Human activity and influence on forests has been occurring for thousands of years and most forests have a long history of exploitation and alteration (Bölöni
Stemwood volume is an important measure in forest management and ecology. It is widely recognized that stemwood volume correlates with woody biomass and carbon content (further on C) in managed and natural forests. However, there is little evidence regarding the quantities of live and dead wood in hemiboreal old-growth forest ecosystems. Wood volume assessment in such ecosystems is rather complicated as these stands vary considerably in the number of trees and cohorts by species, age, dimensions, spatial patterns, and deadwood in all decay stages occurs throughout the forest. In addition, the taper form of trees in old-growth forests may differ from trees in managed forests.
Stem lateral surface area of trees is a valuable trait for evaluating the overall ecological quality of forest stands because it is directly related to niches and habitats for different vertebrates, arthropods, fungi, lichens and bryophytes. Estimating the surface area of a log or tree trunk poses some distinctive challenges not found in the estimation of other tree attributes (Williams
It is evident that the prognosis of any stand descriptive variable in mixed multi-aged and multicohort conditions, as in an old-growth forest, is a lot complex than in the case of pure stands (Fabrika
The aim of this study is to describe and analyse the methodology for calculating single tree height, tree stem lateral surface area (hereafter SLSA), tree volume and carbon content for standing live trees, standing dead trees and for downed deadwood of the main tree species in the stand that formed under natural conditions. As a study question we aim to determine whether the Järvselja old-growth forest is moving into the multiaged condition, where we can expect increasing dominance by shade-tolerant species with the maintenance of high biomass and high but variable amounts of dead wood (Bormann & Likens, 1994).
The study area is in Järvselja Training and Experimental Forest Centre and is a part of the Järvselja nature conservation area. In 1924, an area of 12.8 ha (Raukas, 1967) in the southern part of a 19-hectare compartment was set aside to allow an experiment where all management actions were abandoned (Mathiesen, 1940). In 1936, the area was enlarged to cover the whole compartment and the site was included in the nature conservation registry, obtaining a state-controlled protection status. In 1959, the whole old-growth forest compartment was registered as a botanical-zoological conservation area (Krigul, 1971). Today the old-growth forest and its surrounding compartments are part of the Järvselja nature conservation area that covers altogether 188 ha. According to the site’s conservation plan, this area is divided into two special management zones (Ürgmets and Järvselja) and one, partially limited, management zone (Apna) (Laas
The protected old-growth forest (known as compartment JS226) (Kollom, 2011; Laas
Compartment JS226 (58.28 N and 27.32 E) is divided according to three dominating vegetation types (Lõhmus, 1993): on the eastern side, fresh boreo-nemoral forests with rich groundcover species like
One of the earliest studies about the old-growth forest ground vegetation was carried out by Gustav Vilbaste in 1929. In that study three dominating forest site types were defined and described in the old-growth forest compartment: fresh boreo-nemoral forests, minerotrophic mobile water swamp forest and mixotrophic bog forests (Sepp & Rooma, 1993; Vilbaste, 1929).
There are numerous subsequent descriptive studies about the old-growth forest compartment. Mathiesen published an overview about the compartment in 1940 and Masing wrote about the old-growth forest conditions in 1960 (Masing & Rebane, 1995). Krigul carried out several studies in Järvselja old-growth forest from 1939 to 1971 (see Table 1). While earlier studies focused on volume description of living trees and coarse woody debris (CWD) (Krigul, 1940), later studies focused more extensively on stand health conditions and also presented additional stand-wide inventory data (Kollom, 2011).
Earlier studies on Järvselja old-growth forest.
Author(s) | Publishing year | Measurement year/period | Inventory type* | Citation |
---|---|---|---|---|
Kollom, M. | 2011 | 1922–2010 | 3 | (Kollom, 2011) |
Kasesalu, H. | 2001 | 2001 | 1 | (Kasesalu, 2001) |
Kasesalu, A. | 1985, 1993 | 1982, 1983 | 1 | (Kasesalu, 1985), (Kasesalu, 1993) |
Irdt, E., Rebane, H. | 1985 | 1954–1985 | 1; 2 | (Irdt & Rebane, 1985) |
Pettai, T. | 1985 | 1922–1984 | 3 | (Pettai, 1985) |
Raukas, A. | 1967 | 1958–1959 | 1; 3 | (Raukas, 1967) |
Krigul, T. | 1961 | 1958, 1959 | 3 | (Krigul, 1961) |
Krigul, T. | 1940 | 1939 | 3 | (Krigul, 1940) |
Visnapuu, M. | 1927 | 1927 | 3 | (Krigul, 1940) |
Inventory type: 1) Plot-wide inventory; 2) Transect inventory; 3) Stand-wise inventory.
Irdt and Rebane conducted one of the most important research studies in the period of 1954–1985 (Irdt & Rebane, 1985). They established a complex measurement plot transect in the old-growth forest and remeasured it regularly from 1954 until 1985. The measurements on this transect were carried out on 10 × 10 m plots. They assessed standing live tree diameters, heights, tree layer, geographical location, ground vegetation and soil microsites. Based on those descriptions, Irdt & Rebane (1985) partly described the stand dynamics. Heino Kasesalu published several studies about the old-growth forest, also describing the stand dynamics since 1984 up to 2001 (Kasesalu, 1993; Kasesalu, 2004).
In addition to the studies presented in Table 1, there are stand-wise forest inventory data available, covering a period of 94 years (from 1922 to 2016). Long-term dynamics based on the stand-wise forest management inventory data were analysed by Kollom (2011). In her study, the standing gross volume of all tree species in old-growth forest compartments increased up to 1962, and was then followed by a period of decrease up to 1983. Similar trends were reported by Pettai (1985) and Kasesalu (2004). In the period of 1983–2010, the average volume of the dominating layer showed low fluctuations, but a clear increase in the volume of the supressed spruce layer can be seen starting from 1993 (Kollom, 2011).
From spring until autumn 2013, an inventory was carried out with the aim of covering the study area with tree mapping data. To avoid potentially disruptive extensive measurements on more fragile sites and close to habitats under protection, two methodologies were followed: whole surface inventory (in sub-compartments 6, 9, 10, 11, 12, 13, 14, 15) and partial surface mapping based on permanent sample plots (in sub-compartments 1, 2, 3, 4, 5, 7, 8). To facilitate mapping, additional measurements on tree positions on the site were carried out to establish a network of geodetically accurate reference points (approx. 50 × 50 m interval, RTK GNSS method, with the location accuracy of 0.05–0.5 meters). This resulted in a 72-point grid and the grid points were marked on the ground with metallic rods (see Appendix A). Whole surface mapping covered 9.34 ha and partial mapping covered 10.03 ha. The study area included five different site types:
FieldMap technology (IFER-Monitoring and Mapping Solutions Ltd.) was used in conjunction with geodetically accurate reference points (see Appendix A), where tree distance was measured with a ForestPro impulse laser rangefinder. For tree positioning the Mapstar TruAngle angle encoder together with ForestPro impulse laser rangefinder was used. Tree heights to the live crown base and heights of the lowest dry branch on the tree stem were measured with a Vertex hypsometer to the nearest 0.1 m. Data were collected and stored on site with the FieldMap data collector software. Partial surface stem mapping was carried out on wetter and more fragile sites in parallel with full surface stem mapping elsewhere. Circular plots of various radii (15–20 m) were used in different sub-compartments. Permanent plots were located similarly with FieldMap measurements using the geodetically accurate reference points as shown in Appendix A.
Both full surface and partial surface tree mapping followed the design of the survey protocol of the Estonian Network of Forest Research Plots (ENFRP) (Kiviste
Other tree measurements included position, species, height, and diameter (in two perpendicular directions). If the height of the broken dead tree was under 1.3 m, then the diameter was measured 10 cm below the breakage point or from the root collar (marked accordingly). Standing and broken dead trees were also described according to five decay stages following studies by Fridman & Walheim (2000) and Köster
Assessing the tree height and diameter (H-D) relation of old-growth forests using models that have been developed for managed forest stands has its own challenges (Nigul
We introduced an additional parameter
The selection procedure in the case of n ≥ 9 is as follows: from the weight function
Following the model selection procedure, H-D ratios were assessed, and model solutions calculated by using the measured data per stand element (Figure 1) – a combination of the tree species in a particular cohort in a particular site type and sub-compartment. There were 5 site types and 15 sub-compartments in the Järvselja old-growth forest compartment. Similar calculations were carried out for deciduous and coniferous trees, which resulted in 129 different height curves.
For comparison, we used the two best-performing height curve models from an earlier study by Nigul and colleagues (Nigul Chapman-Richards function with fitted parameters per species (Table 2):
Näslund function with fitted parameters (Table 2; see Equation 1).
H-D model parameters from Nigul
Tree species | Chapman-Richards function (Eq. 5) | Näslund function (Eq. 1) | |||
---|---|---|---|---|---|
a | b | c | a | b | |
SP | 30.67342 | 0.032552 | 0.80312 | 1.59472 | 0.30835 |
NS | 39.02975 | 0.033294 | 1.18444 | 2.16428 | 0.27970 |
BI | 33.57059 | 0.023891 | 0.62549 | 1.19810 | 0.31378 |
CA | 37.72567 | 0.043817 | 0.89476 | 1.28707 | 0.28380 |
BAR | 30.46570 | 0.036539 | 0.85649 | 1.43745 | 0.30966 |
LI | 33.70126 | 0.040448 | 1.07656 | 1.69100 | 0.29469 |
NM | 33.17741 | 0.030304 | 0.76981 | 1.26131 | 0.31403 |
Other | 34.06000 | 0.035000 | 0.91100 | 1.51900 | 0.30000 |
Tree species and tree species codes are as follows: SP – Scots pine; NS – Norway spruce; BI – silver birch and downy birch; CA – common aspen; BAR – black alder; LI – linden family; NM – Norway maple
To achieve comparable results, a scaling factor
All three H-D curves were used to estimate single tree heights and to make comparisons with measured tree heights. Root mean square errors were calculated to assess the goodness of fit (Figure 3).
General information about measured live and dead standing trees is presented in Table 5, and the spatial allocation can be followed in Figure 2 (B). The measured tree height was used for the modelling of the tree stem volume (m3) and the tree stem lateral surface area (SLSA, m2). Missing tree heights were calculated using Equation 4. The calculation principle is described in more detail by Padari (2020). For species-specific tree functions a modification of Ozolinš taper curve formula (Ozolinš, 2002; Silava, 1988) was used for calculating diameter at any tree height:
A volumetric transformation is needed for the tree stem volume calculation based on the taper curve. In the current study it was calculated using the following formula:
SLSA above bark was calculated as follows:
The measured standing snags (see Table 5 for general statistics and Figure 2 (B) for spatial arrangement) were divided into two groups: snags that were at least 1.3 m or taller in height and snags lower in height than 1.3 m (stratification needed due to different calculation methods). For taller snags
For CWD on the site, both co-ordinates and diameters of the bottom and top sides of tree stem sections were measured (see Table 5 for general statistics and Figure 2 (A) for spatial placement). For spatial assessment, a tree stem section was cut if the section was placed outside a particular plot or sub-compartment using GIS analysis. The diameters were interpolated for the cut point and only the sections inside a particular plot or sub-compartment were used for volume calculation. For stem section volume calculations, a truncated cone formula was used:
The stem sections’ lateral surface area was calculated using the stem lateral surface area of a truncated cone as follows:
For the estimation of wood density (wood dry mass per m3) and calculation of the respective C content of fresh (growing trees) timber and timber in different decomposition stages (dead and downed trees), data from different studies were employed. For the estimation of fresh (growing trees) wood densities in different tree species most of the densities used are available from Saarman & Veibri (2006); for grey alder the fresh wood density was available from (Uri
For the assessment of C content in dead and downed stems along the different decay classes (fresh wood and five decay classes), we used available measures on wood density and the relative C content for six tree species. Those are Scots pine, Norway spruce, silver and downy birch, black alder, common alder and common aspen measured by Köster
Wood density and related model parameters for Equation 14.
Species | Fresh wood basic density d0, g/cm3 | Equation constants | |
---|---|---|---|
Pedunculate oak | 584.4 | 529.58 | −88.546 |
European ash | 574.7 | 529.58 | −88.546 |
Elm family | 550.4 | 529.58 | −88.546 |
Larch family | 547.7 | 433.39 | −55.003 |
Fir family | 317.0 | 431.07 | −56.649 |
Willow family | 387.0 | 435.23 | −58.931 |
Wood density along different decay classes was estimated as follows:
Wood density and C relative content according to tree species and decay class (Köster
Variable | Tree species | Decay class | |||||
---|---|---|---|---|---|---|---|
fresh | 1 | 2 | 3 | 4 | 5 | ||
Basic density, g/cm3 | SP | 422.71 | 381.12 | 337.22 | 258.82 | 233.72 | 141.82 |
NS, DF | 375.01 | 410.72 | 354.22 | 280.72 | 191.32 | 124.82 | |
BI, ER | 538.21 | 466.62 | 326.52 | 230.02 | 175.92 | 112.12 | |
CA, LI, NA | 419.21 | 391.32 | 330.62 | 230.62 | 161.12 | 60.72 | |
BAR | 440.51 | 422.42 | 289.42 | 212.92 | 158.92 | 95.62 | |
CAR, CH, BC, OD | 396.03 | 426.92 | 345.32 | 220.72 | 184.92 | 153.62 | |
PO, NM | 584.41 | 486.7 | 389.0 | 291.3 | 193.5 | 95.8 | |
AH | 574.71 | 478.6 | 382.5 | 286.4 | 190.3 | 94.2 | |
EL | 550.41 | 458.4 | 366.3 | 274.3 | 182.3 | 90.2 | |
WI | 387.01 | 334.6 | 282.2 | 229.8 | 177.4 | 125.0 | |
LF | 547.71 | 478.2 | 408.7 | 339.2 | 269.7 | 200.1 | |
FF | 317.01 | 275.3 | 233.7 | 192.0 | 150.4 | 108.7 | |
Carbon relative content, % | SP, LF | 47.464 | 49.032 | 49.262 | 49.562 | 49.582 | 50.212 |
NS, DF, FF | 47.46 | 48.352 | 48.312 | 47.932 | 49.602 | 51.332 | |
BI, ER, WI, PO, AH, NM, EL | 47.005 | 47.162 | 47.692 | 47.452 | 48.802 | 50.122 | |
CA, LI, NA | 47.00 | 47.192 | 47.372 | 47.382 | 46.562 | 46.312 | |
BAR | 47.30 | 47.892 | 48.242 | 48.072 | 48.352 | 48.112 | |
CAR, CH, BC, OD | 47.303 | 48.022 | 48.072 | 48.712 | 47.952 | 48.042 |
Tree species and tree species codes are as follows: CA – common aspen; EL – elm family; BI – silver birch and downy birch; NS – Norway spruce; DF –
The original values from earlier studies are indicated as follows:
For the estimation of the C content for all tree species represented in Järvselja old-growth forest the following substitutions were used: for rowan, the birch values were used, for linden and unknown species the aspen values were used, for hazel, bird cherry and other broadleaved species grey alder values were used and for fir the spruce values were used. The wood density estimations are calculated using Equation 14 and presented in Table 4.
Stem wood C relative content was estimated as follows:
With this study we captured the data from 6205 live trees, 1119 snags, 270 standing dead trees (see Table 5) and 2983 dead wood trunks in Järvselja old-growth forest. The most common tree species in the woody cohorts were Norway spruce and linden (
Summary statistics of the measured data.
Variable | Live trees | Standing dead wood | Snags | Downed dead wood |
---|---|---|---|---|
Number of measured trees, (N) | 6205 | 270 | 1119 | 2983 |
Number of estimated trees in the compartment JS226 | 16227 | 1073 | 2749 | 6112 |
Dominating species* | NS, SP, WI, LI, BAR | NS, SP | NS, SP, CA, BAR | NS, SP |
Mean diameter, D (cm) | 22.5 | 22.8 | 31.3 | 26.9 |
Mean height/length, H/L (m) | 21.3 | 21.8 | 3.9 | 8.6 |
Mean decay class | - | 1.91 | 2.60 | 3.03 |
Mean stem volume, V (m3) | 0.43 | 0.43 | 0.21 | 0.34 |
Mean stem lateral surface area, SLSA (m2) | 7.61 | 7.95 | 2.62 | 5.15 |
Tree species codes are as follows: NS = Norway spruce; SP = Scots pine; WI = willow family; LI = linden family; BAR = black alder; CA = common aspen.
Table 6 condenses the major results of the main stand characteristics as given in different sub-compartments by the measured structural stand cohorts. With a couple of exceptions all structural cohorts (live trees, dead standing trees, snags and downed trees) were recorded in all sub-compartments. Only live trees and snags were recorded in the sub-compartments 1 and 14. All the stands in Järvselja old-growth forest were mixed species stands and the most abundant tree species in all cohorts is Norway spruce (NS). Spruce is also the most common species in the current structural cohorts of dead trees, snags and downed stems.
Stand characteristics in sub-compartments.
Sub-compartment | Area, ha | Cohort | Stand composition1 | N | G | M | S | C |
---|---|---|---|---|---|---|---|---|
per hectare2 | ||||||||
1 | 0.60 | Live | 50NS25BAR19SP2BI2WI1AH1LI | 1505 | 21.2 | 198.0 | 4696 | 38.263 |
Snags | 87NA7NS6BAR | 127 | 6.4 | 7.5 | 119 | 0.623 | ||
Downed | 51NS2SP+BAR47NA | 281 | 137.8 | 1916 | 21.968 | |||
2 | 0.74 | Live | 62SP38NS | 905 | 31.4 | 339.5 | 6585 | 65.224 |
Dead | 57NS26BI17SP | 151 | 4.4 | 44.7 | 1038 | 6.918 | ||
Snags | 74SP22NS4NA | 82 | 1.5 | 9.9 | 246 | 1.579 | ||
Downed | 30SP27BI13NS30NA | 164 | 23.5 | 499 | 3.795 | |||
3 | 1.13 | Live | 58SP29NS9BAR4BI | 952 | 31.9 | 309.0 | 6509 | 60.798 |
Dead | 59NS41SP | 167 | 1.3 | 8.8 | 340 | 1.464 | ||
Snags | 35SP34BI30NS1NA | 134 | 2.8 | 10.3 | 264 | 1.595 | ||
Downed | 70NS10BI1SP17NA | 184 | 16.8 | 441 | 2.545 | |||
4 | 3.37 | Live | 59SP26NS9BI6BAR | 921 | 33.2 | 330.2 | 6656 | 66.027 |
Dead | 80SP20NS | 63 | 2.6 | 24.6 | 500 | 4.319 | ||
Snags | 44SP38NA10BI8NS | 183 | 7.8 | 37.7 | 655 | 5.999 | ||
Downed | 28NS17SP16BI2CA37NA | 310 | 53.2 | 1197 | 7.167 | |||
5 | 1.11 | Live | 33WI22LI11AH11BI10NM5RE1CA1DF | 1435 | 36.6 | 360.3 | 7063 | 77.277 |
Dead | 100NS | 14 | 2.8 | 37.4 | 406 | 6.401 | ||
Snags | 67CA29NS3NA1RE | 225 | 35.3 | 105.3 | 805 | 11.803 | ||
Downed | 40NS9BI3NM1BAR+WI+EL47NA | 394 | 318.0 | 3650 | 37.188 | |||
6 | 0.25 | Live | 68LI28NS3NM1AH | 501 | 38.1 | 497.6 | 7276 | 97.085 |
Dead | 100NS | 4 | 0.1 | 0.6 | 22 | 0.123 | ||
Snags | 62NS22NA12LI4BAR | 61 | 8.8 | 7.8 | 71 | 1.070 | ||
Downed | 59NS7LI4BAR3BI27NA | 151 | 85.8 | 1044 | 11.600 | |||
7 | 1.37 | Live | 56NS41SP2BAR1LI | 1032 | 29.9 | 310.8 | 6170 | 58.481 |
Dead | 55NS45SP | 146 | 6.8 | 74.0 | 1480 | 11.615 | ||
Snags | 99NS1NA | 167 | 7.4 | 19.4 | 303 | 3.035 | ||
Downed | 87NS7SP6NA | 375 | 56.7 | 1325 | 7.928 | |||
8 | 1.71 | Live | 43NS33SP13BAR10BI1OD | 828 | 37.1 | 369.5 | 6886 | 72.923 |
Dead | 62NS38SP | 79 | 3.6 | 35.1 | 665 | 6.179 | ||
Snags | 62NS18SP10BAR4NA4FF2BI | 152 | 6.0 | 19.8 | 367 | 3.120 | ||
Downed | 76NS15BI5SP4NA | 308 | 48.2 | 1012 | 6.774 | |||
9 | 2.52 | Live | 56NS15LI14BAR7BI5CA2NM1SP | 711 | 40.0 | 497.7 | 7249 | 96.452 |
Dead | 97NS2NM1LI | 26 | 1.3 | 16.4 | 235 | 3.033 | ||
Snags | 44NS17BI10NA9BAR7CA6LI6CAR1RE | 131 | 16.6 | 40.2 | 367 | 5.717 | ||
Downed | 56NS9BI6BAR3LI+CA+NM+SP+AH26NA | 268 | 160.8 | 1883 | 18.707 | |||
10 | 0.64 | Live | 68NS15BAR8BI5SP1NM1CA1BC1OD | 819 | 25.5 | 260.6 | 5449 | 49.877 |
Dead | 80NS15SP4BAR1NM | 50 | 2.0 | 20.8 | 401 | 3.514 | ||
Snags | 76NS11NA7BI4BAR2SP | 233 | 19.0 | 33.0 | 452 | 3.806 | ||
Downed | 75NS10BI6FF3BAR2SP4NA | 439 | 138.5 | 2213 | 15.252 | |||
11 | 0.89 | Live | 71NS11SP10BAR5BI1NM1FF1OD | 661 | 26.0 | 296.7 | 5288 | 56.064 |
Dead | 91NS6SP3AH | 34 | 2.0 | 23.6 | 397 | 4.135 | ||
Snags | 81NS8SP6NA2BI1BAR1FF1AH | 157 | 15.6 | 23.4 | 272 | 3.106 | ||
Downed | 73NS8BI6SP2AH1BAR+FF10NA | 384 | 151.8 | 2334 | 17.569 | |||
12 | 2.31 | Live | 50BAR31NS7BI6SP5LI1OD | 578 | 32.7 | 361.9 | 5530 | 72.801 |
Dead | 66NS15BAR9BI8SP1LI1AH | 20 | 1.2 | 12.7 | 201 | 2.266 | ||
Snags | 36BAR28NA22NS10BI1CAR1AH1OD | 83 | 7.1 | 20.7 | 195 | 2.393 | ||
Downed | 48NS14BI11BAR4SP2LI2AH1NM+FF18NA | 394 | 98.4 | 1807 | 14.534 | |||
13 | 0.95 | Live | 61LI29NS5NM2AH2BAR1BI | 661 | 38.0 | 467.8 | 7076 | 92.608 |
Dead | 99NS1BAR | 15 | 0.6 | 7.1 | 120 | 1.161 | ||
Snags | 59NS24NA11LI4BAR2OD | 77 | 10.7 | 13.1 | 132 | 1.686 | ||
Downed | 57NS8BAR7LI3SP1BI1AH1NM+EL+FF+ER+BC22NA | 256 | 154.0 | 1768 | 20.462 | |||
14 | 0.15 | Live | 38BAR26LI17NS10BI4AH2BC2FF1NM | 907 | 23.5 | 214.5 | 4877 | 44.431 |
Snags | 69NS21NM5BI5NA | 172 | 16.1 | 16.6 | 219 | 1.735 | ||
Downed | 56NS20BI5BAR2NM+BC+EL+LI17NA | 687 | 163.7 | 2395 | 15.524 | |||
15 | 1.64 | Live | 48NS23LI11BAR6CA4NM4BI3AH1OD | 562 | 31.4 | 386.6 | 5784 | 76.092 |
Dead | 45NS20BI18AH13NM4LI | 12 | 1.2 | 15.0 | 179 | 3.005 | ||
Snags | 56NS13BI9NA8LI8BAR2AH1CA1RE1OD | 111 | 11.4 | 24.5 | 257 | 3.467 | ||
Downed | 50NS6LI5BI5NM4BAR3AH3CA+FF+BC+WI+ER+EL24NA | 308 | 136.6 | 1898 | 19.182 | |||
Compartment | 19.38 | Live | 46NS20LI18BAR6SP5BI2NM2CA 1AH+WI+ER+FF+EL+BC+DF+OD | 837 | 33.3 | 363.5 | 6375 | 71.717 |
Dead | 75NS10SP6BI3BAR3NM2AH1LI | 55 | 2.3 | 24.0 | 440 | 4.115 | ||
Snags | 49NS11BAR10BI5CA4LI3SP1AH1RE2OD14NA | 142 | 10.9 | 29.7 | 372 | 4.084 | ||
Downed | 53NS9BI4BAR3SP2LI1NM1AH1CA+FF+WI+EL+BC+ER26NA | 315 | 107.6 | 1624 | 13.889 |
Tree species and tree species codes are as follows: CA – common aspen; BI – silver birch and downy birch; NS – Norway spruce; BAR – black alder; SP – Scots pine; WI – willow family; AH – European ash; LI – linden family; ER – European rowan; BC – bird cherry; NM – Norway maple; DF –
Variables as follows: N – number of trees, G – basal area at DBH height, m2, M – standing volume, m3, S – cumulative stem lateral surface area, m2, C – carbon content, Mg.
The live tree basal area ranged between 21.3 and 38.1 m2 per hectare indicating that the stands growing in Järvselja old-growth forest have maintained high basal area despite moving beyond the even-aged, stem-exclusion stage of development. The standing volume of live trees was 203–498 m3 per hectare, indicating a generally high stocking density. The standing dead wood volume ranged from 7 to 73 m3 per hectare. The largest standing volume was registered in the
When the average diameter of standing live and dead trees was similar (22.5 and 22.8, accordingly), then in the case of standing snags and downed stems (31.3 and 26.9, accordingly) it is considerably higher and indicating a break-down of larger trees. The downed stems’ dead wood volume ranged from 16.8 to 163.7 with an average of 107.6 m3 per hectare.
The three H-D curves (1) Näslund function with iterated regression analysis, (2) Chapman-Richards function with previously fitted parameters and (3) Näslund function, also using the previously fitted parameters were used to calculate the tree heights which were subsequently compared to actual measured tree heights. For the Näslund function with the iterated regression (Equation 4) and the scaled parameters the lowest root mean squared error (RMSE) was found. Only for two tree species (grey alder and common hazel) the Chapman-Richards function with previously fitted parameters showed better results (see Figure 3).
The share of standing live and dead trees and the share of downed dead wood in different stands in the sub-compartments are presented in Table 7. The lowest share of live trees was 43.9% in sub-compartment 5 and the highest 89.6 in sub-compartment 3; the average share for the compartment was 69.3%. The share of downed dead wood ranged from 4.9% to 41.5 % and 20.5% on average for the compartment. The occurrence of high live tree biomass and considerably high downed wood volume indicate that with a couple of exceptions there is no strong evidence of structural stand break-down in Järvselja old-growth forest. Only in the case of sub-compartments 1, 5, and 14 a clear heavy disturbance or breakdown effect is recorded.
Volume and C content of live and dead trees in sub-compartments.
Sub-compartment | Volume, m3/ha | C content MgC/ha | ||||||
---|---|---|---|---|---|---|---|---|
1 | 343.4 | 60.85 | ||||||
2 | 417.5 | 77.52 | ||||||
3 | 345.0 | 66.40 | ||||||
4 | 445.7 | 83.51 | ||||||
5 | 820.9 | 132.67 | ||||||
6 | 591.7 | 109.88 | ||||||
7 | 460.9 | 81.06 | ||||||
8 | 472.6 | 89.00 | ||||||
9 | 715.2 | 123.91 | ||||||
10 | 452.8 | 72.45 | ||||||
11 | 495.4 | 80.87 | ||||||
12 | 493.7 | 91.99 | ||||||
13 | 641.9 | 115.92 | ||||||
14 | 394.7 | 61.69 | ||||||
15 | 562.7 | 101.75 | ||||||
Compartment | 524.9 | 93.81 |
Our results of species occurrence in structural cohorts (live trees, dead standing trees, snags and downed trees) in all sub-compartments indicate that Järvselja old-growth forest is moving into the old multiaged condition (Frelich, 2002) with maintained or slightly elevated tree species richness. Although the increase in dominating and co-dominating tree species is desired and is expected after the stand was set aside from anthropogenic disturbances, there can be complex reasons for such a development (Jõgiste
The long-term dynamics of live tree species composition in Järvselja old-growth forest is shown in Figure 4. During the last 100 years, the number of tree species has slightly increased with the inclusion of linden and black alder (Kasesalu, 2004; Kollom, 2011; Krigul, 1940). Birch, common aspen and Scots pine have been slightly but gradually declining (Kollom, 2011). In late succession the shade-intolerant species decline in abundance, compared to stand initiation and stem exclusion conditions (Frelich, 2002), but the regeneration is not totally excluded. This also coincides well with the concept of cumulative disturbance severity, where the vertical direction of disturbance (i.e., starting in the canopy and then to the understory or vice versa) is intermixed with the degree of tree mortality (Kern
It is interesting to see Norway spruce presence in all structural cohorts, including in the dead wood and downed trees strata. This can be seen in the long-term tree species composition dynamics in the forest management inventory data (Figure 4 A) where spruce slowly catches up and overtakes aspen and birch as stands age. Depending on the stand age and forest disturbance dynamics we can expect the spruce to be favoured by patch dynamics caused by gap formation, with shifting mosaic development. Still, it is difficult to say based on the current study if it is a shifting mosaic with changing composition in each gap (neutral dynamics) or shifting mosaic with gaps holding the similar composition as before (positive dynamics) (Frelich, 2016) or it could be a combination of both conditions. Earlier studies from more boreal conditions by Sirén (1955) indicated that spruce acquired dominance approximately 80 years after stand replacing disturbances and when the stand variables were getting close to secondary succession levels (Shorohova
A separate question arises when trying to set the average standing volume results of the current study into context with the long-term forest management inventory data (see Figure 4 B) for comparison on the whole-compartment level. A clear difference becomes visible in the average standing volume estimate of the live trees structural cohort, where, in comparison with the latest forest management inventory results in 2010 and 2016, the average standing volume in our study indicates a considerably higher average standing volume in 2013. This situation, where in fully stocked conditions a systematic deviation in comparison with forest management inventory data becomes evident, has been reported by Arumäe & Lang (2016). There can be several contributing reasons for this systematic deviation, but the main origin of the difference is likely to be in the differences of methods used: single-tree sampling versus stand-wise variable-size point-based sampling (known also as Bitterlich sampling, or angle-count sampling). The variable-size point-based sampling has its hidden sets of field sampling based shortcomings that were reported by multiple authors (Eastaugh & Hasenauer, 2013; Packard & Radtke, 2007; Piqué
Based on different studies carried out in the last few decades, measured volumes of dead wood in naturally developing forests in Estonia vary greatly. There are several contributing factors: a) the time since the protection status (stand measurements often occur on protected sites), b) the current offset of dominant tree species and site conditions, c) stand age and/or d) the imprints of forest disturbance history (Jõgiste
Studies carried out in Estonia containing information about the volume of coarse woody debris (CWD) in unmanaged forests (located often in nature protection areas), or locating in both, unmanaged and commercial forests.
Location | Citation | Site description | Dominant tree species1 | Protection/management regime2 | Average amount of dead wood, m3/ha | |
---|---|---|---|---|---|---|
A | Karula National Park | (Köster |
water swamp forest, dry boreal forest | NS, BI, SP, BAR | NR and RMZ | 27.6 |
B | Alam-Pedja Nature Reserve | (Lõhmus |
mostly forests on wet soils | BI, SP, NS, CA, CAR, BAR, other | MAN | 9.0 |
NR | 6.2 | |||||
C | Lahemaa National Park | (Köster |
dry boreal, heath and ombro-trophic bog forests | NS, BI, SP | NR | 85.9 |
RMZ | 63.2 | |||||
D | Estonia | (Lõhmus & Kraut, 2010) | dry boreal forest | SP | mature MAN | 10 |
meso-eutrophic forest | conifer/deciduous mixtures | 62 | ||||
eutrophic boreo-nemoral forest | conifer/deciduous mixtures | 43 | ||||
water swamp forest | BAR, BI | 52 | ||||
dry boreal forest | SP | NAT | 36 | |||
meso-eutrophic forest | conifer/deciduous mixtures | 144 | ||||
eutrophic boreo-nemoral forest | conifer/deciduous mixtures | 198 | ||||
water swamp forest | BAR, BI | 140 | ||||
(Põldveer |
mixed oligo-mesotrophic and mesotrophic forests on mineral soils | SP | MAN | 28.9 | ||
REC | 33.9 | |||||
NAT | 49.3 | |||||
NS | MAN | 15.3 | ||||
REC | 46.6 | |||||
NAT | 85.1 |
Tree species and tree species codes are as follows: CA – Common aspen; BI – silver birch and downy birch; NS – Norway spruce; BAR – black alder; CAR – common alder; SP – Scots pine.
Protection/management regime are as follows: NR – in nature reserve, RMZ – in special or restricted management zone, NAT – in natural forest without visible signs of direct human influence, REC – in recovering forest with possible signs of past management, yet the present human impact on forest structure is insignificant, MAN – commercial forest.
Most of the studies presented in Table 8 did not provide information about the decay stages of dead wood; the exceptions were Lõhmus
Tree canopy structure and tree mortality patterns are related to certain site conditions, tree age and diameter distribution, dominant species, severity of disturbance, time since the last disturbance, and spatial structure in natural boreal forests (Shorohova