Indicator Values Research Articles

The carbonized materials structure levels from molecular to macrostructure is analyzed. A study was conducted to find correlations between the granular carbonized materials electrical resistance and other substance physicochemical properties. It is proven theoretically and experimentally that determining the electrical resistance for a granular material, rather than a finely ground sample, is a more informative indicator for reflecting the microstructural features of the material, its reactivity, strength, and clarifying the carbonization conditions. A method is developed for determining the granular materials electrical resistance in the rotating drum interelectrode space, with determination of the indicator value in the cold and hot state for the substance under investigation. An indicator of the granular matter electrical resistance based on the heating time to 670 °C at a drum power supply constant voltage is introduced. Calculated dependencies is obtained for predicting, based on experiment results, some quality indicators for such a carbonized material as metallurgical coke: structural strength, apparent density, reactivity, gasification degree, and electrical resistivity. Better correlations is achieved with these indicators than with the standard electrical resistance on the "micropress" device, which indicates a better reflection of the carbonized materials substance supramolecular structure.

The object of the study is the process of energy transition to renewable energy sources (RES) at the enterprise or regional level, aimed at replacing traditional carbon-based sources of electricity. One of the most problematic issues is the insufficient consideration of energy security factors in existing forecasting models, which leads to risks of electricity shortages, especially under conditions of RES intermittency and geopolitical challenges such as military attacks or import dependence. A literature review showed that existing models do not account for dynamic constraints in the implementation of RES, which limits their practical applicability for ensuring power system resilience. In the course of the research, numerical modeling methods were used, in particular an adaptation of the logistic growth equation with an integrated dynamic security factor Sb(t). This makes it possible to fill the gaps in existing models with regard to risk assessment and ensuring system stability. The obtained logistic model predicts the energy transition with RES reaching a 68% share in 24 years for a typical region without compromising security. This is due to the fact that the proposed model has such features as the integration of the coefficient of energy transition rate (CETR) and the dynamic constraint Sb(t), which adapts to changes in demand and reserve. This allows identifying the potential to increase system resilience through the optimal balance of RES and traditional sources during the transition. As a result, it becomes possible to achieve such indicator values as a 68% share of RES, owing to the model’s flexibility to local conditions (variations of ρ, γ, k) and the consideration of worst-case scenarios (CF.min). Compared with similar known models, this provides advantages such as adaptability to regional risks, more accurate forecasting of the transition rate, and reduction of blackout probability. This is particularly relevant for vulnerable power systems, both in Ukraine and worldwide.

Abstract Metabolic interactions between microbiomes and algal hosts within the phycosphere of marine macroalgae are drawing increasing attention due to their roles in food webs, global nutrient cycles, industries, and their potential as food resources. However, these relations remain poorly understood. In this study, 43 marine macroalgae, including red, brown, and green algae, were collected from the coastal areas of Korea. We identified the bacterial communities within the loosely and tightly attached environments (LAEs and TAEs, respectively) of the phycosphere, along with those in the surrounding seawater, using 16S rRNA gene sequencing. β -Diversity analysis revealed significant differences between the bacterial communities among the three, with minimal variation related to sampling location or algal color. Indicator value analysis identified Pseudoalteromonas (in the LAE and TAE), Psychromonas (in the LAE), Marinomonas (in the LAE), and Litorimonas (in the TAE) as the dominant taxa in the phycosphere, in contrast to seawater. Network analysis suggested positive correlations among taxa within the same environments and negative correlations between those in the LAE and TAE, highlighting their distinct ecological conditions. Analysis using the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States and Kyoto Encyclopedia of Genes and Genomes pathways revealed functional variations between the phycosphere- and seawater-residing microbes. The microbial taxa–function relationships were assessed through Spearman’s rank-order correlation. Additionally, bacterial species belonging to the core taxa were isolated and their genomes sequenced. Their metabolic traits were analyzed via bioinformatics, recognizing key metabolic features essential for symbiotic interactions with algal hosts and survival within the phycosphere. The findings of this study advance our understanding of the marine algal phycosphere microbiome by detailing the metabolic characteristics of potential keystone species.

Leaf nitrogen and chlorophyll, crucial crop status indicators, enable precision fertilization through rapid monitoring. This study investigated greenhouse tomatoes subjected to varying nitrogen concentrations in nutrient solutions. Hyperspectral data from leaves across ten nitrogen levels, different growth stages, and leaf positions were integrated with synchronously measured nitrogen and chlorophyll contents. The analysis systematically revealed differences in these indicators under nitrogen stress at various growth stages and leaf positions. The 12-step “coarse–fine–optimal” feature wavelength selection strategy was proposed to identify sensitive spectral bands. The PLSR model was established with a strong predictive performance. Using the optimal model, indicator values for each pixel were retrieved and visualized via pseudocolor imaging, illustrating the distribution of physiological parameters at different scales and growth stages, and aiding in the interpretation of nitrogen stress responses. This study provides a scientific basis for optimizing nitrogen fertilization strategies, contributing to improved tomato yield and quality, reduced environmental impact, and the sustainable development of facility-based agriculture.

Disclosure: S.J. Russell: Beta Bionics. R.R. Selagamsetty,: Beta Bionics. C.S. Balliro: Beta Bionics. E. Damiano: Beta Bionics.Background: The iLet bionic pancreas is an automated insulin delivery system that is initialized with only body weight. The only user input is meal announcements without carbohydrate counting. Meals and snacks are announced as a type (Breakfast, Lunch, or Dinner) and a relative size for that type (Usual for me, More, or Less). The iLet then autonomously determines the size of meal doses. All basal and correction insulin is determined autonomously by the iLet, which adapts continuously to changing insulin needs. The only input from the health care provider is the glucose target profile. Objective: The objective of this analysis was to assess the association between the number of meals announced by the user per day on one hand, and the frequency of user interaction with the iLet (determine by number of swipes to unlock the iLet) on the other, on continuous glucose monitoring (CGM) outcomes during real-world use of the iLet bionic pancreas by adults (≥18 years of age) during the first 18 months after FDA clearance. This analysis was undertaken with the goal of providing users and health care providers information they can use to obtain the best glycemic control from the iLet. Methods: Commercial users of the iLet who had a pre-iLet HbA1c value available and at least 3 weeks of iLet data in the cloud (n=5,987) were included in the analysis. Glucose management indicator (GMI) values and percentage of time in ranges (%70-180 mg/dl, %<70 mg/dl, and %<54 mg/dl) were calculated from all available CGM data. Users were classified according to the average number of meal announcements per day (MPD; from <0.5 to ≥4.5 per day in 0.5 meal increments) and separately according to the number of swipes to unlock the (STU; ≤4, 4-<13, and ≥13 swipes to unlock per day). Results: Mean baseline HbA1c was 8.6%; mean iLet GMI was 7.2%. Groups with <2.5 MPD had higher GMI and lower %70-180 mg/dl than those with ≥2.5 MPD. Groups with ≥2.5 to <4.5 MPD all had similar outcomes, with lower GMI and higher %70-180 mg/dl than groups with <2.5 MDP. There was little difference in %<70 mg/dl and %<54 mg/dl from <0.5 to <4.5 MPD. The ≥4.5 MPD group had lower GMI and higher %70-180 mg/dl than others, but it also had higher %<70 mg/dl and %<54 mg/dl. GMI and %<54 mg/dl was similar for all levels of STU. Higher STU was associated with higher %70-180 mg/dl and higher %<70 mg/dl. Discussion/Conclusion: In users of the iLet bionic pancreas the best outcomes were achieved by those announcing 2.5 to <4.5 MPD. This may correspond to typical numbers of meals and snacks consumed by users. Announcement of ≥4.5 MPD was associated with lower GMI and higher %70-180 mg/dl, but also higher %<54 mg/dl. Users announcing ≥4.5 MPD may be announcing “ghost” meals to obtain correction insulin, which risks “stacking” on top of iLet-determined correction doses and may lead to increased hypoglycemia. Higher STU was associated with higher %70-180 mg/dl and %<70 mg/dl but little difference in GMI and %<54 mg/dl.Presentation: Monday, July 14, 2025

Phytoindication represents a long-established ecological approach; however, its conceptual basis remains contested, particularly concerning whether it is merely a surrogate for measuring environmental factors or a distinct method for assessing biotic system responses. In this study, we analysed vegetation communities of the sandy terrace in the Dnipro-Oril Nature Reserve (Ukraine) using ecological indicator values, naturalness, and hemeroby indices. The Dnipro-Oril Nature Reserve provides an ideal setting for this study, as it integrates strong natural gradients of soil moisture, nutrient availability, and topography with pronounced anthropogenic influences from the surrounding industrial landscape. This allows the assessment of both natural and human-driven components of ecological variability within a single system. A dataset of 1079 relevés was collected and classified into 24 associations. Multivariate analyses were applied to reveal different aspects of vegetation–environment relationships: MANOVA was used to assess whether plant associations differed significantly in their ecological indicator profiles, CCA to identify the main gradients of species composition constrained by environmental factors, and partial CCA to isolate the specific patterns of vegetation response attributable to individual predictors while controlling for covariates. We found that the indicator values were not independent but strongly intercorrelated, reflecting integrated biotic responses rather than methodological artefacts. This was confirmed by consistent ecological interpretation of the principal component structure and the concordance between ordination patterns and vegetation classification results. Two primary gradients were identified: a natural gradient, which combines soil moisture and nutrient availability with decreasing light, temperature, continentality, and soil pH; and an anthropogenic gradient, represented by the hemeroby–naturalness axis. The interplay of these gradients offers a comprehensive explanation for vegetation structure across various spatial scales, with natural factors shaping community types and anthropogenic influences exerting broader, less specific effects due to their diffuse impact across multiple plant associations. Our findings reveal a novel conceptual perspective, supporting the view that phytoindication is a unique ecological tool for assessing the integrated response of plant communities to environmental drivers, including both natural and anthropogenic gradients, rather than a simplified or less precise substitute for instrumental measurements. Nevertheless, the use of phytoindication does not eliminate the need for instrumental measurements in situations requiring precise quantification of specific physical or chemical environmental parameters. The correlated structure of indicator values revealed in this study demonstrates that phytoindication patterns are specific to each landscape. Therefore, comparative assessments across regions or time periods should be based on the correlation patterns of indicator values rather than their absolute scores.

Connectivity between lakes and tributaries is essential for freshwater ecosystem health. However, integrated studies of macroinvertebrate assemblages across these interconnected systems remain limited in tropical Africa. This study examined the structure of the macroinvertebrate community and the ecological health of Lake Kivu and its tributaries using multimetric indices. Macroinvertebrates were collected from 23 lake sites and 53 tributary sites between 2010 and 2022. Diversity indices were quantified, community differences were tested using permutational multivariate analysis (PERMANOVA), whereas Indicator value analysis (Indval) was performed to identify ecosystem-taxa associations. The ecological health status of the lake was assessed using the Multimetric Index for Lake Hawassa (MMIH), and the Macroinvertebrate-Based Multimetric Index for Biotic Integrity (MMIBI) for tributaries. Lake and tributary systems exhibited distinct community compositions, with molluscs dominating the lake and insects prevalent in tributaries. Families Thiaridae, Bithyniidae and Planorbidae were prevalent in the lake, while Baetidae and Chironomidae were common in the tributaries. Indicator species analyses revealed strong habitat affinities of Melanoides tuberculata and Gabbiella humerosa to the lake, and Radix natalensis and Pisidium kenianum to the rivers. The diversity indices indicated significantly higher macroinvertebrate diversity in the tributaries (p < 0.001), whereas molluscan diversity was greater in the lake (p < 0.05). The results classified the lake sites as having "fair" to "good" ecological status, while the tributaries ranged from "poor" to "moderate", reflecting the varying levels of anthropogenic pressure. These findings highlight the ecological distinctiveness of lacustrine and riverine systems, and demonstrate the effectiveness of using macroinvertebrates for integrated, basin-scale monitoring and management.

Background/Objectives: Proper nutrition and a balanced lifestyle are key determinants of overall human well-being, influencing both physical and mental health. Likewise, physical activity and daily lifestyle choices play a vital role in sustaining the proper functioning of physiological systems and preventing chronic diseases. Methods: This qualitative study was conducted between April and July 2025 among students and employees of the Faculty of Exact and Natural Sciences at Jan Kochanowski University. Data were gathered using the standardized KomPAN® 2.2 questionnaire, which assessed dietary habits, lifestyle behaviors, and demographic factors. Participants were selected according to defined inclusion and exclusion criteria, focusing on full-time students and research employees reporting well-being-related difficulties. Statistical analysis employed multivariate techniques, including Indicator Value Analysis in PAST 5.2.1 and Principal Component Analysis in Canoco 5.0, to identify significant differences between groups. Results: The results showed that students consumed more fruits and vegetables but also more fast food and sweetened beverages, while employees differed mainly in lifestyle characteristics such as urban residence and higher education level. Gender-related analyses indicated that women selected specific food products more often, whereas men were more physically active. Conclusions: The findings highlight the need for targeted well-being and nutrition support programs within academic institutions.

ABSTRACTThe composition of high‐latitude plant communities has changed over the past decades in response to several global change drivers. However, less is known about how these compositional long‐term changes are reflected in the total cover of plant species that do or do not interact with pollinators. Using species‐specific indicator values for pollinator dependence and nectar production, we provide empirical evidence on how compositional changes in vascular plant communities over the past 50 years are reflected in the cover of pollinator‐dependent and pollinator‐independent plants, as well as the cover of pollen‐ and nectar‐rewarding and non‐nectar plants, in two ecosystems in northern Fennoscandia. We show that the average cover of pollinator‐independent plants greatly increased in both tundra and herb‐rich forest communities over time. Average cover of pollinator‐dependent plants slightly increased in tundra but decreased in herb‐rich forests. The average cover of pollen‐nectar plants increased in the tundra but decreased in herb‐rich forests over time. At the same time, the cover of non‐nectar plants increased in both ecosystems. The observed changes were strongly driven by the increased cover of evergreen dwarf shrubs in the tundra and the decline of forb cover in herb‐rich forests. The observed changes were comparable between sites that had been disturbed by human land use and sites that remained in a natural or semi‐natural state. Our results suggest that, in terms of average plant coverage, high‐latitude plant communities have broadly become less dependent on insect pollination over the past 50 years. By documenting long‐term changes in the pollination strategies of high‐latitude plant communities, our study underscores the need to explore how shifts in plant community composition are linked to pollination processes and broader plant–pollinator dynamics. We highlight patterns that warrant further investigation and offer perspectives for future research on plant–pollinator interactions in northern ecosystems under global change.

In multi-objective optimization, set-based quality indicators are a cornerstone of benchmarking and performance assessment. They capture the quality of a set of tradeoff solutions by reducing it to a scalar number. One of the most commonly used setbased metrics is the R2 indicator, which describes the expected utility of a solution set to a decision-maker under a distribution of utility functions. Typically, this indicator is applied by discretizing the latter distribution, yielding a weakly Pareto-compliant indicator. In consequence, adding a nondominated or dominating solution to a solution set may - but does not have to - improve the indicator's value. In this paper, we reinvestigate the R2 indicator under the premise that we have a continuous, uniform distribution of (Tchebycheff) utility functions. We analyze its properties in detail, demonstrating that this continuous variant is indeed Pareto-compliant - that is, any beneficial solution will improve the metric's value. Additionally, we provide efficient computational procedures that (a) compute this metric for bi-objective problems in O(NlogN), and (b) can perform incremental updates to the indicator whenever solutions are added to (or removed from) the current set of solutions, without needing to recompute the indicator for the entire set. As a result, this work contributes to the state-of-the-art Pareto-compliant unary performance metrics, such as the hypervolume indicator, offering an efficient and promising alternative.

ABSTRACTEffective cumulative temperature and developmental zero point are important indicators for estimating the timing of organism development and the area of distribution. These indicators are generally considered to have unique values for different species of organisms and are also important for predicting the distribution range of animals and plants, especially insect pests. These values generally are species‐specific, but there is variation within populations in traits having a genetic component. However, there are no studies on what kind of selection pressure affects these indicator values. To address this issue, it would be worthwhile to compare these values using individuals of strains that have been artificially selected for life‐history traits by rearing them at various temperatures and calculating these indicators from developmental days and temperatures. In the present study, eggs were taken from adults of strains with many generations of artificial selection on two life‐history traits (age at reproduction and developmental period) of the melon fly, Zeugodacus cucurbitae, under constant temperature conditions. Eggs were reared at five different temperatures, and the effective cumulative temperatures and developmental zero points of the larval and developmental periods were compared. The results demonstrate that artificial selection on life‐history traits in Z. cucurbitae induces evolutionary changes in both the effective cumulative temperature and the developmental zero point across successive generations.

Heat stroke (HS) can lead to myocardial injury (MI), a critical factor affecting patient prognosis. The triglyceride-glucose (TyG) index, a surrogate marker for insulin resistance, has been associated with MI in patients with ischemic stroke and diabetes. However, its relationship with MI in HS patients remains unclear. This study aimed to explore the correlation between the TyG index and MI in HS patients. Clinical data from HS patients admitted to the emergency department of West China Hospital, Sichuan University, between July 1, 2022, and September 30, 2023, were retrospectively analyzed. Patients were divided into MI and non-MI groups based on the presence of MI. MI was defined as cardiac troponin ≥ 1.5 ng/mL. Multivariate logistic regression evaluated the association between the TyG index at admission and MI. A restricted cubic spline (modeled with four knots) was used to assess the dose-response relationship between the TyG index and MI. The study included 169 HS patients (mean age: 55 years; 85 [50.3%] male), of whom 63 (32.7%) developed MI. After adjusting for confounders, multivariate logistic regression revealed a nonlinear association between the TyG index and MI risk. Restricted cubic spline analysis revealed a non-linear relationship between the TyG index and MI risk, with a decreasing trend observed for TyG values ≤ 8.897, followed by a marked increase in risk for values ≥ 8.966. Female patients and those in specific age groups (18–44 and 75–89 years) exhibited higher risk of MI. This study identifies a U-shaped relationship between the TyG index and MI in HS patients, highlighting the TyG index’s potential indicator value and underscoring the importance of gender and age in risk assessment.

ABSTRACTAimIntracontinental range expansion of organisms is expected to be more and more frequent due to anthropogenic climate and land‐use changes, but its impact on ecosystems and consequences to nature conservation or economy are not well understood. Our study focuses on a range‐expanding neonative annual plant, Xeranthemum cylindraceum (Asteraceae, tribe Cardueae), which has become common in pastures. We aimed to assess the potential impact of this species on recipient grassland communities in the new range and to compare its performance between the native and neonative range.LocationGrasslands in Romania (neonative range) and Bulgaria (native range).MethodsWe surveyed plots from very low to very high abundances of the target species in grassland stands. To compare the vegetation between cover categories of X. cylindraceum and between the two study regions, we calculated species richness, Shannon diversity and community weighted mean of Ellenberg and disturbance indicator values. We also compared the vegetation composition based on species life span, habitat preference and guild.ResultsOur results show that species richness and diversity do not decrease with the increasing abundance of X. cylindraceum in recipient grasslands. However, the cover of specialist and long‐lived species was lower, while that of ruderal and short‐lived species was higher in vegetation patches with medium to high X. cylindraceum abundance. In the neonative range, this pattern overlapped with an increased disturbance severity and soil nitrogen content indicated by community composition, which bears clear signs of grazing disturbance forcefully transforming plant composition and causing ruderalisation.ConclusionsWe conclude that the range‐expanding X. cylindraceum does not raise conservation problems, since it is not impacting recipient grassland communities in its neonative range. However, it appears to benefit from grazing disturbance. As a toxic, unpalatable species, it decreases the economic value of intensively used grasslands, pointing out the need for decreasing stocking rates in intensively used pastures.

Gray matter microstructural abnormalities in temporal lobe epilepsy with hippocampal sclerosis and MRI negative.

The process capability index (PCI) is an important tool for determining the yield of the manufacturing process. Traditional PCIs are frequently used for normally distributed data. However, in practice, the data may follow a non-normal distribution, and traditional PCIs cannot be directly used. In this paper, we propose four PCIs for the Weibull distribution. The proposed PCIs have interpretability for process analysis and improvement and provide an exact functional relationship between the indicator values and non-conforming proportion. Additionally, when the parameters are unknown, we provide two estimation methods for the proposed PCIs: Modified approximate SC estimation (MASC) and bias-corrected MASC estimation (CMASC). These methods directly assess the PCIs without estimating the distribution parameters. The simulation results show that, under different skewness and sample sizes, the CMASC method outperforms the other methods and exhibits greater robustness to distributional skewness. Finally, an example demonstrates the process analysis and improvement strategy proposed in this study.

Parasitic plants inhabit a wide range of ecosystems worldwide, where they may have critical roles as "ecosystem engineers". We examined the ecology of parasitic plants in Europe. We aimed to identify habitat preferences, spatial distribution, and environmental drivers of parasitic plant functional types: euphytoid hemiparasites, obligate root parasites, and parasitic vines, and assess individual species' ecological niches. We analysed 244 parasitic plant species in a dataset of 819,452 vegetation plots across European natural vegetation. We used a boosted regression tree model to assess the effects of macro-climate, topography, and habitat descriptors (open, wet, saline) on the distribution of parasitic plant functional types. We analysed their distribution along the gradients of ecological indicator values. Finally, we determined the niches of individual species along all the environmental gradients. Parasitic plants occur across Europe and in nearly all habitats. Euphytoid hemiparasites (173 species) are most abundant in colder environments with moderate to high precipitation and low precipitation seasonality. In contrast, obligate root parasites (52 species) and parasitic vines (12 species) are primarily associated with warm-temperate to Mediterranean dry climates. All three functional types prefer nutrient-poor to moderately rich conditions. Some species diverge from the trend of their functional type. The spatial distribution and niches of parasitic plant functional types correspond to their fundamental physiological properties, including mode of resource acquisition and level of photosynthesis. Euphytoid hemiparasites are likely to be negatively affected by climate warming, while obligate root parasites and parasitic vines might benefit from future warmer and drier climates.

Quantifying the effects of road-building on bird communities before and after activities.

Many years of experience show that in most cases the company’s development strategies, which are an essential condition for their competitiveness, have been unsuccessful. The main reason for this situation is that the possibilities of implementing such strategies have not been properly assessed. This is a difficult task, as it includes both internal and external situations of the company, which are reflected by many indicators. The company’s ability to properly evaluate them can be described by the concept of its strategic potential. By its very nature, it is a complex phenomenon, so multi-criteria methods are suitable for quantitative assessment of its condition. Today, they are all based on linear estimation, i.e. the importance of the indicator does not depend on its value. In real life, everything happens non-linearly, so it is appropriate to integrate such an approach into the assessment of the state of socioeconomic phenomena or processes. In this case, the transformed value of the indicator follows a double exponential distribution, which is one of the three limiting cases of the distribution of statistics, corresponding to the curve. The assessment of the strategic potential of four construction companies was carried out based on the known four linear multi-criteria evaluation methods, both those that do not require and those that do require knowledge of the weights of the indicators ‒ sum of places, geometric mean, SAW, TOPSIS and PROETHEE. Non-linear evaluation was carried out in a geometric-analytical way. The obtained results, expressed in ratings, are the same when evaluated by PROMETHEE II and the geometric-analytical method and are equally different compared to the SAW and TOPSIS methods. On the other hand, compared to the PROMETHEE II method, the geometric-analytical method is much simpler and therefore easily automated. In addition, it can be applied in cases where some of the indicator values are negative.

ABSTRACTSoil health is central to sustainable agriculture and a key goal of regenerative and organic farming. However, monitoring changes in soil health remains challenging due to the lack of regionally relevant benchmarks and context‐specific indicators. This study assessed the impacts of long‐term and combined regenerative management practices on soil health across 87 California vineyards with diverse management histories, microclimates, and soils. Three key indicators, including aggregate stability, mineralizable carbon, and soil organic carbon, were used to develop region‐specific soil health scoring functions. These were adapted from Cornell's Comprehensive Assessment of Soil Health and the Soil Health Institute frameworks. Indicator values generally trended lower than existing benchmarks, emphasizing the need for crop‐ and region‐specific scoring systems. Results from mixed‐effects models and fuzzy‐set qualitative comparative analysis (fsQCA) indicate that long‐term cover cropping (≥ 10 years) was the most consistent driver of high soil health scores, especially when combined with other practices. Livestock integration improved soil organic carbon and mineralizable carbon scores in under 10 years, showing potential to accelerate soil health benefits. Our results highlight the importance of tailoring practices to local soil and climate conditions. Findings also support the development of more flexible, regionally informed soil health frameworks.

We face increasing concerns about how the local diversity of native plant communities responds to various drivers of global change, yet often lack comprehensive studies that integrate several components of diversity and the effects of both local and regional drivers of change. We analyzed changes in taxonomic, functional, and phylogenetic diversity across 2681 (semi-)permanent temperate forest understory plots surveyed and resurveyed for all vascular plants over intervals of 15-78 yr, spanning 72 regions distributed across Europe. We quantified temporal changes in these diversity indices and assessed their responses to changes in both local drivers (plot-level overstory cover, indicator values for soil nutrients) and regional shifts in macroclimate and nitrogen deposition. Overall, local changes in taxonomic, functional, and phylogenetic diversity were centered around zero, reflecting - on average - little net change in forest diversity. Observed diversity changes mostly reflected local conditions such as overstory cover change and baseline soil nutrients rather than regional drivers of large-scale change. Changes in phylogenetic diversity correlated positively with changes in taxonomic diversity but negatively with changes in functional diversity. Our findings underscore the importance of local habitat management and multifaceted diversity monitoring for effective biodiversity conservation in temperate forests.