The aim of this study was to quantify the motion demands of match-play in elite U12-U16 year old soccer players. 112 players from two professional soccer clubs at five age-group levels (U12-U16) were monitored during competitive matches (n = 14) using 5 Hz non-differential Global Positioning System (NdGPS). Velocity thresholds were normalised for each age-group using the mean squad times for a flying 10 m sprint test as a reference point. Match performance was reported as total distance, high-intensity distance, very high-intensity distance and sprint distance.Data were reported both in absolute (m) and relative (m · min -1 ) terms due to a rolling substitute policy. U15 (1.35 ± 0.09 s) and U16 (1.31 ± 0.06 s) players were significantly quicker than the U12 (1.58 ± 0.10 s), U13 (1.52 ± 0.07 s) and U14 (1.51 ± 0.08 s) players in the flying 10m sprint test (P<0.001). The U16 age-group covered significantly more absolute total distance (U16 > U12, U13, U14), high-intensity distance (U16 > U12, U13, U14, U15), very high-intensity distance (U16 > U12, U13) and sprint distance (U16 > U12, U13) than their younger counterparts (P<0.05). When the data are considered relative to match exposure, few differences are apparent. Training prescription for youth soccer players should consider the specific demands of competitive match-play at each age-group.

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International audienceLand cover and land use changes can have a wide variety of ecological effects, including significant impacts on soils and water quality. In rural areas, even subtle changes in farming practices can affect landscape features and functions, and consequently the environment. Fine-scale analyses have to be performed to better understand the land cover change processes. At the same time, models of land cover change have to be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to propose and implement sustainable and efficient environmental policies. Future landscape studies can provide a framework to forecast how land use and land cover changes is likely to react differently to subtle changes. This paper proposes a four step framework to forecast landscape futures at fine scales by coupling scenarios and landscape modelling approaches. This methodology has been tested on two contrasting agricultural landscapes located in the United States and France, to identify possible landscape changes based on forecasting and backcasting agriculture intensification scenarios. Both examples demonstrate that relatively subtle land cover and land use changes can have a large impact on future landscapes. Results highlight how such subtle changes have to be considered in term of quantity, location, and frequency of land use and land cover to appropriately assess environmental impacts on water pollution (France) and soil erosion (US). The results highlight opportunities for improvements in landscape modelling

Four experiments examined the effects of delays to reinforcement on key peck sequences of pigeons maintained under multiple schedules of contingencies that produced variable or repetitive behavior. In Experiments 1, 2, and 4, in the repeat component only the sequence right-right-left-left earned food, and in the vary component four-response sequences different from the previous 10 earned food. Experiments 1 and 2 examined the effects of nonresetting and resetting delays to reinforcement, respectively. In Experiment 3, in the repeat component sequences had to be the same as one of the previous three, whereas in the vary component sequences had to be different from each of the previous three for food. Experiment 4 compared postreinforcer delays to prereinforcement delays. With immediate reinforcement sequences occurred at a similar rate in the two components, but were less variable in the repeat component. Delays to reinforcement decreased the rate of sequences similarly in both components, but affected variability differently. Variability increased in the repeat component, but was unaffected in the vary component. These effects occurred regardless of the manner in which the delay to reinforcement was programmed or the contingency used to generate repetitive behavior. Furthermore, the effects were unique to prereinforcement delays.

Purpose:Soccer referees’ physical match performances at the start of the second half (46–60 min) were evaluated in relation to both the corresponding phase of the first half (0–15 min) and players’ performances during the same match periods.Methods:Match analysis data were collected (Prozone, UK) from 12 soccer referees on 152 English Premier League matches during the 2008/09 soccer season. Physical match performance categories for referees and players were total distance, high-speed running distance (speed >5.5 m/s), and sprinting distance (>7.0 m/s). The referees’ heart rate was recorded from the start of their warm-up to the end of the match. The referees’ average distances (in meters) from the ball and fouls were also calculated.Results:No substantial differences were observed in duration (16:42 ± 2:35 vs 16:27 ± 1:00 min) or intensity (107 ± 11 vs 106 ± 14 beats/min) of the referees’ preparation periods immediately before each half. Physical match performance was reduced during the initial phase of the second half when compared with the first half in both referees (effect sizes—standardized mean differences—0.19 to 0.73) and players (effect sizes 0.20 to 1.01). The degree of the decreased performance was consistent between referees and players for total distance (4.7 m), high-speed running (1.5 m), and sprinting (1.1 m). The referees were closer to the ball (effect size 0.52) during the opening phase the second half.Conclusion:Given the similarity in the referees’ preparation periods, it may be that the reduced physical match performances observed in soccer referees during the opening stages of the second half are a consequence of a slower tempo of play.

In elite-level soccer, player motion characteristics are commonly generated from match play and training situations using semiautomated video analysis systems and global positioning system (GPS) technology, respectively. Before such data are used collectively to quantify global player load, it is necessary to understand both the level of agreement and direction of bias between the systems so that specific interventions can be made based on the reported results. The aim of this report was to compare data derived from both systems for physical match performances. Six elite-level soccer players were analyzed during a competitive match using semiautomated video analysis (ProZone® [PZ]) and GPS (MinimaxX) simultaneously. Total distances (TDs), high speed running (HSR), very high speed running (VHSR), sprinting distance (SPR), and high-intensity running distance (HIR; >4.0 m·s(-1)) were reported in 15-minute match periods. The GPS reported higher values than PZ did for TD (GPS: 1,755.4 ± 245.4 m; PZ: 1,631.3 ± 239.5 m; p < 0.05); PZ reported higher values for SPR and HIR than GPS did (SPR: PZ, 34.1 ± 24.0 m; GPS: 20.3 ± 15.8 m; HIR: PZ, 368.1 ± 129.8 m; GPS: 317.0 ± 92.5 m; p < 0.05). Caution should be exercised when using match-load (PZ) and training-load (GPS) data interchangeably.

[1] Satellite-derived land cover land use (LCLU), snow and albedo data, and incoming surface solar radiation reanalysis data were used to study the impact of LCLU change from 1973 to 2000 on surface albedo and radiative forcing for 58 ecoregions covering 69% of the conterminous United States. A net positive surface radiative forcing (i.e., warming) of 0.029 Wm −2 due to LCLU albedo change from 1973 to 2000 was estimated. The forcings for individual ecoregions were similar in magnitude to current global forcing estimates, with the most negative forcing (as low as −0.367 Wm −2 ) due to the transition to forest and the most positive forcing (up to 0.337 Wm −2 ) due to the conversion to grass/shrub. Snow exacerbated both negative and positive forcing for LCLU transitions between snow-hiding and snow-revealing LCLU classes. The surface radiative forcing estimates were highly sensitive to snow-free interannual albedo variability that had a percent average monthly variation from 1.6% to 4.3% across the ecoregions. The results described in this paper enhance our understanding of contemporary LCLU change on surface radiative forcing and suggest that future forcing estimates should model snow and interannual albedo variation.Citation: Barnes, C. A., and D. P. Roy (2010), Radiative forcing over the conterminous United States due to contemporary land cover land use change and sensitivity to snow and interannual albedo variability,