Development, implementation, and validation of a new method for meta-analysis of voxel-based neuroimage studies

[spa] The objective of this thesis was to develop a method for the meta-analysis of neuroimaging studies that overcomes the drawbacks of the neuroimaging meta-analytic methods described above. To this end, we modified AES-SDM (Radua et al. (2014)) to incorporate several major changes that address each of the above limitations. This has resulted in a new method, called SDM-PSI, with profound differences from any previous neuroimaging meta-analytic method. I divided this overarching objective into the following individual objectives: 1. Accurately identify and circumscribe the drawbacks of the neuroimaging metaanalytic methods present at the time of the conception of this thesis. 2. Develop the statistical techniques of the new method. Optimize the usage of maximum likelihood estimation (MLE) to estimate the distribution of the missing information of the neuroimaging studies and combine it with the usage of multiple imputation techniques to recreate this non-published information. This combination shall intend to obtain better estimates of effect sizes in areas where CBM studies did not report results. 3. Develop an algorithm for the new method viable for being implemented efficiently, providing an implementation that can be successfully used in real-world scenarios. 4. Modify the SDM meta-analytic method to incorporate these new statistical techniques, as well as other novel changes in the field such as a standard subject-based permutation test instead of the spatial permutation approach used by previous methods. 5. Design and develop an algorithm for the usage of the standard permutation test as part of the SDM method. A computationally efficient implementation of such an algorithm shall also be feasible. 6. Adopt the scope not only of theoretical-methodological work but also of practical work with usable results and implementations ready to be used by the neuroimage meta-analysis community. This shall include the development of powerful software and a graphical user interface. 7. Disseminate the new method to ease the adoption of its application by the scientific community. This included the release of the new software in a user-friendly form, writing and recording a visual publication [117], and proactively seeking collaboration studies with scientific teams from other institutions and labs that would provide the first publications making use of the new method. The first objective is addressed in the first published article that comprises this thesis; the second and third objectives are addressed in the second published article; the fourth, fifth and sixth objectives are addressed in the third published article, and the seventh objective is addressed in the fourth published article

Representative taxa in field trials for environmental risk assessment of genetically modified maize

When assessing the benefits and risks of transgenic crops, one consideration is their relative effects on non-target arthropod (NTA) abundance and functions within agroecosystems. Several laboratory and field trials have been conducted in Spain since the late 1990s to assess this issue. A consideration in the design of field trials is whether it is necessary to sample most NTAs living in the crop or only representative taxa that perform main ecological functions and have a good capacity to detect small changes in their abundance. Small changes in the field abundance of an effective representative taxon should be detectable using standard experimental protocols. The ability of a species to reveal differences across treatments may be analysed by examining the detectable treatment effects for surveyed non-target organisms. Analysis of data from several NTAs recorded in 14 field trials conducted over 10 years using complete block designs allowed us to select a number of representative taxa capable of detecting changes in the density or activity of arthropod herbivores, predators, parasitoids and decomposers in transgenic and non-transgenic maize varieties. The most suitable NTA as representative taxa (with detectable treatment effects below 50%) included leafhoppers among arthropod herbivores, Orius spp., Araneae, and Carabidae among predators, chalcidids, particularly the family Mymaridae, among parasitoids and Chloropidae as decomposer. Details of sampling techniques for each sampled taxa and their advantages and disadvantages are discussed. It is concluded that abundance of taxa is the most influential factor determining their capacity to detect changes caused by genetically modified varieties.Peer ReviewedPostprint (published version

Planting period is the main factor for controlling maize rough dwarf disease

Maize rough dwarf virus (MRDV) is one of the main yield-limiting factors of maize in the Mediterranean. However, knowledge about the interactions between the agroecosystem and the virus–vector–host relationship continues to be limited. We used multi-model inference to test a landscape-scale approach together with variables measured in the field, and we estimated the effects of early and late planting on MRDV incidence. The results revealed that the virus incidence increased by 3% when the planting was delayed, and this increase was coincident with the first peak of the vector population. The variables at the field and landscape scales with a strong effect on virus incidence were the proportions of grasses in adjacent crops, in uncultivated areas, and in edges close to maize plants. Grass plant cover in the edges also affected virus incidence, but these effects varied with the planting period. These findings provide new insights into the causes of MRDV incidence and may provide some guidance to growers to reduce losses caused by the virus. Among the recommendations to be prioritized are early planting, management of grasses at field edges, and non-overlapping cultivation of maize and winter cereals in the same area.info:eu-repo/semantics/publishedVersio