Questions: Do islet area, number of biotopes and distance from the mainland shape lichen species richness on islets? Are there any species- or substrate group-specific trends associated with these factors?

Location: Islets of the west Estonian Archipelago, Estonia.

Methods: A species list was compiled for each of the 32 islets and the relative abundance of each species was estimated. The lichens were divided into seven groups according to their substrate preferences. Generalized linear model (GLIM) analysis was applied to test the effect of the islet traits on the number of lichen species on the islets and in the substrate groups. The probability of presence/absence and abundance of the most frequent species according to the islet traits were tested with GLIM and general linear mixed model.

Results: The lichen flora of the islets consisted of 326 taxa, the number of lichen species per islet varied from 2 to 197. Total number of species per islet and within the substrate groups was positively correlated with islet area and with number of biotopes, and negatively correlated with distance from the mainland; however, these relationships varied among the substrate groups. Although individual lichen species showed variation in responses, general trends in island biogeography were evident.

Conclusions: The distribution pattern of lichens on the studied islets follows the theory of island biogeography: the number of species per islet depends on isolation, area and biotope diversity. Species specific traits, such as dispersal strategy and growth form, as well as availability of a particular substrate are important for formation of the lichen flora on islets.

Nomenclature: Randlane & Saag (1999, 2004) and Santesson et al. (2004) for lichens; Leht, M. (ed.) 1999 for vascular plants.

Abbreviations: AIC = Akaike's information criterion; GLIM = Generalized linear model; TLC = Thin layer chromatography.

Question: To which extent do external ecological factors effect Corynephorus grassland vegetation?

Location: Central Netherlands.

Methods: We implemented different treatments (sand deposition, litter deposition, nitrogen input, mechanical disturbance, control) in permanent plots representing different successional phases in Corynephorus grassland. Plots were recorded just before the treatments and during the subsequent two years. Vegetation changes were analysed by Redundancy Analysis for repeated measurements and Correspondence Analysis, changes in single species abundances by ANOVA.

Results: Species composition hardly changed during the observation period. Several single species abundances showed significant responses to different treatments, most often decrements as direct effects of cover, removal, or dieback. However, Corynephorus canescens and Polytrichum piliferum benefited from sand deposition, the exotic moss Campylopus introflexus from litter deposition. In the colonization phase Polytrichum, Campylopus and Cladonia diversa increased irrespective treatment. Therophytes such as Spergula morisonii showed the strongest negative response to drought, grasses (e.g. Corynephorus canescens) and bryophytes (e.g. Polytrichum piliferum) were less susceptible. Most lichens did not respond at all.

Conclusions: The experiment confirms the high stability of Corynephorus grassland vegetation. Most vegetation changes are in accordance with the hypothetical series of successional phases. In contrast, changes in abundance of single species express considerable dynamics within the vegetation. Species responses also depend on extreme weather conditions as well as on the successional phase of the grassland vegetation and therefore on the competition situation.

Abbreviations: CA = Correspondence Analysis; RDA = Redundancy Analysis.

Nomenclature: Wisskirchen & Haeupler (1998) for vascular plants; Koperski et al. (2000) for bryophytes; van Herk & Aptroot (2004) for lichens; Ettl & Gärtner (1995) for algae.

Question: Can lichen diversity of an earlier succession stage be restored in dune grassland after fire in a region with high nitrogen deposition?

Location: Calcium-poor coastal dunes in the Wadden district, The Netherlands.

Methods: We sampled dune grassland by using a large continuous transect of 4 m × 4 m blocks on both a south slope and a west slope. The sampling was conducted in the lichen-rich Violo-Corynephoretum in 1966, in the vegetation dominated by tall graminoids in 1990 and in the recovering vegetation for eight years after a wildfire in 1993. Vegetation succession in the blocks is visualised in stacked bar graphs and ordination diagrams (DCA). In 1966 relevés were made within the blocks, and from 1990 until 2001 permanent quadrats were studied.

Results: Between 1966 and 1990 the lichen-rich open grassland became dominated by tall graminoids and developed partly into a dwarf-shrub heath, resulting in a severe loss of lichen diversity. After the fire a lush vegetation of tall graminoids with an abundant moss cover developed. In 2001 the vegetation was still very different from the lichen-rich vegetation in 1966.

Conclusions: Fire alone will not change dunes dominated by tall graminoids into open lichen-rich grasslands in an area with high aerial nitrogen deposition. After fire, additional intervention is recommended, such as large-scale clearing of the burned vegetation and actively promoting deposition of sand, either blown in from foredunes, from re-activated blow-outs or artificially brought to the site.

Abbreviations: L = Light; N = Nitrogen; NMDS = Non-metric multidimensional scaling; PQ = Permanent quadrat; R = Acidity reaction; RD = Rijks-Driehoeksmeting; VC = Violo-Corynephoretum.

Nomenclature: Phanerogams: van der Meijden (1996); Mosses: Dirkse et al. (1999); Lichens: Aptroot et al. (2004).

Question/Location: We modelled lichen epiphyte biomass in relation to topography, stand structure, and lichen community composition in the central Cascades of western Oregon.

Methods: Sampling was stratified by stand structure. Epiphyte biomass was estimated based on lichen litter for three functional groups: cyanolichens, forage lichens, and matrix lichens. Regression models for estimating lichen biomass (log₁₀ kg.ha⁻¹) were developed based on three pools of predictors, each pool demanding different levels of effort to obtain the data. First, we created models from topographic predictors that are easily extracted from GIS data. We then developed models based on both topographic and stand-structure variables. Finally, we developed models using topography, stand structure, and lichen community data.

Results/Conclusions: Lichen biomass changed with elevation, cyanolichen biomass highest at low elevations (470–950 m) and forage lichen biomass highest at higher elevations (950–1470 m). Lichen biomass was lowest in even-aged young stands and highest in mature stands with remnant trees and in old-growth. Stands with remnant trees had more lichen biomass than even-aged stands.

Models with the greatest explanatory power were: cyanolichen biomass predicted as a function of elevation, stand age index, the sum of Lobaria oregana and L. pulmonaria abundance, and cyanolichen species richness (R² = 0.85); forage lichen biomass predicted as a function of stand age index and, Alectoria sarmentosa abundance (R² = 0.55); and matrix lichen biomass predicted as a function of stand age index and matrix lichen abundance (R² = 0.58). These models are useful tools for understanding and predicting the distribution of epiphytic macrolichen biomass at a landscape scale.

Nomenclature: McCune & Geiser (1997).

Abbreviations: AI = age index; OG = old growth; PNW = Pacific Northwest.

Question: How consistent are relationships of forest lichen community composition with environmental variables across geographic scales within region and across regions?

Location: Northwestern continental USA and east central continental USA.

Method: Four macrolichen data sets were compiled using identical plot sample protocol: species abundance estimated in 0.4-ha permanent plots on a systematic grid, as part of government (USDA-FS) forest inventory programs. One data set in each region represented a large area; the other represented part of the large area. We used global NMS ordination of plots based on species abundance to extract major axes of variation in community composition. Correlations of species, guilds, and environmental variables with ordination axes were compared between geographic scales for the two regions.

Results: Primary axes of community variation at larger scales were correlated with climate variables and related geographic variables such as latitude and elevation, and with pollution. Forest vegetation variables such as stand age and tree species composition became more important at small scales. Community variation unexplained by macro-environment variables also became more important at small scales. Of several hundred species tested, ten lichen species showed consistent behaviour between scales within region (one also across regions) and are thus potential general indicators of ecological conditions in forests. Of six lichen guilds tested, several show strong patterns not consistently related to environmental conditions

Conclusions: Interpretation of lichen species and community composition as indicating particular environmental conditions is context-dependent in most cases. Observed relationships should not be generalized beyond the geographic and ecological scale of observation.

Abbreviations: NMS = Global Non-metric Multidimensional Scaling ordination.

Nomenclature: Esslinger (2005) for lichens; Mitchell & More (2002) for tree species.

Question: Is the pendulous epiphytic indicator lichen Alectoria sarmentosa influenced by proximity to forest edge in natural old-growth forests?

Location: Large (28 400 ha), naturally heterogeneous boreal landscape in northern Sweden dominated by old-growth Picea abies forest in a matrix of open wetland.

Methods: The abundance of A. sarmentosa and forest structure were quantified in ten edge-interior transects (0–100 m) at southern to western forest edges. Four 10 m × 50 m plots were sampled along each transect. Mass of A. sarmentosa in the lower canopy (0–5 m) of P. abies was estimated from maximum thallus length.

Results: The maximum length of A. sarmentosa was four times lower, and the lichen mass 16 times lower, at the forest edge compared to the forest interior. Lichen mass showed a monotonic decrease from the interior to the edge. Mean distance of edge influence was 58 m for lichen mass, and extended longer into the forest than changes in stand structural variables. The response of A. sarmentosa to edges is a result of a combination of changes in microclimate and substrate availability.

Conclusions: The indicator species A. sarmentosa is strongly affected by proximity to forest edge in natural old-growth forests. Edge influence is thus important in controlling the abundance of this group of pendulous lichens in natural forest ecosystems. Distance of edge influence was longer in natural wetland-forest ecotones than previously reported for fragmented forests; this was probably due to higher lichen abundance and lower site productivity in the study area. Understanding lichen response to natural landscape structure may help us to improve conditions for epiphytes in managed forests.

Abbreviations: DEI = Distance of edge influence; GIS = Geographic information system; MEI = Magnitude of edge influence.

Nomenclature: Santesson et al. (2004) for lichens, Karlsson (1997) for vascular plants.

Questions: What are the most relevant environmental variables influencing the distribution and the species richness of epiphytic lichens in heterogeneous areas of the Mediterranean region? What is the relative importance of substrate- vs. environmental-related variables? How do climatic and disturbance factors interact?

Location: The study was carried out in the Liguria region (northwestern Italy). This is a complex region where steep environmental gradients occur over a few kilometres of longitude and latitude.

Methods: Data on lichen species frequencies, collected on the basis of stratified random sampling, were analyzed using non-metric multidimensional scaling (NMS) and DCA. Indicator Value Analysis (IVA) analysis was used to find indicator species for the environmental predictors.

Results: In the survey area, epiphytic lichen distribution depends on both substrate- and environment-related factors. Climatic variables (in particular average yearly temperature and rainfall), anthropogenic pressures (particularly harvesting and atmospheric pollution), bark pH and texture were associated with the main axes of variability in the dataset. Mean annual rainfall is the best predictor for epiphytic lichen richness in the survey area. The particular effects of the Mediterranean region (e.g. the influence of forest fires) and of heterogeneous areas (the variability of diversity in relation to habitat) were pointed out. Several indicator species, closely linked to particular ecological conditions, were found for both substrate-and environment-related variables.

Conclusions: The main variables involved seemed to be the same reported for other areas, but their relative importance and their spatial scale of action were in some cases different, probably due to the geomorphological and climatic heterogeneity of the survey area. The significant influence of climatic predictors and disturbance factors on epiphytic lichens was confirmed, suggesting that these organisms may be used successfully to describe ecological trends in natural environments, also providing practical information at ecosystem level.

Nomenclature: Nimis (2003).

Abbreviations: NMS: Non-metric Multidimensional Scaling. IVA = Indicator Value Analysis.

Question: Populus tremula (Aspen) is a post-fire successional tree with a large number of host-specific lichens. One, Ramalina sinensis, will colonize very young aspen stands. The apothecia of this species are attacked by a parasitic fungus, Abrothallus suecicus. The incidence and severity of disease caused by this parasite was studied in nine stands between 22 and 180 years old.

Location: Central Sweden.

Method: Thalli of R. sinensis were randomly sampled from nine stands. Each thallus was weighed and the number of diseased and non-diseased apothecia were scored for each thallus.

Results: The data show (1) an increase in both disease incidence and disease severity with increasing stand age; (2) that smaller thalli show an increasing probability of being diseased in older stands; (3) that high disease levels prevail in older aspen stands; and (4) a broad variation in disease severity for thalli of similar size in the four older stands.

Conclusions: The studied chronosequence is too short to elucidate whether the Abrothallus-Ramalina system is driven by disease escape in space and time, or co-existence. However, the high disease levels in older stands suggest that conservation programs aiming to sustain this system cannot only focus on preservation of isolated old-growth stands, but also need to incorporate continuous creation of young stands. If succession is ignored, conservation of organisms originally adapted to, now vanishing, large-scale disturbance regimes is likely to fail. We point out the need to assess the role of disease in conservation.

Nomenclature: Hawksworth et al. (1995); Karlsson (1997); Santesson et al. (2004).

Question: We present a general structural carbon - nutrient balance hypothesis parallel to Bryant et al.'s defensive chemistry hypothesis. Our hypothesis suggests that because herb species require a lower investment of carbon per unit length of stem than do woody plants, herbs should be at a competitive advantage where the leaf area of plants in the ground layer is limited by light (or fixed carbon, C) rather than soil resources (R) such as nutrients or water. We test the derivative predictions that in temperate deciduous forests (1) herb cover and species richness increase as soil resources increase, and (2) woody ground-layer cover, density, and species richness increase as soil resources decrease.

Location: To maximize generality, the eight temperate deciduous forest sites were dispersed along an 800 km band from the Coastal Plain of eastern North Carolina to the Central Basin of middle Tennessee, USA.

Methods: Soil nutrients and moisture, herb cover and woody stem densities were observed in six plots at each site, randomly located in high, medium, and low herb cover areas. Multiple regression, correlation, and Redundancy Analysis ordination were used to test predictions.

Results: Plants with herbaceous (low C:R) stems are generally abundant where soil moisture and basic cations (Ca, Mg) are high (low C:R environments), and woody (high C:R) plant cover, basal area, stem density, and species richness are all greatest on dry or nutrient-poor soils (high C:R environments). Plots with intermediate soil resource availability and herb cover have the most species, and maximum herb species richness occurs at higher soil resource levels than maximum woody species richness.

Conclusions: Our observations are consistent with our structural carbon - nutrient balance hypothesis.

Nomenclature: Kartesz (1999).

Abbreviations: C = fixed carbon; R = soil resource (minerals and water)

Questions: What is the observed relationship between biomass and species richness across both spatial and temporal scales in communities of submerged annual macrophytes? Does the number of plots sampled affect detection of hump-shaped pattern?

Location: Doñana National Park, southwestern Spain.

Methods: A total of 102 plots were sampled during four hydrological cycles. In each hydrological cycle, the plots were distributed randomly along an environmental flooding gradient in three contrasted microhabitats located in the transition zone just below the upper marsh. In each plot (0.5 m × 0.5 m), plant density and above- and below-ground biomass of submerged vegetation were measured. The hump-shaped model was tested by using a generalized linear model (GLM). A bootstrap procedure was used to test the effect of the number of plots on the ability to detect hump-shaped patterns.

Result: The area exhibited low species density with a range of 1 - 9 species and low values of biomass with a range of 0.2–87.6 g-DW / 0.25 m². When data from all years and all microhabitats were combined, the relationships between biomass and species richness showed a hump-shaped pattern. The number of plots was large enough to allow detection of the hump-shaped pattern across microhabitats but it was too small to confirm the hump-shaped pattern within each individual microhabitat.

Conclusion: This study provides evidence of hump-shaped patterns across microhabitats when GLM analysis is used. In communities of submerged annual macrophytes in Mediterranean wetlands, the highest species density occurs in intermediate values of biomass. The bootstrap procedure indicates that the number of plots affects the detection of hump-shaped patterns.

Abbreviations: AIC = Akaikes information criterion; GLM = Generalized linear model.

Nomenclature: Valdés et al. 1987; Corillion 1961 and Wood & Imahori (1965) for charophytes.

Questions: How do forest types differ in their distinctiveness among islands in relation to environmental and anthropogenic disturbance gradients? Are biogeographic factors also involved?

Location: Tonga, ca. 170 oceanic islands totalling 700 km² spread across 8° of latitude in Western Polynesia.

Method: Relative basal area was analysed for 134 species of woody plants in 187 plots. We used clustering, indirect gradient analysis, and indicator species analysis to identify continuous and discontinuous variation in species composition across geographical, environmental and disturbance gradients. Partial DCA related environmental to compositional gradients for each major forest type after accounting for locality. CCA and partial CCA partitioned observed compositional variation into components explained by environment/disturbance, locality and covariation between them.

Results: Differences among forest types are related to environment and degree of anthropogenic disturbance. After accounting for inter-island differences, compositional variation (1) in coastal forest types is related to substrate, steepness and proximity to coast; (2) in early-successional, lowland rain forest to proximity to the coast, steepness and cultivation disturbance; (3) in late-successional, lowland forest types to elevation. For coastal/littoral forests, most of the compositional variation (71%) is explained by disturbance and environmental variables that do not covary with island while for both early and late-successional forests there is a higher degree of compositional variation reflecting covariation between disturbance/environment and island.

Conclusions: There are regional similarities, across islands, among littoral/coastal forest types dominated by widespread seawater-dispersed species. The early-successional species that dominate secondary forests are distributed broadly across islands and environmental gradients, consistent with the gradient-in-time model of succession. Among-island differences in early-successional forest may reflect differences in land-use practices rather than environmental differences or biogeographical history. In late-successional forests, variation in composition among islands can be partly explained by differences among islands and hypothesized tight links between species and environment. Disentangling the effects of anthropogenic disturbance history versus biogeographic history on late-successional forest in this region awaits further study.

Abbreviations: GA = Group averaging; MRPP = Multi-response Permutation Procedure; NMS = Non-metric Multidimensional Scaling; pCCA = Partial CCA.

Nomenclature: Smith (1979, 1981, 1985, 1988, 1991); for species not treated by Smith: Yuncker (1959), Whistler (1991), Wagner et al. (1999).

Question: How do reduced levels of summer grazing by reindeer affect the abundance, composition and species richness of mountain plant communities?

Location: Arctic-alpine mountain vegetation 700–850 m a.s.l., Saana Conservation Area, northwestern Finnish Lapland.

Methods: Permanent plots were established in 1990 and resampled in 1999 or 2001. The number of reindeer had considerably declined from the 1980s to the 1990s and we followed the recovery of vegetation. The comparisons between 1990 and 1999/2001 were made at seven sites differing in their original grazing pressure.

Results: At the initially heavily grazed sites, lichen abundances increased, but at the lightly grazed sites the abundances of lichens decreased. Graminoids declined at all sites, but the change seemed to be greatest at the most heavily grazed sites. Forbs increased slightly across all sites. At the species level, lichens and graminoids responded most notably to the reduction of grazing pressure. Individual species responses in shrubs were variable and among forbs, typical species of species-rich Dryas heaths increased. Total species richness increased at all sites and the change was greater at heavily grazed sites. This increase resulted mainly from increased bryophyte and lichen species richness but also from a slight increase in vascular plant species richness.

Conclusions: These results suggest that lichens are the group most responsive to the reduction of heavy summer grazing by reindeer and that lichens and forbs typical in arctic-alpine Dryas heaths are favoured over graminoids under reduced grazing. Heavy grazing decreases overall species richness with the most pronounced effects on bryophyte and lichen species richness. The results support the hypothesis that heavy summer grazing may shift the composition of mountain plant communities towards that of grasslands and show how this shift may be reversed under reduced grazing.

Nomenclature: Hämet-Ahti et al. (1998) for vascular plants; Vitikainen et al. (1997) for lichens and Söderström & Hedenäs (1998) for bryophytes.

In landscapes subject to intensive agriculture, both soil fertility and vegetation disturbance are capable of impacting strongly, evenly and simultaneously on the herbaceous plant cover and each tends to impose uniformity on the traits of constituent species. In more natural and ancient grasslands greater spatial and temporal variation in both productivity and disturbance occurs and both factors have been implicated in the maintenance of species-richness in herbaceous communities. However, empirical data suggest that disturbance is the more potent driver of trait differentiation and species co-existence at a local scale. This may arise from the great diversity in opportunities for establishment, growth or reproduction that arise when the intensity of competition is reduced by damage to the vegetation.

In contrast to the diversifying effects of local disturbances, productivity-related plant traits (growth rate, leaf longevity, leaf chemistry, leaf toughness, decomposition rate) appear to be less variable on a local scale. This difference in the effects of the productivity and disturbance filters arises from the relative constancy of productivity within the community and the diversity in agency and in spatial and temporal scales exhibited by disturbance events. Also, evolutionary responses to disturbances involve minor adaptive shifts in phenological and regenerative traits and are more likely to occur as micro-evolutionary steps than the shifts in linked traits in the core physiology associated with the capacity to exploit productive and unproductive habitats.

During the assembly of a community and over its subsequent lifespan filters with diversifying and convergent effects may operate simultaneously on recruitment from the local species pool and impose contrasted effects on the similarity of the trait values exhibited by co-existing species. Moreover, as a consequence of the frequent association of productivity with the convergence filter, an additional difference is predicted in terms of the effects of the two filters on ecosystem functioning. Convergence in traits selected by the productivity filter will exert effects on both the plant community and the ecosystem while divergent effects of the disturbance filter will be restricted to the plant community.