14 resultados para phenophase response to climate change

em eResearch Archive - Queensland Department of Agriculture


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Abstract The paper evaluates the effect of future climate change (as per the CSIRO Mk3.5 A1FI future climate projection) on cotton yield in Southern Queensland and Northern NSW, eastern Australia by using of the biophysical simulation model APSIM (Agricultural Production Systems sIMulator). The simulations of cotton production show that changes in the influential meteorological parameters caused by climate change would lead to decreased future cotton yields without the effect of CO2 fertilisation. By 2050 the yields would decrease by 17 %. Including the effects of CO2 fertilisation ameliorates the effect of decreased water availability and yields increase by 5.9 % by 2030, but then decrease by 3.6 % in 2050. Importantly, it was necessary to increase irrigation amounts by almost 50 % to maintain adequate soil moisture levels. The effect of CO2 was found to have an important positive impact of the yield in spite of deleterious climate change. This implies that the physiological response of plants to climate change needs to be thoroughly understood to avoid making erroneous projections of yield and potentially stifling investment or increasing risk.

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There is an increasing need to understand what makes vegetation at some locations more sensitive to climate change than others. For savanna rangelands, this requires building knowledge of how forage production in different land types will respond to climate change, and identifying how location-specific land type characteristics, climate and land management control the magnitude and direction of its responses to change. Here, a simulation analysis is used to explore how forage production in 14 land types of the north-eastern Australian rangelands responds to three climate change scenarios of +3A degrees C, +17% rainfall; +2A degrees C, -7% rainfall; and +3A degrees C, -46% rainfall. Our results demonstrate that the controls on forage production responses are complex, with functional characteristics of land types interacting to determine the magnitude and direction of change. Forage production may increase by up to 60% or decrease by up to 90% in response to the extreme scenarios of change. The magnitude of these responses is dependent on whether forage production is water or nitrogen (N) limited, and how climate changes influence these limiting conditions. Forage production responds most to changes in temperature and moisture availability in land types that are water-limited, and shows the least amount of change when growth is restricted by N availability. The fertilisation effects of doubled atmospheric CO2 were found to offset declines in forage production under 2A degrees C warming and a 7% reduction in rainfall. However, rising tree densities and declining land condition are shown to reduce potential opportunities from increases in forage production and raise the sensitivity of pastures to climate-induced water stress. Knowledge of these interactions can be applied in engaging with stakeholders to identify adaptation options.

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Aims to build adaptive capacity within Qld's mixed farming (cropping/beef) sector.

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This study presents the use of a whole farm model in a participatory modelling research approach to examine the sensitivity of four contrasting case study farms to a likely climate change scenario. The newly generated information was used to support discussions with the participating farmers in the search for options to design more profitable and sustainable farming systems in Queensland Australia. The four case studies contrasted in key systems characteristics: opportunism in decision making, i.e. flexible versus rigid crop rotations; function, i.e. production of livestock or crops; and level of intensification, i.e. dryland versus irrigated agriculture. Tested tactical and strategic changes under a baseline and climate change scenario (CCS) involved changes in the allocation of land between cropping and grazing enterprises, alternative allocations of limited irrigation water across cropping enterprises, and different management rules for planting wheat and sorghum in rainfed cropping. The results show that expected impacts from a likely climate change scenario were evident in the following increasing order: the irrigated cropping farm case study, the cropping and grazing farm, the more opportunistic rainfed cropping farm and the least opportunistic rainfed cropping farm. We concluded that in most cases the participating farmers were operating close to the efficiency frontier (i.e. in the relationship between profits and risks). This indicated that options to adapt to climate change might need to evolve from investments in the development of more innovative cropping and grazing systems and/or transformational changes on existing farming systems. We expect that even though assimilating expected changes in climate seems to be rather intangible and premature for these farmers, as innovations are developed, adaptation is likely to follow quickly. The multiple interactions among farm management components in complex and dynamic farm businesses operating in a variable and changing climate, make the use of whole farm participatory modelling approaches valuable tools to quantify benefits and trade-offs from alternative farming systems designs in the search for improved profitability and resilience.

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As climate change continues to impact socio-ecological systems, tools that assist conservation managers to understand vulnerability and target adaptations are essential. Quantitative assessments of vulnerability are rare because available frameworks are complex and lack guidance for dealing with data limitations and integrating across scales and disciplines. This paper describes a semi-quantitative method for assessing vulnerability to climate change that integrates socio-ecological factors to address management objectives and support decision-making. The method applies a framework first adopted by the Intergovernmental Panel on Climate Change and uses a structured 10-step process. The scores for each framework element are normalized and multiplied to produce a vulnerability score and then the assessed components are ranked from high to low vulnerability. Sensitivity analyses determine which indicators most influence the analysis and the resultant decision-making process so data quality for these indicators can be reviewed to increase robustness. Prioritisation of components for conservation considers other economic, social and cultural values with vulnerability rankings to target actions that reduce vulnerability to climate change by decreasing exposure or sensitivity and/or increasing adaptive capacity. This framework provides practical decision-support and has been applied to marine ecosystems and fisheries, with two case applications provided as examples: (1) food security in Pacific Island nations under climate-driven fish declines, and (2) fisheries in the Gulf of Carpentaria, northern Australia. The step-wise process outlined here is broadly applicable and can be undertaken with minimal resources using existing data, thereby having great potential to inform adaptive natural resource management in diverse locations.

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Climate change is emerging as the single greatest threat to coral-reef ecosystems.The most immediate impacts will be a loss of diversity and changes to fish community composition and may lead to eventual declines in abundance and productivity of key fisheries species. A key component of this research is to assess effects of projected changes in environmental conditions (temperature and ocean acidity) due to climate change on reproduction, growth and development of coral trout (Plectropomus leopardis).Ultimately, this research will fill key knowledge gaps about climate change impacts on larger fishes, which are fundamental to optimizing resilience-based management, and in turn improve the adaptive capacity of industries and communities along the Great Barrier Reef.

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The project uses participatory methods to engage primary producers and advisers in central Queensland, southern Queensland, and north east New South Wales on-farm trials and demonstrations to adapt mixed farming systems to changed climate conditions. The focus is adaptation to climate change but will support abatement of greenhouse gas emissions by building soil carbon, better managing soil nitrogen and soil organic carbon. Data will be collected and integrated with data from Round 1 of the Climate Change Research Program to extend industry understanding beyond a general awareness of ‘climate change’. Nitrous oxide and soil carbon data will help farmers/advisers understand the implications of climate change and develop adaptation strategies for a more sustainable, climate sensitive future.

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Australia’s and New Zealand’s major agricultural manure management emission sources are reported to be, in descending order of magnitude: (1) methane (CH4) from dairy farms in both countries; (2) CH4 from pig farms in Australia; and nitrous oxide (N2O) from (3) beef feedlots and (4) poultry sheds in Australia. We used literature to critically review these inventory estimates. Alarmingly for dairy farm CH4 (1), our review revealed assumptions and omissions that when addressed could dramatically increase this emission estimate. The estimate of CH4 from Australian pig farms (2) appears to be accurate, according to industry data and field measurements. The N2O emission estimates for beef feedlots (3) and poultry sheds (4) are based on northern hemisphere default factors whose appropriateness for Australia is questionable and unverified. Therefore, most of Australasia’s key livestock manure management greenhouse gas (GHG) emission profiles are either questionable or are unsubstantiated by region-specific research. Encouragingly, GHG from dairy shed manure are relatively easy to mitigate because they are a point source which can be managed by several ‘close-to-market’ abatement solutions. Reducing these manure emissions therefore constitutes an opportunity for meaningful action sooner compared with the more difficult-to-implement and long-term strategies that currently dominate agricultural GHG mitigation research. At an international level, our review highlights the critical need to carefully reassess GHG emission profiles, particularly if such assessments have not been made since the compilation of original inventories. Failure to act in this regard presents the very real risk of missing the ‘low hanging fruit’ in the rush towards a meaningful response to climate change

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The eucalypt leaf beetle, Paropsis atomaria Olivier, is an increasingly important pest of eucalypt plantations in subtropical eastern Australia. A process-based model, ParopSys, was developed using DYMEXTM and was found to accurately predict the beetle populations. Climate change scenarios within the latest Australian climate model forecast range were run in ParopSys at three locations to predict changes in beetle performance. Relative population peaks of early generations did not change but shifted to earlier in the season. Temperature increases of 1.0 to 1.5 ºC or greater predicted an extra generation of adults at Gympie and Canberra, but not for Lowmead, where increased populations of late season adults were observed under all scenarios. Furthermore, an additional generation of late-larval stages was predicted at temperature increases of greater than 1.0 ºC at Lowmead. Management strategies to address these changes are discussed, as are requirements to improve the predictive capacity of the model.

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This application was developed in response to the widely recognised concern that climate change will result in changes to marine life and ecosystems, and hence fisheries, throughout Australia with tropical marine ecosystems in northern Australia identified as being particularly vulnerable. These changes are predicted to vary spatially depending on local climate and biophysical processes. Northern Australia is one of three major Australian regions predicted to be impacted. The project addresses the important FRDC strategic challenge of improving the management of aquatic natural resources to ensure their sustainability through research and management that accounts for the effects that climate change may have on the resources.

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Contribute to the current understanding of climate impacts on cut flower and foliage growing in Queensland.

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Many aquatic species are linked to environmental drivers such as temperature and salinity through processes such as spawning, recruitment and growth. Information is needed on how fished species may respond to altered environmental drivers under climate change so that adaptive management strategies can be developed. Barramundi (Lates calcarifer) is a highly prized species of the Indo-West Pacific, whose recruitment and growth is driven by river discharge. We developed a monthly age- and length-structured population model for barramundi. Monte Carlo Markov Chain simulations were used to explore the population's response to altered river discharges under modelled total licenced water abstraction and projected climate change, derived and downscaled from Global Climate Model A1FI. Mean values of exploitable biomass, annual catch, maximum sustainable yield and spawning stock size were significantly reduced under scenarios where river discharge was reduced; despite including uncertainty. These results suggest that the upstream use of water resources and climate change have potential to significantly reduce downstream barramundi stock sizes and harvests and may undermine the inherent resilience of estuarine-dependent fisheries. © 2012 CSIRO.

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West Africa is highly vulnerable to climate hazards and better quantification and understanding of the impact of climate change on crop yields are urgently needed. Here we provide an assessment of near-term climate change impacts on sorghum yields in West Africa and account for uncertainties both in future climate scenarios and in crop models. Towards this goal, we use simulations of nine bias-corrected CMIP5 climate models and two crop models (SARRA-H and APSIM) to evaluate the robustness of projected crop yield impacts in this area. In broad agreement with the full CMIP5 ensemble, our subset of bias-corrected climate models projects a mean warming of +2.8 °C in the decades of 2031–2060 compared to a baseline of 1961–1990 and a robust change in rainfall in West Africa with less rain in the Western part of the Sahel (Senegal, South-West Mali) and more rain in Central Sahel (Burkina Faso, South-West Niger). Projected rainfall deficits are concentrated in early monsoon season in the Western part of the Sahel while positive rainfall changes are found in late monsoon season all over the Sahel, suggesting a shift in the seasonality of the monsoon. In response to such climate change, but without accounting for direct crop responses to CO2, mean crop yield decreases by about 16–20% and year-to-year variability increases in the Western part of the Sahel, while the eastern domain sees much milder impacts. Such differences in climate and impacts projections between the Western and Eastern parts of the Sahel are highly consistent across the climate and crop models used in this study. We investigate the robustness of impacts for different choices of cultivars, nutrient treatments, and crop responses to CO2. Adverse impacts on mean yield and yield variability are lowest for modern cultivars, as their short and nearly fixed growth cycle appears to be more resilient to the seasonality shift of the monsoon, thus suggesting shorter season varieties could be considered a potential adaptation to ongoing climate changes. Easing nitrogen stress via increasing fertilizer inputs would increase absolute yields, but also make the crops more responsive to climate stresses, thus enhancing the negative impacts of climate change in a relative sense. Finally, CO2 fertilization would significantly offset the negative climate

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Carbon (C) sequestration in soils is a means for increasing soil organic carbon (SOC) stocks and is a potential tool for climate change mitigation. One recommended management practice to increase SOC stocks is nitrogen (N) fertilisation, however examples of positive, negative or null SOC effects in response to N addition exist. We evaluated the relative importance of plant molecular structure, soil physical properties and soil ecological stoichiometry in explaining the retention of SOC with and without N addition. We tracked the transformation of 13C pulse-labelled buffel grass (Cenchrus ciliaris L.), wheat (Triticum aestivum L.) and lucerne (Medicago sativa L.) material to the <53 μm silt + clay soil organic C fraction, hereafter named “humus”, over 365-days of incubation in four contrasting agricultural soils, with and without urea-N addition. We hypothesised that: a) humus retention would be soil and litter dependent; b) humus retention would be litter independent once litter C:N ratios were standardised with urea-N addition; and c) humus retention would be improved by urea-N addition. Two and three-way factorial analysis of variance indicated that 13C humus was consistently soil and litter dependent, even when litter C:N ratios were standardised, and that the effect of urea-N addition on 13C humus was also soil and litter dependent. A boosted regression analysis of the effect of 44 plant and soil explanatory variables demonstrated that soil biological and chemical properties had the greatest relative influence on 13C humus. Regression tree analyses demonstrated that the greatest gains in 13C humus occurred in soils of relatively low total organic C, dissolved organic C and microbial biomass C (MBC), or with a combination of relatively high MBC and low C:N ratio. The greatest losses in 13C humus occurred in soils with a combination of relatively high MBC and low total N or increasing C:N ratio. We conclude that soil variables involved in soil ecological stoichiometry exert a greater relative influence on incorporating organic matter as humus compared to plant molecular structure and soil physical properties. Furthermore, we conclude that the effect of N fertilisation on humus retention is dependent upon soil ecological stoichiometry.