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At least 343 records · Page 19Linked to original sources
USGS2025

Potential water-quality and hydrology stressors on freshwater mussels with development of environmental DNA assays for selected mussels and macroinvertebrates in Big Darby Creek Basin, Ohio, 2020–22

The richness and abundance of freshwater mussels in the Big Darby Creek Basin has declined in recent decades, according to survey results published by the Ohio Biological Survey. In October 2016, a major mussel die-off of undetermined cause reportedly affected over 50 miles of Big Darby Creek; however, fishes and other wildlife were not noticeably impacted. Pollution, habitat destruction, climate change, and hydrologic modification have all been theorized as potential reasons for the widespread declines in freshwater mussel populations in North America. To better understand potential stressors to mussels and other aquatic organisms in the Big Darby Creek Basin, the U.S. Geological Survey, in cooperation with the Ohio Water Development Authority, evaluated water quality and temporal changes in hydrology at selected locations. In addition, environmental deoxyribonucleic acid (eDNA) quantitative polymerase chain reaction (qPCR) assays were developed to detect the presence of selected mussels and macroinvertebrates using stream water. Time-weighted average concentrations of pesticides, organic wastewater compounds (OWCs), and polycyclic aromatic hydrocarbons (PAHs) were determined for selected locations within the Big Darby Creek Basin. Passive samplers designed to mimic the respiratory exposure of aquatic organisms and the bioconcentration of organic contaminants into their fatty tissues were deployed three times annually at three sites within the Big Darby Creek Basin in 2020 and 2021. Analyses were done for 204 pesticide compounds, 38 OWCs, and 33 PAHs. Of the 204 pesticide compounds, 70 were detected in at least one sample; 30 were detected in all samples. Herbicides and herbicide degradates were the pesticides most frequently detected and also had some of the highest concentrations of the pesticides detected in this study. Three herbicides (atrazine, ametryn, and metribuzin) were detected in at least 88 percent of samples and two fungicides (azoxystrobin and propiconazole) were detected in all samples. Of the 38 OWCs, 24 were detected in at least one sample; however, only one ( N , N -diethyltoluamide [DEET]) was detected in all samples. Of the 33 PAHs, 29 were detected in at least one sample; 12 were detected in all samples. A continuous water-quality monitor was operated seasonally on Big Darby Creek above Georgesville, Ohio, from 2020 to 2022. Dissolved oxygen concentrations generally followed a daily cycle, peaking in early evening and troughing around sunrise. There were occasional 24-hour swings in dissolved oxygen concentration that had a range exceeding 10 milligrams per liter. However, dissolved oxygen concentrations never fell below Ohio’s aquatic life criteria for warmwater habitats (outside of mixing zones) of 4.0 milligrams per liter as an instantaneous minimum and 5.0 milligrams per liter as a minimum 24-hour average. The Ohio water-quality criteria for temperatures are 29.4 degrees Celsius as an instantaneous maximum and 27.8 degrees Celsius as a 24-hour average maximum. In 2020, there were 10 days when the maximum instantaneous value for temperature was exceeded and 3 consecutive days when the maximum 24-hour average temperature was exceeded. Streamflow time-series data from three gaging stations within the Big Darby Creek Basin were evaluated for trends in annual flow statistics and daily nonexceedance probabilities over time. In general, the evaluation of streamflow conditions at the Big Darby Creek gage (with 97 years of record) indicated that streamflow changed between water years 1922 and 2021. During that time span, flows in general increased, the number of high-flow pulses became more frequent, and low-flow pulses and extreme low-flow periods became less frequent. The only strong indication of trends over time in annual flow statistics for the relatively short records for the other two gages (on Little Darby Creek, with 25 years of record, and Hellbranch Run, with 29 years of record) was that as time went on, reversals between rising and falling periods became more frequent. The U.S. Geological Survey Ohio Water Microbiology Laboratory developed eDNA qPCR assays to detect Epioblasma rangiana (northern riffleshell mussels), Chimarra obscura (a species of caddisfly), Maccaffertium pulchellum (a species of mayfly), and optimized a preexisting eDNA qPCR assay to detect for Ptychobranchus fasciolaris (kidneyshell mussels). The assays were validated by using environmental sampling methods. Assay sensitivity was established by determining the limits of detection and quantification. Water samples were collected at 12 sites in the Big Darby Creek Basin between 2020 and 2022 and analyzed for eDNA with the qPCR assays developed for this study.

Ohio↗
USGS2025

Computing discharge using the entropy-based probability concept

This report describes the techniques and methods for computing the mean-channel velocity and discharge using the entropy-based probability concept (probability concept). The method is an alternative to or augments standard streamgaging methods adopted by the U.S. Geological Survey (USGS). Although sensor technology for measuring the mean velocity and discharge has advanced, standard streamgaging and computational methods have remained relatively unchanged since the USGS established its first streamgage at the Rio Grande at Embudo, New Mexico in 1889. Standard streamgaging methods rely on integrating velocities and depths measured at multiple verticals at a channel cross section (standard cross section) to compute a discharge. The probability concept computes discharge at a single vertical (y-axis) using the ratio of the mean-channel velocity (mean velocity) and maximum velocity, the measured maximum velocity, and the area as a function of stage at the standard cross section. Proper siting and operation and maintenance are required. If siting is conducted appropriately, the probability concept parameters and the y-axis stationing will be similar for different streamflow conditions. The timing of operation and maintenance visits should be based on hydrologic and meteorologic occurrences and seasonality and should capture low, medium, high, and opportunistic streamflow conditions. Advantages of the probability concept are the capacity to (1) compute discharge time series immediately after streamgage siting, (2) compute discharge for complex streamflow conditions that cannot be quantified by stage-discharge methods, (3) augment time-series data where gaps exist, and (4) integrate with surface velocity sensors such as Doppler velocity radars and cameras, which are not subject to damage caused by ice, debris, and flood flows. Potential sources of bias in discharge derived from the probability concept include (1) rain, (2) wind, and (3) geomorphologic and hydraulic instabilities. Recommendations to address these biases are provided. This report guides users through the steps to parameterize the probability concept, process field data, and compute the mean velocity and discharge using the probability concept.

Techniques and Methods↗
USGS2012

Approaches in highly parameterized inversion: TSPROC, a general time-series processor to assist in model calibration and result summarization

The TSPROC ( T ime S eries PROC essor) computer software uses a simple scripting language to process and analyze time series. It was developed primarily to assist in the calibration of environmental models. The software is designed to perform calculations on time-series data commonly associated with surface-water models, including calculation of flow volumes, transformation by means of basic arithmetic operations, and generation of seasonal and annual statistics and hydrologic indices. TSPROC can also be used to generate some of the key input files required to perform parameter optimization by means of the PEST ( P arameter EST imation) computer software. Through the use of TSPROC, the objective function for use in the model-calibration process can be focused on specific components of a hydrograph.

Techniques and Methods↗
USGS2001

Trends in peak flows of selected streams in Kansas

The possibility of a systematic change in flood potential led to an investigation of trends in the magnitude of annual peak flows in Kansas. Efficient design of highway bridges and other flood-plain structures depends on accurate understanding of flood characteristics. The Kendall's tau test was used to identify trends at 40 stream-gaging stations during the 40-year period 1958–97. Records from 13 (32 percent) of the stations showed significant trends at the 95-percent confidence level. Only three of the records (8 percent) analyzed had increasing trends, whereas 10 records (25 percent) had decreasing trends, all of which were for stations located in the western one-half of the State. An analysis of flow volume using mean annual discharge at 29 stations in Kansas resulted in 6 stations (21 percent) with significant trends in flow volumes. All six trends were decreasing and occurred in the western one-half of the State. The Kendall's tau test also was used to identify peak-flow trends over the entire period of record for 54 stream-gaging stations in Kansas. Of the 23 records (43 percent) showing significant trends, 16 (30 percent) were decreasing, and 7 (13 percent) were increasing. The trend test then was applied to 30-year periods moving in 5-year increments to identify time periods within each station record when trends were occurring. Systematic changes in precipitation patterns and long-term declines in ground-water levels in some stream basins may be contributing to peak-flow trends. To help explain the cause of the streamflow trends, the Kendall's tau test was applied to total annual precipitation and ground-water levels in Kansas. In western Kansas, the lack of precipitation and presence of decreasing trends in ground-water levels indicated that declining water tables are contributing to decreasing trends in peak streamflow. Declining water tables are caused by ground-water withdrawals and other factors such as construction of ponds and terraces. Peak-flow records containing trends introduce statistical error into flood-frequency analysis. To examine the effect of trends on flood-frequency analysis, statistically significant trends were added systematically to four nontrending station records. Flood magnitudes estimated on the basis of each data series were compared. The added trends resulted in changes in the 100-year flood magnitudes of as much as 70 percent.

Kansas↗
USGS1997

Relations of Tualatin River water temperatures to natural and human-caused factors

Aquatic research has long shown that the survival of cold-water fish, such as salmon and trout, decreases markedly as water temperatures increase above a critical threshold, particularly during sensitive life stages of the fish. In an effort to improve the overall health of aquatic ecosystems, the State of Oregon in 1996 adopted a maximum water-temperature standard of 17.8 degrees Celsius (68 degrees Fahrenheit), based on a 7-day moving average of daily maximum temperatures, for most water bodies in the State. Anthropogenic activities are not permitted to raise the temperature of a water body above this level. In the Tualatin River, a tributary of the Willamette River located in northwestern Oregon, water temperatures periodically surpass this threshold during the low-flow summer and fall months.An investigation by the U.S. Geological Survey quantified existing seasonal, diel, and spatial patterns of water temperatures in the main stem of the river, assessed the relation of water temperatures to natural climatic conditions and anthropogenic factors (such as wastewater-treatment-plant effluent and modification of riparian shading), and assessed the impact of various flow management practices on stream temperatures. Half-hourly temperature measurements were recorded at 13 monitoring sites from river mile (RM) 63.9 to RM 3.4 from May to November of 1994. Four synoptic water- temperature surveys also were conducted in the upstream and downstream vicinities of two wastewater-treatment-plant outfalls. Temperature and streamflow time-series data were used to calibrate two dynamic-flow heat-transfer models, DAFLOW-BLTM (RM 63.9-38.4) and CE-QUAL-W2 (RM 38.4-3.4). Simulations from the models provided a basis for approximating 'natural' historical temperature patterns, performing effluent and riparian-shading sensitivity analyses, and evaluating mitigation management scenarios under 1994 climatic conditions. Findings from the investigation included (1) under 'natural' conditions the temperature of the river would exceed the State standard of 17.8 degrees Celsius at many locations during the low-flow season, (2) current operation of wastewater-treatment plants increases the temperature of the river downstream of the plants under low-flow conditions, (3) river temperature is significantly affected by riparian shade variations along both the tributaries and the main stem, (4) flow releases during the low-flow season from the Henry Hagg Lake reservoir decrease the river temperature in the upper section, and (5) removal of a low diversion dam at RM 3.4 would slightly decrease temperatures below RM 10.0.

Oregon↗
USGS1998

A demonstration of the instream flow incremental methodology, Shenandoah River, Virginia

Current and projected demands on the water resources of the Shenandoah River have increased concerns for the potential effect of these demands on the natural integrity of the Shenandoah River system. The Instream Flow Incremental Method (IFIM) process attempts to integrate concepts of water-supply planning, analytical hydraulic engineering models, and empirically derived habitat versus flow functions to address water-use and instream-flow issues and questions concerning life-stage specific effects on selected species and the general well being of aquatic biological populations. The demonstration project also sets the stage for the identification and compilation of the major instream-flow issues in the Shenandoah River Basin, development of the required multidisciplinary technical team to conduct more detailed studies, and development of basin specific habitat and flow requirements for fish species, species assemblages, and various water uses in the Shenandoah River Basin. This report presents the results of an IFIM demonstration project, conducted on the main stem Shenandoah River in Virginia, during 1996 and 1997, using the Physical Habitat Simulation System (PHABSIM) model. Output from PHABSIM is used to address the general flow requirements for water supply and recreation and habitat for selected life stages of several fish species. The model output is only a small part of the information necessary for effective decision making and management of river resources. The information by itself is usually insufficient for formulation of recommendations regarding instream-flow requirements. Additional information, for example, can be obtained by analysis of habitat time-series data, habitat duration data, and habitat bottlenecks. Alternative-flow analysis and habitat-duration curves are presented.

Virginia↗
USGS2021

Geochemistry of coastal permafrost and erosion-driven organic matter fluxes to the Beaufort Sea near Drew Point, Alaska

Accelerating erosion of the Alaska Beaufort Sea coast is increasing inputs of organic matter from land to the Arctic Ocean, and improved estimates of organic matter stocks in eroding coastal permafrost are needed to assess their mobilization rates under contemporary conditions. We collected three permafrost cores (4.5–7.5 m long) along a geomorphic gradient near Drew Point, Alaska, where recent erosion rates average 17.2 m year −1 . Down-core patterns indicate that organic-rich soils and lacustrine sediments (12–45% total organic carbon; TOC) in the active layer and upper permafrost accumulated during the Holocene. Deeper permafrost (below 3 m elevation) mainly consists of Late Pleistocene marine sediments with lower organic matter content (∼1% TOC), lower C:N ratios, and higher δ 13 C values. Radiocarbon-based estimates of organic carbon accumulation rates were 11.3 ± 3.6 g TOC m −2 year −1 during the Holocene and 0.5 ± 0.1 g TOC m −2 year −1 during the Late Pleistocene (12–38 kyr BP). Within relict marine sediments, porewater salinities increased with depth. Elevated salinity near sea level (∼20–37 in thawed samples) inhibited freezing despite year-round temperatures below 0°C. We used organic matter stock estimates from the cores in combination with remote sensing time-series data to estimate carbon fluxes for a 9 km stretch of coastline near Drew Point. Erosional fluxes of TOC averaged 1,369 kg C m −1 year −1 during the 21st century (2002–2018), nearly doubling the average flux of the previous half-century (1955–2002). Our estimate of the 21st century erosional TOC flux year −1 from this 9 km coastline (12,318 metric tons C year −1 ) is similar to the annual TOC flux from the Kuparuk River, which drains a 8,107 km 2 area east of Drew Point and ranks as the third largest river on the North Slope of Alaska. Total nitrogen fluxes via coastal erosion at Drew Point were also quantified, and were similar to those from the Kuparuk River. This study emphasizes that coastal erosion represents a significant pathway for carbon and nitrogen trapped in permafrost to enter modern biogeochemical cycles, where it may fuel food webs and greenhouse gas emissions in the marine environment.

Alaska↗
USGS2022

Assessing the accuracy and potential for improvement of the national land cover database’s tree canopy cover dataset in urban areas of the conterminous United States

The National Land Cover Database (NLCD) provides time-series data characterizing the land surface for the United States, including land cover and tree canopy cover (NLCD-TC). NLCD-TC was first published for 2001, followed by versions for 2011 (released in 2016) and 2011 and 2016 (released in 2019). As the only nationwide tree canopy layer, there is value in assessing NLCD-TC accuracy, given the need for cross-city comparisons of urban forest characteristics. Accuracy assessments have only been conducted for the 2001 data and suggest substantial inaccuracies for that dataset in cities. For the most recent NLCD-TC version, we used various datasets that characterize the built environment, weather, and climate to assess their accuracy in different contexts within 27 cities. Overall, NLCD underestimates tree canopy in urban areas by 9.9% when compared to estimates derived from those high-resolution datasets. Underestimation is greater in higher-density urban areas (13.9%) than in suburban areas (11.0%) and undeveloped areas (6.4%). To evaluate how NLCD-TC error in cities could be reduced, we developed a decision tree model that uses various remotely sensed and built-environment datasets such as building footprints, urban morphology types, NDVI (Normalized Difference Vegetation Index), and surface temperature as explanatory variables. This predictive model removes bias and improves the accuracy of NLCD-TC by about 3%. Finally, we show the potential applications of improved urban tree cover data through the examples of ecosystem accounting in Seattle, WA, and Denver, CO. The outputs of rainfall interception and urban heat mitigation models were highly sensitive to the choice of tree cover input data. Corrected data brought results closer to those from high-resolution model runs in all cases, with some variation by city, model, and ecosystem type. This suggests paths forward for improving the quality of urban environmental models that require tree canopy data as a key model input.

Remote Sensing↗
USGS2026

Climate-adaptive urban planning: Quantitative assessment of drought impacts and practical strategies for climate-resilient urban green spaces

Urban green spaces (UGSs) are vital for enhancing a city’s resilience and livability; however, their functionality is increasingly jeopardized by drought, particularly in water-scarce regions. This study evaluates drought impact on UGSs in Metropolitan Adelaide, Australia, a representative semi-arid urban system, using satellite-derived Normalized Difference Vegetation Index (NDVI) time-series data spanning 2000–2020. Vegetation dynamics were analyzed through Seasonal-Trend decomposition using Loess (STL), standardized anomaly assessment, lagged Pearson correlation, Ordinary Least Squares (OLS) regression, and Mann–Kendall trend analysis. To isolate climatically sensitive signals, 29 urban lawn patches were examined separately from mixed urban canopy, given their shallow root systems and direct dependence on surface moisture. NDVI declined by approximately 0.09 units during the Millennium Drought (2001–2009), with summer greenness deficits reaching 24% below the 20-year benchmark. Temperature was the dominant driver of lawn NDVI variability (r = −0.863, R 2 = 74.5%), substantially exceeding the effect of rainfall (r = 0.156, R 2 = 2.4%). El Niño–Southern Oscillation (ENSO) cycles modulated vegetation responses, with La Niña years supporting recovery and El Niño years amplifying decline. Post-drought recovery remained incomplete, with NDVI deficits of 8–20% persisting through 2020; full recovery was observed only in 2017, coinciding with the highest recorded summer rainfall. No significant directional trend was detected over the full study period (Mann–Kendall τ = 0.005, p = 0.908). These findings demonstrate that heat, rather than water limitation alone, is the primary driver of vegetation stress in urban systems, highlighting the benefits of integrated management strategies that address both warming and moisture deficits to sustain urban green infrastructure under future climate conditions. We introduce the concept of “urban greenery drought,” referring to a form of vegetation stress in managed urban landscapes where greenness is reduced primarily by elevated temperature and atmospheric demand despite water availability.

Adelaide↗
USGS2021

HydroMet: A new code for automated objective optimization of hydrometeorological thresholds for landslide initiation

Landslide detection and warning systems are important tools for mitigation of potential hazards in landslide prone areas. Traditionally, warning systems for shallow landslides have been informed by rainfall intensity-duration thresholds. More recent advances have introduced the concept of hydrometeorological thresholds that are informed not only by rainfall, but also by subsurface hydrological measurements. Previously, hydrometeorological thresholds have been shown to improve capabilities for forecasting shallow landslides, and they may ultimately be adapted to more generalized landslide forecasting. We present HydroMet, a code developed in Python by the U.S. Geological Survey, which allows users to guide the automated estimation of hydrometeorological thresholds for a site or area of interest, with the flexibility to select preferred threshold variables for the antecedent hydrologic conditions and the triggering meteorological conditions. Users can import hydrologic time-series data, including rainfall, soil-water content, and pore-water pressure, along with the times of known landslide occurrences, and then conduct objective optimization of warning thresholds using receiver operating characteristics. HydroMet presents many additional options, including selecting the threshold formula, the timescale of possible threshold variables, and the skill statistics used for optimization. Users can develop dual-stage thresholds for watch and warning alerts, with a lower, risk-averse threshold to avoid missed alarms and a less conservative threshold to minimize false alarms. Users may also choose to split their inventory data into calibration and evaluation subsets to independently evaluate the performance of optimized thresholds. We present output and applications of HydroMet using monitoring data from landslide-prone areas in the U.S. to demonstrate its utility and ability to produce thresholds with limited missed and false alarms for informing the next generation of reliable landslide warning systems.

Water↗
USGS2016

Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain

Estuarine navigation channels have long been recognized as conduits for saltwater intrusion into coastal wetlands. Salt flux decomposition and time series measurements of velocity and salinity were used to examine salt flux components and drivers of baroclinic and barotropic exchange in the Houma Navigation Channel, an estuarine channel located in the Mississippi River delta plain that receives substantial freshwater inputs from the Mississippi-Atchafalaya River system at its inland extent. Two modes of vertical current structure were identified from the time series data. The first mode, accounting for 90% of the total flow field variability, strongly resembled a barotropic current structure and was coherent with alongshelf wind stress over the coastal Gulf of Mexico. The second mode was indicative of gravitational circulation and was linked to variability in tidal stirring and the horizontal salinity gradient along the channel’s length. Tidal oscillatory salt flux was more important than gravitational circulation in transporting salt upestuary, except over equatorial phases of the fortnightly tidal cycle during times when river inflows were minimal. During all tidal cycles sampled, the advective flux, driven by a combination of freshwater discharge and wind-driven changes in storage, was the dominant transport term, and net flux of salt was always out of the estuary. These findings indicate that although human-made channels can effectively facilitate inland intrusion of saline water, this intrusion can be minimized or even reversed when they are subject to significant freshwater inputs.

Louisiana↗
USGS2012

Perils of correlating CUSUM-transformed variables to infer ecological relationships (Breton et al. 2006; Glibert 2010)

We comment on a nonstandard statistical treatment of time-series data first published by Breton et al. (2006) in Limnology and Oceanography and, more recently, used by Glibert (2010) in Reviews in Fisheries Science. In both papers, the authors make strong inferences about the underlying causes of population variability based on correlations between cumulative sum (CUSUM) transformations of organism abundances and environmental variables. Breton et al. (2006) reported correlations between CUSUM-transformed values of diatom biomass in Belgian coastal waters and the North Atlantic Oscillation, and between meteorological and hydrological variables. Each correlation of CUSUM-transformed variables was judged to be statistically significant. On the basis of these correlations, Breton et al. (2006) developed "the first evidence of synergy between climate and human-induced river-based nitrate inputs with respect to their effects on the magnitude of spring Phaeocystis colony blooms and their dominance over diatoms."

Limnology and Oceanography↗
USGS2014

Uncertainty and extreme events in future climate and hydrologic projections for the Pacific Northwest: providing a basis for vulnerability and core/corridor assessments

The purpose of this project was to (1) provide an internally-consistent set of downscaled projections across the Western U.S., (2) include information about projection uncertainty, and (3) assess projected changes of hydrologic extremes. These objectives were designed to address decision support needs for climate adaptation and resource management actions. Specifically, understanding of uncertainty in climate projections – in particular for extreme events – is currently a key scientific and management barrier to adaptation planning and vulnerability assessment. The new dataset fills in the Northwest domain to cover a key gap in the previous dataset, adds additional projections (both from other global climate models and a comparison with dynamical downscaling) and includes an assessment of changes to flow and soil moisture extremes. This new information can be used to assess variations in impacts across the landscape, uncertainty in projections, and how these differ as a function of region, variable, and time period. In this project, existing University of Washington Climate Impacts Group (UW CIG) products were extended to develop a comprehensive data archive that accounts (in a reigorous and physically based way) for climate model uncertainty in future climate and hydrologic scenarios. These products can be used to determine likely impacts on vegetation and aquatic habitat in the Pacific Northwest (PNW) region, including WA, OR, ID, northwest MT to the continental divide, northern CA, NV, UT, and the Columbia Basin portion of western WY New data series and summaries produced for this project include: 1) extreme statistics for surface hydrology (e.g. frequency of soil moisture and summer water deficit) and streamflow (e.g. the 100-year flood, extreme 7-day low flows with a 10-year recurrence interval); 2) snowpack vulnerability as indicated by the ratio of April 1 snow water to cool-season precipitation; and, 3) uncertainty analyses for multiple climate scenarios.

Arizona, California, Colorado, Idaho, Montana, Nev↗
USGS2015

Estimating concentrations of fine-grained and total suspended sediment from close-range remote sensing imagery

Fluvial sediment, a vital surface water resource, is hazardous in excess. Suspended sediment, the most prevalent source of impairment of river systems, can adversely affect flood control, navigation, fisheries and aquatic ecosystems, recreation, and water supply (e.g., Rasmussen et al., 2009; Qu, 2014). Monitoring programs typically focus on suspended-sediment concentration (SSC) and discharge (SSQ). These time-series data are used to study changes to basin hydrology, geomorphology, and ecology caused by disturbances. The U.S. Geological Survey (USGS) has traditionally used physical sediment sample-based methods (Edwards and Glysson, 1999; Nolan et al., 2005; Gray et al., 2008) to compute SSC and SSQ from continuous streamflow data using a sediment transport-curve (e.g., Walling, 1977) or hydrologic interpretation (Porterfield, 1972). Accuracy of these data is typically constrained by the resources required to collect and analyze intermittent physical samples. Quantifying SSC using continuous instream turbidity is rapidly becoming common practice among sediment monitoring programs. Estimations of SSC and SSQ are modeled from linear regression analysis of concurrent turbidity and physical samples. Sediment-surrogate technologies such as turbidity promise near real-time information, increased accuracy, and reduced cost compared to traditional physical sample-based methods (Walling, 1977; Uhrich and Bragg, 2003; Gray and Gartner, 2009; Rasmussen et al., 2009; Landers et al., 2012; Landers and Sturm, 2013; Uhrich et al., 2014). Statistical comparisons among SSQ computation methods show that turbidity-SSC regression models can have much less uncertainty than streamflow-based sediment transport-curves or hydrologic interpretation (Walling, 1977; Lewis, 1996; Glysson et al., 2001; Lee et al., 2008). However, computation of SSC and SSQ records from continuous instream turbidity data is not without challenges; some of these include environmental fouling, calibration, and data range among sensors. Of greatest interest to many programs is a hysteresis in the relationship between turbidity and SSC, attributed to temporal variation of particle size distribution (Landers and Sturm, 2013; Uhrich et al., 2014). This phenomenon causes increased uncertainty in regression-estimated values of SSC, due to changes in nephelometric reflectance off the varying grain sizes in suspension (Uhrich et al., 2014). Here, we assess the feasibility and application of close-range remote sensing to quantify SSC and particle size distribution of a disturbed, and highly-turbid, river system. We use a consumer-grade digital camera to acquire imagery of the river surface and a depth-integrating sampler to collect concurrent suspended-sediment samples. We then develop two empirical linear regression models to relate image spectral information to concentrations of fine sediment (clay to silt) and total suspended sediment. Before presenting our regression model development, we briefly summarize each data-acquisition method.

Conference Paper↗
USGS2014

Linking environmental variability to population and community dynamics

Linking population and community responses to environmental variability lies at the heart of ecology, yet methodological approaches vary and existence of broad patterns spanning taxonomic groups remains unclear. We review the characteristics of environmental and biological variability. Classic approaches to link environmental variability to population and community variability are discussed as are the importance of biotic factors such as life history and community interactions. In addition to classic approaches, newer techniques such as information theory and artificial neural networks are reviewed. The establishment and expansion of observing networks will provide new long-term ecological time-series data, and with it, opportunities to incorporate environmental variability into research. This review can help guide future research in the field of ecological and environmental variability.

Book chapter↗
USGS1994

A seabird monitoring program for the North Pacific

Seabird monitoring is the accumulation of time series data on any aspect of seabird distribution, abundance, demography, or behavior. Typical studies include annual or less frequent measures of numbers or productivity; less commonly, the focus is on marine habitat use, phenology, food habits, or survival. The key requirement is that observations are replicated over time and made with sufficient precision and accuracy to permit the meaningful analysis of variability and trends. Along the Pacific coast of North America, seabird monitoring has consumed substantial amounts of public funding since the early 1970s. The effort has been largely uncoordinated among the many entities involved, including provincial, state, and federal agencies, some private organizations, university faculty, and students. We reaffirm the rationale for monitoring seabirds, review briefly the nature and accomplishments of the existing effort, and suggest actions needed to improve the effectiveness of seabird monitoring in the Pacific. In particular, we propose and describe a comprehensive Seabird Monitoring Database designed specifically to work with observations on seabird population parameters that are replicated over time.

Transactions of the North American Wildlife and Na↗
USGS2014

2013 status of the Lake Ontario lower trophic levels

Phosphorus showed high variation across nearshore (10 m depth) sites but was more stable at offshore (20 m and deeper) stations. In June and July, sites at the mouth of the Niagara River and at Oak Orchard had high phosphorus concentrations (20 – 46 μg/L). Epilimnetic average April-Oct total phosphorus (TP) ranged between 6.9 and 19.9 μg/L in the nearshore and between 5.8 and 10.2 μg/L in the offshore. Average April-Oct soluble reactive phosphorus (SRP) ranged from 0.9 to 7.3 μg/L in the nearshore and 0.8 to 1.4 μg/L in the offshore. TP and SRP were significantly higher in the nearshore than in the offshore. Spring TP has declined in the longer data series (since 1981), but not since 1995. It averaged 8.4 μg/L in the nearshore and 5.0 μg/L in the offshore in 2013—below the 10 μg/L target set by the Great Lakes Water Quality Agreement of 1978 for offshore waters of Lake Ontario. Offshore summer chlorophyll-a declined significantly in both the short- (1995-2013) and long-term (1981-2013) time series at a rate of 3-4% per year. Nearshore chlorophyll-a increased after 2003 but then declined again after 2009. Epilimnetic chlorophyll-aaveraged between 0.5 and 1.3 μg/L across sites with no difference between nearshore and offshore habitats. Average seasonal Secchi disk depth ranged from 4.5 m to 10.6 m and was higher in the offshore (average 8.1 m) than nearshore stations (6.3 m). These values are indicative of oligotrophic conditions in both habitats. In 2013, Apr/May - Oct epilimnetic zooplankton size and total biomass were significantly higher in the offshore than the nearshore. However, with the exception of Limnocalanus (higher in offshore), there were no differences between habitats for any of the zooplankton groups. Most of the zooplankton biomass was in the metalimnion and hypolimnion during the day in 2013. Between 65 and 98% of zooplankton biomass was found below the thermocline throughout the year. The predatory cladoceran Cercopagis continued to be abundant in the summer, peaking at ~7 mg/m3in the offshore. Bythotrephes peaked in October (~0.7 mg/m3), but Bythotrephes biomass was at its lowest biomass in both offshore and nearshore stations since 2005. Summer nearshore zooplankton density and biomass have declined significantly since 1995 at rates of 9-10% per year. Nearshore epilimnetic zooplankton density and biomass have remained stable since 2005 at low levels relative to previous years. Summer offshore zooplankton density and biomass in the epilimnion of Lake Ontario have also declined since 1995 at rates of 10-14% per year, but those declines are marginally significant; density declined significantly in the long-term (since 1981) but has remained at a lower stable level since 2005. Bosminid and cyclopoid copepod biomass declined significantly in nearshore waters. The same pattern occurred in the offshore but declines were significant for bosminids and marginally significant for cyclopoid copepods. Daphnid biomass has also declined significantly in the nearshore. The decline in Daphnid biomass nearshore and Bythotrephes biomass offshore and nearshore is indicative of increased planktivory by alewife. Significant declines in Bosminid and cyclopoid copepod biomass is indicative of increased invertebrate predation by Cercopagis and Bythotrephes in recent years.

Lake Ontario↗
USGS2015

2014 status of the Lake Ontario lower trophic levels

Soluble reactive phosphorus (SRP) concentrations have been stable in nearshore and offshore habitats since 1998 (0.4 – 3.3 μg/L). SRP concentrations were low in 2014; Apr/May – Oct mean values were <1 μg/L at most sites. Spring TP concentrations at individual sites exceeded 10 μg/L on occasion, but spring means were below the 10 μg/L target set by the Great Lakes Water Quality Agreement of 1978 for offshore waters of Lake Ontario. TP concentrations were low at both nearshore and offshore locations; Apr/May – Oct mean values from individual sites ranged from 4.6 – 9.1 μg/L. Spring TP has declined significantly in the longer data series (since 1981), but not since 1995 indicating stable nutrient loading into Lake Ontario for nearly two decades. It averaged 7.8 μg/L in the nearshore and 5.6 μg/L in the offshore in 2014. Chlorophyll-a and secchi depth values are indicative of oligotrophic conditions in nearshore and offshore habitats. Offshore summer chlorophyll-a declined significantly in both the short- (2000-2014) and long-term (1981-2014) time series at a rate of 4-6% per year. Nearshore chlorophyll-a increased after 2003 but then declined again after 2009. Epilimnetic chlorophyll-a averaged between 0.6 and 1.6 μg/L across sites with no difference between nearshore and offshore habitats. Apr/May – Oct Secchi depth ranged from 4.0 m to 10.8 m at individual sites and was higher in the offshore (average 9.1 m) than nearshore (5.9 m). In 2014, Apr/May – Oct epilimnetic zooplankton density, size, and biomass were not different between the offshore and the nearshore, and there were no differences in epilimnetic biomass between offshore and nearshore areas for any of the zooplankton groups. Zooplankton density and biomass peaked in September, an atypical pattern. This coincided with peaks in calanoid copepod, daphnid, and Holopedium biomass. Holopedium biomass in the nearshore increased significantly since 1995. The predatory cladoceran Cercopagis continued to be abundant in the summer, peaking at ~10 mg/m3in the offshore. Bythotrephes biomass was at its lowest level since 2005 in both offshore and nearshore habitats. Summer nearshore zooplankton density and biomass have declined significantly since 1995 at rates of 9-10% per year but have remained stable since 2005. However, bosminids and daphnids increased in 2013 and 2014. Summer offshore zooplankton density and biomass declined significantly in the long-term (since 1981), but remained at a lower stable level 2000 – 2014. A positive change point in 2013 is due to increases in bosminids, cyclopoid copepods, and daphnids. The observed decline in zooplankton biomass may be due in part to redistribution of zooplankton throughout the water column. Most of the zooplankton biomass was in the metalimnion and hypolimnion during the stratified period in 2014. By October, the bulk of the biomass was in the epilimnion.

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