University of Alcalá

About: University of Alcalá is a education organization based out in Alcalá de Henares, Spain. It is known for research contribution in the topics: Population & Receptor. The organization has 10795 authors who have published 20718 publications receiving 410089 citations. The organization is also known as: University of Alcala & University of Alcala de Henares.

Regional Convergence in Productivity and Productive Structure: The Spanish Case:

Abstract: This article analyzes the evolution of regional differences in Spain and emphasizes the importance of a disaggregate analysis at a sectoral level. In particular, the authors observe convergence in productivity at the aggregate regional level but not at the sectoral level. Aggregate convergence seems to be due to the gradual homogenization of regional productive structures. This result may modify some of the conclusions drawn in the recent literature regarding the mechanisms that have generated convergence. In addition, we examine the so-called beta convergence hypothesis using a fixed-effects model. The results show the importance of regional specificity captured by the fixed effects and have implications that are very different from those of beta convergence analyses with cross-section data.

Two Trebouxia algae with different physiological performances are ever‐present in lichen thalli of Ramalina farinacea. Coexistence versus Competition?

Abstract: This study was funded by the Spanish Ministry of Education and Science (CGL2006-12917-C02-01/02), the Spanish Ministry of Science and Innovation (CGL2009-13429-C02-01/02), the AECID (PCI_A/024755/09) and the Generalitat Valenciana (PROMETEO 174/2008 GVA). We are grateful to Dr J. Gimeno-Romeu (University of California, Davis, USA) and to Dr P. J. G. de Nova (IREC, Ciudad Real, Spain), who were the first to isolate DNA from Ramalina farinacea thalli in our group. Wendy Ran revised the manuscript in English.

Applying the conservativeness principle to REDD to deal with the uncertainties of the estimates

Abstract: A common paradigm when the reduction of emissions from deforestations is estimated for the purpose of promoting it as a mitigation option in the context of the United Nations Framework Convention on Climate Change (UNFCCC) is that high uncertainties in input data—i.e., area change and C stock change/area—may seriously undermine the credibility of the estimates and therefore of reduced deforestation as a mitigation option. In this paper, we show how a series of concepts and methodological tools—already existing in UNFCCC decisions and IPCC guidance documents—may greatly help to deal with the uncertainties of the estimates of reduced emissions from deforestation.