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At least 181 records · Page 10Linked to original sources
USGS1981

Mesurol as a bird repellent on wine grapes in Oregon and California

Field tests were conducted in California and Oregon from July to October 1978 to evaluate the effectiveness of Mesurol as a repellent to reduce bird damage to ripening wine grapes. A block of vines composed of two similar, adjacent plots was delineated at each of 20 vineyards. One randomly chosen plot within each block was treated with up to three applications of Mesurol (75% wettable powder) at a mean rate of 3.1 kg/ha. Damage assessments at harvest showed that the treatment significantly reduced bird damage in both states, but the actual level of bird damage protection provided by the treatment could not be calculated. Based on bird censuses, the primary grape-depredating species in Oregon vineyards was the American robin ( Turdus migratorius ), whereas house finches ( Carpodacus mexicanus ), California quail ( Lophortyx californicus ), goldfinches ( Spinus spp.), and robins were the primary species in California.

American Journal of Enology and Viticulture↗
USGS1977

Use of a hybrid computer in engineering-seismology research

A hybrid computer is an important tool in the seismological research conducted by the U.S. Geological Survey in support of the Energy Research and Development Administration nuclear explosion testing program at the Nevada Test Site and the U.S. Geological Survey Earthquake Hazard Reduction Program. The hybrid computer system, which employs both digital and analog computational techniques, facilitates efficient seismic data processing. Standard data processing operations include: (1) preview of dubbed magnetic tapes of data; (2) correction of data for instrument response; (3) derivation of displacement and acceleration time histories from velocity recordings; (4) extraction of peak-amplitude data; (5) digitization of time histories; (6) rotation of instrumental axes; (7) derivation of response spectra; and (8) derivation of relative transfer functions between recording sites. Catalog of time histories and response spectra of ground motion from nuclear explosions and earthquakes that have been processed by the hybrid computer are used in the Earthquake Hazard Research Program to evaluate the effects of source, propagation path, and site effects on recorded ground motion; to assess seismic risk; to predict system response; and to solve system design problems.

Journal of Research of the U.S. Geological Survey↗
USGS2017

Prediction and visualization of redox conditions in the groundwater of Central Valley, California

Regional-scale, three-dimensional continuous probability models, were constructed for aspects of redox conditions in the groundwater system of the Central Valley, California. These models yield grids depicting the probability that groundwater in a particular location will have dissolved oxygen (DO) concentrations less than selected threshold values representing anoxic groundwater conditions, or will have dissolved manganese (Mn) concentrations greater than selected threshold values representing secondary drinking water-quality contaminant levels (SMCL) and health-based screening levels (HBSL). The probability models were constrained by the alluvial boundary of the Central Valley to a depth of approximately 300 m. Probability distribution grids can be extracted from the 3-D models at any desired depth, and are of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to anoxic conditions. Models were constructed using a Boosted Regression Trees (BRT) machine learning technique that produces many trees as part of an additive model and has the ability to handle many variables, automatically incorporate interactions, and is resistant to collinearity. Machine learning methods for statistical prediction are becoming increasing popular in that they do not require assumptions associated with traditional hypothesis testing. Models were constructed using measured dissolved oxygen and manganese concentrations sampled from 2767 wells within the alluvial boundary of the Central Valley, and over 60 explanatory variables representing regional-scale soil properties, soil chemistry, land use, aquifer textures, and aquifer hydrologic properties. Models were trained on a USGS dataset of 932 wells, and evaluated on an independent hold-out dataset of 1835 wells from the California Division of Drinking Water. We used cross-validation to assess the predictive performance of models of varying complexity, as a basis for selecting final models. Trained models were applied to cross-validation testing data and a separate hold-out dataset to evaluate model predictive performance by emphasizing three model metrics of fit: Kappa; accuracy; and the area under the receiver operator characteristic curve (ROC). The final trained models were used for mapping predictions at discrete depths to a depth of 304.8 m. Trained DO and Mn models had accuracies of 86–100%, Kappa values of 0.69–0.99, and ROC values of 0.92–1.0. Model accuracies for cross-validation testing datasets were 82–95% and ROC values were 0.87–0.91, indicating good predictive performance. Kappas for the cross-validation testing dataset were 0.30–0.69, indicating fair to substantial agreement between testing observations and model predictions. Hold-out data were available for the manganese model only and indicated accuracies of 89–97%, ROC values of 0.73–0.75, and Kappa values of 0.06–0.30. The predictive performance of both the DO and Mn models was reasonable, considering all three of these fit metrics and the low percentages of low-DO and high-Mn events in the data.

California↗
USGS2023

Evaluation of shoreline rotenone application to control Largemouth Bass recruitment in small impoundments

Objective Reducing Largemouth Bass Micropterus salmoides recruitment and therefore population density could benefit recreational fisheries in small impoundments by improving individual growth rates and increasing the average size and condition of Largemouth Bass. To achieve these effects, methods of controlling Largemouth Bass recruitment should avoid reducing the productivity of their primary prey species, the Bluegill Lepomis macrochirus . Methods We tested this hypothesis by evaluating the effects of shoreline rotenone application on the density of Bluegill and the density, growth, and survival of age-0 and age-1 Largemouth Bass in 15 Alabama small impoundments. Result After treatment, Largemouth Bass age-0 densities declined and mean age-1 length increased, whereas Bluegill populations were not significantly reduced. Conclusion Our study indicates that shoreline rotenone application may be a valuable method for reducing Largemouth Bass recruitment and increasing the growth of age-1 Largemouth Bass in small impoundments. However, further research is needed to understand the effects of treatment on nontarget fishes and to better assess the effects of factors such as impoundment surface area and treatment frequency and duration on the ultimate utility of the approach.

Alabama↗
USGS2012

A simulation-based approach for designing effective field-sampling programs to evaluate contamination risk of groundwater supplies

An approach to model discrimination and network design for evaluation of groundwater contamination risk is proposed and demonstrated by application to a site in a glaciofluvial aquifer in Sweden. The approach consists of first hypothesizing alternative conceptual models of hydrogeology at the site on the basis of both quantitative data and qualitative information. The conceptual models are then expressed as two-dimensional numerical models of groundwater flow and solute transport, and model attributes controlling risk to the water supply are determined by simulation. Model predictions of response to a specific field test are made with each model that affects risk. Regions for effective measurement networks are then identified. Effective networks are those that capture sufficient information to determine which of the hypothesized models best describes the system with a minimum of measurement points. For the example site in Sweden, the network is designed such that important system parameters may be accurately estimated at the same time as model discrimination is carried out.

Hydrogeology Journal↗
USGS1993

Effects of harness transmitters on behavior and reproduction of wild mallards

Radio telemetry has been an important research tool in waterfowl studies for >20 years, yet little effort has been made to evaluate potential effects of transmitters on the birds that carry them. As part of a 4-year mallard (Anas platyrhynchos) study in the prairie pothole region of North Dakota and Minnesota, we compared radio-marked and unmarked female mallards in terms of percent time observed feeding, resting, and preening; nest initiation date; and clutch size and egg volume. Radio-marked females carried a 23-g back-mounted transmitter attached with a 2-loop harness (Dwyer 1972). On average, radio-marked females tended to feed less, rest and preen more, initiate nests later, and lay smaller clutches and eggs than unmarked females. Thus, behavioral and reproductive data from ducks marked with back-mounted harness-attached transmitters may be biased. We recommend that new designs of radio packages be field tested and caution that effects may be masked under extreme environmental conditions.

Journal of Wildlife Management↗
USGS2015

Using a Bayesian network to predict barrier island geomorphologic characteristics

Quantifying geomorphic variability of coastal environments is important for understanding and describing the vulnerability of coastal topography, infrastructure, and ecosystems to future storms and sea level rise. Here we use a Bayesian network (BN) to test the importance of multiple interactions between barrier island geomorphic variables. This approach models complex interactions and handles uncertainty, which is intrinsic to future sea level rise, storminess, or anthropogenic processes (e.g., beach nourishment and other forms of coastal management). The BN was developed and tested at Assateague Island, Maryland/Virginia, USA, a barrier island with sufficient geomorphic and temporal variability to evaluate our approach. We tested the ability to predict dune height, beach width, and beach height variables using inputs that included longer-term, larger-scale, or external variables (historical shoreline change rates, distances to inlets, barrier width, mean barrier elevation, and anthropogenic modification). Data sets from three different years spanning nearly a decade sampled substantial temporal variability and serve as a proxy for analysis of future conditions. We show that distinct geomorphic conditions are associated with different long-term shoreline change rates and that the most skillful predictions of dune height, beach width, and beach height depend on including multiple input variables simultaneously. The predictive relationships are robust to variations in the amount of input data and to variations in model complexity. The resulting model can be used to evaluate scenarios related to coastal management plans and/or future scenarios where shoreline change rates may differ from those observed historically.

Maryland and Virginia↗
USGS2008

Evaluation of a nonlethal technique for determining sex of freshwater mussels

The shells of most North American freshwater mussel species are not sexually dimorphic. During the brooding period, gravid females can be identified by inspection of marsupial gills; however, it is difficult to separate nongravid females from males in species lacking sexual dimorphism. The ability to differentiate males from females throughout the year would assist mussel conservation and research. Our objective was to test the accuracy and safety of a method to determine the sex of live mussels. We used a syringe to extract ???0.2 mL of gonadal fluid from 67 Elliptio dilatata and 65 Actinonaias ligamentina. The fluid was stained and examined microscopically for developing gametes. This method was safe and effective for determining the sex of mussels. After 1 y, survival was indistinguishable between test and control groups for both species. We sacrificed 4 to 7 E. dilatata and A. ligamentina at 3-mo intervals and examined histological sections of gonads. Sex assigned from examination of gonadal fluid and histological sections agreed in most cases (E. dilatata: 100%, A. ligamentina: 89%). ?? 2008 by The North American Benthological Society.

Journal of the North American Benthological Societ↗
USGS1995

Applying computer simulation models as learning tools in fishery management

Computer models can be powerful tools for addressing many problems in fishery management, but uncertainty about how to apply models and how they should perform can lead to a cautious approach to modeling. Within this approach, we expect models to make quantitative predictions but only after all model inputs have been estimated from empirical data and after the model has been tested for agreement with an independent data set. I review the limitations to this approach and show how models can be more useful as tools for organizing data and concepts, learning about the system to be managed, and exploring management options. Fishery management requires deciding what actions to pursue to meet management objectives. Models do not make decisions for us but can provide valuable input to the decision‐making process. When empirical data are lacking. preliminary modeling with parameters derived from other sources can help determine priorities for data collection. When evaluating models for management applications, we should attempt to define the conditions under which the model is a useful, analytical tool (its domain of applicability) and should focus on the decisions made using modeling results, rather than on quantitative model predictions. I describe an example of modeling used as a learning tool for the yellow perch Perca flavescens fishery in Green Bay, Lake Michigan.

Wisconsin↗
USGS2015

U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2014 annual report

This is the seventh report produced by the U.S. Geological Survey (USGS) for the Wyoming Landscape Conservation Initiative (WLCI) to detail annual activities conducted by the USGS for addressing specific management needs identified by WLCI partners. In FY2014, there were 26 projects, including a new one that was completed, two others that were also completed, and several that entered new phases or directions. The 26 projects fall into several categories: (1) synthesizing and analyzing existing data to identify current conditions on the landscape and using the data to develop models for projecting past and future landscape conditions; (2) monitoring indicators of ecosystem conditions and the effectiveness of on-the-ground habitat projects; (3) conducting research to elucidate the mechanisms underlying wildlife and habitat responses to changing land uses; (4) managing and making accessible the large number of databases, maps, and other products being developed; and (5) coordinating efforts among WLCI partners, helping them use USGS-developed decision-support tools, and integrating WLCI outcomes with future habitat enhancement and research projects. The new (completed) project was the development and publication of a public outreach piece for visitors of Fossil Butte National Monument. The final product was a USGS Fact Sheet that capitalized on previously collected elk-monitoring data to interpret the ecology of the Monument’s elk population and the importance of the Monument’s habitats to this highly visible wildlife species. One of the completed projects entailed developing and evaluating a synthetic approach to high-resolution satellite imagery for use in effectiveness monitoring, which culminated in a journal article. The other completed project was a coalescing of two similar tasks under data and information management that pertain to Web application development and the development of outreach and graphic products into a single integrated project that focuses on developing and maintaining/upgrading Web applications and other tools for visualizing, mapping, and using geospatial data. Major accomplishments for FY2014 included several publications, including Part B of an energy resources map that (with Part A) depicts coal, wind, oil, gas, oil shale, uranium, and solar energy production in the WLCI region. Two published works associated with sage-grouse included a Wildlife Monograph on prioritizing species’ habitats across large landscapes, multiple seasons, and novel areas (using sage-grouse in Wyoming as an example), and a USGS Data Series report that includes both the data used in the habitat-prioritization models and the habitat prioritization models developed for sage-grouse. Our Science Team also published a framework for conducting large, collaborative projects that rely on geospatial data, and a paper that describes the efficacy of fusing satellite data collected at various resolutions for measuring and monitoring vegetation changes. These products are all invaluable tools for maximizing the efficiency and effectiveness of managing species of concern, conducting future landscape-scale assessments, and monitoring status and trends of landscape conditions. Other highlights of FY2014 included a renewed effort to gather and analyze wildlife and habitat status and trend data for the WLCI Interagency Monitoring Database (IAMD) to assess long-term trends and cumulative effects associated with land-use and climate changes. Water-monitoring efforts included drilling four new groundwater-monitoring wells in the Green and New Fork River basins near the proposed Normally Pressured Lance Formation energy development, and continued data collection at established water-monitoring sites. Three additional wells were sampled as part of the Wyoming Groundwater Monitoring Network, bringing the total to 19 Network wells sampled in the WLCI region since 2010. Combined, these water-monitoring efforts can help to identify potential changes in water quality or levels that may result from land-use changes. Major terrestrial monitoring accomplishments included processing satellite imagery from 1985−2010 to develop a historical perspective of long-term vegetation changes, which can serve as a basis for monitoring current and future trends in sagebrush steppe. Such data are crucial tools for agencies tasked with sage-grouse management and conservation. The USGS WLCI Science Team also continued monitoring and testing methods for evaluating WLCI habitat treatments designed to promote aspen regeneration and enhance sage-grouse habitat, and to assess how those treatments influence invasive species distributions and ungulate herbivory. Highlights included analyzing field data collected to elucidate the relationships between sage-grouse habitat use and the proximity of energy infrastructure, and using new instruments to measure productivity responses of aspen woodlands to various factors. Numerous FY2014 accomplishments specifically addressed agency needs to manage and conserve Wyoming’s wildlife species of concern. A pygmy rabbit habitat model and Wyoming distribution map were completed to identify factors associated with rabbit habitat occupancy. Previous work on sage-grouse population dynamics was expanded to better understand the factors that drive long-term viability of sage-grouse populations and to develop a tool that helps to identify key factors limiting sage-grouse persistence in Wyoming. Field work and data analyses continued for elucidating the relationships between sagebrush songbird abundance and productivity, the intensity of energy development, and community dynamics of nest predators. For the mule deer study, mixed mountain shrublands important to migrating and wintering mule deer were mapped and delivered to WLCI partners. Additionally, the relationships between energy development and crucial winter habitat for mule deer were evaluated, and a new phase of work was implemented to better understand relationships between plant phenology and mule deer migration movements. Finally, initial analyses of data collected to evaluate fish-community composition in relation to habitat quality indicate that water quality, as measured by concentrations of hydrocarbons, water temperature, and others parameters, has been diminished in subwatersheds with higher levels of energy development. Overall, the outcomes and products of these wildlife studies contribute significantly to the information and tools needed for addressing effects of land-use changes on Wyoming’s species of concern. Finally, capabilities of the WLCI Web site and the USGS ScienceBase infrastructure were maintained and upgraded to help ensure access to and efficient use of all the WLCI data, products, assessment tools, and outreach materials that have been developed. Of particular note is the completion of three Web applications developed for mapping (1) the 1900−2008 progression of oil and gas development;(2) the predicted distributions of Wyoming’s Species of Greatest Conservation Need; and (3) the locations of coal and wind energy production, sage-grouse distribution and core management areas, and alternative routes for transmission lines within the WLCI region. Collectively, these applications tools provide WLCI planners and managers with powerful tools for better understanding the distributions of wildlife species and potential alternatives for energy development.

Wyoming↗
USGS2015

Is income breeding an appropriate construct for waterfowl?

Breeding birds use a range of nutrient accumulation and allocation strategies to meet the nutritional demands of clutch formation and incubation. On one end of the spectrum, capital breeders use stored nutrients acquired prior to clutch formation and incubation to sustain metabolism during reproduction, while on the opposite end, income breeders derive nutrients solely from exogenous sources on the breeding grounds. Blue-winged Teal ( Anas discors ) are an ideal candidate to test for adoption of an income strategy among migratory waterfowl because of their small body size, temperate breeding range, and timing of reproduction relative to pulses in nutrient availability within breeding habitats. We collected migrating and pre-breeding Blue-winged Teal ( n = 110) during the warmest spring in over a century in the southern edge of the species’ breeding range, which produced ideal conditions to test for adoption of an income breeding strategy among migratory waterfowl. Regression analyses revealed that females accumulated protein and fat reserves early in follicle development and appeared to mobilize at least some reserves coincident with the onset of clutch formation. Accumulation and subsequent mobilization of nutrient reserves was inconsistent with adherence to an income breeding strategy and suggested breeding Blue-winged Teal used capital (albeit locally acquired) for reproduction. Our results add to existing knowledge on the ubiquity of endogenous nutrient reserve accumulation prior to and during reproduction by waterfowl, perhaps suggesting endogenous nutrient reserves are universally used for clutch formation or incubation to some degree. If indeed Blue-winged Teal and other waterfowl universally use capital for breeding, research and conservation efforts should shift from evaluating whether an income breeding strategy is used and focus on when and where necessary capital is acquired prior to clutch formation.

Journal of Ornithology↗
USGS2026

Evaluating alternative methods for modeling trap efficiencies of out-migrating juvenile salmonids

Objective We aimed to compare two machine learning approaches—boosted beta regression (BBR) and beta mixed model forest (BMF)—to a Bayesian mixed-effects beta regression (BME) for the prediction of rotary screw trap (RST) efficiency for out-migrating juvenile salmonids from environmental covariates. Methods We identified two machine learning approaches that shared the ability to model overdispersed probabilities. We compared the BBR and BMF machine learning models to a BME model to evaluate precision in detection probability prediction and model performance on bias in parameter estimation. We tested our three candidate models using a simulation study to understand the specific advantages and disadvantages of each when the data set was increasingly sparse and the capture probabilities were realistically small. We then applied the models to a case study of RST data from the Klamath River in California, United States. Results The BME and BMF outperformed BBR in all simulated scenarios, although the BMF displayed poor explanatory power. In the case study, the BME and BMF identified environmental covariates that predicted RST efficiency. Conclusions Using the BME as a benchmark for comparing machine learning approaches to trap efficiency modeling, our simulations and case study demonstrated that the BMF performed well and is a viable modeling approach with strong predictive power. The BME model would be the preferred modeling approach when its strong explanatory power is desired.

North American Journal of Fisheries Management↗
USGS2014

Distance to human populations influences epidemiology of respiratory disease in desert tortoises

We explored variables likely to affect health of Agassiz's desert tortoises (Gopherus agassizii) in a 1,183-km2 study area in the central Mojave Desert of California between 2005 and 2008. We evaluated 1,004 tortoises for prevalence and spatial distribution of 2 pathogens, Mycoplasma agassizii and M. testudineum, that cause upper respiratory tract disease. We defined tortoises as test-positive if they were positive by culture and/or DNA identification or positive or suspect for specific antibody for either of the two pathogens. We used covariates of habitat (vegetation, elevation, slope, and aspect), tortoise size and sex, distance from another test-positive tortoise, and anthropogenic variables (distances to roads, agricultural areas, playas, urban areas, and centroids of human-populated census blocks). We used both logistic regression models and regression trees to evaluate the 2 species of Mycoplasma separately. The prevalence of test-positive tortoises was low: 1.49% (15/1,004) for M. agassizii and 2.89% (29/1,004) for M. testudineum. The spatial distributions of test-positive tortoises for the 2 Mycoplasma species showed little overlap; only 2 tortoises were test-positive for both diseases. However, the spatial distributions did not differ statistically between the 2 species. We consistently found higher prevalence of test-positive tortoises with shorter distances to centroids of human-populated census blocks. The relationship between distance to human-populated census blocks and tortoises that are test-positive for M. agassizii and potentially M. testudineum may be related to release or escape of captive tortoises because the prevalence of M. agassizii in captive tortoises is high. Our findings have application to other species of chelonians where both domestic captive and wild populations exist. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Journal of Wildlife Management↗
USGS2007

Selection of den sites by black bears in the southern Appalachians

We evaluated selection of den sites by American black bears (Ursus americanus) in the Pisgah Bear Sanctuary, western North Carolina, by comparing characteristics of dens at 53 den sites with availability of habitat characteristics in annual home ranges of bears and in the study area. We also tested whether den-site selection differed by sex, age, and reproductive status of bears. In addition, we evaluated whether the den component of an existing habitat model for black bears predicted where bears would select den sites. We found bears selected den sites far from gravel roads, on steep slopes, and at high elevations relative to what was available in both annual home ranges and in the study area. Den-site selection did not differ by sex or age, but it differed by reproductive status. Adult females with cubs preferred to den in areas that were relatively far from gravel roads, but adult females without cubs did not. The habitat model overestimated the value of areas near gravel roads, underestimated the value of moderately steep areas, and did not include elevation as a predictor variable. Our results highlight the importance of evaluating den selection in terms of both use and availability of den characteristics. ?? 2007 American Society of Mammalogists.

Journal of Mammalogy↗
USGS2012

Body condition of Morelet’s Crocodiles ( Crocodylus moreletii ) from northern Belize

Body condition factors have been used as an indicator of health and well-being of crocodilians. We evaluated body condition of Morelet's Crocodiles ( Crocodylus moreletii ) in northern Belize in relation to biotic (size, sex, and habitat) and abiotic (location, water level, and air temperature) factors. We also tested the hypothesis that high water levels and warm temperatures combine or interact to result in a decrease in body condition. Size class, temperature, and water level explained 20% of the variability in condition of Morelet's Crocodiles in this study. We found that adult crocodiles had higher condition scores than juveniles/subadults but that sex, habitat, and site had no effect. We confirmed our hypothesis that warm temperatures and high water levels interact to decrease body condition. We related body condition of Morelet's Crocodiles to natural fluctuations in air temperatures and water levels in northern Belize, providing baseline conditions for population and ecosystem monitoring.

Journal of Herpetology↗
USGS2009

Oxalosis in wild desert tortoises, Gopherus agassizii

We necropsied a moribund, wild adult male desert tortoise ( Gopherus agassizii ) with clinical signs of respiratory disease and elevated plasma biochemical analytes indicative of renal disease (blood urea nitrogen [415 mg/dl], uric acid [11.8 mg/dl], sodium >180 mmol/l] and chloride [139 mmol/l]). Moderate numbers of birefringent oxalate crystals, based on infrared and electron microscopy, were present within renal tubules; small numbers were seen in colloid within thyroid follicles. A retrospective analysis of 66 additional cases of wild desert tortoises was conducted to determine whether similar crystals were present in thyroid and kidney. The tortoises, from the Mojave and Sonoran deserts, were necropsied between 1992 and 2003 and included juveniles and adults. Tortoises were classified as healthy (those that died due to trauma and where no disease was identified after necropsy and evaluation by standard laboratory tests used for other tortoises) or not healthy (having one or more diseases or lesions). For all 67 necropsied tortoises, small numbers of crystals of similar appearance were present in thyroid glands from 44 of 54 cases (81%) and in kidneys from three of 65 cases (5%). Presence of oxalates did not differ significantly between healthy and unhealthy tortoises, between age classes, or between desert region, and their presence was considered an incidental finding. Small numbers of oxalate crystals seen within the kidney of two additional tortoises also were considered an incidental finding. Although the source of the calcium oxalate could not be determined, desert tortoises are herbivores, and a plant origin seems most likely. Studies are needed to evaluate the oxalate content of plants consumed by desert tortoises, and particularly those in the area where the tortoise in renal failure was found.

Journal of Wildlife Diseases↗
USGS2014

Call broadcasting and automated recorders as tools for anuran surveys in a subarctic tundra landscape

Relatively little is known about population ecology of anurans in arctic and subarctic tundra regions, in part because it is difficult to survey anurans in these landscapes. Anuran survey protocols developed for temperate regions have limited applicability in arctic and subarctic tundra landscapes, which may lack roads and vehicle access, and experience variable and inclement weather during short anuran breeding seasons. To evaluate approaches to address some of the limitations of surveying anurans in tundra landscapes, we assessed the effectiveness of using breeding call broadcasts to increase detection of Boreal Chorus Frogs ( Pseudacris maculata ) and Wood Frogs ( Lithobates sylvaticus ) near Cape Churchill, Manitoba, Canada. We also evaluated how counts of anurans derived from automated audio recorders compared with those obtained simultaneously by observers. We detected on average 0.4 additional Wood Frogs per survey when we broadcasted calls ( x̄ = 0.82, SD = 1.38), an increase of > 40% compared to surveys without broadcasts ( x̄ = 1.24, SD = 1.51; Wilcoxon test; Z = 2.73, P = 0.006). In contrast, broadcasting Boreal Chorus Frog calls did not increase the number of chorus frog detections (Wilcoxon test; Z < 0.001, P > 0.90). Detections of Wood Frogs in a 100-m radius were lower via automated recorders ( x̄ = 0.60, SD = 0.87 SD) than by observers during simultaneous surveys ( x̄ = 0.96, SD = 1.27 Z = 2.07, P = 0.038), but those of Boreal Chorus Frogs were not different (x = 1.72, SD = 1.31; x̄ = 1.44, SD = 1.5; Z = 1.55, P > 0.121). Our results suggest that broadcasting calls can increase detection of Wood Frogs, and that automated recorders are useful in detecting both Wood Frogs and Boreal Chorus Fogs in arctic and subarctic tundra landscapes.

The Journal of North American Herpetology↗
USGS2022

A machine learning approach to identify barriers in stream networks demonstrates high prevalence of unmapped riverine dams

Restoring stream ecosystem integrity by removing unused or derelict dams has become a priority for watershed conservation globally. However, efforts to restore connectivity are constrained by the availability of accurate dam inventories which often overlook smaller unmapped riverine dams. Here we develop and test a machine learning approach to identify unmapped dams using a combination of publicly available topographic and geospatial habitat data. Specifically, we trained a random forest classification algorithm to identify unmapped dams using digitally engineered predictor variables and known dam sites for validation. We applied our algorithm to two subbasins in the Hudson River watershed, USA , and quantified connectivity impacts, as well as evaluated a range of predictor sets to examine tradeoffs between classification accuracy and model parameterization effort. The random forest classifier achieved high accuracy in predicting dam sites (true positive rate = 89%, false positive rate = 1.2%) using a subset of variables related to stream slope and presence of upstream lentic habitats. Unmapped dams were prevalent throughout the two test watersheds. In fact, existing dam inventories underestimated the true number of dams by ∼80–94%. Accounting for previously unmapped dams resulted in a 62–90% decrease in dendritic connectivity indices for migratory fishes. Unmapped dams may be pervasive and can dramatically bias stream connectivity information. However, we find that machine learning approaches can provide an accurate and scalable means of identifying unmapped dams that can guide efforts to develop accurate dam inventories, thereby informing and empowering efforts to better manage them.

New York↗