The Ecological Strategies of Aquatic Ranunculus Species

A survey involving repeated visits to 56 river sites with a variety of Batrachian Ranunculus species was carried out. Analysis of the data using CANOCO suggested that the following measured environmental variables were the most important in determining the plant community composition; pH, sediment nitrogen, phosphate and potassium concentration, shade, water velocity, water phosphate concentration and elevation. In addition, management by cutting and grazing and poaching by cattle were important variables. Chemical analysis of plant and sediment samples revealed significant positive correlations between the concentrations of Ranunculus shoot tissue phosphate and water phosphate, Ranunculus phosphate and sediment phosphate, and Ranunculus nitrogen and water nitrate. A series of transplant trials were carried out to determine to what extent it was possible for Ranunculus species to survive outside of the conditions in which they were found in the survey. Three of the stresses identified in the survey were further investigated in experimental work; shade, low water velocity and eutrophication. A field experiment was carried out on a tributary of the River Frome (a chalk stream dominated by Ranunculus penicillatus subsp. pseudofluitans'). The change in community composition in shaded plots compared with unshaded plots was measured during the growing season. The following season the experiment was repeated, but with the additional stress of reduced water velocity. During the first season the Ranunculus cover was much less in the shaded plots, and the cover of other members of the plant community was also significantly less in the shaded plots. During the season with reduced water velocity Elodea canadensis rather than R. penicillatus subsp. pseudofluitans became the dominant species, and the community reacted in a similar way to the shade stress. There was less total plant growth (more visible substrate) in the low velocity (increased stress) season and a higher species diversity. The effects of elevated phosphate concentration were investigated in an experiment in a pair of artificial recirculating rivers. One of the rivers had the phosphate input raised from 40 mugP I-1 to 200 mugP I-1, which resulted in prolific filamentous algal growth. R. penicillatus subsp. pseudofluitans and Potamogeton pectinatus plants showed a reduction in growth in the elevated phosphate (presumably due to shading from the algae), and where Ranunculus and Potamogeton plants were grown next to each other, the Ranunculus root biomass was significantly reduced. Several experiments were carried out on the effects of disturbance on Ranunculus penicillatus subsp. pseudofluitans. Ranunculus clumps were cut repeatedly in the River Rye. It was discovered that after the first and second cuts, the shoots showed increased growth but after the third cut they showed decreased growth. By contrast, in two experiments carried out in polluted sites (Gogar Burn and the headwaters of the River Hull), there was no evidence for an increase in growth after a single cut. Ranunculus species are associated both with particular current velocities and particular sediment particle sizes. Does this correlation with sediment imply that the sediment causes the distribution, or is sediment texture itself simply a reflection of current velocity? An experiment in the Mouse Water found no correlation between Ranunculus growth and sediment particle size, suggesting that current velocity is the primary determinant. Throughout the thesis the data were interpreted in terms of C-S-R strategy theory. A greenhouse shading experiment ranked four Ranunculus taxa in terms of their stress-tolerance (R. hederaceus > R. circinatus > R. penicillatus subsp. pseudofluitans > R. fluitans). The data from the survey were used to devise integrated indices of stress ana disturbance for each site surveyed, and this was then used to determine the importance of stress and disturbance in the habitats occupied by the various Ranunculus species, and by implication the importance of stress and disturbance in the strategy of those species, i. e. the C-S-R strategy of each species. A further survey was carried out of 57 river sites with Ranunculus species present, and various morphological attributes were measured on the plants. These attributes were then regressed against the strategy of the plant in order to determine which traits are associated with a particular strategy. Stress-tolerant species tend to have floating leaves, lack divided submerged leaves, and tend to have small, weak shoots. Disturbance-tolerant species lack floating leaves and have large, strong shoots. Competitive taxa tend to have long submerged leaves, and lack floating leaves

Log-concavity of matroid h-vectors and mixed Eulerian numbers

For any matroid $M$, we compute the Tutte polynomial $T_M(x,y)$ using the mixed intersection numbers of certain tautological classes in the combinatorial Chow ring $A^\bullet(M)$ arising from Grassmannians. Using mixed Hodge-Riemann relations, we deduce a strengthening of the log-concavity of the h-vector of a matroid complex, improving on an old conjecture of Dawson whose proof was announced recently by Ardila, Denham and Huh.Comment: 29 pages, comments welcome

Collaboration on procurement of e-content between the National Health Service and higher education in the UK

Collaboration on procurement of e-content across health libraries in the NHS and in higher education should have advantages in avoiding unnecessary duplication of purchased content. The aim of the paper is to examine some of the strategies for ensuring that collaboration across the two sectors, works effectively. The paper is based on a report to the Joint Information Systems Committee of the Funding Councils (for higher and further education) in the UK, and the NHS Library and Knowledge Development Network on research conducted in 2006. The methods included interviews (n=39) with representatives from NHS and higher education bodies, representatives of independent health libraries, the National Library for Health, collective agencies, publishers and aggregators. There were common interests in functionality/interfaces, open access, and better metrics for estimating usage that might contribute to discussions with publishers over the licence terms. There are differences in the type of resource each sector might deem core. The extent of existing collaboration on purchasing and related collection management activities varied considerably across the UK. Three possible paths for cooperative activity were identified: 1) sharing information and joint advocacy; 2) building the technical infrastructure; and 3) joint procurement. Mapping of the stages, roles, actors and stakeholders in some processes was done with ‘use cases’ (Unified Modeling Language) to help identify some of the risks involved. Concludes that collaborative procurement of e-content activities should focus on health services research requirements, open access needs across the sectors, and more innovative analysis of usage statistics to profile usage and inform cost analyses of the impact of new roles for health librarians, and cost analyses of e-resources on a life cycle basis

Tautological classes of matroids

We introduce certain torus-equivariant classes on permutohedral varieties which we call "tautological classes of matroids" as a new geometric framework for studying matroids. Using this framework, we unify and extend many recent developments in matroid theory arising from its interaction with algebraic geometry. We achieve this by establishing a Chow-theoretic description and a log-concavity property for a 4-variable transformation of the Tutte polynomial, and by establishing an exceptional Hirzebruch-Riemann-Roch-type formula for permutohedral varieties that translates between K-theory and Chow theory.Comment: 69 pages; comments welcome. v2: minor edits, addition of subsection 10.

Measuring Behavior 2018 Conference Proceedings

These proceedings contain the papers presented at Measuring Behavior 2018, the 11th International Conference on Methods and Techniques in Behavioral Research. The conference was organised by Manchester Metropolitan University, in collaboration with Noldus Information Technology. The conference was held during June 5th – 8th, 2018 in Manchester, UK. Building on the format that has emerged from previous meetings, we hosted a fascinating program about a wide variety of methodological aspects of the behavioral sciences. We had scientific presentations scheduled into seven general oral sessions and fifteen symposia, which covered a topical spread from rodent to human behavior. We had fourteen demonstrations, in which academics and companies demonstrated their latest prototypes. The scientific program also contained three workshops, one tutorial and a number of scientific discussion sessions. We also had scientific tours of our facilities at Manchester Metropolitan Univeristy, and the nearby British Cycling Velodrome. We hope this proceedings caters for many of your interests and we look forward to seeing and hearing more of your contributions

Volume segmentation and analysis of biological materials using SuRVoS (Super-region Volume Segmentation) workbench

Segmentation is the process of isolating specific regions or objects within an imaged volume, so that further study can be undertaken on these areas of interest. When considering the analysis of complex biological systems, the segmentation of three-dimensional image data is a time consuming and labor intensive step. With the increased availability of many imaging modalities and with automated data collection schemes, this poses an increased challenge for the modern experimental biologist to move from data to knowledge. This publication describes the use of SuRVoS Workbench, a program designed to address these issues by providing methods to semi-automatically segment complex biological volumetric data. Three datasets of differing magnification and imaging modalities are presented here, each highlighting different strategies of segmenting with SuRVoS. Phase contrast X-ray tomography (microCT) of the fruiting body of a plant is used to demonstrate segmentation using model training, cryo electron tomography (cryoET) of human platelets is used to demonstrate segmentation using super- and megavoxels, and cryo soft X-ray tomography (cryoSXT) of a mammalian cell line is used to demonstrate the label splitting tools. Strategies and parameters for each datatype are also presented. By blending a selection of semi-automatic processes into a single interactive tool, SuRVoS provides several benefits. Overall time to segment volumetric data is reduced by a factor of five when compared to manual segmentation, a mainstay in many image processing fields. This is a significant savings when full manual segmentation can take weeks of effort. Additionally, subjectivity is addressed through the use of computationally identified boundaries, and splitting complex collections of objects by their calculated properties rather than on a case-by-case basis

SuRVoS: Super-Region Volume Segmentation workbench

Segmentation of biological volumes is a crucial step needed to fully analyse their scientific content. Not having access to convenient tools with which to segment or annotate the data means many biological volumes remain under-utilised. Automatic segmentation of biological volumes is still a very challenging research field, and current methods usually require a large amount of manually-produced training data to deliver a high-quality segmentation. However, the complex appearance of cellular features and the high variance from one sample to another, along with the time-consuming work of manually labelling complete volumes, makes the required training data very scarce or non-existent. Thus, fully automatic approaches are often infeasible for many practical applications. With the aim of unifying the segmentation power of automatic approaches with the user expertise and ability to manually annotate biological samples, we present a new workbench named SuRVoS (Super-Region Volume Segmentation). Within this software, a volume to be segmented is first partitioned into hierarchical segmentation layers (named Super-Regions) and is then interactively segmented with the user's knowledge input in the form of training annotations. SuRVoS first learns from and then extends user inputs to the rest of the volume, while using Super-Regions for quicker and easier segmentation than when using a voxel grid. These benefits are especially noticeable on noisy, low-dose, biological datasets