Site‐specific weed management—constraints and opportunities for the weed research community: Insights from a workshop

The adoption of site‐specific weed management (SSWM) technologies by farmers is not aligned with the scientific achievements in this field. While scientists have demonstrated significant success in real‐time weed identification, phenotyping and accurate weed mapping by using various sensors and platforms, the integration by farmers of SSWM and weed phenotyping tools into weed management protocols is limited. This gap was therefore a central topic of discussion at the most recent workshop of the SSWM Working Group arranged by the European Weed Research Society (EWRS). This insight paper aims to summarise the presentations and discussions of some of the workshop panels and to highlight different aspects of weed identification and spray application that were thought to hinder SSWM adoption. It also aims to share views and thoughts regarding steps that can be taken to facilitate future implementation of SSWM

Crossover phenomena in spin models with medium-range interactions and self-avoiding walks with medium-range jumps

We study crossover phenomena in a model of self-avoiding walks with medium-range jumps, that corresponds to the limit $N\to 0$ of an $N$-vector spin system with medium-range interactions. In particular, we consider the critical crossover limit that interpolates between the Gaussian and the Wilson-Fisher fixed point. The corresponding crossover functions are computed using field-theoretical methods and an appropriate mean-field expansion. The critical crossover limit is accurately studied by numerical Monte Carlo simulations, which are much more efficient for walk models than for spin systems. Monte Carlo data are compared with the field-theoretical predictions concerning the critical crossover functions, finding a good agreement. We also verify the predictions for the scaling behavior of the leading nonuniversal corrections. We determine phenomenological parametrizations that are exact in the critical crossover limit, have the correct scaling behavior for the leading correction, and describe the nonuniversal lscrossover behavior of our data for any finite range.Comment: 43 pages, revte

BARRA v1.0: the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia

The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) is the first atmospheric regional reanalysis over a large region covering Australia, New Zealand, and Southeast Asia. The production of the reanalysis with approximately 12&thinsp;km horizontal resolution – BARRA-R – is well underway with completion expected in 2019. This paper describes the numerical weather forecast model, the data assimilation methods, the forcing and observational data used to produce BARRA-R, and analyses results from the 2003–2016 reanalysis. BARRA-R provides a realistic depiction of the meteorology at and near the surface over land as diagnosed by temperature, wind speed, surface pressure, and precipitation. Comparing against the global reanalyses ERA-Interim and MERRA-2, BARRA-R scores lower root mean square errors when evaluated against (point-scale) 2&thinsp;m temperature, 10&thinsp;m wind speed, and surface pressure observations. It also shows reduced biases in daily 2&thinsp;m temperature maximum and minimum at 5&thinsp;km resolution and a higher frequency of very heavy precipitation days at 5 and 25&thinsp;km resolution when compared to gridded satellite and gauge analyses. Some issues with BARRA-R are also identified: biases in 10&thinsp;m wind, lower precipitation than observed over the tropical oceans, and higher precipitation over regions with higher elevations in south Asia and New Zealand. Some of these issues could be improved through dynamical downscaling of BARRA-R fields using convective-scale (&lt;2&thinsp;km) models.</p

Reviewing research priorities in weed ecology, evolution and management: A horizon scan

Weedy plants pose a major threat to food security, biodiversity, ecosystem services and consequently to human health and wellbeing. However, many currently used weed management approaches are increasingly unsustainable. To address this knowledge and practice gap, in June 2014, 35 weed and invasion ecologists, weed scientists, evolutionary biologists and social scientists convened a workshop to explore current and future perspectives and approaches in weed ecology and management. A horizon scanning exercise ranked a list of 124 pre-submitted questions to identify a priority list of 30 questions. These questions are discussed under seven themed headings that represent areas for renewed and emerging focus for the disciplines of weed research and practice. The themed areas considered the need for transdisciplinarity, increased adoption of integrated weed management and agroecological approaches, better understanding of weed evolution, climate change, weed invasiveness and finally, disciplinary challenges for weed science. Almost all the challenges identified rested on the need for continued efforts to diversify and integrate agroecological, socio-economic and technological approaches in weed management. These challenges are not newly conceived, though their continued prominence as research priorities highlights an ongoing intransigence that must be addressed through a more system-oriented and transdisciplinary research agenda that seeks an embedded integration of public and private research approaches. This horizon scanning exercise thus set out the building blocks needed for future weed management research and practice; however, the challenge ahead is to identify effective ways in which sufficient research and implementation efforts can be directed towards these needs

Influenza A (H1N1) in Victoria, Australia: A Community Case Series and Analysis of Household Transmission

We characterise the clinical features and household transmission of pandemic influenza A (pH1N1) in community cases from Victoria, Australia in 2009.Questionnaires were used to collect information on epidemiological characteristics, illness features and co-morbidities of cases identified in the 2009 Victorian Influenza Sentinel Surveillance program.The median age of 132 index cases was 21 years, of whom 54 (41%) were under 18 years old and 28 (21%) had medical co-morbidities. The median symptom duration was significantly shorter for children who received antivirals than in those who did not (p = 0.03). Assumed influenza transmission was observed in 63 (51%) households. Influenza-like illness (ILI) developed in 115 of 351 household contacts, a crude secondary attack rate of 33%. Increased ILI rates were seen in households with larger numbers of children but not larger numbers of adults. Multivariate analysis indicated contacts of cases with cough and diarrhoea, and contacts in quarantined households were significantly more likely to develop influenza-like symptoms.Most cases of pH1N1 in our study were mild with similar clinical characteristics to seasonal influenza. Illness and case features relating to virus excretion, age and household quarantine may have influenced secondary ILI rates within households

Time scales and exponential trends to equilibrium: Gaussian model problems

We review results on the exponential convergence of multi- dimensional Ornstein-Uhlenbeck processes and discuss related notions of characteristic timescales with concrete model systems. We focus, on the one hand, on exit time distributions and provide ecplicit expressions for the exponential rate of the distribution in the small noise limit. On the other hand, we consider relaxation timescales of the process to its equi- librium measured in terms of relative entropy and discuss the connection with exit probabilities. Along these lines, we study examples which il- lustrate specific properties of the relaxation and discuss the possibility of deriving a simulation-based, empirical definition of slow and fast de- grees of freedom which builds upon a partitioning of the relative entropy functional in conjuction with the observed relaxation behaviour