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Little is known about the population status of many marsh-dependent birds in North America but recent efforts have focused on collecting more reliable information and estimates of population trends. As part of that effort, a standardized survey protocol was developed in 1999 that provided guidance for conducting marsh bird surveys throughout North America such that data would be consistent among locations. The original survey protocol has been revised to provide greater clarification on many issues as the number of individuals using the protocol has grown. The Standardized North American Marsh Bird Monitoring Protocol instructs surveyors to conduct an initial 5-minute passive point-count survey followed by a series of 1-minute segments during which marsh bird calls are broadcast into the marsh following a standardized approach. Surveyors are instructed to record each individual bird from the suite of 26 focal species that are present in their local area on separate lines of a datasheet and estimate the distance to each bird. Also, surveyors are required to record whether each individual bird was detected within each 1-minute subsegment of the survey. These data allow analysts to use several different approaches for estimating detection probability. The Standardized North American Marsh Bird Monitoring Protocol provides detailed instructions that explain the field methods used to monitor marsh birds in North America.

Natal dispersal is a key demographic trait that affects population dynamics, and intraspecific variation in dispersal affects gene flow among populations and source-sink dynamics. However, relatively little is known about the selective pressures and trade-offs that animals face when departing their natal area due to the logistical difficulties associated with monitoring animals during this critical life stage. We used a randomized block design to examine the selective pressure that influence dispersal timing in juvenile burrowing owls ( Athene cunicularia ) by experimentally altering both food and ectoparasites at 135 nests. We also examined the effects of local food abundance, ectoparasite loads, and parental departure on natal dispersal timing. Juvenile burrowing owls varied widely in natal dispersal timing, and phenotypic plasticity in dispersal timing was evident in juvenile owls’ response to our experimental treatments, local conditions, and their parents’ departure from the natal area. Moreover, juveniles responded differently than their parents to experimental manipulation of food and ectoparasite loads. Juveniles typically dispersed shortly after their parents departed the natal area, but delayed dispersing more than 2 weeks after parental departure if they did not receive experimental food supplements during a low-food year. In contrast, the experimental food supplements did not affect the migratory departure decisions of adult owls in either year. Juveniles at nests treated for ectoparasites initiated dispersal at a younger age (and prior to adults in the high-food year) compared to juveniles at control nests. In contrast, parents at nests treated for ectoparasites departed later than parents at control nests. Our results suggest that unfavorable conditions (low food or high ectoparasite loads) caused juveniles to delay dispersal, but prompted adults to depart sooner. Our results highlight the extent of intraspecific variation in natal dispersal timing, and demonstrate that ecological conditions affect dispersal decisions of parents and offspring differently, which can create important trade-offs that likely affect life history strategies and responses to climatic changes.

Highly pathogenic avian influenza virus (HPAIV) has caused extensive mortalities in wild birds with a disproportionate impact on raptors since 2021. The population‐level impact of HPAIV can be informed by telemetry studies that track large samples of initially healthy, wild birds. We leveraged movement data from 71 rough‐legged hawks (Buteo lagopus) across all major North American migratory bird flyways concurrent with the 2022–2023 HPAIV outbreak and identified a total of 29 mortalities, of which 11 were confirmed, and an additional ~9 were estimated to have been caused by HPAIV. We estimated a 28% HPAIV cause‐specific mortality rate among rough‐legged hawks during a single year concurrent with the HPAIV outbreak in North America. Additionally, the overall mortality rate during the HPAIV outbreak (47%) was significantly higher than baseline annual mortality rates (3%–17%) suggesting that HPAIV‐caused deaths were additive above baseline mortality levels. HPAIV mortalities were concentrated within the Central and Atlantic flyways during prebreeding migration and peaked in April 2022 when large‐scale HPAIV mortalities were reported in other wild birds throughout North America. HPAIV exposure was most likely caused by scavenging or preying on infected waterfowl, as rough‐legged hawks are known to opportunistically scavenge during the nonbreeding season. We utilized movement data to identify a continental‐scale HPAIV cause‐specific mortality event in rough‐legged hawks that has the potential to exacerbate ongoing population declines. Our study highlights the usefulness of monitoring movement data to pinpoint sources of mortality that can help better understand the drivers of population change, even if studies are focused on other research questions. We utilized movement data to identify a continental‐scale mortality event caused by highly pathogenic avian influenza virus (HPAIV) in a single species of migratory bird, the rough‐legged hawk (Buteo lagopus). We estimated an HPAIV cause‐specific annual mortality rate of 28% that substantially elevated the overall annual mortality rate (47%) above baseline levels (3%–17%) and has the potential to exacerbate ongoing population declines.

DNA metabarcoding is a rapidly advancing tool for diet assessment in wildlife ecology. Studies have used a variety of field collection methods to evaluate diet; however, there is a pressing need to understand the differences among sampling methods and the downstream inferential consequences they may have on our ability to document diet accurately and efficiently. We evaluated seven DNA metabarcoding sampling methods to assess the diet of a large avian predator: Buteo lagopus (rough‐legged hawk). We collected beak swabs, talon swabs, cheek (buccal) swabs, cloacal swabs, and cloacal loops from captured birds, and collected fecal samples from both captured and uncaptured birds. We described and compared variation in prey recovery within and among the seven sampling methods and identified appropriate analytical methods to compare diet among individuals sampled via different methods. Beak and talon swabs produced the highest prey detection rates, yielded the greatest prey richness per sample, and contributed the most to an individual's total prey richness per sampling occasion compared to other sampling methods. Within individuals sampled using five methods during a single capture occasion, cloacal swabs and cheek swabs positively predicted prey richness and average prey mass, respectively, from fecal samples. While all methods identified similar dominant prey taxa that were consistent with prior diet studies, beak and talon swabs detected greater prey richness at both the individual and population levels. We propose a food residue duration hypothesis whereby methods which sample areas containing food DNA consumed from longer and more continuous pre‐sampling time intervals explain variation among sampling methods in observed prey richness. Choice of sampling method can influence predator diet characterization and is particularly important if researchers wish to quantify uncommon diet items or compare diet metrics using samples collected via different methods. We evaluated seven DNA metabarcoding sampling methods to assess the diet of a large avian predator: Buteo lagopus (rough‐legged hawk). While all sampling methods identified similar dominant prey taxa that were consistent with prior diet studies, swabbing the beak and talons produced greater prey detection rates and prey richness at both the individual and population levels.

Aim Anticipating and mitigating the impacts of climate change on species diversity in montane ecosystems requires a mechanistic understanding of drivers of current patterns of diversity. We documented the shape of elevational gradients in avian species richness in North America and tested a suite of a priori predictions for each of five mechanistic hypotheses to explain those patterns. Location United States Methods We used predicted occupancy maps generated from species distribution models for each of 646 breeding birds to document elevational patterns in avian species richness across the six largest U.S. mountain ranges. We used spatially explicit biotic and abiotic data to test five mechanistic hypotheses proposed to explain geographic variation in species richness. Results Elevational gradients in avian species richness followed a consistent pattern of low elevation plateau‐mid‐elevation peak (as per McCain, 2009). We found support for three of the five hypotheses to explain the underlying cause of this pattern: the habitat heterogeneity, temperature, and primary productivity hypotheses. Main Conclusions Species richness typically decreases with elevation, but the primary cause and precise shape of the relationship remain topics of debate. We used a novel approach to study the richness‐elevation relationship and our results are unique in that they show a consistent relationship between species richness and elevation among 6 mountain ranges, and universal support for three hypotheses proposed to explain the underlying cause of the observed relationship. Taken together, these results suggest that elevational variation in food availability may be the ecological process that best explains elevational gradients in avian species richness in North America. Although much attention has focused on the role of abiotic factors, particularly temperature, in limiting species’ ranges, our results offer compelling evidence that other processes also influence (and may better explain) elevational gradients in species richness. We documented the shape of elevational gradients in avian species richness across the entirety of six U.S. mountain ranges and tested mechanistic hypotheses to explain those patterns. Elevational gradients in avian species richness followed a consistent pattern of low elevation plateau‐mid‐elevation peak (as per McCain, 2009). We found support for three hypotheses to explain this pattern: the Habitat Heterogeneity, Temperature, and Productivity Hypotheses.

Geographic distributions are a basic component of a species’ ecology, and predicting distributions is a fundamental task of conservation and resource management. Reliable prediction depends on identification of appropriate scales of effect for environmental data, and scale‐optimization techniques are thus desirable to identify optimal scales for predictor variables. Recent statistical developments have also advanced methods of model selection based explicitly on predictive ability, which differ from commonly used methods that regulate model structures via anticipated predictive performance. Such methods are beginning to permeate into species distribution models (SDMs), yet there remains no consensus methodology for developing optimally predictive multi‐scale SDMs when covariate data are collected over a range of scales. Thus, we compared the performance of common approaches for scale optimization and model selection in terms of their ability to produce optimally predictive multi‐scale Bayesian occupancy models for predicting a species distribution, using models of the breeding distribution for King Rails (Rallus elegans) as a case study. Our results demonstrate sizable gains in predictive performance for hierarchical occupancy models selected via their ability to predict out‐of‐sample data using the logarithmic scoring rule, as compared to models selected using information criteria (deviance information criteria [DIC] and Watanabe information criteria [WAIC]). Information criteria commonly selected individual covariates, as well as scales of effect for those covariates, with suboptimal predictive performance. Performance of models selected using the logarithmic scoring rule was also robust across the method of scale optimization, which was not true for models selected using DIC and WAIC. Thus, we demonstrate empirical benefits of study designs and statistical tools that enable covariate and scale selection based explicitly on predictive ability. Our results also imply that more careful consideration of what constitutes an optimal scale is warranted in many ecological applications, as the meaning of optimal is not independent of the technique used for scale selection.

Seasonal declines in avian clutch size are well documented, but seasonal variation in other reproductive parameters has received less attention. For example, the probability of complete brood mortality typically explains much of the variation in reproductive success and often varies seasonally, but we know little about the underlying cause of that variation. This oversight is surprising given that nest predation influences many other life-history traits and varies throughout the breeding season in many songbirds. To determine the underlying causes of observed seasonal decreases in risk of nest predation, we modeled nest predation of Dusky Flycatchers (Empidonax oberholseri) in northern California as a function of foliage phenology, energetic demand, developmental stage, conspecific nest density, food availability for nest predators, and nest predator abundance. Seasonal variation in the risk of nest predation was not associated with seasonal changes in energetic demand, conspecific nest density, or predator abundance. Instead, seasonal variation in the risk of nest predation was associated with foliage density (early, but not late, in the breeding season) and seasonal changes in food available to nest predators. Supplemental food provided to nest predators resulted in a numerical response by nest predators, increasing the risk of nest predation at nests that were near supplemental feeders. Our results suggest that seasonal changes in foliage density and factors associated with changes in food availability for nest predators are important drivers of temporal patterns in risk of avian nest predation.

Setting land aside has long been a primary approach for protecting biodiversity; however, the efficacy of this approach has been questioned. We examined whether protecting lands positively influences bird species in the U.S., and thus overall biodiversity. We used the North American Breeding Bird Survey and Protected Areas Database of the U.S. to assess effects of protected and multiple-use lands on the prevalence and long-term population trends of imperiled and non-imperiled bird species. We evaluated whether both presence and proportional area of protected and multiple-use lands surrounding survey routes affected prevalence and population trends for imperiled and non-imperiled species. Regarding presence of these lands surrounding these survey routes, our results suggest that imperiled and non-imperiled species are using the combination of protected and multiple-use lands more than undesignated lands. We found no difference between protected and multiple-use lands. Mean population trends were negative for imperiled species in all land categories and did not differ between the land categories. Regarding proportion of protected lands surrounding the survey routes, we found that neither the prevalence nor population trends of imperiled or non-imperiled species was positively associated with any land category. We conclude that, although many species (in both groups) tend to be using these protected and multiple-use lands more frequently than undesignated lands, this protection does not appear to improve population trends. Our results may be influenced by external pressures (e.g., habitat fragmentation), the size of protected lands, the high mobility of birds that allows them to use a combination of all land categories, and management strategies that result in similar habitat between protected and multiple-use lands, or our approach to detect limited relationships. Overall, our results suggest that the combination of protected and multiple-use lands is insufficient, alone, to prevent declines in avian biodiversity at a national scale.

In herbivores, survival and reproduction are influenced by quality and quantity of forage, and hence, diet and foraging behavior are the foundation of an herbivore's life history strategy. Given the importance of diet to most herbivores, it is imperative that we know the species of plants they prefer, especially for herbivorous species that are at risk for extinction. However, it is often difficult to identify the diet of small herbivores because: (a) They are difficult to observe, (b) collecting stomach contents requires sacrificing animals, and (c) microhistology requires accurately identifying taxa from partially digested plant fragments and likely overemphasizes less‐digestible taxa. The northern Idaho ground squirrel (Urocitellus brunneus) is federally threatened in the United States under the Endangered Species Act. We used DNA metabarcoding techniques to identify the diet of 188 squirrels at 11 study sites from fecal samples. We identified 42 families, 126 genera, and 120 species of plants in the squirrel's diet. Our use of three gene regions was beneficial because reliance on only one gene region (e.g., only trnL) would have caused us to miss >30% of the taxa in their diet. Northern Idaho ground squirrel diet differed between spring and summer, frequency of many plants in the diet differed from their frequency within their foraging areas (evidence of selective foraging), and several plant genera in their diet were associated with survival. Our results suggest that while these squirrels are generalists (they consume a wide variety of plant species), they are also selective and do not eat plants relative to availability. Consumption of particular genera such as Perideridia may be associated with higher overwinter survival. Diet and foraging behavior are the foundation of an herbivore's life history strategy and it is imperative that we know the species of plants they prefer. We used DNA metabarcoding techniques to noninvasively sample the threatened northern Idaho ground squirrel (Urocitellus brunneus) diet. We used three gene regions and found that diets differed on the genus level between season, availability, and survival was associated with particular plants.

Greater sage‐grouse (hereafter sage‐grouse; Centrocercus urophasianus) populations have declined across their range. Increased nest predation as a result of anthropogenic land use is one mechanism proposed to explain these declines. However, sage‐grouse contend with a diverse suite of nest predators that vary in functional traits (e.g., search tactics or hunting mode) and abundance. Consequently, generalizing about factors influencing nest fate is challenging. Identifying the explicit predator species responsible for nest predation events is, therefore, critical to understanding causal mechanisms linking land use to patterns of sage‐grouse nest success. Cattle grazing is often assumed to adversely affect sage‐grouse recruitment by reducing grass height (and hence cover), thereby facilitating nest detection by predators. However, recent evidence found little support for the hypothesized effect of grazing on nest fate at the pasture scale. Rather, nest success appears to be similar on pastures grazed at varying intensities. One possible explanation for the lack of observed effect involves a localized response by one or more nest predators. The presence of cattle may cause a temporary reduction in predator density and/or use within a pasture (the cattle avoidance hypothesis). The cattle avoidance hypothesis predicts a decreased probability of at least one sage‐grouse nest predator predating sage‐grouse nests in pastures with livestock relative to pastures without livestock present during the nesting season. To test the cattle avoidance hypothesis, we collected predator DNA from eggshells from predated nests and used genetic methods to identify the sage‐grouse nest predator(s) responsible for the predation event. We evaluated the influence of habitat and grazing on predator‐specific nest predation. We evaluated the efficacy of our genetic method by deploying artificial nests with trail cameras and compared the results of our genetic method to the species captured via trail camera. Our molecular methods identified at least one nest predator captured predating artificial nests via trail camera for 33 of 35 (94%) artificial nests. We detected nest predators via our molecular analysis at 76 of 114 (67%) predated sage‐grouse nests. The primary predators detected at sage‐grouse nests were coyotes (Canis latrans) and corvids (Corvidea). Grazing did not influence the probability of nest predation by either coyotes or corvids. Sagebrush canopy cover was negatively associated with the probability a coyote predated a nest, distance to water was positively associated with the probability a corvid predated a nest, and average minimum temperature was negatively associated with the probability that either a coyote or a corvid predated a nest. Our study provides a framework for implementing an effective, non‐invasive method for identifying sage‐grouse nest predators that can be used to better understand how management actions at local and regional scales may impact an important component of sage‐grouse recruitment. We used DNA collected from eggshells from predated sage‐grouse nests to identify nest predators. We evaluated the influence of habitat and grazing on predator‐specific nest predation. We evaluated the efficacy of our genetic method by deploying artificial nests with trail cameras and compared the results of our genetic method to the species captured via trail camera.