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USGS2023

AIMS for wildlife: Developing an automated interactive monitoring system to integrate real-time movement and environmental data for true adaptive management

To effectively manage species and habitats at multiple scales, population and land managers require rapid information on wildlife use of managed areas and responses to landscape conditions and management actions. GPS tracking studies of wildlife are particularly informative to species ecology, habitat use, and conservation. Combining GPS data with administrative data and a diverse suite of remotely sensed, geo-referenced environmental (e.g., climatic) data, would more comprehensively inform how animals interact with and utilize habitats and ecosystems and our goal was to create a conceptual model for a system that would accomplish this – the ‘Automated Interactive Monitoring System (AIMS) for Wildlife’. Our objective for this study was to develop a Customized Wildlife Report (CWR) - the first AIMS for Wildlife deliverable product. CWRs collate and summarize our 8-year GPS tracking dataset of ∼11 million locations from 1338 individual (16 species) avifauna and make actionable, real-time data on animal movements and trends in a specific area of interest available to managers and stakeholders for rapid application in day-to-day management. The CWR exemplar presented in this paper was developed to address needs identified by habitat managers of Sacramento National Wildlife Refuge and illustrates the highly specific, information offered and how it contributes to assessing the efficacy of conservation actions while allowing for near real-time adaptive management. The report can be easily customized for any of the thousands of wildlife refuges or regional areas of interest in the United States, emphasizing the broad application of an animal movement data stream. Utilizing diverse, extensive telemetry data streams through scientific collaboration can aid managers and conservation stakeholders with short and long-term research and conservation planning and help address a cadre of issues from local-scale habitat management to improving the understanding of landscape level impacts like drought, wildfire, and climate change on wildlife populations.

Journal of Environmental Management↗

USGS2019

A natural‐origin steelhead population's response to exclusion of hatchery fish

It is asserted that reduction or elimination of hatchery stocking will increase natural‐origin salmon Oncorhynchus spp. and steelhead O. mykiss production. We conducted an analysis of steelhead population census data (1958–2017) to determine whether elimination of summer steelhead stocking in the upper Clackamas River in 1998 increased the productivity of natural‐origin winter steelhead. A Bayesian state–space stock–recruitment model was fitted to the adult steelhead data set, and productivity was estimated as a function of hatchery‐origin spawner abundance as well as other environmental factors. When used as a predictive variable in our model, the abundance of hatchery summer steelhead spawners (1972–2001) did not have a negative effect on winter steelhead recruitment. However, spill at North Fork Dam (the gateway to the upper Clackamas River basin) and the Pacific Decadal Oscillation (an index of ocean conditions) were both negatively associated with winter steelhead recruitment. Moreover, winter steelhead abundance in the upper Clackamas River basin failed to rebound to abundances observed in years prior to the hatchery program, and fluctuations in winter steelhead abundance were correlated with those of other regional winter steelhead stocks. Our assessment underscores the need for studies that (1) directly quantify the effects of hatchery fish on the production of natural‐origin salmon and steelhead, (2) empirically test published theories about mechanisms of hatchery fish impacts on natural‐origin populations, and (3) document population responses to major changes in hatchery programs.

Oregon↗

USGS2012

Fluid geochemistry of Yucca Mountain and vicinity

Yucca Mountain, a site in southwest Nevada, has been proposed for a deep underground radioactive waste repository. An extensive database of geochemical and isotopic characteristics has been established for pore waters and gases from the unsaturated zone, perched water, and saturated zone waters in the Yucca Mountain area. The development of this database has been driven by diverse needs of the Yucca Mountain Project, especially those aspects of the project involving process modeling and performance assessment. Water and gas chemistries influence the sorption behavior of radionuclides and the solubility of the radionuclide compounds that form. The chemistry of waters that may infiltrate the proposed repository will be determined in part by that of water present in the unsaturated zone above the proposed repository horizon, whereas pore-water compositions beneath the repository horizon will influence the sorption behavior of the radionuclides transported toward the water table. However, more relevant to the discussion in this chapter, development and testing of conceptual flow and transport models for the Yucca Mountain hydrologic system are strengthened through the incorporation of natural environmental tracer data into the process. Chemical and isotopic data are used to establish bounds on key hydrologic parameters and to provide corroborative evidence for model assumptions and predictions. Examples of specific issues addressed by these data include spatial and temporal variability in net fluxes, the role of faults in controlling flow paths, fracture-matrix interactions, the age and origin of perched water, and the distribution of water traveltimes.

Nevada↗

USGS2009

Hydrologic conditions and a firm-yield assessment for J.B. Converse Lake, Mobile County, Alabama, 1991-2006

J.B. Converse (Converse) Lake is the primary source of drinking water for the city of Mobile, Alabama. Concerns regarding the ability of the reservoir to meet current and future water demands during drought conditions have prompted this study. The 1991 through 2006 water years included a drought that occurred during 2000, and drought conditions currently (2007) are affecting the area. To assist officials of the Mobile Area Water and Sewer System in planning for future demands for drinking water in the Mobile metropolitan area, the firm yield for Converse Lake was estimated by the U.S. Geological Survey. The firm yield of Converse Lake was estimated using the Massachusetts Department of Environmental Protection’s firm-yield-estimator (FYE) model, which recently was refined by the U.S. Geological Survey. The model uses a mass-balance approach to determine the maximum average daily withdrawal rate that can be sustained during a period of record that includes a drought of record. If the reservoir is in contact with an aquifer, the FYE also includes routines that estimate the volume of ground-water and surface-water exchange between the aquifer and the reservoir. The average daily firm yield for Converse Lake was estimated to be 79 million gallons per day using the FYE routine that does not include ground-water exchange between the reservoir and the adjacent aquifer. Observed lake levels and withdrawals during the drought of 2000 indicate that more than 74 million gallons per day of water were withdrawn without complete depletion of reservoir storage. Therefore, it is likely that ground-water exchange with the reservoir may supplement available reservoir storage. If water exchange occurs between the aquifer and the reservoir, an increase in the volume of water available to the reservoir may occur during a drought. To quantify the potential ground-water contribution to reservoir storage, an analytical solution was applied to the FYE simulation of Converse Lake to estimate ground-water exchange between the reservoir and the aquifer. Aquifer properties required by the FYE were estimated by model calibration to observed water levels that occurred during the drought of 2000. When ground-water exchange between the reservoir and adjacent aquifer is included, the average daily firm yield increased to 83 million gallons per day. The estimate of 83 million gallons per day incorporates both total surface-water flow and ground-water exchange components. This analysis indicated that direct ground-water interaction contributes about 5 percent of the firm yield of Converse Lake. However, the average daily firm yield of 83 million gallons per day, based in part on calibrated values for aquifer transmissivity and storage, can be used only as a guideline until these aquifer properties can be defined better by field investigation in the Converse Lake watershed.

Alabama↗

USGS2022

Global genetic diversity status and trends: Towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well-being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within-species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: ( i ) Genetic Diversity; ( ii ) Genetic Differentiation; ( iii ) Inbreeding; and ( iv ) Effective Population Size ( N e ). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large-scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long-term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.

Biological Reviews↗

USGS2005

River nutrient loads and catchment size

We have used a total of 496 sample sites to calibrate a simple regression model for calculating dissolved inorganic nutrient fluxes via runoff to the ocean. The regression uses the logarithms of runoff and human population as the independent variables and estimates the logarithms of dissolved inorganic nitrogen and phosphorus loading with R 2 values near 0.8. This predictive capability is about the same as has been derived for total nutrient loading with process-based models requiring more detailed information on independent variables. We conclude that population and runoff are robust proxies for the more detailed application, landscape modification, and in-stream processing estimated by more process-based models. The regression model has then been applied to a demonstration data set of 1353 river catchments draining to the sea from the North American continent south of the Canadian border. The geographic extents of these basins were extracted from a 1-km digital elevation model for North America, and both runoff and population were estimated for each basin. Most of the basins (72% of the total) are smaller than 103 km2, and both runoff and population density are higher and more variable among small basins than among larger ones.While total load to the ocean can probably be adequately estimated from large systems only, analysis of the geographic distribution of nutrient loading requires consideration of the small basins, which can exhibit significant hydrologic and demographic heterogeneity between systems over their range even within the same geographic region. High-resolution regional and local analysis is necessary for environmental assessment and management. ?? Springer 2005.

Biogeochemistry↗

USGS2021

Informed breeding dispersal following stochastic changes to patch quality in a pond-breeding amphibian

The unidirectional movement of animals between breeding patches (i.e. breeding dispersal) has profound implications for the ecological and evolutionary dynamics of spatially structured populations. In spatiotemporally variable environments, individuals are expected to adjust their dispersal decisions according to information gathered on the environmental and/or social cues that reflect the fitness prospects in a given breeding patch (i.e. informed dispersal). A paucity of empirical work limited our understanding of the ability of animals to depart from low-quality breeding patches and settle in high-quality breeding patches. We examined the capacity of individuals to respond to stochastic changes in habitat quality via informed breeding dispersal in a pond-breeding amphibian. We conducted a 5-year (2015–2019) capture–recapture study of boreal toads Anaxyrus boreas boreas ( n = 1,100) that breed in beaver ponds in western Wyoming, USA. During early spring of 2017, an extreme flooding event destroyed several beaver dams and resulted in the loss of breeding habitat. We used multi-state models to investigate how temporal changes in pond characteristics influenced breeding dispersal, and determine whether movement decisions were in accordance with prospects for reproductive fitness. Boreal toads more often departed from low-quality breeding ponds (without successful metamorphosis) and settled in high-quality breeding ponds (with successful metamorphosis). Movement decisions were context-dependent and associated with pond characteristics altered by beaver dam destruction. Individuals were more likely to depart from shallow ponds with high vegetation cover and settle in deep ponds with low vegetation cover. The probability of metamorphosis was related to the same environmental cues, suggesting that boreal toads assess the fitness prospects of a breeding patch and adjust movement decisions accordingly (i.e. informed breeding dispersal). We demonstrated that stochastic variability in environmental conditions and habitat quality can underpin dispersal behaviour in amphibians. Our study highlighted the mechanistic linkages between habitat change, movement behaviour and prospects for reproductive performance, which is critical for understanding how wild animals respond to rapid environmental change.

Wyoming↗

USGS2015

Landscapes for energy and wildlife: conservation prioritization for golden eagles across large spatial scales

Proactive conservation planning for species requires the identification of important spatial attributes across ecologically relevant scales in a model-based framework. However, it is often difficult to develop predictive models, as the explanatory data required for model development across regional management scales is rarely available. Golden eagles are a large-ranging predator of conservation concern in the United States that may be negatively affected by wind energy development. Thus, identifying landscapes least likely to pose conflict between eagles and wind development via shared space prior to development will be critical for conserving populations in the face of imposing development. We used publicly available data on golden eagle nests to generate predictive models of golden eagle nesting sites in Wyoming, USA, using a suite of environmental and anthropogenic variables. By overlaying predictive models of golden eagle nesting habitat with wind energy resource maps, we highlight areas of potential conflict among eagle nesting habitat and wind development. However, our results suggest that wind potential and the relative probability of golden eagle nesting are not necessarily spatially correlated. Indeed, the majority of our sample frame includes areas with disparate predictions between suitable nesting habitat and potential for developing wind energy resources. Map predictions cannot replace on-the-ground monitoring for potential risk of wind turbines on wildlife populations, though they provide industry and managers a useful framework to first assess potential development.

Wyoming↗

USGS2020

Effects of snowpack, temperature, and disease on the demography of a wild population of amphibians

Understanding the demographic consequences of interactions among pathogens, hosts, and weather conditions is critical in determining how amphibian populations respond to disease and in identifying site-specific conservation actions that can be developed to bolster persistence of amphibian populations. We investigated population dynamics in Boreal Toads ( Anaxyrus boreas ) relative to abiotic (fall temperatures and snowpack) and biotic (the abundance of another anuran host and disease) characteristics of the local environment in Wyoming, USA. We used capture–recapture data and a multistate model where state was treated as a hidden Markov process to incorporate disease state uncertainty and assess our a priori hypotheses. Our results indicated that snowpack during the coldest week of winter is more influential to toad survival, disease transition probabilities, and the population-level prevalence of the amphibian chytrid fungus ( Batrachochytrium dendrobatidis ) in the spring, than temperatures in the fall or the presence of another host. As hypothesized, apparent survival at low (i.e., <25 cm) snowpack (0.22; confidence interval [CI] = 0.15–0.31) was lower than apparent survival at high snowpack (90.65; CI = 0.50–0.78). Our findings highlight the potential for local environmental factors, like snowpack, to influence disease and host persistence, and demonstrate the ecological complexity of disease effects on population demography in natural environments. This work further emphasizes the need for improved understanding of how climate change may influence the relationships among pathogens, hosts, and their environment for wild animal populations challenged by disease.

Wyoming↗

USGS2024

Infectivity of wild-bird origin Influenza A viruses in Minnesota wetlands across seasons

The environmental tenacity of influenza A viruses (IAVs) in the environment likely plays a role in their transmission; IAVs are able to remain infectious in aquatic habitats and may have the capacity to seed outbreaks when susceptible wild bird hosts utilize these same environments months or even seasons later. Here, we aimed to assess the persistence of low-pathogenicity IAVs from naturally infected ducks in Northwestern Minnesota through a field experiment. Viral infectivity was measured using replicate samples maintained in distilled water in a laboratory setting as well as in filtered water from four natural water bodies maintained in steel perforated drums (hereafter, mesocosms) within the field from autumn 2020 to spring 2021. There was limited evidence for the extended persistence of IAVs held in mesocosms; from 65 initial IAV-positive samples, only six IAVs persisted to at least 202 days in the mesocosms compared to 17 viruses persisting at least this long when held under temperature-controlled laboratory settings in distilled water. When accounting for the initial titer of samples, viruses detected at a higher concentration at the initiation of the experiment persisted longer than those with a lower starting titer. A parallel experimental laboratory model was used to further explore the effects of water type on viral persistence, and the results supported the finding of reduced tenacity of IAVs held in mesocosms compared to distilled water. The results of this investigation provide evidence that many factors, including temperature and physicochemical properties, impact the duration of viral infectivity in natural settings, further extending our understanding of the potential and limitations of environmental-based methodologies to recover infectious IAVs.

Minnesota↗

USGS2019

New approach to assessing age uncertainties – The 2300-year varve chronology from Eklutna Lake, Alaska (USA)

Developing robust chronological frameworks of lacustrine sediment is central to reconstructing past environmental changes. We present varve chronologies from five sites extending back 2300 years from Eklutna Lake, in the Chugach Mountains of south-central Alaska. The chronologies are built from image analysis of high-resolution photographs and CT scans of sediment cores. The age uncertainty of each record is tested by three methods. We first present varve chronologies from individual sites and reconcile the difference in varve delimitation from two observers. The varve chronologies from each site are then compared to each other using a series of marker beds that can be traced across the lake basin. Finally, using a new Bayesian probabilistic model, we develop age models that incorporate information regarding age uncertainty from the multiple-observer method and the age distribution of marker layers from multiple cores. To evaluate the accuracy of the Bayesian model output, we used seven radiocarbon ages from terrestrial macrofossils and four tephra layers traceable across the core sites. The major-element geochemistry of the tephra layers and their ages are presented here for the first time. The Bayesian age model offers a new approach to quantifying age uncertainty in inter-correlated cores of varved sediment.

Alaska↗

USGS2015

Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14

Harmful cyanobacterial “algal” blooms (cyanoHABs) and associated toxins, such as microcystin, are a major water-quality issue for Lake Erie and inland lakes in Ohio. Predicting when and where a bloom may occur is important to protect the public that uses and consumes a water resource; however, predictions are complicated and likely site specific because of the many factors affecting toxin production. Monitoring for a variety of environmental and water-quality factors, for concentrations of cyanobacteria by molecular methods, and for algal pigments such as chlorophyll and phycocyanin by using optical sensors may provide data that can be used to predict the occurrence of cyanoHABs. To test these monitoring approaches, water-quality samples were collected at Ohio recreational sites during May–November in 2013 and 2014. In 2013, samples were collected monthly at eight sites at eight lakes to facilitate an initial assessment and select sites for more intensive sampling during 2014. In 2014, samples were collected approximately weekly at five sites at three lakes. Physical water-quality parameters were measured at the time of sampling. Composite samples were preserved and analyzed for dissolved and total nutrients, toxins, phytoplankton abundance and biovolume, and cyanobacterial genes by molecular methods. Molecular assays were done to enumerate (1) general cyanobacteria, (2) general Microcystis and Dolichospermum ( Anabaena ), (3) mcyE genes for Microcystis , Dolichospermum ( Anabaena ), and Planktothrix targeting deoxyribonucleic acid (DNA), and (4) mcyE transcripts for Microcystis , Dolichospermum ( Anabaena ), and Planktothrix targeting ribonucleic acid (RNA).The DNA assays for the mcyE gene provide data on cyanobacteria that have the potential to produce microcystin, whereas the RNA assays provide data on cyanobacteria that are actively transcribing the toxin gene. Environmental data were obtained from available online sources. Quality-control (QC) samples were collected and analyzed for all constituents to characterize bias and variability; however, QC data for molecular assays were examined in more detail than for the other constituents. The QC data for molecular assays suggested that sampling variability and qPCR variability were small in comparison with the combined variability associated with sample filtering, extraction and purification, and the matrix itself. A total of 46 water-quality samples were collected during 2013 at 8 beach sites—Buck Creek, Buckeye Crystal, Deer Creek, Harsha Main, Maumee Bay State Park (MBSP) Inland (negative control site), MBSP Lake Erie, Port Clinton, and Sandusky Bay. Microcystin was detected in 67–100 percent of samples at all sites except for MBSP Inland, where microcystin was detected in only 20 percent of samples. Microcystin concentrations ranged from <0.10 to 48 micrograms per liter (µ/L), with the widest range found at MBSP Lake Erie and the highest concentrations found at Buckeye Crystal. Saxitoxin was detected in five samples, and cylindrospermopsin was not detected in any samples. A total of 65 water-quality samples were collected during 2014 at 5 sites on 3 lakes—Buckeye Fairfield and Onion Island, Harsha Main and Campers, and MBSP Lake Erie beach. Four of the sites were bathing beaches and one site, Onion Island, was an offshore boater swim area. Concentrations of microcystin ranged from <0.10 to 240 µ/L and, as in 2013, the widest range was found at MBSP Lake Erie. At Buckeye Lake, microcystin concentrations were consistently high (greater than 20 µ/L), ranging from 23 to 81 µ/L. At Harsha Main and Campers, microcystin concentrations ranged from <0.10 to 15 µ/L. Saxitoxin was detected in four samples collected at MBSP Lake Erie. Throughout the 2014 season, the cyanobacterial community, as determined by molecular and microscopy methods, and the dominance associated with the highest microcystin concentrations were unique to individual lakes. At Buckeye Lake, Planktothrix dominated the cyanobacterial community throughout the season and Planktothrix DNA and RNA were found in 100 percent of samples; Microcystis mcyE DNA was found in low concentrations. At Harsha Lake, Dolichospermum and Microcystis were a substantial percentage of the community from late May through August, and the highest microcystin concentrations occurred in June and July. At MBSP Lake Erie, Microcystis generally dominated from mid-July through early November, and the highest microcystin concentrations occurred in August. Spearman’s correlation coefficient (rho) was computed to determine the relations between environmental and water-quality factors and microcystin concentrations at four sites—Buckeye Fairfield, Buckeye Onion Island, Harsha Main, and MBSP Lake Erie. Factors were evaluated for use as potential independent variables in two types of predictive models—daily and long-term models. Easily or continuously measured water-quality factors and available environmental data are used for daily predictions that do not require a site visit. Data from factors used in daily predictions and results from samples collected and analyzed in a laboratory are used for long-term predictions (a few days to several weeks). A few statistically significant correlations (p ≤ 0.05) between microcystin concentrations and factors for both daily and long-term predictions were found at Buckeye Onion Island, and many were found at Harsha Main and MBSP Lake Erie. There were only a few statistically significant factors for daily predictions at Buckeye Fairfield, likely because of the lack of variability in microcystin concentrations. Among factors for daily predictions, phycocyanin had the highest Spearman’s correlation to microcystin concentrations (rho = 0.79 to 0.93) at all sites except for Buckeye Fairfield. Turbidity, pH, algae category, and Secchi depth were significantly correlated to microcystin concentrations at Harsha Main and MBSP Lake Erie. Algae categories were observational categories from 0 (none) to 4 (extreme). Several discharge variables (Maumee River at Waterville, river mouth is approximately 3.5 miles from the beach) at MBSP Lake Erie were promising environmental factors for daily predictions. In addition to discrete water-quality measurements recorded at Harsha Main at the time of sampling, many manipulated measurements (factors derived from mathematical manipulation of time-series data) available from a nearby continuous monitor were strongly correlated to microcystin concentrations; the highest correlation was found for the relation between microcystin concentrations and the antecedent 7-day average phycocyanin (rho = 0.98). For long-term predictions, the most highly correlated molecular assays were Planktothrix mcyE DNA at Buckeye Onion Island and Microcystis mcyE DNA at Harsha Main and MBSP Lake Erie. Concentrations of several nutrient constituents were significantly correlated to microcystin concentrations including total nitrogen at Buckeye Onion Island, ammonia and nitrate plus nitrite (both negatively correlated) at Harsha Main and MBSP Lake Erie, and total phosphorus at MBSP Lake Erie. The results of this study showed that water-quality and environmental variables are promising for use in site-specific daily or long-term predictive models. In order to develop more accurate models to predict toxin concentrations at freshwater lake sites, data need to be collected more frequently and for consecutive days in future studies.

Ohio↗

USGS2013

Fine-scale hydrologic modeling for regional landscape applications: the California Basin Characterization Model development and performance

Introduction Resource managers need spatially explicit models of hydrologic response to changes in key climatic drivers across variable landscape conditions. We demonstrate the utility of a Basin Characterization Model for California (CA-BCM) to integrate high-resolution data on physical watershed characteristics with historical or projected climate data to predict watershed-specific hydrologic responses. Methods The CA-BCM applies a monthly regional water-balance model to simulate hydrologic responses to climate at the spatial resolution of a 270-m grid. The model has been calibrated using a total of 159 relatively unimpaired watersheds for the California region. Results As a result of calibration, predicted basin discharge closely matches measured data for validation watersheds. The CA-BCM recharge and runoff estimates, combined with estimates of snowpack and timing of snowmelt, provide a basis for assessing variations in water availability. Another important output variable, climatic water deficit , integrates the combined effects of temperature and rainfall on site-specific soil moisture, a factor that plants may respond to more directly than air temperature and precipitation alone. Model outputs are calculated for each grid cell, allowing results to be summarized for a variety of planning units including hillslopes, watersheds, ecoregions, or political boundaries. Conclusions The ability to confidently calculate hydrologic outputs at fine spatial scales provides a new suite of hydrologic predictor variables that can be used for a variety of purposes, such as projections of changes in water availability, environmental demand, or distribution of plants and habitats. Here we present the framework of the CA-BCM model for the California hydrologic region, a test of model performance on 159 watersheds, summary results for the region for the 1981–2010 time period, and changes since the 1951–1980 time period.

California↗

USGS2014

Assessing the solubility controls on vanadium in groundwater, northeastern San Joaquin Valley, CA

The solubility controls on vanadium (V) in groundwater were studied due to concerns over possible harmful health effects of ingesting V in drinking water. Vanadium concentrations in the northeastern San Joaquin Valley ranged from <3 μg/L to 70 μg/L with a median of 21 μg/L. Concentrations of V were highest in samples collected from oxic groundwater (49% > 25 μg/L) and lowest in samples collected from anoxic groundwater (70% < 0.8 μg/L). In oxic groundwater, speciation modeling (SM) using PHREEQC predicted that V exists primarily as the oxyanion H 2 VO 4 − . Adsorption/desorption reactions with mineral surfaces and associated oxide coatings were indicated as the primary solubility control of V 5+ oxyanions in groundwater. Environmental data showed that V concentrations in oxic groundwater generally increased with increasing groundwater pH. However, data from adsorption isotherm experiments indicated that small variations in pH (7.4–8.2) were not likely as an important a factor as the inherent adsorption capacity of oxide assemblages coating the surface of mineral grains. In suboxic groundwater, accurate SM modeling was difficult since Eh measurements of source water were not measured in this study. Vanadium concentrations in suboxic groundwater decreased with increasing pH indicating that V may exist as an oxycationic species [e.g. V(OH) 3 + ]. Vanadium may complex with dissolved inorganic and organic ligands under suboxic conditions, which could alter the adsorption behavior of V in groundwater. Speciation modeling did not predict the existence of V-inorganic ligand complexes and organic ligands were not collected as part of this study. More work is needed to determine processes governing V solubility under suboxic groundwater conditions. Under anoxic groundwater conditions, SM predicts that aqueous V exists as the uncharged V(OH) 3 molecule. However, exceedingly low V concentrations show that V is sparingly soluble in anoxic conditions. Results indicated that V may be precipitating as V 3+ - or mixed V 3+ /Fe 3+ -oxides in anoxic groundwater, which is consistent with results of a previous study. The fact that V appears insoluble in anoxic (Fe reducing) redox conditions indicates that the behavior of V is different than arsenic (As) in aquifer systems where the reductive dissolution of Fe-oxides with As adsorbed to the surface is a well-documented mechanism for increasing As concentrations in groundwater. This hypothesis is supported by the relation of V to As concentrations in oxic versus anoxic redox conditions. Sequential extraction procedures (SEP) applied to aquifer material showed that the greatest amount of V was recovered by the nitric acid (HNO 3 ) extract (37–71%), followed by the oxalate-ascorbic acid extract (19–60%) and the oxalate extract (3–14%). These results indicate that V was not associated with the solid phase as an easily exchangeable fraction. Although the total amount of V recovered was greatest for the HNO 3 extract that targets V adsorbed to sorption sites of crystalline Al, Fe and Mn oxides, the greatest V saturation of sorption sites appeared to occur on the amorphous and poorly crystalline oxide solid phases targeted by the oxalate and oxalate-ascorbic acid extracts respectively. Adsorption isotherm experiments showed no correlation between V sorption and any of the fractions identified by the SEP. This lack of correlation indicates the application of an SEP alone is not adequate to estimate the sorption characteristics of V in an aquifer system.

California↗

USGS2001

Recent growth of conifer species of western North America: Assessing spatial patterns of radial growth trends

We explored spatial patterns of low-frequency variability in radial tree growth among western North American conifer species and identified predictors of the variability in these patterns. Using 185 sites from the International Tree-Ring Data Bank, each of which contained 10a??60 raw ring-width series, we rebuilt two chronologies for each site, using two conservative methods designed to retain any low-frequency variability associated with recent environmental change. We used factor analysis to identify regional low-frequency patterns in site chronologies and estimated the slope of the growth trend since 1850 at each site from a combination of linear regression and time-series techniques. This slope was the response variable in a regression-tree model to predict the effects of environmental gradients and species-level differences on growth trends. Growth patterns at 27 sites from the American Southwest were consistent with quasi-periodic patterns of drought. Either 12 or 32 of the 185 sites demonstrated patterns of increasing growth between 1850 and 1980 A.D., depending on the standardization technique used. Pronounced growth increases were associated with high-elevation sites (above 3000 m) and high-latitude sites in maritime climates. Future research focused on these high-elevation and high-latitude sites should address the precise mechanisms responsible for increased 20th century growth.

Canadian Journal of Forest Research↗

USGS2024

Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA

Grass carp ( Ctenopharyngodon idella ), an invasive cyprinid within the Laurentian Great Lakes, is naturally reproducing in several Lake Erie tributaries, which has raised concerns of the species’ spread throughout Lake Erie and the other Great Lakes. Knowledge of the recent invasion extent outside of the western basin of Lake Erie, particularly in eastern tributaries and nearshore waters, is limited. Understanding the invasion extent would improve the efficacy of ongoing coordinated multi-agency control efforts. Molecular tools, such as environmental DNA (eDNA), have shown promise for early detection of aquatic invasive species. In this study, water samples (N = 476) were collected for grass carp eDNA monthly between May and November in 2018 and 2019, at three sites in the Michigan waters of Lake Erie and the Detroit River. We fit Bayesian multi-scale occupancy models to determine differences in eDNA capture and detection probability among grass carp qPCR assays, sampling sites, and across time. To determine whether grass carp were physically present, and to validate eDNA samples, we quantified recent grass carp presence in sampled areas using an existing acoustic telemetry and field sampling framework. Our results indicate that grass carp eDNA capture probability differed among sites, but there was no difference among months. Positive grass carp eDNA detections were observed across multiple months at each site, with 69% of site-specific sampling events testing positive for grass carp eDNA on at least one assay and replicate. The majority (65%) of weeks where positive eDNA sampling detections occurred also concurrently had one or more grass carp detected via acoustic telemetry 1–6 days prior. Our results highlight the potential utility of using eDNA to monitor the invasion extent of grass carp within the nearshore waters of Lake Erie. However, further evaluation of the factors that influence grass carp eDNA characteristics among sites within Lake Erie are needed to determine its efficacy for surveillance protocols by natural resource management agencies.

Lake Erie↗

USGS2018

Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling

A wide range of research shows that nutrient availability strongly influences terrestrial carbon (C) cycling and shapes ecosystem responses to environmental changes and hence terrestrial feedbacks to climate. Nonetheless, our understanding of nutrient controls remains far from complete and poorly quantified, at least partly due to a lack of informative, comparable, and accessible datasets at regional-to-global scales. A growing research infrastructure of multi-site networks are providing valuable data on C fluxes and stocks and are monitoring their responses to global environmental change and measuring responses to experimental treatments. These networks thus provide an opportunity for improving our understanding of C-nutrient cycle interactions and our ability to model them. However, coherent information on how nutrient cycling interacts with observed C cycle patterns is still generally lacking. Here, we argue that complementing available C-cycle measurements from monitoring and experimental sites with data characterizing nutrient availability will greatly enhance their power and will improve our capacity to forecast future trajectories of terrestrial C cycling and climate. Therefore, we propose a set of complementary measurements that are relatively easy to conduct routinely at any site or experiment and that, in combination with C cycle observations, can provide a robust characterization of the effects of nutrient availability across sites. In addition, we discuss the power of different observable variables for informing the formulation of models and constraining their predictions. Most widely available measurements of nutrient availability often do not align well with current modelling needs. This highlights the importance to foster the interaction between the empirical and modelling communities for setting future research priorities.

Environmental Research Letters↗

USGS1994

Accuracy, reproducibility, and interpretation of fatty acid methyl ester profiles of model bacterial communities

We determined the accuracy and reproducibility of whole-community fatty acid methyl ester (FAME) analysis with two model bacterial communities differing in composition by using the Microbial ID, Inc. (MIDI), system. The biomass, taxonomic structure, and expected MIDI-FAME profiles under a variety of environmental conditions were known for these model communities a priori. Not all members of each community could be detected in the composite profile because of lack of fatty acid 'signatures' in some isolates or because of variations (approximately fivefold) in fatty acid yield across taxa. MIDI- FAME profiles of replicate subsamples of a given community were similar in terms of fatty acid yield per unit of community dry weight and relative proportions of specific fatty acids. Principal-components analysis (PCA) of MIDI-FAME profiles resulted in a clear separation of the two different communities and a clustering of replicates of each community from two separate experiments on the first PCA axis. The first PCA axis accounted for 57.1% of the variance in the data and was correlated with fatty acids that varied significantly between communities and reflected the underlying community taxonomic structure. On the basis of our data, community fatty acid profiles can be used to assess the relative similarities and differences of microbial communities that differ in taxonomic composition. However, detailed interpretation of community fatty acid profiles in terms of biomass or community taxonomic composition must be viewed with caution until our knowledge of the quantitative and qualitative distribution of fatty acids over a wide variety of taxa and the effects of growth conditions on fatty acid profiles is more extensive.

Applied and Environmental Microbiology↗