Morphometric analysis of aeolian bedforms in the Namib Sand Sea using ASTER data

The ASTER Global Digital Elevation Model (GDEM) has made elevation data at 30 m spatial resolution freely available, enabling reinvestigation of morphometric relationships derived from limited field data using much larger sample sizes. These data are used to analyse a range of morphometric relationships derived for dunes (between dune height, spacing, and equivalent sand thickness) in the Namib Sand Sea, which was chosen because there are a number of extant studies that could be used for comparison with the results. The relative accuracy of GDEM for capturing dune height and shape was tested against multiple individual ASTER DEM scenes and against field surveys, highlighting the smoothing of the dune crest and resultant underestimation of dune height, and the omission of the smallest dunes, because of the 30 m sampling of ASTER DEM products. It is demonstrated that morphometric relationships derived from GDEM data are broadly comparable with relationships derived by previous methods, across a range of different dune types. The data confirm patterns of dune height, spacing and equivalent sand thickness mapped previously in the Namib Sand Sea, but add new detail to these patterns.

The correlation structure of spatial autoregressions

This paper investigates how the correlations implied by a first-order simultaneous autoregressive (SAR(1)) process are affected by the weights matrix and the autocorrelation parameter. A graph theoretic representation of the covariances in terms of walks connecting the spatial units helps to clarify a number of correlation properties of the processes. In particular, we study some implications of row-standardizing the weights matrix, the dependence of the correlations on graph distance, and the behavior of the correlations at the extremes of the parameter space. Throughout the analysis differences between directed and undirected networks are emphasized. The graph theoretic representation also clarifies why it is difficult to relate properties ofW to correlation properties of SAR(1) models defined on irregular lattices.

Integrated cytokine and metabolic analysis of pathological responses to parasite exposure in rodents

Parasitic infections cause a myriad of responses in their mammalian hosts, on immune as well as on metabolic level. A multiplex panel of cytokines and metabolites derived from four parasite-rodent models, namely, Plasmodium berghei-mouse, Trypanosoma brucei brucei-mouse, Schistosoma mansoni-mouse, and Fasciola hepatica-rat were statistically coanalyzed. 1H NMR spectroscopy and multivariate statistical analysis were used to characterize the urine and plasma metabolite profiles in infected and noninfected animals. Each parasite generated a unique metabolic signature in the host. Plasma cytokine concentrations were obtained using the ‘Meso Scale Discovery’ multi cytokine assay platform. Multivariate data integration methods were subsequently used to elucidate the component of the metabolic signature which is associated with inflammation and to determine specific metabolic correlates with parasite-induced changes in plasma cytokine levels. For example, the relative levels of acetyl glycoproteins extracted from the plasma metabolite profile in the P. berghei-infected mice were statistically correlated with IFN-γ, whereas the same cytokine was anticorrelated with glucose levels. Both the metabolic and the cytokine data showed a similar spatial distribution in principal component analysis scores plots constructed for the combined murine data, with samples from all infected animals clustering according to the parasite species and whereby the protozoan infections (P. berghei and T. b. brucei) grouped separately from the helminth infection (S. mansoni). For S. mansoni, the main infection-responsive cytokines were IL-4 and IL-5, which covaried with lactate, choline, and D-3-hydroxybutyrate. This study demonstrates that the inherently differential immune response to single and multicellular parasites not only manifests in the cytokine expression, but also consequently imprints on the metabolic signature, and calls for in-depth analysis to further explore direct links between immune features and biochemical pathways.

Global trends and factors associated with the illegal killing of elephants: a hierarchical bayesian analysis of carcass encounter data

Elephant poaching and the ivory trade remain high on the agenda at meetings of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Well-informed debates require robust estimates of trends, the spatial distribution of poaching, and drivers of poaching. We present an analysis of trends and drivers of an indicator of elephant poaching of all elephant species. The site-based monitoring system known as Monitoring the Illegal Killing of Elephants (MIKE), set up by the 10th Conference of the Parties of CITES in 1997, produces carcass encounter data reported mainly by anti-poaching patrols. Data analyzed were site by year totals of 6,337 carcasses from 66 sites in Africa and Asia from 2002–2009. Analysis of these observational data is a serious challenge to traditional statistical methods because of the opportunistic and non-random nature of patrols, and the heterogeneity across sites. Adopting a Bayesian hierarchical modeling approach, we used the proportion of carcasses that were illegally killed (PIKE) as a poaching index, to estimate the trend and the effects of site- and country-level factors associated with poaching. Important drivers of illegal killing that emerged at country level were poor governance and low levels of human development, and at site level, forest cover and area of the site in regions where human population density is low. After a drop from 2002, PIKE remained fairly constant from 2003 until 2006, after which it increased until 2008. The results for 2009 indicate a decline. Sites with PIKE ranging from the lowest to the highest were identified. The results of the analysis provide a sound information base for scientific evidence-based decision making in the CITES process.

Spatial patterns of office employment in the New York region

This study analyzes the regional spatial dynamics of the New York region for a period of roughly twenty years and places the effects of the 9/11 terrorist attacks in the context of longer-term regional dynamics. The analysis reveals that office-using industries are still heavily concentrated in Manhattan despite ongoing decentralization in many of these industries over the last twenty years. Financial services tend to be highly concentrated in Manhattan whereas administrative and support services are the least concentrated of the six major office-using industry groups. Although office employment has been by and large stagnant in Manhattan for at least two decades, growth of output per worker has outpaced the CMSA as well as the national average. This productivity differential is mainly attributable to competitive advantages of office-using industries in Manhattan and not to differences in industry composition. Finally, the zip-code level analysis of the Manhattan core area yielded further evidence of the existence of significant spillover effects at the small-scale level.

Plane wave discontinuous Galerkin methods for the 2D Helmholtz equation: analysis of the $p$-version

Plane wave discontinuous Galerkin (PWDG) methods are a class of Trefftz-type methods for the spatial discretization of boundary value problems for the Helmholtz operator $-\Delta-\omega^2$, $\omega>0$. They include the so-called ultra weak variational formulation from [O. Cessenat and B. Després, SIAM J. Numer. Anal., 35 (1998), pp. 255–299]. This paper is concerned with the a priori convergence analysis of PWDG in the case of $p$-refinement, that is, the study of the asymptotic behavior of relevant error norms as the number of plane wave directions in the local trial spaces is increased. For convex domains in two space dimensions, we derive convergence rates, employing mesh skeleton-based norms, duality techniques from [P. Monk and D. Wang, Comput. Methods Appl. Mech. Engrg., 175 (1999), pp. 121–136], and plane wave approximation theory.

Blueberry supplementation induces spatial memory improvements and region-specific regulation of hippocampal BDNF mRNA expression in young rats

Rationale: Flavonoid-rich foods have been shown to be able to reverse age-related cognitive deficits in memory and learning in both animals and humans. However, to date, there have been only a limited number of studies investigating the effects of flavonoid-rich foods on cognition in young/healthy animals. Objectives: The aim of this study was to investigate the effects of a blueberry-rich diet in young animals using a spatial working memory paradigm, the delayed non-match task, using an eight-arm radial maze. Furthermore, the mechanisms underlying such behavioural effects were investigated. Results: We show that a 7-week supplementation with a blueberry diet (2 % w/w) improves the spatial memory performance of young rats (2 months old). Blueberry-fed animals also exhibited a faster rate of learning compared to those on the control diet. These behavioural outputs were accompanied by the activation of extracellular signal-related kinase (ERK1/2), increases in total cAMP-response element binding protein (CREB) and elevated levels of pro- and mature brain-derived neurotrophic factor (BDNF) in the hippocampus. Changes in hippocampal CREB correlated well with memory performance. Further regional analysis of BDNF gene expression in the hippocampus revealed a specific increase in BDNF mRNA in the dentate gyrus and CA1 areas of hippocampi of blueberry-fed animals. Conclusions: The present study suggests that consumption of flavonoid-rich blueberries has a positive impact on spatial learning performance in young healthy animals, and these improvements are linked to the activation of ERK–CREB– BDNF pathway in the hippocampus.

The distribution of London residential property prices and the role of spatial lock-in

Much of mainstream economic analysis assumes that markets adjust smoothly, through prices, to changes in economic conditions. However, this is not necessarily the case for local housing markets, whose spatial structures may exhibit persistence, so that conditions may not be those most suited to the requirements of modern-day living. Persistence can arise from the existence of transaction costs. The paper tests the proposition that housing markets in Inner London exhibit a degree of path dependence, through the construction of a three-equation model, and examines the impact of variables constructed for the 19th and early 20th centuries on modern house prices. These include 19th-century social structures, slum clearance programmes and the 1908 underground network. Each is found to be significant. The tests require the construction of novel historical datasets, which are also described in the paper.

Multi-year droughts in Europe: analysis of development and causes

Whilst hydrological systems can show resilience to short-term streamflow deficiencies during within-year droughts, prolonged deficits during multi-year droughts are a significant threat to water resources security in Europe. This study uses a threshold-based objective classification of regional hydrological drought to qualitatively examine the characteristics, spatio-temporal evolution and synoptic climatic drivers of multi-year drought events in 1962–64, 1975–76 and 1995–97, on a European scale but with particular focus on the UK. Whilst all three events are multi-year, pan-European phenomena, their development and causes can be contrasted. The critical factor in explaining the unprecedented severity of the 1975–76 event is the consecutive occurrence of winter and summer drought. In contrast, 1962–64 was a succession of dry winters, mitigated by quiescent summers, whilst 1995–97 lacked spatial coherence and was interrupted by wet interludes. Synoptic climatic conditions vary within and between multi-year droughts, suggesting that regional factors modulate the climate signal in streamflow drought occurrence. Despite being underpinned by qualitatively similar climatic conditions and commonalities in evolution and characteristics, each of the three droughts has a unique spatio-temporal signature. An improved understanding of the spatio-temporal evolution and characteristics of multi-year droughts has much to contribute to monitoring and forecasting capability, and to improved mitigation strategies.

The 20 February 2010 Madeira flash-floods: synoptic analysis and extreme rainfall assessment

This study aims to characterise the rainfall exceptionality and the meteorological context of the 20 February 2010 flash-floods in Madeira (Portugal). Daily and hourly precipitation records from the available rain-gauge station networks are evaluated in order to reconstitute the temporal evolution of the rainstorm, as its geographic incidence, contributing to understand the flash-flood dynamics and the type and spatial distribution of the associated impacts. The exceptionality of the rainstorm is further confirmed by the return period associated with the daily precipitation registered at the two long-term record stations, with 146.9 mm observed in the city of Funchal and 333.8 mm on the mountain top, corresponding to an estimated return period of approximately 290 yr and 90 yr, respectively. Furthermore, the synoptic associated situation responsible for the flash-floods is analysed using different sources of information, e.g., weather charts, reanalysis data, Meteosat images and radiosounding data, with the focus on two main issues: (1) the dynamical conditions that promoted such anomalous humidity availability over the Madeira region on 20 February 2010 and (2) the uplift mechanism that induced deep convection activity.

Optical characterization of the growth and spatial structure of a substorm onset arc

We present a detailed case study of the characteristics of auroral forms that constitute the first ionospheric signatures of substorm expansion phase onset. Analysis of the optical frequency and along-arc (azimuthal) wave number spectra provides the strongest constraint to date on the potential mechanisms and instabilities in the near-Earth magnetosphere that accompany auroral onset and which precede poleward arc expansion and auroral breakup. We evaluate the frequency and growth rates of the auroral forms as a function of azimuthal wave number to determine whether these wave characteristics are consistent with current models of the substorm onset mechanism. We find that the frequency, spatial scales, and growth rates of the auroral forms are most consistent with the cross-field current instability or a ballooning instability, most likely triggered close to the inner edge of the ion plasma sheet. This result is supportive of a near-Earth plasma sheet initiation of the substorm expansion phase. We also present evidence that the frequency and phase characteristics of the auroral undulations may be generated via resonant processes operating along the geomagnetic field. Our observations provide the most powerful constraint to date on the ionospheric manifestation of the physical processes operating during the first few minutes around auroral substorm onset.

Analysis of frequency and intensity of European winter storm events from a multi-model perspective, at synoptic and regional scales

This study focuses on the analysis of winter (October-November-December-January-February-March; ONDJFM) storm events and their changes due to increased anthropogenic greenhouse gas concentrations over Europe. In order to assess uncertainties that are due to model formulation, 4 regional climate models (RCMs) with 5 high resolution experiments, and 4 global general circulation models (GCMs) are considered. Firstly, cyclone systems as synoptic scale processes in winter are investigated, as they are a principal cause of the occurrence of extreme, damage-causing wind speeds. This is achieved by use of an objective cyclone identification and tracking algorithm applied to GCMs. Secondly, changes in extreme near-surface wind speeds are analysed. Based on percentile thresholds, the studied extreme wind speed indices allow a consistent analysis over Europe that takes systematic deviations of the models into account. Relative changes in both intensity and frequency of extreme winds and their related uncertainties are assessed and related to changing patterns of extreme cyclones. A common feature of all investigated GCMs is a reduced track density over central Europe under climate change conditions, if all systems are considered. If only extreme (i.e. the strongest 5%) cyclones are taken into account, an increasing cyclone activity for western parts of central Europe is apparent; however, the climate change signal reveals a reduced spatial coherency when compared to all systems, which exposes partially contrary results. With respect to extreme wind speeds, significant positive changes in intensity and frequency are obtained over at least 3 and 20% of the European domain under study (35–72°N and 15°W–43°E), respectively. Location and extension of the affected areas (up to 60 and 50% of the domain for intensity and frequency, respectively), as well as levels of changes (up to +15 and +200% for intensity and frequency, respectively) are shown to be highly dependent on the driving GCM, whereas differences between RCMs when driven by the same GCM are relatively small.

Multiscale geostatistical analysis of AVHRR, SPOT-VGT, and MODIS global NDVI products

Global NDVI data are routinely derived from the AVHRR, SPOT-VGT, and MODIS/Terra earth observation records for a range of applications from terrestrial vegetation monitoring to climate change modeling. This has led to a substantial interest in the harmonization of multisensor records. Most evaluations of the internal consistency and continuity of global multisensor NDVI products have focused on time-series harmonization in the spectral domain, often neglecting the spatial domain. We fill this void by applying variogram modeling (a) to evaluate the differences in spatial variability between 8-km AVHRR, 1-km SPOT-VGT, and 1-km, 500-m, and 250-m MODIS NDVI products over eight EOS (Earth Observing System) validation sites, and (b) to characterize the decay of spatial variability as a function of pixel size (i.e. data regularization) for spatially aggregated Landsat ETM+ NDVI products and a real multisensor dataset. First, we demonstrate that the conjunctive analysis of two variogram properties – the sill and the mean length scale metric – provides a robust assessment of the differences in spatial variability between multiscale NDVI products that are due to spatial (nominal pixel size, point spread function, and view angle) and non-spatial (sensor calibration, cloud clearing, atmospheric corrections, and length of multi-day compositing period) factors. Next, we show that as the nominal pixel size increases, the decay of spatial information content follows a logarithmic relationship with stronger fit value for the spatially aggregated NDVI products (R2 = 0.9321) than for the native-resolution AVHRR, SPOT-VGT, and MODIS NDVI products (R2 = 0.5064). This relationship serves as a reference for evaluation of the differences in spatial variability and length scales in multiscale datasets at native or aggregated spatial resolutions. The outcomes of this study suggest that multisensor NDVI records cannot be integrated into a long-term data record without proper consideration of all factors affecting their spatial consistency. Hence, we propose an approach for selecting the spatial resolution, at which differences in spatial variability between NDVI products from multiple sensors are minimized. This approach provides practical guidance for the harmonization of long-term multisensor datasets.

Mobile-to-mobile MIMO transmit-receive diversity systems: analysis and performance in three-dimensional double-correlated channels

Mobile-to-mobile (M-to-M) communications are expected to play a crucial role in future wireless systems and networks. In this paper, we consider M-to-M multiple-input multiple-output (MIMO) maximal ratio combining system and assess its performance in spatially correlated channels. The analysis assumes double-correlated Rayleigh-and-Lognormal fading channels and is performed in terms of average symbol error probability, outage probability, and ergodic capacity. To obtain the receive and transmit spatial correlation functions needed for the performance analysis, we used a three-dimensional (3D) M-to-M MIMO channel model, which takes into account the effects of fast fading and shadowing. The expressions for the considered metrics are derived as a function of the average signal-to-noise ratio per receive antenna in closed-form and are further approximated using the recursive adaptive Simpson quadrature method. Numerical results are provided to show the effects of system parameters, such as distance between antenna elements, maximum elevation angle of scatterers, orientation angle of antenna array in the x–y plane, angle between the x–y plane and the antenna array orientation, and degree of scattering in the x–y plane, on the system performance. Copyright © 2011 John Wiley & Sons, Ltd.