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Sci Total Environ ; 698: 134129, 2020 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-31499344


Forest health status is negatively influenced by climate change, air pollution and other disturbances. Extreme droughts reduce stand productivity, increase vulnerability to pests, and can even provoke mortality. Growth dynamics at tree and forest stand levels are considered the main indicators of stability and productivity in forest ecosystem structures. The main climate drivers for tree growth were identified using basal area increment (BAI) as a synthetic indicator. BAI chronologies were obtained from increment cores for 1960-2012 period. Six species were analysed in an attempt to identify their growth limiting factors. For the most important oak species in Romania, resilience components were computed in order to analyse their response to drought events. Moreover, growth dynamics were analysed for two species in mixed and monoculture forests. The results suggest that - in comparison to Picea abies and Fagus sylvatica, the sensitivity of Quercus spp. is much higher (0.3-0.47). Oakspecies situated in the most drought-affected areas are sensitive to rainfall values from the previous autumn, current spring, and early summer, with April monthly values having the most significant effect on BAI increment (r = 0.47*) The most sensitive species to drought is Q. cerris and Q. frainetto. Their BAI reduction during drought is >50% compared with the BAI values before the drought period. The recovery capacity of tree growth following drought events is lower for Q. robur and Q. petraea and higher for Q. cerris and Q. frainetto. The mixed forest stands have not showed a constant higher resistance to drought.

Mudança Climática , Monitoramento Ambiental , Agricultura Florestal , Florestas , Árvores , Secas , Ecossistema , Fagus , Quercus , Romênia , Estações do Ano
Sci Total Environ ; 698: 134074, 2020 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-31505359


This study aims to investigate the combined use of two types of remote sensing data - ALS derived and digital aerial photogrammetry data (based on imagery collected by airborne UAV sensors) - along with intensive field measurements for extracting and predicting tree and stand parameters in even-aged mixed forests. The study is located in South West Romania and analyzes data collected from mixed-species plots. The main tree species within each plot are Norway spruce (Picea abies L. Karst.) and Beech (Fagus sylvatica L.). The ALS data were used to extract the digital terrain model (DTM), digital surface model (DSM) and normalized canopy height model (CHM). Object-Based Image Analysis (OBIA) classification was performed to automatically detect and separate the main tree species. A local filtering algorithm with a canopy-height based variable window size was applied to identify the position, height and crown diameter of the main tree species within each plot. The filter was separately applied for each of the plots and for the areas covered with Norway spruce and beech trees, respectively (i.e. as resulted from OBIA classification). The dbh was predicted based on ALS data by statistical Monte Carlo simulations and a linear regression model that relates field dbh for each tree species with their corresponding ALS-derived tree height and crown diameter. The overall RMSE for each of the tree species within all the plots was 5.8 cm for the Norway spruce trees, respectively 5.9 cm for the beech trees. The results indicate a higher individual tree detection rate and subsequently a more precise estimation of dendrometric parameters for Norway spruce compared to beech trees located in spruce-beech even-aged mixed stands. Further investigations are required, particularly in the case of choosing the best method for individual tree detection of beech trees located in temperate even-aged mixed stands.

Monitoramento Ambiental , Tecnologia de Sensoriamento Remoto , Árvores , Fagus , Florestas , Lasers , Luz , Picea , Romênia
Sci Total Environ ; 689: 1104-1114, 2019 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-31466150


Natural and anthropogenic disturbances pose a significant threat to forest condition. Continuous, reliable and accurate forest monitoring systems are needed to provide early warning of potential declines in forest condition. To address that need, state-of-the-art simulations models were used to evaluate the utility of C-, L- and P-band synthetic aperture radar (SAR) sensors within an integrated Earth-Observation monitoring system for beech, oak and coniferous forests in Romania. The electromagnetic simulations showed differentiated sensitivity to vegetation water content, leaf area index, and forest disturbance depending on SAR wavelength and forest structure. C-band data was largely influenced by foliage volume and therefore may be useful for monitoring defoliation. Changes in water content modulated the C-band signal by <1 dB which may be insufficient for a meaningful retrieval of drought effects on forest. C-band sensitivity to significant clear-cuts was rather low (1.5 dB). More subtle effects such as selective logging or thinning may not be easily detected using C- or L-band data with the longer P-band needed for retrieving small intensity forest disturbances. Overall, the simulations emphasize that additional effort is needed to overcome current limitations arising from the use of a single frequency, acquisition time and geometry by tapping the advantages of dense time series, and by combining acquisitions from active and passive sensors. The simulation results may be applicable to forests outside of Romania since the forests types used in the study have similar morphological characteristics to forests elsewhere in Europe.

Monitoramento Ambiental/métodos , Florestas , Radar , Romênia