Next Article in Journal
Some Stochastic Aspects of Safety Work of Steel Wire Ropes Used in Mining-Shaft Hoists
Previous Article in Journal
Thermal Preference May Facilitate Spatial Coexistence of Two Invasive Fish Species in Lake Bosten, China
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Stand Structure Beats Age for Ground Cover Vegetation in Ageing Hemiboreal Scots Pine and Norway Spruce Stands

Latvian State Forest Research Institute “Silava”, Rigas Street 111, LV-2169 Salaspils, Latvia
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(9), 7594; https://doi.org/10.3390/su15097594
Submission received: 15 March 2023 / Revised: 19 April 2023 / Accepted: 2 May 2023 / Published: 5 May 2023
(This article belongs to the Section Sustainable Forestry)

Abstract

:
Intensifying forest management and a reduction in the rotation period necessitates the development of intensive biodiversity conservation strategies, such as the triad concept, which aims at ensuring habitat connectivity. Such an approach depends on the relationships between biodiversity components and manageable stand characteristics. Mostly, the biological value of stands has been associated with age, although stand structures, which are often intercorrelated with age, might be of primary importance. The relationships between ground cover vegetation, which is a principal component and indicator of the biological value of temperate conifer forests, and stand characteristics were assessed in pre-harvesting/harvesting age and old-growth coniferous stands in the eastern Baltic region (Latvia). The old-growth stands were nearly two times older than the pre-harvesting/harvesting age stands. Both stand groups showed generally similar ground cover flora, though ground cover vegetation showed higher variability in the old-growth stands. The principal gradients of ground cover vegetation were related to light, site fertility, and structural diversity, as well as the degree of deciduous (particularly Betula spp.) admixture in a tree stand. Considering the explicit contrasts, stand age did not affect ground cover vegetation, implying the principal effects of stand structure, which are manageable characteristics. This implies the potential for specific management to aid the ecological connectivity of stands in commercial forest landscapes.

1. Introduction

The increasing demand for timber necessitates the intensification of forest management [1,2]. In Northern Europe and the Eastern Baltic region, the application of intensive forest management is increasing the productivity of stands [3], thus allowing a reduction of rotation period, which is crucial for meeting the demand and economic performance [4,5]. The strong relationship between forest age and the vulnerability to disturbances [6], particularly for the non-climatic climax species [7], supports the shortening of the rotation period to reduce economic risk [8]. This also agrees with the green course and climate goals, as the maximum biomass production (and hence carbon sequestration) appears to be reached at substantially earlier stages than the OG stage and is independent of the degree of management [9].
The shortening of the rotation period could affect forest ecosystem services with effects on biodiversity, and hence ecosystem stability is mostly considered negative or neutral [6,10]. Such effects have been related to the dynamics, composition, and structure of the stands, the persistence of which has been related to the abundance and diversity of forest-dwelling species [11]. Under such conditions, practices actively stimulating biological diversity and connectivity appear necessary to maintain a wider spectrum of ecosystem services and the stability of the intensively managed forest landscape [12,13]. The triad zoning, incorporating a network of reserves and areas, which are managed extensively according to the sharing-sparing and near-natural principles, into the intensively managed forest landscape has been suggested [14,15]. Still, due to complexity, there is still uncertainty about the optimal solutions for such an approach [16,17]. Hence, local information on the efficiency of the extensively managed stands/areas for maintaining ecological networks and biodiversity is crucial for sustaining the multifunctionality of intensively managed forests under the triad concept [15,18,19].
In the highly managed European landscape, the old-growth (OG) forests are considered among the ecosystems most valuable for biodiversity, which contrast with the simplified composition and structure of commercial stands [20]. Regarding the OG forests, it has been presumed that their biodiversity value is a primary result of age and, hence, is a specific (late) stage of succession, as hinted by bryophytes and mycorrhizae [21,22,23]. However, the richness of vascular ground cover vegetation and, subsequently, the species related to it favours (increases after) disturbances, implying a relation to specific stand structures/openings and the local rejuvenation of the tree stand [24,25]. After a clear-cut in coniferous stands in the hemiboreal zone, vegetation can become similar to that in OG stands by the age of 70 years (corresponding to harvesting or pre-harvesting age and mid-successional stage) as the tree stand diversifies and canopy openings appear [11,14,26,27]. Thus, stand age alone cannot not be considered the sole predictor of the biodiversity value of a stand, and a complex assessment of composition and structures, as well as history, which have primary effects, is needed [26,28,29]. However, age is often correlated with the crucial structural characteristics and composition of stands, implying their sufficiency for screening [30].
The composition and structural diversity of canopy trees, hence the vertical structure and openings of the canopy [31,32] along with the deadwood of different decay stages [33,34] and veteran trees bearing various microhabitats [35,36] have been identified as the principal determinants of the biological value of a stand. The explicit positive effect of such structures has been observed on ground cover, bird, and ground-dwelling communities [28]. The main differences between the intensively managed and the conservancy OG forests can be largely attributed to the characteristics of canopy trees [25,37,38], which are manageable by close-to-natural regeneration and selective cutting [14]. Regarding the triad approach, this highlights the high potential to increase the functionality of extensively managed areas, even at a relatively young (maturing) age [15,28]. The local disentanglement of the effects of stand characteristics is necessary [17]. The ground cover vegetation is closely related to the forest development stages [26], playing a vital role as a habitat and food for faunal communities [39,40], nutrient cycling [41], stand productivity [42], and in forest regeneration and succession [43,44]. Furthermore, ground cover vegetation is directly affected both by natural disturbances and management; therefore, its inventory is widely used for the assessment of biodiversity [28,45].
In the Eastern Baltic region and Latvia in particular, the projected changes in tree distribution largely concern the economically important Scots pine Pinus sylvestris and Norway spruce Picea abies [46,47]. These species are anticipated to decrease in abundance [48] due to intensifying disturbances [49,50,51,52]. Nevertheless, a network of OG pine and spruce forests still persists in Latvia, aiding the multifunctionality of the forest [53,54], yet its connectivity might be affected by the decreasing age of managed commercial stands, and hence specific management appears necessary to sustain it.
The aim of this study was to compare ground cover vegetation between OG and the pre-harvesting/harvesting age (PHH) stands of Scots pine and Norway spruce stands in Latvia and to assess the main stand characteristics affecting the diversity of ground cover vegetation. We hypothesised that the canopy tree dimension and stand density were the primary determinants of ground cover vegetation, with the stand age having a secondary effect.

2. Materials and Methods

2.1. Study Area and Stand Selection

The relationships between dimensions and the structure of tree stands and ground cover vegetation were studied in 27 OG and 47 PHH forest patches dominated by Scots pine and Norway spruce dispersed across the territory of Latvia (55°40′–58°05′ N, 20°58′–28°14′ E; Figure 1). This study region represented the hemiboreal forest zone, where coniferous and broadleaved trees are mixed both at the stand as well as the landscape level [55]. According to the national forest inventory, forests cover 53% of the territory of Latvia, among which 26 and 19% of stands are dominated by Scots pine and Norway spruce, respectively. The study region represents lowland conditions (<250 m a.s.l.) with a generally flat topography. Postglacial mesotrophic mineral podzolic soils (sandy and silty) are the most common edaphic conditions of the forest lands (40% of the area). The climatic conditions can be described as moist continental [56], though with explicit coastal features due to the dominant westerlies bringing air masses from the Baltic Sea and Northern Atlantic. The mean annual temperature was +6.5 °C, with February being the coldest and July the warmest month, respectively (with the mean monthly temperature of −3.1 and 17.8 °C, respectively). The mean annual precipitation was 686 mm, and the highest monthly precipitation fell during the vegetation period (May–September; ca. 75 mm/month). Climatic changes were expressed as warming, particularly during the dormant period, which has been extending the vegetation period, as well as increasing the variability of the thermal and precipitation regime in summer, with warmer dry periods tending to extend [57].
A stratified selection of the OG stands was based on the national forest inventory database. Stands dominated by conifers were selected according to the criteria of the age of dominant cohort >160 years, area of >0.5 ha, distance from villages (or larger settlements) and roads of >5 and 1 km, respectively, and no recent record of management (e.g., thinning). The selection was also made to represent the regional distribution of the forest. The pre-selected stands were visited to check their actual compliance with the criteria, and increment cores were taken to verify age. In case of signs of recent (younger than 40–50 years) management (stumps, sawn surfaces of logs, etc.), stands were not investigated. For comparison, one or two adjacent conventionally managed (undergone thinning) PHH stands (80–110 years for pine and 60–90 years for spruce according to the regional specifics of commercial management) with similar composition and edaphic conditions were selected from the inventory. The verified age of the selected OG and PHH stands ranged 164–219 and 69–96 years, with a mean value of 184 and 79 years, respectively. Hence, the stands explicitly differed by age.

2.2. Measurements and Census

In each stand, depending on size, four to eight circular plots with an area of 500 m2 were established (Figure 2); in total, 109 and 188 plots were set in the OG and PHH age stands, respectively (Figure 3). Within each plot, the dimensions and positions of all trees (living and dead) with a diameter at breast height (DBH) exceeding 6 cm were recorded. To account undergrowth and advanced growth, in a 90° segment of a 100 m2 subplot (with a common centre), the dimensions of all trees with DBH of 2.1–6.0 cm were measured. The measurements were performed in February and March 2020. For the lying deadwood thicker than 6 cm, the length and diameter at the thin and thick ends within the sample plot were measured, as well as the decay stage, which was recorded according to [58].
Vegetation was surveyed in June and July 2021. The relative projective cover of ground cover vegetation in each plot was recorded according to a grid of 12 grid plots of 1 × 1 m arranged regularly according to the four cardinal directions with the spacing of one m around the common centre (Figure 2). The cover of individual species was recorded for the herbaceous vascular plant, the woody plant (at the herbaceous layer) and the bryophyte layers. Thus, the total projective cover of plots was allowed to exceed 100%, yet such a restriction was applied to each of the ground cover vegetation layers. The projective cover of wood debris and bare soil was also recorded.

2.3. Statistical Analysis

For the description of the tree stand in each plot, density, basal area, and standing stock (according to a local equation [59]) of the canopy, as well as the undergrowth trees, was calculated. The volume of standing deadwood was calculated according to the national equation [59], yet the volume of lying deadwood was calculated as for a truncated cone. The diversity of DBH and tree height (H) in each plot was characterised by the interquartile difference (iqrD and iqrH, respectively). For the description of stand composition, the proportion of coniferous and deciduous species in the canopy, the proportions of each canopy species (according to their number), mean DBH, H, the basal area of the canopy and understory trees (canopy strata) by species and taxonomic groups were also calculated.
The mean projective cover of species of the 12 grid plots was calculated to describe the ground cover vegetation of the plots. Species richness, occurrence (% of plots with a species), total cover, and Shannon–Wiener index (H′) were calculated to describe the diversity of ground cover vegetation in each plot. A simple t-test was used to compare these metrics between the age groups. Ellenberg’s indirect environmental indicator values/indices (ordinal scale) for vascular plants and Düll’s values for bryophytes (i.e., nutrients/nitrogen, light, reaction, temperature, continentality, and moisture) [60] were reciprocally estimated as the proxies of the site conditions of the plots. Such estimates are sufficient to substitute the resource-demanding direct environmental measurements [60]. The nonparametric ANOSIM (analysis of similarity), which is a randomization method used for the evaluation of similarity of multidimensional vegetation data within and among groups of observation, was used to compare the ground cover vegetation (and its components) of the plots between the OG and PHH stands using the “anosim” function and Bray’s distance [61]; 5000 permutations were performed. The ground cover vegetation matrix of the plots was used as the response, and the age group was used for contrast (grouping variable).
The detrended correspondence analysis (DCA, detrending with 26 segments and downweighing rare species) based on the relative cover of species in the plots [62] was used to assess the main ecological gradients and communities of ground cover vegetation in the studied stands. To assess the relationships of the two main ecological gradients of ground cover vegetation with the tree stand and site conditions (represented by Ellenberg’s indicator values), correlations between DCA axes and the matrix of the stand characteristics (containing 70 variables in total, among which 50 were differential characteristics of a tree stand, e.g., iqrD, iqrH, mean DBH, H, basal area of trees of different canopy strata and species, etc.) were estimated.
The sets of the environmental and stand characteristics showing the strongest relationships with the DCA scores of the first two gradients of the plots were distinguished using a linear mixed multiple regression analysis. Stand and site characteristics showing correlations with DCA axes were tested as the sets of predictors, and an arbitrary selection principle (considering ecological meaning) was used to select the best-fitting set of the effects. As multiple plots per stand were established, the stand was included in the models as a random intercept term. Predictors were checked for collinearity using the variance inflation factor, and model residuals were checked for compliance with the assumptions using diagnostic plots. Data analysis was conducted in R v. 4.2.2 [63] using the packages “lme4” [64] and “vegan” [61].

3. Results

The studied PHH and OG stands had a similar standing volume (mean ± standard error of 413.1 ± 8.7 and 429.1 ± 17.9 m3 ha−1, respectively), though they had a wider range in the second (91.1–932.1 and 82.8–1233.9, respectively). However, the PHH stands were two times denser than the OG stands, with a mean density of canopy trees of 502.9 ± 11.8 and 261.1 ± 9.7 trees ha−1, ranging 120–1040 and 60 to 820 trees ha−1, respectively. The amount of deadwood was two times higher in the OG than in the PHH age stands (43.9 ± 4.2 and 24.9 ± 2.1 m3 ha−1, respectively), and approximately half of it was lying.
The PHH stands (canopy and undergrowth) were composed of 14 trees species; their canopies were dominated by spruce (ca. 369 trees ha−1) and pine (ca. 146 trees ha−1) with an admixture of silver birch Betula pendula Roth. (ca. 73 trees ha−1) and common aspen Populus tremula L. (ca. 35 trees ha−1). The OG stands were more diverse with 20 tree species; their canopies were co-dominated by spruce (ca. 167 trees ha−1) and pine (ca. 96 trees ha−1) with an admixture of silver birch (ca. 29 trees ha−1), wych Elm Ulmus glabra Huds. (ca. 23 trees ha−1), common aspen (ca. 17 trees ha−1) and black alder Alnus glutinosa (L.) Gaertn. (ca. 12 trees ha−1). Accordingly, the admixture of deciduous canopy trees was higher in the OG compared to the PHH stands (24 vs. 12%, respectively). The stands of both age groups had an explicit understory (secondary canopy layer), which was formed by conifers and deciduous species, among which Norway spruce was the most common (21.4% and 24.9% of understory trees in the PHH and OG stands, respectively). The undergrowth in the PHH stands was dominated by hazel (46%, ca. 125 axes ha−1), but in the OG stands by hazel (34%, ca. 350 axes ha−1) and spruce (17%, ca. 176 trees ha−1).
The ground cover vegetation richness of the studied stands was generally intermediate. In total, 175 ground cover species were surveyed, among which 118, 28, and 29 were vascular herbaceous plants, woody plants, and bryophytes, respectively. The age of the stand had an effect on ground cover species richness. The total ground cover vegetation species richness, as well as the richness of vascular plants and bryophytes, was higher in the PHH age than in the OG stands (total richness 21.1 ± 2.4 and 19.1 ± 2.7 species per plot, p-value = 0.03; Table 1). Irrespectively of the age group, the evenness of ground cover species distribution was similar, as indicated by the lack of differences in the Shannon diversity index (p-value > 0.13), which was intermediate (H′ = 2.40), and hence, indicated a lack of dominance.
The studied stands were rich in litter, which covered approximately one-third of the sample plot area (30.2 ± 1.2%). Bare soil was estimated with a mean relative cover of 7.9 ± 0.7% of the grid plots, irrespective of the age group, indicating a similar level of disturbance. The total projective cover of ground cover vegetation exceeded 100% in both age groups indicating an overlap of the layers, among which bryophytes were the most abundant, particularly in the PHH stands. Herbaceous vascular plants were slightly less abundant, while woody plants (including seedlings of trees) were scarce.
The composition of ground cover vegetation in the studied stands was significantly similar, as the differences between the age groups estimated by ANOSIM were negligible (R = 0.08; p-value < 0.001). The composition of bryophytes and vascular plants showed an even higher similarity (for both, R = 0.007, p-value < 0.001), indicating that the stable equilibrium of ground cover vegetation had been reached. Generalist species, e.g., Vaccinium myrtillus, Oxalis acetosella, Luzula pilosa, Calamagrostis arundinacea, Hylocomium splendens, Pleurozium schreberi were the most common in the ground cover vegetation of the studied stands (Table 2). Nevertheless, there was a higher richness of the rare vascular species (e.g., Campanula persicifolia, Lathraea squamaria) in the PHH age stands.
Based on the projective cover of ground cover vegetation, two continuous principal gradients were estimated by the DCA (Figure 4A,B). The ordination of the stands (plots) showed that the age groups completely overlapped, though the OG stands showed a somewhat wider range of scores of the first two gradients, indicating higher diversity of local conditions. The primary gradient represented by the first axis of DCA was apparently related to light conditions, as indicated by its correlation with Ellenberg’s indicator values. Light (L, Figure 4B) was also positively intercorrelated with continentality, temperature, humidity, and reaction (acidity) while being negatively related to the diversity of vascular ground cover vegetation, indicating collinear effects of environmental factors. Among the tested characteristics of the tree stand, the proportion of conifers correlated with the first gradient, relating conifers with increased light transmission. Among the correlated variables, light, reaction, moisture, the proportion of conifers, and Betula sp. in the canopy were estimated by multiple regression to have consistent non-collinear relationships with the primary gradient (Table 3). The effects of the share of the main conifer species in the canopy (Scots pine and Norway spruce), however, differed, as indicated by contrasting correlations with the gradients (Figure 4B).
The complexity of the effects of the environmental variables related to the first gradient was also supported by species ordinations (Figure 4A). Species favouring open conditions, such as Ledum palustre, Vaccinium uliginosum, and Aulacomnium palustris, were associated with the high light part of the gradient, while the species favouring oligotrophic/mesotrophic semi-open conditions, e.g., Vaccinium myrtillus, Vaccinium vitis-idaea, Pleurozium schreberi, and Hylocomium splendens were related to the mid-part of the first gradient. However, the high light conditions were generally related to a narrow and specific set of ground cover species, as indicated by the correlation with vascular species richness and evenness (Figure 4B). In contrast, the low light part of the gradient, which coincided with sites that had a higher admixture of deciduous trees, was associated with shade-tolerant forest species, e.g., Athyrium sp., Oxalis acetosella, Hepatica nobilis, and Actea spicata, as well as the presence of seedlings of Tilia cordata and Fraxinus excelsior (Figure 4A). This part of the gradient was associated with most of the accounted ground cover species; hence, vegetation was more diverse (higher richness and H′), even though the share of litter was the highest.
The second gradient of the ground cover vegetation of the studied stands was continuous, yet shorter than the first (Figure 4B). Still, a small group of three plots with increased score values representing fern-rich sites was distinguished (Figure 4A,B). The gradient was apparently related to fertility, as implied by its correlations with nitrogen value (N, Figure 4A), tree height, and standing volume, as well as the variability in tree dimensions (interquartile range, qD, Figure 4A,B). Accordingly, the gradient correlated with the abundance of vascular (positively) and bryophyte (negatively) ground cover species and richness (Figure 4B) were associated with the fertile and nutrient-poor parts of the gradient, respectively (Figure 4A). The strongest correlation with the second gradient was estimated for Mycelis muralis, Athyrium filix-femina and Oxalis acetosella. Among the stand characteristics, nitrogen value and the total standing stock had non-colinear relationships with the second gradient; however, these effects were affected by the stand (random effect), as indicated by the explicit differences between the conditional and marginal R2 values (Table 3). Additionally, species associated with low scores of the second gradient were hygrophytes, e.g., Phragmites australis, Carex cinerea, as well as Sphagnum sp., thus suggesting relationships to moisture, particularly soil waterlogging. Stand age, which was considered as a principal driver, had a negligible relation with the main estimated gradients despite the explicit differences among the stand groups, thus indicating the stand structure to have a primary effect on ground cover vegetation.

4. Discussion

The ground flora in stands of both age groups was generally typical for a mesotrophic hemiboreal forest on freely draining mineral soils within the region [66,67]. The estimated continuous gradients (Figure 4A) indicated that conditions essential for ground cover vegetation have equalized in stands older than 70 years [26], though the diversification of local conditions occurred. The most common vascular and bryophyte ground cover species were Vaccinium myrtillus, Hylocomium splendens, and Pleurozium schreberi (Table 2), indicating the late successional stage of development while implying stand history without intensive disturbances [68,69,70]. The abundance of these species could be explained by explicit competitiveness [71], particularly under the oligotrophic and acidic conditions caused by conifer litter decomposition [72,73]. Under more shaded conditions under spruce and caused by deciduous trees, Oxalis acetosella, which is also an indicator of the late successional stage [74], was common (Table 2), supporting the stable equilibrium of ground cover vegetation. The estimated minor dissimilarities in the composition of the ground cover vegetation of the age groups could likely be attributed to the outlying OG plots (Figure 4A), which was likely due to micro-site conditions (e.g., more fertile depression with discharge) favouring ferns Athyrium sp. [75]. However, the highest species richness (especially of vascular plants) in the PHH stands could be explained by the specific stand development stage, when species (particularly herbaceous) favouring large-scale disturbance still remained [24,26]. Furthermore, similar ground cover diversity (H′) supported the fact that the equilibrium of ground cover vegetation [71] had already been reached by the PHH.
Despite the differences in age of the studied stands, the light conditions, fertility and structural diversity of tree stand, which determine the microclimate [76], were the main drivers of ground cover vegetation, as explicitly indicated by the sample plot and species ordination (Figure 4A,B). Light, though, was intercorrelated with temperature, humidity, and continentality indices (Figure 4B), stressing the role of the canopy layer structure on microclimate [32]. Although light availability has been positively related to ground cover species richness in deciduous forests [31,77], the opposite was observed (Figure 4B), suggesting contrasting relationships in coniferous stands. Such differences might be partially related to the higher occurrence of feather mosses and dwarf shrubs, which outcompete other ground cover vegetation lifeforms when conditions stabilize in oligotrophic/mesotrophic stands [71]. Hence, lower light conditions in the stands with a higher admixture of deciduous trees in the canopy were related to higher ground cover richness (Figure 4B), linking the diversity of the tree stand and ground cover vegetation [31,78].
The litter of deciduous trees is less acidic compared to that of conifers [79], thus providing more favourable (fertile) conditions for a higher number of vascular ground cover species due to nutrient availability [80]. Deciduous litter also affects the humidity and thermal regime of the top-soil layers, thus facilitating the development of vascular species [81,82]. This highlights the positive effects of deciduous admixture (Figure 4B), particularly birch (Table 3), in coniferous stands [79,83]. Alternatively, the relationships between light conditions and ground cover vegetation might be related to the occurrence of the stands in the hemiboreal zone, where interactions between boreal and nemoral species can be specific [27].
The second estimated gradient for ground cover vegetation (DCA2; Figure 4A,B) was related to fertility, as indicated by the relationships with the nitrogen value and total standing volume (Table 3). This showed edaphic conditions to have a secondary role under the canopies of the tree stand, where the light was strictly limiting [31,77]. The second gradient was also clearly correlated with the characteristics of the tree stand, such as the H and DBH distribution of trees (Figure 4B), prioritizing the effects of the stand structure, which are manageable, over the stand age [84], even though these characteristics are usually intercorrelated [30]. However, standing and laying deadwood, which is considered as one of the main factors promoting biodiversity [33,34], did not show relationships with ground cover vegetation (Figure 4A,B), albeit OG stands showing comparable amounts to nature reserves (mean 32.9 m3 ha–1, [85]). This also suggested comparable effects of deadwood in PHH and OG stands. Still, deadwood is of primary importance for the invertebrate and epixylic communities [86,87], which were not surveyed.
The main stand characteristic of interest in this study, stand age, appeared secondary to the composition and structure of PHH and OG coniferous stands in the hemiboreal zone, contradicting the assumption of stand age as the key characteristic for the most researched part of the biodiversity—forest ground vegetation [28,29]. Hence, stand structures (canopy composition, cover and species proportion, standing volume of the canopy, understory density and height), which are generally manageable [88], were estimated as the primary drivers of ground cover vegetation. This indicates the potential for specific management to facilitate biological diversity and the ecological connectivity of habitats under a reduction in the rotation period in intensively managed forest landscapes [18], thus supporting the implementation of the triad conservation concept [15]. For this, closeness to natural management appears promising, as it would increase stand structural diversity [14].

5. Conclusions

The prevalence of relationships between ground cover vegetation and structural characteristics rather than stand age in hemiboreal coniferous PHH and OG stands confirmed the study hypothesis. Such relationships imply that specific management could be implemented to sustain the biodiversity of commercial stands by the pre-harvesting age, thus aiding ecological connectivity under an intensively managed landscape. Considering a similar floristic composition in PHH and OG stands, their main differences were related to the structural and compositional diversity of the tree stand, which favoured the ground cover species with a lower occurrence. This also implies that the currently applied rotation period of ca. 70–110 appears efficient for ground cover vegetation, which is host for large proportion of other taxonomic groups, to reach a stable state. Accordingly, a conservative management strategy regarding the rotation period while facilitating the compositional and structural diversity of stands appears efficient for areas crucial for connectivity under the triad conservation concept, aiding the sustainability and multifunctionality of forests.

Author Contributions

Conceptualization, I.M., R.M. and Ā.J.; methodology, Ā.J., D.J., I.J. and A.A.L.; software, I.M. and R.M.; validation, R.M. and Ā.J.; formal analysis, I.M. and R.M.; investigation, D.J., A.A.L. and I.J.; resources, Ā.J.; data curation, I.M., R.M., Ā.J., D.J., I.J. and A.A.L.; writing—original draft preparation, I.M. and R.M.; writing—review and editing, I.M., R.M. and Ā.J.; visualization, I.M. and R.M.; supervision, Ā.J.; project administration, Ā.J.; funding acquisition, Ā.J. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the project “The role of old-growth forests in mitigating climate change: information for Latvian and European Union Forest and sectoral policy makers”, and part of data collection was conducted in project “Effect of forestry on the forest ecosystem and related ecosystem services”.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The author declares no conflict of interest.

References

  1. Routa, J.; Kilpeläinen, A.; Ikonen, V.P.; Asikainen, A.; Venäläinen, A.; Peltola, H. Effects of intensified silviculture on timber production and its economic profitability in boreal Norway spruce and Scots pine stands under changing climatic conditions. For. Int. J. For. Res. 2019, 92, 648–658. [Google Scholar] [CrossRef]
  2. Temperli, C.; Stadelmann, G.; Thürig, E.; Brang, P. Silvicultural strategies for increased timber harvesting in a Central European mountain landscape. Eur. J. For. Res. 2017, 136, 493–509. [Google Scholar] [CrossRef]
  3. Socha, J.; Solberg, S.; Tymińska-Czabańska, L.; Tompalski, P.; Vallet, P. Height growth rate of Scots pine in Central Europe increased by 29% between 1900 and 2000 due to changes in site productivity. For. Ecol. Manag. 2021, 490, 119102. [Google Scholar] [CrossRef]
  4. Lange, M.; Türke, M.; Pašalić, E.; Boch, S.; Hessenmöller, D.; Müller, J.; Prati, D.; Socher, S.A.; Fischer, M.; Weisser, W.W.; et al. Effects of forest management on ground-dwelling beetles (Coleoptera; Carabidae, Staphylinidae) in Central Europe are mainly mediated by changes in forest structure. For. Ecol. Manag. 2014, 329, 166–176. [Google Scholar] [CrossRef]
  5. Södra Skog, Lönsamt Med Kortare Omloppstid i Granskog. [Shorter Rotations are Profitable in Spruce Forest] (Press Release). 2012. Available online: https://www.sodra.com/sv/se/om-sodra/pressrum/pressmeddelanden/lonsamt-med-kortare-omloppstid-i-granskog/ (accessed on 20 February 2023). (In Swedish).
  6. Zimová, S.; Dobor, L.; Hlásny, T.; Rammer, W.; Seidl, R. Reducing rotation age to address increasing disturbances in Central Europe: Potential and limitations. For. Ecol. Manag. 2020, 475, 118408. [Google Scholar] [CrossRef] [PubMed]
  7. Petrokas, R.; Baliuckas, V.; Manton, M. Successional categorization of European hemi-boreal forest tree species. Plants 2020, 9, 1381. [Google Scholar] [CrossRef]
  8. Hanewinkel, M.; Cullmann, D.A.; Schelhaas, M.-J.; Nabuurs, G.J.; Zimmermann, N.E. Climate change may cause severe loss in the economic value of European forest land. Nat. Clim. Chang. 2013, 3, 203–207. [Google Scholar] [CrossRef]
  9. Molina-Valero, J.A.; Camarero, J.J.; Alvarez-Gonzalez, J.G.; Cerioni, M.; Hevia, A.; Sanchez-Salguero, R.; Martín-Benito, D.; Perez-Cruzado, C. Mature forests hold maximum live biomass stocks. For. Ecol. Manag. 2021, 480, 118635. [Google Scholar] [CrossRef]
  10. Roberge, J.-M.; Laudon, H.; Björkman, C.; Ranius, T.; Sandström, C.; Felton, A.; Sténs, A.; Nordin, A.; Granström, A.; Widemo, F.; et al. Socio-ecological implications of modifying rotation lengths in forestry. Ambio 2016, 45, 109–123. [Google Scholar] [CrossRef] [PubMed]
  11. Gao, T.; Hedblom, M.; Emilsson, T.; Nielsen, A.B. The role of forest stand structure as biodiversity indicator. For. Ecol. Manag. 2014, 330, 82–93. [Google Scholar] [CrossRef]
  12. Humphrey, J.W. Benefits to biodiversity from developing old-growth conditions in British upland spruce plantations: A review and recommendations. Forestry 2005, 78, 33–53. [Google Scholar] [CrossRef]
  13. Zanchi, G.; Brady, M.V. Evaluating the contribution of forest ecosystem services to societal welfare through linking dynamic ecosystem modelling with economic valuation. Ecosyst. Serv. 2019, 39, 101011. [Google Scholar] [CrossRef]
  14. Bauhus, J.; Puettmann, K.; Messier, C. Silviculture for old-growth attributes. For. Ecol. Manag. 2009, 258, 525–537. [Google Scholar] [CrossRef]
  15. Betts, M.G.; Phalan, B.T.; Wolf, C.; Baker, S.C.; Messier, C.; Puettmann, K.J.; Green, R.; Harris, S.H.; Edwards, D.P.; Lindenmayer, D.B.; et al. Producing wood at least cost to biodiversity: Integrating T riad and sharing–sparing approaches to inform forest landscape management. Biol. Rev. 2021, 96, 1301–1317. [Google Scholar] [CrossRef] [PubMed]
  16. Himes, A.; Betts, M.; Messier, C.; Seymour, R. Perspectives: Thirty years of triad forestry, a critical clarification of theory and recommendations for implementation and testing. For. Ecol. Manag. 2022, 510, 120103. [Google Scholar] [CrossRef]
  17. Kraus, D.; Krumm, F. (Eds.) Integrative Approaches as an Opportunity for the Conservation of Forest Biodiversity; European Forest Institute: Freiburg, Germany, 2013; 284p. [Google Scholar]
  18. Royer-Tardif, S.; Bauhus, J.; Doyon, F.; Nolet, P.; Thiffault, N.; Aubin, I. Revisiting the functional zoning concept under climate change to expand the portfolio of adaptation options. Forests 2021, 12, 273. [Google Scholar] [CrossRef]
  19. Tittler, R.; Filotas, E.; Kroese, J.; Messier, C. Maximizing conservation and production with intensive forest management: It’s all about location. Environ. Manag. 2015, 56, 1104–1117. [Google Scholar] [CrossRef]
  20. Burrascano, S.; Keeton, W.S.; Sabatini, F.M.; Blasi, C. Commonality and variability in the structural attributes of moist temperate old-growth forests: A global review. For. Ecol. Manag. 2013, 291, 458–479. [Google Scholar] [CrossRef]
  21. Crites, S.; Dale, M.R. Diversity and abundance of bryophytes, lichens, and fungi in relation to woody substrate and successional stage in aspen mixedwood boreal forests. Can. J. Bot. 1998, 76, 641–651. [Google Scholar] [CrossRef]
  22. Torresan, C.; del Río, M.; Hilmers, T.; Notarangelo, M.; Bielak, K.; Binder, F.; Boncina, A.; Bosela, M.; Forrester, D.I.; Hobi, M.L.; et al. Importance of tree species size dominance and heterogeneity on the productivity of spruce-fir-beech mountain forest stands in Europe. For. Ecol. Manag. 2020, 457, 117716. [Google Scholar] [CrossRef]
  23. Viljur, M.; Abella, S.R.; Adámek, M.; Alencar, J.B.R.; Barber, N.A.; Beudert, B.; Burkle, L.A.; Cagnolo, L.; Campos, B.R.; Chao, A.; et al. The effect of natural disturbances on forest biodiversity: An ecological synthesis. Biol. Rev. 2022, 97, 1930–1947. [Google Scholar] [CrossRef] [PubMed]
  24. Mayor, S.J.; Cahill, J.F., Jr.; He, F.; Sólymos, P.; Boutin, S. Regional boreal biodiversity peaks at intermediate human disturbance. Nat. Commun. 2012, 3, 1142. [Google Scholar] [CrossRef] [PubMed]
  25. Paillet, Y.; Bergès, L.; Hjältén, J.; Ódor, P.; Avon, C.; Bernhardt-Römermann, M.; Bijlsma, R.-J.; De Bruyn, L.; Fuhr, M.; Grandin, U.; et al. Biodiversity differences between managed and unmanaged forests: Meta-analysis of species richness in Europe. Conserv. Biol. 2010, 24, 101–112. [Google Scholar] [CrossRef] [PubMed]
  26. Chernenkova, T.; Kotlov, I.; Belyaeva, N.; Suslova, E.; Morozova, O.; Pesterova, O.; Arkhipova, M. Role of silviculture in the formation of Norway spruce forests along the southern edge of their range in the Central Russian Plain. Forests 2020, 11, 778. [Google Scholar] [CrossRef]
  27. Marozas, V.; Sasnauskiene, J. Changes of ground vegetation after shelter wood cuttings in pine forests, the hemiboreal zone, Lithuania. Balt. For. 2021, 27, 72–79. [Google Scholar] [CrossRef]
  28. Oettel, J.; Lapin, K. Linking forest management and biodiversity indicators to strengthen sustainable forest management in Europe. Ecol. Indic. 2021, 122, 107275. [Google Scholar] [CrossRef]
  29. Smith, G.F.; Gittings, T.; Wilson, M.; French, L.; Oxbrough, A.; O’donoghue, S.; O’halloran, J.; Kelly, D.L.; Mitchell, F.J.G.; Kelly, T.; et al. Identifying practical indicators of biodiversity for stand-level management of plantation forests. In Plantation Forests and Biodiversity: Oxymoron or Opportunity? Topics in Biodiversity and Conservation; Brockerhoff, E.G., Jactel, H., Parrotta, J.A., Quine, C.P., Sayer, J., Hawksworth, D.L., Eds.; Springer: Dordrecht, The Netherlands, 2007; Volume 9. [Google Scholar] [CrossRef]
  30. Ćosović, M.; Bugalho, M.N.; Thom, D.; Borges, J.G. Stand structural characteristics are the most practical biodiversity indicators for forest management planning in Europe. Forests 2020, 11, 343. [Google Scholar] [CrossRef]
  31. Barbier, S.; Gosselin, F.; Balandier, P. Influence of tree species on understory vegetation diversity and mechanisms involved: A critical review for temperate and boreal forests. For. Ecol. Manag. 2008, 254, 1–15. [Google Scholar] [CrossRef]
  32. Coote, L.; Dietzsch, A.C.; Wilson, M.W.; Graham, C.T.; Fuller, L.; Walsh, A.T.; Irwin, S.; Kelly, D.L.; Mitchell, F.J.; Kelly, T.C.; et al. Testing indicators of biodiversity for plantation forests. Ecol. Indic. 2013, 32, 107–115. [Google Scholar] [CrossRef]
  33. Lassauce, A.; Paillet, Y.; Jactel, H.; Bouget, C. Deadwood as a surrogate for forest biodiversity: Meta-analysis of correlations between deadwood volume and species richness of saproxylic organisms. Ecol. Indic. 2011, 11, 1027–1039. [Google Scholar] [CrossRef]
  34. Parisi, F.; Lombardi, F.; Sciarretta, A.; Tognetti, R.; Campanaro, A.; Marchetti, M.; Trematerra, P. Spatial patterns of saproxylic beetles in a relic silver fir forest (Central Italy), relationships with forest structure and biodiversity indicators. For. Ecol. Manag. 2016, 381, 217–234. [Google Scholar] [CrossRef]
  35. Larrieu, L.; Paillet, Y.; Winter, S.; Bütler, R.; Kraus, D.; Krumm, F.; Lachat, T.; Michel, A.K.; Regnery, B.; Vandekerkhove, K. Tree related microhabitats in temperate and Mediterranean European forests: A hierarchical typology for inventory standardization. Ecol. Indic. 2018, 84, 194–207. [Google Scholar] [CrossRef]
  36. Sever, K.; Nagel, T.A. Patterns of tree microhabitats across a gradient of managed to old-growth conditions: A case study from beech dominated forests of South-Eastern Slovenia. Acta Silvae Ligni 2019, 118, 29–40. [Google Scholar] [CrossRef]
  37. Commarmot, B.; Bachofen, H.; Bundziak, Y.; Bürgi, A.; Ramp, B.; Shparyk, Y.; Sukhariuk, D.; Viter, R.; Zingg, A. Structures of virgin and managed beech forests in Uholka (Ukraine) and Sihlwald (Switzerland): A comparative study. For. Snow Landsc. Res. 2005, 79, 45–56. [Google Scholar]
  38. Humphrey, J.W.; Davey, S.; Peace, A.J.; Ferris, R.; Harding, K. Lichens and bryophyte communities of planted and semi-natural forests in Britain: The influence of site type, stand structure and deadwood. Biol. Conserv. 2002, 107, 165–180. [Google Scholar] [CrossRef]
  39. Felton, A.M.; Wam, H.K.; Stolter, C.; Mathisen, K.M.; Wallgren, M. The complexity of interacting nutritional drivers behind food selection, a review of northern cervids. Ecosphere 2018, 9, e02230. [Google Scholar] [CrossRef]
  40. Felton, A.; Knight, E.; Wood, J.; Zammit, C.; Lindenmayer, D. A meta-analysis of fauna and flora species richness and abundance in plantations and pasture lands. Biol. Conserv. 2010, 143, 545–554. [Google Scholar] [CrossRef]
  41. Hart, S.A.; Chen, H.Y.H. Understory vegetation dynamics of North American boreal forests. Crit. Rev. Plant Sci. 2006, 25, 381–397. [Google Scholar] [CrossRef]
  42. Chavez, V.; Macdonald, S.E. Partitioning vascular understory diversity in mixedwood boreal forests: The importance of mixed canopies for diversity conservation. For. Ecol. Manag. 2012, 271, 19–26. [Google Scholar] [CrossRef]
  43. Nilsson, M.C.; Wardle, D.A. Understory vegetation as a forest ecosystem driver: Evidence from the northern Swedish boreal forest. Front. Ecol. Environ. 2005, 3, 421–428. [Google Scholar] [CrossRef]
  44. O’Brien, M.J.; O’Hara, K.L.; Erbilgin, N.; Wood, D.L. Overstory and shrub effects on natural regeneration processes in native Pinus radiata stands. For. Ecol. Manag. 2007, 240, 178–185. [Google Scholar] [CrossRef]
  45. Kuuluvainen, T.; Angelstam, P.; Frelich, L.; Jõgiste, K.; Koivula, M.; Kubota, Y.; Lafleur, B.; Macdonald, E. Natural disturbance-based forest management: Moving beyond retention and continuous-cover forestry. Front. For. Glob. Chang. 2021, 4, 629020. [Google Scholar] [CrossRef]
  46. Durrant, T.H.; De Rigo, D.; Caudullo, G. Pinus sylvestris in Europe: Distribution, habitat, usage and threats. Eur. Atlas For. Tree Species 2016, 14, 845–846. [Google Scholar]
  47. Schlyter, P.; Stjernquist, I.; Barring, L.; Jonsson, A.M.; Nilsson, C. Assessment of the impacts of climate change and weather extremes on boreal forests in northern Europe, focusing on Norway spruce. Clim. Res. 2006, 31, 75–84. [Google Scholar] [CrossRef]
  48. Buras, A.; Menzel, A. Projecting tree species composition changes of European forests for 2061–2090 under RCP 4.5 and RCP 8.5 scenarios. Front. Plant Sci. 2019, 9, 1986. [Google Scholar] [CrossRef]
  49. Albert, M.; Nagel, R.V.; Nuske, R.; Sutmöller, J.; Spellmann, H. Tree species selection in the face of drought risk—Uncertainty in forest planning. Forests 2017, 8, 363. [Google Scholar] [CrossRef]
  50. Jactel, H.; Petit, J.; Desprez-Loustau, M.L.; Delzon, S.; Piou, D.; Battisti, A.; Koricheva, J. Drought effects on damage by forest insects and pathogens: A meta-analysis. Glob. Chang. Biol. 2012, 18, 267–276. [Google Scholar] [CrossRef]
  51. Krisans, O.; Saleniece, R.; Rust, S.; Elferts, D.; Kapostins, R.; Jansons, A.; Matisons, R. Effect of bark-stripping on mechanical stability of Norway spruce. Forests 2020, 11, 357. [Google Scholar] [CrossRef]
  52. Seidl, R.; Thom, D.; Kautz, M.; Martin-Benito, D.; Peltoniemi, M.; Vacchiano, G.; Wild, J.; Ascoli, D.; Petr, M.; Honkaniemi, J.; et al. Forest disturbances under climate change. Nat. Clim. Chang. 2017, 7, 395–402. [Google Scholar] [CrossRef]
  53. Ķēniņa, L.; Elferts, D.; Jaunslaviete, I.; Bāders, E.; Jansons, Ā. Sustaining Carbon Storage: Lessons from Hemiboreal Old-Growth Coniferous and Deciduous Forest Stands. For. Sci. 2023, 69, 158–166. [Google Scholar] [CrossRef]
  54. Ķēniņa, L.; Elferts, D.; Jaunslaviete, I.; Bāders, E.; Šņepsts, G.; Jansons, Ā. Tree biomass–a fragile carbon storage in old-growth birch and aspen stands in hemiboreal Latvia. Balt. For. 2022, 28, N654. [Google Scholar] [CrossRef]
  55. Ahti, T.; Hämet-Ahti, L.; Jalas, J. Vegetation zones and their sections in northwestern Europe. Ann. Bot. Fenn. 1968, 5, 169–211. [Google Scholar]
  56. Kottek, M.; Grieser, J.; Beck, C.; Rudolf, B.; Rubel, F. World map of the Köppen-Geiger climate classification updated. Meteorol. Z. 2006, 15, 259–263. [Google Scholar] [CrossRef]
  57. Avotniece, Z.; Rodinov, V.; Lizuma, L.; Briede, A.; Kļaviņš, M. Trends in frequency of extreme climate events in Latvia. Baltica 2010, 23, 135–148. [Google Scholar]
  58. Sandström, F.; Petersson, H.; Kruys, N.; Ståhl, G. Biomass conversion factors (density and carbon concentration) by decay classes for dead wood of Pinus sylvestris, Picea abies and Betula spp. in boreal forests of Sweden. For. Ecol. Manag. 2017, 243, 19–27. [Google Scholar] [CrossRef]
  59. Liepa, I. Tree Growth Study; LUA: Jelgava, Latvia, 1996; 123p. (In Latvian) [Google Scholar]
  60. Ellenberg, H.; Weber, H.E.; Düll, R.; Wirth, V.; Werner, W.; Paulissen, D. Zeigerwerte von Pflanzen in Mitteleuropa, 2nd ed.; Scripta Geobotanica: Göttingen, Germany, 1992; pp. 1–248. [Google Scholar]
  61. Oksanen, J.; Simpson, G.; Blanchet, F.G.; Kindt, R.; Legendre, P.; Minchin, P.; Hara, R.; Solymos, P.; Stevens, H. Vegan: Community Ecology Package, R Package Version 2.6-4. 2022. Available online: https://CRAN.R-project.org/package=vegan (accessed on 31 March 2023).
  62. Correa-Metrio, A.; Dechnik, Y.; Lozano-García, S.; Caballero, M. Detrended correspondence analysis: A useful tool to quantify ecological changes from fossil data sets. Boletín Soc. Geológica Mex. 2014, 66, 135–143. [Google Scholar] [CrossRef]
  63. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2022; Available online: https://www.R-project.org/ (accessed on 15 March 2023).
  64. Bates, D.; Maechler, M.; Bolker, B.; Walker, S. Fitting Linear Mixed-Effects Models Using lme4. J. Stat. Softw. 2015, 67, 1–48. [Google Scholar] [CrossRef]
  65. Heinken, T.; Diekmann, M.; Liira, J.; Orczewska, A.; Schmidt, M.; Brunet, J.; Chytrý, M.; Chabrerie, O.; Decocq, G.; De Frenne, P.; et al. The European forest plant species list (EuForPlant): Concept and applications. J. Veg. Sci. 2022, 33, e13132. [Google Scholar] [CrossRef]
  66. Bušs, K. Forest Ecology and Typology; Zinātne: Rīga, Latvia, 1981; 68p. (In Latvian) [Google Scholar]
  67. Marozas, V.; Racinskas, J.; Bartkevicius, E. Dynamics of ground vegetation after surface fires in hemiboreal Pinus sylvestris forests. For. Ecol. Manag. 2007, 250, 47–55. [Google Scholar] [CrossRef]
  68. Busby, J.R.; Bliss, L.C.; Hamilton, C.D. Microclimate control of growth rates and habitats of the boreal forest mosses, Tomenthypnum nitens and Hylocomium splendens. Ecol. Monogr. 1978, 48, 95–110. [Google Scholar] [CrossRef]
  69. Lõhmus, A.; Remm, L. Disentangling the effects of seminatural forestry on an ecosystem good: Bilberry (Vaccinium myrtillus) in Estonia. For. Ecol. Manag. 2017, 404, 75–83. [Google Scholar] [CrossRef]
  70. Timoshok, E.E. The ecology of bilberry (Vaccinium myrtillus L.) and cowberry (Vaccinium vitis-idaea L.) in Western Siberia. Russ. J. Ecol. 2000, 31, 8–13. [Google Scholar] [CrossRef]
  71. Petersson, L.; Holmström, E.; Lindbladh, M.; Felton, A. Tree species impact on understory vegetation: Vascular plant communities of Scots pine and Norway spruce managed stands in northern Europe. For. Ecol. Manag. 2019, 448, 330–345. [Google Scholar] [CrossRef]
  72. Augusto, L.; De Schrijver, A.; Vesterdal, L.; Smolander, A.; Prescott, C.; Ranger, J. Influences of evergreen gymnosperm and deciduous angiosperm tree species on the functioning of temperate and boreal forests. Biol. Rev. 2015, 90, 444–466. [Google Scholar] [CrossRef] [PubMed]
  73. Augusto, L.; Dupouey, J.L.; Ranger, J. Effects of tree species on understory vegetation and environmental conditions in temperate forests. Ann. For. Sci. 2003, 60, 823–831. [Google Scholar] [CrossRef]
  74. Packham, J.R. Biological Flora of the British Isles. No. 141. Oxalis acetosella L. J. Ecol. 1978, 66, 669–693. [Google Scholar] [CrossRef]
  75. Hitchcock, C.L.; Cronquist, A.; Ownbey, M.; Thompson, J.W. Vascular Plants of the Pacific Northwest; University of Washington Press: Washington, DC, USA, 1969; 914p. [Google Scholar]
  76. Kovács, B.; Tinya, F.; Ódor, P. Stand structural drivers of microclimate in mature temperate mixed forests. Agric. For. Meteorol. 2017, 234, 11–21. [Google Scholar] [CrossRef]
  77. French, L.J.; Smith, G.F.; Kelly, D.L.; Mitchell, F.J.; O’Donoghue, S.; Iremonger, S.F.; McKee, A.M. Ground flora communities in temperate oceanic plantation forests and the influence of silvicultural, geographic and edaphic factors. For. Ecol. Manag. 2008, 255, 476–494. [Google Scholar] [CrossRef]
  78. Coroi, M.; Skeffington, M.S.; Giller, P.; Smith, C.; Gormally, M.; O’Donovan, G. Vegetation diversity and stand structure in streamside forests in the south of Ireland. For. Ecol. Manag. 2004, 202, 39–57. [Google Scholar] [CrossRef]
  79. Saetre, P.; Saetre, L.S.; Brandtberg, P.O.; Lundkvist, H.; Bengtsson, J. Ground vegetation composition and heterogeneity in pure Norway spruce and mixed Norway spruce–birch stands. Can. J. For. Res. 1997, 27, 2034–2042. [Google Scholar] [CrossRef]
  80. Eriksson, O. Seedling recruitment in deciduous forest herbs: The effects of litter, soil chemistry and seedbank. Flora 1995, 190, 65–70. [Google Scholar] [CrossRef]
  81. Esteso-Martínez, J.; Gil-Pelegrín, E. Frost resistance of seeds in Mediterranean oaks and the role of litter in the thermal protection of acorns. Ann. For. Sci. 2004, 61, 481–486. [Google Scholar] [CrossRef]
  82. Graae, B.J.; Heskjær, V.S. A comparison of understorey vegetation between untouched and managed deciduous forest in Denmark. For. Ecol. Manag. 1997, 96, 111–123. [Google Scholar] [CrossRef]
  83. Ellsworth, J.; Harrington, R.; Fownes, J. Seedling emergence, growth, and allocation of oriental bittersweet: Effects of seed input, seed bank, and forest floor litter. For. Ecol. Manag. 2004, 190, 255–264. [Google Scholar] [CrossRef]
  84. Moning, C.; Werth, S.; Dziock, F.; Bässler, C.; Bradtka, J.; Hothorn, T.; Müller, J. Lichen diversity in temperate montane forests is influenced by forest structure more than climate. For. Ecol. Manag. 2009, 258, 745–751. [Google Scholar] [CrossRef]
  85. Bujoczek, L.; Bujoczek, M.; Zięba, S. How much, why and where? Deadwood in forest ecosystems: The case of Poland. Ecol. Indic. 2021, 121, 107027. [Google Scholar] [CrossRef]
  86. Andringa, J.I.; Zuo, J.; Berg, M.P.; Klein, R.; Veer, J.V.; de Geus, R.; de Beaumont, M.; Goudzwaard, L.; van Hal, J.; Broekman, R.; et al. Combining tree species and decay stages to increase invertebrate diversity in dead wood. For. Ecol. Manag. 2019, 441, 80–88. [Google Scholar] [CrossRef]
  87. Dittrich, S.; Jacob, M.; Bade, C.; Leuschner, C.; Hauck, M. The significance of deadwood for total bryophyte, lichen, and vascular plant diversity in an old-growth spruce forest. Plant Ecol. 2014, 215, 1123–1137. [Google Scholar] [CrossRef]
  88. Fries, C.; Johansson, O.; Pettersson, B.; Simonsson, P. Silvicultural models to maintain and restore natural stand structures in Swedish boreal forests. For. Ecol. Manag. 1997, 94, 89–103. [Google Scholar] [CrossRef]
Figure 1. Location of the studied sample plots.
Figure 1. Location of the studied sample plots.
Sustainability 15 07594 g001
Figure 2. The scheme of a sample plot, sector of subplot and grid plots used for census of the vegetation in the studied OG and PHH stands dominated by Scots pine and Norway spruce.
Figure 2. The scheme of a sample plot, sector of subplot and grid plots used for census of the vegetation in the studied OG and PHH stands dominated by Scots pine and Norway spruce.
Sustainability 15 07594 g002
Figure 3. Frequency of the established sample plots according to stand age.
Figure 3. Frequency of the established sample plots according to stand age.
Sustainability 15 07594 g003
Figure 4. DCA ordination of ground cover vegetation species (A) and sample plots (B) according to their projective (relative) cover in the coniferous stands of pre-harvesting/harvesting and old-growth age. Species acronyms (eight letters) were used according to [65]. Abbreviations of vector names: L—light, T—temperature, K—continentality, F—moisture, R—reaction, N—nitrogen, H′_total—Shannon–Wiener diversity index of all species, H′_vascular—Shannon–Wiener diversity index of vascular species, H′_woody—Shannon–Wiener diversity index of woody species, H′_moss—Shannon–Wiener diversity index of bryophytes, Rich_total—richness of all species, Rich_vascular—richness of vascular species, Rich_woody—richness of woody species, Rich_moss—richness of bryophytes, Cover_litter—cover of litter layer, Cover_vascular—cover of vascular layer, Cover_moss—cover of bryophyte layer, Height_canopy—canopy height, Height_III—understory height, Density_coniferous—density of coniferous in canopy, Density_III—understory density, M_III—understory stock, G_total—total basal area, iqrD—interquartile range of canopy tree diameter, Coniferous_%—proportion of coniferous in canopy, Spruce_%—proportion of spruce in canopy, Spruce_II_%—proportion of spruce in second canopy layer, Density_pine_canopy—density of canopy pine, Age—stand age. Note that scales differ between the panels.
Figure 4. DCA ordination of ground cover vegetation species (A) and sample plots (B) according to their projective (relative) cover in the coniferous stands of pre-harvesting/harvesting and old-growth age. Species acronyms (eight letters) were used according to [65]. Abbreviations of vector names: L—light, T—temperature, K—continentality, F—moisture, R—reaction, N—nitrogen, H′_total—Shannon–Wiener diversity index of all species, H′_vascular—Shannon–Wiener diversity index of vascular species, H′_woody—Shannon–Wiener diversity index of woody species, H′_moss—Shannon–Wiener diversity index of bryophytes, Rich_total—richness of all species, Rich_vascular—richness of vascular species, Rich_woody—richness of woody species, Rich_moss—richness of bryophytes, Cover_litter—cover of litter layer, Cover_vascular—cover of vascular layer, Cover_moss—cover of bryophyte layer, Height_canopy—canopy height, Height_III—understory height, Density_coniferous—density of coniferous in canopy, Density_III—understory density, M_III—understory stock, G_total—total basal area, iqrD—interquartile range of canopy tree diameter, Coniferous_%—proportion of coniferous in canopy, Spruce_%—proportion of spruce in canopy, Spruce_II_%—proportion of spruce in second canopy layer, Density_pine_canopy—density of canopy pine, Age—stand age. Note that scales differ between the panels.
Sustainability 15 07594 g004
Table 1. General description of ground cover vegetation in the studied coniferous stands of pre-harvesting/harvesting (PHH) and old-growth (OG) age in the hemiboreal forest zone, Latvia. SE—standard error.
Table 1. General description of ground cover vegetation in the studied coniferous stands of pre-harvesting/harvesting (PHH) and old-growth (OG) age in the hemiboreal forest zone, Latvia. SE—standard error.
Ground FloraVascularWoodyBryophyte
MeanSEMeanSEMeanSEMeanSE
Number of speciesPHH21.132.3511.631.633.070.476.420.66
OG19.082.6810.671.782.710.675.710.96
Relative projective cover (%)PHH112.034.3443.485.533.771.1964.786.28
OG103.196.0642.577.082.611.1958.019.90
Shannon-Wiener indexPHH2.450.141.890.171.250.110.480.13
OG2.370.161.830.191.10.160.440.17
Table 2. Occurrence (% of plots) and mean projective cover (% of area) of most common species in the pre-harvesting/harvesting age and old-growth stands (plots).
Table 2. Occurrence (% of plots) and mean projective cover (% of area) of most common species in the pre-harvesting/harvesting age and old-growth stands (plots).
Pre-Harvesting/Harvesting Age StandsOld-Growth Stands
SpeciesCoverOccurrenceSpeciesCoverOccurrence
Vaccinium myrtillus18.2789.36Vaccinium myrtillus14.3079.82
Oxalis acetosella9.5578.19Oxalis acetosella12.6380.73
Calamagrostis arundinacea9.5476.60Calamagrostis arundinacea4.3854.13
Maianthemum bifolium2.4279.26Maianthemum bifolium3.3681.65
Pteridium aquilinum2.3528.19Luzula pilosa2.7777.98
Luzula pilosa2.0370.21Vaccinium vitis-idaea2.5850.46
Vaccinium vitis-idaea2.0241.49Pteridium aquilinum2.0720.18
Carex digitata1.7946.81Athyrium filix-femina1.8321.10
Melampyrum pratense1.7537.23Trientalis europaea1.6657.80
Trientalis europaea1.6867.02Melampyrum pratense1.6131.19
Rubus saxatilis1.5932.45Rubus saxatilis1.7026.61
Dryopteris carthusiana1.4543.09Dryopteris carthusiana1.5737.61
Festuca ovina1.2513.30Carex digitata1.5642.20
Table 3. The relationships between the first two gradients of ground cover vegetation in the studied coniferous stands of pre-harvesting/harvesting and old-growth age and stand/site characteristics.
Table 3. The relationships between the first two gradients of ground cover vegetation in the studied coniferous stands of pre-harvesting/harvesting and old-growth age and stand/site characteristics.
DCA1
Fixed effects
χ2p-value
Light357.7<0.001
Reaction120.0<0.001
Moisture15.6<0.001
Canopy coniferous, %74.6<0.001
Understory stock5.00.02
Density of Betula in canopy13.0<0.001
Model performance
R2, marginal0.77
R2, conditional0.88
DCA2
Fixed effects
χ2p-value
Nitrogen36.4<0.001
Total standing stock6.80.009
Model performance
R2, marginal0.13
R2, conditional0.70
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Matisone, I.; Jansone, D.; Jaunslaviete, I.; Matisons, R.; Liepiņa, A.A.; Jansons, Ā. Stand Structure Beats Age for Ground Cover Vegetation in Ageing Hemiboreal Scots Pine and Norway Spruce Stands. Sustainability 2023, 15, 7594. https://doi.org/10.3390/su15097594

AMA Style

Matisone I, Jansone D, Jaunslaviete I, Matisons R, Liepiņa AA, Jansons Ā. Stand Structure Beats Age for Ground Cover Vegetation in Ageing Hemiboreal Scots Pine and Norway Spruce Stands. Sustainability. 2023; 15(9):7594. https://doi.org/10.3390/su15097594

Chicago/Turabian Style

Matisone, Ilze, Diāna Jansone, Ieva Jaunslaviete, Roberts Matisons, Agnese Anta Liepiņa, and Āris Jansons. 2023. "Stand Structure Beats Age for Ground Cover Vegetation in Ageing Hemiboreal Scots Pine and Norway Spruce Stands" Sustainability 15, no. 9: 7594. https://doi.org/10.3390/su15097594

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop