Biological significance of dead biomass retention trait in Mediterranean Basin species: an analysis between different successional niches and regeneration strategies as functional groups

Standing dead biomass retention is considered one of the most relevant fuel structural traits to affect plant flammability. However, very little is known about the biological significance of this trait and its distribution between different functional groups. Our aim was to analyse how the proportion of dead biomass produced in Mediterranean species is related to the successional niche of species (early-, mid- and late-successional stages) and the regeneration strategy of species (seeders and resprouters). We evaluated biomass distribution by size classes and standing dead biomass retention in nine dominant species from the Mediterranean Basin in different development stages (5, 9, 14 and 26 years since the last fire). The results revealed significant differences in the standing dead biomass retention of species that presented a distinct successional niche or regeneration strategy. These differences were restricted to the oldest ages studied (>9 years). Tree and small tree resprouters, typical in late-successional stages, presented slight variations with age and a less marked trend to retain dead biomass, while seeder shrubs and dwarf shrubs, characteristic of early-successional stages, showed high dead biomass loads. Our results suggest that the species that tend to retain more dead branches are colonising species that may promote fire in early-successional stages.

Enrichment of the Phenotypic and Genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Currently there are an overwhelming number of scientific publications in Life Sciences, especially in Genetics and Biotechnology. This huge amount of information is structured in corporate Data Warehouses (DW) or in Biological Databases (e.g. UniProt, RCSB Protein Data Bank, CEREALAB or GenBank), whose main drawback is its cost of updating that makes it obsolete easily. However, these Databases are the main tool for enterprises when they want to update their internal information, for example when a plant breeder enterprise needs to enrich its genetic information (internal structured Database) with recently discovered genes related to specific phenotypic traits (external unstructured data) in order to choose the desired parentals for breeding programs. In this paper, we propose to complement the internal information with external data from the Web using Question Answering (QA) techniques. We go a step further by providing a complete framework for integrating unstructured and structured information by combining traditional Databases and DW architectures with QA systems. The great advantage of our framework is that decision makers can compare instantaneously internal data with external data from competitors, thereby allowing taking quick strategic decisions based on richer data.