Geology topics

Daren M. Carlisle

Publications and source records attributed to Daren M. Carlisle.

At least 37 records · Page 2Linked to original sources

USGS2020

Multi-region assessment of pharmaceutical exposures and predicted effects in USA wadeable urban-gradient streams

Human-use pharmaceuticals in urban streams link aquatic-ecosystem health to human health. Pharmaceutical mixtures have been widely reported in larger streams due to historical emphasis on wastewater-treatment plant (WWTP) sources, with limited investigation of pharmaceutical exposures and potential effects in smaller headwater streams. In 2014–2017, the United States Geological Survey measured 111 pharmaceutical compounds in 308 headwater streams (261 urban-gradient sites sampled 3–5 times, 47 putative low-impact sites sampled once) in 4 regions across the US. Simultaneous exposures to multiple pharmaceutical compounds (pharmaceutical mixtures) were observed in 91% of streams (248 urban-gradient, 32 low-impact), with 88 analytes detected across all sites and cumulative maximum concentrations up to 36,142 ng/L per site. Cumulative detections and concentrations correlated to urban land use and presence/absence of permitted WWTP discharges, but pharmaceutical mixtures also were common in the 75% of sampled streams without WWTP. Cumulative exposure-activity ratios (EAR) indicated widespread transient exposures with high probability of molecular effects to vertebrates. Considering the potential individual and interactive effects of the detected pharmaceuticals and the recognized analytical underestimation of the pharmaceutical-contaminant (unassessed parent compounds, metabolites, degradates) space, these results demonstrate a nation-wide environmental concern and the need for watershed-scale mitigation of in-stream pharmaceutical contamination.

Alabama, California, Connecticut, Georgia, Delawar↗

USGS2020

Sustaining Environmental Capital Initiative summary report

Federal agencies need credible scientific information to determine the production and value of ecosystem services in an efficient and timely manner. The U.S. Geological Survey addresses this scientific information need through the Sustaining Environmental Capital Initiative project. The project has relied on U.S. Geological Survey expertise related to water, fisheries, advanced modeling, and economics and other social sciences to conduct eight case studies across a range of environment types, including water-based environments, deserts, sagebrush ecosystems, floodplains, and forests. The Sustaining Environmental Capital Initiative also supported the development and expansion of four tools with the intent of adding content and usability for partners’ decision-making needs. The tools are the Natural Value Resource Center, Benefit Transfer Toolkit, Riverine Environmental Flow Decision Support System, and Artificial Intelligence for Ecosystem Services modeling platform.

Open-File Report↗

USGS2020

Diatom enumeration method influences biological assessments of southeastern USA streams

Current fixed-count enumeration methods for benthic diatoms are likely inadequate for most research and monitoring objectives. These methods underestimate taxa richness and may fail to detect losses of species caused by human impacts. Consequently, the full potential of diatoms is not realized in current assessments of biological integrity or species diversity. In this study, we hypothesize that alternative enumeration methods differ in their ability to quantify species composition. Furthermore, we hypothesize that an alternative to the traditional fixed-count method will improve both performance of observed/expected (O/E) indices derived from River Inver- tebrate Prediction and Classification System models and the discrimination of reference-quality and human-modified sites by other standard metrics used in biological assessments. To test these hypotheses, we assessed 1) how well 3 counting methods characterized species richness in a subset of 15 samples of stream benthic diatoms and 2) how counting method affected the performance of O/E indices and metrics by comparing the traditional fixed- count method against the best-performing alternative method. These latter comparisons were based on samples collected from 68 reference-quality streams and 20 streams located along an urban disturbance gradient. We dem- onstrate that traditional fixed counts failed to detect >1⁄2 of species present in most of the 68 reference-quality sites. Instead, timed-presence data produced the O/E index with the best performance and a level of precision similar to published invertebrate O/E indices. Furthermore, the O/E index based on the timed-presence data allowed us to determine which species are most often lost with urbanization. We found that traditional fixed-count and alter- native timed-presence data produce metrics that are nearly equally able to discriminate between reference and dis- turbed sites. This study demonstrates that alternative counting methods improve species detection and require up to ∼30% less effort.

Arkansas, Alabama, Georgia, Louisiana, Maryland, M↗

USGS2020

Common insecticide disrupts aquatic communities: A mesocosm-to-field ecological risk assessment of fipronil and its degradates in U.S. streams

Insecticides in streams are increasingly a global concern, yet information on safe concentrations for aquatic ecosystems is sparse. In a 30-day mesocosm experiment exposing native benthic aquatic invertebrates to the common insecticide fipronil and four degradates, fipronil compounds caused altered emergence and trophic cascades. Effect concentrations eliciting a 50% response (EC 50 ) were developed for fipronil and its sulfide, sulfone, and desulfinyl degradates; taxa were insensitive to fipronil amide. Hazard concentrations for 5% of affected species derived from up to 15 mesocosm EC 50 values were used to convert fipronil compound concentrations in field samples to the sum of toxic units (∑TU Fipronils ). Mean ∑TU Fipronils exceeded 1 (indicating toxicity) in 16% of streams sampled from five regional studies. The Species at Risk invertebrate metric was negatively associated with ∑TU Fipronils in four of five regions sampled. This ecological risk assessment indicates that low concentrations of fipronil compounds degrade stream communities in multiple regions of the United States.

Science Advances↗

USGS2019

Severity and extent of alterations to natural streamflow regimes based on hydrologic metrics in the conterminous United States, 1980–2014

Alteration of the natural streamflow regime by land and water management, such as land-cover change and dams, is associated with aquatic ecosystem degradation. The severity and geographic extent of streamflow alteration at regional and national scales, however, remain largely unquantified. The primary goal of this study is to characterize the severity and extent of alterations to natural streamflow regimes for 1980–2014 based on hydrologic metrics at 3,355 U.S. Geological Survey streamgages in the conterminous United States. Twelve hydrologic metrics with known relevance to aquatic ecosystem health were used to characterize the streamflow regime. Alterations to the 12 hydrologic metrics were quantified by taking ratios of the metrics calculated from observed daily streamflow records divided by the same metrics predicted for natural conditions by random forest statistical models. Some level of streamflow alteration (diminishment or inflation of hydrologic metrics) compared to natural conditions was indicated at about 80 percent of the assessed streamgages across the conterminous United States. The severity of alteration differed among ecoregions because of differences in dominant land and water management practices. Finally, when compared over the period 1980–2014, climate variability generally played a minor role in the alteration of streamflows across the United States when compared to the effects of land and water management.

Conterminous United States↗

USGS2019

Flow modification in the Nation’s streams and rivers

This report summarizes a national assessment of flowing waters conducted by the U.S. Geological Survey’s (USGS) National Water-Quality Assessment (NAWQA) Project and addresses several pressing questions about the modification of natural flows in streams and rivers. The assessment is based on the integration, modeling, and synthesis of monitoring data collected by the USGS and the U.S. Environmental Protection Agency at more than 7,000 streams and rivers across the conterminous United States from 1980 to 2014. Key findings include the following. First, flow in many of the Nation’s streams and rivers is different from what it would be under natural conditions. In particular, low flows are more frequent, are of shorter duration, and vary less from one year to the next than they would naturally. In addition, high flows have been reduced in magnitude, are of shorter duration, are less frequent, and vary less from one year to the next than they would naturally. Other characteristics of natural flows also have been modified. Second, over the last 60 years (1955–2014), climatic trends have caused a change of 50 percent or more in one or more streamflow attributes at two-thirds of climate-sensitive streamgaging sites. However, these climate-induced changes have been less influential on streamflow modification than have land and water-management practices. Third, in every region assessed, streamflow modification was associated with reduced ecological health, as indicated by two biological communities—invertebrates and fish. Biological communities were increasingly likely to be impaired (defined as having lost a statistically significant number of species) in streams with flows most different from natural conditions. Finally, several case studies are presented that illustrate viable management strategies for balancing the water needs of people and ecosystems.

Circular↗

USGS2019

Projected urban growth in the Southeastern USA puts small streams at risk

Future land-use development has the potential to profoundly affect the health of aquatic ecosystems in the coming decades. We developed regression models predicting the loss of sensitive fish (R2=0.39) and macroinvertebrate (R2=0.64) taxa as a function of urban and agricultural land uses and applied them to projected urbanization of the rapidly urbanizing Piedmont ecoregion of the southeastern USA for 2030 and 2060. The regression models are based on a 2014 investigation of water quality and ecology of 75 wadeable streams across the region. Based on these projections, stream kilometers experiencing >50% loss of sensitive fish and invertebrate taxa will nearly quadruple to 19,500 and 38,950 km by 2060 (16 and 32% of small stream kilometers in the region), respectively. Uncertainty was assessed using the 20 and 80% probability of urbanization for the land-use projection model and using the 95% confidence intervals for the regression models. Adverse effects on stream health were linked to elevated concentrations of contaminants and nutrients, low dissolved oxygen, and streamflow alteration, all associated with urbanization. The results of this analysis provide a warning of potential risks from future urbanization and perhaps some guidance on how those risks might be mitigated.

PLoS ONE↗

USGS2019

Regional-scale associations between indicators of biological integrity and indicators of streamflow modification

Although streamflow is widely recognized as a controlling factor in stream health, empirical relations between indicators of anthropogenic modification of streamflow and ecological indicators have been elusive. The objective of this report is to build upon specific findings reported in recent publications by providing a library of empirical models that describe the relations between streamflow modification and indicators of biological integrity. Biological monitoring data from 812 streams and rivers across the United States were matched with sites where daily streamflow was also monitored by the U.S. Geological Survey. Of these sites, 118 were sampled by the U.S. Geological Survey along gradients of streamflow modification within 3 regional focus studies. The integrity of invertebrate and fish communities was expressed as a binary variable, “impaired” or “unimpaired,” signifying whether or not the composition and structure of the biological community was statistically reduced relative to regional reference sites. Streamflow modification at each gaged site was quantified with 509 streamflow statistics scaled to express the ratio of observed streamflow conditions to site-specific expected conditions in the absence of human influences on watershed hydrology. For each region, generalized additive modeling was used to examine relations between each indicator of streamflow modification and indicators of biological integrity (response variable). In every region examined, statistically defensible and ecologically realistic relations were found between indicators of streamflow modification and indicators of biological integrity. These findings can aid practitioners and managers seeking to (1) propose empirically based hypotheses about the specific components of streamflow regimes that are critical to aquatic communities, which can subsequently be explored in detail in a region or river basin of interest; and (2) predict biological responses to anthropogenic modification of specific components of the streamflow regime.

Open-File Report↗

USGS2019

Effects of urban multi-stressors on three stream biotic assemblages

During 2014, the U.S. Geological Survey (USGS) National Water-Quality Assessment(NAWQA) project assessed stream quality in 75 streams across an urban disturbance gradient within the Piedmont ecoregion of southeastern United States. Our objectives were to identify primary instream stressors affecting algal, macroinvertebrate and fish assemblages in wadeable streams. Biotic communities were surveyed once at each site, and various instream stressors were measured during a 4-week index period preceding the ecological sampling. The measured stressors included nutrients; contaminants in water, passive samplers, and sediment; instream habitat; and flow variability. All nine boosted regression tree models – three for each of algae, invertebrates, and fish – had cross-validation R 2 (CV R 2 ) values of 0.41 or above, and an invertebrate model had the highest CV R 2 of 0.65. At least one contaminant metric was important in every model, and minimum daytime dissolved oxygen (DO), nutrients, and flow alteration were important explanatory variables in many of the models. Physical habitat metrics such as sediment substrate were only moderately important. Flow alteration metrics were useful factors in eight of the nine models. Total phosphorus, acetanilide herbicides and flow (time since last peak) were important in all three algal models, whereas insecticide metrics (especially those representing fipronil and imidacloprid) were dominant in the invertebrate models. DO values below approximately 7 mg/L corresponded to a strong decrease in sensitive taxa or an increase in tolerant taxa. DO also showed strong interactions with other variables, particularly contaminants and sediment, where the combined effect of low DO and elevated contaminants increased the impact on the biota more than each variable individually. Contaminants and flow alteration were strongly correlated to urbanization, indicating the importance of urbanization to ecological stream condition in the region.

Science of the Total Environment↗

USGS2018

Linking the agricultural landscape of the Midwest to stream health with structural equation modeling

Multiple physical and chemical stressors can simultaneously affect the biological condition of streams. To better understand the complex interactions of land-use practices, water quality, and ecological integrity of streams, the U.S. Geological Survey National Water Quality Assessment Project is conducting regional-scale assessments of stream condition across the United States. In the summer of 2013, weekly water samples were collected from 100 streams in the Midwestern United States. Employing watershed theory, we used structural equation modeling (SEM) to represent a general hypothesis for how 16 variables (previously identified to be important to stream condition) might be inter-related. Again, using SEM, we evaluated the ability of this “stressor network” to explain variations in multimetrics of algal, invertebrate, and fish community health, trimming away any environmental variables not contributing to an explanation of the ecological responses. Seven environmental variables—agricultural and urban land use, sand content of soils, basin area, percent riparian area as forest, channel erosion, and relative bed stability—were found to be important for all three-community metrics. The algal and invertebrate models included water-chemistry variables not included in the fish model. Results suggest that ecological integrity of Midwest streams are affected by both agricultural and urban land uses and by the natural geologic setting, as indicated by the sand content of soils. Chemicals related to crops (pesticides and nutrients) and residential uses (pyrethroids) were found to be more strongly related to ecological integrity than were natural factors (riparian forest, watershed soil character).

Environmental Science & Technology↗

USGS2018

Effects of antecedent streamflow and sample timing on trend assessments of fish, invertebrate, and diatom communities

Detecting trends in biological attributes is central to many stream monitoring programs; however, understanding how natural variability in environmental factors affects trend results is not well understood. We evaluated the influence of antecedent streamflow and sample timing (covariates) on trend estimates for fish, invertebrate, and diatom taxa richness and biological condition from 2002 to 2012 at 51 sites distributed across the conterminous United States. A combination of linear regression and Kendall‐tau test for trends were used to evaluate covariate influence on trend estimates. Adjusting for covariates changed the magnitude of trend estimates in two‐thirds of cases on average by 21%, most often reducing the estimated magnitude of the trend. Additionally, covariates influenced the interpretation of over one‐third of trend estimates by either strengthening or weakening trends after adjustment. Our findings clearly indicate that antecedent streamflow and sample timing influences trend estimates and subsequent interpretation. Accounting for covariates during trend analysis will enhance stream monitoring programs by providing a better understanding and interpretation of estimated changes in biological endpoints at monitored sites. Failure to account for antecedent streamflow and sample timing may lead to mischaracterization of a trend and/or misunderstanding of potential causes.

Journal of the American Water Resources Associatio↗

USGS2018

A database of natural monthly streamflow estimates from 1950 to 2015 for the conterminous United States

Quantifying and understanding the natural streamflow regime, defined as expected streamflow that would occur in the absence of anthropogenic modification to the hydrologic system, is critically important for the development of management strategies aimed at protecting aquatic ecosystems. Water balance models have been applied frequently to estimate natural flows, but are limited in the number of predictor variables that can be included. Here, a statistical machine learning technique — random forest modeling — was applied to estimate natural flows at a monthly time‐step from 1950 to 2015 for >2.5 million stream reaches in the conterminous United States (U.S.) using 200 potential predictor variables. We describe the development and documentation of this dataset and assess model performance. Model fit statistics (mean Nash–Sutcliffe efficiency = 0.85; observed/expected ratio = 0.94) indicate good correspondence between predicted and observed flows at nearly 2,000 streamgages. As an example application of the dataset, the observed streamflow record at a site prior to and after the construction of an upstream reservoir was compared with estimated natural flows to demonstrate the magnitude of seasonal depletions in streamflow due to the reservoir. This dataset can be applied to quantify natural and anthropogenic processes contributing to streamflow depletion or augmentation, and assess associated ecological effects.

Journal of the American Water Resources Associatio↗

USGS2018

Sensitivity of streamflow to climate change in California

Climate change is rapidly altering the global water cycle, exposing vulnerabilities in both social and environmental systems. However, uncertainty in future climate predictions makes it difficult to design and evaluate strategies for building climate resilience. In regions such as California, characterized by stressed water-supply systems, high natural climate variability, and substantial uncertainty in future precipitation projections, alternative approaches to assessing climate risks may be useful. Here, we develop a hydrologic sensitivity approach to estimate regional streamflow responses to climate change in California. We use statistical models to predict monthly streamflow from physical catchment features and evaluate how flow changes with incremental changes in precipitation and temperature. The results indicate unique regional and monthly flow responses to climate change, with early summer flows (May - July) in interior mountain region having the greatest sensitivity to temperature and winter flow (December - March) in the xeric region having the greatest sensitivity to precipitation. When evaluated over the range of global climate model projections for mid-century (2040-2069), models generally suggest shifts in streamflow regimes towards higher wet season flows and lower dry season flows relative to historical conditions. The sensitivity analysis provides insight into catchment- and regional-scale hydrologic responses in California and complements other approaches for understanding the consequences of climatic change for water and risk management.

California↗

USGS2018

The Midwest Stream Quality Assessment—Influences of human activities on streams

Healthy streams and the fish and other organisms that live in them contribute to our quality of life. Extensive modification of the landscape in the Midwestern United States, however, has profoundly affected the condition of streams. Row crops and pavement have replaced grasslands and woodlands, streams have been straightened, and wetlands and fields have been drained. Runoff from agricultural and urban land brings sediment and chemicals to streams. What is the chemical, physical, and biological condition of Midwestern streams? Which physical and chemical stressors are adversely affecting biological communities, what are their origins, and how might we lessen or avoid their adverse effects? In 2013, the U.S. Geological Survey (USGS) conducted the Midwest Stream Quality Assessment to evaluate how human activities affect the biological condition of Midwestern streams. In collaboration with the U.S. Environmental Protection Agency National Rivers and Streams Assessment, the USGS sampled 100 streams, chosen to be representative of the different types of watersheds in the region. Biological condition was evaluated based on the number and diversity of fish, algae, and invertebrates in the streams. Changes to the physical habitat and chemical characteristics of the streams—“stressors”—were assessed, and their relation to landscape factors and biological condition was explored by using mathematical models. The data and models help us to better understand how the human activities on the landscape are affecting streams in the region.

Fact Sheet↗

USGS2017

Patterns and magnitude of flow alteration in California, USA

Quantifying the natural flow regime is essential for management of water resources and conservation of aquatic ecosystems. Understanding the degree to which anthropogenic activities have altered flows is critical for developing effective conservation strategies. Assessing flow alteration requires estimates of flows expected in the absence of human influence and under current land use and water management. There are several techniques to predict flows in streams and rivers; however, none have been applied to make predictions of natural flow conditions over large regions and time periods. We utilised machine learning statistical models to predict natural monthly flows (natural streamflows without the influence of water management or anthropogenic land use) in California from 1950 to 2015, using time-dependent and fixed watershed variables from reference stream gages. These models were then used to make estimates of mean, maximum and minimum monthly flows in all streams in the state. We compared observed flows measured at 540 stream gages across the state with expected natural flows at the same locations, to quantify the type, frequency and magnitude of flow alteration over the past 20 years (1996–2015). A gage was considered altered if an observed flow metric (monthly mean, annual maximum, annual minimum) fell outside the 80% prediction interval of the modelled flow estimate. We found that 95% of the 540 stream gages in California had at least 1 month of altered flows over the past 20 years, and 11% of gages were frequently altered (over two-thirds of the months recorded had evidence of altered flows). The type of alteration varied across the state with flows being either depleted, inflated or a mix of both at different times of the year. Most altered gages (68%) exhibited both depletion and inflation in monthly flows over the time period. Inflation of monthly mean flows was most prevalent during the summer months, while depletion of monthly flows was evident throughout the year. Type, frequency and magnitude of flow alteration varied by region. Flow depletion was present at >80% of gages in the North Coast and Central Coast, flow inflation was measured at >80% of gages in the South Coast and San Francisco Bay and both depletion and inflation were evident at >80% of gages in the Sacramento River and San Joaquin and Tulare regions. Annual maximum flows were consistently depleted and annual minimum flows were commonly inflated in the Sierra Nevada and Central Valley (Sacramento River and San Joaquin and Tulare regions). This is the first study to comprehensively assess flow alteration at stream gages across California. Understanding the patterns and degree of alteration can aid in prioritising streams for environmental flow assessment and developing conservation strategies for native freshwater biota.

California↗

USGS2017

Streamflow alteration and habitat ramifications for a threatened fish species in the Central United States

In the Central United States, the Arkansas darter ( Etheostoma cragini ) is listed as a threatened fish species by the State of Kansas. Survival of the darter is threatened by loss of habitat caused by changing streamflow conditions, in particular flow depletion. Future management of darter populations and habitats requires an understanding of streamflow conditions and how those conditions may have changed over time in response to natural and anthropogenic factors. In Kansas, streamflow alteration was assessed at 9 U.S. Geological Survey streamgages in 6 priority basins with no pronounced long-term trends in precipitation. The assessment was based on a comparison of observed (O) and predicted expected (E) reference conditions for 29 flow metrics. The O/E results indicated a likely or possible diminished flow condition in 2 basins; the primary cause of which is groundwater-level declines resulting from groundwater pumping for irrigated agriculture. In these 2 basins, habitat characteristics adversely affected by flow depletion may include stream connectivity, pools, and water temperature. The other 4 basins were minimally affected, or unaffected, by flow depletion and therefore may provide the best opportunity for preservation of darter habitat. Through the O/E analysis, anthropogenic streamflow alteration was quantified and the results will enable better-informed decisions pertaining to the future management of darters in Kansas.

Kansas↗

USGS2017

Classification of California streams using combined deductive and inductive approaches: Setting the foundation for analysis of hydrologic alteration

Regional classification of streams is an early step in the Ecological Limits of Hydrologic Alteration framework. Many stream classifications are based on an inductive approach using hydrologic data from minimally disturbed basins, but this approach may underrepresent streams from heavily disturbed basins or sparsely gaged arid regions. An alternative is a deductive approach, using watershed climate, land use, and geomorphology to classify streams, but this approach may miss important hydrological characteristics of streams. We classified all stream reaches in California using both approaches. First, we used Bayesian and hierarchical clustering to classify reaches according to watershed characteristics. Streams were clustered into seven classes according to elevation, sedimentary rock, and winter precipitation. Permutation-based analysis of variance and random forest analyses were used to determine which hydrologic variables best separate streams into their respective classes. Stream typology (i.e., the class that a stream reach is assigned to) is shaped mainly by patterns of high and mean flow behavior within the stream's landscape context. Additionally, random forest was used to determine which hydrologic variables best separate minimally disturbed reference streams from non-reference streams in each of the seven classes. In contrast to stream typology, deviation from reference conditions is more difficult to detect and is largely defined by changes in low-flow variables, average daily flow, and duration of flow. Our combined deductive/inductive approach allows us to estimate flow under minimally disturbed conditions based on the deductive analysis and compare to measured flow based on the inductive analysis in order to estimate hydrologic change.

California↗

USGS2017

Predictability and selection of hydrologic metrics in riverine ecohydrology

The natural flow regime is critical to the health of riverine ecosystems. Many hydrologic metrics (HMs) have been developed to describe natural flow regimes, quantify flow alteration, and provide the hydrologic foundation for the development of environmental flow standards. Many applications require the use of models to predict expected natural values of HMs from basin characteristics at sites with no observed records of unimpaired flows. However, the error associated with HM estimation has not been evaluated. The primary goal of our study was to provide guidance for river scientists and managers in the selection, use, and interpretation of HMs for stream classification and hydroecological investigations of river ecosystems. We evaluated the predictability of a broad suite of HMs for the conterminous USA based on random forest statistical models. We also examined how the predictability of metrics varied among unique components of the flow regime. Roughly 40% of 612 HMs we examined could be predicted reliably from basin characteristics. The predictable metrics were disproportionately represented in 5 flow components: asymmetry, seasonality, magnitude, variability, and average monthly flows. Most metrics that represent extreme hydrological events (i.e., high and low flows) could not be reliably predicted. Roughly ⅔ of the evaluated HMs were incalculable or highly biased at intermittent/ephemeral streams because of the need for logarithmic transformations or scaling by other HMs, such as mean flows or percentile flow thresholds. Scaling metrics by drainage area tended to improve predictability. We recommend that the predictability of HMs be given greater consideration in studies and applications in which they are used to characterize and assess alteration of streamflow regimes.

Freshwater Science↗