Biological Sciences Database
Mapping total nitrogen in ash after a wildland fire: a microplot analysisItem type:Publication, [Bendrojo azoto pelenuose po gaisro teritorinis pasiskirstymas: mažos teritorijos analizė]research article[2010][S4][N012,T004][9]; ;Úbeda, XavierBaltrėnaitė-Gedienė, EditaEkologija = Ecology / Lietuvos mokslų akademija, Gamtos tyrimų centras. Vilnius : Lietuvos mokslų akademijos leidykla, 2010, vol. 56, no. 3-4., p. 144-152Nitrogen (N), due its low temperature volatilization, is one of the elements most vulnerable to fire. This effect depends on fire severity, which varies depending on biophysical conditions which can be heterogeneous across the landscape. Hence, fire effects on N can be variable. The aim of this study was to establish the ash total nitrogen (TN) spatial variability in a microplot designed in a burned area, and to test several methods in order to identify the most accurate one for interpolating the variable. In total, we selected four deterministic interpolation methods – inverse distance to a weight (IDW), with the weight of 1, 2, 3, 4 and 5, local polynomial (LP), with the power of 1 and 2, global polynomial (GP), radial basis functions (RBF) – spline with tension (SPT), completely regularized spline (CRS), multiquadratic (MTQ), inverse multiquadratic (IMTQ) and thin plate spline (TPS) – and two geostatistical methods: ordinary kriging (OK) and simple kriging (SK). In total, we tested 15 techniques. Ash TN was negatively related to fire severity showed a good spatial structure across the plot. The linear model was the best, which means that the variability of ash TN content increased in all the area of interest. The highest concentration of TN was observed in the northeast part of the plot and the lowest in the Southwest. From all test methods, MTQ was most accurate, and IDW5 was the worst predictor. In general, RBF and the geostatistical methods were most precise and IDW was less accurate, which means that ash TN distribution has some specific features and does not exhibit a small-scale variation. The distribution of the variable depends on species distribution, temperature and probably on vegetation moisture during fire evolution.
10 Assessment of sustainable development in transitionItem type:Publication, [Darnaus vystymosi vertinimas pereinamosios ekonomikos sąlygomis]research article[2007][S4][S004,N012,T004][7] ;Burinskienė, MarijaEkologija. Vilnius : Lietuvos mokslų akademijos leidykla, 2007, Vol. 53, supplement., p. 27-33The aim of the article is to present the priorities of the EU sustainable development strategy and a methodological framework for monitoring the implementation of the EU sustainable development targets relevant to the energy sector. These targets are interrelated and can be addressed using a framework connecting the indicators with policies and measures aiming to achieve specific targets established by indicators and to show the interlinkages among the specific indicators and the interaction between policies and measures targeting specific indicators. The energy sector is a specific scope of sustainable development issues and is integrated in almost all priority areas of the EU sustainable development strategy: climate change mitigation and clean energy, sustainable transport, sustainable consumption and sustainable production, conservation and management of natural resources, public health, poverty and other social problems.
4 Acoustic signalling of the Great Black-headed Gull Larus ichthyaetus pallasItem type:Publication, research article[1988][S4][N012][8]; Buzun, ValerieBioacoustics : the international journal of animal sound and its recording / editor Brian Lewis, City of London Polytechnic. [Bicester] : A B Academic Publishers, 1988, vol. 1, no. 1., p. 49-564