Soil management, seed treatment and soil compaction on the sowing furrows affect grain yields of upland rice genotypes.

The water availability for flood irrigated rice (Oryza sativa L.) is decreasing worldwide. Therefore, developing technologies to allow growing rice in aerobic condition, such as a no-tillage system (NTS) can contribute to produce upland rice grains without yield losses and also in saving more water. The objective of this study was to determine the effect of soil management, seed treatment and compaction on the sowing furrow on grain yield of upland rice genotypes. We made two trials, one in an NTS and another using conventional tillage, CT (one plowing and two diskings). The field experiments were performed in the Central Region of Brazil in Cerrado soils. For each trial, the experimental design was a randomized block design in a factorial scheme, with three replications. The treatments consisted of a combination of 10 genotypes with 2 compaction pressures on the sowing furrow (25 kPa and 126kPa) and 2 types of seed treatment (with and without pesticide). Under CT, the seed treatment did not contribute to increase upland rice grain yields. However, under NTS the grain yield of some genotypes [BRS Esmeralda (from 723 to 1,766 kg ha-1), BRS Pepita (from 930 to 1,874 kg ha-1), AB072044 (from 523 to 1,579 kg ha-1), and AB072085 (from 632 to 1,636 kg ha-1) at 25 kPA soil compaction pressure, and Sertaneja (from 994 to 2,167 kg ha-1), BRS Pepita (from 1,161 to 2,100 kg ha-1), and AB072085 (from 958 to 2,213 kg ha-1), at 126 kPA soil compaction pressure] increased with the use of this practice. At CT the higher soil compaction pressure on the sowing furrow (from 25 kPa to 126 kPa) increased rice grain yield only when it was used seed treatment and the genotypes Serra Dourada (from 1,239 to 2,178 kg ha-1), Sertaneja (from 1,510 to 2,379 kg ha-1), and Cambará (from 1,877 to 2,831 kg ha-1). On the other hand, under NTS, increasing soil compaction pressure on the sowing furrow allowed for an increased rice grain yield of Serra Dourada (from 1,553 to 2,347 kg ha-1), Esmeralda (from 723 to 1,643 kg ha-1), AB072044 (from 523 to 2,040 kg ha-1), and Cambará (from 1,243 to 2,032 kg ha-1) without seed treatment and Sertaneja (from 1,385 to 2,167 kg ha-1) and AB072044 (from 1,579 to 2,356 kg ha-1) with seed treatment. In CT the most productive genotypes were AB062008 (2,714 kg ha-1) and BRSMG Caravera (2,479 kg ha-1), while at NTS were the genotypes: BRSGO Serra Dourada (2,118 kg ha-1), AB072047 (1,888 kg ha-1), AB062008 (1,823 kg ha-1), BRSMG Caravera (1,737 kg ha-1), Cambará (1,716 kg ha-1), AB072044 (1,625 kg ha-1), BRS Esmeralda (1,604 kg ha-1), and BRS Pepita (1,516 kg ha-1).

Weather variability, tides, and Barmah Forest Virus Disease in the Gladstone region, Australia

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

Power law distributions in pattern dynamics of attacker-defender dyads in the team sport of Rugby Union : phenomena in a region of self-organized criticality?

In the region of self-organized criticality (SOC) interdependency between multi-agent system components exists and slight changes in near-neighbor interactions can break the balance of equally poised options leading to transitions in system order. In this region, frequency of events of differing magnitudes exhibits a power law distribution. The aim of this paper was to investigate whether a power law distribution characterized attacker-defender interactions in team sports. For this purpose we observed attacker and defender in a dyadic sub-phase of rugby union near the try line. Videogrammetry was used to capture players’ motion over time as player locations were digitized. Power laws were calculated for the rate of change of players’ relative position. Data revealed that three emergent patterns from dyadic system interactions (i.e., try; unsuccessful tackle; effective tackle) displayed a power law distribution. Results suggested that pattern forming dynamics dyads in rugby union exhibited SOC. It was concluded that rugby union dyads evolve in SOC regions suggesting that players’ decisions and actions are governed by local interactions rules.

How useful is expert opinion for predicting the distribution of a species within and beyond the region of expertise? A case study using brush-tailed rock-wallabiesPetrogale penicillata

1. Species' distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species' distribution information is expert opinion. This study evaluates expert knowledge and its source. In particular, we determine whether models built on expert knowledge apply over multiple regions or only within the region where the knowledge was derived. 2. The case study focuses on the distribution of the brush-tailed rock-wallaby Petrogale penicillata in eastern Australia. We brought together from two biogeographically different regions substantial and well-designed field data and knowledge from nine experts. We used a novel elicitation tool within a geographical information system to systematically collect expert opinions. The tool utilized an indirect approach to elicitation, asking experts simpler questions about observable rather than abstract quantities, with measures in place to identify uncertainty and offer feedback. Bayesian analysis was used to combine field data and expert knowledge in each region to determine: (i) how expert opinion affected models based on field data and (ii) how similar expert-informed models were within regions and across regions. 3. The elicitation tool effectively captured the experts' opinions and their uncertainties. Experts were comfortable with the map-based elicitation approach used, especially with graphical feedback. Experts tended to predict lower values of species occurrence compared with field data. 4. Across experts, consensus on effect sizes occurred for several habitat variables. Expert opinion generally influenced predictions from field data. However, south-east Queensland and north-east New South Wales experts had different opinions on the influence of elevation and geology, with these differences attributable to geological differences between these regions. 5. Synthesis and applications. When formulated as priors in Bayesian analysis, expert opinion is useful for modifying or strengthening patterns exhibited by empirical data sets that are limited in size or scope. Nevertheless, the ability of an expert to extrapolate beyond their region of knowledge may be poor. Hence there is significant merit in obtaining information from local experts when compiling species' distribution models across several regions.