Age structure and productivity of conifer stands in Latvia | Latvijas skujkoku audžu vecumstruktūra un ražība
2009
Libiete, Z., Latvian State Forest Research Inst. Silava, Salaspils (Latvia) | Jansons, J., Latvian State Forest Research Inst. Silava, Salaspils (Latvia) | Zalitis, T., Latvian State Forest Research Inst. Silava, Salaspils (Latvia)
According to the statistics, forest stands dominated by conifers take up 46% of the forest area. Pine and spruce are also economically most important tree species in Latvia. In Latvia, there is a lack of extensive research regarding the productivity and age 1 LVMI structure of conifers, mainly due to the costly and complex collecting of the necessary data set. National forest inventory (Forest resource monitoring) launched in 2004 provides statistically credible and up-to-date information about the situation in all Latvian forests, including information about current annual volume increment. In this research the productivity of pine and spruce stands of all age classes was analyzed, and the impact of regional localization and growing conditions on the stand productivity was evaluated. Study material was collected in 2004, 2005, 2006 and 2007 in the frames of National forest inventory. Data about 1228 sample plots dominated by pine and 572 sample plots dominated by spruce was selected for the analysis. The productivity of the stands was analyzed in 10-year age classes, as well as in four age groups: young, middle-aged, pre-mature, mature and over-mature stands. The stand productivity was characterized by total standing volume of the dominant stand (m**3haE-1) and current annual volume increment of pine or spruce of the dominant stand, respectively (m**3haE-1 a year). The productivity was compared between two regions – Western Latvia and Eastern Latvia, and among five types of growing conditions – forests on dry mineral soils, forests on wet mineral soils, forests on wet peat soils, forests on drained mineral soils and forests on drained peat soils. T-test, one-way ANOVA and linear regression analysis were applied in this study. It was found out that current mean annual volume increment in pine stands culminates at the age of 21-50 years but in the spruce stands – at the age of 21-40 years. In almost all age groups both the standing volume of the dominant stand and current annual volume increment of dominant tree species was found to be greater in spruce stands. In all age groups of both pine and spruce stands the impact of the annual volume increment on the standing volume was statistically significant (į=0.05); however, the linear correlation was considerably more pronounced in young stands (R=0.87 for pine stands and R=0.63 for spruce stands). It points to the necessity of creating favourable conditions for the formation of high current annual volume increment exactly in this age group, mainly emphasizing silvicultural methods which aim at reducing mutual competition among the trees – the choice of appropriate planting density and early thinnings. Significant regional volume differences were detected only in pre-mature (p=0.043) and mature and over-mature (p=0.036) pine stands; in both cases the mean standing volume was greater in Western Latvia. Significant regional differences of the current annual volume increment were detected in young pine stands (p=0.044), middle aged spruce stands (p=0.000), pre-mature pine and spruce stands (p=0.021 and p=0.020, respectively) and mature and over-mature pine stands (p=0.027). The current annual volume increment of young pine stands in the Western region was greater than that in the Eastern region. The opposite was true for the other analyzed groups. The productivity of pine and spruce stands on dry mineral soils and drained mineral soils on average is the highest, while pine and spruce stands of low productivity are most oft en found on wet mineral soils and wet peat soils. The results of this study provide detailed information about the productivity of pine and spruce stands in connection with the stand age, regional localization and growing conditions. The data of National forest inventory presents opportunity to perform analysis in a relatively short time and obtain valuable and up-to-date knowledge regarding different forest stand parameters and their mutual connection. However, the specific character and limitations of NFI data must be taken into account. The sample plots are established in a regular grid according to exact geographic coordinates, therefore they may not always give the best characteristics of a particular forest stand, thus decreasing the representatively of the data. Moreover, only the first cycle of the NFI in Latvia is complete at present; therefore the information is for the time being static and unsuitable for making any development forecasts. The importance of permanent, regularly re-measured sample plots cannot be denied in this context.
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