Litter legacy after spruce plantation removal hampers initial vegetation establishment

Journal Pre-proof Litter legacy after spruce plantation removal hampers initial vegetation establishment Jonas Morsing, Sebastian Kepfer-Rojas, Lars Baastrup-Spohr, ´ Alexia Lopez Rodr´ıguez, Karsten Raulund-Rasmussen

PII:

S1439-1791(19)30306-8

DOI:

https://doi.org/10.1016/j.baae.2019.11.006

Reference:

BAAE 51223

To appear in:

Basic and Applied Ecology

Received Date:

30 April 2019

Accepted Date:

19 November 2019

´ Please cite this article as: Morsing J, Kepfer-Rojas S, Baastrup-Spohr L, Lopez Rodr´ıguez A, Raulund-Rasmussen K, Litter legacy after spruce plantation removal hampers initial vegetation establishment, Basic and Applied Ecology (2019), doi: https://doi.org/10.1016/j.baae.2019.11.006

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Litter legacy after spruce plantation removal hampers initial vegetation establishment

Jonas Morsinga*, Sebastian Kepfer-Rojasa, Lars Baastrup-Spohrb, Alexia López Rodrígueza, Karsten RaulundRasmussena

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a) Section for Forest, Nature and Biomass, Department of Geosciences and Natural Resource Management, University of Copenhagen, Rolighedsvej 23, 1958 Frederiksberg C, Denmark

b) Freshwater Biological Section, Department of Biology, University of Copenhagen, Universitetsparken 4,

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3. Floor, 2100 Copenhagen Ø, Denmark

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* Corresponding author. E-mail address: [email protected].

Highlights

Presence of spruce litter alters vegetation development after clear-cut.

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Spruce litter can be considered a degrading legacy after plantation removal.

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By litter removal, early stage vegetation establishment can be enhanced.

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Wildlife grazing can suppress the litter removal effect.

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Abstract

Restoration of areas used for intensive even-aged Norway spruce (Picea abies Karst.) plantations often involves felling and subsequent spontaneous vegetation succession. However, the accumulated litter layer may hamper vegetation development, and thereby postpone recovery or even change the outcome.

We studied effects of the litter layer on vegetation establishment during two seasons following a clear-cut of Norway spruce in Denmark. We experimentally assessed the response of multiple vegetation properties to litter removal, with and without wildlife exclusion by fencing, and in combination with sowing of trees, while fencing. Burning was tested as an alternative way to remove the litter layer. Vegetation establishment was poor, when the litter layer was intact, and cover developed slowly remaining below 10% after two years, irrespective of fencing. In contrast, litter removal and fencing together gave

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significantly faster recovery and reached nearly 60% mean cover. Vegetation cover was driven by few dominant species, especially the sedge Carex pilulifera. Species richness was similar in all treatments, but increased with sowing of trees. Fencing resulted in taller birch seedlings independently of litter removal, but enhanced by seedling density. Litter removal seemed to favor species with lighter seeds, lower specific

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leaf area (SLA) and lower Ellenberg N value, i.e. associated with relative infertile conditions. Disturbing the

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litter by burning seemed to have an effect comparable to mechanical removal, and could be a management alternative.

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Our results showed that a persistent litter layer after spruce plantation removal may hamper the initial vegetation establishment. Actively removing litter may serve as an additional restoration intervention to

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overcome this legacy. However, as grazing can keep this potential in check, wildlife exclusion may be necessary as well. To speed up recovery and diversify vegetation structure after spruce plantation removal,

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we suggest patchy disturbance of the litter, essentially combined with wildlife exclusion.

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Keywords: Dispersal filter; Ecological restoration; Forest; Grazing exclusion; Secondary succession; Seedbank

Introduction

Monospecies plantations became widespread in Europe during the 19th and 20th century (Richardson & Rejmánek 2004). In lowlands, plantations often consist of coniferous species outside their natural range such as Norway spruce (Picea abies Karst.) (Hansen & Spiecker 2005; von Teuffel, Heinrich & Baumgarten 2004). In Denmark, approximately 21% of the forest area is spruce plantations (Nord-Larsen, Johannsen, Arndal, Riis-Nielsen, Thomsen et al. 2017). The even-aged monocultures are known to significantly change the environment compared to native deciduous or mixed forests, and have thus changed the local biodiversity of many lowland European forests (Felton, Lindbladh, Brunet & Fritz 2010; Heine, Hausen,

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Ottermanns, Schäffer & Roß-Nickoll 2019).

Increasing interest in forest biodiversity conservation in Europe (Halme, Allen, Auniņš, Bradshaw, Brūmelis et al. 2013; Petersen, Strange, Anthon, Bjørner & Rahbek 2016) and predictions of future production

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limitations of Norway spruce (Huang, Fonti, Larsen, Ræbild, Callesen et al. 2017), have led to increased

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focus on restoration through spontaneous secondary succession after clear-cut (Saure, Vetaas, Odland & Vandvik 2013). A rapid increase in ground vegetation cover can be expected from the abrupt increase in

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available light (Barbier, Gosselin & Balandier 2008; Härdtle, von Oheimb & Westphal 2003; Sercu, Baeten, van Coillie, Martel, Lens et al. 2017), but may be hampered by local environmental and biotic factors.

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A litter legacy could act as an unresolved aspect of the plantation. Under densely planted Norway spruce, a thick mor layer of only slightly decomposed litter develops (Berg & McClaugherty 2014; Joly, Milcu,

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Scherer-Lorenzen, Jean, Bussotti et al. 2017). Compared with broadleaved deciduous litter, spruce litter has a high C:N ratio and a relatively low pH (Dawud, Raulund-Rasmussen, Ratcliffe, Domisch, Finér et al. 2017;

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Vesterdal & Raulund-Rasmussen 1998). This litter layer can affect the development of the vegetation in different ways. At the time of felling, the litter itself will be the seed bed for the existing seed bank, often consisting of relatively large and short-lived seeds (Bossuyt & Hermy 2001; Kjellsson 1992). Depending on litter type and quality, a litter layer represents cold, moist and nutrient-rich conditions (Xiong & Nilsson 1997), likely reflected in functional traits of the germinating vegetation community. In addition, litter layers

act as physical barriers for establishing vegetation by filtering for species that can penetrate it (Barbier et al. 2008; Xiong et al. 1997). Such effects may persist after clear-cutting (Loydi, Lohse, Otte, Donath & Eckstein 2013; Stahlheber, Crispin, Anton & D'Antonio 2015), but again depend on litter type, quality and quantity. As an example, Koorem, Price and Moora (2011) experimentally found addition of Norway spruce litter to hamper seedling emergence more than deciduous litter from Hazel (Corylus avellana), an effect that increased with depth of the litter.

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Active removal of the litter layer after Norway spruce plantation removal could thus be expected to enhance germination and establishment of a new vegetation layer. Allison and Ausden (2006) studied

heathland restoration potential and documented a better short-term establishment of Calluna vulgaris where Norway spruce litter was experimentally removed. Also Rydgren, Hestmark and Okland (1998) found

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different vegetation development depending on the severity of soil and litter disturbance, when they

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mimicked Norway spruce uprooting. More generally, following litter removal, the conditions of the exposed mineral soil can lead to changes in the functional trait composition of the community (i.e. community

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weighted means (CMW)). Trait-based ecology suggests that conservative species with a “slow” ecological strategy will be favored in these conditions (Reich 2014), leading to communities with lower average values

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of specific leaf area (SLA) and with lower Ellenberg N indicator values. Vegetation establishment and successional direction in spruce clear-cuts will further be affected by wild

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ungulate presence (Ramirez, Jansen, den Ouden, Goudzwaard and Poorter 2019) and wildlife exclusion may be necessary to ensure vegetation development in response to litter removal. In addition, the remaining

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seed bank in the mineral soil after litter removal may be insufficient for forest restoration (Bossuyt and Honnay 2008). Where spruce plantations are found on former heathlands, the mineral soil seed bank will likely contain relative large proportions of long-persistent seeds (~30-200 years) with low seed mass such as C. vulgaris (Bossuyt et al. 2001; Kjellsson 1992). After spruce plantation felling and litter removal, addition

of tree seeds to the seed bank may thus be a necessary intervention to accelerate the development towards forest. In practical applications, extraction costs may preclude mechanical litter removal in forest restoration. Burning could be an alternative, even though both outcome (e.g. Čugunovs, Tuittila, Mehtätalo, Pekkola, Sara-Aho et al. 2017) and cost-effectiveness are unclear (Halme et al. 2013). In relation to restoration of former Norway spruce plantations, there is a lack of in situ testing of the effect

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of a spruce litter legacy, and tools to overcome it. In this study, we present the results of a two year experiment conducted within a larger restoration project including Norway spruce plantation removal. Specifically we tested how the initial ground vegetation establishment responded to experimental

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restoration treatments of the litter layer, i.e. by mechanical removal or burning. The response to litter

removal was investigated with and without influence of wildlife grazing, i.e. by fencing, and in combination

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with additional sowing of trees, while fencing. Responses were assessed primarily by vegetation cover, and in addition as plant species richness and height of trees. Finally we used community weighted traits and an

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ecological indicator value to interpret the responses to the treatments.

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Materials and methods Study area

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The experimental site was located within the restoration area along the headwater stream ‘Øle Å’, on the

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Danish Baltic island Bornholm (55°05'45"N 15°01'31"E), within a Natura2000 protected area. In autumn 2014, 6 ha of intensively managed Norway spruce stands were felled and removed, stretching 3.5 km along the stream (Kallenbach, Sand-Jensen, Morsing, Martinsen, Kragh et al. 2018; Morsing, Sand-Jensen, Båstrup-Spohr, Larsen & Raulund-Rasmussen 2017). Thereafter, the area was left for open-ended successional development to enhance ecological integrity and recreational possibilities. The specific stand was 31 years at the time of felling. The area had a flat topography approximately 90 m.a.s.l., and was

characterized by a sandy Inceptisol soil and a mean pH (CaCl2) of 3.2 in top 5 cm mineral soil below the litter layer. Seasonal water logging was found within 40 cm and bedrock within 2 m. Mean monthly temperatures (norm 2006-2015) vary from 1 °C in February to 18 °C in August with an annual mean precipitation of 719 mm (Danish Meteorological Institute 2019). Experimental setup and data collection A randomized experiment was established, consisting of six treatments applied to 2x2 m plots, and

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replicated in three blocks (Fig. 1, Table 1). Blocks were 5x9 m to allow buffers precluding interference between treated plots. The area designated for the experiment was sheltered from ground disturbance during the felling campaign. The treatments were combinations of litter disturbance, fencing and sowing of

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trees, and were applied during winter 2014-2015. Litter was removed manually by hand and rake until the appearance of mineral soil. Few scattered needles stayed behind. A 2-m-tall woven wire fence to exclude

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large wildlife (deer) was erected simultaneously. Seeds of Alnus glutinosa, Betula pendula, Pinus sylvestris and Quercus robur were sown by hand, each species on a quarter of a plot. Burning was done manually

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with a handheld gas weed burner in late winter. As the litter layer was moist and with abundant fungal mycelium, it was loosened by a rake to aerate for one month between two individual burning campaigns.

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The burning treatment ignited but did not entirely remove the litter layer until the mineral soil. At the time of the felling, there were no vascular plants within the plots, except for one tiny Q. robur seedling.

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Each plot was divided into 16 subplots of 0.25 m² (Fig. 1). Vegetation cover was estimated visually per

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subplot by at least two observers, both as cover per species and as total cover, i.e. where overlapping leaves of different species counted only once. Differences between small cover classes are more easily distinguished than small differences between larger classes (Peet, Wentworth & White 1998). Thus we used a modified Londo scale following Zaplata, Winter, Anton, Kollmann and Ulrich (2013) (≤0.1% (0.1), >0.1%– 0.5% (0.5), >0.5%–1% (1), >1%–2% (2), in 1% steps up to 10, >10%–15% (15), >15%–20% (20); in 10% steps up to 100). All tree seedlings were counted in each subplot and the height from ground to topmost bud was

measured for seedlings higher than 10 cm. In total six assessments were completed (June, August and October in 2015 and in 2016). Vascular plants were identified to species level. Betula pendula and B. pubescens were both observed, but as they are often indistinguishable in the germination stage (Muller 1978) they were treated as one species. Because B. pendula was the more frequent of the two and the most common in the area, ecological indicator values for this species were used in the analyses. Blackberries were collectively treated as Rubus

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fruticosus agg.. To describe the vegetation composition, we assigned the species to four functional groups (see Appendix A: Table 1 and 2): ‘graminoids’, ‘forbs’, ‘shrubs’ (dwarf and half shrubs) and ‘trees’ (larger shrubs and trees).

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Data analysis

The development of total vegetation cover as a function of time (6 levels) and treatments (6 levels) was

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modelled using a Gaussian linear mixed-effects model. The interaction of time and treatment was included

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to investigate temporal differences in the treatment effect. Data exploration following the protocol of Zuur and Ieno (2016) showed better model fit by log10 transforming the response variable. We used backward

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model selection, starting with inclusion of all response variables as well as the interaction between time and treatment, and proceeded by removing the least significant one by one, until only significant ones

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remained.

Total yearly vascular plant species richness was similarly modelled as a function of time and treatment, but

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using a generalized linear mixed-effects model with a Poisson distribution as often used for count data. . To investigate the effect of treatments on the mean height of Betula ssp. seedlings at the final assessment (October 2016), we fitted a linear mixed-effects model with the two explanatory variables treatment and number of Betula ssp. seedlings at the first assessment. We included a variance structure for treatment (varIdent in ‘nlme’) to account for observed variance heterogeneity.

For the three mixed-effects models, we used subplots as measurement units (n=288). However, as subplot can be argued to be sacrificial pseudoreplicates with consequent increased risk of Type I errors (Gibson 2015; Hurlbert 1984), we modelled the dependency structure by nesting subplots within a random intercept of plot and block. Thereby, we both account for spatial and temporal dependency among observations of the same subplot. Comparisons among treatments were tested with a post-hoc Tukey Honest Significant Difference test (Tukey HSD) at each sampling time, on back-transformed estimates.

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We used two functional traits together with Ellenberg indicator values for nitrogen in order to analyze the functional response of the community to the different treatments. We focused on indicators related to the seed bank composition, i.e. seed mass (mg), Ellenberg N value as a proxy for soil fertility, and specific leaf area (SLA) (mm²/mg) to reflect nutrient acquisition ability and thus opportunity for rapid growth after

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disturbance (see Appendix A: Table 1 and 2). Community weighted means (CWM) for each trait were

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calculated for each subplot based on cover per species, using the August samples, as these represent the most developed vegetation community of each year, prior to defoliation of deciduous trees. As CWM

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values did not show homogeneous variance they were analyzed with non-parametric Kruskal-Wallis tests on plot mean values (n=3) per year (2 levels) followed by post-hoc Dunn's test of multiple comparisons.

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Quercus robur was omitted from the seed mass analysis as an outlier due to its superior size. One trait value was not available for two subordinate species (see Appendix A: Table 2). However, they accounted

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for less than 10% cover in subplots where present, and were therefore not expected to influence the result significantly (Pakeman & Quested 2007).

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All statistical analyses and graphics were made with R version 3.5.1 (R Core Team 2018). The “lme4” (Bates, Mächler, Bolker & Walker 2015), “lmerTest” (Kuznetsova, Brockhoff & Christensen 2017) and “nlme” (Pinheiro, Bates, DebRoy, Sarkar & Team 2018) packages were used to fit models and to find significance levels and significance of interactions. Contrasts between treatments over time were tested with TukeyHSD obtained with the “emmeans” package (Lenth 2018). Kruskal-Wallis tests were done with the “stats”

package incorporated in R (R Core Team 2018), and Dunn’s test using the “dunn.test” package (Dinno 2017). Visualizations were made with the “ggplot2” (Wickham 2016) and “cowplot” (Wilke 2018) packages. Results Total vegetation cover increased over time (Fig. 2), with increasing difference between treatments (Table 2, see Appendix A: Table 3). From the end of the first season, total vegetation cover was highest where litter removal and fencing were combined (Fig. 2). Total vegetation cover in the fenced and litter removal plots

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respectively developed similarly to the control, whereas cover was intermediate when fenced and burned and where litter removal, fencing and sowing was combined. Nearly half of the random variation was

associated with the repeated measuring of the same subplots (~44%), a quarter with the subplots being

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nested in plots (~27%) and with residual variance (~26%), but only a small fraction associated with spatial variation between blocks (~3%).

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In total 32 plant species were observed in the experiment (see Appendix A: Table 2), with 24 in 2015 and 31

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in 2016 (see Appendix A: Table 4). Mean species richness per subplot increased to 4.9 (SE=1.6) through the two seasons across treatments (Table 2, see Appendix A: Table 5), with a difference between treatments

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both years (Table 2). Post hoc pairwise comparisons showed that species richness was higher where additional trees were sown in fenced, litter removal plots compared to fencing alone (Fig. 3). Nearly half of the species were uniquely observed in one subplot, and were thus present with only a small mean cover

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(see Appendix A: Table 4). Four tree species were sown, and a total of ten tree species were observed

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germinating. By cover, the dominant functional group was graminoids, of which C. pilulifera dominated (see Appendix A: Table 4).

The height of Betula ssp. was greatest in fenced or fenced and burned plots (Fig. 4 , see Appendix A: Table 6). Height was positively correlated with the number of Betula ssp. seedlings at the first assessment (Table 2). At this point, the absolute highest density (352 in 0.25 m²) was observed where B. pendula was sown (not shown).

For the three CWM trait and indicator values, an intact litter layer was in general associated with higher mean values but also larger variation irrespective of fencing (Fig. 5). In the second season, both seed mass and SLA differed between treatments (Table 2). Control and fencing showed highest values, while litter removal showed lowest seed mass (Fig. 5A) and litter removal together with fencing and sowing showed lowest SLA (Fig. 5B). A similar pattern was found in CWM Ellenberg N values (Fig. 5C), with a treatment effect in the first season (Table 2), with lowest values where the litter was disturbed and intermediate

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values where litter removal was combined with fencing and sowing. Discussion Spontaneous establishment after spruce clear-cut

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Under control conditions, i.e. where Norway spruce plantation was felled and removed but no other actions taken, vegetation establishment was relatively poor and development slow. Many subplots

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remained un-vegetated throughout the two seasons, and the mean vegetation cover remained below 10%.

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This pattern is analogous to other studies of spruce clear-cuts, where only 11.7% cover were observed after two years in a study in the UK while an investigation from Germany reported sustained incomplete ground

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vegetation cover after 4 years (Borchard, Hardtle, Streitberger, Stuhldreher, Thiele et al. 2017; Spracklen, Lane, Spracklen, Williams & Kunin 2013).

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In our experiment, the dominant species in terms of cover in the control was the graminoid Carex pilulifera, reaching 8% mean cover. C. pilulifera is common in dry acid sandy habitats and forest clearings in Europe,

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and has relative large and long-persistent seeds (Kjellsson 1992) like Rubus idaeus, Senecio sylvaticus and Holcus lanatus, which also established frequently. S. sylvaticus may benefit from the unoccupied and relatively nutrient-rich conditions after clear-cuts (Halpern 1989), and completed several reproductive cycles during the study period. Betula sp., which in contrast has lighter, short-lived seeds, was also common. Several other species were observed, but with limited occurrences in single subplots. The

available species pool thus appeared rather large, consisting of both persistent seeds already present and some recently deposited. Effect of removing the litter The dominant species when litter was removed was also C. pilulifera, and while this species reached higher mean cover than in control, we found no difference in total vegetation cover. We found that community weighted mean (CWM) seed mass, specific leaf area (SLA) and Ellenberg N value were all lower when litter

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was removed. In boreal spruce forests, Rydgren et al. (1998) showed increasingly different vegetation composition in relation to severity of litter and soil disturbance, when mimicking storm-induced tree

uprooting. We found no difference in species number following litter removal. However, the lower seed

species germinated which the litter otherwise suppressed.

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mass suggests that species with heavier seeds may have been removed along with the litter, while other

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If trait and indicator values for adult plants also reflect those of seedlings, as documented by Fraaije, ter

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Braak, Verduyn, Breeman, Verhoeven et al. (2015), our results of lower CWM Ellenberg N value and SLA indicated that the litter removal exposed a relatively infertile environment (Hill, Mountford, Roy & Bunce

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1999), and favored species with a conservative strategy respectively. As an example, we uniquely observed Calluna vulgaris germinating in treatments where the litter was disturbed, similarly to Allison et al. (2006) and Borchard et al. (2017). Heathland species, such as C. vulgaris, are known to persist well under spruce

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plantations (Bossuyt et al. 2001; Kjellsson 1992). In accordance, the plantation studied here was established

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on a heathland in the late 19th century. This implies that litter after spruce plantation removal constitutes a legacy that hampers certain vegetation from emerging, as suggested by Koorem et al. (2011). Even smallscale disturbances may thus enable later variation in the community. Excluding wildlife grazing

Fencing in itself, without disturbing the litter, resulted in a similar vegetation composition as the control, in terms of total vegetation cover and CWM trait and indicator values. Looking at species identity, we found higher cover of highly palatable species like Epilobium angustifolium and Rubus idaeus inside the fences, but lower cover of C. pilulifera. Tree seedlings such as Betula sp. performed better when fenced, reaching double the mean height during the second season, even though the fence did not exclude herbivores up to the size of rabbits. The ungulates roe deer (Capreolus capreolus L.) and fallow deer (Dama dama L.) are present in the area, and their exclusion may well change the vegetation composition and development

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(Bernes, Macura, Jonsson, Junninen, Müller et al. 2018; Boulanger, Dupouey, Archaux, Badeau, Baltzinger et al. 2018).

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Synergistic effect of combining treatments

Litter removal in combination with fencing had a similar effect on CWM trait and indicator values as litter

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removal alone. We found a significant synergistic effect in terms of increased total vegetation cover. While species richness was unaffected, certain species developed higher cover. Most notably was the

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considerable increase in C. pilulifera cover, and to some degree Betula sp.. Apparently, presence of litter hampered the germination or growth of the dominant C. pilulifera, whereas grazing reduced it when

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growing in the mineral soil outside the fences. As we did not see a positive effect of fencing on total vegetation cover where the litter layer was intact (no difference between control and fencing), this leads to

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speculations on different herbivory tolerance in relation to the soil properties (Hawkes & Sullivan 2001). Such an interaction was not influencing height of Betula sp., where fencing irrespective of litter removal

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resulted in taller seedlings than at control. Restoration via spruce plantation removal may therefore benefit from even small-scale measures to exclude wildlife grazing where the litter is disturbed, in order to accelerate vegetation development, which later could be expected to increase the spatial variation. Although a two-year study is insufficient to answer the long-term impact on succession, initial recruitment may be important for the later vegetation

composition. Fraaije et al. (2015) showed the importance of niche differentiation in recruitment processes, and the establishment of certain species may give priority effects to later establishing species (Fukami 2015). By changing the composition of emerging species and by reducing their growth in terms of cover, spruce litter influenced the recruitment process after plantation removal. Additional sowing of trees We found a positive effect of seedling density on Betula sp. height across treatments. We supplemented

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the natural seed bank by sowing trees to enhance seedling density experimentally. However, the establishment rate of the Betula sp. was poor, with many seedlings dying during the first season. Betula sp. cover and height was thus not improved by sowing per se. Sown Alnus glutinosa, Pinus sylvestris and

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Quercus robur all established with some individuals. Evaluation of the community effect of tree sowing was not possible after two seasons, but sowing increased the CWM Ellenberg N value and decreased the CWM

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SLA. Both results could be an effect of slightly decreased relative cover of C. pilulifera.

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Burning the litter

In burned and fenced plots, we found a similar effect to where the litter was mechanically removed behind

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fence. The only difference was even taller Betula sp. seedlings. This could indicate increased nutrient availability after burning. Burning after clear-cut is a common practice to enhance biodiversity or forest

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regeneration in boreal forests (Halme et al. 2013), but we found no studies on ground vegetation development in burnt Norway spruce clear-cuts. Allison et al. (2006) questioned the feasibility of

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mechanical litter removal, and thoroughly discussed the practicality of large-scale implementation, and potential marketization difficulties due to high abstraction and transportation costs. Our results points at prescribed burning to be a practical alternative, even though the litter was only partially disturbed by burning. Conclusion

Overall, our results showed that a persistent litter layer after spruce plantation removal might hamper the establishment of a new vegetation cover. Litter removal triggered a slightly different vegetation composition as expressed in CWM trait and indicator values, and exclusion of wildlife grazing was in this case instrumental to speed up vegetation development. As such, litter is arguably a degrading legacy for a rapid or diverse recovery. Actively removing the litter may serve as an additional restoration tool to overcome this legacy. However, as ungulate grazing can keep this potential in check, wildlife exclusion may be necessary as well. To speed up recovery and structurally diversify vegetation development after spruce

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plantation removal, we suggest patchy disturbance of the litter layer, essentially in combination with

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wildlife exclusion.

Declaration of interests

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☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

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We thank Jesus Serrano, Kristiyan Panayotov, Emilie Hansen, Juliette Babin, Julia Maschler, Malene Bang, Esther Henrichsen, Fanny Grabmayr, Lasse Gottlieb and Rita Buttenschøn for field assistance and useful

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comments, and Malene for graphical artwork. We are grateful for the useful comments from three

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anonymous reviewers, the guest editor and the editor. The Nature Agency assisted with burning, Levinsen & Abies A/S provided free tree seeds and Skovshoved Møbelfabrik provided a free field cot for nondestructive investigation of emerging plants within the plots, all of which we gratefully welcome. Funding: This work was supported by the Villum Foundation [grant number VKR022981].

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Fig. 1. The experiment consisted of three blocks within a larger restoration area, where 6 ha of Norway spruce was felled along 3.5 km headwater stream in 2014. On the picture, deciduous trees cover the

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stream itself in the middle of the intervention area (approximately 50 m wide). (A) Each block contained 6 treated plots. (B) Each plot was subdivided in 16 subplots for measurements. © Oblique angel photo of

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May 18th 2017 by ‘Agency for Data supply and Efficiency’, retrieved November 2018.

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Fig. 2. Temporal development in total vegetation cover (%), measured in 0.25 m² subplots. Letters indicate grouping of significantly different treatments at the sampling time, based on estimates from a linear mixed-

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effects model (see text), and tested with post-hoc TukeyHSD contrasts (alpha = 0.05).

Fig. 3. Richness of observed vascular plant species per year. Letters indicate grouping of significantly different treatments at the sampling time, based on estimates from a generalized mixed-effects model (see

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text), and tested with post-hoc TukeyHSD contrasts (alpha = 0.05).

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Fig. 4. Mean height of Betula ssp. seedlings per treatment at the end of the second growing season, measured in 0.25 m² subplots. Letters indicate grouping of significantly different treatments, based on estimates from a linear mixed-effects model (see text), and tested with post-hoc TukeyHSD contrasts (alpha

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= 0.05).

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Fig. 5. Community cover weighted mean seed mass (A), specific leaf area (SLA) (B), and Ellenberg N values (C) per treatment in August each year per 8 m² plot. Lower-case letters indicate grouping of significantly different treatments, tested with post-hoc Dunn’s Test (alpha = 0.05).

Table 1. Treatments in the experiment. Treatment

Control

No additional treatment after felling of Norway spruce. The litter layer was undisturbed by the felling.

Fencing

Large wildlife was excluded by a 200 cm woven wire fence. The litter layer was undisturbed by the felling.

Litter removal

The litter layer was mechanically removed until the top of the mineral soil by hand and using a rake.

Litter removal + fencing

Combination of ‘Litter removal’ and ‘Fencing’.

Litter removal + fencing + sowing

Combination of ‘Litter removal’ and ‘Fencing’ combined with sowing of Alnus glutinosa, Betula pendula, Pinus sylvestris and Quercus robur in separate subplots.

Burning + fencing

The litter layer was partially burned using a handheld gas burner in combination with ‘Fencing’.

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Name of treatment

Table 2. Test statistics on initial vegetation development. The effect of time and treatment on total vegetation cover and species richness, and effects of treatment and initial number of Betula sprouts on Betula height, were obtained by mixed effect models. The effects of treatment in August each year on community weighted mean (CWM) seed mass, specific leaf area (SLA) and Ellenberg N value were obtained

F / χ²

P

5, 10 5, 1407.2 25, 1407.2

4.546 789.852 10.652

0.0201 <0.0001 <0.0001

1 5

164.929 11.271

<0.0001 0.0463

5, 7 1, 78

20.991 8.400

0.0004 0.0049

5 5

9.444 13.49

0.0926 0.0192

5 5

8.906 11.175

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5 5

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DF

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Total vegetation cover Time Treatment Time*Treatment Species richness Time Treatment Betula height Treatment No. of sprouts CWM seed mass Treatment 2015 Treatment 2016 CWM SLA Treatment 2015 Treatment 2016 CWM Ellenberg N Treatment 2015 Treatment 2016

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by Kruskal-Wallis tests. Chi-squared-values are in italic.

0.1129 0.0480

0.0139 0.0926