Geology topics

G. Scott Boomer

Publications and source records attributed to G. Scott Boomer.

14 recordsLinked to original sources

USGS2025

Foundational principles of an applied cultural evolutionary science for natural resource management and conservation

Culture, as the filter through which people view the world and a key determinant of human behaviour, is central to the practice of natural resource management and conservation. Conservation is intended to moderate the impacts of human cultural modification of the environment, exists as an endeavour because it is culturally valued, and acts largely through policies to encourage or discourage targeted human behaviours. However, culture is not static; as organisms and ecologies evolve, so too does culture exist as a dynamic, interconnected, coevolving element of the social–ecological systems in which management action is situated and implemented. Cultural evolution (CE) offers a valuable theoretical contribution to the scientific understanding of culture, cultural diversity and culture change and has the potential to be harnessed in the applied research and practice of conservation social science. We illustrate the essential principles necessary to grow an applied science of CE for natural resource management and conservation, and identify opportunities for CE to provide valuable information for science-based decision making and help conservation institutions and organizations adapt to the ongoing challenges posed by culture change. This transdisciplinary integration can contribute to improved outcomes across conservation objectives and build more resilient, sustainable social–ecological systems.

Philosophical Transactions of the Royal Society B ↗

USGS2025

Integrating hunter dynamics and waterfowl dynamics to inform harvest management

The successful conservation and management of North American waterfowl relies upon an adaptive harvest management framework that accounts for changes in the system state and critical uncertainties related to the dynamics of waterfowl populations and habitats. Increasing recognition of the importance of the human dimensions of the harvest process, particularly those related to hunters, has motivated calls for the integration of social objectives into waterfowl conservation programs and decision making. We introduce a framework for modeling the dynamics of hunter populations and behavior alongside those of waterfowl populations. Using Bayesian estimation, we fit a dynamic state space model to observational data from the Mid-Continent mallard ( Anas platyrhynchos ) system over a 20-year period and estimated parameter values for the relative effects of a set of hypothesized drivers of hunter recruitment, retention, reactivation, participation, and success rates. We then made projections across 3 future scenarios to examine the continuation of current trends, the potential effects of a shift to a moderate regulatory framework as informed by expert elicitation, and increased hunter recruitment to maintain a stable hunter population. We found that a theoretical stable state exists for Mid-Continent mallard and hunter populations but that the influence of broader sociocultural shifts and increasing hunter mortality from an aging base pose significant challenges for efforts to stabilize the ongoing decline of active hunter numbers, even under favorable regulatory conditions. This modeling framework and results from it can be used to inform decision processes in the management of game populations that seek to include social objectives and assess the potential trade-offs of prioritizing across social and ecological objectives. We emphasize the need for focused human dimensions expertise throughout the process of fully integrating goals for waterfowl populations, habitats, and people in waterfowl conservation.

Journal of Wildlife Management↗

USGS2021

Decision-support framework for linking regional-scale management actions to continental-scale conservation of wide-ranging species

Anas acuta (Northern pintail; hereafter pintail) was selected as a model species on which to base a decision-support framework linking regional actions to continental-scale population and harvest objectives. This framework was then used to engage stakeholders, such as Landscape Conservation Cooperatives’ (LCCs’) habitat management partners within areas of importance to pintails, while maximizing cross-taxa effects from the framework. The mathematical framework for the model had been previously developed for pintails. A key assumption incorporated into the model is that density dependence in survival occurs during the post-hunting (winter) period, where resources are hypothesized to be limiting. Because few data are available to directly inform this process, the approach used was to build a hierarchical Bayesian integrated population model (IPM) that simultaneously uses data from bird-band recoveries, breeding population counts, and harvest surveys to estimate values of parameters of an annual population projection model, including population size, survival rate, reproductive rate, and process and observation error variances, that are logically consistent with each other, given the mathematical structure imposed through the IPM. The main accomplishments of this study are (1) development of an IPM for pintail to guide harvest and habitat management, (2) development of a Prairie Parkland Region breeding submodel to predict pintail productivity, (3) development of statistical methodology to estimate pintail productivity (as measured by the ratio of juvenile to adults in hunter-collected wing samples) and winter survival and to relate these estimates to covariates, and (4) illustration of how to use a model and estimated parameter values to predict pintail population size and sustainable harvest as a function of habitat. Estimation of pintail survival from bird-banding data shows that there has been relatively little variation in survival over the period 1960–2013. A productivity model showed strong effects of breeding ground conditions, wintering-ground precipitation, and density dependence on pintail productivity. Thus, most temporal variation in pintail demographic rates has been due to effects on reproduction and not survival, including effects of breeding or wintering-ground habitat. These results indicate that habitat conservation efforts may be most effective if they focus on maintaining or increasing breeding and wintering-ground habitat to increase pintail productivity rather than pintail survival. Environmental perturbations in excess of historical experience, such as what could occur under climate change, might have meaningful effects on survival but cannot be estimated with current data. Direct effects of climate, land use, or management are likely to be greater on productivity than survival, but substantial uncertainty remains about predictions of equilibrium population size and sustainable yield.

Open-File Report↗

USGS2021

Evaluation of a two-season banding program to estimate and model migratory bird survival

The management of North American waterfowl is predicated on long-term, continental scale banding implemented prior to the hunting season (i.e., July–September) and subsequent reporting of bands recovered by hunters. However, single-season banding and encounter operations have a number of characteristics that limit their application to estimating demographic rates and evaluating hypothesized limiting factors throughout the annual cycle. We designed and implemented a 2-season banding program for American black ducks ( Anas rubripes ), mallards ( A . platyrhynchos ), and hybrids in eastern North America to evaluate potential application to annual life cycle conservation and sport harvest management. We assessed model fit and compared estimates of annual survival among data types (i.e., pre-hunting season only [July–September], post-hunting season only [January–March], and 2-season [pre- and post-hunting season]) to evaluate model assumptions and potential application to population modeling and management. There was generally high agreement between estimates of annual survival derived using 2-season and pre-season only data for all age and sex cohorts. Estimates of annual survival derived from post-season banding data only were consistently higher for adult females and juveniles of both sexes. We found patterns of seasonal survival varied by species, age, and to a lesser extent, sex. Hunter recovered birds exhibited similar spatial distributions regardless of banding season suggesting banded samples were from the same population. In contrast, Goodness-Of-Fit tests suggest this assumption was statistically violated in some regions and years. We conclude that estimates of seasonal and annual survival for black ducks and mallards based on the 2-season banding program are valid and accurate based on model fit statistics, similarity in survival estimates across data and models, and similarities in the distribution of recoveries. The 2-season program provides greater precision and insight into the survival process and will improve the ability of researchers and managers to test competing hypotheses regarding population regulation resulting in more effective management.

Ecological Applications↗

USGS2021

Opinion: A preferred approach for dealing with reproducibility and replicability in science

Science impacts our daily lives and guides national and international policies (1). Thus, results of scientific studies are of paramount importance; yet, there are concerns that many studies are not reproducible or replicable (2). To address these concerns, the National Research Council conducted a Consensus Study [NASEM 2019 (3)] that provides definitions of key concepts, discussions of problems, and recommendations for dealing with these problems. These recommendations are useful and well considered, but they do not go far enough in our opinion. The NASEM recommendations treat reproducibility and replicability as single-study issues, despite clear acknowledgement of the limitations of isolated studies and the need for research synthesis (3). We advocate a strategic approach to research, focusing on the accumulation of evidence via designed sequences of studies, as a means of dealing more effectively with reproducibility, replicability, and related problems. These sequences are designed to provide iterative tests based on comparison of data from empirical studies with predictions from competing hypotheses. Evidence is then formally accumulated based on the relative predictive abilities of the different hypotheses as the sequential studies proceed.

Proceedings of the National Academy of Sciences of↗

USGS2018

The non-linear, interactive effects of population density and climate drive the geographical patterns of waterfowl survival

On-going climate change has major impacts on ecological processes and patterns. Understanding the impacts of climate on the geographical patterns of survival can provide insights to how population dynamics r espond to climate change and provide important information for the development of appropriate conservation strategies at regional scales. It is challenging to understand the impacts of climate on survival, however, due to the fact that the non-linear relationship between survival and climate can be modified by density-dependent processes. In this study we extended the Brownie model to partition hunting and non-hunting mortalities and linked non-hunting survival to covariates. We applied this model to four decades (1972–2014) of waterfowl band-recovery, breeding population s urvey, and precipitation and temperature data covering multiple ecological regions to examine the non-linear, interactive effects of population density and climate on waterfowl non-hunting survival at a regional scale. Our results showed that the non-linear effect of temperature on waterfowl non-hunting survival was modified by breeding population density. The concave relationship between non-hunting survival and temperature suggested that the effects of warming on waterfowl survival might be multifaceted. Furthermore, the relationship between non-hunting survival and temperature was stronger when population density was higher, suggesting that high-density populations may be less buffered against warming than low-density populations. Our study revealed distinct relationships between waterfowl non-hunting survival and climate across and within ecological regions, highlighting the importance of considering different conservation strategies according to region-specific population and climate conditions. Our findings and associated novel modelling approach have wide implications in conservation practice.

Biological Conservation↗

USGS2018

Science alive and well in North American wildlife management

Artelle et al. (1) entitled a recent article with the provocative claim: “Hallmarks of science missing from North American wildlife management”. Although we agree with some of the concerns and recommendations of Artelle et al. (1), we believe that the article is misleading about the distinction between science and management, the role of science in wise management, and the degree to which science is used in North American wildlife management. Here we distinguish between science and management, specify an appropriate role of science in management, and document the explicit use of science in at least some programs of North American wildlife management.

Science Advances↗

USGS2017

Spatially explicit dynamic N-mixture models

Knowledge of demographic parameters such as survival, reproduction, emigration, and immigration is essential to understand metapopulation dynamics. Traditionally the estimation of these demographic parameters requires intensive data from marked animals. The development of dynamic N-mixture models makes it possible to estimate demographic parameters from count data of unmarked animals, but the original dynamic N-mixture model does not distinguish emigration and immigration from survival and reproduction, limiting its ability to explain important metapopulation processes such as movement among local populations. In this study we developed a spatially explicit dynamic N-mixture model that estimates survival, reproduction, emigration, local population size, and detection probability from count data under the assumption that movement only occurs among adjacent habitat patches. Simulation studies showed that the inference of our model depends on detection probability, local population size, and the implementation of robust sampling design. Our model provides reliable estimates of survival, reproduction, and emigration when detection probability is high, regardless of local population size or the type of sampling design. When detection probability is low, however, our model only provides reliable estimates of survival, reproduction, and emigration when local population size is moderate to high and robust sampling design is used. A sensitivity analysis showed that our model is robust against the violation of the assumption that movement only occurs among adjacent habitat patches, suggesting wide applications of this model. Our model can be used to improve our understanding of metapopulation dynamics based on count data that are relatively easy to collect in many systems.

Population Ecology↗

USGS2017

A comment on “temporal variation in survival and recovery rates of lesser scaup”

Concerns about declines in the abundance of lesser scaup ( Aythya affinis ) have promoted a number of analyses to understand reasons for this decline. Unfortunately, most of these analyses, including that of Arnold et al. (2016 Journal of Wildlife Management 80: 850–861), are based on observational studies leading to weak inference. Although we commend the efforts of Arnold et al. (2016 Journal of Wildlife Management 80: 850–861), we think their conclusions are over-stated given their retrospective analysis. Further, we note a number of inconsistencies in their reasoning and offer alternative conclusions that can be drawn from their analysis. Given the uncertainty still surrounding management of lesser scaup, we do not believe it is prudent to abandon or greatly modify adaptive management approaches designed specifically to make optimal decisions in the face of uncertainty. The current learning-based and recursive approach to management appears to be providing adequate guidance for harvest without punctuated changes to harvest levels, as Arnold et al. (2016 Journal of Wildlife Management 80: 850–861) recommend.

Journal of Wildlife Management↗

USGS2017

Integrating Breeding Bird Survey and demographic data to estimate Wood Duck population size in the Atlantic Flyway

The U.S. Fish and Wildlife Service (USFWS) uses data from the North American Breeding Bird Survey (BBS) to assist in monitoring and management of some migratory birds. However, BBS analyses provide indices of population change rather than estimates of population size, precluding their use in developing abundance-based objectives and limiting applicability to harvest management. Wood Ducks ( Aix sponsa ) are important harvested birds in the Atlantic Flyway (AF) that are difficult to detect during aerial surveys because they prefer forested habitat. We integrated Wood Duck count data from a ground-plot survey in the northeastern U.S. with AF-wide BBS, banding, parts collection, and harvest data to derive estimates of population size for the AF. Overlapping results between the smaller-scale intensive ground-plot survey and the BBS in the northeastern U.S. provided a means for scaling BBS indices to the breeding population size estimates. We applied these scaling factors to BBS results for portions of the AF lacking intensive surveys. Banding data provided estimates of annual survival and harvest rates; the latter, when combined with parts-collection data, provided estimates of recruitment. We used the harvest data to estimate fall population size. Our estimates of breeding population size and variability from the integrated population model (N̄ = 0.99 million, SD = 0.04) were similar to estimates of breeding population size based solely on data from the AF ground-plot surveys and the BBS (N̄ = 1.01 million, SD = 0.04) from 1998 to 2015. Integrating BBS data with other data provided reliable population size estimates for Wood Ducks at a scale useful for harvest and habitat management in the AF, and allowed us to derive estimates of important demographic parameters (e.g., seasonal survival rates, sex ratio) that were not directly informed by data.

The Condor↗

USGS2015

On formally integrating science and policy: walking the walk

The contribution of science to the development and implementation of policy is typically neither direct nor transparent. In 1995, the U.S. Fish and Wildlife Service (FWS) made a decision that was unprecedented in natural resource management, turning to an unused and unproven decision process to carry out trust responsibilities mandated by an international treaty. The decision process was adopted for the establishment of annual sport hunting regulations for the most economically important duck population in North America, the 6 to 11 million mallards Anas platyrhynchos breeding in the mid-continent region of north-central United States and central Canada. The key idea underlying the adopted decision process was to formally embed within it a scientific process designed to reduce uncertainty (learn) and thus make better decisions in the future. The scientific process entails use of models to develop predictions of competing hypotheses about system response to the selected action at each decision point. These prediction not only are used to select the optimal management action, but also are compared with the subsequent estimates of system state variables, providing evidence for modifying degrees of confidence in, and hence relative influence of, these models at the next decision point. Science and learning in one step are formally and directly incorporated into the next decision, contrasting with the usual ad hoc and indirect use of scientific results in policy development and decision-making. Application of this approach over the last 20 years has led to a substantial reduction in uncertainty, as well as to an increase in transparency and defensibility of annual decisions and a decrease in the contentiousness of the decision process. As resource managers are faced with increased uncertainty associated with various components of global change, this approach provides a roadmap for the future scientific management of natural resources.

Journal of Applied Ecology↗

USGS2015

Multilevel learning in the adaptive management of waterfowl harvests: 20 years and counting

In 1995, the U.S. Fish and Wildlife Service implemented an adaptive harvest management program (AHM) for the sport harvest of midcontinent mallards ( Anas platyrhynchos ). The program has been successful in reducing long-standing contentiousness in the regulatory process, while integrating science and policy in a coherent, rigorous, and transparent fashion. After 20 years, much has been learned about the relationship among waterfowl populations, their environment, and hunting regulations, with each increment of learning contributing to better management decisions. At the same time, however, much has been changing in the social, institutional, and environmental arenas that provide context for the AHM process. Declines in hunter numbers, competition from more pressing conservation issues, and global-change processes are increasingly challenging waterfowl managers to faithfully reflect the needs and desires of stakeholders, to account for an increasing number of institutional constraints, and to (probabilistically) predict the consequences of regulatory policy in a changing environment. We review the lessons learned from the AHM process so far, and describe emerging challenges and ways in which they may be addressed. We conclude that the practice of AHM has greatly increased an awareness of the roles of social values, trade-offs, and attitudes toward risk in regulatory decision-making. Nevertheless, going forward the waterfowl management community will need to focus not only on the relationships among habitat, harvest, and waterfowl populations, but on the ways in which society values waterfowl and how those values can change over time.

Wildlife Society Bulletin↗

USGS2012

Allowable levels of take for the trade in Nearctic songbirds

The take of Nearctic songbirds for the caged-bird trade is an important cultural and economic activity in Mexico, but its sustainability has been questioned. We relied on the theta-logistic population model to explore options for setting allowable levels of take for 11 species of passerines that were subject to legal take in Mexico in 2010. Because estimates of population size necessary for making periodic adjustments to levels of take are not routinely available, we examined the conditions under which a constant level of take might contribute to population depletion (i.e., a population below its level of maximum net productivity). The chance of depleting a population is highest when levels of take are based on population sizes that happen to be much lower or higher than the level of maximum net productivity, when environmental variation is relatively high and serially correlated, and when the interval between estimation of population size is relatively long (≥5 years). To estimate demographic rates of songbirds involved in the Mexican trade we relied on published information and allometric relationships to develop probability distributions for key rates, and then sampled from those distributions to characterize the uncertainty in potential levels of take. Estimates of the intrinsic rate of growth (r) were highly variable, but median estimates were consistent with those expected for relatively short-lived, highly fecund species. Allowing for the possibility of nonlinear density dependence generally resulted in allowable levels of take that were lower than would have been the case under an assumption of linearity. Levels of take authorized by the Mexican government in 2010 for the 11 species we examined were small in comparison to relatively conservative allowable levels of take (i.e., those intended to achieve 50% of maximum sustainable yield). However, the actual levels of take in Mexico are unknown and almost certainly exceed the authorized take. Also, the take of Nearctic songbirds in other Latin American and Caribbean countries ultimately must be considered in assessing population-level impacts.

Ecological Applications↗

USGS2010

Estimating migratory game-bird productivity by integrating age ratio and banding data

Context: Reproduction is a critical component of fitness, and understanding factors that influence temporal and spatial dynamics in reproductive output is important for effective management and conservation. Although several indices of reproductive output for wide-ranging species, such as migratory birds, exist, there has been no theoretical justification for their estimators or associated measures of variance. Aims: The aims of our research were to develop statistical justification for an estimator of reproduction and associated variances on the basis of an existing national wing-collection survey and banding data, and to demonstrate the applicability of this estimator to a migratory game bird. Methods: We used a Bayesian hierarchical modelling approach to integrate wing-collection data, which provides information on population age ratios, and band-recovery data, which provides information on recovery probabilities of various age classes, for American woodcock ( Scolopax minor ) to estimate productivity and associated measures of variance. We present two models of relative vulnerability between age classes: one model assumed that adult recovery probabilities were higher, but that annual fluctuations were synchronous between the two age classes (i.e. an additive effect of age and year). The second model assumed that adults, on average, had higher recovery probabilities than did juveniles and that annual fluctuations were asynchronous through time (i.e. an interaction between age and year). Key results: Fitting our models within a hierarchical Bayesian framework efficiently incorporates the two data types into a single estimator and derives appropriate variances for the productivity estimator. Further, use of Bayesian methods enabled us to derive credible intervals that avoid the reliance on asymptotic assumptions. When applied to American woodcock data, the additive model resulted in biologically realistic and more precise age-ratio estimates each year and is adequate when the relative vulnerability to sampling only slightly varies or does not vary among components of a population (e.g. age, sex class) among years. Therefore, we recommend using woodcock indices from our analysis based on this model. Conclusions: We provide a flexible modelling framework for estimating productivity and associated variances that can incorporate ecological covariates to explore various factors that could drive annual dynamics in productivity. Applying our model to the American woodcock data indicated that assumptions about the variability in relative recovery probabilities could greatly influence the precision of our productivity estimator. Therefore, researchers should carefully consider the assumption of temporally variable relative recovery probabilities (i.e. ratio of juvenile to adults' recovery probability) for different age classes when applying this estimator. Implications: Several national and international management strategies for migratory game birds in North America rely on measures of productivity from harvest survey parts collections, without a justification of the estimator or providing estimates of precision. We derive an estimator of productivity with realistic measures of uncertainty that can be directly incorporated into management plans or ecological studies across large spatial scales.

Wildlife Research↗