Search Results (1,118)

Understanding how main plant functional strategies scale from species to communities is critical for guiding restoration in tropical disturbed areas by unsustainable livestock grazing; yet, the patterns and drivers of functional trait space along successional trajectories remain poorly understood. Here, we investigated functional trait space using principal component analyses (PCAs) based on eight traits related to leaf, stem, and seed morphology across 226 tree species and 33 forest communities along a chronosequence of natural regeneration following cattle ranching abandonment in deforested landscapes of the Colombian Amazon. We identified three species-level functional axes—namely, the ‘Structural–Reproductive Allocation Axis’, the ‘Mechanical Support and Tissue Investment Axis’, and the ‘Leaf Economics Axis’—and two community-level axes: the ‘Colonization–Longevity Axis’ and the ‘Persistence–Acquisition Axis’. These axes aligned with the life-history strategies of short-lived pioneers, long-lived pioneers, and old-growth species, and reflected their relationships with key environmental drivers. Community-level functional composition reflected species-level patterns, but was also shaped by soil properties, microclimate, and tree species richness. Forest age and precipitation promoted conservative strategies, while declining soil fertility suggested a decoupling between above- and belowground recovery. Functional richness and divergence were highest in mid-successional forests dominated by long-lived pioneers. Our findings highlight the role of environmental and successional filters in shaping functional trait space and emphasize the value of functionally diverse communities. Particularly, our results indicate that long-lived pioneers (LLP) such as Astrocaryum chambira Burret and Pouteria campanulata Baehni, with traits like large height, intermediate wood density, and larger seed size, represent ideal candidates for early enrichment strategies due to their facilitation roles in succession supporting restoration efforts in regenerating Amazonian forests. Full article

Digital twins play a crucial role in linking data with practical solutions. They convert raw measurements into actionable insights, enabling spatial planning that addresses environmental challenges and meets the needs of local communities. This paper presents the development of a digital geospatial twin for a residential district in Burgas, the largest port city on Bulgaria’s southern Black Sea coast. The aim is to provide up-to-date geospatial data quickly and efficiently, and to merge available data into a single, accurate model. This model is used to test three scenarios for revitalizing coastal functions and improving a waterfront urban park in collaboration with stakeholders. The methodology combines aerial photogrammetry, ground-based mobile laser scanning (MLS), and airborne laser scanning (ALS), allowing for robust 3D modeling and terrain reconstruction across different land cover conditions. The current topography, areas at risk from geological hazards, and the vegetation structure with detailed attribute data for each tree are analyzed. These data are used to evaluate the strengths and limitations of the site concerning the desired functionality of the waterfront, considering urban priorities, community needs, and the necessity of addressing contemporary climate challenges. The carbon storage potential under various development scenarios is assessed. Through effective visualization and communication with residents and professional stakeholders, collaborative development processes have been facilitated through a series of workshops focused on coastal transformation. The results aim to support the design of climate-neutral urban solutions that mitigate natural risks without compromising the area’s essential functions, such as residential living and recreation. Full article

The ornamental plant sector is characterized by the production of a large variety of genera, species and cultivars that are much more numerous than those of other agricultural production sectors. Many countries throughout the world are involved in an intensive exchange of potted plants, cut flowers and propagation material. This intense trade exchange favors the introduction of the causal agents of new diseases on farms, in parks, along tree-lined avenues and in city gardens. Global warming can favor plant pathogens that thrive under high temperatures. Moreover, the interaction between the ongoing increase in temperature and in the CO₂ concentration has caused a significant increase in the disease severity of many pathosystems. The numerous reports of new plant pathogens on ornamental plants in Italy in recent years fall into this context. In plant pathology research, living labs incorporate the complexities and variability of natural conditions, and they can thus be used to conduct experiments and test hypotheses. A private garden, located in the hamlet of Bariola (Piedmont, Biella province, northern Italy), has become an ideal living lab that is used to monitor the evolution of the phytosanitary situation of ornamental plants. The results obtained in this living lab are reported hereafter. Moreover, new trends in disease prevention and management, such as the adoption of appropriate prevention practices, water and fertilization management and use of environmentally friendly methods to reduce pesticide use as part of an integrated pest management approach, are also examined. Full article

High-performance computing (HPC) data centers are experiencing rising energy consumption, despite the urgent need for increased efficiency. In this study, we develop an approach inspired by digital twins to enhance energy and thermal management in an HPC facility. We create a comprehensive framework that incorporates a digital twin for the CRESCO7 supercomputer cluster at ENEA in Italy, integrating data-driven time series forecasting with an interactive analytical dashboard for resource prediction. We begin by reviewing relevant literature on digital twins and modern time series modeling techniques. After ingesting and cleansing sensor and job scheduling datasets, we perform exploratory and inferential analyses to understand key correlations. We then conduct descriptive statistical analyses and identify important features, which are used to train machine learning models for accurate short- and medium-term forecasts of power and temperature. These models feed into a simulated environment that provides real-time prediction metrics and a holistic “health score” for each node, all visualized in a dashboard built with Streamlit. The results demonstrate that a digital twin-based approach can help data center operators efficiently plan resources and maintenance, ultimately reducing the carbon footprint and improving energy efficiency. The proposed framework uniquely combines concepts inspired by digital twins with time series machine learning and interactive visualization for enhanced HPC energy planning. Key contributions include the novel integration of predictive models into a live virtual replica of the HPC cluster, employing a gradient-boosted tree-based LightGBM model. Our findings underscore the potential of data-driven digital twins to facilitate sustainable and intelligent management of HPC data centers. Full article

The Fernald Feed Materials Production Center (FMPC), located in Fernald, Ohio, USA, released radon (Rn) as a byproduct of the processing of uranium materials during the years from 1951 to 1989. Rn is a colorless, odorless gas that emits charged alpha radiation that interacts with cells in the lung and trachea-bronchial tree, leading to DNA damage, mutations, and tumor initiation. The purpose of this project was to use evidence collected by the Fernald Dosimetry Reconstruction Project and other sources to estimate the outdoor Rn exposure to individuals in the community immediately surrounding the FMPC during the years of plant operation. Using previously tabulated source terms, diffusion and meteorological data, and self-reported detailed residential histories, we estimated radon exposure for approximately 9300 persons who lived at more than 14,000 addresses. The results indicated that a portion of the population cohort experiences mean annual Rn exposure exceeding the U.S. Environmental Protection Agency (EPA) action limit of 4 pCiL⁻¹. These exposure estimates support the analysis of the incidence of lung cancer in the Fernald Community Cohort (FCC). Full article

This study investigates the spatial heterogeneity of carbon pools in young Betula sp. stands on former arable lands in the southern Moscow region, Russia. The findings could be useful for the current estimates and predictions of the carbon balance in such forest ecosystems. The research focuses on understanding the interactions between plant cover and the environment, i.e., how environmental factors such as stand density, tree diameter and height, light conditions, and soil properties affect ecosystem carbon pools. We also studied how heterogeneity in edaphic conditions affects the formation of plant cover, particularly tree regeneration and the development of ground layer vegetation. Field measurements were conducted on a permanent 50 × 50 m sampling plot divided into 5 × 5 m subplots, in order to capture variability in vegetation and soil characteristics. Key findings reveal significant differences in carbon stocks across subplots with varying stand densities and light conditions. This highlights the role of the spatial heterogeneity of soil properties and vegetation cover in carbon sequestration. The study demonstrates the feasibility of indirect estimation of carbon stocks using stand parameters (density, height, and diameter), with results that closely match direct measurements. The total ecosystem carbon stock was estimated at 80.47 t ha⁻¹, with the soil contribution exceeding that of living biomass and dead organic matter. This research emphasizes the importance of accounting for spatial heterogeneity in carbon assessments of post-agricultural ecosystems, providing a methodological framework for future studies. Full article

The southern conifer Agathis australis (D.Don) Lindl. is a large and long-lived species endemic to Aotearoa New Zealand. It is threatened due to past logging activities, pathogen attack and potentially climate change, with increasing severity and frequency of drought and heatwaves across its distribution. Like many large tree species, little is known about the carbon dynamics of this ecologically and culturally significant species. We explored seasonal variations in non-structural carbohydrates (NSCs) and growth in trees ranging from 20 to 175 cm diameter at breast height (DBH). NSCs were seasonally stable with no measurable pattern across seasons. However, we found growth rates standardised to basal area and sapwood area (growth efficiency) declined with tree age and stem NSC concentrations (including total NSCs, sugars and starch) all increased as trees aged. Total NSC concentrations were 0.3%–0.6% dry mass for small trees and 0.8%–1.8% dry mass for larger trees, with strong relationships between DBH and total NSC, sugar and starch in stems but not roots. Cumulative growth efficiency across the two-year study period declined as tree size increased. Furthermore, there was an inverse relationship between growth efficiency across the two-year study period and NSC concentrations of stems. This relationship was driven by differences in carbon dynamics in trees of different sizes, with trees progressing to a more conservative carbon strategy as they aged. Simultaneously declining growth efficiency and increasing NSC concentrations as trees age could be evidence for active NSC accumulation to buffer against carbon starvation in larger trees. Our study provides new insights into changing carbon dynamics as trees age and may be evidence for active carbon accumulation in older trees. This may provide the key for understanding the role of carbon processes in tree longevity. Full article

The ongoing decade of UN restoration matches with the European goal of bringing nature back into our lives, including in urban systems, and Nature Restoration Regulation. Within such a framework, this work is aimed at highlighting the ecological rationale and strategic value of an NRRP measure devoted to forest restoration in Italian Metropolitan Cities, and at assessing respective preliminary results. Therefore, the measure’s overarching goal (not to create urban parks or gardens, but activate forest recovery), geographic extent and scope (over 4000 ha and more than 4 million planted trees and shrubs across the country), plantation model (mandatory use of native species consistent with local potential vegetation, density of 1000 seedlings per ha, use of at least four tree and four shrub species in each project, with a minimum proportion of 70% for trees, certified provenance for reproductive material), and compulsory management activities (maintenance and replacement of any dead plants for at least five years), are herein shown and explained under an ecological perspective. Current implementation outcomes were thus assessed in terms of coherence and expected biodiversity benefits, especially with respect to ecological and biogeographic consistency of planted forests, representativity in relation to national and European plant diversity, biogeographic interest and conservation concern of adopted plants, and potential contribution to the EU Habitats Directive. Compliance with international strategic goals and normative rules, along with recognizable advantages of the measure and limitations to be solved, are finally discussed. In conclusion, the forestation model proposed for the Italian Metropolitan Cities proved to be fully applicable in its ecological rationale, with expected benefits in terms of biodiversity support plainly met, and even exceeded, at the current stage of implementation, especially in terms of the contribution to protected habitats. These promising preliminary results allow the model to be recognized at the international level as a good practice that may help achieve protection targets and sustainable development goals within and beyond urban systems. Full article

True slime molds (Eumycetozoa) remain under-explored globally, particularly in water-logged forest habitats. Despite evidence suggesting a high biodiversity potential in the Knyszyn Forest of north-eastern Poland, no systematic effort had previously been undertaken there. In the present survey, plant substrates from eight swampy sub-compartments were incubated for over four months, resulting in the detection of fifteen slime mold species. Four of these taxa are newly reported for northern and north-eastern Poland, while several have been recorded only a handful of times in the global literature. These findings underscore how damp, nutrient-rich conditions foster Eumycetozoa and demonstrate the effectiveness of moist-chamber culturing in revealing rare or overlooked taxa. Current evidence shows that, although slime molds may occasionally colonize living plant or fungal tissues, their influence on crop productivity and tree vitality is negligible; they are therefore better regarded as biodiversity indicators than as pathogens or pests. By establishing a replicable framework for studying water-logged environments worldwide, this work highlights the ecological importance of swamp forests in sustaining microbial and slime mold diversity. Full article

Background: Comprehensive Geriatric Assessment (CGA) is essential for evaluating older cancer patients, but significant gaps persist in both research and clinical practice. This study aimed (I) to identify the CGA elements that most influence anti-cancer treatment decisions in older patients and (II) to explore the predictive value of CGA components for mortality. Methods: This observational study included older patients with newly diagnosed, histologically confirmed solid or hematological cancers, recruited consecutively from 2003 to 2023. Participants were followed for four years. The data collected included CGA measures of functional (Activities of Daily Living-ADL), cognitive (Mini-Mental State Examination-MMSE), and emotional (Geriatric Depression Scale-GDS) domains. Patients were categorized into frail, vulnerable, or fit groups based on Balducci’s criteria. Statistical analyses included decision tree modeling and Cox regression to identify predictors of mortality. Results: A total of 7022 patients (3222 females) were included, with a mean age of 78.3 ± 12.9 years. The key CGA factors influencing treatment decisions were ADL (first step), cohabitation status (second step), and age (last step). After four years, 21.9% patients had died. Higher GDS scores (OR 1.04, 95% CI 1.01–1.07, p = 0.04) were independently associated with survival in men and living with family members (OR 1.67, 95% CI 1.35–2.07, p < 0.001) in women. Younger patients (<77 years) showed both MMSE and GDS as significant risk factors for mortality. Conclusions: Functional capacity, cohabitation status, and GDS scores are crucial for guiding treatment decisions and predicting mortality in older cancer patients, emphasizing the need for a multidimensional geriatric assessment. Full article

Background/Objectives: Laboratory tests conducted in community settings are occasionally repeated within hours of presentation to pediatric emergency departments (PEDs). Reducing unnecessary repetitions can ease child discomfort and alleviate the healthcare burden without compromising the diagnostic process or quality of care. The aim of this study was to develop a decision tree (DT) model to guide physicians in minimizing unnecessary repeat blood tests in PEDs. The minimal decision tree (MDT) algorithm was selected for its interpretability and capacity to generate optimally pruned classification trees. Methods: Children aged 3 months to 18 years with community-based complete blood count (CBC), electrolyte (ELE), and C-reactive protein (CRP) measurements obtained between 2016 and 2023 were included. Repeat tests performed in the pediatric emergency department within 12 h were evaluated by comparing paired measurements, with tests considered justified when values transitioned from normal to abnormal ranges or changed by ≥20%. Additionally, sensitivity analyses were conducted for absolute change thresholds of 10% and 30% and for repeat intervals of 6, 18, and 24 h. Results: Among 7813 children visits in this study, 6044, 1941, and 2771 underwent repeated CBC, ELE, and CRP tests, respectively. The mean ages of patients undergoing CRP, ELE, and CBC testing were 6.33 ± 5.38, 7.91 ± 5.71, and 5.08 ± 5.28 years, respectively. The majority were of middle socio-economic class, with 66.61–71.24% living in urban areas. Pain was the predominant presented complaint (83.69–85.99%), and in most cases (83.69–85.99%), the examination was conducted by a pediatrician. The DT model was developed and evaluated on training and validation cohorts, and it demonstrated high accuracy in predicting the need for repeat CBC and ELE tests but not CRP. Performance of the DT model significantly exceeded that of the logistic regression model. Conclusions: The data-driven guide derived from the DT model provides clinicians with a practical, interpretable tool to minimize unnecessary repeat laboratory testing, thereby enhancing patient care and optimizing healthcare resource utilization. Full article

Deadwood is essential for the forest ecosystem productivity and stability. A growing body of evidence indicates that deadwood-inhabiting microbes are effective decomposition agents, yet little is known about how changes in microbial communities during the initial deadwood decay. In a small forest area, we performed dense sampling from the top, middle, and bottom portions of two representative Pinus massoniana cultivars logs to track deadwood xylem microbiota shift during the initial deadwood decay. We found xylem mycobiota varied dramatically during the initial deadwood decay. Deadwood microbes might largely originate from the endophytic microbes of living trees during the initial deadwood decay. Notably, bark type is an important driving factor for xylem mycobiota changes during the initial deadwood decay. Ten upregulated metabolites were screened out by a univariate analysis approach. Moreover, our correlation analysis suggests that enriched microbes at class level was significantly correlated with the upregulated metabolites during the initial deadwood decay. Our work provides new insights into the process of mycobiota and metabolite changes during the initial deadwood decay. Full article

Urban green spaces (UGSs) and forests play a vital role in shaping sustainable and livable cities, offering not only ecological benefits but also spaces that are essential for human well-being, social interactions, and everyday life. Understanding the landscape features that resonate most with public preferences is essential for enhancing the appeal, accessibility, and functionality of these environments. However, traditional approaches—such as surveys or single-data analyses—often lack the nuance needed to capture the complex and multisensory nature of human responses to green spaces. This study explores a cross-modal methodology that integrates natural language processing (NLP) and deep learning techniques to analyze text and image data collected from public reviews of 19 urban parks in Nanjing. By capturing both subjective emotional expressions and objective visual impressions, this study reveals a consistent public preference for natural landscapes, particularly those featuring evergreen trees, shrubs, and floral elements. Text-based data reflect users’ lived experiences and nuanced perceptions, while image data offers insights into visual appeal and spatial composition. By bridging human-centered insights with data-driven analysis, this research provides a robust framework for evaluating landscape preferences. It also underscores the importance of designing green spaces that are not only ecologically sound but also emotionally resonant and socially inclusive. The findings offer valuable guidance for the planning, design, and adaptive management of urban green infrastructure in ways that support healthier, more responsive, and smarter urban environments. Full article

Our research focused on the roost preferences of two bat species in a forest environment. Throughout the Anthropocene, people have heavily altered the landscape. Forested habitation has declined, with remaining forests becoming fragmented and often deprived of old trees that provide shelter opportunities for bats. TReMs (tree-related microhabitats) are essential for forest-dwelling bat species as they provide an opportunity to roost and shelter. Following an infestation of Ips typographus L., the Białowieża Forest is saturated with dead spruce trees. We investigated roost selection in two forest-dwelling species, Barbastella barbastellus and Pipistrellus pygmaeus. To examine similarities or differences in roost selection between species, we radio-tracked 24 barbastelles and 13 soprano pipistrelles over three breeding seasons. We located a total of 48 barbastelle roosts and 15 pipistrelle roosts, together with the characteristics of the surroundings. We found that barbastelles select roosts almost exclusively in dead spruce trees (43/48), while pipistrelles selected roosts predominantly in live (n = 8) and dead (n = 5) broadleaved trees. Our results show that both bat species have clear differences in roost tree preference. In our study area, with an abundance of exfoliating bark, barbastelles showed a preference for roosting under flaking bark despite the availability of crevices within broadleaved trees. Our findings provide useful insight into forestry practices, highlighting the importance of standing dead trees. Full article

Logs supplied in Papua New Guinea and Indonesia are predominantly sourced from fast-growing tree species of plantation forests. The timber primarily consists of sapwood, which is highly susceptible to biodeterioration. At a training center, CCA (chromated copper arsenate) is still used for wood preservation, while in the wood industry, ACQ (alkaline copper quaternary) is commonly applied to enhance the service life of timber. In the future, polystyrene impregnation or other non-biocidal treatments could potentially serve this purpose. This study aimed to determine the discoloration and resistance of polystyrene-impregnated and CCA-preserved woods. Wood samples, Anisoptera thurifera and Octomeles sumatrana from Papua New Guinea, and Anthocephalus cadamba and Falcataria moluccana from Indonesia, were used. The wood samples were treated with polystyrene impregnation, CCA preservation, or left untreated, then exposed at the PNG Forest Research Institute site for four months. After treatment, the color change in polystyrene-impregnated wood was minor, whereas CCA-preserved wood exhibited a noticeably different color compared to untreated wood. The average polymer loading for polystyrene-impregnated wood reached 147%, while the average CCA retention was 8.4 kg/m³. Densities of untreated-, polystyrene-, and CCA-wood were 0.42, 0.64, and 0.45 g/cm³, respectively, and moisture contents were 15.8%, 9.4%, and 13.4%, respectively. CCA preservation proved highly effective in preventing termite attacks; however, CCA is hazardous to living organisms, including humans. Polystyrene impregnation also significantly improved wood resistance to subterranean termites, as indicated by lower weight loss and a higher protection level compared to untreated wood. Additionally, polystyrene treatment is nonhazardous and safe for living organisms, making it a promising option for enhancing wood resistance to termite attacks in the future as an alternative to the biocides currently in use. Full article