Feeding Ecology and Territorial Behavior of the Yellow Warbler

A controversy dating from the appearance of Altum\u27s book, Der Vogel und sein Leben, 1868 (Mayr, 1935) is that of the biological function or functions of the territorial behavior in birds. However, attention was not focused upon this problem until the advent of Howard\u27s book, Territory in Bird Life, published in 1920. In a general review of the problem Hinde (1956) discussed several functions of the territory and presented evidence both for and against their importance. The more important of these presumed functions are; (1) limitation of population density; (2) facilitation of pair formation and maintenance of the pair bond; (3) reduction in interference with reproductive activities by other members of the species; (4) provision of an adequate food supply for rearing the young; (5) reduction of loss to predators; (6) reduction of time spent in aggression; and (7) prevention of epidemics

Implementation and testing of a simple data assimilation algorithm in the regional air pollution forecast model, DEOM

A simple data assimilation algorithm based on statistical interpolation has been developed and coupled to a long-range chemistry transport model, the Danish Eulerian Operational Model (DEOM), applied for air pollution forecasting at the National Environmental Research Institute (NERI), Denmark. In this paper, the algorithm and the results from experiments designed to find the optimal setup of the algorithm are described. The algorithm has been developed and optimized via eight different experiments where the results from different model setups have been tested against measurements from the EMEP (European Monitoring and Evaluation Programme) network covering a half-year period, April–September 1999. The best performing setup of the data assimilation algorithm for surface ozone concentrations has been found, including the combination of determining the covariances using the Hollingsworth method, varying the correlation length according to the number of adjacent observation stations and applying the assimilation routine at three successive hours during the morning. Improvements in the correlation coefficient in the range of 0.1 to 0.21 between the results from the reference and the optimal configuration of the data assimilation algorithm, were found. The data assimilation algorithm will in the future be used in the operational THOR integrated air pollution forecast system, which includes the DEOM

Age Study of Minnesota Red Fox Using Cementum Annulae Counts and Tooth X-Rays

A prerequisite to the proper management of an animal species is understanding of its population dynamics. Attempting this, the age structure of 297 red fox trapped or shot in southern Minnesota was investigated, using the techniques of tooth sectioning and x-ray. Results from two seasons (1977 and 1978) were similar, with 76.8 percent of the harvested population being juveniles (78.4 percent, 1977 and 74.6 percent, 1978), whereas only 0 .6 percent of the total were in the 4½ year old class. The percentage of juveniles corresponds closely to the numbers predicted by a Department of Natural Resources model developed by Al Berner of the Farmland Research Unit. If a population reacts in a density-dependent manner, an increase in the breeding density should reduce the reproductive rate, and vice-versa. Data of this paper tend to support the premise that the reproductive rate in Minnesota red fox is affected in a density-dependent manner

Assimilation of OMI NO₂ retrievals into the limited-area chemistry-transport model DEHM (V2009.0) with a 3-D OI algorithm

Data assimilation is the process of combining real-world observations with a modelled geophysical field. The increasing abundance of satellite retrievals of atmospheric trace gases makes chemical data assimilation an increasingly viable method for deriving more accurate analysed fields and initial conditions for air quality forecasts. We implemented a three-dimensional optimal interpolation (OI) scheme to assimilate retrievals of NO2 tropospheric columns from the Ozone Monitoring Instrument into the Danish Eulerian Hemispheric Model (DEHM, version V2009.0), a three-dimensional, regional-scale, offline chemistry-transport model. The background error covariance matrix, B, was estimated based on differences in the NO2 concentration field between paired simulations using different meteorological inputs. Background error correlations were modelled as non-separable, horizontally homogeneous and isotropic. Parameters were estimated for each month and for each hour to allow for seasonal and diurnal patterns in NO2 concentrations. Three experiments were run to compare the effects of observation thinning and the choice of observation errors. Model performance was assessed by comparing the analysed fields to an independent set of observations: ground-based measurements from European air-quality monitoring stations. The analysed NO2 and O3 concentrations were more accurate than those from a reference simulation without assimilation, with increased temporal correlation for both species. Thinning of satellite data and the use of constant observation errors yielded a better balance between the observed increments and the prescribed error covariances, with no appreciable degradation in the surface concentrations due to the observation thinning. Forecasts were also considered and these showed rather limited influence from the initial conditions once the effects of the diurnal cycle are accounted for. The simple OI scheme was effective and computationally feasible in this context, where only a single species was assimilated, adjusting the three-dimensional field for this compound. Limitations of the assimilation scheme are discussed

Operational mapping of atmospheric nitrogen deposition to the Baltic Sea

International audienceA new model system for mapping and forecasting nitrogen deposition to the Baltic Sea has been developed. The system is based on the Lagrangian variable scale transport-chemistry model ACDEP (Atmospheric Chemistry and Deposition model), and aims at delivering deposition estimates to be used as input to marine ecosystem models. The system is tested by comparison of model results to measurements from monitoring stations around the Baltic Sea. The comparison shows that observed annual mean ambient air concentrations and wet depositions are well reproduced by the model. Diurnal mean concentrations of NHx (sum of NH3 and NH4+) and NO2 are fairly well reproduced, whereas concentrations of total nitrate (sum of HNO3 and NO3-) are somewhat overestimated. Wet depositions of nitrate and ammonia are fairly well described for annual mean values, whereas the discrepancy is high for the monthly mean values and the wet depositions are rather poorly described concerning the diurnal mean values. The model calculations show that the annual atmospheric nitrogen deposition has a pronounced south--north gradient with depositions in the range about 1.0 T N km-2 in the south and 0.2 T N km-2 in the north. The results show that in 1999 the maximum diurnal mean deposition to the Danish waters appeared during the summer in the algae growth season. For the northern parts of the Baltic the highest depositions were distributed over most of the year. Total deposition to the Baltic Sea was for the year 1999 estimated to 318 kT N for an area of 464 406 km2 equivalent to an average deposition of 684 kg N/km2

Energy expenditure during sleep, sleep deprivation and sleep following sleep deprivation in adult humans

Sleep has been proposed to be a physiological adaptation to conserve energy, but little research has examined this proposed function of sleep in humans. We quantified effects of sleep, sleep deprivation and recovery sleep on whole-body total daily energy expenditure (EE) and on EE during the habitual day and nighttime. We also determined effects of sleep stage during baseline and recovery sleep on EE. Seven healthy participants aged 22 ± 5 years (mean ± s.d.) maintained ∼8 h per night sleep schedules for 1 week before the study and consumed a weight-maintenance diet for 3 days prior to and during the laboratory protocol. Following a habituation night, subjects lived in a whole-room indirect calorimeter for 3 days. The first 24 h served as baseline – 16 h wakefulness, 8 h scheduled sleep – and this was followed by 40 h sleep deprivation and 8 h scheduled recovery sleep. Findings show that, compared to baseline, 24 h EE was significantly increased by ∼7% during the first 24 h of sleep deprivation and was significantly decreased by ∼5% during recovery, which included hours awake 25–40 and 8 h recovery sleep. During the night time, EE was significantly increased by ∼32% on the sleep deprivation night and significantly decreased by ∼4% during recovery sleep compared to baseline. Small differences in EE were observed among sleep stages, but wakefulness during the sleep episode was associated with increased energy expenditure. These findings provide support for the hypothesis that sleep conserves energy and that sleep deprivation increases total daily EE in humans