Diversity responses to climatic factors in plant communities are well understood from experiments, but less known in natural conditions due to the rarity of appropriate long-term observational data. In this paper, we use long-term transect data sampled annually in three natural grasslands of different species pools, soils, landscape contexts and land use histories. Analyzing these specific belt transect data of contiguous small sampling units enabled us to explore scale dependence and spatial synchrony of diversity patterns within and among sites. The 14-year study period covered several droughts, including one extreme event between 2011 and 2012. We demonstrated that all natural grasslands responded to droughts by considerable fluctuations of diversity, but, overall, they remained stable. The plant functional group of annuals showed high resilience at all sites, while perennials were resistant to droughts. Our results were robust to changing spatial scales of observations, and we also demonstrated that within-site spatial synchrony could be used as a sensitive indicator of external climatic effects. We propose the broad application of high-resolution belt transects for powerful and adaptive vegetation monitoring in the future.

Quantifying within-community variability and understanding the related assembly rules are important in developing and assessing grassland restoration. Beta diversity has great potential, revealing mechanisms behind community-level changes in succession. Here, we introduce two simple beta diversity indices: Microhabitat Diversity is the Shannon diversity of patches formed by the locally dominant species, and Multiplet Diversity is the Shannon diversity of subordinate species richness categories detected at a fine scale. Using null models, we tested the biotic filtering effects of dominants on the distribution of subordinates. Based on long-term vegetation monitoring data, we tested the utility of these models in grassland restoration. Sites sown with seed mixture and developing spontaneously were compared and used as test data for exploring the proposed indices. Microhabitat Diversity was larger at spontaneously developing sites, and its local maxima reflected reorganization in the mosaic structure of the community. Species richness categories with zero or one subordinate species were typical in sown grassland, while small 5 cm × 5 cm microsites where 2, 3, or 4 subordinate species co-occured were more frequent in spontaneous succession. Contrary to expectation, a slight convergence of beta diversity measures was revealed after 15 years of succession between passive and active restorations. Microhabitat Diversity and Multiplet Diversity are simple indices that complement existing methods and provide new insights into grassland restoration.

Monitoring designs are often suffering from the inherent non-stationarity of the monitored systems. To overcome this limition, we propose a sampling designs based on high resolution mapping and spatial analyses with double spatial scaling process. Applying for vegetation, we record the presence of plant species along 26 m or 52 m long belt transects of 520 (or 1040) units of 0.5 cm x 0.5 cm contiguous microquadrats. Beta diversity (represented as the diversity of species combinations) is estimated by subsequent computerised samplings from the baseline transect data sets. Beta diversity is scaled with changing resolutions across a range of scales from 5 cm x 5 cm to 5 cm x 500 cm. Second, it is also scaled using moving window. Local maximum of beta diversity is repeatedly calculated in 5 m extent observational windows shifted along the transect with 1 m lag, and the spatial variability of vegetation is visualized by the related beta-diversity profile. Using field example, we demonstrate that beta diversity, when applied with our methodology, is a sensitive indicator, and it can reveal more information than alpha or gamma diversity.

Dominant species form species-specific fine-scale vegetation matrices in grasslands that regulate community dynamics, diversity and ecosystem functioning. The structure of these dynamic microscale landscapes was analyzed and compared between primary and secondary plant communities. We explored fine-scale monitoring data along permanent transects over seven consecutive years. Spatial and temporal patterns of dominant grass species (Festuca valesiaca, Alopecurus pratensis and Poa angustifolia) were analyzed using information theory models. These matrix-forming species showed high spatiotemporal variability in all grasslands. However, consistent differences were found between primary and secondary grasslands in the spatial and temporal organization of the vegetation matrix. Alopecurus pratensis and Poa angustifolia had coarse-scale patchiness with stronger aggregation in secondary grasslands. The spatial patterns of Festuca valesiaca were nearly random in both types of grasslands. Strong associations were observed among the spatial patterns of each species across years, with a stronger dependence in secondary grasslands. In contrast, the rate of fine-scale dynamics was higher in primary grasslands. The complexity of microhabitats within the matrix was higher in primary grasslands, often involving two to three dominant species, while, in secondary grasslands, patches formed by a single dominant species were more frequent. In the spatial variability of small-scale subordinate species richness, significant, temporally consistent differences were found. Higher variability in secondary grasslands suggests stronger and more spatially variable microhabitat filtering. We recommend that grassland management and restoration practices be guided by preliminary information on the spatial organization of primary grasslands. Enhancing the complexity of the matrix formed by dominant species can further improve the condition of secondary grasslands.

Deeper understanding on natural forest dynamics requires long-term data series from forests that have not been affected by human interventions, which are often scarce especially in the Pannonian Bioregion. Unmanaged, but regularly inventoried forest reserves provide an opportunity to fill this gap. The dataset provides repeated inventory data for 233 permanent plots situated in the core areas of six forest reserves selected from primary forests (Kékes), long abandoned forests (Kecskés-galya, Szalafő, Várhegy) and abandoned ones (Hidegvíz-völgy, Nagy Istrázsa-hegy). The sampled old stands represent the four most widespread hilly forest types in Hungary: Carpathian submountainous beech forest; sessile oak-hornbeam forest; Turkey oak and sessile oak forest; downy oak forest. In each plot, stand level attributes included main mensuration variables (canopy closure, stand height, tree density, basal area, living and dead volume, lying deadwood and admixture of the main tree species). Tree level attributes (diameter at breast height, height measured and estimated, crown position in the canopy, health status, tree history of all trees or shrubs having diameter larger or equal to 5 cm) were also measured in two inventories (after 6-16 years) for a total of 6,986 individual trees sampled in all plots. Fagus sylvatica L., Quercus petraea agg., Q. cerris L., Q. pubescens Willd., Carpinus betulus L., Acer campestre L. and Cornus mas L. were the most abundant. The individual tree history classification refers to regeneration ingrowth, growing phase, mortality, decaying phase and disappearance events, that can be used for calculation of various stand dynamics attributes. The dataset offers valuable opportunities for quantifying changes in stand structures and tree population dynamic attributes after the abandonment of management. Inventory data can be integrated with environmental and climatic information to understand the drivers of forest stand dynamics under a changing climate.