Factors shaping submerged bryophyte communities: A conceptual model for small mountain streams in Germany

Limnologica 42 (2012) 242–250

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Factors shaping submerged bryophyte communities: A conceptual model for small mountain streams in Germany Horst Tremp a,∗ , Dorothea Kampmann b , Ralf Schulz a a b

Institute for Environmental Sciences, University of Koblenz-Landau, Campus Landau, Fortstrasse 7, D-76829 Landau/Pfalz, Germany Department of Physical Geography, Goethe University, Altenhöferallee 1, D-60438 Frankfurt, Main, Germany

a r t i c l e

i n f o

Article history: Received 26 July 2011 Received in revised form 8 January 2012 Accepted 9 January 2012 Keywords: Aquatic bryophytes Distribution patterns Species response curves Water Framework Directive

a b s t r a c t Several models explaining species composition of aquatic bryophytes are available for specific regions. However, a more general, conceptual model applicable to a broader range of regions is lacking. We present a conceptual model ranking environmental factors determining submerged bryophyte communities in small mountain streams. It was tested on a dataset of 54 stream sections after removing the effect of stream size and altitude. Species responses were modeled with pH as predictor variable based on 97 stream sites covering six mountain regions all over Germany. Multiple regressions revealed the importance of primary growth factors (light, Ep(CO2 )) and substrate for the total submerged bryophyte coverage. The known distinction of hard- and softwater bryoflora was clearly supported. The floristic composition of headwaters was predominantly determined by the bicarbonate/ionic strength complex. Species response to pH values supported this result and thus our conceptual model. The primary growth resources light, Ep(CO2 ) and availability of coarse streambed material explained one third (Radjusted 2 = 0.34) of total submerged bryophyte cover. Disturbances, predominantly spates, reduce biomass but do not affect the basic floristic structure. In conclusion, conceptual models and monitoring methods focusing on aquatic bryophytes need to clearly distinguish “aquatic” from “submersed by chance”. All “aquatic bryophytes” found in Germany can also occur at least temporarily at non-submerged sites. Therefore, a distinction between primary growth factors and additional resources is recommended to disentangle factors determining aquatic bryophyte communities. © 2012 Elsevier GmbH. All rights reserved.

Introduction Ecological information for the small group of submerged bryophytes and their role in stream ecosystems is sparse. Reasons may be their low dominance and spatially heterogeneous arrangement in many stream types (Stream Bryophyte Group, 1999) or their reputation as an exclusive group studied only by specialists. In zoological investigations submerged bryophytes are commonly regarded as a substrate (phytal) because they provide a unique habitat for macroinvertebrates (Butcher, 1933; Suren, 1993; Riis and Biggs, 2003). They also offer macroinvertebrates shelter against physically and chemically related impacts (e.g. Glime, 1994; Parker et al., 2007). Aquatic bryophytes have rarely been used for classification purposes (e.g. stream typology) or as bioindicator (Zechmeister et al., 2003), as there are much fewer experts

∗ Corresponding author. Tel.: +49 7032 893717. E-mail address: [email protected] (H. Tremp). 0075-9511/$ – see front matter © 2012 Elsevier GmbH. All rights reserved. doi:10.1016/j.limno.2012.01.003

for bryophytes than for macroinvertebrates, amphibians or algae (Fritz et al., 2009). In contrast to vascular plants, the high potential for vegetative and generative (spores) propagation of submerged bryophytes leads to a high similarity of its flora in the holarctic, thus Central Europe and Scandinavia share many species with Northern America and Canada (Frahm and Vitt, 1993; Dierßen, 2001). Terms like water mosses, stream bryophytes or aquatic bryophytes are difficult to define in a rigorous way biologically. All three terms assume that the aquatic medium is either the only or the most favored site where these species show maximum growth and complete their life cycle including spore-germination, protonema formation, gametophyte- and sporophyte induction and growth as well as spore dispersal (Tremp, 1999). Following this definition all aquatic bryophytes in Germany might be regarded as facultative aquatics as discussed already decades ago by Elßmann (1923). Some of them prefer – but not mandatory – a permanent submerged stage, but even with the genus Fontinalis sporophyte development does not occur in a long-term fully denudated situation. From early desiccation experiments (Irmscher, 1912) it is

H. Tremp et al. / Limnologica 42 (2012) 242–250

known that leaves of Fontinalis antipyretica die after 14 days but the stems will regenerate after four weeks of drought. Several species of the genus Fontinalis can survive up to one year in humid places (Glime, 1971) or even falling dry over several weeks, as is commonly found in ephemeral and periodical karstic streams or in mountain streams over wintertime. In such conditions aquatic bryophytes survive on the dry land, under cold-dry conditions or even covered with snow. Compared to submerged vascular plants “water mosses” seem to be ecologically unspecialized, considering that the vegetative stages of most mosses, even such of dry habitats as Grimmia pulvinata or Bryum argenteum, are able to survive completely submerged conditions over one year (Elßmann, 1923). Growth experiments by Zastrow (1934) showed that aquatic and amphibic forms of aquatic bryophytes could be transferred into each other and vice versa. Goebel (1889; cited in Gessner, 1955) called bryophytes “halbe Wasserpflanzen” (semi waterplants) as submerged forms of amphibic or terrestrial bryophytes are often not only falsely identified but also treated as new species. Summing up Gessner’s (1955, p. 270) remark about the amphibic mode of life of some bryopytes “. . . viable in both air and water, but nowhere completely at home” seems justified. The search for specific adaptive species traits to cope with the selective forces of their habitat is therefore questionable. The only but most important trait shared by all aquatic bryophytes is their high regenerative capacity, e.g. sprouting from small pieces of stems tightly attached with rhizoids and leaves which are able to develop rhizoids. It is stated that their non-adaptive strategy makes them so successful in dealing with the harsh environment of the land–water ecotone in headwater streams, where aquatic vascular plants, adapted well to the aquatic environment, cannot cope with such selective forces. Aquatic bryophytes try to occupy highly disturbed sites of severe stress. Grime (1977) assigned no viable plant strategy to such habitat characteristics. But Kautsky’s (1988) stunted strategy type, complementing the CSR strategy, matches the comparatively small, slow-growing, long living species with many various types of vegetative diaspores well. At the small scale in streams, a vertical bryophyte zonation on boulders and walls can be found (Watson, 1919; Glime, 1970; Craw, 1976; Glime and Vitt, 1987). It shows an increasing species richness within the gradient from submerged to the semi-aquatic, hygropetric or splash zone (Vitt et al., 1986; Glime and Vitt, 1987; Muotka and Virtanen, 1995). Muotka and Virtanen (1995) described the shift from truly aquatic species to facultative aquatics and semi aquatics along the vertical gradient as being gradual. This zone can also be regarded as shelter zone for aquatic species from where recovery after spates might occur (Tremp and Kohler, 1993). Besides vertical zonation in structurally rich streams, longitudinal changes, classified and termed upper, middle and lower zone (Holmes and Whitton, 1977), on vegetation occur. Often the upper zone is dominated by bryophytes. The upper zone in silicate streams can be divided floristically further when alkalinity and pH rise with distance from the source (Demars and Thiébaut, 2008) and can be distinct when a stable acidity gradient of physiological relevance – i.e. pH 4–7 – is developed (Tremp and Kohler, 1993; Tremp, 1999). Numerous publications in relation with the European Water Framework Directive (EU, 2000; Hering et al., 2006; Szoszkiewicz et al., 2006) stimulated scientific research in this field and gave proposals for monitoring. However the application (Staniszewski et al., 2006) and applicability (Demars and Edwards, 2009) of macrophytes, and even more bryophytes in freshwater monitoring is still limited and sometimes questionable due to lack of sound data. Hence, the present paper has the following three objectives:

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Fig. 1. Conceptual model of the abiotic environment and strictly submerged bryophytes in streams. The bryophyte community firstly differs between hardwater and softwater type. The three corners of the triangle indicate site factors which reduce submerged bryophytes directly: mechanical stress due to substrate instability/current velocity and the subsequent grinding of plant material. Carbonate-incrustation and high acidity reduces aquatic species occurrence dramatically. Apart from these extremes the primary growth factors (inner circle) shape the bryophyte community.

(i) we propose an integrative conceptual model for submersed bryophyte composition and structure; (ii) we then test some of its predictions using data collected across Germany; (iii) finally we compare our findings with existing conceptual models from Northern America, New Zealand and Finland. A conceptual model of aquatic bryophyte occurrence Several conceptual models in aquatic bryophyte ecology can be found, for regions of different relief energy, i.e. for alpine streams (Suren, 1996; Suren and Ormerod, 1998; Suren and Duncan, 1999) or lower mountainous streams of the boreal zone (Muotka and Virtanen, 1995), and a general model for aquatic macrophytes (Riis and Biggs, 2001). A conceptual model, applicable to a broader range of regions, however, is lacking (Fig. 1). The ranking of the impact of environmental variables on species composition depends primarily on the specific range of the values of variables considered, secondly on the regions investigated, and thirdly on the bryophyte mapping method. Many investigations, however, cover only a restricted range of environmental parameters (many sampling points in the same stream). For example, the effect on the floristic composition only becomes evident when a wide range of substrates is covered. Moreover, all complexes of environmental variables can be overridden by the influence of the relief energy (see Table 1). Fig. 1 shows the factors and factor complexes which are postulated as primary for structuring aquatic bryophyte communities in headwater streams. The model highlights first the softwater–hardwater gradient, which differentiates the community structure. Secondly, it depicts the productivity factors (=primary growth factors), which enable growth of permanent submerged bryophytes, and thirdly the disturbance regime due to transported solids (bed instability, grinding effect), which modifies the aquatic bryophyte communities and in its extremes prevents the development of true aquatic macrophyte vegetation. This view is obtained from streams where movement of bed material is common, destroying vegetation almost completely. Nevertheless, some bryophytes can be found at sheltered sites as in the lee of large boulders above the middle water layer. The conceptual model (Fig. 1;

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Table 1 Environmental factors predominantly differentiating stream bryophyte vegetation. The primary growth factors water and temperature are not taken into account. Light, turbidity CO2 and turbulence to enhance its acquisition Nutrients Altitude Current velocity, water level fluctuation Flow variability, disturbance, streambed stability Saprobity, organic pollution Ionic strength and buffering incorporating electrical conductivity, total hardness, temporary hardness, pH, aluminum

inner circle) for aquatic bryophytes includes a view expressed in Slack and Glime (1985) that community structure of aquatic bryophytes is primarily controlled by non-equilibrium processes to which the species respond as opportunists. This includes the fact that aquatic bryophytes are highly adaptive to changing ambient light and nutrient conditions as well as temperature (Maberly, 1985). Their ability to adapt has to be taken into account not only over a short period of time and quick physiological responses but also due to their evergreen status over the entire annual growth period and even over their whole lifetime existence. Thus, they encompass stages where they might exist only in a cryptic stage, e.g. as rhizoid fragments. The environmental factors are assigned different weightings by the individual authors (Table 1). Materials and methods Study sites

Ylla et al. (2007) Jenkins and Proctor (1985), Proctor (1990) Steinman (1994), Vanderpoorten and Palm (1998), Vanderpoorten and Durwael (1999) Ormerod et al. (1994), Suren and Ormerod (1998) Vitt and Glime (1984), Glime and Vitt (1987) Englund (1991), Muotka and Virtanen (1995), Suren and Ormerod (1998), Riis and Biggs (2003) Kolkwitz (1950), Szoszkiewicz et al. (2006) Watson (1919), Butcher (1933), Sørensen (1948), Vitt et al. (1986), Frahm (1992), Tremp and Kohler (1993), Tremp (1999), Vanderpoorten et al. (2000)

laboratory. Species known to occur submerged only occasionally (i.e. due to higher water table) like Racomitrium aciculare (Hedw.) Brid., Dichodontium pellucidum (Hedw.) Schimp. and Thamnobryum alopecurum (Hedw.) Gangulee were not assessed. Only permanently submerged plants of the frequently occurring amphiphytes were included, e.g. Berula erecta (Huds.) Coville. For the core dataset cover estimates for species were recorded, taking only the wetted area into account. In shallow mountain brooks species individuals seldom overlap. This facilitates species cover estimation in percentages. Prerequisites for this mapping procedure are good visibility, low numbers of true submerged species, and a stream width of less than 3 m. These conditions were encountered in almost all cases. In the additional dataset truly aquatic species were mapped by presence–absence. Nomenclature of higher plants follows the German standard list of Wisskirchen and Haeupler (1998), for bryophytes the bryophyte flora of Baden-Württemberg (Nebel and Philippi, 2000–2005) was used.

The core dataset consists of 54 sections of 100 m each, investigated in 52 mountain streams in the state of Baden-Württemberg (SW-Germany, see Fig. 2). The width of the streambed is relatively small in proportion to its roughness. Thus, the dragging power of stream velocity, without taking transported solids into account, seldom exceeds the tolerance of aquatic cryptogams. Due to the unique heterogeneous geology of Baden-Württemberg (Embleton, 1983) streams originated from Gneiss and Granite base rock formation, Triassic red sandstone, limestone and the highly variable Keuper formation, Jurassic limestone as well as Pleistocene moraine material. The field work was conducted in 1996 and 1997. A dataset of 96 stream sections in 69 streams situated in mountain regions in the Southern, Western and Northern part of Germany as the Odenwald, Pfälzer Wald, Solling and the Harz mountains was used for comparison. The field work here was conducted between 1992 and 1994. In both datasets spatially induced floristic autocorrelation is reduced, due to sampling the same stream manifold, which weakens the explaining effect of environmental variables (Borcard et al., 1992; Isaak and Hubert, 2001; Heino and Virtanen, 2006). Most mountain streams were situated in forested catchments, thus the plant species were not exposed to excessive nutrient inputs. With only a few exceptions the streams are summercold; therefore, extreme temperature ranges are not found and a pronounced seasonality effect on submerged species is of minor relevance. Species sampling For the generation of both datasets, the submerged vegetation, bryophytes, vascular plants and algae of genus Batrachospermum and Hildenbrandia were mapped from June to September by wading through the shallow brooks. Species which could not be identified on the spot were collected and determined in the

Fig. 2. Map showing the 54 sampled reaches in 52 different 1st and 2nd (3rd) order streams Baden-Württemberg (SW-Germany). In the western part, silicatic mountain ranges (Black Forest, Southern Odenwald) strech from SSW–NNE direction (quadrats). The other regions with underlying Triassic limestone, the Keuper formation and Jurassic limestone are situated in the center. Moraine material covers parts of SE of Baden-Württemberg.

H. Tremp et al. / Limnologica 42 (2012) 242–250

Environmental variables For the core dataset (n = 54) the following environmental variables were recorded: • Substratum. The percentage cover of substratum was estimated according to the classes loam (special type of bedrock material), mud (sedimented organic and anorganic fine material), sand (<0.2 cm), gravel/pebble (0.2–6.3 cm), stones/cobble (6.3–20 cm), blocks (>20 cm), bedrock (underlying bedrock and sinter formation) and wood. To focus on the question of streambed stability, the sediment fractions were differentiated only in finer (gravel, sand, mud) more instable material and coarser bed material (block, stone). • Physico-chemistry. Water temperature, pH and electrical conductivity were measured once per mapping section with WTW (Wissenschaftlich-Technische Werkstätten Ltd.) devices. Acid neutralizing capacity (ANC4.3 ) was measured titrating 100 ml of stream water sample with hydrochloric acid of a normality of either 0.01 N or 0.1 N with potentiometric endpoint detection on pH 4.3. To give a rough estimate of excess carbon dioxide partial pressures Ep(CO2 ) from pH and ANC4.3 measurements corrected for temperature, we applied the formula given in Neal et al. (1998a, second equation on p. 173). This equation allows for variation in temperature and average ionic strength. Ep(CO2 ) is the ratio of CO2 to what would normally be dissolved in water of the same temperature at equilibrium. The intention was to get a measure which combines pH and ANC4.3 and thus allows an estimate of the CO2 supply for aquatic bryophytes in a multiple regression model. • Stream flow characteristics. The discharge was estimated by multiplying the cross-section of suitable sites (i.e. approximately rectangular) by current velocity estimated with small pieces of wood drifting over a distance of between 5 and 10 m. Watercover was estimated in percentage with respect to emerged structures within the flowing water. Turbulence was estimated on a five point ordinal scale ranging from no flow to strong turbulent flow. • Insolation. The insolation was expressed in hours of potential direct sunshine on the water surface. In each mapping section it was measured at meters 0, 50 and 100 with a horizontoscope developed by F. Tonne (Schütz and Brang, 1995). This is an acrylic hemisphere with an integrated compass and sun path chart of – here 49◦ – northern latitude. The sun tracks give the astronomic sunshine duration at the 15th of every month. This value was multiplied by 30 and the results for all months summed up, which resulted in potential sunshine hours per year. A mean value of the three estimates was used for analysis. • Altitude. Altitude in meters above sea level was taken directly from maps (1: 25,000). For the additional dataset (n = 96) only data on pH and ANC4.3 and altitude were available. Data analyses Species composition–environment interaction was analyzed for the core dataset (n = 54) by means of partial canonical correspondence analysis (pCCA). The unimodal ordination method was chosen because the gradient length of the first axis of the DCA ˇ detrended by segments was larger than four (Lepˇs and Smilauer, 2003). Scaling is focussed on inter-species distances. The analyses should focus on reach scale variables, consequently altitude and the variable discharge, which approximates stream size, were entered as covariables, their influence thus factored out. Since the covariables were not strongly correlated to the remaining variables, the explaining power of the latter was kept. Statistical analyses

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ˇ 2002). were performed with Canoco 4.5 (Ter Braak and Smilauer, This ordination method may be applied to non-normal data, however, ecological structures emerge more clearly when the data do not show a strong asymmetry (Legendre and Legendre, 1998). We applied logarithmic and arcsine-squareroot data-transformation to reduce impacts of outliers and approximate normal distribution. Graphically expressed frequency distributions and the asymptotic significance (P) of a Kolmogorov–Smirnov test showed high values, so normal distribution could be assumed with exception for the chemistry data. As we sampled different geological areas, pH, conductivity and acid neutralizing capacity were distributed bimodal, which cannot be treated with usual transformations. Subsequently all abiotic variables were standardized for analysis. Percentage values of species cover estimates were log(y + 1) transformed and rare ˇ species downweighted (Lepˇs and Smilauer, 2003). Species occurring in less than three mapping sections were excluded. Species response curves were thus fitted for species with at least 25 occurrences in the extended dataset. These were Scapania undulata (L.) Dumort., Chiloscyphus polyanthos (L.) Corda, Brachythecium rivulare Schimp., Rhynchostegium riparioides (Hedw.) Cardot, Amblystegium tenax (Hedw.) C.E.O. Jensen, and Fissidens crassipes Wilson ex Bruch and Schimp. Segments showing none of these species were eliminated, yielding a sample size of n = 145. Species occurrence was expressed as presence–absence therefore their probability of occurrence was modeled as a parameter of the binoˇ 2003). The model was fitted mial distribution (Lepˇs and Smilauer, using the logit link function (Ter Braak and Looman, 1987). The model complexity of the generalized linear models (GLMs) – simple linear (linear) or second order polynomial (quadratic) – was chosen by using the Akaike Information Criterion (AIC). Here smaller values indicate better, more parsimonious, models (Akaike, 1978). Significance of the model was determined by a deviance based F-test comparing the fitted models with the 0-model f(y) = const. (Lepˇs ˇ and Smilauer, 2003). Relationship between submerged vegetation cover and environmental variables was analyzed with a multiple regression model using Systat 10.2.

Results Ordination results At 54 sampling sites of the core dataset 39 true submerged species – 26 bryophytes, 3 macrophytic algae, 1 macrophytic lichen and 9 vascular macrophytes – were found. Species–environment interaction was analyzed by means of partial canonical correspondence analysis (pCCA) to test if the conceptual model (Fig. 1) is supported by real data. The overall variance in species dispersion (total inertia) was 4.19, including the covariables altitude and discharge (3.66). The eigenvalue of the highly significant first canonical axis (EV = 0.533; P = 0.002) explains 14.6% of the variability of species data. Variability in species composition was explained to 22.5% by the two first ordination axes (Fig. 3) and to 31.0% by all. Besides variables with unique information indicated by a low variance inflating factor in the analysis, highly redundant variables (electrical conductivity, ANC4.3 , bed material, watercover) occurred (Table 2). The ordination diagram (Fig. 3) shows the community structure of aquatic bryophytes indicating a strong dependency on physico-chemistry: ANC4.3 , pH and electrical conductivity. Two vascular amphiphytes with a low frequency (Veronica anagallis-aquatica L., Nasturtium officinalis L.) showed a different pattern. The species structure deducted from the diagram (Fig. 3) is concurrent with field observations for mountain streams over a broad range of geological entities. In Table 2 the environmental variables

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H. Tremp et al. / Limnologica 42 (2012) 242–250 Cra fil

Cra com

0.8

Rhynchostegium riparioides Scapania undulata

pH Hil riv

con0.4 El. ductivity

Amb ten Bat mon

Ver bec Amb rip

0.2 ANC4.3

* **

Gly flu Bra riv Rhy rip Hyg och

0.0 Watercovered area

Pha aru

-0.2

Probability of occurrence

0.6

-0.4

1.0

*Temperature **Gravel+sand+mud

Fon ant Fis cra

1.0

Agr sto

Turbulent+ strong turb.

Chi pol Bra plu Mar ema Sca und Hyo arm

Pot. hours of sunshine

Nas off

Block+ stone

0.8

0.6

Amblystegium tenax

Chiloscyphus polyanthos

0.4 Brachythecium rivulare

0.2 Fis

Ver ana

-0.6 -1.0 -0.8 -0.6 -0.4 -0.2 0.0

0.2

0.4

0.6

are ranked following their variance explaining effect for submerged macrophyte distribution. Due to the strong correlation among the chemical variables, which can be expected from their causal relationships, their conditional value (Lambda-A) decreases, independent of which variable was chosen first. Bed material variables provided a low significant contribution to species differentiation (Table 2). The influence of turbulence and direct sunlight was not significant. Species response curves The species response curves illustrate the functional relationship between the pH gradient and the probability of species occurrence. Species response (Fig. 4) to a single physic-chemical variable (Table 2) based on the complete dataset, supports the already indicated differences of species reactions to the water chemistry complex (Fig. 3) more precisely. All regressions were significant (P < 0.002). A linear model was fitted for three species, for the other species a second order polynomial model. For the latter values of species optimum ± standard error and tolerance along the pH-gradient were obtained: S. undulata (pH 4.32 ± 0.37; tolerance = 1.12), B. rivulare (pH 6.78 ± 0.16; tolerance = 0.85) and C. polyanthos (pH 6.86 ± 0.82; tolerance = 0.82). Multiple linear regression model The fraction of variance of the submerged vegetation cover accounted for by the multiple linear regression model (Radjusted 2 ) is 0.34 (Table 3). Slopes of all the resource variables are positive and Table 2 Forward selection of directly measured variables of a partial canonical correspondence analysis (pCCA). The variables altitude and discharge were treated as covariables. P refers to the significance level obtained with a Monte Carlo permutation test (499 permutations).

a

Acid neutralizing capacity4.3 pH Water temperature Water covered area Blocks + stones Gravel + sand + mud Turbulent + strong turbulent a Electrical conductivity Potential hours of sunshine a

a

sip

es

0.8

0.0 4.0

Fig. 3. Biplot of species and directly measured environmental variables along the first two axes of pCCA. Because altitude and discharge were entered as co-variables they are not shown in the diagram.

Variable

sid

ras sc en

Marginal

Conditional effects

Lambda-1

Lambda-A

P

F

0.48 0.26 0.19 0.36 0.27 0.21 0.24 0.48 0.12

0.48 0.13 0.12 0.11 0.13 0.12 0.06 0.09 0.06

0.002 0.060 0.076 0.042 0.028 0.016 0.358 0.160 0.360

7.63 2.00 1.91 1.95 2.15 2.14 1.51 1.11 1.09

Independent (marginal) effects of chemistry variables are high (Lambda-1).

5.0

6.0

7.0

8.0

9.0

pH Fig. 4. Species response curves fitted with a generalized linear model (GLM). For occurrence of Brachythecium rivulare, Chiloscyphus polyanthos and Scapania undulata a second order polynomial predictor was appropriate. For the other species a linear predictor fitted the species data better.

significant, so it can be concluded that there is a positive relationship to the response variable. Considering the standard coefficients it can be concluded that every single resource contributes to a same amount to submerged vegetation cover, which is predominantly bryophyte cover. The Durbin–Watson coefficient (2.058) provides no hint to strongly autocorrelated residuals, which would have inflated the analysis result. Beside large scale variables (hard–softwater type) taxonomic richness becomes locally modified by structural variables (Table 4). Variance of the taxonomic richness accounted for by the multiple linear regression model (Radjusted 2 ) is 37% (Durbin–Watson coefficient 2.080). Discussion To verify our proposed model of environmental factors determining aquatic bryophyte community structure, an extensive dataset of truly aquatic bryophytes, investigated over a broad range of environmental situations, was used. In contrast to other habitat templates, where substrate stability and disturbance were the main focus (Suren, 1996; Suren and Ormerod, 1998; Suren and Duncan, 1999; Muotka and Virtanen, 1995), our findings support the softand hardwater phenomenon as the most discriminating cause of bryophyte species composition. Primary growth factors, bed structure, and disturbance can be addressed as secondary factors. These might only modify the communities, impoverishing or enhancing species richness. Implemented environmental variables Sunshine duration estimates would have been more precise if measured in wintertime, too, when there is no dense foliage. Nevertheless, the estimates are more satisfying compared to the often used percentage of tree shading at zenith estimates (foliage cover). This is not sufficient because light not from above, but shining from the sides often accounts for a considerable part of direct sunlight reaching the water surface. Contrastingly, with the here used horizontoscope method, bank height is considered adequately. In macrophyte rich streams estimates of bed material coverage in winter and in summer would have been reasonable as temporary sedimentation occurs during the vegetation period. Average current velocity, often used as surrogate for CO2 supply, can be very similar in a turbulent upland stream and in apparently low flowing lowland rivers (Proctor, 1990). Therefore, Ep(CO2 ), even as a rough

H. Tremp et al. / Limnologica 42 (2012) 242–250

247

Table 3 ANOVA table and parameter estimates for the multiple linear regression model linking the resource variables light (potential sunshine duration) and excess carbon dioxide Ep(CO2 ) and stable substrate (blocks and stones) with submerged vegetation cover. Small differences are due to rounding errors.

Regression Residual

Constant Pot. sunshine duration Ep(CO2 ) Blocks and stones

Sum of squares

df

Mean square

F-ratio

P

5.647 9.128

3 45

1.882 0.203

9.281

<0.001

Coefficients

Std. error

−1.671 0.544 0.531 0.011

0.530 0.201 0.178 0.004

Std. coefficients 0.339 0.355 0.367

estimation, might be better suited (Demars and Trémolières, 2009) for quantifying the supply of carbon dioxide especially on aquatic bryophytes, for which it is the only carbon source. The range of 0.3 up to 44 times saturation matches the reported values from Neal et al. (1998b) and Demars and Trémolières (2009) well.

Mapping procedure At 54 sampling sites (52 streams) of the core dataset 39 true submerged species – 26 bryophytes, 3 macrophytic algae, 1 macrophytic lichen and 9 vascular macrophytes – were found. In these small streams aquatic macrophytes of genus Ranunculus or Potamogeton, which usually occur in mid-size and larger streams, were missing. The mapping procedure is comparable to many macrophyte investigations which allows for comparisons (e.g. Hering et al., 2006). However, it does not match the phytosociological bryophyte mapping where quadrat size rarely exceeds 0.1 m2 . But with respect to the reach scale (Frissell et al., 1986), variability caused by different plot sizes due to different streambed widths is small compared to variability in species richness. All aquatic and many terrestrial bryophytes are able to occur in the intermediate spray zone, but only a few species are able to occur at permanently inundated sites. Species of the semi-aquatic zone are mostly affected by variables other than water quality (Vanderpoorten and Palm, 1998). Defining instream-bryophytes “between two banks” (Scarlett and O’Hare, 2006) results in high numbers of species but it incorporates numerous semi-aquatic and terrestrial species, which can be found elsewhere, too. Good comparisons are possible when a clear distinction is made, as in Heino and Virtanen (2006). With the exception of Amblystegium (Leptodictyum) riparium, known as a species which is able to occur permanently submerged, our findings are in concordance with those named “obligatory aquatic” in Dierßen (2001) and also those listed in Appendix 1 of Heino and Virtanen (2006). Including such knowledge species, which are inundated only by chance due to higher water table, could be classified accordingly. Often terrestrial bryophyte species are incorporated in species lists of aquatic habitats (Schaumburg et al., 2004; Meilinger et al., 2005), which seems unavoidable in times of higher discharge, but will weaken

Tolerance

t-Value

P

0.871 0.963 0.883

−3.158 2.702 2.978 2.939

0.003 0.010 0.005 0.005

the interpretative ecological strength in investigations and assessment approaches. Differentiating aquatic bryophytes sensu Vitt and Glime (1984) in “obligatory” (i.e. obligate aquatics occur only submerged) and “facultative” (i.e. often submerged but able to tolerate periods of desiccation) seems inappropriate. Even species named “obligate aquatics” are able to live outside water over prolonged periods of time. The permanently moist, but not submerged spray zone provides suitable conditions for all aquatic bryophytes. Because of the strict definition of bryophytes in this study, i.e. occurring submerged over a prolonged period of time, 50% fewer species were incorporated in the analysis compared to other investigations. Recently published European datasets (Holmes et al., 1998; Szoszkiewicz et al., 2006; Demars and Edwards, 2009) are available, allowing comparisons of species demands and for defining species as true aquatics and thus suitable for “in stream monitoring”. If focussing on true aquatic species the thalweg mapping procedure applied by Fritz et al. (2009) seems very promising.

Ordination results We avoided problems of measuring environmental variables with too narrow ranges by the number of sampled regions and there found different geologies. The chosen variables match the proposed model (Fig. 1) fully. Despite focusing only on small mountain streams, we observed a complete species turnover due to the strong discriminating factor geology, which is closely related to the variables ANC4.3 , electrical conductivity and pH. These have to be seen as a complex, which can be assigned to soft- and hardwaters. Values of electric conductivity between 200 and 300 ␮S/cm were completely lacking in the Baden-Württemberg core-dataset. Floristic comparison shows that this bimodality acts as simple discriminator between soft- and hardwater bryophyte communities at a first glance. The following species were restricted to waters of electric conductivity lower than 200 ␮S/cm: S. undulata (L.) Dumort., Marsupella emarginata (Ehrh.) Dumort., Hyocomium armoricum (Brid.) Wijk & Margad., Hygrohypnum ochraceum (Wilson) Loeske, Brachythecium plumosum (Hedw.) Schimp. and Fontinalis squamosa Hedw. The observed effect of pH or buffering capacity is not naturally linked to substrate. Even in Triassic red sandstone areas a

Table 4 ANOVA table and parameter estimates for the multiple linear regression model linking the resource variable wetted area between banks (watercover) and stable substrate (blocks and stones) with submerged species numbers. Small differences are due to rounding errors.

Regression Residual

Constant Watercover Blocks and stones

Sum of squares

df

Mean square

F-ratio

P

118.693 183.307

2 46

59.347 3.985

14.893

<0.0005

Coefficients

Std. error

−4.033 0.099 0.062

1.655 0.020 0.017

Std. coefficients 0.586 0.443

Tolerance

t-Value

P

0.920 0.920

−2.437 4.895 3.696

0.019 0.000 0.001

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calciphilous aquatic bryophyte flora might occur if the sandstone is percolated with circumneutral or alkaline water. This is the case when carbonate rich geological layers cover the acid Buntsandstein layer (Tremp and Kohler, 1993). Substrate should be classified according to its lifespan of surface which affects the attachment and detachment of bryophytes. Aquatic bryophytes are nearly absent from weakly inundated sedimentary bedrock like siltstones (Suren and Ormerod, 1998) and loamy bed material. In these situations not only the adhesion problem persist as, e.g. A. tenax is able to overgrow loamy bedrock (pers. observation), but turbidity and silting provide further stress for aquatics at those stands so they might not be suitable for bryophyte growth at all. Recently, many authors have rediscovered that pH, electrical conductivity and alkalinity were the most discriminating variables for macrophytes in general. Our groupings of aquatic bryophytes and their communities are generally consistent to other authors in the same or adjacent mountain regions as the Vosges (Frahm, 1992; Thiébaut et al., 1998; Vanderpoorten and Klein, 1999; Demars and Thiébaut, 2008), the Ore Mountains (Baumann and Stetzka, 1999), Westphalian Mountains (Schmidt, 1993), Harz Mountains (Bley, 1987), Black Forest (Vanderpoorten and Klein, 1999), Odenwald and Spessart (Philippi, 1987). In conclusion, macroscale variables – most pertinent geochemistry – influence community type and thus broadly defined taxonomic richness, while microscale variables (substrate size, streambed stability) influence the abundance of bryophytes. This also reflects the findings of Scarlett and O’Hare (2006). Some experimental evidence for the discrimination of the acidity–alkalinity complex is given earlier (Tremp and Kohler, 1993), but still the ecological amplitude of the species is not fully known. Wilkinson and Ormerod (1994) and Brandrud (2002) found some negative effects on Nardia compressa and an increase of acidsensitive macrophyte species due to catchment liming, which is crucial for our understanding of the behavior of soft- and hardwater (bryo)flora. But single causal relationships due to the shift towards hydrogen carbonate seem improbable and further experimental work in situ is needed for a deeper understanding of this pattern in nature. Nutrients were not included and thus our model might be incomplete. Therefore, it has to be pondered if nutrient deficiency was limiting at several sites. In highly acidic waters with high aluminum content phosphate is precipitated efficiently. The same assumption about low phosphate content could be relevant in alkaline travertine forming waters. But at both extremes of the possible phosphate range a few bryophyte species still show a comparatively high productivity. We conclude that nutrients do not seem to be a crucial factor considering their continuous supply and the comparatively low productivity of bryophytes (Muotka and Virtanen, 1995; Glime and Vitt, 1984). Additionally Demars and Thiébaut (2008) and Vanderpoorten et al. (2000) identify pH, alkalinity and conductivity in silicatic streams as confounding factors of nitrate and phosphate and so their effect is difficult to evaluate. Compared to mosses and leafy liverworts thalloid species are the most susceptible to the grinding effect of suspended solids. Thus in highly disturbed streams, species like Riccardia chamaedryfolia (With.) Grolle become very rare, occurring only at sheltered sites. Additionally, thalloid liverworts are affected stronger by freezing (Dilks and Proctor, 1975). Disturbance measures by the means of instability indices (Suren, 1996; Muotka and Virtanen, 1995; Townsend et al., 1997; Suren and Duncan, 1999) were not adequately implemented in our analysis. Nevertheless, considering the conceptional model (Fig. 1), disturbance is regarded as an important factor. It might mask the bryophyte community to an unrecognizable state, especially when bryophytes cannot withstand the disturbance intensity and frequency at a certain site. In this case disturbance might shape but not change the species composition.

Species response curves GLM results after application of generalized additive models (GAMs) were graphically comparable as in terms of residual deviance of the different models. The preferences of slightly acid (S. undulata), circumneutral (C. polyanthos, B. rivulare) and neutral to alkaline waters (R. riparioides, A. tenax, F. crassipes) could be demonstrated clearly. For a few species, our results fulfill the demands expressed by Demars and Thiébaut (2008), but it is clear that such analyses are data-intensive. Due to the restricted geographical range of the investigation the ecological range of all modeled species was at best approximated considering the holarctic distribution area of these species. Nevertheless, the shown species response is suitable to complement earlier findings of Vanderpoorten and Klein (1999) and support those presented by Heegard et al. (2001) for lakes in Northern Ireland. Regardless of the usefulness of modeling, species response probabilities of species occurrence at the extremes is rather model-driven than ecologically sound. Thus, no truly aquatic occurrence of the species (except S. undulata) was found in the present study in the field, at sites with pH below 5. Vegetation cover/taxonomic richness regression model In mountain streams, which are characterized by frequent disturbances and thus high heterogeneity in the reach scale (Frissell et al., 1986), plenty of resources such as light, CO2 , and stable substrate for attachment seem reasonable prerequisites for a higher submerged vegetation cover. A linear regression model including these variables explained a large part (34%) of the response variable. The implementation of turbulence instead of Ep(CO2 ) – both variables reflect CO2 availability – fitted less well and thus showed that they are not interchangeable. Other authors (Suren, 1996; Suren and Ormerod, 1998) regressed bryophyte cover against stability and disturbance variables of the streambed and gained a much better explanation of variance (63% and 65% respectively). Thus, the implementation of a disturbance/stability variable might have improved our model considerably. A one to one comparison would not be appropriate with these models as the sampling strategy differs; species from the splash zone were included, the range of percentage cover being higher. From their experiments Ylla et al. (2007) provided evidence that light limitation is the factor that mostly constrains the metabolism of algae and mosses in headwater streams. All primary growth factors have at least the potential to restrict the growth of aquatic bryophytes, but probably no single primary growth factor (Fig. 1) will lead to entire depletion of bryophytes. In heavily shaded streams two-dimensionally shadow forms of usually radially symmetrical mosses grow restricted to emerged sites, or finally the tiny F. crassipes becomes the only species present. Light acts independently from often highly correlated instream variables. Considering the correlative structure between taxonomic richness and vegetation cover (Spearman correlation coefficient: 0.64) the relationship found here explains only a small part (15%) for truly aquatic species diversity in mountain streams. Implementing only structural parameters as blocks, stones, and wetted area a relationship to taxonomic richness of aquatic species occurred. Hierarchical models including higher scale variables such as stream size and discharge, acting as confounding variables, would be needed to evaluate the influence of such small scale variables adequately. As long as a disturbance regime is present, with which only the regenerative capabilities of aquatic bryophytes are able to cope with, an increase of the resources will lead to a higher vegetation cover and species richness. When using our cover determinations as a surrogate for standing crop, a linear cover–species richness relationship occurs rather than a hump-backed (Muotka and Virtanen, 1995).

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Results of Virtanen et al. (2001) support quadratic as well as linear relationships depending on bed structure. Such findings are in contrast to stream types with an only moderate disturbance regime where highly productive macrophytes might monopolize space – at least temporarily. The influence of environmental variables on aquatic bryophytes The lack of species like R. riparioides, C. polyanthos or F. squamosa in streams with pH permanently lower than 5.0 (Frahm, 1992; Tremp and Kohler, 1993) is unlikely explained only with instant hydronium-ion or aluminum toxicity. In short-term experiments under such conditions, these species are still viable but their growth and branching capability is reduced. At pH values lower than 5.0 an effect on protonema development of sensitive species was found, but photosynthetic capacity under relevant pH conditions (pH < 4.0) of adult plants remained unimpaired (Tremp and Kohler, 1993). Therefore, there is still only weak physiologically based evidence for the observed species zonation across strong pH gradients in mountain streams. But it can be concluded, that simple explanations and short time effects of stressors are highly improbable. In naturally acid and even in acidified small mountain brooks submerged bryophytes do not disappear due to low pH, but rather under alkaline conditions in case of strong travertine formation. Here only the capability to grow faster than encrustation development allows such species to prevent photosynthetic active organs of dying off. Only under low or short term periodic travertine formation, bryophytes living in a completely submerged stage are able to tolerate encrustation. Situations where growth is enhanced, e.g. high turbulence or even aerial assimilation, are not considered here. Glime (2007) states that under high pH values bryophyte growth is restricted to waterfalls, where high turbulence permits gaseous atmospheric CO2 to come in contact with the moss. In between the extremes of highly acid waters and limestone incrustation pH becomes an important key factor due to its modification of the CO2 supply. Nevertheless, pH will only serve as a key factor as long as turbulence and partly emersion of species will not compensate the high diffusion resistance of water. Our results show the floristic differences between soft- and hardwater clearly. The level of pH can be considered as a macroscale variable which acts superiorly compared to bed stability and disturbance due to floods. These factors affect silicate and limestone mountain streams alike. Even though streambed stability is extremely important, it cannot serve as discriminator dividing softand hardwater bryophyte communities. Small scale vertical zonation, concordant to structural richness, may serve as an important habitat factor. Especially the spray zone acts as shelter allowing high species richness of aquatic bryophytes, which are able to re-enter the aquatic habitat after disturbance and destruction (Tremp, 1999). Besides the discussed extreme environmental constraints there seems to be no single dominant primary growth factor (Fig. 1), which limits the growth of aquatic macrophytes (bryophytes) during the entire vegetation period (Maberly, 1985; Carr et al., 1997). Instead, their growth is limited by benthic algae competing for space. Conclusions As stated by Bates (2000) for terrestrial bryophytes the distinction between calcicole (calcium-loving) and calcifuge (calcium-hating) species can be seen as the principal dichotomy in a regional aquatic bryophyte flora, too. But still the functional link from the soft–hardwater complex to the community composition of aquatic bryophytes has to be explained ecologically in a rigorous way and seems still open for further debate.

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