Nested-plot Series Research Articles

Scale-dependent patterns and drivers of vascular plant, bryophyte and lichen diversity in dry grasslands of the Swiss inneralpine valleys

The inner-alpine dry valleys of the Swiss Alps are characterized by subcontinental climate, leading to many peculiarities in dry grassland species composition. Despite their well-known uniqueness, comprehensive studies on biodiversity patterns of the dry grasslands in these valleys were still missing. To close this gap, we sampled 161 10-m2 vegetation plots in the Rhône, Rhine and Inn valleys, recording vascular plants, terricolous bryophyte and lichen species, as well as environmental data. Additionally, we tested the scale-dependence of environmental drivers using 34 nested-plot series with seven grain sizes (0.0001–100 m2). We analysed the effects of environmental drivers related to productivity/stress, disturbance and within-plot heterogeneity on species richness. Mean species richness ranged from 2.3 species in 0.0001 m2 to 58.8 species in 100 m2. For all taxa combined, the most relevant drivers at the grain size of 10 m2 were southing (negative), litter (negative), mean annual precipitation (unimodal), gravel cover (negative), inclination (unimodal) and mean annual precipitation (unimodal). For vascular plants the pattern was similar, while bryophyte and lichen richness differed by the opposite relationship to mean annual precipitation as well as negative influences of mean herb layer height, grazing and mowing. The explained variance of the multiple regression model increased with grain size, with very low values for the smallest two grain sizes. While southing and litter had high importance for the fiver larger grain sizes, pH and gravel cover were particularly important at the intermediate grain sizes, and inclination and mean annual precipitation for the two largest grain sizes. The findings emphasize the importance of taxonomic group and grain size for patterns and drivers of species richness in vegetation, consistent with ecological theory. Differences in the diversity–environment relationships among the three taxonomic groups can partly be explained by asymmetric competition that leads to low bryophyte and lichen diversity where vascular plants do well and vice versa. The relatively low alpha diversity of vascular plants in dry grasslands in Swiss inner-alpine valleys compared to similar communities in other parts of the Palaearctic remains puzzling, especially because Swiss stands are often large and well-preserved.

Fine-grain beta diversity in Palaearctic open vegetation: variability within and between biomes and vegetation types

Aims: To quantify how fine-grain (within-plot) beta diversity differs among biomes and vegetation types. Study area: Palaearctic biogeographic realm. Methods: We extracted 4,654 nested-plot series with at least four different grain sizes between 0.0001 m² and 1,024 m² from the GrassPlot database spanning broad geographic and ecological gradients. Next, we calculated the slope parameter (z-value) of the power-law species–area relationship (SAR) to use as a measure of multiplicative beta diversity. We did this separately for vascular plants, bryophytes and lichens and for the three groups combined (complete vegetation). We then tested whether z-values differed between biomes, ecological-physiognomic vegetation types at coarse and fine levels and phytosociological classes. Results: We found that z-values varied significantly among biomes and vegetation types. The explanatory power of area for species richness was highest for vascular plants, followed by complete vegetation, bryophytes and lichens. Within each species group, the explained variance increased with typological resolution. In vascular plants, adjusted R2 was 0.14 for biomes, but reached 0.50 for phytosociological classes. Among the biomes, mean z-values were particularly high in the Subtropics with winter rain (Mediterranean biome) and the Dry tropics and subtropics. Natural grasslands had higher z-values than secondary grasslands. Alpine and Mediterranean vegetation types had particularly high z-values whereas managed grasslands with benign soil and climate conditions and saline communities were characterised by particularly low z-values. Conclusions: In this study relating fine-grain beta diversity to typological units, we found distinct patterns. As we explain in a conceptual figure, these can be related to ultimate drivers, such as productivity, stress and disturbance, which can influence z-values via multiple pathways. The provided means, medians and quantiles of z-values for a wide range of typological entities provide benchmarks for local to continental studies, while calling for additional data from under-represented units. Syntaxonomic references: Mucina et al. (2016) for classes occurring in Europe; Ermakov (2012) for classes restricted to Asia. Abbreviations: ANOVA = analysis of variance; EDGG = Eurasian Dry Grassland Group; SAR = species-area relationship.

Fine-grain beta diversity in Palaearctic open vegetation: variability within and between biomes and vegetation types

Aims: To quantify how fine-grain (within-plot) beta diversity differs among biomes and vegetation types. Study area: Palaearctic biogeographic realm. Methods: We extracted 4,654 nested-plot series with at least four different grain sizes between 0.0001 m² and 1,024 m² from the GrassPlot database spanning broad geographic and ecological gradients. Next, we calculated the slope parameter (z-value) of the power-law species–area relationship (SAR) to use as a measure of multiplicative beta diversity. We did this separately for vascular plants, bryophytes and lichens and for the three groups combined (complete vegetation). We then tested whether z-values differed between biomes, ecological-physiognomic vegetation types at coarse and fine levels and phytosociological classes. Results: We found that z-values varied significantly among biomes and vegetation types. The explanatory power of area for species richness was highest for vascular plants, followed by complete vegetation, bryophytes and lichens. Within each species group, the explained variance increased with typological resolution. In vascular plants, adjusted R2 was 0.14 for biomes, but reached 0.50 for phytosociological classes. Among the biomes, mean z-values were particularly high in the Subtropics with winter rain (Mediterranean biome) and the Dry tropics and subtropics. Natural grasslands had higher z-values than secondary grasslands. Alpine and Mediterranean vegetation types had particularly high z-values whereas managed grasslands with benign soil and climate conditions and saline communities were characterised by particularly low z-values. Conclusions: In this study relating fine-grain beta diversity to typological units, we found distinct patterns. As we explain in a conceptual figure, these can be related to ultimate drivers, such as productivity, stress and disturbance, which can influence z-values via multiple pathways. The provided means, medians and quantiles of z-values for a wide range of typological entities provide benchmarks for local to continental studies, while calling for additional data from under-represented units. Syntaxonomic references: Mucina et al. (2016) for classes occurring in Europe; Ermakov (2012) for classes restricted to Asia. Abbreviations: ANOVA = analysis of variance; EDGG = Eurasian Dry Grassland Group; SAR = species-area relationship.

GrassPlot v. 2.00 – first update on the database of multi-scale plant diversity in Palaearctic grasslands

GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). Following a previous Long Database Report (Dengler et al. 2018, Phytocoenologia 48, 331–347), we provide here the first update on content and functionality of GrassPlot. The current version (GrassPlot v. 2.00) contains a total of 190,673 plots of different grain sizes across 28,171 independent plots, with 4,654 nested-plot series including at least four grain sizes. The database has improved its content as well as its functionality, including addition and harmonization of header data (land use, information on nestedness, structure and ecology) and preparation of species composition data. Currently, GrassPlot data are intensively used for broad-scale analyses of different aspects of alpha and beta diversity in grassland ecosystems.

Dry grasslands of the central valleys of the Alps from a European perspective: the example of Ausserberg (Valais, Switzerland)

Abstract The upper Rhone valley in the Swiss canton of Valais is one of the driest and most continental of the inner-alpine valleys and harbours a rich xerothermic flora. We studied syntaxonomy and ecology of dry grasslands and their species richness patterns. In 2018 we recorded 28 vegetation plots (10 m2) and three nested-plot series of 0.0001 to 100 m2 on the south-facing slopes above the village of Ausserberg. Mean richness of all species ranged from 1.7 on 1 cm2 to 47.3 on 100 m2, with little contribution of bryophytes and lichens. The species-area relationship for total richness closely followed a power function. Modified TWINSPAN yielded a three-cluster solution, which could easily be matched with three orders of the class Festuco-Brometea: Stipo pulcherrimae-Festucetalia pallentis (xeric, rocky), Festucetalia valesiacae (xeric, non-rocky) and Brachypodietalia pinnati (meso-xeric). The subdivision of the xeric types into two orders is new for Swiss dry grasslands, where these types up to now had been joined in a single alliance Stipo-Poion within the Festucetalia valesiacae.

Diversity loss in grasslands due to the increasing dominance of alien and native competitive herbs

The increasing dominance of competitive plant species may reduce species richness of plant communities. Yet, species richness may depend on spatial scale and the alien versus native status of the dominant species. To explore the dominance effects of alien versus native species on species richness, we sampled semi-natural grasslands in southwestern Poland. We established 100 m2 squares at different grassland sites, and in two opposite corners we placed two series of five nested plots (0.001, 0.01, 0.1, 1 and 10 m2), in which we recorded all vascular plant species. Next, we selected squares with a strongly dominant plant in one corner (high-dominance series) and with no strong dominant in the opposite corner (low-dominance series). The number of species per plot and the slopes of the species–area curves fitted to each nested-plot series were used to assess whether the alien vs. native status of the dominant species influences species-richness pattern across scales. We found a significantly lower number of species in the high-dominance series than in the low-dominance series, regardless of the alien versus native status of the dominant species. The slopes of the species–area curves indicated that the rate of species accumulation with increasing area was faster in the high-dominance series than in the low-dominance series; however, this pattern did not depend on the alien vs. native status of the dominants. Our study confirms that increasing dominance is linked to a decline in species richness, but reveals that alien dominants do not have a stronger impact than native dominants.

Exploring the drivers of vascular plant richness at very fine spatial scale in sub-Mediterranean limestone grasslands (Central Apennines, Italy)

Secondary dry grasslands in Europe can host high levels of vascular plant richness at small spatial scales. However, in Southern Europe their biodiversity patterns are largely unexplored. In this work, we aim at: (i) estimating plant species richness patterns at very fine scales in montane dry grasslands, on limestone bedrock, in Abruzzo Lazio and Molise National Park (Central Apennines, Italy); (ii) assessing the most important physical and edaphic drivers of biodiversity patterns at multiple plot sizes. We used randomly placed nested-plot series where we measured alpha-diversity at three different plot sizes (1 m2, 0.1 m2 and 0.01 m2) and within-plot beta-diversity (as expressed by the slope of the species-area curve across plot sizes). Variable selection was performed by means of Random Forests. Relationships between selected variables and diversity measures were then assessed using Regression Trees, Linear and Generalized Linear Models. Overall, results pointed to topographically-controlled edaphic factors (soil pH and silt fraction) as the main drivers positively influencing alpha-diversity at all spatial scales, with a positive effect of rock cover and slope inclination at smaller spatial grains. Beta-diversity was positively influenced by rock cover. We suggest that high-pH, steep and/or rocky sites feature higher species richness because they lack competitive grass species. Our results are in agreement with previous works underlining the importance of less productive habitats for the conservation of secondary grassland biodiversity.

GrassPlot – a database of multi-scale plant diversity in Palaearctic grasslands

GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database sPlot. Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board.

Scale-dependent effects of grazing on the species richness of alkaline and sand grasslands

Extensively managed pastures harbour rare and endangered species and have a decisive role in maintaining grassland biodiversity. Traditional herding of local robust cattle breeds is considered as a feasible tool for preserving these habitats. We studied the scale-dependent effects of grazing on the species richness and composition of three dry grassland types in the Great Hungarian Plain: Achilleo setaceae-Festucetum pseudovinae and Artemisio santonici-Festucetum pseudovinae alkaline grasslands, and Potentillo arenariae-Festucetum pseudovinae sand grassland. We asked the following questions: (1) Does extensive grazing have a scale-dependent effect on plant species richness of alkaline and sand grasslands? (2) How does grazing affect the proportion of specialists, generalists and weeds in the three grassland types? We sampled ten sites of each grassland type, including five extensively grazed and five non-grazed sites (altogether we had 30 sites). We used a series of nested plots each consisting of 10 plots from the size of 0.01 m² to 16 m². We revealed that grazing has contrasting effects in the three grassland types, and had a considerable effect on their species richness even at small scales. In both alkaline grassland types, total species richness was overall higher in grazed plots but it increased in a similar manner for both ungrazed and grazed habitats across plot sizes. Small-scale heterogeneity likely due to the uneven distribution of grazing, trampling and defecation together with mitigated rate of competition allowed more species to co-exist even at small scales in grazed alkaline grasslands. Grazing increased the richness of specialists, but likely due to the salt stress, establishment of weeds was hampered. Open gaps formed by trampling likely supported the establishment of several specialist species such as Plantago tenuiflora and Puccinellia limosa which are typical to open alkali grasslands. Contrary, in sand grasslands, we did not detect any effect of grazing on total species richness, likely due to the adverse effect of grazing on the species richness of specialists and weeds. In contrast with the former findings we detected significantly higher species richness in 0.01 m² and 0.0625 m² plots in the grazed sand grasslands, but found no differences at larger scales. Whilst species richness of specialists was significantly decreased, richness of weeds was increased by grazing. Decrease in the specialist species richness was likely due to the lack of their evolutionary adaptation to grazing. Degradation caused by grazing and trampling together with the propagule pressure from the neighbouring anthropo-genic habitats resulted in an increased richness of weeds in the grazed sites.

Scale- and taxon-dependent patterns of plant diversity in steppes of Khakassia, South Siberia (Russia)

The drivers of plant richness at fine spatial scales in steppe ecosystems are still not sufficiently understood. Our main research questions were: (i) How rich in plant species are the natural steppes of Southern Siberia compared to natural and semi-natural grasslands in other regions of the Palaearctic? (ii) What are the main environmental drivers of the diversity patterns in these steppes? (iii) What are the diversity–environment relationships and do they vary between spatial scales and among different taxonomic groups? We sampled the steppe vegetation (vascular plants, bryophytes and lichens) in Khakassia (Russia) with 39 nested-plot series (0.0001–100-m2 plot size) and 54 additional 10-m2 quadrats across the regional range of steppe types and measured various environmental variables. We measured β-diversity using z-values of power-law species–area relationships. GLM analyses were performed to assess the importance of environmental variables as predictors of species richness and z-value. Khakassian steppes showed both high α- and β-diversity. We found significant scale dependence for the z-values, which had their highest values at small spatial scales and then decreased exponentially. Total species richness was controlled predominantly by heat load index, mean annual precipitation, humus content and soil skeleton content. The positive role of soil pH was evident only for vascular plant species richness. Similar to other studies, we found that the importance of environmental factors strongly differed among taxonomic groups and across spatial scales, thus highlighting the need to study more than one taxon and more than one plot size to get a reliable picture.

Patterns and drivers of phytodiversity in steppe grasslands of Central Podolia (Ukraine)

We asked: (i) Which environmental factors determine the level of α-diversity at several scales and β-diversity in steppic grasslands? (ii) How do the effects of environmental factors on α- and β-diversity vary between the different taxonomic groups (vascular plants, bryophytes, lichens)? We sampled nested-plot series ranging from 0.0001 to 100 m2 and additional 10-m2 plots, covering different vegetation types and management regimes in steppes and semi-natural dry grasslands of Central Podolia (Ukraine). We recorded all terricolous taxa and used topographic, soil, land-use and climatic variables as predictors. Richness-environment relationships at different scales and across taxonomic groups were assessed with multimodel inference. We also fitted power-law species-area relationships, using the exponent (z value) as a measure of β-diversity. In general, the richness values in the study region were intermediate compared to those known from similar grasslands throughout the Palaearctic, but for 1 cm2 we found seven species of vascular plants, a new world record. Heat index was the most important factor for vascular plants and bryophytes (negative relation), while lichen diversity depended mainly on stone and rock cover (positive). The explanatory power of climate-related variables increased with increasing grain size, while anthropogenic burning was the most important factor for richness patterns at the finest grain sizes (positive effect). The z values showed more variation at the finest grain sizes, but no significant differences in their mean between scales. The results highlight the importance of integrating scale into ecological analyses and nature conservation assessments in order to understand and manage biological diversity in steppe ecosystems.

Database Species-Area Relationships in Palaearctic Grasslands

The Database Species-Area Relationships in Palaearctic Grasslands (GIVD ID EU-00-003) is an initiative of the European Dry Grassland Group (EDGG) and primarily functions as repository for all data sampled during the EDGG Research Expeditions. During these expeditions two types of highly standardised sampling of dry grassland vegetation in the Palaearctic realm are carried out: (i) nested-plot sampling on squares of 0.0001, 0.001, 0.01, 0.1, 1, 10, and 100 m2; (ii) additional normal releves of 10-m2 plots. For all plot sizes, the terricolous vascular plants, bryophytes, and lichens are recorded that are superficially present (shoot presence). Additionally, for all 10-m2 plots species cover is estimated directly in percent and a wide range of topographic, soil, and land use parameters is determined. Five such expeditions have been carried out so far (2009: Transylvania, Romania; 2010: Central Podolia, Ukraine; 2011: NW Bulgaria; 2012a: Sicily, Italy; 2012b: N Greece). Additionally, the database contains similar nested-plot data from published and unpublished sources covering dry grasslands in Czech Republic, Estonia, Germany, the Netherlands, Russia, Sweden, Switzerland, and the United Kingdom. The vegetation classes Festuco-Brometea and Koelerio-Corynephoretea prevail, but there are also some data from Mediterranean grasslands. Presently, the database contains data from 402 nested-plot series plus 325 separate 10m2 plots. Data from future EDGG Expeditions will be added and we are open to add other nested-plot data from any type of grassland in the Palaearctic. This huge collection of nested-plot data is very valuable for the study of species-area relationships (SARs) in grasslands and how their function types and parameters (e.g. the z-values of the power-law SARs) depend on grassland type, region, and taxon considered. The 10-m2 plots from the EDGG Expeditions (from inside and outside the nested plots) are an important contribution to consistent large-scale classifications as they were sampled by using a uniform plot size, recording also non-vascular plants, and consistently determining a set of plot-based plot-based environmental variables. The dataset will be available to the scientific public based on individual arrangements.

Sampling-Design Effects on Properties of Species-Area Relationships – A Case Study from Estonian Dry Grassland Communities

Despite widespread use of species-area relationships (SARs), dispute remains over the most representative SAR model. Using data of small-scale SARs of Estonian dry grassland communities, we address three questions: (1) Which model describes these SARs best when known artifacts are excluded? (2) How do deviating sampling procedures (marginal instead of central position of the smaller plots in relation to the largest plot; single values instead of average values; randomly located subplots instead of nested subplots) influence the properties of the SARs? (3) Are those effects likely to bias the selection of the best model? Our general dataset consisted of 16 series of nested-plots (1 cm2–100 m2, any-part system), each of which comprised five series of subplots located in the four corners and the centre of the 100-m2 plot. Data for the three pairs of compared sampling designs were generated from this dataset by subsampling. Five function types (power, quadratic power, logarithmic, Michaelis-Menten, Lomolino) were fitted with non-linear regression. In some of the communities, we found extremely high species densities (including bryophytes and lichens), namely up to eight species in 1 cm2 and up to 140 species in 100 m2, which appear to be the highest documented values on these scales. For SARs constructed from nested-plot average-value data, the regular power function generally was the best model, closely followed by the quadratic power function, while the logarithmic and Michaelis-Menten functions performed poorly throughout. However, the relative fit of the latter two models increased significantly relative to the respective best model when the single-value or random-sampling method was applied, however, the power function normally remained far superior. These results confirm the hypothesis that both single-value and random-sampling approaches cause artifacts by increasing stochasticity in the data, which can lead to the selection of inappropriate models.