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Defoliation is the main parameter for assessing tree crown conditions, and is the result of cumulative interactions among different types of stressors, including climate, air pollution, pests and diseases, and management systems. Here, we evaluated a long-term data series (1992-2013) provided by the ICP-Forests Level I monitoring network (16 × 16 km) in Romania. Specifically, we investigated how climate influences defoliation at different spatial and temporal levels using statistical analyses. Using periodic climatic data (mean temperature and precipitation) derived from a daily grid dataset (ROCADA) with a resolution of 0.1 × 0.1° (10 × 10 km), we quantified how climatic parameters were correlated with defoliation, which was expressed as the mean tree defoliation per plot (DEF), and the proportion of damaged trees (crown defoliation > 25% - fDEF). The cross-correlation (Spearman r) between defoliation indicators and temperature was positive and relatively constant over time for all broadleaves and conifers, combined and separately, except for Fagus sylvatica (European beech), which had a negative cross-correlation coefficient. The correlation obtained for precipitation was similar to that obtained for temperature; however, this relationship was negative (except, again, for beech). The temporal influence of temperature on defoliation was much lower than that of precipitation, which had the greatest influence in dry regions (south and southeast Romania), especially for Quercus species. Furthermore, precipitation had a positive influence in moderate climate regions for conifers that were situated outside their natural distribution ranges. For beech and conifers situated at the upper altitudinal limits, temperature was negatively correlated with defoliation, i.e., temperature had a positive influence on health status.

This paper is devoted to the analysis of the mean-square stability of a class of linear time-varying impulsive Itô-type stochastic systems. We succeed to obtain necessary and sufficient stability conditions in the general time-varying case. This result is obtained thanks to the theory of positive operators on Hilbert spaces. The problem of statefeedback stabilization is treated as well. [ABSTRACT FROM AUTHOR]

This paper presents six species of Oniscidea recorded until now in the Piatra Craiului National Park in Romania: Ligidium hypnorum, Mesoniscus graniger, Hyloniscus dacicus, Trichoniscus carpaticus, Trachelipus nodulosus, and Trachelipus difficilis rotundatus.

This paper present an exemple of the applicability of dendroclimatological research methods in the study of forest ecosystems, using the dendrochronological series from Giumalau Secular Forest (GIUA - Norway spruce), Slatioara Secular Forest (SLAA -Norway spruce, SLAB - Silver fir) and Demacusa Basin (DEMA - Silver fir). In the case of the Norway spruce, respectively the GIUA and SLAA dendrochronological series, one can notice a significant negative correlation with the temperatures from the end of the previous vegetation season (July, August, and September) and positive with the rainfalls from that period. The same type of reaction concerning the previous vegetation season is also present in the case of the Silver fir, but the intensity is lower. As far as the current vegetation season is concerned, the Norway spruce has a significant positive reaction (GIUA - February, March, SLAA - April, July) to the regime of rainfalls. The thermal regime at the end of the season of vegetative repose and at the beginning of the vegetation season, months January - June induces a positive response from the Norway spruce. The Norway spruce’s response to modification of the thermal regime in the vegetation season, months July-August, is negative, the high temperatures directly and indirectly determining a decrease of the growth in diameter rhythm. In case of the dendrochronological series from Giumalau Secular Forest - GIUA - the temperature in August is negative and significantly correlated with the growth index. The end of the vegetation season, namely September, has a positive influence on growth, as far as the thermal regime is concerned, the reaction being negative to pluviometric regime. In the case of the Silver fir, there is a positive reaction, even very strong and significant in the case of Slatioara-s series of growth indexes - SLAB, to temperatures from the cold season (December-March). The same positive response can be noticed in the case of the temperatures from the vegetation season (July - August), for the series of indexes from Demacusa Basin, the correlation being significant in the case of the temperatures from August. The rainfalls at the beginning of vegetation season (April - June) determine an acceleration of radial growth rhythm, but the correlation is insignificant from the statistical point of view. The comparative analysis of the series of real and estimated by statistical models growth indexes indicates a very good reliability of the response functions. Distribution of residual errors is random, except for the period 1985-1992 in the case of dendrochronological series from Slatioara (Norway spruce and Silver fir) and Demacusa, when the statistic model systematically overestimates the growth indexes. The explanation can be found in the presence of a disturbance signal with intense manifestation in this period, the hypothesis issued being the presence of some phenomena of intense pollution. This manifestation is very obvious, especially in the case of the Norway spruce from Slatioara Secular Forest - SLAA.

The present structure of natural forest ecosystems from the North of Eastern Carpathian, his heterogeneity, is the results of the historic disturbances. The wind damage represent the most important disturbance factor in these forests, with significant impacts on growth process through the modification of the spatial stand structure. The effects of the disturbance factor on the growth process is visible by a high acceleration of growth over more than 10 years. Using the tools of dendroecology, respectively the graphical analysis of radial growth and primary growth index, obtained by the separation of signal, was possible to establish the disturbance regime in forest form the North of Eastern Carpathians. In Rodna Mountains windthrow frequency is lower than in Moldova basin, where we can see a major disturbance at every 35-40 years. Interesting is that the windthrow from 1815- 1820 is preset in all dendrochronological series, more or less intensive, having a great impact on the landscape of superior basin of Bila, determining the apperance of the stands from BILB and BILC and a high destructuration of stone pine ecosystem from BILD. Other important disturbance are from 1880- 1890, very evident in the dendrochronological series from GIUA, SLAA, BILB, PUTB. This disturbance, assimilated with a windthow, was mentioned in historic books dated in 26 June 1885 in the North of Eastern Carpathians.

The knowledge of natural risk of occurrence of drought period represents a necessity for the foun­dation of afforests technologies and silvicultural operations. The idea of synthesis is in the book of H. Walter (1974) and is based on the using of cli­matic diagrams type Walter - Leith for the delimitation of drought climate of Romania (Donița, 1967; Barbu și Cenușă 1975). Walter (1974) consider that the period·in which the precipitation curve at P = 2T scale is under the temperature curve is a drought period and the peri­od in which the precipitation curve at P = 3T scale is under the temperature curve is a aridity period. The delimitation of drought zone on the base of cli­matic diagrams type Walter-Leith (P < 2T) and aridity zone (P < 3T) in function of length of drought period or aridity period was made on basis of the analysis of the means from 27 weather station. The greatest correlation was found between the numbers of drought (aridity) days and the annual mean precipitation or station (r = -0.82). The maxi­mum number or days with drought is registered in the regions with precipitations smaller that 400 mm /year and is great that 50 day or drought and 150 day of aridity. and the minimum in the regions with Pma greater that 600 mm /years. Practically in these regions the drought is missing and the num­ber of aridity days is lower than 50 days/year. The multiple regression between number of drought days (aridity) and the geographic (altitude, latitude, longitude) and climate parameters (Tma, Pma) were established. Nu = 245 - 0.015AIt - 3,52Lat + 0,67Long - 0,37Pma + 1 0,6 Tma (R multiple = 0,88; R2 = 0,78); Ns = 102,4 - 0,15Alt - 0,034Lat + 1,92Long - 0,36Pm + 13,89 Tma (R multiple = 0,915; R2 = 0,838). The multiple correlation coefficients calculated have very significant values. This permit the graph­ical representation or number of drought days (arid­ity) in relation with 2-5 geographical parameters using geostatistical analysis.

A new method is used for evaluation of the stability of tree against the wind and to testing the theoretical stability models. The base principle of the uniform couple method is the relative identical environment conditions (site, stand and airflow) by using a couple of one damaged tree and two undamaged trees (the most close). Using the index statistical method it was possible to evaluate the direction of influences of the biometrical and qualitative tree parameters. Height and the ratio between height and diameter of the damaged tree were higher than the same parameters of undamaged trees in 73 % and 83 % of the paars, respectively. The influence of defects, especially the root decay, is the most important in the stability of tree against the wind. Over 50 % of damaged tree have defects. The method of uniform couple is an alternative to destructive methods for testing, in site condition, by mechanical methods, the stability of tree and to validate the theoretical models.

This paper presents a likehood model for estimating the risk of windthrow by extreme value analysis. We use the Gumbel model for modelling the catastrophic windthrow at the European level through that we can estimate the probability to appear wind damage with k intensity in a t time period. The return period of a wind damage with an intensity above 1 million m 3 is 3.6 years, and above 10 million m3 is 8.5 years