Spatial model of site index based on Y-ray spectrometry and a digital elevation model for two Pinus species in Tuan Toolara State Forest, Queensland, Australia

Site index prediction models are an important aid for forest management and planning activities. This paper introduces a multiple regression model for spatially mapping and comparing site indices for two Pinus species (Pinus elliottii Engelm. and Queensland hybrid, a P. elliottii x Pinus caribaea Morelet hybrid) based on independent variables derived from two major sources: g-ray spectrometry (potassium (K), thorium (Th), and uranium (U)) and a digital elevation model (elevation, slope, curvature, hillshade, flow accumulation, and distance to streams). In addition, interpolated rainfall was tested. Species were coded as a dichotomous dummy variable; interaction effects between species and the g-ray spectrometric and geomorphologic variables were considered. The model explained up to 60% of the variance of site index and the standard error of estimate was 1.9 m. Uranium, elevation, distance to streams, thorium, and flow accumulation significantly correlate to the spatial variation of the site index of both species, and hillshade, curvature, elevation and slope accounted for the extra variability of one species over the other. The predicted site indices varied between 20.0 and 27.3 m for P. elliottii, and between 23.1 and 33.1 m for Queensland hybrid; the advantage of Queensland hybrid over P. elliottii ranged from 1.8 to 6.8 m, with the mean at 4.0 m. This compartment-based prediction and comparison study provides not only an overview of forest productivity of the whole plantation area studied but also a management tool at compartment scale.

QTL mapping of multiple foliar disease and root-lesion nematode resistances in wheat.

A genetic linkage map, based on a cross between the synthetic hexaploid CPI133872 and the bread wheat cultivar Janz, was established using 111 F1-derived doubled haploid lines. The population was phenotyped in multiple years and/or locations for seven disease resistance traits, namely, Septoria tritici blotch (Mycosphaeralla graminicola), yellow leaf spot also known as tan spot (Pyrenophora tritici-repentis), stripe rust (Puccinia striiformis f. sp. tritici), leaf rust (Puccinia triticina), stem rust (Puccinia graminis f. sp. tritici) and two species of root-lesion nematode (Pratylenchyus thornei and P. neglectus). The DH population was also scored for coleoptile colour and the presence of the seedling leaf rust resistance gene Lr24. Implementation of a multiple-QTL model identified a tightly linked cluster of foliar disease resistance QTL in chromosome 3DL. Major QTL each for resistance to Septoria tritici blotch and yellow leaf spot were contributed by the synthetic hexaploid parent CPI133872 and linked in repulsion with the coincident Lr24Sr24/ locus carried by parent Janz. This is the first report of linked QTL for Septoria tritici blotch and yellow leaf spot contributed by the same parent. Additional QTL for yellow leaf spot were detected in 5AS and 5BL. Consistent QTL for stripe rust resistance were identified in chromosomes 1BL, 4BL and 7DS, with the QTL in 7DS corresponding to the Yr18Lr34/ region. Three major QTL for P. thornei resistance (2BS, 6DS, 6DL) and two for P. neglectus resistance (2BS, 6DS) were detected. The recombinants combining resistance to Septoria tritici blotch, yellow leaf spot, rust diseases and root-lesion nematodes from parents CPI133872 and Janz constitute valuable germplasm for the transfer of multiple disease resistance into new wheat cultivars.

Time-dependent instantaneous mortality rates from multiple tagging experiments with exact times of release and recovery

Instantaneous natural mortality rates and a nonparametric hunting mortality function are estimated from a multiple-year tagging experiment with arbitrary, time-dependent fishing or hunting mortality. Our theory allows animals to be tagged over a range of times in each year, and to take time to mix into the population. Animals are recovered by hunting or fishing, and death events from natural causes occur but are not observed. We combine a long-standing approach based on yearly totals, described by Brownie et al. (1985, Statistical Inference from Band Recovery Data: A Handbook, Second edition, United States Fish and Wildlife Service, Washington, Resource Publication, 156), with an exact-time-of-recovery approach originated by Hearn, Sandland and Hampton (1987, Journal du Conseil International pour l'Exploration de la Mer, 43, 107-117), who modeled times at liberty without regard to time of tagging. Our model allows for exact times of release and recovery, incomplete reporting of recoveries, and potential tag shedding. We apply our methods to data on the heavily exploited southern bluefin tuna (Thunnus maccoyii).

Estimation in a multiplicative mixed model involving a genetic relationship matrix.

Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

Detection and use of QTL for complex traits in multiple environments.

QTL mapping methods for complex traits are challenged by new developments in marker technology, phenotyping platforms, and breeding methods. In meeting these challenges, QTL mapping approaches will need to also acknowledge the central roles of QTL by environment interactions (QEI) and QTL by trait interactions in the expression of complex traits like yield. This paper presents an overview of mixed model QTL methodology that is suitable for many types of populations and that allows predictive modeling of QEI, both for environmental and developmental gradients. Attention is also given to multi-trait QTL models which are essential to interpret the genetic basis of trait correlations. Biophysical (crop growth) model simulations are proposed as a complement to statistical QTL mapping for the interpretation of the nature of QEI and to investigate better methods for the dissection of complex traits into component traits and their genetic controls.

Characterising insect plant host relationships facilitates understanding multiple host use

Weed biocontrol relies on host specificity testing, usually carried out under quarantine conditions to predict the future host range of candidate control agents. The predictive power of host testing can be scrutinised directly with Aconophora compressa, previously released against the weed Lantana camara L. (lantana) because its ecology in its new range (Australia) is known and includes the unanticipated use of several host species. Glasshouse based predictions of field host use from experiments designed a posteriori can therefore be compared against known field host use. Adult survival, reproductive output and egg maturation were quantified. Adult survival did not differ statistically across the four verbenaceous hosts used in Australia. Oviposition was significantly highest on fiddlewood (Citharexylum spinosum L.), followed by lantana, on which oviposition was significantly higher than on two varieties of Duranta erecta (‘‘geisha girl’’ and ‘‘Sheena’s gold’’; all Verbenaceae). Oviposition rates across Duranta varieties were not significantly different from each other but were significantly higher than on the two non-verbenaceous hosts (Jacaranda mimosifolia D. Don: Bignoneaceae (jacaranda) and Myoporum acuminatum R. Br.: Myoporaceae (Myoporum)). Production of adult A. compressa was modelled across the hosts tested. The only major discrepancy between model output and their relative abundance across hosts in the field was that densities on lantana in the field were much lower than predicted by the model. The adults may, therefore, not locate lantana under field conditions and/or adults may find lantana but leave after laying relatively few eggs. Fiddlewood is the only primary host plant of A. compressa in Australia, whereas lantana and the others are used secondarily or incidentally. The distinction between primary, secondary and incidental hosts of a herbivore species helps to predict the intensity and regularity of host use by that herbivore. Populations of the primary host plants of a released biological control agent are most likely to be consistently impacted by the herbivore, whereas secondary and incidental host plant species are unlikely to be impacted consistently. As a consequence, potential biocontrol agents should be released only against hosts to which they have been shown to be primarily adapted.

Membrane fractionation technologies for high quality mill sugar and value-added by products - an integrated sugar production process concept model.

Membrane filtration technology has been proven to be a technically sound process to improve the quality of clarified cane juice and subsequently to increase the productivity of crystallisation and the quality of sugar production. However, commercial applications have been hindered because the benefits to crystallisation and sugar quality have not outweighed the increased processing costs associated with membrane applications. An 'Integrated Sugar Production Process (ISPP) Concept Model' is proposed to recover more value from the non-sucrose streams generated by membrane processing. Pilot scale membrane fractionation trials confirmed the technical feasibility of separating high-molecular weight, antioxidant and reducing sugar fractions from cane juice in forms suitable for value recovery. It was also found that up to 40% of potassium salts from the juice can be removed by membrane application while removing the similar amount of water with potential energy saving in subsequent evaporation. Application of ISPP would allow sugar industry to co-produce multiple products and high quality mill sugar while eliminating energy intensive refining processes.

Multiple host use by a sap-sucking membracid: population consequences of nymphal development on primary and secondary host plant species

Aconophora compressa is a gregarious, sap-sucking insect that uses multiple host plant species. Nymphal host plant species (and variety) significantly affected nymphal survival, nymphal development rate and the subsequent size and fecundity of adults, with fiddlewood ( Citharexylum spinosum ) being significantly best in all respects. Nymphs that developed on a relatively poor host ( Duranta erecta var “geisha girl”) and which were moved to fiddlewood as adults laid significantly fewer eggs (mean ± SE = 836 ± 130) than those that developed solely on fiddlewood (1,329 ± 105). Adults on geisha girl, regardless of having been reared as nymphs on fiddlewood or geisha girl, laid significantly fewer eggs (342 ± 83 and 317 ± 74, respectively) than adults on fiddlewood. A simple model that incorporates host plant related survival, development rate and fecundity suggests that the population dynamics of A. compressa are governed mainly by fiddlewood, the primary host. The results have general implications for understanding the population dynamics of herbivores that use multiple host plant species, and also for the way in which weed biological control host testing methods should be conducted.

Variation in water extraction with maize plant density and its impact on model application

The use of maize simulation models to determine the optimum plant population for rainfed environments allows the evaluation of plant populations over multiple years and locations at a lower cost than traditional field experimentation. However the APSIM maize model that has been used to conduct some of these 'virtual' experiments assumes that the maximum rate of soil water extraction by the crop root system is constant across plant populations. This untested assumption may cause grain yield to be overestimated in lower plant populations. A field experiment was conducted to determine whether maximum rates of water extraction vary with plant population, and the maximum rate of soil water extraction was estimated for three plant populations (2.4, 3.5 and 5.5 plants m(-2)) under water limited conditions. Maximum soil water extraction rates in the field experiment decreased linearly with plant population, and no difference was detected between plant populations for the crop lower limit of soil water extraction. Re-analysis of previous maize simulation experiments demonstrated that the use of inappropriately high extraction-rate parameters at low plant populations inflated predictions of grain yield, and could cause erroneous recommendations to be made for plant population. The results demonstrate the importance of validating crop simulation models across the range of intended treatments. (C) 2013 Elsevier E.V. All rights reserved.

QTL analysis in multiple sorghum populations facilitates the dissection of the genetic and physiological control of tillering

Tillering in sorghum can be associated with either the carbon supply–demand (S/D) balance of the plant or an intrinsic propensity to tiller (PTT). Knowledge of the genetic control of tillering could assist breeders in selecting germplasm with tillering characteristics appropriate for their target environments. The aims of this study were to identify QTL for tillering and component traits associated with the S/D balance or PTT, to develop a framework model for the genetic control of tillering in sorghum. Four mapping populations were grown in a number of experiments in south east Queensland, Australia. The QTL analysis suggested that the contribution of traits associated with either the S/D balance or PTT to the genotypic differences in tillering differed among populations. Thirty-four tillering QTL were identified across the populations, of which 15 were novel to this study. Additionally, half of the tillering QTL co-located with QTL for component traits. A comparison of tillering QTL and candidate gene locations identified numerous coincident QTL and gene locations across populations, including the identification of common non-synonymous SNPs in the parental genotypes of two mapping populations in a sorghum homologue of MAX1, a gene involved in the control of tiller bud outgrowth through the production of strigolactones. Combined with a framework for crop physiological processes that underpin genotypic differences in tillering, the co-location of QTL for tillering and component traits and candidate genes allowed the development of a framework QTL model for the genetic control of tillering in sorghum.