Search

Conventional life-history theory predicts that energy-demanding events such as reproduction and migration must be temporally segregated to avoid resource limitation. Here, we provide, to our knowledge, the first direct evidence of 'itinerant breeding' in a migratory bird, an incredibly rare breeding strategy (less than 0.1% of extant bird species) that involves the temporal overlap of migratory and reproductive periods of the annual cycle. Based on GPS-tracking of over 200 female American woodcock, most female woodcock (greater than 80%) nested more than once (some up to six times) with short re-nest intervals, and females moved northwards on average 800 km between first and second nests, and then smaller distances ( ca 200+ km) between subsequent nesting attempts. Reliance on ephemeral habitat for breeding, ground-nesting and key aspects of life history that reduce both the costs of reproduction and migration probably explain the prevalence of this rare phenotype in woodcock and why itinerant breeding so rarely occurs in other bird species.

For wide-ranging species in temperate environments, populations at high-latitude range limits are subject to more extreme conditions, colder temperatures, and greater snow accumulation compared with their core range. As climate change progresses, these bounding pressures may become more moderate on average, while extreme weather occurs more frequently. Individuals can mitigate temporarily extreme conditions by changing daily activity budgets and exhibiting plasticity in resource selection, both of which facilitate existence at and expansion of high-latitude range boundaries. However, relatively little work has explored how animals moderate movement and vary resource selection with changing weather, and a general framework for such investigations is lacking. We applied hidden Markov models and step selection functions to GPS data from wintering wild turkeys (Meleagris gallopavo) near their northern range limit to identify how weather influenced transition among discrete movement states, as well as state-specific resource selection. We found that turkeys were more likely to spend time in a stationary state as wind chill temperatures decreased and snow depth increased. Both stationary and roosting turkeys selected conifer forests and avoided land covers associated with foraging, such as agriculture and residential areas, while shifting their strength of selection for these features during poor weather. In contrast, mobile turkeys showed relatively weak resource selection, with less response in selection coefficients during poor weather. Our findings illustrate that behavioral plasticity in response to weather was context dependent, but movement behaviors most associated with poor weather were also those in which resource selection was most plastic. Given our results, the potential for wild turkey range expansion will partly be determined by the availability of habitat that allows them to withstand periodic inclement weather. Combining hidden Markov models with step selection functions is broadly applicable for evaluating plasticity in animal behavior and dynamic resource selection in response to changing weather. We studied turkeys at northern range limits, but this approach is applicable for any system expected to experience significant changes in the coming decade, and may be particularly relevant to populations existing at range peripheries., (© 2022 The Ecological Society of America.)

Abundance estimation is a critical component of conservation planning, particularly for exploited species where managers set regulations to restrict harvest based on current population size. An increasingly common approach for abundance estimation is through integrated population modeling (IPM), which uses multiple data sources in a joint likelihood to estimate abundance and additional demographic parameters. Lincoln estimators are one commonly used IPM component for harvested species, which combine information on the rate and total number of individuals harvested within an integrated band-recovery framework to estimate abundance at large scales. A major assumption of the Lincoln estimator is that banding and recoveries are representative of the whole population, which may be violated if major sources of spatial heterogeneity in survival or harvest rates are not incorporated into the model. We developed an approach to account for spatial variation in harvest rates using a spatial predictive process, which we incorporated into a Lincoln estimator IPM. We simulated data under different configurations of sample sizes, harvest rates, and sources of spatial heterogeneity in harvest rate to assess potential model bias in parameter estimates. We then applied the model to data collected from a field study of wild turkeys ( Meleagris gallapavo ) to estimate local and statewide abundance in Maine, USA. We found that the band recovery model that incorporated a spatial predictive process consistently provided estimates of adult and juvenile abundance with low bias across a variety of spatial configurations of harvest rate and sampling intensities. When applied to data collected on wild turkeys, a model that did not incorporate spatial heterogeneity underestimated the harvest rate in some subregions. Consistent with simulation results, this led to overestimation of both local and statewide abundance. Our work demonstrates that a spatial predictive process is a viable mechanism to account for spatial variation in harvest rates and limit bias in abundance estimates. This approach could be extended to large-scale band recovery data sets and has applicability for the estimation of population parameters in other ecological models as well., Competing Interests: All authors involved attest to having no conflicts of interest related to the submitted manuscript., (© 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Growing populations of Wild Turkeys (Meleagris gallopavo) may result in increased disease transmission among wildlife and spillover to poultry. Lymphoproliferative disease virus (LPDV) is an avian retrovirus that is widespread in Wild Turkeys of eastern North America, and infections may influence mortality and parasite co-infections. We aimed to identify individual and spatial risk factors of LPDV in Maine's Wild Turkeys. We also surveyed for co-infections between LPDV and reticuloendotheliosis virus (REV), Mycoplasma gallisepticum, and Salmonella pullorum to estimate trends in prevalence and examine covariance with LPDV. From 2017 to 2020, we sampled tissues from hunter-harvested (n=72) and live-captured (n=627) Wild Turkeys, in spring and winter, respectively, for molecular detection of LPDV and REV. In a subset of captured individuals (n=235), we estimated seroprevalence of the bacteria M. gallisepticum and S. pullorum using a plate agglutination test. Infection rates for LPDV and REV were 59% and 16% respectively, with a co-infection rate of 10%. Seroprevalence for M. gallisepticum and S. pullorum were 74% and 3.4%, with LPDV co-infection rates of 51% and 2.6%, respectively. Infection with LPDV and seroprevalence of M. gallisepticum and S. pullorum decreased, whereas REV infection increased, between 2018 and 2020. Females (64%), adults (72%), and individuals sampled in spring (76%) had higher risks of LPDV infection than males (47%), juveniles (39%), and individuals sampled in winter (57%). Furthermore, LPDV infection increased with percent forested cover (β=0.014±0.007) and decreased with percent agriculture cover for juveniles (β=-0.061±0.018) sampled in winter. These data enhance our understanding of individual and spatial predictors of LPDV infection in Wild Turkeys and aid in assessing the associated risk to Wild Turkey populations and poultry operations., (© Wildlife Disease Association 2022.)

Weather is a source of environmental variation that can affect population vital rates. However, the influence of weather on individual fitness is spatially heterogeneous and can be driven by other environmental factors, such as habitat composition. Therefore, individuals can experience reduced fitness (e.g., decreased reproductive success) during poor environmental conditions through poor decisions regarding habitat selection. This requires, however, that habitat selection is adaptive and that the organism can correctly interpret the environmental cues to modify habitat use. Greater Sage-Grouse (Centrocercus urophasianus) are an obligate of the sagebrush ecosystems of western North America, relying on sagebrush for food and cover. Greater Sage-Grouse chicks, however, require foods with high nutrient content (i.e., forbs and insects), the abundance of which is both temporally and spatially dynamic and related primarily to water availability. Our goal was to assess whether nest site selection and movements of broods by females reduced the negative effect of drought on offspring survival. As predicted, chick survival was negatively influenced by drought severity. We found that sage-grouse females generally preferred to nest and raise their young in locations where their chicks would experience higher survival. We also found that use of habitats positively associated with chick survival were also positively associated with drought severity, which suggests that females reduced drought impacts on their dependent young by selecting more favorable environments during drought years. Although our findings suggest that female nest site selection and brood movement rates can reduce the negative effects of drought on early offspring survival, the influence of severe drought conditions was not completely mitigated by female behavior, and that drought conditions should be considered a threat to Greater Sage-Grouse population persistence., (© 2016 by the Ecological Society of America.)

Iconic sagebrush ecosystems of the American West are threatened by larger and more frequent wildfires that can kill sagebrush and facilitate invasion by annual grasses, creating a cycle that alters sagebrush ecosystem recovery post disturbance. Thwarting this accelerated grass-fire cycle is at the forefront of current national conservation efforts, yet its impacts on wildlife populations inhabiting these ecosystems have not been quantified rigorously. Within a Bayesian framework, we modeled 30 y of wildfire and climatic effects on population rates of change of a sagebrush-obligate species, the greater sage-grouse, across the Great Basin of western North America. Importantly, our modeling also accounted for variation in sagebrush recovery time post fire as determined by underlying soil properties that influence ecosystem resilience to disturbance and resistance to invasion. Our results demonstrate that the cumulative loss of sagebrush to direct and indirect effects of wildfire has contributed strongly to declining sage-grouse populations over the past 30 y at large spatial scales. Moreover, long-lasting effects from wildfire nullified pulses of sage-grouse population growth that typically follow years of higher precipitation. If wildfire trends continue unabated, model projections indicate sage-grouse populations will be reduced to 43% of their current numbers over the next three decades. Our results provide a timely example of how altered fire regimes are disrupting recovery of sagebrush ecosystems and leading to substantial declines of a widespread indicator species. Accordingly, we present scenario-based stochastic projections to inform conservation actions that may help offset the adverse effects of wildfire on sage-grouse and other wildlife populations., Competing Interests: The authors declare no conflict of interest.

Background: Mating systems that reduce dispersal and lead to non-random mating might increase the potential for genetic structure to arise at fine geographic scales. Greater sage-grouse (Centrocercus urophasianus) have a lek-based mating system and exhibit high site fidelity and skewed mating ratios. We quantified population structure by analyzing variation at 27,866 single-nucleotide polymorphisms in 140 males from ten leks (within five lek complexes) occurring in a small geographic region in central Nevada., Results: Lek complexes, and to a lesser extent individual leks, formed statistically identifiable clusters in ordination analyses, providing evidence for fine-scale geographic genetic differentiation. Lek geography predicted genetic differentiation even at a small geographic scale, which could be sharpened by strong site fidelity. Relatedness was also higher among individuals within lek complexes (and leks), suggesting that reproductive skew, where few males participate in most of the successful matings, could also potentially contribute to genetic differentiation. Models incorporating a habitat resistance surface as a proxy for potentially reduced movement due to landscape features indicated that both geographic distance and habitat suitability (i.e. preferred habitat) predicted genetic structure, with no significant effect of man-made barriers to movement (i.e. power lines and roads). Finally, we illustrate how data sets containing fewer loci (<4000) had less statistical precision and failed to detect the full degree of genetic structure., Conclusion: Our results suggest that habitat features and lek site geography of sage-grouse shape fine scale genetic structure, and highlight how larger data sets can have increased precision and accuracy for quantifying ecologically relevant genetic structure over small geographic scales.

Plant phenological processes produce temporal variation in the height and cover of vegetation. Key aspects of animal life cycles, such as reproduction, often coincide with the growing season and therefore may inherently covary with plant growth. When evaluating the influence of vegetation variables on demographic rates, the decision about when to measure vegetation relative to the timing of demographic events is important to avoid confounding between the demographic rate of interest and vegetation covariates. Such confounding could bias estimated effect sizes or produce results that are entirely spurious. We investigated how the timing of vegetation sampling affected the modeled relationship between vegetation structure and nest survival of greater sage-grouse ( Centrocercus urophasianus ), using both simulated and observational data. We used the height of live grasses surrounding nests as an explanatory covariate, and analyzed its effect on daily nest survival. We compared results between models that included grass height measured at the time of nest fate (hatch or failure) with models where grass height was measured on a standardized date - that of predicted hatch date. Parameters linking grass height to nest survival based on measurements at nest fate produced more competitive models, but slope coefficients of grass height effects were biased high relative to truth in simulated scenarios. In contrast, measurements taken at predicted hatch date accurately predicted the influence of grass height on nest survival. Observational data produced similar results. Our results demonstrate the importance of properly considering confounding between demographic traits and plant phenology. Not doing so can produce results that are plausible, but ultimately inaccurate.

Predictive species distributional models are a cornerstone of wildlife conservation planning. Constructing such models requires robust underpinning science that integrates formerly disparate data types to achieve effective species management.Greater sage-grouse Centrocercus urophasianus , hereafter 'sage-grouse' populations are declining throughout sagebrush-steppe ecosystems in North America, particularly within the Great Basin, which heightens the need for novel management tools that maximize the use of available information.Herein, we improve upon existing species distribution models by combining information about sage-grouse habitat quality, distribution and abundance from multiple data sources. To measure habitat, we created spatially explicit maps depicting habitat selection indices (HSI) informed by >35 500 independent telemetry locations from >1600 sage-grouse collected over 15 years across much of the Great Basin. These indices were derived from models that accounted for selection at different spatial scales and seasons. A region-wide HSI was calculated using the HSI surfaces modelled for 12 independent subregions and then demarcated into distinct habitat quality classes.We also employed a novel index to describe landscape patterns of sage-grouse abundance and space use (AUI). The AUI is a probabilistic composite of the following: (i) breeding density patterns based on the spatial configuration of breeding leks and associated trends in male attendance; and (ii) year-round patterns of space use indexed by the decreasing probability of use with increasing distance to leks. The continuous AUI surface was then reclassified into two classes representing high and low/no use and abundance. Synthesis and application s. Using the example of sage-grouse, we demonstrate how the joint application of indices of habitat selection, abundance and space use derived from multiple data sources yields a composite map that can guide effective allocation of management intensity across multiple spatial scales. As applied to sage-grouse, the composite map identifies spatially explicit management categories within sagebrush steppe that are most critical to sustaining sage-grouse populations as well as those areas where changes in land use would likely have minimal impact. Importantly, collaborative efforts among stakeholders guide which intersections of habitat selection indices and abundance and space use classes are used to define management categories. Because sage-grouse are an umbrella species, our joint-index modelling approach can help target effective conservation for other sagebrush obligate species and can be readily applied to species in other ecosystems with similar life histories, such as central-placed breeding.

Prebreeding survival is an important life history component that affects both parental fitness and population persistence. In birds, prebreeding can be separated into pre- and postfledging periods; carryover effects from the prefledging period may influence postfledging survival. We investigated effects of body condition at fledging, and climatic variation, on postfledging survival of radio-marked greater sage-grouse (Centrocercus urophasianus) in the Great Basin Desert of the western United States. We hypothesized that body condition would influence postfledging survival as a carryover effect from the prefledging period, and we predicted that climatic variation may mediate this carryover effect or, alternatively, would act directly on survival during the postfledging period. Individual body condition had a strong positive effect on postfledging survival of juvenile females, suggesting carryover effects from the prefledging period. Females in the upper 25th percentile of body condition scores had a postfledging survival probability more than twice that (Φ = 0.51 ± 0.06 SE) of females in the bottom 25th percentile (Φ = 0.21 ± 0.05 SE). A similar effect could not be detected for males. We also found evidence for temperature and precipitation effects on monthly survival rates of both sexes. After controlling for site-level variation, postfledging survival was nearly twice as great following the coolest and wettest growing season (Φ = 0.77 ± 0.05 SE) compared with the hottest and driest growing season (Φ = 0.39 ± 0.05 SE). We found no relationships between individual body condition and temperature or precipitation, suggesting that carryover effects operated independently of background climatic variation. The temperature and precipitation effects we observed likely produced a direct effect on mortality risk during the postfledging period. Conservation actions that focus on improving prefledging habitat for sage-grouse may have indirect benefits to survival during postfledging, due to carryover effects between the two life phases.