scholarly journals Quantitative and qualitative attributes of dead wood in dominated by Carpinus betulus L. forests in Kaniv Nature Reserve

2021 ◽  
pp. 42-53
Author(s):  
O. Chornobrov ◽  
V. Shevchik ◽  
I. Solomakha
Keyword(s):  
Tree Species ◽  
Dead Wood ◽  
Nature Reserve ◽  
Structural Features ◽  
Average Volume ◽  
Carpinus Betulus ◽  
Permanent Sample Plots ◽  
Norway Maple ◽  
Standing Dead ◽  
Fallen Dead Wood

The article presents the quantitative and qualitative attributes of dead wood in forests dominated by Carpinus betulus L. in Kaniv Nature Reserve. The study was conducted in 130–140-year natural common hornbeam forests on two permanent sample plots of 0.24 ha each by identifying and measuring all components of standing and lying (fallen) dead wood. It was found that wood detritus has an average volume of 39.8 m3/ha consists of standing dead trees (23.1%) and fallen dead wood (76.9%). The species composition is dominated by common hornbeam (96.5%), and the share of Norway maple (Acer platanoides L.) is low (3.5%). Wood of II (13.2 m3/ha, 33.1%) and III (12.2 m3/ha, 30.7%) classes of destruction predominates. Standing dead wood is formed by only one tree species — common hornbeam and has an average volume of 9.2 m3/ha. It is represented mainly by standing broken trees. The volume of standing dead wood is dominated by wood detritus of the II stage of decomposition (95.7%). Fallen dead wood is formed by two tree species — common hornbeam (95.4%) and Norway maple (4.6%), has an average volume of 30.6 m3/ha. It is represented by whole uprooted and broken fallen trees (trunks), fragments of fallen trees (trunks) and rough branches. Lying dead wood is represented by detritus of all five classes of decomposition, but wood of III (12.2 m3/ha, 39.9%) and IV (9.6 m3/ha, 31.4%) classes predominates. The volume of fallen dead wood is mainly formed by components with an average diameter of 10.1–30.0 cm (75.7%). The diversity of fractions and components, structural features, sizes and stages of decomposition of dead wood can be important in the formation of potential habitats and substrates for a number of species of living organisms.

scholarly journals Features of coarse woody debris volume formation in fresh sudibrova conditions in Zmiini islands tract of Kaniv Nature Reserve

2021 ◽  
pp. 102-112
Author(s):  
O. Chornobrov
Keyword(s):  
Scots Pine ◽  
Tree Species ◽  
Dead Wood ◽  
Nature Reserve ◽  
Woody Debris ◽  
Wood Volume ◽  
Dead Trees ◽  
Norway Maple ◽  
Standing Dead ◽  
Common Oak

Dead wood (woody debris) is an important component of forest ecosystems. It performs a number of ecological and environmental functions. The article studies the peculiarities of the formation of coarse wood detritus volume and its qualitative structure in forests in the conditions of fresh sudibrova of the Zmiiini Islands tract of Kaniv Nature Reserve. The study of dead wood was carried out in 140-year-old pine-oak forests of natural origin on a permanent sample plot (0.24 ha) by identifying and measuring of standing and lying deadwood components. It was found that dead wood in the forest ecosystem was formed due to the dying of trees of five species: common oak (Quercus robur L.), Scots pine (Pinus sylvestris L.), Norway maple (Acer platanoides L.), small-leaved lime (Tilia cordata Mill.) and common hornbeam (Carpinus betulus L.), and has a volume 56.3 m3·ha–1. Dead wood volume is dominated by standing dead trees — 82.1%, and the share of lying dead wood, respectively, is 17.9%. The main part of dead wood volume is formed by two tree species — common oak and Scots pine, the share of which together is 94.3%. Common oak and Scots pine is characterized by a predominance of standing dead wood, while for other tree species — lying dead wood. In general, dead wood is formed by detritus of I–IV classes of destruction, at the same time detritus of class II decomposition has a significant advantage (70.5%), recently dead wood has a much smaller share (I class, 24.8%), and other classes of destruction have insignificant shares, which together do not exceed 5.0%. No woody detritus of the last (V) class of destruction was detected. Volume of standing dead wood is 46.2 m3·ha–1, and is formed by whole and broken dead trees. In terms of species composition, common oak has a significant advantage (74.5%), Scots pine has a much smaller share (25.1%), and the share of Norway maple is insignificant (0.4%). The total standing dead wood volume is dominated by wood of class II destruction (33.0 m3·ha–1, 71.4%) compared with class I (13.2 m3·ha–1, 28.6%). Lying dead wood is represented by four classes of destruction (I–IV), however, no woody debris was found at the late (last) stage of decomposition (class V). In terms of volume, the second class of destruction has an absolute advantage (6.7 m3·ha–1, 66.3%), much less class III detritus (2.3 m3·ha–1, 22.8%). Lying dead wood of common oak is represented by all four classes of destruction, among which III (40.5%) and I (33.3%) classes predominate. Lying dead wood of other tree species is characterized by the predominance of II or III classes of destruction. The main factors in the formation of woody detritus in the pine-oak forest in the Zmiiini Islands tract could be the impact of adverse climatic conditions (long periods without precipitation in summer), which led to the weakening of individual trees and their death, gusts of wind that broke individual tree trunks, low-intensity snow breaks, and the influence of biotic factors (insects, pathogens).

scholarly journals Dead wood and mycoflora in Nature Reserve Polom, Protected Landscape Area Železné hory

2012 ◽  
Vol 50 (No. 3) ◽  
pp. 118-134
Author(s):  
L. Jankovský ◽  
J. Beránek ◽  
AVágner
Keyword(s):  
Mycorrhizal Fungi ◽  
Dead Wood ◽  
Nature Reserve ◽  
Wood Decomposition ◽  
Fomitopsis Pinicola ◽  
Permanent Sample Plots ◽  
Fomes Fomentarius ◽  
Predominant Species ◽  
Dominant Component ◽  
The Dead

Activity of fungi participating in the dead wood decomposition was studied in the Velk&yacute; Polom Nature Reserve, Protected Landscape Area Železn&eacute; hory. Two game-proof fences of an area of 0.30 ha (570 m alt.) and 0.19 ha (620 m alt.) were <br />used as permanent sample plots. In both the plots, activities were monitored of wood-destroying fungi in 126.82 m<sup>3</sup> dead wood, 104.05 m<sup>3 </sup>of which were in beech. After conversion to an area, the volume amounts to 258.82 m<sup>3</sup> per ha. In the whole reserve, almost 220 species of macromycetes were recorded in the course of a mycological survey. Wood-destroying fungi are the dominant component of mycoflora representing more than 50% identified taxa of in the period under study. The proportion of mycorrhizal fungi amounted to 14%. A series of macromycetes considered to be saprophytes is bound to products of wood decomposition. Fomes fomentarius (L.) Fr., Fomitopsis pinicola (Sowerby) P. Karst., Ustulina deusta (Fr.) Petrak, Hypoxylon fragiforme (Pers.) Kickx, Ganoderma lipsiense (Batsch) Atk. and the genus Armillaria were the predominant species of wood-decaying fungi. As for rare macro-fungi, it is possible to mention Ascotremella faginea (Peck) Seaver, Stropharia albocrenulata (Peck) Kreisel and Tricholomopsis decora (Fr.) Singer.

scholarly journals Inventory of dead wood in the Kněhyně-Čertův mlýn National Nature Reserve, the Moravian-Silesian Beskids

2012 ◽  
Vol 50 (No. 4) ◽  
pp. 171-180 ◽  
Author(s):  
L. Jankovský ◽  
D. Lička ◽  
K. Ježek
Keyword(s):  
Forest Ecosystems ◽  
Dead Wood ◽  
Nature Reserve ◽  
Mountain Forest ◽  
National Nature Reserve ◽  
Dead Trees ◽  
Decomposition Processes ◽  
Standing Dead ◽  
Recorded Data ◽  
Standing Dead Trees

In four permanent experimental plots, dead wood was inventory under conditions of mountain forest ecosystems of the Kněhyně-Čertův ml&yacute;n National Nature Reserve, the Moravian-Silesian Beskids. Down woody material, standing dead trees as well as living trees were recorded. Data obtained were used to determine partial and summarized volumes of dead wood and its proportion in a living stand. Each of the surveyed areas was described not only from the viewpoint of mensuration but also with respect to subsequently carried out studies of biodiversity of wood mycoflora, succession of decomposition processes, natural regeneration on the dead wood etc. Mean volume of dead wood and a share in the total standing volume reaches 132 m<sup>3</sup>/ha(40%), of this 86 m<sup>3</sup>/hais down woody material and 46 m<sup>3</sup>/havolume of standing dead trees. Mean total standing volume per ha amounted to 332 m<sup>3</sup>/ha in the region of the Kněhyně-Čertův ml&yacute;n NNR.

scholarly journals WOODY NECROMASS STOCK IN MIXED OMBROPHILOUS FOREST USING DIFFERENT SAMPLING METHODS

2018 ◽  
Vol 31 (3) ◽  
pp. 674-680 ◽  
Author(s):  
KARINA HENKEL PROCEKE DE DEUS ◽  
AFONSO FIGUEIREDO FILHO ◽  
ANDREA NOGUEIRA DIAS ◽  
IZABEL PASSOS BONETE
Keyword(s):  
Dead Wood ◽  
Sampling Methods ◽  
Sampling Error ◽  
Permanent Sample Plots ◽  
Area Sampling ◽  
Fixed Area ◽  
Ombrophilous Forest ◽  
Fallen Dead Wood ◽  
Line Intercept ◽  
Volume Size

ABSTRACT The objective of this study was to quantify the necromass stock in a Mixed Ombrophilous Forest (MOF) fragment in the National Forest of Irati, State of Paraná, Brazil. Two sampling methods were tested: FA1, consisting of a fixed area (FA) approach with sample units measuring 2,500 m2 (50 m × 50 m); and FA2, consisting of fixed area sampling units measuring 500 m2 (10 m × 50 m) and line intercept sampling (LI) using 50 m lines. Data were collected on permanent sample plots installed in the area, consisting of 25 square blocks of 1 ha. Fallen dead wood pieces with a diameter = 10 cm were used in the analysis. The dead wood was classified into three degrees of decomposition, and masses were calculated as the corresponding density at each class. The tested sampling methods were evaluated using coefficient of variation and relative sampling error, and the nonparametric Kruskal-Wallis test was used to compare the results between the methods. Volume size of fallen dead wood did not statistically differ between the methods, but variation in necromass volume was lower in the FA1 method, whereas the FA2 method had a smaller sampling error. Overall sampling error ranged from 23.4-27.92%; lowering the sampling error to 15% would require a high sampling intensity (FA1: 42 area units [a.u.], FA2: 99 a.u., and LI: 236 a.u.). Total necromass weights amounted to 4.67 Mg.ha-1 (FA1); 5.16 Mg.ha-1 (FA2) and 4.58 Mg.ha-1 (IL), and carbon stock estimates were 2.00 Mg.C.ha-1 (FA1); 2.20 Mg.C.ha-1 (FA2) and 1.96 Mg.C.ha-1 (IL).

scholarly journals Large-Scale Mapping of Tree Species and Dead Trees in Šumava National Park and Bavarian Forest National Park Using Lidar and Multispectral Imagery

2020 ◽  
Vol 12 (4) ◽  
pp. 661 ◽  
Author(s):  
Peter Krzystek ◽  
Alla Serebryanyk ◽  
Claudius Schnörr ◽  
Jaroslav Červenka ◽  
Marco Heurich
Keyword(s):  
Tree Species ◽  
National Park ◽  
Large Scale ◽  
Dead Wood ◽  
Multispectral Imagery ◽  
Normalized Cut ◽  
Dead Trees ◽  
Standing Dead ◽  
Standing Dead Trees ◽  
Bavarian Forest

Knowledge of forest structures—and of dead wood in particular—is fundamental to understanding, managing, and preserving the biodiversity of our forests. Lidar is a valuable technology for the area-wide mapping of trees in 3D because of its capability to penetrate vegetation. In essence, this technique enables the detection of single trees and their properties in all forest layers. This paper highlights a successful mapping of tree species—subdivided into conifers and broadleaf trees—and standing dead wood in a large forest 924 km2 in size. As a novelty, we calibrate the critical stopping criterion of the tree segmentation based on a normalized cut with regard to coniferous and broadleaf trees. The experiments were conducted in Šumava National Park and Bavarian Forest National Park. For both parks, lidar data were acquired at a point density of 55 points/m2. Aerial multispectral imagery was captured for Šumava National Park at a ground sample distance (GSD) of 17 cm and for Bavarian Forest National Park at 9.5 cm GSD. Classification of the two tree groups and standing dead wood—located in areas of pest infestation—is based on a diverse set of features (geometric, intensity-based, 3D shape contexts, multispectral-based) and well-known classifiers (Random forest and logistic regression). We show that the effect of under- and oversegmentation can be reduced by the modified normalized cut segmentation, thereby improving the precision by 13%. Conifers, broadleaf trees, and standing dead trees are classified with overall accuracies better than 90%. All in all, this experiment demonstrates the feasibility of large-scale and high-accuracy mapping of single conifers, broadleaf trees, and standing dead trees using lidar and aerial imagery.

scholarly journals Estimation of coarse woody debris stocks in forest ecosystems of Slobozhansky national nature park

2021 ◽  
Author(s):  
O. Furdychko ◽  
◽  
O. Chornobrov ◽  
I. Solomakha ◽  
I. Tymochko ◽  
...  
Keyword(s):  
Coarse Woody Debris ◽  
Forest Inventory ◽  
Forest Ecosystems ◽  
Dead Wood ◽  
Woody Debris ◽  
Forest Stands ◽  
Dead Trees ◽  
Standing Dead ◽  
Fallen Dead Wood ◽  
Total Stock

Dead wood is an important component of forest ecosystems. It performs a number of environmental functions. Coarse woody debris includes standing dead trees, fallen dead trees, fragments of fallen trees (trunks), branches (fragments of branches), and rough tree roots. It is a substrate and habitat for living organisms, including a number of species of mosses, lichens, fungi, invertebrates, as well as birds and mammals. Woody detritus plays an important role in the biological cycle of substances and energy, and carbon deposition, is a source of nutrients. Therefore, the study of quantitative and qualitative features of dead wood, in particular on protected areas, is a considerable nowadays problem. The aim of the work is to estimate identified by forest inventory stocks of dead wood in forest ecosystems of Slobozhansky NNP by categories, as well as to analyze the distribution of its volumes in stands of dominant tree species and forest types. The estimation of coarse woody debris stocks was performed based on forest inventory data of Slobozhansky National Nature Park conducted by Ukrainian State Project Forestry Production association “Ukrderzhlisproekt”. Data from 493 forest stands of nine tree species were analyzed. The stock of the following fractions of coarse woody debris was studied: standing dead wood, fallen (downed) dead wood. Data analysis was performed using MS Excel 2016 software. It was found that the total area of forest stands in which standing or downed dead wood was found during forest inventory was 2149.8 ha, or 47.5% of the total forest area of NNP. The total stock of coarse woody debris was 19478 m3, more than 95% of which is concentrated in the stands of Scots pine (Pinus sylvestris L.) (78.8%) and pedunculate oak (Quercus robur L.) (16.6%). Standing dead wood prevailed (62.1%) fallen dead wood (37.9%) in the structure of dead wood volume. The volume of dead wood was in the range of 5–50 m3∙ha–1, and on average in studied forest ecosystems in which it was found was 9.1 m3∙ha–1. In Scots pine forest stands coarse woody debris was found on an area of 1703.5 hectares with total stock of 15355 m3, consists of standing dead trees (9952 m3, 64.8%) and fallen dead wood (5403 m3, 35.2%). The volume of dead wood in forest stands was 5–50 m3∙ha–1, on average – 9.0 m3∙ha–1. In pedunculate oak stands coarse wood debris was found on an area of 384.7 hectares with a total stock of 3224 m3, consists of standing dead wood (1469 m3, 45.6%) and fallen dead wood (1755 m3, 54.4%). The volume of dead wood in forest stands was 5–20 m3∙ha–1, on average – 8.4 m3∙ha–1.

scholarly journals Classification of Tree Species as Well as Standing Dead Trees Using Triple Wavelength ALS in a Temperate Forest

2019 ◽  
Vol 11 (22) ◽  
pp. 2614 ◽  
Author(s):  
Nina Amiri ◽  
Peter Krzystek ◽  
Marco Heurich ◽  
Andrew Skidmore
Keyword(s):  
Tree Species ◽  
Feature Selection Method ◽  
Silver Fir ◽  
Maximum Point ◽  
Individual Tree ◽  
Dead Trees ◽  
Multi Wavelength ◽  
Standing Dead ◽  
Standing Dead Trees ◽  
532 Nm

Knowledge about forest structures, particularly of deadwood, is fundamental for understanding, protecting, and conserving forest biodiversity. While individual tree-based approaches using single wavelength airborne laserscanning (ALS) can successfully distinguish broadleaf and coniferous trees, they still perform multiple tree species classifications with limited accuracy. Moreover, the mapping of standing dead trees is becoming increasingly important for damage calculation after pest infestation or biodiversity assessment. Recent advances in sensor technology have led to the development of new ALS systems that provide up to three different wavelengths. In this study, we present a novel method which classifies three tree species (Norway spruce, European beech, Silver fir), and dead spruce trees with crowns using full waveform ALS data acquired from three different sensors (wavelengths 532 nm, 1064 nm, 1550 nm). The ALS data were acquired in the Bavarian Forest National Park (Germany) under leaf-on conditions with a maximum point density of 200 points/m 2 . To avoid overfitting of the classifier and to find the most prominent features, we embed a forward feature selection method. We tested our classification procedure using 20 sample plots with 586 measured reference trees. Using single wavelength datasets, the highest accuracy achieved was 74% (wavelength = 1064 nm), followed by 69% (wavelength = 1550 nm) and 65% (wavelength = 532 nm). An improvement of 8–17% over single wavelength datasets was achieved when the multi wavelength data were used. Overall, the contribution of the waveform-based features to the classification accuracy was higher than that of the geometric features by approximately 10%. Our results show that the features derived from a multi wavelength ALS point cloud significantly improve the detailed mapping of tree species and standing dead trees.

A Note on the Association of Fall Cankerworm (Alsophila pometaria (Harr.)) with Winter Moth (Operophtera brumata (Linn.)) (Lepidoptera: Geometridae)

1958 ◽  
Vol 90 (9) ◽  
pp. 538-540 ◽  
Author(s):  
C. C. Smith
Keyword(s):  
Tree Species ◽  
Life Histories ◽  
Quercus Rubra ◽  
Acer Platanoides ◽  
Operophtera Brumata ◽  
Ulmus Americana ◽  
Winter Moth ◽  
The Third ◽  
Norway Maple ◽  
Fall Cankerworm

The fall cankerworm, Alsophila pometaria (Harr.), and the winter moth, Operophtera brumata (Linn.), both feed to a great extent on the same tree species and prefer apple, Malus spp., red oak, Quercus rubra L., basswood, Tilia spp., white elm, Ulmus americana L., and Norway maple, Acer platanoides L. They also have similar life-histories and habits (Smith 1950 and 1953). Both lay their eggs on the trees in the fall and overwinter in this stage. The eggs hatch about the same time and the larvae of (both species mature about the third week in June. They drop to the ground and form cocoons at a depth of about an inch. The adults emerge about the same time, commencing usually during the last week in October and continuing until early December or until the ground freezes.

Ontario's forest growth and yield modelling program: Advances resulting from the Forestry Research Partnership

2008 ◽  
Vol 84 (5) ◽  
pp. 694-703 ◽  
Author(s):  
Mahadev Sharma ◽  
John Parton ◽  
Murray Woods ◽  
Peter Newton ◽  
Margaret Penner ◽  
...  
Keyword(s):  
Tree Species ◽  
Stand Density ◽  
Forest Growth ◽  
Growth And Yield ◽  
Research Partnership ◽  
Wood Supply ◽  
Permanent Sample Plots ◽  
Forestry Research ◽  
Research Activities ◽  
Forest Growth And Yield

The province of Ontario holds approximately 70.2 million hectares of forests: about 17% of Canada’s and 2% of the world’s forests. Approximately 21 million hectares are managed as commercial forests, with an annual harvest in the early part of the decade approaching 200 000 ha. Yield tables developed by Walter Plonski in the 1950s provide the basis for most wood supply calculations and growth projections in Ontario. However, due to changes in legislation, policy, and the planning process, they no longer fully meet the needs of resource managers. Furthermore, Plonski`s tables are not appropriate for the range of silvicultural options now practised in Ontario. In October 1999, the Canadian Ecology Centre- Forestry Research Partnership (CEC-FRP) was formed and initiated a series of projects that collectively aimed at characterizing, quantifying and ultimately increasing the economically available wood supply. Comprehensive, defensible, and reliable forecasts of forest growth and yield were identified as key knowledge gaps. The CEC-FRP, with support from the broader science community and forest industry, initiated several new research activities to address these needs, the results of which are outlined briefly in this paper. We describe new stand level models (e.g., benchmark yield curves, FVS Ontario, stand density management diagrams) that were developed using data collected from permanent sample plots and permanent growth plots established and remeasured during the past 5 decades. Similarly, we discuss new height–diameter equations developed for 8 major commercial tree species that specifically account for stand density. As well, we introduce a CEC-FRP-supported project aimed at developing new taper equations for plantation grown jack pine and black spruce trees established at varying densities. Furthermore, we provide an overview of various projects undertaken to explore measures of site productivity. Available growth intercept and site index equations are being evaluated and new equations are being developed for major commercial tree species as needed. We illustrate how these efforts are advancing Ontario’s growth and yield program and supporting the CEC-FRP in achieving its objective of increasing the supply of fibre by 10% in 10 years while maintaining forest sustainability. Key words: permanent sample plots (PSPs), permanent growth plots (PGPs), normal yield tables, sustainable forest management, NEBIE plot network, forest inventory, Forest Vegetation Simulator

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