973 resultados para Reserve Selection Procedures


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Manual grading of prawns restricts the number that can be harvested. A restricted harvest size places a limit on the opposing within family and between family sources of selection pressure. A simulation study with inbreeding constrained at 0.5% per generation, a harvest size of 2000, heritability of 0.3, common family environmental effect of 0.1, indicates that maximum response to selection could be achieved with as few as 40 families. Increasing the number of families above 80 may reduce total selection response. It is important to be aware that increasing the number of families may not always yield a greater genetic response.

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Understanding plant demography and plant response to herbivory is critical to the selection of effective weed biological control agents. We adopt the metaphor of 'filters' to suggest how agent prioritisation may be improved to narrow our choices down to those likely to be most effective in achieving the desired weed management outcome. Models can serve to capture our level of knowledge (or ignorance) about our study system and we illustrate how one type of modelling approach (matrix models) may be useful in identifying the weak link in a plant life cycle by using a hypothetical and an actual weed example (Parkinsonia aculeata). Once the vulnerable stage has been identified we propose that studying plant response to herbivory (simulated and/or actual) can help identify the guilds of herbivores to which a plant is most likely to succumb. Taking only potentially effective agents through the filter of host specificity may improve the chances of releasing safe and effective agents. The methods we outline may not always lead us definitively to the successful agent(s), but such an empirical, data-driven approach will make the basis for agent selection explicit and serve as testable hypotheses once agents are released.

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In order to investigate the effect of long term recurrent selection on the pattern of gene diversity, thirty randomly-selected individuals from the progenitors (p) and four selection cycles (C0, C3, C6 and C11) were sampled for DNA analysis from the tropical maize (Zea mays L.) breeding populations, Atherton 1 (AT1) and Atherton 2 (AT2). Fifteen polymorphic Simple Sequence Repeat markers amplified a total of 284 and 257 alleles in AT1 and AT2 populations, respectively. Reductions in the number of alleles were observed at advanced selection cycles. About 11 and 12% of the alleles in AT1 and AT2 populations respectively, were near to fixation. However, a higher number of alleles (37% in AT1 and 33% in AT2) were close to extinction. Fisher's exact test and analysis of molecular variance (AMOVA) showed significant population differentiations. Gene diversity estimates and AMOVA revealed increased genetic differentiations at the expense of loss of heterozygosity. Population differentiations were mainly due to fixation of complementary alleles at a locus in the two breeding populations. The estimates of effective population at an advanced selection cycle were close to the population size predicted by the breeding method.

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The quality of species distribution models (SDMs) relies to a large degree on the quality of the input data, from bioclimatic indices to environmental and habitat descriptors (Austin, 2002). Recent reviews of SDM techniques, have sought to optimize predictive performance e.g. Elith et al., 2006. In general SDMs employ one of three approaches to variable selection. The simplest approach relies on the expert to select the variables, as in environmental niche models Nix, 1986 or a generalized linear model without variable selection (Miller and Franklin, 2002). A second approach explicitly incorporates variable selection into model fitting, which allows examination of particular combinations of variables. Examples include generalized linear or additive models with variable selection (Hastie et al. 2002); or classification trees with complexity or model based pruning (Breiman et al., 1984, Zeileis, 2008). A third approach uses model averaging, to summarize the overall contribution of a variable, without considering particular combinations. Examples include neural networks, boosted or bagged regression trees and Maximum Entropy as compared in Elith et al. 2006. Typically, users of SDMs will either consider a small number of variable sets, via the first approach, or else supply all of the candidate variables (often numbering more than a hundred) to the second or third approaches. Bayesian SDMs exist, with several methods for eliciting and encoding priors on model parameters (see review in Low Choy et al. 2010). However few methods have been published for informative variable selection; one example is Bayesian trees (O’Leary 2008). Here we report an elicitation protocol that helps makes explicit a priori expert judgements on the quality of candidate variables. This protocol can be flexibly applied to any of the three approaches to variable selection, described above, Bayesian or otherwise. We demonstrate how this information can be obtained then used to guide variable selection in classical or machine learning SDMs, or to define priors within Bayesian SDMs.

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Joint project with the University of Queensland that will use the recurrent selection breeding method to produce adapted, high-yielding and disease resistant wheat parents to breeders.

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Three new procedures for the extrapolation of series coefficients from a given power series expansion are proposed. They are based on (i) a novel resummation identity, (ii) parametrised Euler transformation (pet) and (iii) a modifiedpet. Several examples taken from the Ising model series expansions, ferrimagnetic systems, etc., are illustrated. Apart from these applications, the higher order virial coefficients for hard spheres and hard discs have also been evaluated using the new techniques and these are compared with the estimates obtained by other methods. A satisfactory agreement is revealed between the two.

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This thesis examines the feasibility of a forest inventory method based on two-phase sampling in estimating forest attributes at the stand or substand levels for forest management purposes. The method is based on multi-source forest inventory combining auxiliary data consisting of remote sensing imagery or other geographic information and field measurements. Auxiliary data are utilized as first-phase data for covering all inventory units. Various methods were examined for improving the accuracy of the forest estimates. Pre-processing of auxiliary data in the form of correcting the spectral properties of aerial imagery was examined (I), as was the selection of aerial image features for estimating forest attributes (II). Various spatial units were compared for extracting image features in a remote sensing aided forest inventory utilizing very high resolution imagery (III). A number of data sources were combined and different weighting procedures were tested in estimating forest attributes (IV, V). Correction of the spectral properties of aerial images proved to be a straightforward and advantageous method for improving the correlation between the image features and the measured forest attributes. Testing different image features that can be extracted from aerial photographs (and other very high resolution images) showed that the images contain a wealth of relevant information that can be extracted only by utilizing the spatial organization of the image pixel values. Furthermore, careful selection of image features for the inventory task generally gives better results than inputting all extractable features to the estimation procedure. When the spatial units for extracting very high resolution image features were examined, an approach based on image segmentation generally showed advantages compared with a traditional sample plot-based approach. Combining several data sources resulted in more accurate estimates than any of the individual data sources alone. The best combined estimate can be derived by weighting the estimates produced by the individual data sources by the inverse values of their mean square errors. Despite the fact that the plot-level estimation accuracy in two-phase sampling inventory can be improved in many ways, the accuracy of forest estimates based mainly on single-view satellite and aerial imagery is a relatively poor basis for making stand-level management decisions.

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We carried out a discriminant analysis with identity by descent (IBD) at each marker as inputs, and the sib pair type (affected-affected versus affected-unaffected) as the output. Using simple logistic regression for this discriminant analysis, we illustrate the importance of comparing models with different number of parameters. Such model comparisons are best carried out using either the Akaike information criterion (AIC) or the Bayesian information criterion (BIC). When AIC (or BIC) stepwise variable selection was applied to the German Asthma data set, a group of markers were selected which provide the best fit to the data (assuming an additive effect). Interestingly, these 25-26 markers were not identical to those with the highest (in magnitude) single-locus lod scores.

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The aphid parasitoid Lysiphlebus testaceipes is a potentially valuable biological control agent of Aphis gossypii a major worldwide pest of cotton. One means of increasing the abundance of a biological control agent is to provide an alternative host habitat adjacent to cropping, from which they can provide pest control services in the crop. Host selection and parasitism rate of an alternative host aphid, Aphis craccivora by L. testaceipes were studied in a series of experiments that tested its host suitability relative to A. gossypii on cotton, hibiscus and mungbean. Host acceptance, as measured by number of ovipositions was much greater in A. craccivora compared to A. gossypii, while more host aphids were accepted on mungbean than cotton. When given a choice L. testaceipes attacks more 4th instar and adult stages (63% and 70%, respectively) of both hosts than 2nd instar nymphs (47%). In a switching (host choice) experiment, L. testaceipes preferentially attacked A. craccivora on mungbean over A. gossypii on cotton. Observations of parasitoid contact with A. gossypii cornicle secretion suggest it provides a useful deterrent against parasitoid attack. From these experiments it appears L. testaceipes has a preference for A. craccivora and mungbean compared to A. gossypii and cotton, in this respect using A. craccivora and mungbean as alternative habitat may not work as the parasitoid is unlikely to switch away from its preferred host. © 2012.

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The studies presented in this thesis contribute to the understanding of evolutionary ecology of three major viruses threatening cultivated sweetpotato (Ipomoea batatas Lam) in East Africa: Sweet potato feathery mottle virus (SPFMV; genus Potyvirus; Potyviridae), Sweet potato chlorotic stunt virus (SPCSV; genus Crinivirus; Closteroviridae) and Sweet potato mild mottle virus (SPMMV; genus Ipomovirus; Potyviridae). The viruses were serologically detected and the positive results confirmed by RT-PCR and sequencing. SPFMV was detected in 24 wild plant species of family Convolvulacea (genera Ipomoea, Lepistemon and Hewittia), of which 19 species were new natural hosts for SPFMV. SPMMV and SPCSV were detected in wild plants belonging to 21 and 12 species (genera Ipomoea, Lepistemon and Hewittia), respectively, all of which were previously unknown to be natural hosts of these viruses. SPFMV was the most abundant virus being detected in 17% of the plants, while SPMMV and SPCSV were detected in 9.8% and 5.4% of the assessed plants, respectively. Wild plants in Uganda were infected with the East African (EA), common (C), and the ordinary (O) strains, or co-infected with the EA and the C strain of SPFMV. The viruses and virus-like diseases were more frequent in the eastern agro-ecological zone than the western and central zones, which contrasted with known incidences of these viruses in sweetpotato crops, except for northern zone where incidences were lowest in wild plants as in sweetpotato. The NIb/CP junction in SPMMV was determined experimentally which facilitated CP-based phylogenetic and evolutionary analyses of SPMMV. Isolates of all the three viruses from wild plants were genetically similar to those found in cultivated sweetpotatoes in East Africa. There was no evidence of host-driven population genetic structures suggesting frequent transmission of these viruses between their wild and cultivated hosts. The p22 RNA silencing suppressor-encoding sequence was absent in a few SPCSV isolates, but regardless of this, SPCSV isolates incited sweet potato virus disease (SPVD) in sweetpotato plants co-infected with SPFMV, indicating that p22 is redundant for synergism between SCSV and SPFMV. Molecular evolutionary analysis revealed that isolates of strain EA of SPFMV that is largely restricted geographically in East Africa experience frequent recombination in comparison to isolates of strain C that is globally distributed. Moreover, non-homologous recombination events between strains EA and C were rare, despite frequent co-infections of these strains in wild plants, suggesting purifying selection against non-homologous recombinants between these strains or that such recombinants are mostly not infectious. Recombination was detected also in the 5 - and 3 -proximal regions of the SPMMV genome providing the first evidence of recombination in genus Ipomovirus, but no recombination events were detected in the characterized genomic regions of SPCSV. Strong purifying selection was implicated on evolution of majority of amino acids of the proteins encoded by the analyzed genomic regions of SPFMV, SPMMV and SPCSV. However, positive selection was predicted on 17 amino acids distributed over the whole the coat protein (CP) in the globally distributed strain C, as compared to only 4 amino acids in the multifunctional CP N-terminus (CP-NT) of strain EA largely restricted geographically to East Africa. A few amino acid sites in the N-terminus of SPMMV P1, the p7 protein and RNA silencing suppressor proteins p22 and RNase3 of SPCSV were also submitted to positive selection. Positively selected amino acids may constitute ligand-binding domains that determine interactions with plant host and/or insect vector factors. The P1 proteinase of SPMMV (genus Ipomovirus) seems to respond to needs of adaptation, which was not observed with the helper component proteinase (HC-Pro) of SPMMV, although the HC-Pro is responsible for many important molecular interactions in genus Potyvirus. Because the centre of origin of cultivated sweetpotato is in the Americas from where the crop was dispersed to other continents in recent history (except for the Australasia and South Pacific region), it would be expected that identical viruses and their strains occur worldwide, presuming virus dispersal with the host. Apparently, this seems not to be the case with SPMMV, the strain EA of SPFMV and the strain EA of SPCSV that are largely geographically confined in East Africa where they are predominant and occur both in natural and agro-ecosystems. The geographical distribution of plant viruses is constrained more by virus-vector relations than by virus-host interactions, which in accordance of the wide range of natural host species and the geographical confinement to East Africa suggest that these viruses existed in East African wild plants before the introduction of sweetpotato. Subsequently, these studies provide compelling evidence that East Africa constitutes a cradle of SPFMV strain EA, SPCSV strain EA, and SPMMV. Therefore, sweet potato virus disease (SPVD) in East Africa may be one of the examples of damaging virus diseases resulting from exchange of viruses between introduced crops and indigenous wild plant species. Keywords: Convolvulaceae, East Africa, epidemiology, evolution, genetic variability, Ipomoea, recombination, SPCSV, SPFMV, SPMMV, selection pressure, sweetpotato, wild plant species Author s Address: Arthur K. Tugume, Department of Agricultural Sciences, Faculty of Agriculture and Forestry, University of Helsinki, Latokartanonkaari 7, P.O Box 27, FIN-00014, Helsinki, Finland. Email: tugume.arthur@helsinki.fi Author s Present Address: Arthur K. Tugume, Department of Botany, Faculty of Science, Makerere University, P.O. Box 7062, Kampala, Uganda. Email: aktugume@botany.mak.ac.ug, tugumeka@yahoo.com

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Knowing the chromosomal areas or actual genes affecting the traits under selection would add more information to be used in the selection decisions which would potentially lead to higher genetic response. The first objective of this study was to map quantitative trait loci (QTL) affecting economically important traits in the Finnish Ayrshire population. The second objective was to investigate the effects of using QTL information in marker-assisted selection (MAS) on the genetic response and the linkage disequilibrium between the different parts of the genome. Whole genome scans were carried out on a grand-daughter design with 12 half-sib families and a total of 493 sons. Twelve different traits were studied: milk yield, protein yield, protein content, fat yield, fat content, somatic cell score (SCS), mastitis treatments, other veterinary treatments, days open, fertility treatments, non-return rate, and calf mortality. The average spacing of the typed markers was 20 cM with 2 to 14 markers per chromosome. Associations between markers and traits were analyzed with multiple marker regression. Significance was determined by permutation and genome-wise P-values obtained by Bonferroni correction. The benefits from MAS were investigated by simulation: a conventional progeny testing scheme was compared to a scheme where QTL information was used within families to select among full-sibs in the male path. Two QTL on different chromosomes were modelled. The effects of different starting frequencies of the favourable alleles and different size of the QTL effects were evaluated. A large number of QTL, 48 in total, were detected at 5% or higher chromosome-wise significance. QTL for milk production were found on 8 chromosomes, for SCS on 6, for mastitis treatments on 1, for other veterinary treatments on 5, for days open on 7, for fertility treatments on 7, for calf mortality on 6, and for non-return rate on 2 chromosomes. In the simulation study the total genetic response was faster with MAS than with conventional selection and the advantage of MAS persisted over the studied generations. The rate of response and the difference between the selection schemes reflected clearly the changes in allele frequencies of the favourable QTL. The disequilibrium between the polygenes and QTL was always negative and it was larger with larger QTL size. The disequilibrium between the two QTL was larger with QTL of large effect and it was somewhat larger with MAS for scenarios with starting frequencies below 0.5 for QTL of moderate size and below 0.3 for large QTL. In conclusion, several QTL affecting economically important traits of dairy cattle were detected. Further studies are needed to verify these QTL, check their presence in the present breeding population, look for pleiotropy and fine map the most interesting QTL regions. The results of the simulation studies show that using MAS together with embryo transfer to pre-select young bulls within families is a useful approach to increase the genetic merit of the AI-bulls compared to conventional selection.

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Evaluation of a series of spotted gum (Corymbia citirodora) progeny trials, established in the subtropical region of Queensland, Australia, was undertaken to provide information for the development of advanced-generation breeding populations suitable for pulp production. Measurements of growth at two ages were combined with assessments of wood density and pulp yield from a selected sample of provenances to provide comparisons between provenances, to generate genetic parameter estimates and to predict genetic gain potential. Although growth at this age was moderate relative to other eucalypts, the near-infrared predictions of average wood density of 756 kg m(-3) and pulp yield of 55% indicate the species has considerable potential as a pulpwood crop. A pulp productivity breeding objective was used to identify production populations using a range of selection trait weightings to determine potential genetic gain for pulp productivity. Genetic parameters indicated (1) levels of genetic control were moderate for all traits and higher for wood property traits, (2) genetic improvements could be achieved by selection among and within provenances with greater levels of improvement available from selection within populations, (3) genotype by environment interactions were negligible, (4) genetic correlations between traits were favourable, and (5) selection of volume production alone would maximise improvements in pulp productivity.