Assessing the potential distribution of invasive alien species Amorpha fruticosa (Mill.) in the Mureş Floodplain Natural Park (Romania) using GIS and logistic regression

The assessment of invasive terrestrial plant species in the Romanian protected areas is an important research direction, especially since the adventive species have become biological hazards with significant impacts on biodiversity. Due to limited resources being available for the control of the invasive plants, the modelling of the spatial potential distribution is particularly useful in order to find the best measures to eliminate them or prevent their introduction and spread, as well as including them in the management plans of protected areas. Thus, the present paper aims to assess one of the most disturbing invasive terrestrial plant species in Europe – A. fruticosa in one of the most important natural protected area in Romania, i.e. Mureş Floodplain Natural Park (V IUCN category and RAMSAR –Wetlands of International Importance). The current study is a geographical approach seeking to explain the spatial relationships between this invasive species and several explanatory factors (soil type, depth to water, vegetation cover, forest fragmentation and distance to near waters, roads and settlements) and to assess its potential distribution by integrating GIS and logistic regression into spatial simulation. The resultant probability map can be used by the park’s administration in implementing the Management Plan in terms of identifying the areas with the highest occurrence potential of A. fruticosa according to the primary habitats and ecosystems and setting up actions for its eradication/limitation

Invasive terrestrial plant species in the Romanian protected areas. A review of the geographical aspects

Geographical factors play an essential role in the occurrence and spread of invasive species worldwide, and their particular analysis at regional and local scales becomes important in understanding species development patterns. The present paper discusses the relationships between some key geographical factors and the Invasive Terrestrial Plant Species (ITPS) distribution, and their environmental implications in a few protected areas in Romania. The authors focused their attention on three of the foremost invaders (i.e. Amorpha fruticosa, Ailanthus altissima and Fallopia japonica) making use of the information provided by the scientific literature and some illustrative examples developed in the framework of the FP7 enviroGRIDS project. The study is aimed to increase the knowledge of the ITPS and, specifically, to contribute to the geographical understanding of the role played by the driving factors in their distribution and spread in various habitats and ecosystems. The results will further support the control efforts in protected areas where, often, valuable native species are at risk of being replaced by non-native species

Driving factors of urban sprawl in the Romanian plain. Regional and temporal modelling using logistic regression

The paper investigates built-up areas expansion after the 1990 in one of the highly urbanized regions of Romania - Romanian Plain, in order to explore the urban sprawl phenomena and its temporal and regional disparities in relation to some of the main distance driving factors. The research uses Landsat 4/5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper (ETM), and Landsat 8 Operational Land Imager (OLI) imagery to derive built-up areas and quantify their expansion over time in relation to fourteen distance explanatory factors: i.e. previous built-up areas, main road infrastructure, Bucharest city’s boundary, location of the urban centres classified according to demographic size and main economic function, forest land and water bodies. To estimate the influence of the predictors, the binary logistic regression was applied. Furthermore, to estimate the effectiveness of the predictor set in the variation of built-up areas expansion, the pseudo R2 was calculated and discussed. Moreover, to understand the future potential trend of urban sprawl and its spatial pattern, the probability maps were generated by integrating the regression coefficients of the statistically significant predictors into the spatial modeling. For the results performance assessment, the statistic Receiver Operating Characteristic and the pixel-based comparison between the real and predicted data were used. To assess possible differences at spatial and temporal scale, the analysis was carried out at regional level, for two periods: 1990–2002 and 2002–2018. In general, our findings show inverse relationship between the distance driving factors and built-up areas expansion, but the estimated predictive power suggests important disparities within the study area over the analysed periods. Overall, the statistical analysis indicate that the distance to previous build-up areas, distance to road infrastructure, distance to Bucharest and other large urban centres, and distance to urban centres with dominant industrial and service functions were more influential to urban sprawl after 1990. Furthermore, the predicted spatial data shows the highest potential of urban sprawl in the future around Bucharest, in the proximity of existing built-up areas and road infrastructure. Because of its predictive character, the present study is to be a useful tool for land managers and policy makers

Modelling land use/cover change to assess future urban sprawl in Romania

The current paper aims at assessing future urban sprawl in Romania based on predicted land use/cover change (2007–2050) simulated using CLUE-S model (the Conversion of Land Use and its Effects at Small regional extent) and CORINE Land Cover (CLC) database. Given the regional particularities of land use/cover change, the CLUE-S model was applied for each Development Region of Romania (NUTS 2 level). The authors analysed various biophysical and socio-economic explanatory variables associated with the current patterns of urban expansion and assessed future urban sprawl based on historical built-up expansion. The model shows increasing built-up areas mainly in relation to the decreasing in agricultural lands, especially inside and outside the cities limits, with significant differences at the regional level. The results provide support for the decision-makers and local communities in promoting less consumption of land resource and the protection of the environment

Post-communist land use changes related to urban sprawl in the Romanian metropolitan areas

The landscape pattern of the Romanian urban system has experienced significant transformations as a result of the rapid and irreversible changes undertaken after the fall of the communism. In Romania almost 34% of its total population are living in metropolitan areas. The paper is aiming to analyse the landscape-related challenges land-use/land-cover changes in the Romanian metropolitan areas in relation with the main factors involved in the patterns of change: demographic, political and natural. Based on the investigation of relevant cartographic supports of the last 20 years, the authors are making use of different GIS methods in order to conduct a series of complex analysis of the spatial-temporal landscape challenges. The paper will mainly focus on four metropolitan areas considered as case-studies: the capital-city (Bucharest) and the three functional metropolitan areas (Oradea, Iaşi and Constanţa), each metropolitan area is facing different patterns and causes of change

The Estimation of Regional Energy Consumption Based on the Energy Consumption Rate at National Level. Case Study: The Romanian Danube Valley

Based on the national level data on energy consumption by final consumption sectors (agricultural, industrial, construction, residential and transport), the present study is aimed at estimating the energy consumption at county level. The overall energy Romania has consumed throughout a year has been broken down into ‘demographic’ and ‘economic’ components. The changes in the two components were determined on an annual basis for the following reference years: 1995, 2000, 2005, 2010 and 2015. The variables used in the current investigation were assembled into two groups of indicators: demographic (urban population, population size, proportion of the population aged 65 years and over, the economically active population divided according to activities of national economy: agriculture, industry, transport), and economic (GDP per capita, energy consumption by the activities of the national economy: agriculture, residential, industry, transport). In some cases, where a significant share of the population worked in the industry sector (with the probability of a diversified industry), our calculations overestimated energy consumption. This may also be due to the cumulative effect of some demographic factors (i.e., the high degree of urbanization). The paper discusses the effect of the demographic variables (e.g., size, age and occupational structures) have on energy consumption. The paper shows that the economic growth Romania has been subject to since the year 2000 has led to a rise in energy consumption for two economic activities (agriculture, transportation) and it also turned out that improving the technologies used in industry has a positive effect on energy efficiency. Energy efficiency depends, in addition to the technologies used in each economic activity, on demographic factors. Some of the demographic factors have different trends in terms of energy consumption. The effect of the population size must be explained in the context of changes in the structure by age groups (aging of the population), changes in fertility and mortality rates. Moreover, the economic structure changes alongside the alterations undergone by the demographic structure. This, in turn, changes production and consumption, transport infrastructure, as well as social services. In order to draw firm conclusions about the relationship between energy consumption and population structure by age group, further detailed studies are needed, including making use of other indicators

Estimation of Future Changes in Aboveground Forest Carbon Stock in Romania. A Prediction Based on Forest-Cover Pattern Scenario

The aboveground forest biomass plays a key role in the global carbon cycle and is considered a large and constant carbon reservoir. Hence, exploring the future potential changes in forest-cover pattern can help to estimate the trend of forest biomass and therefore, carbon stock in a certain area. As a result, the present paper attempts to model the potential changes in aboveground forest carbon stock based on the forest-cover pattern scenario simulated for 2050. Specifically, the resulting aboveground forest biomass, estimated for 2015 using the allometric equation based on diameter at breast height and the estimated forest density, was used as baseline data in the present approach. These spatial data were integrated into the forest-cover pattern scenario, predicted by using a spatially explicit model, i.e., the Conversion of Land Use and its Effects at Small regional extent (CLUE-S), in order to estimate the potential variation of aboveground forest carbon stock. Our results suggest an overall increase by approximately 4% in the aboveground forest carbon stock until 2050 in Romania. However, important differences in the forest-cover pattern change were predicted on the regional scale, thus highlighting that the rates of carbon accumulation will change significantly in large areas. This study may increase the knowledge of aboveground forest biomass and the future trend of carbon stock in the European countries. Furthermore, due to their predictive character, the results may provide a background for further studies, in order to investigate the potential ecological, socio-economic and forest management responses to the changes in the aboveground forest carbon stock. However, in view of the uncertainties associated with the data accuracy and methodology used, it is presumed that the results include several spatial errors related to the estimation of aboveground forest biomass and simulation of future forest-cover pattern change and therefore, represent an uncertainty for the practical management of applications and decisions

National-scale landslide susceptibility map of Romania in a European methodological framework

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