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Episodic, patchy disturbances characterize an old-growth Picea abies dominated forest landscape in northeastern Europe
Forest Ecology and Management 320 (2014) 96–103
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Episodic, patchy disturbances characterize an old-growth Picea abies dominated forest landscape in northeastern Europe Timo Kuuluvainen a,⇑, Tuomo H. Wallenius a, Heikki Kauhanen b, Tuomas Aakala a, Kari Mikkola c, Natalia Demidova d, Boris Ogibin d a
Department of Forest Sciences, University of Helsinki, P.O. Box 27, Latokartanonkaari 7, FIN-00014 Helsinki, Finland Metla Kolari, Muoniontie 21A, 95900 Kolari, Finland Metla Rovaniemi, Eteläranta 55, 96300 Rovaniemi, Finland d Northern Research Institute of Forestry, Nikitov Str. 13, 163062 Archangelsk, Russia b c
a r t i c l e
i n f o
Article history: Received 6 November 2013 Received in revised form 14 February 2014 Accepted 17 February 2014 Available online 22 March 2014 Keywords: Boreal forest Forest dynamics Forest structure Landscape pattern Norway spruce Partial disturbance
a b s t r a c t The conventional theory of boreal forest dynamics recognizes two distinct disturbance regime types, small-scale gap dynamics and dynamics driven by large stand-replacing disturbances. We used satellite imagery and extensive field measurements to examine the landscape-level pattern and impact of an extensive disturbance episode that occurred in the early 2000s in primeval forest dominated by Picea abies in the Arkhangelsk region, Russia, due to drought and subsequent bark beetle (Ips typographus) outbreak. We also quantified forest age structures and deadwood characteristics at the landscape-level to study how such disturbances shape forest structures over larger scales. Satellite image analysis revealed that disturbance patches covered about 16% of the land area in the 12 km 12 km landscape studied. The size of the disturbance patches was strongly skewed toward small ones (median size 0.12 ha) and they were distributed across the landscape with some tendency of aggregation. The landscape forest matrix was dominated by old-growth forest. The dominant trees in the forest were established prior to 1850, and approximately half of the forest had established prior to 1800. However, the patchy occurrence of younger forest suggests that the landscape previously was subject to patchy disturbance similar to the recent one. This conclusion also gained support from historical records. We conclude that the structure and dynamics of the studied primeval forest landscape was driven by the combined impact of small-scale ‘‘background’’ mortality (classical gap dynamics) and infrequent episodes of patchy intermediate severity and scale disturbances. Ó 2014 Elsevier B.V. All rights reserved.
1. Introduction Conventionally, the dynamics of boreal forests have been described to operate at two alternative spatial scales, small or large (Sernander, 1936; Hunter, 1993; Seymour et al., 2002). The small cycle dynamics refers to gap-phase dynamics taking place in latesuccessional forests as tree age related mortality due to fungi, insects and physical forces (McCarthy, 2001; Kneeshaw et al., 2011; Shorohova et al., 2009). On the other hand, the large cycle dynamics refers to occasional catastrophic stand-replacing disturbances due to physical factors such as severe fire or storms, which may occur irrespective of forest age and structure. Such severe disturbances initiate secondary successions from ‘‘bare ground’’ often characterized by even-aged forest development (Sirén, 1955; ⇑ Corresponding author. Tel.: +358 919158116; fax: +358 919158100. E-mail address: Timo.Kuuluvainen@helsinki.fi (T. Kuuluvainen). http://dx.doi.org/10.1016/j.foreco.2014.02.024 0378-1127/Ó 2014 Elsevier B.V. All rights reserved.
Syrjänen et al., 1994; Kneeshaw et al., 2011). However, the legitimacy of the conceptual model of the small cycle versus the large cycle model of forest dynamics has recently been questioned by accumulating evidence indicating that the reality is more diverse and that partial, intermediate severity disturbances play a significant role in boreal forest dynamics (Worrall et al., 2005; Kneeshaw et al., 2011; Kuuluvainen and Aakala, 2011). In European boreal forests, gap dynamics has been suggested to be a typical feature of unmanaged late-successional forests dominated by Norway spruce (Picea abies (L.) Karst.) (Sernander, 1936; Kuuluvainen, 1994; Shorohova et al., 2009; Kuuluvainen and Aakala, 2011). Norway spruce is a shade-tolerant but fire-intolerant tree species distributed across boreal Eurasia (Nikolov and Helmisaari, 1992). It thrives best on mesic and high to medium productive sites, but because of its shade-tolerance it is able to occupy also more dry and poor soils if forest fires are absent. It has even been suggested that the invasion of landscapes by Norway
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spruce can lower the probability of fire (Ohlson et al., 2011). In nonpyrogenic late-successional Norway spruce forests the main factors causing tree mortality include inter-tree competition and senescence (as predisposing factors), drought, pathogenic fungi, insects, and wind and snow breakage (Lännenpää et al., 2008; Aakala et al., 2011; Kneeshaw et al., 2011). In the created canopy gaps trees are able to regenerate continuously, especially in specific microsites such as tree fall pits and large decayed logs (Grenfell et al., 2011; Vodde et al., 2011). A regional-scale intermediate-severity disturbance episode has recently been reported in the extensive primeval spruce forests in north-western Russia (Nevolin et al., 2005; Ogibin and Demidova, 2009; Aakala et al., 2011). Research results indicate that the likely cause of this major forest dieback was a severe drought episode in the early 2000s (Aakala et al., 2011). Tree mortality was further increased by the bark beetle outbreak that followed due to abundance of dead and weakened trees. During the period 1999–2004 an average of 21% of P. abies were killed in five studied stands in the area (Aakala et al., 2011). At the stand scale, such an event has a profound and long-lasting impact on stand structure and its development (e.g. Aakala et al., 2011). However, we are lacking information on how such intermediate disturbances shape primeval forest structure at the landscape scale. This information is indispensable ‘‘reference knowledge’’ for developing ecosystem-based forest management and restoration approaches based on natural disturbance dynamics (Gauthier et al., 2009; Kauhanen et al., 2009; Kuuluvainen and Grenfell, 2012; Halme et al., 2013). In this study the purpose was to examine and document the landscape-level impact and pattern of the recent episodic disturbance in a primeval forest dominated by P. abies in the Archangelsk region in north-western Europe. We also documented the forest age structure and dead wood characteristics, to assess how disturbance shapes these structural features, and to assess its role as a landscape-level driver of forest dynamics. Finally, the results are discussed in the context of our current understanding of primeval spruce taiga forest dynamics and forest dynamics theory in general.
2. Materials and methods 2.1. Study area The study was carried out in the Arkhangelsk province, north-western Russia, at 63°00 N, 44°10 E, approximately 300 km southeast of the city of Arkhangelsk (Fig. 1). Our study area is located between Dvina and Pinega rivers in the southern part of a large primeval forest massif of around one million hectares (Lindholm et al., 2013). The area belongs to the transition zone between the middle-boreal and northern boreal vegetation zones (Ahti et al., 1968). Mean annual temperature is 2.0 °C and total precipitation 540 mm (mean 1900–1999). The coldest month is January (mean temperature 13.0 °C) and the warmest is July (15.1 °C). On average, highest precipitation occurs in August (72 mm) and February is the driest month (24 mm). The forests grow on thick quaternary deposits of gleyic podzoluvisols, which combined with the flat topography of the area leads to poor drainage (Batjes, 2005). The dominant series of forest types are according to Russian classification system Piceetum myrtilloso-hylocomiosum, P. polytrichoso-myrtillosum and P. myrtilloso-sphagnosum with Carex globularis and Equisetum sylvaticum (Zagidullina, 2009; Zagidullina and Lisitsyna, 2012; Zagidullina and Mirin, 2013). Herb-rich forests with tall herbs (e.g. Filipendula ulmaria, Aconitum septentrionale, Veratrum lobelianum and Cirsium oleraceum) prevail along creeks and in moist depressions.
97
Fig. 1. The geographic location of the study area in the Archangelsk region, NW Russia.
The forests have historically experienced very low anthropogenic influence; they have never been logged and are located far from settlements. However, light selective cuttings might have taken place locally during 19–20th centuries (Kuznetsov, 1912), when only a limited number of the best quality trees were removed from the forest. However, the forest is currently chipped away in its fringes by systematic clear cutting which is also visible in the southern part of our study area (see Fig. 4). Fire is evidently rather rare in the spruce-dominated landscapes (Ohlson et al., 2011). However, some isolated regenerated fire areas were visible in the satellite imagery covering an extended region, and some signs of past fires were also found in our specific study area. Historical accounts (Kuznetsov, 1912; Nevolin et al., 2005) and a recent stand scale analysis of disturbance history in the P. abies stands on mineral soils (Aakala et al., 2011) have shown that the study area has been subjected to episodic disturbances also in the past. In short, the forest has been subjected to several episodic disturbances during the past 200 years, between which stand dynamics were driven by small-scale gap dynamics. Based on an analysis of climate-tree growth relationships (Aakala and Kuuluvainen, 2011) and field observations on trees that were killed during the most recent episode, Aakala et al. (2011) concluded that the gleyic soils in the area predispose the shallow-rooted P. abies to droughts during exceptionally warm summers, which together with the bark beetle (Ips typographus) resulted in extensive tree mortality (see Fig. 2). These conclusions agree with descriptions from elsewhere in the region (Nevolin et al., 2005), suggesting a region-wide phenomenon, and reinforcing the idea of climate as the inciting factor.
2.2. Sampling The studied forest area was located about 60 km from the Dvina-river in the far end of a railway track that was recently built for forest cuttings in a natural spruce dominated landscape. The size of the landscape subject to field sampling was 72 km2, within which three different types of study plots were located and measured (Fig. 3). First, we systematically sampled 68 plots in a systematic grid of 8 km 9 km, with 1 km distance between neighboring plots (subsequently referred as grid plots). Second,
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Fig. 2. Photographs of disturbance patches created in the recent tree mortality episode. (a) A small patch with almost complete tree mortality and mostly downed dead trees. (b) A disturbance patch with only partial tree mortality and mostly standing dead trees.
we subjectively selected 14 plots (subjective plots) on representative sites of different vegetation types in the area. Finally, five transects (size 40 400 m) were located on representative nonpaludified mineral soil forests, each of these included four plots (transect plots) at 100 m intervals (data from Aakala et al., 2011). There was some variation in the site types represented by the sampled plots. Most of the plots belonged to the Piceetum myrtilloso-hylocomiosum site type class, but also plots representing P. polytrichoso-myrtillosum and paludified P. myrtilloso-sphagnosum site types existed. The center points of the grid and subjective plots were located with a GPS and temporarily marked with a small flagpole or other clear sign. The radius of the plots varied between 10–30 m, depending on the measured forest characteristic (smaller in dense and larger in sparse forest). When measuring trees in circular sample plots the inclusion or exclusion of border trees were checked by the distance measuring device Vertex (Haglöf Sweden AB, Lycksele, Sweden). 2.3. Land covers classification and satellite image analysis The study plots (and eventually the whole landscape) were classified into the following classes according to their land cover: (1) Dead standing tree patches (at least 20% of the coverage seen by the satellite is composed of dead trees, most of which were standing). (2) Fallen tree patches (at least 20% of the coverage seen by the satellite is composed of dead trees, most of which were fallen). (3) Herb rich and deciduous forests (at least 35% coverage of herbaceous plants or deciduous trees dominating the plot). (4) Spruce mires and spruce dominated forest. (5) Open peatlands and pine bogs. (6) Water. (7) Roads and recent clear cuttings.
The canopy coverage of different tree species were subjectively estimated within 20 m from the center of the study plots. In addition, coverage of herbaceous plants, dwarf shrubs, dead trees and other land covers were estimated in 5% classes. The sum of all coverage types was adjusted to be 100%. This means that for example coverage of herbaceous plants that grew under a dense canopy of trees was estimated to be smaller than similar herbaceous vegetation on treeless sites. Landsat 7 ETM satellite image acquired on 14.7.2006 (code: 177-16), was used in the analysis. The analyses were carried out using ERDAS Imagine satellite image analysis package. The study area of 12.3 12.1 km was clipped from the whole scene and its resolution was enhanced from the original 28.5 m pixel size to 14.25 m using the panchromatic channel and reverse principal component analysis method (Welch and Ehlers, 1987). The classification was done using supervised classification method. First a set of 35 training sample plots were used to generate spectral signatures for six landscape classes and the final classification was done using the fuzzy classification and convolution algorithm (Jensen, 1996). The classification accuracy was studied by comparing the results with the 68 grid plots (Fig. 3). Kappa statistics was calculated using Erdas Imagine. Kappa coefficient is a measure of agreement (Cohen, 1960) between the satellite image classification results and the verified control points (grid plots). The Kappa coefficient takes into account (subtracts) the expected agreement by chance. The overall classification accuracy was 72% and the Kappa statistics value was 0.47. This Kappa statistics value indicates that our classification was clearly better than an expected classification by chance. A random classification would yield a value close to zero and a perfect match would equal to one. Landis and Koch (1977) benchmark the Kappa statistics from 0.4 to 0.6 as ‘‘moderate’’. Our classification accuracy, though not excellent, should allow a fair interpretation of the results. 2.4. Forest age and dead wood The forest age on the systematic grid plots and subjectively located plots was studied by coring the three apparently oldest trees within 20 m from the center of each plot. In addition, in the transect plots three dominant or co-dominant trees closest to the transect centerline at 50, 150, 250, and 350 m were sampled. Increment cores were extracted from the trunk base as low as possible and the sampling height was recorded. A total of 332 increment cores were glued to core mounts and sanded for good visibility of the annual rings and finally analyzed for their age under a stereo microscope. Annual rings were counted from bark to the pith of tree. If the coring sample did not include the pith, the missing rings to the pith were estimated based on the curvature and thickness of the innermost annual ring (Arno and Sneck, 1977). Timber volume in the grid plots and subjective plots was determined based on relascope readings at three points located 15 m from the plot center in compass directions 60°, 180° and 300°. Diameters at breast height (DBH) and heights of median individuals of each tree species were measured. In order to obtain per hectare volumes for the different tree species, we first calculated the volume of each median tree, using volume integrals of Laasasenaho’s (1982) taper curves. Then, the basal area of the species was divided by the cross-sectional area of the median tree and then multiplied by the volume of the median tree. Finally, the volumes per hectare in a plot were calculated as the average of the three relascope points. Dead trees were inventoried for their species, DBH and decay class. The radius of the inventory was first selected depending on estimated number of dead trees. The aimed number of inventoried
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Fig. 3. The studied forest landscape and the location of the systematic grid plots (filled stars), subjectively located plots (single open circles) and the transect plots (open circles in rows).
trees was 20 within a radius of 30 m at maximum. All trees exceeding 10 cm at breast height within the pre-selected radius were measured. The locations of fallen trees were determined based on the stump. Logs without apparent stump but thicker end within the plot radius were also measured. Standing dead trees were classified into 5 decay classes based on the position (standing or fallen) and presence of needles and branches of certain order, as well as the shape of the log (see Table 1).
3. Results
than 8 ha (Fig. 5). The mean size of disturbance patches was 0.50 ha (SD = 2.76) and the median 0.12 ha, the minimum and maximum sizes being, 0.02 ha and 114.59 ha, respectively. The largest disturbance patch, located in the northern part of our study area (Fig. 4), was exceptional as the second-largest patches were only about 27 ha in size (Fig. 5). However, these descriptive statistics do not give the whole picture. Importantly, although the disturbance patches were spread all over the landscape, there was also a clear tendency towards aggregation (Fig. 4). This means that that the share of disturbance patches from land area varied greatly within the landscape.
3.1. Landscape structure and disturbance characteristics
3.2. Forest age distribution
Based on satellite image analysis, the disturbed patches comprised 14% of the landscape area, when excluding water and cut areas (Table 2 and Fig. 4). Disturbed area with fallen trees covered 3% and that with standing dead trees 11% of the landscape. In the following the adjacent fallen and standing dead tree disturbance patches are combined. This was done because the majority of both standing and fallen dead trees in the forest originated from the episodic disturbance 1999–2004, as shown by the study of Aakala et al. (2011 and Fig. 1 therein). In addition, these two types of disturbance patches, when spatially connected, together represent functional disturbance units with two different phases of development: patches of standing dead trees will soon become patches of fallen trees, as snags fall down. Altogether 2351 separate disturbance patches were detected in the land area of 8469 ha. The size distribution of disturbance patches was strongly skewed toward smaller patches, while larger patches were rare (skewness = 31.52, SE = 0.05; Fig. 5): 96% of patches were smaller than 2 ha and 99% of patches were smaller
In spite of the recent tree mortality episode (1999–2004, Aakala et al., 2011), the studied landscape was clearly dominated by old forest (Fig. 6). This was the conclusion both from data from the systematically located grid plots, and when subjectively located and transect plots were taken into analysis. A large majority of the forest had established prior to 1850. The oldest stands dated back to late 1600. Around half of the plots had trees established prior to 1800 and was thus over 200 years of age at the time of sampling in 2007. Only a few percent of plots represented forest younger than 100 years (Fig. 6). 3.3. Volumes of living and dead trees, decay class distributions Overall, the total wood volumes, including living and dead material, were around 300 m3 ha 1 in all land cover types, except for peatlands (which included open canopied pine mires) (Table 3). In the disturbance patches most of the wood volume was in standing or fallen dead trees. In these patches the total volume of dead
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Fig. 4. The study landscape with its main land cover elements and the distribution of the disturbance patches created in the recent tree mortality episode, according to the ground-truth based satellite image analysis.
Table 1 Decay classification and explanation of classes for standing (S1–S5) and downed (D) dead trees. All trees taller than 1.3 m where classified as standing trees. Class
Explanation
S1
Recently dead: small branches with at least some foliage (red/brown) still attached Foliage absent. Small twigs still present, cambium dried or absent Smallest twigs absent, largest branches still present Snapped. Only largest branches possibly present Less than 2 m high. Branches gone Similar to standing dead S1 Similar to standing dead S2 Similar to standing dead S3 Only largest branches possibly present, log shape round No branches, loss of log shape Covered with ground vegetation
S2 S3 S4 S5 D1 D2 D3 D4 D5 D6
Table 2 The distribution of the studied landscape into the main land cover types and the share of disturbance patches of the landscape area. Land cover type
a
trees was up to 200 m3 ha 1. However, these patches often also had significant amounts of living trees, indicating that the disturbance had been partial, i.e. killing only some proportion of the trees (see Fig. 2). As can be expected, the decay class distribution of standing dead spruce trees was weighted toward earlier decay stages (Fig. 7). From the relatively even distribution of downed spruce and birch trees into different decay classes it can be seen that the studied primeval forest is in general characterized by good continuity of dead wood (Fig. 7). The fact that standing dead trees represented early decay stages, while fallen logs were in later decay classes and lacked early decay stages (Fig. 7), indicates that trees in the studied forest have mostly died standing.
Area, ha
% of Area excluding water and recent cuttings
Dead standing tree patches Fallen tree patches
933 254
11.02 3.00
Total of disturbance patches
1187
14.02
Deciduous forest Spruce dominated forest Peatlands Water Recent cuttings
1654 4790 838 6 547
19.53 56.56 9.89 0.06a 5.36a
Total all
9022
From total landscape area.
4. Discussion In this study we examined the structure and disturbance characteristics of a primeval boreal forest landscape dominated by Norway spruce in northwestern Europe that had experienced a disturbance episode (1999–2004) triggered by severe drought and mediated by subsequent bark beetle outbreak (Aakala et al., 2011). The analysis based on satellite image mapping showed that the disturbance patches with fallen or standing dead trees covered around 14% of the land area of the forest landscape. Thus around 1/6 of the forest had suffered from total or partial tree
101
6
2266
4
40 18 12 5
2
Log (frequency)
8
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2
2
2 1
1
0
1
1
3
5
7
9
11 13 15 17 19 21 23 25 27
Size (ha) Fig. 5. The frequency distribution of disturbance patches in area classes in the studied landscape. Adjacent disturbance patches with standing and downed tree are combined. The largest ‘outlier’ patch (115 ha) was excluded from the data. Note the logarithmic scale of the y-axis. The actual frequencies are marked above bars.
Fig. 6. The age class distribution of forest in the sample plots, shown separately in systematic grid plots, subjectively located plots and transect plots.
mortality at the time of analysis (satellite photo taken 2006) (Fig. 4). The size distribution of disturbance patches was strongly weighted toward small ones. The median patch size was 0.12 ha and 96% of the patches were smaller than 2 ha (Fig. 5). This kind of distribution of canopy openings (gaps, patches) has also previously been documented in pristine late-successional boreal forests, subjected to episodic disturbances (e.g. Kneeshaw and
Bergeron, 1998; Pham et al., 2004; Caron et al., 2009). However, the studied landscape also had some larger disturbance patches: the largest one was 115 ha in size (Figs. 4 and 5). In general, the disturbance patches were distributed all across the landscape but some degree of aggregation was evident (Fig. 4). One possible explanation for this is that some parts of the landscape were more susceptible to the disturbance than others. Stands on mineral soils appeared be influenced more than paludified sites (personal observation), supporting the idea of drought as an inciting factor (Aakala and Kuuluvainen, 2011; Aakala et al., 2011). However, the aggregation tendency may also be due to the bark beetle outbreak spreading from drought-killed foci of trees into the adjacent similarly drought-stressed forest. The predominantly small size of the patches is also consistent with the short dispersal distance of I. typographus in outbreak situations (Wermelinger, 2004). Apart from the disturbance patches, the studied landscape was dominated by old spruce forest. This ‘matrix’ forest was evidently characterized by continuous ‘background tree mortality’ (Fig. 1 in Aakala et al., 2011), conforming to the classical gap-phase disturbance regime of late-successional forests (Kuuluvainen, 1994). This kind of dynamics provides a continuous supply of dead wood, where all decay classes are continuously present in the forest (Fig. 7). Our results thus corroborate the earlier conclusions by Aakala et al. (2011) and, importantly, extend them to the landscape-scale, as opposed to their stand scale analysis. The landscape disturbance regime, as a whole, can be described as consisting of this background dynamics, with infrequent episodes of higher tree mortality, which was triggered by summer drought and accentuated by subsequent bark beetle outbreaks (Aakala et al., 2011). Unfortunately, our satellite image analysis did not allow separation of background mortality patches from the episodic mortality patches. Moreover, distinguishing these two theoretically different disturbance patch types may be difficult, because they are probably spatially intermingled in the landscape. The sparse occurrence of younger forest in the old-growth dominated landscape (Fig. 6) suggest that patchy disturbance, similar to that observed in the recent episode, has also taken place in the past in the landscape. This conclusion is also in agreement with the historical accounts available from the area (Kuznetsov, 1912; Nevolin et al., 2005). However, Aakala et al. (2011) suggested, based on dendrochronological disturbance reconstruction that the recent disturbance magnitude may have been more severe compared to the earlier ones. 4.1. Implications for forest dynamics theory According to conventional understanding of boreal forest dynamics, primeval forests are characterized by two alternative modes of disturbance regimes. Small scale gap dynamics are
Table 3 The volumes of living and dead spruces, birches and other tree species as divided into the main land cover types in the study area. Based on systematic grid plots and subjectively located plots (see Fig. 3). Land cover type
Dead standing tree patches Fallen tree patches Deciduous forest Spruce dominated forest Peatlands Recent cuttings Mean of landscapea a
Excluding recent cuttings.
Living tree vol., m3 ha
1
Dead tree vol., m3 ha
1
Total tree vol., m3 ha
Spruce
Birch
Others
Spruce
Birch
Others
67.0 32.7 142.7 138.4 18.6 18.0 111.7
18.0 36.3 35.9 21.2 12.9 – 22.4
1.6 3.7 – 1.2 13.4 – 2.6
178.8 193.0 129.6 95.6 22.8 13.5 98.5
52.0 10.0 8.8 10.0 – 2.5 11.1
– – – 12.1 – 1.6
317.4 275.7 317.0 266.4 79.8 34.0 247.9
1
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Volume of dead trees, m3
Volume of dead trees, m3
102
Spruce snags
30
20
20
10
10
0
1
2
3
4
5
Birch snags
3
0
2
1
1
0
0 2
3
1
4
5
2
3
4
5
6
Birch downed woody debris
3
2
1
Spruce downed woody debris
30
1
2
3
4
5
6
Decay class
Decay class
Fig. 7. Decay class distributions of spruce snags, spruce downed woody debris, birch snags, birch downed woody debris. For description of decay classes see Table 1.
considered to be prevalent in late-successional forests which have escaped severe disturbances for long periods of time (Sernander, 1936; Kuuluvainen, 1994; Caron et al., 2009). On the other hand more rare large scale ‘catastrophic’ stand-replacing disturbances are thought to every now and then initiate even-aged stand development (Sirén, 1955; Hunter, 1993). These two disturbance regimes can be termed small cycle and large cycle dynamics (Kuuluvainen, 2009). However, the results of this study from a primeval spruce dominated landscape do not conform to this dichotomy, but demonstrate a more complex and multi-scaled disturbance regime with a combination of continuous background mortality (small-scale gap dynamics) and periodical landscape-scale intermediate-severity mortality episodes. This regime conforms to the ‘nested bicycle’ model of forest dynamics suggested by Worrall et al. (2005), and documented in Picea-Abies forests in New Hampshire, USA, where gap-phase cycles are nested within the long-term disturbance cycle. Overall, our results demonstrate a complex pattern of disturbance dynamics that is characterized by multi-scaled spatiotemporal occurrence disturbances of varying severity. This observation is in concert with accumulating evidence from boreal forests from elsewhere, documenting the prevalence and ecological importance of small-scale disturbances and temporally variable intermediateseverity disturbances in natural boreal forest ecosystems (Lampainen et al., 2004; Wallenius, 2002; Wallenius et al., 2005; Worrall et al., 2005; Kneeshaw et al., 2011; Kuuluvainen and Aakala, 2011,). 5. Conclusions The documented landscape-level pattern and impacts of disturbances in a primeval P. abies dominated landscape in northwestern Europe, together with earlier studies (Aakala et al., 2011) and historical records (Kuznetsov, 1912; Nevolin et al., 2005) point out that this old-growth dominated forest landscape was characterized by a multi-scaled disturbance regime comprised of a combination of continuous background mortality (small-scale gap dynamics) and periodical landscape-scale intermediate-severity mortality episodes. The ecosystem is clearly resilient to this kind of
disturbance regime and able to reorganize (Fig. 2), and thus faces no threat of losing its ecological integrity due to disturbance, as has been feared. However, in the warming climate the drought and thus tree mortality episodes may become more severe. The harvesting of this forest is currently based on systematic clear cutting. To maintain some ecological qualities of the forest, a more diversified management approach should be implemented. To produce spatial pattern of disturbances similar to one documented in this study would require the use of a mix of clear cutting with variable retention and partial cutting and group harvesting. Acknowledgements We thank Roman Kurzhunov, Peter Peltonen, Andrei Sudakov, Nikolai Petuhov, Laura Kahala, Petteri Mönkkönen, Oksana Shvedova and Evgeni Mogutov for their valuable contribution in different parts of the research. References Aakala, T., Kuuluvainen, T., 2011. Summer droughts depress radial growth of Picea abies in pristine taiga of the Arkhangelsk province, northwestern Russia. Dendrochronologia 29, 67–75. Aakala, T., Kuuluvainen, T., Wallenius, T., Kauhanen, H., 2011. Tree mortality episodes in the intact Picea abies-dominated taiga in the Arkhangelsk region of northern European Russia. J. Veg. Sci. 22, 322–333. Ahti, T.L., Hämet-Ahti, L., Jalas, J., 1968. Vegetation zones and their sections in northwestern Europe. Annales Botanici Fennici 5, 169–211. Arno, S.F., Sneck, K.M., 1977. A method for determining fire history in coniferous forests of the mountain west. USDA Forest Service Intermountain Forest and Range Experiment Station, General Technical Report, INT-42. Batjes, N.H., 2005. SOTER-based soil parameter estimates for Central and Eastern. Caron, M.N., Kneeshaw, D.D., De Grandpré, L., Kauhanen, H., Kuuluvainen, T., 2009. Canopy gap characteristics and disturbance dynamics in old-growth Picea abies stands in northern Fennoscandia: is the forest in quasi-equilibrium? Annales Botanici Fennici 46 (4), 251–262. Cohen, J., 1960. A coefficient of agreement for nominal scales. Educ. Psychol. Measur. 20, 37–46. Gauthier, S., Vaillancourt, M.-A., Leduc, A., DeGarndpre, L., Kneeshaw, D., Morin, H., Drapeau, P., Bergeron, Y., 2009. Ecosystem management in the boreal forest. Presses de l ’ Université du Québec, Québec, Que. Grenfell, R., Aakala, T., Kuuluvainen, T., 2011. Microsite occupancy and the spatial structure of understory regeneration in three late-successional Norway spruce forests in northern Europe. Silva Fennica 45 (5), 1093–1110.
T. Kuuluvainen et al. / Forest Ecology and Management 320 (2014) 96–103 ˇ ada, V., Clear, J.L., Halme, P., Allen, K.A., Aunin ß š, A., Bradshaw, R.H.W., Brumelis, G., C Eriksson, A.-M., Hannon, G., Hyvärinen, E., Ikauniece, S., Irše˙naite˙, R., Jonsson, B.G., Junninen, K., Kareksela, S., Komonen, A., Kotiaho, J.S., Kouki, J., Kuuluvainen, T., Oldén, A., Mazziotta, A., Mönkkönen, M., Nyholm, K., Shorohova, E., Strange, N., Toivanen, T., Vanha-Majamaa, I., Wallenius, T., Ylisirniö, A.-L., Zin, E., 2013. Challenges of ecological restoration: lessons from forests in northern Europe. Biol. Conserv. 167, 248–256. Hunter Jr., M.L., 1993. Natural fire regimes as spatial models for managing boreal forests. Biol. Conserv. 65 (2), 115–120. Jensen, J.R., 1996. Introductory Digital Image Processing: A Remote Sensing Perspective, 2d ed. Prentice-Hall, Englewood Cliffs, New Jersey. Kauhanen, H., Neshataev, V., Huhta, E., Vuopio, M., 2009. Northern Coniferous Forests – Tools through research for the sustainable use of forests in the Barents Region. In Russian. Available at:. Kneeshaw, D., Bergeron, Y., 1998. Canopy gap characteristics and tree replacement in the southeastern boreal forest. Ecology 79, 783–794. Kneeshaw, D., Bergeron, Y., Kuuluvainen, T., 2011. Forest ecosystem structure and disturbance dynamics across the circumboreal forest. In: Millington, A., Blumler, M., Schickhoff, U. (Eds.). The SAGE Handbook of biogeography. Texas A&M. pp. 263–280. Kuuluvainen, T., 1994. Gap disturbance, ground microtopography, and the regeneration dynamics of boreal coniferous forests in Finland: a review. Biodiversity issue of Annales Zoologici Fennici 31, 35–51. Kuuluvainen, T., 2009. Forest management and biodiversity conservation based on natural ecosystem dynamics in northern Europe: the complexity challenge. Ambio 38 (6), 309–315. Kuuluvainen, T., Aakala, T., 2011. Natural forest dynamics in boreal Fennoscandia: a review and classification. Silva Fennica 45 (5), 823–841. Kuuluvainen, T., Grenfell, R., 2012. Natural disturbance emulation in boreal forest ecosystem management: theories, strategies and a comparison with conventional even-aged management. Can. J. For. Res. 42, 1185–1203. Kuznetsov, N.A., 1912. Dvina spruce forests. Lesnoi Zurnal 10, 1165–1204 (in Russian). Laasasenaho, J., 1982. Taper curve and volume functions for pine, spruce and birch. Communicationes Instituti Fororestalis Fenniae 108, 1–74. Lampainen, J., Kuuluvainen, T., Wallenius, T.H., Karjalainen, L., Vanha-Majamaa, I., 2004. Long-term forest structure and regeneration after wildfire in Russian Karelia. J. Veg. Sci. 15, 245–256. Landis, J.R., Koch, G.G., 1977. The measurement of observer agreement for categorical data. Biometrics 33 (1), 159–174. Lännenpää, A., Aakala, T., Kauhanen, H., Kuuluvainen, T., 2008. Tree mortality agents in pristine Norway spruce forests in northern Fennoscandia. Silva Fennica 42 (2), 151–163. Lindholm, T., Heikkilä, R., Kuhmonen, A., Jakovlev, J., 2013. The result of ecological gap analysis for nature conservation in northwest Russia to be utilized in international co-operation. In: Kobyakov, K., Jakovlev, J. (Eds.), 2013: Atlas of high conservation value areas, and analysis of gaps and representativeness of the protected area network in northwest Russia: Arkhangelsk, Vologda, Leningrad, and Murmansk Regions, Republic of Karelia, and City of St. Petersburg. Finnish Environment Institute, Helsinki, p. 517. McCarthy, J., 2001. Gap dynamics of forest trees: a review with particular attention to boreal forests. Environ. Rev. 9, 1–59. Nevolin, O., Gritsynin, A., Torkhov, S., 2005. On decay and downfall of over-mature spruce forests in Beresnik forestry unit of Arkhangelsk region. Lesnoi Zurnal 6, 7–22 (in Russian). Nikolov, N., Helmisaari, H., 1992. Silvics of the circumpolar boreal tree species. In: Shugart, H., Leemans, R., Bonan, G.B. (Eds.). A systems analysis of the global boreal forest. p. 13–84.
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Ogibin, B.N., Demidova, N.A., 2009. Successional dynamics of old-growth spruce forests in the watersheds of the rivers Northern Dvina-Pinega in the Arkhangelsk Region. In: Kauhanen, H., Neshataev, V., Huhta, E., Vuopio, M. (Eds.). Northern Coniferous Forests – tools through research for the sustainable use of forests in the Barents Region. Finnish Forest Research Institute, Helsinki (in Russian). Available at:. Ohlson, M., Brown, J.K., Birks, H.J.B., Grytnes, J.-A., Hörnberg, G., Niklasson, M., Seppa, H., Bradshaw, R.J.W., 2011. Invasion of Norway spruce diversifies the fire regime in the boreal European forests. J. Ecol. 99, 395–403. Pham, A.T., De Grandpre, L., Gauthier, S., Bergeron, Y., 2004. Gap dynamics and replacement patterns in gaps in the northeastern boreal forest of Quebec. Can. J. For. Res. 34, 353–364. Sernander, R., 1936. Granskär och Fiby urskog. En studie över stormluckornas och marbuskarnas betydelse i den svenska granskogens regeneration. Acta Phytogeographica Suecica 8, 232 p. Seymour, R.S., White, A.S., deMaynadier, P.G., 2002. Natural disturbance regimes in northeastern North America – evaluating silvicultural systems using natural scales and frequencies. For. Ecol. Manage. 155, 357–367. Shorohova, E., Kuuluvainen, T., Kangur, A., Jogiste, K., 2009. Natural stand structures, disturbance regimes and successional dynamics in the Eurasian boreal forests: a review with special reference to Russian studies. Annals For. Sci. 66 (2), 201. http://dx.doi.org/10.1051/forest/2008083. Sirén, G., 1955. The development of spruce forest on raw humus sites and its ecology. Acta Forestalia Fennica 62, 1–363. Syrjänen, K., Kalliola, R., Puolasmaa, A., Mattsson, J., 1994. Landscape structure and forest dynamics in subcontinental Russian European taiga. Ann. Zool. Fenn. 31, 19–34. Vodde, F., Jogiste, K., Kubota, Y., Kuuluvainen, T., Köster, K., Lukjanova, A., Metslaid, M., Yoshida, T., 2011. The influence of storm-induced microsites to tree regeneration patterns in boreal and hemiboreal forest. J. For. Res. http:// dx.doi.org/10.1007/s10310-011-0273-6. Wallenius, T., 2002. Forest age distribution and traces of past fires in a natural boreal landscape dominated by Picea abies. Silva Fennica 36 (1), 201–211. Wallenius, T., Pitkänen, A., Kuuluvainen, T., Pennanen, J., Karttunen, H., 2005. Fire history and forest age distribution of an unmanaged Picea abies dominated landscape. Can. J. For. Res. 35, 1540–1552. Welch, R., Ehlers, W., 1987. Merging multiresolution SPOT HRV and Landsat TM data. Photogram. Eng. Remote Sens. 53 (3), 301–303. Wermelinger, B., 2004. Ecology and management of the spruce bark beetle Ips typographus – a review of recent research. For. Ecol. Manage. 202, 67–82. Worrall, J.J., Lee, T.D., Harrington, T.C., 2005. Forest dynamics and agents that initiate and expand canopy gaps in Picea-Abies forests of Crawford Notch, New Hampshire, USA. J. Ecol. 93, 178–190. Zagidullina, A., 2009. Vegetation of intact forest landscape on the watershed between northern Dvina and Pinega rivers. In: Kauhanen, H., Neshataev, V., Vuopio, M. (Eds.). Finnish Forest Research Institute, Helsinki (in Russian). Zagidullina, A., Lisitsyna, O., 2012. The structure of vegetation and the pattern of the large-scale natural disturbances in pristine forest landscapes of Russian North (east part of Arkhangelsk region – west part of Komi Republic). Articles and Lectures of IV Conference ‘‘Actual problems of Geobotany’’, October 1–7, 2012, Ufa, Media print (in Russsian), pp. 382–390. Zagidullina, A., Mirin, D.M., 2013. Physical–geographical characteristics of the watershed between Northern Dvina and Pinega rivers. In: Gluškovskaya, N.B., Zagidullina, A.T., Korepanov, V.I., Kotkova, V.M., Kušnevskaya, Mirin, D.M., Stolpovsky, A.P., Filippov, B. Ju. (Eds.). Landscape and biodiversity in the watershed of Northern Dvina and Pinega, St. Petersburg (in Russian), 116 p.
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Forest Ecology and Management journal homepage: www.elsevier.com/locate/foreco
Episodic, patchy disturbances characterize an old-growth Picea abies dominated forest landscape in northeastern Europe Timo Kuuluvainen a,⇑, Tuomo H. Wallenius a, Heikki Kauhanen b, Tuomas Aakala a, Kari Mikkola c, Natalia Demidova d, Boris Ogibin d a
Department of Forest Sciences, University of Helsinki, P.O. Box 27, Latokartanonkaari 7, FIN-00014 Helsinki, Finland Metla Kolari, Muoniontie 21A, 95900 Kolari, Finland Metla Rovaniemi, Eteläranta 55, 96300 Rovaniemi, Finland d Northern Research Institute of Forestry, Nikitov Str. 13, 163062 Archangelsk, Russia b c
a r t i c l e
i n f o
Article history: Received 6 November 2013 Received in revised form 14 February 2014 Accepted 17 February 2014 Available online 22 March 2014 Keywords: Boreal forest Forest dynamics Forest structure Landscape pattern Norway spruce Partial disturbance
a b s t r a c t The conventional theory of boreal forest dynamics recognizes two distinct disturbance regime types, small-scale gap dynamics and dynamics driven by large stand-replacing disturbances. We used satellite imagery and extensive field measurements to examine the landscape-level pattern and impact of an extensive disturbance episode that occurred in the early 2000s in primeval forest dominated by Picea abies in the Arkhangelsk region, Russia, due to drought and subsequent bark beetle (Ips typographus) outbreak. We also quantified forest age structures and deadwood characteristics at the landscape-level to study how such disturbances shape forest structures over larger scales. Satellite image analysis revealed that disturbance patches covered about 16% of the land area in the 12 km 12 km landscape studied. The size of the disturbance patches was strongly skewed toward small ones (median size 0.12 ha) and they were distributed across the landscape with some tendency of aggregation. The landscape forest matrix was dominated by old-growth forest. The dominant trees in the forest were established prior to 1850, and approximately half of the forest had established prior to 1800. However, the patchy occurrence of younger forest suggests that the landscape previously was subject to patchy disturbance similar to the recent one. This conclusion also gained support from historical records. We conclude that the structure and dynamics of the studied primeval forest landscape was driven by the combined impact of small-scale ‘‘background’’ mortality (classical gap dynamics) and infrequent episodes of patchy intermediate severity and scale disturbances. Ó 2014 Elsevier B.V. All rights reserved.
1. Introduction Conventionally, the dynamics of boreal forests have been described to operate at two alternative spatial scales, small or large (Sernander, 1936; Hunter, 1993; Seymour et al., 2002). The small cycle dynamics refers to gap-phase dynamics taking place in latesuccessional forests as tree age related mortality due to fungi, insects and physical forces (McCarthy, 2001; Kneeshaw et al., 2011; Shorohova et al., 2009). On the other hand, the large cycle dynamics refers to occasional catastrophic stand-replacing disturbances due to physical factors such as severe fire or storms, which may occur irrespective of forest age and structure. Such severe disturbances initiate secondary successions from ‘‘bare ground’’ often characterized by even-aged forest development (Sirén, 1955; ⇑ Corresponding author. Tel.: +358 919158116; fax: +358 919158100. E-mail address: Timo.Kuuluvainen@helsinki.fi (T. Kuuluvainen). http://dx.doi.org/10.1016/j.foreco.2014.02.024 0378-1127/Ó 2014 Elsevier B.V. All rights reserved.
Syrjänen et al., 1994; Kneeshaw et al., 2011). However, the legitimacy of the conceptual model of the small cycle versus the large cycle model of forest dynamics has recently been questioned by accumulating evidence indicating that the reality is more diverse and that partial, intermediate severity disturbances play a significant role in boreal forest dynamics (Worrall et al., 2005; Kneeshaw et al., 2011; Kuuluvainen and Aakala, 2011). In European boreal forests, gap dynamics has been suggested to be a typical feature of unmanaged late-successional forests dominated by Norway spruce (Picea abies (L.) Karst.) (Sernander, 1936; Kuuluvainen, 1994; Shorohova et al., 2009; Kuuluvainen and Aakala, 2011). Norway spruce is a shade-tolerant but fire-intolerant tree species distributed across boreal Eurasia (Nikolov and Helmisaari, 1992). It thrives best on mesic and high to medium productive sites, but because of its shade-tolerance it is able to occupy also more dry and poor soils if forest fires are absent. It has even been suggested that the invasion of landscapes by Norway
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spruce can lower the probability of fire (Ohlson et al., 2011). In nonpyrogenic late-successional Norway spruce forests the main factors causing tree mortality include inter-tree competition and senescence (as predisposing factors), drought, pathogenic fungi, insects, and wind and snow breakage (Lännenpää et al., 2008; Aakala et al., 2011; Kneeshaw et al., 2011). In the created canopy gaps trees are able to regenerate continuously, especially in specific microsites such as tree fall pits and large decayed logs (Grenfell et al., 2011; Vodde et al., 2011). A regional-scale intermediate-severity disturbance episode has recently been reported in the extensive primeval spruce forests in north-western Russia (Nevolin et al., 2005; Ogibin and Demidova, 2009; Aakala et al., 2011). Research results indicate that the likely cause of this major forest dieback was a severe drought episode in the early 2000s (Aakala et al., 2011). Tree mortality was further increased by the bark beetle outbreak that followed due to abundance of dead and weakened trees. During the period 1999–2004 an average of 21% of P. abies were killed in five studied stands in the area (Aakala et al., 2011). At the stand scale, such an event has a profound and long-lasting impact on stand structure and its development (e.g. Aakala et al., 2011). However, we are lacking information on how such intermediate disturbances shape primeval forest structure at the landscape scale. This information is indispensable ‘‘reference knowledge’’ for developing ecosystem-based forest management and restoration approaches based on natural disturbance dynamics (Gauthier et al., 2009; Kauhanen et al., 2009; Kuuluvainen and Grenfell, 2012; Halme et al., 2013). In this study the purpose was to examine and document the landscape-level impact and pattern of the recent episodic disturbance in a primeval forest dominated by P. abies in the Archangelsk region in north-western Europe. We also documented the forest age structure and dead wood characteristics, to assess how disturbance shapes these structural features, and to assess its role as a landscape-level driver of forest dynamics. Finally, the results are discussed in the context of our current understanding of primeval spruce taiga forest dynamics and forest dynamics theory in general.
2. Materials and methods 2.1. Study area The study was carried out in the Arkhangelsk province, north-western Russia, at 63°00 N, 44°10 E, approximately 300 km southeast of the city of Arkhangelsk (Fig. 1). Our study area is located between Dvina and Pinega rivers in the southern part of a large primeval forest massif of around one million hectares (Lindholm et al., 2013). The area belongs to the transition zone between the middle-boreal and northern boreal vegetation zones (Ahti et al., 1968). Mean annual temperature is 2.0 °C and total precipitation 540 mm (mean 1900–1999). The coldest month is January (mean temperature 13.0 °C) and the warmest is July (15.1 °C). On average, highest precipitation occurs in August (72 mm) and February is the driest month (24 mm). The forests grow on thick quaternary deposits of gleyic podzoluvisols, which combined with the flat topography of the area leads to poor drainage (Batjes, 2005). The dominant series of forest types are according to Russian classification system Piceetum myrtilloso-hylocomiosum, P. polytrichoso-myrtillosum and P. myrtilloso-sphagnosum with Carex globularis and Equisetum sylvaticum (Zagidullina, 2009; Zagidullina and Lisitsyna, 2012; Zagidullina and Mirin, 2013). Herb-rich forests with tall herbs (e.g. Filipendula ulmaria, Aconitum septentrionale, Veratrum lobelianum and Cirsium oleraceum) prevail along creeks and in moist depressions.
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Fig. 1. The geographic location of the study area in the Archangelsk region, NW Russia.
The forests have historically experienced very low anthropogenic influence; they have never been logged and are located far from settlements. However, light selective cuttings might have taken place locally during 19–20th centuries (Kuznetsov, 1912), when only a limited number of the best quality trees were removed from the forest. However, the forest is currently chipped away in its fringes by systematic clear cutting which is also visible in the southern part of our study area (see Fig. 4). Fire is evidently rather rare in the spruce-dominated landscapes (Ohlson et al., 2011). However, some isolated regenerated fire areas were visible in the satellite imagery covering an extended region, and some signs of past fires were also found in our specific study area. Historical accounts (Kuznetsov, 1912; Nevolin et al., 2005) and a recent stand scale analysis of disturbance history in the P. abies stands on mineral soils (Aakala et al., 2011) have shown that the study area has been subjected to episodic disturbances also in the past. In short, the forest has been subjected to several episodic disturbances during the past 200 years, between which stand dynamics were driven by small-scale gap dynamics. Based on an analysis of climate-tree growth relationships (Aakala and Kuuluvainen, 2011) and field observations on trees that were killed during the most recent episode, Aakala et al. (2011) concluded that the gleyic soils in the area predispose the shallow-rooted P. abies to droughts during exceptionally warm summers, which together with the bark beetle (Ips typographus) resulted in extensive tree mortality (see Fig. 2). These conclusions agree with descriptions from elsewhere in the region (Nevolin et al., 2005), suggesting a region-wide phenomenon, and reinforcing the idea of climate as the inciting factor.
2.2. Sampling The studied forest area was located about 60 km from the Dvina-river in the far end of a railway track that was recently built for forest cuttings in a natural spruce dominated landscape. The size of the landscape subject to field sampling was 72 km2, within which three different types of study plots were located and measured (Fig. 3). First, we systematically sampled 68 plots in a systematic grid of 8 km 9 km, with 1 km distance between neighboring plots (subsequently referred as grid plots). Second,
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Fig. 2. Photographs of disturbance patches created in the recent tree mortality episode. (a) A small patch with almost complete tree mortality and mostly downed dead trees. (b) A disturbance patch with only partial tree mortality and mostly standing dead trees.
we subjectively selected 14 plots (subjective plots) on representative sites of different vegetation types in the area. Finally, five transects (size 40 400 m) were located on representative nonpaludified mineral soil forests, each of these included four plots (transect plots) at 100 m intervals (data from Aakala et al., 2011). There was some variation in the site types represented by the sampled plots. Most of the plots belonged to the Piceetum myrtilloso-hylocomiosum site type class, but also plots representing P. polytrichoso-myrtillosum and paludified P. myrtilloso-sphagnosum site types existed. The center points of the grid and subjective plots were located with a GPS and temporarily marked with a small flagpole or other clear sign. The radius of the plots varied between 10–30 m, depending on the measured forest characteristic (smaller in dense and larger in sparse forest). When measuring trees in circular sample plots the inclusion or exclusion of border trees were checked by the distance measuring device Vertex (Haglöf Sweden AB, Lycksele, Sweden). 2.3. Land covers classification and satellite image analysis The study plots (and eventually the whole landscape) were classified into the following classes according to their land cover: (1) Dead standing tree patches (at least 20% of the coverage seen by the satellite is composed of dead trees, most of which were standing). (2) Fallen tree patches (at least 20% of the coverage seen by the satellite is composed of dead trees, most of which were fallen). (3) Herb rich and deciduous forests (at least 35% coverage of herbaceous plants or deciduous trees dominating the plot). (4) Spruce mires and spruce dominated forest. (5) Open peatlands and pine bogs. (6) Water. (7) Roads and recent clear cuttings.
The canopy coverage of different tree species were subjectively estimated within 20 m from the center of the study plots. In addition, coverage of herbaceous plants, dwarf shrubs, dead trees and other land covers were estimated in 5% classes. The sum of all coverage types was adjusted to be 100%. This means that for example coverage of herbaceous plants that grew under a dense canopy of trees was estimated to be smaller than similar herbaceous vegetation on treeless sites. Landsat 7 ETM satellite image acquired on 14.7.2006 (code: 177-16), was used in the analysis. The analyses were carried out using ERDAS Imagine satellite image analysis package. The study area of 12.3 12.1 km was clipped from the whole scene and its resolution was enhanced from the original 28.5 m pixel size to 14.25 m using the panchromatic channel and reverse principal component analysis method (Welch and Ehlers, 1987). The classification was done using supervised classification method. First a set of 35 training sample plots were used to generate spectral signatures for six landscape classes and the final classification was done using the fuzzy classification and convolution algorithm (Jensen, 1996). The classification accuracy was studied by comparing the results with the 68 grid plots (Fig. 3). Kappa statistics was calculated using Erdas Imagine. Kappa coefficient is a measure of agreement (Cohen, 1960) between the satellite image classification results and the verified control points (grid plots). The Kappa coefficient takes into account (subtracts) the expected agreement by chance. The overall classification accuracy was 72% and the Kappa statistics value was 0.47. This Kappa statistics value indicates that our classification was clearly better than an expected classification by chance. A random classification would yield a value close to zero and a perfect match would equal to one. Landis and Koch (1977) benchmark the Kappa statistics from 0.4 to 0.6 as ‘‘moderate’’. Our classification accuracy, though not excellent, should allow a fair interpretation of the results. 2.4. Forest age and dead wood The forest age on the systematic grid plots and subjectively located plots was studied by coring the three apparently oldest trees within 20 m from the center of each plot. In addition, in the transect plots three dominant or co-dominant trees closest to the transect centerline at 50, 150, 250, and 350 m were sampled. Increment cores were extracted from the trunk base as low as possible and the sampling height was recorded. A total of 332 increment cores were glued to core mounts and sanded for good visibility of the annual rings and finally analyzed for their age under a stereo microscope. Annual rings were counted from bark to the pith of tree. If the coring sample did not include the pith, the missing rings to the pith were estimated based on the curvature and thickness of the innermost annual ring (Arno and Sneck, 1977). Timber volume in the grid plots and subjective plots was determined based on relascope readings at three points located 15 m from the plot center in compass directions 60°, 180° and 300°. Diameters at breast height (DBH) and heights of median individuals of each tree species were measured. In order to obtain per hectare volumes for the different tree species, we first calculated the volume of each median tree, using volume integrals of Laasasenaho’s (1982) taper curves. Then, the basal area of the species was divided by the cross-sectional area of the median tree and then multiplied by the volume of the median tree. Finally, the volumes per hectare in a plot were calculated as the average of the three relascope points. Dead trees were inventoried for their species, DBH and decay class. The radius of the inventory was first selected depending on estimated number of dead trees. The aimed number of inventoried
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Fig. 3. The studied forest landscape and the location of the systematic grid plots (filled stars), subjectively located plots (single open circles) and the transect plots (open circles in rows).
trees was 20 within a radius of 30 m at maximum. All trees exceeding 10 cm at breast height within the pre-selected radius were measured. The locations of fallen trees were determined based on the stump. Logs without apparent stump but thicker end within the plot radius were also measured. Standing dead trees were classified into 5 decay classes based on the position (standing or fallen) and presence of needles and branches of certain order, as well as the shape of the log (see Table 1).
3. Results
than 8 ha (Fig. 5). The mean size of disturbance patches was 0.50 ha (SD = 2.76) and the median 0.12 ha, the minimum and maximum sizes being, 0.02 ha and 114.59 ha, respectively. The largest disturbance patch, located in the northern part of our study area (Fig. 4), was exceptional as the second-largest patches were only about 27 ha in size (Fig. 5). However, these descriptive statistics do not give the whole picture. Importantly, although the disturbance patches were spread all over the landscape, there was also a clear tendency towards aggregation (Fig. 4). This means that that the share of disturbance patches from land area varied greatly within the landscape.
3.1. Landscape structure and disturbance characteristics
3.2. Forest age distribution
Based on satellite image analysis, the disturbed patches comprised 14% of the landscape area, when excluding water and cut areas (Table 2 and Fig. 4). Disturbed area with fallen trees covered 3% and that with standing dead trees 11% of the landscape. In the following the adjacent fallen and standing dead tree disturbance patches are combined. This was done because the majority of both standing and fallen dead trees in the forest originated from the episodic disturbance 1999–2004, as shown by the study of Aakala et al. (2011 and Fig. 1 therein). In addition, these two types of disturbance patches, when spatially connected, together represent functional disturbance units with two different phases of development: patches of standing dead trees will soon become patches of fallen trees, as snags fall down. Altogether 2351 separate disturbance patches were detected in the land area of 8469 ha. The size distribution of disturbance patches was strongly skewed toward smaller patches, while larger patches were rare (skewness = 31.52, SE = 0.05; Fig. 5): 96% of patches were smaller than 2 ha and 99% of patches were smaller
In spite of the recent tree mortality episode (1999–2004, Aakala et al., 2011), the studied landscape was clearly dominated by old forest (Fig. 6). This was the conclusion both from data from the systematically located grid plots, and when subjectively located and transect plots were taken into analysis. A large majority of the forest had established prior to 1850. The oldest stands dated back to late 1600. Around half of the plots had trees established prior to 1800 and was thus over 200 years of age at the time of sampling in 2007. Only a few percent of plots represented forest younger than 100 years (Fig. 6). 3.3. Volumes of living and dead trees, decay class distributions Overall, the total wood volumes, including living and dead material, were around 300 m3 ha 1 in all land cover types, except for peatlands (which included open canopied pine mires) (Table 3). In the disturbance patches most of the wood volume was in standing or fallen dead trees. In these patches the total volume of dead
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Fig. 4. The study landscape with its main land cover elements and the distribution of the disturbance patches created in the recent tree mortality episode, according to the ground-truth based satellite image analysis.
Table 1 Decay classification and explanation of classes for standing (S1–S5) and downed (D) dead trees. All trees taller than 1.3 m where classified as standing trees. Class
Explanation
S1
Recently dead: small branches with at least some foliage (red/brown) still attached Foliage absent. Small twigs still present, cambium dried or absent Smallest twigs absent, largest branches still present Snapped. Only largest branches possibly present Less than 2 m high. Branches gone Similar to standing dead S1 Similar to standing dead S2 Similar to standing dead S3 Only largest branches possibly present, log shape round No branches, loss of log shape Covered with ground vegetation
S2 S3 S4 S5 D1 D2 D3 D4 D5 D6
Table 2 The distribution of the studied landscape into the main land cover types and the share of disturbance patches of the landscape area. Land cover type
a
trees was up to 200 m3 ha 1. However, these patches often also had significant amounts of living trees, indicating that the disturbance had been partial, i.e. killing only some proportion of the trees (see Fig. 2). As can be expected, the decay class distribution of standing dead spruce trees was weighted toward earlier decay stages (Fig. 7). From the relatively even distribution of downed spruce and birch trees into different decay classes it can be seen that the studied primeval forest is in general characterized by good continuity of dead wood (Fig. 7). The fact that standing dead trees represented early decay stages, while fallen logs were in later decay classes and lacked early decay stages (Fig. 7), indicates that trees in the studied forest have mostly died standing.
Area, ha
% of Area excluding water and recent cuttings
Dead standing tree patches Fallen tree patches
933 254
11.02 3.00
Total of disturbance patches
1187
14.02
Deciduous forest Spruce dominated forest Peatlands Water Recent cuttings
1654 4790 838 6 547
19.53 56.56 9.89 0.06a 5.36a
Total all
9022
From total landscape area.
4. Discussion In this study we examined the structure and disturbance characteristics of a primeval boreal forest landscape dominated by Norway spruce in northwestern Europe that had experienced a disturbance episode (1999–2004) triggered by severe drought and mediated by subsequent bark beetle outbreak (Aakala et al., 2011). The analysis based on satellite image mapping showed that the disturbance patches with fallen or standing dead trees covered around 14% of the land area of the forest landscape. Thus around 1/6 of the forest had suffered from total or partial tree
101
6
2266
4
40 18 12 5
2
Log (frequency)
8
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2
2
2 1
1
0
1
1
3
5
7
9
11 13 15 17 19 21 23 25 27
Size (ha) Fig. 5. The frequency distribution of disturbance patches in area classes in the studied landscape. Adjacent disturbance patches with standing and downed tree are combined. The largest ‘outlier’ patch (115 ha) was excluded from the data. Note the logarithmic scale of the y-axis. The actual frequencies are marked above bars.
Fig. 6. The age class distribution of forest in the sample plots, shown separately in systematic grid plots, subjectively located plots and transect plots.
mortality at the time of analysis (satellite photo taken 2006) (Fig. 4). The size distribution of disturbance patches was strongly weighted toward small ones. The median patch size was 0.12 ha and 96% of the patches were smaller than 2 ha (Fig. 5). This kind of distribution of canopy openings (gaps, patches) has also previously been documented in pristine late-successional boreal forests, subjected to episodic disturbances (e.g. Kneeshaw and
Bergeron, 1998; Pham et al., 2004; Caron et al., 2009). However, the studied landscape also had some larger disturbance patches: the largest one was 115 ha in size (Figs. 4 and 5). In general, the disturbance patches were distributed all across the landscape but some degree of aggregation was evident (Fig. 4). One possible explanation for this is that some parts of the landscape were more susceptible to the disturbance than others. Stands on mineral soils appeared be influenced more than paludified sites (personal observation), supporting the idea of drought as an inciting factor (Aakala and Kuuluvainen, 2011; Aakala et al., 2011). However, the aggregation tendency may also be due to the bark beetle outbreak spreading from drought-killed foci of trees into the adjacent similarly drought-stressed forest. The predominantly small size of the patches is also consistent with the short dispersal distance of I. typographus in outbreak situations (Wermelinger, 2004). Apart from the disturbance patches, the studied landscape was dominated by old spruce forest. This ‘matrix’ forest was evidently characterized by continuous ‘background tree mortality’ (Fig. 1 in Aakala et al., 2011), conforming to the classical gap-phase disturbance regime of late-successional forests (Kuuluvainen, 1994). This kind of dynamics provides a continuous supply of dead wood, where all decay classes are continuously present in the forest (Fig. 7). Our results thus corroborate the earlier conclusions by Aakala et al. (2011) and, importantly, extend them to the landscape-scale, as opposed to their stand scale analysis. The landscape disturbance regime, as a whole, can be described as consisting of this background dynamics, with infrequent episodes of higher tree mortality, which was triggered by summer drought and accentuated by subsequent bark beetle outbreaks (Aakala et al., 2011). Unfortunately, our satellite image analysis did not allow separation of background mortality patches from the episodic mortality patches. Moreover, distinguishing these two theoretically different disturbance patch types may be difficult, because they are probably spatially intermingled in the landscape. The sparse occurrence of younger forest in the old-growth dominated landscape (Fig. 6) suggest that patchy disturbance, similar to that observed in the recent episode, has also taken place in the past in the landscape. This conclusion is also in agreement with the historical accounts available from the area (Kuznetsov, 1912; Nevolin et al., 2005). However, Aakala et al. (2011) suggested, based on dendrochronological disturbance reconstruction that the recent disturbance magnitude may have been more severe compared to the earlier ones. 4.1. Implications for forest dynamics theory According to conventional understanding of boreal forest dynamics, primeval forests are characterized by two alternative modes of disturbance regimes. Small scale gap dynamics are
Table 3 The volumes of living and dead spruces, birches and other tree species as divided into the main land cover types in the study area. Based on systematic grid plots and subjectively located plots (see Fig. 3). Land cover type
Dead standing tree patches Fallen tree patches Deciduous forest Spruce dominated forest Peatlands Recent cuttings Mean of landscapea a
Excluding recent cuttings.
Living tree vol., m3 ha
1
Dead tree vol., m3 ha
1
Total tree vol., m3 ha
Spruce
Birch
Others
Spruce
Birch
Others
67.0 32.7 142.7 138.4 18.6 18.0 111.7
18.0 36.3 35.9 21.2 12.9 – 22.4
1.6 3.7 – 1.2 13.4 – 2.6
178.8 193.0 129.6 95.6 22.8 13.5 98.5
52.0 10.0 8.8 10.0 – 2.5 11.1
– – – 12.1 – 1.6
317.4 275.7 317.0 266.4 79.8 34.0 247.9
1
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Volume of dead trees, m3
Volume of dead trees, m3
102
Spruce snags
30
20
20
10
10
0
1
2
3
4
5
Birch snags
3
0
2
1
1
0
0 2
3
1
4
5
2
3
4
5
6
Birch downed woody debris
3
2
1
Spruce downed woody debris
30
1
2
3
4
5
6
Decay class
Decay class
Fig. 7. Decay class distributions of spruce snags, spruce downed woody debris, birch snags, birch downed woody debris. For description of decay classes see Table 1.
considered to be prevalent in late-successional forests which have escaped severe disturbances for long periods of time (Sernander, 1936; Kuuluvainen, 1994; Caron et al., 2009). On the other hand more rare large scale ‘catastrophic’ stand-replacing disturbances are thought to every now and then initiate even-aged stand development (Sirén, 1955; Hunter, 1993). These two disturbance regimes can be termed small cycle and large cycle dynamics (Kuuluvainen, 2009). However, the results of this study from a primeval spruce dominated landscape do not conform to this dichotomy, but demonstrate a more complex and multi-scaled disturbance regime with a combination of continuous background mortality (small-scale gap dynamics) and periodical landscape-scale intermediate-severity mortality episodes. This regime conforms to the ‘nested bicycle’ model of forest dynamics suggested by Worrall et al. (2005), and documented in Picea-Abies forests in New Hampshire, USA, where gap-phase cycles are nested within the long-term disturbance cycle. Overall, our results demonstrate a complex pattern of disturbance dynamics that is characterized by multi-scaled spatiotemporal occurrence disturbances of varying severity. This observation is in concert with accumulating evidence from boreal forests from elsewhere, documenting the prevalence and ecological importance of small-scale disturbances and temporally variable intermediateseverity disturbances in natural boreal forest ecosystems (Lampainen et al., 2004; Wallenius, 2002; Wallenius et al., 2005; Worrall et al., 2005; Kneeshaw et al., 2011; Kuuluvainen and Aakala, 2011,). 5. Conclusions The documented landscape-level pattern and impacts of disturbances in a primeval P. abies dominated landscape in northwestern Europe, together with earlier studies (Aakala et al., 2011) and historical records (Kuznetsov, 1912; Nevolin et al., 2005) point out that this old-growth dominated forest landscape was characterized by a multi-scaled disturbance regime comprised of a combination of continuous background mortality (small-scale gap dynamics) and periodical landscape-scale intermediate-severity mortality episodes. The ecosystem is clearly resilient to this kind of
disturbance regime and able to reorganize (Fig. 2), and thus faces no threat of losing its ecological integrity due to disturbance, as has been feared. However, in the warming climate the drought and thus tree mortality episodes may become more severe. The harvesting of this forest is currently based on systematic clear cutting. To maintain some ecological qualities of the forest, a more diversified management approach should be implemented. To produce spatial pattern of disturbances similar to one documented in this study would require the use of a mix of clear cutting with variable retention and partial cutting and group harvesting. Acknowledgements We thank Roman Kurzhunov, Peter Peltonen, Andrei Sudakov, Nikolai Petuhov, Laura Kahala, Petteri Mönkkönen, Oksana Shvedova and Evgeni Mogutov for their valuable contribution in different parts of the research. References Aakala, T., Kuuluvainen, T., 2011. Summer droughts depress radial growth of Picea abies in pristine taiga of the Arkhangelsk province, northwestern Russia. Dendrochronologia 29, 67–75. Aakala, T., Kuuluvainen, T., Wallenius, T., Kauhanen, H., 2011. Tree mortality episodes in the intact Picea abies-dominated taiga in the Arkhangelsk region of northern European Russia. J. Veg. Sci. 22, 322–333. Ahti, T.L., Hämet-Ahti, L., Jalas, J., 1968. Vegetation zones and their sections in northwestern Europe. Annales Botanici Fennici 5, 169–211. Arno, S.F., Sneck, K.M., 1977. A method for determining fire history in coniferous forests of the mountain west. USDA Forest Service Intermountain Forest and Range Experiment Station, General Technical Report, INT-42. Batjes, N.H., 2005. SOTER-based soil parameter estimates for Central and Eastern. Caron, M.N., Kneeshaw, D.D., De Grandpré, L., Kauhanen, H., Kuuluvainen, T., 2009. Canopy gap characteristics and disturbance dynamics in old-growth Picea abies stands in northern Fennoscandia: is the forest in quasi-equilibrium? Annales Botanici Fennici 46 (4), 251–262. Cohen, J., 1960. A coefficient of agreement for nominal scales. Educ. Psychol. Measur. 20, 37–46. Gauthier, S., Vaillancourt, M.-A., Leduc, A., DeGarndpre, L., Kneeshaw, D., Morin, H., Drapeau, P., Bergeron, Y., 2009. Ecosystem management in the boreal forest. Presses de l ’ Université du Québec, Québec, Que. Grenfell, R., Aakala, T., Kuuluvainen, T., 2011. Microsite occupancy and the spatial structure of understory regeneration in three late-successional Norway spruce forests in northern Europe. Silva Fennica 45 (5), 1093–1110.
T. Kuuluvainen et al. / Forest Ecology and Management 320 (2014) 96–103 ˇ ada, V., Clear, J.L., Halme, P., Allen, K.A., Aunin ß š, A., Bradshaw, R.H.W., Brumelis, G., C Eriksson, A.-M., Hannon, G., Hyvärinen, E., Ikauniece, S., Irše˙naite˙, R., Jonsson, B.G., Junninen, K., Kareksela, S., Komonen, A., Kotiaho, J.S., Kouki, J., Kuuluvainen, T., Oldén, A., Mazziotta, A., Mönkkönen, M., Nyholm, K., Shorohova, E., Strange, N., Toivanen, T., Vanha-Majamaa, I., Wallenius, T., Ylisirniö, A.-L., Zin, E., 2013. Challenges of ecological restoration: lessons from forests in northern Europe. Biol. Conserv. 167, 248–256. Hunter Jr., M.L., 1993. Natural fire regimes as spatial models for managing boreal forests. Biol. Conserv. 65 (2), 115–120. Jensen, J.R., 1996. Introductory Digital Image Processing: A Remote Sensing Perspective, 2d ed. Prentice-Hall, Englewood Cliffs, New Jersey. Kauhanen, H., Neshataev, V., Huhta, E., Vuopio, M., 2009. Northern Coniferous Forests – Tools through research for the sustainable use of forests in the Barents Region. In Russian. Available at:
103
Ogibin, B.N., Demidova, N.A., 2009. Successional dynamics of old-growth spruce forests in the watersheds of the rivers Northern Dvina-Pinega in the Arkhangelsk Region. In: Kauhanen, H., Neshataev, V., Huhta, E., Vuopio, M. (Eds.). Northern Coniferous Forests – tools through research for the sustainable use of forests in the Barents Region. Finnish Forest Research Institute, Helsinki (in Russian). Available at: