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Understanding the mechanisms by which wild bees survive in modified landscapes is important for their conservation and management as pollinators. Pollen is a critical resource for the completion of bee life cycles, so we investigated how the pollen loads carried by native bee communities change between natural forests and farms dominated by exotic crops and weeds in an agricultural region of south‐east Australia.We found that individual bees tended to carry higher proportions of exotic pollen on farms compared with forests (after accounting for whether they were captured on exotic or native flowers), and the diversity of pollen carried by bees did not differ significantly between native forest and farm sites or along native forest cover gradients. This suggests that the native bees found on farms, which are predominantly different species compared with those found in native forests, are not disadvantaged by the dominance of exotic plants in these habitats (though impacts on larval nutrition were not investigated).While some native bees carried crop pollen, others almost exclusively carried the pollen of agricultural weeds (e.g., Arctotheca and Brassica species), such that some native bee species may pollinate and benefit from crops, whereas others may only persist on farms if agricultural weeds are tolerated. [ABSTRACT FROM AUTHOR]

Arthropod predators and parasitoids support the health and functioning of the world's ecosystems, most notably by supplying biological control services to agricultural landscapes. Quantifying the impact that these organisms have on their prey can be challenging, as direct observation and measurement of arthropod predation is difficult. The use of sentinel prey is one method to measure predator impact; however, despite widespread use, few studies have compared predation on different prey types within a single experiment. This study evaluated the predation rates on four sentinel prey items in grass and wheat fields in south‐east Queensland, Australia. Attack rates on live and dead Helicoverpa armigera eggs, and dead H. armigera larvae and artificial plasticine larvae, were compared and the predators that were attracted to each prey type were documented with the use of field cameras. There was no significant difference in predation rates between sentinel eggs, while dead larvae were significantly more attacked than artificial larvae. Prey were attacked by a diverse range of predators, including ants, beetles, various nymph and juvenile insects and small mammals. Different predators were active in grass and crop fields, with predator activity peaking around dawn and dusk. The same trends were observed within and between the two habitats studied, providing a measure of confidence in the sentinel prey method. A range of different sentinel prey types could be suitable for use in most comparative studies; however, each prey type has its own benefits and limitations, and these should be carefully evaluated to determine which is most suitable to address the research questions. [ABSTRACT FROM AUTHOR]

The conversion of natural vegetation to agriculture is a leading cause of biodiversity decline globally, and can impact negatively on ecosystem services such as pollination. Global meta-analyses find that crop visitation by wild pollinators increases with the amount of natural or semi-natural vegetation in the surrounding landscape. However, these studies typically test the effect of one land cover type, rather than comparing multiple land cover types, and so do not provide information about the land cover arrangements that maximize crop visitation by wild pollinators. We sampled wild bee visitors to apple flowers in 2017 and 2018, and weeds and native plants in apple orchards in 2018, along landscape gradients of native vegetation and non-crop agricultural cover (open grassy areas, grazed or ungrazed) across three widely-separate agricultural regions of southeast Australia. We compared different land cover types as predictors of wild bee visitation to apple orchards, classifying non-crop land cover as: 1) 'natural vegetation' (NV), 2) 'open grassy areas' (OGA), and 3) 'natural vegetation plus open grassy areas' (NVOGA). The dominant flower-visiting wild bees in apple orchards in all regions were soil-nesting species of Halictidae that appear to be capable of exploiting open areas cleared for agriculture; however, even these taxa were rare or absent from orchards in some regions and years. Wild bee visitation to apples was best predicted by OGA in 2017 (positive association), but no land cover type in 2018, while visitation to weeds and native plants increased with both OGA and NV. Comparing different ways of classifying non-crop land cover is important for identifying land management strategies that maximize crop pollination services. However, managing land cover for wild bees may have negligible impacts on apple pollination in southeast Australia where wild bees are often rare in orchards, exhibit between-year variation in land cover associations, and are vastly outnumbered by honeybees (> 90% of visits to apple flowers). • Land cover predicted wild bee visitation to apple flowers in only one of two years. • The amount of open grassy areas in the landscape was the best predictor of wild bee visitation. • Most apple orchard-visiting wild bees were agriculture-tolerant species of Halictidae. [ABSTRACT FROM AUTHOR]

Abstract: Cropping activity has an importance that extends beyond farming communities, to governments, private industries, and to scientific research. We have developed a remote sensing-based method to detect arable cropping activity in central and southern Queensland, Australia, based on time series analysis of the NDVI layer of MODIS-Terra MOD13Q1 (250-m pixel) imagery. Local auto-regression was used to characterise phenological cycles in the NDVI time series. A random forest was then used to model three broad classes of agricultural vegetation (Grazing, Summer Cropping and Winter Cropping), as a function of phenological metrics and the local variance of the NDVI time series. The latter was found to be the most important distinguishing factor between the three classes. Pixel-by-pixel predictions of the random forest were obtained bi-annually for the study area over a 10-year period. Moderate agreement was seen between the predictions of the random forest and (independent) visual interpretation of Landsat imagery (Cohen''s index of agreement, κ c , of 0.59). We then demonstrated how the random forest''s predictions can be used to define the consistency of cropping activity at the spatial scale of an individual farm property; when compared with (independent) visual interpretation of Landsat imagery the agreement was also moderate (κ c =0.68). In comparison with other crop-mapping approaches in the literature, our results have been achieved: (i) without restricting the method to annual NDVI time series; (ii) without assuming that the time series is regularly spaced and periodic; (iii) by considering only the ‘greening-up’ phase of the phenological cycles. [Copyright &y& Elsevier]

BACKGROUND: The redlegged earth mite, Halotydeus destructor Tucker, is an important pest of broad-acre farming systems in Australia, New Zealand and South Africa. In 2006, high levels of resistance to synthetic pyrethroids were discovered in this species in Western Australia. RESULTS: Between 2007 and 2010, the authors monitored resistance in field populations and found it had spread considerably within the state of Western Australia. Twenty-six paddocks from 15 individual properties were identified with resistance, and these paddocks ranged over 480 km. To date, resistance has not been detected in any other Australian state. Resistance in H. destructor appears to be found across the entire pyrethroid group, but not to other chemical classes such as organophosphates and carbamates, or other chemistries with novel modes of action. CONCLUSION: The high levels of resistance occurring in Western Australia have caused considerable economic losses due to ineffective chemical applications and mortality of crop plants at seedling establishment. These findings highlight the need for a comprehensive resistance surveillance programme to be developed for H. destructor within Australia. Growers need to consider non-chemical approaches for pest control and should be encouraged to implement pesticide resistance management programmes for H. destructor. Copyright © 2011 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Purpose: Past life cycle assessments (LCA) of sugarcane ( Saccharum officinarum) production have commonly been based on limited datasets, and variability has not been well described. In this work, Australian sugarcane production was assessed more comprehensively in order to generate a robust set of LCA results for use in subsequent assessments of sugarcane products and also to investigate: (1) variability due to regional differences, (2) factors influencing variability, and (3) significance of the impacts. Methods: An average scenario for Australian sugarcane production was modeled based on data for the state of Queensland (98% of Australian production). Life cycle impact assessment (LCIA) results were generated using Impact 2002+, modified to be more representative of Australian conditions, and with the inclusion of water use and land use indicators. A Monte Carlo uncertainty analysis, using minimum and maximum values for production data, was undertaken to evaluate variability. Different regional production practices were also modeled to identify factors that influence variability. Normalization aimed to show the significance of total Australian sugarcane production relative to total Australian impacts. Results and discussion: Considerable variability was found in the LCIA results, with the key variables being yield, N use efficiency, the susceptibility of soils to N leakage, irrigation (water and energy intensity), and pre-harvest burning. N leakage was found to be an important issue that influences a range of impact categories. When normalized against total national impacts, water use and land use appear to be the most significant impacts (based on simple indicators of consumption), followed by eutrophication potential, acidification potential, and respiratory impacts, whereas non-renewable energy input and global warming are less significant. The results suggest that toxicity impacts are insignificant; however, this may not be supported by other observations that link pesticide loss from sugarcane to toxicity concerns in receiving waters and is a subject for further research. Conclusions and recommendations: The potential for significant variability in the impacts from sugarcane growing suggests a need for LCAs of sugarcane systems to consider ranges for key variables. The key variables and significant impacts identified in this work can guide data collection priorities for future assessment of sugarcane and possibly other Australian cropping systems. To further develop LCA as a useful predictive tool for Australian agricultural systems, further development and testing of impact assessment models for eutrophication, toxicity, and land and water resource depletion appropriate for Australia and its subregions will be required. [ABSTRACT FROM AUTHOR]

Background: A growing ability and interest in the collection of data, together with the development and adoption of the FAIR guiding principles, has increased the amount of data available in many disciplines. This has given rise to an urgent need for robust metadata. Within the Australian grains industry, data from over thousands of on-farm research trials (Trial Projects) have been made available via the Online Farm Trials (OFT) website. OFT Trial Project metadata were developed as filters to refine front-end database searches, but could also be used as a dataset to investigate trends in metadata elements. Australian grains crops are being sown earlier, but whether on-farm research trials reflect this change is currently unknown. Methods: We investigated whether OFT Trial Project metadata could be used to detect trends in sowing dates of on-farm crop research trials across Australia, testing the hypothesis that research trials are being sown earlier in line with local farming practices. The investigation included 15 autumn-sown, winter crop species listed in the database, with trial records from 1993 to 2019. Results: Our analyses showed that (i) OFT Trial Project metadata can be used as a dataset to detect trends in sowing date; and (ii) cropping research trials are being sown earlier in Victoria and Western Australia, but no trend exists within the other states. Discussion/Conclusion: Our findings show that OFT Trial Project metadata can be used to detect trends in crop sowing date, suggesting that metadata could also be used to detect trends in other metadata elements such as harvest date. Because OFT is a national database of research trials, further assessment of metadata may uncover important agronomic, cultural or economic trends within or across the Australian cropping regions. New information could then be used to lead practice change and increase productivity within the Australian grains industry., Competing Interests: No competing interests were disclosed., (Copyright: © 2020 Walters J et al.)