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)...     

Contributions of paraecologists and parataxonomists to research,conservation, and social development

Citizen science has been gaining momentum in the United States and Europe, where citizens are literate and often interested in science. However, in developing countries, which have a dire need for environmental data, such programs are slow to emerge, despite the large and untapped human resources in close proximity to areas of high biodiversity and poorly known floras and faunas. Thus, we propose that the parataxonomist and paraecologist approach, which originates from citizen‐based science, is well suited to rural areas in developing countries. Being a paraecologist or a parataxonomist is a vocation and entails full‐time employment underpinned by extensive training, whereas citizen science involves the temporary engagement of volunteers. Both approaches have their merits depending on the context and objectives of the research. We examined 4 ongoing paraecologist or parataxonomist programs in Costa Rica, India, Papua New Guinea, and southern Africa and compared their origins, long‐term objectives, implementation strategies, activities, key challenges, achievements, and implications for resident communities. The programs supported ongoing research on biodiversity assessment, monitoring, and management, and participants engaged in non‐academic capacity development in these fields. The programs in Southern Africa related to specific projects, whereas the programs in Costa Rica, India, and Papua New Guinea were designed for the long term, provided sufficient funding was available. The main focus of the paraecologists’ and parataxonomists’ activities ranged from collection and processing of specimens (Costa Rica and Papua New Guinea) or of socioeconomic and natural science data (India and Southern Africa) to communication between scientists and residents (India and Southern Africa). As members of both the local land user and research communities, paraecologists and parataxonomists can greatly improve the flow of biodiversity information to all users, from local stakeholders to international academia.     

Performance Assessment of a 3D Hydrodynamic Model Using High Temporal Resolution Measurements in a Shallow Urban Lake

Urban lakes provide many ecosystem services, e.g., flood control, nature protection, coolness island, recreation. Hydrodynamic models will increasingly be used to enhance these benefits. We present the first validation of a three-dimensional (3D) hydrodynamic model on a small shallow lake with high resolution and high frequency measurements. Lake Créteil, France (area 0.4 km², mean depth 4.5 m, and catchment area 1 km²) is a former gravel pit and now part of a regional park. The model Delft3D-FLOW was calibrated on a one-month period, with continuous measurements of temperature at five depths at the center of the lake and at three depths at two other stations, and with current speed profiles at the centre of the lake. The model was then verified on 18 1-month periods with similar temperature measurements. The model reproduced very well the temperature dynamics, including the alternation between mixing and stratification periods and internal wave patterns. The mean absolute errors over the five depths at the central point remained below 0.55^°C in spring and summer, the most favorable seasons for phytoplankton growth. Horizontal temperature differences, which rose up to 3^°C at the beginning of stratification periods, were also well reproduced, as well as current speeds. These results are very promising for assessing nutrient and pollutant diffusion, settling and resuspension, as well as for understanding how phytoplankton blooms start in small shallow lakes.