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At least 973 records · Page 54Linked to original sources
USGS2015

Analyzing high resolution topography for advancing the understanding of mass and energy transfer through landscapes: A review

The study of mass and energy transfer across landscapes has recently evolved to comprehensive considerations acknowledging the role of biota and humans as geomorphic agents, as well as the importance of small-scale landscape features. A contributing and supporting factor to this evolution is the emergence over the last two decades of technologies able to acquire high resolution topography (HRT) (meter and sub-meter resolution) data. Landscape features can now be captured at an appropriately fine spatial resolution at which surface processes operate; this has revolutionized the way we study Earth-surface processes. The wealth of information contained in HRT also presents considerable challenges. For example, selection of the most appropriate type of HRT data for a given application is not trivial. No definitive approach exists for identifying and filtering erroneous or unwanted data, yet inappropriate filtering can create artifacts or eliminate/distort critical features. Estimates of errors and uncertainty are often poorly defined and typically fail to represent the spatial heterogeneity of the dataset, which may introduce bias or error for many analyses. For ease of use, gridded products are typically preferred rather than the more information-rich point cloud representations. Thus many users take advantage of only a fraction of the available data, which has furthermore been subjected to a series of operations often not known or investigated by the user. Lastly, standard HRT analysis work-flows are yet to be established for many popular HRT operations, which has contributed to the limited use of point cloud data. In this review, we identify key research questions relevant to the Earth-surface processes community within the theme of mass and energy transfer across landscapes and offer guidance on how to identify the most appropriate topographic data type for the analysis of interest. We describe the operations commonly performed from raw data to raster products and we identify key considerations and suggest appropriate work-flows for each, pointing to useful resources and available tools. Future research directions should stimulate further development of tools that take advantage of the wealth of information contained in the HRT data and address the present and upcoming research needs such as the ability to filter out unwanted data, compute spatially variable estimates of uncertainty and perform multi-scale analyses. While we focus primarily on HRT applications for mass and energy transfer, we envision this review to be relevant beyond the Earth-surface processes community for a much broader range of applications involving the analysis of HRT.

Earth-Science Reviews↗
USGS2013

Integrating resource selection information with spatial capture--recapture

1. Understanding space usage and resource selection is a primary focus of many studies of animal populations. Usually, such studies are based on location data obtained from telemetry, and resource selection functions (RSFs) are used for inference. Another important focus of wildlife research is estimation and modeling population size and density. Recently developed spatial capture–recapture (SCR) models accomplish this objective using individual encounter history data with auxiliary spatial information on location of capture. SCR models include encounter probability functions that are intuitively related to RSFs, but to date, no one has extended SCR models to allow for explicit inference about space usage and resource selection. 2. In this paper we develop the first statistical framework for jointly modeling space usage, resource selection, and population density by integrating SCR data, such as from camera traps, mist-nets, or conventional catch traps, with resource selection data from telemetered individuals. We provide a framework for estimation based on marginal likelihood, wherein we estimate simultaneously the parameters of the SCR and RSF models. 3. Our method leads to increases in precision for estimating parameters of ordinary SCR models. Importantly, we also find that SCR models alone can estimate parameters of RSFs and, as such, SCR methods can be used as the sole source for studying space-usage; however, precision will be higher when telemetry data are available. 4. Finally, we find that SCR models using standard symmetric and stationary encounter probability models may not fully explain variation in encounter probability due to space usage, and therefore produce biased estimates of density when animal space usage is related to resource selection. Consequently, it is important that space usage be taken into consideration, if possible, in studies focused on estimating density using capture–recapture methods.

Methods in Ecology and Evolution↗
USGS2021

Nesting, brood rearing, and summer habitat selection by translocated greater sage‐grouse in North Dakota, USA

Human enterprise has led to large‐scale changes in landscapes and altered wildlife population distribution and abundance, necessitating efficient and effective conservation strategies for impacted species. Greater sage‐grouse ( Centrocercus urophasianus ; hereafter sage‐grouse) are a widespread sagebrush ( Artemisia spp.) obligate species that has experienced population declines since the mid‐1900s resulting from habitat loss and expansion of anthropogenic features into sagebrush ecosystems. Habitat loss is especially evident in North Dakota, USA, on the northeastern fringe of sage‐grouse’ distribution, where a remnant population remains despite recent development of energy‐related infrastructure. Resource managers in this region have determined a need to augment sage‐grouse populations using translocation techniques that can be important management tools for countering species decline from range contraction. Although translocations are a common tool for wildlife management, very little research has evaluated habitat following translocation, to track individual behaviors such as habitat selection and fidelity to the release site, which can help inform habitat requirements to guide selection of future release sites. We provide an example where locations from previously released radio‐marked sage‐grouse are used in a resource selection function framework to evaluate habitat selection following translocation and identify areas of seasonal habitat to inform habitat management and potential restoration needs. We also evaluated possible changes in seasonal habitat since the late 1980s using spatial data provided by the Rangeland Analysis Platform coupled with resource selection modeling results. Our results serve as critical baseline information for habitat used by translocated individuals across life stages in this study area, and will inform future evaluations of population performance and potential for long‐term recovery.

Montana, North Dakota, South Dakota, Wyoming↗
USGS2018

Variation in the vital rates of an Antarctic marine predator: the role of individual heterogeneity

Variation in life‐history traits such as lifespan and lifetime reproductive output is thought to arise, in part, due to among‐individual differences in the underlying probabilities of survival and reproduction. However, the stochastic nature of demographic processes can also generate considerable variation in fitness‐related traits among otherwise‐identical individuals. An improved understanding of life‐history evolution and population dynamics therefore depends on evaluating the relative role of each of these processes. Here, we used a 33‐yr data set with reproductive histories for 1,274 female Weddell seals from Erebus Bay, Antarctica, to assess the strength of evidence for among‐individual heterogeneity in the probabilities of survival and reproduction, while accounting for multiple other sources of variation in vital rates. Our analysis used recent advances in Bayesian model selection techniques and diagnostics to directly compare model fit and predictive power between models that included individual effects on survival and reproduction to those that did not. We found strong evidence for costs of reproduction to both survival and future reproduction, with breeders having rates of survival and subsequent reproduction that were 3% and 6% lower than rates for non‐breeders. We detected age‐related changes in the rates of survival and reproduction, but the patterns differed for the two rates. Survival rates steadily declined from 0.92 at age 7 to 0.56 at the maximal age of 31 yr. In contrast, reproductive rates increased from 0.68 at age 7 to 0.79 at age 16 and then steadily declined to 0.37 for the oldest females. Models that included individual effects explained more variation in observed life histories and had better estimated predictive power than those that did not, indicating their importance in understanding sources of variation among individuals in life‐history traits. We found that among‐individual heterogeneity in survival was small relative to that for reproduction. Our study, which found patterns of variation in vital rates that are consistent with a series of predictions from life‐history theory, is the first to provide a thorough assessment of variation in important vital rates for a long‐lived, high‐latitude marine mammal while taking full advantage of recent developments in model evaluation.

Ecology↗
USGS1970

Volcanic history of the San Juan Mountains, Colorado, as indicated by potassium-argon dating

Volcanic rocks in the San Juan Mountains constitute the largest erosional remnant of a once nearly continuous volcanic field that extended over much of the southern Rocky Mountains and adjacent areas in Oligocene and later time. Recent regional studies have shown that the gross petrologic evolution throughout the San Juan remnant of this field was relatively simple, with initial intermediate lavas and breccias, followed closely in time by more silicic ash-flow tuffs, and ending with a bimodal association of basalt and rhyolite. More limited data from other remnants of the original field indicate a similar evolution. In the San Juan field, voluminous early lavas and breccias - mainly alkali andesite, rhyodacite, and mafic quartz latite - were erupted from numerous scattered central volcanoes onto an eroded tectonically stable terrane. They formed mostly during the interval 35 to 30 m.y. ago, but some probably were erupted earlier and others up to several million years later. About 30 m.y. ago, major volcanic activity changed to explosive ash-flow eruptions of quartz latite and low-silica rhyolite that persisted until about 26 m.y. ago. Source areas for the ash flows are marked by large calderas in the central and western San Juan Mountains. Two groups of lavas and associated rocks of intermediate composition intertongue with the ash-flow sequence: (1) quartz latitic lavas that were erupted in and adjacent to caldera structures and are genetically related to the ash-flow activity; and (2) other, generally more mafic lavas and related rocks that are widely distributed without evident structural relation to the ash-flow eruptive centers. The second group apparently represents a continuation of the early intermediate activity into the period of major ash-flow eruption. In the early Miocene the character of volcanism changed notably. Whereas the Oligocene volcanics are predominantly intermediate lavas and related silicic differentiates, the younger rocks are largely a bimodal association of basalt and high-silica alkali rhyolite. Basalt and minor rhyolite were erupted intermittently through the Miocene and Pliocene, and at one time formed a widespread thin veneer over the older volcanic terrane. The marked contrast between the Oligocene intermediate to low-silica rhyolitic magmas and the later basaltic and rhyolitic magmas implies either different conditions of magma generation or processes of differentiation for the two suites. This petrologic change coincides approximately in time with nearby development of the Rio Grande depression, a major rift that is the local expression of widespread late Cenozoic crustal extension. Whatever the cause of the petrologic change, the progression from predominantly intermediate to bimodal basalt-rhyolite volcanism, approximately concurrent with initiation of late Tertiary crustal extension, appears characteristic of Cenozoic volcanism for much of the western interior United States. © 1970, The Geological Society of America, Inc.

Colorado↗
USGS2023

Wind-energy development alters pronghorn migration at multiple scales

Migration is a critical behavioral strategy necessary for population persistence and ecosystem functioning, but migration routes have been increasingly disrupted by anthropogenic activities, including energy development. Wind energy is the world's fastest growing source of electricity and represents an important alternative to hydrocarbon extraction, but its effects on migratory species beyond birds and bats are not well understood. We evaluated the effects of wind-energy development on pronghorn migration, including behavior and habitat selection, to assess potential effects on connectivity and other functional benefits including stopovers. We monitored GPS-collared female pronghorn from 2010 to 2012 and 2018 to 2020 in south-central Wyoming, USA, an area with multiple wind-energy facilities in various stages of development and operation. Across all time periods, we collected 286 migration sequences from 117 individuals, including 121 spring migrations, 123 fall migrations, and 42 facultative winter migrations. While individuals continued to migrate through wind-energy facilities, pronghorn made important behavioral adjustments relative to turbines during migration. These included avoiding turbines when selecting stopover sites in spring and winter, selecting areas farther from turbines at a small scale in spring and winter, moving more quickly near turbines in spring (although pronghorn moved more slowly near turbines in the fall), and reducing fidelity to migration routes relative to wind turbines under construction in both spring and fall. For example, an increase in distance to turbine from 0 to 1 km translated to a 33% and 300% increase in the relative probability of selection for stopover sites in spring and winter, respectively. The behavioral adjustments pronghorn made relative to wind turbines could reduce the functional benefits of their migration, such as foraging success or the availability of specific routes, over the long term.

Wyoming↗
USGS2022

Spatially explicit management of genetic diversity using ancestry probability surfaces

1. Ecological restoration and conservation efforts are increasing worldwide and the management of intraspecific genetic variation in plants and animals, an important component of biodiversity, is increasingly valued. As a result, tailorable, spatially explicit approaches to map genetic variation are needed to support decision-making and management frameworks related to the recovery of threatened and endangered species and the maintenance of genetic resources in species utilized by humans, such as for restoration or agricultural purposes. 2. Here, we describe and demonstrate a workflow to spatially interpolate patterns of genetic differentiation using novel functions in the R package POPMAPS ( Pop ulation M anagement using A ncestry P robability S urfaces). Our approach uses empirical genetic data to estimate ancestry coefficients across a user-defined landscape correlated with patterns of differentiation in the focal species. The resulting surface, which we term the ancestry probability surface, includes two components: hard population boundaries and estimations of uncertainty that represent confidence in population assignments (i.e., ancestry probabilities). 3. An ancestry probability surface developed for Hilaria jamesii , an important graminoid utilized in restoration across the western United States, demonstrates the functionality of POPMAPS . Genetic distances among empirical sites correlated better with least-cost distances across suitable habitat than with geographic distances, informing the surface over which the interpolation was conducted (i.e., a model indicating habitat suitability). A jackknifing procedure identified parameter values resulting in robust population assignments across the species’ range, which were utilized in downstream analyses to estimate ancestry coefficients from empirical data. Ancestry coefficients were translated into ancestry probabilities, which tended to be low for cells that were intermediate in distance between empirical sampling locations representing different populations or when influenced by empirical sampling locations with mixed genetic ancestry. 4. POPMAPS allows users to tailor parameter values and analytical approaches and thereby incorporate species-specific biological characteristics and desired levels of uncertainty into maps illustrating patterns of genetic differentiation. Ancestry probability surfaces may be used to guide management or investigate further ecological or evolutionary hypotheses. We discuss how maps produced by POPMAPS can inform multiple management challenges including species recovery planning and the utilization of commonly used species in restoration.

Methods in Ecology and Evolution↗
USGS1996

Thermal and mass implications of magmatic evolution in the Lassen volcanic region, California, and minimum constraints on basalt influx to the lower crust

We have analyzed the heat and mass demands of a petrologic model of basalt-driven magmatic evolution in which variously fractionated mafic magmas mix with silicic partial melts of the lower crust. We have formulated steady state heat budgets for two volcanically distinct areas in the Lassen region: the large, late Quaternary, intermediate to silicic Lassen volcanic center and the nearby, coeval, less evolved Caribou volcanic field. At Caribou volcanic field, heat provided by cooling and fractional crystallization of 52 km 3 of basalt is more than sufficient to produce 10 km of rhyolitic melt by partial melting of lower crust. Net heat added by basalt intrusion at Caribou volcanic field is equivalent to an increase in lower crustal heat flow of ∼7 mW m −2 , indicating that the field is not a major crustal thermal anomaly. Addition of cumulates from fractionation is offset by removal of erupted partial melts. A minimum basalt influx of 0.3 km 3 (km 2 Ma) −1 is needed to supply Caribou volcanic field. Our methodology does not fully account for an influx of basalt that remains in the crust as derivative intrusives. On the basis of comparison to deep heat flow, the input of basalt could be ∼3 to 7 times the amount we calculate. At Lassen volcanic center, at least 203 km 3 of mantle-derived basalt is needed to produce 141 km 3 of partial melt and drive the volcanic system. Partial melting mobilizes lower crustal material, augmenting the magmatic volume available for eruption at Lassen volcanic center; thus the erupted volume of 215 km 3 exceeds the calculated basalt input of 203 km 3 . The minimum basalt input of 1.6 km 3 (km 2 Ma) −1 is >5 times the minimum influx to the Caribou volcanic field. Basalt influx high enough to sustain considerable partial melting, coupled with locally high extension rate, is a crucial factor in development of Lassen volcanic center; in contrast, Caribou volcanic field has failed to develop into a large silicic center primarily because basalt supply there has been insufficient.

Journal of Geophysical Research B: Solid Earth↗
USGS2015

Experimental infection of snakes with Ophidiomyces ophiodiicola causes pathological changes that typify snake fungal disease

Snake fungal disease (SFD) is an emerging skin infection of wild snakes in eastern North America. The fungus Ophidiomyces ophiodiicola is frequently associated with the skin lesions that are characteristic of SFD, but a causal relationship between the fungus and the disease has not been established. We experimentally infected captive-bred corn snakes ( Pantherophis guttatus ) in the laboratory with pure cultures of O. ophiodiicola . All snakes in the infected group ( n = 8) developed gross and microscopic lesions identical to those observed in wild snakes with SFD; snakes in the control group ( n = 7) did not develop skin infections. Furthermore, the same strain of O. ophiodiicola used to inoculate snakes was recovered from lesions of all animals in the infected group, but no fungi were isolated from individuals in the control group. Monitoring progression of lesions throughout the experiment captured a range of presentations of SFD that have been described in wild snakes. The host response to the infection included marked recruitment of granulocytes to sites of fungal invasion, increased frequency of molting, and abnormal behaviors, such as anorexia and resting in conspicuous areas of enclosures. While these responses may help snakes to fight infection, they could also impact host fitness and may contribute to mortality in wild snakes with chronic O. ophiodiicola infection. This work provides a basis for understanding the pathogenicity of O. ophiodiicola and the ecology of SFD by using a model system that incorporates a host species that is easy to procure and maintain in the laboratory. IMPORTANCE Skin infections in snakes, referred to as snake fungal disease (SFD), have been reported with increasing frequency in wild snakes in the eastern United States. While most of these infections are associated with the fungus Ophidiomyces ophiodiicola , there has been no conclusive evidence to implicate this fungus as a primary pathogen. Furthermore, it is not understood why the infections affect different host populations differently. Our experiment demonstrates that O. ophiodiicola is the causative agent of SFD and can elicit pathological changes that likely impact fitness of wild snakes. This information, and the laboratory model we describe, will be essential in addressing unresolved questions regarding disease ecology and outcomes of O. ophiodiicola infection and helping to conserve snake populations threatened by the disease. The SFD model of infection also offers utility for exploring larger concepts related to comparative fungal virulence, host response, and host-pathogen evolution.

mBio↗
USGS2019

Temporally adaptive acoustic sampling to maximize detection across a suite of focal wildlife species

Acoustic recordings of the environment can produce species presence–absence data for characterizing populations of sound-producing wildlife over multiple spatial scales. If a species is present at a site but does not vocalize during a scheduled audio recording survey, researchers may incorrectly conclude that the species is absent (“false negative”). The risk of false negatives is compounded when audio devices have sampling constraints, do not record continuously, and must be manually scheduled to operate at pre-selected times of day, particularly when research programs target multiple species with acoustic availability that varies across temporal conditions. We developed a temporally adaptive acoustic sampling algorithm to maximize detection probabilities for a suite of focal species amid sampling constraints. The algorithm combines user-supplied species vocalization models with site-specific weather forecasts to set an optimized sampling schedule for the following day. To test our algorithm, we simulated hourly vocalization probabilities for a suite of focal species in a hypothetical monitoring area for the year 2016. We conducted a factorial experiment that sampled from the 2016 acoustic environment to compare the probability of acoustic detection by a fixed (stationary) schedule versus a temporally adaptive optimized schedule under several sampling efforts and monitoring durations. We found that over the course of a study season, the probability of acoustically capturing a focal species (given presence) at least once via automated acoustic monitoring was greater (and acoustic capture occurred earlier in the season) when using the temporally adaptive optimized schedule as compared to a fixed schedule. The advantages of a temporally adaptive optimized acoustic sampling schedule are magnified when a study duration is short, sampling effort is low, and/or species acoustic availability is minimal. This methodology presents the opportunity to maximize acoustic monitoring sampling efforts amid constraints.

Colorado↗
USGS2022

Assessing vegetation recovery from energy development using a dynamic reference approach

Ecologically relevant references are useful for evaluating ecosystem recovery, but references that are temporally static may be less useful when environmental conditions and disturbances are spatially and temporally heterogeneous. This challenge is particularly acute for ecosystems dominated by sagebrush ( Artemisia spp.), where communities may require decades to recover from disturbance. We demonstrated application of a dynamic reference approach to studying sagebrush recovery using three decades of sagebrush cover estimates from remote sensing (1985–2018). We modelled recovery on former oil and gas well pads ( n = 1200) across southwestern Wyoming, USA, relative to paired references identified by the Disturbance Automated Reference Toolset. We also used quantile regression to account for unmodelled heterogeneity in recovery, and projected recovery from similar disturbance across the landscape. Responses to weather and site-level factors often differed among quantiles, and sagebrush recovery on former well pads increased more when paired reference sites had greater sagebrush cover. Little (<5%) of the landscape was projected to recover within 100 years for low to mid quantiles, and recovery often occurred at higher elevations with cool and moist annual conditions. Conversely, 48%–78% of the landscape recovered quickly (within 25 years) for high quantiles of sagebrush cover. Our study demonstrates advantages of using dynamic reference sites when studying vegetation recovery, as well as how additional inferences obtained from quantile regression can inform management.

Wyoming↗
USGS2017

Design- and model-based recommendations for detecting and quantifying an amphibian pathogen in environmental samples

Accurate pathogen detection is essential for developing management strategies to address emerging infectious diseases, an increasingly prominent threat to wildlife. Sampling for free-living pathogens outside of their hosts has benefits for inference and study efficiency, but is still uncommon. We used a laboratory experiment to evaluate the influences of pathogen concentration, water type, and qPCR inhibitors on the detection and quantification of Batrachochytrium dendrobatidis ( Bd ) using water filtration. We compared results pre- and post-inhibitor removal, and assessed inferential differences when single versus multiple samples were collected across space or time. We found that qPCR inhibition influenced both Bd detection and quantification in natural water samples, resulting in biased inferences about Bd occurrence and abundance. Biases in occurrence could be mitigated by collecting multiple samples in space or time, but biases in Bd quantification were persistent. Differences in Bd concentration resulted in variation in detection probability, indicating that occupancy modeling could be used to explore factors influencing heterogeneity in Bd abundance among samples, sites, or over time. Our work will influence the design of studies involving amphibian disease dynamics and studies utilizing environmental DNA (eDNA) to understand species distributions.

Ecolology and Evolution↗
USGS2017

Life histories and conservation of long-lived reptiles, an illustration with the American crocodile (Crocodylus acutus)

Successful species conservation is dependent on adequate estimates of population dynamics, but age-specific demographics are generally lacking for many long-lived iteroparous species such as large reptiles. Accurate demographic information allows estimation of population growth rate, as well as projection of future population sizes and quantitative analyses of fitness trade-offs involved in the evolution of life-history strategies. Here, a long-term capture–recapture study was conducted from 1978 to 2014 on the American crocodile ( Crocodylus acutus ) in southern Florida. Over the study period, 7,427 hatchlings were marked and 380 individuals were recaptured for as many as 25 years. We estimated survival to be strongly age dependent with hatchlings having the lowest survival rates (16%) but increasing to nearly 90% at adulthood based on mark–recapture models. More than 5% of the female population were predicted to be reproductive by age 8 years; the age-specific proportion of reproductive females steadily increased until age 18 when more than 95% of females were predicted to be reproductive. Population growth rate, estimated from a Leslie–Lefkovitch stage-class model, showed a positive annual growth rate of 4% over the study period. Using a prospective sensitivity analysis, we revealed that the adult stage, as expected, was the most critical stage for population growth rate; however, the survival of younger crocodiles before they became reproductive also had a surprisingly high elasticity. We found that variation in age-specific fecundity has very limited impact on population growth rate in American crocodiles. We used a comparative approach to show that the original life-history strategy of American crocodiles is actually shared by other large, long-lived reptiles: while adult survival rates always have a large impact on population growth, this decreases with declining increasing growth rates, in favour of a higher elasticity of the juvenile stage. Crocodiles, as a long-lived and highly fecund species, deviate from the usual association of life histories of “slow” species. Current management practices are focused on nests and hatchling survival; however, protection efforts that extend to juvenile crocodiles would be most effective for conservation of the species, especially in an ever-developing landscape.

Journal of Animal Ecology↗
USGS2013

Hierarchical spatial capture-recapture models: Modeling population density from stratified populations

Capture–recapture studies are often conducted on populations that are stratified by space, time or other factors. In this paper, we develop a Bayesian spatial capture–recapture (SCR) modelling framework for stratified populations – when sampling occurs within multiple distinct spatial and temporal strata. We describe a hierarchical model that integrates distinct models for both the spatial encounter history data from capture–recapture sampling, and also for modelling variation in density among strata. We use an implementation of data augmentation to parameterize the model in terms of a latent categorical stratum or group membership variable, which provides a convenient implementation in popular BUGS software packages. We provide an example application to an experimental study involving small-mammal sampling on multiple trapping grids over multiple years, where the main interest is in modelling a treatment effect on population density among the trapping grids. Many capture–recapture studies involve some aspect of spatial or temporal replication that requires some attention to modelling variation among groups or strata. We propose a hierarchical model that allows explicit modelling of group or strata effects. Because the model is formulated for individual encounter histories and is easily implemented in the BUGS language and other free software, it also provides a general framework for modelling individual effects, such as are present in SCR models.

Methods in Ecology and Evolution↗
USGS2023

Assimilating ecological theory with empiricism: Using constrained generalized additive models to enhance survival analyses

1. Integrating ecological theory with empirical methods is ubiquitous in ecology using hierarchical Bayesian models. However, there has been little development focused on integration of ecological theory into models for survival analysis. Survival is a fundamental process, linking individual fitness with population dynamics, but incorporating life history strategies to inform survival estimation can be challenging because mortality processes occur at multiple scales. 2. We develop an approach to survival analysis, incorporating model constraints based on a species' life history strategy using functional analytical tools. Specifically, we structurally separate intrinsic patterns of mortality that arise from age-specific processes (e.g. increasing survival during early life stages due to growth or maturation, versus senescence) from extrinsic mortality patterns that arise over different periods of time (e.g. seasonal temporal shifts). We use shape constrained generalized additive models (CGAMs) to obtain age-specific hazard functions that incorporate theoretical information based on classical survivorship curves into the age component of the model and capture extrinsic factors in the time component. 3. We compare the performance of our modelling approach to standard survival modelling tools that do not explicitly incorporate species life history strategy in the model structure, using metrics of predictive power, accuracy, efficiency and computation time. We applied these models to two case studies that reflect different functional shapes for the underlying survivorship curves, examining age-period survival for white-tailed deer Odocoileus virginianus in Wisconsin, USA and Columbian sharp-tailed grouse T ympanuchus phasianellus columbianus in Colorado, USA.

Colorado, Wisconsin↗
USGS2020

Habitat characterization and species distribution model of the only large-lake population of the endangered Silver Chub (Macrhybopsis storeriana, Kirtland 1844)

The endangered Silver Chub ( Macrhybopsis storeriana, Kirtland 1844) is native to North America and primarily riverine, with the only known large‐lake population in Lake Erie. Once a major component of the Lake Erie fish community, it declined and became nearly extirpated in the mid‐1900s. Recent collections in western Lake Erie suggest that Silver Chub may be able to recover, but their habitat and distribution are poorly known. A recent work showed an extensive area of western Lake Erie with the potential to support large numbers of Silver Chub, but was based on a geographically limited dataset. We developed a neural network‐based species distribution model for the Silver Chub in western Lake Erie, improved by new synoptic data and using habitat variables resistant to anthropogenic activities. The Potential model predictions were compared with a model that included anthropogenic‐sensitive variables. The Potential model used 10 habitat variables and performed well, explaining > 99% of data variation and had generally low error rates. Predictions indicated that a large area of the waters approximately 2–9 m deep contained Appropriate habitat and the highest abundances should be supported by habitat in a wide arc through the western end of the basin. The model indicated that Appropriate Silver Chub habitat was associated with relatively deep water, near coastal wetlands, where effective fetch is less than average. Disturbance model predictions were similar, but predicted poorer Silver Chub habitat in more areas than that predicted by the Potential model. Our Potential model reveals Appropriate habitat conditions for Silver Chub and its spatial distribution, indicating that extensive areas of western Lake Erie could support Silver Chub. Comparisons with Disturbance model predictions demonstrate that Potential model predictions may be used in conjunction with analyses of degrading conditions in the system to better conserve and manage for this endangered species.

Michigan, Ohio↗
USGS2018

Modelling sound attenuation in heterogeneous environments for improved bioacoustic sampling of wildlife populations

Acoustic sampling methods are becoming increasingly important in biological monitoring. Sound attenuation is one of the most important dynamics affecting the utility of acoustic data as it directly affects the probability of detection of individuals by acoustic sensor arrays and especially the localization of acoustic signals necessary in telemetry studies. Therefore, models of sound attenuation are necessary to make efficient use of acoustic data in ecological monitoring and assessment applications. Models of attenuation in widespread use are based on Euclidean distance between source and sensor, which is justified under spherical attenuation of sound waves in homogeneous environments. In this paper, I develop a model of sound attenuation based on a non‐Euclidean cost‐weighted distance metric which contains attenuation coefficients that characterize the attenuation of sound due to environmental heterogeneity in the vicinity of an acoustic sensor array. I show that parameters of the proposed attenuation model can be estimated by maximum likelihood using experimental data from an array of fixed sources, thus allowing investigators who use bioacoustic methods to devise explicit models of sound attenuation in situ and apply them to localization of sources and density estimation. In addition, drawing on analogy with spatial capture–recapture models, I argue that parameters of the non‐Euclidean model of attenuation can be estimated when source locations are unknown . Thus, the models can be applied to real field studies which require estimation of attenuation parameters or localization of signals. Models of heterogeneous sound attenuation allow more accurate descriptions of acoustic monitoring data, and therefore should produce more accurate estimates of ecological parameters of interest, including source locations, density, and movement trajectories. Moreover, the ability to test specific hypotheses about the effects of habitat and landscape structure on sound attenuation can improve the design of acoustic monitoring arrays and lead to more efficient deployment of acoustic sensing technology.

Methods in Ecology and Evolution↗
USGS2022

Defining fine-scaled population structure among continuously distributed populations

Understanding wildlife population structure and connectivity can help managers identify conservation strategies, as structure can facilitate the study of population changes and habitat connectivity can provide information on dispersal and biodiversity. To facilitate the use of wildlife monitoring data for improved adaptive management, we developed a novel approach to define hierarchical tiers (multiple scales) of population structure. We defined population structure by combining graph theory with biological inference about dispersal capability (based on movement, gene flow, and habitat condition) and functional processes affecting movement (e.g. habitat selection across scales of landscape preferences). First, we developed least-cost paths between high fidelity sites (habitat patches) using a cost surface, informed from functional processes of habitat characteristics to account for resistance of inter-patch movements. Second, we combined the paths into a multi-path graph construct. Third, we used information on potential connectivity (dispersal distances) and functional connectivity (permeability of fragmented landscapes based on selection preferences) to decompose the graph into hierarchical tiers of connected subpopulations, denoting the degree that dispersal affected population structure. As a case study, we applied our approach across the greater sage-grouse ( Centrocercus urophasianus ) range, a species of conservation concern in western United States. We described the relative importance of local populations and where to potentially avoid landscape disturbances that may negatively affect population connectivity using centrality measures supported by graph theory, and we demonstrated close alignment of the resulting population structure with population densities. This method can be adapted for other species with site fidelity and used as a management tool to evaluate population trends and responses to landscape changes across different temporal and spatial scales.

Methods in Ecology and Evolution↗