Estimates Of Demographic Parameters Research Articles

Modeling movements improves capture–recapture estimates for mobile species with sparse data: Polar bears (Ursus maritimus) in Viscount Melville sound

AbstractWildlife management requires estimates of demographic parameters that are difficult to obtain for mobile species at low densities. Biased parameter estimates often result from capture–recapture (CR) studies due to small sample sizes and unequal recapture probabilities, the latter of which can be caused by animal movements with respect to the sampling area. We developed a multistate CR model designed to minimize biases by including multiple data types (capture, harvest, natural mortality, and telemetry) and accounting for temporary emigration. We applied the model to data collected intensively from 2012 to 2014, and intermittently since the 1970s, for the Viscount Melville (VM) subpopulation of polar bears (Ursus maritimus) in the Canadian Arctic. The number of bears within the VM subpopulation boundary likely increased from an average of 145 (Bayesian 95% credible interval [CRI] [109, 221]) in 1989–1992 to 235 (95% CRI [148, 569]) in 2012–2014. Survival probability increased for all sex and age classes except adult females, for which estimates declined due to unknown reasons. Polar bear movements exhibited Markovian dependence with approximately 28% of the subpopulation located outside of the sampling area each spring. This contributed to inaccurate parameter estimates when using a simpler, single‐state CR model that only included capture data. Although the interpretation of demographic status was complicated by statistical uncertainty and changes in study design, our findings suggest that—as of 2014—the VM polar bear subpopulation had likely recovered from an earlier period of overharvest, was stable, and had not exhibited detectable negative effects of climate warming.

Importance of accounting for imperfect detection of plants in the estimation of population growth rates

Detection of plant individuals is imperfect. Not accounting for this issue can result in biased estimates of demographic parameters as important as population growth rates. In mobile organisms, a common practice is to explicitly account for detection probability during the estimation of most demographic parameters, but no study in plant populations has examined the consequences of ignoring imperfect detectability on the estimation of population growth rates. The lack of accounting for detection probability occurs because plant demographers have frequently assumed that detection is perfect, and because there is a scarcity of studies that formally compare the performance of estimation methods that incorporate detection probabilities with respect to methods that ignore detectabilities. Based on field data of five plant species and data simulations, we compared the performance of three methods that estimate population growth rates, two that do not estimate detection probabilities (direct counts of individuals and the minimum‐number‐alive method) and the other that explicitly accounts for detection probabilities (temporal symmetry models). Our aims were 1) to estimate detection probabilities, and 2) to evaluate the performance of these three methods by calculating bias, accuracy, and precision in their estimates of population growth rates. Our five plant species had imperfect detection. Estimates of population growth rates that explicitly incorporate detectabilities had better performance (less biased estimates, with higher accuracy and precision) than those obtained with the two methods that do not calculate detection probabilities. In these latter methods, bias increases as detection probability decreases. Our findings highlight the importance of using robust analytical methods that account for detection probability of plants during the estimation of critical demographic parameters such as population growth rates. In this way, estimates of plant population parameters will reliably indicate their actual status and quantitative trends.

The tale of the rattle: Using rattle size to understand growth and sexual dimorphism in an insular population of rattlesnakes (Crotalus oreganus caliginis).

Islands have played a key role in our understanding of rapid evolution. A large body of literature has examined morphological changes in response to insularity and isolation, which has yielded useful generalizations about how animals can adapt to live in very small geographic areas. However, understanding the evolution of morphological variation in insular populations often requires detailed data sets on longitudinal patterns of growth and development, and such studies typically necessitate long-term mark-recapture on a large sample of individuals. Rattlesnakes provide a unique opportunity to address some of these difficulties because the addition of rattle segments to the rattle string occurs with regular periodicity and their size directly correlates with the body size of the snake at the time of the ecdysis cycle generating the segment. Here, we used a large database of rattle segment sizes recorded from island (Isla Coronado Sur, Baja California, Mexico) and mainland (Camp Pendleton, California, United States) populations of Western Rattlesnakes (Crotalus oreganus and C. o. caliginis) that separated approximately 10,000 years ago to compare body sizes at different ecdysis cycles, which allowed us to assess differences in growth rates and patterns of sexual size dimorphism. Our results show that rattlesnakes on Isla Coronado Sur appear to be born smaller and grow more slowly than their mainland counterparts, resulting in a "dwarfed" island population. However, despite significant differences in body size, both populations exhibited the same degree of sexual dimorphism. Our study demonstrates the potential to use rattle characteristics to recover detailed estimates of fundamental demographic parameters.

Biogeographic analysis of population density of white-tailed deer in Mexico: Importance of the Protected Natural Areas and Wildlife Management Units

The white-tailed deer Odocoileus virginianus is the wildlife species with the greatest geographic distribution and economic importance in Mexico. This article presents a biogeographic analysis of the population density of this deer species by federal states, vegetation types, biogeographic provinces, and field methods, based on 200 selected studies. Estimates are highly variable and potentially biased due to the different field designs and statistical analyses. The national average density was estimated at 6.9 deer/km2 (SD = 5.1); specifically, 75.5 % of the estimates were less than 10 deer/km2, and only 5.5 % were greater than 15 deer/km2. The highest densities were obtained in the northern region by applying the strip transect counts; while estimations using the fecal group count method were more variable and were the most used method in temperate and tropical dry forest regions. The states with the highest densities were Coahuila, Tamaulipas, Jalisco, Morelos, Michoacán, and Durango. The highest densities were estimated in the xerophilous scrublands of the northeast, intermediate for temperate, tropical dry, and sub-deciduous forests; and the lowest in the tropical wet forest. The highest densities were reported for the Tamaulipeca province followed by the Altiplano Chihuahuense, Sierra Madre Occidental, Costa Pacífica, and Depresión del Balsas. The results of this analysis could guide management strategies for the conservation and sustainable use of this species in extensive UMAs and ANPs, and also to test ecological hypotheses. However, applying more rigorous field design and statistical analysis is important to obtain confident estimates of population density and other demographic parameters to monitor population dynamics.

The Effects of Mutation and Recombination Rate Heterogeneity on the Inference of Demography and the Distribution of Fitness Effects.

Disentangling the effects of demography and selection has remained a focal point of population genetic analysis. Knowledge about mutation and recombination is essential in this endeavor; however, despite clear evidence that both mutation and recombination rates vary across genomes, it is common practice to model both rates as fixed. In this study, we quantify how this unaccounted for rate heterogeneity may impact inference using common approaches for inferring selection (DFE-alpha, Grapes, and polyDFE) and/or demography (fastsimcoal2 and δaδi). We demonstrate that, if not properly modeled, this heterogeneity can increase uncertainty in the estimation of demographic and selective parameters and in some scenarios may result in mis-leading inference. These results highlight the importance of quantifying the fundamental evolutionary parameters of mutation and recombination before utilizing population genomic data to quantify the effects of genetic drift (i.e. as modulated by demographic history) and selection; or, at the least, that the effects of uncertainty in these parameters can and should be directly modeled in downstream inference.

Radiomic tractometry reveals tract-specific imaging biomarkers in white matter

Tract-specific microstructural analysis of the brain’s white matter (WM) using diffusion MRI has been a driver for neuroscientific discovery with a wide range of applications. Tractometry enables localized tissue analysis along tracts but relies on bare summary statistics and reduces complex image information along a tract to few scalar values, and so may miss valuable information. This hampers the applicability of tractometry for predictive modelling. Radiomics is a promising method based on the analysis of numerous quantitative image features beyond what can be visually perceived, but has not yet been used for tract-specific analysis of white matter. Here we introduce radiomic tractometry (RadTract) and show that introducing rich radiomics-based feature sets into the world of tractometry enables improved predictive modelling while retaining the localization capability of tractometry. We demonstrate its value in a series of clinical populations, showcasing its performance in diagnosing disease subgroups in different datasets, as well as estimation of demographic and clinical parameters. We propose that RadTract could spark the establishment of a new generation of tract-specific imaging biomarkers with benefits for a range of applications from basic neuroscience to medical research.

Exact confidence intervals for population growth rate, longevity and generation time

By quantifying key life history parameters in populations, such as growth rate, longevity, and generation time, researchers and administrators can obtain valuable insights into its dynamics. Although point estimates of demographic parameters have been available since the inception of demography as a scientific discipline, the construction of confidence intervals has typically relied on approximations through series expansions or computationally intensive techniques. This study introduces the first mathematical expression for calculating confidence intervals for the aforementioned life history traits when individuals are unidentifiable and data are presented as a life table. The key finding is the accurate estimation of the confidence interval for r, the instantaneous growth rate, which is tested using Monte Carlo simulations with four arbitrary discrete distributions. In comparison to the bootstrap method, the proposed interval construction method proves more efficient, particularly for experiments with a total offspring size below 400. We discuss handling cases where data are organized in extended life tables or as a matrix of vital rates. We have developed and provided accompanying code to facilitate these computations.

FROM POPULATIONAL OBSERVATIONS TO AN ASSESSMENT OF THEIR STATE: EXPERIENCE FROM A COMPREHENSIVE STUDY ON THE DEMOGRAPHIC PARAMETERS OF THE WESTERN SIBERIAN POPULATION OF THE EUROPEAN PIED FLYCATCHER, <i>FICEDULA HYPOLEUCA</i> (MUSCICAPIDAE, PASSERIFORMES)

Key demographic parameters were calculated using the European pied flycatcher (Ficedula hypoleuca) as a model species for the study of bird population ecology. In the Tomsk Region, southeastern part of western Siberia, birds nesting in nest boxes situated in natural forests for 22 years were continuously studied. Where possible, life tables, probability models (CJS), and population matrix models were employed in the calculation of demographics. A comprehensive study of population characteristics made it possible to compare them with the results of other research and to demonstrate the degree of divergence in the estimation of demographic parameters obtained using different methods. On average, nestlings successfully left their nests in 87.6% of breeding attempts. The percentage of immigrants, residents, and autochthons in the static age distribution of females amounted to 41.7, 25.3, and 33.0%, respectively, vs 30.8, 25.3, and 43.9% in males, The maximum age for female autochthons was 7 years, compared to 8 years for male autochthons. Male residents lived to be x + 5 years old, while female residents lived to be x + 7 years old. Autochthonous males and females showed about the same local survival rates. These were the highest in yearlings (0.54) and gradually decreased with the age of individuals. The local survival rate of males of unknown origins is comparable to that of autochthonous males. Females of unknown origins had the lowest local survival rates. Birds could start nesting as young as one year old and as old as six years. Ringing revealed that 68.9% of males started breeding in their first year of life, compared to 59.9% of females that started in their first year. Only 39.2% of females and 46.3% of males among the birds that survived and returned to our control sites started breeding as yearlings, vs 66.9% of two-year-old females and 71.1% of males. The proportion of the birds that returned to their birth place amounted to 11.1%. Females produced 9.1 fledglings on average per lifetime, vs 9.6 fledglings for males. The minimum life expectancy for fledglings was 1.2–1.49 and 1.2–1.62 years, vs the maximum life expectancy for individuals that survived for one year, which was 1.94 and 1.96 years for males and females, respectively. For males and females, the generation time was 3.13–3.32 and 3.18–3.39 years, respectively. The sensitivity and elasticity analysis of the population growth rate based on the constructed projection matrix revealed that it was the survival rate of juvenile and sexually mature individuals between one and two years of age that primarily drove the population growth rate. Using the demographic data obtained for the species’ population in natural habitats in the Southeast of western Siberia and the population matrix model constructed on its basis, we believe it is possible to compare the state of populations inhabiting ecosystems, both unspoiled and disturbed (transformed), in various areas across the distribution range of the European pied flycatcher.

Integrating Pool-seq uncertainties into demographic inference.

Next-generation sequencing of pooled samples (Pool-seq) is a popular method to assess genome-wide diversity patterns in natural and experimental populations. However, Pool-seq is associated with specific sources of noise, such as unequal individual contributions. Consequently, using Pool-seq for the reconstruction of evolutionary history has remained underexplored. Here we describe a novel Approximate Bayesian Computation (ABC) method to infer demographic history, explicitly modelling Pool-seq sources of error. By jointly modelling Pool-seq data, demographic history and the effects of selection due to barrier loci, we obtain estimates of demographic history parameters accounting for technical errors associated with Pool-seq. Our ABC approach is computationally efficient as it relies on simulating subsets of loci (rather than the whole-genome) and on using relative summary statistics and relative model parameters. Our simulation study results indicate Pool-seq data allows distinction between general scenarios of ecotype formation (single versus parallel origin) and to infer relevant demographic parameters (e.g. effective sizes and split times). We exemplify the application of our method to Pool-seq data from the rocky-shore gastropod Littorina saxatilis, sampled on a narrow geographical scale at two Swedish locations where two ecotypes (Wave and Crab) are found. Our model choice and parameter estimates show that ecotypes formed before colonization of the two locations (i.e. single origin) and are maintained despite gene flow. These results indicate that demographic modelling and inference can be successful based on pool-sequencing using ABC, contributing to the development of suitable null models that allow for a better understanding of the genetic basis of divergent adaptation.

Understanding population change: the value of the EuroCES constant-effort ringing programme

ABSTRACT Populations of many common bird species are declining in Europe and effective conservation measures require an understanding of both the environmental and demographic causes of these changes. Capture–mark–recapture analysis of data from standardised ringing sites allows estimation of key demographic parameters, including productivity, survival and population age structure. Volunteers in countries across Europe undertake standardised mist-netting of passerines during the breeding season, from which estimates of these can be derived at large, national spatial scales. The Euring EuroCES programme collates these data in a common format to facilitate the continent-wide analysis of bird population dynamics. Here, I outline the broad characteristics of Constant Effort Site (CES) ringing, and introduce an R package cesr that provides tools to read in and manipulate these data and to produce annual indices of abundance, productivity and survival, for monitoring purposes. These data have been used to identify how climatic and environmental change can affect bird populations, particularly of migratory species, at national and continental scales. I then provide some suggestions for how the programme might further be expanded and integrated with other data sets to provide evidence for the drivers of bird population change and hence benefit informed conservation management.

A hierarchical modelling framework for estimating individual‐ and population‐level reproductive success from movement data

Abstract Rapidly advancing animal telemetry technologies paired with new statistical models can provide insight into the behaviour of otherwise unobservable free‐living animals. Changes in behaviour apparent from pairing telemetry with statistical models often occur as animals undertake key life‐history activities, such as reproduction. For many species that are secretive or occupy remote areas, these life‐history events are difficult to detect with conventional survey techniques, and consequently, vital rates are difficult to estimate. We present a hierarchical modelling framework, which integrates movement data observed via animal‐borne telemetry and optional, infrequent survey data, to estimate individual‐ and population‐level reproductive success. The approach combines a mechanistic movement model and survival model, and allows for assessing the effects of hypothesized individual and environmental covariates on reproductive success. We first tested our approach with simulated data, and then applied it to movement data from migratory golden eagles (Aquila chrysaetos) breeding in southcentral Alaska across four breeding seasons. We show that results supported our biological hypotheses that changes in movement coincided with the timing of reproductive failures, and that changes in movement could be used to assess breeding success (and failure) at the individual and population levels. The analysis also provided evidence of inter‐annual variation in population‐level nest success and the timing of nesting failures. This new approach is adaptable to many species that care for young and can be tracked with telemetry devices, and can provide not only individual‐level information useful for testing ecological hypotheses, but estimates of demographic parameters that can directly inform conservation and management if tagged animals are representative of the population.

Estimation of demographic parameters of some plant species accounting for imperfect detection probabilities

AbstractDetection probability (p) in plants is imperfect in natural conditions due to several factors. This imperfect detectability is rarely accounted for in the estimation of demographic parameters, such as survival probabilities (S) or transition rates between different life states or size classes (ψ), which may result in inaccurate quantitative information about plant populations. In this study, we used previously collected data of five plant species belonging to different families with contrasting life forms and habitats (Flaveria chlorifolia,Mammillaria hernandezii,Neobuxbaumia macrocephala,Govenia lagenophora, andCastilleja tenuiflora), data simulations, multi‐state models (a demographic tool that explicitly accounts forp), and direct estimation of survival and transition rates (i.e., assuming perfect detection) to identify in which species, states, or demographic parameters the bias caused by ignoring our imperfect detectability is more severe. Detection was imperfect (p < 1) for all our study species. In general, ignoring detection probabilities yielded underestimated survival and transition rates in all five species. Biases caused by assuming perfect detection were also large and significant, mainly in inconspicuous life states and size classes, such as seedlings and dry individuals. In contrast, considering detection probabilities resulted in fewer underestimated survival and transition rates, with smaller and mostly nonsignificant biases. Intriguingly, some transitions were overestimated even when accounting for detection probabilities. Our findings highlight the importance of considering that detection of most plant species is imperfect in the field, even in species that are apparently conspicuous, to avoid incorrect inferences about plant populations.

Joint estimation of survival and dispersal effectively corrects the permanent emigration bias in mark-recapture analyses

Robust and reliable estimates of demographic parameters are essential to understand population dynamics. Natal dispersal is a common process in monitored populations and can cause underestimations of survival and dispersal due to permanent emigration. Here, we present a multistate Bayesian capture-mark-recapture approach based on a joint estimation of natal dispersal kernel and detection probabilities to address biases in survival, dispersal, and related demographic parameters when dispersal information is limited. We implement this approach to long-term data of a threatened population: the Bonelli’s eagle in Catalonia (SW Europe). To assess the method’s performance, we compare demographic estimates structured by sex, age, and breeding status in cases of limited versus large data scales, with those of classical models where dispersal and detection probabilities are estimated separately. Results show substantial corrections of demographic estimates. Natal dispersal and permanent emigration probabilities were larger in females, and consequently, female non-breeder survival showed larger differences between separate and joint estimation models. Moreover, our results suggest that estimates are sensitive to the choice of the dispersal kernel, fat-tailed kernels providing larger values in cases of data limitation. This study provides a general multistate framework to model demographic parameters while correcting permanent emigration biases caused by natal dispersal.

The Effect of Environmental Conditions on Captures, Survival and Breeding Success of a Winter-Breeding Seabird.

Few studies have explored local and global environmental effects on the demographic rates of small seabird species such as storm-petrels. We analysed ringing data (from 2011–2022) to investigate the demographic parameters of a breeding population of Band-rumped Storm-petrels Hydrobates castro, which nest on Farilhão Grande Islet, Berlengas archipelago, Portugal. We used capture-mark-recapture analyses to estimate annual capture probabilities, apparent survival and abundance. The effects of environmental and capture effort-related variables on demographic parameters were then evaluated. The mean annual survival estimate was low (0.68 ± 0.02 SE) in comparison to other storm-petrel species, but this estimate substantially increased to 0.79 ± 0.02 after removing transient individuals. During the study period we determined breeding success in 10 years. In four of these years we also monitored breeding attempts with automatic cameras (2014–2017). Breeding success was low (0.56 ± 0.12 fledglings per active nest) with some observed cases of predation by Yellow-legged Gull Larus michahellis of both adults and chicks. The size of the Band-rumped Storm-petrel population was estimated at 1511.0 ± 266.3 SE individuals in 2017 when the mist netting effort was highest. There is no evidence that this population experienced a large decrease over the last 27 years and the trend from the previous 11 years seems to indicate a fluctuation rather than a clear decrease. The North Atlantic Oscillation Index showed a positive effect on the number of captured birds, while there was a negative effect from moonlight and local winds. We conclude that mist netting is a valuable method for long-term demographic studies on ground-nesting seabirds in which nests are difficult to access, but estimates of demographic parameters are influenced by environmental and capture effort-related variables.

A brighter future? Stable and growing sea turtle populations in the Republic of Maldives.

The Indian Ocean represents a significant data gap in the evaluation of sea turtle population status and trends. Like many small island states, the Republic of Maldives has limited baseline data, capacity and resources to gather information on sea turtle abundance, distribution and trends to evaluate their conservation status. We applied a Robust Design methodology to convert opportunistic photographic identification records into estimates of abundance and key demographic parameters for hawksbill sea turtles (Eretmochelys imbricata) and green sea turtles (Chelonia mydas) in the Republic of Maldives. Photographs were collected ad hoc by marine biologists and citizen scientists around the country from May 2016 to November 2019. Across 10 sites in four atolls, we identified 325 unique hawksbill turtles and 291 unique green turtles-where most were juveniles. Our analyses suggest that, even when controlling for survey effort and detectability dynamics, the populations of both species are stable and/or increasing in the short term at many reefs in the Maldives and the country appears to provide excellent habitat for recruiting juvenile turtles of both species. Our results represent one of the first empirical estimations of sea turtle population trends that account for detectability. This approach provides a cost-effective way for small island states in the Global South to evaluate threats to wildlife while accounting for biases inherent in community science data.

Population dynamics and harvest management of eastern mallards

AbstractManaging sustainable harvest of wildlife populations requires regular collection of demographic data and robust estimates of demographic parameters. Estimates can then be used to develop a harvest strategy to guide decision‐making. Mallards (Anas platyrhynchos) are an important species in the Atlantic Flyway for many users and they exhibited exponential growth in the eastern United States between the 1970s and 1990s. Since then, estimates of mallard abundance have declined 16%, prompting the Atlantic Flyway Council and United States Fish and Wildlife Service to implement more restrictive hunting regulations and develop a new harvest strategy predicated on an updated population model. Our primary objective was to develop an integrated population model (IPM) for use in an eastern mallard harvest management strategy. We developed an IPM using annual estimates of breeding abundance, 2‐season banding and recovery data, and hunter‐harvest data from 1998 to 2018. When developing the model, we used novel model selection methods to test various forms of a sub‐model for survival including estimating the degree of harvest additivity and any age‐specific trends. The top survival sub‐model included a negative annual trend on juvenile survival. The IPM posterior estimates for population abundance tracked closely with the observed estimates and estimates of mean annual population growth rate ranged from 0.88 to 1.08. Our population model provided increased precision in abundance estimates compared to survey methods for use in an updated harvest strategy. The IPM posterior estimates of survival rates were relatively stable for adult cohorts, and annual growth rate was positively correlated with the female age ratio, a measure of reproduction. Either or both of those demographic parameters, juvenile survival or reproduction, could be a target for management efforts to address the population decline. The resulting demographic parameters provided information on the equilibrium population size and can be used in an adaptive harvest strategy for mallards in eastern North America.

Age and sex ratios of wintering Long-tailed Ducks Clangula hyemalis can be determined by analysis of photos of flying flocks at sea: A method description

The West Siberian/North European population of Long-tailed Duck Clangula hyemalis that breeds in Fennoscandia and Northwestern Russia, and winters in the Baltic Sea, has declined by at least 65% since the 1990s and is classified as globally vulnerable. To propose effective management actions to stop the decline, knowledge about demographic parameters is required. A photo survey method by which it is possible, in winter, to collect data on sex ratios and production of first-winter birds is presented here. The plumage traits and bill patterns, which are detectable in photos taken at a distance, are described. The traits can be used to discriminate between three categories of birds: adult males, first-winter males, and females. To extrapolate results from several photo surveys and obtain population-wide estimates of demographic parameters, knowledge about non-random distributions of different bird categories is needed. It was found that different age and sex categories were distributed differently across flocks of different sizes. The required sample sizes and the possible constraints and biases related to the photo survey method are discussed.

Comparative spatially explicit approach for testing effects of soil chemicals on terrestrial wildlife bioindicator demographics

Wildlife species are often used as bioindicators to evaluate the extent and severity of environmental contamination and the effectiveness of remediation practices. A common approach for investigating population- or community-level impacts on bioindicators compares demographic parameter estimates (e.g., population size or density) between sites that were subjected to different levels of contamination. However, the traditional analytical method used in such studies is nonspatial capture-recapture, which results in conclusions about potential relationships between demographics and contaminants being inferred indirectly. Here, we extend this comparative approach to the spatially explicit framework, allowing direct estimation of said relationships and comparisons between study areas, by applying spatial capture-recapture (SCR) models to bioindicator (deer mice [Peromyscus spp.]) detection data from two study areas that were subjected to different industrial activities and remediation practices. Bioindicator density differed by 178% between the neighboring study areas, and the area with the highest soil concentrations of polychlorinated biphenyls, chromium, and zinc had the highest bioindicator density. Under the traditional nonspatial approach, we might have concluded that soil chemical levels had negligible influences on demographics. However, by modeling density as a spatial function of select chemical concentrations using SCR models, we found strong support for a positive relationship between density and soil chromium concentrations in one study area (β = 0.82), which was not masked by or associated with habitat-related metrics. To obtain reliable inferences about potential effects of environmental contamination on bioindicator demographics, we contend that a comparative spatially explicit approach using SCR ought to become standard.

Prescribed take levels of downy and hairy woodpeckers in the eastern United States

AbstractHairy (Dryobates villosus) and downy (Dryobates pubescens) woodpeckers occur in high densities in residential areas of the eastern United States. In many areas of their range, they cause damage to wooden structures through foraging, excavation of nesting cavities, and drumming behaviors, causing requests for allowable take permits. Both species hold year‐round territories, which could make them vulnerable to local extirpation with excess take. To meet the requirements of the Migratory Bird Treaty act, the United States Fish and Wildlife Service (USFWS) requested scientifically informed evaluation of take to minimize population effects as part of its approach to reduce human–wildlife conflict. We used a prescribed take approach, which uses data from population, demographic, and management parameter estimates to determine the allowable take from Louisiana to Minnesota and all states east. Furthermore, we used 2 different methods of estimating growth rates to control for demographic uncertainties. The resulting estimates provide take at the state and USFWS regional scales to improve stakeholder choices when setting allowable take. Current authorized take (2016–2018) is below the take that could be sustained by current populations, and current rates of take are not likely to cause population‐level effects. These results were largely consistent across methodologies for calculating the rate of growth for both species. Take still needs to be managed to prevent local extirpation of these resident species. Allowable take estimates should be periodically updated to reflect changing management and population needs for both species.

Assessing the value of monitoring to biological inference and expected management performance for a European goose population

Abstract Informed conservation and management of wildlife require sufficient monitoring to understand population dynamics and to direct conservation actions. Because resources available for monitoring are limited, conservation practitioners must strive to make monitoring as cost‐effective as possible. Our focus was on assessing the value of monitoring to the adaptive harvest management (AHM) programme for pink‐footed geese Anser brachyrhynchus. We conducted a retrospective analysis to assess the costs and benefits of a capture–mark–resight (CMR) programme, a productivity survey and biannual population censuses. Using all available data, we fit an integrated population model (IPM) and assumed that inference derived from it represented the benchmark against which reduced monitoring was to be judged. We then fit IPMs to reduced sets of monitoring data and compared their estimates of demographic parameters and expected management performance against the benchmark IPM. Costs and the precision and accuracy of key demographic parameters decreased with the elimination of monitoring data. Eliminating the CMR programme, while maintaining other monitoring instruments, resulted in the greatest cost savings, usually with small effects on inferential reliability. Productivity surveys were also expensive and some reduction in survey effort may be warranted. The biannual censuses were inexpensive and generally increased inferential reliability. The expected performance of AHM strategies was surprisingly robust to a loss of monitoring data. We attribute this result to explicit consideration of parametric uncertainty in harvest‐strategy optimization and the fact that a broad range of population sizes is acceptable to stakeholders. Synthesis and applications. Our study suggests that existing or potential monitoring instruments for wildlife populations should be scrutinized as to their cost‐effectiveness for improving biological inference and management performance. Using Svalbard pink‐footed geese as a case study, we show that the loss of some existing monitoring instruments may not be as adverse as commonly assumed if data are jointly analysed in an IPM. Finally, regardless of the monitoring data available, we suggest that conservation strategies that explicitly account for uncertainty in demography are more likely to be successful than those that do not.