32 research outputs found
Long-term land-cover/use change in a traditional farming landscape in Romania inferred from pollen data, historical maps and satellite images
Traditional farming landscapes in the temperate
zone that have persisted for millennia can be exceptionally species-rich and are therefore key conservation targets. In contrast to Europe’s West, Eastern Europe harbours widespread traditional farming landscapes, but drastic socio-economic and political changes in the twentieth century are likely to have impacted these landscapes profoundly. We reconstructed long-term land-use/cover and biodiversity changes over the last 150 years in a traditional farming landscape of outstanding species diversity in Transylvania. We used the Regional Estimates of Vegetation Abundance from Large Sites model applied to a pollen record from the Transylvanian Plain and a suite of historical and satellite-based maps. We documented widespread changes in the extent and location of grassland and cropland, a loss of wood pastures as well as a gradual increase in forest extent. Land management in the socialist period (1947–1989) led to grassland expansion, but grassland diversity decreased due to intensive production. Land-use intensity has declined since the collapse of socialism in 1989, resulting in widespread cropland abandonment and conversion to grassland. However, these trends may be
temporary due to both ongoing woody encroachment as
well as grassland management intensification in productive areas. Remarkably, only 8% of all grasslands existed throughout the entire time period (1860–2010), highlighting the importance of land-use history when identifying target areas for conservation, given that old-growth grasslands are most valuable in terms of biodiversity. Combining datasets from different disciplines can yield important additional insights into dynamic landscape and biodiversity changes, informing conservation actions to maintain these species-rich landscapes in the longer term
Geographical variation in morphology of Chaetosiphella stipae stipae Hille Ris Lambers, 1947 (Hemiptera: Aphididae: Chaitophorinae)
Chaetosiphella stipae stipae is a xerothermophilous aphid, associated with Palaearctic temperate steppe zones or dry mountain valleys, where there are grasses from the genus Stipa. Its geographical distribution shows several populations that are spread from Spain, across Europe and Asia Minor, to Mongolia and China. Geographical variation in chaetotaxy and other morphological features were the basis to consider whether individuals from different populations are still the same species. Moreover, using Ch. stipae stipae and Stipa species occurrences, as well as climatic variables, we predict potential geographical distributions of the aphid and its steppe habitat. Additionally, for Stipa species we projected current climatic conditions under four climate change scenarios for 2050 and 2070. While highly variable, our results of morphometric analysis demonstrates that all Ch. stipae stipae populations are one very variable subspecies. And in view of predicted climate change, we expect reduction of Stipa grasslands. The disappearance of these ecosystems could result in stronger separation of the East-European and Asian steppes as well as European ‘warm-stage’ refuges. Therefore, the geographic morphological variability that we see today in the aphid subspecies Ch. stipae stipae may in the future lead to speciation and creation of separate subspecies or species
Analyzing human gaze path during an interactive optimization task
International audienc
Adaptation Mechanism based on Service-Context Distance for Ubiquitous Computing
International audienceService adaptation is one of the main research subjects in Ubiquitous Computing. Dynamic service adaptation, at runtime, is necessary for services that cannot be stopped (banking, airport, etc.). The classical approaches for dynamic adaptation require predicting all service and context states in order to specify service and context-specific adaptation policies. This prediction may lead to a combinatorial explosion. The aim of this research is to create a service and context-independent adaptation mechanism. Our proposal is based on a service-context model that is causally connected with the service and context, in [email protected]. A closed-loop control principle is used for the adaptation mechanism. We introduce an equivalent for the error that is expressed by the notion of service-context distance. This distance represents a measure of how adequate is a service to its context. This distance is computed by some generic, reusable components. The adaptation algorithm that minimizes this distance is also service and context-independent
QoS-based service optimization using differential evolution
The aim of our research is to find an efficient solution to the services QoS optimization problem. This NP-hard problem is well known in the service-oriented computing field: given a business workflow that includes a set of abstract services and a set of concrete service implementations for each abstract service, the goal is to find the optimal combination of concrete services. The majority of recent proposals indicate the Genetic Algorithms (GA) as the best approach for complex workflows. But this problem usually needs to be solved at runtime, a task for which GA may be too slow. We propose a new approach, based on Differential Evolution (DE), that converges faster and it is more scalable and robust than the existing solutions based on Genetic Algorithms