ORCID Profile
0000-0003-2657-3264
Current Organisation
University of Tasmania
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Food Packaging, Preservation and Safety | Food Processing | Higher Education | Food Sciences |
ANZSRC Socio-Economic Objective (SEO)
Processed Food Products and Beverages (excl. Dairy Products) not elsewhere classified | Food Safety
Related Links
Publications
Potential applications of subseasonal-to-seasonal (S2S) predictions
Publisher: Wiley
Date: 06-04-2017
DOI: 10.1002/MET.1654
Biochar increases plant-available water in a sandy loam soil under an aerobic rice crop system
Publisher: Copernicus GmbH
Date: 03-09-2014
Abstract: Abstract. The main objective of this study was to assess the impact of biochar rate (0, 8, 16 and 32 Mg ha−1) on the water retention capacity (WRC) of a sandy loam Dystric Plinthosol. The applied biochar was a by-product of slow pyrolysis (∼450 °C) of eucalyptus wood, milled to pass through a 2000 μm sieve that resulted in a material with an intrinsic porosity ≤10 μm and a specific surface area of ∼3.2 m2 g−1. The biochar was incorporated into the top 15 cm of the soil under an aerobic rice system. Our study focused on both the effects on WRC and rice yields 2 and 3 years after its application. Undisturbed soil s les were collected from 16 plots in two soil layers (5–10 and 15–20 cm). Soil water retention curves were modelled using a nonlinear mixed model which appropriately accounts for uncertainties inherent of spatial variability and repeated measurements taken within a specific soil s le. We found an increase in plant-available water in the upper soil layer proportional to the rate of biochar, with about 0.8% for each Mg ha−1 biochar amendment 2 and 3 years after its application. The impact of biochar on soil WRC was most likely related to an effect in overall porosity of the sandy loam soil, which was evident from an increase in saturated soil moisture and macro porosity with 0.5 and 1.6% for each Mg ha−1 of biochar applied, respectively. The increment in soil WRC did not translate into an increase in rice yield, essentially because in both seasons the amount of rainfall during the critical period for rice production exceeded 650 mm. The use of biochar as a soil amendment can be a worthy strategy to guarantee yield stability under short-term water-limited conditions. Our findings raise the importance of assessing the feasibility of very high application rates of biochar and the inclusion of a detailed analysis of its physical and chemical properties as part of future investigations.
A Peanut Simulation Model: I. Model Development and Testing
Publisher: Wiley
Date: 11-1995
The best farm-level irrigation strategy changes seasonally with fluctuating water availability
Publisher: Elsevier BV
Date: 2012
Spatial impact of projected changes in rainfall and temperature on wheat yields in Australia
Publisher: Springer Science and Business Media LLC
Date: 28-07-2012
Global change impacts on wheat production along an environmental gradient in south Australia
Publisher: Elsevier BV
Date: 09-2001
DOI: 10.1016/S0160-4120(01)00082-4
Abstract: Crop production is likely to change in the future as a result of global changes in CO2 levels in the atmosphere and climate. APSIM, a cropping system model, was used to investigate the potential impact of these changes on the distribution of cropping along an environmental transect in south Australia. The effects of several global change scenarios were studied, including: (1) historical climate and CO2 levels, (2) historic climate with elevated CO2 (700 ppm), (3) warmer climate (+2.4 degrees C) +700 ppm CO2, (4) drier climate (-15% summer, -20% winter rainfall) +2.4 degrees C +700 ppm CO2, (5) wetter climate (+10% summer rainfall) +2.4 degrees C +700 ppm CO2 and (6) most likely climate changes (+1.8 degrees C, -8% annual rainfall) +700 ppm CO2. Based on an analysis of the current cropping boundary, a criterion of 1 t/ha was used to assess potential changes in the boundary under global change. Under most scenarios, the cropping boundary moved northwards with a further 240,000 ha potentially being available for cropping. The exception was the reduced rainfall scenario (4), which resulted in a small retreat of cropping from its current extent. However, the impact of this scenario may only be small (in the order of 10,000-20,000 ha reduction in cropping area). Increases in CO2 levels over the current climate record have resulted in small but significant increases in simulated yields. Model limitations are discussed.
Grains
Publisher: Springer International Publishing
Date: 2020
Identifying optimal sowing and flowering periods for barley in Australia: a modelling approach
Publisher: Elsevier BV
Date: 03-2020
Preface: Climate Predictions for Better Agricultural Risk Management
Publisher: CSIRO Publishing
Date: 2007
DOI: 10.1071/ARV58N10_PR
Potential deep drainage under wheat crops in a Mediterranean climate. I. Temporal and spatial variability
Publisher: CSIRO Publishing
Date: 2001
DOI: 10.1071/AR99186
Abstract: High rates of deep drainage (water loss below the root-zone) in Western Australia are contributing to groundwater recharge and secondary salinity. However, quantifying potential drainage through measurements is h ered by the high degree of complexity of these systems as a result of erse soil types, a range of crops, different rainfall regions, and in particular the inherent season-to-season variability. Simulation models can provide the appropriate means to extrapolate across time and space. The Agricultural Production Systems Simulator (APSIM) was used to analyse deep drainage under wheat crops in the Mediterranean climate of the central Western Australian wheatbelt. In addition to rigorous model testing elsewhere, comparisons between simulated and observed soil water loss, evapotranspiration, and deep drainage for different soil types and seasons confirmed the reasonable performance of the APSIM model. The APSIM model was run with historical weather records (70–90 years) across 2 transects from the coast (high rainfall zone) to the eastern edge of the wheatbelt (low rainfall zone). Soils were classified as 5 major types: deep sand, deep loamy sand, acid loamy sand, shallow duplex (waterlogging), and clay soil (non-waterlogging). Simulations were carried out on these soil types with historical weather records, assuming current crop management and cultivars. Soil water profiles were reset each year to the lower limit of plant-available water, assuming maximum water use in the previous crop. Results stressed the high degree of seasonal variability of deep drainage ranging from 0 to 386 mm at Moora in the high rainfall region (461 mm/year average rainfall), from 0 to 296 mm at Wongan Hills in the medium rainfall region (386 mm/year average rainfall), and from 0 to 234 mm at Merredin in the low rainfall region (310 mm/year average rainfall). The largest amounts of drainage occurred in soils with lowest extractable water-holding capacities. Estimates of annual drainage varied with soil type and location. For ex le, average (s.d.) annual drainage at Moora, Wongan Hills, and Merredin was 134 (73), 90 (61), and 36 (43) mm on a sand, and 57 (64), 26 (43), and 4 (18) mm on a clay soil, respectively. These values are an order of magnitude higher than drainage reported elsewhere under native vegetation. When not resetting the soil each year, carry-over of water left behind in the soil reduced the water storage capacity in the subsequent year, increasing long-term average deep drainage, depending on soil type and rainfall region. The analyses revealed the extent of the excess water problem that currently threatens the sustainability of the wheat-based farming systems in Western Australia.
Inferential, nonparametric statistics to assess the quality of probabilistic forecast systems
Publisher: American Meteorological Society
Date: 02-2007
DOI: 10.1175/MWR3291.1
Abstract: Many statistical forecast systems are available to interested users. To be useful for decision making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and its statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of “quality.” However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what quality entails and how to measure it, leading to confusion and misinformation. A generic framework is presented that quantifies aspects of forecast quality using an inferential approach to calculate nominal significance levels (p values), which can be obtained either by directly applying nonparametric statistical tests such as Kruskal–Wallis (KW) or Kolmogorov–Smirnov (KS) or by using Monte Carlo methods (in the case of forecast skill scores). Once converted to p values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. The analysis demonstrates the importance of providing p values rather than adopting some arbitrarily chosen significance levels such as 0.05 or 0.01, which is still common practice. This is illustrated by applying nonparametric tests (such as KW and KS) and skill scoring methods [linear error in the probability space (LEPS) and ranked probability skill score (RPSS)] to the five-phase Southern Oscillation index classification system using historical rainfall data from Australia, South Africa, and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. It is found that nonparametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system, or quality measure. Eventually such inferential evidence should be complemented by descriptive statistical methods in order to fully assist in operational risk management.
Leveraging Sentiment Distributions to Distinguish Figurative From Literal Health Reports on Twitter
Publisher: ACM
Date: 20-04-2020
The intrinsic plasticity of farm businesses and their resilience to change. An Australian example
Publisher: Elsevier BV
Date: 11-2011
Improving wheat simulation capabilities in Australia from a cropping systems perspective II. Testing simulation capabilities of wheat growth
Publisher: Elsevier BV
Date: 1998
Providing Seasonal-to-Interannual Climate Information for Risk Management and Decision-making
Publisher: Elsevier BV
Date: 2010
SAM: Multi-turn Response Selection Based on Semantic Awareness Matching
Publisher: Association for Computing Machinery (ACM)
Date: 28-02-2023
DOI: 10.1145/3545570
Abstract: Multi-turn response selection is a key issue in retrieval-based chatbots and has attracted considerable attention in the NLP (Natural Language processing) field. So far, researchers have developed many solutions that can select appropriate responses for multi-turn conversations. However, these works are still suffering from the semantic mismatch problem when responses and context share similar words with different meanings. In this article, we propose a novel chatbot model based on Semantic Awareness Matching, called SAM. SAM can capture both similarity and semantic features in the context by a two-layer matching network. Appropriate responses are selected according to the matching probability made through the aggregation of the two feature types. In the evaluation, we pick 4 widely used datasets and compare SAM’s performance to that of 12 other models. Experiment results show that SAM achieves substantial improvements, with up to 1.5% R 10 @1 on Ubuntu Dialogue Corpus V2, 0.5% R 10 @1 on Douban Conversation Corpus, and 1.3% R 10 @1 on E-commerce Corpus.
Silver lining to a climate crisis: multiple prospects for alleviating crop waterlogging under future climates
Publisher: Research Square Platform LLC
Date: 27-07-2022
DOI: 10.21203/RS.3.RS-1863270/V1
Abstract: Extreme weather events threaten food security, yet global assessments of crop waterlogging are rare. Here, we make three important contributions to the literature. First, we develop a paradigm that distils common stress patterns across environments, genotypes and climate horizons. Second, we embed improved process-based understanding into a contemporary farming systems model to discern changes in global crop waterlogging under future climates. Third, we elicit viable systems adaptations to waterlogging. Using projections from 27 global circulation models, we show that yield penalties caused by waterlogging increased from 3–11% historically to 10–20% by 2080. Altering sowing time and adopting waterlogging tolerant genotypes reduced yield penalties by up to 18%, while earlier sowing of winter genotypes alleviated waterlogging risk by 8%. We show that future stress patterns caused by waterlogging are likely to be similar to those occurring historically, suggesting that adaptations for future climates could be successfully designed using current stress patterns.
From rainfall to farm incomes—transforming advice for Australian drought policy. II. Forecasting farm incomes
Publisher: CSIRO Publishing
Date: 2007
DOI: 10.1071/AR06195
Abstract: Australian drought policy is focussed on providing relief from the immediate effects of drought on farm incomes, while enhancing the longer term resilience of rural livelihoods. Despite the socioeconomic nature of these objectives, the information systems created to support the policy have focussed almost exclusively on biophysical measures of climate variability and its effects on agricultural production. In this paper, we demonstrate the ability of bioeconomic modelling to overcome the moral hazard and timing issues that have led to the dominance of these biophysical measures. The Agricultural Farm Income Risk Model (AgFIRM), developed and tested in a companion paper, is used to provide objective, model-based forecasts of annual farm incomes at the beginning of the financial year (July–June). The model was then used to relate climate-induced income variability to the ersity of farm income sources, a practical measure of adaptive capacity that can be positively influenced by policy. Three timeless philosophical arguments are used to discuss the policy relevance of the bioeconomic modelling. These arguments are used to compare the value to decision makers of relatively imprecise, integrative information, with relatively precise, reductionist measures. We conclude that the evolution of bioeconomic modelling systems provides an opportunity to refocus the analytical support for Australian drought policy towards the rural livelihood effects that matter most to governments and rural communities.
Nitrogen Use and Crop Performance of Rice under Aerobic Conditions in a Semiarid Subtropical Environment
Publisher: Wiley
Date: 2014
From rainfall to farm incomes—transforming advice for Australian drought policy. I. Development and testing of a bioeconomic modelling system
Publisher: CSIRO Publishing
Date: 2007
DOI: 10.1071/AR06193
Abstract: In this paper we report the development of a bioeconomic modelling system, AgFIRM, designed to help close a relevance gap between climate science and policy in Australia. We do this by making a simple econometric farm income model responsive to seasonal forecasts of crop and pasture growth for the coming season. The key quantitative innovation was the use of multiple and M-quantile regression to calibrate the farm income model, using simulated crop and pasture growth from 2 agroecological models. The results of model testing demonstrated a capability to reliably forecast the direction of movement in Australian farm incomes in July at the beginning of the financial year (July–June). The structure of the model, and the seasonal climate forecasting system used, meant that its predictive accuracy was greatest across Australia’s cropping regions. In a second paper, Nelson et al. (2007, this issue), we have demonstrated how the bioeconomic modelling system developed here could be used to enhance the value of climate science to Australian drought policy.
Climatic risk to peanut production: a simulation study for Northern Australia
Publisher: CSIRO Publishing
Date: 1995
DOI: 10.1071/EA9950777
Abstract: A dynamic peanut simulation model was used to quantify climatic risk to peanut production in Northern Australia. We demonstrate how district yield information can be usefully combined with simulation results to assess objectively impact and causes of climatic variability on production. Our analysis shows that the rapid expansion of the peanut industry in the region corresponded with relatively stable, above average yields caused by that period in the historical record having above-average and less variable summer rainfall. During this period the timing and amount of rainfall was such that yields higher than average could often be achieved, and harvests were only rarely interrupted by prolonged wet periods. These conditions created unrealistically high expectations of yields by producers, and when the climate was more variable during the 1980s, it was perceived as a greater deviation from the norm than justified by the long-term record.
Assessing Strategies for Orobanche sp. Control Using a Combined Seedbank and Competition Model
Publisher: Wiley
Date: 11-2005
Impact of crop management and environment on the spatio-temporal variance of potato yield at regional scale
Publisher: Elsevier BV
Date: 08-2021
Effects of soil- and climate data aggregation on simulated potato yield and irrigation water requirement
Publisher: Elsevier BV
Date: 03-2020
DOI: 10.1016/J.SCITOTENV.2019.135589
Abstract: Input data aggregation affects crop model estimates at the regional level. Previous studies have focused on the impact of aggregating climate data used to compute crop yields. However, little is known about the combined data aggregation effect of climate (DAE
Cyberbullying Detection from Social Media for the Australian Context
Publisher: CSIRO
Date: 2020
Event frequency and severity of sorghum ergot in Australia
Publisher: CSIRO Publishing
Date: 2000
DOI: 10.1071/AR99117
Abstract: The temporal and regional distribution of the severity and potential number of events of sorghum ergot on grain sorghum in Australia were analysed using daily climatic data from 1957 to 1998. This analysis was conducted using both a rule-based method and a regression model. Between December and March, the main flowering period for most commercial grain sorghum crops, we found a likely increase of ergot events in eastern Australia from south to north as well as from west to east. When crops flowered in April or May the number of potential monthly events increased, particularly in the southern areas. The smallest number of events occurred when flowering occurred between September and December. The temporal and geographic distribution of the number of events and severity of sorghum ergot is closely related to relative humidity during the flowering period. The analysis indicates that grain sorghum crops flowering between early December and February are unlikely to be severely infected with sorghum ergot. Late flowering sorghum has increased risk to severe infection, especially in the coastal regions.
On the relation between weather variables and sorghum ergot infection
Publisher: CSIRO Publishing
Date: 2000
DOI: 10.1071/AR99072
Abstract: Sorghum ergot (Claviceps africana) has had a significant impact on seed production and breeders’ nurseries in Australia since it was first found in 1996. In this paper, 3 distinct key development stages of sorghum that are related to ergot infection were identified: flag leaf stage, pollen starch accumulation stage, and flowering period. Relationships between weather variables during these 3 stages and ergot severity as well as pollen viability were analysed using observed data from 2 field trials, a serial planting trial and a genotype trial, conducted at Gatton, Queensland. The duration of the flag leaf stage and of the flowering period was estimated from thermal time. An infection factor was introduced and calculated based on hourly temperature during the flowering period. This infection factor and the mean relative humidity at 0900 hours during the flowering period were the main factors influencing ergot infection. Mean daily minimum temperature during flag leaf stage also had a significant effect on ergot severity, although no significant relation was found between this mean daily minimum temperature and pollen viability. A linear regression model using the above 3 factors accounted for 94% of the environmentally caused variation in ergot severity observed in the genotype trial.
Examining the yield potential of barley near-isogenic lines using a genotype by environment by management analysis
Publisher: Elsevier BV
Date: 04-2019
Comments on the three-zone approach for social media monitoring
Publisher: Informa UK Limited
Date: 30-09-2019
Global, regional, and national burden of Parkinson's disease, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016
Publisher: Elsevier BV
Date: 11-2018
Participatory Crossover Analysis to Support Discussions about Investments in Irrigation Water Sources
Publisher: MDPI AG
Date: 26-06-2019
DOI: 10.3390/W11071318
Abstract: Regional long-term water management plans depend increasingly on investments by local water users such as farmers. However, local circumstances and in idual situations vary and investment decisions are made under uncertainty. Water users may therefore perceive the costs and benefits very differently, leading to non-uniform investment decisions. This variation can be explored using crossover points. A crossover point represents conditions in which a decision maker assigns equal preference to competing alternatives. This paper presents, applies, and evaluates a framework extending the use of the concept of crossover points to a participatory process in a group setting. We applied the framework in a case study in the Coal River Valley of Tasmania, Australia. Here, farmers can choose from multiple water sources. In this case, the focus on crossover points encouraged participants to engage in candid discussions exploring the personal lines of reasoning underlying their preferences. Participants learned from others’ inputs, and group discussions elicited information and insights considered valuable for both the participants and for outsiders on the factors that influence preferences. We conclude that the approach has a high potential to facilitate learning in groups and to support planning.
Operational seasonal forecasting of crop performance
Publisher: The Royal Society
Date: 24-10-2005
Abstract: Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production.
Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates
Publisher: Springer Science and Business Media LLC
Date: 10-02-0002
DOI: 10.1038/S41467-023-36129-4
Abstract: Extreme weather events threaten food security, yet global assessments of impacts caused by crop waterlogging are rare. Here we first develop a paradigm that distils common stress patterns across environments, genotypes and climate horizons. Second, we embed improved process-based understanding into a farming systems model to discern changes in global crop waterlogging under future climates. Third, we develop avenues for adapting cropping systems to waterlogging contextualised by environment. We find that yield penalties caused by waterlogging increase from 3–11% historically to 10–20% by 2080, with penalties reflecting a trade-off between the duration of waterlogging and the timing of waterlogging relative to crop stage. We document greater potential for waterlogging-tolerant genotypes in environments with longer temperate growing seasons (e.g., UK, France, Russia, China), compared with environments with higher annualised ratios of evapotranspiration to precipitation (e.g., Australia). Under future climates, altering sowing time and adoption of waterlogging-tolerant genotypes reduces yield penalties by 18%, while earlier sowing of winter genotypes alleviates waterlogging by 8%. We highlight the serendipitous outcome wherein waterlogging stress patterns under present conditions are likely to be similar to those in the future, suggesting that adaptations for future climates could be designed using stress patterns realised today.
A Survey on Trust Prediction in Online Social Networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Assessing linear interpolation to generate daily radiation and temperature data for use in crop simulations
Publisher: Elsevier BV
Date: 08-2004
Implications of data aggregation method on crop model outputs – The case of irrigated potato systems in Tasmania, Australia
Publisher: Elsevier BV
Date: 05-2021
A survey of recent methods on deriving topics from Twitter
Publisher: Springer Science and Business Media LLC
Date: 09-01-2020
Understanding the food supply chain from the consumers' perspectives
Publisher: CSIRO
Date: 2018
Properties of a clay soil from 1.5 to 3.5years after biochar application and the impact on rice yield
Publisher: Elsevier BV
Date: 08-2016
Simulating crop–parasitic weed interactions using APSIM: Model evaluation and application
Publisher: Elsevier BV
Date: 04-2006
Influence of air and soil temperatures on grafted and self-rooted Passiflora hybrids
Publisher: Elsevier BV
Date: 07-1990
Barley yellow dwarf virus infection affects physiology, morphology, grain yield and flour pasting properties of wheat
Publisher: CSIRO Publishing
Date: 2019
DOI: 10.1071/CP18364
Abstract: Barley yellow dwarf virus (BYDV) is a phloem-limited virus that is persistently transmitted by aphids and causes significant yield losses in wheat (Triticum aestivum L.). The present study was conducted to investigate the effects of BYDV in wheat on physiological and morphological traits, yield attributes and pasting properties of flour, and to determine any differences for these traits between susceptible and resistant genotypes under BYDV infection. Significant impact on physiological and morphological traits and yield was observed in plants inoculated at the 2-leaf stage (Zadoks scale, Z12), with a greater impact in the three susceptible genotypes than in the resistant genotype. Yield reduction with inoculation at Z12 was 18–49%, and yield reduction with inoculation mid tillering (Z25) was 6–31%. There was a significant reduction in effective tiller number with both inoculation times, but 1000-kernel weight was affected only with early inoculation. Pasting properties were little affected by BYDV infection, with genotype having a larger effect than infection. Grain yield showed negative correlation with tissue-blot immunoassay and visual symptom score, and positive correlation with all gas-exchange parameters, chlorophyll fluorescence, leaf area and biomass weight. The results suggest that stomatal conductance, transpiration rate and chlorophyll fluorescence measurements are suitable for assessment of BYDV infection and for screening BYDV of susceptible and resistant wheat genotypes.
Key weather extremes affecting potato production in The Netherlands
Publisher: Elsevier BV
Date: 02-2012
Over-Optimistic Projected Future Wheat Yield Potential in the North China Plain: The Role of Future Climate Extremes
Publisher: MDPI AG
Date: 07-01-2022
Abstract: Global warming and altered precipitation patterns pose a serious threat to crop production in the North China Plain (NCP). Quantifying the frequency of adverse climate events (e.g., frost, heat and drought) under future climates and assessing how those climatic extreme events would affect yield are important to effectively inform and make science-based adaptation options for agriculture in a changing climate. In this study, we evaluated the effects of heat and frost stress during sensitive phenological stages at four representative sites in the NCP using the APSIM-wheat model. climate data included historical and future climates, the latter being informed by projections from 22 Global Climate Models (GCMs) in the Coupled Model Inter-comparison Project phase 6 (CMIP6) for the period 2031–2060 (2050s). Our results show that current projections of future wheat yield potential in the North China Plain may be overestimated after more accurately accounting for the effects of frost and heat stress in the model, yield projections for 2031-60 decreased from 31% to 9%. Clustering of common drought-stress seasonal patterns into key groups revealed that moderate drought stress environments are likely to be alleviated in the future, although the frequency of severe drought-stress environments would remain similar (25%) to that occurring under the current climate. We highlight the importance of mechanistically accounting for temperature stress on crop physiology, enabling more robust projections of crop yields under future the burgeoning climate crisis.
Automated monitoring of tweets for early detection of the 2014 Ebola epidemic
Publisher: Public Library of Science (PLoS)
Date: 17-03-2020
Predicting optimum crop designs using crop models and seasonal climate forecasts
Publisher: Springer Science and Business Media LLC
Date: 02-02-2018
DOI: 10.1038/S41598-018-20628-2
Abstract: Expected increases in food demand and the need to limit the incorporation of new lands into agriculture to curtail emissions, highlight the urgency to bridge productivity gaps, increase farmers profits and manage risks in dryland cropping. A way to bridge those gaps is to identify optimum combination of genetics (G), and agronomic managements (M) i.e. crop designs (GxM), for the prevailing and expected growing environment (E). Our understanding of crop stress physiology indicates that in hindsight, those optimum crop designs should be known, while the main problem is to predict relevant attributes of the E, at the time of sowing, so that optimum GxM combinations could be informed. Here we test our capacity to inform that “hindsight”, by linking a tested crop model (APSIM) with a skillful seasonal climate forecasting system, to answer “What is the value of the skill in seasonal climate forecasting, to inform crop designs?” Results showed that the GCM POAMA-2 was reliable and skillful, and that when linked with APSIM, optimum crop designs could be informed. We conclude that reliable and skillful GCMs that are easily interfaced with crop simulation models, can be used to inform optimum crop designs, increase farmers profits and reduce risks.
The importance of social identity on password formulations
Publisher: Springer Science and Business Media LLC
Date: 07-11-2021
Correlation between temperature and phenology prediction error in rice (Oryza sativa L.)
Publisher: Elsevier BV
Date: 12-2011
Modelling crop growth and yield under the environmental changes induced by windbreaks. 2. Simulation of potential benefits at selected sites in Australia
Publisher: CSIRO Publishing
Date: 2002
DOI: 10.1071/EA02020
Abstract: Recent reports in Australia and elsewhere have attributed enhanced crop yields to the presence of tree windbreaks on farms. One hypothesis for this observation is that, by reducing wind speed, windbreaks influence crop water and energy balances resulting in lower evaporative demand and increased yield. This paper is the second in a series aimed at developing and using crop and micrometeorological modelling capabilities to explore this hypothesis. Specifically, the objectives of this paper are to assist the interpretation of recent field experimentation on windbreak impacts and to quantify the potential benefits and the likelihood of windbreak effects on crop production through an economic analysis of crop yields predicted for the historical climate record at selected sites in Australia. The APSIM systems model was specified to simulate crop growth under the environmental changes induced by windbreaks and subsequently used to simulate the potential benefits on crop production at 2 actual windbreak sites and 17 hypothetical sites around Australia. With the actual windbreak sites, APSIM closely simulated measured crop growth and yield in open-field conditions. However, neither site demonstrated measurable windbreak impacts and APSIM simulations confirmed that such effects would have been either non-existent or masked by experimental variability in the years under study. For each year of the long-term climate record at 17 sites, APSIM simulated yields of relevant crops for transects behind hypothetical windbreaks that provided protection against all wind. When wind protection from all directions is assumed, average simulated yield increases at 5 H (height of windbreak) ranged from 0.2% for maize at Atherton to 24.6% for wheat grown at Dalby, resulting in gross margin changes of �$14.79/ha.crop and $24.13/ha.crop, respectively, for a 10 m high windbreak and 100 ha paddock and assuming a 20% yield loss due to tree competition in the 1.0�3.5 H section. Averaged across all sites and crops, the simulations predicted a yield advantage of 8.6% at 5 H for protection from wind in any direction, resulting in an average gross margin loss of �$0.60/ha.crop. At the 8 sites with available data for wind direction, and assuming protection only from wind originating within a 90� arc perpendicular to a hypothetical windbreak which was optimally orientated at each site, average simulated yield increases at 5 H ranged from 1.0% for wheat at Orange to 8.6% for wheat grown at Geraldton. For a 10 m high windbreak, 100 ha paddock and an assumed 20% yield loss in the 1.0�3.5 H section, the average result across all sites and crops was a 4.7% yield advantage at 5 H and an average gross margin loss of �$2.49/ha.crop. In conclusion, APSIM simulation and economic analyses indicated that yield benefits from microclimate changes can at least partly offset the opportunity costs of positioning tree windbreaks on farms.
Forecasting regional crop production using SOI phases: an example for the Australian peanut industry
Publisher: CSIRO Publishing
Date: 1997
DOI: 10.1071/A96155
Abstract: Using peanuts as an ex le, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing o/Southern bodies the industtry could profitable to adjust their operations stategically. Significantly , physically based lag-relationships exist between an index of ocean/atmospher EI Niño/southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.
Designing high-yielding wheat crops under late sowing: a case study in southern China
Publisher: Springer Science and Business Media LLC
Date: 04-2022
DOI: 10.1007/S13593-022-00764-W
Abstract: Cropping of rice and wheat ( Triticum aestivum L .) in rotation contiguously in the same field is a fundamental pillar of double-cropping systems in southern China. Yields of such cropping systems are increasingly challenged as climate change (CC) drives increases in autumnal rainfall, delaying rice harvesting and subsequent sowing of wheat. Here, our purpose was to identify prospective traits of wheat crops enabling adaptation to later sowing and successively truncated growing seasons caused by CC. To identify traits that maintained or improved yields, we constructed 4,096 hypothetical genotypes underpinned by step-wise variations in parameters regulating phenology, growth and yield components. We then assimilated biophysical response surfaces through genotype (G) by environment (E) by management (M) analyses (G×E×M) using six locations spread across the breadth of southern China. We showed that later sowing reduced cumulative radiation interception, cumulative thermal time and crop capture of growing season rainfall. The culmination of these factors shortened crop duration and decreased biomass accumulation and retranslocation after anthesis, reducing grain number and penalising yields. Genotypes that had greater radiation use efficiency, longer juvenile phases and greater grain filling rates were more effective in alleviating yield losses with delayed sowing. However, not even the highest yielding genotype × management combination could entirely alleviate yield losses with delayed sowing. Our results suggest that CC and increasingly frequent extreme climatic events may reduce wheat yields in such cropping systems in the absence of other adaptation.
Whole-farm system models in practice: diverse applications
Publisher: Burleigh Dodds Science Publishing
Date: 03-12-2019
Improving wheat simulation capabilities in Australia from a cropping systems perspective III. The integrated wheat model (I_WHEAT)
Publisher: Elsevier BV
Date: 1998
Identification of new QTL for salt tolerance from rice variety Pokkali
Publisher: Wiley
Date: 06-01-2020
DOI: 10.1111/JAC.12387
The impact of extreme climatic events on pasture-based dairy systems: a review
Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/CP16394
Abstract: Extreme climatic events such as heat waves, extreme rainfall and prolonged dry periods are a significant challenge to the productivity and profitability of dairy systems. Despite projections of more frequent extreme events, increasing temperatures and reduced precipitation, studies on the impact of these extreme climatic events on pasture-based dairy systems remain uncommon. The Intergovernmental Panel on Climate Change has estimated Australia to be one of the most negatively impacted regions with additional studies estimating Australian production losses of around 16% in the agricultural sector and 9–19% between the present and 2050 in the south-eastern dairy regions of Australia due to climate change. Here we review the literature on the impact of climate change on pasture-based dairy systems with particular focus on extreme climatic events. We provide an insight into current methods for assessing and quantifying heat stress highlighting the impacts on pastures and animals including the associated potential productivity losses and conclude by outlining potential adaptation strategies for improving the resilience of the whole-farm systems to climate change. Adapting milking routines, calving systems and the introduction of heat stress tolerant dairy cow breeds are some proposed strategies. Changes in pasture production would also include alternative pasture species better adapted to climate extremes such as heat waves and prolonged periods of water deficit. In order to develop effective adaptation strategies we also need to focus on issues such as water availability, animal health and associated energy costs.
EVALUATION OF RADIATION AND TEMPERATURE DATA GENERATORS IN THE AUSTRALIAN TROPICS AND SUBTROPICS USING CROP SIMULATION-MODELS
Publisher: Elsevier BV
Date: 1995
Adaptive irrigation infrastructure — linking insights from human-water interactions and adaptive pathways
Publisher: Elsevier BV
Date: 10-2019
The Potential Value of Seasonal Climate Forecasting in Managing Cropping Systems
Publisher: Springer Netherlands
Date: 2000
Farmers’ views on the future prospects of aerobic rice culture in Pakistan
Publisher: Elsevier BV
Date: 2015
A regulator of early flowering in barley (Hordeum vulgare L.)
Publisher: Public Library of Science (PLoS)
Date: 17-07-2018
Modelling global change impacts on wheat cropping in south-east Queensland, Australia
Publisher: Elsevier BV
Date: 1999
Assessing the sustainability of wheat-based cropping systems using APSIM: model parameterisation and evaluation
Publisher: CSIRO Publishing
Date: 2007
DOI: 10.1071/AR06186
Abstract: Assessing the sustainability of crop and soil management practices in wheat-based rotations requires a well-tested model with the demonstrated ability to sensibly predict crop productivity and changes in the soil resource. The Agricultural Production Systems Simulator (APSIM) suite of models was parameterised and subsequently used to predict biomass production, yield, crop water and nitrogen (N) use, as well as long-term soil water and organic matter dynamics in wheat/chickpea systems at Tel Hadya, north-western Syria. The model satisfactorily simulated the productivity and water and N use of wheat and chickpea crops grown under different N and/or water supply levels in the 1998–99 and 1999–2000 experimental seasons. Analysis of soil-water dynamics showed that the 2-stage soil evaporation model in APSIM’s cascading water-balance module did not sufficiently explain the actual soil drying following crop harvest under conditions where unused water remained in the soil profile. This might have been related to evaporation from soil cracks in the montmorillonitic clay soil, a process not explicitly simulated by APSIM. Soil-water dynamics in wheat–fallow and wheat–chickpea rotations (1987–98) were nevertheless well simulated when the soil water content in 0–0.45 m soil depth was set to ‘air dry’ at the end of the growing season each year. The model satisfactorily simulated the amounts of NO3-N in the soil, whereas it underestimated the amounts of NH4-N. Ammonium fixation might be part of the soil mineral-N dynamics at the study site because montmorillonite is the major clay mineral. This process is not simulated by APSIM’s nitrogen module. APSIM was capable of predicting long-term trends (1985–98) in soil organic matter in wheat–fallow and wheat–chickpea rotations at Tel Hadya as reported in literature. Overall, results showed that the model is generic and mature enough to be extended to this set of environmental conditions and can therefore be applied to assess the sustainability of wheat–chickpea rotations at Tel Hadya.
Weather, climate, and farmers: an overview.
Publisher: Wiley
Date: 12-2006
What risk? I don't understand. An Empirical Study on Users' Understanding of the Terms Used in Security Texts
Publisher: ACM
Date: 05-10-2020
Learning Influence Probabilities and Modelling Influence Diffusion in Twitter
Publisher: ACM
Date: 13-05-2019
A two-step approach to quantify photothermal effects on pre-flowering rice phenology
Publisher: Elsevier BV
Date: 2014
Potential soil water extraction by sunflower on a range of soils
Publisher: Elsevier BV
Date: 02-1993
Analyzing social media data
Publisher: Springer Science and Business Media LLC
Date: 02-04-2019
DOI: 10.3758/S13428-019-01202-8
Abstract: To qualitative researchers, social media offers a novel opportunity to harvest a massive and erse range of content without the need for intrusive or intensive data collection procedures. However, performing a qualitative analysis across a massive social media data set is cumbersome and impractical. Instead, researchers often extract a subset of content to analyze, but a framework to facilitate this process is currently lacking. We present a four-phased framework for improving this extraction process, which blends the capacities of data science techniques to compress large data sets into smaller spaces, with the capabilities of qualitative analysis to address research questions. We demonstrate this framework by investigating the topics of Australian Twitter commentary on climate change, using quantitative (non-negative matrix inter-joint factorization topic alignment) and qualitative (thematic analysis) techniques. Our approach is useful for researchers seeking to perform qualitative analyses of social media, or researchers wanting to supplement their quantitative work with a qualitative analysis of broader social context and meaning.
SOI PHASES AND CLIMATIC RISK TO PEANUT PRODUCTION: A CASE STUDY FOR NORTHERN AUSTRALIA
Publisher: Wiley
Date: 07-1996
DOI: 10.1002/(SICI)1097-0088(199607)16:7<783::AID-JOC58>3.0.CO;2-D
The Sustainability of Organic Grain Production on the Canadian Prairies—A Review
Publisher: Apple Academic Press
Date: 05-04-2016
DOI: 10.1201/B19837-19
Genetic factors increasing barley grain yields under soil waterlogging
Publisher: Wiley
Date: 08-08-2020
DOI: 10.1002/FES3.238
Agronomical, biochemical and histological response of resistant and susceptible wheat and barley under BYDV stress
Publisher: PeerJ
Date: 28-05-2018
DOI: 10.7717/PEERJ.4833
Abstract: Barley yellow dwarf virus-PAV (BYDV-PAV) is one of the major viruses causing a widespread and serious viral disease affecting cereal crops. To gain a better understanding of plant defence mechanisms of BYDV resistance genes ( Bdv2 and RYd2 ) against BYDV-PAV infection, the differences in agronomical, biochemical and histological changes between susceptible and resistant wheat and barley cultivars were investigated. We found that root growth and total dry matter of susceptible cultivars showed greater reduction than that of resistant ones after infection. BYDV infected leaves in susceptible wheat and barley cultivars showed a significant reduction in photosynthetic pigments, an increase in the concentration of reducing sugar. The protein levels were also low in infected leaves. There was a significant increase in total phenol contents in resistant cultivars, which might reflect a protective mechanism of plants against virus infection. In phloem tissue, sieve elements (SE) and companion cells (CC) were severely damaged in susceptible cultivars after infection. It is suggested that restriction of viral movement in the phloem tissue and increased production of phenolic compounds may play a role in the resistance and defensive mechanisms of both Bdv2 and RYd2 against virus infection.
Modelling crop growth and yield under the environmental changes induced by windbreaks 1. Model development and validation
Publisher: CSIRO Publishing
Date: 2002
DOI: 10.1071/EA02019
Abstract: Yield advantages of crops grown behind windbreaks have often been reported, but underlying principles responsible for such changes and their long-term consequences on crop productivity and hence farm income have rarely been quantified. Physiologically and physically sound simulation models could help to achieve this quantification. Hence, the APSIM systems model, which is based on physiological principles such as transpiration efficiency and radiation use efficiency (termed here APSIMTE), and the Soil Canopy Atmosphere Model (SCAM), which is based on the Penman–Monteith equation but includes a full surface energy balance, were employed in developing an approach to quantify such windbreak effects. This resulted in a modified APSIM version (APSIMEO), containing the original Penman equation and a calibration factor to account for crop- and site-specific differences, which were tested against field data and simulations from both the standard APSIMTE and SCAM models. The APSIMEO approach was tested against field data for wheat and mungbean grown in artificial enclosures in south-east Queensland and in south-east Western Australia. For these sheltered conditions, daily transpiration demand estimates from APSIMEO compared closely to SCAM. As the APSIMEO approach needed to be calibrated for in idual crops and environments, average transpiration demand for open field conditions predicted by APSIMEO for a given site was adjusted to equal that obtained using APSIMTE by modifying a calibration parameter β. For wheat, a β-value of 1.0 resulted in best fits for Queensland, while for Western Australia a value of 0.85 was necessary. For mungbean a value of 0.92 resulted in the best fit (Qld). Biomass and yields simulated by APSIMTE and the calibration APSIMEO for wheat and mungbean grown in artificial enclosures were generally distributed around the 1:1 line, with R2 values ranging from 0.92 to 0.97. Finally, APSIMEO was run at 2 sites using long-term climate data to assess the likely year-to-year variability of windbreak effects on crop yields. Assuming a 70% reduction in wind speed as representing the maximum potential windbreak effect, the average yield improvement for the Queensland site was 13% for wheat and 3% for mungbean. For wheat at the WA site the average yield improvement from reduced wind speed was 5%. In any year, however, effects varied from negative, neutral to positive, highlighting the highly variable nature of the expression of windbreak effects. This study has shown how physical and biological modelling approaches can be combined to aid our understanding of systems processes. Both the environmental physics perspective and the biological perspective have shortcomings when issues that sit at the interface of both approaches need to be addressed. While the physical approach has clear advantages when investigating changes in physical parameters such as wind speed, vapour pressure deficit (VPD), temperature or the energy balance of the soil–plant–atmosphere continuum, it cannot deal with complex, biological systems adequately. Conversely, the crop physiological approach can handle such biological interactions in a scientific and robust way while certain atmospheric processes are not considered. The challenge was not to try and capture all these effects in 1 model, but rather to structure a modelling approach in a way that allowed for inclusion of such processes where necessary.
Yield formation and tillering dynamics of direct-seeded rice in flooded and nonflooded soils in the Huai River Basin of China
Publisher: Elsevier BV
Date: 04-2010
Labour productivity: The forgotten yield gap
Publisher: Elsevier BV
Date: 08-2022
Rice in cropping systems—Modelling transitions between flooded and non-flooded soil environments
Publisher: Elsevier BV
Date: 05-2012
Increasing profits and reducing risks in crop production using participatory systems simulation approaches
Publisher: Elsevier BV
Date: 11-2001
Modelling the role of algae in rice crop nutrition and soil organic carbon maintenance
Publisher: Elsevier BV
Date: 05-2012
Food engineering strategies for sustainable food supply chains: Interdisciplinarity is the key
Publisher: Elsevier BV
Date: 05-2022
Cropping systems strategy for effective management of Fusarium wilt in safflower
Publisher: Elsevier BV
Date: 02-2014
Effect of climate variability on event frequency of sorghum ergot in Australia
Publisher: CSIRO Publishing
Date: 2003
DOI: 10.1071/AR02198
Abstract: The significant effect of ergot, caused by Claviceps africana, on the Australian sorghum industry, has led to considerable research on the identification of resistant genotypes and on the climatic conditions that are conducive to ergot outbreaks. Here we show that the potential number of monthly ergot events differs strongly from year to year in accordance with ENSO (El Niño–Southern Oscillation)-related climate variability. The analysis is based on long-term weather records from 50 locations throughout the sorghum-growing areas of Australia and predicts the potential number of monthly ergot events based on phases of the Southern Oscillation Index (SOI). For a given location, we found a significant difference in the number of potential ergot events based on SOI phases in the preceding month, with a consistently positive SOI phase providing the greatest risk for the occurrence of ergot for most months and locations. This analysis provides a relative risk assessment for ergot outbreaks based on location and prevailing climatic conditions, thereby assisting in responsive decision-making to reduce the negative effect of sorghum ergot.
Adaptation science for agriculture and natural resource management — urgency and theoretical basis
Publisher: Elsevier BV
Date: 10-2009
TE- and TM-waves in waveguides of very general cross section
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1963
Assessing the sustainability of wheat-based cropping systems using simulation modelling: sustainability = 42?
Publisher: Springer Science and Business Media LLC
Date: 05-10-2013
Eco‐efficient Agriculture: Concepts, Challenges, and Opportunities
Publisher: Wiley
Date: 03-2010
Genome wide association study reveals novel QTL for barley yellow dwarf virus resistance in wheat
Publisher: Springer Science and Business Media LLC
Date: 21-11-2019
DOI: 10.1186/S12864-019-6249-1
Abstract: Barley yellow dwarf (BYD) is an important virus disease that causes significant reductions in wheat yield. For effective control of Barley yellow dwarf virus through breeding, the identification of genetic sources of resistance is key to success. In this study, 335 geographically erse wheat accessions genotyped using an Illumina iSelect 90 K single nucleotide polymorphisms (SNPs) bead chip array were used to identify new sources of resistance to BYD in different environments. A genome-wide association study (GWAS) performed using all the generalised and mixed linkage models (GLM and MLM, respectively) identified a total of 36 significant marker-trait associations, four of which were consistently detected in the K model. These four novel quantitative trait loci (QTL) were identified on chromosomes 2A, 2B, 6A and 7A and associated with markers IWA3520, IWB24938, WB69770 and IWB57703, respectively. These four QTL showed an additive effect with the average visual symptom score of the lines containing resistance alleles of all four QTL being much lower than those with less favorable alleles. Several Chinese landraces, such as H-205 (Baimazha) and H-014 (Dahongmai) which have all four favorable alleles, showed consistently higher resistance in different field trials. None of them contained the previously described Bdv2, Bdv3 or Bdv4 genes for BYD resistance. This study identified multiple novel QTL for BYD resistance and some resistant wheat genotypes. These will be useful for breeders to generate combinations with and/or without Bdv2 to achieve higher levels and more stable BYD resistance.
An overview of APSIM, a model designed for farming systems simulation
Publisher: Elsevier BV
Date: 2003
Microhair on the adaxial leaf surface of salt secreting halophytic Oryza coarctata Roxb. show distinct morphotypes: Isolation for molecular and functional analysis
Publisher: Elsevier BV
Date: 08-2019
DOI: 10.1016/J.PLANTSCI.2019.05.004
Abstract: Halophytic Oryza coarctata is a good model system to examine mechanisms of salinity tolerance in rice. O. coarctata leaves show the presence of microhairs in adaxial leaf surface furrows that secrete salt under salinity. However, detailed molecular and physiological studies of O. coarctata microhairs are limited due to their relative inaccessibility. This work presents a detailed characterization of O. coarctata leaf features. O. coarctata has two types of microhairs on the adaxial leaf surface: longer microhairs (three morphotypes) lining epidermal furrow walls and shorter microhairs (reported first time) arising from bulliform cells. Microhair morphotypes include (i) finger-like, tubular structures, (ii) tubular hairs with bilobed and flattened heads and (iii) bi-or trifurcated hairs. The unicellular nature of microhairs was confirmed by propidium iodide (PI) staining. An efficient method for the isolation and enrichment of O. coarctata microhairs is presented (yield averaging ˜2 × 10
Comparing water options for irrigation farmers using Modern Portfolio Theory
Publisher: Elsevier BV
Date: 12-2012
Climate Forecast for Better Water Management in Agriculture: A Case Study for Southern India
Publisher: Springer Berlin Heidelberg
Date: 2007
Tracking the Evolution of Clusters in Social Media Streams
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2023
A Sunflower Simulation Model: I. Model Development
Publisher: Wiley
Date: 05-1993
Crop traits enabling yield gains under more frequent extreme climatic events
Publisher: Elsevier BV
Date: 02-2022
DOI: 10.1016/J.SCITOTENV.2021.152170
Abstract: Climate change (CC) in central China will change seasonal patterns of agricultural production through increasingly frequent extreme climatic events (ECEs). Breeding climate-resilient wheat (Triticum aestivum L.) genotypes may mitigate adverse effects of ECEs on crop productivity. To reveal crop traits conducive to long-term yield improvement in the target population of environments, we created 8,192 virtual genotypes with contrasting but realistic ranges of phenology, productivity and waterlogging tolerance. Using these virtual genotypes, we conducted a genotype (G) by environment (E) by management (M) factorial analysis (G×E×M) using locations distributed across the entire cereal cropping zone in mid-China. The G×E×M invoked locally-specific sowing dates under future climates that were premised on shared socioeconomic pathways SSP5-8.5, with a time horizon centred on 2080. Across the simulated adaptation landscape, productivity was primarily driven by yield components and phenology (average grain yield increase of 6-69% across sites with optimal combinations of these traits). When incident solar radiation was not limiting carbon assimilation, ideotypes with higher grain yields were characterised by earlier flowering, higher radiation-use efficiency and larger maximum kernel size. At sites with limited solar radiation, crops required longer growing periods to realise genetic yield potential, although higher radiation-use efficiency and larger maximum kernel size were again prospective traits enabling higher rates of yield gains. By 2080, extreme waterlogging stress in some regions of mid-China will impact substantially on productivity, with yield penalties of up to 1,010 kg ha
Plant neurobiology and green plant intelligence: science, metaphors and nonsense
Publisher: Wiley
Date: 11-12-2007
DOI: 10.1002/JSFA.3131
Towards delivering on the sustainable development goals in greenhouse production systems
Publisher: Elsevier BV
Date: 06-2021
The State of the Art in Modeling Waterlogging Impacts on Plants: What Do We Know and What Do We Need to Know
Publisher: American Geophysical Union (AGU)
Date: 12-2020
DOI: 10.1029/2020EF001801
Three Putative Types of El Niño Revealed by Spatial Variability in Impact on Australian Wheat Yield
Publisher: American Meteorological Society
Date: 15-05-2005
DOI: 10.1175/JCLI3349.1
Abstract: The El Niño–Southern Oscillation (ENSO) phenomenon significantly impacts rainfall and ensuing crop yields in many parts of the world. In Australia, El Niño events are often associated with severe drought conditions. However, El Niño events differ spatially and temporally in their manifestations and impacts, reducing the relevance of ENSO-based seasonal forecasts. In this analysis, three putative types of El Niño are identified among the 24 occurrences since the beginning of the twentieth century. The three types are based on coherent spatial patterns (“footprints”) found in the El Niño impact on Australian wheat yield. This bioindicator reveals aligned spatial patterns in rainfall anomalies, indicating linkage to atmospheric drivers. Analysis of the associated ocean–atmosphere dynamics identifies three types of El Niño differing in the timing of onset and location of major ocean temperature and atmospheric pressure anomalies. Potential causal mechanisms associated with these differences in anomaly patterns need to be investigated further using the increasing capabilities of general circulation models. Any improved predictability would be extremely valuable in forecasting effects of in idual El Niño events on agricultural systems.
Actionable climate knowledge: from analysis to synthesis
Publisher: Inter-Research Science Center
Date: 21-12-2006
DOI: 10.3354/CR033101
From inferential statistics to climate knowledge
Publisher: Copernicus GmbH
Date: 14-02-2006
Abstract: Abstract. Climate variability and change are risk factors for climate sensitive activities such as agriculture. Managing these risks requires "climate knowledge", i.e. a sound understanding of causes and consequences of climate variability and knowledge of potential management options that are suitable in light of the climatic risks posed. Often such information about prognostic variables (e.g. yield, rainfall, run-off) is provided in probabilistic terms (e.g. via cumulative distribution functions, CDF), whereby the quantitative assessments of these alternative management options is based on such CDFs. Sound statistical approaches are needed in order to assess whether difference between such CDFs are intrinsic features of systems dynamics or chance events (i.e. quantifying evidences against an appropriate null hypothesis). Statistical procedures that rely on such a hypothesis testing framework are referred to as "inferential statistics" in contrast to descriptive statistics (e.g. mean, median, variance of population s les, skill scores). Here we report on the extension of some of the existing inferential techniques that provides more relevant and adequate information for decision making under uncertainty.
Effects of sorghum ergot on grain sorghum production: a preliminary climatic analysis
Publisher: CSIRO Publishing
Date: 1997
DOI: 10.1071/A96164
Abstract: Until 1996 the disease ‘sorghum ergot’ (Claviceps africana and Claviceps sorghi) was unknown in Australia. Following an outbreak near Gatton, the disease was found throughout most of the sorghum-producing areas in Queensland within 4 weeks. A climatic risk analysis was conducted to assess the likely timing and frequencies of further outbreaks of the disease across the main sorghum-producing regions of Australia. Based on the information available, likely conditions that could lead to a disease outbreak were formulated and a computer program developed to interrogate an existing database of long-term, daily weather records. Case studies were conducted for 10 key sorghum-producing locations, ranging from Narromine in central New South Wales to Mareeba in far North Queensland and Kununurra in Western Australia. For grain sorghum production, crops flowering in January and February are unlikely to be affected, regardless of location. However, in up to 30% of years, late-sown grain sorghum crops and crops flowering before January could be affected, depending on climatic conditions prior to and around anthesis. The frequency and timing of these events differed strongly temporally and spatially and appeared highest in high rainfall years and in regions with relatively cooler temperatures and more frequent autumn rains. Hybrid seed production (i.e. breeding programs) and forage sorghum production are likely to be more affected due to their inherently low pollen generation, again with strong regional variation. Further applications of the methodology, such as the development of an early warning system, based on phases of the Southern Oscillation Index, are discussed.
Assessing temperature‐based adaptation limits to climate change of temperate perennial fruit crops
Publisher: Wiley
Date: 16-02-2023
DOI: 10.1111/GCB.16601
Abstract: Temperate perennial fruit and nut trees play varying roles in world food ersity—providing edible oils and micronutrient, energy, and protein dense foods. In addition, perennials reuse significant amounts of biomass each year providing a unique resilience. But they also have a unique sensitivity to seasonal temperatures, requiring a period of dormancy for successful growing season production. This paper takes a global view of five temperate tree fruit crops—apples, cherries, almonds, olives, and grapes—and assesses the effects of future temperature changes on thermal suitability. It uses climate data from five earth system models for two CMIP6 climate scenarios and temperature‐related indices of stress to indicate potential future areas where crops cannot be grown and highlight potential new suitable regions. The loss of currently suitable areas and new additions in new locations varies by scenario. In the southern hemisphere (SH), end‐century (2081–2100) suitable areas under the SSP 5–8.5 scenario decline by more than 40% compared to a recent historical period (1991–2010). In the northern hemisphere (NH) suitability increases by 20% to almost 60%. With SSP1‐2.6, however, the changes are much smaller with SH area declining by about 25% and NH increasing by about 10%. The results suggest substantial restructuring of global production for these crops. Essentially, climate change shifts temperature‐suitable locations toward higher latitudes. In the SH, most of the historically suitable areas were already at the southern end of the landmass limiting opportunities for adaptation. If breeding efforts can bring chilling requirements for the major cultivars closer to that currently seen in some cultivars, suitable areas at the end of the century are greater, but higher summer temperatures offset the extent. The high value of fruit crops provides adaptation opportunities such as cultivar selection, canopy cooling using sprinklers, shade netting, and precision irrigation.
Challenges in assessing the regional feasibility of local water storage
Publisher: Informa UK Limited
Date: 16-09-2019
Adapting agriculture to climate change
Publisher: Proceedings of the National Academy of Sciences
Date: 11-12-2007
Abstract: The strong trends in climate change already evident, the likelihood of further changes occurring, and the increasing scale of potential climate impacts give urgency to addressing agricultural adaptation more coherently. There are many potential adaptation options available for marginal change of existing agricultural systems, often variations of existing climate risk management. We show that implementation of these options is likely to have substantial benefits under moderate climate change for some cropping systems. However, there are limits to their effectiveness under more severe climate changes. Hence, more systemic changes in resource allocation need to be considered, such as targeted ersification of production systems and livelihoods. We argue that achieving increased adaptation action will necessitate integration of climate change-related issues with other risk factors, such as climate variability and market risk, and with other policy domains, such as sustainable development. Dealing with the many barriers to effective adaptation will require a comprehensive and dynamic policy approach covering a range of scales and issues, for ex le, from the understanding by farmers of change in risk profiles to the establishment of efficient markets that facilitate response strategies. Science, too, has to adapt. Multidisciplinary problems require multidisciplinary solutions, i.e., a focus on integrated rather than disciplinary science and a strengthening of the interface with decision makers. A crucial component of this approach is the implementation of adaptation assessment frameworks that are relevant, robust, and easily operated by all stakeholders, practitioners, policymakers, and scientists.
Rainfall Variability at Decadal and Longer Time Scales: Signal or Noise?
Publisher: American Meteorological Society
Date: 2005
DOI: 10.1175/JCLI-3263.1
Abstract: Rainfall variability occurs over a wide range of temporal scales. Knowledge and understanding of such variability can lead to improved risk management practices in agricultural and other industries. Analyses of temporal patterns in 100 yr of observed monthly global sea surface temperature and sea level pressure data show that the single most important cause of explainable, terrestrial rainfall variability resides within the El Niño–Southern Oscillation (ENSO) frequency domain (2.5–8.0 yr), followed by a slightly weaker but highly significant decadal signal (9–13 yr), with some evidence of lesser but significant rainfall variability at interdecadal time scales (15–18 yr). Most of the rainfall variability significantly linked to frequencies lower than ENSO occurs in the Australasian region, with smaller effects in North and South America, central and southern Africa, and western Europe. While low-frequency (LF) signals at a decadal frequency are dominant, the variability evident was ENSO-like in all the frequency domains considered. The extent to which such LF variability is (i) predictable and (ii) either part of the overall ENSO variability or caused by independent processes remains an as yet unanswered question. Further progress can only be made through mechanistic studies using a variety of models.
A Sunflower Simulation Model: II. Simulating Production Risks in a Variable Sub‐Tropical Environment
Publisher: Wiley
Date: 07-1927
Stochastic Model for Simulating Maize Yield
Publisher: American Society of Agricultural and Biological Engineers (ASABE)
Date: 2012
DOI: 10.13031/2013.41498
A screening method to detect BYDV ‐PAV resistance in cereals under glasshouse conditions
Publisher: Wiley
Date: 25-06-2018
DOI: 10.1111/PPA.12888
Assessing exceptional drought with a cropping systems simulator: a case study for grain production in northeast Australia
Publisher: Elsevier BV
Date: 07-1998
Assessing Social License to Operate from the Public Discourse on Social Media
Publisher: International Committee on Computational Linguistics
Date: 2020
Near-global impact of the Madden-Julian Oscillation on rainfall
Publisher: American Geophysical Union (AGU)
Date: 05-2006
DOI: 10.1029/2005GL025155
Recognising Agreement and Disagreement between Stances with Reason Comparing Networks
Publisher: Association for Computational Linguistics
Date: 2019
DOI: 10.18653/V1/P19-1460
Probabilistic methods for seasonal forecasting in a changing climate: Cox‐type regression models
Publisher: Wiley
Date: 25-11-2010
DOI: 10.1002/JOC.2042
Negative relationship between dry matter intake and the temperature-humidity index with increasing heat stress in cattle: a global meta-analysis
Publisher: Springer Science and Business Media LLC
Date: 20-07-2021
DOI: 10.1007/S00484-021-02167-0
Abstract: Changes in frequency and severity of heat waves due to climate change pose a considerable challenge to livestock production systems. Although it is well known that heat stress reduces feed intake in cattle, effects of heat stress vary between animal genotypes and climatic conditions and are context specific. To derive a generic global prediction that accounts for the effects of heat stress across genotypes, management and environments, we conducted a systematic literature review and a meta-analysis to assess the relationship between dry matter intake ( DMI ) and the temperature-humidity index ( THI ), two reliable variables for the measurement of feed intake and heat stress in cattle, respectively. We analysed this relationship accounting for covariation in countries, breeds, lactation stage and parity, as well as the efficacy of various physical cooling interventions. Our findings show a significant negative correlation ( r = − 0.82) between THI and DMI , with DMI reduced by 0.45 kg/day for every unit increase in THI . Although differences in the DMI - THI relationship between lactating and non-lactating cows were not significant, effects of THI on DMI varied between lactation stages. Physical cooling interventions (e.g. provision of animal shade or shelter) significantly alleviated heat stress and became increasingly important after THI 68, suggesting that this THI value could be viewed as a threshold for which cooling should be provided. Passive cooling (shading) was more effective at alleviating heat stress compared with active cooling interventions (sprinklers). Our results provide a high-level global equation for THI-DMI across studies, allowing next-users to predict effects of heat stress across environments and animal genotypes.
Molecular mechanisms of salinity tolerance in rice
Publisher: Elsevier BV
Date: 06-2021
Towards groundwater neutral cropping systems in the Alluvial Fans of the North China Plain
Publisher: Elsevier BV
Date: 02-2016
Tasmania’s bio-economy
Publisher: Springer International Publishing
Date: 2017
Prediction of sorghum downy mildew risk in Australia using daily weather data
Publisher: Springer Science and Business Media LLC
Date: 2000
DOI: 10.1071/AP00019
Using similarity measures to select pretraining data for NER
Publisher: Association for Computational Linguistics
Date: 2019
DOI: 10.18653/V1/N19-1149
Impacts of the Madden-Julian oscillation on australian rainfall and circulation
Publisher: American Meteorological Society
Date: 15-03-2009
Abstract: Impacts of the Madden–Julian oscillation (MJO) on Australian rainfall and circulation are examined during all four seasons. The authors examine circulation anomalies and a number of different rainfall metrics, each composited contemporaneously for eight MJO phases derived from the real-time multivariate MJO index. Multiple rainfall metrics are examined to allow for greater relevance of the information for applications. The greatest rainfall impact of the MJO occurs in northern Australia in (austral) summer, although in every season rainfall impacts of various magnitude are found in most locations, associated with corresponding circulation anomalies. In northern Australia in all seasons except winter, the rainfall impact is explained by the direct influence of the MJO’s tropical convective anomalies, while in winter a weaker and more localized signal in northern Australia appears to result from the modulation of the trade winds as they impinge upon the eastern coasts, especially in the northeast. In extratropical Australia, on the other hand, the occurrence of enhanced (suppressed) rainfall appears to result from induced upward (downward) motion within remotely forced extratropical lows (highs), and from anomalous low-level northerly (southerly) winds that transport moisture from the tropics. Induction of extratropical rainfall anomalies by remotely forced lows and highs appears to operate mostly in winter, whereas anomalous meridional moisture transport appears to operate mainly in the summer, autumn, and to some extent in the spring.
Developing rural community health risk assessments for climate change: a Tasmanian pilot study
Publisher: Rural and Remote Health
Date: 22-09-2015
DOI: 10.22605/RRH3174
Deep Multi-Attributed-View Graph Representation Learning
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Development and use of a barley crop simulation model to evaluate production management strategies in north-eastern Australia
Publisher: CSIRO Publishing
Date: 1996
DOI: 10.1071/AR9960997
Abstract: A study was undertaken to identify improved management strategies for barley (Hordeum vulgare L.), particularly in relation to time of planting, location, and frost risk in the variable climate of north-eastern Australia. To achieve this objective, a crop growth simulation model (QBAR) was constructed to integrate the understanding, gained from field experiments, of the dynamics of crop growth as influenced by soil moisture and environmental variables. QBAR simulates the growth and yield potential of barley grown under optimal nutrient supply, in the absence of pests, diseases, and weeds. Genotypic variables have been determined for 4 cultivars commonly grown in the northern cereal production areas. Simulations were conducted using long-term weather data to generate the probabilistic yield outcome of cv. Grimmet for a range of times of planting at 10 locations in the north-eastern Australian grain belt. The study indicated that the common planting times used by growers could be too late under certain circumstances to gain full yield potential. Further applications of QBAR to generating information suitable for crop management decision support packages and crop yield forecasting are discussed.
Identification of New QTL Contributing to Barley Yellow Dwarf Virus-PAV (BYDV-PAV) Resistance in Wheat
Publisher: Scientific Societies
Date: 11-2019
DOI: 10.1094/PDIS-02-19-0271-RE
Abstract: Barley yellow dwarf (BYD) is a major virus disease which dramatically reduces wheat yield. Introducing BYD resistance genes into commercial varieties has been proven to be effective in reducing damage caused by barley yellow dwarf virus (BYDV). However, only one major resistance gene is readily deployable for breeding Bdv2 derived from Thinopyrum intermedium is deployed as a chromosomal translocation. In this study, a double haploid (DH) population was developed from a cross between XuBYDV (introduced from China showing very good resistance to BYD) and H-120 (a BYD-sensitive Chinese accession), and was used to identify QTL for BYD resistance. The population was genotyped using an Infinium iSelect bead chip array targeting 90K gene-based SNPs. The disease resistance of DH lines inoculated with BYDV was assessed at the heading stage. The infections were assessed by tissue blot immunoassay (TBIA). Three new QTL were identified on chromosomes 5A, 6A, and 7A for both symptom and TBIA, with all three resistance alleles being inherited from XuBYDV. Some DH lines with the resistance alleles from all three QTL showed high level resistance to BYD. These new QTL will be useful in breeding programs for pyramiding BYD resistance genes.
The impact of social ties and SARS memory on the public awareness of 2019 novel coronavirus (SARS‑CoV‑2) outbreak
Publisher: Springer Science and Business Media LLC
Date: 26-10-2020
DOI: 10.1038/S41598-020-75318-9
Abstract: This study examines publicly available online search data in China to investigate the spread of public awareness of the 2019 novel coronavirus (SARS-CoV-2) outbreak. We found that cities that had previously suffered from SARS (in 2003–04) and have greater migration ties to Wuhan had earlier, stronger and more durable public awareness of the outbreak. Our data indicate that 48 such cities developed awareness up to 19 days earlier than 255 comparable cities, giving them an opportunity to better prepare. This study suggests that it is important to consider memory of prior catastrophic events as they will influence the public response to emerging threats.
The vulnerability of Australian rural communities to climate variability and change: Part I—Conceptualising and measuring vulnerability
Publisher: Elsevier BV
Date: 02-2010
A Peanut Simulation Model: II. Assessing Regional Production Potential
Publisher: Wiley
Date: 11-1995
Impacts of climate change and climate variability on the competitiveness of wheat and beef cattle production in Emerald, north-east Australia
Publisher: Elsevier BV
Date: 09-2001
DOI: 10.1016/S0160-4120(01)00076-9
Abstract: Emerald, north-east Queensland, is at the northern margin of the wheat cropping region of Australia. The Emerald region was previously used predominantly for grazing beef cattle however, cropping has developed in importance over the past 30 years. We use historical climate records (1890-1998) to simulate and compare wheat yields, grass production and live-weight gain (LWG) over time. The cropping expansion from the 1970s to the early 1990s has occurred in a unique period in the 108-year record with the highest average wheat yields, lowest wheat yield variability and the greatest relative productivity of wheat production against grass production. If this window of opportunity is a result of long-term climate variability, then cropping is likely to decline in the region as conditions return to those experienced earlier in the record. If this increase is related to climate change, then cropping is likely to persist in the region with productivity maintained at current levels particularly through the yield-enhancing effects of increased atmospheric CO2 concentrations. However, this persistence will be influenced by the frequencies of El Niño conditions that may increase with global warming. The high relative productivities experienced over the past few decades have probably biased producers' expectations, and applications for drought support need to take into account the longer-term perspective provided by this analysis. Nevertheless, the last 6 years have the lowest simulated mean LWG production on the record. The identification of poor production periods depended on the production element being addressed and the timescale involved.
The interface between land use systems research and policy: Multiple arrangements and leverages
Publisher: Elsevier BV
Date: 04-2009
The vulnerability of Australian rural communities to climate variability and change: Part II—Integrating impacts with adaptive capacity
Publisher: Elsevier BV
Date: 02-2010
Improving wheat simulation capabilities in Australia from a cropping systems perspective: water and nitrogen effects on spring wheat in a semi-arid environment
Publisher: Elsevier BV
Date: 09-1997
Wild barley shows a wider diversity in genes regulating heading date compared with cultivated barley
Publisher: Springer Science and Business Media LLC
Date: 16-03-2019
Contingency planning for drought — a case study in coping with agrometeorological risks and uncertainties
Publisher: Springer Berlin Heidelberg
Date: 2007
Challenges for weed management in African rice systems in a changing climate
Publisher: Cambridge University Press (CUP)
Date: 25-02-2011
DOI: 10.1017/S0021859611000207
Abstract: Global changes including increases in temperature, atmospheric greenhouse gases, soil degradation and competition for land and water resources, will have multiple impacts on rice production systems in Africa. These changes will affect weed communities, and management approaches must be adapted to take this into account. Higher temperatures and limited water availability will generally advantage C 4 over C 3 plants (e.g. rice). Conversely, elevated carbon dioxide (CO 2 ) levels will improve the competitiveness of rice relative to C 4 weeds, which comprise many of the problem weeds of rice. Increased atmospheric CO 2 levels may also improve tolerance of rice against parasitic weeds, while prevalence of parasitic species may be lified by soil degradation and more frequent droughts or floods. Elevated CO 2 levels tend to promote growth below-ground relative to above-ground, particularly in perennial (C 3 ) species. This may render mechanical control of weeds within a cropping season less effective or even counterproductive. Increased CO 2 levels, rainfall and temperature may also reduce the effectiveness of chemical control, while the implementation of adaptation technologies, such as water-saving irrigation regimes, will have negative consequences for rice–weed competition. Rain-fed production systems are prevalent throughout Africa and these are likely to be most vulnerable to direct effects of climate change (e.g. higher temperatures and changes in rainfall patterns). Effective weed management strategies in these environments could encompass off-season tillage, the use of well-adapted cultivars (i.e. those with drought and heat tolerance, high weed competitiveness and parasitic weed resistance or tolerance) and rotations, intercropping or short, off-season fallows with weed-suppressive legumes including those that suppress parasitic weeds. In irrigated, non-flooded rice systems, weeds are expected to become more serious. Specifically, perennial rhizomatous C 3 weeds and species adapted to hydromorphic conditions are expected to increase in prevalence. By implementing an integrated weed management strategy primarily targeted at weed prevention, dependency on flood water, herbicides and mechanical control can be lessened. Off-season deep tillage, stale seed bed techniques, use of clean seeds and irrigation water, competitive cultivars, timely transplanting at optimum spacing and judicious fertilizer timings are suitable candidate components for such a strategy. Integrated, novel approaches must be developed to assist farmers in coping with the challenges of weed control in the future.
The role of modeling and systems thinking in contemporary agriculture
Publisher: Elsevier
Date: 2019
On tactical crop management using seasonal climate forecasts and simulation modelling: a case study for wheat
Publisher: FapUNIFESP (SciELO)
Date: 06-1997
DOI: 10.1590/S0103-90161997000300014
Abstract: The El Niño/Southern Oscillation phenomenon strongly influences rainfall distribution around the world. Using phases of the Southern Oscillation Index (SOI) allows a probabilistic forecast of future rainfall that can be useful to managers of agricultural systems. Using wheat as an ex le, we show in this study how the SOI phase system, when combined with a cropping systems simulation capability, can be used operationally to Improve tactical crop management and hence increase farm profits and/or decrease production risks. We show the validity of the approach for two contrasting locations, namely Dalby in Northern Australian and Piracicaba in Brazil At Dalby, highest median yields were achieved following a rapidly rising SOI phase in April/May and lowest median yields following a consistently negative phase. Conversely, highest median yields at Piracicaba followed a near zero April/May phase and lowest median yields when the phase was consistently positive. We show how tactical management options can range from crop or cultivar choice to nitrogen management and marketing of the future wheat crop.
Nitrogen availability, water-filled pore space, and N2O-N fluxes after biochar application and nitrogen fertilization
Publisher: FapUNIFESP (SciELO)
Date: 09-2016
DOI: 10.1590/S0100-204X2016000900020
Abstract: Abstract The objective of this work was to investigate the impact of the application of wood biochar, combined with N fertilizations, on N2O-N fluxes, nitrogen availability, and water-filled pore space (WFPS) of a clayey Oxisol under rice (wet season) and common bean (dry season) succession. Manual static chambers were used to quantify N2O-N fluxes from soil immediately after a single application of wood biochar (32 Mg ha-1) and after four crop seasons with N applications (90 kg ha-1 N). Soil ammonium (N-NH4+) and nitrate (N-NO3-) availability, as well as WFPS, was measured together with N2O-N fluxes. There was no interaction between biochar and N fertilization regarding N2O-N fluxes in any of the four seasons monitored, although these fluxes were clearly enhanced by N applications. At 1.5 and 2.5 years after biochar application, the WFPS decreased. In addition, in the seasons characterized by low WFPS, N2O-N fluxes and soil N-NO3- and N-NH4+ availability were enhanced after N applications. Long-term experiments in the field are important to quantify the impacts of biochar on N2O-N fluxes and to determine the dynamics of these fluxes on soil-related variables.
Resilience achieved via multiple compensating subsystems
Publisher: Elsevier BV
Date: 02-2021
Development of a generic crop model template in the cropping system model APSIM
Publisher: Elsevier BV
Date: 12-2002
Tissue-Specific Regulation of Na+ and K+ Transporters Explains Genotypic Differences in Salinity Stress Tolerance in Rice
Publisher: Frontiers Media SA
Date: 11-2019
Europe's diminishing bread basket
Publisher: Springer Science and Business Media LLC
Date: 25-06-2014
DOI: 10.1038/NCLIMATE2289
Seasonal and Inter-Annual Climate Forecasting: The New Tool for Increasing Preparedness to Climate Variability and Change In Agricultural Planning And Operations
Publisher: Springer Science and Business Media LLC
Date: 05-2005
Probabilistic forecasts of the onset of the north Australian wet season
Publisher: American Meteorological Society
Date: 10-2007
DOI: 10.1175/MWR3473.1
Abstract: The amount and timing of early wet-season rainfall are important for the management of many agricultural industries in north Australia. With this in mind, a wet-season onset date is defined based on the accumulation of rainfall to a predefined threshold, starting from 1 September, for each square of a 1° gridded analysis of daily rainfall across the region. Consistent with earlier studies, the interannual variability of the onset dates is shown to be well related to the immediately preceding July–August Southern Oscillation index (SOI). Based on this relationship, a forecast method using logistic regression is developed to predict the probability that onset will occur later than the climatological mean date. This method is expanded to also predict the probabilities that onset will be later than any of a range of threshold dates around the climatological mean. When assessed using cross-validated hindcasts, the skill of the predictions exceeds that of climatological forecasts in the majority of locations in north Australia, especially in the Top End region, Cape York, and central Queensland. At times of strong anomalies in the July–August SOI, the forecasts are reliably emphatic. Furthermore, predictions using tropical Pacific sea surface temperatures (SSTs) as the predictor are also tested. While short-lead (July–August predictor) forecasts are more skillful using the SOI, long-lead (May–June predictor) forecasts are more skillful using Pacific SSTs, indicative of the longer-term memory present in the ocean.
Barley Yellow Dwarf Viruses: Infection Mechanisms and Breeding Strategies
Publisher: Springer Science and Business Media LLC
Date: 10-07-2017
Managing Climatic Risks to Combat Land Degradation and Enhance Food security: Key Information Needs
Publisher: Elsevier BV
Date: 2010
Effects of Seasonal Climate Variability and the Use of Climate Forecasts on Wheat Supply in the United States, Australia, and Canada
Publisher: American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America
Date: 2001
Strategic double cropping on Vertisols: A viable rainfed cropping option in the Indian SAT to increase productivity and reduce risk
Publisher: Elsevier BV
Date: 2015
Harnessing Tweets for Early Detection of an Acute Disease Event
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 2020
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Related Funding Activities
Industrial Transformation Training Centres - Grant ID: IC140100024
Start Date: 05-2015
End Date: 09-2019
Amount: $2,061,605.00
Funder: Australian Research Council
View Funded Activity