A Comparison of Bacterial Indicators and Methods in Rural Surface Waters

The United States Environmental Protection Agency (USEPA) recommends the use of Escherichia coli (E. coli) and enterococci as indicators of enteric pathogens in fresh waters; however, fecal coliform analyses will remain important by virtue of the large amount of historic data collected in prior years. In this study, we attempted, in a real-world situation (i.e., a rural inland watershed in the Piedmont of South Carolina) to compare different bacterial indicators and methods to one another. We compared fecal coliforms, enumerated by membrane filtration with E. coli, enumerated by a commercialized enzyme substrate method and observed E. coli/fecal coliform ratios of 1.63 and 1.2 for two separate tests. In the same watershed, we observed an E. coli/fecal coliform ratio of 0.84 when we used the commercialized enzyme substrate method for both enumerations. Given these results, users of such data should exercise care when they make comparisons between historic membrane filtration data and data acquired through the use of the more modern enzymatic methods. Some sampling and side-by-side testing between methods in a specific watershed may be prudent before any conversion factors between old and new datasets are applied.     

Assessment of Climate Change Effects on Canada's National Park System

To estimate the magnitude of climate change anticipated forCanada's 38 National Parks (NPs) and Park Reserves, seasonaltemperature and precipitation scenarios were constructed for 2050and 2090 using the Canadian Centre for Climate Modelling andAnalysis (CCCma) coupled model (CGCM1). For each park, we assessed impacts on physical systems, species, ecosystems andpeople. Important, widespread changes relate to marine andfreshwater hydrology, glacial balance, waning permafrost, increased natural disturbance, shorter ice season, northern andupward altitudinal species and biome shifts, and changed visitation patterns. Other changes are regional (e.g., combinedEast coast subsidence and sea level rise increase coastal erosionand deposition, whereas, on the Pacific coast, tectonic upliftnegates sea level rise). Further predictions concern individualparks (e.g., Unique fens of Bruce Peninsular NP will migratelakewards with lowered water levels, but structural regulation of Lake Huron for navigation and power generation would destroythe fens). Knowledge gaps are the most important findings. Forexample: we could not form conclusions about glacial massbalance, or its effects on rivers and fjords. Likewise, for theEast Coast Labrador Current we could neither estimate temperature and salinity effects of extra iceberg formation, nor the further effects on marine food chains, and breeding park seabirds. We recommend 1) Research on specific large knowledge gaps; 2) Climate change information exchange with protected area agencies in other northern countries; and 3) incorporating climate uncertainty into park plans and management. We discuss options for a new park management philosophy in the face of massive change and uncertainty.     

A Provisional Fish Index of Biotic Integrity for Assessing Ouachita Mountains Streams in Arkansas, U.S.A.

Multimetric indices are often used to monitor aquatic-resource conditions. We used existing fish-collection data from streams to develop an Index of Biotic Integrity (IBI), which is a multimetric index, for the Ouachita Mountains ecoregion in Arkansas, U.S.A. Each fish-collection site was categorized as reference or non-reference. We examined 62 candidate IBI metrics, and selected 12 non-redundant metrics that differentiated best between reference and non-reference sites. The selected metrics were: Percent (of individuals) as Black Bass; Percent as Benthic Feeders; Percent as Centrarchids; Percent as Cyprinids; Percent as Ictalurids; Percent as Mineral, Site-Prep Spawners; Percent as Mineral, Site-Prep, Parental-Care Spawners; Percent as Simple, Mineral Substrate Spawners; Percent as Miscellaneous, Site-Prep, Parental-Care Spawners; Total Number of Centrarchid Species; Total Number of Arkansas Department of Environmental Quality (ADEQ) Ouachita Mountains Indicator Species; and Total Number of ADEQ Ouachita Mountains Key Species. We standardized each metric to score from 0 to 10 by using linear equations and threshold limits. Some selected IBI metrics had their scoring criteria adjusted to account for watershed size (i.e., stream size). We standardized the IBI to score from 0 to 100. In addition, we determined that our Percent as Black Bass and Percent as Benthic Feeders metrics contributed most to IBI scores in reference conditions, but their contributions decreased with decreasing stream conditions. Reproductive metrics contributed most in degraded stream conditions. Furthermore, we identified relations between IBI metrics and water-quality and land-use variables; some relations were counterintuitive. Unexpected relations may be random observations explained by limited ranges of land-use and water-quality variables. When select water-quality and land-use variables were included in a principal component analysis, a composite Land Use Intensity variable explained most of the model variance. Although the IBI has not been independently validated, the PCA, as well as other superficial analyses, indicated that the IBI should be able to differentiate stream conditions.     

Spatial scales and probability based sampling in determining levels of benthic community degradation in the Chesapeake Bay

The extent of degradation of benthic communities of the Chesapeake Bay was determined by applying a previously developed benthic index of biotic integrity at three spatial scales. Allocation of sampling was probability-based allowing areal estimates of degradation with known confidence intervals. The three spatial scales were: (1) the tidal Chesapeake Bay; (2) the Elizabeth River watershed; and (3) two small tidal creeks within the Southern Branch of the Elizabeth River that are part of a sediment contaminant remediation effort. The areas covered varied from 10^–1 to 10⁴ km² and all were sampled in 1999. The Chesapeake Bay was divided into ten strata, the Elizabeth River into five strata and each of the two tidal creeks was a single stratum. The determination of the number and size of strata was based upon consideration of both managerially useful units for restoration and limitations of funding. Within each stratum 25 random locations were sampled for benthic community condition. In 1999 the percent of the benthos with poor benthic community condition for the entire Chesapeake Bay was 47% and varied from 20% at the mouth of the Bay to 72% in the Potomac River. The estimated area of benthos with poor benthic community condition for the Elizabeth River was 64% and varied from 52–92%. Both small tidal creeks had estimates of 76% of poor benthic community condition. These kinds of estimates allow environmental managers to better direct restoration efforts and evaluate progress towards restoration. Patterns of benthic community condition at smaller spatial scales may not be correctly inferred from larger spatial scales. Comparisons of patterns in benthic community condition across spatial scales, and between combinations of strata, must be cautiously interpreted.     

A Parallel Computation Tool to Enable Dynamic Sensitivity and Model Performance Analysis of APEX: Evapotranspiration Modeling

Global sensitivity analysis can be used for assessing the relative importance of model parameters on model outputs. The sensitivity of parameters usually indicates a temporal variation due to variation in the environmental conditions (e.g., variation in weather or plant growth). In addition, the size of averaging window by which the outputs of a model are aggregated or averaged may impact parameter sensitivities. In this study, temporal variation of parameters sensitives, model performance, as well as the impact of the size of time‐averaging window on evapotranspiration (ET) prediction using the Agricultural Policy/Environmental eXtender (APEX) model are investigated. To achieve these goals, an open‐source package named PARAPEX was developed in R and used to perform dynamic sensitivity and model performance analysis of APEX using parallel computation. PARAPEX reduced the computation time from 5,939 to 379 s (using 20 and 1 computation nodes, respectively). The sensitivity analysis results indicated the parameters accounting for the reducing effect of plant cover on evaporation from the soil surface, the effect of soil on the plant root growth, and the effect of cycling and transformation dynamics of organic matter at the top soil layer as the top sensitive parameters based on the mean daily simulated ET and the Nash–Sutcliffe model performance measure. The dynamic performance analysis indicated poor ET predictions by APEX during the growing seasons. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Analysis of naturalistic driving videos of fleet services drivers to estimate driver error and potentially distracting behaviors as risk factors for rear-end versus angle crashes

Objective: The objective of this study was to estimate the prevalence and odds of fleet driver errors and potentially distracting behaviors just prior to rear-end versus angle crashes.

Methods: Analysis of naturalistic driving videos among fleet services drivers for errors and potentially distracting behaviors occurring in the 6 s before crash impact. Categorical variables were examined using the Pearson's chi-square test, and continuous variables, such as eyes-off-road time, were compared using the Student's t-test. Multivariable logistic regression was used to estimate the odds of a driver error or potentially distracting behavior being present in the seconds before rear-end versus angle crashes.

Results: Of the 229 crashes analyzed, 101 (44%) were rear-end and 128 (56%) were angle crashes. Driver age, gender, and presence of passengers did not differ significantly by crash type. Over 95% of rear-end crashes involved inadequate surveillance compared to only 52% of angle crashes (P < .0001). Almost 65% of rear-end crashes involved a potentially distracting driver behavior, whereas less than 40% of angle crashes involved these behaviors (P < .01). On average, drivers spent 4.4 s with their eyes off the road while operating or manipulating their cell phone. Drivers in rear-end crashes were at 3.06 (95% confidence interval [CI], 1.73–5.44) times adjusted higher odds of being potentially distracted than those in angle crashes.

Conclusions: Fleet driver driving errors and potentially distracting behaviors are frequent. This analysis provides data to inform safe driving interventions for fleet services drivers. Further research is needed in effective interventions to reduce the likelihood of drivers' distracting behaviors and errors that may potentially reducing crashes.     

Designing regional-level stakeholder engagement processes: striving for good governance while meeting the challenges of scale

Stakeholder engagement processes have sought to ensure that state government meets public trust and good governance obligations to citizens. As the expectations of stakeholders and state agencies change, and management focuses on landscape-level interventions, a change in the level at which agencies engage the public is needed. This involves tradeoffs, as different levels call for different engagement design and implementation considerations. To understand how these differences affect decision making, we examine a regional engagement model for deer management in New York that was piloted to replace a sub-regional model. We identify concerns with the old model, objectives for the redesigned model, and explain the logistical and good governance considerations that informed its design. We share our evaluation of the model's process and outcomes, including implications for program design and scale. Overall, despite the pilot model's attention to design components aimed at addressing potential barriers to regional engagement as well as limitations of the previous engagement model, the pilot did not meet many of its objectives, especially those related to representation, resulting in some of the same concerns associated with the model it was intended to enhance and replace. Implications of this for regional-level engagement efforts are discussed.     

Iowa Statewide Stream Nitrate Load Calculated Using In Situ Sensor Network

Various techniques exist to estimate stream nitrate loads when measured concentration data are sparse. The inherent uncertainty associated with load estimation, however, makes tracking progress toward water quality goals more difficult. We used high‐frequency, in situ nitrate sensors strategically deployed across the agricultural state of Iowa to evaluate 2016 stream concentrations at 60 sites and loads at 35 sites. The generated data, collected at an average of 225 days per site, show daily average nitrate‐N yields ranging from 12 to 198 g/ha, with annual yields as high as 53 kg/ha from the intensely drained Des Moines Lobe. Thirteen of the sites that capture water from 82.5% of Iowa's area show statewide nitrate‐N loading in 2016 totaled 477 million kg, or 41% of the load delivered to the Mississippi–Atchafalaya River Basin (MARB). Considering the substantial private and public investment being made to reduce nitrate loading in many states within the MARB, networks of continuous, in situ measurement devices as described here can inform efforts to track year‐to‐year changes in nitrate load related to weather and conservation implementation. Nitrate and other data from the sensor network described in this study are made publicly available in real time through the Iowa Water Quality Information System.     

Cyberinfrastructure and Web Apps for Managing and Disseminating the National Water Model

Hydrologic modeling can be used to provide warnings before, and to support operations during and after floods. Recent technological advances have increased our ability to create hydrologic models over large areas. In the United States (U.S.), a new National Water Model (NWM) that generates hydrologic variables at a national scale was released in August 2016. This model represents a substantial step forward in our ability to predict hydrologic events in a consistent fashion across the entire U.S. Nevertheless, for these hydrologic results to be effectively communicated, they need to be put in context and be presented in a way that is straightforward and facilitates management‐related decisions. The large amounts of data produced by the NWM present one of the major challenges to fulfill this goal. We created a cyberinfrastructure to store NWM results, “accessibility” web applications to retrieve NWM results, and a REST API to access NWM results programmatically. To demonstrate the utility of this cyberinfrastructure, we created additional web apps that illustrate how to use our REST API and communicate hydrologic forecasts with the aid of dynamic flood maps. This work offers a starting point for the development of a more comprehensive toolset to validate the NWM while also improving the ability to access and visualize NWM forecasts, and develop additional national‐scale‐derived products such as flood maps.     

Rheological and Mechanical Properties of Poly(lactic acid)/Bio-Based Polyethylene/Clay Biocomposites Containing Montmorillonite and Vermiculite Clays

Journal of Polymers and the Environment - This work aims to investigate the effect of organically modified montmorillonite (OMMT) and vermiculite (OVT) clays on the properties of poly(lactic acid)...