Fruits and frugivory in neotropical primates and in Amazonian flooded and unflooded forests

The richness and resilience of tropical forest ecosystems are best described by the myriad of ecological interactions linking co-occurring species together. The many functions previously served by ecological links are often only detected once these links are lost. Of particular interest in this regard are the mutualistic networks between fruiting plants and vertebrate frugivores, whose interdependent relationship is fundamental to the functioning of tropical forests. This thesis examined these fruitfrugivore interactions at two contrasting scales, and using two different approaches. On a landscape scale in western Brazilian Amazonia, the focus was on a community-wide assessment, with particular attention paid to the differences between two highly divergent but adjacent species-rich forest types, seasonally-flooded várzea forests and unflooded terra firme forests. As part of this comparison, the powerful role of the annual flood pulse was shown to determine both spatial patterns of forest structure and temporal patterns of fruit production. The strong influence of this seasonal cycle was apparent in the adaptive traits observed in plants and animals, with corresponding effects upon their networks of interactions. The role of frugivore body size as an important trait in relation to the degree of frugivory within consumers was emphasised via one of the most extensive compilations on the feeding ecology of any frugivorous vertebrate taxon. By amassing the observations of feeding records accumulated over several decades of neotropical primate field research, and accounting for the highly variable levels of sampling effort among primate species, the prevalence of frugivory at the mid-high spectrum of body mass was confirmed. This continental-scale metaanalysis also revealed that, despite representing arguably the most observable and wellstudied group of vertebrate frugivores in tropical forests worldwide, most primate species were heavily undersampled in terms of the richness of fruits known to occur in their diets. These astounding gaps in our cumulative knowledge highlight the challenges faced in assembling comprehensive fruit-frugivore networks for entire communities, where the diets of most consumers are even more poorly understood than for primates. This is particularly pertinent in the face of ever-increasing threats to ecosystems comprised of, and sustained by, these complex webs of interactions

Analysis of techniques for mapping environments for fauna survey

A discussion of environmental land classification is presented for the purpose of surveying avifaunal communities. Surveying and mapping land uses the term environment in a special sense. Environment can be mapped into regions whose components are interacting climate terrain, geology, soils and biota. The problem of how to describe the environment for sampling fauna requires an approach which samples the inherent and known variability of all environmental regions present. Discovery of patterns between fauna and environment provide the basis for understanding species/habitat relationships and provides a valuable basis for management or more detailed studies. Two environmental mapping methods commonly employed in faunal survey and management are systematic grids and natural landscape patterns; these were compared to determine their effectiveness for classifying the environment for sampling avifaunal communities. A detailed study was undertaken between 1982-84 in a plot of 8km2 in the Tianjara area. The plot was chosen to encompass a representative sample of the wide range of environments described by Gunn (1985). Analysis of the systematic grids involved sampling a diverse set of environmental attributes into six different grid sizes, including 100m2, 200m2, 300m2, 400m2, 500m2 and 1000m2. Topographic maps and aerial photos provided the sources for measuring the attributes. Results of several analyses showed the 300m2 grid was the most appropriate for the Tianjara area. Analysis of natural landscape patterns involved adoption of the work done by Gunn et al (1984) and led to the preparation of a land unit map for the study plot. Detailed patterns were delineated in 1:27,000 scale air photos and described using the land unit descriptions in Gunn (1985). Results from ground site samples taken to verify the two mapping bases showed that the correspondence between map and ground data was better for sites in systematic grids than for natural landscape patterns. Notwithstanding this, a better understanding of the effects of sampling specific patches of environment was gained from examining sites in natural landscape patterns because it employed a stratified representative sampling strategy, while the systematic grids used a centric systematic sampling strategy. The effect of this was large uniform patches of habitat tended to be more oversampled by sites in systematic grids than was observed for sites in natural landscape patterns. Examination of the relationships between the sampling bases using analyses of environment was not possible because of the lack of sufficient sites in common between the two sampling bases. Comparison of the two sampling bases was, however, possible by using avifaunal data common to both sampling bases. Analysis of the relationships between avifaunal data and environmental groups showed only minor differences between the effectiveness of the two sampling bases to provide practical and realistic descriptions of environment for describing discrete assemblages of birds. The overall conclusion of this study is that any environmental classification, so long as it is based on relevant attributes known to be important for environmental structure and processes, will provide a valuable basis for sampling fauna. A number of points need to be stressed regarding analyses of this type; care needs to be exercised in choosing surrogate environmental attributes between the mapping and ground site data and caution is required when allocating sampling sites to avoid overemphasising area of environmental groups as more important than the inherent variability of the attributes within the environmental groups. An understanding of this problem will greatly improve the nature of sampling fauna in environmental regions

ИНТЕЛЛЕКТУАЛЬНЫЙ числовым программным ДЛЯ MIMD-компьютер

For most scientific and engineering problems simulated on computers the solving of problems of the computational mathematics with approximately given initial data constitutes an intermediate or a final stage. Basic problems of the computational mathematics include the investigating and solving of linear algebraic systems, evaluating of eigenvalues and eigenvectors of matrices, the solving of systems of non-linear equations, numerical integration of initial- value problems for systems of ordinary differential equations.Для більшості наукових та інженерних задач моделювання на ЕОМ рішення задач обчислювальної математики з наближено заданими вихідними даними складає проміжний або остаточний етап. Основні проблеми обчислювальної математики відносяться дослідження і рішення лінійних алгебраїчних систем оцінки власних значень і власних векторів матриць, рішення систем нелінійних рівнянь, чисельного інтегрування початково задач для систем звичайних диференціальних рівнянь.Для большинства научных и инженерных задач моделирования на ЭВМ решение задач вычислительной математики с приближенно заданным исходным данным составляет промежуточный или окончательный этап. Основные проблемы вычислительной математики относятся исследования и решения линейных алгебраических систем оценки собственных значений и собственных векторов матриц, решение систем нелинейных уравнений, численного интегрирования начально задач для систем обыкновенных дифференциальных уравнений

Testing environmental DNA sampling and predictive modeling as means to investigate wood frog (Rana sylvatica) distribution in Alaska and Northern Canada

Thesis (M.S.) University of Alaska Fairbanks, 2017Global amphibian declines over the past 30+ years have led to a greater awareness of amphibian conservation issues. Few amphibian species occur in northern landscapes, however, and the species that do occur are widely dispersed and at the northern extent of their range. Accordingly, amphibian research is not prioritized in northern landscapes. Deficient monitoring practices have resulted in incomplete distribution knowledge that impedes the management of wood frogs (Rana sylvatica) in Alaska and northern Canada. I developed an environmental DNA detection assay to complement monitoring practices at the northern extent of the wood frog's range. This assay was tested to be species-specific, allowing it to be implemented in areas where wood frogs may co-occur with other amphibian species. It can detect wood frog DNA in environmental samples to a concentration of 1.83 x 10⁻³ pg/μL. I further demonstrate that environmental DNA occurrence data can be used to predict wood frog distribution in the Fairbanks North Star Borough. I combined environmental DNA occurrence data with environmental GIS data and analyzed the resulting dataset with machine learning algorithms to define an ecological niche for the wood frog. This niche, when extrapolated to the landscape, results in a species distribution model that attains 74% predictive accuracy. Lastly, I conducted an environmental DNA mega-transect survey along the Elliot/Dalton Highway corridor in Alaska. I combined the results of this survey with citizen science occurrence data from past and current monitoring projects to create a set of alternative occurrence data. This alternative data was combined with environmental GIS data and analyzed with machine learning algorithms to create a species distribution model that achieves 92% predictive accuracy across Alaska and the Yukon Territory, Canada. These results improve upon prior species distribution models developed for wood frogs in Alaska. They provide deeper insights into potential wood frog distribution at high latitudes and elevations in Alaska, where anecdotal observations have previously been recorded. Adoption and widespread use of an environmental DNA monitoring protocol in under-sampled regions of Alaska and northern Canada will generate larger datasets with wider geographic coverage, leading to models with even higher predictive accuracy. Alternative data, including that obtained from environmental DNA and citizen science monitoring, can boost efforts to further develop baseline knowledge of wood frog occurrence in these areas. Species distribution models generated in this research can help guide these efforts. Increasing knowledge of wood frog distribution may assist conservation managers to designate critical habitat, study climate impacts, and make more informed decisions regarding amphibians in northern landscapes.Chapter 1 Development, validation, and evaluation of an assay for the detection of wood frogs (Rana sylvatica) in environmental DNA -- Chapter 2 Application of environmental DNA-based occurrence data in modeling wood frog (Rana sylvatica) distribution in Interior Alaska -- Chapter 3 A reassessment of wood frog (Rana sylvatica) distribution in Alaska and northern Canada based on environmental DNA and citizen science -- Conclusion -- References -- Appendices

Towards Fast and High-quality Biomedical Image Reconstruction

Department of Computer Science and EngineeringReconstruction is an important module in the image analysis pipeline with purposes of isolating the majority of meaningful information that hidden inside the acquired data. The term ???reconstruction??? can be understood and subdivided in several specific tasks in different modalities. For example, in biomedical imaging, such as Computed Tomography (CT), Magnetic Resonance Image (MRI), that term stands for the transformation from the, possibly fully or under-sampled, spectral domains (sinogram for CT and k-space for MRI) to the visible image domains. Or, in connectomics, people usually refer it to segmentation (reconstructing the semantic contact between neuronal connections) or denoising (reconstructing the clean image). In this dissertation research, I will describe a set of my contributed algorithms from conventional to state-of-the-art deep learning methods, with a transition at the data-driven dictionary learning approaches that tackle the reconstruction problems in various image analysis tasks.clos

Optical MIMO communication systems under illumination constraints

Technology for wireless information access has enabled innovation of 'smart' portable consumer devices. These have been widely adopted and have become an integral part of our daily lives. They need ubiquitous connectivity to the internet to provide value added services, maximize their functionality and create a smarter world to live in. Cisco's visual networking index currently predicts wireless data consumption to increase by 61% per year. This will put additional stress on the already stressed wireless access network infrastructure creating a phenomenon called 'spectrum crunch'. At the same time, the solid state devices industry has made remarkable advances in energy efficient light-emitting-diodes (LED). The lighting industry is rapidly adopting LEDs to provide illumination in indoor spaces. Lighting fixtures are positioned to support human activities and thus are well located to act as wireless access points. The visible spectrum (380 nm - 780 nm) is yet unregulated and untapped for wireless access. This provides unique opportunity to upgrade existing lighting infrastructure and create a dense grid of small cells by using this additional 'optical' wireless bandwidth. Under the above model, lighting fixtures will service dual missions of illumination and access points for optical wireless communication (OWC). This dissertation investigates multiple-input multiple-output (MIMO) optical wireless broadcast system under unique constraints imposed by the optical channel and illumination requirements. Sample indexed spatial orthogonal frequency division multiplexing (SIS-OFDM) and metameric modulation (MM) are proposed to achieve higher spectral efficiency by exploiting dimensions of space and color respectively in addition to time and frequency. SIS-OFDM can provide significant additional spectral efficiency of up to (Nsc/2 - 1) x k bits/sym where Nsc is total number of subcarriers and k is number of bits per underlying spatial modulation symbol. MM always generates the true requested illumination color and has the potential to provide better color rendering by incorporating multiple LEDs. A normalization framework is then developed to analyze performance of optical MIMO imaging systems. Performance improvements of up to 45 dB for optical systems have been achieved by decorrelating spatially separate links by incorporating an imaging receiver. The dissertation also studies the impact of visual perception on performance of color shift keying as specified in IEEE 802.15.7 standard. It shows that non-linearity for a practical system can have a performance penalty of up to 15 dB when compared to the simplified linear system abstraction as proposed in the standard. Luminous-signal-to-noise ratio, a novel metric is introduced to compare performance of optical modulation techniques operating at same illumination intensity. The dissertation then introduces singular value decomposition based OWC system architecture to incorporate illumination constraints independent of communication constraints in a MIMO system. It then studies design paradigm for a multi-colored wavelength division multiplexed indoor OWC system

Student Spotlight on Research and Outreach Proceedings

ESF\u27s annual Spotlight Symposium is a dynamic forum where graduate and undergraduate students share the results of their research and community service projects. The Spotlight is a student poster session highlighting scholarly efforts

Estimating Movement from Mobile Telephony Data

Mobile enabled devices are ubiquitous in modern society. The information gathered by their normal service operations has become one of the primary data sources used in the understanding of human mobility, social connection and information transfer. This thesis investigates techniques that can extract useful information from anonymised call detail records (CDR). CDR consist of mobile subscriber data related to people in connection with the network operators, the nature of their communication activity (voice, SMS, data, etc.), duration of the activity and starting time of the activity and servicing cell identification numbers of both the sender and the receiver when available. The main contributions of the research are a methodology for distance measurements which enables the identification of mobile subscriber travel paths and a methodology for population density estimation based on significant mobile subscriber regions of interest. In addition, insights are given into how a mobile network operator may use geographically located subscriber data to create new revenue streams and improved network performance. A range of novel algorithms and techniques underpin the development of these methodologies. These include, among others, techniques for CDR feature extraction, data visualisation and CDR data cleansing. The primary data source used in this body of work was the CDR of Meteor, a mobile network operator in the Republic of Ireland. The Meteor network under investigation has just over 1 million customers, which represents approximately a quarter of the country’s 4.6 million inhabitants, and operates using both 2G and 3G cellular telephony technologies. Results show that the steady state vector analysis of modified Markov chain mobility models can return population density estimates comparable to population estimates obtained through a census. Evaluated using a test dataset, results of travel path identification showed that developed distance measurements achieved greater accuracy when classifying the routes CDR journey trajectories took compared to traditional trajectory distance measurements. Results from subscriber segmentation indicate that subscribers who have perceived similar relationships to geographical features can be grouped based on weighted steady state mobility vectors. Overall, this thesis proposes novel algorithms and techniques for the estimation of movement from mobile telephony data addressing practical issues related to sampling, privacy and spatial uncertainty

LSST Science Book, Version 2.0

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at http://www.lsst.org/lsst/sciboo

From Data to Software to Science with the Rubin Observatory LSST

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science.Comment: White paper from "From Data to Software to Science with the Rubin Observatory LSST" worksho