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At least 1,675 records · Page 93Linked to original sources
USGS2026

American kestrel population trends and vital rates at the continental scale

The American kestrel ( Falco sparverius , hereafter referred to as kestrel) has declined across much of its North American range since at least the mid-1960s. Kestrel population dynamics have been explored through a multitude of local studies and two broad reviews of available data. Across large geographic extents, however, the demographic cause(s) of kestrel population declines remain(s) largely unknown. As part of a collaborative effort to elucidate the drivers of kestrel population declines, we developed a continental-scale integrated population model using band-recovery data, productivity data, and Breeding Bird Survey indices from 1986 to 2019 to estimate indices of annual population sizes, survival, and productivity rates across the continental United States. We detected a decline in population size of ~1%–2% per year. Overall estimates of population growth from 1986 to 2019 suggest a 29% decline in population size (95% CI = −34% to −23%). There was little evidence of a trend in brood size. However, survival of juvenile birds (mean = −0.015, SD = 0.008 and mean = −0.024, SD = 0.010 for females and males, respectively) and adult males (mean = −0.016, SD = 0.010) in the summer declined, suggesting that these vital rates could be contributing to declines in populations over time. Winter adult survival rates (mean = −0.004, SD = 0.009 and mean = −0.009, SD = 0.010 for females and males, respectively) also declined but to a lesser extent than summer survival. For juvenile birds, winter survival increased (mean = 0.006, SD = 0.008 and mean = 0.002, SD = 0.009 for females and males, respectively); however, this was not enough to offset declines in summer survival and annual survival rates declined over the time series. Annual adult survival was also low relative to previous research on kestrel survival rates. Given the importance of survival to population trends, our findings provide support for several previously proposed broad classes of factors potentially contributing to observed population declines: declines in arthropod prey, second-generation rodenticides, neonicotinoid insecticides, and predation.

Ecosphere↗
USGS2017

The interacting roles of climate, soils, and plant production on soil microbial communities at a continental scale

Soil microbial communities control critical ecosystem processes such as decomposition, nutrient cycling, and soil organic matter formation. Continental scale patterns in the composition and functioning of microbial communities are related to climatic, biotic, and edaphic factors such as temperature and precipitation, plant community composition, and soil carbon, nitrogen, and pH. Although these relationships have been well explored individually, the examination of the factors that may act directly on microbial communities vs. those that may act indirectly through other ecosystem properties has not been well developed. To further such understanding, we utilized structural equation modeling (SEM) to evaluate a set of hypotheses about the direct and indirect effects of climatic, biotic, and edaphic variables on microbial communities across the continental United States. The primary goals of this work were to test our current understanding of the interactions among climate, soils, and plants in affecting microbial community composition, and to examine whether variation in the composition of the microbial community affects potential rates of soil enzymatic activities. A model of interacting factors created through SEM shows several expected patterns. Distal factors such as climate had indirect effects on microbial communities by influencing plant productivity, soil mineralogy, and soil pH, but factors related to soil organic matter chemistry had the most direct influence on community composition. We observed that both plant productivity and soil mineral composition were important indirect influences on community composition at the continental scale, both interacting to affect organic matter content and microbial biomass and ultimately community composition. Although soil hydrolytic enzymes were related to the moisture regime and soil carbon, oxidative enzymes were also affected by community composition, reflected in the abundance of soil fungi. These results highlight that soil microbial communities can be modeled within the context of multiple interacting ecosystem properties acting both directly and indirectly on their composition and function, and this provides a rich and informative context with which to examine communities. This work also highlights that variation in climate, microbial biomass, and microbial community composition can affect maximum rates of soil enzyme activities, potentially influencing rates of decomposition and nutrient mineralization in soils.

Ecology↗
USGS2018

Inferring species interactions through joint mark–recapture analysis

Introduced species are frequently implicated in declines of native species. In many cases, however, evidence linking introduced species to native declines is weak. Failure to make strong inferences regarding the role of introduced species can hamper attempts to predict population viability and delay effective management responses. For many species, mark–recapture analysis is the more rigorous form of demographic analysis. However, to our knowledge, there are no mark–recapture models that allow for joint modeling of interacting species. Here, we introduce a two‐species mark–recapture population model in which the vital rates (and capture probabilities) of one species are allowed to vary in response to the abundance of the other species. We use a simulation study to explore bias and choose an approach to model selection. We then use the model to investigate species interactions between endangered humpback chub ( Gila cypha ) and introduced rainbow trout ( Oncorhynchus mykiss ) in the Colorado River between 2009 and 2016. In particular, we test hypotheses about how two environmental factors (turbidity and temperature), intraspecific density dependence, and rainbow trout abundance are related to survival, growth, and capture of juvenile humpback chub. We also project the long‐term effects of different rainbow trout abundances on adult humpback chub abundances. Our simulation study suggests this approach has minimal bias under potentially challenging circumstances (i.e., low capture probabilities) that characterized our application and that model selection using indicator variables could reliably identify the true generating model even when process error was high. When the model was applied to rainbow trout and humpback chub, we identified negative relationships between rainbow trout abundance and the survival, growth, and capture probability of juvenile humpback chub. Effects on interspecific interactions on survival and capture probability were strongly supported, whereas support for the growth effect was weaker. Environmental factors were also identified to be important and in many cases stronger than interspecific interactions, and there was still substantial unexplained variation in growth and survival rates. The general approach presented here for combining mark–recapture data for two species is applicable in many other systems and could be modified to model abundance of the invader via other modeling approaches.

Ecology↗
USGS2019

Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data

Determining the degree to which predation affects prey abundance in natural communities constitutes a key goal of ecological research. Predators can affect prey through both consumptive effects (CEs) and nonconsumptive effects (NCEs), although the contributions of each mechanism to the density of prey populations remain largely hypothetical in most systems. Common statistical methods applied to time series data cannot elucidate the mechanisms responsible for hypothesized predator effects on prey density (e.g., differentiate CEs from NCEs), nor provide parameters for predictive models. State space models (SSMs) applied to time series data offer a way to meet these goals. Here, we employ SSMs to assess effects of an invasive predatory zooplankter, Bythotrephes longimanus, on an important prey species, Daphnia mendotae, in Lake Michigan. We fit mechanistic models in a SSM framework to seasonal time series (1994-2012) using a recently developed, maximum likelihood-based optimization method, iterated filtering, which can overcome challenges in ecological data (e.g. nonlinearities, measurement error, and irregular sampling intervals). Our results indicate that B. longimanus strongly influences D. mendotae dynamics, with mean annual peak densities of B. longimanus observed in Lake Michigan estimated to cause a 61% reduction in D. mendotae population growth rate and a 59% reduction in peak biomass density. Further, the observed B. longimanus effect is most consistent with an NCE via reduced birth rates. The SSM approach also provided estimates for key biological parameters (e.g., demographic rates) and the contribution of dynamic stochasticity and measurement error. Our study therefore provides evidence derived directly from survey data that the invasive zooplankter B. longimanus is affecting zooplankton demographics and offer parameter estimates needed to inform predictive models that explore the effect of B. longimanus under different scenarios such as climate change.

Ecology↗
USGS2019

Identifying occupancy model inadequacies: Can residuals separately assess detection and presence?

Occupancy models are widely applied to estimate species distributions, but few methods exist for model checking. Thorough model assessments can uncover inadequacies and allow for deeper ecological insight by exploring structure in the observed data not accounted for by a model. We introduce occupancy model residual definitions that utilize the posterior distribution of the partially latent occupancy states. Residual‐based assessments are valuable because they can target specific assumptions and identify ways to improve a model, such as adding spatial correlation or meaningful covariates. Our approach defines separate residuals for occupancy and detection, and we use simulation to examine whether missing structure for modeling detection probabilities can be distinguished from that for occupancy probabilities. In many scenarios, our residual diagnostics were able to successfully separate inadequacies at the different model levels, but we describe other situations when this may not be the case. Applying Moran's I residual diagnostics to assess models for silver‐haired (Lasionycteris noctivagans) and little brown (Myotis lucifugus) bats only provided evidence of residual spatial correlation among detections. Targeting specific model assumptions using carefully chosen residual diagnostics is valuable for any analysis, and we remove previous barriers for occupancy analyses — lack of examples and practical advice.

Ecology↗
USGS2022

Predator–prey interactions of terrestrial invertebrates are determined by predator body size and species identity

Predator–prey interactions shape ecosystems and can help maintain biodiversity. However, for many of the earth's most biodiverse and abundant organisms, including terrestrial arthropods, these interactions are difficult or impossible to observe directly with traditional approaches. Based on previous theory, it is likely that predator–prey interactions for these organisms are shaped by a combination of predator traits, including body size and species-specific hunting strategies. In this study, we combined diet DNA metabarcoding data of 173 individual invertebrate predators from nine species (a total of 305 individual predator–prey interactions) with an extensive community body size data set of a well-described invertebrate community to explore how predator traits and identity shape interactions. We found that (1) mean size of prey families in the field usually scaled with predator size, with species-specific variation to a general size-scaling relationship (exceptions likely indicating scavenging or feeding on smaller life stages). We also found that (2) although predator hunting traits, including web and venom use, are thought to shape predator–prey interaction outcomes, predator identity more strongly influenced our indirect measure of the relative size of predators and prey (predator:prey size ratios) than either of these hunting traits. Our findings indicate that predator body size and species identity are important in shaping trophic interactions in invertebrate food webs and could help predict how anthropogenic biodiversity change will influence terrestrial invertebrates, the earth's most diverse animal taxonomic group.

Ecology↗
USGS2022

Fitness homeostasis across an experimental water gradient predicts species' geographic range and climatic breadth

Species range sizes and realized niche breadths vary tremendously. Understanding the source of this variation has been a long-term aim in evolutionary ecology and is a major tool in efforts to ameliorate the impacts of changing climates on species distributions. Species ranges that span a large climatic envelope can be achieved by a collection of specialized genotypes locally adapted to a small range of conditions, by genotypes with stable fitness across variable environments, or a combination of these factors. We asked whether fitness expressed along a key niche axis, water availability, could explain a species' realized niche breadth, its geographic range and climate breadth, in 11 species from a clade of jewelflowers whose range sizes vary by two orders of magnitude. Specifically, we explored whether the range size of a species was related to the ability of genotypes (maternal families) to maintain fitness across a range of experimental water availabilities based on 30-year historical field precipitation regimes. We operationally characterized fitness homeostasis through the coefficient of variation in fitness of a genotype (family) across the experimental water gradient. We found that species with genotypes that had high fitness homeostasis, low variation in fitness over our treatments, had larger climatic niche breadth and geographic range in their field distributions. The result was robust to alternate measures of fitness homeostasis. Our results show that the fitness homeostasis of genotypes can be a major factor contributing to niche breadth and range size in this clade. Fitness homeostasis can buffer species from loss of genetic diversity and under changing climates, provides time for adaptation to future conditions.

Ecology↗
USGS2021

Ontogeny of eDNA shedding during early development in Chinook Salmon (Oncorhynchus tshawytscha)

Knowledge of the timing of major life history events in aquatic species is important for informing conservation and resource management planning. Accordingly, surveys of environmental DNA (eDNA) have been performed to determine the efficacy of eDNA for providing information on life history events, primarily focusing on the timing of events associated with spawning, and these studies have proved successful. However, spawning represents only one part of the life history, and therefore, information on eDNA shedding during other life history stages is needed to fill gaps in knowledge. Here, we explored eDNA shedding during early life history (from fertilized eggs until near yolk sac absorption) in Chinook Salmon ( Oncorhynchus tshawytscha ) at three biomasses in a laboratory environment. We found that fertilized eggs shed little eDNA prior to hatching. Hatching coincided with a spike in eDNA, and we observed a significant and positive relationship between eDNA concentration and the number of hatched eggs. The concentration of eDNA shed by larvae after hatching was not consistent across post-hatch sampling days, suggesting developmental and behavioral changes associated with larval ontogeny may affect eDNA shedding rate. These results indicate that eDNA data may be used to identify hatch timing and verify successful reproduction in oviparous aquatic fishes. The application of eDNA to early life history broadens the capacity of eDNA-based methods for assessing population status and trends.

Environmental DNA↗
USGS2023

Dead-end hollow fiber ultrafiltration capture of environmental DNA for freshwater mussel (Unionidae) species detection with metabarcoding

Insufficient water sample volumes can be a limiting factor for detecting species with environmental DNA (eDNA) from aquatic habitats. We compared detections of freshwater mussel (Unionidae) communities using large water sample volumes and dead-end hollow fiber ultrafiltration (D-HFUF or DEUF) with traditional eDNA filtration methods that use relatively small water sample volumes. Unionid species were detected in approximately 50-L D-HFUF eDNA samples with two mitochondrial DNA metabarcoding markers (COI and ND1) and compared to species detection results from eDNA captured from commonly used 1-L samples filtered with polyethersulfone (PES) filters at three lotic sites in Georgia and Missouri. Of the 431,560 COI and 1,035,472 ND1 reads from all environmental samples of both filter types that passed quality control, 95% (410,755 reads) of COI reads and 85% (883,472 reads) of ND1 reads were assigned to a unionid species. Nineteen different freshwater mussel species were detected across all D-HFUF samples, and 11 species were detected across all PES samples. Reads assigned to the genus Elliptio could not be resolved beyond the genus level with either marker. From D-HFUF samples, 15 and 16 mussel species were detected with the COI and ND1 markers, respectively. From PES samples, nine and seven species were detected with the COI and ND1 markers, respectively. More mussel species were detected at each site in D-HFUF samples than in PES samples regardless of whether results from both markers were combined or evaluated separately. Our results demonstrate the merit of further exploration and optimization of D-HFUF for capturing eDNA from high-volume water samples to facilitate detection of unionids and likely other aquatic organisms.

Environmental DNA↗
USGS2007

Modeling the spatial distribution of landslide-prone colluvium and shallow groundwater on hillslopes of Seattle, WA

Landslides in partially saturated colluvium on Seattle, WA, hillslopes have resulted in property damage and human casualties. We developed statistical models of colluvium and shallow-groundwater distributions to aid landslide hazard assessments. The models were developed using a geographic information system, digital geologic maps, digital topography, subsurface exploration results, the groundwater flow modeling software VS2DI and regression analyses. Input to the colluvium model includes slope, distance to a hillslope-crest escarpment, and escarpment slope and height. We developed different statistical relations for thickness of colluvium on four landforms. Groundwater model input includes colluvium basal slope and distance from the Fraser aquifer. This distance was used to estimate hydraulic conductivity based on the assumption that addition of finer-grained material from down-section would result in lower conductivity. Colluvial groundwater is perched so we estimated its saturated thickness. We used VS2DI to establish relations between saturated thickness and the hydraulic conductivity and basal slope of the colluvium. We developed different statistical relations for three groundwater flow regimes. All model results were validated using observational data that were excluded from calibration. Eighty percent of colluvium thickness predictions were within 25% of observed values and 88% of saturated thickness predictions were within 20% of observed values. The models are based on conditions common to many areas, so our method can provide accurate results for similar regions; relations in our statistical models require calibration for new regions. Our results suggest that Seattle landslides occur in native deposits and colluvium, ultimately in response to surface-water erosion of hillstope toes. Regional groundwater conditions do not appear to strongly affect the general distribution of Seattle landslides; historical landslides were equally dispersed within and outside of the area potentially affected by regional groundwater conditions.

Earth Surface Processes and Landforms↗
USGS2016

Episodic bedrock erosion by gully-head migration, Colorado High Plains, USA

This study explores the frequency of bedrock exposure in a soil-mantled low-relief (i.e. non-mountainous) landscape. In the High Plains of eastern Colorado, gully headcuts are among the few erosional features that will incise through the soil mantle to expose bedrock. We measured the last time of bedrock exposure using optically stimulated luminescence dating of alluvial sediment overlying bedrock in gully headcuts. Our dating suggests that headcuts in adjacent gullies expose bedrock asynchronously, and therefore, the headcuts are unlikely to have been triggered by a base-level drop in the trunk stream. This finding supports the hypothesis that headcuts can develop locally in gullies as a result of focused scour in locations where hydraulic stress during a flash flood is sufficiently high, and/or ground cover is sufficiently weak, to generate a scour hole that undermines vegetation. Alluvium dating also reveals that gullies have been a persistent part of this landscape since the early Holocene.

Colorado↗
USGS2021

Sediment-ecological connectivity in a large river network

Sediment eroded from the headwaters of a large basin strongly influences channels and ecosystems far downstream, but the connection is often difficult to trace. Disturbance-dependent riparian trees are thought to rely primarily on floods for formation of the sand bars necessary for seedling establishment, but pulses of sediment should also promote formation of such features. In order to expand understanding of the role of sediment connectivity in governing ecological processes, here we explore the hypothesis that cottonwood forest along the Green and Yampa Rivers in Utah and Colorado are dominated by trees established a century ago during a period of extensive channel migration caused by significant headwater erosion. Analysis of historical documents and aerial photographs suggests that three key tributaries of the Yampa River underwent significant historical erosion from roughly 1880 to 1940. Average width and depth of tributaries with defined arroyos increased two to six times from historical surveys, resulting in the export of ~30 million metric tons of sediment, sizably increasing the sediment load and channel migration rate of the Yampa and Green Rivers. Establishment of major portions of several downstream cottonwood forests occurred during this period of historical erosion, increased sediment loads, and heightened channel migration rates, and the area of forest dating to that time is much greater than can be explained by high flows alone. Viewed collectively, our findings suggest tributary erosion played a vital role in successful downstream forest establishment, a link we contend is best illustrated through a sediment-ecological connectivity framework. Broadly, this framework facilitates consideration of linkages between morphological and ecological processes at the watershed-scale. Development and utilization of a watershed-scale sediment-ecological connectivity perspective highlights the value of sediment as a critical ecological resource to be managed jointly with flow to ensure the maintenance of vital riverine ecosystems.

Colorado, Utah↗
USGS2024

Wildfire, extreme precipitation and debris flows, oh my! Channel response to compounding disturbances in a mountain stream in the Upper Colorado Basin, USA

Compounding changes in climate and human activities stand to increase sediment input to rivers in many landscapes, including via discrete perturbations such as post-fire debris flows. Because sediment supply is a dominant control on river morphology, understanding mountain river responses to sediment regime perturbations is critical to predicting and addressing downstream effects to infrastructure, water security and aquatic habitat. A growing body of literature explores the causes, likelihood, size and composition of post-fire debris flows, but the channel response to these disturbances remains poorly studied. This study used repeat field surveys, time-lapse photographs and pre- and post-disturbance remote sensing datasets to document and analyse space- and time-varying channel response to post-fire debris flows along a steep mountain stream in the Upper Colorado River Basin, USA. Specifically, we evaluated channel morphology and bed composition changes, correlations between channel changes and valley and channel attributes, and the relative importance of spring snowmelt versus summer monsoon events. Several cross-sectional channel change types were observed from lidar a month after post-fire debris-flow events, including channelized and braided incision into deposits, incision into the pre-fire channel bed, bank erosion and no change. Channel changes were most correlated with pre-fire channel width, valley width and unit stream power, and these relationships could be tested in other burned locations to evaluate their transferability. Repeat channel surveys before and after snowmelt indicate rapid recovery and channel narrowing following major sediment disturbances, although sediment deposits remained in the channel margins. Together, these results highlight the importance of field and remote sensing-based channel surveys to improve understanding of, and potential to predict, mountain channel response to compounding climate disturbances.

Earth Surface Processes and Landforms↗
USGS2025

Hyperspectral imaging of river bathymetry using an ensemble of regression trees

Remote sensing has emerged as an effective tool for characterizing river systems, and machine learning (ML) techniques could make this approach even more powerful. To explore this possibility, we developed an ML-based workflow for hyperspectral imaging of river bathymetry using an ensemble of regression trees (HIRBERT). This approach involves using paired observations of depth and reflectance to select wavelength bands as predictors and then train a depth retrieval model; applying the model to the image yields a spatially continuous bathymetric map. We used data from five rivers with diverse morphologies and optical characteristics to assess whether HIRBERT can (1) provide more accurate depth estimates than a band ratio-based algorithm and (2) extend the range of depths detectable via remote sensing. Relative to single band combinations identified via optimal band ratio analysis (OBRA), regression tree ensembles improved depth retrieval performance, with observed versus predicted (OP) regression R 2 values increasing for all five sites. Similarly, HIRBERT provided more reliable depth estimates than OBRA over the full range of depths present along each river. These results suggest that by incorporating additional spectral information from multiple wavelength bands, ML could enhance bathymetric mapping across a range of river environments. In addition, we show how graphical tools can facilitate interpretation of ML-based depth retrieval models and yield insight regarding relationships between depth and reflectance. The HIRBERT workflow is packaged in free, standalone software developed to support applications in river research and management. Although ML can enhance remote sensing of river bathymetry, the limitations of this approach must also be acknowledged: Field measurements of water depth are required to train a depth retrieval model and the resulting model should only be applied to the image from which the training data were derived. The inherently image-specific nature of this approach implies that developing generalized regression tree ensembles that could be applied at larger scales would require additional research.

California, Idaho, Nebraska, Oregon, Wyoming↗
USGS2025

River ice controls permafrost bank erosion across an Arctic delta

Bank erosion in Arctic rivers helps shape channel geometry, mobilizes carbon from permafrost and influences sediment delivery to the Arctic Ocean. On Alaska's Arctic coastal plain, rivers begin flowing during snowmelt in late spring while extensive river ice persists in channels, such that hydraulics are altered and water is kept cool. The effects of river ice on permafrost bank erosion are poorly understood, primarily due to a dearth of field observations and a lack of river ice in existing models. To address this knowledge gap, we developed a numerical model to simulate the melt of substrate interstitial ice and bank collapse along individual permafrost river banks. We parameterize the model with field observations from riverbanks in three different channels on the Canning River delta, which are disparately impacted by river ice during snowmelt. We explore the bank erosion produced without river ice in the model and with modern river ice model scenarios that we drive with different stages and water temperature boundary conditions. We also compare predicted erosion rates to observations from satellite imagery to validate this approach. In the model, banks are idealized as vertical profiles that rise 1–2 m above the river bed and are comprised of silt- to sand-sized sediment with dense roots in the active layer. Underneath, we generalize bank ice content underneath the active layer to represent ice-rich permafrost on the river corridor boundaries. The model predicts that these ice-rich river banks can erode by 2–6 m/yr. Scenarios without ice underpredict erosion in the distributary channels. Scenarios with varying river ice for different deltaic channels produce erosion rates similar to observations. Our results suggest that the prolonged melt of thick river ice in a delta nonlinearly impacts permafrost bank erosion by blocking river discharge to certain branches, heightening stage across the distributary network and locally limiting river water warming. Given expected changes in air temperature and hydrology, future estimates of Arctic river bank erosion could be improved by considering river ice.

Alaska↗
USGS2026

Site response models based on geometric parameters for southern California sedimentary basins

Site response in sedimentary basins is influenced by complex three-dimensional (3D) features, including trapping of seismic waves, focusing of seismic energy and basin resonance. Current ground motion models (GMMs) incorporate basin effects using one-dimensional parameters like V S30 and shear wave velocity isosurface depths, which are limited in capturing lateral and 3D effects. To address these limitations, we develop seismic site response models based on novel parameters that represent multi-dimensional properties of the Los Angeles Basin (LAB) geometry and shear wave velocity. We define a basin shape for the LAB using depth to subsurface geologic interfaces associated with the oldest sedimentary deposits (depth to a particular shear wave velocity horizon, i.e., 1.5 km/s - z 1.5 ) and the depth to the crystalline basement ( z cb ) which are determined using geologic cross sections and community seismic velocity model profiles. We explore a suite of geometric descriptors computed for the LAB and southern California, from which three parameters with the greatest predictive potential are selected and evaluated using empirical ground motion residual analyses in combination with the Boore et al. GMM. The results demonstrate that the zonal heterogeneity index ( ), standard deviation of the absolute difference between z 1.5 and z cb ( ) and standard deviation of z cb ( ) each provide a reduction in site-to-site variability ( ϕ S2S ) of empirical GMMs. The reduction in ϕ S2S is period-dependent, with average decreases of 3%, 26% and 6% for , , and , respectively. Although these reductions are modest from an engineering application perspective, they are statistically significant, underscoring the inherent difficulty in fully characterising complex basin effects. Collectively, these findings indicate that the inclusion of basin-specific geometric parameters yields measurable, albeit incremental, improvements in site response prediction and establishes a framework for the progressive refinement of seismic hazard characterisation within sedimentary basins.

California↗
USGS2016

Larval aquatic insect responses to cadmium and zinc in experimental streams

To evaluate the risks of metal mixture effects to natural stream communities under ecologically relevant conditions, the authors conducted 30-d tests with benthic macroinvertebrates exposed to cadmium (Cd) and zinc (Zn) in experimental streams. The simultaneous exposures were with Cd and Zn singly and with Cd+Zn mixtures at environmentally relevant ratios. The tests produced concentration–response patterns that for individual taxa were interpreted in the same manner as classic single-species toxicity tests and for community metrics such as taxa richness and mayfly (Ephemeroptera) abundance were interpreted in the same manner as with stream survey data. Effect concentrations from the experimental stream exposures were usually 2 to 3 orders of magnitude lower than those from classic single-species tests. Relative to a response addition model, which assumes that the joint toxicity of the mixtures can be predicted from the product of their responses to individual toxicants, the Cd+Zn mixtures generally showed slightly less than additive toxicity. The authors applied a modeling approach called Tox to explore the mixture toxicity results and to relate the experimental stream results to field data. The approach predicts the accumulation of toxicants (hydrogen, Cd, and Zn) on organisms using a 2-p K a bidentate model that defines interactions between dissolved cations and biological receptors (biotic ligands) and relates that accumulation through a logistic equation to biological response. The Tox modeling was able to predict Cd+Zn mixture responses from the single-metal exposures as well as responses from field data. The similarity of response patterns between the 30-d experimental stream tests and field data supports the environmental relevance of testing aquatic insects in experimental streams.

Environmental Toxicology and Chemistry↗
USGS2020

Legacy and current‐use contaminants in sediments alter macroinvertebrate communities in southeastern US Streams

Sediment contamination of freshwater streams in urban areas is a recognized and growing concern. As a part of a comprehensive regional stream‐quality assessment, stream‐bed sediment was sampled from streams spanning a gradient of urban intensity in the Piedmont ecoregion of the southeastern United States. We evaluated relations between a broad suite of sediment contaminants (metals, current‐use pesticides, organochlorine pesticides, polychlorinated biphenyls, brominated diphenyl ethers, and polycyclic aromatic hydrocarbons), ambient sediment toxicity, and macroinvertebrate communities from 76 sites. Sediment toxicity was evaluated by conducting whole‐sediment laboratory toxicity testing with the amphipod Hyalella azteca (for 28 d) and the midge Chironomus dilutus (for 10 d). Approximately one‐third of the sediment samples were identified as toxic for at least one test species endpoint, although concentrations of contaminants infrequently exceeded toxicity benchmarks. Ratios of contaminant concentrations relative to their benchmarks, both individually and as summed benchmark quotients, were explored on a carbon‐normalized and a dry‐weight basis. Invertebrate taxa measures from ecological surveys tended to decline with increasing urbanization and with sediment contamination. Toxicity test endpoints were more strongly related to sediment contamination than invertebrate community measures were. Sediment chemistry and sediment toxicity provided moderate and weak, respectively, explanatory power for the similarity/dissimilarity of invertebrate communities. The results indicate that current single‐chemical sediment benchmarks may underestimate the effects from mixtures of sediment contaminants experienced by lotic invertebrates.

Alabama, Georgia, South Carolina, North Carolina, ↗