First Telefónica’s Exchanges in Galicia

[Resumen] Telefónica construyó tres centrales en Galicia entre 1928 y 1930 para alojar los equiposde la nueva red automática. Fueron diseñadas por José María de la Vega Samper,que tuvo una gran influencia en el desarrollo de este tipo de arquitectura en España.Las centrales telefónicas son edificios industriales que esconden su naturaleza. Este artículo explica como siguieron el conjunto de principios de diseño que eran habituales en la arquitectura telefónica de Estados Unidos pero poco comunes en Europa.[Abstract] Telefónica built three telephone exchanges in Galicia between 1928 and 1930 tohouse the equipment of the new automatic network. Th ey were designed by JoséMaría de la Vega Samper that has been very infl uential in the development of thiskind of architecture in Spain. Central offi ces are industrial buildings that hide theirnature. Th is paper explains how they followed the set of design principles that werecommon in the American telephone architecture but unusual in Europe

A stochastic generative model of the World Trade Network.

The World Trade Network (WTN) is a network of exchange flows among countries whose topological and statistical properties are a valuable source of information. Degree and strength (weighted degree) are key magnitudes to understand its structure and generative mechanisms. In this work, we describe a stochastic model that yields synthetic networks that closely mimic the properties of annual empirical data. The model combines two popular mechanisms of network generation: preferential attachment and multiplicative process. Agreement between empirical and synthetic networks is checked using the available series from 1962 to 2017.post-print2516 K

Modelo discreto estocástico de dinámica mutualista

Las redes mutualistas son una clase de ecosistemas de gran interés en las que todas las interacciones entre especies son beneficiosas. Pueden modelarse como redes bipartitas con un núcleo de especies muy conectadas, una propiedad llamada anidamiento. Son muy resistentes y estables. La descripción matemática de las redes mutualistas está cimentada en modelos clásicos de población como los de Verhulst y Lotka-Volterra. En este trabajo proponemos una modificación de la formulación tradicional del mutualismo de May, incluyendo un factor de limitación del crecimiento que se basa en la conocida idea de la ecuación logística. Hemos construido una herramienta de simulación (SIGMUND) que permite experimentar con el modelo de forma simple y sencilla. Los resultados pueden ayudar a avanzar la investigación sobre el mutualismo, un campo activo de la ecología y la ciencia de redes

Cambios de la mineralogía de arcillas en el tránsito Paleoceno/Eoceno del dominio Maláguide (Zonas Internas Béticas, S.E. España)

El tránsito Paleoceno/Eoceno del Dominio Maláguide (manto superior y no metamorfizado de la Zona Interna Bética, sectores occidentales de la Cadena Alpina), está caracterizado por una discontinuidad asociada a una laguna estratigráfica, que afecta al Ilerdiense. Durante el paso del Paleoceno al Eoceno se han detectado cambios en el tipo de depósitos condicionados por la naturaleza de las áreas fuentes. Los medios sedimentarios marinos evolucionan de una plataforma mixta a otra carbonatada y los medios continentales cambian de condiciones fluviales a lacustres. El registro mineralógico encontrado en los sedimentos marinos ha permitido deducir variaciones relativas del nivel del mar, que se relacionarían con procesos tectónicos compresivos regionales. También se ha deducido un cambio climático desde un clima estacionalmente seco a otro tropical húmedo. Este cambio climático favoreció, en el medio marino, el cambio de las condiciones de productividad que pasaron de eutróficas, durante el Paleoceno, a oligotróficas durante el Eoceno.The Paleocene/Eocene transition in the Malaguide Domain, upper and unmetamorphosed nappe of the Internal Betic Zone (Western Alpine Belt), is characterized by a stratigraphic unconformity with a stratigraphic gap affecting the Ilerdian. Some depositional changes, conditioned by the nature of the source areas, were detected during the Paleocene/Eocene transition. The sedimentary marine environment evolved from a mixed platform to a carbonated platform, whereas in the continental realm a change from fluvial to lacustrine conditions took place. The mineralogical record found in marine sediments allowed the observation of a variation in the relative sea level curve due to regional compressive tectonic processes and a transition from a seasonally dry climate to a humid tropical climate. This transition favoured, in the marine environment, the change from eutrophic conditions during the Paleocene to oligotrophic conditions during the Eocene

Rethinking the logistic approach for population dynamics of mutualistic interactions

arXiv:1305.5411© 2014 Elsevier Ltd. Mutualistic communities have an internal structure that makes them resilient to external perturbations. Late research has focused on their stability and the topology of the relations between the different organisms to explain the reasons of the system robustness. Much less attention has been invested in analyzing the systems dynamics. The main population models in use are modifications of the r-. K formulation of logistic equation with additional terms to account for the benefits produced by the interspecific interactions. These models have shortcomings as the so-called r-. K formulation diverges under some conditions. In this work, we introduce a model for population dynamics under mutualism that preserves the original logistic formulation. It is mathematically simpler than the widely used type II models, although it shows similar complexity in terms of fixed points and stability of the dynamics. We perform an analytical stability analysis and numerical simulations to study the model behavior in general interaction scenarios including tests of the resilience of its dynamics under external perturbations. Despite its simplicity, our results indicate that the model dynamics shows an important richness that can be used to gain further insights in the dynamics of mutualistic communities.We have received partial financial support from the Spanish Ministry of Economy (MINECO) under projects MTM2012-39101, MODASS (FIS2011-24785), LIMITES (CGL2009-07229), and AdAptA(CGL2012-33528); from the project PGUI of Comunidad de MadridMODELICO-CM/S2009ESP-1691 and from the EU Commission through projects EUNOIA and LASAGNE. J.J.R. acknowledges funding from the Ramón y Cajal program of MINECO.N

Fine scale prediction of ecological community composition using a two-step sequential Machine Learning ensemble

Prediction is one of the last frontiers in ecology. Indeed, predicting fine-scale species composition in natural systems is a complex challenge as multiple abiotic and biotic processes operate simultaneously to determine local species abundances. On the one hand, species intrinsic performance and their tolerance limits to different abiotic pressures modulate species abundances. On the other hand there is growing recognition that species interactions play an equally important role in limiting or promoting such abundances within ecological communities. Here, we present a joint effort between ecologists and data scientists to use data-driven models to predict species abundances using reasonably easy to obtain data. We propose a sequential data-driven modeling approach that in a first step predicts the potential species abundances based on abiotic variables, and in a second step uses these predictions to model the realized abundances once accounting for species competition. Using a curated data set over five years we predict fine-scale species abundances in a highly diverse annual plant community. Our models show a remarkable spatial predictive accuracy using only easy-to-measure variables in the field, yet such predictive power is lost when temporal dynamics are taken into account. This result suggests that predicting future abundances requires longer time series analysis to capture enough variability. In addition, we show that these data-driven models can also suggest how to improve mechanistic models by adding missing variables that affect species performance such as particular soil conditions (e.g. carbonate availability in our case). Robust models for predicting fine-scale species composition informed by the mechanistic understanding of the underlying abiotic and biotic processes can be a pivotal tool for conservation, especially given the human-induced rapid environmental changes we are experiencing. This objective can be achieved by promoting the knowledge gained with classic modelling approaches in ecology and recently developed data-driven models. Author summary Prediction is challenging but recently developed Machine Learning techniques allow to dramatically improve prediction accuracy in several domains. However, these tools are often of little application in ecology due to the hardship of gathering information on the needed explanatory variables, which often comprise not only physical variables such as temperature or soil nutrients, but also information about the complex network of species interactions that modulate species abundances. Here we present a two-step sequential modelling framework that overcomes these constraints. We first infer potential species abundances by training models just with easily obtained abiotic variables and then use this outcome to fine-tune the prediction of the realized species abundances when taking into account the rest of the predicted species in the community. Overall, our results show a promising way forward for fine scale prediction in ecology.O.G. acknowledges support provided by the Ministerio de Ciencia, Innovacion y Universidades (RYC-2017-23666). O.G. and I.B. acknowledge financial support provided by the Secretaria de Estado de Investigacion, Desarrollo e Innovacion (CGL2017-92436-EXP, SIMPLEX and RTI2018-098888-A-I00, MeDiNaS). J.G. acknowledges financial support provided by the Ministerio de Ciencia, Innovacion y Universidades (PGC2018-093854-B-I00). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Two new types of visualization for mutualistic communities based in k-core decomposition

The bipartite graph is the most popular visualization of mutualistic networks. This plot underlines the existence of two guilds of nodes. Links between them are di?cult to follow even with a reduced number of elements, and it is almost impossible to discover organizational patterns. As a result, it is uncommon ?nding graphs of big bipartite networks in the literature. These shortcomings are even worse for networks with real time, strongly non linear interactions, such as mutualistic newtorks. Their internal structure is very important to understand their behaviour and resilience. For instance, it is quite important to know how central is a node and how its removal may trigger a cascade extinction [1]. We have developped two new kinds of visualization, polar and ziggurat plots, based on k-core decomposition. The idea was succesfully applied to very large networks [3] to reduce the ammount of displayed information. Our solution does not reduce information, as mutualistic networks have less than 1000 nodes. Instead, the decomposition discovers an internal organization that has its roots in topological properties

A Simple and Bounded Model of Population Dynamics for Mutualistic Networks

Dynamic population models are based on the Verhulst?s equation (logisitic equation), where the classic Malthusian growth rate is damped by intraspecific competition terms. Mainstream population models for mutualism are modifications of the logistic equation with additional terms to account for the benefits produced by the interspecies interactions. These models have shortcomings as the population divergence under some conditions (May?s equations) or a mathematical complexity that difficults their analytical treatment (Wright?s type II models). In this work, we introduce a model for the population dynamics in mutualism inspired by the logistic equation but cured of divergences. The model is also mathematically more simple than the type II. We use numerical simulations to study the model stability in more general interaction scenarios. Despite its simplicity, our results suggest that the model dynamics are rich and may be used to gain further insights in the dynamics of mutualistic interactions

Los orígenes de la arquitectura telefónica en España: las centrales madrileñas del «Grupo Peninsular»

El desarrollo del negocio telefónico en España fue lento y hay muy pocos edificios diseñados como centrales telefónicas antes de 1924. Este artículo describe el conjunto de tres centrales que el Grupo Peninsular construyó en Madrid entre 1910 y 1917, siguiendo las reglas e ideología sobre arquitectura de American Telephone and Telegraph que inspiraron a las pequeñas empresas privadas europeas de ese periodo

A binomial stochastic simulated study of mutualism

Mutualism is the interaction between two species that results benefitial for both. Mutualistic communities have an internal structure of bipartite network, with a property called nestedness that makes them quite resilient. Research has focused on stability to explain the reasons of this effect but dynamics is less well understood. Theoretical models are modifications of the classical logistic equation with addition l terms to take into account intraspecies interactions, but they are not fully satisfactory for simultaion under all circumstances. We have developed a model of mutualism based on the aggregation of benefit for each species in its equivalent growth rate: dN a j dt = req a jNj a ? |req a j| N a j 2 Ka j dN p l dt = req p lNlp ? |req p l|N K lpp2 l (1) Where the superscripts stands for each of both class of species. With these equtaions, we have built a binomial stochastic simulator for the study of system dynamics. It allows the introduction of external perturbations such as step increases in mortality by plagues, removal of links between species due to evolution or superposition of a predator foodweb. With this toolbox, we have simulated different scenarios that explain, for instance, why newcomer species have more chances of survival if they link to the generalist nested core, and how extinctions can spread and lead to a total collapse with a minimum change of the intensity of the external perturbation