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At least 1,063 records · Page 59Linked to original sources
USGS2011

Modeling of hydroecological feedbacks predicts distinct classes of landscape pattern, process, and restoration potential in shallow aquatic ecosystems

It is widely recognized that interactions between vegetation and flow cause the emergence of channel patterns that are distinct from the standard Schumm classification of river channels. Although landscape pattern is known to be linked to ecosystem services such as habitat provision, pollutant removal, and sustaining biodiversity, the mechanisms responsible for the development and stability of different landscape patterns in shallow, vegetated flows have remained poorly understood. Fortunately, recent advances have made possible large-scale models of flow through vegetated environments that can be run over a range of environmental variables and over timescales of millennia. We describe a new, quasi-3D cellular automata model that couples simulations of shallow-water flow, bed shear stresses, sediment transport, and vegetation dynamics in an efficient manner. That efficiency allowed us to apply the model widely in order to determine how different hydroecological feedbacks control landscape pattern and process in various types of wetlands and floodplains. Distinct classes of landscape pattern were uniquely associated with specific types of allogenic and autogenic drivers in wetland flows. Regular, anisotropically patterned wetlands were dominated by allogenic processes (i.e., processes driven by periodic high water levels and flow velocities that redistribute sediment), relative to autogenic processes (e.g., vegetation production, peat accretion, and gravitational erosion). These anistropically patterned wetlands are therefore particularly prone to hydrologic disturbance. Other classes of wetlands that emerged from simulated interactions included maze-patterned, amorphous, and topographically noisy marshes, open marsh with islands, banded string-pool sequences perpendicular to flow, parallel deep and narrow channels flanked by marsh, and ridge-and-slough patterned marsh oriented parallel to flow. Because vegetation both affects and responds to the balance between the transport capacity of the flow and sediment supply, these vegetated systems exhibit a feedback that is not dominant in most rivers. Consequently, unlike in most rivers, it is not possible to predict the “channel pattern” of a vegetated landscape based only on discharge characteristics and sediment supply; the antecedent vegetation pattern and vegetation dynamics must also be known. In general, the stability of different wetland pattern types is most strongly related to factors controlling the erosion and deposition of sediment at vegetation patch edges, the magnitude of sediment redistribution by flow, patch elevation relative to water level, and the variability of erosion rates in vegetation patches with low flow-resistance. As we exemplify in our case-study of the Everglades ridge and slough landscape, feedback between flow and vegetation also causes hysteresis in landscape evolution trajectories that will affect the potential for landscape restoration. Namely, even if the hydrologic conditions that historically produced higher flows are restored, degraded portions of the ridge and slough landscape are unlikely to revert to their former patterning. As wetlands and floodplains worldwide become increasingly threatened by climate change and urbanization, the greater mechanistic understanding of landscape pattern and process that our analysis provides will improve our ability to forecast and manage the behavior of these ecosystems.

Florida↗
USGS2026

Movement models to predict low-altitude flight of soaring birds using look-ahead environmental factors

Advances in fine-scale movement modeling of soaring birds can aid efforts to understand and resolve the impacts of anthropogenic activities on such birds. Soaring birds often rely on underlying terrain and low-altitude updrafts to govern their flights at rotor-swept altitudes (≤ 200 m above ground level), which puts them at risk of collision with wind turbines. We developed a data-driven Markov model at 1-s resolution that predicts the fine-scale flight behavior of golden eagles ( Aquila chrysaetos ) as a function of ecological covariates at the current location as well as those within an eagle's line of sight. We only considered ecological covariates that are readily available in real-time (ground elevation and wind conditions). Latent factors (age, sex, species, behavioral intent, migratory status) were intentionally left out of the model. We calibrated the model using golden eagle telemetry data collected in two different ecoregions of the United States. Given a starting location, the calibrated model simulates multiple stochastic 3D paths to produce a time-explicit and spatially explicit risk map of turbine collisions. We discovered an empirical relation between the rate of change of heading and the orographic updraft conditions within an eagle's line of sight. Our model performed most effectively when predicting predominantly-soaring flights at rotor-swept altitudes during wind conditions in which turbines are likely to be operational. The calibrated model could be used in concert with automated eagle detection and turbine curtailment technologies. Specifically, once an eagle is detected by those systems, our model could then provide accurate predictions of turbines the eagle is likely to interact with in the near term.

Ecology and Evolution↗
USGS2018

Dynamic occupancy modeling of temperate marine fish in area-based closures

Species distribution models (SDMs) are commonly used to model the spatial structure of species in the marine environment, however, most fail to account for detectability of the target species. This can result in underestimates of occupancy, where nondetection is conflated with absence. The site occupancy model (SOM) overcomes this failure by treating occupancy as a latent variable of the model and incorporates a detection submodel to account for variability in detection rates. These have rarely been applied in the context of marine fish and never for the multiseason dynamic occupancy model (DOM). In this study, a DOM is developed for a designated species of concern, cusk ( Brosme brosme ), over a four-season period. Making novel use of a high-resolution 3-dimensional hydrodynamic model, detectability of cusk is considered as a function of current speed and algae cover. Algal cover on the seabed is measured from video surveys to divide the study area into two distinct regions: those with canopy forming species of algae and those without (henceforth bottom types). Modeled estimates of the proportion of sites occupied in each season are 0.88, 0.45, 0.74, and 0.83. These are significantly greater than the proportion of occupied sites measured from underwater video observations which are 0.57, 0.28, 0.43, and 0.57. Individual fish are detected more frequently with increasing current speed in areas lacking canopy and less frequently with increasing current speed in areas with canopy. The results indicate that, where possible, SDM studies for all marine species should take account of detectability to avoid underestimating the proportion of sites occupied at a given study area. Sampling closed areas or areas of conservation often requires the use of nonphysical, low impact sampling methods like camera surveys. These methods inherently result in detection probabilities less than one, an issue compounded by time-varying features of the environment that are rarely accounted for marine studies. This work highlights the use of modeled hydrodynamics as a tool to correct some of this imbalance.

Gulf of Maine↗
USGS2019

Effects of invasive plants on fire regimes and postfire vegetation diversity in an arid ecosystem

We assessed the impacts of co‐occurring invasive plant species on fire regimes and postfire native communities in the Mojave Desert, western USA. We analyzed the distribution and co‐occurrence patterns of three invasive annual grasses (Bromus rubens, Bromus tectorum, and Schismus spp.) known to alter fuel conditions and community structure, and an invasive forb (Erodium cicutarium) which dominates postfire sites. We developed species distribution models (SDMs) for each of the four taxa and analyzed field plot data to assess the relationship between invasives and fire frequency, years postfire, and the impacts on postfire native herbaceous diversity. Most of the Mojave Desert is highly suitable for at least one of the four invasive species, and 76% of the ecoregion is predicted to have high or very high suitability for the joint occurrence of B. rubens and B. tectorum and 42% high or very high suitability for the joint occurrence of the two Bromus species and E. cicutarium. Analysis of cover from plot data indicated two or more of the species occurred in 77% of the plots, with their cover doubling with each additional species. We found invasive cover in burned plots increased for the first 20 years postfire and recorded two to five times more cover in burned than unburned plots. Analysis also indicated that native species diversity and evenness as negatively associated with higher levels of relative cover of the four invasive taxa. Our findings revealed overlapping distributions of the four invasives; a strong relationship between the invasives and fire frequency; and significant negative impacts of invasives on native herbaceous diversity in the Mojave. This suggests predicting the distributions of co‐occurring invasive species, especially transformer species, will provide a better understanding of where native‐dominated communities are most vulnerable to transformations following fire or other disturbances.

California, Nevada↗
USGS2021

Linking behavioral states to landscape features for improved conservation management

A central theme for conservation is understanding how animals differentially use, and are affected by change in, the landscapes they inhabit. However, it has been challenging to develop conservation schemes for habitat-specific behaviors. Here we use behavioral change point analysis to identify behavioral states of golden eagles ( Aquila chrysaetos ) in the Sonoran and Mojave Deserts of the southwestern United States, and we identify, for each behavioral state, conservation-relevant habitat associations. We modeled behavior using 186,859 GPS points from 48 eagles and identified 2,851 distinct segments comprising four behavioral states. Altitude above ground level (AGL) best differentiated behavioral states, with two clusters of short-distance movement behaviors characterized by low AGL (state 1 AGL = 14 m (median); state 2 AGL = 11 m) and two associated with longer-distance movement behaviors and characterized by higher AGL (state 3 AGL = 108 m; state 4 AGL = 450 m). Behaviors such as perching and low-altitude hunting were associated with short-distance movements in updraft-poor environments, at higher elevations, and over steeper and more north-facing terrain. In contrast, medium-distance movements such as hunting and transiting were over gentle and south-facing slopes. Long-distance transiting occurred over the desert habitats that generate the best updraft. This information can guide management of this species, and our approach provides a template for behavior-specific habitat associations for other species of management concern.

California↗
USGS2017

Imperfect pathogen detection from non-invasive skin swabs biases disease inference

1. Conservation managers rely on accurate estimates of disease parameters, such as pathogen prevalence and infection intensity, to assess disease status of a host population. However, these disease metrics may be biased if low-level infection intensities are missed by sampling methods or laboratory diagnostic tests. These false negatives underestimate pathogen prevalence and overestimate mean infection intensity of infected individuals. 2. Our objectives were two-fold. First, we quantified false negative error rates of Batrachochytrium dendrobatidis on non-invasive skin swabs collected from an amphibian community in El Copé, Panama. We swabbed amphibians twice in sequence, and we used a recently developed hierarchical Bayesian estimator to assess disease status of the population. Second, we developed a novel hierarchical Bayesian model to simultaneously account for imperfect pathogen detection from field sampling and laboratory diagnostic testing. We evaluated the performance of the model using simulations and varying sampling design to quantify the magnitude of bias in estimates of pathogen prevalence and infection intensity. 3. We show that Bd detection probability from skin swabs was related to host infection intensity, where Bd infections < 10 zoospores have < 95% probability of being detected. If imperfect Bd detection was not considered, then Bd prevalence was underestimated by as much as 16%. In the Bd-amphibian system, this indicates a need to correct for imperfect pathogen detection caused by skin swabs in persisting host communities with low-level infections. More generally, our results have implications for study designs in other disease systems, particularly those with similar objectives, biology, and sampling decisions. 4. Uncertainty in pathogen detection is an inherent property of most sampling protocols and diagnostic tests, where the magnitude of bias depends on the study system, type of infection, and false negative error rates. Given that it may be difficult to know this information in advance, we advocate that the most cautious approach is to assume all errors are possible and to accommodate them by adjusting sampling designs. The modeling framework presented here improves the accuracy in estimating pathogen prevalence and infection intensity.

Methods in Ecology and Evolution↗
USGS2016

The source of groundwater and solutes to Many Devils Wash at a former uranium mill site in Shiprock, New Mexico

The Shiprock Disposal Site is the location of the former Navajo Mill (Mill), a uranium ore-processing facility, located on a terrace overlooking the San Juan River in the town of Shiprock, New Mexico. Following the closure of the Mill, all tailings and associated materials were encapsulated in a disposal cell built on top of the former Mill and tailings piles. The milling operations, conducted at the site from 1954 to 1968, created radioactive tailings and process-related wastes that are now found in the groundwater. Elevated concentrations of constituents of concern—ammonium, manganese, nitrate, selenium, strontium, sulfate, and uranium—have also been measured in groundwater seeps in the nearby Many Devils Wash arroyo, leading to the inference that these constituents originated from the Mill. These constituents have also been reported in groundwater that is associated with Mancos Shale, the bedrock that underlies the site. The objective of this report is to increase understanding of the source of water and solutes to the groundwater beneath Many Devils Wash and to establish the background concentrations for groundwater that is in contact with the Mancos Shale at the site. This report presents evidence on three working hypotheses: (1) the water and solutes in Many Devils Wash originated from the operations at the former Mill, (2) groundwater in deep aquifers is upwelling under artesian pressure to recharge the shallow groundwater beneath Many Devils Wash, and (3) the groundwater beneath Many Devils Wash originates as precipitation that infiltrates into the shallow aquifer system and discharges to Many Devils Wash in a series of springs on the east side of the wash. The solute concentrations in the shallow groundwater of Many Devils Wash would result from the interaction of the water and the Mancos Shale if the source of water was upwelling from deep aquifers or precipitation. In order to compare the groundwater from various wells to groundwater that has been affected by Mill activities, a classification system was developed to determine which wells were most likely to have been affected. Affects to groundwater by the Mill were determined by using the reported uranium alpha activity ratios measured in groundwater samples, along with the concentration of the uranium and the location of the wells relative to the Mill. Activity ratios of 1.2 or less were determined to be the most reliable indicator of Mill-affected groundwater. Wells with samples that had a reported activity ratio of 1.2 or less were classified as Mill affected. To compare groundwater with background water-quality, data from groundwater seeps and springs in the Upper Eagle Nest Arroyo and Salt Creek Wash, located north of the San Juan River, are also presented and analyzed. Based on groundwater elevations and tritium concentrations measured in wells located between the disposal cell and Many Devils Wash, Mill water is not likely to reach Many Devils Wash. The tritium concentrations also indicate that groundwater from the Mill has not substantially affected Many Devils Wash in the past. Upwelling from deep aquifers was also determined to be an unlikely source, primarily by comparing the composition of the stable isotopes of water in the shallow groundwater with those reported in groundwater samples from the deeper aquifers. The stable-isotope compositions of the shallow groundwater around the site are enriched relative to the San Juan River and local meteoric lines, which suggests that most of the shallow groundwater has been influenced by evaporation and therefore was recharged at the surface. Several observations indicate that focused recharge is the likely source of groundwater in the area of Many Devils Wash. The visible erosional features in Many Devils Wash provide evidence of piping and groundwater sapping, and the distribution and type of vegetation in Many Devils Wash suggest that the focused recharge of precipitation is occurring. The estimated recharge from precipitation was calculated to be 0.0008 inches per year (in/yr) by using the mass-balance approach from reported seep discharge and 0.0011 in/yr using the chloride mass-balance approach. A conceptual model of groundwater quality beneath Many Devils Wash is presented to explain the source of solutes in the groundwater beneath Many Devils Wash. The major-ion concentrations and geochemical evolution in the groundwater beneath Many Devils Wash and across the study area support the conceptual model that the underlying Mancos Shale is the source of solutes. Differences in the major-ion composition between groundwater samples collected around the site, result from the degree of weathering to the Mancos Shale. The cation distribution appears to be an indicator of effects from the Mill, with samples from the Mill-affected wells largely having a calcium/magnesium-sulfate composition that resembles the reported compositions of more weathered shale; however, that composition could change if the Mill-processed water flowed into areas where the Mancos Shale was less weathered. On the basis of the widespread presence of uranium in the Mancos Shale and the distribution of aqueous uranium in the analog sites and other sites in the region, it appears likely that uranium in the groundwater of Many Devils Wash is naturally sourced from the Mancos Shale.

New Mexico↗
USGS2025

Development of a genotyping-in-thousands by sequencing (GT-seq) panel for identifying individuals and estimating relatedness among Alaska black bears (Ursus americanus)

The management and conservation of large mammals, such as black bears ( Ursus americanus ), have long been informed by genetic estimates of population size and individual dispersal. Amplicon sequencing methods, also known as ‘genotyping-in-thousands-by sequencing’ (GT-seq), now enable the efficient and cost-effective genotyping of hundreds of loci and individuals in the same sequencing run. Here, we develop a GT-seq panel for individual identification and kinship inference in Alaska black bears. Using genomic data from restriction site-associated DNA sequencing of hunter-harvested bears from Southcentral Alaska ( n = 85), we identified 170 microhaplotype and single nucleotide polymorphism (SNP) loci that were highly heterozygous in local populations. To enable sexing of individuals, we also included a previously published sex-linked locus in the GT-seq panel. We empirically validated the GT-seq panel using samples collected at different spatial scales. These samples included tissues ( n = 82) obtained from bears within a small geographic area in Anchorage, Alaska, which were likely to be relatives as well as the hunter-harvested samples collected from geographically widespread locations throughout Southcentral Alaska. Empirical validation indicated high genotyping success and genotype reproducibility across replicate subsamples. Computer simulations demonstrated that the GT-seq panel had ample statistical power for distinguishing distinct individuals and first-order relatives (parent-offspring and full-sibling pairs) from unrelated individuals. As a final proof of concept, the panel was used to identify individual bears and close kin sampled from urban and wild habitats in Anchorage, Alaska. We anticipate that the GT-seq panel will be a useful genomic resource for the monitoring and management of Alaska black bear populations. ons.

Alaska↗
USGS2014

Accounting for tagging-to-harvest mortality in a Brownie tag-recovery model by incorporating radio-telemetry data

The Brownie tag-recovery model is useful for estimating harvest rates but assumes all tagged individuals survive to the first hunting season; otherwise, mortality between time of tagging and the hunting season will cause the Brownie estimator to be negatively biased. Alternatively, fitting animals with radio transmitters can be used to accurately estimate harvest rate but may be more costly. We developed a joint model to estimate harvest and annual survival rates that combines known-fate data from animals fitted with transmitters to estimate the probability of surviving the period from capture to the first hunting season, and data from reward-tagged animals in a Brownie tag-recovery model. We evaluated bias and precision of the joint estimator, and how to optimally allocate effort between animals fitted with radio transmitters and inexpensive ear tags or leg bands. Tagging-to-harvest survival rates from >20 individuals with radio transmitters combined with 50&ndash;100 reward tags resulted in an unbiased and precise estimator of harvest rates. In addition, the joint model can test whether transmitters affect an individual's probability of being harvested. We illustrate application of the model using data from wild turkey, Meleagris gallapavo, to estimate harvest rates, and data from white-tailed deer, Odocoileus virginianus, to evaluate whether the presence of a visible radio transmitter is related to the probability of a deer being harvested. The joint known-fate tag-recovery model eliminates the requirement to capture and mark animals immediately prior to the hunting season to obtain accurate and precise estimates of harvest rate. In addition, the joint model can assess whether marking animals with radio transmitters affects the individual's probability of being harvested, caused by hunter selectivity or changes in a marked animal's behavior.

Ecology and Evolution↗
USGS2024

Behavioral trade-offs and multitasking by elk in relation to predation risk from Mexican gray wolves

Predator non-consumptive effects (NCE) can alter prey foraging time and habitat use, potentially reducing fitness. Prey can mitigate NCEs by increasing vigilance, chewing-vigilance synchronization, and spatiotemporal avoidance of predators. We quantified the relationship between Mexican wolf ( Canis lupus baileyi ) predation risk and elk ( Cervus canadensis ) behavior. We conducted behavioral observations on adult female elk and developed predation risk indices using GPS collar data from Mexican wolves, locations of elk killed by wolves, and landscape covariates. We compared a priori models to determine the best predictors of adult female behavior and multitasking. Metrics that quantified both spatial and temporal predation risk were the most predictive. Vigilance was positively associated with increased predation risk. The effect of predation risk on foraging and resting differed across diurnal periods. During midday when wolf activity was lower, the probability of foraging increased while resting decreased in high-risk areas. During crepuscular periods when elk and wolves were most active, increased predation risk was associated with increased vigilance and slight decreases in foraging. Our results suggest elk are temporally avoiding predation risk from Mexican wolves by trading resting for foraging, a trade-off often not evaluated in behavioral studies. Probability of multitasking depended on canopy openness and an interaction between maternal period and predation risk; multitasking decreased prior to parturition and increased post parturition in high-risk areas. Openness was inversely related to multitasking. These results suggest adult female elk are altering the type of vigilance used depending on resource availability/quality, current energetic needs, and predation risk. Our results highlight potentially important, but often-excluded behaviors and trade-offs prey species may use to reduce the indirect effects of predation and contribute additional context to our understanding of predator–prey dynamics.

Ecology and Evolution↗
USGS2016

A Bayesian approach for temporally scaling climate for modeling ecological systems

With climate change becoming more of concern, many ecologists are including climate variables in their system and statistical models. The Standardized Precipitation Evapotranspiration Index (SPEI) is a drought index that has potential advantages in modeling ecological response variables, including a flexible computation of the index over different timescales. However, little development has been made in terms of the choice of timescale for SPEI. We developed a Bayesian modeling approach for estimating the timescale for SPEI and demonstrated its use in modeling wetland hydrologic dynamics in two different eras (i.e., historical [pre-1970] and contemporary [post-2003]). Our goal was to determine whether differences in climate between the two eras could explain changes in the amount of water in wetlands. Our results showed that wetland water surface areas tended to be larger in wetter conditions, but also changed less in response to climate fluctuations in the contemporary era. We also found that the average timescale parameter was greater in the historical period, compared with the contemporary period. We were not able to determine whether this shift in timescale was due to a change in the timing of wet&ndash;dry periods or whether it was due to changes in the way wetlands responded to climate. Our results suggest that perhaps some interaction between climate and hydrologic response may be at work, and further analysis is needed to determine which has a stronger influence. Despite this, we suggest that our modeling approach enabled us to estimate the relevant timescale for SPEI and make inferences from those estimates. Likewise, our approach provides a mechanism for using prior information with future data to assess whether these patterns may continue over time. We suggest that ecologists consider using temporally scalable climate indices in conjunction with Bayesian analysis for assessing the role of climate in ecological systems.

Ecology and Evolution↗
USGS2015

Mesozoic magmatism and timing of epigenetic Pb-Zn-Ag mineralization in the western Fortymile mining district, east-central Alaska: Zircon U-Pb geochronology, whole-rock geochemistry, and Pb isotopes

The Mesozoic magmatic history of the North American margin records the evolution from a more segmented assemblage of parautochthonous and allochthonous terranes to the more cohesive northern Cordilleran orogenic belt. We characterize the setting of magmatism, tectonism, and epigenetic mineralization in the western Fortymile mining district, east-central Alaska, where parautochthonous and allochthonous Paleozoic tectonic assemblages are juxtaposed, using sensitive high-resolution ion microprobe (SHRIMP) U-Pb zircon geochronology, whole-rock geochemistry, and feldspar Pb isotopes of Mesozoic intrusions and spatially associated mineral prospects. New SHRIMP U-Pb zircon ages and published U-Pb and 40 Ar/ 39 Ar ages indicate four episodes of plutonism in the western Fortymile district: Late Triassic (216-208 Ma), Early Jurassic (199-181 Ma), mid-Cretaceous (112-94 Ma), and Late Cretaceous (70-66 Ma). All age groups have calc-alkalic arc compositions that became more evolved through time. Pb isotope compositions of feldspars from Late Triassic, Early Jurassic, and Late Cretaceous igneous rocks similarly became more radiogenic with time and are consistent with the magmas being mantle derived but extensively contaminated by upper crustal components with evolving Pb isotopic compositions. Feldspar Pb isotopes from mid-Cretaceous rocks have isotopic ratios that indicate magma derivation from upper crustal sources, probably thickened mid-Paleozoic basement. The origin of the mantle component in Late Cretaceous granitoids suggested by Pb isotopic ratios is uncertain, but we propose that it reflects asthenospheric upwelling following slab breakoff and sinking of an inactive inner subduction zone that delivered the previously accreted Wrangellia composite terrane to the North American continental margin, after the outer Farallon subduction zone was established. Epigenetic Pb-Zn-Ag &plusmn; Cu prospects in the western Fortymile district are spatially associated with splays of the northeast-trending Kechumstuk sinistral-normal fault zone and with ca. 68-66 Ma felsic intrusions and dikes. The similarity between Pb isotope compositions of feldspars from the Late Cretaceous igneous bodies and sulfides from the epithermal prospects suggests a Late Cretaceous age for most of the mineralization. Fluid flow along the faults undoubtedly played a major role in mineralization. We interpret displacement on the northeast-trending faults to be a far-field effect of dextral translation along Late Cretaceous plate-scale boundaries and faults that were roughly parallel to the subsequently developed Denali and Tintina fault systems, which currently bound the region.

Alaska↗
USGS2015

Integrated survival analysis using an event-time approach in a Bayesian framework

Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (&le; 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at <5 days old and were lower for chicks with larger birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.

Ecology and Evolution↗
USGS2021

Nine-banded armadillo (Dasyrus novemcinctus) activity patterns are influenced by human activity

As the human footprint upon the landscape expands, wildlife seeking to avoid human contact are losing the option of altering their spatial distribution and instead are shifting their daily activity patterns to be active at different times than humans. In this study, we used game cameras to evaluate how human development and activity were related to the daily activity patterns of the nine-banded armadillo ( Dasypus novemcinctus) along an urban to rural gradient in Arkansas, USA during the winter of 2020–2021. We found that armadillos had substantial behavioral plasticity in regard to the timing of their activity patterns; >95% of armadillo activity was nocturnal at six of the study sites, whereas between 30% and 60% of activity occurred during the day at three other sites. The likelihood of diurnal armadillo activity was best explained by the distance to downtown Fayetteville (the nearest population center) and estimated ambient sound level (both indices of human activity) with armadillos being most active during the day at quiet sites far from Fayetteville. Furthermore, armadillo activity occurred later during the night period (minutes after sunset) at sites near downtown and with higher anthropogenic sound. Anecdotal evidence suggests that the observed activity shift may be in response to not only human activity but also the presence of domestic dogs. Our results provide further evidence that human activity has subtle nonlethal impacts on even common, widespread wildlife species. Because armadillos have low body temperatures and basal metabolism, being active during cold winter nights likely has measurable fitness costs. Nature reserves near human population centers may not serve as safe harbors for wildlife as we intend, and managers could benefit from considering these nonlethal responses in how they manage recreation and visitation in these natural areas.

Arkansas↗
USGS2025

Development of PCR blocking primers enabling DNA metabarcoding analysis of dietary composition in hematophagous sea lamprey

Conventional dietary assessments are challenging in hematophagous species, particularly in sea lamprey ( Petromyzon marinus ). However, recent technological developments and molecular approaches have provided an attractive alternative through the use of DNA metabarcoding. While DNA metabarcoding has been used for dietary analyses in numerous species, including lampreys, applications of universal primers that detect a diverse set of prey items can be limited by the amplification of predator DNA. In this study, we designed and tested eight blocking primers designed to suppress the amplification of sea lamprey DNA with vertebrate-universal primers targeting the mitochondrial 12S rRNA gene. This approach allowed for the use of a single marker to amplify a taxonomically diverse suite of host species, in contrast to previous studies that used multiple taxon-specific primer pairs (e.g., Salmonidae, Cyprinidae, and Catostomidae). Candidate blocking primers evaluated in this study differed in base pair length, end sequence modification, and purification method. Samples with different sea lamprey-to-host DNA ratios were subjected to multiple detection methods including gel electrophoresis, quantitative PCR, and DNA metabarcoding to assess the ability of each blocking primer to selectively suppress amplification of the sea lamprey 12S gene region. All blocking primers tested performed well and demonstrated high effectiveness, suppressing sea lamprey reads by > 99.9% in mock communities and improving host DNA sequence recovery across various sample types, including wild-caught lamprey. Results show that the blocking primers evaluated can facilitate molecular diet analysis in sea lamprey, allowing the amplification of a taxonomically diverse range of host fish species with universal primers.

Great Lakes↗
USGS2022

Foraging habitat selection of shrubland bird community in tropical dry forest

Habitat loss due to increasing anthropogenic disturbance is the major driver for bird population declines across the globe. Within the Eastern Ghats of India, shrubland bird communities are threatened by shrinking of suitable habitats due to increased anthropogenic disturbance and climate change. The development of an effective habitat management strategy is hampered by the absence of data for this bird community. To address this knowledge gap, we examined foraging sites for 14 shrubland bird species, including three declining species, in three study areas representing the shrubland type of forest community in the Eastern Ghats. We recorded microhabitat features within an 11 m radius of observed foraging points and compared these data with similar data from random plots. We used chi-square to test the association between plant species and bird species for sites where they were observed foraging. We observed significant differences between foraging sites of all the study species and random plots, thus indicating selection for foraging habitat. Using linear discriminant analysis, we found that the microhabitat features important for the bird species were shrub density, vegetational height, vertical foliage stratification, grass height, and percent rock cover. Our results show that diet guild and foraging strata influence the foraging microhabitat selection of a species (e.g., ground-foraging species differed significantly from other species). Except for two species, all focal birds were associated with at least one plant species. The plant-bird association was based on foraging, structural, or behavioral preferences. Several key factors affecting foraging habitat such as shrub density can be actively managed at the local scale. Strategic and selective harvesting of forest products and a spatially and temporally controlled livestock grazing regime may allow regeneration of scrubland and create conditions favorable to birds.

Andhra Pradesh↗
USGS2022

Know what you don't know: Embracing state uncertainty in disease-structured multistate models

Hidden Markov models (HMMs) are broadly applicable hierarchical models that derive their utility from separating state processes from observation processes yielding the data. Multistate models such as mark–recapture and dynamic multistate occupancy models are HMMs frequently used in ecology. In their early formulations, states, such as pathogen infection status, were assumed to be perfectly observed without ambiguity. However, state uncertainty is a pervasive feature of many ecological studies, and multievent models were developed to explicitly account for it. We developed a novel extended multievent mark–recapture model that incorporates state uncertainty at multiple levels of detection. Using a disease-structured example, both false negative and false positive state assignment errors are modelled at two levels of state assignment—the pathogen sampling process and the diagnostic process that samples are subjected to. We additionally describe methods to jointly model infection intensity to integrate heterogeneity in ecological parameters, such as mortality and infection dynamics, and the pathogen detection processes. We provide code to simulate and analyse datasets with various underlying ecological processes and fit our model to a mark–recapture dataset of Mixophyes fleayi (Fleay's barred frog) infected with the amphibian chytrid fungus ( Batrachochytrium dendrobatidis , Bd ). In our case study, we found evidence for various state assignment errors: the sampling protocol performed poorly in detecting Bd , pathogen detection was highly dependent on infection intensity and false positives were non-negligible. Incorporating state uncertainty yielded significantly higher estimates of infection prevalence and 4–5 times lower rates of infection state transitions compared to those obtained from a traditional multistate model. Our results highlight that incorporating state assignment errors improves inference on the ecological process, especially when sensitivity and specificity of the state assignment processes are low. The general model structure can be applied to other HMMs, providing a foundation for modelling state uncertainty in related models. For disease-structured multistate models, we recommend conducting robust design surveys and collecting samples during each capture event to facilitate incorporating pathogen detection errors.

Methods in Ecology and Evolution↗
USGS2007

Heavy-mineral provenance in an estuarine environment, Willapa Bay, Washington, USA: palaeogeographic implications and estuarine evolution

Modern sediments from representative localities in Willapa Bay, Washington, comprise two principal heavy-mineral suites. One contains approximately equivalent amounts of hornblende, orthopyroxene, and clinopyroxene; this is derived from the Columbia River, which discharges into the Pacific Ocean a short distance south of the bay. The other suite, dominated by clinopyroxene, is restricted to sands of rivers flowing into the bay from the east. The heavy-mineral distributions within the bay suggest that sand discharged from the Columbia River, borne north by longshore transport and carried into the bay by tidal currents, accounts for nearly all of the sand within the interior of Willapa Bay today. Pleistocene deposits on the east side of the bay contain three heavy-mineral assemblages, two of which are identical to the modern assemblages described above. These assemblages reflect the relative influence of tidal and fluvial processes on the Late Pleistocene deposits (100,000–200,000 BP. Amino acid racemization in Quaternary shell deposits at Willapa Bay, Washington. Geochimica et Cosmochimica Acta 43, 1505–1520). They are also consistent with those processes inferred on the basis of sedimentary structures and stratigraphic relations in about two-thirds of the samples examined. Anomalies can be explained by recycling of sand from older deposits. The persistence of the two heavy-mineral suites suggests that the pattern of estuarine sedimentation in Late Pleistocene deposits closely resembled that of the modern bay. The third heavy-mineral suite is enriched in epidote and occurs in a few older Pleistocene units. On the north side of the bay, the association of this suite with southwest-directed foresets in cross-bedded gravel indicates derivation from the northeast, perhaps from an area of glacial outwash. The presence of this suite in ancient estuarine sands exposed on the northeast side of the bay suggests that input from this northerly source may have intermittently dominated Willapa Bay deposition in the past.

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