Separating the effects of partial submergence and soil oxygen demand on plant physiology

In wetlands, a distinct zonation of plant species composition occurs along moisture gradients, due to differential flooding tolerance of the species involved. However, "flooding" comprises two important, distinct stressors (soil oxygen demand [SOD] and partial submergence) that affect plant survival and growth. To investigate how these two flooding stressors affect plant performance, we executed a factorial experiment (water depth x SOD) for six plant species of nutrient-rich and nutrient-poor conditions, occurring along a moisture gradient in Dutch dune slacks. Physiological, growth, and biomass responses to changed oxygen availability were quantified for all species. The responses were consistent with field zonation, but the two stressors affected species differently. Increased SOD increased root oxygen deprivation, as indicated by either raised porosity or increased alcohol dehydrogenase (ADH) activity in roots of flood-intolerant species (Calamagrostis epigejos and Carex arenaria). While SOD affected root functioning, partial submergence tended more to reduce photosynthesis (as shown both by gas exchange and 13C assimilation), leaf dark respiration, 13C partitioning from shoots to roots, and growth of these species. These processes were especially affected if the root oxygen supply was depleted by a combination of flooding and increased SOD. In contrast, the most flood-tolerant species (Juncus subnodulosus and Typha latifolia) were unaffected by any treatment and maintained high internal oxygen concentrations at the shoot : root junction and low root ADH activity in all treatments. For these species, the internal oxygen transport capacity was well in excess of what was needed to maintain aerobic metabolism across all treatments, although there was some evidence for effects of SOD on their nitrogen partitioning (as indicated by 865N values) and photosynthesis. Two species intermediate in flooding tolerance (Carex nigra and Schoenus nigricans) responded more idiosyncratically, with different parameters responding to different treatments. These results show that partial submergence and soil flooding are two very different stressors to which species respond in different ways, and that their effects on physiology, survival, and growth are interactive. Understanding species zonation with water regimes can be improved by a better appreciation of how these factors affect plant metabolism independently and interactively.     

Extrapair paternity in the swamp sparrow, <Emphasis Type="Italic">Melospiza georgiana</Emphasis>: male access or female preference?

Over the past two decades, the combination of molecular and field methods has revealed considerable variation in the level of extrapair fertilizations among socially monogamous birds. Models predicting extrapair young range in scale from a single population to multiple Orders, and there is no single, unifying theory for these reproductive tactics. We investigated proximate explanations of extrapair fertilizations in two subspecies of the swamp sparrow, Melospiza georgiana georgiana and Melospiza georgiana nigrescens, across a range of social and environmental conditions. The presence of extrapair young was best predicted by the size of two male plumage badges (one correlated with parental care and one with territorial aggression) relative to the badge size of their immediate neighbors, the interaction of these two measures, mean territory size, and the maximum size of the aggression badge among neighbors. The size of the male’s parental care badge (relative to neighbors) was negatively correlated with the probability of lost paternity. The relative size of the aggression badge was positively correlated with the presence of extrapair young when the parental care badge was small and negatively correlated when the badge was large. Controlling for these crown measures, males with larger territories were less likely to suffer losses in paternity. There was no effect of breeding density, breeding synchrony, their interaction, subspecies, or weather during the fertile period on the presence of extrapair young. These results suggest that female preference for males that provide more parental care (or preference for genes that convey this trait) plays a dominant role in extrapair interactions among swamp sparrows. Models based on female assessments of relative mate quality offer a promising explanation of patterns in extrapair fertilizations among bird species.     

Tree growth inference and prediction from diameter censuses and ring widths.

Estimation of tree growth is based on sparse observations of tree diameter, ring widths, or increments read from a dendrometer. From annual measurements on a few trees (e.g., increment cores) or sporadic measurements from many trees (e.g., diameter censuses on mapped plots), relationships with resources, tree size, and climate are extrapolated to whole stands. There has been no way to formally integrate different types of data and problems of estimation that result from (1) multiple sources of observation error, which frequently result in impossible estimates of negative growth, (2) the fact that data are typically sparse (a few trees or a few years), whereas inference is needed broadly (many trees over many years), (3) the fact that some unknown fraction of the variance is shared across the population, and (4) the fact that growth rates of trees within competing stands are not independent. We develop a hierarchical Bayes state space model for tree growth that addresses all of these challenges, allowing for formal inference that is consistent with the available data and the assumption that growth is nonnegative. Prediction follows directly, incorporating the full uncertainty from inference with scenarios for "filling the gaps" for past growth rates and for future conditions affecting growth. An example involving multiple species and multiple stands with tree-ring data and up to 14 years of tree census data illustrates how different levels of information at the tree and stand level contribute to inference and prediction.     

Forecasting air quality time series using deep learning

This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O₃) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O₃ exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours.

Implications: Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution concentration while only monitoring key parameters and without transforming the data set in its entirety, thus allowing real time inputs and continuous prediction.     

Characterizing emissions from open burning of military food waste and ration packaging compositions

Emissions from open burning of military food waste and ration packaging compositions were characterized in response to health concerns from open burning disposal of waste, such as at military forward operating bases. Emissions from current and prototype Meals, Ready-to-Eat (MREs), and material options for their associated fiberboard packaging were quantified to assess contributions of the individual components. MREs account for 67–100% of the particulate matter (PM), volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), and polychlorinated dibenzo-p-dioxins and -furans (PCDDs/PCDFs) emissions when burned in unison with the current fiberboard container and liner. The majority of the particles emitted from these burns are of median diameter 2.5 µm (PM_2.5). Metal emission factors were similar regardless of waste composition. Measurements of VOCs and PAHs indicate that targeted replacement of MRE components may be more effective in reducing emissions than variation of fiberboard-packaging types. Despite MRE composition variation, equivalent emission factors for PM, PAH, VOC, and PCDD/PCDF were seen. Similarly, for fiberboard packaging, composition variations exhibited essentially equivalent PM, PAH, VOC, and PCDD/PCDF emission factors amongst themselves. This study demonstrated a composition-specific analysis of waste burn emissions, assessing the impact of waste component substitution using military rations.     

Energy Communication: Theory and Praxis Towards a Sustainable Energy Future

This essay comments and expands upon an emerging area of research, energy communication, that shares with environmental communication the fraught commitment to simultaneously study communication as an ordinary yet potentially transformative practice, and a strategic endeavour to catalyse change. We begin by defining and situating energy communication within ongoing work on the discursive dimensions of energy extraction, production, distribution, and consumption. We then offer three generative directions for future research related to energy transitions as communicative processes: analysing campaigns’ strategic efforts, critically theorizing energy’s transnational power dynamics, and theorizing the energy democracy movement.     

Differentiating the effects of climate and land use change on European biodiversity: A scenario analysis

Current observed as well as projected changes in biodiversity are the result of multiple interacting factors, with land use and climate change often marked as most important drivers. We aimed to disentangle the separate impacts of these two for sets of vascular plant, bird, butterfly and dragonfly species listed as characteristic for European dry grasslands and wetlands, two habitats of high and threatened biodiversity. We combined articulations of the four frequently used SRES climate scenarios and associated land use change projections for 2030, and assessed their impact on population trends in species (i.e. whether they would probably be declining, stable or increasing). We used the BIOSCORE database tool, which allows assessment of the effects of a range of environmental pressures including climate change as well as land use change. We updated the species lists included in this tool for our two habitat types. We projected species change for two spatial scales: the EU27 covering most of Europe, and the more restricted biogeographic region of ‘Continental Europe’. Other environmental pressures modelled for the four scenarios than land use and climate change generally did not explain a significant part of the variance in species richness change. Changes in characteristic bird and dragonfly species were least pronounced. Land use change was the most important driver for vascular plants in both habitats and spatial scales, leading to a decline in 50–100% of the species included, whereas climate change was more important for wetland dragonflies and birds (40–50 %). Patterns of species decline were similar in continental Europe and the EU27 for wetlands but differed for dry grasslands, where a substantially lower proportion of butterflies and birds declined in continental Europe, and 50 % of bird species increased, probably linked to a projected increase in semi-natural vegetation. In line with the literature using climate envelope models, we found little divergence among the four scenarios. Our findings suggest targeted policies depending on habitat and species group. These are, for dry grasslands, to reduce land use change or its effects and to enhance connectivity, and for wetlands to mitigate climate change effects.     

Superstorm Sandy and the academic achievement of university students

Much of the literature on the consequences of natural disasters has focused on their physical and psychological ramifications. Few researchers have considered how the impacts of a natural disaster can influence academic achievement. This study analyses data collected from nearly 300 students at a mid‐sized, private university in the northeast United States to determine if the effects of Cyclone Sandy in 2012 are associated with measures of academic achievement. The findings reveal that experiencing headaches after the event resulted in a higher likelihood of students suffering a loss of academic motivation. In addition, experiencing headaches and a loss of academic motivation were correlated with a lower grade point average (GPA) during the semester in which Sandy made landfall. However, the more direct effects of the superstorm, including displacement and a loss of power, did not have a significant bearing on academic achievement. Lastly, the paper examines the implications for higher education policy and future research.     

Impacts of pesticides in a Central California estuary

Recent and past studies have documented the prevalence of pyrethroid and organophosphate pesticides in urban and agricultural watersheds in California. While toxic concentrations of these pesticides have been found in freshwater systems, there has been little research into their impacts in marine receiving waters. Our study investigated pesticide impacts in the Santa Maria River estuary, which provides critical habitat to numerous aquatic, terrestrial, and avian species on the central California coast. Runoff from irrigated agriculture constitutes a significant portion of Santa Maria River flow during most of the year, and a number of studies have documented pesticide occurrence and biological impacts in this watershed. Our study extended into the Santa Maria watershed coastal zone and measured pesticide concentrations throughout the estuary, including the water column and sediments. Biological effects were measured at the organism and community levels. Results of this study suggest the Santa Maria River estuary is impacted by current-use pesticides. The majority of water samples were highly toxic to invertebrates (Ceriodaphnia dubia and Hyalella azteca), and chemistry evidence suggests toxicity was associated with the organophosphate pesticide chlorpyrifos, pyrethroid pesticides, or mixtures of both classes of pesticides. A high percentage of sediment samples were also toxic in this estuary, and sediment toxicity occurred when mixtures of chlorpyrifos and pyrethroid pesticides exceeded established toxicity thresholds. Based on a Relative Benthic Index, Santa Maria estuary stations where benthic macroinvertebrate communities were assessed were degraded. Impacts in the Santa Maria River estuary were likely due to the proximity of this system to Orcutt Creek, the tributary which accounts for most of the flow to the lower Santa Maria River. Water and sediment samples from Orcutt Creek were highly toxic to invertebrates due to mixtures of the same pesticides measured in the estuary. This study suggests that the same pyrethroid and organophosphate pesticides that have been shown to cause water and sediment toxicity in urban and agriculture water bodies throughout California, have the potential to affect estuarine habitats. The results establish baseline data in the Santa Maria River estuary to allow evaluation of ecosystem improvement as management initiatives to reduce pesticide runoff are implemented in this watershed.     

Assessment of Wastewater Reuse Effects on Nutrient Loads from Paddy Field Using Field-Scale Water Quality Model

CREAMS-PADDY, a modified version of the field-scale CREAMS model, simulates the hydrologic, sediment, and nutrient cycles in paddy fields. The CREAMS-PADDY model was applied to estimate the effects of using wastewater for irrigation on nutrient loads from paddy fields in Republic of Korea. The model was calibrated and validated using data from two rice paddy fields. The coefficient of determination between observed and simulated total nitrogen and total phosphorus were 0.92 and 0.57, respectively, for the calibration period and 0.84 and 0.73 for the validation period. Simulations showed that when using wastewater for irrigation, the total nitrogen loads increased by 210% and total phosphorus by 1,270% when compared with conventional water irrigation. The total nitrogen and total phosphorus concentration in the ponded water increased by 254 and 534%, respectively, when compared with conventional water irrigation. The effect of reducing N and P fertilizer application rates by 10, 30, and 50% on nutrient loads exiting a paddy field were also simulated using the validated CREAMS-PADDY model. These simulations indicated that total phosphorus loads from the paddy were reduced only slightly by reducing the fertilizer, while total nitrogen loads were reduced by as much as 8.8, 16.6, and 24.4% when N ferlitizer rates were reduced by 10, 30, and 50%, respectively. An erratum to this article can be found at