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At least 37 records · Page 2Linked to original sources
USGS2018

The confluences of ideas leading to, and the flow of ideas emerging from, individual-based modeling of riverine fishes

In this review article, we trace the history of events leading to the development of individual-based models (IBMs) to represent aquatic organisms in rivers and streams. As a metaphor, we present this history as a series of confluences between individual scientists (tributaries) sharing ideas. We describe contributions of these models to science and management. One iconic feature of river IBMs is the linkage between flow and the physical habitat experienced by individual animals, and the first model that focused on this linkage is briefly described. We continue by reviewing the contributions of riverine IBMs to eight broad areas of scientific inquiry. The first four areas include research to understand 1) the effects of flow regimes on fish populations, 2) species interactions (e.g., size-mediated competition and predation), 3) fish movement and habitat selection, and 4) contaminant and water quality impacts on populations. Next, we review research using IBMs 5) to guide conservation biology of imperiled taxa through population viability analysis, including research 6) to understand river fragmentation by dams and reconnection, 7) to understand genetic outcomes for riverine metapopulations, and 8) to anticipate the future effects of temperature and climate change. This rich body of literature has contributed to both theoretical insights (e.g., about animal behavior and life history) and applied insights (e.g., population-level effects of flow regimes, temperature, and the effects of hydropower and other industries that share rivers with aquatic biota). We finish by exploring promising branches that lie ahead in the braided, downstream channel that represents future river modeling research.

Ecological Modelling↗
USGS2002

Analysis and Management of Animal Populations: Modeling, Estimation and Decision Making

This book deals with the processes involved in making informed decisions about the management of animal populations. It covers the modeling of population responses to management actions, the estimation of quantities needed in the modeling effort, and the application of these estimates and models to the development of sound management decisions. The book synthesizes and integrates in a single volume the methods associated with these themes, as they apply to ecological assessment and conservation of animal populations. KEY FEATURES * Integrates population modeling, parameter estimation and * decision-theoretic approaches to management in a single, cohesive framework * Provides authoritative, state-of-the-art descriptions of quantitative * approaches to modeling, estimation and decision-making * Emphasizes the role of mathematical modeling in the conduct of science * and management * Utilizes a unifying biological context, consistent mathematical notation, * and numerous biological examples

Book↗
USGS1987

Distribution and effects of acidic deposition on wildlife and ecosystems

Acidic deposition occurs over most of the United States and the deposition patterns and theoretical vulnerabilities of aquatic ecosystems to chemical changes can be delineated, but few data exist on concomitant biological effects. Hypothetical direct effects are limited primarily to toxicity of various heavy metals mobilized at reduced pH. Results of studies in Scandinavia suggest that aluminum interferes with avian reproduction near acidified lakes. Some amphibian populations located on acid-vulnerable substrates may be adversely affected by reduced pH in the vernal pools used for egg laying and larval growth. Indirect effects on populations are difficult to detect because few historical data exist for wildlife populations and trophic relationships in vulnerable areas. Current research in the U.S.A. focuses on measuring habitat characteristics, food availability, and avian use of vulnerable wetland habitats. Results of Scandinavian studies suggest that some species of waterfowl may prefer acidified, I fish-free habitats because invertebrates essential for meeting nutritional requirements are more easily obtained in the absence of competition from fish. However, avian species dependent on fish would be absent from these habitats. Alteration of either the vegetative structure or primary productivity of wetlands might indirectly affect avian populations by causing decreased invertebrate productivity and consequent food limitations for birds.

Book chapter↗
USGS2010

Fort Collins Science Center- Policy Analysis and Science Assistance Branch : Integrating social, behavioral, economic and biological sciences

The Fort Collins Science Center's Policy Analysis and Science Assistance (PASA) Branch is a team of approximately 22 scientists, technicians, and graduate student researchers. PASA provides unique capabilities in the U.S. Geological Survey by leading projects that integrate social, behavioral, economic, and biological analyses in the context of human-natural resource interactions. Resource planners, managers, and policymakers in the U.S. Departments of the Interior (DOI) and Agriculture (USDA), State and local agencies, as well as international agencies use information from PASA studies to make informed natural resource management and policy decisions. PASA scientists' primary functions are to conduct both theoretical and applied social science research, provide technical assistance, and offer training to advance performance in policy relevant research areas. Management and research issues associated with human-resource interactions typically occur in a unique context, involve difficult to access populations, require knowledge of both natural/biological science in addition to social science, and require the skill to integrate multiple science disciplines. In response to these difficult contexts, PASA researchers apply traditional and state-of-the-art social science methods drawing from the fields of sociology, demography, economics, political science, communications, social-psychology, and applied industrial organization psychology. Social science methods work in concert with our rangeland/agricultural management, wildlife, ecology, and biology capabilities. The goal of PASA's research is to enhance natural resource management, agency functions, policies, and decision-making. Our research is organized into four broad areas of study.

Fact Sheet↗
USGS2014

Estimating habitat carrying capacity for migrating and wintering waterfowl: Considerations, pitfalls and improvements

Population-based habitat conservation planning for migrating and wintering waterfowl in North America is carried out by habitat Joint Venture (JV) initiatives and is based on the premise that food can limit demography (i.e. food limitation hypothesis). Consequently, planners use bioenergetic models to estimate food (energy) availability and population-level energy demands at appropriate spatial and temporal scales, and translate these values into regional habitat objectives. While simple in principle, there are both empirical and theoretical challenges associated with calculating energy supply and demand including: 1) estimating food availability, 2) estimating the energy content of specific foods, 3) extrapolating site-specific estimates of food availability to landscapes for focal species, 4) applicability of estimates from a single species to other species, 5) estimating resting metabolic rate, 6) estimating cost of daily behaviours, and 7) estimating costs of thermoregulation or tissue synthesis. Most models being used are daily ration models (DRMs) whose set of simplifying assumptions are well established and whose use is widely accepted and feasible given the empirical data available to populate such models. However, DRMs do not link habitat objectives to metrics of ultimate ecological importance such as individual body condition or survival, and largely only consider food-producing habitats. Agent-based models (ABMs) provide a possible alternative for creating more biologically realistic models under some conditions; however, ABMs require different types of empirical inputs, many of which have yet to be estimated for key North American waterfowl. Decisions about how JVs can best proceed with habitat conservation would benefit from the use of sensitivity analyses that could identify the empirical and theoretical uncertainties that have the greatest influence on efforts to estimate habitat carrying capacity. Development of ABMs at restricted, yet biologically relevant spatial scales, followed by comparisons of their outputs to those generated from more simplistic, deterministic models can provide a means of assessing degrees of dissimilarity in how alternative models describe desired landscape conditions for migrating and wintering waterfowl.

Wildfowl↗
USGS2017

A discrete stage-structured model of California newt population dynamics during a period of drought

We introduce a mathematical model for studying the population dynamics under drought of the California newt ( Taricha torosa ), a species of special concern in the state of California. Since 2012, California has experienced a record-setting drought, and multiple studies predict drought conditions currently underway will persist and even increase in severity. Recent declines and local extinctions of California newt populations in Santa Monica Mountain streams motivate our study of the impact of drought on newt population sizes. Although newts are terrestrial salamanders, they migrate to streams each spring to breed and lay eggs. Since egg and larval stages occur in water, a precipitation deficit due to drought conditions reduces the space for newt egg-laying and the necessary habitat for larval development. To mathematically forecast newt population dynamics, we develop a nonlinear system of discrete equations that includes demographic parameters such as survival rates for newt life stages and egg production, which depend on habitat availability and rainfall. We estimate these demographic parameters using 15 years of stream survey data collected from Cold Creek in Los Angeles County, California, and our model captures the observed decline of the parameterized Cold Creek newt population. Based upon data analysis, we predict how the number of available newt egg-laying sites varies with annual precipitation. Our model allows us to make predictions about how the length and severity of drought can affect the likelihood of persistence and the time to critical endangerment of a local newt population. We predict that sustained severe drought will critically endanger the newt population but that the newt population can rebound if a drought is sufficiently short.

Journal of Theoretical Biology↗
USGS2014

The influence of interspecific interactions on species range expansion rates

Ongoing and predicted global change makes understanding and predicting species’ range shifts an urgent scientific priority. Here, we provide a synthetic perspective on the so far poorly understood effects of interspecific interactions on range expansion rates. We present theoretical foundations for how interspecific interactions may modulate range expansion rates, consider examples from empirical studies of biological invasions and natural range expansions as well as process-based simulations, and discuss how interspecific interactions can be more broadly represented in process-based, spatiotemporally explicit range forecasts. Theory tells us that interspecific interactions affect expansion rates via alteration of local population growth rates and spatial displacement rates, but also via effects on other demographic parameters. The best empirical evidence for interspecific effects on expansion rates comes from studies of biological invasions. Notably, invasion studies indicate that competitive dominance and release from specialized enemies can enhance expansion rates. Studies of natural range expansions especially point to the potential for competition from resident species to reduce expansion rates. Overall, it is clear that interspecific interactions may have important consequences for range dynamics, but also that their effects have received too little attention to robustly generalize on their importance. We then discuss how interspecific interactions effects can be more widely incorporated in dynamic modeling of range expansions. Importantly, models must describe spatiotemporal variation in both local population dynamics and dispersal. Finally, we derive the following guidelines for when it is particularly important to explicitly represent interspecific interactions in dynamic range expansion forecasts: if most interacting species show correlated spatial or temporal trends in their effects on the target species, if the number of interacting species is low, and if the abundance of one or more strongly interacting species is not closely linked to the abundance of the target species.

Ecography↗
USGS2019

Testing theoretical metapopulation conditions with genotypic data from Boreal Chorus Frogs (Pseudacris maculata)

The metapopulation concept has far-reaching implications in ecology and conservation biology. Hanski’s criteria operationally define metapopulations, yet testing them is hindered by logistical and financial constraints inherent to the collection of long-term demographic data. Hence, ecologists and conservationists often assume metapopulation existence for dispersal-limited species that occupy patchy habitats. To advance understanding of metapopulation theory and improve conservation of metapopulations, we used population and landscape genetic tools to develop a methodological framework for evaluating Hanski’s criteria. We used genotypic data (11 microsatellite loci) from a purported metapopulation of Boreal Chorus Frogs ( Pseudacris maculata (Agassiz, 1850)) in Colorado, U.S.A., to test Hanski’s four criteria. We found support for each criterion: (1) significant genetic differentiation between wetlands, suggesting distinct breeding populations; (2) wetlands had small effective population sizes and recent bottlenecks, suggesting populations do not experience long-term persistence; (3) population graphs provided evidence of gene flow between patches, indicating potential for recolonization; and (4) multiscale bottleneck analyses suggest asynchrony, indicating that simultaneous extinction of all populations was unlikely. Our methodological framework provides a logistically and financially feasible alternative to long-term demographic data for identifying amphibian metapopulations.

Colorado↗
USGS2002

Bet-hedging applications for conservation

One of the early tenets of conservation biology is that population viability is enhanced by maintaining multiple populations of a species. The strength of this tenet is justified by principles of bet-hedging. Management strategies that reduce variance in population size will also reduce risk of extinction. Asynchrony in population fluctuations in independent populations reduces variance in the aggregate of populations whereas environmental correlation among areas increases the risk that all populations will go extinct. We review the theoretical rationale of bet-hedging and suggest applications for conservation management of least terns in Nebraska and grizzly bears in the northern Rocky Mountains of the United States. The risk of extinction for least terns will be reduced if we can sustain the small central Platte River population in addition to the larger population on the lower Platte. Similarly, by restoring grizzly bears to the Bitterroot wilderness of Idaho and Montana can reduce the probability of extinction for grizzly bears in the Rocky Mountains of the United States by as much as 69-93%.

Journal of Biosciences↗
USGS2006

Remote monitoring of fish in small streams: A unified approach using PIT tags

Accurate assessments of fish populations are often limited by re-observation or recapture events. Since the early 1990s, passive integrated transponders (PIT tags) have been used to understand the biology of many fish species. Until recently, PIT applications in small streams have been limited to physical recapture events. To maximize recapture probability, we constructed PIT antenna arrays in small streams to remotely detect individual fish. Experiences from two different laboratories (three case studies) allowed us to develop a unified approach to applying PIT technology for enhancing data assessments. Information on equipment, its installation, tag considerations, and array construction is provided. Theoretical and practical definitions are introduced to standardize metrics for assessing detection efficiency. We demonstrate how certain conditions (stream discharge, vibration, and ambient radio frequency noise) affect the detection efficiency and suggest that by monitoring these conditions, expectations of efficiency can be modified. We emphasize the importance of consistently estimating detection efficiency for fisheries applications.

Fisheries↗
USGS2014

When to be discrete: The importance of time formulation in understanding animal movement

Animal movement is essential to our understanding of population dynamics, animal behavior, and the impacts of global change. Coupled with high-resolution biotelemetry data, exciting new inferences about animal movement have been facilitated by various specifications of contemporary models. These approaches differ, but most share common themes. One key distinction is whether the underlying movement process is conceptualized in discrete or continuous time. This is perhaps the greatest source of confusion among practitioners, both in terms of implementation and biological interpretation. In general, animal movement occurs in continuous time but we observe it at fixed discrete-time intervals. Thus, continuous time is conceptually and theoretically appealing, but in practice it is perhaps more intuitive to interpret movement in discrete intervals. With an emphasis on state-space models, we explore the differences and similarities between continuous and discrete versions of mechanistic movement models, establish some common terminology, and indicate under which circumstances one form might be preferred over another. Counter to the overly simplistic view that discrete- and continuous-time conceptualizations are merely different means to the same end, we present novel mathematical results revealing hitherto unappreciated consequences of model formulation on inferences about animal movement. Notably, the speed and direction of movement are intrinsically linked in current continuous-time random walk formulations, and this can have important implications when interpreting animal behavior. We illustrate these concepts in the context of state-space models with multiple movement behavior states using northern fur seal ( Callorhinus ursinus ) biotelemetry data.

Movement Ecology↗
USGS2015

Fecal indicator organism modeling and microbial source tracking in environmental waters: Chapter 3.4.6

Mathematical models have been widely applied to surface waters to estimate rates of settling, resuspension, flow, dispersion, and advection in order to calculate movement of particles that influence water quality. Of particular interest are the movement, survival, and persistence of microbial pathogens or their surrogates, which may contaminate recreational water, drinking water, or shellfish. Most models devoted to microbial water quality have been focused on fecal indicator organisms (FIO), which act as a surrogate for pathogens and viruses. Process-based modeling and statistical modeling have been used to track contamination events to source and to predict future events. The use of these two types of models require different levels of expertise and input; process-based models rely on theoretical physical constructs to explain present conditions and biological distribution while data-based, statistical models use extant paired data to do the same. The selection of the appropriate model and interpretation of results is critical to proper use of these tools in microbial source tracking. Integration of the modeling approaches could provide insight for tracking and predicting contamination events in real time. A review of modeling efforts reveals that process-based modeling has great promise for microbial source tracking efforts; further, combining the understanding of physical processes influencing FIO contamination developed with process-based models and molecular characterization of the population by gene-based (i.e., biological) or chemical markers may be an effective approach for locating sources and remediating contamination in order to protect human health better.

Book chapter↗
USGS2007

Chinook salmon use of spawning patches: Relative roles of habitat quality, size, and connectivity

Declines in many native fish populations have led to reassessments of management goals and shifted priorities from consumptive uses to species preservation. As management has shifted, relevant environmental characteristics have evolved from traditional metrics that described local habitat quality to characterizations of habitat size and connectivity. Despite the implications this shift has for how habitats may be prioritized for conservation, it has been rare to assess the relative importance of these habitat components. We used an information-theoretic approach to select the best models from sets of logistic regressions that linked habitat quality, size, and connectivity to the occurrence of chinook salmon (Oncorhynchus tshawytscha) nests. Spawning distributions were censused annually from 1995 to 2004, and data were complemented with field measurements that described habitat quality in 43 suitable spawning patches across a stream network that drained 1150 km 2 in central Idaho. Results indicated that the most plausible models were dominated by measures of habitat size and connectivity, whereas habitat quality was of minor importance. Connectivity was the strongest predictor of nest occurrence, but connectivity interacted with habitat size, which became relatively more important when populations were reduced. Comparison of observed nest distributions to null model predictions confirmed that the habitat size association was driven by a biological mechanism when populations were small, but this association may have been an area-related sampling artifact at higher abundances. The implications for habitat management are that the size and connectivity of existing habitat networks should be maintained whenever possible. In situations where habitat restoration is occurring, expansion of existing areas or creation of new habitats in key areas that increase connectivity may be beneficial. Information about habitat size and connectivity also could be used to strategically prioritize areas for improvement of local habitat quality, with areas not meeting minimum thresholds being deemed inappropriate for pursuit of restoration activities. ?? 2007 by the Ecological Society of America.

Ecological Applications↗
USGS2021

Refining the coarse filter approach: Using habitat-based species models to identify rarity and vulnerabilities in the protection of U.S. biodiversity

Preserving biodiversity and its many components is a priority of conservation science and how to efficiently allocate resources to preserve healthy populations of as many species, habitats, and ecosystems as possible. We used the U.S. Geological Survey (USGS) Gap Analysis Project (GAP) species models released in 2018, which identify predicted habitats for terrestrial vertebrates in the conterminous United States, to illustrate hotspots of biodiversity for the major taxonomic groups. This collection represents the first complete compilation of terrestrial vertebrate species models for the conterminous United States (U.S. Geological Survey (USGS), 2018a). We used the species models but not the available subspecies models; this resulted in the inclusion of 282 amphibian models, 621 bird models, 365 mammal models, and 322 reptiles in our analysis. We also used population trend information and made spatial queries to characterize species in three dimensions: geographic range (small or large), habitat breadth (narrow or wide), and population trend (decreasing vs stable or increasing). This characterization allowed us to divide the species into eight groups (A-H) with similar characteristics. Group A species (large geographic range, wide habitat breadth, and stable or increasing population trend) are species that are common now with no indication of becoming rare. Species B-H have theoretical or known characteristics that could lead them to become rare with the H species exhibiting small geographic range, narrow habitat breadth, and decreasing population trend. Finally, we evaluated the prevalence of mapped habitat on protected lands for each species, exploring the patterns of representation in the rare species groups by ecoregion. The species we identified with population and habitat use characteristics that potentially predispose them to being or becoming rare represented a large percentage of each taxon. Potentially rare species were widely distributed among ecoregions. Of the 20 ecoregions in the country, 14 have a greater number of rare species than the national average for at least one taxon. Protection of the habitat for the majority of these rare species is below that recommended (17% of available habitat) by the Convention on Biological Diversity (CBD). The Everglades ecoregion was the only ecoregion that protected more than half of its rare or potentially rare species.

Global Ecology and Conservation↗
USGS2016

Spatially explicit modeling in ecology: A review

The use of spatially explicit models (SEMs) in ecology has grown enormously in the past two decades. One major advancement has been that fine-scale details of landscapes, and of spatially dependent biological processes, such as dispersal and invasion, can now be simulated with great precision, due to improvements in computer technology. Many areas of modeling have shifted toward a focus on capturing these fine-scale details, to improve mechanistic understanding of ecosystems. However, spatially implicit models (SIMs) have played a dominant role in ecology, and arguments have been made that SIMs, which account for the effects of space without specifying spatial positions, have an advantage of being simpler and more broadly applicable, perhaps contributing more to understanding. We address this debate by comparing SEMs and SIMs in examples from the past few decades of modeling research. We argue that, although SIMs have been the dominant approach in the incorporation of space in theoretical ecology, SEMs have unique advantages for addressing pragmatic questions concerning species populations or communities in specific places, because local conditions, such as spatial heterogeneities, organism behaviors, and other contingencies, produce dynamics and patterns that usually cannot be incorporated into simpler SIMs. SEMs are also able to describe mechanisms at the local scale that can create amplifying positive feedbacks at that scale, creating emergent patterns at larger scales, and therefore are important to basic ecological theory. We review the use of SEMs at the level of populations, interacting populations, food webs, and ecosystems and argue that SEMs are not only essential in pragmatic issues, but must play a role in the understanding of causal relationships on landscapes.

Ecosystems↗
USGS2014

Animal reintroductions: an innovative assessment of survival

Quantitative evaluations of reintroductions are infrequent and assessments of milestones reached before a project is completed, or abandoned due to lack of funding, are rare. However, such assessments, which are promoted in adaptive management frameworks, are critical. Quantification can provide defensible estimates of biological success, such as the number of survivors from a released cohort, with associated cost per animal. It is unlikely that the global issues of endangered wildlife and population declines will abate, therefore, assurance colonies and reintroductions are likely to become more common. If such endeavors are to be successful biologically or achieve adequate funding, implementation must be more rigorous and accountable. We use a novel application of a multistate, robust design capture-recapture model to estimate survival of reintroduced tadpoles through metamorphosis (i.e., the number of individuals emerging from the pond) and thereby provide a quantitative measure of effort and success for an "in progress" reintroduction of toads. Our data also suggest that tadpoles released at later developmental stages have an increased probability of survival and that eggs laid in the wild hatched at higher rates than eggs laid by captive toads. We illustrate how an interim assessment can identify problems, highlight successes, and provide information for use in adjusting the effort or implementing a Decision-Theoretic adaptive management strategy.

Biological Conservation↗
USGS2007

A Bayesian state-space formulation of dynamic occupancy models

Species occurrence and its dynamic components, extinction and colonization probabilities, are focal quantities in biogeography and metapopulation biology, and for species conservation assessments. It has been increasingly appreciated that these parameters must be estimated separately from detection probability to avoid the biases induced by nondetection error. Hence, there is now considerable theoretical and practical interest in dynamic occupancy models that contain explicit representations of metapopulation dynamics such as extinction, colonization, and turnover as well as growth rates. We describe a hierarchical parameterization of these models that is analogous to the state-space formulation of models in time series, where the model is represented by two components, one for the partially observable occupancy process and another for the observations conditional on that process. This parameterization naturally allows estimation of all parameters of the conventional approach to occupancy models, but in addition, yields great flexibility and extensibility, e.g., to modeling heterogeneity or latent structure in model parameters. We also highlight the important distinction between population and finite sample inference; the latter yields much more precise estimates for the particular sample at hand. Finite sample estimates can easily be obtained using the state-space representation of the model but are difficult to obtain under the conventional approach of likelihood-based estimation. We use R and Win BUGS to apply the model to two examples. In a standard analysis for the European Crossbill in a large Swiss monitoring program, we fit a model with year-specific parameters. Estimates of the dynamic parameters varied greatly among years, highlighting the irruptive population dynamics of that species. In the second example, we analyze route occupancy of Cerulean Warblers in the North American Breeding Bird Survey (BBS) using a model allowing for site-specific heterogeneity in model parameters. The results indicate relatively low turnover and a stable distribution of Cerulean Warblers which is in contrast to analyses of counts of individuals from the same survey that indicate important declines. This discrepancy illustrates the inertia in occupancy relative to actual abundance. Furthermore, the model reveals a declining patch survival probability, and increasing turnover, toward the edge of the range of the species, which is consistent with metapopulation perspectives on the genesis of range edges. Given detection/non-detection data, dynamic occupancy models as described here have considerable potential for the study of distributions and range dynamics.

Ecology↗
USGS2008

Avian movements and wetland connectivity in landscape conservation

The current conservation crisis calls for research and management to be carried out on a long-term, multi-species basis at large spatial scales. Unfortunately, scientists, managers, and agencies often are stymied in their effort to conduct these large-scale studies because of a lack of appropriate technology, methodology, and funding. This issue is of particular concern in wetland conservation, for which the standard landscape approach may include consideration of a large tract of land but fail to incorporate the suite of wetland sites frequently used by highly mobile organisms such as waterbirds (e.g., shorebirds, wading birds, waterfowl). Typically, these species have population dynamics that require use of multiple wetlands, but this aspect of their life history has often been ignored in planning for their conservation. We outline theoretical, empirical, modeling, and planning problems associated with this issue and suggest solutions to some current obstacles. These solutions represent a tradeoff between typical in-depth single-species studies and more generic multi-species studies. They include studying within- and among-season movements of waterbirds on a spatial scale appropriate to both widely dispersing and more stationary species; multi-species censuses at multiple sites; further development and use of technology such as satellite transmitters and population-specific molecular markers; development of spatially explicit population models that consider within-season movements of waterbirds; and recognition from funding agencies that landscape-level issues cannot adequately be addressed without support for these types of studies.

Conservation Biology↗