Range-wide sources of variation in reproductive rates of northern spotted owls.

We conducted a range-wide investigation of the dynamics of site-level reproductive rate of northern spotted owls using survey data from 11 study areas across the subspecies geographic range collected during 1993-2018. Our analytical approach accounted for imperfect detection of owl pairs and misclassification of successful reproduction (i.e., at least one young fledged) and contributed further insights into northern spotted owl population ecology and dynamics. Both nondetection and state misclassification were important, especially because factors affecting these sources of error also affected focal ecological parameters. Annual probabilities of site occupancy were greatest at sites with successful reproduction in the previous year and lowest for sites not occupied by a pair in the previous year. Site-specific occupancy transition probabilities declined over time and were negatively affected by barred owl presence. Overall, the site-specific probability of successful reproduction showed substantial year-to-year fluctuations and was similar for occupied sites that did or did not experience successful reproduction the previous year. Site-specific probabilities for successful reproduction were very small for sites that were unoccupied the previous year. Barred owl presence negatively affected the probability of successful reproduction by northern spotted owls in Washington and California, as predicted, but the effect in Oregon was mixed. The proportions of sites occupied by northern spotted owl pairs showed steep, near-monotonic declines over the study period, with all study areas showing the lowest observed levels of occupancy to date. If trends continue it is likely that northern spotted owls will become extirpated throughout large portions of their range in the coming decades.

Conspecific and congeneric interactions shape increasing rates of breeding dispersal of northern spotted owls.

Breeding dispersal, the movement from one breeding territory to another, is rare for philopatric species that evolved within relatively stable environments, such as the old-growth coniferous forests of the Pacific Northwest. Although dispersal is not inherently maladaptive, the consequences of increased dispersal on population dynamics in populations whose historical dispersal rates are low could be significant, particularly for a declining species. We examined rates and possible causes of breeding dispersal based on a sample of 4,118 northern spotted owls (Strix occidentalis caurina) monitored in seven study areas over 28 yr, 1990-2017, in Oregon and Washington, USA. Using a multistate mark-resight analysis, we investigated the potential impacts of an emergent congeneric competitor (barred owl Strix varia) and forest alteration (extrinsic factors), and social and individual conditions (intrinsic factors) on 408 successive and 1,372 nonsuccessive dispersal events between years. The annual probability of breeding dispersal increased for individual owls that had also dispersed in the previous year and decreased for owls on territories with historically high levels of reproduction. Intrinsic factors including pair status, prior reproductive success, and experience at a site, were also associated with breeding dispersal movements. The percent of monitored owls dispersing each year increased from ˜7% early in the study to ˜25% at the end of the study, which coincided with a rapid increase in numbers of invasive and competitively dominant barred owls. We suggest that the results presented here can inform spotted owl conservation efforts as we identify factors contributing to changing rates of demographic parameters including site fidelity and breeding dispersal. Our study further shows that increasing rates of breeding dispersal associated with population declines contribute to population instability and vulnerability of northern spotted owls to extinction, and the prognosis is unlikely to change unless active management interventions are undertaken.

A need for speed in Bayesian population models: a practical guide to marginalizing and recovering discrete latent states.

Bayesian population models can be exceedingly slow due, in part, to the choice to simulate discrete latent states. Here, we discuss an alternative approach to discrete latent states, marginalization, that forms the basis of maximum likelihood population models and is much faster. Our manuscript has two goals: (1) to introduce readers unfamiliar with marginalization to the concept and provide worked examples and (2) to address topics associated with marginalization that have not been previously synthesized and are relevant to both Bayesian and maximum likelihood models. We begin by explaining marginalization using a Cormack-Jolly-Seber model. Next, we apply marginalization to multistate capture-recapture, community occupancy, and integrated population models and briefly discuss random effects, priors, and pseudo-R2 . Then, we focus on recovery of discrete latent states, defining different types of conditional probabilities and showing how quantities such as population abundance or species richness can be estimated in marginalized code. Last, we show that occupancy and site-abundance models with auto-covariates can be fit with marginalized code with minimal impact on parameter estimates. Marginalized code was anywhere from five to >1,000 times faster than discrete code and differences in inferences were minimal. Discrete latent states and fully conditional approaches provide the best estimates of conditional probabilities for a given site or individual. However, estimates for parameters and derived quantities such as species richness and abundance are minimally affected by marginalization. In the case of abundance, marginalized code is both quicker and has lower bias than an N-augmentation approach. Understanding how marginalization works shrinks the divide between Bayesian and maximum likelihood approaches to population models. Some models that have only been presented in a Bayesian framework can easily be fit in maximum likelihood. On the other hand, factors such as informative priors, random effects, or pseudo-R2 values may motivate a Bayesian approach in some applications. An understanding of marginalization allows users to minimize the speed that is sacrificed when switching from a maximum likelihood approach. Widespread application of marginalization in Bayesian population models will facilitate more thorough simulation studies, comparisons of alternative model structures, and faster learning.

The past and future roles of competition and habitat in the range-wide occupancy dynamics of Northern Spotted Owls.

Slow ecological processes challenge conservation. Short-term variability can obscure the importance of slower processes that may ultimately determine the state of a system. Furthermore, management actions with slow responses can be hard to justify. One response to slow processes is to explicitly concentrate analysis on state dynamics. Here, we focus on identifying drivers of Northern Spotted Owl (Strix occidentalis caurina) territorial occupancy dynamics across 11 study areas spanning their geographic range and forecasting response to potential management actions. Competition with Barred Owls (Strix varia) has increased Spotted Owl territory extinction probabilities across all study areas and driven recent declines in Spotted Owl populations. Without management intervention, the Northern Spotted Owl subspecies will be extirpated from parts of its current range within decades. In the short term, Barred Owl removal can be effective. Over longer time spans, however, maintaining or improving habitat conditions can help promote the persistence of northern spotted owl populations. In most study areas, habitat effects on expected Northern Spotted Owl territorial occupancy are actually greater than the effects of competition from Barred Owls. This study suggests how intensive management actions (removal of a competitor) with rapid results can complement a slower management action (i.e., promoting forest succession).