Assessing temperature-based adaptation limits to climate change of temperate perennial fruit crops

Temperate perennial fruit and nut trees play varying roles in world food diversity-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.

Crop traits enabling yield gains under more frequent extreme climatic events

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^-1. Ideotypes with optimal G×M could mitigate yield penalty caused by waterlogging by up to 15% under future climates. These results help distil promising crop trait by best management practice combinations that enable higher yields and robust adaptation to future climates and more frequent extreme climatic events, including flash flooding and soil waterlogging.

Negative relationship between dry matter intake and the temperature-humidity index with increasing heat stress in cattle: a global meta-analysis

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.

Effects of soil- and climate data aggregation on simulated potato yield and irrigation water requirement

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_c) and soil (DAE_s) on irrigation water requirement (IWR) in cool-temperate and spatially heterogeneous environments. The aims of this study were to quantify DAE_c and DAE_s of model input data and their combined impacts for simulated irrigated and rainfed yield and IWR. The Agricultural Production Systems sIMulator Next Generation model was applied for the period 1998-2017 across areas suitable for potato (Solanum tuberosum L.) in Tasmania, Australia, using data at 5, 15, 25 and 40 km resolution. Spatial variances of inputs and outputs were evaluated by the relative absolute difference (rAD¯) between the aggregated grids and the 5 km grids. Climate data aggregation resulted in a rAD¯ of 0.7-12.1%, with high values especially for areas with pronounced differences in elevation. The rAD¯ of soil data was higher (5.6-26.3%) than rAD¯ of climate data and was mainly affected by aggregation of organic carbon and maximum plant available water capacity (i.e. the difference between field capacity and wilting point in the effective root zone). For yield estimates, the difference among resolutions (5 km vs. 40 km) was more pronounced for rainfed (rAD¯ = 14.5%) than irrigated conditions (rAD¯ = 3.0%). The rAD¯ of IWR was 15.7% when using input data at 40 km resolution. Therefore, reliable simulations of rainfed yield require a higher spatial resolution than simulation of irrigated yields. This needs to be considered when conducting regional modelling studies across Tasmania. This study also highlights the need to separately quantify the impact of input data aggregation on model outputs to inform about data aggregation errors and identify those variables that explain these errors.

Genome wide association study reveals novel QTL for barley yellow dwarf virus resistance in wheat

Background

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 diverse 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.

Results

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.

Conclusions

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.

Identification of New QTL Contributing to Barley Yellow Dwarf Virus-PAV (BYDV-PAV) Resistance in Wheat

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.

Microhair on the adaxial leaf surface of salt secreting halophytic Oryza coarctata Roxb. show distinct morphotypes: Isolation for molecular and functional analysis

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 × 10⁵/g leaf tissue). The robustness of the microhair isolation procedure was confirmed by subsequent viability staining (PI), total RNA isolation and RT-PCR amplification of O. coarctata trichome-specific WUSCHEL-related homeobox 3B (OcWox3B) and transporter gene-specific cDNA sequences. The present microhair isolation work from O. coarctata paves the way for examining genes involved in ion secretion in this halophytic wild rice model.

Tissue-Specific Regulation of Na+ and K+ Transporters Explains Genotypic Differences in Salinity Stress Tolerance in Rice

Rice (Oryza sativa) is a staple food that feeds more than half the world population. As rice is highly sensitive to soil salinity, current trends in soil salinization threaten global food security. To better understand the mechanistic basis of salinity tolerance in rice, three contrasting rice cultivars-Reiziq (tolerant), Doongara (moderately tolerant), and Koshihikari (sensitive)-were examined and the differences in operation of key ion transporters mediating ionic homeostasis in these genotypes were evaluated. Tolerant varieties had reduced Na⁺ translocation from roots to shoots. Electrophysiological and quantitative reverse transcription PCR experiments showed that tolerant genotypes possessed 2-fold higher net Na⁺ efflux capacity in the root elongation zone. Interestingly, this efflux was only partially mediated by the plasma membrane Na⁺/H⁺ antiporter (OsSOS1), suggesting involvement of some other exclusion mechanisms. No significant difference in Na⁺ exclusion from the mature root zones was found between cultivars, and the transcriptional changes in the salt overly sensitive signaling pathway genes in the elongation zone were not correlated with the genetic variability in salinity tolerance amongst genotypes. The most important hallmark of differential salinity tolerance was in the ability of the plant to retain K⁺ in both root zones. This trait was conferred by at least three complementary mechanisms: (1) its superior ability to activate H⁺-ATPase pump operation, both at transcriptional and functional levels; (2) reduced sensitivity of K⁺ efflux channels to reactive oxygen species; and (3) smaller upregulation in OsGORK and higher upregulation of OsAKT1 in tolerant cultivars in response to salt stress. These traits should be targeted in breeding programs aimed to improve salinity tolerance in commercial rice cultivars.

A regulator of early flowering in barley (Hordeum vulgare L.)

Heading date (HD) of cereals is an important trait for adaptation to diverse environments and is critical for determining yield and quality and the number of genes and gene combinations that confer earliness in barley under short days is limited. In our study, a QTL for early flowering was identified from the cross between an Australian malting barley cultivar and a Chinese landrace. Four sets of near isogenic lines (NILs) were developed with a QTL located on chromosome 5H at the interval of 122.0-129.0 cM. Further experiments were conducted to investigate how this gene was regulated by photoperiod using the NILs with three sowing dates from autumn to summer. The NILs carrying the earliness allele were significantly earlier than the late genotype at all sowing dates. This gene was different from previously reported vernalisation genes that are located at a similar position as no vernalisation was required for all the NILs. The difference between this gene and Eam5 (HvPHYC) locus which also located between two co-segregated markers (3398516S5, 122.5 cM, and 4014046D5, 126.1 cM), is that with the existence of Ppd-H1 (Eam1), Eam5 has no effect on ear emergence under long days while the gene from TX9425 still reduced the time to ear emergency. The locus showed no pleiotropic effects on grain pasting properties and agronomic traits except for spike length and number of spikelets per spike, and thus can be effectively used in breeding programs. The array of early heading dates caused by interactions of Eam5 gene with other maturity genes provides an opportunity to better fine tune heading dates with production environments, which can be critical factor in barley breeding.

Agronomical, biochemical and histological response of resistant and susceptible wheat and barley under BYDV stress

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.

Predicting optimum crop designs using crop models and seasonal climate forecasts

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.

Predicting optimum crop designs using crop models and seasonal climate forecasts

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.

Developing rural community health risk assessments for climate change: a Tasmanian pilot study

INTRODUCTION

This article examines the development and pilot implementation of an approach to support local community decision-makers to plan health adaptation responses to climate change. The approach involves health and wellbeing risk assessment supported through the use of an electronic tool. While climate change is a major foreseeable public health threat, the extent to which health services are prepared for, or able to adequately respond to, climate change impact-related risks remains unclear. Building health decision-support mechanisms in order to involve and empower local stakeholders to help create the basis for agreement on these adaptive actions is an important first step. The primary research question was 'What can be learned from pilot implementation of a community health and well-being risk assessment (CHWRA) information technology-based tool designed to support understanding of, and decision-making on, local community challenges and opportunities associated with health risks posed by climate change?

METHODS

The article examines the complexity of climate change science to adaptation translational processes, with reference to existing research literature on community development. This is done in the context of addressing human health risks for rural and remote communities in Tasmania, Australia. This process is further examined through the pilot implementation of an electronic tool designed to support the translation of physically based climate change impact information into community-level assessments of health risks and adaptation priorities. The procedural and technical nature of the CHWRA tool is described, and the implications of the data gathered from stakeholder workshops held at three rural Tasmanian local government sites are considered and discussed.

RESULTS

Bushfire, depression and waterborne diseases were identified by community stakeholders as being potentially 'catastrophic' health effects 'likely' to 'almost certain' to occur at one or more Tasmanian rural sites - based on an Intergovernmental Panel on Climate Change style of assessment. Consensus statements from stakeholders also suggested concern with health sector adaptation capacity and community resilience, and what community stakeholders defined as 'last straw' climate effects in already stressed communities. Preventative action and community engagement were also seen as important, especially with regard to managing the ways that climate change can multiply socioeconomic and health outcome inequality. Above all, stakeholder responses emphasised the importance of an applied, complexity-oriented understanding of how climate and climate change impacts affect local communities and local services to compromise the overall quality of human health in these communities.

CONCLUSIONS

Complex community-level assessments about climate change and related health risks and responses can be captured electronically in ways that offer potentially actionable information about priorities for health sector adaptation, as a first step in planning. What is valuable about these community judgements is the creation of shared values and commitments. Future iteration of the IT tool could include decision-support modules to support best practice health sector adaptation scenarios, providing participants with opportunities to develop their know-how about health sector adaptation to climate change. If managed carefully, such tools could work within a balanced portfolio of measures to help reduce the rising health burden from climate change.

Assessing the sustainability of wheat-based cropping systems using APSIM: model parameterisation and evaluation

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.

From rainfall to farm incomes—transforming advice for Australian drought policy. I. Development and testing of a bioeconomic modelling system

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.

From rainfall to farm incomes—transforming advice for Australian drought policy. II. Forecasting farm incomes

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 diversity 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.

Operational seasonal forecasting of crop performance

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.

Effect of artificial wind shelters on the growth and yield of rainfed crops

There is great interest in quantifying and understanding how shelter modifies crop growth and development under Australian conditions. Small constructed enclosures (shelters) can consistently reduce wind speed, allowing experiments to be run with replicated sheltered and unsheltered treatments in close proximity. The aim of this study was to quantify the effect on microclimate of consistently reducing wind speed by 70% and explain the consequences for dryland wheat (Triticum aestivum), lupin (Lupinus angustifolius) and mungbean (Vigna radiata) growth and development, at sites in Queensland, Victoria and Western Australia. Crops were grown inside and outside of artificial shelters, 10 by 10 m and extending 1 m above the crop canopy throughout the growing season. Mean daily air and soil temperatures and atmospheric vapour pressure inside the shelters were largely similar to unsheltered conditions. However, clear diurnal trends were evident; daily maximum temperature and vapour pressure deficit (VPD) were increased in shelter when crops were establishing or senescing. When leaf area index (LAI) was reduced in the shelters, soil temperature was greater than in the open, however when LAI was increased in the shelters, soil temperature was less than in the open. Grain yield in shelters ranged between 78 and 120% of unsheltered yield, depending on seasonal conditions and crop species; the mean yield for all sites, crops and years was 99% of unsheltered yield. In the absence of waterlogging, sheltered crops tended to develop more leaf area than unsheltered crops, with an increase in the ratio of leaf area to above-ground biomass. This greater leaf area did not increase soil water use. While LAI was increased by shelter, only 2 of the 6 sheltered crops that were not waterlogged yielded significantly more grain than the unsheltered crops. This may be because the sheltered crops experienced greater maximum temperatures and VPD during anthesis and grain filling than unsheltered crops. Also, net photosynthesis may not have increased in the shelters after canopy closure (LAI>3–4). Lupins, which developed more leaf area inside shelters, may have experienced strong competition for assimilates between developing branches, flowers and fruit. When rainfall was above average and the soil became waterlogged for part of the growing season, grain yield was reduced inside the shelters. Reduced evaporation inside the shelters may have extended the duration and severity of waterlogging and increased stresses on sheltered plants when potential yield was being set. The reductions in wind speed achieved inside the artificial shelters were greater than those likely in conventional tree windbreak systems. Analysis of crop growth illustrated that microclimate modification at this high level of shelter can be both beneficial and harmful, depending on the crop species and climatic conditions during the growing season.

Modelling crop growth and yield under the environmental changes induced by windbreaks 1. Model development and validation

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 individual 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.

The Australian National Windbreaks Program: overview and summary of results

This overview paper presents a description of the National Windbreaks Program (NWP) — its objectives, the main methods used to achieve these objectives and a summary of the key results. It draws these from the individual papers appearing in this special issue, which provide detailed descriptions and discussion about the specific research sites and research methods used, in addition to interpreting and discussing the results. The key findings were the following: (i) Two broad areas of crop and pasture response can be identified downwind of a porous windbreak: a zone of reduced yield associated with competition with the windbreak trees that extended from 1 H to 3 H, where H is the windbreak height, and a zone of unchanged or slightly increased yield stretching downwind to 10 H or 20 H. (ii) Averaged over the paddock, yield gains due to the effect of shelter on microclimate were smaller than expected — especially for cereals. Yield simulations conducted using the APSIM model and 20 years of historical climate data confirmed this result for longer periods and for other crop growing regions in Australia. Larger yield gains were simulated at locations where the latter part of the growing season was characterised by high atmospheric demand and a depleted soil water store. (iii) Economic analyses that account for the costs of establishing windbreaks, losses due to competition and yield gains as a result of shelter found that windbreaks will either lead to a small financial gain or be cost neutral. (iv) Part of the reason for the relatively small changes in yield measured at the field sites was the variable wind climate which meant that the crop was only sheltered for a small proportion of the growing season. In much of southern Australia, where the day-to-day and seasonal variability in wind direction is large, additional windbreaks planted around the paddock perimeter or as closely-spaced rows within the paddock will be needed to provide more consistent levels of shelter. (v) Protection from infrequent, high magnitude wind events that cause plant damage and soil erosion was observed to lead to the largest yield gains. The main forms of direct damage were sandblasting, which either buries or removes seedlings from the soil or damages the leaves and stems, and direct leaf tearing and stripping. (vi) A corollary to these findings is the differing effect that porous windbreaks have on the air temperature and humidity compared to wind. While winds are reduced in strength in a zone that extends from 5 H upwind to at least 25 H downwind of the windbreak, the effects of shelter on temperature and humidity are smaller and restricted mainly to the quiet zone. This means that fewer windbreaks are required to achieve reductions in wind damage than for altering the microclimate. (vii) The wind tunnel experiments illustrate the important aspects of windbreak structure that determine the airflow downwind, and subsequent microclimate changes, in winds oriented both perpendicular and obliquely to porous windbreaks. These results enable a series of guidelines to be forwarded for designing windbreaks for Australian agricultural systems.

Modelling crop growth and yield under the environmental changes induced by windbreaks. 2. Simulation of potential benefits at selected sites in Australia

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.

Impacts of climate change and climate variability on the competitiveness of wheat and beef cattle production in Emerald, north-east Australia

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.

Global change impacts on wheat production along an environmental gradient in south Australia

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.

Potential deep drainage under wheat crops in a Mediterranean climate. I. Temporal and spatial variability

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 hampered by the high degree of complexity of these systems as a result of diverse 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 example, 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.

Event frequency and severity of sorghum ergot in Australia

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

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.

Forecasting regional crop production using SOI phases: an example for the Australian peanut industry

Using peanuts as an example, 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.

Effects of sorghum ergot on grain sorghum production: a preliminary climatic analysis

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.

Development and use of a barley crop simulation model to evaluate production management strategies in north-eastern Australia

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.

Climatic risk to peanut production: a simulation study for Northern Australia

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.