Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

Variation in exotic and native seed arrival and recruitment of bird dispersed species in subtropical forest restoration and regrowth

Invasive bird-dispersed plants often share the same suite of dispersers as co-occurring native species, resulting in a complex management issue. Integrated management strategies could incorporate manipulation of dispersal or establishment processes. To improve our understanding of these processes, we quantified seed rain, recruit and seed bank density, and species richness for bird-dispersed invasive and native species in three early successional subtropical habitats in eastern Australia: tree regrowth, shrub regrowth and native restoration plantings. We investigated the effects of environmental factors (leaf area index (LAI), distance to edge, herbaceous ground cover and distance to nearest neighbour) on seed rain, seed bank and recruit abundance. Propagule availability was not always a good predictor of recruitment. For instance, although native tree seed rain density was similar, and species richness was higher, in native plantings, compared with tree regrowth, recruit density and species richness were lower. Native plantings also received lower densities of invasive tree seed rain than did tree regrowth habitats, but supported a similar density of invasive tree recruits. Invasive shrub seed rain was recorded in highest densities in shrub regrowth sites, but recruit density was similar between habitats. We discuss the role of microsite characteristics in influencing post-dispersal processes and recruit composition, and suggest ways of manipulating these processes as part of an integrated management strategy for bird-dispersed weeds in natural areas.

Landscape structure influences tree density patterns in fragmented woodlands in semi-arid eastern Australia.

Landscape and local-scale influences are important drivers of plant community structure. However, their relative contribution and the degree to which they interact remain unclear. We quantified the extent to which landscape structure, within-patch habitat and their confounding effects determine post-clearing tree densities and composition in agricultural landscapes in eastern subtropical Australia. Landscape structure (incorporating habitat fragmentation and loss) and within-patch (site) features were quantified for 60 remnant patches of Eucalyptus populnea (Myrtaceae) woodland. Tree density and species for three ecological maturity classes (regeneration, early maturity, late maturity) and local site features were assessed in one 100 × 10 m plot per patch. All but one landscape characteristic was determined within a 1.3-km radius of plots; Euclidean nearest neighbour distance was measured inside a 5-km radius. Variation in tree density and composition for each maturity class was partitioned into independent landscape, independent site and joint effects of landscape and site features using redundancy analysis. Independent site effects explained more variation in regeneration density and composition than pure landscape effects; significant predictors were the proportion of early and late maturity trees at a site, rainfall and the associated interaction. Conversely, landscape structure explained greater variation in early and late maturity tree density and composition than site predictors. Area of remnant native vegetation within a landscape and patch characteristics (area, shape, edge contrast) were significant predictors of early maturity tree density. However, 31% of the explained variation in early mature tree differences represented confounding influences of landscape and local variables. We suggest that within-patch characteristics are important in influencing semi-arid woodland tree regeneration. However, independent and confounding effects of landscape structure resulting from previous vegetation clearing may have exerted a greater historical influence on older cohorts and should be accounted for when examining woodland dynamics across a broader range of environments.

Statistical forecasting of the Australian macadamia crop

Three types of forecasts of the total Australian production of macadamia nuts (t nut-in-shell) have been produced early each year since 2001. The first is a long-term forecast, based on the expected production from the tree census data held by the Australian Macadamia Society, suitably scaled up for missing data and assumed new plantings each year. These long-term forecasts range out to 10 years in the future, and form a basis for industry and market planning. Secondly, a statistical adjustment (termed the climate-adjusted forecast) is made annually for the coming crop. As the name suggests, climatic influences are the dominant factors in this adjustment process, however, other terms such as bienniality of bearing, prices and orchard aging are also incorporated. Thirdly, industry personnel are surveyed early each year, with their estimates integrated into a growers and pest-scouts forecast. Initially conducted on a 'whole-country' basis, these models are now constructed separately for the six main production regions of Australia, with these being combined for national totals. Ensembles or suites of step-forward regression models using biologically-relevant variables have been the major statistical method adopted, however, developing methodologies such as nearest-neighbour techniques, general additive models and random forests are continually being evaluated in parallel. The overall error rates average 14% for the climate forecasts, and 12% for the growers' forecasts. These compare with 7.8% for USDA almond forecasts (based on extensive early-crop sampling) and 6.8% for coconut forecasts in Sri Lanka. However, our somewhatdisappointing results were mainly due to a series of poor crops attributed to human reasons, which have now been factored into the models. Notably, the 2012 and 2013 forecasts averaged 7.8 and 4.9% errors, respectively. Future models should also show continuing improvement, as more data-years become available.

A new species of Aptenocanthorn Mathews from North Queensland. (Coleoptera: Scarabaeidae: Scarabaeinae)

Aptenocanthorn monteithi sp. Nov. is described from Atherton Tableland areas in northern Queensland. The nearest relatives are from mountains in eastern New South Wales.

A new flightless species of Aulacopris White from north Queensland (coleoptera : scarabaeidae : scarabaeinae)

Aulacopris mallhewsi sp. nov. is described from mountains behind Cape Tribulation in northern Queensland. Its nearest relatives are in southeastern Queensland. The species is the smallest in the genus and is flightless. Individuals engaged in ball making and ball rolling activities in the laboratory.

Bromus catharticus striate mosaic virus: a new mastrevirus infecting Bromus catharticus from Australia.

Although monocotyledonous-plant-infecting mastreviruses (in the family Geminiviridae) are known to cause economically significant crop losses in certain areas of the world, in Australia, they pose no obvious threat to agriculture. Consequently, only a few Australian monocot-infecting mastreviruses have been described, and only two have had their genomes fully sequenced. Here, we present the third full-genome sequence of an Australian monocot-infecting mastrevirus from Bromus catharticus belonging to a distinct species, which we have tentatively named Bromus catharticus striate mosaic virus (BCSMV). Although the genome of this new virus shares only 57.7% sequence similarity with that of its nearest known relative, Digitaria didactyla striate mosaic virus (DDSMV; also from Australia), it has features typical of all other known mastrevirus genomes. Phylogenetic analysis showed that both the full genome and each of its probable expressed proteins group with the two other characterised Australian monocot-infecting mastreviruses. Besides the BCSMV genome sequence revealing that Australian monocot-infecting mastrevirus diversity rivals that seen in Africa, it has enabled us, for the first, to time detect evidence of recombination amongst the Australian viruses. Specifically, it appears that DDSMV possesses a short intergenic region sequence that has been recombinationally derived from either BCSMV or a close relative that has not yet been identified.

Healthy hardwoods. A field guide to pests, diseases and nutritional disorders in subtropical hardwoods.

Healthy hardwoods: A field guide to pests, diseases and nutritional disorders in subtropical hardwoods can be used to help identify the common damaging insects, fungi and nutritional disorders in young eucalypt (Eucalyptus and Corymbia species) plantations in subtropical eastern Australia. This guide includes photographs of each insect, fungus and nutritional disorder and the damage they cause, along with a brief description to aid identification. A brief host list for insects and fungi, including susceptibility and occurrence, is provided as a guide only. A hand lens will be useful, especially to identify fungi. Although it is possible to identify insects and fungi from these photographs, laboratory examination will sometimes be necessary. For example, microscopes and culturing media might be used to identify fungi. Information about four exotic pests and diseases has also been included in the Biosecurity threats chapter. Potentially, these would have a severe impact on plantation and natural forests if introduced into Australia. To prevent establishment of these pests, early detection and identification is crucial. If an exotic insect or disease is suspected, then an immediate response is required. Usually, the first response will be to contact the nearest Australian Quarantine and Inspection Service office or forestry agency to seek advice.

The spatiotemporal dynamics of Tribolium castaneum (Herbst): adult flight and gene flow.

Tribolium castaneum (Herbst) has been used as a model organism to develop and test important ecological and evolutionary concepts and is also a major pest of grain and grain products globally. This beetle species is assumed to be a good colonizer of grain storages through anthropogenic movement of grain, and active dispersal by flight is considered unlikely. Studies using T. castaneum have therefore used confined or walking insects. We combine an ecological study of dispersal with an analysis of gene flow using microsatellites to investigate the spatiotemporal dynamics and adult flight of T. castaneum in an ecological landscape in eastern Australia. Flying beetles were caught in traps at grain storages and in fields at least 1 km from the nearest stored grain at regular intervals for an entire year. Significantly more beetles were trapped at storages than in fields, and almost no beetles were caught in native vegetation reserves many kilometres from the nearest stored grain. Genetic differentiation between beetles caught at storages and in fields was low, indicating that although T. castaneum is predominantly aggregated around grain storages, active dispersal takes place to the extent that significant gene flow occurs between them, mitigating founder effects and genetic drift. By combining ecological and molecular techniques, we reveal much higher levels of active dispersal through adult flight in T. castaneum than previously thought. We conclude that the implications of adult flight to previous and future studies on this model organism warrant consideration.

Response of Tribolium castaneum and Rhyzopertha dominica to various resources, near and far from grain storage

Tribolium castaneum (Herbst) and Rhyzopertha dominica (F.) are common cosmopolitan pests of stored grain and grain products. We evaluated the relative attraction of T.castaneum and R.dominica to wheat, sorghum and cotton seeds in the field, near grain storage facilities and well away from storages in southern and central Queensland using multiple trapping techniques. The results show that T.castaneum is more strongly attracted to linted cotton seed relative to wheat, whereas R.dominica did not respond to cotton seed at all and was attracted only to wheat. Significantly more adults of T.castaneum (10-15 times) were attracted to traps placed on the ground, near grain storage, than to equivalent traps that were suspended (1.5m above the ground) nearby. These results suggest that Tribolium beetles detect and respond to resources towards the end of their dispersal flight, after which they localize resources while walking. By contrast R.dominica was captured only in suspended traps, which suggests they fly directly onto resources as they localize them. The ability of both species to colonize and reproduce in isolated resource patches within the relatively short time of 1month is illustrated by the returns from the traps deployed in the field (at least 1km from the nearest stored grain) even though they caught only a few beetles. The results presented here provide novel insights about the resource location behaviours of both T.castaneum and R.dominica. In particular, the relationship of T.castaneum with non-cereal resources that are not conventionally associated with this species suggests an emphasis on these other resources in investigating the resource location behaviour of these beetles. This new perspective on the ecology of T. castaneum highlights the potential role of non-cereal resources (such as the lint on cotton seed) in the spread of grain pest infestations.