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Keywords:

  • bryophyte;
  • carbon cycling;
  • chemical traits;
  • classification;
  • decomposition;
  • FTIR-ATR;
  • higher plant;
  • lichen;
  • litter bed;
  • subarctic

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

1. Climate change in the subarctic is expected to influence vegetation composition, specifically bryophyte and lichen communities, thereby modifying litter decomposition rates and carbon (C) dynamics of these systems with possible feedbacks to climate.

2. In a 2-year experiment, we investigated decomposition rates and chemical traits of 27 bryophytes, 17 lichens and 5 vascular plants in litter beds in subarctic Sweden. The majority of the sampled cryptogam species are widespread at higher northern latitudes.

3. Average 2-year litter decomposition rates (exponential mass loss constant k) of lichen (0.44 ± 0.01) and vascular plant (0.56 ± 0.03) species were higher than that of bryophytes (0.11 ± 0.01), while within main cryptogam taxa, species identity was an important determinant of mass loss rates. At cryptogam group level, 2-year litter mass loss of Sphagnum was significantly lower than for non-Sphagnum mosses and liverworts. Within lichens, N2-fixing versus non-N2-fixing lichens showed no variation in decomposability.

4. In a subset of the large species set, mass loss differed both among incubation environments (reflecting nutrient-rich and poor birch forest and Sphagnum peatlands, respectively) and species. The pattern of mass loss across incubation environments was not consistent among cryptogam species. N2-fixing, in contrast to non-N2-fixing lichens with lower nitrogen (N) levels displayed similar decomposition rates across incubation environments. Mass loss of non-Sphagnum mosses was correlated with initial N irrespective of incubation environment.

5. Litter mass loss of cryptogam taxa could be predicted very well from infrared spectra of the initial chemical composition of the species, by application of Fourier transform infrared using an attenuated total reflectance probe. The initial macronutrient concentrations (N, phosphorus, C and cations) and initial litter pH correlated less well.

6.Synthesis. We showed comprehensively that decomposition rates of bryophytes are generally lower than those of lichens and vascular plants. Among bryophyte or lichen species there is also great variation in litter decomposability which depends strongly on species-specific chemistry. Our data will help predict changing land surface feedback to C cycles and climate in cold biomes by understanding long-term climate effects on litter decomposability through shifting vegetation composition.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

Non-vascular cryptogams, namely, lichens and bryophytes, play important roles in ecosystems where environmental stress limits the abundance of vascular plants. At high latitudes where vascular plant productivity is low, they constitute more than half (Matveyeva & Chernov 2000) of all existing autotrophic species and a substantial proportion of the above-ground biomass. The generally low decomposition rates of bryophytes (Heal & French 1974) also lead to great organic matter accumulation and thereby carbon (C) sequestration of a globally significant magnitude (Gorham 1991). These features are closely linked with other important ecosystem functions fulfilled by cryptogams (Cornelissen et al. 2007). Thick layers of live and dead bryophytes, especially peat mosses, control the hydrology of vast peatland areas (Beringer et al. 2001) but also preserve permafrost through their temperature-insulating capacity (Gornall et al. 2007). The N2-fixing capacity of some bryophytes (Solheim, Endal, & Vigstad 1996) and lichens (Crittenden & Kershaw 1978) is especially important in these northern ecosystems where nitrogen (N) availability is low. The turnover rates of new N entered into ecosystems via this pathway will depend partly on cryptogam protective secondary chemistry, which may slow down the cryptogams’ own decomposition rates. Such chemistry may also inhibit decomposition of other species or influence decomposition indirectly by controlling plant communities, for instance lichen compounds inhibiting moss germination or vascular plant regeneration (Lawrey 1986).

Climate warming is anticipated to increase soil nutrient mineralization (Lükewille & Wright 1997; Rustad et al. 2001), thus providing nutrients in highly nutrient-limited environments such as subarctic ecosystems. As a combined effect of both increased temperature and increased mineralization, bigger and faster-growing vascular plant species might out-compete lichens and bryophytes (Cornelissen et al. 2001; Walker et al. 2006). Climate warming may also promote Sphagnum growth which will impact on plant community composition (Lang et al. 2009). These changes in turn might lead to production of plant litter of different quality and, consequently, different decomposition and mineralization rates (Hobbie 1996; Quested et al. 2003).

Given the paramount importance of bryophytes and lichens in general for the above ecosystems’ functions, and the central role their litter dynamics play in these systems, there is a striking lack of information about (i) overall litter decomposability of main cryptogam taxa compared with vascular plants and (ii) the magnitude and potential importance of interspecific variation in litter decomposability within main cryptogam taxa. This contrasts strongly with our knowledge of vascular plants where interspecific variation in traits has long been shown to be a major driver of decomposition rates both between and within higher taxa or functional types (Quested et al. 2003; Cornelissen et al. 2004). Yet, even relatively modest differences in cryptogam decomposability among species or species groups, as related to the species’ secondary chemistry, N2-fixing capacity and structure, may have great implications for regional-scale C sequestration at high latitudes. While poor litter quality has been reported repeatedly for Sphagnum (Hobbie 1996; Scheffer, van Logtestijn, & Verhoeven 2001), there is important interspecific variation in litter decomposability between different Sphagnum species (Clymo 1965; Rochefort, Vitt, & Bayley 1990; Johnson & Damman 1991) and probably between different bryophyte species in general (Hobbie 1996; Hobbie & Gough 2004). The distinction between non-Sphagnum mosses and liverworts may also be relevant, considering the extensive secondary chemistry of liverworts (Asakawa 2004) which might influence decomposition (Asakawa 1994). However, no comparative studies on a wide range of different bryophyte species are available. Similarly, little is known about interspecific variation in lichen decomposability (Wetmore 1982; Esseen & Renhorn 1998; Coxson & Curteanu 2002). Faster decomposition rates were suggested for N2-fixing lichens due to their high N content when compared with non-N2-fixing lichens without additional N input (Crittenden & Kershaw 1978). However, high N concentrations might also reflect high concentrations of defence compounds (Lawrey 1983) inhibiting decomposition. No study comparing these two groups has so far been conducted.

For vascular plants there has been much discussion about interaction effects of litter quality of different species and litter environment (climate, local soil environment) on decomposition rates, which can be important (Vivanco & Austin 2008) or relatively unimportant (Cornelissen et al. 1999) depending on the scope and scale of study. Indirect evidence for interaction effects is given in a study by Sjögersten et al. (2003) where soil organic matter, namely polysaccharide-derived O-alkyls and aromaticity, depended on both vegetation type and study region as well as on their interactions. Although existing studies suggest that habitat influences cryptogam decomposition (e.g. Coxson & Curteanu 2002), habitat–species interactions on cryptogam decomposition have been investigated in a few studies only (Belyea 1996; Turetsky et al. 2008). There are only few or no robust data to separate (biotic or abiotic) environmental from species-dependent litter quality effects on bryophyte and lichen decomposition rates, respectively, in the literature so far.

In order to underpin and predict broad-scale patterns in decomposability among different bryophytes, lichens and vascular plants, we also have to study the chemical traits that determine litter quality. For vascular plants, simultaneous multispecies screenings for litter decomposability in common garden experiments, particularly litter bed studies sensuCornelissen (1996), have revealed consistent variation in leaf litter decomposability as predicted from functional leaf (or leaf litter) traits (Cornwell et al. 2008). In particular, traits related to structural protection (lignin, cellulose and toughness), chemical defence (e.g. polyphenols, tannins), nutrition (N or phosphorus (P)) or pH have been associated with variation in litter decomposability (Palm & Rowland 1997; Cornelissen et al. 2006). In contrast to the large body of literature on this topic for vascular plants, it is not known which traits are the better predictors of lichen decomposition rates. The few studies available for bryophytes revealed N and the ratio of metabolic versus structural carbohydrates as positive mass loss predictors for Hylocomium splendens (Nakatsubo et al. 1997) and Sphagnum (Turetsky et al. 2008), respectively. Understanding and predicting litter decomposability of wide-ranging cryptogam and vascular species will help to predict C dynamics, ecosystem hydrology and feedback to climate in biomes where environmental change will induce both relative shifts from bryophytes or lichens to vascular plants or vice versa, or within cryptogam communities themselves.

Here we present the first-ever multispecies screening of litter decomposability of a wide range of 27 bryophyte and 17 lichen species in a 2-year decomposition experiment in contrasting outdoor litter beds in North Sweden. For comparison we included five vascular plant species known to broadly represent the range of vascular plant litter decomposability (Quested et al. 2003). We specifically tested the following hypotheses: (i) bryophyte and lichen litters are generally less decomposable than vascular plant litter while there is significant and substantial interspecific variation in litter decomposability among bryophyte as well as among lichen species; (ii) the pattern of mass loss across incubation environments is consistent among cryptogam species; and (iii) the variation in litter mass loss between and within main cryptogam taxa can be predicted from the chemistry of the species.

Materials and methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

Litter sampling

Bryophytes and lichens were sampled in the summer of 2004 mainly around Abisko, Sweden (68°21′ N, 18°49′ E) while few were collected on Andøya, Norway (69°07′ N, 15°52′ E) and in Kilpisjärvi, Finland (69°03′ N, 20°50′ E). The lichen Cladonia stellaris was sampled in the Altai Republic, South Siberia (51°04′ N, 85°45′ E) in 1999. All samples were air-dried and stored in paper bags until further preparation.

We focussed on abundant species which together were representative of the European subarctic region (see Appendix S1 in Supporting Information). Species nomenclature follows Hill et al. (2006) for all mosses except Sphagnum; Daniels & Eddy (1985) for Sphagnum species; Damsholt (2002) for liverworts; Santesson et al. (2004) for lichens; and Mossberg & Stenberg (2003) for vascular plants.

Vascular plant litter was included as a reference to previously conducted decomposition experiments. We included five subarctic species (two woody deciduous, one woody evergreen and two herbaceous species) which together broadly represent the range of vascular plant decomposabilities in a broad screening study (Quested et al. 2003; Cornelissen et al. 2004). This litter was sampled in the Abisko area in September 2004. One of the woody deciduous species, Betula pubescens ssp. czerepanovii, suffered from a severe attack by the autumn moth Epirrita autumnata. We therefore tried to avoid damaged leaves since the plants might have developed secondary protective defence compounds.

Preparation of the litter experiment

Three litter beds, poor and rich birch forest and a Sphagnum mire litter bed, were used for standardized litter incubations (Cornelissen 1996) in the experimental garden of the Abisko Scientific Station (annual mean: −0.9 °C, 301.2 mm, long-term average 1961–1990) in subarctic Sweden. Artificial litter bed environments compare to the natural environment as follows: mass loss in natural birch forest (litter bags placed on top) versus litter bed (placed within litter bed) was c. 45–50% (Sjögersten & Wookey 2004) versus 60% (own data) for Betula pubescens ssp. czerepanovii and c. 20% versus 34% for Betula nana (H. M. Quested & J. H. C. Cornelissen, unpublished data). The latter study also showed that litter bags of Empetrum nigrum ssp. hermaphroditum and Epilobium angustifolium, placed on top, lost 20–30% less mass compared to bags placed within the litter bed while the interspecific ranking stayed the same. This indicated that for vascular plants the position of the litter bags, likely to be due to differences in soil moisture, importantly influenced mass loss while differences between natural versus artificial environment might be less pronounced. Although incubated in different environments, studies in the local Stordalen peatland, with litter bags positioned just below the green moss layer, showed 1-year mass loss of 7.3%, 5.7% and 0% for Sphagnum riparium, Sphagnum balticum and Sphagnum fuscum, respectively (Sonesson 1972), comparable to 8.9%, 7.1% and 0.4% in the poor birch forest litter bed in our study. For cryptogams, decomposition rates should be broadly representative of the natural environment since they are in the same climate and in their natural position below the living bryophyte carpet.

Nutrient-poor and -rich birch forest litter beds were established in October 2004 on sand–gravel beds to allow the litter to settle down over winter. The main nutrient-poor birch forest litter bed, for comparing decomposabilities of the complete species set simultaneously and for doing the methodological checks (see below), contained a matrix of nutrient-poor litter from the locally predominant heath birch forest, mainly consisting of birch leaves (Betula pubescens ssp. czerepanovii) and some Vaccinium vitis-idaea and Vaccinium myrtillus leaves. This nutrient-poor litter bed contained 10 compartments of c. 0.65 m2 each to enable a factorial set-up of the experiment, with two harvests with each five replicates (see below for the bryophyte cover on top of the litter bags). The nutrient-rich birch forest litter bed contained birch leaves collected from local meadow birch forest and a large proportion of forbs (e.g. Trollius europaeus, Geum rivale and Filipendula ulmaria). For both litter bed types, we removed all living plant parts as well as dead roots, branches and stones and mixed the leaves thoroughly to ensure a homogeneous incubation environment. The third litter bed consisted of transplanted S. balticum mire cores in drainless plastic trays of 30 × 40 cm and 15 cm height, which had been installed in 2000 and maintained since the study made by Dorrepaal et al. (2005). The trays received distilled water during dry periods. Large openings at two sides of the trays ensured the same water table for all trays.

In early May 2005, litter bags of all 27 bryophytes, 17 lichens and five vascular plants, and the litter bags used for methodological tests, were put out in the nutrient-poor birch forest litter bed (957 litter bags, = 1–5) whereas in the nutrient-rich birch forest and Sphagnum mire litter bed, only the subset of each four bryophytes and lichens was used (40 litter bags per litter bed, = 5). The subset species occurred naturally at least in one of the chosen litter bed environments and were abundant in the area. In the birch forest litter beds, the litter bags were laid down flat, just without overlap, onto the leaf litter, avoiding the compartment borders (edge effects). The litter bags were remoistened with distilled water to ensure optimal litter moisture for soil invertebrate action and decomposition. We assumed that in nature cryptogam decomposition mainly took place under the living cryptogam cover where older bryophyte and lichen segments senesced while still attached to the upper live parts, and where cryptogams were often out-shaded by other cryptogams or vascular plants. Both litter beds were therefore covered with a layer of green bryophytes which was carefully pressed onto the litter bags to ensure good contact. These bryophytes were taken from the nutrient-poor and rich birch forest in large carpets to facilitate further growth of the moss layer. In the case of nutrient-poor litter we applied a c. 6-cm thick cover of H. splendens with intermingled Pleurozium schreberi and for the nutrient-rich litter bed a 2–3 cm thick cover of mainly Brachythecium salebrosum with some Brachythecium starkei and Rhodobryum roseum. A large-mesh chicken wire cover protected the litter beds from rodent damage. During extreme sunshine (3 days in July 2005) the beds were shaded with netting on a frame. In contrast to the leaf litter beds, the litter bags in the Sphagnum mires were inserted vertically into the peat down to a depth of c. 10 cm (lower edge).

Preparation of the litter

After careful rewetting with distilled water, without producing excess water to avoid leaching, the cryptogam samples were thoroughly cleaned from dirt and non-target cryptogam species using tweezers. In contrast to vascular plants, it was often difficult to determine whether parts of cryptogams were dead (litter) or alive. We checked for (lack of) activity of enzymes in the respiration process by incubating cryptogam material in a 1% solution of 2,3,5-triphenyltetrazolium chloride (ISTA 2009), but the subsequent colour changes in living parts were in most species weak (lichens) or inhibited by chlorophyll (bryophytes). Therefore, true litter was identified species by species. Bryophytes were visually divided into the living green parts and the recently senesced parts and older, already visibly decomposed parts, were discarded. For each species we defined specific vertical lengths as live material and recently died material (litter), respectively. Stems of bryophytes might still be alive and not die quickly once buried (Faubert & Rochefort 2002), while outer branches already started to decompose (e.g. H. splendens). Therefore, as the main reference litter for bryophytes, litter was frozen for 20 s in liquid N2 (−196 ºC) to kill any still-living tissues (or 30 s for the rather robust moss Polytrichum commune). Before freezing, the material was air-dried to avoid more damage than necessary to kill the tissue. For comparison, we also included a treatment with live material of all species, frozen in liquid N2.

For lichens it is often difficult to find sufficient true litter. Therefore, senescence was accelerated in the lab. Lichens are known to die under snow when hydrated and no light is available or when temperatures are warm during winter since their thalli respire at T = 0 °C but photosynthesis is negligible (Benedict 1990). Thus, we incubated at least partially living lichens at 100% moisture content and 20 °C in total darkness in an incubation chamber for 63 days from 14 February 2005. Lichens were frequently checked for mould to avoid unforeseen side effects. Most incubated lichens changed visibly, partly in colour and partly in their structure which was seemingly softer. The tetrazolium-test (see above) showed that the fungal part of the lichens was still active and lichen death was only complete in some parts while others were not affected at all. Therefore, after the senescence period, the incubated material was frozen in liquid N2 (see above) for 1 minute. Since hydrated antarctic lichens could survive 12 h freezing in liquid N2 (Kappen et al. 1996), we could not guarantee complete tissue death in all species. Still, the incubated-frozen material was used as the main treatment for the litter bed experiment. Since the incubations might have produced artefacts, we also used live and subsequently frozen material as an additional treatment. For vascular plant litter, easily detachable senesced leaves were hand-picked from living plants in autumn 2005 without any further treatment.

For each species, five replicates (in some species down to two, only one in Barbilophozia atlantica) which, depending on the species, weighed between 100 and 200 mg (down to 50 mg, especially in some liverworts), were pre-weighed and sealed into litter bags. The litter bags with sizes adjusted to match sample volume and ranging from 9 to 34 cm2 consisted of polyester with a mesh size of 200 μm. To calculate true dry weight via moisture content, subsamples from each litter sample were weighed, oven-dried at 70 ºC for 3 days and reweighed.

Harvest

Defined bryophyte litter and incubated lichens were harvested after 1 (May 2006) and 2 years (May 2007), live material only after the second year. Litter bags were cleaned from soil animals, dirt particles and non-target plant parts (mainly Equisetum arvense or roots grown into the bags).

Methodological tests

To check for possible methodological artefacts, we complemented the above standard treatments for bryophytes and lichens, respectively, with additional tests using standard litter (unless otherwise mentioned) of a subset of eight cryptogam species (four bryophytes and lichens each). The species selected to conduct the following tests were abundant in the area and easily collectible: (i) non-freezing: to test whether freezing affected decomposition of the standard litter material (tested on bryophyte litter, incubated lichens and live cryptogam material); (ii) mesh size of 0.9 mm: to test for the effects of excluding some bigger meso-detritivores with 200 μm (Swift, Heal, & Anderson 1979); (iii) true lichen litter: collected based on its structure and colour suggesting complete senescence without freezing treatment; (iv) older bryophyte litter (collected from below the upper fresh litter segment), partly decomposed and frozen, to test the influence of young versus older bryophyte litter on decomposition rate; (5) small litter fragments to test for any effects of greater surface area to volume ratio; (6) low initial litter weight to test for any effects when using 50 mg versus 100–200 mg samples of the same species.

Initial litter chemistry

The undecomposed samples used to determine initial moisture were ground using a ball mill (Mixer Mill MM 200, Retsch, Haan, Germany) before chemical analysis. After digestion of c. 50 mg in 1 mL of a 1 : 4 mixture of 37% (v/v) HCl and 65% (v/v) HNO3 in teflon bombs for 4 h at 140 ºC, 4 mL distilled water were added. P was measured colorimetrically (UV-1601PC; Shimadzu Corp., Kyoto, Japan) with the molybdenum blue method (Murphy & Riley 1962), and calcium (Ca) and magnesium (Mg) were measured with atomic absorption spectroscopy under addition of 1% LaNO3, and sodium (Na) and potassium (K) with atomic emission spectroscopy (both: 1100B Spectrometer, PerkinElmer Inc., Waltham, MA, USA). C and N concentrations were determined by dry combustion with a Carlo Erba NA1500 (Rodana, Italy) elemental analyser. Since the samples were cleaned meticulously, loss-on-ignition at 550 ºC for 4 h needed to be determined only for Racomitrium fasciculare and the lichen Solorina crocea, both of which were collected from environments where contamination by minerals was likely and which showed particularly low C/N values. Tissue pH measurement (WTW Inolab Level 2 pH meter, WTW Sentix Mic electrode; WTW, Weilheim, Germany) followed Cornelissen et al. (2006). Molecular structure of primary and secondary compounds of the ground samples and reference spectra (see below) was analysed spectroscopically by applying Fourier transform infrared using an attenuated total reflectance probe (FTIR-ATR) (NexusTM 670, ATR Cell DuraScope, Thermo Nicolet, Madison, WI, USA) with a resolution of 4 cm−1 and 32 scans. Organic compounds were identified based on Socrates (2001) aided by reference spectra, which included components that were presumably important in decomposition or were typically found in some taxa. Measurements included α-D-glucose monohydrate, D-fructose, mannitol, starch (potato-derived), L-cysteine, glycine, L-glutamic acid, chitin (crab-derived), cellulose, lignin and usnic acid. We used vascular plant-derived lignin and crab-derived chitin as an approximation of lignin-like components and chitin found in bryophytes and lichens, respectively. As peaks of the majority of plant compounds are overlapping, the resulting mass loss predictors can merely be indicative and need to be verified in further analysis.

Data analysis

Some litter bags of S. fuscum showed a slight gain in mass, mainly after 2 years of incubation, possibly due to accumulation of colloidal matter or absorption of solid organic matter (cf. Johnson & Damman 1991; Dorrepaal et al. 2005). Negative mass loss values of Sphagnum were set to zero before analysis. Data were checked for normality and mass loss percentages, unless otherwise stated, arcsine(√x/100)-transformed. Since anova was robust to heterogeneity of variance as long as sample size was nearly equal, we proceeded with analysis (spss 14.0 for Windows; SPSS Inc., Chicago, IL, USA) even when homoscedasticity assumptions were not fully met (Zar 1999).

Methodological checks on any effects of freezing, small fragments, low weight, older bryophyte litter or true lichen litter, mesh size and live material on mass loss were carried out by independent t-tests (n = 2–5), with ‘standard litter’ (see above) as the control treatment. Subsequently, data were Bonferroni-corrected across all cryptogams and per main cryptogam group (four bryophytes and lichens each). Effect size L was calculated as = ln(Xt/Xc) with X being the mean value of mass loss of treatment (t) and control groups (c). The confidence interval of L was calculated as λ ± Cα/2σ(L) with σ2(L) = (SDt)2/ntXt2+(SDc)2/ncXc2. Cα/2 is the two-tailed critical value of the standard normal distribution and n is the number of samples used. L was considered to be significant if its size was larger than the confidence limit (Gurevitch & Hedges 1999; Gurevitch, Curtis, & Jones 2001).

The effect of time and main taxon (main taxa: bryophytes, lichens, vascular plants) on mass loss was tested in a repeated-measurement anova (data ranked across both harvests, = 5–26). Mass losses of main taxa (= 5–26), cryptogam groups (within bryophytes: Sphagnum, non-Sphagnum moss, liverwort, within lichens: N2-fixing lichen, non-N2-fixing lichen; = 4–16) and Cladonia versus non-Cladonia species (including or excluding N2-fixing lichens; = 6–11) were subsequently compared in separate one-way anovas and Tukey tests for each harvest (data ranked, = 4–16). Likewise, untransformed N [%] was compared between N2-fixing lichens and non-N2-fixing lichens. Since Levene proved to be significant for N and the larger variation was found in the group with smaller replication (N2-fixing lichens), we equalized sample size randomly (= 5). The exponential mass loss constant k (Olson 1963) was calculated per block of the litter experiment.

Effect of time and species on mass loss were analysed in a repeated-measurement anova (= 5). Since Levene proved to be significant and sample size was unequal, species with replication below five were excluded. Values for litter bags damaged during harvesting (five species, one litter bag per species) were replaced by averaging the remaining samples.

The effect of group (or species) and litter bed type and their interactions on mass loss was tested in several two-way anovas. Species were first tested across all cryptogams and subsequently within the groups of lichens and mosses followed by a Tukey test (= 5). Untransformed N [%] of non-N2-fixing versus N2-fixing lichens were compared in a one-way anova (= 2).

Infrared spectra were used to calculate extinction E = ln(I0/I), followed by ground correction to correct for multiple scattering of light inside the probe. Ground correction was based on subtraction of the trajectory described by a disk rolling over the surface of the extinction spectrum (T. Klahn, unpublished method). Principal component analysis (PCA) was applied to show the scattering of cryptogam groups and vascular plants depending on their infrared spectra using The Unscrambler v9.8 (CAMO Software AS, Oslo, Norway). We used partial least squares regression (PLSR) to analyse the relationship between mass loss (ln-transformed; Sphagnum arcsine-square-root-transformed) versus macronutrients and pH, and mass loss (ln-transformed; Sphagnum and vascular plants arcsine-square-root-transformed) versus infrared spectra. pH and macronutrients were ln-transformed and subsequently 0–1 range-normalized (Min = 0; Max = 1) within each main taxon or cryptogam group before analysis. Only significant variables determined with Jack-knifing (full cross validation) were included in the final regression. Since no valid regression was found for liverworts (Table 4) and a PCA of infrared spectra revealed clustering of liverworts of the Scapaniaceae family, we analysed the liverwort group at family, order and (sub)class level following the classification of Goffinet & Shaw (2009).

Table 4.   Calibration and prediction of mass loss (ln-transformed; Sphagnum and vascular plants arscine-square-root-transformed) versus infrared spectra for main taxa and cryptogam groups (PLSR, = 5–54). PC, principal component; RMSE, root mean square error; Cal or Pred, calibration or prediction
Main taxaLichenBryophyteVascular plant
GroupAllN2-fixing lichenNon-N2-fixing lichenAll SphagnumNon-Sphagnum mossLiverwortAll
  1. *No significant variables.

n34102454832145
No. PCs423345–*2
R2Cal0.830.960.820.540.980.730.97
R2Pred0.740.910.750.430.920.60 0.70
RMSECal0.170.090.160.640.020.250.03
RMSEPred0.220.150.200.730.040.31 0.10
SlopeCal0.830.960.820.540.980.730.97
SlopePred0.750.970.760.470.930.68 1.16
InterceptCal0.680.140.731.330.010.820.03
InterceptPred1.020.110.971.530.020.98 −0.11

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

Methodological tests

One out of four lichen species showed significant differences in mass loss between low initial weight or true litter versus the ‘standard’ decomposition material (see Appendix S1). The Bonferroni-correction resulted in non-significance for the test of low weight for all cryptogams and at lichen group level, whereas true lichen litter remained significantly different from the standard at both levels of grouping. Testing older bryophyte litter versus standard litter revealed no significant effect. Freezing live material affected only one bryophyte species out of eight cryptogams. After Bonferroni-correction, this result remained significant when regarding the moss group alone, whereas it was non-significant across all cryptogams. Freezing of litter material, fragmentation and mesh size did not affect mass loss significantly compared with the litter standard. Methodological tests which were significant in the independent t-tests also showed significant effect sizes while effect size indicated significance for one additional species when testing older bryophyte litter. Comparing the mass loss of live versus litter material gave significant differences for 2 lichens out of 17, and 7 bryophytes out of 26, while effect size indicated a significant effect for four lichens and nine bryophytes. Differences between live versus litter material were still significant for one lichen and one liverwort after Bonferroni-correction across the whole group of cryptogams or within the groups of lichens and bryophytes separately. The emerging overall pattern is for cryptogam mass loss to be rather robust to the methodological differences. However, when comparing live versus litter material, some species (especially liverworts) seem to be more susceptible than others, and choice of litter material should be carefully considered.

Decomposability among and within main cryptogam taxa

Both time (F1 = 104.6, < 0.001) and main taxa (i.e. bryophytes, lichens, vascular plants; F2 = 38.6, < 0.001) influenced mass loss rates significantly whereas the interaction of these two factors showed no effect (F2 = 0.9, = 0.42). Both 1-year and 2-year mass loss were similar between lichens and vascular plants whereas bryophytes showed significantly lower values, as indicated also by the mean k values (Fig. 1).

image

Figure 1.  Comparison of mass loss (+SE) among the main taxa lichens, bryophytes and vascular plants, and the cryptogam groups Sphagnum, non-Sphagnum moss, liverwort and N2-fixing lichen, non-N2-fixing lichen, after 1 and 2 years of decomposition (separate one-way anovas for each harvest, data ranked, = 5–26). Different letters indicate significance at = 0.05 (Tukey). Note the negative contribution of Sphagnum after 2 years caused by mass gain of some Sphagnum species. Decay rate k± SE [yr−1]: kBryophyte = 0.11 ± 0.01, kLichen = 0.44 ± 0.01, kVascular plant = 0.56 ± 0.03, knon-Sphagnum moss = 0.11 ± 0.01, kLiverwort = 0.19 ± 0.01, kSphagnum = 0.03 ± 0.01, kN2-fixing lichen = 0.41 ± 0.02, knon-N2-fixing lichen = 0.45 ± 0.02.

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Within the bryophytes, Sphagnum, non-Sphagnum mosses and liverworts showed no significant differences in 1-year mass loss (F2 = 2.50, = 0.10) whereas 2-year mass loss revealed a significantly lower mass loss of Sphagnum (negative contributionyear2 caused by mass gain of some Sphagnum species overruling the minute losses of others), compared with either non-Sphagnum mosses or liverworts (F2 = 6.30; = 0.007). Within the lichens, 1-year (F1 = 0.27, = 0.61) and 2-year mass losses (F1 = 0.04, = 0.84) of N2-fixing lichens were not significantly different from non-N2-fixing lichens despite significant differences in initial N (F1 = 17.8, = 0.003). Mean 2-year mass loss, macronutrients and pH are shown in Table 1.

Table 1.   Mean (SE) mass loss [%], macronutrients [%] and pH for main taxa and cryptogam groups
Main taxaLichenBryophyteVascular plant
GroupAllN2-fixing lichenNon-N2-fixing lichenAll SphagnumNon-Sphagnum mossLiverwortAll
Mass loss57.05 (4.44)55.90 (8.62)57.47 (5.37)20.07 (2.51)5.80 (2.09)20.07 (2.12)28.21 (6.91)67.31 (6.68)
pH5.04 (0.09)5.44 (0.23)4.90 (0.06)5.34 (0.07)5.27 (0.19)5.36 (0.10)5.30 (0.13)4.72 (0.31)
Na0.05 (0.01)0.03 (0.01)0.05 (0.02)0.06 (0.01)0.03 (0.00)0.05 (0.02)0.09 (0.03)0.02 (0.01)
K0.26 (0.07)0.60 (0.21)0.14 (0.02)0.20 (0.03)0.26 (0.04)0.20 (0.04)0.18 (0.04)0.32 (0.10)
Ca0.15 (0.06)0.27 (0.19)0.11 (0.04)0.52 (0.09)0.42 (0.08)0.52 (0.15)0.55 (0.11)1.23 (0.55)
Mg0.07 (0.01)0.11 (0.02)0.05 (0.01)0.15 (0.05)0.21 (0.03)0.12 (0.05)0.19 (0.04)0.39 (0.10)
N0.95 (0.20)2.19 (0.37)0.51 (0.06)0.71 (0.04)0.75 (0.03)0.66 (0.05)0.78 (0.11)0.64 (0.12)
C44.90 (0.30)46.35 (0.42)44.38 (0.27)45.35 (0.38)45.49 (0.38)46.08 (0.40)43.61 (0.90)48.46 (2.14)
P0.10 (0.02)0.17 (0.08)0.07 (0.01)0.05 (0.00)0.03 (0.01)0.05 (0.01)0.04 (0.01)0.10 (0.05)
C/N81.99 (11.03)24.59 (5.15)102.49 (10.14)70.65 (4.88)60.63 (2.10)76.28 (6.74)63.50 (10.32)92.34 (24.24)
N/P15.26 (4.62)31.62 (16.19)9.42 (1.18)21.71 (3.36)36.49 (12.22)15.28 (2.13)27.95 (8.81)12.88 (4.47)
C/P937.02 (175.16)883.84 (488.89)956.02 (176.86)1491.90 (261.98)2247.10 (771.83)1303.89 (365.60)1490.10 (381.26)1546.89 (942.28)

The differences among species were highly significant within each of the main taxa bryophytes, lichens and vascular plants as well as for the groups Sphagnum, non-Sphagnum moss, liverwort, N2-fixing and non-N2-fixing lichen, with significant time × species interactions for bryophytes, N2-fixing lichens and liverworts. As an exception, time itself was not a significant determinant of Sphagnum mass loss (Table 2).

Table 2.   Effect of time and species on mass loss within main taxa and cryptogam groups (repeated-measurement anova, data arscine-square-root-transformed, = 5)
Main taxaGroupSourced.f.FP
BryophyteAllTime1177.3<0.001
Species2031.6<0.001
Time × species204.8<0.001
SphagnumTime10.90.36
Species359.2<0.001
Time × species32.00.16
Non-Sphagnum mossTime1165.2<0.001
Species1416.0<0.001
Time × species141.60.10
LiverwortTime1103.7<0.001
Species551.2<0.001
Time × species55.40.005
LichenAllTime1379.8<0.001
Species1656.7<0.001
Time × species161.60.11
N2-fixing lichenTime1175.9<0.001
Species463.4<0.001
Time × species43.30.032
Non-N2-fixing lichenTime1254.5<0.001
Species1159.0<0.001
Time × species110.90.56
Vascular plantAllTime162.1<0.001
Species440.1<0.001
Time × species42.20.11

Within the bryophytes, Sphagnum species showed the lowest decomposition rates, with no species exceeding 10% (Fig. 2). Non-Sphagnum mosses ranged from 0.2% to 36% which was lower than mass losses for most of the lichens and lower than for any of the vascular plants. Liverworts showed a wide range in decomposition rates from 9% to 60%, the high value for Lophozia lycopodioides being comparable with mass loss of vascular plants. Low lichen decomposition rates of 20–40% were mainly found in the Cladoniaceae, even though up to 50% mass loss was measured in this family. Mass loss of Cladonia species was significantly lower compared with non-Cladonia species, both when excluding (F1 = 22.53; = 0.001) or including N2-fixing lichens (F1 = 8.23; = 0.012). With about 90% mass loss, Alectoria ochroleuca even exceeded the mass loss of highly decomposable vascular plants such as the forb Cornus suecica. Both N2-fixing and non-N2-fixing lichens showed a similar range in decomposition, the highest values reached by the latter group.

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Figure 2.  Two-year mass loss (+SE) of bryophytes (Sphagnum, non-Sphagnum moss, liverwort), lichens (non-N2-fixing lichen, N2-fixing lichen) and vascular plants in the nutrient-poor birch forest litter bed (= 1–5).

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The influence of litter bed type on decomposition

At main taxon level, litter bed type showed a trend (F2 = 3.06, = 0.051) of influencing mass loss, whereas main taxa (F1 = 73.93, < 0.001) and their interaction (F2 = 8.69, < 0.001) were significant determinants of mass loss. At species level, species and litter bed type and their interactions significantly influenced mass loss across all cryptogams and within the non-Sphagnum mosses and lichens, respectively (Table 3).

Table 3.   Effect of species and litter bed type on mass loss across all cryptogams and within the cryptogam groups non-Sphagnum mosses and lichens after 2 years of incubation (separate two-way anovas, data arcsine-square-root transformed, = 5)
 Sourced.f.FP
Across main taxa
 All CryptogamsSpecies7128.14<0.001
Litter bed217.15<0.001
Species × litter bed1411.40<0.001
Within main taxa
 Non-Sphagnum mossesSpecies391.40<0.001
Litter bed237.73<0.001
Species × litter bed66.37<0.001
 LichensSpecies370.94<0.001
Litter bed228.93<0.001
Species × litter bed64.160.002

Of the eight species chosen for this part of the study, lichen and moss species reacted differently to the varying litter bed environments (Fig. 3). The non-N2-fixing Cladonia species showed the highest mass loss when decomposing in nutrient-poor birch forest litter relative to decomposition in nutrient-rich birch forest litter and Sphagnum mire. Cladonia had significantly lower N (F1 = 87.0; = 0.011) compared with the N2-fixing lichens, Peltigera aphthosa and Nephroma arcticum, which in turn were unaffected by incubation environment showing equally high decomposition rates. Mosses, except Racomitrium lanuginosum with overall low decomposition rates independent of the litter bed environment, showed an increase in mass loss when decomposing in Sphagnum peat. The nutrient-rich litter bed negatively affected decomposition rates of Hylocomium splendens and Polytrichum commune. Within each incubation environment, linear regression revealed that moss mass loss was significantly related to cryptogam tissue N (R2poor birch forest = 0.92, = 0.039; R2rich birch forest = 0.92, = 0.043; R2mire = 0.92, = 0.041).

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Figure 3.  Effects of nutrient-poor and nutrient-rich birch forest and Sphagnum mire litter bed on mass loss (+SE) of four lichen (left side) and four non-Sphagnum moss species (right side) after 2 years of incubation [one-way anova, data arcsine-square-root transformed, different letters indicate significance at P < 0.05 (Tukey), = 5].

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The relation of initial litter chemistry and decomposability

Differentiation of cryptogams and vascular plants based on infrared spectra

Principal component analysis showed that infrared spectra, despite a certain overlap, clearly differentiated among lichens, liverworts, non-Sphagnum mosses and vascular plants, whereas Sphagnum species were located within the group of non-Sphagnum mosses. Non-N2-fixing and N2-fixing lichens were not clearly separated in the PCA (Fig. 4) but all Cladonia species were clustered at values below −0.04 along axis 1.

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Figure 4.  Differentiation of cryptogam groups and vascular plants by infrared spectra (data untransformed, principal components analysis, = 118).

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Infrared spectra in relation to mass loss

Mass loss in relation to infrared spectra showed higher R2Pred values (0.74, 0.43 and 0.70) as opposed to 0.07, 0.12 and 0.46 when using macronutrients and pH (Tables 4 and 5) for lichens, bryophytes and vascular plants respectively. The error of the model (RMSEPred) increased from 0.22, 0.73 and 0.10 to 0.40, 0.90 and 0.18 for the same groups (note the deviating transformations for vascular plants). Further division into N2-fixing lichens, non-N2-fixing lichens, Sphagnum and non-Sphagnum mosses and liverworts enhanced the correlation for all groups except liverworts where no significant variables were found. Sphagnum showed a high R2Pred. of 0.92 and a very small error of 0.04 (Table 4). Analysing the liverworts at increasing taxonomical levels showed a decrease of R2Pred. from family (Scapaniaceae) to order (0.55 to 0.41), followed by a small increase of RMSEPred (0.42 to 0.44). At subclass and class level, R2Pred. increased from 0.61 to 0.83 and RMSEPred decreased from 0.32 to 0.27. The number of principal components increased from family/order to (sub)class (details see Appendix S2).

Table 5.   Calibration, prediction and regression coefficients of mass loss (ln-transformed; Sphagnum arscine-square-root-transformed) versus macronutrients [%] and pH (PLSR, chemical variables within main taxa or cryptogam group ln-range-normalized, = 5–54). Only significant variables are shown. PC, principal component; RMSE, root mean square error; Cal or Pred, calibration or prediction
Main taxaLichenBryophyteVascular plant
GroupAllN2-fixing lichenNon-N2-fixing lichenAllSphagnumNon-Sphagnum mossLiverwortAll
  1. *No significant variables.

  2. Y(2a) = k0 + k1x1 + k2x2 + … +knxn; x, significant chemical variables (pH to Mg).

n34102454832145
No. PCs111121–*1
R2Cal0.110.590.460.170.930.410.58
R2Pred0.070.430.370.120.870.36 0.46
RMSECal0.380.290.280.860.030.360.13
RMSEPred0.400.380.320.900.050.39 0.18
SlopeCal0.110.590.460.170.930.410.58
SlopePred0.060.370.390.130.820.37 0.41
InterceptCal3.581.642.202.390.021.741.75
InterceptPred3.772.572.482.500.051.86 2.45
Regression coefficients k
 k03.833.243.481.980.092.043.95
 pH0.16 0.30    
 N0.201.060.30 0.060.42 
 C   −0.24   
 P   1.68 0.490.44
 K0.20 0.33 0.300.32 
 Ca  0.29 −0.04  
 Mg     0.31 

Infrared spectra of structural (cellulose, chitin) and metabolic (sugars, starch) carbohydrates, amino acids (proteins/peptides c. 6.04, 10.00–10.58, 11.11–12.50 and c. 13.79/e.g. 7.69–7.87 μm) and aromatic compounds (c. 6.00, 7.75–11.11 and 11.11–15.27 μm; e.g. usnic acid, lignin) are shown in Fig. 5 (note: absorption bands of compounds are overlapping). Lipids (not shown) absorb at numerous bands (e.g. 3.51, 5.78, 9.22, 10.31 and 13.99 μm). Considering solely larger regression coefficients, mass loss of N2-fixing lichens was positively related to amino acids (proteins, peptides), lipids and structural (c. 3.5, 7.74 and 10.54 μm) and metabolic carbohydrates (c. 3.5, 7.74 μm). Mass loss of non-N2-fixing lichens related positively to structural and metabolic carbohydrates, amino acids and aromatic compounds (9.26, 9.82 μm) while strongly negatively relating to the latter two components (14.01–14.99 μm). Mass loss of non-Sphagnum mosses related positively to proteins (amino acids), lipids and aromatic compounds (13.68–14.20 μm) and negatively to carbohydrates (metabolic and structural), amino acids, lipids and aromatic compounds (9.19–9.45 μm). Sphagnum mass loss was positively related to proteins (amino acids) and metabolic and structural carbohydrates (10.65–11.63 μm) and negatively to aromatic compounds, proteins (amino acids) and metabolic and structural carbohydrates (6.39, 9.67 and 11.81 μm). The liverwort family Scapaniaceae related both positively (12.41–12.71 μm) and negatively (6.40 μm) to proteins (amino acids) and aromatic compounds. Vascular plants were positively related to metabolic and structural carbohydrates, lipids and amino acids (3.43, 3.51, 8.66 and 10.33 μm) and negatively to carbohydrates (structural and metabolic), amino acids (proteins) and aromatic compounds (9.77, 12.80–13.65 μm).

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Figure 5.  Cryptogam, vascular plant and reference spectra and regression coefficients (significant coefficients only) of non-N2-fixing lichens (inline image) and N2-fixing lichens (inline image) (left side), and non-Sphagnum mosses (inline image), Sphagnum (inline image), Scapaniaceae (liverworts, inline image) and vascular plants (inline image) (right side). Only larger regression coeffients are marked.

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Macronutrients and pH in relation to mass loss

Sodium was not a significant predictor of mass loss and excluded in all regressions (Table 5). Overall regressions for lichens and bryophytes showed low R2Pred values. Lichens were significantly positively related to pH, N and K, and bryophytes positively to P and negatively to C. Subsequent analyses of N2-fixing lichens, non-N2-fixing lichens, Sphagnum and non-Sphagnum mosses and liverworts resulted in enhanced correlations, steeper slopes and smaller model errors (RMSEPred.; except liverworts), with Sphagnum showing an exceptionally high R2Pred of 0.87 and a small error (RMSEPred.) of 0.05. N was significantly and positively related to mass loss in N2-fixing lichens, while for non-N2-fixing lichens K, pH, N and Ca showed a positive relation to mass loss of about the same magnitude. Sphagnum mass loss related strongly positively to K, to a lesser extent to N, and negatively to Ca. Mass loss of non-Sphagnum mosses related positively to P and N, and to a lesser extent to K and Mg. For liverworts no significant variables could be determined. Even though the PCA on elemental composition did not reveal any clustering, we followed the taxonomical classification as suggested for the wavelength data. N and Na were significant determinants of mass loss at family (regression coefficients: k0 = 0.35, kN = 0.45, kNa = 0.35) and N at order level (k0 = 0.52, kN = 0.42), while at subclass level no such relationship was found. From family to order, R2Pred decreased from 0.75 to 0.47, while RMSEPred increased from 0.13 to 0.17 (details see Appendix S2).

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

Variation in decomposability among and within main cryptogam taxa

Our study was the first to reveal consistent patterns of variation in litter decomposability of a wide range of non-vascular cryptogams when incubated in a standard environment. While there were several significant interactions between litter incubation environment or incubation period and species group identity on mass loss rates, the general pattern was that of a strong influence of cryptogam taxonomic identity on litter mass loss.

Both rapid and slow lichen mass loss for non-Cladonia (Wetmore 1982) and Cladonia (Moore 1984), respectively, have been reported in comparison to vascular plants, emphasizing the importance of taxonomic identity. Despite expected antibacterial activity (e.g. Vartia 1973), lichen decomposition rates in our study were generally comparable with those of vascular plants. Stark & Hyvärinen (2003) suggested that the microbial community growing underneath lichens is well adapted to the lichen secondary metabolites, utilizing them as a C source, which might also explain the high turnover rates in our study. Even certain Cladoniaceae, a less degradable group compared with non-Cladonia lichens, reached mass losses of up to 50% after 2 years of incubation. Crittenden & Kershaw (1978) proposed that N2-fixing lichens exhibited higher N contents and that decomposition rates of N2-fixers should therefore be greater than those of non-N2-fixing lichens. In our study, N2-fixing and non-N2-fixing lichens displayed similar high decomposition rates in spite of N in N2-fixing lichens indeed being significantly higher than in non-N2-fixing lichens. N2-fixing lichens, as opposed to non-N2-fixing lichens, decomposed equally well in contrasting litter beds, suggesting that at higher N concentrations the microbial community is not limited by substrate N leading to fast decomposition decoupled from substrate N (Coulson & Butterfield 1978).

Bryophytes comprising Sphagnum, non-Sphagnum mosses and liverworts showed consistently low decomposability compared with vascular plants. This has been shown earlier for Sphagnum and single bryophyte species (Hobbie 1996; Aerts, Verhoeven, & Whigham 1999; Liu, Fox, & Xu 2000) but ours is the first explicit and comprehensive test of the general low degradability of bryophyte litter. Within the Polytrichaceae, mass loss ranged from 10% to 35%, emphasizing that even closely related species can diverge strongly in decomposability. The overall lower decomposition rates found for Sphagnum have been attributed to structural, lignin-like and soluble phenolic compounds (Verhoeven & Liefveld 1997), both of which are also found in non-Sphagnum mosses (Erickson & Miksche 1974; Zinsmeister & Mues 1990; Ligrone et al. 2008), and decomposition-inhibiting bacteria associated with Sphagnum (Opelt, Berg, & Berg 2007). While most liverworts decomposed slowly too, as related presumably to high contents of secondary metabolites (Asakawa 1994), a few species reached decomposition rates higher than those of any mosses in our study. Despite their suggested antibacterial activity (Zhu et al. 2006), oil bodies, known to contain large amounts of terpenoids and aromatic compounds (Asakawa 2004), do not seem powerful enough to inhibit decomposition. This may be due to volatilization of most oil body content within days or weeks after collection. The interaction effect of time and species among liverworts implies a wide heterogeneity of species responses to decomposition over time, possibly due to subgroups within the liverwort group as indicated by chemosystematic differences between, for instance, the Jungermannidae (e.g. Lophozia lycopodioides) and Marchantiidae (Marchantia alpestris) (Asakawa 2004). While we were able to reveal the importance of species identity on litter mass loss, little is known about the intraspecific variability in mass loss of species growing at contrasting sites or in different geographic regions, with possible feedbacks on chemical composition (cf. Bakken 1995) and, consequently, litter decomposability. Furthermore, little is known about mass loss rates of cryptogam species on longer time scales which could deviate considerably from our shorter-term results.

Species-environment interactions on mass loss

Mass loss across and within groups was significantly affected by species (or group) identity, litter bed environment (at species level) and their interactions. This contrasts with earlier studies investigating predominantly Sphagnum where no significant interaction was found (Belyea 1996; Turetsky et al. 2008). The deviating results may be due to the strongly contrasting environments (birch forest vs. mire) used in our study or to the species chosen. Decomposition rates for Cladonia species were highest in the nutrient-poor birch forest litter environment where the species naturally occurred and microbial communities might therefore be well adapted (Stark & Hyvärinen 2003). In the nutrient-rich birch forest environment where Cladonia species are naturally absent in the Abisko region, accordingly lower mass loss rates were found. Decomposition rates of Cladonia species were also lower in the peatland environment. Correspondingly, Tolonen (1971) found subfossil remnants of lichens in peat cores. Wetmore (1982) suggested thallus structure and firmness of the fungal cortex as determinants for lichen decomposition, while usnic acid content, known for its antibiotic effects (Cocchietto et al. 2002), did not determine mass loss of the species in his study. Fumarprotocetraric acid, present in Cladonia rangiferina and C. arbuscula, is known to be more toxic at lower pH values (Gardner & Mueller 1981), and possibly also negatively affects decomposition rates. Mass loss rates of Peltigera aphthosa and Nephroma arcticum, both free of fumarprotocetraric acid and with significantly greater N content compared with the Cladoniaceae, were equally high under all environmental conditions, possibly due to local microbial increases which is due to high N content (Coulson & Butterfield 1978). Crittenden & Kershaw (1978) proposed leaching and structural damage as possible pathways for N which, in lichens, consisted to a large degree of amino acid N (Solberg 1970). In N-limited environments as common in the (High) Arctic (Shaver & Chapin 1995), amino acids are readily taken up by mosses (Krab et al. 2008), lichens (Dahlman et al. 2004) and vascular plants (Chapin, Moilanen, & Kielland 1993). Regarding non-Sphagnum mosses, the regression of N versus mass loss proved to be significant, with Racomitrium lanuginosum exhibiting extremely low N values (see also Pakarinen & Vitt 1974). In contrast, Turetsky et al. (2008) reported k values of both Sphagnum and non-Sphagnum mosses to be positively related to the ratio of metabolic to structural carbohydrates, but not to N. As a peatland hummock-builder, R. lanuginosum displayed equally low decomposition rates independent of site which might not only be due to low N values, but also to high values of structural carbohydrates as found in hummock-building Sphagnum species (Turetsky et al. 2008). In contrast, most of the other non-Sphagnum mosses showed a tendency towards increased mass loss rates in the peatland environment. Leaching in the wet mire environment could be a minor cause for enhanced mass loss rates compared with the birch forest but the low soluble content in mosses (Pakarinen & Vitt 1974; Turetsky 2003) cannot account for more than 1–10% of total mass loss. Maybe more importantly, low moisture could have inhibited moss decomposition (cf. Flanagan & Veum 1974; Meentemeyer 1978), especially in the nutrient-rich birch forest litter bed where bryophyte cover was thin and might have dried out during warm periods. Furthermore, the habitat-specific soil fauna can be expected to influence decomposition rates to various extents in the contrasting habitats of peat and mineral sites (Coulson & Butterfield 1978). Except for N2-fixing lichens and R. lanuginosum, where mass loss did not vary across habitats, environment influenced decomposition rates of non-N2-fixing lichens and bryophytes as shown in previous investigations (Coulson & Butterfield 1978; Wetmore 1982; Belyea 1996; Coxson & Curteanu 2002). This complicates predictions of changing decomposition patterns based on species shifts at the landscape level. Future studies should include bacterial, fungal and soil fauna communities of the various ecosystems and investigate a wider range of cryptogam species, including both Sphagnum species and liverworts, in order to unravel the underlying mechanisms of species–environment interactions on cryptogam mass loss.

The relation of initial litter chemistry and decomposability

Principal component analysis based on infrared spectra showed a clear separation of lichens, liverworts, mosses (including Sphagnum) and vascular plants. Relations of overall lichen or bryophyte mass loss to macronutrients and pH were weak while at cryptogam group level, R2 improved considerably. The same pattern, although less pronounced, was found for relations of mass loss to infrared spectra. In both analyses, R2 for liverworts decreased from family to order while R2 for the genus Sphagnum was high. Even with increasing numbers of principal components, regressions were only valid up to class level (Jungermanniopsida) suggesting that Marchantiopsida (Marchantia alpestris) showed a different decomposition pattern. Taxonomic identity might be important when predicting mass loss, possibly due to differences in carbohydrate partitioning (structural vs. metabolic), as has been suggested for true mosses versus Sphagnum species (Turetsky et al. 2008). Differences in chemical components, their allocation and respective mass loss might also be related to habitat, as hydric species with a constant nutrient input have been found to show higher protein levels, both higher or lower metabolic carbohydrate content and within the genus Sphagnum, higher allocation to photosynthetic tissue compared with species from drier habitats (Pakarinen & Vitt 1974; Rice 1995; Davey 1999). Furthermore, availability and type of conductive tissue (Hébant 1977) might influence mass loss, enabling redistribution of easily decomposable components (e.g. Sveinbjörnsson & Oechel 1991; Hakala & Sewón 1992). The lower R2 for non-Sphagnum mosses suggests that indeed further division of this large and heterogeneous group is likely to improve mass loss predictions.

Due to considerable overlap of peaks characterizing plant compounds, only indications of possible cryptogam mass loss predictors can be given. Next steps should include analysis of bryophyte and lichen components with conventional laboratory assays, thereby linking wavelengths to chemical compounds. At this stage, we considered compounds as positive or negative mass loss predictors in analogy with predictors known for vascular plants (Palm & Rowland 1997). Metabolic carbohydrates, lipids and proteins as easily decomposable components should be positively related to mass loss, and structural and non-soluble aromatic components negatively. Soluble phenolics, however, may either serve as energy source or inhibit decomposition (Palm & Rowland 1997). N2-fixing lichens showed mainly positive predictors of mass loss, i.e. metabolic carbohydrates, lipids and amino acids (proteins, peptides). The latter were reflected in the significant relation of mass loss to N, emphasizing the importance of N-limitation in the (sub) Arctic (Shaver & Chapin 1995). In contrast, non-N2-fixing lichens revealed also negative predictors, i.e. aromatic compounds (see regression coefficients between 14.01 and 14.99 μm; but note the positive relation at 9.26, 9.82 μm). Mass loss was further positively determined by N, Ca, K and pH. While the influence of other components (e.g. lichen acids) on pH cannot be excluded, it correlated well with the sum of Ca, Mg and K for vascular plants (Cornelissen et al. 2006) and lichens (< 0.001, R2 = 0.53; see Appendix S3). Ca, often present as Ca oxalate crystals (Brown 1987), might positively influence decomposition via the dietary needs of the decomposer community (Swift, Heal, & Anderson 1979; Nicolai 1988) or provide an indirect positive link to decomposition since both Ca and K were significantly correlated to N (R2Ca = 0.54, < 0.001, excluding Umbilicaria; R2K =0.61, < 0.001). Similar interconnections have been found for vascular plants (Swift, Heal, & Anderson 1979).

Since bryophytes generally had low decomposition rates, the chemistry underlying low degradability is of particular interest. Mass losses among Sphagnum species as well as among non-Sphagnum mosses were negatively related to structural carbohydrates (cf. Turetsky et al. 2008) and aromatic compounds, the latter indicating polyphenols substituting lignin in bryophytes (Erickson & Miksche 1974). The positive relation of K to mass loss among Sphagnum and non-Sphagnum mosses may reflect the mainly intracellular location of K in green shoots where N, P and metabolic activity are highest (Pakarinen & Vitt 1974; Brown & Wells 1990). Indeed, proteins (N) and lipids (P), and proteins and metabolic carbohydrates were related to mass loss of non-Sphagnum and Sphagnum mosses, respectively. Extracellularly located Ca is known to increase in older, less metabolically active tissue (Vitt & Pakarinen 1987) explaining indirectly its negative impact on Sphagnum decomposition. This Ca accumulation is mainly attributed to death of tissue providing additional exchange sites (Brown & Wells 1990), which are especially numerous in Sphagnum with its high cation exchange capacities (Clymo 1963). Mg, a positive predictor of mass loss for non-Sphagnum mosses, might be indirectly linked to decomposition, being the cofactor of the N-rich photosynthetic enzyme Rubisco.

For the liverwort family Scapaniaceae, mass loss was positively related to (N in) proteins, while aromatic compounds (as in non-Sphagnum mosses) related both positively and negatively. Structural polyphenolics in liverworts (Erickson & Miksche 1974) are likely to negatively influence decomposition while soluble aromatic liverwort compounds, known to be biologically active (Asakawa 1994), may be antimicrobial in soil or serve as energy source, as suggested for lichens (Stark & Hyvärinen 2003). The positive relation between Na and mass loss might be linked to Na requirements of the decomposer community (Swift, Heal, & Anderson 1979). Na availability in liverwort tissue may reflect environmental conditions or as fungi show high Na levels (Swift, Heal, & Anderson 1979), relates to basidiomycetous infections, repeatedly found in jungermannialean liverworts (Duckett, Russell, & Ligrone 2006).

The infrared measure was not only faster and easier to conduct, but smaller sample amounts were needed which is of major importance when processing minute samples of liverworts. However, measurements of macronutrients and pH might be easier to achieve and could be used to predict mass loss of cryptogam groups. If FTIR-ATR is not available, including analytical determinations of structural and metabolic carbohydrates, proteins and aromatic compounds (both soluble phenolics and lignin-like compounds) should improve predictions. To investigate if and how initial chemistry of the generally less degradable bryophytes relates to final-stage decomposition, screening multiple species over longer time periods will be necessary.

Conclusions

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

Understanding and predicting mass loss rates of cryptogams is crucial in cool and cold environments where C stocks in litter are enormous and profound climate change is expected to alter vegetation compositions, their related litter compositions and ultimately the C balance. Our study has shown that both higher taxon and species identity are important determinants of mass loss rates over time, with bryophytes being consistently less degradable across taxa. As the pattern of decomposition across litter bed types was not consistent among cryptogam species, future studies should further investigate the interactions of species identity and environment to fully understand and predict mass loss rates for different ecosystems. Interspecific variation in cryptogam and vascular plant litter mass loss was clearly related to initial litter chemistry. The consistent differences between species-based litter decomposabilities of cryptogam and vascular plant taxa representative of cold northern ecosystems will be most useful in formulating and testing predictions about the consequences of climate-induced shifts in vegetation composition for C cycling.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

The authors would like to acknowledge the Abisko Scientific Research Station which financially supported this work and provided facilities, and Anne Temesváry and Anders Eriksson who helped to maintain the experiment. Many thanks to Matthias Ahrens who kindly verified bryophyte species identification. The authors are grateful for the generous support by the Fraunhofer Institute for Chemical Technology (ICT) for facilitating the FTIR-ATR measurements. Many thanks to Norbert Leist of the Staatliche Landwirtschaftliche Untersuchungs- und Forschungsanstalt Augustenberg (LUFA Augustenberg) for advice on the viability test. The authors like to acknowledge A. Hölzer for technical support and the Staatliches Museum für Naturkunde Karlsruhe for generous provision of work space to S.L. Many thanks to the FAZIT-STIFTUNG for financial support enabling completion of this work. This study was financed by grant ALW-852.00.070 of the Netherlands Organisation for Scientific Research (NWO).

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  4. Materials and methods
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  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information
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Supporting Information

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conclusions
  8. Acknowledgements
  9. References
  10. Supporting Information

Appendix S1. Methodological tests.

Appendix S2. Calibration, prediction and regression coefficients of liverwort mass loss vs. infrared spectra, and macronutrients and pH, at family, order and (sub-)class level.

Appendix S3. Relation between pH and the sum of Ca, Mg and K for non-N2-fixing and N2-fixing lichens.

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