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Understanding the natural history of model organisms is important for the effective use of their genomic resourses. Arabidopsis lyrata has emerged as a useful plant for studying ecological and evolutionary genetics, based on its extensive natural variation, sequenced genome and close relationship to A. thaliana. We studied genetic diversity across the entire range of European Arabidopsis lyrata ssp. petraea, in order to explore how population history has influenced population structure. We sampled multiple populations from each region, using nuclear and chloroplast genome markers, and combined population genetic and phylogeographic approaches. Within-population diversity is substantial for nuclear allozyme markers (mean P = 0.610, A(e) = 1.580, H-e = 0.277) and significantly partitioned among populations (F- ST = 0.271). The Northern populations have modestly increased inbreeding (F-IS = 0.163 verses F-IS = 0.093), but retain comparable diversity to central European populations. Bottlenecks are common among central and northern Europe populations, indicating recent demographic history as a dominant factor in structuring the European diversity. Although the genetic structure was detected at all geographic scales, two clear differentiated units covering northern and central European areas (F-CT = 0.155) were identified by Bayesian analysis and supported by regional pairwise F-CT calculations. A highly similar geographic pattern was observed from the distribution of chloroplast haplotypes, with the dominant northern haplotypes absent from central Europe. We conclude A. l. petraea's cold-tolerance and preference for disturbed habitats enabled glacial survival between the alpine and Nordic glaciers in central Europe and an additional cryptic refugium. While German populations are probable peri-glacial leftovers, Eastern Austrian populations have diversity patterns possibly compatible with longer-term survival.
Pompeii, buried by the explosive A. D. 79 eruption of Somma-Vesuvius, is one of the most studied ancient cities in the Roman world. However, until very recently, the rural settlement in its hinterland had been largely ignored by systematic archaeological research. The ancient landscape around Pompeii consisted of a dense network of Roman farms (villae rusticae). They are believed to have played a vital role in ancient rural life and economy and thus represented the interactive rural-urban relationship in the Sarno River plain. The systematic investigation of published work combined with new fieldwork has yielded a data set of 140 villae rusticae in the Sarno River plain. Geographic information system based spatial statistics as well as predictive modeling were applied to gain a more detailed understanding of the ancient rural settlement structure in relation to the underlying paleoenvironmental and socioeconomic conditions. A high-resolution pre-A. D. 79 paleolandscape model of the Sarno River plain was utilized. The aim of this paper is to address theoretical considerations, the methodological implementation, and the archaeological discussion of the analysis of the ancient rural settlements and agriculture around Pompeii. (C) 2016 Wiley Periodicals, Inc.
Decisions for the conservation of biodiversity and sustainable management of natural resources are typically related to large scales, i.e. the landscape level. However, understanding and predicting the effects of land use and climate change on scales relevant for decision-making requires to include both, large scale vegetation dynamics and small scale processes, such as soil-plant interactions. Integrating the results of multiple BIOTA subprojects enabled us to include necessary data of soil science, botany, socio-economics and remote sensing into a high resolution, process-based and spatially-explicit model. Using an example from a sustainably-used research farm and a communally used and degraded farming area in semiarid southern Namibia we show the power of simulation models as a tool to integrate processes across disciplines and scales.
In semi-arid savannas, unsustainable land use can lead to degradation of entire landscapes, e.g. in the form of shrub encroachment. This leads to habitat loss and is assumed to reduce species diversity. In BIOTA phase 1, we investigated the effects of land use on population dynamics on farm scale. In phase 2 we scale up to consider the whole regional landscape consisting of a diverse mosaic of farms with different historic and present land use intensities. This mosaic creates a heterogeneous, dynamic pattern of structural diversity at a large spatial scale. Understanding how the region-wide dynamic land use pattern affects the abundance of animal and plant species requires the integration of processes on large as well as on small spatial scales. In our multidisciplinary approach, we integrate information from remote sensing, genetic and ecological field studies as well as small scale process models in a dynamic region-wide simulation tool. <hr> Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006.