Articles containing the keyword 'recovery'

Postfire recovery of species diversity (including a number of species, entropy of species relative coverage (Shannon index of species diversity) was studied in lichen and green moss site types of Scots pine (Pinus sylvestris L.) forests in the central part of the Kola Peninsula. The results obtained indicate the difference in the dynamics of characteristics of biodiversity of forest components during postfire recovery. The stabilization of separate components of forest community varies in time from 5–15 to 120–140 years after the fire. Characteristics of the dwarf shrub and herb stratum recovered and stabilized 5–15 years after fire, while the complete stabilization of characteristics of moss-lichen cover is observed in community with fire ages of 90–140 years. Species richness of tree stratum recovered 120–140 years after fire. Time of complete stabilization of species richness of the community was estimated 120–140 years after fire. The size of the area over which characteristics of the biodiversity were estimated effected the mean values and, in most cases, the character of variation of studied characteristics. Over an area of 1 x 1 m dynamics of characteristics of species diversity coincide in forests of the studied types. Regardless of forest type within the area of 100 m² species richness recovered 30 years after the fire (i.e. 3–5 times earlier than the establishment of the complete stabilization of the forest structure). That means that floristic composition of the forest remained unchanged from 30 to 210 years after the fire.

• Gorshkov, E-mail: vg@mm.unknown
• Bakkal, E-mail: ib@mm.unknown

Investigations carried out in the Kola peninsula (northern taiga) and in the South-western part of Western Siberia (southern taiga and forest-steppe) revealed identical course of the postfire restoration process of forest litter thickness in Scots pine (Pinus sylvestris L.) forests. Despite the differences in mean annual temperature (2°C) and other climatic characteristics the recovery time for thickness of forest litter in both regions amounts to 90–100 years after fire in pine forests of lichen site type and 120–140 years – in green moss type; the thickness of forest litter therewith corresponds 3–4 cm and 7–8 cm respectively. That mean that within the natural borders of pine forests, communities of a specific type possess uniform characteristics of restoration. On the basis of empirical data, it appears that the predicted increase of mean annual temperature of earth surface by (2°C) will not bring changes into the character of postfire recovery of forest litter thickness. It was shown that during the period of the recovery, which spans about 90 years after fire in pine forests of lichen and green moss-lichen site types and 140 years in ones of green moss site types, the rate of increasing of carbon store in the forest litter averaged 0.6 t ha^-1 year^-1, 0.1 t ha^-1 year^-1 and 0.2 t ha^-1 year^-1, respectively.

• Gorshkov, E-mail: vg@mm.unknown
• Bakkal, E-mail: ib@mm.unknown
• Stavrova, E-mail: ns@mm.unknown

Certain biocides used in production of tree nursery stock exterminate undesirable organisms but cause an abnormal growth stimulation of plants. The reforestation material has decreased survival potential because of high degree of succulence, top:root and height:diameter ratios, and low specific gravity and root surface area. Some fumigants impede mycorrhizae development and arrest phosphorus uptake. Recovery of growth potential was achieved by aluminium sulphate and/or fermented compost inoculated with mycorrhiza-forming fungi.

The PDF includes a summary in Finnish.

• Iyer, E-mail: ji@mm.unknown
• Chesters, E-mail: gc@mm.unknown
• Wilde, E-mail: sw@mm.unknown

The present paper is a preliminary report of a project designed to determine the order of profitability of various forest improvement measures – seeding and planting, drainage, and fertilization – in various types of stands and in different parts of the country on drained peatlands. Sample plot data on the effect of draining on increment was derived from areas drained 28– 36 years ago. The study was carried out in the southern half of Finland.

The observations on increment changes are based on two measurements of the sample stands 12 years apart. Supplementary calculations indicate that the stands on drained peatland, depending on site quality and tree species, have either continued to grow like mineral-soil sites of similar fertility or have somewhat increased their growth rate.

The effect of draining intensity was studied using strip measurements. It was found that both the total amount of wood produced (current stand + cutting removal + natural removal) and the current annual volume increment for the 5-year period systematically decrease as the ditch interval increases. The decrease is, however, relatively slight. In Eriophorum vaginatum pine swamps, the total amount of wood produced and the increment show a decrease of ca. 20% with an increase in ditch interval from 20 to 60 metres. In other sites, the decrease is ca. 5-10%

It can be concluded that if the increase in ditch interval do not result in considerably poorer timber assortment distributions than indicates by stand production and increment, it is profitable to pan for a relatively large ditch interval and a slightly smaller than maximum wood production. Supplementary data and check calculations may cause some changes in these preliminary results.

The PDF includes a summary in English.

• Seppälä, E-mail: ks@mm.unknown

Hybrid aspen (Populus tremula L. × P. tremuloides Michx.) is known with outstanding growth rate and some favourable wood characteristics, but models for stand management have not yet been prepared in northern Europe. This study introduces methods and models to predict tree dimensions, diameter at breast height (dbh) and tree height for a hybrid aspen plantation using data from repeatedly measured permanent sample plots established in clonal plantations in southern Finland. Dbh distributions using parameter recovery method for the Weibull function was used with Näslund’s height curve to model tree heights. According to the goodness-of-fit statistics of Kolmogorov-Smirnov and the Error Index, the arithmetic mean diameter (D) and basal area-weighted mean diameter (DG) provided more stable parameter recovery for the Weibull distribution than the median diameter (DM) and basal area-weighted median diameter (DGM), while DG showed the best overall fit. Thus, Näslund’s height curve was modelled using DG with Lorey’s height (HG), age, basal area (BA), and tree dbh (Model 1). Also, Model 2 was tested using all predictors of Model 1 with the number of trees per ha (TPH). All predictors were shown to be significant in both Models, showing slightly different behaviour. Model 1 was sensitive to the mean characteristics, DG and HG, while Model 2 was sensitive to stand density, including both BA and TPH as predictors. Model 1 was considered more reasonable to apply based on our results. Consequently, the parameter recovery method using DG and Näslund’s models were applicable for predicting tree diameter and height.

• Lee, Natural Resources Institute Finland (Luke), Natural resources, Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0000-0003-1586-9385 E-mail: daesung.lee@luke.fi
• Siipilehto, Natural Resources Institute Finland (Luke), Natural resources, Latokartanonkaari 9, FI-00790 Helsinki, Finland E-mail: jouni.siipilehto@luke.fi
• Hynynen, Natural Resources Institute Finland (Luke), Natural resources, Vipusenkuja 5, FI-57200 Savonlinna, Finland https://orcid.org/0000-0002-9132-8612 E-mail: jari.hynynen@luke.fi

Detailed pre-harvest information about the volumes and properties of growing stocks is needed for increased precision in wood procurement planning for just-in-time wood deliveries by cut-to-length (CTL) harvesters. In the study, the non-parametric Most Similar Neighbour (MSN) methodology was evaluated for predicting external quality of Scots pine and Norway spruce, expressed as stem sections fulfilling the saw log dimension and quality requirements of Finnish forest industry, as they affect the recovery of timber assortments and the value of a pre-harvest stand. Effects of external tree quality were evaluated using saw log recovery and saw log reduction caused by stem defects, as well as total timber value (€) and average unit value (€ m^–3) in a stand. Root mean square error (RMSE) of saw log recovery and reduction were 9.12 percentile points (pp) for Scots pine and 6.38 pp for Norway spruce stands. In the unit value considerations, the predictions compared with measurements resulted in the RMSE of 3.50 € m^–3 and the bias of 0.58 € m^–3 in Scots pine stands and 2.60 € m^–3, and 0.35 € m^–3 in Norway spruce stands, respectively. The presented MSN based approach together with the utilization of the external stem quality database included in the ARVO software could provide dimension and external quality predictions usable for pre-harvest assessment of timber stock at a stand level. This prediction methodology is usable especially in analyses where timber assortment recoveries, values and unit prices are compared when different bucking objectives are used.

• Malinen, University of Eastern Finland, School of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: jukka.malinen@uef.fi
• Kilpeläinen, Natural Resources Institute Finland (Luke), Production systems, Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: harri.kilpelainen@luke.fi
• Verkasalo, Natural Resources Institute Finland (Luke), Production systems, Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: erkki.verkasalo@luke.fi

Tree bucking, defined as the process in which a stem is segmented into shorter logs of varying lengths, has a significant effect on the value adding potential of a forest enterprise. Because of its importance in terms of correct product and length combinations, improper bucking can lead to financial losses. In this study, two treatments (OFF: quality bucking performed by the operator while using hot keys and ON: automatic bucking using the optimized suggestions from the harvester on-board computer; OBC) were tested in a Norway spruce (Picea abies [L.] Karst.) dominated stand located in Germany. Both treatments had the aim to maximize the value of a stem. The research took place in an 80-year old spruce and beech stand under a regenerative cutting. Fully-mechanized harvesting was performed with an 8-wheel Ponsse Bear single-grip harvester equipped with a H8 harvesting head. Results indicated that the product recovery of the two treatments differed by 4% in undamaged trees (no broken tree-tops or stems) to the benefit of manual bucking. However, the revenue of trees subjected to optimized bucking were up to 4% higher (in average 3%) than those of the manual bucking once expressed on a per cubic meter basis. Moreover, the harvesting productivity of the ON treatment was at the maximum 17% higher compared to the OFF treatment. Based on the results from this case study, the use of an optimization software in Norway spruce dominated stands with the aim to maximize the value of single stems showed promising results.

• Labelle, Assistant Professorship of Forest Operations, Department of Ecology and Ecosystem Management, Technical University of Munich, Hans-Carl-von-Carlowitz-Platz 2, D-85354 Freising, Germany E-mail: eric.labelle@tum.de
• Huß, Assistant Professorship of Forest Operations, Department of Ecology and Ecosystem Management, Technical University of Munich, Hans-Carl-von-Carlowitz-Platz 2, D-85354 Freising, Germany E-mail: linus.huss@gmx.de

Accurate timber assortment information is required before cuttings to optimize wood allocation and logging activities. Timber assortments can be derived from diameter-height distribution that is most often predicted from the stand characteristics provided by forest inventory. The aim of this study was to assess and compare the accuracy of three different pre-harvest inventory methods in predicting the structure of mainly Scots pine-dominated, clear-cut stands. The investigated methods were an area-based approach (ABA) based on airborne laser scanning data, the smartphone-based forest inventory Trestima app and the more conventional pre-harvest inventory method called EMO. The estimates of diameter-height distributions based on each method were compared to accurate tree taper data measured and registered by the harvester’s measurement systems during the final cut. According to our results, grid-level ABA and Trestima were generally the most accurate methods for predicting diameter-height distribution. ABA provides predictions for systematic 16 m × 16 m grids from which stand-wise characteristics are aggregated. In order to enable multimodal stand-wise distributions, distributions must be predicted for each grid cell and then aggregated for the stand level, instead of predicting a distribution from the aggregated stand-level characteristics. Trestima required a sufficient sample for reliable results. EMO provided accurate results for the dominating Scots pine but, it could not capture minor admixtures. ABA seemed rather trustworthy in predicting stand characteristics and diameter distribution of standing trees prior to harvesting. Therefore, if up-to-date ABA information is available, only limited benefits can be obtained from stand-specific inventory using Trestima or EMO in mature pine or spruce-dominated forests.

• Siipilehto, Natural Research Institute Finland (Luke), Management and Production of Renewable Resources, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: jouni.siipilehto@luke.fi
• Lindeman,  Natural Research Institute Finland, Green Technology, Kaironiementie 15, 39700 Parkano E-mail: harri.lindeman@luke.fi
• Vastaranta, University of Helsinki, Department of Forest Sciences, P.O. Box 62 (Viikinkaari 11), FI-00014 University of Helsinki E-mail: mikko.vastaranta@helsinki.fi
• Yu, Finnish Geospatial Research Institute (FGI), Department of Remote Sensing and Photogrammetry, National Land Survey of Finland, P.O. Box 15 (Geodeetinrinne 2), FI-02431, Masala, Finland E-mail: xiaowei.yu@maanmittauslaitos.fi
• Uusitalo,  Natural Research Institute Finland, Green Technology, Kaironiementie 15, 39700 Parkano E-mail: jori.uusitalo@luke.fi

• Tikkanen, Department of Biology, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland (Current: School of Forest Sciences, University of Eastern Finland, P.O. Box 111, FI-80101 Joensuu, Finland) & Interdisciplinary Research and Educational Center of Cross-border Communication CARELICA, Institute of History, Political and Social Sciences, Petrozavodsk State University, 33 Lenin Prospectus, 185910 Petrozavodsk, Republic of Karelia, Russia E-mail: Olli-Pekka.Tikkanen@uef.fi
• Chernyakova, Interdisciplinary Research and Educational Center of Cross-border Communication CARELICA, Institute of History, Political and Social Sciences, Petrozavodsk State University, 33 Lenin Prospectus, 185910 Petrozavodsk, Republic of Karelia, Russia E-mail: irina.chernyakova@onego.ru

• Siipilehto, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: jouni.siipilehto@metla.fi
• Mehtätalo, University of Eastern Finland, School of Computing, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: lauri.mehtatalo@uef.fi

• Kilpeläinen, Finnish Forest Research Institute, Eastern Finland Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: hk@nn.fi
• Lindblad, Finnish Forest Research Institute, Eastern Finland Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jl@nn.fi
• Heräjärvi, Finnish Forest Research Institute, Eastern Finland Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: henrik.herajarvi@metla.fi
• Verkasalo, Finnish Forest Research Institute, Eastern Finland Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: ev@nn.fi

• Spinelli, CNR/IVALSA, Via Madonna del Piano - Palazzo F, I-50019 Sesto Fiorentino (FI), Italy E-mail: spinelli@ivalsa.cnr.it
• Nati, CNR/IVALSA, Via Madonna del Piano - Palazzo F, I-50019 Sesto Fiorentino (FI), Italy E-mail: cn@nn.it
• Magagnotti, CNR/IVALSA, Via Madonna del Piano - Palazzo F, I-50019 Sesto Fiorentino (FI), Italy E-mail: nm@nn.it

• Saarsalmi, The Finnish Forest Research Institute, Vantaa Research Centre, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: anna.saarsalmi@metla.fi
• Tamminen, The Finnish Forest Research Institute, Vantaa Research Centre, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: pt@nn.fi