and vital rates, dispersal and migration behavior, and the degree of isolation among populations. Addressing the latter gap in our knowledge is of particular importance for understanding the distinct evolutionary histories of populations, delineating management units, and guiding potential translocation efforts (Pope & Crawford 2004).
Much of the current data on patterns of population differentiation come from qualitative analyses of plumage variation. Five subspecies of Mountain Quail have been described based on these plumage analyses, four of which occur in California (van Rossem 1937; Gutiérrez & Delehanty 1999). O. p. palmeri is found in mesic coast ranges from Washington state south to San Luis Obispo Co., California with a gap around the bay area. O. p. pictus is found in the interior coast ranges eastward across northern California and south through the central sierras. O. p. eremophilus occurs in the more arid mountains of southern California and ranges northward through both the southern Sierras and southern coast ranges. Finally, O. p. russelli is confined to the Little San Bernardino Mountains of southern California. The validity of these subspecies has been questioned and the geographic boundaries among subspecies is fairly arbitrary in certain cases (Grinnell & Miller 1944). Genetic data will be important for testing subspecies designations, refining management units for Mountain Quail, and determining whether local adaptation to different climatic regimes exist within the species.
Genetic data have long played a critical role in documenting patterns of population structure that can inform conservation units (Allendorf et al. 2022). The power to resolve even fine-scale patterns of genetic structure has improved dramatically with increasing affordability of genome-scale datasets. Genomic datasets also provide novel opportunities to understand the genetic health of populations through quantification of genetic diversity and to explore local adaptation to distinct environments that may be important to consider in population management. For example, genomic analyses of sage-grouse (Centrocercus spp.) revealed fine-scale patterns of population structure and documented signatures of selection at several genes that may be associated with their dietary specialization on sagebrush (Artemisia spp.), plants rich in toxic secondary metabolites (Oh et al. 2019). Little genetic data of any kind exist for Mountain Quail.
Whole genome sequences from 29 California samples of Mountain Quail were recently obtained as part of the California Conservation Genomics Project (CCGP; Shaffer et al. 2022). Preliminary analyses of this dataset indicate that structure does exist among California populations of the Mountain Quail (FIGURE 1). The principal divide is between populations in the mountains of southern California and more northern populations. Evidence for additional structure also exists within the Sierra Nevada, and between northern coastal ranges and the Sierra Nevada (Fig. 1). However, major geographic gaps exist among the samples included in preliminary analyses. These gaps make it difficult to exclude the possibility of isolation by distance and hamper population delimitation efforts. Filling these gaps will be critical for establishing accurate management units for Mountain Quail in California. To this end, we are partnering with CDFW personnel to obtain an additional 100 Mountain Quail samples from these sample gaps. We plan to generate whole genome sequences from these additional quail samples to address the following objectives:
- Resolve patterns of population structure among Mountain Quail populations in California.
- Quantify genetic diversity across different populations of Mountain Quail.
- Explore patterns of adaptive differentiation among populations to further establish the importance of certain populations as management units.