Modeling the Radial Stem Growth of the Pine (Pinus sylvestris L.) Forests Using the Satellite-Derived NDVI and LST (MODIS/AQUA) Data

The paper considers a new approach to modeling the relationship between the increase in woody phytomass in the pine forest and satellite-derived Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) (MODIS/AQUA) data. The developed model combines the phenological and forest growth processes. For the analysis, NDVI and LST (MODIS) satellite data were used together with the measurements of tree-ring widths (TRW). NDVI data contain features of each growing season. The models include parameters of parabolic approximation of NDVI and LST time series transformed using principal component analysis. The study shows that the current rate of TRW is determined by the total values of principal components of the satellite indices over the season and the rate of tree increment in the preceding year.

Dendroindication of ecoclimatic condition in forest remediation area within Northern Steppe of Ukraine

We analyzed ring width, latewood width and earlywood width of Pinus sylvestris trees under normal and flood condition in Dnipropetrovsk region, within Northern Steppe of Ukraine. Precipitation from February to August seems to be the most stable climatic factor which influenced Scots pine growth rate and caused the difference between maximum and minimum ring width in normal conditions. Meteorological conditions were mainly associated with general ring values and earlywood width, and were less associated with latewood width values. Assessment of the effect of climatic signals on tree rings’ growth process in living and dead trees and in the normal and flood condition by analyses of correlation and response function was conducted. Average annual temperatures affected the tree growth negatively in normal conditions and tree increment positively in flood conditions. Annual precipitation was correlated positively with ring width, earlywood width series in normal conditions, but negatively with these series in flood conditions.

Evaluating the performance of semi-distance-independent competition indices in predicting the basal area growth of individual trees

Recent individual-tree growth models use either distance-dependent or distance-independent competition measures to predict tree increment. However, both measures have deficiencies: the latter because the effects of local variation in spacing are not represented, and the former because they cannot be calculated from normal inventory data for lack of spatial information. To overcome these shortcomings, the new class of semi-distance-independent competition indices was proposed. A semi-distance-independent competition index is a distance-independent competition measure that uses only the trees of a single small sample plot that includes the subject tree. Moreover, a semi-distance-independent competition index can be calculated in an analogous way to a distance-dependent competition index by using sample plot size, tree attributes, and intertree distances. However, many semi-distance-independent competition measures are based on simple tree attributes. Therefore, the objective of this study was to analyze if the semi-distance-independent competition indices explain the variation in measurements of tree increment more or less effectively than a set of classical distance-dependent competition indices. The results show that some of the semi-distance-independent competition indices explain at least as much variation in measurements of tree increment as any of the distance-dependent competition indices.