Understanding animal movement is essential to elucidate how animals interact, survive, and thrive in a changing world. Recent technological advances in data collection and management have transformed our understanding of animal "movement ecology" (the integrated study of organismal movement), creating a big-data discipline that benefits from rapid, cost-effective generation of large amounts of data on movements of animals in the wild. These high-throughput wildlife tracking systems now allow more thorough investigation of variation among individuals and species across space and time, the nature of biological interactions, and behavioral responses to the environment. Movement ecology is rapidly expanding scientific frontiers through large interdisciplinary and collaborative frameworks, providing improved opportunities for conservation and insights into the movements of wild animals, and their causes and consequences.

Induced point mutations are important genetic resources for their ability to create hypo- and hypermorphic alleles that are useful for understanding gene functions and breeding. However, such mutant populations have only been developed for a few temperate maize varieties, mainly B73 and W22, yet no tropical maize inbred lines have been mutagenized and made available to the public to date. We developed a novel Ethyl Methanesulfonate (EMS) induced mutation resource in maize comprising 2050 independent M2 mutant families in the elite tropical maize inbred ML10. By phenotypic screening, we showed that this population is of comparable quality with other mutagenized populations in maize. To illustrate the usefulness of this population for gene discovery, we performed rapid mapping-by-sequencing to clone a fasciated-ear mutant and identify a causal promoter deletion in ZmCLE7 (CLE7). Our mapping procedure does not require crossing to an unrelated parent, thus is suitable for mapping subtle traits and ones affected by heterosis. This first EMS population in tropical maize is expected to be very useful for the maize research community. Also, the EMS mutagenesis and rapid mapping-by-sequencing pipeline described here illustrate the power of performing forward genetics in diverse maize germplasms of choice, which can lead to novel gene discovery due to divergent genetic backgrounds.

Background: Length-for-age is considered the indicator of choice in monitoring the long-term impact of chronic nutritional deficiency. Aim: We hypothesized that short term increments of body weight cross-correlate with increments of the lower leg length. Sample and methods: We re-analyzed the association between weekly measurements of weight and of lower leg length in 34 healthy German children, aged 2.9-15.9 years. The data are a subset of measurements originally published in 1988 (Hermanussen et al. 1988a). As the growth measurements were often not equally spaced in time due to interposed holidays and illness, the incremental rates for weight and lower leg length were smoothed using spline functions. Autocorrelation and cross-correlation functions were calculated for weight increments and lower leg length increments. Results: Height and weight increments are pulsatile. Autocorrelations indicated that mini growth spurts occur at irregular intervals. Lack of cross-correlations between weight and lower leg length indicated that mini spurts in weight gain do not coincide with mini spurts in length gain even when considering lag times of up to 10 weeks. Short term changes of weight gain and lower leg length gain in healthy children show no temporal association.

A biosensor for phenolic compounds based on a chemically modified laccase from Coriolus hirsula immobilized on functionalized screen-printed carbon electrodes (SPCEs) was achieved. Different enzyme modifications and immobilization strategies were analyzed. The electrochemical response of the immobilized laccase on SPCEs modified with carboxyl functionalized multi-walled carbon nanotubes (COOH-MWCNT) was the highest when laccase was aminated prior to the adsorption onto the working electrode. The developed lactase biosensor sensitivity toward different phenolic compounds was assessed to determine the biosensor response with several phenolic compounds. The highest response was obtained for ABTS with a saturation value of I-max = 27.94 mu A. The electrocatalytic efficiency (I-max/K-m(app)) was the highest for ABTS (5588 mu A mu M-1) followed by syringaldazine (3014 mu A.mu M-1). The sensors were considerably stable, whereby 99.5, 82 and 77% of the catalytic response using catechol as substrate was retained after 4, 8 and 10 successive cycles of reuse respectively, with response time average of 5 s for 12 cycles. No loss of activity was observed after 20 days of storage.

Following the extinction of dinosaurs, the great adaptive radiation of mammals occurred, giving rise to an astonishing ecological and phenotypic diversity of mammalian species. Even closely related species often inhabit vastly different habitats, where they encounter diverse environmental challenges and are exposed to different evolutionary pressures. As a response, mammals evolved various adaptive phenotypes over time, such as morphological, physiological and behavioural ones. Mammalian genomes vary in their content and structure and this variation represents the molecular mechanism for the long-term evolution of phenotypic variation. However, understanding this molecular basis of adaptive phenotypic variation is usually not straightforward. The recent development of sequencing technologies and bioinformatics tools has enabled a better insight into mammalian genomes. Through these advances, it was acknowledged that mammalian genomes differ more, both within and between species, as a consequence of structural variation compared to single-nucleotide differences. Structural variant types investigated in this thesis - such as deletion, duplication, inversion and insertion, represent a change in the structure of the genome, impacting the size, copy number, orientation and content of DNA sequences. Unlike short variants, structural variants can span multiple genes. They can alter gene dosage, and cause notable gene expression differences and subsequently phenotypic differences. Thus, they can lead to a more dramatic effect on the fitness (reproductive success) of individuals, local adaptation of populations and speciation. In this thesis, I investigated and evaluated the potential functional effect of structural variations on the genomes of mustelid species. To detect the genomic regions associated with phenotypic variation I assembled the first reference genome of the tayra (Eira barbara) relying on linked-read sequencing technology to achieve a high level of genome completeness important for reliable structural variant discovery. I then set up a bioinformatics pipeline to conduct a comparative genomic analysis and explore variation between mustelid species living in different environments. I found numerous genes associated with species-specific phenotypes related to diet, body condition and reproduction among others, to be impacted by structural variants. Furthermore, I investigated the effects of artificial selection on structural variants in mice selected for high fertility, increased body mass and high endurance. Through selective breeding of each mouse line, the desired phenotypes have spread within these populations, while maintaining structural variants specific to each line. In comparison to the control line, the litter size has doubled in the fertility lines, individuals in the high body mass lines have become considerably larger, and mice selected for treadmill performance covered substantially more distance. Structural variants were found in higher numbers in these trait-selected lines than in the control line when compared to the mouse reference genome. Moreover, we have found twice as many structural variants spanning protein-coding genes (specific to each line) in trait-selected lines. Several of these variants affect genes associated with selected phenotypic traits. These results imply that structural variation does indeed contribute to the evolution of the selected phenotypes and is heritable. Finally, I suggest a set of critical metrics of genomic data that should be considered for a stringent structural variation analysis as comparative genomic studies strongly rely on the contiguity and completeness of genome assemblies. Because most of the available data used to represent reference genomes of mammalian species is generated using short-read sequencing technologies, we may have incomplete knowledge of genomic features. Therefore, a cautious structural variation analysis is required to minimize the effect of technical constraints. The impact of structural variants on the adaptive evolution of mammalian genomes is slowly gaining more focus but it is still incorporated in only a small number of population studies. In my thesis, I advocate the inclusion of structural variants in studies of genomic diversity for a more comprehensive insight into genomic variation within and between species, and its effect on adaptive evolution.

A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.

The current trends of crop yield improvements are not expected to meet the projected rise in demand. Genomic selection uses molecular markers and machine learning to identify superior genotypes with improved traits, such as growth. Plant growth directly depends on rates of metabolic reactions which transform nutrients into the building blocks of biomass. Here, we predict growth of Arabidopsis thaliana accessions by employing genomic prediction of reaction rates estimated from accession-specific metabolic models. We demonstrate that, comparing to classical genomic selection on the available data sets for 67 accessions, our approach improves the prediction accuracy for growth within and across nitrogen environments by 32.6% and 51.4%, respectively, and from optimal nitrogen to low carbon environment by 50.4%. Therefore, integration of molecular markers into metabolic models offers an approach to predict traits directly related to metabolism, and its usefulness in breeding can be examined by gathering matching datasets in crops. An increase in genomic selection (GS) accuracy can accelerate genetic gain by shortening the breeding cycles. Here, the authors introduce a network-based GS method that uses metabolic models and improves the prediction accuracy of Arabidopsis growth within and across environments.

Objectives: To assess trends in growth in different developmental periods and trends in developmental tempo in Polish boys between 1966 and 2012. Methods: Data on 34 828 boys aged 7 to 18 years were collected during Polish Anthropological Surveys conducted in 1966, 1978, 1988, and 2012. Biological parameters, related to onset of adolescent growth spurt (OGS) and peak height velocity (PHV), were derived from a Preece-Baines 1 model (PB1). Childhood (height at 7 years of age), pre-adolescent (height at OGS) and adolescent growth (adult height minus height at OGS) were identified. Results: Positive secular trend between 1966 and 2012 in adult height accounted for, on average, 1.5 cm/decade, with varying intensity between the Surveys. Decline in both age at OGS and APHV between 1966 and 2012 (1.5 and 1.4 years, respectively) indicated an acceleration in developmental tempo, on average, by 0.3 year/decade. Increases in the contribution to the trend in adult height gained during growth in particular developmental periods between 1966 and 2012 were as followed-childhood: 0.6%, pre-adolescent growth: -3.1%, adolescent growth: 3.1%. Conclusions: Secular trend in developmental tempo and growth among boys reflects changes in living conditions and socio-political aspirations in Poland during nearly 50 years. Acceleration in tempo is already visible at age at OGS, whereas the trend in adult height occurs largely during adolescence, pointing to different regulation of developmental tempo and growth in body height. This finding emphasizes the importance of extending public health intervention into children's growth up until adolescence.

Dictyostelium amoebae perform a semi-closed mitosis, in which the nuclear envelope is fenestrated at the insertion sites of the mitotic centrosomes and around the central spindle during karyokinesis. During late telophase the centrosome relocates to the cytoplasmic side of the nucleus, the central spindle disassembles and the nuclear fenestrae become closed. Our data indicate that Dictyostelium spastin (DdSpastin) is a microtubule-binding and severing type I membrane protein that plays a role in this process. Its mitotic localization is in agreement with a requirement for the removal of microtubules that would hinder closure of the fenestrae. Furthermore, DdSpastin interacts with the HeH/ LEM-family protein Src1 in BioID analyses as well as the inner nuclear membrane protein Sun1, and shows subcellular co-localizations with Src1, Sun1, the ESCRT component CHMP7 and the IST1-like protein filactin, suggesting that the principal pathway of mitotic nuclear envelope remodeling is conserved between animals and Dictyostelium amoebae.