A multinational SDI-based system to facilitate disaster risk management in the Andean Community

A useful strategy for improving disaster risk management is sharing spatial data across different technical organizations using shared information systems. However, the implementation of this type of system requires a large effort, so it is difficult to find fully implemented and sustainable information systems that facilitate sharing multinational spatial data about disasters, especially in developing countries. In this paper, we describe a pioneer system for sharing spatial information that we developed for the Andean Community. This system, called SIAPAD (Andean Information System for Disaster Prevention and Relief), integrates spatial information from 37 technical organizations in the Andean countries (Bolivia, Colombia, Ecuador, and Peru). SIAPAD was based on the concept of a thematic Spatial Data Infrastructure (SDI) and includes a web application, called GEORiesgo, which helps users to find relevant information with a knowledge-based system. In the paper, we describe the design and implementation of SIAPAD together with general conclusions and future directions which we learned as a result of this work.

Application of Decision Theory methods for a Community of Madrid Soil classification case

A land classification method was designed for the Community of Madrid (CM), which has lands suitable for either agriculture use or natural spaces. The process started from an extensive previous CM study that contains sets of land attributes with data for 122 types and a minimum-requirements method providing a land quality classification (SQ) for each land. Borrowing some tools from Operations Research (OR) and from Decision Science, that SQ has been complemented by an additive valuation method that involves a more restricted set of 13 representative attributes analysed using Attribute Valuation Functions to obtain a quality index, QI, and by an original composite method that uses a fuzzy set procedure to obtain a combined quality index, CQI, that contains relevant information from both the SQ and the QI methods.

Regional and seasonal patterns of litterfall in tropical South America

The production of aboveground soft tissue represents an important share of total net primary production in tropical rain forests. Here we draw from a large number of published and unpublished datasets (n = 81 sites) to assess the determinants of litterfall variation across South American tropical forests. We show that across old-growth tropical rainforests, litterfall averages 8.61±1.91Mgha?1 yr?1 (mean±standard deviation, in dry mass units). Secondary forests have a lower annual litterfall than old-growth tropical forests with a mean of 8.01±3.41Mgha?1 yr?1. Annual litterfall shows no significant variation with total annual rainfall, either globally or within forest types. It does not vary consistently with soil type, except in the poorest soils (white sand soils), where litterfall is significantly lower than in other soil types (5.42±1.91Mgha?1 yr?1). We also study the determinants of litterfall seasonality, and find that it does not depend on annual rainfall or on soil type. However, litterfall seasonality is significantly positively correlated with rainfall seasonality. Finally, we assess how much carbon is stored in reproductive organs relative to photosynthetic organs. Mean leaf fall is 5.74±1.83Mgha?1 yr?1 (71% of total litterfall). Mean allocation into reproductive organs is 0.69±0.40Mgha?1 yr?1 (9% of total litterfall). The investment into reproductive organs divided by leaf litterfall increases with soil fertility, suggesting that on poor soils, the allocation to photosynthetic organs is prioritized over that to reproduction. Finally, we discuss the ecological and biogeochemical implications of these results.

Gender differences in physical activity and sport demanded by adult population of Community of Madrid

The communication presents part of the results of the study DEP2010- 19801/Plan Nacional I+D+i 2010-2013.