Land condition monitoring information for reef catchments: a new era

Land condition monitoring information is required for the strategic management of grazing land and for a better understanding of ecosystem processes. Yet, for policy makers and those land managers whose properties are situated within north-eastern Australia's vast Great Barrier Reef catchments, there has been a general lack of geospatial land condition monitoring information. This paper provides an overview of integrated land monitoring activity in rangeland areas of two major Reef catchments in Queensland: the Burdekin and Fitzroy regions. The project aims were to assemble land condition monitoring datasets that would assist grazing land management and support decision-makers investing public funds; and deliver these data to natural resource management(NRM) community groups, which had been given increased responsibility for delivering local environmental outcomes. We describe the rationale and processes used to produce new land condition monitoring datasets derived from remotely sensed Landsat thematic mapper (TM) and high resolution SPOT 5 satellite imagery and from rapid land condition ground assessment. Specific products include subcatchment groundcover change maps, regional mapping of indicative very poor land condition, and stratified land condition site summaries. Their application, integration, and limitations are discussed. The major innovation is a better understanding of NRM issues with respect to land condition across vast regional areas, and the effective transfer of decision-making capacity to the local level. Likewise, with an increased ability to address policy questions from an evidence-based position, combined with increased cooperation between community, industry and all levels of government, a new era has emerged for decision-makers in rangeland management.

Using harvest statistics to monitor temporal variation in kangaroo density and harvest rate

Management of the commercial harvest of kangaroos relies on quotas set annually as a proportion of regular estimates of population size. Surveys to generate these estimates are expensive and, in the larger states, logistically difficult; a cheaper alternative is desirable. Rainfall is a disappointingly poor predictor of kangaroo rate of increase in many areas, but harvest statistics (sex ratio, carcass weight, skin size and animals shot per unit time) potentially offer cost-effective indirect monitoring of population abundance (and therefore trend) and status (i.e. under-or overharvest). Furthermore, because harvest data are collected continuously and throughout the harvested areas, they offer the promise of more intensive and more representative coverage of harvest areas than aerial surveys do. To be useful, harvest statistics would need to have a close and known relationship with either population size or harvest rate. We assessed this using longterm (11-22 years) data for three kangaroo species (Macropus rufus, M. giganteus and M. fuliginosus) and common wallaroos (M. robustus) across South Australia, New South Wales and Queensland. Regional variation in kangaroo body size, population composition, shooter efficiency and selectivity required separate analyses in different regions. Two approaches were taken. First, monthly harvest statistics were modelled as a function of a number of explanatory variables, including kangaroo density, harvest rate and rainfall. Second, density and harvest rate were modelled as a function of harvest statistics. Both approaches incorporated a correlated error structure. Many but not all regions had relationships with sufficient precision to be useful for indirect monitoring. However, there was no single relationship that could be applied across an entire state or across species. Combined with rainfall-driven population models and applied at a regional level, these relationships could be used to reduce the frequency of aerial surveys without compromising decisions about harvest management.

Sustaining productivity of tropical red snappers using new monitoring and reference points

OBJECTIVES: 1. Analyse current monitoring and logbook data sets, as well as survey and other information,to establish whether these data provide sufficient power to develop critical indicators of fishery performance. 2. Provide a risk analysis that examines the use of age structure and catch rate information for development of critical indicators, and response rules for those criteria, in the absence of other fishery information. 3. Develop a monitoring program that uses commercial vessels from the fishery to provide independent data.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.

The importance of cotton disease surveys in Queensland for monitoring endemic diseases and detecting new pathogens and pests

The cotton industry in Australia funds biannual disease surveys conducted by plant pathologists. The objective of these surveys is to monitor the distribution and importance of key endemic pests and record the presence or absence of new or exotic diseases. Surveys have been conducted in Queensland since 2002/03, with surveillance undertaken by experienced plant pathologists. Monitoring of endemic diseases indicates the impact of farming practices on disease incidence and severity. The information collected gives direction to cotton disease research. Routine diagnostics has provided early detection of new disease problems which include 1) the identification of Nematospora coryli, a pathogenic yeast associated with seed and internal boll rot; and 2) Rotylenchulus reniformis, a plant-parasitic nematode. This finding established the need for an intensive survey of the Theodore district revealing that reniform was prevalent across the district at populations causing up to 30% yield loss. Surveys have identified an exotic defoliating strain (VCG 1A) and non-defoliating strains of Verticillium dahliae, which cause Verticillium wilt. An intensive study of the diversity of V. dahliae and the impact these strains have on cotton are underway. Results demonstrate the necessity of general multi-pest surveillance systems in broad acre agriculture in providing (1) an ongoing evaluation of current integrated disease management practices and (2) early detection for a suite of exotic pests and previously unknown pests.

Correlation of plasma IGF-I concentrations and growth rate in aquacultured finfish: a tool for assessing the potential of new diets

A recently developed radioimmunoassay (RIA) for measuring insulin-like growth factor (IGF-I) in a variety of fish species was used to investigate the correlation between growth rate and circulating IGF-I concentrations of barramundi (Lates calcarifer), Atlantic salmon (Salmo salar) and Southern Bluefin tuna (Thunnus maccoyii). Plasma IGF-I concentration significantly increased with increasing ration size in barramundi and IGF-I concentration was positively correlated to growth rates obtained in Atlantic salmon (r2=0.67) and barramundi (r2=0.65) when fed a variety of diet formulations. IGF-I was also positively correlated to protein concentration (r2=0.59). This evidence suggested that measuring IGF-I concentration may provide a useful tool for monitoring fish growth rate and also as a method to rapidly assess different aquaculture diets. However, no such correlation was demonstrated in the tuna study probably due to seasonal cooling of sea surface temperature shortly before blood was sampled. Thus, some recommendations for the design and sampling strategy of nutritional trials where IGF-I concentrations are measured are discussed

Stock assessment of the Queensland-New South Wales tailor fishery (Pomatomus saltatrix)

Data on catch sizes, catch rates, length-frequency and age composition from the Australian east coast tailor fishery are analysed by three different population dynamic models: a surplus production model, an age-structured model, and a model in which the population is structured by both age and length. The population is found to be very heavily exploited, with its ability to reproduce dependent on the fishery’s incomplete selectivity of one-year-old fish. Estimates of recent harvest rates (proportion of fish available to the fishery that are actually caught in a single year) are over 80%. It is estimated that only 30–50% of one-year-old fish are available to the fishery. Results from the age-length-structured model indicate that both exploitable biomass (total mass of fish selected by the fishery) and egg production have fallen to about half the levels that prevailed in the 1970s, and about 40% of virgin levels. Two-year-old fish appear to have become smaller over the history of the fishery. This is assumed to be due to increased fishing pressure combined with non-selectivity of small one-year-old fish, whereby the one-year-old fish that survive fishing are small and grow into small two-year-old fish the following year. An alternative hypothesis is that the stock has undergone a genetic change towards smaller fish; the true explanation is unknown. The instantaneous natural mortality rate of tailor is hypothesised to be higher than previously thought, with values between 0.8 and 1.3 yr–1 consistent with the models. These values apply only to tailor up to about three years of age, and it is possible that a lower value applies to fish older than three. The analysis finds no evidence that fishing pressure has yet affected recruitment. If a recruitment downturn were to occur, however, under current management and fishing pressure there is a strong chance that the fishery would need a complete closure for several years to recover, and even then recovery would be uncertain. Therefore it is highly desirable to better protect the spawning stock. The major recommendations are • An increase in the minimum size limit from 30cm to 40cm in order to allow most one-year-old fish to spawn, and • An experiment on discard mortality to gauge the proportion of fish between 30cm and 40cm that are likely to survive being caught and released by recreational line fishers (the dominant component of the fishery, currently harvesting roughly 1000t p.a. versus about 200t p.a. from the commercial fishery).

A new data source for fisheries resource assessment: genetic estimates of the effective number of spawners. Final Report to the Fisheries Research and Development Corporation.

The development of innovative methods of stock assessment is a priority for State and Commonwealth fisheries agencies. It is driven by the need to facilitate sustainable exploitation of naturally occurring fisheries resources for the current and future economic, social and environmental well being of Australia. This project was initiated in this context and took advantage of considerable recent achievements in genomics that are shaping our comprehension of the DNA of humans and animals. The basic idea behind this project was that genetic estimates of effective population size, which can be made from empirical measurements of genetic drift, were equivalent to estimates of the successful number of spawners that is an important parameter in process of fisheries stock assessment. The broad objectives of this study were to 1. Critically evaluate a variety of mathematical methods of calculating effective spawner numbers (Ne) by a. conducting comprehensive computer simulations, and by b. analysis of empirical data collected from the Moreton Bay population of tiger prawns (P. esculentus). 2. Lay the groundwork for the application of the technology in the northern prawn fishery (NPF). 3. Produce software for the calculation of Ne, and to make it widely available. The project pulled together a range of mathematical models for estimating current effective population size from diverse sources. Some of them had been recently implemented with the latest statistical methods (eg. Bayesian framework Berthier, Beaumont et al. 2002), while others had lower profiles (eg. Pudovkin, Zaykin et al. 1996; Rousset and Raymond 1995). Computer code and later software with a user-friendly interface (NeEstimator) was produced to implement the methods. This was used as a basis for simulation experiments to evaluate the performance of the methods with an individual-based model of a prawn population. Following the guidelines suggested by computer simulations, the tiger prawn population in Moreton Bay (south-east Queensland) was sampled for genetic analysis with eight microsatellite loci in three successive spring spawning seasons in 2001, 2002 and 2003. As predicted by the simulations, the estimates had non-infinite upper confidence limits, which is a major achievement for the application of the method to a naturally-occurring, short generation, highly fecund invertebrate species. The genetic estimate of the number of successful spawners was around 1000 individuals in two consecutive years. This contrasts with about 500,000 prawns participating in spawning. It is not possible to distinguish successful from non-successful spawners so we suggest a high level of protection for the entire spawning population. We interpret the difference in numbers between successful and non-successful spawners as a large variation in the number of offspring per family that survive – a large number of families have no surviving offspring, while a few have a large number. We explored various ways in which Ne can be useful in fisheries management. It can be a surrogate for spawning population size, assuming the ratio between Ne and spawning population size has been previously calculated for that species. Alternatively, it can be a surrogate for recruitment, again assuming that the ratio between Ne and recruitment has been previously determined. The number of species that can be analysed in this way, however, is likely to be small because of species-specific life history requirements that need to be satisfied for accuracy. The most universal approach would be to integrate Ne with spawning stock-recruitment models, so that these models are more accurate when applied to fisheries populations. A pathway to achieve this was established in this project, which we predict will significantly improve fisheries sustainability in the future. Regardless of the success of integrating Ne into spawning stock-recruitment models, Ne could be used as a fisheries monitoring tool. Declines in spawning stock size or increases in natural or harvest mortality would be reflected by a decline in Ne. This would be good for data-poor fisheries and provides fishery independent information, however, we suggest a species-by-species approach. Some species may be too numerous or experiencing too much migration for the method to work. During the project two important theoretical studies of the simultaneous estimation of effective population size and migration were published (Vitalis and Couvet 2001b; Wang and Whitlock 2003). These methods, combined with collection of preliminary genetic data from the tiger prawn population in southern Gulf of Carpentaria population and a computer simulation study that evaluated the effect of differing reproductive strategies on genetic estimates, suggest that this technology could make an important contribution to the stock assessment process in the northern prawn fishery (NPF). Advances in the genomics world are rapid and already a cheaper, more reliable substitute for microsatellite loci in this technology is available. Digital data from single nucleotide polymorphisms (SNPs) are likely to super cede ‘analogue’ microsatellite data, making it cheaper and easier to apply the method to species with large population sizes.

New tools for management of phosphine resistance

Phosphine is the primary fumigant used to protect the majority of the world' s grain and a variety of other stored commodities from insect pests. Phosphine is playing an increasingly important role in the protection of commodities for two primary reasons. Firstly, use of the alternative fumigant, methyl bromide, has been sharply curtailed and is tightly regulated due to its role in ozone depletion, and secondly, consumers are becoming increasingly intolerant of contact pesticides. Niche alternatives to phosphine exist, but they suffer from a range of factors that limit their use, including: 1) Limited commercial adoption due to expense or slow mode of action; 2) Poor efficacy due to low toxicity, rapid sorption, limited volatility or high density; 3) Public health concerns due to toxicity to handlers or nearby residents, as well as risk of explosion; 4) Poor consumer acceptance due to toxic residues or smell. These same factors limit the prospects of quickly identifying and deploying a new fumigant. Given that resistance toward phosphine is increasing among insect pests, improved monitoring and management of resistance is a priority. Knowledge of the mode of action of phosphine as well as the mechanisms of resistance may also greatly reduce the effort and expense of identifying synergists or novel replacement compounds.

Simulating pasture growth rates in Australian and New Zealand grazing systems

DairyMod, EcoMod, and the SGS Pasture Model are mechanistic biophysical models developed to explore scenarios in grazing systems. The aim of this manuscript was to test the ability of the models to simulate net herbage accumulation rates of ryegrass-based pastures across a range of environments and pasture management systems in Australia and New Zealand. Measured monthly net herbage accumulation rate and accumulated yield data were collated from ten grazing system experiments at eight sites ranging from cool temperate to subtropical environments. The local climate, soil, pasture species, and management (N fertiliser, irrigation, and grazing or cutting pattern) were described in the model for each site, and net herbage accumulation rates modelled. The model adequately simulated the monthly net herbage accumulation rates across the range of environments, based on the summary statistics and observed patterns of seasonal growth, particularly when the variability in measured herbage accumulation rates was taken into account. Agreement between modelled and observed growth rates was more accurate and precise in temperate than in subtropical environments, and in winter and summer than in autumn and spring. Similarly, agreement between predicted and observed accumulated yields was more accurate than monthly net herbage accumulation. Different temperature parameters were used to describe the growth of perennial ryegrass cultivars and annual ryegrass; these differences were in line with observed growth patterns and breeding objectives. Results are discussed in the context of the difficulties in measuring pasture growth rates and model limitations.

Seagrass-Watch: Engaging Torres Strait Islanders in marine habitat monitoring

Involvement in scientifically structured habitat monitoring is a relatively new concept to the peoples of Torres Strait. The approach we used was to focus on awareness, and to build the capacity of groups to participate using Seagrass-Watch as the vehicle to provide education and training in monitoring marine ecosystems. The project successfully delivered quality scientifically rigorous baseline information on the seasonality of seagrasses in the Torres Strait-a first for this region. Eight seagrass species were identified across the monitoring sites. Seagrass cover varied within and between years. Preliminary evidence indicated that drivers for seagrass variability were climate related. Generally, seagrass abundance increased during the north-west monsoon (Kuki), possibly a consequence of elevated nutrients, lower tidal exposure times, less wind, and higher air temperatures. Low seagrass abundance coincided with the presence of greater winds and longer periods of exposure at low tides during the south-east trade wind season (Sager). No seasonal patterns were apparent when frequency of disturbance from high sedimentation and human impacts was high. Seagrass-Watch has been incorporated in to the Thursday Island High School's Marine Studies Unit ensuring continuity of monitoring. The students, teachers, and other interested individuals involved in Seagrass-Watch have mastered the necessary scientific procedures to monitor seagrass meadows, and developed skills in coordinating a monitoring program and skills in mentoring younger students. This has increased the participants' self-esteem and confidence, and given them an insight into how they may participate in the future management of their sea country.

Reassessing spatial and temporal dynamics of kangaroo populations

Long-running datasets from aerial surveys of kangaroos (Macropus giganteus, Macropus [uliginosus, Macropus robustus and Macropus rufus) across Queensland, New South Wales and South Australia have been analysed, seeking better predictors of rates of increase which would allow aerial surveys to be undertaken less frequently than annually. Early models of changes in kangaroo numbers in response to rainfall had shown great promise, but much variability. We used normalised difference vegetation index (NDVI) instead, reasoning that changes in pasture condition would provide a better predictor than rainfall. However, except at a fine scale, NDVI proved no better; although two linked periods of rainfall proved useful predictors of rates of increase, this was only in some areas for some species. The good correlations reported in earlier studies were a consequence of data dominated by large droughtinduced adult mortality, whereas over a longer time frame and where changes between years are less dramatic, juvenile survival has the strongest influence on dynamics. Further, harvesting, density dependence and competition with domestic stock are additional and important influences and it is now clear that kangaroo movement has a greater influence on population dynamics than had been assumed. Accordingly, previous conclusions about kangaroo populations as simple systems driven by rainfall need to be reassessed. Examination of this large dataset has permitted descriptions of shifts in distribution of three species across eastern Australia, changes in dispersion in response to rainfall, and an evaluation of using harvest statistics as an index of density and harvest rate. These results have been combined into a risk assessment and decision theory framework to identify optimal monitoring strategies.

Fisheries Queensland Long Term Monitoring Program Underwater Visual Census of twenty-four reefs on the Great Barrier Reef between 1999 and 2004.

In 1999, the Department of Employment, Economic Development and Innovation (DEEDI), Fisheries Queensland undertook a new initiative to collect long term monitoring data of various important stocks including reef fish. This data and monitoring manual for the reef fish component of that program which was based on Underwater Visual Census methodology of 24 reefs on the Great Barrier Reef between 1999 and 2004. Data was collected using six 50m x 5m transects at 4 sites on 24 reefs. Benthic cover type was also recorded for 10m of each transect. The attached Access Database contains 5 tables being: SITE DETAILS TABLE Survey year Data entry complete REF survey site ID Site # (1-4) Location (reef name) Site Date (date surveyed) Observer 1 (3 initials to identify who estimated fish lengths and recorded benthic cover) TRANSECT DETAILS Survey ID Transect Number (1-6) Time (the transect was surveyed) Visibility (in metres) Minimum Depth surveyed (m) Maximum Depth surveyed (m) Percent of survey completed (%) Comments SUBSTRATE Survey ID Transect Number (1-6) then % cover of each of eth following categories of benthic cover types Dead Coral Live Coral Soft Coral Rubble Sand Sponge Algae Sea Grass Other COORDINATES (over survey sites) from -14 38.792 to -19 44.233 and from 145 21.507 to 149 55.515 SIGHTINGS ID Survey ID Transect Number (1-6) CAAB Code Scientific Name Reef Fish Length (estimated Fork Length of fish; -1 = unknown or not recorded) Outside Transect (if a fish was observed outside a transect -1 was recorded) Morph Code (F = footballer morph for Plectropomus laevis, S = Spawning colour morph displayed)

Paddock to Reef Monitoring & Evaluation - Economic analysis of ‘ABCD’ cane management for Tully

The economic analysis is based on the A, B, C and D management practice framework for water quality improvement developed in 2007/2008 by the respective natural resource management region. This document focuses on the economic implications of these management practices in the Tully region. A review of the management practices is currently being undertaken to clarify some issues and incorporate new knowledge since the earlier version of the framework. However, this updated version is not yet complete and so the Paddock to Reef project has used the most current available version of the framework for the modelling and economics.