Winter Hydrology and NO3− Concentrations in a Forested Watershed: A Detailed Field Study in the Adirondack Mountains of New York1

Abstract: More than 85% of NO₃^? losses from watersheds in the northeastern United States are exported during winter months (October 1 to May 30). Interannual variability in NO₃^? loads to individual streams is closely related to interannual climatic variations, particularly during the winter. The objective of our study was to understand how climatic and hydrogeological factors influence NO₃^? dynamics in small watersheds during the winter. Physical parameters including snow depth, soil temperature, stream discharge, and water table elevation were monitored during the 2007‐2008 winter in two small catchments in the Adirondack Mountains, New York State. Snowpack persisted from mid‐December to mid‐April, insulating soils such that only two isolated instances of soil frost were observed during the study period. NO₃^? export during a mid‐winter rain‐on‐snowmelt event comprised between 8 and 16% of the total stream NO₃^? load for the four‐month winter study period. This can be compared with the NO₃^? exported during the final spring melt, which comprised between 38 and 45% of the total four‐month winter NO₃^? load. Our findings indicate that minor melt events were detectable with changes in soil temperature, streamflow, groundwater level, and snow depth. But, based on loading, these events were relatively minor contributors to winter NO₃^? loss. A warmer climate and fluctuating snowpack may result in more major mid‐winter melt events and greater NO₃^? export to surface waters.     

Leveraging social media and deep learning to detect rare megafauna in video surveys

Deep learning has become a key tool for the automated monitoring of animal populations with video surveys. However, obtaining large numbers of images to train such models is a major challenge for rare and elusive species because field video surveys provide few sightings. We designed a method that takes advantage of videos accumulated on social media for training deep-learning models to detect rare megafauna species in the field. We trained convolutional neural networks (CNNs) with social media images and tested them on images collected from field surveys. We applied our method to aerial video surveys of dugongs (Dugong dugon) in New Caledonia (southwestern Pacific). CNNs trained with 1303 social media images yielded 25% false positives and 38% false negatives when tested on independent field video surveys. Incorporating a small number of images from New Caledonia (equivalent to 12% of social media images) in the training data set resulted in a nearly 50% decrease in false negatives. Our results highlight how and the extent to which images collected on social media can offer a solid basis for training deep-learning models for rare megafauna detection and that the incorporation of a few images from the study site further boosts detection accuracy. Our method provides a new generation of deep-learning models that can be used to rapidly and accurately process field video surveys for the monitoring of rare megafauna.     

Understanding the processes in a historically relevant thermal and mineral spring water by using mixing and inverse geochemical models

Environmental Geochemistry and Health - The thermal mineral water of Peñón de los Baños spa (Mexico City) has been used for over 500 years starting in pre-Hispanic times and...     

Responses of soil nitrification activities to copper after a moisture stress

Environmental Science and Pollution Research - Some steps of the soil nitrogen (N) cycle are sensitive to environmental pressures like soil moisture or contamination, which are expected to evolve...     

Optimization and assessment of an electrochemical advanced oxidation system for synthetic stormwater treatment

Environmental Science and Pollution Research - Electrochemical advanced oxidation processes (eAOPs) such as the current advanced oxidation system (AOS) are a type of electrochemical wastewater...     

Monitoring tricyclazole residues in rice paddy watersheds

Pesticide application to rice paddies may affect the quality of environmental resources such as groundwater and surface water. The distribution of residues of tricyclazole, an environmentally persistent fungicide used widely in Italy, was monitored in the network of surface water bodies surrounding the main rice production area in Italy. The location of monitoring sites was based on the potential risk for contamination with tricyclazole. This was determined as a function of the area of rice grown, the geographical distribution of rice crops susceptible to the pest, and sales of tricyclazole. Monitoring sites were also located to represent different spatial scales (farm, catchment and basin). For water samples taken shortly after application in July and August, the highest concentrations of tricyclazole were measured at the farm sites. However, residues were also detected at the catchment and basin scale. The 95% of the measured residue levels was below 9.80, 1.20 and 1.15 microg l(-1), at the farm, catchment and basin scales, respectively. In sediment, tricyclazole residues were detected in 12 out 176 samples collected with the 95% of the measured residue levels below the concentration of 0.03 mg kg(-1). Residues were sporadically detected in samples taken after the crop was harvested in November and December. Variables such as the scale of sampling, the season and the year, were significant in determining pesticide residue distribution. The type of water body was less significant.     

Dissolution of resin acids, retene and wood sterols from contaminated lake sediments

The dissolution potency of hydrophobic resin acids (RAs), retene and wood sterols from sediments was studied. These wood extractives and their metabolites are sorbed from pulp and paper mill effluents to downstream sediments. With harmful components like these, sediments can pose a hazard to the aquatic environment. Therefore, sediment elutriates with water were produced under variable conditions (agitation rate and efficiency, time), and concentrations of the dissoluted compounds were analyzed. Both naturally contaminated field sediments and artificially spiked sediments were studied. By vigorous agitation RAs can be released fast from the sediment matrix and equilibrium reached within 3 days. Compared to RAs, desorption of retene from lake sediment was slower and did not completely reach equilibrium in 23 days. Sterols spiked to pristine sediment with a 33-day contact time desorbed faster than those associated authentically with industrial sediment of from a contaminated lake. Simulating the water turbulence adjacent to a sediment surface by low and high rate of agitation in the laboratory, an increase in the mixing rate after 43-day elutriation suddenly released a high amount of wood sterols. The results indicate wide variation between hazardous chemicals in their tendency to dissolution from sediment solids. Erosion and hydrology adjacent to the sediment surface, as well as risks from dredging activities of sediments, may expose lake biota to bioactive chemicals.     

The allocation of prestigious positions in organizational science: accumulative advantage,sponsored mobility,and contest mobility

More than 200 freshly minted doctoral graduates enter the field of organization science every year. A non‐trivial number of existing faculty members move from one university to another every year, while other organization science faculty leave academia to enter retirement, consulting, or industry. Despite the importance of this large, complex system of entries and exits, few attempts have been made to explicitly understand how the system works. Drawing upon sociology of science and careers research, we studied the underlying form of the position allocation system by focusing on the relative importance of research success and prior affiliations as antecedents of movement and stability across positions. We used three theoretical models: accumulative advantage, sponsored mobility, and contest mobility. Tracking hundreds of faculty members for 16 years post doctorate, we find a downward cascading of affiliation prestige over time that affects people more dramatically and quickly than we expected, especially women. Accumulative advantage, the most predictive of our models, does help to maintain relative but not absolute prestige, at least until its effects wane in later years of the career. These findings are relevant to scholars interested in the sociology of science, organization scholars interested in the underlying dynamics of their discipline, and individuals making career choices. Copyright © 2005 John Wiley & Sons, Ltd.