Contextualizing local-scale point sample data using global-scale spatial datasets: Lessons learnt from the analysis of large-scale land acquisitions

This paper examines how the geospatial accuracy of samples and sample size influence conclusions from geospatial analyses. It does so using the example of a study investigating the global phenomenon of large-scale land acquisitions and the socio-ecological characteristics of the areas they target. First, we analysed land deal datasets of varying geospatial accuracy and varying sizes and compared the results in terms of land cover, population density, and two indicators for agricultural potential: yield gap and availability of uncultivated land that is suitable for rainfed agriculture. We found that an increase in geospatial accuracy led to a substantial and greater change in conclusions about the land cover types targeted than an increase in sample size, suggesting that using a sample of higher geospatial accuracy does more to improve results than using a larger sample. The same finding emerged for population density, yield gap, and the availability of uncultivated land suitable for rainfed agriculture. Furthermore, the statistical median proved to be more consistent than the mean when comparing the descriptive statistics for datasets of different geospatial accuracy. Second, we analysed effects of geospatial accuracy on estimations regarding the potential for advancing agricultural development in target contexts. Our results show that the target contexts of the majority of land deals in our sample whose geolocation is known with a high level of accuracy contain smaller amounts of suitable, but uncultivated land than regional- and national-scale averages suggest. Consequently, the more target contexts vary within a country, the more detailed the spatial scale of analysis has to be in order to draw meaningful conclusions about the phenomena under investigation. We therefore advise against using national-scale statistics to approximate or characterize phenomena that have a local-scale impact, particularly if key indicators vary widely within a country.

WEAVE: Efficient Geographical Routing in Large-Scale Networks

We propose WEAVE, a geographical 2D/3D routing protocol that maintains information on a small number of waypoints and checkpoints for forwarding packets to any destination. Nodes obtain the routing information from partial traces gathered in incoming packets and use a system of checkpoints along with the segments of routes to weave end-to-end paths close to the shortest ones. WEAVE does not generate any control traffic, it is suitable for routing in both 2D and 3D networks, and does not require any strong assumption on the underlying network graph such as the Unit Disk or a Planar Graph. WEAVE compares favorably with existing protocols in both testbed experiments and simulations.

Large-scale land acquisition and its effects on the water balance in investor and host countries

This study examines the validity of the assumption that international large-scale land acquisition (LSLA) is motivated by the desire to secure control over water resources, which is commonly referred to as ‘water grabbing’. This assumption was repeatedly expressed in recent years, ascribing the said motivation to the Gulf States in particular. However, it must be considered of hypothetical nature, as the few global studies conducted so far focused primarily on the effects of LSLA on host countries or on trade in virtual water. In this study, we analyse the effects of 475 intended or concluded land deals recorded in the Land Matrix database on the water balance in both host and investor countries. We also examine how these effects relate to water stress and how they contribute to global trade in virtual water. The analysis shows that implementation of the LSLAs in our sample would result in global water savings based on virtual water trade. At the level of individual LSLA host countries, however, water use intensity would increase, particularly in 15 sub-Saharan states. From an investor country perspective, the analysis reveals that countries often suspected of using LSLA to relieve pressure on their domestic water resources—such as China, India, and all Gulf States except Saudi Arabia—invest in agricultural activities abroad that are less water-intensive compared to their average domestic crop production. Conversely, large investor countries such as the United States, Saudi Arabia, Singapore, and Japan are disproportionately externalizing crop water consumption through their international land investments. Statistical analyses also show that host countries with abundant water resources are not per se favoured targets of LSLA. Indeed, further analysis reveals that land investments originating in water-stressed countries have only a weak tendency to target areas with a smaller water risk.

Grabbing or investment? On judging large-scale land acquisitions

Although analyses of large-scale land acquisitions (LSLA) often contain an explicit or implicit normative judgment about such projects, they rarely deduce such judgment from a nuanced balancing of pros and cons. This paper uses assessments about a well-researched LSLA in Sierra Leone to show that a utilitarian approach tends to lead to the conclusion that positive effects prevail, whereas deontological approaches lead to an emphasis on negative aspects. LSLA are probably the most radical land-use change in the history of humankind. This process of radical transformation poses a challenge for balanced evaluations. Thus, we line out a framework that focuses on the options of local residents but sets boundaries of acceptability through the core contents of human rights. In addition, systemic implications of a project need to be regarded.

Large-scale dust jets in the coma of 67P/Churyumov-Gerasimenko as seen by the OSIRIS instrument onboard Rosetta

Context. During the most recent perihelion passage in 2009 of comet 67P/Churyumov-Gerasimenko (67P), ground-based observations showed an anisotropic dust coma where jet-like features were detected at similar to 1.3 AU from the Sun. The current perihelion passage is exceptional as the Rosetta spacecraft is monitoring the nucleus activity since March 2014, when a clear dust coma was already surrounding the nucleus at 4.3 AU from the Sun. Subsequently, the OSIRIS camera also witnessed an outburst in activity between April 27 and 30, and since mid-July, the dust coma at rh similar to 3.7-3.6 AU preperihelion is clearly non-isotropic, pointing to the existence of dust jet-like features. Aims. We aim to ascertain on the nucleus surface the origin of the dust jet-like features detected as early as in mid-July 2014. This will help to establish how the localized comet nucleus activity compares with that seen in previous apparitions and will also help following its evolution as the comet approaches its perihelion, at which phase most of the jets were detected from ground-based observations. Determining these areas also allows locating them in regions on the nucleus with spectroscopic or geomorphological distinct characteristics. Methods. Three series of dust images of comet 67P obtained with the Wide Angle Camera (WAC) of the OSIRIS instrument onboard the Rosetta spacecraft were processed with different enhancement techniques. This was made to clearly show the existence of jet-like features in the dust coma, whose appearance toward the observer changed as a result of the rotation of the comet nucleus and of the changing observing geometry from the spacecraft. The position angles of these features in the coma together with information on the observing geometry, nucleus shape, and rotation, allowed us to determine the most likely locations on the nucleus surface where the jets originate from. Results. Geometrical tracing of jet sources indicates that the activity of the nucleus of 67P gave rise during July and August 2014 to large-scale jet-like features from the Hapi, Hathor, Anuket, and Aten regions, confirming that active regions may be present on the nucleus localized at 60. northern latitude as deduced from previous comet apparitions. There are also hints that large-scale jets observed from the ground are possibly composed, at their place of origin on the nucleus surface, of numerous small-scale features.

Enriching plant diversity in grasslands by large-scale experimental sward disturbance and seed addition along gradients of land-use intensity

Aims The relationship between biodiversity and ecosystem functioning is among the most active areas of ecological research. Furthermore, enhancing the diversity of degraded ecosystems is a major goal in applied restoration ecology. In grasslands, many species may be locally absent due to dispersal or microsite limitation and may therefore profit from mechanical disturbance of the resident vegetation. We established a seed addition and disturbance experiment across several grassland sites of different land use to test whether plant diversity can be increased in these grasslands. Additionally, the experiment will allow us testing the consequences of increased plant diversity for ecosystem processes and for the diversity of other taxa in real-world ecosystems. Here we present details of the experimental design and report results from the first vegetation survey one year after disturbance and seed addition. Moreover, we tested whether the effects of seed addition and disturbance varied among grassland depending on their land use or pre-disturbance plant diversity. Methods A full-factorial experiment was installed in 73 grasslands in three regions across Germany. Grasslands were under regular agricultural use, but varied in the type and the intensity of management, thereby representing the range of management typical for large parts of Central Europe. The disturbance treatment consisted of disturbing the top 10 cm of the sward using a rotavator or rotary harrow. Seed addition consisted of sowing a high-diversity seed mixture of regional plant species. These species were all regionally present, but often locally absent, depending on the resident vegetation composition and richness of each grassland. Important findings One year after sward disturbance it had significantly increased cover of bare soil, seedling species richness and numbers of seedlings. Seed addition had increased plant species richness, but only in combination with sward disturbance. The increase in species richness, when both seed addition and disturbance was applied, was higher at high land-use intensity and low resident diversity. Thus, we show that at least the early recruitment of many species is possible also at high land-use intensity, indicating the potential to restore and enhance biodiversity of species-poor agricultural grasslands. Our newly established experiment provides a unique platform for broad-scale research on the land-use dependence of future trajectories of vegetation diversity and composition and their effects on ecosystem functioning.

Integrated Segmentation of Brain Tumor Images for Radiotherapy and Neurosurgery

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

The surface temperatures of Earth: steps towards integrated understanding of variability and change

Surface temperature is a key aspect of weather and climate, but the term may refer to different quantities that play interconnected roles and are observed by different means. In a community-based activity in June 2012, the EarthTemp Network brought together 55 researchers from five continents to improve the interaction between scientific communities who focus on surface temperature in particular domains, to exploit the strengths of different observing systems and to better meet the needs of different communities. The workshop identified key needs for progress towards meeting scientific and societal requirements for surface temperature understanding and information, which are presented in this community paper. A "whole-Earth" perspective is required with more integrated, collaborative approaches to observing and understanding Earth's various surface temperatures. It is necessary to build understanding of the relationships between different surface temperatures, where presently inadequate, and undertake large-scale systematic intercomparisons. Datasets need to be easier to obtain and exploit for a wide constituency of users, with the differences and complementarities communicated in readily understood terms, and realistic and consistent uncertainty information provided. Steps were also recommended to curate and make available data that are presently inaccessible, develop new observing systems and build capacities to accelerate progress in the accuracy and usability of surface temperature datasets.

Quantitative 3D strain analysis in analogue experiments: Integration of X-ray computed tomography and digital volume correlation techniques

The combination of scaled analogue experiments, material mechanics, X-ray computed tomography (XRCT) and Digital Volume Correlation techniques (DVC) is a powerful new tool not only to examine the 3 dimensional structure and kinematic evolution of complex deformation structures in scaled analogue experiments, but also to fully quantify their spatial strain distribution and complete strain history. Digital image correlation (DIC) is an important advance in quantitative physical modelling and helps to understand non-linear deformation processes. Optical non-intrusive (DIC) techniques enable the quantification of localised and distributed deformation in analogue experiments based either on images taken through transparent sidewalls (2D DIC) or on surface views (3D DIC). X-ray computed tomography (XRCT) analysis permits the non-destructive visualisation of the internal structure and kinematic evolution of scaled analogue experiments simulating tectonic evolution of complex geological structures. The combination of XRCT sectional image data of analogue experiments with 2D DIC only allows quantification of 2D displacement and strain components in section direction. This completely omits the potential of CT experiments for full 3D strain analysis of complex, non-cylindrical deformation structures. In this study, we apply digital volume correlation (DVC) techniques on XRCT scan data of “solid” analogue experiments to fully quantify the internal displacement and strain in 3 dimensions over time. Our first results indicate that the application of DVC techniques on XRCT volume data can successfully be used to quantify the 3D spatial and temporal strain patterns inside analogue experiments. We demonstrate the potential of combining DVC techniques and XRCT volume imaging for 3D strain analysis of a contractional experiment simulating the development of a non-cylindrical pop-up structure. Furthermore, we discuss various options for optimisation of granular materials, pattern generation, and data acquisition for increased resolution and accuracy of the strain results. Three-dimensional strain analysis of analogue models is of particular interest for geological and seismic interpretations of complex, non-cylindrical geological structures. The volume strain data enable the analysis of the large-scale and small-scale strain history of geological structures.

The structural substrate of brain function: analysis of brain structural networks based on diffusion-weighted imaging

The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.

Neutrino physics with multi-ton scale liquid xenon detectors

We study the sensitivity of large-scale xenon detectors to low-energy solar neutrinos, to coherent neutrino-nucleus scattering and to neutrinoless double beta decay. As a concrete example, we consider the xenon part of the proposed DARWIN (Dark Matter WIMP Search with Noble Liquids) experiment. We perform detailed Monte Carlo simulations of the expected backgrounds, considering realistic energy resolutions and thresholds in the detector. In a low-energy window of 2–30 keV, where the sensitivity to solar pp and 7Be-neutrinos is highest, an integrated pp-neutrino rate of 5900 events can be reached in a fiducial mass of 14 tons of natural xenon, after 5 years of data. The pp-neutrino flux could thus be measured with a statistical uncertainty around 1%, reaching the precision of solar model predictions. These low-energy solar neutrinos will be the limiting background to the dark matter search channel for WIMP-nucleon cross sections below ~2X 10-48 cm2 and WIMP masses around 50 GeV c 2, for an assumed 99.5% rejection of electronic recoils due to elastic neutrino-electron scatters. Nuclear recoils from coherent scattering of solar neutrinos will limit the sensitivity to WIMP masses below ~6 GeV c-2 to cross sections above ~4X10-45cm2. DARWIN could reach a competitive half-life sensitivity of 5.6X1026 y to the neutrinoless double beta decay of 136Xe after 5 years of data, using 6 tons of natural xenon in the central detector region.