Delivering information and technology to the mango industry - Stage 2

Access to relevant and timely information and training resources has emerged as a significant issue from the Delivering Mango Technology (DMT) project. This project will facilitate providing managing information and technology tools for growers. Using a range of methods, including workshops, events, and web based technology facilitated through the Australian Mango Industry Association’s (AMIA) website, DMT stage 2 will develop a high profile delivery vehicle to building industry knowledge and resources .

Remote Sensing - based precision agriculture tool for the sugar industry

The project will produce practical and relevant benchmarks, protocols and recommendations for the adoption of remote sensing technologies for improved in season management and therefore production within the Australian sugar cane industry.

Agronomic Packages for Improved Yield and Quality in the Australian Peanut Industry

Monitoring aflatoxin and developing improved peanut drying practices, cadmium management and web based irrigation decision support systems.

Spatially based data delivery and recording sys-Aust Sugar Cane industry

Establish an internet platform where spatially referenced data can be viewed, entered and stored.

Internet based spatial data delivery and reporting system for cotton industry

Development of an internet based spatial data delivery and reporting system for the Australian Cotton Industry.

Smart technologies for peanut industry

Commercialisation and adoption of remote sensing and GIS technologies for improved production forecasting, productivity, quality and paddock- to- plate tracking within the Australian Peanut Industry.

Enhancing supplies of high quality barley to meet pork industry demands

Producing barley varieties that have incrased grain yield and consistent or higher energy for pigs, as well as resistance to the major diseases of barley.

Cross-industry preparedness for Cotton leaf curl disease

Cotton leaf curl disease (CLCuD) is a major biosecurity threat to the Australian cotton industry. This proposal seeks cross-industry investment from the cotton (CRDC) and horticulture (HAL) industries to address the threat of exotic whitefly-transmitted viruses. Testing of silverleaf whitefly, the vector of CLCuD, could provide an alternative, cheaper strategy for early warning disease surveillance compared to surveys for disease symptoms. Control of whitefly-transmitted viruses in Australia and overseas will be reviewed to produce an integrated management package for their control in Australia. This will also involve a workshop with key stakeholders and selected overseas participants, to develop a working party to help formulate this package.

Benchmarking water management in the Australian cotton industry

Benchmarking irrigation performance has always been a challenge. As part of the Rural Water Use Efficiency (RWUE3) project the team in, collaboration with the Cotton Catchments Communities CRC, National Certificate of Educational Achievement and the Knowledge Management Phase 2 project, aimed to standardise the irrigation indices in use within the cotton industry. This was achieved through: - the delivery of training workshops - access to benchmarking tools - promotion of benchmarking as a best practice to be adopted on farm.

The Potential for a New Value Adding Industry for Noni Tropical Fruit Producers

Morinda citrifolia (noni) grows widely throughout the Pacific and is native to Australia. It is a source of traditional medicine amongst Coastal Aboriginal Communities in Cape York, the Pacific Islands and South East Asia, and in recent years has experienced significant economic growth worldwide through a variety of health and cosmetic claims. The largest markets for noni are North America, Europe, Japan, Mexico, Asia and Australia with the worldwide market for these products estimated at US$400 million.

Economic evaluation of precision controlled traffic farming in the Australian sugar industry: a case study of an early adopter

Controlled traffic has been identified as the most practical method of reducing compaction-related soil structural degradation in the Australian sugarcane industry. GPS auto-steer systems are required to maximize this potential. Unfortunately there is a perception that little economic gain will result from investing in this technology. Regardless, a number of growers have made the investment and are reaping substantial economic and lifestyle rewards. In this paper we assess the cost effectiveness of installing GPS guidance and using it to implement Precision Controlled Traffic Farming (PCTF) based on the experience of an early adopter. The Farm Economic Analysis Tool (FEAT) model was used with data provided by the grower to demonstrate the benefits of implementing PCTF. The results clearly show that a farming system based on PCTF and the minimum tillage improved farm gross margin by 11.8% and reduced fuel usage by 58%, compared to producers' traditional practice. PCTF and minimum tillage provide sugar producers with a tool to manage the price cost squeeze at a time of low sugar prices. These data provide producers with the evidence that investment in PCTF is economically prudent.

The Queensland forest industry

An overview of the commercial growing, management and processing of forest products in Queensland.

Harvest strategy evaluations and co-management for the Moreton Bay Trawl Fishery

Non-Technical Summary Seafood CRC Project 2009/774. Harvest strategy evaluations and co-management for the Moreton Bay Trawl Fishery Principal Investigator: Dr Tony Courtney, Principal Fisheries Biologist Fisheries and Aquaculture, Agri-Science Queensland Department of Agriculture, Fisheries and Forestry Level B1, Ecosciences Precinct, Joe Baker St, Dutton Park, Queensland 4102 Email: tony.courtney@daff.qld.gov.au Project objectives: 1. Review the literature and data (i.e., economic, biological and logbook) relevant to the Moreton Bay trawl fishery. 2. Identify and prioritise management objectives for the Moreton Bay trawl fishery, as identified by the trawl fishers. 3. Undertake an economic analysis of Moreton Bay trawl fishery. 4. Quantify long-term changes to fishing power for the Moreton Bay trawl fishery. 5. Assess priority harvest strategies identified in 2 (above). Present results to, and discuss results with, Moreton Bay Seafood Industry Association (MBSIA), fishers and Fisheries Queensland. Note: Additional, specific objectives for 2 (above) were developed by fishers and the MBSIA after commencement of the project. These are presented in detail in section 5 (below). The project was an initiative of the MBSIA, primarily in response to falling profitability in the Moreton Bay prawn trawl fishery. The analyses were undertaken by a consortium of DAFF, CSIRO and University of Queensland researchers. This report adopted the Australian Standard Fish Names (http://www.fishnames.com.au/). Trends in catch and effort The Moreton Bay otter trawl fishery is a multispecies fishery, with the majority of the catch composed of Greasyback Prawns (Metapenaeus bennettae), Brown Tiger Prawns (Penaeus esculentus), Eastern King Prawns (Melicertus plebejus), squid (Uroteuthis spp., Sepioteuthis spp.), Banana Prawns (Fenneropenaeus merguiensis), Endeavour Prawns (Metapenaeus ensis, Metapenaeus endeavouri) and Moreton Bay bugs (Thenus parindicus). Other commercially important byproduct includes blue swimmer crabs (Portunus armatus), three-spot crabs (Portunus sanguinolentus), cuttlefish (Sepia spp.) and mantis shrimp (Oratosquilla spp.). Logbook catch and effort data show that total annual reported catch of prawns from the Moreton Bay otter trawl fishery has declined to 315 t in 2008 from a maximum of 901 t in 1990. The number of active licensed vessels participating in the fishery has also declined from 207 in 1991 to 57 in 2010. Similarly, fishing effort has fallen from a peak of 13,312 boat-days in 1999 to 3817 boat-days in 2008 – a 71% reduction. The declines in catch and effort are largely attributed to reduced profitability in the fishery due to increased operational costs and depressed prawn prices. The low prawn prices appear to be attributed to Australian aquacultured prawns and imported aquacultured vannamei prawns, displacing the markets for trawl-caught prawns, especially small species such as Greasyback Prawns which traditionally dominated landings in Moreton Bay. In recent years, the relatively high Australian dollar has resulted in reduced exports of Australian wild-caught prawns. This has increased supply on the domestic market which has also suppressed price increases. Since 2002, Brown Tiger Prawns have dominated annual reported landings in the Moreton Bay fishery. While total catch and effort in the bay have declined to historically low levels, the annual catch and catch rates of Brown Tiger Prawns have been at record highs in recent years. This appears to be at least partially attributed to the tiger prawn stock having recovered from excessive effort in previous decades. The total annual value of the Moreton Bay trawl fishery catch, including byproduct, is about $5 million, of which Brown Tiger Prawns account for about $2 million. Eastern King Prawns make up about 10% of the catch and are mainly caught in the bay from October to December as they migrate to offshore waters outside the bay where they contribute to a large mono-specific trawl fishery. Some of the Eastern King Prawns harvested in Moreton Bay may be growth overfished (i.e., caught below the size required to maximise yield or value), although the optimum size-at-capture was not determined in this study. Banana Prawns typically make up about 5% of the catch, but can exceed 20%, particularly following heavy rainfall. Economic analysis of the fishery From the economic survey, cash profits were, on average, positive for both fleet segments in both years of the survey. However, after the opportunity cost of capital and depreciation were taken into account, the residual owner-operator income was relatively low, and substantially lower than the average share of revenue paid to employed skippers. Consequently, owner-operators were earning less than their opportunity cost of their labour, suggesting that the fleets were economically unviable in the longer term. The M2 licensed fleet were, on average, earning similar boat cash profits as the T1/M1 fleet, although after the higher capital costs were accounted for the T1/M1 boats were earning substantially lower returns to owner-operator labour. The mean technical efficiency for the fleet as a whole was estimated to be 0.67. That is, on average, the boats were only catching 67 per cent of what was possible given their level of inputs (hours fished and hull units). Almost one-quarter of observations had efficiency scores above 0.8, suggesting a substantial proportion of the fleet are relatively efficient, but some are also relatively inefficient. Both fleets had similar efficiency distributions, with median technical efficiency score of 0.71 and 0.67 for the M2 and T1/M1 boats respectively. These scores are reasonably consistent with other studies of prawn trawl fleets in Australia, although higher average efficiency scores were found in the NSW prawn trawl fleet. From the inefficiency model, several factors were found to significantly influence vessel efficiency. These included the number of years of experience as skipper, the number of generations that the skipper’s family had been fishing and the number of years schooling. Skippers with more schooling were significantly more efficient than skippers with lower levels of schooling, consistent with other studies. Skippers who had been fishing longer were, in fact, less efficient than newer skippers. However, this was mitigated in the case of skippers whose family had been involved in fishing for several generations, consistent with other studies and suggesting that skill was passed through by families over successive generations. Both the linear and log-linear regression models of total fishing effort against the marginal profit per hour performed reasonably well, explaining between 70 and 84 per cent of the variation in fishing effort. As the models had different dependent variables (one logged and the other not logged) this is not a good basis for model choice. A better comparator is the square root of the mean square error (SMSE) expressed as a percentage of the mean total effort. On this criterion, both models performed very similarly. The linear model suggests that each additional dollar of average profits per hour in the fishery increases total effort by around 26 hours each month. From the log linear model, each percentage increase in profits per hour increases total fishing effort by 0.13 per cent. Both models indicate that economic performance is a key driver of fishing effort in the fishery. The effect of removing the boat-replacement policy is to increase individual vessel profitability, catch and effort, but the overall increase in catch is less than that removed by the boats that must exit the fishery. That is, the smaller fleet (in terms of boat numbers) is more profitable but the overall catch is not expected to be greater than before. This assumes, however, that active boats are removed, and that these were also taking an average level of catch. If inactive boats are removed, then catch of the remaining group as a whole could increase by between 14 and 17 per cent depending on the degree to which costs are reduced with the new boats. This is still substantially lower than historical levels of catch by the fleet. Fishing power analyses An analysis of logbook data from 1988 to 2010, and survey information on fishing gear, was performed to estimate the long-term variation in the fleet’s ability to catch prawns (known as fishing power) and to derive abundance estimates of the three most commercially important prawn species (i.e., Brown Tiger, Eastern King and Greasyback Prawns). Generalised linear models were used to explain the variation in catch as a function of effort (i.e., hours fished per day), vessel and gear characteristics, onboard technologies, population abundance and environmental factors. This analysis estimated that fishing power associated with Brown Tiger and Eastern King Prawns increased over the past 20 years by 10–30% and declined by approximately 10% for greasybacks. The density of tiger prawns was estimated to have almost tripled from around 0.5 kg per hectare in 1988 to 1.5 kg/ha in 2010. The density of Eastern King Prawns was estimated to have fluctuated between 1 and 2 kg per hectare over this time period, without any noticeable overall trend, while Greasyback Prawn densities were estimated to have fluctuated between 2 and 6 kg per hectare, also without any distinctive trend. A model of tiger prawn catches was developed to evaluate the impact of fishing on prawn survival rates in Moreton Bay. The model was fitted to logbook data using the maximum-likelihood method to provide estimates of the natural mortality rate (0.038 and 0.062 per week) and catchability (which can be defined as the proportion of the fished population that is removed by one unit of effort, in this case, estimated to be 2.5 ± 0.4 E-04 per boat-day). This approach provided a method for industry and scientists to develop together a realistic model of the dynamics of the fishery. Several aspects need to be developed further to make this model acceptable to industry. Firstly, there is considerable evidence to suggest that temperature influences prawn catchability. This ecological effect should be incorporated before developing meaningful harvest strategies. Secondly, total effort has to be allocated between each species. Such allocation of effort could be included in the model by estimating several catchability coefficients. Nevertheless, the work presented in this report is a stepping stone towards estimating essential fishery parameters and developing representative mathematical models required to evaluate harvest strategies. Developing a method that allowed an effective discussion between industry, management and scientists took longer than anticipated. As a result, harvest strategy evaluations were preliminary and only included the most valuable species in the fishery, Brown Tiger Prawns. Additional analyses and data collection, including information on catch composition from field sampling, migration rates and recruitment, would improve the modelling. Harvest strategy evaluations As the harvest strategy evaluations are preliminary, the following results should not be adopted for management purposes until more thorough evaluations are performed. The effects, of closing the fishery for one calendar month, on the annual catch and value of Brown Tiger Prawns were investigated. Each of the 12 months (i.e., January to December) was evaluated. The results were compared against historical records to determine the magnitude of gain or loss associated with the closure. Uncertainty regarding the trawl selectivity was addressed using two selectivity curves, one with a weight at 50% selection (S50%) of 7 g, based on research data, and a second with S50% of 14 g, put forward by industry. In both cases, it was concluded that any monthly closure after February would not be beneficial to the industry. The magnitude of the benefit of closing the fishery in either January or February was sensitive to which mesh selectivity curve that was assumed, with greater benefit achieved when the smaller selectivity curve (i.e., S50% = 7 g) was assumed. Using the smaller selectivity (S50% = 7 g), the expected increase in catch value was 10–20% which equates to $200,000 to $400,000 annually, while the larger selectivity curve (S50% = 14 g) suggested catch value would be improved by 5–10%, or $100,000 to $200,000. The harvest strategy evaluations showed that greater benefits, in the order of 30–60% increases in the tiger annual catch value, could have been obtained by closing the fishery early in the year when annual effort levels were high (i.e., > 10,000 boat-days). In recent years, as effort levels have declined (i.e., ~4000 boat-days annually), expected benefits from such closures are more modest. In essence, temporal closures offer greater benefit when fishing mortality rates are high. A spatial analysis of Brown Tiger Prawn catch and effort was also undertaken to obtain a better understanding of the prawn population dynamics. This indicated that, to improve profitability of the fishery, fishers could consider closing the fishery in the period from June to October, which is already a period of low profitability. This would protect the Brown Tiger Prawn spawning stock, increase catch rates of all species in the lucrative pre-Christmas period (November–December), and provide fishers with time to do vessel maintenance, arrange markets for the next season’s harvest, and, if they wish, work at other jobs. The analysis found that the instantaneous rate of total mortality (Z) for the March–June period did not vary significantly over the last two decades. As the Brown Tiger Prawn population in Moreton Bay has clearly increased over this time period, an interesting conclusion is that the instantaneous rate of natural mortality (M) must have increased, suggesting that tiger prawn natural mortality may be density-dependent at this time of year. Mortality rates of tiger prawns for June–October were found to have decreased over the last two decades, which has probably had a positive effect on spawning stocks in the October–November spawning period. Abiotic effects on the prawns The influence of air temperature, rainfall, freshwater flow, the southern oscillation index (SOI) and lunar phase on the catch rates of the four main prawn species were investigated. The analyses were based on over 200,000 daily logbook catch records over 23 years (i.e., 1988–2010). Freshwater flow was more influential than rainfall and SOI, and of the various sources of flow, the Brisbane River has the greatest volume and influence on Moreton Bay prawn catches. A number of time-lags were also considered. Flow in the preceding month prior to catch (i.e., 30 days prior, Logflow1_30) and two months prior (31–60 days prior, Logflow31_60) had strong positive effects on Banana Prawn catch rates. Average air temperature in the preceding 4-6 months (Temp121_180) also had a large positive effect on Banana Prawn catch rates. Flow in the month immediately preceding catch (Logflow1_30) had a strong positive influence on Greasyback Prawn catch rates. Air temperature in the preceding two months prior to catch (Temp1_60) had a large positive effect on Brown Tiger Prawn catch rates. No obvious or marked effects were detected for Eastern King Prawns, although interestingly, catch rates declined with increasing air temperature 4–6 months prior to catch. As most Eastern King Prawn catches in Moreton Bay occur in October to December, the results suggest catch rates decline with increasing winter temperatures. In most cases, the prawn catch rates declined with the waxing lunar phase (high luminance/full moon), and increased with the waning moon (low luminance/new moon). The SOI explains little additional variation in prawn catch rates (~ <2%), although its influence was higher for Banana Prawns. Extrapolating findings of the analyses to long-term climate change effects should be interpreted with caution. That said, the results are consistent with likely increases in abundance in the region for the two tropical species, Banana Prawns and Brown Tiger Prawns, as coastal temperatures rise. Conversely, declines in abundance could be expected for the two temperate species, Greasyback and Eastern King Prawns. Corporate management structures An examination of alternative governance systems was requested by the industry at one of the early meetings, particularly systems that may give them greater autonomy in decision making as well as help improve the marketing of their product. Consequently, a review of alternative management systems was undertaken, with a particular focus on the potential for self-management of small fisheries (small in terms of number of participants) and corporate management. The review looks at systems that have been implemented or proposed for other small fisheries internationally, with a particular focus on self-management as well as the potential benefits and challenges for corporate management. This review also highlighted particular opportunities for the Moreton Bay prawn fishery. Corporate management differs from other co-management and even self-management arrangements in that ‘ownership’ of the fishery is devolved to a company in which fishers and government are shareholders. The company manages the fishery as well as coordinates marketing to ensure that the best prices are received and that the catch taken meets the demands of the market. Coordinated harvesting will also result in increased profits, which are returned to fishers in the form of dividends. Corporate management offers many of the potential benefits of an individual quota system without formally implementing such a system. A corporate management model offers an advantage over a self-management model in that it can coordinate both marketing and management to take advantage of this unique geographical advantage. For such a system to be successful, the fishery needs to be relatively small and self- contained. Small in this sense is in terms of number of operators. The Moreton Bay prawn fishery satisfies these key conditions for a successful self-management and potentially corporate management system. The fishery is small both in terms of number of participants and geography. Unlike other fisheries that have progressed down the self-management route, the key market for the product from the Moreton Bay fishery is right at its doorstep. Corporate management also presents a number of challenges. First, it will require changes in the way fishers operate. In particular, the decision on when to fish and what to catch will be taken away from the individual and decided by the collective. Problems will develop if individuals do not join the corporation but continue to fish and market their own product separately. While this may seem an attractive option to fishers who believe they can do better independently, this is likely to be just a short- term advantage with an overall long-run cost to themselves as well as the rest of the industry. There are also a number of other areas that need further consideration, particularly in relation to the allocation of shares, including who should be allocated shares (e.g. just boat owners or also some employed skippers). Similarly, how harvesting activity is to be allocated by the corporation to the fishers. These are largely issues that cannot be answered without substantial consultation with those likely to be affected, and these groups cannot give these issues serious consideration until the point at which they are likely to become a reality. Given the current structure and complexity of the fishery, it is unlikely that such a management structure will be feasible in the short term. However, the fishery is a prime candidate for such a model, and development of such a management structure in the future should be considered as an option for the longer term.

Relocation of Intensive Agriculture to Northern Australia: The Case of the Rice Industry

Development of new agricultural industries in northern Australia is seen as a way to provide food security in the face of reduced water availability in existing regions in the south. This report aims to identify some of the possible economic consequences of developing a rice industry in the Burdekin region, while there is a reduction of output in the Riverina. Annual rice production in the Riverina peaked at 1.7 M tonnes, but the long-term outlook, given climate change impacts on that region and government water buy-backs, is more likely to be less than 800,000 tonnes. Growers are highly efficient water users by international standards, but the ability to offset an anticipated reduction in water availability through further efficiency gains is limited. In recent years growers in the Riverina have diversified their farms to a greater extent and secondary production systems include beef, sheep and wheat. Production in north Queensland is in its infancy, but a potentially suitable farming system has been developed by including rice within the sugarcane system without competition and in fact contributing to the production of sugar by increasing yields and controlling weeds. The economic outcomes are estimated a large scale, dynamic, computable general equilibrium (CGE) model of the world economy (Tasman Global), scaled down to regional level. CGE models mimic the workings of the economy through a system of interdependent behavioural and accounting equations which are linked to an input-output database. When an economic shock or change is applied to a model, each of the markets adjusts according to the set of behavioural parameters which are underpinned by economic theory. In this study the model is driven by reducing production in the Riverina in accordance with relationships found between water availability and the production of rice and replacement by other crops and by increasing ride production in the Burdekin. Three scenarios were considered: • Scenario 1: Rice is grown using the fallow period between the last ratoon crop of sugarcane and the new planting. In this scenario there is no competition between rice and sugarcane • Scenario 2: Rice displaces sugarcane production • Scenario 3: Rice is grown on additional land and does not compete with sugarcane. Two time periods were used, 2030 and 2070, which are the conventional time points to consider climate change impacts. Under scenario 1, real economic output declines in the Riverina by $45 million in 2030 and by $139 million in 2070. This is only partially offset by the increased real economic output in the Burdekin of $35 million and $131 million respectively.

Relocation of Intensive Agriculture to Northern Queensland The Cotton Industry

Development of new agricultural industries in northern Australia is often perceived as a solution to changes in water availability that have occurred within southern Australia as a result of changes to government policy in response to and exacerbated by climate change. This report examines the likely private, social and community costs and benefits associated with the establishment of a cotton industry in the Burdekin. The research undertaken covers three spatial scales by modelling the response of cotton and to climate change at the crop and farm scale and linking this to regional scale modelling of the economy. Modelling crop growth as either a standalone crop or as part of a farm enterprise provides the clearest picture of how yields and water use will be affected under climate change. The alternative to this is to undertake very costly trials in environmental chambers. For this reason it is critical that funding for model development especially for crops being crop in novel environments be seen as a high priority for climate change and adaptation studies. Crop level simulations not only provide information on how the crop responds to climate change, they also illustrate that that these responses are the result of complex interactions and cannot necessarily be derived from the climate information alone. These simulations showed that climate change would lead to decreased cotton yields in 2030 and 2050 without the affect of CO2 fertilisation. Without CO2 fertilisation, yields would be decreased by 3.2% and 17.8%. Including CO2 fertilisation increased yields initially by 5.9%, but these were reduced by 3.6% in 2050. This still represents a major offset and at least ameliorates the impact of climate change on yield. To cope with the decreased in-crop rainfall (4.5% by 2030 and 15.8% in 2050) and an initial increase in evapotranspiration of 2% in 2030 and