Seasonal changes in microbial dissolved organic sulfur transformations in coastal waters

The marine trace gas dimethylsulfide (DMS) is the single most important biogenic source of atmospheric sulfur, accounting for up to 80% of global biogenic sulfur emissions. Approximately 300 million tons of DMS are produced annually, but the majority is degraded by microbes in seawater. The DMS precursor dimethylsulfoniopropionate (DMSP) and oxidation product dimethylsulphoxide (DMSO) are also important organic sulfur reservoirs. However, the marine sinks of dissolved DMSO remain unknown. We used a novel combination of stable and radiotracers to determine seasonal changes in multiple dissolved organic sulfur transformation rates to ascertain whether microbial uptake of dissolved DMSO was a significant loss pathway. Surface concentrations of DMS ranged from 0.5 to 17.0 nM with biological consumption rates between 2.4 and 40.8 nM·d−1. DMS produced from the reduction of DMSO was not a significant process. Surface concentrations of total DMSO ranged from 2.3 to 102 nM with biological consumption of dissolved DMSO between 2.9 and 111 nM·d−1. Comparisons between 14C2-DMSO assimilation and dissimilation rates suggest that the majority of dissolved DMSO was respired (>94%). Radiotracer microbial consumption rates suggest that dissimilation of dissolved DMSO to CO2 can be a significant loss pathway in coastal waters, illustrating the significance of bacteria in controlling organic sulfur seawater concentrations

Investigative study of seasonal changes in Quality Parameters of Oluwa River Water, Agbabu area of Nigeria

Physico-chemical parameters of River Oluwa water in Agbabu, Nigeria were investigated to determine its quality characteristics and establish seasonal effects on the water. Water from the river was collected at five different points in dry season (March, 2008 and 2009) and rainy season (July, 2008 and 2009). Insitu parameters (pH, EC and Turbidity) were measured using Horiba Water Checker Model U-10 while TDS was by Lovibond CM – 21 Tintometer. Subsequently in the Laboratory, Na+ and K+ were determined using flame photometric methods while Ca2+, Mg2+, HCO3-, SO42-, Cl-, PO42- and NO3- were determined by wet analysis. River Oluwa water was alkaline with average pH of 7.41 and 7.53 in dry and rainy seasons respectively. Electrical conductivity (EC) was high during dry season (av. 630.44 µS/cm), but low in the rainy season (av. 317.58 µS/cm) due to long residence time in dry season allowing more water-rock interaction. Turbidity's average values of 0.14 NTU and 2.29 NTU in dry and rainy seasons respectively suggested moderate pollution with particulate matter. The order of average cations concentrations in the dry and rainy seasons was Ca2+ K+ Na+ Mg2+ while that of the anions was HCO3- Cl- SO42- NO3-. The ions concentrations though lower in rainy season, Ca2+-HCO3- water was dominant in both seasons. Quality evaluation for irrigation revealed that the water was suitable for all irrigation purposes. River Oluwa water was soft, low mineralized, chemically potable, suitable for irrigation but with lower ionic concentrations in rainy season

Seasonal changes in anthropometric and physical characteristics within English academy rugby league players.

Professional rugby league clubs implement training programmes for the development of anthropometric and physical characteristics within an academy programme. However, research that examines seasonal changes in these characteristics is limited. The purpose of the study was to evaluate the seasonal changes in anthropometric and physical characteristics of academy rugby league players by age category (i.e., under 14, 16, 18, 20). Data were collected on 75 players pre- and postseason over a 6-year period (resulting in a total of 195 assessments). Anthropometric (body mass, sum of 4 skinfolds) and physical (10- and 20-m sprint, vertical jump, Yo-Yo intermittent recovery test and 1 repetition maximum squat, bench press, and prone row) measures were collected. The under 14s and 16s showed greater seasonal improvements in body mass (e.g., under 14s = 7.4 ± 4.3% vs. under 20s = 1.2 ± 3.3%) and vertical jump performance than under 18s and under 20s. In contrast, under 18s and under 20s players showed greater seasonal improvements in Yo-Yo performance and 10-m sprint (e.g., under 14s = 1.3 ± 3.9% vs. under 20s = -1.9 ± 1.2%) in comparison to under 14s and under 16s. Seasonal strength improvements were greater for the under 18s compared with under 20s. This study provides comparative data for seasonal changes in anthropometric and physical characteristics within rugby league players aged 13-20 years. Coaches should be aware that seasonal improvements in speed may not exist within younger age categories, until changes in body mass stabilize and consider monitoring changes in other characteristics (e.g., momentum). Large interplayer variability suggests that player development should be considered on an individual and longitudinal basis

Seasonal and interannual changes in cirrus

Statistics on cirrus clouds using the multispectral data from the GOES/VAS satellite have been collected since 1985. The method used to diagnose cirrus clouds and a summary of the first two years of data was given in Wylie and Menzel (1989) and at the 1988 FIRE meeting in Vail, CO. This study was expanded to three years of data which allows a more detailed discussion of the geographical and seasonal changes in cloud cover. Interannual changes in cloud cover also were studied. GOES/VAS cloud retrievals also were compared to atmospheric dynamic parameters and to radiative attenuation data taken by a lidar. Some of the highlights of these studies are discussed

A Cross-Season Correspondence Dataset for Robust Semantic Segmentation

In this paper, we present a method to utilize 2D-2D point matches between images taken during different image conditions to train a convolutional neural network for semantic segmentation. Enforcing label consistency across the matches makes the final segmentation algorithm robust to seasonal changes. We describe how these 2D-2D matches can be generated with little human interaction by geometrically matching points from 3D models built from images. Two cross-season correspondence datasets are created providing 2D-2D matches across seasonal changes as well as from day to night. The datasets are made publicly available to facilitate further research. We show that adding the correspondences as extra supervision during training improves the segmentation performance of the convolutional neural network, making it more robust to seasonal changes and weather conditions.Comment: In Proc. CVPR 201

Seasonal Adjustment Methods : An Application to the Turkish Monetary Aggregates

Seasonality can be defined as a pattern of a time series, which repeats at regular intervals every year. Seasonal fluctuations in data make it difficult to analyse whether changes in data for a given period reflect important increases or decreases in the level of the data, or are due to regularly occurring variation. In search for the economic measures that are independent of seasonal variations, methods had been developed to remove the effect of seasonal changes from the original data to produce seasonally adjusted data. The seasonally adjusted data, providing more readily interpretable measures of changes occurring in a given period, reflects real economic movements without the misleading seasonal changes. The choice of method for seasonal adjustment is crucial for the removal of all seasonal effects in the data. Seasonal adjustment is normally done using the off-the-shelf programs-most commonly worldwide by one of the programs in the X-11 family, X-12 ARIMA, the latest improved version. Another program in common use is the TRAMO/SEATS package developed by the Bank of Spain and promoted by Eurostat. In this study, the performances of two seasonal adjustment methods, X-12 ARIMA and TRAMO/SEATS, on the monetary aggregates will be studied. In section five, the two methods are applied to the M2 monetary aggregate series, and the resulting seasonally adjusted series are compared using specific criteria. In sections six and seven, some of the issues that should be concerned in the process of seasonal adjustment, are discussed.Seasonal Adjustment, TRAMO/SEATS, X-12 ARIMA

Seasonal changes in growth of coho salmon (Oncorhynchus kisutch) off Oregon and Washington and concurrent changes in the spacing of scale circuli

In this study we present new information on seasonal variation in absolute growth rate in length of coho salmon (Oncorhynchus kisutch) in the ocean off Oregon and Washington, and relate these changes in growth rate to concurrent changes in the spacing of scale circuli. Average spacing of scale circuli and average rate of circulus formation were significantly and positively correlated with average growth rate among groups of juvenile and maturing coho salmon and thus could provide estimates of growth between age groups and seasons. Regression analyses indicated that the spacing of circuli was proportional to the scale growth rate raised to the 0.4−0.6 power. Seasonal changes in the spacing of scale circuli reflected seasonal changes in apparent growth rates of fish. Spacing of circuli at the scale margin was greatest during the spring and early summer, decreased during the summer, and was lowest in winter or early spring. Changes over time in length of fish caught during research cruises indicated that the average growth rate of juvenile coho salmon between June and September was about 1.3 mm/d and then decreased during the fall and winter to about 0.6 mm/d. Average growth rate of maturing fish was about 2 mm/d between May and June, then decreased to about 1 mm/d between June and September. Average apparent growth rates of groups of maturing coded-wire−tagged coho salmon caught in the ocean hook-and-line fisheries also decreased between June and September. Our results indicate that seasonal change in the spacing of scale circuli is a useful indicator of seasonal change in growth rate of coho salmon in the ocean

Seasonal deuterium excess in a Tien Shan ice core: Influence of moisture transport and recycling in Central Asia

Stable water isotope (δ18O, δD) data from a high elevation (5100 masl) ice core recovered from the Tien Shan Mountains, Kyrgyzstan, display a seasonal cycle in deuterium excess (d = δD − 8*δ18O) related to changes in the regional hydrologic cycle during 1994–2000. While there is a strong correlation (r2 = 0.98) between δ18O and δD in the ice core samples, the regression slope (6.9) and mean d value (23.0) are significantly different than the global meteoric water line values. The resulting time-series ice core d profile contains distinct winter maxima and summer minima, with a yearly d amplitude of ∼15–20‰. Local-scale processes that may affect d values preserved in the ice core are not consistent with the observed seasonal variability. Data from Central Asian monitoring sites in the Global Network of Isotopes in Precipitation (GNIP) have similar seasonal d changes. We suggest that regional-scale hydrological conditions, including seasonal changes in moisture source, transport, and recycling in the Caspian/Aral Sea region, are responsible for the observed spatial and temporal d variability