John R. Sauer’s research while affiliated with United States Geological Survey and other places

As climate change alters the global environment, it is critical to understand the relationship between shifting climate suitability and species distributions. Key questions include whether observed changes in population abundance are aligned with the velocity and direction of shifts predicted by climate suitability models and if the responses are consistent among species with similar ecological traits. We examined the direction and velocity of the observed abundance-based distribution centroids compared with the model-predicted bioclimatic distribution centroids of 250 bird species across the United States from 1969 to 2011. We hypothesized that there is a significant positive correlation in both direction and velocity between the observed and the modeled shifts. We then tested five additional hypotheses that predicted differential shifting velocity based on ecological adaptability and climate change exposure. Contrary to our hypotheses, we found large differences between the observed and modeled shifts among all studied bird species and within specific ecological guilds. However, temperate migrants and habitat generalist species tended to have higher velocity of observed shifts than other species. Neotropical migratory and wetland birds also had significantly different observed velocities than their counterparts, which may be due to their climate change exposure. The velocity based on modeled bioclimatic suitability did not exhibit significant differences among most guilds. Boreal forest birds were the only guild with significantly faster modeled-shifts than the other groups, suggesting an elevated conservation risk for high latitude and altitude species. The highly idiosyncratic species responses to climate and the mismatch between shifts in modeled and observed distribution centroids highlight the challenge of predicting species distribution change based solely on climate suitability and the importance of non-climatic factors traits in shaping species distributions.

Effectively managing take of wildlife resulting from human activities poses a major challenge for applied conservation. Demographic data essential to decisions regarding take are often expensive to collect and are either not available or based on limited studies for many species. Therefore, modeling approaches that efficiently integrate available information are important to improving the scientific basis for sustainable take thresholds. We used the prescribed take level (PTL) framework to estimate allowable take for bald eagles (Haliaeetus leucocephalus) in the conterminous United States. We developed an integrated population model (IPM) that incorporates multiple sources of information and then use the model output as the scientific basis for components of the PTL framework. Our IPM is structured to identify key parameters needed for the PTL and to quantify uncertainties in those parameters at the scale at which the United States Fish and Wildlife Service manages take. Our IPM indicated that mean survival of birds >1 year old was high and precise (0.91, 95% CI = 0.90–0.92), whereas mean survival of first‐year eagles was lower and more variable (0.69, 95% CI = 0.62–0.78). We assumed that density dependence influenced recruitment by affecting the probability of breeding, which was highly imprecise and estimated to have declined from approximately 0.988 (95% CI = 0.985–0.993) to 0.66 (95% CI = 0.34–0.99) between 1994 and 2018. We sampled values from the posterior distributions of the IPM for use in the PTL and estimated that allowable take (e.g., permitted take for energy development, incidental collisions with human made structures, or removal of nests for development) ranged from approximately 12,000 to 20,000 individual eagles depending on risk tolerance and form of density dependence at the scale of the conterminous United States excluding the Southwest. Model‐based thresholds for allowable take can be inaccurate if the assumptions of the underlying framework are not met, if the influence of permitted take is under‐estimated, or if undetected population declines occur from other sources. Continued monitoring and use of the IPM and PTL frameworks to identify key uncertainties in bald eagle population dynamics and management of allowable take can mitigate this potential bias, especially where improved information could reduce the risk of permitting non‐sustainable take. We used the Prescribed Take Level framework to incorporate management objectives, risk tolerance, population size, and demographic rates to revise previous estimates of allowable take for bald eagles in the conterminous United States. We developed an integrated population model to provide stronger inferences from contemporary demographic data to inform the estimates of allowable take. The United States Fish and Wildlife Service can use the allowable take thresholds we provide for permitting take as specified in the Bald and Golden Eagle Protection Act.

Status and trends of American Woodcock Scolopax minor populations in the eastern and central US and Canada are monitored via a Singing-ground Survey , conducted just after sunset along roadsides in spring. Annual analyses of the survey produce estimates of trend and annual indexes of abundance for 25 states and provinces, eastern and central management regions, and survey-wide. In recent years, a log-linear hierarchical model that defines year effects as random effects in the context of a slope parameter (the S Model) has been used to model population change. Recently, alternative models have been proposed for analysis of Singing-ground Survey data. Analysis of a similar roadside survey, the North American Breeding Bird Survey , has indicated that alternative models are preferable for almost all species analyzed in the Breeding Bird Survey. Here, we use leave-one-out cross validation to compare model fit for the present Singing-ground Survey model to fits of three alternative models, including a model that describes population change as the difference in expected counts between successive years (the D model) and two models that include t -distributed extra-Poisson overdispersion effects (H models) as opposed to normally-distributed extra-Poisson overdispersion. Leave-one-out cross validation results indicate that the D model was favored by the Bayesian predictive information criterion but a pairwise t -test indicated that model D was not significantly better-fitting to Singing-ground Survey data than the S model. The H models are not preferable to the alternatives with normally-distributed overdispersion. All models provided generally similar estimates of trend and annual indexes suggesting that, within this model set, choice of model will not lead to alternative conclusions regarding population change. However, as in Breeding Bird Survey analyses, we note a tendency for S model results to provide slightly more extreme estimates of trend relative to D models. We recommend use of the D model for future Singing-ground Survey analyses.

The North American Breeding Bird Survey (BBS) provides data that can be used in complex, multiscale analyses of population change, while controlling for scale‐specific nuisance factors. Many alternative models can be fit to the data, but most model selection procedures are not appropriate for hierarchical models. Leave‐one‐out cross‐validation (LOOCV), in which relative model fit is assessed by omitting an observation and assessing the prediction of a model fit using the remainder of the data, provides a reasonable approach for assessing models, but is time consuming and not feasible to apply for all observations in large data sets. We report the first large‐scale formal model selection for BBS data, applying LOOCV to stratified random samples of observations from BBS data. Our results are for 548 species of North American birds, comparing the fit of four alternative models that differ in year effect structures and in descriptions of extra‐Poisson overdispersion. We use a hierarchical model among species to evaluate posterior probabilities that models are best for individual species. Models in which differences in year effects are conditionally independent (D models) were generally favored over models in which year effects are modeled by a slope parameter and a random year effect (S models), and models in which extra‐Poisson overdispersion effects are independent and t‐distributed (H models) tended to be favored over models where overdispersion was independent and normally distributed. Our conclusions lead us to recommend a change from the conventional S model to D and H models for the vast majority of species (544/548). Comparison of estimated population trends based on the favored model relative to the S model currently used for BBS summaries indicates no consistent differences in estimated trends. Of the 18 species that showed large differences in estimated trends between models, estimated trends from the default S model were more extreme, reflecting the influence of the slope parameter in that model for species that are undergoing large population changes. WAIC, a computationally simpler alternative to LOOCV, does not appear to be a reliable alternative to LOOCV.

Staggering decline of bird populations Because birds are conspicuous and easy to identify and count, reliable records of their occurrence have been gathered over many decades in many parts of the world. Drawing on such data for North America, Rosenberg et al. report wide-spread population declines of birds over the past half-century, resulting in the cumulative loss of billions of breeding individuals across a wide range of species and habitats. They show that declines are not restricted to rare and threatened species—those once considered common and wide-spread are also diminished. These results have major implications for ecosystem integrity, the conservation of wildlife more broadly, and policies associated with the protection of birds and native ecosystems on which they depend. Science , this issue p. 120

Analysis of North American Breeding Bird Survey (BBS) data requires controls for factors that influence detectability of birds along survey routes. Identifying factors that influence the counting process and incorporating them into analyses is a primary means of limiting bias in estimates of population change. Twedt (2015) implemented an alternative counting protocol on operational and nonrandom BBS survey routes in the southeastern United States. Observers on selected routes employed a time–distance protocol in which they recorded birds in 1-min intervals and in 2 distance categories. We hypothesized that processing and recording observations using this time–distance protocol could cause observers to count fewer birds relative to observers using the standard protocol. We used a hierarchical log-linear model with a categorical covariate associated with protocol (standard vs. time–distance) to assess whether use of the time–distance protocol had a measurable effect on counting birds along BBS routes. We applied this model to BBS data from portions of 8 states in which the time–distance protocol was implemented and estimated a protocol effect for 167 bird species. We documented a significant overall effect of the time–distance protocol on observers’ counts of birds. On average, the effect of the time–distance protocol was a 10% decline in counted birds; 80% of species had lower counts when the time–distance protocol was used on a survey route. However, because the time–distance protocol was only used on a small portion of the operational BBS routes and for a limited time, including the covariate for the time–distance protocol data had insignificant effects on analysis of population change. Although the covariate controlled for the effects of the time–distance protocol in BBS data, the results emphasize the importance of standardization as well as a need to track and, if necessary, control in analyses for changes in counting procedures along BBS routes.

Black vultures (Coragyps atratus) have been increasing in density and expanding their range in the eastern United States since at least the 1960s. In many areas, their densities have increased to the level where they are causing damage to property and livestock and the number of requests for allowable take permits has increased throughout these areas. The United States Fish and Wildlife Service (USFWS) requires updated information to help inform the number of take permits that could reduce conflicts while meeting obligations under the Migratory Bird Treaty Act. We expanded analyses used to estimate allowable take in Virginia to cover the range of black vultures in the eastern United States. We used the prescribed take level approach, which integrates demographic rates, population size estimates, and management objectives into an estimate of allowable take. We provide estimates of allowable take at 4 different scales: individual states, Bird Conservation Regions, USFWS administrative regions, and flyways. Our updated population time series provides evidence of rapidly increasing black vulture populations in many regions of the eastern United States, with an overall population estimate of approximately 4.26 million in 2015 in the Atlantic and Mississippi Flyways. Estimated allowable take ranged from a few hundred individuals per year in states at the northern end of the species range to approximately 287,000/year over the entire eastern United States. The USFWS has no legal mandate regarding the spatial scale at which take should be managed and we found little biological evidence of subpopulation structure for black vultures in the eastern United States. We suggest that allowable take for the species be implemented at a scale that meets stakeholder objectives (e.g., reducing conflict, and ensuring that black vultures are not extirpated from local areas) and is efficient for administrative and monitoring purposes. Published 2018. This article is a U.S. Government work and is in the public domain in the USA. We estimated allowable lethal take of black vultures at different spatial scales throughout the eastern portion of the United States. Population size of this species has been increasing rapidly and sustainable allowable take ranged from a few hundred individuals in states along the northern portion of their range to approximately 287,000 individuals range‐wide in the eastern United States.

N‐mixture models provide an appealing alternative to mark‐recapture models, in that they allow for estimation of detection probability and population size from count data, without requiring that individual animals be identified. There is, however, a cost to using the N‐mixture models: inference is very sensitive to the model's assumptions. We consider the effects of three violations of assumptions which might reasonably be expected in practice: double counting, unmodeled variation in population size over time, and unmodeled variation in detection probability over time. These three examples show that small violations of assumptions can lead to large biases in estimation. The violations of assumptions we consider are not only small qualitatively, but are also small in the sense that they are unlikely to be detected using goodness‐of‐fit tests. In cases where reliable estimates of population size are needed, we encourage investigators to allocate resources to acquiring additional data, such as recaptures of marked individuals, for estimation of detection probabilities. This article is protected by copyright. All rights reserved.