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Results for “Modeling and Using Context”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 613 records · Page 34Linked to original sources

USGS2025

Automated methods for processing camera trap video data for distance sampling

Context Population monitoring is an essential need for tracking biodiversity and judging efficacy of conservation management actions, both globally and in the Pacific. However, population monitoring efforts are often temporally inconsistent and limited to small scales. Motion-activated cameras (‘camera traps’) offer a way to cost-effectively monitor populations, but they also generate large amounts of data that are time intensive to process. Aims To develop an automated pipeline for processing videos of ungulates (Philippine deer, Rusa marianna ; and pigs, Sus scrofa ) on Andersen Air Force Base in Guam. Methods We processed camera videos with a machine learning model for object detection and classification. To estimate density using distance sampling methods, we used a separate machine learning model to estimate the distance of target animals from the camera. We compared density estimates generated using manual versus automated methods and assessed accuracy and processing time saved. Key results The object detection and classification model achieved an overall accuracy >80% and F1 score ≥0.9 and saved 36.9 h of processing time. The automated distance estimation was fairly accurate, with a 1.1 m (±1.4 m) difference from manual distance estimates, and saved 16.8 h of processing time. Density estimates did not differ substantially between manual and automated distance estimation. Conclusions Machine learning models accurately processed camera videos, allowing efficient estimates of density from camera data. Implications Further adoption of motion-activated cameras coupled with automated processing could lead to continuous, large-scale monitoring of populations, helping to understand and address changes in biodiversity.

Guam↗

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↗

USGS2019

Left out in the rain: Comparing productivity of two associated species exposes a leak in the umbrella species concept

Multi-species approaches to wildlife management have become commonplace and purport to benefit entire biological communities. These strategies aim to manage different, often taxonomically distant species under a single regime based on shared habitat associations and/or co-occurrence in the landscape. We tested the efficacy of multi-species management in the context of creating and maintaining early-successional forest cover types using two species of migratory birds that breed in eastern North America and are each the focus of intensive, concurrent, and overlapping management. American woodcock ( Scolopax minor ) and golden-winged warblers ( Vermivora chrysoptera ) breed in similar diverse-forest landscapes. Each species purportedly benefits from management for the other species and both are often used as flagship species for the creation of young forest and the conservation of associated avian communities. However, the landscape-species relationships that drive reproductive success and population stability in these species have not been explicitly compared. Here, we use previously published spatially-explicit models of productivity (the number of juveniles raised to a biologically significant milestone) to identify the relationship(s) between productivity of American woodcock and golden-winged warblers across a shared landscape. We found productivity to be negatively associated between these species on the same landscape at all spatial scales we modelled (1 m 2 –100 ha). Our results suggest that, with regards to productivity, American woodcock and golden-winged warblers have opposing relationships with the composition of the landscapes in which they coexist and therefore should not be assumed to benefit similarly from any individual management action at any relevant spatial scale.

Biological Conservation↗

USGS2017

A Bayesian method for assessing multiscalespecies-habitat relationships

Context Scientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multi-scale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large. Objectives Our objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance. Methods We introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA. Results Our method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%. Conclusions Given the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships.

Nebraska↗

USGS2016

Lake oxygen isotopes as recorders of North American Rocky Mountain hydroclimate: Holocene patterns and variability at multi-decadal to millennial time scales

Lake sediment oxygen isotope records (calcium carbonate-δ 18 O) in the western North American Cordillera developed during the past decade provide substantial evidence of Pacific ocean–atmosphere forcing of hydroclimatic variability during the Holocene. Here we present an overview of 18 lake sediment δ 18 O records along with a new compilation of lake water δ 18 O and δ 2 H that are used to characterize lake sediment sensitivity to precipitation-δ 18 O in contrast to fractionation by evaporation. Of the 18 records, 14 have substantial sensitivity to evaporation. Two records reflect precipitation-δ 18 O since the middle Holocene, Jellybean and Bison Lakes, and are geographically positioned in the northern and southern regions of the study area. Their comparative analysis indicates a sequence of time-varying north–south precipitation-δ 18 O patterns that is evidence for a highly non-stationary influence by Pacific ocean–atmosphere processes on the hydroclimate of western North America. These observations are discussed within the context of previous research on North Pacific precipitation-δ 18 O based on empirical and modeling methods. The Jellybean and Bison Lake records indicate that a prominent precipitation-δ 18 O dipole (enriched-north and depleted-south) was sustained between ~ 3.5 and 1.5 ka, which contrasts with earlier Holocene patterns, and appears to indicate the onset of a dominant tropical control on North Pacific ocean–atmosphere dynamics. This remains the state of the system today. Higher frequency reversals of the north–south precipitation-δ 18 O dipole between ~ 2.5 and 1.5 ka, and during the Medieval Climate Anomaly and the Little Ice Age, also suggest more varieties of Pacific ocean–atmosphere modes than a single Pacific Decadal Oscillation (PDO) type analogue. Results indicate that further investigation of precipitation-δ 18 O patterns on short (observational) and long (Holocene) time scales is needed to improve our understanding of the processes that drive regional precipitation-δ 18 O responses to Pacific ocean–atmosphere variability, which in turn, will lead to a better understanding of internal Pacific ocean–atmosphere variability and its response to external climate forcing mechanisms.

North American Rocky Mountain↗

USGS2022

Evaluating temporal and spatial transferability of a tidal inundation model for foraging waterbirds

For ecosystem models to be applicable outside their context of development, temporal and spatial transferability must be demonstrated. This presents a challenge for modeling intertidal ecosystems where spatiotemporal variation arises at multiple scales. Models specializing in tidal dynamics are generally inhibited from having wider ecological applications by coarse spatiotemporal resolution or high user competency. The Tidal Inundation Model of Shallow-water Availability (TiMSA) uniquely simulates tides to empirically derive a time-integrated measure of availability for a shallow-water depth range defined by the user. To evaluate temporal and spatiotemporal transferability, we employed TiMSA at the development site in the Florida Keys and at novel subsites in the Florida Bay (application site) under a different time period (application period). We used foraging little blue herons ( Egretta caerulea ) as the ecological unit with which to constrain the model's “water depth window,” that is, range of water depths to estimate shallow-water availability. At the development site, temporally consistent water depth windows contrasted with interannual variation in shallow-water availability, which revealed short-term changes in Little Blue Heron foraging habitat. At the application site, water depth accuracy varied by subsite and was correlated with spatial error in bathymetric elevation. Although TiMSA parameters were sensitive to environmental temporal variation and uncertainty in spatial data, a spatially explicit water depth window generated reliable estimates of shallow-water conditions over space and time at the development and application sites. By exploring the contributing factors to model error, we provide solutions to reduce uncertainty of TiMSA parameters at potential application sites and recommendations for addressing bathymetric inaccuracy in digital elevation models. Accurately quantifying spatiotemporal changes of shallow water has implications for monitoring habitat conditions for tidally influenced species and projecting future changes to coastal ecosystems in response to anthropogenic stressors and natural disturbances such as sea level rise.

Florida↗

USGS2022

Hot, wet and rare: Modelling the occupancy dynamics of the narrowly distributed Dixie Valley toad

Context: Small population sizes and no possibility of metapopulation rescue put narrowly distributed endemic species under elevated risk of extinction from anthropogenic change. Desert spring wetlands host many endemic species that require aquatic habitat and are isolated by the surrounding xeric terrestrial habitat. Aims: We sought to model the occupancy dynamics of the Dixie Valley toad ( Anaxyrus williamsi ), a recently described species endemic to a small desert spring wetland complex in Nevada, USA. Methods: We divided the species’ range into 20 m × 20 m cells and surveyed for Dixie Valley toads at 60 cells during six primary periods from 2018 to 2021, following an occupancy study design. We analysed our survey data by using a multi-state dynamic occupancy model to estimate the probability of adult occurrence, colonisation, site survival, and larval occurrence and the relationship of each to environmental covariates. Key results: The detection probabilities of adult and larval toads were affected by survey length and time of day. Adult Dixie Valley toads were widely distributed, with detections in 75% of surveyed cells at some point during the 3-year study, whereas larvae were observed only in 20% of cells during the study. Dixie Valley toad larvae were more likely to occur in cells far from spring heads with a high coverage of surface water, low emergent vegetation cover, and water temperatures between 20°C and 28°C. Adult toads were more likely to occur in cells with a greater coverage of surface water and water depth >10 cm. Cells with more emergent vegetation cover and surface water were more likely to be colonised by adult toads. Conclusions: Our results showed that Dixie Valley toads are highly dependent on surface water in both spring and autumn. Adults and larvae require different environmental conditions, with larvae occurring farther from spring heads and in fewer cells. Implications: Disturbances to the hydrology of the desert spring wetlands in Dixie Valley could threaten the persistence of this narrowly distributed toad.

Wildlife Research↗

USGS2025

Lake sturgeon behavioral diversity in the Laurentian Great Lakes: Migratory patterns across populations and habitats

Background Characterizing the diversity of migration behaviors from the individual to the population level is essential for understanding how organisms respond to environmental variation and how these responses affect survival and habitat use. Lake sturgeon ( Acipenser fulvescens ) is a species of special concern in the Laurentian Great Lakes that are long-lived and generally classified as intermittent, adfluvial spawners. Observations of lake sturgeon movements at ecologically relevant spatiotemporal scales have shown that migration behavior often varies among individuals within the same population. However, studies on individual populations, particularly when focused only on a part of the life cycle (e.g., often spawning), provide just a partial understanding of the species’ full migratory scope and processes underlying expression of different migratory behaviors. To better understand lake sturgeon migratory diversity, we characterized and compared migratory behaviors of six lake sturgeon populations occupying environments that varied in habitat availability and connectivity in different Laurentian Great Lakes. Methods Sequence analysis combined with agglomerative hierarchical clustering and visual inspection of daily location data were used to identify distinct lake sturgeon migratory behaviors present in each population. Results Seven distinct migratory behaviors were identified based on differential patterns of lake and river use that encompass spawning and other seasonal periods. Behaviors were categorized as annual spring river, intermittent spring river, intermittent two-step, annual summer river, annual winter river, and annual interlake migrants along with river residents. The presence and frequency of migratory behaviors varied substantially among populations. Conclusions Our study demonstrated that migratory diversity is a general feature of lake sturgeon life history that may be partially shaped by habitat availability and connectivity. Given these results, we propose a conceptual model that links habitat availability and connectivity to migratory diversity and predict a positive association between them. This updated framework provides a cohesive basis for understanding lake sturgeon migratory behavior across variable ecological contexts in the Laurentian Great Lakes and will help promote future research to refute or refine the model.

Laurentian Great Lakes↗

USGS2024

Don’t move a mussel: The role of key environmental drivers and management scale in assessing spatial variation in dreissenid spread risk in the Missouri River Basin

The spread of non-native freshwater mussels in North America is a growing threat that has already resulted in substantial ecological and economic damage to infested areas. A primary vector by which invasive mussels spread is watercraft that are transported over land from an infested waterbody to an uninfested waterbody. Management efforts such as watercraft inspection and detection programs that attempt to intercept infected watercraft can help limit this type of spread, but optimizing the effectiveness of these programs under limited resources is complicated. Studies have looked at developing watercraft inspection and decontamination program strategies that focus on policy-specific objectives such as maximizing the number of infested watercraft interceptions. However, there is limited work that has considered the heterogeneous impact of protection efforts across different regions and waterbodies. Knowledge about this heterogeneity can highlight regions that would benefit the most from protection as well as regions that would require less effort to protect, e.g., areas with naturally unsuitable water quality for dreissenids. To this end, we construct a composite relative risk index (CRR) for watersheds within the Missouri River Basin, a region in the United States on the front line of dreissenid spread. The CRR uses a model that mirrors an expected value model but uses relative indexing as a proxy for the model components. The CRR incorporates a wide array of data sets to account for the direct and indirect damages from a potential infestation along with the risk of an infestation occurring. Our results suggest that the relative priority of a specific watershed—measured through CRR—can depend on whether we consider the entire Missouri River Basin or just the watersheds in the same state. This also indicates substantial state-level heterogeneity in the CRR. Another contribution is that the CRR index includes user-specified weights for certain parameters so that a user can adjust the relative importance of various factors to match their specific context. An accompanying web tool allows users to view the CRR results and adjust multiple parameters to see the resulting impacts on the CCR for watersheds in the Missouri River Basin.

Missouri River Basin↗

USGS2025

Volcanic gases reflect magma stalling and launching depths

Many open-vent arc volcanoes display two modes in their continuous gas emissions, one with a characteristic CO 2 / S T ratio typical of periods of quiescent degassing and another punctuated by high CO 2 / S T gas emitted in the weeks before eruption, a recently recognized eruption precursor. In this study we explore the origin of the two modes of degassing revealed by time-series gas data at Turrialba volcano (Costa Rica) in the context of new melt inclusion (MI) data. To reconstruct the c[CO 2 ] of undegassed magma, we developed a rapid-quench piston-cylinder assembly to rehomogenize the vapor bubble commonly contained in MIs. We focus on olivine-hosted MIs from a mafic scoria sample erupted from Turrialba in 1864–1866. The reconstructed CO 2 contents in MIs decrease from ∼4000 to <1000 ppmw as S contents decrease from 3500 to <1000 ppmw. The highest reconstructed S and CO 2 in the MIs resulted in an initial magmatic CO 2 / S T ratio (molar) of 0.83. Informed by the MI data, we modeled the decompression degassing of Turrialba magma and vapor composition using the Sulfur_X and EVo models. Instead of being controlled by initial magmatic CO 2 /S T ratio as suggested by previous studies, we find that the quiescent gas emitted from Turrialba during 2014–2018 (CO 2 / S T = 2.3 ± 0.8, molar) appears to reflectequilibrium with magmas stored at 4–8 km (Sulfur_X) or 2 km (EVo) depth, when H 2 O is degassing extensively from the magma. A magma storage region at 4–8 km is also supported by seismic tomography. The second gas mode is noted by spikes in CO 2 / S T ∼ 7.9 ± 2 in the weeks prior to eruption. This gas reflects equilibrium with a magma at 12–18 km (Sulfur_X) or 4–8 km (EVo), where the ascending magma is saturated with a CO 2 -rich vapor. Thus, there are two important trans crustal depths beneath the volcano: one where the rate of H 2 O loss from the magma and thus magma viscosity increases, and one at greater depths where high CO 2 /S T vapor forms and may facilitate dike propagation. We interpret the shallower, H 2 O-loss region as the main site of magma stalling and storage, where quiescent gas is generated continuously. We interpret the greater depth (12–18 km) as the source of the precursory gas that precedes eruption, and where the mafic melt lastly equilibrated with a mush zone before ascending and triggering eruption weeks later. This hypothesis is ripe for testing at other volcanoes that exhibit two modes in gas geochemistry.

Turrialba volcano↗

USGS2023

Where can managers effectively resist climate-driven ecological transformation in pinyon-juniper woodlands of the US Southwest?

Pinyon–juniper (PJ) woodlands are an important component of dryland ecosystems across the US West and are potentially susceptible to ecological transformation. However, predicting woodland futures is complicated by species-specific strategies for persisting and reproducing under drought conditions, uncertainty in future climate, and limitations to inferring demographic rates from forest inventory data. Here, we leverage new demographic models to quantify how climate change is expected to alter population demographics in five PJ tree species in the US West and place our results in the context of a climate adaptation framework to resist, accept, or direct ecological transformation. Two of five study species, Pinus edulis and Juniperus monosperma , are projected to experience population declines, driven by both rising mortality and decreasing recruitment rates. These declines are reasonably consistent across various climate futures, and the magnitude of uncertainty in population growth due to future climate is less than uncertainty due to how demographic rates will respond to changing climate. We assess the effectiveness of management to reduce tree density and mitigate competition, and use the results to classify southwest woodlands into areas where transformation is (a) unlikely and can be passively resisted, (b) likely but may be resisted by active management, and (c) likely unavoidable, requiring managers to accept or direct the trajectory. Population declines are projected to promote ecological transformation in the warmer and drier PJ communities of the southwest, encompassing 37.1%–81.1% of our sites, depending on future climate scenarios. Less than 20% of sites expected to transform away from PJ have potential to retain existing tree composition by density reduction. Our results inform where this adaptation strategy could successfully resist ecological transformation in coming decades and allow for a portfolio design approach across the geographic range of PJ woodlands.

Arizona, Colorado, New Mexico, Utah↗

USGS2022

The Coastal Imaging Research Network (CIRN)

The Coastal Imaging Research Network (CIRN) is an international group of researchers who exploit signatures of phenomena in imagery of coastal, estuarine, and riverine environments. CIRN participants develop and implement new coastal imaging methodologies. The research objective of the group is to use imagery to gain a better fundamental understanding of the processes shaping those environments. Coastal imaging data may also be used to derive inputs for model boundary and initial conditions through assimilation, to validate models, and to make management decisions. CIRN was officially formed in 2016 to provide an integrative, multi-institutional group to collaborate on remotely sensed data techniques. As of 2021, the network is a collaboration between researchers from approximately 16 countries and includes investigators from universities, government laboratories and agencies, non-profits, and private companies. CIRN has a strong emphasis on education, exemplified by hosting annual “boot camps” to teach photogrammetry fundamentals and toolboxes from the CIRN code repository, as well as hosting an annual meeting for its members to present coastal imaging research. In this review article, we provide context for the development of CIRN as well as describe the goals and accomplishments of the CIRN community. We highlight components of CIRN’s resources for researchers worldwide including an open-source GitHub repository and coding boot camps. Finally, we provide CIRN’s perspective on the future of coastal imaging.

Remote Sensing↗

USGS2026

Morphometric properties of the CP-21 landing site on the Moon at Mons Gruithuisen Gamma

Characterizing terrain surface properties is an essential step in assessing the feasibility of landing successfully at a location on a planetary surface. Slopes and terrain ruggedness index (TRI) values derived from high-resolution (2 m pixel −1 ) digital terrain models provided important constraints in selecting the landing site for the upcoming Payloads and Research Investigations on the Surface of the Moon program as part of the Commercial Lunar Payload Services task order CP-21 mission. The selected landing site needed to balance safety requirements with the ability to achieve the science and exploration goals of the Lunar Vulkan Imaging and Spectroscopy Explorer payload. In this study, we compare several morphometric parameters in the context of the CP-21 landing site on Mons Gruithuisen Gamma, or the Gamma dome, and quantify the information they convey about lunar surface properties to assess their utility for future landing site evaluation. TRI was found to be a useful metric for assessing landing site safety. Metrics that better decouple slope and surface roughness, the vector ruggedness measure and the standard deviation of slope, provided additional information about surface characteristics and textures such as the degree to which roughness is isotropic.

Planetary Science Journal↗

USGS2015

Habitat edges have weak effects on duck nest survival at local spatial scales

Edge effects on nesting success have been documented in breeding birds in a variety of contexts, but there is still uncertainty in how edge type and spatial scale determine the magnitude and detectability of edge effects. Habitat edges are often viewed as predator corridors that surround or penetrate core habitat and increase the risk of predation for nearby nests. We studied the effects of three different types of potential predator corridors (main perimeter roads, field boundaries, and ATV trails within fields) on waterfowl nest survival in California. We measured the distance from duck nests to the nearest edge of each type, and used distance as a covariate in a logistic exposure analysis of nest survival. We found only weak evidence for edge effects due to predation. The best supported model of nest survival included all three distance categories, and while all coefficient estimates were positive (indicating that survival increased with distance from edge), 85% coefficient confidence intervals approached or bounded zero indicating an overall weak effect of habitat edges on nest success. We suggest that given the configuration of edges at our site, there may be few areas far enough from hard edges to be considered ‘core’ habitat, making edge effects on nest survival particularly difficult to detect.

Ardea↗

USGS2011

Effects of harvest and climate on population dynamics of northern bobwhites in south Florida

Context: Hunting-related (hereafter harvest) mortality is assumed to be compensatory in many exploited species. However, when harvest mortality is additive, hunting can lead to population declines, especially on public land where hunting pressure can be intense. Recent studies indicate that excessive hunting may have contributed to the decline of a northern bobwhite ( Colinus virginianus ) population in south Florida. Aims: This study aimed to estimate population growth rates to determine potential and actual contribution of vital rates to annual changes in population growth rates, and to evaluate the role of harvest and climatic variables on bobwhite population decline. Methods: We used demographic parameters estimated from a six-year study to parameterise population matrix models and conduct prospective and retrospective perturbation analyses. Key results: The stochastic population growth rate (λ S = 0.144) was proportionally more sensitive to adult winter survival and survival of fledglings, nests and broods from first nesting attempts; the same variables were primarily responsible for annual changes in population growth rate. Demographic parameters associated with second nesting attempts made virtually no contribution to population growth rate. All harvest scenarios consistently revealed a substantial impact of harvest on bobwhite population dynamics. If the lowest harvest level recorded in the study period (i.e. 0.08 birds harvested per day per km 2 in 2008) was applied, λ S would increase by 32.1%. Winter temperatures and precipitation negatively affected winter survival, and precipitation acted synergistically with harvest in affecting winter survival. Conclusions: Our results suggest that reduction in winter survival due to overharvest has been an important cause of the decline in our study population, but that climatic factors might have also played a role. Thus, for management actions to be effective, assessing the contribution of primary (e.g. harvesting) but also secondary factors (e.g. climate) to population decline may be necessary. Implications: Reducing hunting pressure would be necessary for the recovery of the bobwhite population at our study site. In addition, an adaptive harvest management strategy that considers weather conditions in setting harvest quota would help reverse the population decline further.

Florida↗

USGS2021

A structured approach to remediation site assessment: Lessons from 15 years of fish spawning habitat creation in the St. Clair‐Detroit River system

Ideally, restoration re‐establishes natural processes in degraded habitats (e.g., flow and sediment regimes). However, in altered systems where process‐based restoration is not feasible, habitat construction is another approach to mitigate degradation. Because habitat construction does not directly focus on restoring processes that build and maintain desired habitats, projects must be developed and placed within the contemporary regulatory, ecological, and hydrogeomorphic context of a system, to maximize effectiveness. Here, we develop a framework for evaluating the regulatory, ecological, and hydrogeomorphic components using 15 years of fish spawning habitat construction in the St. Clair‐Detroit River System. The process began by identifying regulatory requirements at a coarse resolution to quickly focus on locations where ecological potential and hydrogeomorphic constraints could be assessed at finer resolutions. Next, ecological potential was assessed using a lithophilic fish spawning habitat suitability index. The suitability index identified five sites for habitat construction and Lake sturgeon spawning was documented at each site following construction. However, qualitative monitoring showed fine sediments accumulated at older sites. Thus, geomorphic assessments were incorporated to identify sediment sources and model flow within targeted areas. Since geomorphic assessments required the finest resolution and had the most uncertainty, they were conducted after broad‐scale regulatory considerations and ecological assessments narrowed focus to a few candidate sites. The order of operations identified in this case study evolved from the iterative approach of the restoration team, but in retrospect, it helped develop a framework that directed project development resources to aspects with more uncertainty, where learning is most critical.

Michigan, Ontario↗

USGS2012

Modeling aeolian transport in response to succession, disturbance and future climate: Dynamic long-term risk assessment for contaminant redistribution

Aeolian sediment transport is a fundamental process redistributing sediment, nutrients, and contaminants in dryland ecosystems. Over time frames of centuries or longer, horizontal sediment fluxes and associated rates of contaminant transport are likely to be influenced by succession, disturbances, and changes in climate, yet models of horizontal sediment transport that account for these fundamental factors are lacking, precluding in large part accurate assessment of human health risks associated with persistent soil-bound contaminants. We present a simple model based on empirical measurements of horizontal sediment transport (predominantly saltation) to predict potential contaminant transport rates for recently disturbed sites such as a landfill cover. Omnidirectional transport is estimated within vegetation that changes using a simple Markov model that simulates successional trajectory and considers three types of short-term disturbances (surface fire, crown fire, and drought-induced plant mortality) under current and projected climates. The model results highlight that movement of contaminated soil is sensitive to vegetation dynamics and increases substantially (e.g., > fivefold) when disturbance and/or future climate are considered. The time-dependent responses in horizontal sediment fluxes and associated contaminant fluxes were sensitive to variability in the timing of disturbance, with longer intervals between disturbance allowing woody plants to become dominant and crown fire and drought abruptly reducing woody plant cover. Our results, which have direct implications for contaminant transport and landfill management in the specific context of our assessment, also have general relevance because they highlight the need to more fully account for vegetation dynamics, disturbance, and changing climate in aeolian process studies.

Aeolian Research↗

USGS2019

Using maintenance records from a long-term sensor monitoring network to evaluate the relationship between maintenance schedule and data quality

Sensor-based environmental monitoring networks are beginning to provide the large-scale, long-term data required to address important fundamental and applied questions in ecology. However, the data quality from deployed sensors can be difficult and costly to ensure. In this study, we use maintenance records from the 12-year history of Louisiana’s Coastwide Reference Monitoring System (CRMS) to assess the relationship between various dimensions of data quality and the frequency of field visits to the sensors. We use hierarchical Bayesian models to estimate the probability of missing data, the probability that a corrective offset of the sensor is required, and the magnitude of required offsets for water elevation and salinity data. We compared these estimates to predetermined risk thresholds to the help identify maintenance schedules that balanced the efficient use of labor resources without sacrificing data quality. We found that the relationship between data quality and increasing maintenance interval varied across metrics. Additionally, for most metrics, the maintenance interval when the metric’s credible interval and risk threshold intersected varied throughout the year and with wetland type. These results suggest that complex maintenance schedules, in which field visits vary in frequency throughout the year and with environmental context, are likely to provide the best tradeoff between labor cost and data quality. This analysis demonstrates that quantitative assessment of maintenance records can positively impact the sustainability of long-term data collection projects by helping identify new potential efficiencies in monitoring program management.

Louisiana↗