Spreading of Invasive Species in Greenways: a GIS-based Case Study in Hungary

The fast spread of invasive species is leading to a reduction in biodiversity and habitat loss for native species. It is especially important to consider the environmental aspects during greenway planning. Ecological corridors are designed to assure the migration of species between the valuable conservation areas and to reduce the spreading ability of invasive species. This paper analyses the proportion invasive species on the greenways (ecological corridors) of the Southern Hungarian Great Plain NUTS 2 statistical region, in Hungary. The spreading conditions and dynamics of invasive species were compared inside and outside greenways. The study aims to define the ecological factors that influence the spread of two invasive species: silver berry (Elaeagnus angustifolia) and common milkweed (Asclepias syriaca). Another goal was to prepare the hazard map of invasive species for a study area based on the results. This map can be used to make recommendations for the modification of ecological networks. Georeferred point based landscape photographs of the EU project LUCAS (Land Use/Cover Area Statistical Survey) were used for our research. LUCAS allows monitoring of environmental changes because of the fieldwork based landscape photographs were taken in every (more than 1000) sample points of the study area. The LUCAS points with a high number of silver berry (Elaeagnus angustifolia) and common milkweed (Asclepias syriaca) were easily identified from the photos based on the morphology. The chosen points of the database give good opportunity to examine how large the proportion of invasive species is in the elements of the ecological network (ecological core area, corridor and buffer area) in the Southern Hungarian Great Plain NUTS 2 level statistical region study area. To assess the degrees of hazard the geographical factors influencing the spread of invasive species were examined using digital databases referring to soil, land cover, land cover change and drainage system maps. Based on these analyses the hazard map was prepared considering the above mentioned invasive species. The showed methods and results will be able to add some new useful tools for greenway, and ecological network planning

Acute escitalopram treatment inhibits REM sleep rebound and activation of MCH-expressing neurons in the lateral hypothalamus after long term selective REM sleep deprivation.

RATIONALE: Selective rapid eye movement sleep (REMS) deprivation using the platform-on-water ("flower pot") method causes sleep rebound with increased REMS, decreased REMS latency, and activation of the melanin-concentrating hormone (MCH) expressing neurons in the hypothalamus. MCH is implicated in the pathomechanism of depression regarding its influence on mood, feeding behavior, and REMS. OBJECTIVES: We investigated the effects of the most selective serotonin reuptake inhibitor escitalopram on sleep rebound following REMS deprivation and, in parallel, on the activation of MCH-containing neurons. METHODS: Escitalopram or vehicle (10 mg/kg, intraperitoneally) was administered to REMS-deprived (72 h) or home cage male Wistar rats. During the 3-h-long "rebound sleep", electroencephalography was recorded, followed by an MCH/Fos double immunohistochemistry. RESULTS: During REMS rebound, the time spent in REMS and the number of MCH/Fos double-labeled neurons in the lateral hypothalamus increased markedly, and REMS latency showed a significant decrease. All these effects of REMS deprivation were significantly attenuated by escitalopram treatment. Besides the REMS-suppressing effects, escitalopram caused an increase in amount of and decrease in latency of slow wave sleep during the rebound. CONCLUSIONS: These results show that despite the high REMS pressure caused by REMS deprivation procedure, escitalopram has the ability to suppress REMS rebound, as well as to diminish the activation of MCH-containing neurons, in parallel. Escitalopram caused a shift from REMS to slow wave sleep during the rebound. Furthermore, these data point to the potential connection between the serotonergic system and MCH in sleep regulation, which can be relevant in depression and in other mood disorders

Application of GIS for a Climate Change Prepared Disaster Management in Csongrád County, Hungary

The work of disaster management can only properly be supported by data stored in certified databases, since correct decisions can be made on the base of such data. Nowadays these data can be found in databases managed by several organisations, or only a part of the necessary data is available through GIS services. The tasks of disaster management include prevention, i.e. the preparation for potential incidents and the elaboration of related scenarios and plans taking into consideration the altering risk landscape caused by climate change. The development of modelling processes and applications based on GIS databases and the integration of the results in work processes gain ground more and more in this work phase. Geoinformatics is able to provide support for decision-making in two ways: in strategic planning and in the operative task solution. The present study demonstrates a multi-hazard multi-scale GIS tool development in Csongrád County (Hungary) in accordance with the aims of the Sendai Framework. This geoinformatic tool is applicable to support the decision-making not only of the management board but the deployed rescue units in case of an evacuation through the optimized locations of the gathering places