Analysis of organic nitrogen removal in municipal wastewater by reverse osmosis

The results of a pilot study that was conducted to determine the total nitrogen removal by the reverse osmosis process are presented. The organic nitrogen removal rates are compared with removals observed from three full-scale reverse osmosis facilities and four pilot studies. The results of this analysis suggest that organic nitrogen removal is variable and that reverse osmosis may not consistently produce total nitrogen levels less than 1.0 mg/L without additional treatment. Three hypotheses to explain the variability in organic nitrogen removal in the different data sets are presented.     

Multivariate trade-offs, succession, and phenological differentiation in a guild of colonial invertebrates

For competing species limited by one or few resources, diversity is thought to be maintained by trade-offs that allow niche differentiation without resource partitioning. However, few studies have quantified multiple key traits for each species in a guild and shown that trade-offs among these traits apply across the guild. Here we document strong bivariate and multivariate relationships among growth rate, fecundity, longevity, and overgrowth ability for six co-occurring colonial invertebrates. We find that all four of these traits are constrained to a single "fast-slow" niche axis that mechanistically relates life history variation to a colonization-competition trade-off. The location of species on this axis strongly predicts the timing of their peak abundance during succession. We also find that species closer to each other on the fast-slow axis are more likely to differ in reproductive phenology, suggesting a secondary dimension of niche differentiation for otherwise similar species.     

Predicting species distributions from samples collected along roadsides

Predictive models of species distributions are typically developed with data collected along roads. Roadside sampling may provide a biased (nonrandom) sample; however, it is currently unknown whether roadside sampling limits the accuracy of predictions generated by species distribution models. We tested whether roadside sampling affects the accuracy of predictions generated by species distribution models by using a prospective sampling strategy designed specifically to address this issue. We built models from roadside data and validated model predictions at paired locations on unpaved roads and 200 m away from roads (off road), spatially and temporally independent from the data used for model building. We predicted species distributions of 15 bird species on the basis of point-count data from a landbird monitoring program in Montana and Idaho (U.S.A.). We used hierarchical occupancy models to account for imperfect detection. We expected predictions of species distributions derived from roadside-sampling data would be less accurate when validated with data from off-road sampling than when it was validated with data from roadside sampling and that model accuracy would be differentially affected by whether species were generalists, associated with edges, or associated with interior forest. Model performance measures (kappa, area under the curve of a receiver operating characteristic plot, and true skill statistic) did not differ between model predictions of roadside and off-road distributions of species. Furthermore, performance measures did not differ among edge, generalist, and interior species, despite a difference in vegetation structure along roadsides and off road and that 2 of the 15 species were more likely to occur along roadsides. If the range of environmental gradients is surveyed in roadside-sampling efforts, our results suggest that surveys along unpaved roads can be a valuable, unbiased source of information for species distribution models.     

A 200-year perspective on alternative stable state theory and lake management from a biomanipulated shallow lake

Multiple stressors to a shallow lake ecosystem have the ability to control the relative stability of alternative states (clear, macrophyte-dominated or turbid, algal-dominated). As a consequence, the use of remedial biomanipulations to induce trophic cascades and shift a turbid lake to a clear state is often only a temporary solution. Here we show the instability of short-term manipulations in the shallow Lake Christina (Minnesota, USA) is governed by the long-term state following a regime shift in the lake. During the modern, managed period of the lake, three top-down manipulations (fish kills) were undertaken inducing temporary (5-10 years) unstable clear-water states. Paleoecological remains of diatoms, along with proxies of primary production (total chlorophyll a and total organic carbon accumulation rate) and trophic state (total P) from sediment records clearly show a single regime shift in the lake during the early 1950s; following this shift, the functioning of the lake ecosystem is dominated by a persistent turbid state. We find that multiple stressors contributed to the regime shift. First, the lake began to eutrophy (from agricultural land use and/or increased waterfowl populations), leading to a dramatic increase in primary production. Soon after, the construction of a dam in 1936 effectively doubled the depth of the lake, compounded by increases in regional humidity; this resulted in an increase in planktivorous and benthivorous fish reducing phytoplankton grazers. These factors further conspired to increase the stability of a turbid regime during the modern managed period, such that switches to a clear-water state were inherently unstable and the lake consistently returned to a turbid state. We conclude that while top-down manipulations have had measurable impacts on the lake state, they have not been effective in providing a return to an ecosystem similar to the stable historical period. Our work offers an example of a well-studied ecosystem forced by multiple stressors into a new long-term managed period, where manipulated clear-water states are temporary, managed features.     

Near-term ecological forecasting for dynamic aeroconservation of migratory birds

Near-term ecological forecasting has the potential to mitigate negative impacts of human modifications on wildlife by directing efficient action through relevant and timely predictions. We used the U.S. avian migration system to highlight ecological forecasting applications for aeroconservation. We used millions of observations from 143 weather surveillance radars to construct and evaluate a migration forecasting system for nocturnal bird migration over the contiguous United States. We identified the number of nights of mitigation required to reduce the risk of aerial hazards to 50% of avian migrants passing a given area in spring and autumn based on dynamic forecasts of migration activity. We also investigated an alternative approach, that is, employing a fixed conservation strategy based on time windows that historically capture 50% of migratory passage. In practice, during both spring and autumn, dynamic forecasts required fewer action nights compared with fixed window selection at all locations (spring: mean of 7.3 more alert days; fall: mean of 12.8 more alert days). This pattern resulted in part from the pulsed nature of bird migration captured in the radar data, where the majority (54.3%) of birds move on 10% of a migration season's nights. Our results highlight the benefits of near-term ecological forecasting and the potential advantages of dynamic mitigation strategies over static ones, especially in the face of increasing risks to migrating birds from light pollution, wind energy infrastructure, and collisions with structures.     

Calibration and Validation of ADAPT and SWAT for Field‐Scale Runoff Prediction1

Abstract: The pollutant reduction possible with a given agricultural best‐management practice (BMP) is complex and site‐specific. Water‐quality models can evaluate BMPs, but model results are often limited by the lack of calibrated parameters for a given BMP. This study calibrated runoff prediction of two models (ADAPT and SWAT) for individual field plots having one till and two no‐till management practices. The factors used for runoff calibration were curve number II (CN_II) and saturated hydraulic conductivity (Ksat) for ADAPT, and CN_II, Ksat, and available water capacity for SWAT. Results were evaluated using coefficient of determination (R²), Nash‐Sutcliffe efficiency (E_f), root‐mean square error, median‐based E_f, and sign tests. Results indicated that for ADAPT, the best‐fit CN_II was 66 for the NT/SB (no‐till plot with surface‐broadcast fertilizer) treatment, 68 for the NT/DB (no‐till with deep‐banded fertilizer) treatment, and 70 for the tilled plot, whereas for SWAT the best‐fit CN_II was much higher, 86, for all treatments. Neither agreed with the textbook CN_II, 78, for sorghum in silty clay loam soil. The best‐fit model parameters for both runoff calibration phases had excellent correlation to monthly totals and moderate correlation to individual events.     

Quantifying Tradeoffs Associated with Hydrologic Environmental Flow Methods

Freshwater management requires balancing and tradingoff multiple objectives, many of which may be competing. Ecological needs for freshwater are often described in terms of environmental flow recommendations (e.g., minimum flows), and there are many techniques for developing these recommendations, which range from hydrologic rules to multidisciplinary analyses supported by large teams of subject matter experts. Although hydrologic rules are well acknowledged as overly simplified, these techniques remain the state‐of‐the‐practice in many locations. This article seeks to add complexity to the application of these techniques by studying the emergent properties of hydrologic environmental flow methodologies. Two hydrologic rules are applied: minimum flow criteria and sustainability boundaries. Objectives and metrics associated with withdrawal rate and similarity to natural flow regimes are used to tradeoff economic and environmental needs, respectively, over a range of flow thresholds and value judgments. A case study of hypothetical water withdrawals on the Middle Oconee River near Athens, Georgia is applied to demonstrate these techniques. For this case study, sustainability boundaries emerge as preferable relative to both environmental and economic outcomes. Methods applied here provide a mechanism for examining the role of stakeholder values and tradeoffs in application of hydrologic rules for environmental flows.     

Model‐Based Nitrogen and Phosphorus (Nutrient) Criteria for Large Temperate Rivers: 1. Model Development and Application

An initial inquiry into model‐based numeric nitrogen and phosphorus (nutrient) criteria for large rivers is presented. Field data collection and associated modeling were conducted on a segment of the lower Yellowstone River in the northwestern United States to assess the feasibility of deriving numeric nutrient criteria using mechanistic water‐quality models. The steady‐state one‐dimensional model QUAL2K and a transect‐based companion model AT2K were calibrated and confirmed against low‐flow conditions at a time when river loadings, water column chemistry, and diurnal indicators were approximately steady state. Predictive simulation was then implemented via nutrient perturbation to evaluate the steady‐state and diurnal response of the river to incremental nutrient additions. In this first part of a two‐part series, we detail our modeling approach, model selection, calibration and confirmation, sensitivity analysis, model outcomes, and associated uncertainty. In the second part (Suplee et al., 2015) we describe the criteria development process using the tools described herein. Both articles provide a fundamental understanding of the process required to develop site‐specific numeric nutrient criteria using models in applied regulatory settings.