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Ellenberg indicator values (EIV) are widely used in vegetation ecology, but the values for many species in Southeastern Europe are not available due to incomplete knowledge of their ecology: it is therefore of paramount importance to estimate missing values in existing databases. The entire EIV set for a single species can be missing or a single EIV can be missing for species for which other indicator values are available. Our aim here is to provide a simple method to impute missing values for species who have missing data in a single or multiple EIV. For this purpose, we adopt a multiple imputation procedure and compare a number of imputation methods on the basis of two datasets: i) “indices”, the set of 9 Ellenberg indicators taken from literature, available for 10,824 species and ii) “vegetation”, a set describing the physical and climatic characteristics (Light, Temperature, Continentality, Soil moisture, Nitrogen, Soil pH, Hemeroby index, Humidity, Organic_matter) of 29,935 relevés from Southeastern Europe where at least one tree species is present. The imputation methods we considered are: k-Nearest Neighbour, multiple linear regression (with or without collinearity correction), Reprediction Algorithm, Weighted Averaging (WA) and Weighted Averaging Partial Least Squares (WAPLS) regression. The different methods of imputation were compared by looking at the output produced and its deviation from the “true” observed values for a set of species with known EIVs. We have considered a set of species with known EIVs and proceeded to multiple imputation using the methods above; as a measure of performance we adopted the mean squared error (MSE) estimate, and expert judgement of ecological consistency. Models based on Regression and k-Nearest Neighbour seem to outperform the others. On the contrary, Reprediction algorithm in its different forms: produced less satisfactory results.Imputation of missing values is generally based on expert knowledge or on some variant of weighted averaging (also known as Hill’s method). Here we show that other methods may be more effective and should be appropriately considered by vegetation scientists, since those may allow the application of EIVs in other biogeographic regions.

Climatic variables are useful but often weak predictors of plant functional trait variation across ecosystems. Here the authors investigate how assigning plant communities to a habitat hierarchy improves the explanatory power of climate-trait relationships at the continental scale.

In this Report, three previously published nomenclatural proposals are discussed, and recommendations on acceptance or rejection of these proposals are provided. The proposals concern the following syntaxa: Berberidion Braun-Blanquet 1950, Aceretalia pseudoplatani Moor 1976 and Festucetalia valesiacae Braun-Blanquet et Tüxen ex Braun-Blanquet 1950. Abbreviations: CCCN = Committee for the Change and Conservation of Names; GPN = Working Group for Phytosociological Nomenclature; ICPN = International Code of Phytosociological Nomenclature.

In this research, we analyzed functional plant traits and life forms of plant species growing on five forest gaps in the Dinaric fir–beech forest in Slovenia. The forest gaps were created as a result of natural disturbances. We selected 18 functional plant traits, whose values were obtained from the BiolFlor database. With the help of the JUICE program, we calculated the frequency of occurrence in individual forest gaps for each functional plant trait. Then, we calculated Spearman’s correlation coefficient at p < 0.05 between the occurrence of individual functional plant traits and each forest gap. Individual locations differed statistically in 87 categories of plant functional traits. The forest gap Nad Drago differed statistically from the other forest gaps in 16 functional plant traits. Forest gaps are mainly colonized by perennials and herbaceous perennials and chamaephytes. These are plant species that begin to flower in June and July, bloom for two or three months, and are pollinated by insects, mainly hover flies and wild bees. This colonizing plant species reproduce via seeds or spores and vegetatively. Furthermore, birds and forest mammals are the vectors of fruit and seed dispersal.

Aristolochia clematitis L. is a perennial herbaceous plant distributed throughout Europe, Asia Minor and Caucasus. It has been used as a medicinal plant since antiquity but not in recent times because it contains poisonous aristolochic acid, causing progressive kidney failure. The aim of this work was to study Aristolochia clematitis ecology on the basis of vegetation plots from the European Vegetation Archive, and to investigate the differentiation of its ecological niche using a co-occurrence-based measure of ecological specialization (ESI). The ecological niche was studied on three spatial scales: on the entire distribution area, its differentiation across 200 × 200 km grid cells and the differences between three central and three marginal regions. Our results suggest that Aristolochia clematitis has a very broad ecological niche occurring in a range of different habitats and climatic conditions, with a trend of a niche width decrease with the distance from the geographical center. The plant prefers more stable communities with less anthropogenic influence moving towards the margin of the distribution area. Specialization towards the marginal area is a result of evolutionary history, which refers to the recent anthropogenically induced spread from its original home range. A high incidence of Aristolochia clematitis in the vegetation of arable lands and market gardens as well as anthropogenic herbaceous vegetation in the distribution center corresponds to the geographical incidence of Balkan Endemic Nephropathy.

Wetland forests and scrub (WFS) are conditioned by the strong impact of water. They consist of various vegetation types, depending on many factors such as type and duration of flooding, water table level and its fluctuation, river current strength, substrate ability to retain water, etc. WFS vegetation has been insufficiently studied in the Balkan Peninsula, especially in Bosnia and Herzegovina. By means of numerical classification, we aimed to classify Western Balkans WFS at the alliance level, and to identify the main underlying ecological gradients driving the variation in species composition. The dataset containing all published and available unpublished relevés from Slovenia, Croatia and Bosnia and Herzegovina was first classified using the EuroVegChecklist Expert System in Juice software in order to assign the corresponding class to each of the relevés. Relevés were subsequently analyzed within each of the four WFS classes (Alno glutinosae-Populetea albae, Salicetea purpureae, Alnetea glutinosae and Franguletea). Cluster analysis resulted in eight alliances, Salicion albae, Salicion triandrae, Salicion eleagno-daphnoidis, Alno-Quercion, Alnion incanae, Alnion glutinosae, Betulion pubescentis and Salicion cinereae, while one cluster could not be assigned with certainty. Edafic factors were found to be the most important factors determining the floristic composition and syntaxa differentiation of WFS in the study area.

Aims: The accurate classification of habitats is essential for effective biodiversity conservation. The goal of this study was to harness the potential of deep learning to advance habitat identification in Europe. We aimed to develop and evaluate models capable of assigning vegetation‐plot records to the habitats of the European Nature Information System (EUNIS), a widely used reference framework for European habitat types. Location: The framework was designed for use in Europe and adjacent areas (e.g., Anatolia, Caucasus). Methods: We leveraged deep‐learning techniques, such as transformers (i.e., models with attention components able to learn contextual relations between categorical and numerical features) that we trained using spatial k‐fold cross‐validation (CV) on vegetation plots sourced from the European Vegetation Archive (EVA), to show that they have great potential for classifying vegetation‐plot records. We tested different network architectures, feature encodings, hyperparameter tuning and noise addition strategies to identify the optimal model. We used an independent test set from the National Plant Monitoring Scheme (NPMS) to evaluate its performance and compare its results against the traditional expert systems. Results: Exploration of the use of deep learning applied to species composition and plot‐location criteria for habitat classification led to the development of a framework containing a wide range of models. Our selected algorithm, applied to European habitat types, significantly improved habitat classification accuracy, achieving a more than twofold improvement compared to the previous state‐of‐the‐art (SOTA) method on an external data set, clearly outperforming expert systems. The framework is shared and maintained through a GitHub repository. Conclusions: Our results demonstrate the potential benefits of the adoption of deep learning for improving the accuracy of vegetation classification. They highlight the importance of incorporating advanced technologies into habitat monitoring. These algorithms have shown to be better suited for habitat type prediction than expert systems. They push the accuracy score on a database containing hundreds of thousands of standardized presence/absence European surveys to 88.74%, as assessed by expert judgment. Finally, our results showcase that species dominance is a strong marker of ecosystems and that the exact cover abundance of the flora is not required to train neural networks with predictive performances. The framework we developed can be used by researchers and practitioners to accurately classify habitats. [ABSTRACT FROM AUTHOR]

This study presents the results of an in-depth study on landscape changes over the last two centuries in the region of Bela krajina, south-eastern Slovenia. Since this region is situated along the Slovenian–Croatian border, immigration and emigration are permanent fixtures in the region. Due to historical reasons, population structure and land use changes occurred. With regard to these processes, two case studies were selected: settlements of Adlešiči and Bojanci. Adlešiči is a village mainly inhabited by farmers of catholic religion. Bojanci was colonized by Orthodox Uskoki, i.e. refugees from Ottoman Empire who become Habsburg soldiers who lived a military life and had different attitude towards land cultivation. Landscapes in these two settlements have its own distinctive patterns contrasting to each other in the land use, showing historically distinctive cultural landscapes. The study aimed to interpret the development of cultural landscapes in these settlements by analysing the land use changes and identifying the factors that influenced it. Even though these sites have different management regimes, they are both affected by difficult karst terrain and isolation. The results confirmed the land abandonment and overgrowth of agricultural land in both case studies, however, at different rates.

In this study, the objects of research were circular and concave karstic depressions, called sinkholes or dolines. All these negative topographic anomalies were previously recognized as safe havens for cool-adapted species on karstic plateaus. However, the high geodiversity of doline landforms on karst plateaus does not ensure that all dolines are really safe havens that should be considered for conservation status. We propose the use of indicator species to identify different dolines' “sections” and their overall types to identify dolines with high conservation value for cool-adapted species. We aimed to divide dolines into landform-vegetation units (LVU) according to basic geomorphic characteristics and indicator plant species.We carried out intensive sampling of vegetation plots (n = 286) across 10 dolines of different geomorphology ranging from 20 m to 100 m in diameter and from 2 m to 20 m in depth. Each doline was classified into a maximum of four LVUs: bottom, lower slope, upper slope and top. Vascular plants were used as a proxy for ecosystem biodiversity and indicator of ecological conditions. The diversity of vascular plant communities was sampled along N–S transects from one side of the doline over the bottom to the other side. Geodiversity parameters of individual dolines were calculated using a high-resolution digital elevation model (LiDAR / Light Detection And Ranging) and their significance was established by permutation test in CCA (Canonical Correlation Analysis). The floristic gradient was established by the first axis of PCoA (Principal Coordinates Analysis) and shows the species turn-over along the trajectory. Discrete plant communities were determined by TWINSPAN (Two-Way Indicator Species ANnalysis) classification. Based on this analysis, transects were disintegrated into four LVUs. Communities within LVUs were compared by Ellenberg indicator values and according to habitat preference of species. The indicator (also termed diagnostic) plant species were calculated by fidelity measure and related to ecological conditions along transects.We found that all four LVUs appear only in dolines that are at least 13.5 m deep and those can serve as a good safe haven for cool-adapted species in foreseen climatic change. We also confirmed that doline depth is the most important factors influencing the plant community composition. The results can be directly transformed to other karst regions (karst plateaus) with the same zonal vegetation, but calibration is needed in case of their application in other areas.

Sand dunes are one of the critically endangered habitats in Europe. This vegetation type is under a strong anthropogenic influence. Its natural value is very high since many plant species with a narrow distribution are found there. The classification of Serbian sand-dune vegetation and the status of the described associations has not been validated by numerical analyses. This research presents an evaluation of sand-dune vegetation in Serbia on the basis of literature data, as well as new releves. Psammophytic vegetation in Serbia was classified into two alliances, annual and ruderal Bassio laniflorae-Bromion tectori and perennial Festucion vaginate. The aim of this research was the classification of the alliance Festucion vaginatae, perennial, drought-tolerant, tussock-forming vegetation on sand. As proposed by OptimClass, Jaccard distance and flexible beta data (β=-0.25) were used for the classification. Classification results were confirmed by detrended correspondence analysis (DCA) ordination. The result of the classification established that only two associations, Alysso gmelini-Festucetum vaginatae and Festucetum vaginatae, are present in Serbia. These associations are divided into groups that mostly correspond to traditional subassociations. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. III43002: Biosensing technology and global systems for continuous research sand integrated management of ecosystems]

We analyzed plants and their traits in dolines, which are characteristic enclosed terrain depressions on carbonate (karst) plateaus. These landforms range from a few meters to over 100 m in diameter, their depth generally varying from a few meters to a few tens of meters. A pronounced ecological gradient can be found from the bottom to the top, starting from humid, cool and shaded bottoms to sunny, dry and warm slopes and tops. We sampled dolines of various depths and analyzed the distribution of plant species on the gradient and how this distribution is reflected in plant traits: chorotypes, life forms, plant architecture and strategies. We used the transect method and sampled the floristic composition from the doline bottom to the top. We collected information about plant traits from various literature sources. The results show life forms and plant architecture explain this gradient well and, to a lesser extent, also chorotypes, but functional strategies have a low explanatory power. Life forms and plant architecture are the result of adaptation of species to the environment, and chorotypes are defined as species with an overlapping geographical distribution pattern due to their distribution and environmental histories. Functional strategies, which have evolved to enable plants to succeed in various environments, unexpectedly have a low explanatory power.

We studied species turnover and changes of ecological conditions and plant strategies on forest gaps created by natural disturbances (sleet, windthrow). We studied five forest gaps and a control plot within in the Dinaric silver fir-beech forest in the southern part of Slovenia. Forest gaps varied in age and size. The total number of recorded species in gaps was 184, with the highest number (106) at the largest forest gap and with the 58 species at the control locality in a juvenile beech forest. Forest gaps were predominantly colonised mostly by species of understory, forest margins, and forest clearings. The species presented in all forest gaps are representatives of the understory of beech forests. Species colonising forest gaps prefer habitats with more sunlight, medium wet to dry soil, and are tolerant to high daily and seasonal temperature fluctuations. In gaps, the community of plant species has a competitive strategy, which is also complemented with a stress-tolerator strategy. We determined that a forest gap represents a significant habitat patch, especially for those plant species which were not present there before.

Since grasslands provide many ecosystem services, there are often different opinions on their management (e.g., agronomy, ecology, botany). Multidisciplinary research on this topic is therefore needed. This article focuses on the impact of ecological conditions, functional groups, ecological strategies, floristic composition (through habitat preference of species), major floristic gradients (presented as first two NMDS axes), and the management on forage quality. We estimated the forage quality using indicator values. All of the available vegetation plots in the region on wet and mesic meadows, managed pastures, and tall-herb meadow/pasture fringes on deeper or shallower soils (i.e., grasslands) were collected, organized in a database, and elaborated according to standard procedure. We used a widely accepted grassland classification system that uses floristic composition to define grassland types. Based on an NMDS ordination diagram and according to functional groups, ecological strategies, and habitat preferences (behavior of species) and management, we defined three major groups: mesic meadows (mowed), wet meadows (mowed), and pastures (grazed). We correlated all groups’ functional groups, ecological strategies, habitat preferences (behavior of species), major floristic gradients, management, and forage quality. We found that forage quality mainly depends on moisture conditions and that nutrients and grazing are less important. Within the grasslands under consideration, mesic meadows and mesic pastures have the highest forage quality.