Detecting spatial homogeneity in the world trade web with Detrended Fluctuation Analysis

In a spatially embedded network, that is a network where nodes can be uniquely determined in a system of coordinates, links' weights might be affected by metric distances coupling every pair of nodes (dyads). In order to assess to what extent metric distances affect relationships (link's weights) in a spatially embedded network, we propose a methodology based on DFA (Detrended Fluctuation Analysis). DFA is a well developed methodology to evaluate autocorrelations and estimate long-range behaviour in time series. We argue it can be further extended to spatially ordered series in order to assess autocorrelations in values. A scaling exponent of 0.5 (uncorrelated data) would thereby signal a perfect homogeneous space embedding the network. We apply the proposed methodology to the World Trade Web (WTW) during the years 1949-2000 and we find, in some contrast with predictions of gravity models, a declining influence of distances on trading relationships.Comment: 15 pages, 7 figure

Assessing plant diversity and composition in grasslands across spatial scales: the standardised EDGG sampling methodology

This paper presents the details of the EDGG sampling methodology and its underlying rationales. The methodology has been applied during EDGG Research Expeditions and EDGG Field Workshops since 2009, and has been subsequently adopted by various other researchers. The core of the sampling are the EDGG Biodiversity Plots, which are 100‐m2 squares comprising, in two opposite corners, nested‐plot series of 0.0001, 0.001, 0.01, 0.1, 1 and 10 m2 square plots, in which all terricolous vascular plants, bryophytes and lichens are recorded using the shoot presence method. In the 10‐m2 plots, species cover is also estimated as a percentage and various environmental and structural parameters are recorded. Usually the EDGG Biodiversity Plots are complemented by the sampling of additional 10 m2 normal plots with the same parameters as the 10‐m2 corners of the first, allowing coverage of a greater environmental diversity and the achievement of higher statistical power in the subsequent analyses for this important grain size. The EDGG sampling methodology has been refined over the years, while its core has turned out to generate high‐quality, standardised data in an effective manner, which facilitates a multitude of analyses. In this paper we provide the current versions of our guidelines, field forms and data entry spreadsheets, as open‐access Online Resources to facilitate the easy implementation of this methodology by other researchers. We also discuss potential future additions and modifications to the approach, among which the most promising are the use of stratified‐random methods to a priori localise the plots and ideas to sample invertebrate taxa on the same plots and grain sizes, such as grasshoppers (Orthoptera) and vegetation‐dwelling spiders (Araneae). As with any other method, the EDGG sampling methodology is not ideal for every single purpose, but with its continuous improvements and its flexibility, it is a good multi‐ purpose approach. A particularly advantageous element, lacking in most other sampling schemes, including classical phytosociogical sampling, is the multi‐scale and multi‐taxon approach, which provides data that allow for deeper understanding of the generalities and idiosyncrasies of biodiversity patterns and their underlying drivers across scales and taxa

Probabilistic and preferential sampling approaches offer integrated perspectives of Italian forest diversity

Aim: Assessing the performances of different sampling approaches for documenting community diversity may help to identify optimal sampling efforts and strategies, and to enhance conservation and monitoring planning. Here, we used two data sets based on probabilistic and preferential sampling schemes of Italian forest vegetation to analyze the multifaceted performances of the two approaches across three major forest types at a large scale. Location: Italy. Methods: We pooled 804 probabilistic and 16,259 preferential forest plots as samples of vascular plant diversity across the country. We balanced the two data sets in terms of sizes, plot size, geographical position, and vegetation types. For each of the two data sets, 1000 subsets of 201 random plots were compared by calculating the shared and exclusive indicator species, their overlap in the multivariate space, and the areas encompassed by spatially-constrained rarefaction curves. We then calculated an index of performance using the ratio between the additional and total information collected by each sampling approach. The performances were tested and evaluated across the three major forest types. Results: The probabilistic approach performed better in estimating species richness and diversity of species assemblages, but did not detect other components of the regional diversity, such as azonal forests. The preferential approach outperformed the probabilistic approach in detecting forest-specialist species and plant diversity hotspots. Conclusions: Using a novel workflow based on vegetation-plot exclusivities and commonalities, our study suggests probabilistic and preferential sampling approaches are to be used in combination for better conservation and monitor planning purposes to detect multiple aspects of plant community diversity. Our findings can assist the implementation of national conservation planning and large-scale monitoring of biodiversit

GrassPlot : the database of multi-scale plant diversity in Palaearctic grasslands

Understanding patterns and drivers of phytodiversity as well as ecological scaling laws and assembly rules constitute core interests both of vegetation ecologists and macroecologists. To enhance our understanding of these issues, we compiled the new “Database of Scale-Dependent Phytodiversity Patterns in Palaearctic Grasslands” (GrassPlot; GIVD ID EU-00-003) within the framework of the Eurasian Dry Grassland Group (EDGG). GrassPlot contains high-quality plot observations (relevés) of eight standard grain sizes (0.0001; 0.001 … 1000 m²) as well as nested-plot series with at least four different grain sizes. The scope of GrassPlot are the grasslands as well as other herb- or cryptogam-dominated terrestrial and semi-terrestrial vegetation types from the whole Palaearctic biogeographic realm (Europe, North Africa, West, Central and North Asia)

Species-area relationships in continuous vegetation : evidence from Palaearctic grasslands

Aim Species–area relationships (SARs) are fundamental scaling laws in ecology although their shape is still disputed. At larger areas, power laws best represent SARs. Yet, it remains unclear whether SARs follow other shapes at finer spatial grains in continuous vegetation. We asked which function describes SARs best at small grains and explored how sampling methodology or the environment influence SAR shape. Location Palaearctic grasslands and other non‐forested habitats. Taxa Vascular plants, bryophytes and lichens. Methods We used the GrassPlot database, containing standardized vegetation‐plot data from vascular plants, bryophytes and lichens spanning a wide range of grassland types throughout the Palaearctic and including 2,057 nested‐plot series with at least seven grain sizes ranging from 1 cm2 to 1,024 m2. Using nonlinear regression, we assessed the appropriateness of different SAR functions (power, power quadratic, power breakpoint, logarithmic, Michaelis–Menten). Based on AICc, we tested whether the ranking of functions differed among taxonomic groups, methodological settings, biomes or vegetation types. Results The power function was the most suitable function across the studied taxonomic groups. The superiority of this function increased from lichens to bryophytes to vascular plants to all three taxonomic groups together. The sampling method was highly influential as rooted presence sampling decreased the performance of the power function. By contrast, biome and vegetation type had practically no influence on the superiority of the power law. Main conclusions We conclude that SARs of sessile organisms at smaller spatial grains are best approximated by a power function. This coincides with several other comprehensive studies of SARs at different grain sizes and for different taxa, thus supporting the general appropriateness of the power function for modelling species diversity over a wide range of grain sizes. The poor performance of the Michaelis–Menten function demonstrates that richness within plant communities generally does not approach any saturation, thus calling into question the concept of minimal area.publishedVersio

The Signal Processing Firmware for the Low Frequency Aperture Array

The signal processing firmware that has been developed for the Low Frequency Aperture Array component of the Square Kilometre Array is described. The firmware is implemented on a dual FPGA board, that is capable of processing the streams from 16 dual polarization antennas. Data processing includes channelization of the sampled data for each antenna, correction for instrumental response and for geometric delays and formation of one or more beams by combining the aligned streams. The channelizer uses an oversampling polyphase filterbank architecture, allowing a frequency continuous processing of the input signal without discontinuities between spectral channels. Each board processes the streams from 16 antennas, as part of larger beamforming system, linked by standard Ethernet interconnections. There are envisaged to be 8192 of these signal processing platforms in the first phase of the Square Kilometre array so particular attention has been devoted to ensure the design is low cost and low power

The Digital Signal Processing Platform for the Low Frequency Aperture Array: Preliminary Results on the Data Acquisition Unit

A signal processing hardware platform has been developed for the Low Frequency Aperture Array component of the Square Kilometre Array (SKA). The processing board, called an Analog Digital Unit (ADU), is able to acquire and digitize broadband (up to 500MHz bandwidth) radio-frequency streams from 16 dual polarized antennas, channel the data streams and then combine them flexibly as part of a larger beamforming system. It is envisaged that there will be more than 8000 of these signal processing platforms in the first phase of the SKA, so particular attention has been devoted to ensure the design is low-cost and low-power. This paper describes the main features of the data acquisition unit of such a platform and presents preliminary results characterizing its performance

Development of a New Digital Signal Processing Platform for the Square Kilometre Array

A novel digital hardware platform has been designed for the Low Frequency Aperture Array (LFAA) component of the Square Kilometre Array (SKA). This board, called Analog Digital Unit (ADU), is a 6U board containing sixteen dual-inputs Analog to Digital Converters (ADC) and two Field Programmable Gate Array (FPGA) devices, capable of digitizing and processing 32 RF input signals. We present the main features of the board and the signal processing firmware that has been developed for LFAA. Although the ADU has been conceived mainly for the low frequency band (50-350 MHz), its use has been proved effective also for higher frequencies (375-650 MHz). In this paper we describe also the application of ADU as the digital acquisition and processing system for PHAROS2, a cryogenically cooled 4-8 GHz Phased Array Feed (PAF) demonstrator. The final part is focused on the future developments of the board

GrassPlot - a database of multi-scale plant diversity in Palaearctic grasslands

GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board

Complex Systems Approaches in Investigating Series of Data: Multidisciplinary Applications in Economics and Physiology

Scaling properties are among the most important quantifiers of complexity in many real systems, including chaotic dynamical systems, biological systems and financial markets. The presence of scaling usually points out a non-trivial self-organizing behavior and temporal correlations. This thesis reports on a nontrivial use of the Detrended Fluctuation Analysis and its generalizations, like the Generalized Hurst Exponent and its weighted version. We discussed about their practical applicability to datasets originating from completely different fields of research, from economics to physiology. The innovative features of this thesis are twofold: on one side it has been possible to verify that the DFA turned out to be a successful technique even when the dataset is not equally temporally spaced; on the other side, it has been possible to obtain - after the combination of the DFA with a complementary tool of investigation - a discriminating procedure and a classification instrument, well suited for diagnostic and clinical purposes. Moreover the same procedures, once extended to GHE analysis, allowed to characterize the multifractal features and cross-correlation properties in commodities markets in order to identify different scales and temporal horizons in trading procedures. This is of crucial importance for the improvement of reliability of risk management and option pricing models