Phenotyping novel stay-green traits to capture genetic variation in senescence dynamics

Stay-green plants retain green leaves longer after anthesis and can have improved yield, particularly under water limitation. As senescence is a dynamic process, genotypes with different senescence patterns may exhibit similar final normalised difference vegetative index (NDVI). By monitoring NDVI from as early as awn emergence to maturity, we demonstrate that analysing senescence dynamics improves insight into genotypic stay-green variation. A senescence evaluation tool was developed to fit a logistic function to NDVI data and used to analyse data from three environments for a wheat (Triticum aestivum L.) population whose lines contrast for stay-green. Key stay-green traits were estimated including, maximum NDVI, senescence rate and a trait integrating NDVI variation after anthesis, as well as the timing from anthesis to onset, midpoint and conclusion of senescence. The integrative trait and the timing to onset and mid-senescence exhibited high positive correlations with yield and a high heritability in the three studied environments. Senescence rate was correlated with yield in some environments, whereas maximum NDVI was associated with yield in a drought-stressed environment. Where resources preclude frequent measurements, we found that NDVI measurements may be restricted to the period of rapid senescence, but caution is required when dealing with lines of different phenology. In contrast, regular monitoring during the whole period after flowering allows the estimation of senescence dynamics traits that may be reliably compared across genotypes and environments. We anticipate that selection for stay-green traits will enhance genetic progress towards high-yielding, stay-green germplasm.

Early-season movement dynamics of phytophagous pest and natural enemies across a native vegetation-crop ecotone

There is limited understanding about how insect movement patterns are influenced by landscape features, and how landscapes can be managed to suppress pest phytophage populations in crops. Theory suggests that the relative timing of pest and natural enemy arrival in crops may influence pest suppression. However, there is a lack of data to substantiate this claim. We investigate the movement patterns of insects from native vegetation (NV) and discuss the implications of these patterns for pest control services. Using bi-directional interception traps we quantified the number of insects crossing an NV/crop ecotone relative to a control crop/crop interface in two agricultural regions early in the growing season. We used these data to infer patterns of movement and net flux. At the community-level, insect movement patterns were influenced by ecotone in two out of three years by region combinations. At the functional-group level, pests and parasitoids showed similar movement patterns from NV very soon after crop emergence. However, movement across the control interface increased towards the end of the early-season sampling period. Predators consistently moved more often from NV into crops than vice versa, even after crop emergence. Not all species showed a significant response to ecotone, however when a response was detected, these species showed similar patterns between the two regions. Our results highlight the importance of NV for the recruitment of natural enemies for early season crop immigration that may be potentially important for pest suppression. However, NV was also associated with crop immigration by some pest species. Hence, NV offers both opportunities and risks for pest management. The development of targeted NV management may reduce the risk of crop immigration by pests, but not of natural enemies.

Ecological processes and large-scale climate relationships in northern coniferous forests

Ilmasto vaikuttaa ekologisiin prosesseihin eri tasoilla. Suuren mittakaavan ilmastoprosessit, yhdessä ilmakehän ja valtamerien kanssa, säätelevät paikallisia sääilmiöitä suurilla alueilla (mantereista pallopuoliskoihin). Tämä väistöskirja pyrkii selittämään kuinka suuren mittakaavan ilmasto on vaikuttanut tiettyihin ekologisiin prosesseihin pohjoisella havumetsäalueella. Valitut prosessit olivat puiden vuosilustojen kasvu, metsäpalojen esiintyminen ja vuoristomäntykovakuoriaisen aiheuttamat puukuolemat. Suuren mittakaavan ilmaston löydettiin vaikuttaneen näiden prosessien esiintymistiheyteen, kestoon ja levinneisyyteen keskeisten sään muuttujien välityksellä hyvin laajoilla alueilla. Tutkituilla prosesseilla oli vahva yhteys laajan mittakaavan ilmastoon. Yhteys on kuitenkin ollut hyvin dynaaminen ja muuttunut 1900-luvulla ilmastonmuutoksen aiheuttaessa muutoksia suuren mittakaavan ja alueellisten ilmastoprosessien välisiin sisäisiin suhteisiin.

Eurasian large mammal dynamics in response to changing environments during the Late Neogene

Nisäkkäiden levinneisyyteen, niiden morfologisiin ja ekologisiin piirteisiin vaikuttavat ympäristön sekä lyhyet että pitkäkestoiset muutokset, etenkin ilmaston ja kasvillisuuden vaihtelut. Työssä tutkittiin nisäkkäiden sopeutumista ilmastonmuutoksiin Euraasiassa viimeisen 24 miljoonan vuoden aikana. Tutkimuksessa keskityttiin varsinkin viimeiseen kahteen miljoonaan vuoteen, jonka aikana ilmasto muuttui voimakkaasti ja ihmisen toiminta alkoi tulla merkittäväksi. Tämän takia on usein vaikea erottaa, kummasta em. seikasta jonkin nisäkäslajin sukupuutto tai häviäminen alueelta johtui. Aineistona käytettiin laajaa venäjänkielistä kirjallisuutta, josta löytyvät tiedot ovat kääntämättöminä jääneet aiemmin länsimaisen tutkimuksen ulkopuolelle. Työssä käytettiin myös NOW-tietokantaa, jossa on fossiilisten nisäkkäiden löytöpaikat sekä niiden iät.

Weed dynamics as influenced by tillage system, sowing time and weed competition duration in dry-seeded rice

Cultural practices alter patterns of crop growth and can modify dynamics of weed-crop competition, and hence need to be investigated to evolve sustainable weed management in dry-seeded rice (DSR). Studies on weed dynamics in DSR sown at different times under two tillage systems were conducted at the Agronomic Research Farm, University of Agriculture, Faisalabad, Pakistan. A commonly grown fine rice cultivar 'Super Basmati' was sown on 15th June and 7th July of 2010 and 2011 under zero-till (ZT) and conventional tillage (CONT) and it was subjected to different durations of weed competition [10, 20, 30, 40, and 50 days after sowing (DAS) and season-long competition]. Weed-free plots were maintained under each tillage system and sowing time for comparison. Grassy weeds were higher under ZT while CONT had higher relative proportion of broad-leaved weeds in terms of density and biomass. Density of sedges was higher by 175% in the crop sown on the 7th July than on the 15th June. Delaying sowing time of DSR from mid June to the first week of July reduced weed density by 69 and 43% but their biomass remained unaffected. Tillage systems had no effect on total weed biomass. Plots subjected to season-long weed competition had mostly grasses while broad-leaved weeds were not observed at harvest. In the second year of study, dominance of grassy weeds was increased under both tillage systems and sowing times. Significantly less biomass (48%) of grassy weeds was observed under CONT than ZT in 2010; however, during 2011, this effect was non-significant. Trianthema portulacastrum and Dactyloctenium aegyptium were the dominant broad-leaved and grassy weeds, respectively. Cyperus rotundus was the dominant sedge weed, especially in the crop sown on the 7th July. Relative yield loss (RYL) ranged from 3 to 13% and 7 to16% when weeds were allowed to compete only for 20 DAS. Under season-long weed competition, RYL ranged from 68 to 77% in 2010 and 74 to80% in 2011. The sowing time of 15th June was effective in minimizing weed proliferation and rectifying yield penalty associated with the 7th July sowing. The results suggest that DSR in Pakistan should preferably be sown on 15th June under CONT systems and weeds must be controlled before 20 DAS to avoid yield losses. Successful adoption of DSR at growers' fields in Pakistan will depend on whether growers can control weeds and prevent shifts in weed population from intractable weeds to more difficult-to-control weeds as a consequence of DSR adoption.

Regularized numerical integration of multibody dynamics with the generalized alpha method*

This paper discusses the consistent regularization property of the generalized α method when applied as an integrator to an initial value high index and singular differential-algebraic equation model of a multibody system. The regularization comes from within the discretization itself and the discretization remains consistent over the range of values the regularization parameter may take. The regularization involves increase of the smallest singular values of the ill-conditioned Jacobian of the discretization and is different from Baumgarte and similar techniques which tend to be inconsistent for poor choice of regularization parameter. This regularization also helps where pre-conditioning the Jacobian by scaling is of limited effect, for example, when the scleronomic constraints contain multiple closed loops or singular configuration or when high index path constraints are present. The feed-forward control in Kane's equation models is additionally considered in the numerical examples to illustrate the effect of regularization. The discretization presented in this work is adopted to the first order DAE system (unlike the original method which is intended for second order systems) for its A-stability and same order of accuracy for positions and velocities.

Population dynamics of Thaumastocoris peregrinus in Eucalyptus plantations of South Africa

Thaumastocoris peregrinus is a sap-sucking insect that infests non-native Eucalyptus plantations in Africa, New Zealand, South America and parts of Southern Europe, in addition to street trees in parts of its native range of Australia. In South Africa, pronounced fluctuations in the population densities have been observed. To characterise spatiotemporal variability in T. peregrinus abundance and the factors that might influence it, we monitored adult population densities at six sites in the main eucalypt growing regions of South Africa. At each site, twenty yellow sticky traps were monitored weekly for 30 months, together with climatic data. We also characterised the influence of temperature on growth and survival experimentally and used this to model how temperature may influence population dynamics. T. peregrinus was present throughout the year at all sites, with annual site-specific peaks in abundance. Peaks occurred during autumn (February–April) for the Pretoria site, summer (November–January) for the Zululand site and spring (August–October) for the Tzaneen, Sabie and Piet Retief monitoring sites. Temperature (both experimental and field-collected), humidity and rainfall were mostly weakly, or not at all, associated with population fluctuations. It is clear that a complex interaction of these and other factors (e.g. host quality) influence population fluctuations in an annual, site specific cycle. The results obtained not only provide insights into the biology of T. peregrinus, but will also be important for future planning of monitoring and control programs using semiochemicals, chemical insecticides or biological control agents.

Effect of water quality and season on the population dynamics of Cabomba caroliniana in subtropical Queensland, Australia

Cabomba caroliniana is a submersed aquatic macrophyte that originates from the Americas and is currently invading temperate, subtropical, and tropical freshwater habitats around the world. Despite being a nuisance in many countries, little is known about its ecology. We monitored C. caroliniana populations in three reservoirs in subtropical Queensland, Australia, over 5.5 years. Although biomass, stem length, and plant density of the C. caroliniana stands fluctuated over time, they did not exhibit clear seasonal patterns. Water depth was the most important environmental factor explaining C. caroliniana abundance. Plant biomass was greatest at depths from 2–4 m and rooted plants were not found beyond 5 m. Plant density was greatest in shallow water and decreased with depth, most likely as a function of decreasing light and increasing physical stress. We tested the effect of a range of water physico-chemical parameters. The concentration of phosphorus in the water column was the variable that explained most of the variation in C. caroliniana population parameters. We found that in subtropical Australia, C. caroliniana abundance does not appear to be affected by seasonal conditions but is influenced by other environmental variables such as water depth and nutrient loading. Therefore, further spread will more likely be governed by local habitat rather than climatic conditions.

Effect of water quality and season on the population dynamics of Cabomba caroliniana in subtropical Queensland, Australia

Cabomba caroliniana is a submersed aquatic macrophyte that originates from the Americas and is currently invading temperate, subtropical, and tropical freshwater habitats around the world. Despite being a nuisance in many countries, little is known about its ecology. We monitored C. caroliniana populations in three reservoirs in subtropical Queensland, Australia, over 5.5 years. Although biomass, stem length, and plant density of the C. caroliniana stands fluctuated over time, they did not exhibit clear seasonal patterns. Water depth was the most important environmental factor explaining C. caroliniana abundance. Plant biomass was greatest at depths from 2–4 m and rooted plants were not found beyond 5 m. Plant density was greatest in shallow water and decreased with depth, most likely as a function of decreasing light and increasing physical stress. We tested the effect of a range of water physico-chemical parameters. The concentration of phosphorus in the water column was the variable that explained most of the variation in C. caroliniana population parameters. We found that in subtropical Australia, C. caroliniana abundance does not appear to be affected by seasonal conditions but is influenced by other environmental variables such as water depth and nutrient loading. Therefore, further spread will more likely be governed by local habitat rather than climatic conditions.

Bayesian statistical analysis of bacterial diversity

Bacteria play an important role in many ecological systems. The molecular characterization of bacteria using either cultivation-dependent or cultivation-independent methods reveals the large scale of bacterial diversity in natural communities, and the vastness of subpopulations within a species or genus. Understanding how bacterial diversity varies across different environments and also within populations should provide insights into many important questions of bacterial evolution and population dynamics. This thesis presents novel statistical methods for analyzing bacterial diversity using widely employed molecular fingerprinting techniques. The first objective of this thesis was to develop Bayesian clustering models to identify bacterial population structures. Bacterial isolates were identified using multilous sequence typing (MLST), and Bayesian clustering models were used to explore the evolutionary relationships among isolates. Our method involves the inference of genetic population structures via an unsupervised clustering framework where the dependence between loci is represented using graphical models. The population dynamics that generate such a population stratification were investigated using a stochastic model, in which homologous recombination between subpopulations can be quantified within a gene flow network. The second part of the thesis focuses on cluster analysis of community compositional data produced by two different cultivation-independent analyses: terminal restriction fragment length polymorphism (T-RFLP) analysis, and fatty acid methyl ester (FAME) analysis. The cluster analysis aims to group bacterial communities that are similar in composition, which is an important step for understanding the overall influences of environmental and ecological perturbations on bacterial diversity. A common feature of T-RFLP and FAME data is zero-inflation, which indicates that the observation of a zero value is much more frequent than would be expected, for example, from a Poisson distribution in the discrete case, or a Gaussian distribution in the continuous case. We provided two strategies for modeling zero-inflation in the clustering framework, which were validated by both synthetic and empirical complex data sets. We show in the thesis that our model that takes into account dependencies between loci in MLST data can produce better clustering results than those methods which assume independent loci. Furthermore, computer algorithms that are efficient in analyzing large scale data were adopted for meeting the increasing computational need. Our method that detects homologous recombination in subpopulations may provide a theoretical criterion for defining bacterial species. The clustering of bacterial community data include T-RFLP and FAME provides an initial effort for discovering the evolutionary dynamics that structure and maintain bacterial diversity in the natural environment.

Neutron Scattering and Molecular Dynamics Evidence for Levitation Effect in Nanopores

Neutron Scattering and Molecular Dynamics Evidence for Levitation Effect in Nanopores ... Neutron scattering measurements and molecular dynamics simulations have been carried out on the three isomers of pentane (neopentane (neo), isopentane (iso), and n-pentane (n-)) adsorbed in zeolite NaY. ... In order to understand this surprising dependence, the dimensionless levitation parameter, γ, for atomic systems may be modified to suit molecular systems.

Ecological Networks in Stored Grain: Key Postharvest Nodes for Emerging Pests, Pathogens, and Mycotoxins

Wheat is at peak quality soon after harvest. Subsequently, diverse biota use wheat as a resource in storage, including insects and mycotoxin-producing fungi. Transportation networks for stored grain are crucial to food security and provide a model system for an analysis of the population structure, evolution, and dispersal of biota in networks. We evaluated the structure of rail networks for grain transport in the United States and Eastern Australia to identify the shortest paths for the anthropogenic dispersal of pests and mycotoxins, as well as the major sources, sinks, and bridges for movement. We found important differences in the risk profile in these two countries and identified priority control points for sampling, detection, and management. An understanding of these key locations and roles within the network is a new type of basic research result in postharvest science and will provide insights for the integrated pest management of high-risk subpopulations, such as pesticide-resistant insect pests.