Geology topics

Daren M. Carlisle

Publications and source records attributed to Daren M. Carlisle.

At least 19 recordsLinked to original sources

USGS2025

Integrating theory and empirical patterns: Fish body size distributions, life history traits, and environmental flows in streams

Individual size distributions (ISDs) are prominent in ecological research and may support resource managers with ecosystem-scale objectives. We use a database of individual size measurements for US stream fishes to test for direct and indirect effects of traits, flow regimes, and land use on the interspecific ISD exponent. Path analysis indicates that traits have strong, direct effects on ISD. Flow and land use effects on the exponent are largely indirectly mediated by their influences on species traits. ISD exponents increase (abundances of larger-bodied individuals increase, relative to smaller-bodied) when environments favor higher trophic levels, warmer thermal tolerances, and periodic life histories. Alternatively, ISD exponents decrease in systems that favor opportunistic life histories. Our flexible modeling framework that includes direct and indirect effects of traits, flow regimes, and land use on ISD could be expanded to incorporate additional variables that interact with flow (e.g., temperature and physical habitat) to assess of effects of multiple stressors on aquatic ecosystem functioning.

Science Advances↗

USGS2024

Before the fire: Predicting burn severity and potential post-fire debris-flow hazards to Colorado River Cutthroat Trout (Oncorhynchus clarkii pleuriticus) conservation populations

Background Colorado River Cutthroat Trout (CRCT; Oncorhynchus clarkii pleuriticus ) conservation populations may be at risk from wildfire and post-fire debris flows hazards. Aim To predict burn severity and potential post-fire debris flow hazard classifications to CRCT conservation populations before wildfires occur. Methods We used remote sensing, spatial analyses, and machine learning to model 28 wildfire incidents (2016–2020) and spatially predict burn severity from pre-wildfire environmental factors to evaluate the likelihood (%) and volume (m 3 ) hazard classification of post-fire debris flow. Key results Burn severity was best predicted by fuels, followed by topography, physical ecosystem conditions, and weather (mean adjusted R 2 = 0.54). Predictions of high or moderate burn severity covered 1.1 (15% of study area) and 1.5 (19% of study area) million ha, respectively, and varied by watershed. Combined high or moderate debris flow hazard classification included 80% of stream reaches with conservation populations and 97% of conservation population point nodes. Conclusions Predicted burn severity and potential post-fire debris flow indicated moderate to high hazard for CRCT conservation populations native to the Green and Yampa rivers of the Upper Colorado River Basin. Implications Future management actions can incorporate predicted burn severity and potential post-fire debris flow to mitigate impacts to CRCT and other at-risk resource values before a wildfire occurs.

Colorado, Utah, Wyoming↗

USGS2024

Quantifying form resistance is essential for estimating summer low and bankfull flow from stream survey channel morphology

Reliable estimates of low flow and flood discharge at ungaged locations are required for evaluating stream flow alteration, designing culverts and stream crossings, and interpreting regional surveys of habitat and biotic condition. Very few stream gaging stations are located on small, remote streams, which typically have complex channel morphology. Adequate gaging is also lacking on larger streams that are remote, smaller than those typically gaged, or have channel morphology not conducive to installation of gages. Complex channels typically contain large scale hydraulic roughness elements that dominate flow patterns (i.e., form roughness), making it difficult to measure channel cross-section area and water velocity, or to measure channel volume even where discharge is known. In channels with large channel form roughness, it is equally difficult to estimate discharge using commonly applied equations based on slope and channel dimensions or basin area. We employed a novel approach that explicitly accounts for hydraulic resistance from large wood and riffle-pool morphology (form roughness) in calculating low flow and bankfull discharge from stream and river physical habitat data collected from 4229 stream and river sites in the conterminous US (CONUS) sampled in 2008–9 and 2013–14 as part of the US Environmental Protection Agency's N ational R ivers and S treams A ssessment (NRSA). Hydraulic resistance derived from form roughness clearly dominated resistance derived from bed particles (particle resistance) during summer low flows in wadeable streams across the spectrum of channel slopes and substrate sizes smaller than boulders. Under bankfull conditions, the influence of form resistance relative to particle resistance was diminished, but form resistance still dominated except in large low gradient rivers lacking complex channels, and in streams or rivers with boulder-size bed particles. We validated our hydraulic resistance estimates by comparing measured discharges with calculated discharges that used those hydraulic resistance estimates along with measured NRSA channel morphology data. Morphology-based summer discharge (low flow) estimates and direct field measurements of discharge in 2333 wadeable CONUS streams showed reasonable agreement (median difference < 2.5×) for discharges ranging from 3.6 × 10 −5 to 123 m 3 /s and drainage areas of 0.12 to 171,000 km 2 . In a subset of 759 of NRSA's larger wadeable stream and non-wadeable river sites where nearby U.S. Geological Survey (USGS) gage data were available and adequate, our morphology-based summer discharge estimates agreed fairly well (median difference < 2.0×) with USGS 20-yr average August mean flows ranging from 0.003 to 16,000 m 3 /s. Similarly, morphology-based estimates of bankfull flow ranging from 0.3 to 100,000 m 3 /s agreed reasonably well with the 1.5-yr recurrence interval flood in these gaged sites (median deviation <2.2×). These findings demonstrate the importance of quantifying flow resistance from large-scale form roughness features in natural channels and provide a novel approach for estimating discharge from widely available survey data. This will allow examination of discharge and its ecological influence across the full range of stream and river sizes sampled by NRSA or other synoptic surveys where comprehensive measures of biota, physical habitat, and chemistry are also made. Although these morphology-based estimates exhibit some variability, they are adequate for examining regional patterns in discharge and flow alteration and their association with instream biota and anthropogenic disturbances, providing summer low and bankfull flow information where reliable estimates are lacking.

Geomorphology↗

USGS2024

Assessing the added value of antecedent streamflow alteration information in modeling stream biological condition

In stream systems, disentangling relationships between biology and flow and subsequent prediction of these relationships to unsampled streams is a common objective of large-scale ecological modeling. Often, streamflow metrics are derived from aggregating continuous streamflow records available at a subset of stream gages into long-term flow regime descriptors. Despite demonstrated value, shortcomings of these long-term approaches include spatial restriction to locations with long-term continuous flow records (commonly, biased toward larger systems) and omission of potentially ecologically important short-term (i.e., ≤1 year) antecedent streamflow information. We used long-term flow regime and short-term antecedent streamflow alteration information to evaluate relative performance in modeling stream fish biological condition. We compared results to understand whether short-term antecedent streamflow information improved models of fish biological condition. Results indicated that models incorporating short-term antecedent data performed better than those relying solely on long-term flow regime data (kappa statistic = 0.29 and 0.23, respectively) and improved prediction accuracy among stream sizes and in six of nine ecoregions. Additionally, models relying solely on short-term streamflow information performed similarly to those with only long-term streamflow information (kappa = 0.23). Incorporating short-term antecedent streamflow metrics may provide added ecological information not fully captured by long-term flow regime summaries in macroscale modeling efforts or perform similarly to long-term streamflow data when long-term data are not available.

Science of the Total Environment↗

USGS2024

Using models of local environmental conditions for biological assessment

A common approach for biological assessment is to compare current observations of biota at a site to predictions of the biota that would occur if the site were in reference condition. To estimate these reference expectations, predictive bioassessment models use only data collected at reference sites and estimate relationships between biota and environmental variables that are unaffected by human activities (i.e., immutable variables). However, in some areas where human activities are pervasive, few reference sites are available. Here, we introduce a new approach for bioassessment, in which we first estimate relationships between widely available measurements of both immutable and human-influenced landscape variables and local environmental conditions (conductivity, dissolved total P, total suspended solids, percentage of sand and fines in the substrate, and dissolved organic C), and then we estimate the relationship between these local environmental variables and total macroinvertebrate richness. We then calculate the values of the local environmental variables under reference conditions by adjusting predictors that are strongly influenced by human activities to levels that are consistent with those observed at reference sites. Reference values of local environmental variables are then combined with the model for taxon richness to calculate taxon richness expected under reference conditions. Predictions of total taxon richness in validation data using the new approach are similar in accuracy and precision as predictions calculated using a traditional approach that focuses only on reference site data. The new approach complements existing bioassessment methods by highlighting types of sites in which estimates of reference expectations are uncertain and by improving our understanding of how instream stressors affect expected total taxon richness.

conterminous United States↗

USGS2023

Indicators of the effects of climate change on freshwater ecosystems

Freshwater ecosystems, including lakes, streams, and wetlands, are responsive to climate change and other natural and anthropogenic stresses. These ecosystems are frequently hydrologically and ecologically connected with one another and their surrounding landscapes, thereby integrating changes throughout their watersheds. The responses of any given freshwater ecosystem to climate change depend on the magnitude of climate forcing, interactions with other anthropogenic and natural changes, and the characteristics of the ecosystem itself. Therefore, the magnitude and manner in which freshwater ecosystems respond to climate change are difficult to predict a priori. We present a conceptual model to elucidate how freshwater ecosystems are altered by climate change. We identify eleven indicators that describe the response of freshwater ecosystems to climate change, discuss their potential value and limitations, and describe supporting measurements. Indicators are organized in three interrelated categories: hydrologic, water quality, and ecosystem structure and function. The indicators are supported by data sets with a wide range of temporal and spatial coverage, and they inform important scientific and management needs. Together, these indicators improve the understanding and management of the effects of climate change on freshwater ecosystems.

Climate Change↗

USGS2022

Modeling functional flows in California rivers

Environmental flows are critical to the recovery and conservation of freshwater ecosystems worldwide. However, estimating desired ranges of environmental flows across large, diverse landscapes is challenging. To advance protections of environmental flows for streams in California, USA, we developed a statewide modeling approach focused on functional components of the natural flow regime. Functional flow components in California streams—fall pulse flows, wet season peak flows and base flows, the spring flow recession, and dry season baseflows—support essential physical and ecological processes in riverine ecosystems. These functional flow components can be represented by functional flow metrics (FFMs) and quantified by their magnitude, timing, frequency, duration, and rate-of-change from daily streamflow records. After quantifying FFMs at reference-quality streamflow gages in California, we used machine-learning methods to estimate their natural range of values for all stream reaches in the state based on physical watershed characteristics and climatic factors. We found that the models performed well in predicting FFMs in streams across a diversity of landscape and climate contexts, according to several model performance criteria. Using the predicted FFM values, we established initial estimates of ecological flows that are expected to support critical functions and are broadly protective of ecosystem health. Modeling functional flows statewide offers a pathway for increasing the pace and scale of environmental flow protections in California and beyond.

California↗

USGS2022

Toward improved prediction of streamflow effects on freshwater fishes

Understanding the effects of hydrology on fish populations is essential to managing for native fish conservation. However, despite decades of research illustrating streamflow influences on fish habitat, reproduction and survival, biologists remain challenged when tasked with predicting how fish populations will respond to changes in flow regimes. This uncertainty stems from insufficient understanding of the context-dependent mechanisms underlying fish responses to, for example, periods of reduced flow or altered frequency of high-flow events. We aim to address this gap by drawing on previous research to hypothesize mechanisms by which low- and high-flows influence fish populations and communities, identifying challenges that stem from data limitations and ecological complexity, and outlining research directions that can advance an empirical basis for prediction. Focusing flow-ecology research on testing and refining mechanistic hypotheses can help narrow management uncertainties and better support species conservation in changing flow regimes.

Fisheries Magazine↗

USGS2022

Biological assessments of aquatic ecosystems

The aim of biological assessments (or bioassessments) is to provide decision makers and managers the scientific information and tools needed to protect and restore aquatic life. Biological assessments typically include several critical elements, including development of ecological indicators, indices of ecological status, benchmarks by which to gauge impairment, ways to identify the stressors causing ecological impairment, and biological criteria and standards to protect aquatic life. New scientific tools are emerging that should improve the accuracy and precision of biological assessments, but the major challenges to effective protection and restoration of aquatic life are political and economic rather than scientific.

Book chapter↗

USGS2022

A web-based tool for assessing the condition of benthic diatom assemblages in streams and rivers of the conterminous United States

Benthic diatom assemblages are known to be indicative of water quality but have yet to be widely adopted in biological assessments in the United States due to several limitations. Our goal was to address some of these limitations by developing regional multi-metric indices (MMIs) that are robust to inter-laboratory taxonomic inconsistency, adjusted for natural covariates, and sensitive to a wide range of anthropogenic stressors. We aggregated bioassessment data from two national-scale federal programs and used a data-driven analysis in which all-possible combinations of 2–7 metrics were compared for three measures of performance. After ranking the best-performing MMIs, we selected the final MMIs by evaluating stress-response relations in independent regional datasets of diatom samples paired with measures of several water-quality stressors, including herbicides and streamflow flashiness. Each regional MMI performed well at calibration sites and represented diverse aspects of the structure and function of diatom communities. Most metrics included in the best MMIs were modeled to account for natural variation including climate, topography, soil characteristics, lithology, and groundwater influence on streamflow. MMI performance improved with higher numbers of component metrics, but this effect diminished beyond six metrics. Component metrics of MMIs were associated with a broad suite of measured stressors in every region, including salinity, nutrients, herbicides, and streamflow flashiness. We provide a web-based software application that allows users in the conterminous United States to apply our MMIs to their own datasets and compare MMI scores from their sites to a broader regional context.

Ecological Indicators↗

USGS2022

Natural and anthropogenic influences on benthic cyanobacteria in streams of the northeastern United States

Benthic cyanobacteria are widespread in streams and rivers and have the potential to release toxins. In large numbers, these microorganisms and their toxins present a risk to human health. Cyanobacterial abundance in stream biofilms is typically related to single or a limited set of environmental factors, mainly light availability, water temperature, and nutrient concentrations. However, these factors may act synergistically with watershed characteristics and other stressors, such as anthropogenic pollutants, to affect cyanobacteria. We investigated the influence of multiple regional and local variables on the abundance of benthic cyanobacterial genera in streams using all subsets generalized additive modeling. We examined watershed factors (topography, geology, and climate) alongside in-stream factors (geomorphology, hydrology, pH, specific conductance, nutrients, organic contaminants, and dissolved metals) from 76 sites along an urban gradient in the northeast United States. Each genus responded to a distinct combination of environmental variables, demonstrating strong intergeneric variation in environmental selection of realized niches. Four of the 7 potentially toxigenic genera that we modeled were positively influenced by water temperature or nutrients. Nonetheless, watershed characteristics, streamflow, and/or other water quality pollutants were equally or more influential for the potentially toxigenic genera. Additionally, the relationships between cyanobacterial abundance and environmental factors varied in shape and direction across many genera. In particular, with increasing concentrations of herbicides, polychlorinated biphenyls, or metals, the abundance of roughly half of the affected genera decreased, while the others increased. These results likely demonstrate novel toxic effects of the pollutants on cyanobacterial genera in the environment, while indicating that unmeasured biotic interactions may lead to positive responses for other genera. Our results emphasize the need to consider variables beyond those that are most frequently measured or implicated (e.g., water temperature and nutrients) to more fully understand the environmental conditions that influence the distributions and abundance of potentially harmful cyanobacteria.

Connecticut, Massachusetts, New Hampshire. New Yor↗

USGS2022

Ecological consequences of neonicotinoid mixtures in streams

Neonicotinoid mixtures are common in streams worldwide, but corresponding ecological responses are poorly understood. We combined experimental and observational studies to narrow this knowledge gap. The mesocosm experiment determined that concentrations of the neonicotinoids imidacloprid and clothianidin (range of exposures, 0 to 11.9 μg/liter) above the hazard concentration for 5% of species (0.017 and 0.010 μg/liter, respectively) caused a loss in taxa abundance and richness, disrupted adult emergence, and altered trophodynamics, while mixtures of the two neonicotinoids caused dose-dependent synergistic effects. In 85 Coastal California streams, neonicotinoids were commonly detected [59% of samples ( n = 340), 72% of streams], frequently occurred as mixtures (56% of streams), and potential toxicity was dominated by imidacloprid (maximum = 1.92 μg/liter) and clothianidin (maximum = 2.51 μg/liter). Ecological responses in the field were consistent with the synergistic effects observed in the mesocosm experiment, indicating that neonicotinoid mixtures pose greater than expected risks to stream health.

Science Advances↗

USGS2021

Estimating invertebrate response to changes in total nitrogen, total phosphorus, and specific conductance at sites where invertebrate data are unavailable

The purpose of this report is to describe a possible approach to estimate changes in invertebrate taxa richness at sites with known water-quality trends but no invertebrate data. In this study, data from 1,322 sites were used to describe invertebrate response to changes in total nitrogen, total phosphorus, or specific conductance, and to estimate changes in invertebrate taxa richness at 259 sites with reported water-quality trends but no invertebrate data. Sites were stratified using propensity score analysis to control for confounding factors (for example, climate, land use, land cover). Generalized linear models were developed to describe changes in invertebrate taxa richness along gradients of total nitrogen, total phosphorus, and specific conductance values. The magnitude and direction of invertebrate response to gradients of water quality varied among parameters and strata, with changes in invertebrate taxa richness per natural log unit change in concentration ranging from –7 to +6. However, estimated changes in invertebrate taxa richness at sites with known water-quality trends were much less and did not exceed three taxa until changes in concentration were greater than 50 percent. Applying this approach provides (1) a first screening to identify where changes in invertebrate taxa richness are likely to occur and (2) the necessary groundwork to improve estimation of invertebrate response to trends in water quality where biological data are lacking.

Scientific Investigations Report↗

USGS2021

Linking altered flow regimes to biological condition: An example using benthic macroinvertebrates in small streams of the Chesapeake Bay watershed

Regionally scaled assessments of hydrologic alteration for small streams and its effects on freshwater taxa are often inhibited by a low number of stream gages. To overcome this limitation, we paired modeled estimates of hydrologic alteration to a benthic macroinvertebrate index of biotic integrity data for 4522 stream reaches across the Chesapeake Bay watershed. Using separate random-forest models, we predicted flow status (inflated, diminished, or indeterminant) for 12 published hydrologic metrics (HMs) that characterize the main components of flow regimes. We used these models to predict each HM status for each stream reach in the watershed, and linked predictions to macroinvertebrate condition samples collected from streams with drainage areas less than 200 km 2 . Flow alteration was calculated as the number of HMs with inflated or diminished status and ranged from 0 (no HM inflated or diminished) to 12 (all 12 HMs inflated or diminished). When focused solely on the stream condition and flow-alteration relationship, degraded macroinvertebrate condition was, depending on the number of HMs used, 3.8–4.7 times more likely in a flow-altered site; this likelihood was over twofold higher in the urban-focused dataset (8.7–10.8), and was never significant in the agriculture-focused dataset. Logistic regression analysis using the entire dataset showed for every unit increase in flow-alteration intensity, the odds of a degraded condition increased 3.7%. Our results provide an indication of whether altered streamflow is a possible driver of degraded biological conditions, information that could help managers prioritize management actions and lead to more effective restoration efforts.

Chesapeake Bay watershed↗

USGS2021

Multi-region assessment of chemical mixture exposures and predicted cumulative effects in USA wadeable urban/agriculture-gradient streams

Chemical-contaminant mixtures are widely reported in large stream reaches in urban/agriculture-developed watersheds, but mixture compositions and aggregate biological effects are less well understood in corresponding smaller headwaters , which comprise most of stream length, riparian connectivity, and spatial biodiversity. During 2014–2017, the U.S. Geological Survey (USGS) measured 389 unique organic analytes (pharmaceutical, pesticide, organic wastewater indicators) in 305 headwater streams within four contiguous United States (US) regions. Potential aquatic biological effects were evaluated for estimated maximum and median exposure conditions using multiple lines of evidence, including occurrence/concentrations of designed-bioactive pesticides and pharmaceuticals and cumulative risk screening based on vertebrate-centric ToxCast™ exposure-response data and on invertebrate and nonvascular plant aquatic life benchmarks. Mixed-contaminant exposures were ubiquitous and varied, with 78% (304) of analytes detected at least once and cumulative maximum concentrations up to more than 156,000 ng/L. Designed bioactives represented 83% of detected analytes. Contaminant summary metrics correlated strong-positive (rho (ρ): 0.569–0.719) to multiple watershed-development metrics, only weak-positive to point-source discharges (ρ: 0.225–353), and moderate- to strong-negative with multiple instream invertebrate metrics (ρ: −0.373 to −0.652). Risk screening indicated common exposures with high probability of vertebrate-centric molecular effects and of acute toxicity to invertebrates, respectively. The results confirm exposures to broad and diverse contaminant mixtures and provide convincing multiple lines of evidence that chemical contaminants contribute substantially to adverse multi-stressor effects in headwater-stream communities.

Science of the Total Environment↗

USGS2021

Multiple in-stream stressors degrade biological assemblages in five U.S. regions

Biological assemblages in streams are affected by a wide variety of physical and chemical stressors associated with land-use development, yet the importance of combinations of different types of stressors is not well known. From 2013 to 2017, the U.S. Geological Survey completed multi-stressor/multi-assemblage stream ecological assessments in five regions of the United States (434 streams total). Diatom, invertebrate, and fish communities were enumerated, and five types of potential stressors were quantified: habitat disturbance, excess nutrients, high flows, basic water quality, and contaminants in water and sediment. Boosted regression tree (BRT) models for each biological assemblage and region generally included variables from all five stressor types and multiple stressors types in each model was the norm. Classification and regression tree (CART) models then were used to determine thresholds for each BRT model variable above which there appeared to be adverse effects (multi-metric index (MMI) models only). In every region and assemblage there was a significant inverse relation between the MMI and the number of stressors exerting potentially adverse effects. The number of elevated instream stressors often varied substantially for a given level of land-use development and the number of elevated stressors was a better predictor of biological condition than was development. Using the adverse effects-levels that were developed based on the BRT model results, 68% of the streams had two or more stressors with potentially adverse effects and 35% had four or more. Our results indicate that relatively small increases in the number of stressors of different types can have a large effect on a stream ecosystem.

Science of the Total Environment↗

USGS2020

Ecological forecasting—21st century science for 21st century management

Natural resource managers are coping with rapid changes in both environmental conditions and ecosystems. Enabled by recent advances in data collection and assimilation, short-term ecological forecasting may be a powerful tool to help resource managers anticipate impending near-term changes in ecosystem conditions or dynamics. Managers may use the information in forecasts to minimize the adverse effects of ecological stressors and optimize the effectiveness of management actions. To explore the potential for ecological forecasting to enhance natural resource management, the U.S. Geological Survey (USGS) convened a workshop titled "Building Capacity for Applied Short-Term Ecological Forecasting" on May 29—31, 2019, with participants from several Federal agencies, including the Bureau of Land Management, the U.S. Fish and Wildlife Service, the National Park Service, and the National Oceanic and Atmospheric Administration as well as all mission areas within the USGS. Participants broadly agreed that short-term ecological forecasting—on the order of days to years into the future—has tremendous potential to improve the quality and timeliness of information available to guide resource management decisions. Participants considered how ecological forecasting could directly affect their agency missions and specified numerous critical tools for addressing natural resource management concerns in the 21st century that could be enhanced by ecological forecasting. Given this breadth of possible applications for forecast products, participants developed a repeatable framework for evaluating potential value of a forecast product for enhancing resource management. Applying that process to a large list of forecast ideas that were developed in a brainstorming session, participants identified a small set of promising forecast products that illustrate the value of ecological forecasting for informing resource management. Workshop outcomes also include insights about important likely obstacles and next steps. In particular, reliable production and delivery of operational ecological forecasts will require a sustained commitment by research agencies, in partnership with resource management agencies, to maintain and improve forecasting tools and capabilities.

Open-File Report↗

USGS2020

Biofilms provide new insight into pesticide occurrence in streams and links to aquatic ecological communities

Streambed sediment is commonly analyzed to assess occurrence of hydrophobic pesticides and risks to aquatic communities. However, stream biofilms also have the potential to accumulate pesticides and may be consumed by aquatic organisms. To better characterize risks to aquatic life, the U.S. Geological Survey Regional Stream Quality Assessment measured 93 current-use and 3 legacy pesticides in bed sediment and biofilm from 54 small streams in California across a range of land-use settings. On average, 4 times as many current-use pesticides were detected in biofilm at a site (median of 2) as in sediment (median of 0.5). Of 31 current-use pesticides detected, 20 were detected more frequently in biofilm than sediment and 10 equally frequently. Pyrethroids as a class were the most potentially toxic to benthic invertebrates, and of the nine pyrethroids detected, seven occurred more frequently in biofilm than sediment. We constructive General Additive Models to investigate relations between pesticides and six metrics of benthic community structure. Pesticides in biofilm improved fit in four of the six models, and pesticides in sediment improved fit in two. The results indicate that sampling of stream biofilms can complement bed-sediment sampling by identifying more current-use pesticides present and better estimating ecological risks.

California↗