Ecosystem monitoring at global baseline sites

Integrated ecosystem and pollutant monitoring is being conducted at prototype global baseline sites in remote areas of the Noatak National Preserve, Alaska, the Wind River Mountains, Wyoming, and Torres del Paine National Park, Chile. A systems approach has been used in the design of these projects. This approach includes: (1) evaluation of source-receptor relationships, (2) multimedia (i.e., air, water, soil, biota) monitoring of key contaminant pathways within the environment, (3) the use of selected ecosystem parameters to detect anthropogenic influence, and (4) the application of a systems conceptual framework as a heuristic tool.Initial short-term studies of air quality (e.g. SO₂, NO₂) plus trace metal concentrations in mosses generally indicate pristine conditions at all three of the above sites as expected although trace metals in mosses were higher at the Wyoming site. Selected ecosystem parameters for both terrestrial (e.g. litter decomposition) and aquatic (e.g. shredders, a macroinvertebrate functional feeding group) habitats at the Wyoming site reflected baseline conditions when compared to other studies.Plans also are being made to use U.S. Department of Energy Research Parks for global change monitoring. This will involve cross-site analyses of existing ecological databases and the design of a future monitoring network based on a systems approach as outlined in this paper.     

Precision And Accuracy Of Pest And Pathogen Damage Assessment In Young Eucalypt Plantations

Fungal pathogens, browsing mammals, birds, insects, nutrient deficiencies, drought, frost and waterlogging are all damaging agents to plantation species. The subsequent loss in leaf tissue or reduced photosynthetic potential can reduce growth and potentially lead to tree death. The Crown Damage Index (CDI) was developed in Australia to quantify damage in young eucalypt plantations. The accuracy and precision of assessing damage at a tree level were determined to ensure the reliability, objectivity and repeatability of the CDI method. Nine assessors, with varying levels of experience, estimated damage on three plots of fifty trees each, to obtain an understanding of the subjectivity of assessing damage caused by insects (e.g. Chrysophtharta spp.) and fungal pathogens (e.g. Mycosphaerella spp.) on Eucalyptus globulus. Damage levels were measured by destructive sampling to enable direct comparisons between estimates and damage levels to be made. The most experienced assessors provided the most repeatable estimates and were generally the most accurate. The incidence of foliar necrosis was the least subjective measure while defoliation was the most subjective and the least accurate of the indices measured. All assessors, regardless of experience, were able to predict the Crown Damage Index (a combined index of all damage classes) to within 12% of measured damage levels.     

An Overview of Data Integration Methods for Regional Assessment

The U.S. Environmental Protections Agency's (U.S. EPA) Regional Vulnerability Assessment(ReVA) program has focused much of its research over the last five years on developing and evaluating integration methods for spatial data. An initial strategic priority was to use existing data from monitoring programs, model results, and other spatial data. Because most of these data were not collected with an intention of integrating into a regional assessment of conditions and vulnerabilities, issues exist that may preclude the use of some methods or require some sort of data preparation. Additionally, to support multi-criteria decision-making, methods need to be able to address a series of assessment questions that provide insights into where environmental risks are a priority. This paper provides an overview of twelve spatial integration methods that can be applied towards regional assessment, along with preliminary results as to how sensitive each method is to data issues that will likely be encountered with the use of existing data.     

A Preliminary Assessment of the Montréal Process Indicators of Air Pollution for the United States

Air pollutants pose a risk to forest health and vitality in the United States. Here we present the major findings from a national scale air pollution assessment that is part of the United States' 2003 Report on Sustainable Forests. We examine trends and the percent forest subjected to specific levels of ozone and wet deposition of sulfate, nitrate, and ammonium. Results are reported by Resource Planning Act (RPA) reporting region and integrated by forest type using multivariate clustering. Estimates of sulfate deposition for forested areas had decreasing trends (1994-2000) across RPA regions that were statistically significant for North and South RPA regions. Nitrate deposition rates were relatively constant for the 1994 to 2000 period, but the South RPA region had a statistically decreasing trend. The North and South RPA regions experienced the highest ammonium deposition rates and showed slightly decreasing trends. Ozone concentrations were highest in portions of the Pacific Coast RPA region and relatively high across much of the South RPA region. Both the South and Rocky Mountain RPA regions had an increasing trend in ozone exposure. Ozone-induced foliar injury to sensitive species was recorded in all regions except for the Rocky Mountain region. The multivariate analysis showed that the oak-hickory and loblolly-shortleaf pine forest types were generally exposed to more air pollution than other forest types, and the redwood, western white pine, and larch forest types were generally exposed to less. These findings offer a new approach to national air pollution assessments and are intended to help focus research and planning initiatives related to air pollution and forest health.     

Transition Pathways to Sustainable Agricultural Water Management: A Review of Integrated Modeling Approaches

Agricultural water management (AWM) is an interdisciplinary concern, cutting across traditional domains such as agronomy, climatology, geology, economics, and sociology. Each of these disciplines has developed numerous process‐based and empirical models for AWM. However, models that simulate all major hydrologic, water quality, and crop growth processes in agricultural systems are still lacking. As computers become more powerful, more researchers are choosing to integrate existing models to account for these major processes rather than building new cross‐disciplinary models. Model integration carries the hope that, as in a real system, the sum of the model will be greater than the parts. However, models based upon simplified and unrealistic assumptions of physical or empirical processes can generate misleading results which are not useful for informing policy. In this article, we use literature and case studies from the High Plains Aquifer and Southeastern United States regions to elucidate the challenges and opportunities associated with integrated modeling for AWM and recommend conditions in which to use integrated models. Additionally, we examine the potential contributions of integrated modeling to AWM — the actual practice of conserving water while maximizing productivity. 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.     

Spatial Convergence in Major Dissolved Ion Concentrations and Implications of Headwater Mining for Downstream Water Quality

Spatial patterns in major dissolved solute concentrations were examined to better understand impact of surface coal mining in headwaters on downstream water chemistry. Sixty sites were sampled seasonally from 2012 to 2014 in an eastern Kentucky watershed. Watershed areas (WA) ranged from 1.6 to 400.5 km² and were mostly forested (58%–95%), but some drained as much as 31% surface mining. Measures of total dissolved solutes and most component ions were positively correlated with mining. Analytes showed strong convergent spatial patterns with high variability in headwaters (<15 km² WA) that stabilized downstream (WA > 75 km²), indicating hydrologic mixing primarily controls downstream values. Mean headwater solute concentrations were a good predictor of downstream values, with % differences ranging from 0.55% (Na⁺) to 28.78% (Mg²⁺). In a mined scenario where all headwaters had impacts, downstream solute concentrations roughly doubled. Alternatively, if mining impacts to headwaters were minimized, downstream solute concentrations better approximated the 300 μS/cm conductivity criterion deemed protective of aquatic life. Temporal variability also had convergent spatial patterns and mined streams were less variable due to unnaturally stable hydrology. The highly conserved nature of dissolved solutes from mining activities and lack of viable treatment options suggest forested, unmined watersheds would provide dilution that would be protective of downstream aquatic life.     

DNA fingerprints of orange roughy,Hoplostethus atlanticus: a population comparison

Genetic variability among Hoplostethus atlanticus collected from two spawning grounds east and west of New Zealand was examined using DNA fingerprints as revealed by hybridization with three clonal probes: 33.15, M13 and 3HVR. The 33.15 and 3HVR fingerprints revealed a complex pattern of restriction fragments, apparently refecting a multi-locus system of highly variable minisatellite alleles similar to the pattern of alleles reported in other vertebrates. The M13 fingerprints revealed a distinct pattern of restriction fragments of high molecular weight, reflecting a single-locus system that overlapped with the family of minisatellite alleles observed in 33.15 fingerprints. In a sample of 12 orange roughy collected on a single regional spawning site, the average percent similarity of 33.15 fingerprints was 21.15% (SD=17.75), the average percent similarity of 3HVR fingerprints was 14.32% (SD=14.45) and the inferred average allelic frequency of the M13 single-locus system was 0.071. A comparison of 33.15 and M13 fingerprints from two distant spawning sites ground New Zealand revealed no obvious regional differences. The variability of orange roughy fingerprints was so great, however, that regional comparisons could not be considered conclusive indicators of genetic identity. Our results provide a preliminary assessment of the power and pitfalls of using DNA-level markers for the population analysis of marine fish.     

Towards Real‐Time Continental Scale Streamflow Simulation in Continuous and Discrete Space

The National Weather Service (NWS) forecasts floods at approximately 3,600 locations across the United States (U.S.). However, the river network, as defined by the 1:100,000 scale National Hydrography Dataset‐Plus (NHDPlus) dataset, consists of 2.7 million river segments. Through the National Flood Interoperability Experiment, a continental scale streamflow simulation and forecast system was implemented and continuously operated through the summer of 2015. This system leveraged the WRF‐Hydro framework, initialized on a 3‐km grid, the Routing Application for the Parallel Computation of Discharge river routing model, operating on the NHDPlus, and real‐time atmospheric forcing to continuously forecast streamflow. Although this system produced forecasts, this paper presents a study of the three‐month nowcast to demonstrate the capacity to seamlessly predict reach scale streamflow at the continental scale. In addition, this paper evaluates the impact of reservoirs, through a case study in Texas. Validation of the uncalibrated model using observed hourly streamflow at 5,701 U.S. Geological Survey gages shows 26% demonstrate PBias ≤ |25%|, 11% demonstrate Nash‐Sutcliffe Efficiency (NSE) ≥ 0.25, and 6% demonstrate both PBias ≤ |25%| and NSE ≥ 0.25. When evaluating the impact of reservoirs, the analysis shows when reservoirs are included, NSE ≥ 0.25 for 56% of the gages downstream while NSE ≥ 0.25 for 11% when they are not. The results presented here provide a benchmark for the evolving hydrology program within the NWS and supports their efforts to develop a reach scale flood forecasting system for the country.     

Assessment of the Extreme Rainfall Event at Nashville,TN and the Surrounding Region on May 1–3, 2010

This paper analyzes the May 1–3, 2010 rainfall event that affected the south‐central United States, including parts of Mississippi, Tennessee, and Kentucky. The storm is evaluated in terms of its synoptic setting, along with the temporal distributions, and spatial patterns of the rainfall. In addition, the recurrence interval of the storm is assessed and the implications for hydrologic structure designs are discussed. The event was associated with an upper‐level trough and stationary frontal boundary to the west of the rainfall region, which remained quasi‐stationary for a period of 48 h. Heavy rainfall was produced by two slow‐moving mesoscale convective complexes, combined with abundant atmospheric moisture. Storm totals exceeding 330 mm occurred within a large elongated area extending from Memphis to Nashville. Isolated rainfall totals over 480 mm were reported in some areas, with NEXRAD weather radar rainfall estimates up to 501 mm. An extreme value analysis was performed for one‐ and two‐day rainfall totals at Nashville and Brownsville, Tennessee, as well as for gridded rainfall estimates for the entire region using the Storm Precipitation Analysis System. Results suggest maximum rainfall totals for some durations during the May 1–3, 2010 event exceeded the 1,000‐year rainfall values from National Oceanic and Atmospheric Administration Atlas 14 for a large portion of the region and reached up to 80% of the probable maximum precipitation values for some area sizes and durations.     

Development of community of practice to support quantitative risk assessment for synthetic biology products: contaminant bioremediation and invasive carp control as cases

Synthetic biology has the potential for a broad array of applications. However, realization of this potential is challenged by the paucity of relevant data for conventional risk assessment protocols, a limitation due to to the relative nascence of the field, as well as the poorly characterized and prioritized hazard, exposure, and dose–response considerations associated with the development and use of synthetic biology-derived organisms. Where quantitative risk assessment approaches are necessarily to fulfill regulatory requirements for review of products containing genetically modified organisms, this paper reviews one potential avenue for early-stage quantitative risk assessment for biosafety considerations of synthetic biology organism deployment into the environment. Building from discussion from a March 2018 US Army Engineer Research and Development Center workshop on developing such quantitative risk assessment for synthetic biology, this paper reviews the findings and discussion of workshop participants. This paper concludes that, while synthetic biology risk assessment and governance will continue to refine and develop in the coming years, a quantitative framework that builds from existing practice is one potentially beneficial option for risk assessors that must contend with the technology’s limited hazard characterization or exposure assessment considerations in the near term.