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At least 721 records · Page 40Linked to original sources
USGS2020

Development of genetic baseline information to support the conservation and management of wild Brook Trout in North Carolina

Following centuries of declines, there is growing interest in conserving extant wild populations and reintroducing Brook Trout ( Salvelinus fontinalis ) populations of native ancestry. A population genetic baseline can enhance conservation outcomes and promote restoration success. Consequently, it is important to document existing patterns of genetic variation across the landscape and translate these data into an approachable format for fisheries managers. We genotyped 9,507 Brook Trout representing 467 wild collections at 12 microsatellite loci to establish a genetic baseline for North Carolina, USA. Rarefied allelic richness and observed heterozygosity, which reflect within‐population diversity, were low to moderate relative to levels typically observed at higher latitudes (means = 3.12 and 0.42, respectively). Effective population sizes varied widely, but were often very low (151 collections with an estimated N e < 10). Despite decades of intensive stocking across the state, we found little to no evidence of hatchery introgression in most populations. Although genetic variation was significant at a variety of spatial scales (mean pairwise F ’ ST = 0.73), substantial genetic variation occurred between patches within individual watersheds. Analysis of molecular variance (AMOVA) found that a substantial portion (28.5%) of the observed genetic variation was attributed to differences among populations, with additional genetic variation among hydrological units (HUCs; 16.0%, 16.6%, 12.1%, and 9.4% of the overall variation among twelve‐, ten‐, eight‐, and six‐digit HUCs, respectively). We discuss a suite of potential applications for this type of genetic data to enhance management outcomes, such as conservation prioritization and selection of source stocks for reintroductions or genetic rescue.

North Carolina↗
USGS2022

Informing management of Henrys Lake, Idaho using an integrated catch-at-age model

Henrys Lake, Idaho, supports a popular fishery for Yellowstone Cutthroat Trout Oncorhynchus clarkii bouvieri and Yellowstone Cutthroat Trout × Rainbow Trout O. mykiss hybrids. A majority of the adult population of fish in Henrys Lake are of hatchery origin that were stocked as fingerlings. The fishery is closed to angling during the late winter and spring months, but fisheries managers are considering opening the fishery year-round with catch-and-release-only regulations or with a two-fish bag limit during the extended season. However, there is concern that the proposed management actions may negatively affect the current fishery. Therefore, we developed an integrated catch-at-age model to estimate population parameters for trout in Henrys Lake and used a simulation model to evaluate alternative management actions. Results of this study suggest that catch and release of both Yellowstone Cutthroat Trout and hybrids would increase and that abundance of trout in the spring (i.e., the start of the traditional season) would decrease under both proposed bag limits. Losses in abundance can be mitigated by stocking additional fish as long as no more than approximately 1,520,000 Yellowstone Cutthroat Trout are stocked annually. If catch-and-release-only regulations are implemented during the newly proposed season, total harvest is expected to decrease compared to the current fishery due to additional catch-and-release mortality. Ultimately, managers will need to prioritize harvest or catch-and-release opportunity, both of which provide additional utility to anglers, when choosing how to proceed with bag limit regulations.

Idaho↗
USGS2019

UAV-derived estimates of forest structure to inform ponderosa pine forest restoration

Restoring forest ecosystems has become an increasingly high priority for land managers across the American West. Millions of hectares of forest are in need of drastic yet strategic reductions in density (e.g., basal area). Meeting the restoration and management goals requires quantifying metrics of vertical and horizontal forest structure, which has relied upon field‐based measurements, manned airborne or satellite remote sensing datasets. We used unmanned aerial vehicle (UAV ) image‐derived Structure‐from‐Motion (SfM) models and high‐resolution multispectral orthoimagery in this study to quantify vertical and horizontal forest structure at both the fine‐ (<4 ha) and mid‐scales (4–400 ha) across a forest density gradient. We then used these forest structure estimates to assess specific objectives of a forest restoration treatment. At the fine‐scale, we found that estimates of individual tree height and canopy diameter were most accurate in low‐density conditions, with accuracies degrading significantly in high‐density conditions. Mid‐scale estimates of canopy cover and forest density followed a similar pattern across the density gradient, demonstrating the effectiveness of UAV image‐derived estimates in low‐ to medium‐density conditions as well as the challenges associated with high‐density conditions. We found that post‐treatment conditions met a majority of the prescription objectives and demonstrate the UAV image application in quantifying changes from a mechanical thinning treatment. We provide a novel approach to forest restoration monitoring using UAV ‐derived data, one that considers varying density conditions and spatial scales. Future research should consider a more spatially extensive sampling design, including different restoration treatments, as well as experimenting with different combinations of equipment, flight parameters, and data processing workflows.

Western United States↗
USGS2018

Acoustic telemetry and benthic habitat mapping inform the spatial ecology of Shortnose Sturgeon in the Hudson River, New York, USA

A history of overexploitation and industrialization of riverine habitats has impacted the Shortnose Sturgeon Acipenser brevirostrum , leading this species to become one of the earliest listed under the U.S. Endangered Species Act. The present understanding of Shortnose Sturgeon spatial ecology is based on observations from a limited number of Atlantic coastal rivers. To better understand Shortnose Sturgeon in the Hudson River, New York, we used acoustic telemetry to characterize seasonal habitat use and to identify regions of the river where seasonal sturgeon activity occurred. From 2012 to 2016, 101 adult fish were tagged and tracked, and sturgeon detections per unit effort (a metric of fish observation standardized by search effort) were evaluated against benthic habitat variables by using generalized additive regression models. Models indicated strong habitat associations in the spring season defined by gravel-dominated substrates and specific depth ranges, presumably associated with spawning activity. During summer, Shortnose Sturgeon were more dispersed, associating with muddy habitats, whereas in fall/winter, sturgeon congregated in specific regions of the river. These data demonstrate that river use and habitat associations vary seasonally and identify important areas for managing overlap between seasonal habitat use by Shortnose Sturgeon and human activity on the river.

New York↗
USGS2023

Survey optimization for invasive Burmese pythons informed by camera traps

The Burmese python ( Python bivittatus ) is an invasive predator responsible for broad mammal declines in South Florida, United States. Despite their large size, pythons remain cryptic and require multifaceted approaches for detection. We evaluated a novel technique by deploying camera traps at known locations of radiotagged pythons in the Florida Keys. We estimated daily detection probabilities of snakes and plotted diel activity patterns. Our results suggest camera traps can effectively survey pythons but seasonality and camera trigger mechanisms affect utility. Pythons were most detectable with time-lapse camera traps and more detectable in winter. The diel activity pattern of pythons peaked midday through early afternoon, indicating an optimal survey time for other search methods. Artificial intelligence can alleviate photo volume, so we recommend a combination of motion detection and time-lapse with shorter time (1 min) intervals for python-specific surveys and where camera traps are deployed to monitor mammals to improve passive python detection.

Florida↗
USGS2019

Informing sea turtle outreach efforts to maximize effectiveness

Most sea turtle (Cheloniidae) species worldwide are endangered or threatened, with threats causing harm to sea turtles predominantly human‐induced. Thus, prevention of further declines to these imperiled species will require alteration of human behaviors. Regulations, incentives, and environmental education are 3 strategies that could be used to alter human behavior. Our goal was to determine how to maximize effectiveness of one of these strategies—education efforts. We investigated knowledge deficiencies and light pollution behaviors of individuals living in a region with nesting sea turtles, in an effort to determine the best approach to promote sea turtle conservation. During 2014, we mailed a survey to 3,000 property owners in 4 coastal counties in Florida, USA, to achieve 3 objectives: assess what topic areas were misunderstood; discern who had knowledge deficiencies; and determine who had adopted turtle‐friendly lighting practices. The best predictors of knowledge included geographic factors (county, proximity of residences to the beach), demographic characteristics (age), and behaviors (individual's beach visitation rates). One practice that can reduce harm to sea turtles was common: use of window treatments to reduce light pollution. However, other practices harmful to sea turtles were prevalent, including long durations of use of outdoor lighting and use of light bulbs with wavelengths that can disturb sea turtles. Our results suggest that educational efforts could be enhanced by specifically focusing on increasing awareness of the effects of human actions on sea turtles, targeting individuals who visit the beach infrequently and live far from it to foster greater connection with these ecosystems, and publicizing a variety of options that could reduce harm to sea turtles so individuals feel a sense of freedom of choice.

Florida↗
USGS2025

Informing adaptive management to reduce ungulate aggregations: A case study involving winter feeding of elk

In the United States, wildlife managers are entrusted with preserving culturally and economically important ungulate populations in the face of the ongoing spread of chronic wasting disease (CWD). The U.S. Fish and Wildlife Service established an adaptive management plan to reduce the reliance of elk ( Cervus canadensis ) on supplemental winter feeding on the National Elk Refuge. The end goal of reducing the unnaturally high aggregation of elk during the winter is to mitigate the threat of disease outbreaks and to meet the objectives of sustainable populations of elk on the refuge. In this case study, we evaluated 6 years (2017–2022) of data from GPS-collared elk to determine the efficacy of shortening the length of the annual feeding period on the refuge to reduce elk aggregation. We measured aggregation using proximity rates, based on pairwise interactions over time, in both raw form as an index as well as predicted proximity as a function of other abiotic influences. We created a new R package, wildagg , to help with the process of computing the metrics from our study and to increase reproducibility in the future. Aggregation declined in years with less feeding on the refuge according to raw aggregation metrics when examined in isolation and dependent on the baseline feeding year used for comparison. However, accounting for abiotic factors while modeling proximity rates suggested in some years the decision to shorten the feeding period had less influence on aggregation than predicted. Our results underscore the complexity of measuring management outcomes and the usefulness of multiple approaches to evaluation.

Wyoming↗
USGS2025

Causal networks to inform decisions for ecological restoration

The release of contaminants into the environment can occur from anthropogenic activities, such as oil extraction and transportation, mining, and industrial processes. Remediation associated with reducing contaminant concentrations, and restoration that improves animals and supporting habitat, are often needed to restore ecosystems to their pre-release, baseline condition. We demonstrated the application of Bayesian Decision Networks (BDNs) with two Natural Resource Damage Assessment and Restoration (NRDAR) case studies. We use a stylized case study of riparian restoration following the remediation of a mine-impacted site to evaluate proposed restoration actions aimed at restoring Song Sparrow ( Melospiza melodia ) populations to baseline conditions. We then use a settled NRDAR case with implemented restoration in the Upper Arkansas River (UAR, Colorado, USA) to demonstrate the application of BDNs to evaluate and forecast restoration effectiveness for Brown Trout ( Salmo trutta ) (i.e., restoration effectiveness assessment). The riparian restoration model showed differences in the effects of restoration actions on Song Sparrow populations, with the time to reach baseline generally reduced with increased restoration costs, indicating trade-offs between costs and expected recovery. The UAR model showed recovery of Brown Trout populations (i.e., uplift) in response to improved instream habitat restoration, along with forecasted improvements. While the BDNs we developed were specific to two case studies, the structure is adaptable to a diversity of sites, resources, and actions. We suggest that causal network modeling can provide restoration practitioners with a decision advisory tool useful for a wide range of projects.

Environmental Management↗
USGS2011

Data logging of body temperatures provides precise information on phenology of reproductive events in a free-living arctic hibernator

Precise measures of phenology are critical to understanding how animals organize their annual cycles and how individuals and populations respond to climate-induced changes in physical and ecological stressors. We show that patterns of core body temperature ( T b ) can be used to precisely determine the timing of key seasonal events including hibernation, mating and parturition, and immergence and emergence from the hibernacula in free-living arctic ground squirrels ( Urocitellus parryii ). Using temperature loggers that recorded T b every 20 min for up to 18 months, we monitored core T b from three females that subsequently gave birth in captivity and from 66 female and 57 male ground squirrels free-living in the northern foothills of the Brooks Range Alaska. In addition, dates of emergence from hibernation were visually confirmed for four free-living male squirrels. Average T b in captive females decreased by 0.5–1.0°C during gestation and abruptly increased by 1–1.5°C on the day of parturition. In free-living females, similar shifts in T b were observed in 78% ( n = 9) of yearlings and 94% ( n = 31) of adults; females without the shift are assumed not to have given birth. Three of four ground squirrels for which dates of emergence from hibernation were visually confirmed did not exhibit obvious diurnal rhythms in T b until they first emerged onto the surface when T b patterns became diurnal. In free-living males undergoing reproductive maturation, this pre-emergence euthermic interval averaged 20.4 days ( n = 56). T b -loggers represent a cost-effective and logistically feasible method to precisely investigate the phenology of reproduction and hibernation in ground squirrels.

Journal of Comparative Physiology B: Biochemical, ↗
USGS2023

Linked foraging and bioenergetics modeling may inform fish parasite infection dynamics

The parasitic copepod Salmincola californiensis infects Pacific salmon and trout ( Oncorhynchus spp.) and often reaches high prevalence and intensity in reservoirs compared to stream systems. Recent research indicates that temperature plays a fundamental role in copepod development and fish susceptibility. Here, we expand a linked foraging and bioenergetics model to simulate infection risk. Based on juvenile salmon vertical migration patterns, we add estimates of copepod generations produced and thermal strata metrics that appear associated with copepodid aggregations and increased infection. Severe damage on hosts may be caused by the infectious copepodid, a life-stage not readily visible and thus not detectable using traditional fish screenings. We discuss model limitations, opportunities for future research, and the potential for inclusion of copepod expansion equations to existing linked bioenergetics models or observed behaviors of salmonids in other lentic systems. We demonstrate that using a temperature sensitive model framework that includes copepod infection dynamics is useful in interpreting other lines of evidence, such as fish mortality estimates. Collectively, our work provides a testable framework for future comparisons of infection potential and demonstrates how bioenergetics models may be useful in understanding host–parasite interactions.

Environmental Biology of Fishes↗
USGS2020

Climate- and disturbance-driven changes in subsistence berries in coastal Alaska: Indigenous knowledge to inform ecological inference

Berry-producing plants are a key subsistence resource in Indigenous Alaskan communities. High-latitude coastal regions are particularly impacted by global climate change due to their location at the land-sea ecotone subjecting them to terrestrial stressors as well as shifts in ocean dynamics. While vegetation changes have been documented for the subarctic coastal region of Alaska, we know little about permafrost underlain portions of the landscape that support berry communities. To fill this gap surveys were administered in four communities within the Yukon-Kuskokwim Delta, to identify observations of changes in berry resources and integrate Indigenous Knowledge of drivers of changes with climate projections. We found that while most participants agreed on several observed changes and drivers, many important differences were identified at the community level. Regional consensus can be used in combination with climate projections to forecast potential future impacts to berry resources while distinctions at the community level can help us to untangle local scale disturbances.

Alaska↗
USGS2014

Reduced population variance in strontium isotope values informs domesticated turkey use at Chaco Canyon, New Mexico, USA

Traditionally strontium isotopes (87Sr/86Sr) have been used as a sourcing tool in numerous archaeological artifact classes. The research presented here demonstrates that 87Sr/86Srbioapatite ratios also can be used at a population level to investigate the presence of domesticated animals and methods of management. The proposed methodology combines ecology, isotope geochemistry, and behavioral ecology to assess the presence and nature of turkey (Meleagris gallopavo) domestication. This case study utilizes 87Sr/86Srbioapatite ratios from teeth and bones of archaeological turkey, deer (Odocoileus sp.), lagomorph (Lepus sp. and Sylvilagus sp.), and prairie-dog (Cynomys sp.) from Chaco Canyon, New Mexico, U.S.A. (ca. A.D. 800 – 1250). Wild deer and turkey from the southwestern U.S.A. have much larger home ranges and dispersal behaviors (measured in kilometers) when compared to lagomorphs and prairie dogs (measured in meters). Hunted deer and wild turkey from archaeological contexts at Chaco Canyon are expected to have a higher variance in their 87Sr/86Srbioapatite ratios, when compared to small range taxa (lagomorphs and prairie dogs). Contrary to this expectation, 87Sr/86Srbioapatite values of turkey bones from Chacoan assemblages have a much lower variance than deer and are similar to that of smaller mammals. The sampled turkey values show variability most similar to lagomorphs and prairie dogs, suggesting the turkeys from Chaco Canyon were consuming a uniform diet and/or were constrained within a limited home range, indicating at least proto-domestication. The population approach has wide applicability for evaluating the presence and nature of domestication when combined with paleoecology and behavioral ecology in a variety of animals and environments.

New Mexico↗
USGS2021

How well do proxy species models inform conservation of surrogate species?

Context Proxy species, which represent suites of organisms with similar habitat requirements, are common in conservation. Landscape Capability (LC) models aim to quantify the spatially-explicit capability of landscapes to support proxy species that represent suites of forest birds. Objectives We evaluated the North Atlantic Landscape Conservation Cooperative (NALCC) proxy models of LC and represented species framework across 13 states in the northeastern United States from Virginia to Maine. We validated a suite of questions related to co-occurrence of proxy and represented species with a compilation of independent datasets. Methods We tested proxy species LC models ability to explain represented species’ occurrences, including using multiple proxies together, and benchmarked against empirical data and land cover type classifications. We tested effect of several factors on predictive ability including relative range overlap and ecological and taxonomic dissimilarity between proxy and represented species. Results LC models performed variably, but represented species occurrences were rarely predicted as accurately as proxy species. Models improved predictions over macrohabitat classifications. Using multiple proxies together occasionally improved predictions of represented species. Considerable range overlap was needed for models to be predictive of represented species. Ecological and taxonomic similarity had no effect on predictive ability. LC models worked similarly to using empirical observations, suggesting shortcomings were because of imperfect surrogacy. Conclusions Conservation proxies as representatives of species groups that are associated with macrohabitats are useful, but empirical data are necessary to evaluate proxy species’ effectiveness. Habitat-based models can provide similar predictive ability as empirical observations of proxies and represent a useful tool in conservation planning.

Landscape Ecology↗
USGS2022

Lacunarity as a tool for assessing landscape configuration over time and informing long-term monitoring: An example using seagrass

Context Seagrasses are submerged marine plants that have been declining globally at increasing rates. Natural resource managers rely on monitoring programs to detect and understand changes in these ecosystems. Technological advancements are allowing for the development of patch-level seagrass maps, which can be used to explore seagrass meadow spatial patterns. Objectives Our research questions involved comparing lacunarity, a measure of landscape configuration, for seagrass to assess cross-site differences in areal coverage and spatial patterns through time. We also discussed how lacunarity could help natural resource managers with monitoring program development and restoration decisions and evaluation. Methods We assessed lacunarity of seagrass meadows for various box sizes (0.0001 ha to 400.4 ha) around Cat Island and Ship Island, Mississippi (USA). For Cat Island, we used seagrass data from 2011 to 2014. For Ship Island, we used seagrass data for seven dates between 1963 and 2014. Results Cat Island, which had more continuous seagrass meadows, had lower lacunarity (i.e., denser coverage) compared to Ship Island, which had patchier seagrass beds. For Ship Island, we found a signal of disturbance and path toward recovery from Hurricane Camille in 1969. Finally, we highlighted how lacunarity curves could be used as one of multiple considerations for designing monitoring programs, which are commonly used for seagrass monitoring. Conclusions Lacunarity can help quantify spatial pattern dynamics, but more importantly, it can assist with natural resource management by defining fragmentation and potential scales for monitoring. This approach could be applied to other environments, especially other coastal ecosystems.

Mississippi↗
USGS2018

Population vulnerability to tsunami hazards informed by previous and projected disasters: A case study of American Samoa

Population vulnerability from tsunamis is a function of the number and location of individuals in hazard zones and their ability to reach safety before wave arrival. Previous tsunami disasters can provide insight on likely evacuation behavior, but post-disaster assessments have not been used extensively in evacuation modeling. We demonstrate the utility of post-disaster assessments in pedestrian evacuation modeling for tsunami hazards and use the US territory of American Samoa as our case study. We model pedestrian travel times out of tsunami inundation zones recreated for the 2009 M w 8.1 Samoa earthquake, as well as for a probable maximum tsunami zone for future threats. Modeling assumptions are guided by fatality trends and observations of 2009 evacuation behavior, including insights on departure delays, environmental cues, transportation mode, and demographic characteristics. Differences in actual fatalities from the 2009 disaster and modeled population vulnerability suggest that a single set of estimated travel times to safety does not fully characterize evacuation potential of a dispersed, at-risk population. Efforts to prepare coastal communities in American Samoa for future tsunamis may be challenging given substantial differences in wave characteristics and evacuation potential of the probable maximum hazard compared to the 2009 event.

American Samoa↗
USGS2024

Sediment budget of a Maumee River headwater tributary: How streambank erosion, streambed-sediment storage, and streambed-sediment source inform our understanding of legacy phosphorus

Objective We described source and phosphorus (P) retention potential of soft, fine-grained, streambed sediment and associated phosphorus (sed-P) during summer low-flow conditions. Combining in-channel, sed-P storage with relative age provided context on relevance to western Lake Erie Basin management goals. Methods In 2019, rapid geomorphic assessment (30 reaches) compared streambed-sediment storage (S) to streambank erosion (E), providing annual sediment budgets (S:E). Streambed sediment (13 reaches) was fingerprinted and analyzed for sed-P. The P saturation ratio (PSR; four reaches) quantified potential sorption/desorption of dissolved P (DP) between the water column and streambed sediment. Analyses were supplemented with data from 2017 and 2021. The ratio of two fallout radionuclides, beryllium-7 (54-day half-life) and excess lead-210 (22.3 years), apportioned “new” sediment based on time since rainfall contact. Results Streambed sediment was mostly streambank (54–96%) for contributing areas > 2.7 km 2 ; for upstream reaches, a larger percentage was apportioned as upland (cropland, pasture, forest, and road), with < 30% streambank. Streambank erosion correlated with contributing area; however, soil type (ecoregion), stream characteristics, and land use combined to drive streambed-sediment storage. Individual-reach S:E (accumulation of 0.01–35 years of streambank erosion) differentiated erosional and depositional in-channel environments. Most reaches indicated that 17–57% of sediment had recent contact with rainfall. Streambed-sediment PSR indicated a low potential for further sorption of DP from the water column; one reach was a P source when sampled. Conclusion Sed-P was higher in streambed sediment than in source samples, which varied by land use and ecoregion. This indicates homogenization resulting from in-stream sorption of DP during sediment transport that occurs over multiple events.

Indiana, Ohio↗
USGS2019

Can multi-element fingerprinting of soils inform assessments of chemical connectivity between depressional wetlands?

The question of wetland connectivity is particularly relevant regarding depressional wetlands because these wetlands often seem to be “isolated” from other wetlands on a landscape. In this study, multi-element fingerprinting of soils was used to assess similarity in element composition of depressional-wetland soils as a measure of wetland connectivity. We determined the concentrations of 63 elements in the surface soil (top 10 cm) for ten sequences, each consisting of at least one recharge, one flow-through and one discharge depressional wetland in the Prairie Pothole Region of North Dakota. Across all wetlands, soil pH, organic matter content, and electrical conductivity were the most important variables explaining variation in element concentrations. Electrical conductivity and pH significantly increased along a recharge to flow-through to discharge gradient, as did concentrations of As, B, Ca, Co, Hf, Li, Mg, Na, S, Sb, and Sr. Concentrations of Ag, Cd, Cu, P, Pb, Rb, and Se showed the reverse pattern. Similarity-tree analysis revealed that recharge and discharge wetlands clustered in different groups, but that flow-through wetlands were distributed across the spectrum. Our study supports the idea that wetlands in the PPR are chemically connected through surface-water and groundwater flows, and erosional processes, but also behave as independent units within a larger hydrologic landscape.

North Dakota↗