A comparison of mark-recapture distance-sampling methods applied to aerial surveys of eastern grey kangaroos

Aerial surveys of kangaroos (Macropus spp.) in Queensland are used to make economically important judgements on the levels of viable commercial harvest. Previous analysis methods for aerial kangaroo surveys have used both mark-recapture methodologies and conventional distance-sampling analyses. Conventional distance sampling has the disadvantage that detection is assumed to be perfect on the transect line, while mark-recapture methods are notoriously sensitive to problems with unmodelled heterogeneity in capture probabilities. We introduce three methodologies for combining together mark-recapture and distance-sampling data, aimed at exploiting the strengths of both methodologies and overcoming the weaknesses. Of these methods, two are based on the assumption of full independence between observers in the mark-recapture component, and this appears to introduce more bias in density estimation than it resolves through allowing uncertain trackline detection. Both of these methods give lower density estimates than conventional distance sampling, indicating a clear failure of the independence assumption. The third method, termed point independence, appears to perform very well, giving credible density estimates and good properties in terms of goodness-of-fit and percentage coefficient of variation. Estimated densities of eastern grey kangaroos range from 21 to 36 individuals km-2, with estimated coefficients of variation between 11% and 14% and estimated trackline detection probabilities primarily between 0.7 and 0.9.

Sustaining productivity of a Vertosol at Warra, Queensland, with fertilisers, no-tillage or legumes. 9. Production and nitrogen benefits from mixed grass and legume pastures in rotation with wheat

Reduced supplies of nitrogen (N) in many soils of southern Queensland that were cropped exhaustively with cereals over many decades have been the focus of much research to avoid declines in profitability and sustainability of farming systems. A 45-month period of mixed grass (purple pigeon grass, Setaria incrassata Stapf; Rhodes grass, Chloris gayana Kunth.) and legume (lucerne, Medicago sativa L.; annual medics, M. scutellata L. Mill. and M. truncatula Gaertn.) pasture was one of several options that were compared at a fertility-depleted Vertosol at Warra, southern Queensland, to improve grain yields or increase grain protein concentration of subsequent wheat crops. Objectives of the study were to measure the productivity of a mixed grass and legume pasture grown over 45 months (cut and removed over 36 months) and its effects on yield and protein concentrations of the following wheat crops. Pasture production (DM t/ha) and aboveground plant N yield (kg/ha) for grass, legume (including a small amount of weeds) and total components of pasture responded linearly to total rainfall over the duration of each of 3 pastures sown in 1986, 1987 and 1988. Averaged over the 3 pastures, each 100 mm of rainfall resulted in 0.52 t/ha of grass, 0.44 t/ha of legume and 0.97 t/ha of total pasture DM, there being little variation between the 3 pastures. Aboveground plant N yield of the 3 pastures ranged from 17.2 to 20.5 kg/ha per 100 mm rainfall. Aboveground legume N in response to total rainfall was similar (10.6 - 13.2 kg/ha. 100 mm rainfall) across the 3 pastures in spite of very different populations of legumes and grasses at establishment. Aboveground grass N yield was 5.2 - 7.0 kg/ha per 100mm rainfall. In most wheat crops following pasture, wheat yields were similar to that of unfertilised wheat except in 1990 and 1994, when grain yields were significantly higher but similar to that for continuous wheat fertilised with 75 kg N/ha. In contrast, grain protein concentrations of most wheat crops following pasture responded positively, being substantially higher than unfertilised wheat but similar to that of wheat fertilised with 75 kg N/ha. Grain protein averaged over all years of assay was increased by 25 - 40% compared with that of unfertilised wheat. Stored water supplies after pasture were < 134mm (< 55% of plant available water capacity); for most assay crops water storages were 67 - 110 mm, an equivalent wet soil depth of only 0.3 - 0.45 m. Thus, the crop assays of pasture benefits were limited by low water supply to wheat crops. Moreover, the severity of common root rot in wheat crop was not reduced by pasture - wheat rotation.

Genomic regions influencing seminal root traits in barley

Water availability is a major limiting factor for crop production, making drought adaptation and its many component traits a desirable attribute of plant cultivars. Previous studies in cereal crops indicate that root traits expressed at early plant developmental stages, such as seminal root angle and root number, are associated with water extraction at different depths. Here, we conducted the first study to map seminal root traits in barley (Hordeum vulgare L.). Using a recently developed high-throughput phenotyping method, a panel of 30 barley genotypes and a doubled-haploid (DH) population (ND24260 × 'Flagship') comprising 330 lines genotyped with diversity array technology (DArT) markers were evaluated for seminal root angle (deviation from vertical) and root number under controlled environmental conditions. A high degree of phenotypic variation was observed in the panel of 30 genotypes: 13.5 to 82.2 and 3.6 to 6.9° for root angle and root number, respectively. A similar range was observed in the DH population: 16.4 to 70.5 and 3.6 to 6.5° for root angle and number, respectively. Seven quantitative trait loci (QTL) for seminal root traits (root angle, two QTL; root number, five QTL) were detected in the DH population. A major QTL influencing both root angle and root number (RAQ2/RNQ4) was positioned on chromosome 5HL. Across-species analysis identified 10 common genes underlying root trait QTL in barley, wheat (Triticum aestivum L.), and sorghum [Sorghum bicolor (L.) Moench]. Here, we provide insight into seminal root phenotypes and provide a first look at the genetics controlling these traits in barley.