The tule elk (Cervus elaphus nannodes) was reintroduced to Point Reyes National Seashore, California in 1978. After exhibiting irruptive growth for 20 years, elk abundances have fluctuated. Three subpopulations of elk currently inhabit Pt. Reyes: a fenced subpopulation at high density; a free-ranging subpopulation in designated wilderness at low density; and a free-ranging subpopulation on active ranchland at low density. Little is known about the spatial ecology and population dynamics of tule elk. This unusual situation provided an opportunity to quantify and compare factors affecting the home ranges, group sizes, resource selection, small-scale movements and population dynamics of tule elk. I collected biweekly fixes on radio-collared elk cows between 2005 and 2008 to examine herd structures, space use patterns, grouping behavior and survival rates of tule elk. Radio-telemetry data revealed 6 herds of elk at Pt. Reyes (4 at Tomales), which had distinct herd ranges and showed little spatial interaction. Fixed kernel home ranges were some of the smallest for elk in North America (217 ha, SE = 35), and were negatively correlated with elk density. Home range sizes were 300% smaller than previous estimated for elk at Pt. Reyes in 1998. The sizes of elk groups peaked during the winter and mid-summer, and were smallest during the spring parturition and fall rutting periods. Elk with larger home range sizes generally formed smaller groups. Resource selection function (RSF) results indicated that tule elk at Pt. Reyes selected flat, grassland-dominated habitats over hilly, scrub and forest habitats; although resource selection patterns varied among herds. Elk shifted to lower elevations, steeper slopes and more scrub-dominated habitats during the dry season (May - October). Most elk showed an aversion to areas close to roads and trails, but this result was not consistent across all herds. I quantified small-scale movement patterns of tule elk using hourly fixes from GPS-collared elk. Elk exhibited daily cycles in their movement patterns by increased their hourly movements in the morning and evening hours. Elk daily movements were longest during wet spring months and shortest during the dry fall months. Elk slowed when traveling through homogeneous grassland habitat. Windy conditions caused elk to slow, but precipitation had no effect on elk movement. Elk moved faster when closer to roads and trails. Elk in higher density herds moved slower on an hourly scale than lower density herds, but herd density had no affect on daily movement patterns. Using known-fate models applied to radio-telemetry data, I estimated annual cow elk survival was 0.96 (SE = 0.02). I captured and monitored radio-collared elk calves from 2005 to 2007 to estimate calf survival and causes of mortality. Using known-fate models, I estimated annual survival for elk calves was 0.81 (SE = 0.02). The primary cause of death for both cows and calves was starvation, which was often accompanied by copper and selenium deficiencies. Sensitivity and elasticity estimates of elk vital rates revealed that adult cow elk survival contributed the most (30%) to elk annual population change (λ). The D Ranch and Limantour herds were expected irruptive growth and by 2018 increase to 393 and 389 elk, respectively, based on stochastic population projection models. The projected future abundance of elk in the Tomales herds was dependant on the previous year's annual rainfall: models projected increases in elk abundance following years of above-average rainfall but no change in elk abundance following years of below-average rainfall. Future growth of the D Ranch and Limantour elk herds will likely concentrate on adjacent ranchlands, given RSF models results, and will likely result in future conflicts between NPS management, unless proactive actions are taken.

Long-term, large-scale monitoring of wildlife metacommunities is needed to recognize population declines early enough to identify environmental stressors and facilitate adaptive planning. Potential outcomes include information supporting the designation of new species of conservation concern, or better yet, conservation actions that avert the need for conferring critical statuses. By surveying multiple species, declines of individual species need not be considered in isolation, but can be compared to responses of other species in the metacommunity. However, multi-species monitoring presents a variety of new challenges in terms of appropriate survey methods and analytical techniques for drawing valid ecological inferences.

In this study, I investigated several related aspects of multi-species monitoring. One theme was the role of automated survey methods (e.g., audio recorders and camera stations) that leave a permanent record and easily provide for temporal replication of surveys. I applied occupancy models to repeat surveys for addressing detection probability and providing unbiased estimates of species occurrence. Lastly, I evaluated several novel quantitative methods for comparing community properties using monitoring data.

In the first chapter I considered the effectiveness of automated recorders for monitoring common birds in California forests. I applied single-species occupancy models to 46 species using 5 years of monitoring data in which automated recorders were placed at 453 random sites across a 5.4-million-ha northern California study area. The devices were programmed to record sounds during up to 3 surveys each morning on 3 consecutive days during the breeding season when songbirds were singing from territories. Skilled interpreters reviewed these recordings to identify all species heard during each survey. With Monte Carlo simulation and results from occupancy models, I demonstrated 80% power for monitoring declines as small as 2.5% per year over 20 years for 32 species given a sampling effort of 100 new sites per year. I also determined an effective survey area radius of 30 m to 50 m for automated recorders, and showed that the devices provided similar occupancy estimates as traditional point counts despite lower survey-level detection probability.

In the second chapter I applied multi-species occupancy models to the calculation of biodiversity indices describing metacommunity organization. I used the same automated recorder data set for birds from Chapter One. Specifically, I applied simulation and Bayesian hierarchical models to demonstrate how a failure to address detection probability heterogeneity underestimates the evenness of species occupancy distributions. In models of the bird data I found that a number of species traits (migration, foraging guild, territoriality, body size) were informative in explaining detection probability. By pooling information from common species in a multi-species model, I was able to draw stronger inferences about rarer species than by modeling these species individually. Lastly, I illustrated the ecological significance of species-traits modeling and found that warbler and woodpecker occupancies were evener than for sparrows.

In the third chapter, I proposed a new quantitative method for comparing species abundance distributions. I illustrated this method using avian point count surveys from 4 research forests in California. I applied bootstrap resampling to probabilistically compare the abundances of intermediate ranks among and within species abundance distributions. I found higher abundances of intermediately-common species on 2 of the forests, and ascribed this finding to differences in forest productivity and habitat complexity leading to greater niche partitioning of resources. At the metacommunity-level, I found higher abundances of intermediately-common species for neotropical migrants compared to resident birds.

.

In the fourth chapter, I considered the use of baited camera stations for monitoring Pacific fisher (Pekania pennant pacifica) and other mammals. Cameras were placed at 172 randomly selected forest sites across 2.8 million ha of northwestern California. The duration of each survey was 2 to 4 weeks. I estimated regional occupancy from these data at 2 survey scales (e.g., individual sites [0.465] and pairs of sites 1.6 km apart [0.651]). I also demonstrated 80% power for monitoring declines as small as 2.0% per year over 20 years given a sampling effort of 100 new sites per year. Lastly, I calculated the median latency to first detection for 13 other species of mammals detected at > 5% of sites, showed that latency was < 6 days for 10 of these species, and argued that these results strengthen the case for expanding the use of camera traps to multi-species monitoring.