Importance of stand structure and neighborhood in European beech regeneration

Forest Ecology and Management 448 (2019) 57–66

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Importance of stand structure and neighborhood in European beech regeneration

T

⁎

Povilas Žemaitisa, , Wojciech Gilb, Zbigniew Borowskib a b

Institute of Forestry, Lithuanian Research Centre for Agriculture and Forestry, Liepų str. 1, Girionys, Kaunas District LT-53101, Lithuania Forest Research Institute, Sękocin Stary, Braci Leśnej 3, 05–090 Raszyn, Poland

A R T I C LE I N FO

A B S T R A C T

Keywords: Fagus sylvatica Seedlings Saplings Closed canopy Ontogeny Competition Understory

The European beech (Fagus sylvatica L.) is a competitive and shade-tolerant species, with its natural regeneration in closed-canopy stands affected by a number of variables. The study aimed to identify factors related to beech regeneration by focusing on two main questions: (1) can we identify environmental and stand structural characteristics that promote beech regeneration or indicate suitable conditions for regeneration under closed canopy conditions, and (2) do environmental and stand structural characteristics favorable for beech regeneration differ among the ontogeny of seedlings and saplings? To answer these questions, we sampled four beech-dominated forest complexes in northern and southern Poland. Study plots were established in sites with varying overstory composition, including beech-dominated, mixed, and conifer-dominated stands. In the analyzed forest complexes, regeneration consisted mostly of beech seedlings and saplings with admixture of shade tolerant or intermediate light-tolerant species—Norway spruce (Picea abies (L.) Karst.), silver fir (Abies alba Mill.), hornbeam (Carpinus betulus L.), and sycamore maple (Acer pseudoplatanus L.). The average density of beech regeneration was 9047, 10,305, 5198 and 8972 trees ha−1 in forest complexes 1, 2, 3 and 4, respectively; however, the interplot variation of the regeneration density was high. Beech regeneration occurrence were determined by stand structural characteristics. Beech regeneration decreases as stand density increases and increases with stand basal area and the percentage of beech in the dominant canopy layer. The ecological prerequisites favorable for beech regeneration abundance differ with the ontogeny of seedlings and saplings—the smallest seedlings regeneration was determined by stand structural variables to a greater extent, while more advanced regeneration abundance was also associated with light-demanding species regeneration abundance. Under closed canopy conditions, beech regeneration abundance was weakly influenced by intra/interspecific competition from surrounding vegetation; however, canopy openings may increase it, therefore, competition aspects should be taken into account in the selection of forest management practices.

1. Introduction Tree species range limits and their success in creating forest communities depend on their physiological optimums and tolerance for climatic (Svenning and Skov, 2005; Normand et al., 2009) and edaphic conditions (Velazco et al., 2017), biotic stressors (pests, pathogens, game browsing) (HilleRisLambers et al., 2013), growth strategy, and interspecific competitiveness (Ettinger and HilleRisLambers, 2017). Identification of tree species’ growth strategies, such as shade tolerance, growing speed, and longevity, could be important for assessing woody plants invasions (Closset-Kopp et al., 2007; Martin et al., 2009; Shouman et al., 2017), long-term forest dynamics (Canham, 1989; Valladares and Niinemets, 2008; Heiri et al., 2009) and developing forest management systems (Schütz, 2002). It is evident that tree ⁎

species’ shade tolerance is crucial for natural forest regeneration under a closed canopy, enables the changing of stand structure without external triggers such as natural or anthropogenic disturbances, and maintains the stability and continuity of forest biocoenosis (Hunter and Barbour, 2001; Klopčič et al., 2015; Lienard et al., 2015). If tree species’ ability to compete with other tree species is described by the natural range and abundance of biogeocoenoses within range, then European beech (Fagus sylvatica L.) can be named as one of the most competitive species in Central Europe’s deciduous forests (Boratyńska and Boratyński, 1990; Ellenberg and Leuschner, 2010). European beech has a very high shade tolerance, which typically leads to the dominance of beech in European forest ecosystems (Ellenberg and Leuschner, 2010). Based on the frequency of mast years, European beech generally reproduce by natural regeneration occurring every

Corresponding author. E-mail addresses: [email protected] (P. Žemaitis), [email protected] (W. Gil), [email protected] (Z. Borowski).

https://doi.org/10.1016/j.foreco.2019.05.066 Received 27 February 2019; Received in revised form 24 May 2019; Accepted 26 May 2019 0378-1127/ © 2019 Elsevier B.V. All rights reserved.

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Fig. 1. Regeneration study areas in Poland (A) and schematic sampling design in each forest complex (B).

related but also determined by stand structural characteristics such as stand density or overstory species composition (transparent crown species) (Pretzsch et al., 2015). One good example is a multi-layered canopy of Scots pine (Pinus sylvestris L.) stands with an admixture of beech (Pretzsch et al., 2015). The admixture of coniferous tree species in beech stand has a positive effect on light penetration through the canopy (Emborg, 1998; Ligot et al., 2016; Forrester et al., 2018). A wide spectrum of variables contribute to beech regeneration (Madsen and Larsen, 1997; Ponge and Ferdy, 1997; Coll et al., 2003; Collet and Chenost, 2006; Olesen and Madsen, 2008), so regeneration patterns and understory species composition cannot be explained simply by light conditions in certain parts of a stand or canopy gap (Rozenbergar et al., 2007). High density of advanced regeneration could lead to sparse new regeneration due to inter/intra-specific competition (Lin et al., 2014). Competition from ground-layer vegetation must also be considered as a factor (Mountford et al., 2006). However, the selection of forest site-dependent shelterwood management strategies reduce competition from surrounding vegetation (Diaci et al., 2012; Vacek et al., 2017). Moreover, different environmental and stand structural conditions are important among the seedlings’ ontogeny (Ammer et al., 2008; Klopčič et al., 2015) and are likely climate dependent (Silva et al., 2012). A study by Silva et al. (2012) shows that beech regeneration patterns and seedlings’ vitality at the southwest distribution edge are influenced by climatic conditions; higher precipitation and temperature during the growing season increased seedling density, while late spring and early autumn frosts caused it to decrease. Despite the fact that factors affecting beech regeneration abundance

3–10 years on average (Drobyshev et al., 2010; Bogdziewicz et al., 2017). The quantity and quality of the seed rain are important factors for successful forest regeneration (Hofgaard, 1993; Olesen and Madsen, 2008). Success of the initial beech seedling establishment and development is determined by the environmental conditions in the regeneration niche (Peltier et al., 1997; Topoliantz and Ponge, 2000). Although beech tolerates very low light, seedling density and mortality rate is closely related to light regime (Emborg, 1998; Petritan et al., 2007; Olesen and Madsen, 2008; Wagner et al., 2010). Seedling establishment is related both to stand development phase (Topoliantz and Ponge, 2000) and stand structural characteristics (Emborg, 1998; Klopčič et al., 2015), as this alters the light regime below the canopy. Canopy gaps caused by natural forest dynamics (treefall due to competition and tree age), windthrow, or forest management practices could be crucial for regeneration and could further influence saplings’ development and establishment in the lower (middle) canopy layer or could impact the ability of beech (Collet et al., 2001; Mountford et al., 2006; Kenderes et al., 2008) and other tree species to reach the dominant canopy layer (Canham, 1988; Coates and Burton, 1997; Yamamoto, 2000; Baier et al., 2007; Berg et al., 2018). The size, shape, age, and temporal changes of gaps influence the regeneration patterns due to ecological traits of the beech tree (Mountford et al., 2006; Kenderes et al., 2008). Also, the presence of advance regeneration could be an important factor in explaining regeneration patterns in artificially created gaps (Madsen and Hahn, 2008) because of growth release after the canopy opens (Collet and Chenost, 2006). Nevertheless, beech regeneration, establishment, and further development could be not only canopy-gap 58

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2.2. Sampling design and data collection

have previously been studied widely, few studies were focused on regularities among seedlings’ ontogeny (Rozenbergar et al., 2007; Ammer et al., 2008; Klopčič et al., 2015). Moreover, the factors which may have an impact on beech regeneration varied among the studies (Ammer et al., 2008; Klopčič et al., 2015). The idea of our study was to combine stand structural indicators used in forestry practices with overstory and understory neighborhood, ground-layer vegetation (herbs, moss and ferns), and coarse woody debris variables to identify factors that determine beech regeneration in closed-canopy stands in different developmental stages of natural beech regeneration. The research covers a variety of beech stands to increase generality of our results. We selected mixed and monospecific beech stands to focus on two main questions: (1) can we identify environmental and stand structural characteristics that promote beech regeneration or indicate suitable conditions for regeneration under closed canopy conditions, and (2) do environmental and stand structural characteristics favorable for beech regeneration differ among seedlings and saplings?

Two transects were established 400–600 m apart in each forest complex. Ten study plots were established on each transect, yielding a total of 80 plots (per four forest complexes) that were spaced every 100 m. Three study plots (Forest complex 1) were removed from the analyses due to heavy wind outbreaks. Around each study plot center, three concentric circular subplots were established: P1 = 10 m2 (radius 1.78 m), P2 = 100 m2 (radius 5.64 m) and P3 = 500 m2 (radius 12.62 m) (Fig. 1B) (Czerepko, 2008). All ground-layer vegetation species were identified, and their percent cover was estimated visually. Three groups of ground-layer vegetation were distinguished: ferns, moss, and herbs. Regenerating trees of all species, defined as individuals with diameter at breast height (DBH) ≤ 7 cm, were assigned to three development stages according to their height: H0 ≤ 50 cm, H1 = 51–130 cm and H2 < 130 cm. Development stage H0 was assessed in the P1 sample area, and development stage H1 and H2 were assessed in the P2 sample area. Ground-layer vegetation cover was assessed in the P2 sample area. Trees with DBH > 7 cm were assessed in a P3 sample area and were considered overstory. DBH, tree height, number of tree species per plot, and number of trees per plot were assessed for all overstory trees. Ground-level quantity of coarse woody debris was also estimated and plotted on a P3 sample area using methodology applied in the project BioSoil Forest Biodiversity as per Czerepko (2008). In brief, measurements were made on circular subplots with an area of 500 m2, on which fallen dead trees (coarse woody debris), stumps, and snags were measured. Stumps were included in the analysis if their diameter was greater than 10 cm. The cubic volume of coarse woody debris wood was calculated. The coarse woody debris was grouped into three categories: total coarse woody debris, coarse woody debris of deciduous trees, and coarse woody debris of coniferous trees.

2. Methods 2.1. Study area In this study, four forest complexes were selected in northern and southern Poland. Sudety Zachodnie (Forest Complex 1) and Lasy Bieszczadzkie (Forest Complex 3) represented northern Polish higher elevation beech forests, while Lasy Elbląsko-Żulawskie (Forest Complex 2) and Lasy Środkowopomorskie (Forest Complex 4) represented southern Polish lowland beech forests (Fig. 1A). The study plots in Sudety Zachodnie forest complex were located near Szklarska Poręba city (50°49′32″N, 15°31′21″E) at an altitude of 700 m a.s.l. The temperature in this location ranges from 14.2 °C in the warmest month (July) to −1 °C in the coldest month (February), with an annual average temperature from 3.8 to 6.3 °C. The annual precipitation in this location is around 1073 mm. The study plots in Lasy Šrodkowopomorskie forest complex were located near Polanów city (54°07′10″N, 16°41′12″E). Temperature here ranges from 16.4 °C during the warmest month (July) to −1.7 °C in the coldest month (February), with an annual long-term average of 7.4 °C. The annual precipitation during the vegetation period is around 540 mm. The study plots in Lasy Elbląsko-Žulawskie forest complex were located near Elbląg city (54°09′07″N, 19°24′31″E). Temperature at this site ranges from 17.8 °C in the warmest month (July) and 2.3 °C in the coldest month (February), with an annual average of 7.5 °C. Annual precipitation ranges from 500 to 700 mm. The study plots in Lasy Bieszczadzkie forest complex were located near Wetlina village (49°08′54″N, 22°28′31″'E) at an altitude of 800 m a.s.l. The long-term average annual temperature in lower altitude (700–800 m a.s.l.) is 2.5–4 °C, with annual precipitation from 1000 to 1200 mm. The climate of all studied areas is temperate continental. Tree species composition in the four analyzed forest complexes varied from monospecific stands in Lasy Bieszczadzkie to mixed beech forests in the other three stands (Table 1). Brown acid soils are prevalent dominant in Sudety Zachodnie and Lasy Bieszczadzkie forest complexes, brown podzolic soils are prevalent in Lasy Šrodkowopomorskie, and brown acid soils and brown podzolic soils are both prevailing Lasy Elbląsko-Žulawskie. The forest stands in Lasy Šrodkowopomorskie, Sudety Zachodnie, and Lasy Elbląsko-Žulawskie had an average age of 140 years, whereas the stands in Lasy Bieszczadzkie were 100 years old on average. The analyzed experimental plots were located in stands where for the last 40 years no tending cuts and other planned harvesting was carried out. In the case of the youngest stands – in the Forest Complex 3, the lack of harvesting resulted from the limited availability of the area. Other forest complex stand characteristics are presented in Tables 1 and 2.

2.3. Data analysis Stand basal area was investigated for every study plot. Importance values in the overstory layer were calculated as follows: importance value = (relative density + relative basal area)/2 (Parker et al., 1985). Relative density was calculated as follows: relative density = (number of individuals of the species/number of individuals of all species) * 100. Relative basal area was calculated as follows: relative basal area = (basal area of the species/basal area of all species) * 100 (Cottam and Curtis, 1956). Stand volume was calculated according to the formula of the tree volume: vq = (π/40000) * d2 * h * fq, where vq – volume of the tree (m3), d – DBH (cm), h – tree height (m), fq – form factor of the stem. Sources of equations for DBH form factor are follows: silver fir (Bruchwald, 1992), Douglas fir (Pseudotsuga menziesii) (Kenk and Hradetzky, 1984), European larch (Larix decidua Mill.), European aspen (Populus tremula L.) and hornbeam (Bruchwald and Zasada, 2010; Wróblewski and Zasada, 2001), black alder (Alnus glutinosa L.) (Dudzińska and Bruchwald, 2003), pedunculated oak (Quercus robur L.), sycamore maple (Bruchwald et al., 1994), European beech of lowland origin (Dudzińska, 2003), European beech of mountain origin (Dudzińska, 2002), Norway spruce (Bruchwald and Rymer-Dudzińska, 1996), Scots pine (Bruchwald 1996). All variables were standardized to 1 ha. A principal components analysis (PCA) was used to visualize the multi-correlation structure of variables. Multinomial logistic regression was used to evaluate environmental and stand structural variables that determine the occurrence of beech regeneration. A general linear model was used to evaluate variables which determine abundance of different development stages of beech regeneration. A p < 0.05 was considered statistically significant. Best models were simplified to the minimal adequate model applying stepwise deletion (backward selection) of non-significant variables and interactions. Variables used in the analyses are presented in Table 3. The PCA was performed using CANOCO software (Ter Braak and Smilauer, 2002). Multinomial logistic 59

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Table 1 Characteristics of four analyzed forest complexes. Number are given as mean of sample plots in each forest complex. Forest complex

Number of sample plots

Forest type

Number of trees ha−1

Mean stand age

Basal area, m2 ha−1

DBH mean

Stand volume m3 ha−1

CWD, m3 ha−1

Species composition, % (calculated by basal area)

Beech importance value

1 2 3 4

17 20 20 20

MMFF MIFF MOFF MIFF

280 244 350 512

140 140 100 140

36.2 28.1 32.9 45.2

37.3 33.1 32.3 34.2

477.1 382.9 449.4 550.7

35.5 11.0 22.8 55.5

47PA36FS10LD5PS1PM1BP* 52FS17PA9LD8BP6PS4PT2AP2TC 98FS1AA1AP1AG 71FS15PS7BP5QR2CB

42.5 58.5 97.2 74.2

Note: MMFF – Mixed Mountain Fresh Forest; MIFF – Mixed Fresh Forest; MOFF – Mountain Fresh Forest; DBH – diameter at breast height; CWD – coarse woody debris. * e.g. 47PA36FS means that 47% of Picea abies and 36% of Fagus sylvatica consist of total forest overstory composition (calculated by basal area); PA – Picea abies; FS – Fagus sylvatica; LD – Larix decidua; PS – Pinus sylvestris; PM – Pseudotsuga menziesii; BP – Betula pendula; PT – Populus tremula; AP – Acer pseudoplatanus; TC – Tilia cordata; AA – Abies alba; AG – Alnus glutinosa; QR – Quercus robur; CB – Carpinus betulus.

of plots without any beech regeneration was observed among development stage H0. However, in forest complexes 2, 3, and 4, abundance of beech regeneration was highest from development stage H0, whereas in forest complex 1, it was highest from development stage H2. Other tree species’ regeneration was significantly less and was found in a very low percentage of plots.

regression and a general linear model were performed using STATISTICA 12 software (StatSoft, 2013).

3. Results 3.1. Forests structural characteristics and natural regeneration

3.2. Relations between explanatory variables and beech regeneration

The average density of living trees characterized by ≥7 cm DBH amounted to 280 ha−1, 244 ha−1, 350 ha−1, and 512 ha−1 in forest complexes 1, 2, 3, and 4, respectively (Table 1). The average diameter in forest complexes ranged from 32.3 to 37.3 cm. The average basal area in forest complexes 1, 2, 3, and 4 was 36.2 m2 ha−1, 28.1 m2 ha−1, 32.9 m2 ha−1, and 45.2 m2 ha−1. According to the results of the basal area analysis and beech importance value, European beech was the dominant component in forest complexes 2, 3, and 4; in forest complex 1, dominance was shared with Norway spruce (Picea abies (L.) Karst.) with an importance value of 42.5%. Forest complex 3 may be considered a monospecific beech forest. The average volume of coarse woody debris was highest in forest complex 4 at 55.5 m3 ha−1 and lowest in forest complex 2 at 11.0 m3 ha−1. Natural tree regeneration was observed in 66 plots (82.5%), with beech regeneration found in 64 of the 77 assessed plots (80.0%). In all forest complexes, regeneration generally consisted mostly of beech as follows: 85.5% in forest complex 1; 90.0% in forest complex 2; 83.1% in forest complex 3, and 92.5% in forest complex 4. The beech share of understory tree species composition was higher than its share in the dominant canopy layer (Table 1). In all forest complexes, an average of 7943 beech trees ha−1 were found per plot. The average density of beech regeneration was 9047, 10,305, 5198, and 8972 trees ha−1 in forest complexes 1, 2, 3, and 4, respectively, but the inter-plot variation of the regeneration density was high (Tables 4 and 5). Over forest complexes 1, 2, and 4, a lack of beech regeneration was detected in five (26%), eight (40%) and two (10%) plots, respectively; in forest complex 1, beech regeneration was observed in all plots. The highest percentage

A PCA yielded positions of the environmental and stand structural variables compared to beech regeneration abundance (Fig. 2). The position of the different development stages of beech regeneration indicates an association with different environmental and stand structural variables. Beech seedling stage H0 appeared to be associated with the second axis and stood opposite moss abundance. Development stage H1 correlated positively with with the coarse woody debris group, basal area and overstory density, and negatively with ground-layer vegetation including ferns, herbs, moss, and combined cover. The tallest beech saplings belonging to the H2 developmental stage correlated positively with the number of tree species per plot and basal area of coniferous trees in plot, and negatively with the average stand diameter, maximal beech tree diameter in a plot, and basal area of beech trees in a plot (Fig. 2). 3.3. Identification of explanatory variables for beech regeneration Beech regeneration did not occur in 20% of plots (Table 5). Therefore, we used two models to specify relevant explanatory variables of beech regeneration: (1) multinomial logistic regression to evaluate environmental and stand structural variables that determine the occurrence of regeneration, and (2) a general linear model to evaluate variables that determine the abundance of different development stages beech regeneration. Table 6 shows the effects of environmental and stand structural

Table 2 Distribution of trees (DBH ≥ 7 cm) in DBH classes in four forest complexes. Forest complex

DBH classes

1

N ha−1 (%)

2

N ha−1 (%)

3 4

N ha N ha

−1

−1

(%) (%)

1 > 7–15 cm

2 > 15–25 cm

3 > 25–35 cm

4 > 35–45 cm

5 > 45–55 cm

6 > 55–65 cm

7 > 65–75 cm

8 > 75–85 cm

Total

40 (14.3) 72 (29.5) 74 (21.1) 82 (16)

36 (12.8) 68 (27.9) 84 (24.0) 116 (22.8)

66 (23.6) 34 (13.9) 88 (25.1) 134 (26.3)

78 (27.9) 26 (10.8) 48 (13.7) 88 (17.3)

40 (14.3) 24 (9.8) 26 (7.4) 56 (10.6)

20 (7.1) 12 (4.9) 22 (6.3) 36 (7)

–

–

280 (100)

6 (2.4) 8 (2.3) –

2 (0.8) –

244 (100)

–

512 (100)

Note: DBH – diameter at breast height. 60

350 (100)

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Table 3 Variables used to explain beech regeneration. Species in the overstory and regeneration level are distinguished by capital letters and lower case letters. Explanatory variable

Abbreviation

Unit

Mean (min–max)

Neighborhood: Pedunculate oak in the overstory/regeneration European larch in the overstory/regeneration Hornbeam in the overstory/regeneration Silver fir in the overstory/regeneration Sycamore maple in the overstory/regeneration Norway spruce in the overstory/regeneration Silver birch in the overstory/regeneration European aspen in the overstory/regeneration Box elder in the overstory/regeneration Small-leaved lime in the overstory/regeneration Scots pine in the overstory/regeneration Black alder in the overstory/regeneration Douglas fir in the overstory/regeneration European beech in the overstory/regeneration Common hazel in understory Glossy buckthorn in understory European mountain ash in the regeneration

QR/Qr LD/Ld CB/Cb AA/Aa AP/Ap PA/Pa BP/Bp PT/Pt AN/An TC/Tc PS/Ps AG/Ag PM/Pm FS/Fs Ca Fa Sa

% of trees % of trees % of trees % of trees % of trees % of trees % of trees % of trees % of trees % of trees % of trees % of trees % of trees % of trees N ha−1 N ha−1 N ha−1

Coarse woody debris: Total Deciduous trees Coniferous trees

DWT DWD DWC

m3 ha−1 m3 ha−1 m3 ha−1

31.0 (0.1–158.4) 12.3 (0–62.5) 15.2 (0–117.3)

Stand parameters: Basal area, total Basal area, conifer trees Basal area, beech trees Average stand diameter Maximal diameter beech tree Overstory density Number of tree species per plot Stand volume

BA %Conifers %Beech D DB NT NS SV

m2 ha−1 % of total basal area % of total basal area cm cm N ha−1 N per plot m3 ha−1

34.8 (17.8–68.9) 7.9 (0–96) 70.3 (0–100) 34 (18.3–65.2) 46.1 (33–79) 179.2 (60–540) 1.9 (1–5) 460.1 (159.1–867.7)

Ground-layer vegetation cover: Total Moss Herbs Ferns

MFH Moss Herbs Ferns

% % % %

21.5 (0–85) 7.1 (0–50) 12.9 (0–80) 1.5 (0–10)

per per per per per per per per per per per per per per

ha−1*/N ha−1 ha−1/N ha−1 ha−1/N ha−1 ha−1/N ha−1 ha−1/N ha−1 ha−1/N ha−1 ha−1/N ha−1 ha−1/N ha−1 ha−1/N ha−1 ha−1/N ha−1 ha−1/N ha−1 ha−1/N ha−1 ha−1/N ha−1 ha−1/N ha−1

1.5 (0–23)/41 (0–1000) 4.3 (0–75)/62 (0–3600) 0.8 (0–52)/203 (0–9000) 0.9 (0–35)/97 (0–2000) 0.2 (0–9)/312 (0–15,000) 10.3 (0–92) /163 (0–6000) 3.8 (0–59)/15 (0–1000) 0.3 (0–9)/27 (0–2000) 0.5 (0–43)/4 (0–400) 0.4 (0–32)/1 (0–100) 4.1 (0–82)/189 (0–1400) 0.3 (0–7)/1 (0–100) 0.7 (0–51)/1 (0–100) 72.0 (0–100)/7943 (0–46,800) 19 (0–1300) 2.7 (0–100) 21 (0–2000)

* % of total trees per ha−1 were calculated by basal area.

Table 4 Natural regeneration abundance in four forest complexes. Number are given as mean of sample plots in each forest complex. Tree species are grouped in three shade tolerance categories. Shade tolerant species*

Intermediate shade tolerant*

Shade intolerant*

Forest complex

N of plots

Development stage

Fs, N ha−1

Aa, N ha−1

Cb, N ha−1

An, N ha−1

Ap, N ha−1

Pa, N ha−1

Tc, N ha−1

Sa, N ha−1

Ag, N ha−1

Sc, N ha−1

Ld, N ha−1

Bp, N ha−1

Qr, N ha−1

Pt, N ha−1

Ps, N ha−1

1

17

H0 H1 H2 H0-2

1650 1397 6000 9047

– – – –

– – – –

– – – –

– – – –

850 – – 850

– – – –

125 – 125

– – – –

25 – – 25

25 15 5 45

25 5 5 35

– – – –

– – – –

25 – – 25

2

20

H0 H1 H2 H0-2

9200 480 625 10,305

25 – – 25

225 3 – 228

– 3 8 11

125 – 23 148

225 58 13 296

200 – – 200

– 23 – 23

– – –

– – – –

50 – – 50

100 3 3 106

50 3 – 53

– – – –

– – – –

3

20

H0 H1 H2 H0-2

3075 958 1165 5198

100 73 192 365

– – – –

– – – –

675 3 – 678

– – – –

– – – –

– – – –

– – 3 5

– – – –

– – – –

– – – –

– – – –

– – – –

– – – –

4

20

H0 H1 H2 H0-2

6900 1687 385 8972

– – – –

500 – – 500

– – – –

– – – –

50 – – 50

– – – –

– – – –

– – – –

25 – – 25

– – – –

– – – –

125 – – 125

50 – – 50

– – – –

* Note: Tree species shade tolerance classified according Ellenberg (1979). H0 – beech regeneration (h ≤ 50 cm); H1 – beech regeneration (h = 51–130 cm); H2 – beech regeneration (h < 130 cm, DBH 7 cm or less); H0-2 – total beech regeneration. Fs – Fagus sylvatica; Aa – Abies alba; Cb – Carpinus betulus; An – Acer negundo; Ap – Acer pseudoplatanus; Pa – Picea abies; Tc – Tilia cordata; Sa – Sorbus aucuparia; Ag – Alnus glutinosa; Sc – Salix caprea; Ld – Larix decidua; Bp – Betula pendula; Qr – Quercus robur; Pt – Populus tremula; Ps – Pinus sylvestris. 61

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Table 5 Inter-plot beech regeneration in four forest complexes. Forest complex

Development stage

No. of sample plots

No. of plots without regeneration (given in %)

1

H0 H1 H2 H0-2

17

13 (76%) 9 (53%) 6 (35%) 5 (29%)

2

H0 H1 H2 H0-2

20

11 (55%) 15 (75%) 10 (50%) 8 (40%)

3

H0 H1 H2 H0-2

20

4 3 3 0

(20%) (15%) (15%) (0%)

4

H0 H1 H2 H0-2

20

9 8 6 2

(45%) (40%) (30%) (10%)

Note: H0 – beech regeneration (h ≤ 50 cm); H1 – beech regeneration (h = 51–130 cm); H2 – beech regeneration (h < 130 cm, DBH 7 cm or less); H0-2 – total beech regeneration.

variables on seedling and sapling occurrence based on the results of the multinomial logistic regression. The deletion of non-significant variables led to a model with a minimum of three explanatory variables. This model includes overstory density (OR: 0.837; 95% CI: 0.736–0.952), total basal area (OR: 1.073; 95% CI: 1.019–1.130), and basal area of beech trees (OR: 1.019; 95% CI: 1.002–1.036). The model shows that the probability of beech regeneration decreases as stand density increases and regeneration increases with stand basal area and basal area of beech trees in the dominant canopy layer. Table 7 shows the effects of environmental and stand structural variables on different development stages of seedling and sapling abundance based on the results of a general linear model. The regression model’s R2 varied between 0.18 (H0 model) and 0.66 (H1 model). Average stand diameter, coarse woody debris of coniferous trees, European aspen regeneration abundance, European aspen in the overstory, and European larch in the overstory were identified as important variables to overall regeneration abundance average. Among the three beech regeneration development stages, different variables were of importance for regeneration abundance. For beeches of the H0 development stage, the variables with significant effects were identified as total basal area, basal area of beech trees, overstory density, and pedunculate oak regeneration. Total coarse woody debris, abundance of H2 class beech regeneration, average stand diameter, and regeneration abundance variables of silver birch (Betula pendula Roth.), hornbeam (Carpinus betulus L.), and European larch had significant effects on H1 abundance. Finally, the basal area of coniferous trees in the stand, average stand diameter, and silver birch regeneration abundance were found to have significant effects on H2 abundance.

Fig. 2. Results of a principal components analysis (PCA) for the environmental and stand structural variables (a) and study plots (b). The length of the arrow is proportional to its importance and the angle between two arrows reflects the magnitude of the correlation between variables. PCA Axis 1 explains 23.36% of variation and PCA Axis 2 explains 15.91% of the variation. Variables are coded as follows: %Beech – basal area of beech trees; %Conifers – basal area of coniferous trees; D – average stand diameter; Moss – moss ground vegetation cover (%); Fern – ferns ground vegetation cover (%); Herbs – herbs ground vegetation cover (%); MFH – moss, ferns and herbs ground vegetation cover (%); NS – number of species per plot; H0 – beech regeneration (h ≤ 50 cm); H1 – beech regeneration (h = 51–130 cm); H2 – beech regeneration (h < 130 cm, DBH ≤ 7 cm); DB – maximal beech tree diameter in a plot; NT – overstory density (N ha−1); BA – total basal area (DBH > 7 cm); DWC – coarse woody debris of coniferous trees; DWD – coarse woody debris of deciduous trees; DWT – total coarse woody debris; SV – stand volume (m3 ha−1).

4. Discussion 4.1. Abundance of natural beech regeneration In all analyzed forest complexes, regeneration consisted mostly of beech seedlings and saplings. Beech share in the understory tree species composition was higher than in the dominant canopy layer. In forest complexes where beech markedly dominated in overstory tree species compositions (forest complex 3), total beech regeneration abundance was almost two times lower compared with mixed beech forests (Tables 1 and 4). Also, understory species composition was less numerous: only beech, silver fir, and sycamore maple (Acer pseudoplatanus L.) regeneration were found. While significantly higher more advanced

beech regeneration (H2) abundance was observed in forest complex 1, where lowest dominance of beech in overstory were identified. The amount of regeneration among other tree species, shade tolerant or intermediate light-tolerant species were most abundant: Norway spruce, silver fir (Abies alba Mill.), hornbeam, and sycamore maple (Acer pseudoplatanus L.). Beech dominance among the understory is likely determined by closed canopy conditions in which beech outcompete other species due to shade tolerance (Pena et al., 2010; 62

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Table 6 Results of multinomial logistic regression model for factors associated with beech regeneration performance. Model

Coefficient

Estimate

p-value

OR

95% CI

Model Chi2

Model p-value

H0-2

NT BA %Beech

−0.177 0.007 0.001

< 0.01 < 0.01 < 0.05

0.837 1.073 1.019

0.736–0.952 1.019–1.130 1.002–1.036

15.40

< 0.001

Note: H0-2 – total beech regeneration. NT – overstory density (N ha−1); BA – total basal area (DBH > 7 cm); %Beech – basal area of beech trees.

including coarse woody debris, basal area, stand diameter, overstory density, and ground layer vegetation cover (Table 3). Our model showed that, with increasing overstory density, the probability of beech regeneration occurrence decreases, as was also observed by Monserud and Sterba (1999). Negative overstory density impact on natural beech regeneration has also been stated in other studies (Madsen and Larsen, 1997; Collet et al., 2001, 2002; Agestam et al., 2003). Conspecific overstory composition and total basal area showed positive effects on beech occurrence, and previous studies have yielded similar results, showing that conspecific canopy composition may have a positive effect on regeneration density in the early development stages of seedlings (Wada and Ribbens, 1997; Annighöfer et al., 2015). In several studies, stand basal area was presented as a factor which negatively correlates with the light that penetrates the overstory, therefore usually determining lower regeneration abundance (Stancioiu and O’Hara, 2006). However, as was shown by Ramage and Mangana (2017), higher basal area of conspecific tree species may have a positive effect on seedlings’ density. For example, Klopčič et al. (2015) used a zero-inflated negative binomial model to show that basal area increased model odds in the recruitment of light-demanding and shade-tolerant species by 7.9% and 4.4%, respectively. In our analysis, we also used ground-layer vegetation cover as a variable, as this could describe site conditions and act as competing vegetation (Coll et al., 2003; Bílek et al., 2009; Vacek et al., 2017). PCA results showed that ground-layer vegetation and beech regeneration occupied opposite positions. However, the different variables representing ground vegetation were not identified as significant in our

Szwagrzyk et al., 2012). The slower regeneration (seedlings and saplings) growing rate of more light-demanding species has been described by Stancioiu and O’Hara (2006). Also, the much higher mortality of seedlings in their ‘establishment’, ‘overgrowth’ and ‘recruitment’ phases has been found by Klopčič et al. (2015). Even though average beech regeneration was abundant (Table 4), variability of regeneration abundance among plots was very high, with some plots lacking regeneration altogether, especially in the H0 seedling stage (Table 5). Data analysis also showed that the lack of H0 seedlings could not be explained by intraspecific competition with more developed beech saplings—that is, in plots without seedlings, regeneration was usually found in very low density (mostly less than a few hundred trees per ha−1) of more developed saplings. It also showed that lack of seedlings was not affected by interspecific competition with the understory woody vegetation layer because of the lack of regeneration of other tree species. 4.2. Variables determining the occurrence of beech regeneration Our results clearly show a variety of regeneration densities among the plots. We determined that variation of regeneration density is the outcome of stand structural characteristics and neighborhood. Previous studies have shown that natural beech regeneration and growth success depend on several variables, including stand structural characteristics, neighborhood, ground-layer vegetation, belowground resource availability, seedling age, light availability, and other factors (e.g., Ammer et al., 2008). Therefore, we analyzed a wide spectrum of variables,

Table 7 General linear models for factors associated with beech total beech regeneration abundance (H0-2) and regeneration in H0, H1, H2 seedlings development stages. Model

Coefficient

Beta

Std. err. of Beta

B

Std. err. of B

t

p

R2

p

H0

Intercept BA %Beech NT Qr

1908.1 44.9 16.3 113.9 2.8

−0.90 2.73 2.30 −1.92 1.74

0.37 < 0.01 < 0.05 < 0.05 0.08

< 0.01

0.140 0.111 0.136 0.108

−1719.8 122.8 37.6 −219.4 4.9

0.18

0.382 0.255 −0.263 0.189

Intercept DWT H2 D Bp Cb Ld

432.9 2.7 0.03 12.31 1.17 0.11 0.32

−1.59 5.76 6.20 1.54 4.61 3.67 3.02

0.11 < 0.00001 < 0.00001 0.09 < 0.00001 < 0.001 < 0.01

< 0.00001

0.071 0.072 0.076 0.075 0.072 0.076

−687.6 15.5 0.2 19.0 5.4 0.4 0.9

0.66

0.407 0.448 0.117 0.349 0.264 0.230

Intercept %Conifers D Bp

1662.5 152.9 41.3 945.6

−0.07 2.50 1.77 −2.91

0.94 < 0.05 < 0.05 < 0.01

< 0.001

0.105 0.105 1.105

−118.2 383.1 73.1 −2756.7

0.20

0.264 0.186 −0.308

Intercept D DWC Pt PT LD

2461.6 67.0 22.7 3.1 2658.1 1488.1

0.02 1.92 2.51 2.50 3.81 −2.03

0.98 < 0.05 < 0.05 < 0.05 < 0.001 < 0.05

< 0.00001

0.102 0.099 0.098 0.108 0.104

58.6 128.9 57.1 7.6 10130.0 −3025

0.35

0.198 0.248 0.246 0.414 −0.211

H1

H2

H0-2

Note: H0 – beech regeneration (h ≤ 50 cm); H1 – beech regeneration (h = 51–130 cm); H2 – beech regeneration (h < 130 cm, DBH 7 cm or less); H0-2 – total beech regeneration. BA – total basal area (DBH more than 7 cm); %Beech – basal area of beech trees; NT – overstory density (N ha−1); Qr – Quercus robur regeneration; DWT – total coarse woody debris; D – average stand diameter; Bp – Betula pendula regeneration; Cb – Carpinus betulus regeneration; Ld – Larix decidua regeneration; %Cinifers – basal area of coniferous trees; DWC – coarse woody debris of coniferous trees; Pt – Populus tremula regeneration; PT – Populus tremula in overstory; LD – Larix decidua in overstory. 63

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model for beech regeneration occurrence.

spectrum of variables that are important for beech seedlings occurrence and density. Previously, factors affecting beech regeneration abundance among seedlings’ ontogeny was almost unrecognized (Ammer et al., 2008); to some extent, this complicates interpretation of the results.

4.3. Variables determining abundance of beech regeneration We highlighted stand structural and environmental variables favorable for beech regeneration and demonstrated different ecological prerequisites for each developmental stage of beech regeneration abundance (Table 7). In our study, pioneer species and shade-intolerant species regeneration (silver birch, European aspen, pedunculated oak, and European larch) were selected as beech regeneration-associated factors. Regeneration abundance of this species could be associated with better light availability due to canopy gaps or other stand structural characteristics (Ligot et al., 2013; Annighöfer et al., 2015). According to regression analysis, H0 regeneration abundance was determined to a greater extent by stand structural characteristics (overstory density and stand basal area) and conspecific species composition, while light-demanding species regeneration were selected as important for more advanced regeneration (H1 and H2). More advanced regeneration was also associated with total coarse woody debris amount in the stand and the basal area of coniferous tree species in the overstory. In our study, total coarse woody debris amount differed significantly between plots from 0.1 m3 to 158.4 m3 (Table 3). Therefore, in plots with higher coarse woody debris amount, the overstory could be relatively open due to canopy gaps as an outcome of fallen trees. The relation between canopy gaps and downed coarse woody debris was revealed by Tanhuanpää et al. (2015). It has been previously shown that canopy gaps could create more favorable conditions for regeneration and sapling development in stands (Emborg, 1998; Topoliantz and Ponge, 2000; Collet et al., 2001; Kenderes et al., 2008). However, large canopy openings are not preferred for beech regeneration; small beech seedlings preferably recruit on microsites under closed canopy or close to the gap edges with lower levels of direct and diffuse radiation, as they do not prefer high levels of direct and diffuse radiation (Rozenbergar et al., 2007). According to Pretzsch (2014) conifer admixture in the overstory changes the canopy structure. Relative light intensity is very low under beech-dominant canopies, and the admixture of other tree species increases light penetration (Emborg, 1998; Forrester et al., 2018). Conspecific negative density dependence was shown for American beech (Fagus grandifolia Ehrh.) saplings density (Ramage and Mangana, 2017). In our investigated stands, coniferous trees constitute a considerable part of the basal area and 47% of plots had an admixture of coniferous trees. Our results correspond with a few research studies that have analyzed age or seedlings’ size- in relation to resource requirements for beech seedlings occurrence and growth (Rozenbergar et al., 2007; Ammer et al., 2008; Annighöfer, 2018). Ammer et al. (2008) found that belowground resource availability was more important for small seedlings, while the importance of light availability increased with seedlings’ size. As was shown by Rozenbergar et al. (2007), large beech seedlings’ height and height increments were higher on microsites receiving the highest levels of direct and diffuse radiation, while seedlings’ density was not affected by light. Increased light availability had a positive effect on seedlings’ diameter growth, as observed by Annighöfer (2018). Seedlings’ size depended on the importance of stand structural characteristics, neighborhood, and belowground resources has been stated for pedunculate oak and sessile oak (Quercus petrea (Matt.) Liebl.) (Annighöfer et al., 2015). However, most of these previous studies selected canopy gaps as a stand structural variable that affects beech regeneration, while other stand structural characteristics and the overstory neighborhood were less of a focal point. The importance of light in beech regeneration has been widely stated (e.g., Ponge and Ferdy, 1997; Collet et al., 2002; Ritter et al., 2005; Ammer et al., 2008; Wagner et al., 2009); nevertheless, regeneration patterns and understory species composition cannot be explained solely by light conditions in certain parts of a stand or canopy gap (Rozenbergar et al., 2007). This was confirmed by our results, which identified a wide

5. Conclusion Our results indicate that stand structural and environmental characteristics determine beech abundance among the plots with outcomes ranging from abundant regeneration to a complete lack of regeneration. Stand structural variables and species composition were found to be significant for the occurrence of beech regeneration (multinomial logistic regression). The abundance of beech regeneration was relatively moderate explained by the use of general linear model (R2 varying from 0.18 to 0.66). However, the importance of variables changes in relation to the development stages of beech: the H0 development stage regeneration abundance was determined to a greater extent by stand structural variables, while taller saplings – additional with light-demanding species regeneration abundance (regeneration-associated factors), what may indicate increased light requirements with seedlings size. Correlation between beech regeneration abundance and regeneration-associated factors—especially pioneer tree species’ regeneration (silver birch, European aspen)—may indicate the conditions suitable for beech regeneration (i.e., better light availability). Our results also showed that occurrence and abundance of beech regeneration under closed-canopy conditions was weakly influenced by intra/interspecific competition in the understory, as well as by ground layer vegetation. This is probably due to closed-canopy conditions in which beech outcompete other species due to shade tolerance. Beech regeneration dominance among the understory vegetation layer shows that monospecific and mixed beech stands could maintain stability and continuity of beech-dominated biocoenosis in estimated forest complexes. Forest management practices may facilitate beech regeneration by reducing overstory density; however, higher canopy openings could increase interspecific competition with light-demanding and pioneer tree species, as well as with ground-layer vegetation cover. Understandably, prevailing species in the overstory determine future regeneration composition. In areas that lack of target tree species, it is not expedient to expect these species to regenerate; however, pioneer tree species such as silver birch and European aspen may regenerate due to high seed dispersal. Acknowledgements The study was financially supported by the State Forests National Forest Holding of Poland (grant no 500-377 to ZB). Thanks goes to the field assistants and students who helped with the fieldwork, especially Bogdan Pawlak, Adam Wójcicki and Dorota Dobrowolska. References Agestam, E., Ekö, P.M., Nilsson, U., Welander, N.T., 2003. The effects of shelterwood density and site preparation on natural regeneration of Fagus sylvatica in southern Sweden. For. Ecol. Manage. 176, 61–73. https://doi.org/10.1016/S0378-1127(02) 00277-3. Ammer, C., Stimm, B., Mosandl, R., 2008. Ontogenetic variation in the relative influence of light and belowground resources on European beech seedling growth. Tree Physiol. 28, 721–728. https://doi.org/10.1093/treephys/28.5.721. Annighöfer, P., 2018. Stress relief through gap creation? Growth response of a shade tolerant species (Fagus sylvatica L.) to a changed light environment. For. Ecol. Manage. 415–416, 139–147. https://doi.org/10.1016/j.foreco.2018.02.027. Annighöfer, P., Beckschäfer, P., Vor, T., Ammer, C., 2015. Regeneration patterns of European oak species (Quercus petraea (Matt.) Liebl., Quercus robur L.) in dependence of environment and neighborhood. PLoS ONE. 10 (8), e0134935. https://doi. org/10.1371/journal.pone.0134935. Baier, P., Meyer, J., Gottlein, A., 2007. Regeneration niches of Norway spruce (Picea abies [L.] Karst.) saplings in small canopy gaps in mixed mountain forests of the Bavarian Limestone Alps. Eur. J. For. Res. 26, 11–22. https://doi.org/10.1007/s10342-0050091-5. Berg, E.C., Zarnoch, S.J., McNab, W.H., 2018. Twenty-year survivorship of tree seedlings

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