Temporal Control of Metabolic Amplitude by Nocturnin

International audienc

Photoperiod Alters Phase Difference Between Activity Onset in vivo and mPer2::luc Peak in vitro

Photoperiod is a significant modulator of behavior and physiology for many organisms. In rodents changes in photoperiod are associated with changes in circadian period and photic resetting of circadian pacemakers. Utilizing rhythms of in vivo behavior and in vitro mPer2::luc expression, we investigated whether different entrainment photoperiods [light:dark (L:D) 16:8 and L:D 8:16] alter the period or phase relationships between these rhythms and the entraining light cycle in Per2::luc C57BL/6J mice. We also tested whether mPer2::luc rhythms differs in anterior and posterior suprachiasmatic nucleus (SCN) slices. Our results demonstrate that photoperiod significantly changes the timing of the mPer2::luc peak relative to the time of light offset and the activity onset in vivo. In both L:D 8:16 and L:D 16:8 the mPer2::luc peak maintained a more stable phase relationship to activity offset, while altering the phase relationship to activity onset. After the initial cycle in culture, the period, phase, and peaks per cycle were not signifi-cantly different for anterior vs. posterior SCN slices taken from animals within one photoperiod. After short-photoperiod treatment, anterior SCN slices showed increased-amplitude Per2::luc waveforms and posterior SCN slices showed shorter-duration peak width. Finally, the SCN tissue in vitro did not demonstrate differences in period attributable to photoperiod pretreatment, indicating that period after-effects observed in behavioral rhythms after long- and short-day photoperiods are not sustained in Per2::luc rhythms in vitro. The change in phase relationship to activity onset suggests that Per2::luc rhythms in the SCN may track activity offset rather than activity onset. The reduced amplitude rhythms following long-photoperiod treatment may represent a loss of coupling of component oscillators

COMPARISON OF LOAD ESTIMATION METHODS FOR CALCULATING TOTAL MAXIMUM DAILY LOAD (TMDL) IN AGRICULTURAL WATERSHEDS

Waterbodies that are too polluted to meet established water quality standards are designated specific maximum amounts of pollutant that the waterbody can receive and still be considered safe for designated uses, known as Total Maximum Daily Loads (TMDL). Regulating TMDLs requires estimating pollution load which can be difficult since pollutant concentration can often only be measured on a biweekly or monthly basis. Some of the most established methods for calculating load use an averaging technique; however, this method relies on a normal distribution of flow, which is often not the case for agricultural watersheds where flows consist primarily of irrigation runoff and are determined by human activity

Use of continuous and grab sample data for calculating total maximum daily load (TMDL) in agricultural watersheds

Measuring the discharge of diffuse pollution from agricultural watersheds presents unique challenges. Flows in agricultural watersheds, particularly in Mediterranean climates, can be predominately irrigation runoff and exhibit large diurnal fluctuation in both volume and concentration. Flow and pollutant concentrations in these smaller watersheds dominated by human activity do not conform to a normal distribution and it is not clear if parametric methods are appropriate or accurate for load calculations. The objective of this study was to compare the accuracy of five load estimation methods to calculate pollutant loads from agricultural watersheds. Calculation of loads using results from discrete (grab) samples was compared with the true-load computed using in situ continuous monitoring measurements. A new method is introduced that uses a non-parametric measure of central tendency (the median) to calculate loads (median-load). The median-load method was compared to more commonly used parametric estimation methods which rely on using the mean as a measure of central tendency (mean-load and daily-load), a method that utilizes the total flow volume (volume-load), and a method that uses measure of flow at the time of sampling (instantaneous-load). Using measurements from ten watersheds in the San Joaquin Valley of California, the average percent error compared to the true-load for total dissolved solids (TDS) was 7.3% for the median-load, 6.9% for the mean-load, 6.9% for the volume-load, 16.9% for the instantaneous-load, and 18.7% for the daily-load methods of calculation. The results of this study show that parametric methods are surprisingly accurate, even for data that have starkly non-normal distributions and are highly skewed

COMPARISON OF LOAD ESTIMATION METHODS FOR CALCULATING TOTAL MAXIMUM DAILY LOAD (TMDL) IN AGRICULTURAL WATERSHEDS

Waterbodies that are too polluted to meet established water quality standards are designated specific maximum amounts of pollutant that the waterbody can receive and still be considered safe for designated uses, known as Total Maximum Daily Loads (TMDL). Regulating TMDLs requires estimating pollution load which can be difficult since pollutant concentration can often only be measured on a biweekly or monthly basis. Some of the most established methods for calculating load use an averaging technique; however, this method relies on a normal distribution of flow, which is often not the case for agricultural watersheds where flows consist primarily of irrigation runoff and are determined by human activity

Evaluation of watershed-derived mass loads to prioritize TMDL decision-making

A total maximum daily load (TMDL) for oxygen demanding substances is being implemented in the San Joaquin River (SJR) in California (USA) due to frequently occurring low dissolved oxygen conditions. The SJR is a eutrophic river, heavily impacted by agriculture. A mass balance was developed to identify the sources of oxygen-demanding substances and nutrients to the river with the objective of providing a scientific basis for management actions needed to meet TMDL requirements. Data were collected for flow and water quality and mass loads calculated for sites within the main stem of the SJR, river inputs (tributaries), and diversions in the study area. Using a quadrant analysis, tributary flows and loads are ranked to identify targets for water quality improvement efforts. Additionally, all mass loads were summed (inputs minus diversions) and compared with observed loads at the downstream limit of the study area. The mass balance analysis identifies major contributors of mass loads and mass balance closure is assessed for each constituent. These analysis methods inform the TMDL process which includes a load allocation, and is useful for determining locations for implementation of improvement projects needed to improve the health of the river