51 resultados para Radar meteorology


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We investigated the influence of rainfall patterns on the water-use efficiency of wheat in a transect between Horsham (36°S) and Emerald (23°S) in eastern Australia. Water-use efficiency was defined in terms of biomass and transpiration, WUEB/T, and grain yield and evapotranspiration, WUEY/ET. Our working hypothesis is that latitudinal trends in WUEY/ET of water-limited crops are the complex result of southward increasing WUEB/T and soil evaporation, and season-dependent trends in harvest index. Our approach included: (a) analysis of long-term records to establish latitudinal gradients of amount, seasonality, and size-structure of rainfall; and (b) modelling wheat development, growth, yield, water budget components, and derived variables including WUEB/T and WUEY/ET. Annual median rainfall declined from around 600 mm in northern locations to 380 mm in the south. Median seasonal rain (from sowing to harvest) doubled between Emerald and Horsham, whereas median off-season rainfall (harvest to sowing) ranged from 460 mm at Emerald to 156 mm at Horsham. The contribution of small events (≤ 5 mm) to seasonal rainfall was negligible at Emerald (median 15 mm) and substantial at Horsham (105 mm). Power law coefficients (τ), i.e. the slopes of the regression between size and number of events in a log-log scale, captured the latitudinal gradient characterised by an increasing dominance of small events from north to south during the growing season. Median modelled WUEB/T increased from 46 kg/ha.mm at Emerald to 73 kg/ha.mm at Horsham, in response to decreasing atmospheric demand. Median modelled soil evaporation during the growing season increased from 70 mm at Emerald to 172 mm at Horsham. This was explained by the size-structure of rainfall characterised with parameter τ, rather than by the total amount of rainfall. Median modelled harvest index ranged from 0.25 to 0.34 across locations, and had a season-dependent latitudinal pattern, i.e. it was greater in northern locations in dry seasons in association with wetter soil profiles at sowing. There was a season-dependent latitudinal pattern in modelled WUEY/ET. In drier seasons, high soil evaporation driven by a very strong dominance of small events, and lower harvest index override the putative advantage of low atmospheric demand and associated higher WUEB/T in southern locations, hence the significant southwards decrease in WUEY/ET. In wetter seasons, when large events contribute a significant proportion of seasonal rain, higher WUEB/T in southern locations may translate into high WUEY/ET. Linear boundary functions (French-Schultz type models) accounting for latitudinal gradients in its parameters, slope, and x-intercept, were fitted to scatter-plots of modelled yield v. evapotranspiration. The x-intercept of the model is re-interpreted in terms of rainfall size structure, and the slope or efficiency multiplier is described in terms of the radiation, temperature, and air humidity properties of the environment. Implications for crop management and breeding are discussed.

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This paper is the first of a series that investigates whether new cropping systems with permanent raised beds (PRBs) or Flat land could be successfully used to increase farmers' incomes from rainfed crops in Lombok in Eastern Indonesia. This paper discusses the rice phase of the cropping system. Low grain yields of dry-seeded rice (Oryza sativa) grown on Flat land on Vertisols in the rainfed region of southern Lombok, Eastern Indonesia, are probably mainly due to (a) erratic rainfall (870-1220 mm/yr), with water often limiting at sensitive growth stages, (b) consistently high temperatures (average maximum - 31 C), and (c) low solar radiation. Farmers are therefore poor, and labour is hard and costly, as all operations are manual. Two replicated field experiments were run at Wakan (annual rainfall = 868 mm) and Kawo (1215 mm) for 3 years (2001/2002 to 2003/2004) on Vertisols in southern Lombok. Dry-seeded rice was grown in 4 treatments with or without manual tillage on (a) PRBs, 1.2 m wide, 200 mm high, separated by furrows 300 mm wide, 200 mill deep, with no rice sown in the well-graded furrows, and (b) well-graded Flat land. Excess surface water was harvested from each treatment and used for irrigation after the vegetative stage of the rice. All operations were manual. There were no differences between treatments in grain yield of rice (mean grain yield = 681 g/m(2)) which could be partly explained by total number of tillers/hill and mean panicle length, but not number of productive tillers/hill, plant height or weight of 1000 grains. When the data from both treatments on PRBs and from both treatments on Flat land, each year at each site were analysed, there were also no differences in grain yield of rice (g/m(2)). When rainfall in the wet season up to harvest was over 1000 mm (Year 2; Wakan, Kawo), or plants were water-stressed during crop establishment (Year 1; Wakan) or during grain-fill (Year 3: Kawo), there were significant differences in grain yield (g/1.5 m(2)) between treatments; generally the grain yield (g/1.5 m(2)) on PRBs with or without tillage was less than that on Flat land with or without tillage. However, when the data from both treatments on PRBs and from both treatments on Flat land, each year at each site, were analysed, the greater grain yield of dry-seeded rice on Flat land (mean yield 1 092 g/1.5 m(2)) than that on PRBs (mean 815 g/1.5 m(2)) was mainly because there were 25% more plants on Flat land. Overall when the data in the 2 outer rows and the 2 inner rows on PRBs were each combined, there was a higher number of productive tillers in the combined outer rows (mean 20.7 tillers/hill) compared with that in the combined inner rows on each PRB (mean 18.2 tillers/hill). However, there were no differences in grain yield between combined rows (mean 142 g/m row). Hence with a gap of 500 mm (the distance between the outer rows of plants on adjacent raised beds), plants did not compensate in grain yield for missing plants in furrows. This suggests that rice (a) also sown in furrows, or (b) sown in 7 rows with narrower row-spacing, or (c) sown in 6 rows with slightly wider row-spacing, and narrower gap between outer rows on adjacent beds, may further increase grain yield (g/1.5 m(2)) in this system of PRBs. The growth and the grain yield (y in g/m(2)) of rainfed rice (with rainfall on-site the only source of water for irrigation) depended mainly on the rainfall (x in mm) in the wet season up to harvest (due either to site or year) with y = 1. 1x -308; r(2) = 0.54; p < 0.005. However, 280 mm (i.e. 32%) of the rainfall was not directly used to produce grain (i.e. when y = 0 g/m(2)). Manual tillage did not affect growth and grain yield of rice (g/m(2); g/1.5 m(2)), either on PRB or on Flat land.

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Rainfall variability is a challenge to sustainable and pro. table cattle production in northern Australia. Strategies recommended to manage for rainfall variability, like light or variable stocking, are not widely adopted. This is due partly to the perception that sustainability and profitability are incompatible. A large, long-term grazing trial was initiated in 1997 in north Queensland, Australia, to test the effect of different grazing strategies on cattle production. These strategies are: (i) constant light stocking (LSR) at long-term carrying capacity (LTCC); (ii) constant heavy stocking (HSR) at twice LTCC; (iii) rotational wet-season spelling (R/Spell) at 1.5 LTCC; (iv) variable stocking (VAR), with stocking rates adjusted in May based on available pasture; and (v) a Southern Oscillation Index (SOI) variable strategy, with stocking rates adjusted in November, based on available pasture and SOI seasonal forecasts. Animal performance varied markedly over the 10 years for which data is presented, due to pronounced differences in rainfall and pasture availability. Nonetheless, lighter stocking at or about LTCC consistently gave the best individual liveweight gain (LWG), condition score and skeletal growth; mean LWG per annum was thus highest in the LSR (113 kg), intermediate in the R/Spell (104 kg) and lowest in the HSR(86 kg). MeanLWGwas 106 kg in the VAR and 103 kg in the SOI but, in all years, the relative performance of these strategies was dependent upon the stocking rate applied. After 2 years on the trial, steers from lightly stocked strategies were 60-100 kg heavier and received appreciable carcass price premiums at the meatworks compared to those under heavy stocking. In contrast, LWG per unit area was greatest at stocking rates of about twice LTCC; mean LWG/ha was thus greatest in the HSR (21 kg/ha), but this strategy required drought feeding in four of the 10 years and was unsustainable. Although LWG/ha was lower in the LSR (mean 14 kg/ha), or in strategies that reduced stocking rates in dry years like the VAR(mean 18 kg/ha) and SOI (mean 17 kg/ha), these strategies did not require drought feeding and appeared sustainable. The R/Spell strategy (mean 16 kg/ha) was compromised by an ill-timed fire, but also performed satisfactorily. The present results provide important evidence challenging the assumption that sustainable management in a variable environment is unprofitable. Further research is required to fully quantify the long-term effects of these strategies on land condition and profitability and to extrapolate the results to breeder performance at the property level.

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For pasture growth in the semi-arid tropics of north-east Australia, where up to 80% of annual rainfall occurs between December and March, the timing and distribution of rainfall events is often more important than the total amount. In particular, the timing of the 'green break of the season' (GBOS) at the end of the dry season, when new pasture growth becomes available as forage and a live-weight gain is measured in cattle, affects several important management decisions that prevent overgrazing and pasture degradation. Currently, beef producers in the region use a GBOS rule based on rainfall (e. g. 40mm of rain over three days by 1 December) to define the event and make their management decisions. A survey of 16 beef producers in north-east Queensland shows three quarters of respondents use a rainfall amount that occurs in only half or less than half of all years at their location. In addition, only half the producers expect the GBOS to occur within two weeks of the median date calculated by the CSIRO plant growth days model GRIM. This result suggests that in the producer rules, either the rainfall quantity or the period of time over which the rain is expected, is unrealistic. Despite only 37% of beef producers indicating that they use a southern oscillation index (SOI) forecast in their decisions, cross validated LEPS (linear error in probability space) analyses showed both the average 3 month July-September SOI and the 2 month August-September SOI have significant forecast skill in predicting the probability of both the amount of wet season rainfall and the timing of the GBOS. The communication and implementation of a rigorous and realistic definition of the GBOS, and the likely impacts of anthropogenic climate change on the region are discussed in the context of the sustainable management of northern Australian rangelands.

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Grazing is a major land use in Australia's rangelands. The 'safe' livestock carrying capacity (LCC) required to maintain resource condition is strongly dependent on climate. We reviewed: the approaches for quantifying LCC; current trends in climate and their effect on components of the grazing system; implications of the 'best estimates' of climate change projections for LCC; the agreement and disagreement between the current trends and projections; and the adequacy of current models of forage production in simulating the impact of climate change. We report the results of a sensitivity study of climate change impacts on forage production across the rangelands, and we discuss the more general issues facing grazing enterprises associated with climate change, such as 'known uncertainties' and adaptation responses (e.g. use of climate risk assessment). We found that the method of quantifying LCC from a combination of estimates (simulations) of long-term (>30 years) forage production and successful grazier experience has been well tested across northern Australian rangelands with different climatic regions. This methodology provides a sound base for the assessment of climate change impacts, even though there are many identified gaps in knowledge. The evaluation of current trends indicated substantial differences in the trends of annual rainfall (and simulated forage production) across Australian rangelands with general increases in most of western Australian rangelands ( including northern regions of the Northern Territory) and decreases in eastern Australian rangelands and south-western Western Australia. Some of the projected changes in rainfall and temperature appear small compared with year-to-year variability. Nevertheless, the impacts on rangeland production systems are expected to be important in terms of required managerial and enterprise adaptations. Some important aspects of climate systems science remain unresolved, and we suggest that a risk-averse approach to rangeland management, based on the 'best estimate' projections, in combination with appropriate responses to short-term (1-5 years) climate variability, would reduce the risk of resource degradation. Climate change projections - including changes in rainfall, temperature, carbon dioxide and other climatic variables - if realised, are likely to affect forage and animal production, and ecosystem functioning. The major known uncertainties in quantifying climate change impacts are: (i) carbon dioxide effects on forage production, quality, nutrient cycling and competition between life forms (e.g. grass, shrubs and trees); and (ii) the future role of woody plants including effects of. re, climatic extremes and management for carbon storage. In a simple example of simulating climate change impacts on forage production, we found that increased temperature (3 degrees C) was likely to result in a decrease in forage production for most rangeland locations (e. g. -21% calculated as an unweighted average across 90 locations). The increase in temperature exacerbated or reduced the effects of a 10% decrease/increase in rainfall respectively (-33% or -9%). Estimates of the beneficial effects of increased CO2 (from 350 to 650 ppm) on forage production and water use efficiency indicated enhanced forage production (+26%). The increase was approximately equivalent to the decline in forage production associated with a 3 degrees C temperature increase. The large magnitude of these opposing effects emphasised the importance of the uncertainties in quantifying the impacts of these components of climate change. We anticipate decreases in LCC given that the 'best estimate' of climate change across the rangelands is for a decline (or little change) in rainfall and an increase in temperature. As a consequence, we suggest that public policy have regard for: the implications for livestock enterprises, regional communities, potential resource damage, animal welfare and human distress. However, the capability to quantify these warnings is yet to be developed and this important task remains as a challenge for rangeland and climate systems science.

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The complexity, variability and vastness of the northern Australian rangelands make it difficult to assess the risks associated with climate change. In this paper we present a methodology to help industry and primary producers assess risks associated with climate change and to assess the effectiveness of adaptation options in managing those risks. Our assessment involved three steps. Initially, the impacts and adaptation responses were documented in matrices by ‘experts’ (rangeland and climate scientists). Then, a modified risk management framework was used to develop risk management matrices that identified important impacts, areas of greatest vulnerability (combination of potential impact and adaptive capacity) and priority areas for action at the industry level. The process was easy to implement and useful for arranging and analysing large amounts of information (both complex and interacting). Lastly, regional extension officers (after minimal ‘climate literacy’ training) could build on existing knowledge provided here and implement the risk management process in workshops with rangeland land managers. Their participation is likely to identify relevant and robust adaptive responses that are most likely to be included in regional and property management decisions. The process developed here for the grazing industry could be modified and used in other industries and sectors. By 2030, some areas of northern Australia will experience more droughts and lower summer rainfall. This poses a serious threat to the rangelands. Although the impacts and adaptive responses will vary between ecological and geographic systems, climate change is expected to have noticeable detrimental effects: reduced pasture growth and surface water availability; increased competition from woody vegetation; decreased production per head (beef and wool) and gross margin; and adverse impacts on biodiversity. Further research and development is needed to identify the most vulnerable regions, and to inform policy in time to facilitate transitional change and enable land managers to implement those changes.

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Climate change projections for Australia predict increasing temperatures, changes to rainfall patterns, and elevated atmospheric carbon dioxide (CO2) concentrations. The aims of this study were to predict plant production responses to elevated CO2 concentrations using the SGS Pasture Model and DairyMod, and then to quantify the effects of climate change scenarios for 2030 and 2070 on predicted pasture growth, species composition, and soil moisture conditions of 5 existing pasture systems in climates ranging from cool temperate to subtropical, relative to a historical baseline. Three future climate scenarios were created for each site by adjusting historical climate data according to temperature and rainfall change projections for 2030, 2070 mid-and 2070 high-emission scenarios, using output from the CSIRO Mark 3 global climate model. In the absence of other climate changes, mean annual pasture production at an elevated CO2 concentration of 550 ppm was predicted to be 24-29% higher than at 380 ppm CO2 in temperate (C-3) species-dominant pastures in southern Australia, with lower mean responses in a mixed C-3/C-4 pasture at Barraba in northern New South Wales (17%) and in a C-4 pasture at Mutdapilly in south-eastern Queensland (9%). In the future climate scenarios at the Barraba and Mutdapilly sites in subtropical and subhumid climates, respectively, where climate projections indicated warming of up to 4.4 degrees C, with little change in annual rainfall, modelling predicted increased pasture production and a shift towards C-4 species dominance. In Mediterranean, temperate, and cool temperate climates, climate change projections indicated warming of up to 3.3 degrees C, with annual rainfall reduced by up to 28%. Under future climate scenarios at Wagga Wagga, NSW, and Ellinbank, Victoria, our study predicted increased winter and early spring pasture growth rates, but this was counteracted by a predicted shorter spring growing season, with annual pasture production higher than the baseline under the 2030 climate scenario, but reduced by up to 19% under the 2070 high scenario. In a cool temperate environment at Elliott, Tasmania, annual production was higher than the baseline in all 3 future climate scenarios, but highest in the 2070 mid scenario. At the Wagga Wagga, Ellinbank, and Elliott sites the effect of rainfall declines on pasture production was moderated by a predicted reduction in drainage below the root zone and, at Ellinbank, the use of deeper rooted plant systems was shown to be an effective adaptation to mitigate some of the effect of lower rainfall.

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Because of the variable and changing environment, advisors and farmers are seeking systems that provide risk management support at a number of time scales. The Agricultural Production Systems Research Unit, Toowoomba, Australia has developed a suite of tools to assist advisors and farmers to better manage risk in cropping. These tools range from simple rainfall analysis tools (Rainman, HowWet, HowOften) through crop simulation tools (WhopperCropper and YieldProphet) to the most complex, APSFarm, a whole-farm analysis tool. Most are derivatives of the APSIM crop model. These tools encompass a range of complexity and potential benefit to both the farming community and for government policy. This paper describes, the development and usage of two specific products; WhopperCropper and APSFarm. WhopperCropper facilitates simulation-aided discussion of growers' exposure to risk when comparing alternative crop input options. The user can readily generate 'what-if' scenarios that separate the major influences whilst holding other factors constant. Interactions of the major inputs can also be tested. A manager can examine the effects of input levels (and Southern Oscillation Index phase) to broadly determine input levels that match their attitude to risk. APSFarm has been used to demonstrate that management changes can have different effects in short and long time periods. It can be used to test local advisors and farmers' knowledge and experience of their desired rotation system. This study has shown that crop type has a larger influence than more conservative minimum soil water triggers in the long term. However, in short term dry periods, minimum soil water triggers and maximum area of the various crops can give significant financial gains.

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Time to first root in cuttings varies under different environmental conditions and understanding these differences is critical for optimizing propagation of commercial forestry species. Temperature environment (15, 25, 30 or 352C) had no effect on the cellular stages in root formation of the Slash * Caribbean Pine hybrid over 16 weeks as determined by histology. Initially callus cells formed in the cortex, then tracheids developed and formed primordia leading to external roots. However, speed of development followed a growth curve with the fastest development occurring at 25C and slowest at 15C with rooting percentages at week 12 of 80 and 0% respectively. Cutting survival was good in the three cooler temperature regimes (>80%) but reduced to 59% at 35C. Root formation appeared to be dependant on the initiation of tracheids because all un-rooted cuttings had callus tissue but no tracheids, irrespective of temperature treatment and clone.

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Rainfall variability is a major challenge to sustainable management in semi-arid rangelands. We present empirical evidence from a large, long-term grazing trial in northern Australia on the relative performance of constant heavy stocking, moderate stocking at long-term carrying capacity and variable stocking in coping with climate variability over a range of rainfall years. Moderate stocking gave good economic returns, maintained pasture condition and minimised soil loss and runoff. Heavy stocking was neither sustainable nor profitable in the long term. Variable stocking generally performed well but suffered economic loss and some decline in pasture condition in the transition from good to poor years. Importantly, our results show that sustainable and profitable management are compatible in semi-arid rangelands.

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We compared daily net radiation (Rn) estimates from 19 methods with the ASCE-EWRI Rn estimates in two climates: Clay Center, Nebraska (sub-humid) and Davis, California (semi-arid) for the calendar year. The performances of all 20 methods, including the ASCE-EWRI Rn method, were then evaluated against Rn data measured over a non-stressed maize canopy during two growing seasons in 2005 and 2006 at Clay Center. Methods differ in terms of inputs, structure, and equation intricacy. Most methods differ in estimating the cloudiness factor, emissivity (e), and calculating net longwave radiation (Rnl). All methods use albedo (a) of 0.23 for a reference grass/alfalfa surface. When comparing the performance of all 20 Rn methods with measured Rn, we hypothesized that the a values for grass/alfalfa and non-stressed maize canopy were similar enough to only cause minor differences in Rn and grass- and alfalfa-reference evapotranspiration (ETo and ETr) estimates. The measured seasonal average a for the maize canopy was 0.19 in both years. Using a = 0.19 instead of a = 0.23 resulted in 6% overestimation of Rn. Using a = 0.19 instead of a = 0.23 for ETo and ETr estimations, the 6% difference in Rn translated to only 4% and 3% differences in ETo and ETr, respectively, supporting the validity of our hypothesis. Most methods had good correlations with the ASCE-EWRI Rn (r2 > 0.95). The root mean square difference (RMSD) was less than 2 MJ m-2 d-1 between 12 methods and the ASCE-EWRI Rn at Clay Center and between 14 methods and the ASCE-EWRI Rn at Davis. The performance of some methods showed variations between the two climates. In general, r2 values were higher for the semi-arid climate than for the sub-humid climate. Methods that use dynamic e as a function of mean air temperature performed better in both climates than those that calculate e using actual vapor pressure. The ASCE-EWRI-estimated Rn values had one of the best agreements with the measured Rn (r2 = 0.93, RMSD = 1.44 MJ m-2 d-1), and estimates were within 7% of the measured Rn. The Rn estimates from six methods, including the ASCE-EWRI, were not significantly different from measured Rn. Most methods underestimated measured Rn by 6% to 23%. Some of the differences between measured and estimated Rn were attributed to the poor estimation of Rnl. We conducted sensitivity analyses to evaluate the effect of Rnl on Rn, ETo, and ETr. The Rnl effect on Rn was linear and strong, but its effect on ETo and ETr was subsidiary. Results suggest that the Rn data measured over green vegetation (e.g., irrigated maize canopy) can be an alternative Rn data source for ET estimations when measured Rn data over the reference surface are not available. In the absence of measured Rn, another alternative would be using one of the Rn models that we analyzed when all the input variables are not available to solve the ASCE-EWRI Rn equation. Our results can be used to provide practical information on which method to select based on data availability for reliable estimates of daily Rn in climates similar to Clay Center and Davis.

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Genotype-environment interactions (GEI) limit genetic gain for complex traits such as tolerance to drought. Characterization of the crop environment is an important step in understanding GEI. A modelling approach is proposed here to characterize broadly (large geographic area, long-term period) and locally (field experiment) drought-related environmental stresses, which enables breeders to analyse their experimental trials with regard to the broad population of environments that they target. Water-deficit patterns experienced by wheat crops were determined for drought-prone north-eastern Australia, using the APSIM crop model to account for the interactions of crops with their environment (e.g. feedback of plant growth on water depletion). Simulations based on more than 100 years of historical climate data were conducted for representative locations, soils, and management systems, for a check cultivar, Hartog. The three main environment types identified differed in their patterns of simulated water stress around flowering and during grain-filling. Over the entire region, the terminal drought-stress pattern was most common (50% of production environments) followed by a flowering stress (24%), although the frequencies of occurrence of the three types varied greatly across regions, years, and management. This environment classification was applied to 16 trials relevant to late stages testing of a breeding programme. The incorporation of the independently-determined environment types in a statistical analysis assisted interpretation of the GEI for yield among the 18 representative genotypes by reducing the relative effect of GEI compared with genotypic variance, and helped to identify opportunities to improve breeding and germplasm-testing strategies for this region.

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Climate affects the custard apple industry in a range of ways through impacts on growth, disease risk, fruit set and industry location. Climates in Australia are influenced by surrounding oceans, and are very variable from year to year. However, amidst this variability there are significant trends, with Australian annual mean temperatures increasing since 1910, and particularly since 1950, with night-time temperatures increasing faster (0.11oC/decade) than daytime temperatures (0.06oC/decade). These temperature increases and other climate changes are expected to continue as a result of greenhouse gas emissions, with ongoing impacts on the custard apple industry. Five sites were chosen to assess possible future climate changes : Mareeba, Yeppoon, Bundaberg, Nambour and Lismore, these sites representing the extent of the majority of custard apple production in eastern Australia. A fifth site (Coffs Harbour) was selected as it is south of the current production regions. A mean warming of 0.8 to 1.2oC is anticipated over most of these sites by the year 2030, relative to 1990. This paper assesses the potential effects of climate change on custard apple production, and suggests strategies for adaptation.

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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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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.