International projects
Tracking surrogates for intraspecific biodiversity: towards efficient selection strategies for the conservation of natural genetic resources using comparative mapping and modelling approaches
Organisations (1)
Abstract
Species richness is the most widely used measure for biodiversity assessment. However it is intraspecific diversity (genetic polymorphism) that represents the evolutionary and adaptive potential of each species in changing environments. We propose to study possible correlations between intraspecific diversity and species richness or habitat variation. Our objectives are:(i) to find and explain possible relationships among inter- and intraspecific plant diversity and habitat variation,(ii) to elaborate a modelling approach to predict intraspecific plant diversity, using more efficiently accessible surrogates, on a large scale,(iii) to establish tools for the design of a network of protected areas to effectively ensure the sustainable management of natural genetic resources. We will ask the following questions, using the Alps and the Carpathians as model systems:(i) is there congruence between intra-/interspecific biodiversity?(ii) Do areas of high endemism, often coinciding with glacial refugia, harbour a great degree of intraspecific diversity?(iii) Is habitat variation, characterised by environmental parameters, a good surrogate for intra- and interspecific diversity? In order to accomplish our aims, we will map the intraspecific diversity by using molecular markers in 25 model species, map the species richness on the same area using mainly existing data on plant distributions, compile environmental data for a map of habitat diversity, compare theses maps to find possible correlations among these variables. Based on modelling and simulation techniques, we will develop a web-based public platform for efficiently selecting nature reserve networks which comprise the highest proportion of both intra- and interspecific diversities. Our integrative approach should help to better understand and predict ecosystem patterns on a large scale. The established platform will provide an innovative and efficient technology for observing and managing biodiversity.
