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USGS1985

Total chemical management in photographic processing

The mission of the U. S. Geological Survey's Earth Resources Observation Systems (EROS) Data Center is to produce high-quality photographs of the earth taken from aircraft and Landsat satellite. In order to meet the criteria of producing research-quality photographs, while at the same time meeting strict environmental restrictions, a total photographic chemical management system was installed. This involved a three-part operation consisting of the design of a modern chemical analysis laboratory, the implementation of a chemical regeneration system, and the installation of a waste treatment system, including in-plant pretreatment and outside secondary waste treatment. Over the last ten years the result of this program has yielded high-quality photographs while saving approximately 30,000 per year and meeting all Environmental Protection Agency (EPA) restrictions.

Journal of Imaging Technology↗

USGS2015

Modelling regional land change scenarios to assess land abandonment and reforestation dynamics in the Pyrenees (France)

Over the last decades and centuries, European mountain landscapes have experienced substantial transformations. Natural and anthropogenic LULC changes (land use and land cover changes), especially agro-pastoral activities, have directly influenced the spatial organization and composition of European mountain landscapes. For the past sixty years, natural reforestation has been occurring due to a decline in both agricultural production activities and rural population. Stakeholders, to better anticipate future changes, need spatially and temporally explicit models to identify areas at risk of land change and possible abandonment. This paper presents an integrated approach combining forecasting scenarios and a LULC changes simulation model to assess where LULC changes may occur in the Pyrenees Mountains, based on historical LULC trends and a range of future socio-economic drivers. The proposed methodology considers local specificities of the Pyrenean valleys, sub-regional climate and topographical properties, and regional economic policies. Results indicate that some regions are projected to face strong abandonment, regardless of the scenario conditions. Overall, high rates of change are associated with administrative regions where land productivity is highly dependent on socio-economic drivers and climatic and environmental conditions limit intensive (agricultural and/or pastoral) production and profitability. The combination of the results for the four scenarios allows assessments of where encroachment (e.g. colonization by shrublands) and reforestation are the most probable. This assessment intends to provide insight into the potential future development of the Pyrenees to help identify areas that are the most sensitive to change and to guide decision makers to help their management decisions.

Journal of Mountain Science↗

USGS2023

Machine-learning model to delineate sub-surface agricultural drainage from satellite imagery

Knowing subsurface drainage (tile-drain) extent is integral to understanding how landscapes respond to precipitation events and subsequent days of drying, as well as how soil characteristics and land management influence stream response. Consequently, a time series of tile-drain extent would inform one aspect of land management that complicates our ability to explain streamflow and water-quality as a function of climate variability or conservation management. We trained a UNet machine-learning model, a convolutional neural network designed to highlight objects of interest within an image, to delineate tile-drain networks in panchromatic satellite imagery without additional data on soils, topography, or historical tile-drain extent. This was done by training the model to match the accuracy of human experts manually tracing the surface representation of tile drains in satellite imagery. Our approach began with a library of images that were used to train and quantify the accuracy of the model, with model performance tested on imagery from two areas that were not used to train the model. Satellite imagery included acquisition dates from 2008 to 2020. Training imagery was from agricultural areas within the US Great Lakes basin. Validation imagery was from the upper Maumee River, tributary to western Lake Erie, and an Indiana, Ohio-River headwater tributary. Our analysis of the satellite imagery paired with meteorological and soil data found that during spring, a combination of relatively high solar radiation, intermediate soil-water content and bare fields enabled the best model performance. Each area of interest was heavily tile-drained, where better understanding the movement of water, nutrients, and sediment from fields to downstream water bodies is key to managing harmful algal blooms and hypoxia. The trained UNet model successfully identified tile drains visible in the validation imagery with an accuracy of 93%–96% and balanced accuracy of 52%–54%, similar to performance for training data (95% and 63%, respectively). Model performance will benefit from ongoing contributions to the training library.

Indiana, Michigan, Ohio, Wisconsin↗

USGS1990

Monitoring moisture storage in trees using time domain reflectometry

Laboratory and field tests were performed to examine the feasibility of using time domain reflectometry (TDR) to monitor changes in the moisture storage of the woody parts of trees. To serve as wave guides for the TDR signal, pairs of stainless steel rods (13 cm long, 0.32 cm in diameter, and 2.5 cm separation) were driven into parallel pilot holes drilled into the woody parts of trees, and a cable testing oscilloscope was used to determine the apparent dielectric constant. A laboratory calibration test was performed on two sapwood samples, so that the relation between the volumetric water content and the apparent dielectric constant of the sapwood could be determined over a range of water contents. The resulting calibration curve for these sapwood samples was significantly different than the general calibration curve used for soils, showing a smaller change in the apparent dielectric constant for a given change in the volumetric water content than is typical for soils. The calibration curve was used to estimate the average volumetric water content to a depth of 13 cm in living trees. One field experiment was conducted on an English walnut tree ( Juglans regia ) with a diameter of 40 cm, growing in a flood-irrigated orchard on a Hanford sandy loam near Modesto, California (U.S.A.). Rods were driven into the tree at about 50 cm above the soil surface and monitored hourly for the month of August, 1988. The moisture content determined by TDR showed a gradual decrease from 0.44 to 0.42 cm 3 cm −3 over a two week period prior to flood irrigation, followed by a rapid rise to 0.47 cm 3 cm −3 over a four day period after irrigation, then again a gradual decline approaching the next irrigation. A second field experiment was made on ten evergreen and deciduous trees with diameters ranging from 30 to 120 cm, growing in the foothills of the Coast Range of central California. Rods were driven into each tree at 50 to 100 cm above the soil surface and monitored on a biweekly to monthly basis for over a year. Most trees showed an early spring maximum in moisture content determined by TDR associated with leaf growth, and a late summer minimum in moisture content associated with the end of the dry season. Moisture contents ranged from 0.20 to 0.70 cm 3 cm −3 , with an annual percentage change in moisture of 15% to 70% depending on species and environmental conditions. A final field test was performed in northern New Mexico (U.S.A.) to examine the effect of trunk freezing on TDR measurements. This test confirmed that freezing conditions were recorded as a total loss of liquid water by the TDR method. These results suggest that further TDR calibration for wood, plus some understanding of the relation between tree moisture and physiological stress could be useful to several disciplines, ranging from irrigation scheduling to watershed management to forest ecology.

California↗

USGS2024

Annotated bibliography of scientific research relevant to oil and gas reclamation best management practices in the western United States, published from 1969 through 2020

Integrating recent scientific knowledge into management decisions supports effective natural resource management and can lead to better resource outcomes. However, finding and accessing scientific knowledge can be time consuming and costly. To assist in this process, the U.S. Geological Survey has created a series of annotated bibliographies on topics of management concern for lands in the western United States (U.S.). Oil and gas development on public lands is a long-standing and substantial component of local and regional economies and has expanded in recent decades, particularly on public lands in the western U.S. This development is associated with extensive networks of pipelines, roads, and processing facilities, across which reclamation is Federally mandated following initial well pad development (“interim” reclamation) and once resource extraction is complete (“final” reclamation). Reclamation is critical for recovering ecological services to energy-affected lands, including vegetation productivity, wildlife habitat, water and air quality, and soil stability (for example, resistance to wind and water erosion). However, reclamation of oil and gas affected lands in the western U.S. has proved challenging due to an array of regulatory and environmental factors, such as minimally developed soils, short growing seasons, herbivory, high winds, invasive species, rugged terrain, and in particular, arid climates associated with low total precipitation, high evapotranspiration rates, and highly variable precipitation patterns. We compiled and summarized journal articles, government reports, technical reports, proceedings, and theses and dissertations relevant to oil and gas reclamation. We constrained our search to products published on or before December 31, 2020 but did not limit our search by a starting date; the earliest product resulting from this effort was published in March 1969. Second, we manually scanned the last 15 years (2005-2020) of tables of contents in journals, bibliographies, and proceedings of which we were aware would contain articles highly relevant to this bibliography. We carried out the search for these products through multiple means: (1) performing a structured search of two reference databases, (2) examining articles published since 2005 in highly relevant scientific journals and conference proceedings, and (3) reviewing additional material suggested by authors of products identified in steps 1 and 2. Our search was intentionally broad in order to identify as much relevant work as possible, much of which is professionally applied and tested within the industry of oil and gas reclamation, but which remains unpublished in scientific journals. We refined the initial list of products by removing: (1) duplicates, (2) products not written in English, (3) products that were not relevant to the arid ecosystems of western North America, (4) products that were not released as research, data products, or review articles in journals or as formal scientific reports, and (5) products with data which were not relevant to reclamation of oil and gas-affected lands, or for which the study did not present new data, findings, or syntheses relevant to reclamation of oil and gas-affected lands. We summarized each product using a consistent structure (background, objectives, methods, location, findings, and implications) and assigned standardized management topics to each. Management topics are intended to aid online searching within the bibliography and are described in more detail in the Methods Section of this report; they include what type of disturbance the product addresses (well pads, mining, pipelines), what aspect of oil and gas reclamation they pertain to (practices, standards, monitoring), what type of data are present in the product (for instance soil or vegetation recovery data), and an indication if the product were from a source other than a published, peer-reviewed outlet (such as dissertations or unpublished professional reports – these are identified as grey literature). The review process for this annotated bibliography included an initial internal colleague review of each summary, requesting input on each summary from an author of the original product, and a formal peer-review. Our initial searches resulted in 3,197 total products, of which 290 met our criteria for inclusion. “Reclamation Practices” is by far the management topic most addressed, followed by “Reclamation Monitoring,” for example, products assessing what and how monitoring methods are used to track and measure reclamation outcome. This document may be accessed at https://doi.org/10.3133/ofr20231068 or from the U.S. Geological Survey Publication Warehouse ( https://pubs.usgs.gov/ ). The 1-page product summaries herein will also be used to create a bibliography at https://apps.usgs.gov/science-for-resource-managers that includes links to each original product, where available, and in which subject matter will be searchable by topic, location, and year. The studies compiled and summarized here may inform planning and management actions that seek to reclaim landscapes across the western U.S. which have been affected by oil and gas development.

Open-File Report↗

USGS1968

Effect of predator reduction on waterfowl nesting success

A 6-year study to determine the effect of nest-predator removal on waterfowl nesting success was conducted at the Agassiz National Wildlife Refuge in northwestern Minnesota from 1959 through 1964. Predators were removed from the west side of the Refuge while the east side served as a control area. At the end of 3 years, these areas were reversed to reduce the effects of environmental influences. The effect of predator removal was measured by a simulated nest study to determine predation pressure, a check of natural nest success, and weekly breeding pair and brood counts. Results indicated that 60 percent more Class I ducklings were produced on the units where predator control was conducted. Until more is known, reduction of predators to increase waterfowl nesting success should be limited to intensively managed production areas where substantial nest losses are demonstrated.

Minnesota↗

USGS2025

Detection probabilities of Flathead Catfish in small Kansas impoundments

A primary challenge of Flathead Catfish Pylodictis olivaris management is uncertainty associated with sampling strategies and resulting ambiguity in population-level information. Assessment of impoundment and environmental conditions that affect detection probability may aid in reducing sample variance and benefit inferences regarding changes to Flathead Catfish populations. We sampled eight small impoundments in Kansas (37–114 surface ha) using low-frequency electrofishing in summer, 2021. We revisited sites nine times over three months using an occupancy modeling framework to estimate the influence of impoundment and environmental conditions on detection probability of Flathead Catfish. We employed an information theoretic approach and ranked models built with impoundment as a random effect and three environmental variables predicted to influence detection of Flathead Catfish in small impoundments. Detection probability across all populations was 0.526 (SE = 0.020) and was influenced by water temperature, mean depth of the impoundment, and proportion of impoundment sampled. Generally, detection probability increased with all measured variables. The inclusion of detection probability in assessments of Flathead Catfish in small impoundments can inform interpretation of catch-related metrics. Further, variable detection suggests collection of multiple samples during a defined sampling period might be more suitable for characterizing populations than a single sample.

Kansas↗

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↗

USGS2020

Low stand density moderates growth declines during hot droughts in semi-arid forests

Increasing heat and aridity in coming decades is expected to negatively impact tree growth and threaten forest sustainability in dry areas. Maintaining low stand density has the potential to mitigate the negative effects of increasingly severe droughts by minimizing competitive intensity. However, the direct impact of stand density on the growing environment (i.e. soil moisture), and the specific drought metrics that best quantify that environment, are not well explored for any forest ecosystem. We examined the relationship of varying stand density (i.e. basal area) on soil moisture and stand‐level growth in a long‐term (multi‐decadal), ponderosa pine Pinus ponderosa , forest management experiment. We accounted for the influence of stand‐level density on moisture availability by measuring and modelling soil moisture using an ecosystem water balance model. To quantify the growing environment, we developed metrics of ecological drought that integrate the influence of moisture availability in the soil with moisture demand by the atmosphere. We paired these results with stand‐level dendrochronological data, avoiding the potential bias introduced from individual tree‐based assessments, and used critical climate period analysis to identify the timing and duration of these drought metrics that most relate to forest growth. We found that stand‐level growth is highly responsive to the combination of high temperature and low soil moisture. Growth in all stands was negatively related to temperature and positively related to moisture availability, although the sensitivity of growth to those conditions varied among stand density treatments. Growth enhancement during cool years is greatest in low density stands. In addition, low density stands displayed substantially higher long‐term average growth than higher density stands and maintained higher growth even when temperatures were high. Growth in low density stands also increased more than higher density stands in response to greater long‐term moisture availability. Synthesis and applications . We quantified the influence of stand‐level density on the environmental conditions that determine tree growth and related forest growth to patterns of moisture supply and demand. Our drought metrics, and analytical approach for quantifying drought impacts on forest growth, are a novel approach for assessing forest vulnerability to drought under climate change. These results provide new perspective on the potential for density management to mitigate drought stress and maintain forest stand growth during and after drought events in water‐limited forests.

Arizona↗

USGS2025

Exploring the science and data foundation for Federal public lands decisions

Public lands provide diverse resources, values, and services worldwide. Laws and policies typically require consideration of science in public lands decisions, and resource managers are committed to science-informed decision-making. However, it can be challenging for managers to use, and document the use of, science and data in their decisions. To better understand science and data use in Federal public lands decisions in the United States, we assessed the number, type, and age of documents cited in 70 Environmental Assessments (EAs) completed by the Bureau of Land Management (BLM) in Colorado from 2015–2019. We focused on the BLM, as they manage the largest area of public lands in the United States. We selected Colorado as our study area, as actions proposed on BLM lands in Colorado are representative of those across the nation. Fifty percent of citations were categorized as science and 23% as data. EAs contained an average of 17 citations (range 0–111), with documents analyzing effects of oil and gas development and recreation actions including the highest and lowest mean number of citations (41 and 6, respectively). Of individual resource analysis sections within EAs, 24% contained ≥1 science citation and 21% contained ≥1 data citation. Journal articles were the most cited type of document (26% of citations) followed by non-BLM inventories (13%). Forty-seven percent of citations were relatively recent (2010 or later); the oldest citation was from 1927. Commonly analyzed resources with the highest mean number of citations were socioeconomics, mineral resources, and noise. Fourteen of 33 commonly analyzed resources included <1 citation on average. Actions and resources with no or few citations represent opportunities for strengthening the transparent use of science and data in public lands decision-making.

Colorado↗

USGS2025

Bait trapping of waterfowl increases the environmental contamination of avian influenza virus (AIV)

Highly pathogenic avian influenza virus (HPAIV) H5Nx clade 2.3.4.4b has circulated in North America since late 2021, resulting in higher rates of morbidity and mortality in wild birds than observed in this region before. The objective of this study was to determine whether baiting, which is widely conducted in Canada and the United States as part of waterfowl management practices (e.g., duck banding), influences the occurrence of avian influenza virus (AIV) in wetlands. We used a quasi-experimental design, collecting superficial sediment samples ( n = 336) and fecal samples ( n = 242) from paired baited (treatment) and non-baited (control) sites at 2 wetlands in Saskatchewan, Canada, between August and September 2022. We visited sampling sites 3 times during the sampling period: prior to the commencement of baiting activities ( t0 ), approximately 14 days after t0 ( t1 ), and 24 days after t0 ( t2 ). We screened samples for AIV using real-time reverse-transcriptase polymerase chain reaction (rRT-PCR) targeting the matrix gene and subjected the PCR-positive samples to next-generation sequencing. We used a mixed-effects logistic regression model to estimate the effect of baiting on the odds of AIV positivity in sediment samples, while controlling for clustering by wetland. At control sites, we did not detect evidence for a difference in the odds of AIV detection in sediment at t1 or t2 versus t0 ; however, at baited sites, the odds of AIV detection at t1 were 5.43 (95% CI = 1.99, 14.79) times the odds at t0 and at t2 the odds of AIV detection were 8.73 (95% CI = 3.29, 23.18) times the odds at t0 . We detected HPAIV clade 2.3.4.4b H5N1 in sediment at 1 treatment site following baiting. There was also a trend towards increased fecal AIV positivity and increased fecal and sediment AIV diversity in baited versus non-baited sites; however, there was insufficient power to determine if these findings were statistically significant. Overall, our results indicate that baiting is associated with localized increases in AIV environmental contamination, with baiting potentially creating concentrated areas of AIV accumulation. As such, wetland baiting activities may pose a risk to wildlife population health through the propagation of AIV in wetlands and the waterfowl using those environments and efforts to replace, refine, or reduce this activity may be warranted depending on local ecosystem contexts and cost-benefit analyses.

Saskatchewan↗

USGS2024

Great Lakes mallard population dynamics

Breeding mallard ( Anas platyrhynchos ) populations in the Great Lakes region (Michigan, Minnesota, Wisconsin, USA) declined by >40% between 2000–2022 based on abundance data collected during spring aerial surveys. Mallards are an important waterfowl species in this region, where an estimated 60–80% of the mallard harvest is composed of locally banded birds. Extensive population monitoring datasets are available for mallards, presenting an opportunity to address complex questions such as estimating productivity at large spatial and temporal scales, identifying the effects of harvest on mallard demography, quantifying mechanisms for harvest compensation, and integrating multiple datasets to quantify the demographic drivers of population change. Our objective was to simultaneously examine factors affecting demographic parameters and their relative contribution to Great Lakes mallard population dynamics. We used 32 years of banding, band recovery, and aerial survey data collected for mallards from Michigan and Wisconsin to develop an integrated population model (IPM). We used age ratios at banding to estimate productivity, band recoveries from hunter-harvested birds to estimate annual survival and cause-specific mortality (i.e., harvest or non-hunting), and modeled abundance using aerial survey and demographic parameter estimates from 1991–2022. The IPM results indicated the decline in Great Lakes mallard abundance was caused by increased non-hunting mortality and a decline in productivity. Productivity varied spatially but temporally declined with the loss of Conservation Reserve Program area. Moreover, our productivity assessment provided evidence of density dependence in reproduction. Non-hunting mortality was 3.5–6.7 times and 1.3–4.2 times greater than harvest mortality for adult and juvenile female mallards, respectively, indicating environmental factors during spring and summer, not harvest, most greatly influenced annual mortality for female mallards. Our IPM reduced uncertainty in the factors affecting Great Lakes mallard population dynamics and indicated management actions that address non-hunting mortality and productivity would be most effective in increasing Great Lakes mallard abundance.

Michigan, Wisconsin↗

USGS2023

Remote sensing evaluation of winter cover crop springtime performance and the impact of delayed termination

In 2019, the Maryland Department of Agriculture's Winter Cover Crop Program introduced a delayed termination incentive (after May 1) to promote springtime biomass accumulation. We used satellite imagery calibrated with springtime in situ measurements collected from 2006–2021 ( n = 722) to derive biomass estimates for Maryland fields planted to cereal cover crop species (286,200 ha total over two seasons). Cover crop C content remained steady throughout the cover crop growing season (42.6% of biomass), whereas N concentration had an inverse relationship with biomass and ranged from 1.7 to 2.9%. Throughout Maryland, delayed termination fields ( n = 19,120; average termination of May 18) were, on average, estimated to accumulate an additional 789 kg of biomass, 15 kg of N, and 336 kg of C per hectare when compared to fields associated with standard termination dates ( n = 28,811; average termination of April 16). Over two cover crop seasons (2019–2021), the delayed termination incentive yielded an extra 75,660,000 kg biomass, 1,526,000 kg N, and 32,230,000 kg C across 96,040 hectares. Regularly terminated field incentives cost an average of US$0.10 per kg of biomass and $4.09 per kg of N, with variability associated with agronomic management (species, planting method). Delayed termination fields cost of $0.08 per kg of biomass and $3.51 per kg of N. Late-planted cover crops that were terminated early had minimal environmental benefit, and wheat, which comprised 68% of cover crop area, performed poorly compared with other cereal species. Our findings demonstrate that substantial additional springtime biomass, C, and N accumulation were achieved through the delayed termination incentive.

Maryland↗

USGS2013

Measuring environmental change in forest ecosystems by repeated soil sampling: a North American perspective

Environmental change is monitored in North America through repeated measurements of weather, stream and river flow, air and water quality, and most recently, soil properties. Some skepticism remains, however, about whether repeated soil sampling can effectively distinguish between temporal and spatial variability, and efforts to document soil change in forest ecosystems through repeated measurements are largely nascent and uncoordinated. In eastern North America, repeated soil sampling has begun to provide valuable information on environmental problems such as air pollution. This review synthesizes the current state of the science to further the development and use of soil resampling as an integral method for recording and understanding environmental change in forested settings. The origins of soil resampling reach back to the 19th century in England and Russia. The concepts and methodologies involved in forest soil resampling are reviewed and evaluated through a discussion of how temporal and spatial variability can be addressed with a variety of sampling approaches. Key resampling studies demonstrate the type of results that can be obtained through differing approaches. Ongoing, large-scale issues such as recovery from acidification, long-term N deposition, C sequestration, effects of climate change, impacts from invasive species, and the increasing intensification of soil management all warrant the use of soil resampling as an essential tool for environmental monitoring and assessment. Furthermore, with better awareness of the value of soil resampling, studies can be designed with a long-term perspective so that information can be efficiently obtained well into the future to address problems that have not yet surfaced.

Journal of Environmental Quality↗

USGS2016

Environmental factors influence lesser scaup migration chronology and population monitoring

Identifying environmental metrics specific to lesser scaup ( Aythya affinis ; scaup) spring migration chronology may help inform development of conservation, management and population monitoring. Our objective was to determine how environmental conditions influence spring migration of lesser scaup to assess the effectiveness of the Waterfowl Breeding Population and Habitat Survey in accurately estimating scaup populations. We first compared peak timing of mallard ( Anas platyrhynchos ) and scaup migration from weekly ground surveys in North Dakota, USA because the Waterfowl Breeding Population and Habitat Survey is designed to capture annual mallard migration. As predicted, we detected that peak timing of scaup and mallard migrations differed in 25 of 36 years investigated (1980–2010). We marked scaup with satellite transmitters ( n = 78; 7,403 locations) at Long Point, Lake Erie, Ontario, Canada; Pool 19 of the Mississippi River, Iowa and Illinois, USA; and Presque Isle Bay, Lake Erie, Pennsylvania, USA. We tested the assumption that our marked scaup were representative of the continental population using the traditional survey area by comparing timing of migration of marked birds and scaup counted in the North Dakota Game and Fish Department survey. We detected a strong positive correlation between marked scaup and the survey data, which indicated that marked scaup were representative of the population. We subsequently used our validated sample of marked scaup to investigate the effects of annual variation in temperature, precipitation, and ice cover on spring migration chronology in the traditional and eastern survey areas of the Waterfowl Breeding Population and Habitat Survey, 2005–2010. We evaluated competing environmental models to explain variation in timing and rate of scaup migration at large-scale and local levels. Spring migration of scaup occurred earlier and faster during springs with warmer temperatures and greater precipitation, variables known to influence energy budgets and wetland availability. Our results suggest that surveys designed to index abundance of breeding mallards is imprecise for estimating scaup abundance, and inaccurate at estimating breeding population size by survey stratum.

Journal of Wildlife Management↗

USGS2000

Predictability of Bristol Bay, Alaska, sockeye salmon returns one to four years in the future

Historically, forecast error for returns of sockeye salmon Oncorhynchus nerka to Bristol Bay, Alaska, has been large. Using cross-validation forecast error as our criterion, we selected forecast models for each of the nine principal Bristol Bay drainages. Competing forecast models included stock-recruitment relationships, environmental variables, prior returns of siblings, or combinations of these predictors. For most stocks, we found prior returns of siblings to be the best single predictor of returns; however, forecast accuracy was low even when multiple predictors were considered. For a typical drainage, an 80% confidence interval ranged from one half to double the point forecast. These confidence intervals appeared to be appropriately wide.

Alaska↗

USGS2017

Contribution of manipulable and non-manipulable environmental factors to trapping efficiency of invasive sea lamprey

We identified aspects of the trapping process that afforded opportunities for improving trap efficiency of invasive sea lamprey ( Petromyzon marinus ) in a Great Lake's tributary. Capturing a sea lamprey requires it to encounter the trap, enter, and be retained until removed. Probabilities of these events depend on the interplay between sea lamprey behavior, environmental conditions, and trap design. We first tested how strongly seasonal patterns in daily trap catches (a measure of trapping success) were related to nightly rates of trap encounter, entry, and retention (outcomes of sea lamprey behavior). We then tested the degree to which variation in rates of trap encounter, entry, and retention were related to environmental features that control agents can manipulate (attractant pheromone addition, discharge) and features agents cannot manipulate (water temperature, season), but could be used as indicators for when to increase trapping effort. Daily trap catch was most strongly associated with rate of encounter. Relative and absolute measures of predictive strength for environmental factors that managers could potentially manipulate were low, suggesting that opportunities to improve trapping success by manipulating factors that affect rates of encounter, entry, and retention are limited. According to results at this trap, more sea lamprey would be captured by increasing trapping effort early in the season when sea lamprey encounter rates with traps are high. The approach used in this study could be applied to trapping of other invasive or valued species.

Journal of Great Lakes Research↗

USGS2016

Prediction of pesticide toxicity in Midwest streams

The occurrence of pesticide mixtures is common in stream waters of the United States, and the impact of multiple compounds on aquatic organisms is not well understood. Watershed Regressions for Pesticides (WARP) models were developed to predict Pesticide Toxicity Index (PTI) values in unmonitored streams in the Midwest and are referred to as WARP-PTI models. The PTI is a tool for assessing the relative toxicity of pesticide mixtures to fish, benthic invertebrates, and cladocera in stream water. One hundred stream sites in the Midwest were sampled weekly in May through August 2013, and the highest calculated PTI for each site was used as the WARP-PTI model response variable. Watershed characteristics that represent pesticide sources and transport were used as the WARP-PTI model explanatory variables. Three WARP-PTI models—fish, benthic invertebrates, and cladocera—were developed that include watershed characteristics describing toxicity-weighted agricultural use intensity, land use, agricultural management practices, soil properties, precipitation, and hydrologic properties. The models explained between 41 and 48% of the variability in the measured PTI values. WARP-PTI model evaluation with independent data showed reasonable performance with no clear bias. The models were applied to streams in the Midwest to demonstrate extrapolation for a regional assessment to indicate vulnerable streams and to guide more intensive monitoring.

Midwest↗