Stylization: a method for preserving the character of climate sensitive habitat

Stylization is a method of ornamental plant use usually applied in urban open space and garden design based on aesthetic consideration. Stylization can be seen as a nature-imitating ornamental plant application which evokes the scenery rather than an ecological plant application which assists the processes and functions observed in the nature. From a different point of view, stylization of natural or semi-natural habitats can sometimes serve as a method for preserving the physiognomy of the plant associations that may be affected by the climate change of the 21st century. The vulnerability of the Hungarian habitats has thus far been examined by the researchers only from the botanical point of view but not in terms of its landscape design value. In Hungary coniferous forests are edaphic and classified on this basis. The General National Habitat Classification System (Á-NÉR) distinguishes calcareous Scots pine forests and acidofrequent coniferous forests. The latter seems to be highly sensitive to climate change according to ecological models. The physiognomy and species pool of its subtypes are strongly determined by the dominant coniferous species that can be Norway spruce (Picea abies) or Scots pine (Pinus sylvestris). We are going to discuss the methodology of stylization of climate sensitive habitats and briefly refer to acidofrequent coniferous forests as a case study. In the course of stylization those coniferous and deciduous tree species of the studied habitat that are water demanding should be substituted by drought tolerant ones with similar characteristics. A list of the proposed taxa is going to be given

Methods of modeling the future shift of the so called Moesz-line

It is important to the landscape architects to become acquainted with the results of the regional climate models so they can adapt to the warmer and more arid future climate. Modelling the potential distribution area of certain plants, which was the theme of our former research, can be a convenient method to visualize the effects of the climate change. A similar but slightly better method is modelling the Moesz-line, which gives information on distribution and usability of numerous plants simultaneously. Our aim is to display the results on maps and compare the different modelling methods (Line modelling, Distribution modelling, Isotherm modelling). The results are spectacular and meet our expectations: according to two of the three tested methods the Moesz-line will shift from South Slovakia to Central Poland in the next 60 years

Impression of the global climate change on the ornamental plant usage in Hungary

The climate modeling, which has adequate spatial and temporal resolution, shows that the future climate of the Carpathian Basin will be much more arid and hot than nowadays. The currently used and taught assortment of the ligneous ornamental plants should be urgently revised. It is aimed in my research to collect the species which will probably be introduced in the future. They can be gathered from the Hungarian botanical gardens and research centers and from the spatially analogous territories. The collected taxa should be examined with GIS software if they will really suffer our future climate

Modeling the Impacts of Climate Change on Phytogeographical Units. A Case Study of the Moesz Line

Regional climate models (RCMs) provide reliable climatic predictions for the next 90 years with high horizontal and temporal resolution. In the 21st century northward latitudinal and upward altitudinal shift of the distribution of plant species and phytogeographical units is expected. It is discussed how the modeling of phytogeographical unit can be reduced to modeling plant distributions. Predicted shift of the Moesz line is studied as case study (with three different modeling approaches) using 36 parameters of REMO regional climate data-set, ArcGIS geographic information software, and periods of 1961-1990 (reference period), 2011-2040, and 2041-2070. The disadvantages of this relatively simple climate envelope modeling (CEM) approach are then discussed and several ways of model improvement are suggested. Some statistical and artificial intelligence (AI) methods (logistic regression, cluster analysis and other clustering methods, decision tree, evolutionary algorithm, artificial neural network) are able to provide development of the model. Among them artificial neural networks (ANN) seems to be the most suitable algorithm for this purpose, which provides a black box method for distribution modeling

A Moesz-vonal jövőben várható elmozdulásának térinformatikai modellezési lehetőségei

According to the results of the regional climate models our future climate will be warmer and more arid. It has a high importance that the landscape architecture should become acquainted with the expected change to become able to adapt to it. Therefore, it is necessary to draw the future distribution of the plants or to model the shift of the Moesz-line, which characterizes multiple plants simultaneously, to visualize the extent and the direction of the climate change. Our research aimed to model the Moesz-line and display the results on maps, and compare the different modeling methods (Line modeling, Distribution modeling, Isotherm modeling). The model gave impressive results that meet our expectations. Two of the three proved methods showed that the Moesz-line will shift to Central Poland by 2070

Negative impact of climate change on the distribution of some conifers

A climate envelope model was run on the distribution of four coniferous species (European silver fir, European larch, Norway spruce, and Swiss pine). The model was supported by EUFORGEN area database, ArcGIS 10 and PAST software, andREMO climate model. Prediction periods were 2011-40 and 2041-70

Modeling the future distribution of Mediterranean Pinus species

The potential future distribution of four Mediterranean pines was aimed to be modeled supported by EUFORGEN digital area database (distribution maps), ESRI ArcGIS 10 software’s Spatial Analyst module (modeling environment), PAST (calibration of the model with statistical method), and REMO regional climate model (climatic data). The studied species were Pinus brutia, Pinus halepensis, Pinus pinaster, and Pinus pinea. The climate data were available in a 25 km resolution grid for the reference period (1961-90) and two future periods (2011-40, 2041-70). The climate model was based on the IPCC SRES A1B scenario. The model results show explicit shift of the distributions to the north in case of three of the four studied species. The future (2041-70) climate of Western Hungary seems to be suitable for Pinus pinaster

Modeling the Impacts of Climate Change on Phytogeographical Units: A Case Study of the Moesz Line

Regional climate models (RCMs) provide reliable climatic predictions for the next 90 years with high horizontal and temporal resolution. In the 21st century northward latitudinal and upward altitudinal shift of the distribution of plant species and phytogeographical units is expected. It is discussed how the modeling of phytogeographical unit can be reduced to modeling plant distributions. Predicted shift of the Moesz line is studied as case study (with three different modeling approaches) using 36 parameters of REMO regional climate dataset, ArcGIS geographic information software, and periods of 1961-1990 (reference period), 2011-2040, and 2041-2070. The disadvantages of this relatively simple climate envelope modeling (CEM) approach are then discussed and several ways of model improvement are suggested. Some statistical and artificial intelligence (AI) methods (logistic regression, cluster analysis and other clustering methods, decision tree, evolutionary algorithm, artificial neural network) are able to provide development of the model. Among them artificial neural networks (ANN) seems to be the most suitable algorithm for this purpose, which provides a black box method for distribution modeling