A moving target—incorporating knowledge of the spatial ecology of fish into the assessment and management of freshwater fish populations

Freshwater fish move vertically and horizontally through the aquatic landscape for a variety of reasons, such as to find and exploit patchy resources or to locate essential habitats (e.g., for spawning). Inherent challenges exist with the assessment of fish populations because they are moving targets. We submit that quantifying and describing the spatial ecology of fish and their habitat is an important component of freshwater fishery assessment and management. With a growing number of tools available for studying the spatial ecology of fishes (e.g., telemetry, population genetics, hydroacoustics, otolith microchemistry, stable isotope analysis), new knowledge can now be generated and incorporated into biological assessment and fishery management. For example, knowing when, where, and how to deploy assessment gears is essential to inform, refine, or calibrate assessment protocols. Such information is also useful for quantifying or avoiding bycatch of imperiled species. Knowledge of habitat connectivity and usage can identify critically important migration corridors and habitats and can be used to improve our understanding of variables that influence spatial structuring of fish populations. Similarly, demographic processes are partly driven by the behavior of fish and mediated by environmental drivers. Information on these processes is critical to the development and application of realistic population dynamics models. Collectively, biological assessment, when informed by knowledge of spatial ecology, can provide managers with the ability to understand how and when fish and their habitats may be exposed to different threats. Naturally, this knowledge helps to better evaluate or develop strategies to protect the long-term viability of fishery production. Failure to understand the spatial ecology of fishes and to incorporate spatiotemporal data can bias population assessments and forecasts and potentially lead to ineffective or counterproductive management actions.     

Toxicodynamic modeling of 137Cs to estimate white-tailed deer background levels for the Department of Energy's Savannah River Site

The U.S. Department of Energy's (USDOE) Savannah River Site (SRS) is a former nuclear weapon material production and current research facility adjacent to the Savannah River in South Carolina, USA. The purpose of this study was to determine the background radiocesium (¹³⁷Cs) body burden (e.g., from global fallout) for white-tailed deer (Odocoileus virginianus) inhabiting the SRS. To differentiate what the background burden is for the SRS versus ¹³⁷Cs obtained from SRS nuclear activities, data were analyzed spatially, temporally and compared to other off-site hunting areas near the SRS. The specific objectives of this study were: to compare SRS and offsite deer herds based on time and space; to interpret comparisons based on how data were collected as well as the effect of environmental and anthropogenic influences; to determine what the ecological half-life/decay rate is for ¹³⁷Cs in the SRS deer herd; and to give a recommendation to what should be considered the background ¹³⁷Cs level in the SRS deer herd. Based on the available information and analyses, it is recommended that the determination of what is considered background for the SRS deer herd be derived from data collected from the SRS deer herd itself and not offsite collections for a variety of reasons. Offsite data show extreme variability most likely due to environmental factors such as soil type and land-use patterns (e.g., forest, agriculture, residential activities). This can be seen from results where samples from offsite military bases (Fort Jackson and Fort Stewart) without anthropogenic ¹³⁷Cs sources were much higher than both the SRS and a nearby (Sandhills) study site. Moreover, deer from private hunting grounds have the potential to be baited with corn, thus artificially lowering their ¹³⁷Cs body burdens compared to other free-ranging deer. Additionally, sample size for offsite collections were not robust enough to calculate a temporal decay curve with an upper confidence level to determine if the herds are following predicted radioactive decay rates like the SRS or if the variability is due to those points described above. Using mean yearly values, the ecological half-life for ¹³⁷Cs body burdens for SRS white-tailed deer was determined to be 28.79 years—very close to the 30.2 years physical half-life.     

Silver near municipal wastewater discharges into western Lake Ontario,Canada

Because of the widespread use of silver nanoparticles in commercial products, discharges of municipal wastewater may be a point source of silver in the aquatic environment. We monitored two sites in western Lake Ontario impacted by discharges from wastewater treatment plants serving the City of Toronto. Concentrations of silver were elevated in bottom sediments and suspended sediments collected at the two sites. We also deployed two types of passive samplers in the water column at the two sites, the newly developed Carbon Nanotube Integrative Samplers for monitoring “CNIS-labile” silver and Diffusive Gradient in Thin Film samplers for monitoring “DGT-labile” silver. Results from these passive samplers indicated that the concentrations of silver at the two sites were either below detection limits or were in the ng/L range. In laboratory experiments where the sediments were re-suspended in Milli-Q water, a small proportion of the silver (i.e., <?25%) was labile and partitioned as colloidal or dissolved silver into the liquid phase after agitation. Nanoparticles tentatively identified as silver nanoparticles were detected by single-particle ICP-MS in suspension after agitation of both suspended and bottom sediments. Therefore, there is a need to assess whether silver species, including silver nanoparticles are transported from wastewater treatment plants into sediments in the aquatic environment. This study is unique in focusing on the in situ distribution of silver in natural waters and in sediments that are potentially impacted by urban sources of nanoparticles.     

Dividing and Uniting Through Naming: The Case of North Carolina's Sea-Level-Rise Policy

Opponents of a proposed sea-level-rise policy in North Carolina, USA, reasoned rhetorically to promote a narrative claiming that the policy supporters’ efforts had failed to meet the criteria of “good” science and the American dream expectancy of “progress.” The critics worked to hinder policy adoption by naming as “villains” scientists who provided research to support the proposed policy. In addition, the opponents named their own efforts to prevent policy based on “bad” science that would “destroy” the American dream as “heroic.” To more effectively respond to such narratives, scientists and policy proponents need to shift away from reporting just climate change “facts” in the attempt to gain stakeholder support for mitigation and adaptation initiatives. They need to move toward reasoning rhetorically to construct narratives that encourage the public to name them as the “heroes” who will achieve the American dream by their actions to mitigate climate-change outcomes.     

Analysis of short-term ozone and PM2.5 measurements: Characteristics and relationships for air sensor messaging

Air quality sensors are becoming increasingly available to the general public, providing individuals and communities with information on fine-scale, local air quality in increments as short as 1 min. Current health studies do not support linking 1-min exposures to adverse health effects; therefore, the potential health implications of such ambient exposures are unclear. The U.S. Environmental Protection Agency (EPA) establishes the National Ambient Air Quality Standards (NAAQS) and Air Quality Index (AQI) on the best science available, which typically uses longer averaging periods (e.g., 8 hr; 24 hr). Another consideration for interpreting sensor data is the variable relationship between pollutant concentrations measured by sensors, which are short-term (1 min to 1 hr), and the longer term averages used in the NAAQS and AQI. In addition, sensors often do not meet federal performance or quality assurance requirements, which introduces uncertainty in the accuracy and interpretation of these readings. This article describes a statistical analysis of data from regulatory monitors and new real-time technology from Village Green benches to inform the interpretation and communication of short-term air sensor data. We investigate the characteristics of this novel data set and the temporal relationships of short-term concentrations to 8-hr average (ozone) and 24-hr average (PM_2.5) concentrations to examine how sensor readings may relate to the NAAQS and AQI categories, and ultimately to inform breakpoints for sensor messages. We consider the empirical distributions of the maximum 8-hr averages (ozone) and 24-hr averages (PM_2.5) given the corresponding short-term concentrations, and provide a probabilistic assessment. The result is a robust, empirical comparison that includes events of interest for air quality exceedances and public health communication. Concentration breakpoints are developed for short-term sensor readings such that, to the extent possible, the related air quality messages that are conveyed to the public are consistent with messages related to the NAAQS and AQI.

Implications: Real-time sensors have the potential to provide important information about fine-scale current air quality and local air quality events. The statistical analysis of short-term regulatory and sensor data, coupled with policy considerations and known health effects experienced over longer averaging times, supports interpretation of such short-term data and efforts to communicate local air quality.     

The forgotten pillar: a definition for the measurement of social sustainability in American cities

This article provides a timely review of the interdisciplinary and disjointed literature on social sustainability and identifies some readily available measures of this concept for American cities. Based upon a comprehensive review of the literature, four broad dimensions are identified as being reflective of social sustainability: equal access and opportunity, environmental justice, community and the value of place, and basic human needs. Breaking these four dimensions into measurable indicators, this research provides a method for researchers and for American cities to begin to evaluate and to assess social sustainability efforts within their jurisdictions.     

Probability analyses of combining background concentrations with model-predicted concentrations

In order to calculate total concentrations for comparison to ambient air quality standards, monitored background concentrations are often combined with model predicted concentrations. Models have low skill in predicting the locations or time series of observed concentrations. Further, adding fixed points on the probability distributions of monitored and predicted concentrations is very conservative and not mathematically correct. Simply adding the 99th percentile predicted to the 99th percentile background will not yield the 99th percentile of the combined distributions. Instead, an appropriate distribution can be created by calculating all possible pairwise combinations of the 1-hr daily maximum observed background and daily maximum predicted concentration, from which a 99th percentile total value can be obtained. This paper reviews some techniques commonly used for determining background concentrations and combining modeled and background concentrations. The paper proposes an approach to determine the joint probabilities of occurrence of modeled and background concentrations. The pairwise combinations approach yields a more realistic prediction of total concentrations than the U.S. Environmental Protection Agency's (EPA) guidance approach and agrees with the probabilistic form of the National Ambient Air Quality Standards.

Implications: EPA's current approaches to determining background concentrations for compliance modeling purposes often lead to “double counting” of background concentrations and actual plume impacts and thus lead to overpredictions of total impacts. Further, the current Tier 1 approach of simply adding the top ends of the background and model predicted concentrations (e.g., adding the 99th percentiles of these distributions together) results in design value concentrations at probabilities in excess of the form of the National Ambient Air Quality Standards.     

Comparative statistical study of hourly precipitation determined by radar-based Stage IV and ground-based methods in the North Central United States

Detailed hourly precipitation data are required for long-range modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants using the CALPUFF model. In sparsely populated areas such as the north central United States, ground-based precipitation measurement stations may be too widely spaced to offer a complete and accurate spatial representation of hourly precipitation within a modeling domain. The availability of remotely sensed precipitation data by satellite and the National Weather Service array of next-generation radars (NEXRAD) deployed nationally provide an opportunity to improve on the paucity of data for these areas. Before adopting a new method of precipitation estimation in a modeling protocol, it should be compared with the ground-based precipitation measurements, which are currently relied upon for modeling purposes. This paper presents a statistical comparison between hourly precipitation measurements for the years 2006 through 2008 at 25 ground-based stations in the north central United States and radar-based precipitation measurements available from the National Center for Environmental Predictions (NCEP) as Stage IV data at the nearest grid cell to each selected precipitation station. It was found that the statistical agreement between the two methods depends strongly on whether the ground-based hourly precipitation is measured to within 0.1 in/hr or to within 0.01 in/hr. The results of the statistical comparison indicate that it would be more accurate to use gridded Stage IV precipitation data in a gridded dispersion model for a long-range simulation, than to rely on precipitation data interpolated between widely scattered rain gauges.

Implications:

The current reliance on ground-based rain gauges for precipitation events and hourly data for modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants results in potentially large discontinuity in data coverage and the need to extrapolate data between monitoring stations. The use of radar-based precipitation data, which is available for the entire continental United States and nearby areas, would resolve these data gaps and provide a complete and accurate spatial representation of hourly precipitation within a large modeling domain.     

Future year ozone source attribution modeling study using CMAQ-ISAM

ABSTRACT

To achieve the current United States National Ambient Air Quality Standards (NAAQS) attainment level for ozone or particulate matter, current photochemical air quality models include tools to determine source apportionment and/or source sensitivity. Previous studies by the authors have used the Ozone and Particulate Matter Source Apportionment Technology and Higher-order Decoupled Direct Method probing tools in CAMx to investigate these source-receptor relationships for ozone. The recently available source apportionment for CMAQ, referred to as the Integrated Source Apportionment Method (ISAM), was used in this study to conduct future year (2030) source attribution modeling. The CMAQ-ISAM ozone source attribution results for selected cities across the U.S. showed boundary conditions were the dominant contributor to the future year highest July maximum daily 8-hour average (MDA8) ozone concentrations. Point sources were generally larger contributors in the eastern U.S. than in the western U.S. The contributions of on-road mobile emissions were around 5 ppb at most of the cities selected for analysis. Off-road mobile source contributions were around 20 ppb or nearly 30%. Since boundary conditions play an important role in future year ozone levels, it is important to characterize future year boundary conditions accurately. The current implementation of ISAM in CMAQ 5.0.2 requires significant computing resources for ozone source attribution, making it difficult to conduct long-term simulations for large domains. The computing requirements for PM source attribution are even more onerous. CMAQ 5.2 was released after this study was completed, and does not include ISAM. If an efficient version of ISAM becomes available, it could be used in long-term ozone and PM2.5 studies. Implications: Ozone source attribution results provide useful information on important emission source contribution categories and provide some initial guidance on future emission reduction strategies. This study explains a new source apportionment technique, CMAQ-ISAM, and compares it to CAMx OSAT. The techniques have similar results: ozone’s highest source contributor is boundary conditions, followed by point sources, then off-road mobile sources. The current version of ISAM in CMAQ 5.0.2 requires significant computing resources for ozone source attribution, while the computing requirements for PM source attribution are even more onerous. CMAQ 5.2 was released after this study was completed, and does not include ISAM.     

Nutrient leaching in a Colombian savanna Oxisol amended with biochar

Nutrient leaching in highly weathered tropical soils often poses a challenge for crop production. We investigated the effects of applying 20 t ha biochar (BC) to a Colombian savanna Oxisol on soil hydrology and nutrient leaching in field experiments. Measurements were made over the third and fourth years after a single BC application. Nutrient contents in the soil solution were measured under one maize and one soybean crop each year that were routinely fertilized with mineral fertilizers. Leaching by unsaturated water flux was calculated using soil solution sampled with suction cup lysimeters and water flux estimates generated by the model HYDRUS 1-D. No significant difference ( > 0.05) was observed in surface-saturated hydraulic conductivity or soil water retention curves, resulting in no relevant changes in water percolation after BC additions in the studied soils. However, due to differences in soil solution concentrations, leaching of inorganic N, Ca, Mg, and K measured up to a depth of 0.6 m increased ( < 0.05), whereas P leaching decreased, and leaching of all nutrients (except P) at a depth of 1.2 m was significantly reduced with BC application. Changes in leaching at 2.0 m depth with BC additions were about one order of magnitude lower than at other depths, except for P. Biochar applications increased soil solution concentrations and downward movement of nutrients in the root zone and decreased leaching of Ca, Mg, and Sr at 1.2 m, possibly by a combination of retention and crop nutrient uptake.