The effects of stand characteristics on the understory vegetation in Quercus petraea and Q. cerris dominated forests

The shelterwood system used in Hungary has many effects on the composition and structure of the herb layer. The aim of our study was to identify the main variables that affect the occurence of herbs and seedlings in Turkey oak-sessile oak (Quercus cerris and Q. petraea) stands. The study was carried out in the Bükk mountains, Hungary. 122 sampling plots were established in 50-150 year old oak forests, where we studied the species composition and structure of the understorey and overstorey. The occurence of herbs was affected by canopy closure, the heterogenity and patchiness of the stand, the slope and the east-west component of the aspect. The composition of saplings was significantly explained by the ratio of the two major oak species in the stand and the proximity of the adult plants. An important result for forest management was that sessile oaks were able to regenerate almost only where they were dominant in the overstorey

Steppe woodlands with Tatarian Maple (Aceri tatarici-Quercetum pubescentis-roboris) on the great Hungarian plain and its neighbourhood. An unfinished synthesis with supplementary notes

This paper presents the so far only partially published research material of the late Bálint Zólyomi on one of his major fields of interest, the forest steppe vegetation. The phytosociological tables presented here were found in his bequest indicating that he was going to publish a grand synthesis on this topic, which, however, has not come true. Since no written text accompanied the original tables, a historical overview and a short explanation to the tables are also provided

Evolution and environment of the eastern linear pottery culture: A case study in the site of Polgár-Piócási-Dűlő

A salvage excavation preceding a major investment project was conducted in 2006–2007, during which associated settlement features of a Middle Neolithic, Eastern Linear Pottery Culture (Alföld Linearbandkeramik – ALBK) were uncovered in an area called Piócási-dűlő on the eastern outskirts of Polgár. The features of the ALBK settlement date from two periods. The cluster of multi-functional pits yielding a rich assortment of finds, the handful of post-holes and an unusual ritual well found in the southern part of the investigated area formed one unit from the earliest phase of the Middle Neolithic (ALBK I). The settlement’s other occupation can be assigned to the late phase of the Middle Neolithic (ALBK IV). Five houseplans representing the remains of timber-framed buildings outlined a distinct area with three multi-functional pits. Associated with the above features were 8 burials. The preliminary archaeobotanical results from Polgár–Piócási-dűlő are based on the plant material found within the sediments of 11 archaeological structures, which mainly represent pits and a welI. It can be stated that the natural environment offered habitats in which oak trees dominated in the local vegetation, forming floodplain forests and wooded steppes. They also provided food in the form of fruits and formed an optimal habitat for domestic animals. Arable fields were probably also established in the vicinity of the settlements, suggested by findings of macroscopic plant remains that represented cultivated species. In both settlement phases lithic production activities are manifested both by the local on-site lithic production and – most importantly – by the presence of imported, mainly mesolocal, raw materials that point to contacts with deposit areas, or off-site preliminary working of obsidian and limnoquartzites. The kit of harvesting tools and a large number of grinding stones – especially in the younger phase – for the preparation of plant food suggest a major role of plant cultivation

EUNIS Habitat Classification: Expert system, characteristic species combinations and distribution maps of European habitats

Aim: The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their unequivocal identification. Our goal was to develop a tool for assigning vegetation‐plot records to the habitats of the EUNIS system, use it to classify a European vegetation‐plot database, and compile statistically‐derived characteristic species combinations and distribution maps for these habitats. Location: Europe. Methods: We developed the classification expert system EUNIS‐ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set‐theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species‐to‐habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat. Results: Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man‐made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination. Conclusions: EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electronic expert system EUNIS‐ESy. The data provided and the expert system have considerable potential for future use in European nature conservation planning, monitoring and assessment

Classification of mesic grasslands and their transitions of South Transdanubia (Hungary)

Relevés from meadows and pastures of South Transdanubia (Hungary) are evaluated by clustering and ordination methods. The relevé selection focused on the Arrhenatheretalia order but its transitions towards other types were also included. The groups of relevés are delimited and described according to differential, dominant and constant species. Ecological conditions of the groups were compared using indicator values. Nine groups were distinguished, four of them belonging strictly to the order Arrhenatheretalia. Each alliance of Arrhenatheretalia presented in the study area (Cynosurion, Arrhenatherion) was represented by two groups. Groups from these two alliances are separated along a light gradient, while groups of the same alliance differ in nutrient values. Within Cynosurion, the nutrient-poor group cannot be identified unambiguously as any syntaxa previously known from Hungary. The nutrient-rich Cynosurion meadows are similar to Lolio–Cynosuretum, however, they show a stronger relationship with wet meadows. Within Arrhenatherion, Pastinaco–Arrhenatheretum is recognised as a hay meadow of nutrient-rich soils. The other meadow type is similar to Filipendulo–Arrhenatheretum, thus raising syntaxonomical problems. There are transitional groups towards semi-dry and wet meadows, one dynamic phase and one outlier group among the other five clusters

Role-Based Teamwork Activity Recognition In Observations Of Embodied Agent Actions

Recognizing team actions in the behavior of embodied agents has many practical applications and had seen significant progress in recent years. One approach with proven results is based on HMM-based recognition of spatio-temporal patterns in the behavior of the agents. While it had been shown to work on real-world datasets, this approach was found to be brittle. In this paper we present two contributions which together can significantly increase the robustness of teamwork activity recognition. First we introduce a technique to reduce high dimensional continuous input data to a set of discrete features, which capture the essential components of the team actions. Second, we prefix the actual team action recognition with a role recognition module, which allows us to present the recognizer with arbitrarily shuffled input, and still obtain high recognition rates. We validate the improved accuracy and robustness of the team action recognizer on datasets derived from captured real world data. Copyright © 2008, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved

Teamwork Recognition Of Embodied Agents With Hidden Markov Models

Recognizing and annotating the occurrence of team actions in observations of embodied agents has applications in surveillance or in training of military or sport teams. We describe the team actions through a spatio-temporal cor-related pattern of movement, which can be modeled by a Hidden Markov Model. The hand-crafting of these models is a difficult task of knowledge engineering, even in application domains where explicit, natural language descriptions of the team actions are available. The main contribution of this paper is an approach through which the library of HMM representations can be acquired from a small number of hand annotated, representative samples of the specific movement patterns. A series of experiments, performed on a dataset describing a real-world terrestrial warfare exercise validates our method and shows good recognition accuracy even in the presence of noisy data. The speed of the recognition engine is sufficiently fast to allow real time annotation of incoming observations. ©2007 IEEE