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USGS2013

Salton Sea ecosystem monitoring and assessment plan

The Salton Sea, California’s largest lake, provides essential habitat for several fish and wildlife species and is an important cultural and recreational resource. It has no outlet, and dissolved salts contained in the inflows concentrate in the Salton Sea through evaporation. The salinity of the Salton Sea, which is currently nearly one and a half times the salinity of ocean water, has been increasing as a result of evaporative processes and low freshwater inputs. Further reductions in inflows from water conservation, recycling, and transfers will lower the level of the Salton Sea and accelerate the rate of salinity increases, reduce the suitability of fish and wildlife habitat, and affect air quality by exposing lakebed playa that could generate dust. Legislation enacted in 2003 to implement the Quantification Settlement Agreement (QSA) stated the Legislature’s intent for the State of California to undertake the restoration of the Salton Sea ecosystem. As required by the legislation, the California Resources Agency (now California Natural Resources Agency) produced the Salton Sea Ecosystem Restoration Study and final Programmatic Environmental Impact Report (PEIR; California Resources Agency, 2007) with the stated purpose to “develop a preferred alternative by exploring alternative ways to restore important ecological functions of the Salton Sea that have existed for about 100 years.” A decision regarding a preferred alternative currently resides with the California State Legislature (Legislature), which has yet to take action. As part of efforts to identify an ecosystem restoration program for the Salton Sea, and in anticipation of direction from the Legislature, the California Department of Water Resources (DWR), California Department of Fish and Wildlife (CDFW), U.S. Bureau of Reclamation (Reclamation), and U.S. Geological Survey (USGS) established a team to develop a monitoring and assessment plan (MAP). This plan is the product of that effort. The goal of the MAP is to provide a guide for data collection, analysis, management, and reporting to inform management actions for the Salton Sea ecosystem. Monitoring activities are directed at species and habitats that could be affected by or drive future restoration activities. The MAP is not intended to be a prescriptive document. Rather, it is envisioned to be a flexible, program-level guide that articulates high-level goals and objectives, and establishes broad sideboards within which future project-level investigations and studies will be evaluated and authorized. As such, the MAP, by design, does not, for example, include detailed protocols describing how investigations will be implemented. It is anticipated that detailed study proposals will be prepared as part of an implementation plan that will include such things as specific sampling objectives, sampling schemes, and statistical and spatial limits.

California↗

USGS2016

Conifer density within lake catchments predicts fish mercury concentrations in remote subalpine lakes

Remote high-elevation lakes represent unique environments for evaluating the bioaccumulation of atmospherically deposited mercury through freshwater food webs, as well as for evaluating the relative importance of mercury loading versus landscape influences on mercury bioaccumulation. The increase in mercury deposition to these systems over the past century, coupled with their limited exposure to direct anthropogenic disturbance make them useful indicators for estimating how changes in mercury emissions may propagate to changes in Hg bioaccumulation and ecological risk. We evaluated mercury concentrations in resident fish from 28 high-elevation, sub-alpine lakes in the Pacific Northwest region of the United States. Fish total mercury (THg) concentrations ranged from 4 to 438 ng/g wet weight, with a geometric mean concentration (±standard error) of 43 ± 2 ng/g ww. Fish THg concentrations were negatively correlated with relative condition factor, indicating that faster growing fish that are in better condition have lower THg concentrations. Across the 28 study lakes, mean THg concentrations of resident salmonid fishes varied as much as 18-fold among lakes. We used a hierarchal statistical approach to evaluate the relative importance of physiological, limnological, and catchment drivers of fish Hg concentrations. Our top statistical model explained 87% of the variability in fish THg concentrations among lakes with four key landscape and limnological variables: catchment conifer density (basal area of conifers within a lake's catchment), lake surface area, aqueous dissolved sulfate, and dissolved organic carbon. Conifer density within a lake's catchment was the most important variable explaining fish THg concentrations across lakes, with THg concentrations differing by more than 400 percent across the forest density spectrum. These results illustrate the importance of landscape characteristics in controlling mercury bioaccumulation in fish.

Environmental Pollution↗

USGS2021

Stable oxygen isotopes in shallow marine ostracodes from the northern Bering and Chukchi Seas

Stable oxygen isotope measurements on calcitic valves of benthic ostracodes (δ18Oost) from the northern Bering and Chukchi Seas were used to examine ecological and hydrographic processes governing ostracode and associated seawater δ18O values. Five cryophilic taxa were analyzed for δ18Oost values: Sarsicytheridea bradii; Paracyprideis pseudopunctillata; Heterocyprideis sorbyana; Heterocyprideis fascis; and the subarctic species Normanicythere leioderma. Controls on the stable oxygen isotope composition of ostracode calcite were investigated by first establishing species' vital effects and then comparing δ18Oost to seawater δ18O values (that ranged from −2.7 to −0.5‰), CTD temperature (−1.7 to 8.7 °C) and salinity (30–34) measured at sampling stations in the Bering and Chukchi Seas during the six summers of 2013–2018. Results from 297 δ18Oost measurements from 53 sites on the Bering and Chukchi Sea continental shelves are consistent with the temporal and spatial variation in δ18O values of continental shelf bottom water, as impacted by seasonality, regional hydrography, and physical processes (i.e., sea-ice melt and extent, vertical mixing, precipitation/evaporation). Regression statistics for δ18Oost values of two species, N. leioderma and P. pseudopunctillata, showed correlations to temperature and salinity that may facilitate prediction of water-mass characteristics when applied to sediment core records. Specifically, a significant linear regression relationship was found between δ18Oost values of N. leioderma and P. pseudopunctillata and temperature (R2 = 0.67 and 0.52, respectively). A principal component analysis confirmed temperature as the main controlling factor in the δ18Oost values of all species except S. bradii, with samples of distinct water masses grouping together. The δ18Oost values of S. bradii exhibited a narrow range of values (~3 to 4.5‰) across a temperature range of 10 °C. Due to strong vital effects and possibly other undetermined factors, the incorporation of δ18Oost in S. bradii was not driven by any obvious predominant environmental factors.

Marine Micropaleontology↗

USGS2014

Evaluating the efficiency of environmental monitoring programs

Statistical uncertainty analyses can be used to improve the efficiency of environmental monitoring, allowing sampling designs to maximize information gained relative to resources required for data collection and analysis. In this paper, we illustrate four methods of data analysis appropriate to four types of environmental monitoring designs. To analyze a long-term record from a single site, we applied a general linear model to weekly stream chemistry data at Biscuit Brook, NY, to simulate the effects of reducing sampling effort and to evaluate statistical confidence in the detection of change over time. To illustrate a detectable difference analysis, we analyzed a one-time survey of mercury concentrations in loon tissues in lakes in the Adirondack Park, NY, demonstrating the effects of sampling intensity on statistical power and the selection of a resampling interval. To illustrate a bootstrapping method, we analyzed the plot-level sampling intensity of forest inventory at the Hubbard Brook Experimental Forest, NH, to quantify the sampling regime needed to achieve a desired confidence interval. Finally, to analyze time-series data from multiple sites, we assessed the number of lakes and the number of samples per year needed to monitor change over time in Adirondack lake chemistry using a repeated-measures mixed-effects model. Evaluations of time series and synoptic long-term monitoring data can help determine whether sampling should be re-allocated in space or time to optimize the use of financial and human resources.

Ecological Indicators↗

USGS2001

Spatial paradigms of lotic diatom distribution: A landscape ecology perspective

Spatial distributional patterns of benthic diatoms and their relation to current velocity were investigated in an unshaded cobble-bottom reach of White Creek (Washington County, NY). On 27 August 1999, diatoms were sampled and current velocity and depth were measured on a regular square sampling grid with a grain size of 0.01 m2, interval of 0.5 m, and extent of 16 m2. The relative abundance of the 18 common diatom species enumerated in the 81 samples was subjected to detrended correspondence analysis (DCA). The first axis (DCA1) explained 51% of the variance in diatom data and separated the samples according to current regimes. The spatial autocorrelation of DCA1 sample scores in deposition and erosion regions of White Creek was determined by Moran's I statistic to indicate patch size. In White Creek the patch length of all diatom communities was more than 3.1 m, whereas the patch width was 1 m in the deposition region and 0.5 m in the erosion region. There were 5 dominant diatom taxa, Achnanthes minutissima Ku??tz. et vars, Fragilaria capucina Dezmazie??res et vars, F. crotonensis Kitt., Diatoma vulgaris Bory, and Synedra ulna (Nitz.) Ehr. et vars. The patch length of the dominant species varied from 1 to more than 4.1 m, whereas the patch width, if defined, was 0.5 m. Achnanthes minutissima and F. capucina, the two diatom species with the highest relative abundance, displayed spatially structured patches of low abundance and comparatively random patches of high abundance, suggesting broad scale abiotic control of species performance in low abundance regions and finer scale biotic control of high abundance areas. Another objective of this study was to test the hypothesis that higher current velocities, which generally impede immigration, would increase randomness and complexity (i.e. homogeneity of diatom distributional patterns). The spatial complexity in low versus high velocity transects was determined by calculating the respective fractal dimension (D) of DCA1 scores. D of DCA1 was higher in the higher current velocity transects, suggesting that spatial complexity and homogeneity of diatom communities increased in faster currents. Partial canonical correspondence analysis was conducted on diatom, environmental, and spatial data to assess how much of the variance in species distribution could be attributed to environmental (current velocity and depth) versus spatial factors. The variance of species data, explained by the environment (exclusively current velocity), was 38%; whereas space alone contributed only 10%, indicating that 1) current velocity was the major factor that controlled diatom distribution in streams and 2) there were other spatially dependent variables, most likely biotic, but their role in shaping diatom communities was minor.

Journal of Phycology↗

USGS2016

Detection limits of quantitative and digital PCR assays and their influence in presence-absence surveys of environmental DNA

A set of universal guidelines is needed to determine the limit of detection (LOD) in PCR-based analyses of low concentration DNA. In particular, environmental DNA (eDNA) studies require sensitive and reliable methods to detect rare and cryptic species through shed genetic material in environmental samples. Current strategies for assessing detection limits of eDNA are either too stringent or subjective, possibly resulting in biased estimates of species’ presence. Here, a conservative LOD analysis grounded in analytical chemistry is proposed to correct for overestimated DNA concentrations predominantly caused by the concentration plateau, a nonlinear relationship between expected and measured DNA concentrations. We have used statistical criteria to establish formal mathematical models for both quantitative and droplet digital PCR. To assess the method, a new Grass Carp ( Ctenopharyngodon idella ) TaqMan assay was developed and tested on both PCR platforms using eDNA in water samples. The LOD adjustment reduced Grass Carp occupancy and detection estimates while increasing uncertainty – indicating that caution needs to be applied to eDNA data without LOD correction. Compared to quantitative PCR, digital PCR had higher occurrence estimates due to increased sensitivity and dilution of inhibitors at low concentrations. Without accurate LOD correction, species occurrence and detection probabilities based on eDNA estimates are prone to a source of bias that cannot be reduced by an increase in sample size or PCR replicates. Other applications also could benefit from a standardized LOD such as GMO food analysis, and forensic and clinical diagnostics.

Molecular Ecology Resources↗

USGS2007

Iteroparity in the variable environment of the salamander Ambystoma tigrinum

Simultaneous estimation of survival, reproduction, and movement is essential to understanding how species maximize lifetime reproduction in environments that vary across space and time. We conducted a four-year, capture–recapture study of three populations of eastern tiger salamanders ( Ambystoma tigrinum tigrinum ) and used multistate mark–recapture statistical methods to estimate the manner in which movement, survival, and breeding probabilities vary under different environmental conditions across years and among populations and habitats. We inferred how individuals may mitigate risks of mortality and reproductive failure by deferring breeding or by moving among populations. Movement probabilities among populations were extremely low despite high spatiotemporal variation in reproductive success and survival, suggesting possible costs to movements among breeding ponds. Breeding probabilities varied between wet and dry years and according to whether or not breeding was attempted in the previous year. Estimates of survival in the nonbreeding, forest habitat varied among populations but were consistent across time. Survival in breeding ponds was generally high in years with average or high precipitation, except for males in an especially ephemeral pond. A drought year incurred severe survival costs in all ponds to animals that attempted breeding. Female salamanders appear to defer these episodic survival costs of breeding by choosing not to breed in years when the risk of adult mortality is high. Using stochastic simulations of survival and breeding under historical climate conditions, we found that an interaction between breeding probabilities and mortality limits the probability of multiple breeding attempts differently between the sexes and among populations.

Virginia↗

USGS2007

Spatial design and strength of spatial signal: Effects on covariance estimation

In a spatial regression context, scientists are often interested in a physical interpretation of components of the parametric covariance function. For example, spatial covariance parameter estimates in ecological settings have been interpreted to describe spatial heterogeneity or “patchiness” in a landscape that cannot be explained by measured covariates. In this article, we investigate the influence of the strength of spatial dependence on maximum likelihood (ML) and restricted maximum likelihood (REML) estimates of covariance parameters in an exponential-with-nugget model, and we also examine these influences under different sampling designs—specifically, lattice designs and more realistic random and cluster designs—at differing intensities of sampling ( n =144 and 361). We find that neither ML nor REML estimates perform well when the range parameter and/or the nugget-to-sill ratio is large—ML tends to underestimate the autocorrelation function and REML produces highly variable estimates of the autocorrelation function. The best estimates of both the covariance parameters and the autocorrelation function come under the cluster sampling design and large sample sizes. As a motivating example, we consider a spatial model for stream sulfate concentration.

Journal of Agricultural, Biological, and Environme↗

USGS2004

Comparison of fluorescence microscopy and solid-phase cytometry methods for counting bacteria in water

Total direct counts of bacterial abundance are central in assessing the biomass and bacteriological quality of water in ecological and industrial applications. Several factors have been identified that contribute to the variability in bacterial abundance counts when using fluorescent microscopy, the most significant of which is retaining an adequate number of cells per filter to ensure an acceptable level of statistical confidence in the resulting data. Previous studies that have assessed the components of total-direct-count methods that contribute to this variance have attempted to maintain a bacterial cell abundance value per filter of approximately 10 6 cells filter -1 . In this study we have established the lower limit for the number of bacterial cells per filter at which the statistical reliability of the abundance estimate is no longer acceptable. Our results indicate that when the numbers of bacterial cells per filter were progressively reduced below 10 5 , the microscopic methods increasingly overestimated the true bacterial abundance (range, 15.0 to 99.3%). The solid-phase cytometer only slightly overestimated the true bacterial abundances and was more consistent over the same range of bacterial abundances per filter (range, 8.9 to 12.5%). The solid-phase cytometer method for conducting total direct counts of bacteria was less biased and performed significantly better than any of the microscope methods. It was also found that microscopic count data from counting 5 fields on three separate filters were statistically equivalent to data from counting 20 fields on a single filter.

Applied and Environmental Microbiology↗

USGS2020

Hydrogeomorphological controls on reach‐scale distributions of cichlid nest sites in a small neotropical river

The Cichlidae are among the most diversified families of fish in the Neotropics and represent an important component of aquatic biodiversity. Understanding cichlid nest‐site selection is important for assemblages facing uncertain futures due to species invasions and environmental change. This information could be used to predict how inter‐ and intraspecific competition for reproductive space may affect populations with changing community dynamics or to identify areas as targets for conservation. We investigated which hydrogeomorphological factors correlated to preferred nest sites of four native cichlid species in the Bladen River, Belize. We recorded the locations of nest sites and collected habitat data through the study reach, including flow velocity, depth, sediment type, fish cover type richness and distance to the bank. Nest locations and physical habitat data were used to construct spatially explicit habitat models using boosted regression trees (BRTs). The models provided statistically significant evidence that physical habitat variables influence the distribution of the nest sites. We found that all species except Archocentrus spilurus were associated with substrate, specifically sand. Thorichthys meeki was also associated with lower water velocities, whereas Cichlasoma salvini was influenced by all five variables. Vieja maculicauda and Archocentrus spilurus were both influenced by flow velocity, distance to bank and depth, although A. spilurus preferred deeper, slightly faster locations about the same distance to the bank. This study suggests that the spatial distribution of nest sites within this cichlid community is significantly different than random and is at least partially governed by physical controls.

Monkey River Basin↗

USGS2016

Evaluating land cover influences on model uncertainties—A case study of cropland carbon dynamics in the Mid-Continent Intensive Campaign region

Quantifying spatial and temporal patterns of carbon sources and sinks and their uncertainties across agriculture-dominated areas remains challenging for understanding regional carbon cycles. Characteristics of local land cover inputs could impact the regional carbon estimates but the effect has not been fully evaluated in the past. Within the North American Carbon Program Mid-Continent Intensive (MCI) Campaign, three models were developed to estimate carbon fluxes on croplands: an inventory-based model, the Environmental Policy Integrated Climate (EPIC) model, and the General Ensemble biogeochemical Modeling System (GEMS) model. They all provided estimates of three major carbon fluxes on cropland: net primary production (NPP), net ecosystem production (NEP), and soil organic carbon (SOC) change. Using data mining and spatial statistics, we studied the spatial distribution of the carbon fluxes uncertainties and the relationships between the uncertainties and the land cover characteristics. Results indicated that uncertainties for all three carbon fluxes were not randomly distributed, but instead formed multiple clusters within the MCI region. We investigated the impacts of three land cover characteristics on the fluxes uncertainties: cropland percentage, cropland richness and cropland diversity. The results indicated that cropland percentage significantly influenced the uncertainties of NPP and NEP, but not on the uncertainties of SOC change. Greater uncertainties of NPP and NEP were found in counties with small cropland percentage than the counties with large cropland percentage. Cropland species richness and diversity also showed negative correlations with the model uncertainties. Our study demonstrated that the land cover characteristics contributed to the uncertainties of regional carbon fluxes estimates. The approaches we used in this study can be applied to other ecosystem models to identify the areas with high uncertainties and where models can be improved to reduce overall uncertainties for regional carbon flux estimates.

Mid-Continent Intensive Campaign region↗

USGS2016

Detecting significant change in stream benthic macroinvertebrate communities in wilderness areas

A major challenge in the biological monitoring of stream ecosystems in protected wilderness areas is discerning whether temporal changes in community structure are significantly outside of a reference condition that represents natural or acceptable annual variation in population cycles. Otherwise sites could erroneously be classified as impaired. Long-term datasets are essential for understanding these trends, to ascertain whether any changes in community structure significantly beyond the reference condition are permanent shifts or with time move back to within previous limits. To this end, we searched for long-term (>8 years) quantitative data sets of macroinvertebrate communities in wadeable rivers collected by similar methods and time of year in protected wilderness areas with minimal anthropogenic disturbance. Four geographic areas with datasets that met these criteria in the USA were identified, namely: McLaughlin Nature Reserve in California (1 stream), Great Smoky Mountains National Park in Tennesse-North Carolina (14 streams), Wind River Wilderness Areas in Wyoming (3 streams) and Denali National Park and Preserve in Alaska (6 streams). Two statistical approaches were applied: Taxonomic Distinctness (TD) to describe changes in diversity over time and non-metric multidimensional scaling (MDS) to describe changes over time in community persistence (Jaccards Index) and community stability (Bray–Curtis Index). Control charts were used to determine if years in MDS plots were significantly outside a reference condition. For Hunting Creek, TD showed three years outside natural variation which could be attributed to severe hydrological events but years outside the natural-variation funnel at sites in other geographical areas were inconsistent and could not be explained by environmental variables. TD identified simulated severe pollutant events which caused the removal of entire invertebrate assemblages but not simulated water temperature shifts. Within a region, both MDS analyses typically identified similar years as exceeding reference condition variation, illustrating the utility of the approach for identifying wider spatial scale effects that influence more than one stream. MDS responded to both simulated water temperature stress and a pollutant event, and generally outlying years on MDS plots could be explained by environmental variables, particularly higher precipitation. Multivariate control charts successfully identified whether shifts in community structure identified by MDS were significant and whether the shift represented a press disturbance (long-term change) or a pulse disturbance. We consider a combination of TD and MDS with control charts to be a potentially powerful tool for determining years significantly outside of a reference condition variation.

Alaska, California, North Carolina, Tennesse, Wyom↗

USGS2018

A geostatistical state‐space model of animal densities for stream networks

Population dynamics are often correlated in space and time due to correlations in environmental drivers as well as synchrony induced by individual dispersal. Many statistical analyses of populations ignore potential autocorrelations and assume that survey methods (distance and time between samples) eliminate these correlations, allowing samples to be treated independently. If these assumptions are incorrect, results and therefore inference may be biased and uncertainty underestimated. We developed a novel statistical method to account for spatiotemporal correlations within dendritic stream networks, while accounting for imperfect detection in the surveys. Through simulations, we found this model decreased predictive error relative to standard statistical methods when data were spatially correlated based on stream distance and performed similarly when data were not correlated. We found that increasing the number of years surveyed substantially improved the model accuracy when estimating spatial and temporal correlation coefficients, especially from 10 to 15 yr. Increasing the number of survey sites within the network improved the performance of the nonspatial model but only marginally improved the density estimates in the spatiotemporal model. We applied this model to brook trout data from the West Susquehanna Watershed in Pennsylvania collected over 34 yr from 1981 to 2014. We found the model including temporal and spatiotemporal autocorrelation best described young of the year (YOY) and adult density patterns. YOY densities were positively related to forest cover and negatively related to spring temperatures with low temporal autocorrelation and moderately high spatiotemporal correlation. Adult densities were less strongly affected by climatic conditions and less temporally variable than YOY but with similar spatiotemporal correlation and higher temporal autocorrelation.

Ecological Applications↗

USGS2020

Effects of stormwater runoff from selected bridge decks on conditions of water, sediment, and biological quality in receiving waters in South Carolina, 2013 to 2018

The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, investigated the effects of stormwater runoff from bridge decks on stream water quality conditions in South Carolina. The investigation assessed 5 bridges in 3 physiographic provinces in South Carolina (Piedmont, Upper Coastal Plain, and Lower Coast Plain) that had a range of bridge, traffic, and hydrologic characteristics. The five selected South Carolina bridge sites (coincident with U.S. Geological Survey stations) and corresponding highways were Lynches River at Effingham (station 02132000; U.S. Highway 52), North Fork Edisto River at Orangeburg (station 02173500; U.S. Highway 301), Turkey Creek above Huger (station 02172035; South Carolina Highway 41), South Fork Edisto River near Denmark (station 02173000; U.S. Highway 321), and Fishing Creek at Highway 5 below York (station 021473415; South Carolina Highway 5). Bridge decks at the selected sites used open chutes, scuppers, and downspouts to drain stormwater directly into the receiving water at evenly spaced intervals. Stream water, sediment, and biological samples were collected and analyzed for a variety of constituents to evaluate the stream conditions for this study. Five to six stream samples were collected at transects upstream and downstream from each selected bridge site using the equal-width-increment technique during observable stormwater runoff. Routine samples of the receiving waters were collected 12 to 14 times at the upstream transect during nonstorm conditions. Samples were analyzed for physical properties, suspended sediment, nutrients, major ions, trace metals, polycyclic aromatic hydrocarbons, and Escherichia coli . Bridge-deck sediment and streambed sediment at upstream and downstream transects were collected once at each bridge site and analyzed for metals and semivolatile organic compounds that include polycyclic aromatic hydrocarbons. Benthic macroinvertebrate community surveys were conducted once using Hester-Dendy multiplate artificial substrate samplers deployed at multiple upstream and downstream transects concurrently. Statistical analysis of the water-quality data determined that stormwater runoff from bridges did not significantly degrade physical properties, nor nutrient, trace-metal, Escherichia coli , and suspended-sediment concentrations at the selected sites beyond the variability at the upstream transect (no bridge influence) during the study period. During storm sampling at the bridge sites, water-quality conditions were statistically similar upstream and downstream from each bridge, except for greater turbidity, total nitrogen, and total organic nitrogen plus ammonia concentrations found downstream from the bridge site on Fishing Creek; higher total chromium concentrations detected downstream from the bridge site on Turkey Creek; and increased Escherichia coli concentrations found downstream from the bridge site on the North Fork Edisto River. Total recoverable lead, cadmium, and copper concentrations were the only trace metals that periodically exceeded the South Carolina Department of Health and Environmental Control freshwater aquatic-life criteria at some bridge sites (lead, copper, and cadmium in Turkey Creek; cadmium and lead in Fishing Creek; lead in the South Fork Edisto River and Lynches River), but the exceedances occurred more frequently during routine sampling upstream from the bridge sites than during storm sampling at upstream and downstream transects. In general, stormwater runoff from the bridge decks did not seem to be the major source of metal enrichment in receiving waters during the study period. North Fork and South Fork Edisto Rivers and Turkey Creek had only one storm sample that exceeded South Carolina Department of Health and Environmental Control recreational criterion for Escherichia coli at both the upstream and downstream locations, while Fishing Creek had more frequent exceedances. Polycyclic aromatic hydrocarbons were detected infrequently in the stream samples. In general, sediment trace-metal concentrations were below the threshold and probable effect concentration at all bridge sites, except for the chromium concentration (45.1 milligrams per kilogram) detected upstream from the bridge site on Fishing Creek that exceeded the threshold effect concentration of 43.4 milligrams per kilogram. Based on enrichment ratios less than 1.5, bridge-deck runoff did not seem to be affecting trace-metal accumulation in the streambed sediment downstream from the bridge sites, except for lead at the bridge site on the Lynches River and manganese at the bridge site on Fishing Creek. Individual polycyclic aromatic compound concentrations and the sum of 18 compounds did not exceed any threshold and probable effect concentrations, indicating polycyclic aromatic hydrocarbon concentrations in the streambed sediment at downstream and upstream transects were not likely to affect the health of benthic macroinvertebrate communities. Although the cumulative polycyclic aromatic hydrocarbon concentrations in downstream sediment at the sites on Turkey and Fishing Creeks were well below the threshold effect concentration of 1,610 micrograms per kilogram, the 3- to 100-fold increase in downstream concentrations indicated a strong probability of a bridge-deck runoff source. Overall, benthic macroinvertebrate community health downstream from the bridge sites did not seem to be affected by bridge-deck runoff based on several multivariate analyses that indicated statistically similar benthic macroinvertebrate communities at upstream and downstream transects. Of the five bridge sites in this study, the site on Turkey Creek seemed to have the least healthy benthic macroinvertebrate communities because of the lowest Ephemeroptera, Plecoptera, and Trichoptera spp. (mayflies, stoneflies, and caddisflies, respectively) taxa, species richness, and diversity; and the highest biotic indices, indicative of poorer ecological health, at upstream and downstream transects. This ecological finding was not unexpected because of seasonal periods of negligible flow when dissolved-oxygen concentrations fell below 4 milligrams per liter during the study period. Of the five bridge sites in this study, the site on the South Fork Edisto River seemed to have healthier benthic macroinvertebrate communities because of the greater mean Ephemeroptera, Plecoptera, and Trichoptera spp. taxa; and lower mean biotic indices at upstream and downstream transects.

Scientific Investigations Report↗

USGS2006

Hierarchical models of animal abundance and occurrence

Much of animal ecology is devoted to studies of abundance and occurrence of species, based on surveys of spatially referenced sample units. These surveys frequently yield sparse counts that are contaminated by imperfect detection, making direct inference about abundance or occurrence based on observational data infeasible. This article describes a flexible hierarchical modeling framework for estimation and inference about animal abundance and occurrence from survey data that are subject to imperfect detection. Within this framework, we specify models of abundance and detectability of animals at the level of the local populations defined by the sample units. Information at the level of the local population is aggregated by specifying models that describe variation in abundance and detection among sites. We describe likelihood-based and Bayesian methods for estimation and inference under the resulting hierarchical model. We provide two examples of the application of hierarchical models to animal survey data, the first based on removal counts of stream fish and the second based on avian quadrat counts. For both examples, we provide a Bayesian analysis of the models using the software WinBUGS.

Journal of Agricultural, Biological, and Environme↗

USGS2017

Imputation approaches for animal movement modeling

The analysis of telemetry data is common in animal ecological studies. While the collection of telemetry data for individual animals has improved dramatically, the methods to properly account for inherent uncertainties (e.g., measurement error, dependence, barriers to movement) have lagged behind. Still, many new statistical approaches have been developed to infer unknown quantities affecting animal movement or predict movement based on telemetry data. Hierarchical statistical models are useful to account for some of the aforementioned uncertainties, as well as provide population-level inference, but they often come with an increased computational burden. For certain types of statistical models, it is straightforward to provide inference if the latent true animal trajectory is known, but challenging otherwise. In these cases, approaches related to multiple imputation have been employed to account for the uncertainty associated with our knowledge of the latent trajectory. Despite the increasing use of imputation approaches for modeling animal movement, the general sensitivity and accuracy of these methods have not been explored in detail. We provide an introduction to animal movement modeling and describe how imputation approaches may be helpful for certain types of models. We also assess the performance of imputation approaches in two simulation studies. Our simulation studies suggests that inference for model parameters directly related to the location of an individual may be more accurate than inference for parameters associated with higher-order processes such as velocity or acceleration. Finally, we apply these methods to analyze a telemetry data set involving northern fur seals ( Callorhinus ursinus ) in the Bering Sea. Supplementary materials accompanying this paper appear online.

Journal of Agricultural, Biological, and Environme↗

USGS2021

Vegetation community monitoring: Species composition and biophysical gradients in Klamath Network parks

The Klamath Network of the National Park Service consists of six park units located in northern California and southern Oregon. The Network began implementing a vegetation monitoring protocol in 2011 to identify ecologically significant vegetation trends in the parks. The premise of the protocol is that multivariate analyses of species composition data is the most robust early detection means for identifying vegetation change over time. Here we present these community metrics, based on our initial sampling efforts. We use these metrics to establish a baseline for comparison in future trend analysis, and to evaluate the adequacy of the protocol for meeting the Network’s objectives of detecting temporal changes across contrasting vegetation types. The park landscapes were subdivided into three strata: Matrix (low- to mid-elevation upland habitats), Riparian (within 10 meters of a perennial stream), and High-Elevation (above a predefined elevation, park specific). Across the three strata, we established a total of 241 permanent plots at random locations to measure complete species composition and cover. We describe baseline biophysical conditions and relate them to the data obtained from all 241 plots using ordination analyses. The unconstrained gradient analyses were moderately robust at illustrating the relationships among plots and correlating them to environmental gradients. We also prepared species accumulation curves representing gamma diversity, which showed overall species richness, and also illustrated how well the observed vs. expected richness values of each stratum were captured by the sampling. Most park/strata were well sampled; for others, we found that additional samples would improve how well the protocol captures the vegetation composition within park/strata. Specifically, all sample frames at Whiskeytown and the High-Elevation sample frames at Lassen were not well sampled. Comparisons of alpha diversity values showed High-Elevations had the lowest diversity, while Riparian areas were by far the most diverse across all parks. The Matrix stratum at Oregon Caves National Monument was also especially diverse and had the highest Matrix alpha diversity we observed in all parks We suggest that after three rounds of sampling, the Network perform analyses to identify possible ways to improve statistical power. These options include adding sites or lengthening the sampling interval. Results of these analyses could support protocol modifications. This report on vegetation composition is the first in a series of analysis and synthesis reports. Future analysis and synthesis reports will analyze structure and function.

California, Oregon↗

USGS2018

A comparison of the chemical sensitivities between in vitro and in vivo propagated juvenile freshwater mussels: Implications for standard toxicity testing

Unionid mussels are ecologically important and are globally imperiled. Toxicants contribute to mussel declines, and toxicity tests using juvenile mussels—a sensitive life stage—are valuable in determining thresholds used to set water quality criteria. In vitro culture methods provide an efficient way to propagate juveniles for toxicity testing, but their relative chemical sensitivity compared with in vivo propagated juveniles is unknown. Current testing guidelines caution against using in vitro cultured juveniles until this sensitivity is described. Our objective was to evaluate the relative sensitivity of juvenile mussels produced from both in vitro and in vivo propagation methods to selected chemicals. We conducted 96-h acute toxicity tests according to ASTM International guidelines with 3 mussel species and 6 toxicants: chloride, nickel, ammonia, and 3 copper-based compounds. Statistically significant differences between in vitro and in vivo juvenile 96-h median effect concentrations were observed in 8 of 17 tests, and in vitro juveniles were more sensitive in 6 of the 8 significant differences. At 96 h, 4 of the 8 statistically different tests for a given chemical were within a factor of 2, which is the intralaboratory variation demonstrated in a recent evaluation of mussel toxicity tests. We found that although differences in chemical sensitivity exist between in vitro and in vivo propagated juvenile mussels, they are within normal toxicity test variation. Therefore, in vitro propagated juvenile mussels may be appropriate for use in ASTM International-based toxicity testing.

Environmental Toxicology and Chemistry↗