Review of range-wide vital rates quantifies eastern wild Turkey population trajectory.

Recent declines in eastern wild turkeys (Meleagris gallopavo silvestris) have prompted increased interest in management and research of this important game species. However, the mechanisms underlying these declines are unclear, leaving uncertainty in how best to manage this species. Foundational to effective management of wildlife species is understanding the biotic and abiotic factors that influence demographic parameters and the contribution of vital rates to population growth. Our objectives for this study were to (1) conduct a literature review to collect all published vital rates for eastern wild turkey over the last 50 years, (2) perform a scoping review of the biotic and abiotic factors that have been studied relative to wild turkey vital rates and highlight areas that require additional research, and (3) use the published vital rates to populate a life-stage simulation analysis (LSA) and identify the vital rates that make the greatest contribution to population growth. Based on published vital rates for eastern wild turkey, we estimated a mean asymptotic population growth rate (λ) of 0.91 (95% CI = 0.71, 1.12). Vital rates associated with after-second-year (ASY) females were most influential in determining population growth. Survival of ASY females had the greatest elasticity (0.53), while reproduction of ASY females had lower elasticity (0.21), but high process variance, causing it to explain a greater proportion of variance in λ. Our scoping review found that most research has focused on the effects of habitat characteristics at nest sites and the direct effects of harvest on adult survival, while research on topics such as disease, weather, predators, or anthropogenic activity on vital rates has received less attention. We recommend that future research take a more mechanistic approach to understanding variation in wild turkey vital rates as this will assist managers in determining the most appropriate management approach.

Climate change and expanding invasive species drive widespread declines of native trout in the northern Rocky Mountains, USA.

Climate change and invasive species are major threats to native biodiversity, but few empirical studies have examined their combined effects at large spatial and temporal scales. Using 21,917 surveys collected over 30 years, we quantified the impacts of climate change on the past and future distributions of five interacting native and invasive trout species throughout the northern Rocky Mountains, USA. We found that the occupancy of native bull trout and cutthroat trout declined by 18 and 6%, respectively (1993­2018), and was predicted to decrease by an additional 39 and 16% by 2080. However, reasons for these occupancy reductions markedly differed among species: Climate-driven increases in water temperature and decreases in summer flow likely caused declines of bull trout, while climate-induced expansion of invasive species largely drove declines of cutthroat trout. Our results demonstrate that climate change can affect ecologically similar, co-occurring native species through distinct pathways, necessitating species-specific management actions.

Environmental variability directly affects the prevalence of divorce in monogamous albatrosses.

In many socially monogamous species, divorce is a strategy used to correct for sub-optimal partnerships and is informed by measures of previous breeding performance. The environment affects the productivity and survival of populations, thus indirectly affecting divorce via changes in demographic rates. However, whether environmental fluctuations directly modulate the prevalence of divorce in a population remains poorly understood. Here, using a longitudinal dataset on the long-lived black-browed albatross (Thalassarche melanophris) as a model organism, we test the hypothesis that environmental variability directly affects divorce. We found that divorce rate varied across years (1% to 8%). Individuals were more likely to divorce after breeding failures. However, regardless of previous breeding performance, the probability of divorce was directly affected by the environment, increasing in years with warm sea surface temperature anomalies (SSTA). Furthermore, our state-space models show that warm SSTA increased the probability of switching mates in females in successful relationships. For the first time, to our knowledge, we document the disruptive effects of challenging environmental conditions on the breeding processes of a monogamous population, potentially mediated by higher reproductive costs, changes in phenology and physiological stress. Environmentally driven divorce may therefore represent an overlooked consequence of global change.

Assessing the robustness of time-to-event models for estimating unmarked wildlife abundance using remote cameras.

Recently developed methods, including time-to-event and space-to-event models, estimate the abundance of unmarked populations from encounter rates with camera trap arrays, addressing a gap in noninvasive wildlife monitoring. However, estimating abundance from encounter rates relies on assumptions that can be difficult to meet in the field, including random movement, population closure, and an accurate estimate of movement speed. Understanding how these models respond to violation of these assumptions will assist in making them more applicable in real-world settings. We used simulated walk models to test the effects of violating the assumptions of the time-to-event model under four scenarios: (1) incorrectly estimating movement speed, (2) violating closure, (3) individuals moving within simplified territories (i.e., movement restricted to partially overlapping circles), (4) and individuals clustering in preferred habitat. The time-to-event model was robust to closure violations, territoriality, and clustering when cameras were placed randomly. However, the model failed to estimate abundance accurately when movement speed was incorrectly estimated or cameras were placed nonrandomly with respect to habitat. We show that the time-to-event model can provide unbiased estimates of abundance when some assumptions that are commonly violated in wildlife studies are not met. Having a robust method for estimating the abundance of unmarked populations with remote cameras will allow practitioners to monitor a more diverse array of populations noninvasively. With the time-to-event model, placing cameras randomly with respect to animal movement and accurately estimating movement speed allows unbiased estimation of abundance. The model is robust to violating the other assumptions we tested.

Ecological traits and the spatial structure of competitive coexistence among carnivores.

Competition is a widespread interaction among carnivores, ultimately manifested through one or more dimensions of the species' ecological niche. One of the most explicit manifestations of competitive interactions regards spatial displacement. Its interpretation under a theoretical context provides an important tool to deepen our understanding of biological systems and communities, but also for wildlife management and conservation. We used Bayesian multispecies occupancy models on camera-trapping data from multiple sites in Southwestern Europe (SWE) to investigate competitive interactions within a carnivore guild, and to evaluate how species' ecological traits are shaping coexistence patterns. Seventeen out of 26 pairwise interactions departed from a hypothesis of independent occurrence, with spatial association being twice as frequent as avoidance. Association behaviors were only detected among mesocarnivores, while avoidance mainly involved mesocarnivores avoiding the apex predator (n = 4) and mesocarnivore-only interactions (n = 2). Body mass ratios, defined as the dominant over the subordinate species body mass, revealed an important negative effect ( ß^=-0.38;CI95=-0.81to-0.06 ) on co-occurrence probability, and support that spatially explicit competitive interactions are mostly expressed by larger species able to dominate over smaller ones, with a threshold in body mass ratios of ~4, above which local-scale intraguild coexistence is unlikely. We found a weak relationship between pairwise trophic niche overlap and the probability of coexistence ( ß^=-0.19;CI95=-0.58to0.21 ), suggesting that competition for feeding resources may not be a key driver of competition, at least at the scale of our analysis. Despite local-scale avoidance, regional-scale coexistence appears to be maintained by the spatial structuring of the competitive environment. We provide evidence that SWE ecosystems consist of spatially structured competitive environments, and propose that coexistence among near-sized species is likely achieved through the interplay of "facultative" and "behavioral" character displacements. Factors influencing carnivore coexistence likely include context-dependent density and trait-mediated effects, which should be carefully considered for a sound understanding of the mechanisms regulating these communities.

Estimating large carnivore populations at global scale based on spatial predictions of density and distribution - Application to the jaguar (Panthera onca).

Broad scale population estimates of declining species are desired for conservation efforts. However, for many secretive species including large carnivores, such estimates are often difficult. Based on published density estimates obtained through camera trapping, presence/absence data, and globally available predictive variables derived from satellite imagery, we modelled density and occurrence of a large carnivore, the jaguar, across the species' entire range. We then combined these models in a hierarchical framework to estimate the total population. Our models indicate that potential jaguar density is best predicted by measures of primary productivity, with the highest densities in the most productive tropical habitats and a clear declining gradient with distance from the equator. Jaguar distribution, in contrast, is determined by the combined effects of human impacts and environmental factors: probability of jaguar occurrence increased with forest cover, mean temperature, and annual precipitation and declined with increases in human foot print index and human density. Probability of occurrence was also significantly higher for protected areas than outside of them. We estimated the world's jaguar population at 173,000 (95% CI: 138,000-208,000) individuals, mostly concentrated in the Amazon Basin; elsewhere, populations tend to be small and fragmented. The high number of jaguars results from the large total area still occupied (almost 9 million km2) and low human densities (< 1 person/km2) coinciding with high primary productivity in the core area of jaguar range. Our results show the importance of protected areas for jaguar persistence. We conclude that combining modelling of density and distribution can reveal ecological patterns and processes at global scales, can provide robust estimates for use in species assessments, and can guide broad-scale conservation actions.

Sampling scales define occupancy and underlying occupancy-abundance relationships in animals.

Occupancy-abundance (OA) relationships are a foundational ecological phenomenon and field of study, and occupancy models are increasingly used to track population trends and understand ecological interactions. However, these two fields of ecological inquiry remain largely isolated, despite growing appreciation of the importance of integration. For example, using occupancy models to infer trends in abundance is predicated on positive OA relationships. Many occupancy studies collect data that violate geographical closure assumptions due to the choice of sampling scales and application to mobile organisms, which may change how occupancy and abundance are related. Little research, however, has explored how different occupancy sampling designs affect OA relationships. We develop a conceptual framework for understanding how sampling scales affect the definition of occupancy for mobile organisms, which drives OA relationships. We explore how spatial and temporal sampling scales, and the choice of sampling unit (areal vs. point sampling), affect OA relationships. We develop predictions using simulations, and test them using empirical occupancy data from remote cameras on 11 medium-large mammals. Surprisingly, our simulations demonstrate that when using point sampling, OA relationships are unaffected by spatial sampling grain (i.e., cell size). In contrast, when using areal sampling (e.g., species atlas data), OA relationships are affected by spatial grain. Furthermore, OA relationships are also affected by temporal sampling scales, where the curvature of the OA relationship increases with temporal sampling duration. Our empirical results support these predictions, showing that at any given abundance, the spatial grain of point sampling does not affect occupancy estimates, but longer surveys do increase occupancy estimates. For rare species (low occupancy), estimates of occupancy will quickly increase with longer surveys, even while abundance remains constant. Our results also clearly demonstrate that occupancy for mobile species without geographical closure is not true occupancy. The independence of occupancy estimates from spatial sampling grain depends on the sampling unit. Point-sampling surveys can, however, provide unbiased estimates of occupancy for multiple species simultaneously, irrespective of home-range size. The use of occupancy for trend monitoring needs to explicitly articulate how the chosen sampling scales define occupancy and affect the occupancy-abundance relationship.

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions.

Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer's sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer's sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical design and analyses ensures reliable knowledge about bird populations that is relevant and integral to bird conservation at multiple scales.

Assessing the importance of demographic parameters for population dynamics using Bayesian integrated population modeling.

To successfully respond to changing habitat, climate or harvest, managers need to identify the most effective strategies to reverse population trends of declining species and/or manage harvest of game species. A classic approach in conservation biology for the last two decades has been the use of matrix population models to determine the most important vital rates affecting population growth rate (λ), that is, sensitivity. Ecologists quickly realized the critical role of environmental variability in vital rates affecting λ by developing approaches such as life-stage simulation analysis (LSA) that account for both sensitivity and variability of a vital rate. These LSA methods used matrix-population modeling and Monte Carlo simulation methods, but faced challenges in integrating data from different sources, disentangling process and sampling variation, and in their flexibility. Here, we developed a Bayesian integrated population model (IPM) for two populations of a large herbivore, elk (Cervus canadensis) in Montana, USA. We then extended the IPM to evaluate sensitivity in a Bayesian framework. We integrated known-fate survival data from radio-marked adults and juveniles, fecundity data, and population counts in a hierarchical population model that explicitly accounted for process and sampling variance. Next, we tested the prevailing paradigm in large herbivore population ecology that juvenile survival of neonates <90 d old drives λ using our Bayesian LSA approach. In contrast to the prevailing paradigm in large herbivore ecology, we found that adult female survival explained more of the variation in λ than elk calf survival, and that summer and winter elk calf survival periods were nearly equivalent in importance for λ. Our Bayesian IPM improved precision of our vital rate estimates and highlighted discrepancies between count and vital rate data that could refine population monitoring, demonstrating that combining sensitivity analysis with population modeling in a Bayesian framework can provide multiple advantages. Our Bayesian LSA framework will provide a useful approach to addressing conservation challenges across a variety of species and data types.

A large-scale perspective for managing prairie avifauna assemblages across the western US: influences of habitat, land ownership and latitude.

Future demands for increased food production are expected to have severe impacts on prairie biodiversity and ecosystem integrity. Prairie avifauna of North America have experienced drastic population declines, prompting numerous conservation efforts, which have been informed primarily by small-scale studies. We applied a large-scale perspective that integrates scale dependency in avian responses by analyzing observations of 20 prairie bird species (17 grassland obligates and three sagebrush obligate species) from 2009-2012 in the western prairie region of the United States. We employed a multi-species model approach to examine the relationship of land ownership, habitat, and latitude to landscape-scale species richness. Our findings suggest that patterns and processes influencing avian assemblages at the focal-scale (e.g., inference at the sampling unit) may not function at the landscape-scale (e.g., inference amongst sampling units). Individual species responses to land ownership, habitat and latitude were highly variable. The broad spatial extent of our study demonstrates the need to include lands in private ownership to assess biodiversity and the importance of maintaining habitat diversity to support avian assemblages. Lastly, focal-scale information can document species presence within a study area, but landscape-scale information provides an essential complement to inform conservation actions and policies by placing local biodiversity in the context of an entire region, landscape or ecosystem.

Estimating Sonoran pronghorn abundance and survival with fecal DNA and capture-recapture methods.

Population abundance estimates are important for management but can be challenging to determine in low-density, wide-ranging, and endangered species, such as Sonoran pronghorn (Antilocapra americana sonoriensis). The Sonoran pronghorn population has been increasing; however, population estimates are currently derived from a biennial aerial count that does not provide survival or recruitment estimates. We identified individuals through noninvasively collected fecal DNA and used robust-design capture-recapture to estimate abundance and survival for Sonoran pronghorn in the United States from 2013 to 2014. In 2014 we generated separate population estimates for pronghorn gathered near 13 different artificial water holes and for pronghorn not near water holes. The population using artificial water holes had 116 (95% CI 102-131) and 121 individuals (95% CI 112-132) in 2013 and 2014, respectively. For all locations, we estimated there were 144 individuals (95% CI 132-157). Adults had higher annual survival probabilities (0.83, 95% CI 0.69-0.92) than fawns (0.41, 95% CI 0.21-0.65). Our use of targeted noninvasive genetic sampling and capture-recapture with Sonoran pronghorn fecal DNA was an effective method for monitoring a large proportion of the population. Our results provided the first survival estimates for this population in over 2 decades and precise estimates of the population using artificial water holes. Our method could be used for targeted sampling of broadly distributed species in other systems, such as in African savanna ecosystems, where many species congregate at watering sites.

Examining Temporal Sample Scale and Model Choice with Spatial Capture-Recapture Models in the Common Leopard Panthera pardus.

Many large carnivores occupy a wide geographic distribution, and face threats from habitat loss and fragmentation, poaching, prey depletion, and human wildlife-conflicts. Conservation requires robust techniques for estimating population densities and trends, but the elusive nature and low densities of many large carnivores make them difficult to detect. Spatial capture-recapture (SCR) models provide a means for handling imperfect detectability, while linking population estimates to individual movement patterns to provide more accurate estimates than standard approaches. Within this framework, we investigate the effect of different sample interval lengths on density estimates, using simulations and a common leopard (Panthera pardus) model system. We apply Bayesian SCR methods to 89 simulated datasets and camera-trapping data from 22 leopards captured 82 times during winter 2010-2011 in Royal Manas National Park, Bhutan. We show that sample interval length from daily, weekly, monthly or quarterly periods did not appreciably affect median abundance or density, but did influence precision. We observed the largest gains in precision when moving from quarterly to shorter intervals. We therefore recommend daily sampling intervals for monitoring rare or elusive species where practicable, but note that monthly or quarterly sample periods can have similar informative value. We further develop a novel application of Bayes factors to select models where multiple ecological factors are integrated into density estimation. Our simulations demonstrate that these methods can help identify the "true" explanatory mechanisms underlying the data. Using this method, we found strong evidence for sex-specific movement distributions in leopards, suggesting that sexual patterns of space-use influence density. This model estimated a density of 10.0 leopards/100 km2 (95% credibility interval: 6.25-15.93), comparable to contemporary estimates in Asia. These SCR methods provide a guide to monitor and observe the effect of management interventions on leopards and other species of conservation interest.

Snowshoe hares display limited phenotypic plasticity to mismatch in seasonal camouflage.

As duration of snow cover decreases owing to climate change, species undergoing seasonal colour moults can become colour mismatched with their background. The immediate adaptive solution to this mismatch is phenotypic plasticity, either in phenology of seasonal colour moults or in behaviours that reduce mismatch or its consequences. We observed nearly 200 snowshoe hares across a wide range of snow conditions and two study sites in Montana, USA, and found minimal plasticity in response to mismatch between coat colour and background. We found that moult phenology varied between study sites, likely due to differences in photoperiod and climate, but was largely fixed within study sites with only minimal plasticity to snow conditions during the spring white-to-brown moult. We also found no evidence that hares modify their behaviour in response to colour mismatch. Hiding and fleeing behaviours and resting spot preference of hares were more affected by variables related to season, site and concealment by vegetation, than by colour mismatch. We conclude that plasticity in moult phenology and behaviours in snowshoe hares is insufficient for adaptation to camouflage mismatch, suggesting that any future adaptation to climate change will require natural selection on moult phenology or behaviour.

Camouflage mismatch in seasonal coat color due to decreased snow duration.

Most examples of seasonal mismatches in phenology span multiple trophic levels, with timing of animal reproduction, hibernation, or migration becoming detached from peak food supply. The consequences of such mismatches are difficult to link to specific future climate change scenarios because the responses across trophic levels have complex underlying climate drivers often confounded by other stressors. In contrast, seasonal coat color polyphenism creating camouflage against snow is a direct and potentially severe type of seasonal mismatch if crypsis becomes compromised by the animal being white when snow is absent. It is unknown whether plasticity in the initiation or rate of coat color change will be able to reduce mismatch between the seasonal coat color and an increasingly snow-free background. We find that natural populations of snowshoe hares exposed to 3 y of widely varying snowpack have plasticity in the rate of the spring white-to-brown molt, but not in either the initiation dates of color change or the rate of the fall brown-to-white molt. Using an ensemble of locally downscaled climate projections, we also show that annual average duration of snowpack is forecast to decrease by 29-35 d by midcentury and 40-69 d by the end of the century. Without evolution in coat color phenology, the reduced snow duration will increase the number of days that white hares will be mismatched on a snowless background by four- to eightfold by the end of the century. This novel and visually compelling climate change-induced stressor likely applies to >9 widely distributed mammals with seasonal coat color.

Select tissue mineral concentrations and chronic wasting disease status in mule deer from North-central Colorado.

Trace mineral imbalances have been suggested as having a causative or contributory role in chronic wasting disease (CWD), a prion disease of several North American cervid species. To begin exploring relationships between tissue mineral concentrations and CWD in natural systems, we measured liver tissue concentrations of copper, manganese, and molybdenum in samples from 447 apparently healthy, adult (> or = 2 yr old) mule deer (Odocoileus hemionus) culled or vehicle killed from free-ranging populations in north-central Colorado, United States, where CWD occurs naturally; we also measured copper concentrations in brain-stem (medulla oblongata at the obex) tissue from 181 of these deer. Analyses revealed a wide range of concentrations of all three minerals among sampled deer (copper: 5.6-331 ppm in liver, 1.5-31.9 ppm in obex; manganese: 0.1-21.4 ppm in liver; molybdenum: 0.5-4.0 ppm in liver). Bayesian multiple regression analysis revealed a negative association between obex copper (-0.097; 95% credible interval -0.192 to -0.006) and the probability of sampled deer also being infected with CWD, as well as a positive association between liver manganese (0.158; 95% credible interval 0.066 to 0.253) and probability of infection. We could not discern whether the tendencies toward lower brain-stem copper concentrations or higher systemic manganese concentrations in infected deer preceded prion infection or rather were the result of infection and its subsequent effects, although the distribution of trace mineral concentrations in infected deer seemed more suggestive of the latter.

Lions and prions and deer demise.

BACKGROUND: Contagious prion diseases--scrapie of sheep and chronic wasting disease of several species in the deer family--give rise to epidemics that seem capable of compromising host population viability. Despite this prospect, the ecological consequences of prion disease epidemics in natural populations have received little consideration. METHODOLOGY/PRINCIPAL FINDINGS: Using a cohort study design, we found that prion infection dramatically lowered survival of free-ranging adult (>2-year-old) mule deer (Odocoileus hemionus): estimated average life expectancy was 5.2 additional years for uninfected deer but only 1.6 additional years for infected deer. Prion infection also increased nearly fourfold the rate of mountain lions (Puma concolor) preying on deer, suggesting that epidemics may alter predator-prey dynamics by facilitating hunting success. Despite selective predation, about one fourth of the adult deer we sampled were infected. High prevalence and low survival of infected deer provided a plausible explanation for the marked decline in this deer population since the 1980s. CONCLUSION: Remarkably high infection rates sustained in the face of intense predation show that even seemingly complete ecosystems may offer little resistance to the spread and persistence of contagious prion diseases. Moreover, the depression of infected populations may lead to local imbalances in food webs and nutrient cycling in ecosystems in which deer are important herbivores.

Epidemic pasteurellosis in a bighorn sheep population coinciding with the appearance of a domestic sheep.

A pneumonia epidemic reduced bighorn sheep (Ovis canadensis) survival and recruitment during 1997-2000 in a population comprised of three interconnected wintering herds (Kenosha Mountains, Sugarloaf Mountain, Twin Eagles) that inhabited the Kenosha and Tarryall Mountain ranges in central Colorado, USA. The onset of this epidemic coincided temporally and spatially with the appearance of a single domestic sheep (Ovis aires) on the Sugarloaf Mountain herd's winter range in December 1997. Although only bighorns in the Sugarloaf Mountain herd were affected in 1997-98, cases also occurred during 1998-99 in the other two wintering herds, likely after the epidemic spread via established seasonal movements of male bighorns. In all, we located 86 bighorn carcasses during 1997-2000. Three species of Pasteurella were isolated in various combinations from affected lung tissues from 20 bighorn carcasses where tissues were available and suitable for diagnostic evaluation; with one exception, beta-hemolytic mannheimia (Pasteurella) haemolytica (primarily reported as biogroup 1(G) or 1(alphaG)) was isolated from lung tissues of cases evaluated during winter 1997-98. The epidemic dramatically lowered adult bighorn monthly survival in all three herds; a model that included an acute epidemic effect, differing between sexes and with vaccination status, that diminished linearly over the next 12 mo best represented field data. In addition to the direct mortality associated with epidemics in these three herds, lamb recruitment in years following the pneumonia epidemic also was depressed as compared to years prior to the epidemic. Based on observations presented here, pasteurellosis epidemics in free-ranging bighorn sheep can arise through incursion of domestic sheep onto native ranges, and thus minimizing contact between domestic and bighorn sheep appears to be a logical principle for bighorn sheep conservation.

Understanding abundance patterns of a declining seabird: implications for monitoring.

The Kittlitz's Murrelet (Brachyramphus brevirostris) is a rare, non-colonial seabird often associated with tidewater glaciers and a recent candidate for listing under the Endangered Species Act. We estimated abundance of Kittlitz's Murrelets across space and time from at-sea surveys along the coast of Alaska (USA) and then used these data to develop spatial models to describe abundance patterns and identify environmental factors affecting abundance. Over a five-week period in the summer of 2005, we recorded 794 Kittlitz's Murrelets, 16 Marbled Murrelets (B. marmoratus), and 70 unidentified murrelets. The overall population estimate (N, mean +/- SE) during the peak period (3-9 July) was 1317 +/- 294 birds, decreasing to 68 +/- 37 by the last survey period (31 July-6 August). Density of Kittlitz's Murrelets was highest in pelagic waters of Taan Fjord (18.6 +/- 7.8 birds/km2, mean +/- SE) during 10-16 July. Spatial models identified consistent "hotspots" of Kittlitz's Murrelets, including several small areas where high densities of murrelets were found throughout the survey period. Of the explanatory variables that we evaluated, tidal current strength influenced murrelet abundance most consistently, with higher abundance associated with strong tidal currents. Simulations based on the empirically derived estimates of variation demonstrated that spatial variation strongly influenced power to detect trend, although power changed little across the threefold difference in the coefficient of variation on detection probability. We include recommendations for monitoring Kittlitz's Murrelets (or other marine species) when there is a high degree of uncertainty about factors affecting abundance, especially spatial variability.

Review of capture-recapture methods applicable to noninvasive genetic sampling.

The use of noninvasive genetic sampling to identify individual animals for capture-recapture studies has become widespread in the past decade. Strong emphasis has been placed on the field protocols and genetic analyses with fruitful results. Little attention has been paid to the capture-recapture application for this specific type of data beyond stating the effects of assumption violations. Here, we review the broad class of capture-recapture methods that are available for use with DNA-based capture-recapture data, noting the array of biologically interesting parameters such as survival, emigration rates, state transition rates and the finite rate of population change that can be estimated from such data. We highlight recent developments in capture-recapture theory specifically designed for noninvasive genetic sampling data.