REGIONAL DIFFERENCES OF FINAL FELLING SAWLOG OUTCOME IN LATVIA

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1 FORESTRY AND WOOD PROCESSING REGIONAL DIFFERENCES OF FINAL FELLING Latvia University of Agriculture Abstract Pine, spruce and birch stem s quality is different in regions of Latvia, but the differences are not included in the tables and models of assortment outcome. Therefore, it is not possible to predict accurately the outcome of round wood assortments. The aim of the research was to evaluate the regional differences of final felling sawlog outcome for Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.) and birch (Betula spp.) in Latvia and to set the regions with a different sawlog outcome. Data from 1645 final felling areas was used for pine, 1202 for spruce and 1531 for birch from the years Firstly, the sawlog outcome of 97 territorial units was set by using the data of the final felling areas sawlog outcome of pine, spruce and birch. Secondly, territorial units with a similar sawlog outcome were consolidated in regions. The smallest regional difference of sawlog outcome was found for spruce (9.4%), slightly larger for pine (10.5%) and the largest difference for birch (16.2%). Three regions with the different sawlog outcome were found for Scot pine, six for Norway spruce and seven for birch. Several spruces and birch regions have similar sawlog outcome but those do not have borders. They are between regions with higher or lower sawlog outcome. Sawlog outcome of neighbouring regions differ for at least 4 5%. Key words: sawlog outcome, region, Pinus sylvestris, Picea abies, Betula spp. Introduction In various studies of pine, spruce and birch stems quality it was found out that the quality differs in the regions of Latvia, but regional quality differences are not included in the round wood assortment tables and models. Therefore, it is not possible to predict accurately the outcome of round wood assortments in the various regions of Latvia. The regional differences of pine stems quality are being the most widely studied, both, comparing the final felling stands and comparing stands in breeding trials. Comparing the final felling age pine stands for high quality sawlog outcome estimation, it was found out that the stands in north east Latvia are better than in north west Latvia (Zālītis and Špalte, 1998). A similar study was also realized later and researchers found out that stands of east have higher branch-free stem sections than in the south of Latvia (Zālītis and Špalte, 2000). 28 years old stands were compared in breeding trials in four Latvian regions (west, central, south-east and north-east). The researcher found out that stands of the west have less straight stems and have higher branch thickness, but stands of the northeast have more straight stems and less thick branches (Baumanis et al., 2001). Partially similar knowledge was acquired in following breeding trials. Length of the stems branch-free section and quality, branch angle and branch thickness was compared in 21 pine stands. It was found out that the east populations are better than west populations, only stem straightness does not differ between populations (Neimane, 2009a; Neimane et al., 2009b). 33 final felling age spruce stands were compared for estimation of spruce regional quality differences in two regions. Researchers found out that the outcome of the high quality sawlog does not differ between the west and the east parts of Latvia (Špalte and Zālītis, 2003). Regional quality differences of birch stems were investigated in other study with a similar principle. The high quality veneer logs outcome was compared in birch stands. The study was based on regression function prepared from 760 measured birch stems. High quality veneer logs outcome of birch stands was set with regression function (factors: the diameter and height). Forest inventory data of 257 forest districts of Latvia was exploited. Researchers found out that there are quality differences in the regions of Latvia. Stands with lower veneer logs outcome mainly are located in the western part of Latvia (Zālītis et al., 2002). The birch stands quality regional differences were evaluated with the same methodology by using the National forest inventory data. The researcher found out that there is a significant difference in the quality between the east Latvia and the west Latvia. Lower veneer logs outcome is in the western part of Latvia (Zālītis, 2008). In the study of pine, spruce and birch stems surface it was also found out that there are regional differences. However, the amount of data is not enough for general conclusions (Dubrovskis et al., 2013). Different results of pine, spruce and birch steams quality were found using the National forest inventory data. To characterize the quality, the branch-free section of stem was used. In the study it was found out that the branch-free section of stems of pine, spruces and birch does not differ between western, eastern and southern regions (Lībiete, 2006). Conclusive findings were not found about regional differences of stems quality and round wood assortments outcome. In addition, different breakdown of regions were applied in studies. 70 RESEARCH FOR RURAL DEVELOPMENT 2014, VOLUME 2

2 REGIONAL DIFFERENCES OF FINAL FELLING Nowadays the round wood production data is stored in databases that open up the opportunity to use many of the felling area data on a wide territory. The regional differences of round wood assortments outcome can be found out by using the whole Latvia s territory data of final felling round wood production. The aim of the research was to evaluate the regional differences of final felling sawlog outcome for Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.) and birch (Betula spp.) and set the regions with a different sawlog outcome in Latvia. Materials and Methods The study was carried out in the year Several years data of round wood productions was used. The territory of Latvia was divided into 97 territorial units and there was calculated average sawlog outcome of each species. Territorial areas with similar sawlog outcome were consolidated. Materials for this study were taken from JSC Latvijas valsts meži years final felling areas throughout the whole territory of Latvia. For each final felling area the data was collected; firstly, forest inventory data, secondly, round wood assortments or stands volume and thirdly, the structure of each tree species. The largest part of felling areas data of round wood assortments was collected from harvester production files. During tree felling, harvesters collect data about each felled tree: species, number of trees, produced round wood assortments volume and assortment type: firewood, pulpwood, sawlogs (2 8 diameter and quality classes), veneer logs. For simplification the birch veneer logs were combined with the birch sawlogs. Minimal diameter of birch veneer logs were changed in the middle of the year In order to prevent the birch veneer logs outcome differences over the years, data of the year 2011 was excluded from the calculations. The proportion of the year 2010 birch veneer logs outcome was increased by 3.74%. The percentage was obtained from relationship between the year 2010 and 2012 proportion of veneer logs at the same age, the same site index and the same forest type stands. Pine, spruce and birch sawlog outcome was calculated as the proportion of sawlog volume of each species from the total round wood assortment volume of each species. In pine and spruce sawlog category there was the sawlog with the diameter larger than 10 cm (not included low quality sawlog - sleepers) included, in the birch sawlog category there were birch veneer logs and sawlog with the diameter larger than 12 cm included. Round wood assortment volume assessment from stands measured by callipers were used for stands, which did not have production files of harvesters. The distribution of round wood assortments was not available in stands measured by callipers. But, each tree had been included into one of the five groups: thick, medium and small sawlog, pulpwood and firewood. The sawlog outcome was calculated from the thick sawlog volume multiplied by coefficients: pine 0.86, spruce 0.84 and birch Coefficient values were obtained by calculating the difference between the sawlog volume and round wood assortment volume of thick sawlog at the same age, the same site index and the same forest type stands. It should be noted that it is impossible to find the correlation between the two volumes; therefore, for each species there was calculated one the average coefficient. Forest type groups, site index and ages of each species first stage trees were stated from forest inventory data in the felling year. Felling area can be created from multiple stands, which may include stands with different age, forest type, sit index. So, the problem is setting average values. Therefore, the felling areas that are created in one stand or in part of one stand were used in the research. Site index was set by the dominant tree species. The felling areas larger than 1ha were used to reduce possible risks that the whole stand could not be included in the felling area. Additionally, the tress of first storey and tress of second storey are not possible to divide (sawlog outcome from second storey trees is lower) for felling areas felled by harvesters. Therefore, felling areas with minimum 50 m 3 ha -1 of pine or birch round wood assortments, for spruce 100 m 3 ha -1 of spruce round wood assortments, were chosen for pine and birch sawlog outcome calculations. Regional differences of sawlog outcome by using species dominant site index and forest type were set. The data of each species was supplemented with data of those site indexes and forest types which did not differ from the characteristic values of the species. The same principle was used to select the age range. Data used for study is showed in Table 1. The smallest territorial unit of JSC Latvijas valsts meži a block district was used in order to determine the regional differences of sawlog outcome. The number of block district is 97 with the average size of ha, and it covers practically the whole territory of Latvia. The average sawlog outcome and representativeness of sample were calculated for each species, for each block district. Then, block districts were consolidated (approximately ten iterations) in regions with a similar sawlog outcome. After each consolidation sawlog outcome and representativeness of sample were recalculated for regions of consolidated block districts. Block districts were combined in regions until the sawlog outcome of each species between regions statistically differ significantly, it was determined by T-test. RESEARCH FOR RURAL DEVELOPMENT 2014, VOLUME 2 71

3 REGIONAL DIFFERENCES OF FINAL FELLING Table 1 Characteristics of species site index, groups of forest types and number of felling units used for study Indicator Pine Spruce Birch Sit index I un II I a, I un II I a un I Age, years Groups of forest types Dry, wet mineral soils, drained mineral soils All Dry, drained mineral soils Number of felling areas At first, neighbouring block districts were combined with less than 3 4% differences of sawlog outcome and at the least moderate representativeness of sample. Finally, block districts were consolidated (single and multiple existing together) whose representativeness of sample was poor. Individual block districts were added to the nearest group of block districts, based on assessment of territorial configuration. Several block districts existing together were consolidated gradually and consolidated with similar value groups. Finally, correlation was tested between species regional differences of the sawlog outcome by using correlation analysis. The region s average sawlog outcome was used for comparison of each block district. Results and Discussion Data of the final felling areas (measured by harvesters or callipers) was used for setting pine, spruce and birch regions with different sawlog outcome (Figure 1, 2, 3) and the regional differences of final felling sawlog outcome for pine, spruce and birch in Latvia estimated. Regions have complex geographical forms; therefore, codes were assigned to them. Three regions for pine, six for spruce and seven for birch with different sawlog outcome were found. Each pine region has a different sawlog outcome. Several spruces and birch regions have similar sawlog outcome, but those do not have borders (they are between regions with higher or lower sawlog outcome). Sawlog outcome values and coefficients of variation are shown for regions of each tree species in Table 2. The smallest regional difference of sawlog outcome was found for spruce (9.4%), slightly larger for pine (10.5%) and the largest for birch (16.2%). It should be noted that coefficient of variation of sawlog outcome for birch is 2.9 times and for spruces 1.6 times greater than the coefficient of variation of Figure 1. Scot pine (Pinus sylvestris L.) regions of final felling sawlog outcome in Latvia (regions with sawlog outcome: 70-75%, 75-80%, 80-85%, borders of Latvia s administrative units, codes of regions: P1, P2, P3). 72 RESEARCH FOR RURAL DEVELOPMENT 2014, VOLUME 2

4 REGIONAL DIFFERENCES OF FINAL FELLING Figure 2. Norway spruce (Picea abies (L.) Karst.) regions of final felling sawlog outcome in Latvia (regions with sawlog outcome: 55-60%, 60-65%, 65-70%, borders of Latvia s administrative units, codes of regions: E1, E2, E3, E4, E5, E6). Figure 3. Birch (Betula spp.) regions of final felling sawlog outcome in Latvia (regions with sawlog outcome: 45-50%, 50-55%, 60-65%, borders of Latvia s administrative units, codes of regions: B1, B2, B3, B4, B5, B6, B7). sawlog outcome for pine. This means that the birch sawlog output values are much more dispersed around the sample mean value. One of the reasons could be that Latvia has two birch species: Silver birch (Betula pendula Roth.) and Downy birch (Betula pubescens Ehrh.), but their data is not counted separately. Zālītis (2002) research confirms that the veneer log outcome from Silver birch is 47% and Downy birch 35% (Zālītis et al., 2002). For all species neighbouring sawlog outcome regions differ at least 4 5% and do not have borders between regions with similar values. The difference RESEARCH FOR RURAL DEVELOPMENT 2014, VOLUME 2 73

5 REGIONAL DIFFERENCES OF FINAL FELLING Statistics of final felling sawlog outcome regions Table 2 Species Scot pine (Pinus sylvestris L.) Norway spruce (Picea abies (L.) Karst.) Birch (Betula spp.) Regions Sawlog outcome and standard Sawlog outcome coefficients error,% of variation P ± P ± P ± Average 79.4 ± E ± E ± E ± E ± E ± E ± Average 61.2 ± B ± B ± B ± B ± B ± B ± B ± Average 51.1 ± was significant (p<0.01) between average sawlog outcome of neighbouring regions (pine P1/P2 and P1/P3; spruce E1/E2, E2/E3, E3/E5, E4/E5, E5/E6; birch B1/B2, B2/B3, B2/B4, B3/B4, B3/B7, B5/B6, B6/B7). Thus, it is an opportunity to use the regions of sawlog outcome for improvement of round wood assortment models. The study findings suggest that all tree species are equal to the general trend to the east increase the sawlog outcome. This is also confirmed by other study s findings, the worst quality of pine stands is in the south, the medium quality in the west and the highest quality is in the east (Zālītis and Špalte, 2002). It coincides with breeding researches in which it was found out that lower pine stands quality is in the west, the highest is in the east (Baumanis et al., 2001; Neimane et al., 2009b). Also, on the birch stands there are similar results of the studies that confirm that the stem quality is the worst in the western part of Latvia (Zālītis et al., 2002; Zālītis, 2008). According to Lībiete (2006), the pines, spruce and birch stem quality (branch-free sections) should not show the quality differences, but results acquired in this study show the opposite results. However, above mentioned studies assessed stems branch-free section or sawlog outcome of the highest quality, which differs from our study, used sawlog classification. The correlation between tree species regions was examined, comparing all species sawlog outcome values. Correlation between pine and spruce regions is moderate (r=0.49; p<0.05), between the birch and spruce regions is weak (r=0.21; p<0.05) and between birch and pine regions no correlation (r=0.19; p>0.05). Study results allow to conclude that coniferous trees regional differences are partially determined by similar factors, but birch regional differences are determined by different factors. In further studies the possible factors should be analysed. Conclusions 1. The outcome of the final felling sawlog for Scot pine, Norway spruce and birch differ regionally in Latvia. The smallest regional difference of sawlog outcome was found for spruce (9.4%), slightly larger for pine (10.5%) and the largest for birch (16.2%). 2. Three regions with different sawlog outcome were found for Scot pine, six for Norway spruce and seven for birch in Latvia. Several spruces and birch regions have similar sawlog outcome, but those do not have borders. They are between regions with higher or lower sawlog outcome. For all species neighbouring sawlog outcome in regions differ for at least 4 5%. Acknowledgements The author expresses appreciation to AS Latvijas valsts meži for the possibility of using the final felling round wood assortment production and forest inventory data. 74 RESEARCH FOR RURAL DEVELOPMENT 2014, VOLUME 2

6 REGIONAL DIFFERENCES OF FINAL FELLING References 1. Baumanis I., Gailis A., Liepiņš K. (2001) Latvijas priežu provinienču salīdzinājums (Comparison of Scots pine provenances in Latvia). Mežzinātne, 46, lpp. (in Latvian). 2. Dubrovskis D., Sarmulis Z., Daģis S., Zīmelis A., Šmits I., Krūmiņš M., Baltmanis R. (2013) Koku stumbra formas veidules un sortimentu iznākuma prognožu noteikšana. Zinātniskā pētījuma starpatskaite (Projection of tree stems surface form and round wood assortments outcome. Overview of research). Available at: 25 February (in Latvian). 3. Lībiete Z. (2006) Pētījums par priedes, bērza un egles audžu ražības un stumbra kvalitātes reģionālajām atšķirībām Latvijā uz meža statistiskās inventarizācijas parauglaukumu bāzes. Pārskats par Meža attīstības fonda pasūtīto pētījumu (A study of regional differences of pine, birch and spruce stands productions and stem quality in Latvia based on National forest inventory sample plots. Overview of Forest development fund financed research). Latvian State Forest Research Institute Silava, Salaspils, 45 lpp. (in Latvian). 4. Neimane U. (2009a) Geographical differences in growth and quality characters of scots pine Latvian populations. In: Gaile Z., Zvirbule-Bērziņa A., Assouline G., Špoģis K., Ciproviča I., Kaķītis A., Dumbrauskas A. (eds), Research for Rural Development 2009, Annual 15th International Scientific Conference Proceedings, Latvia University of Agriculture, Jelgava, Latvia, pp Neimane U., Veinberga I., Ruņģis D. (2009b) Parastās priedes populāciju ģeogrāfisko atšķirību fenotipiskās un ģenētiskās īpašības Latvijas teritorijā (Phenotypic and genetic aspects of geographical differences in Scots pine populations of Latvia). Mežzinātne, 53, 3 15.lpp. (in Latvian). 6. Špalte E., Zālītis P. (2003) Latvijas egļu audžu kvalitāte ciršanas vecumā (The quality of spruce stands in Latvia at the felling age). Mežzinātne, 46, lpp. (in Latvian). 7. Zālītis P., Špalte E. (1998) Latvijas priežu audžu kvalitāte ciršanas vecumā (Standing volume and stemwood quality spruce at the cutting age). Mežzinātne, 41, lpp. (in Latvian). 8. Zālītis P., Špalte E. (2000) Priežu kokaudžu krāja un stumbra koksnes kvalitāte ciršanas vecumā (Standing volume and steamwood quality of pine at the cuttinga age). Mežzinātne, 43, lpp. (in Latvian). 9. Zālītis P., Špalte E., Liepiņš K. (2002) Augstvērtīgu bērzu audžu diagnostika, ģenētisko un ekoloģisko faktoru, kā arī mežsaimniecisko pasākumu ietekmes noteikšana pēc bērzu stumbru kvalitātes rādītājiem (Diagnostics of high quality birch stands, determination of impact of genetic and ecological factors and silvicultural activities on birch steamwood quality). Mežzinātne, 45, lpp. (in Latvian). 10. Zālītis T. (2008) Kārpainā bērza (Betula pendula Roth.) augšanas gaitu un stumbra kvalitāti ietekmējošie faktori auglīgajos meža tipos Latvijā. Promocijas darba kopsavilkums. (The factors influencing the growth and stem quality of Silver birch (Betula pendula Roth.) stands on fertile site types in Latvia. Resume of the PhD paper). Latvijas Lauksaimniecības universitāte, Jelgava, 50. lpp. (in Latvian). RESEARCH FOR RURAL DEVELOPMENT 2014, VOLUME 2 75