Influence of Riparian Seepage Zones on Nitrate Variability in Two Agricultural Headwater Streams

Riparian seeps have been recognized for their contributions to stream flow in headwater catchments, but there is limited data on how seeps affect stream water quality. The objective of this study was to examine the effect of seeps on the variability of stream NO₃‐N concentrations in FD36 and RS, two agricultural catchments in Pennsylvania. Stream samples were collected at 10‐m intervals over reaches of 550 (FD36) and 490 m (RS) on 21 occasions between April 2009 and January 2012. Semi‐variogram analysis was used to quantify longitudinal patterns in stream NO₃‐N concentration. Seep water was collected at 14 sites in FD36 and 7 in RS, but the number of flowing seeps depended on antecedent conditions. Seep NO₃‐N concentrations were variable (0.1‐29.5 mg/l) and were often greater downslope of cropped fields compared to other land uses. During base flow, longitudinal variability in stream NO₃‐N concentrations increased as the number of flowing seeps increased. The influence of seeps on the variability of stream NO₃‐N concentrations was less during storm flow compared to the variability of base flow NO₃‐N concentrations. However, 24 h after a storm in FD36, an increase in the number of flowing seeps and decreasing streamflow resulted in the greatest longitudinal variability in stream NO₃‐N concentrations recorded. Results indicate seeps are important areas of NO₃‐N delivery to streams where targeted adoption of mitigation measures may substantially improve stream water quality.     

Resolution and Analysis of Spatial Variations and Patterns in an Urban Lake with Rapid Profiling Instrumentation

Rapid response vertical profiling instrumentation was used to document spatial variability and patterns in a small urban lake, Onondaga Lake, associated with multiple drivers. Paired profiles of temperature, specific conductance (SC), turbidity (T_n), fluorometric chlorophyll a (Chl_f), and nitrate nitrogen (NO₃^?) were collected at >30 fixed locations (a “gridding”) weekly, over the spring to fall interval of several years. These gridding data are analyzed (1) to characterize phytoplankton (Chl_f) patchiness in the lake's upper waters, (2) to establish the representativeness of a single long‐term site for monitoring lake‐wide conditions, and (3) to resolve spatial patterns of multiple tracers imparted by buoyancy effects of inflows. Multiple buoyancy signatures were resolved, including overflows from less dense inflows, and interflows to metalimnetic depths and underflows to the bottom from the plunging of more dense inputs. Three different metrics had utility as tracers in depicting the buoyancy signatures as follows: (1) SC, for salinity‐enriched tributaries and the more dilute river that receives the lake's outflow, (2) T_n, for the tributaries during runoff events, and (3) NO₃^?, for the effluent of a domestic waste treatment facility and from the addition of NO₃^? solution to control methyl mercury. The plunging inflow phenomenon, which frequently prevailed, has important management implications.     

Characterization of the archaeal community fouling a membrane bioreactor

Biofilm formation, one of the primary causes of biofouling, results in reduced membrane flux or increased transmembrane pressure and thus represents a major impediment to the wider implementation of membrane bioreactor(MBR) technologies for water purification. Most studies have focused on the role of bacteria in membrane fouling as they are the most dominant and best studied organisms present in the MBR. In contrast, there is limited information on the role of the archaeal community in biofilm formation in MBRs. This study investigated the composition of the archaeal community during the process of biofouling in an MBR. The archaeal community was observed to have lower richness and diversity in the biofilm than the sludge during the establishment of biofilms at low transmembrane pressure(TMP). Clustering of the communities based on the Bray–Curtis similarity matrix indicated that a subset of the sludge archaeal community formed the initial biofilms. The archaeal community in the biofilm was mainly composed of Thermoprotei, Thermoplasmata,Thermococci, Methanopyri, Methanomicrobia and Halobacteria. Among them, the Thermoprotei and Thermoplasmata were present at higher relative proportions in the biofilms than they were in the sludge. Additionally, the Thermoprotei, Thermoplasmata and Thermococci were the dominant organisms detected in the initial biofilms at low TMP, while as the TMP increased, the Methanopyri, Methanomicrobia, Aciduliprofundum and Halobacteria were present at higher abundances in the biofilms at high TMP.     

Ten ways remote sensing can contribute to conservation

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners’ use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain‐referral survey. We then used a workshop‐based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real‐time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing‐derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions?     

Reducing the healthcare costs of urban air pollution: the South African experience

Air pollutants often have adverse effects on human health. This paper investigates and ranks a set of policy and technological interventions intended to reduce such health costs in the high population density areas of South Africa. It initially uses a simple benefit-cost rule, later extended to capture sectoral employment impacts. Although the focus of state air quality legislation is on industrial pollutants, the most efficient interventions were found to be at household level. These included such low-cost interventions as training householders to place kindling above rather than below the coal in a fireplace and insulating roofs. The first non-household policies to emerge involved vehicle fuels and technologies. Most proposed industrial interventions failed a simple cost-benefit test. The paper's policy messages are that interventions should begin with households and that further industry controls are not yet justifiable in their present forms as these relate to the health care costs of such interventions.     

Using GIS to Generate Spatially Balanced Random Survey Designs for Natural Resource Applications

Sampling of a population is frequently required to understand trends and patterns in natural resource management because financial and time constraints preclude a complete census. A rigorous probability-based survey design specifies where to sample so that inferences from the sample apply to the entire population. Probability survey designs should be used in natural resource and environmental management situations because they provide the mathematical foundation for statistical inference. Development of long-term monitoring designs demand survey designs that achieve statistical rigor and are efficient but remain flexible to inevitable logistical or practical constraints during field data collection. Here we describe an approach to probability-based survey design, called the Reversed Randomized Quadrant-Recursive Raster, based on the concept of spatially balanced sampling and implemented in a geographic information system. This provides environmental managers a practical tool to generate flexible and efficient survey designs for natural resource applications. Factors commonly used to modify sampling intensity, such as categories, gradients, or accessibility, can be readily incorporated into the spatially balanced sample design.     

Riverine Threat Indices to Assess Watershed Condition and Identify Primary Management Capacity of Agriculture Natural Resource Management Agencies

Managers can improve conservation of lotic systems over large geographies if they have tools to assess total watershed conditions for individual stream segments and can identify segments where conservation practices are most likely to be successful (i.e., primary management capacity). The goal of this research was to develop a suite of threat indices to help agriculture resource management agencies select and prioritize watersheds across Missouri River basin in which to implement agriculture conservation practices. We quantified watershed percentages or densities of 17 threat metrics that represent major sources of ecological stress to stream communities into five threat indices: agriculture, urban, point-source pollution, infrastructure, and all non-agriculture threats. We identified stream segments where agriculture management agencies had primary management capacity. Agriculture watershed condition differed by ecoregion and considerable local variation was observed among stream segments in ecoregions of high agriculture threats. Stream segments with high non-agriculture threats were most concentrated near urban areas, but showed high local variability. 60 % of stream segments in the basin were classified as under U.S. Department of Agriculture’s Natural Resources Conservation Service (NRCS) primary management capacity and most segments were in regions of high agricultural threats. NRCS primary management capacity was locally variable which highlights the importance of assessing total watershed condition for multiple threats. Our threat indices can be used by agriculture resource management agencies to prioritize conservation actions and investments based on: (a) relative severity of all threats, (b) relative severity of agricultural threats, and (c) and degree of primary management capacity.