Search Results (4,301)

Against a backdrop of global climate fluctuations and intensifying human activities, wetlands are undergoing severe degradation. Understanding the mechanisms that govern wetland evolution is essential for the sustainable development of wetland ecosystems. However, wetland evolution is highly heterogeneous across space and time, and existing studies have generally paid insufficient attention to nonlinear effects and interactions among driving mechanisms, limiting a comprehensive understanding of its intrinsic processes. We integrated the Light Gradient Boosting Machine model with SHapley Additive exPlanations to explain the nonlinear driving mechanisms of spatiotemporal wetland evolution across the Sanjiang Plain using multitemporal remote sensing data from 1990 to 2023. Wetland dynamics exhibited a stage-dependent pattern characterized by substantial natural-wetland loss in the early period, followed by partial marsh-wetland recovery and continued artificial-wetland expansion. Artificial wetlands expanded continuously, whereas marsh wetlands declined markedly before 2005 and showed partial recovery thereafter. From 1990 to 2005, wetland evolution was mainly controlled by topographic and climatic factors. From 2005 to 2023, the influence of socioeconomic development and proximity to the road network on wetland change intensified. Nonlinear interactions among driving factors shifted from synergistic promotion by natural factors in the early stage to inhibitory effects among natural, socioeconomic, and locational factors in the later stage. This stage-specific change in driving mechanisms was crucial to the shift in dominant drivers of wetland evolution. By characterizing single-factor nonlinear effects and multifactor interactions, this study reveals the stage-specific driving mechanisms of wetland evolution in the Sanjiang Plain and provides scientific support for regional wetland management and remote sensing monitoring. Full article

Background: Alcohol-associated liver disease (ALD) involves ethanol-related metabolic injury, inflammation, gut–liver dysfunction, and progressive loss of skeletal muscle and functional reserve. Exercise could influence several of these pathways, but ALD-specific evidence remains limited. We therefore evaluated exercise as an adjunct, not a substitute for established care, across the ALD spectrum. Methods: We conducted a structured narrative review of PubMed/MEDLINE, Google Scholar, and publisher records updated through 20 August 2026. Evidence was classified as direct human ALD/MetALD evidence, direct preclinical alcohol-injury evidence, indirect clinical evidence from MASLD or mixed-etiology cirrhosis, or mechanistic evidence from broader exercise biology. Results: Direct human evidence is predominantly observational. Leisure-time physical activity is associated with lower liver mortality across drinking patterns and with lower odds of at-risk advanced fibrosis in MetALD/ALD. These associations do not establish the efficacy of structured exercise training. Preclinical alcohol-injury models support redox- and Nrf2-mediated hepatoprotection, whereas proposed effects on AMPK-SIRT1-PGC-1α signaling, mitochondrial quality, gut microbial metabolites, myokines, and ammonia handling remain largely extrapolated. Metabolomic studies identify disturbances in redox balance, lipid intermediates, acylcarnitines, bile acids, and amino acid and tryptophan metabolism. These alterations provide candidate endpoints for future trials. Myostatin and decorin are associated with ALD severity, but their responsiveness to exercise is unknown. We therefore propose a stage-specific research and practice framework with explicit safety considerations. Conclusions: Exercise is a promising but unproven multisystem adjunct for ALD. It should complement abstinence support, alcohol use disorder care, nutrition, and standard medical management. ALD-specific trials should integrate metabolomics, liver outcomes, functional measures, sex, alcohol exposure, disease stage, and adverse events. Full article

The triterpenoid and polysaccharide constituents of Ganoderma lucidum (GL) are believed to influence key pathogenic pathways in Alzheimer’s disease (AD). This study first examined the molecular rationale for GL’s neuroprotective properties by subjecting its principal triterpenoids, Ganoderic Acid A&B, to computational profiling. Molecular docking was performed against human acetylcholinesterase (AChE), TNF-α, COX-2, IL-6, caspase-3, Bcl-2, and the Keap1–Nrf2 complex using CB-Dock2, alongside SwissADME-based physicochemical and ProTox-3.0-based toxicological screening. These targeted pathways were then biologically validated in an in vitro AD model induced by Aβ_1–42 toxicity in SH-SY5Y cells, assessing AChE activity, apoptosis, ROS levels, mitochondrial membrane potential (MMP), and cytokine expression (COX-2, TGF-β1, IL-6, TNF-α, IL-10). Docking revealed high binding affinities of both triterpenoids toward all seven targets (Vina scores: −7.3 to −10.4 kcal/mol), predicting strong modulation of cholinergic, inflammatory, apoptotic, and antioxidant pathways. Consistent with these predictions, GL extract significantly reduced TNF-α, COX-2, and IL-6 mRNA and protein levels, attenuated ROS accumulation, preserved MMP except at 500 µg/mL, and exerted a concentration-dependent antiapoptotic effect. IL-10 and TGF-β1 showed complex, dose-dependent patterns, reflecting indirect regulatory responses. Together, these findings support GL’s neuroprotective potential against Aβ-induced toxicity through direct engagement of cholinergic, inflammatory, apoptotic, and antioxidant regulatory proteins. Full article

Divergence exponents (DEs), also termed maximum Lyapunov exponents, are computed from stride-to-stride fluctuations and have traditionally been read as measures of gait stability. We assessed the evidence for reinterpreting the long-term DE as a new measure of gait complexity and automaticity alongside the already validated complexity measures such as the detrended fluctuation analysis (DFA) scaling exponent and multiscale entropy. We searched Web of Science databases through January 2026 for studies applying Rosenstein’s algorithm to human gait and appraised study quality. We meta-analyzed correlations between long-term DE and the DFA scaling exponent and synthesized perturbation, cueing, and between-subject studies. Sixty-two studies (2000–2026) were included, among which 44% were of high quality. Across six datasets from five studies (189 participants), long-term DE correlated positively with the DFA scaling exponent (r = 0.64, 95% CI 0.34–0.82; I² = 82%). Perturbation increased short-term DEs while reducing long-term DEs (up to 51%), and cueing reduced long-term DEs (up to 86%) with little effect on short-term DEs; between-subject patterns were heterogeneous. Convergent and experimental evidence supports reinterpreting the long-term DE as a measure of gait complexity. These reinterpreted studies reinforce the proposed link between gait complexity and automaticity, a link that is shared across complexity measures and still indirect, awaiting joint recording with cortical activity. Full article

Vaccine responses differ substantially among individuals and across populations. Although factors such as age, genetics, and vaccine type are recognized contributors, they do not fully explain this heterogeneity. Emerging evidence suggests that the human microbiota, particularly the gut microbiota, may modulate immune responses to vaccination and represents a potentially modifiable component of immunity. This review integrates data from human studies, microbiota-targeted clinical trials, and experiments using germ-free and humanized models to clarify the mechanisms underlying microbiota–immune system interactions during vaccination. Identified mechanisms include pattern-recognition receptor signaling, modulation of innate immune activation, regulation of germinal-center responses, maintenance of mucosal barrier integrity, and the influence of microbial metabolites on T and B lymphocytes. The relevance of these pathways varies by age, developmental stage, and vaccine platform, including live-attenuated, inactivated, subunit, viral-vector, and mRNA vaccines. Additional factors such as diet, antibiotic exposure, infections, medications, and environmental or social determinants also affect both the microbiota and vaccine outcomes. Current research explores approaches to improve vaccine potency through microbiota modulation using probiotics, prebiotics, synbiotics, postbiotics, and engineered microbes, though clinical results remain inconsistent. A greater understanding of microbiota–vaccine interactions may enable personalized immunization strategies; however, further research is required to establish causality and identify actionable microbial targets. Longitudinal studies using multi-omics, advanced cellular analyses, robust clinical trials, and in silico modeling are essential to determine whether microbiome-based interventions can improve vaccine efficacy and durability. Full article

Wetlands support fisheries and other livelihoods but can also bring people into close contact with crocodilians. Human–crocodile conflict has been documented across Africa, Asia, Australia and the Americas, yet indirect economic costs, including damage to fishing gear, remain less studied than attacks on people or livestock. We analysed questionnaire data from 379 respondents in purposively selected crocodile-exposed fishing communities in the southern Sudd Wetlands, South Sudan. The study quantified seasonal patterns of Nile crocodile (Crocodylus niloticus) damage to fishing gear, reporting pathways, conflict-resolution perceptions, responses to damaged gear and likely annual damaged-net categories. Reporting pathways were defined as the social and institutional channels through which respondents said gear-damage incidents were communicated; handling responses were defined as actions taken after gear was damaged. As expected from seasonal variation in floodplain use, the water level and fishing activity, reported damage was concentrated from July to December, with September the being most frequently selected main damage month (157 respondents; 41.4%). Quarterly ordinal responses differed among seasons (Friedman test: ${\chi }^2=721.54$, df = 3, $p<0.001$). Cumulative link models that included both quarters and the broader survey area showed the largest odds-ratio contrasts for July–September and October–December, whereas broader-area contrasts were smaller, and their confidence intervals overlapped one. Reporting was dominated by informal and community pathways: fishing-camp leadership, family members and other fishers each reached 100% agreement, whereas wildlife authorities received no affirmative reporting. Respondents also expressed little confidence in formal conflict resolution: 100% agreed that crocodile-related gear-damage conflicts were difficult to resolve, and 0% agreed that government would compensate for damaged gear. Damaged nets were mainly abandoned and replaced; repair was rare (1.6%). The most likely annual damaged-net category was 1–5 nets/year/participant (275 respondents; 72.6%). Because the survey was purposive, the results should be interpreted as patterns among sampled respondents and locations, not as prevalence estimates for all fishers in the Sudd Wetlands or South Sudan. The findings indicate that seasonal gear damage, weak formal reporting to wildlife institutions and limited institutional confidence should be central considerations in crocodile-conflict management. Full article

Background/Objectives: This study aims to determine the indirect costs associated with the disease process in patients hospitalized for acute coronary syndrome and to analyze the sociodemographic and clinical factors influencing these costs. Methods: This prospective, single-center, observational cost-of-illness study evaluated 146 ACS patients at a tertiary cardiology clinic over an index episode extending from admission to 30 days after discharge, from a patient and household perspective that excludes direct medical costs. Excluding six patients (one death, five early retirements), 140 patients were analyzed. Productivity losses were measured with the iMTA Productivity Cost Questionnaire and valued using the Human Capital Approach; SCORE2, GRACE and MIDAS scores were also recorded. Costs are reported in 2025 international dollars (Int$, OECD PPP factor 16.20). Factors associated with total indirect cost were examined with a Gamma generalized linear model with a log link, containing five prespecified covariates: sex, occupational group, age, GRACE and MIDAS. Results: The mean age was 61 ± 12 years, and 69.9% of the cohort were male. The median total indirect cost per patient was 1007 Int$. In the actively employed subgroup, the median absenteeism cost was 1450 Int$, while the median household production loss for the entire cohort was 340 Int$. The multivariate Gamma GLM identified occupational status (p < 0.001) and female sex (p = 0.004) as variables independently associated with total indirect costs, whereas age and clinical/prognostic scores (GRACE, MIDAS) lacked statistical significance. Compared to patients outside the labor force, total costs were 4.8 and 4.1 times higher for white-collar and blue-collar workers, respectively. Conclusions: ACS imposes a significant short-term indirect cost burden at the patient and household levels, driven by absenteeism among actively employed patients and by household production losses among those outside the labor force. These findings indicate that the early post-discharge economic burden is patterned primarily by labor force position and by the distribution of unpaid domestic work rather than by clinical severity. Full article

Background: Prostate cancer (PC) is a heterogeneous disease in which the histopathological grade does not always reflect underlying biological behavior. While transcriptomic studies have provided insight into tumor biology, grade-associated molecular changes remain incompletely defined, particularly in underrepresented populations such as those from the Middle East and North Africa (MENA) region. Methods: In this study, we used a pathology-guided transcriptomic approach to examine gene expression patterns across PC grades in a MENA cohort. RNA sequencing was performed on formalin-fixed paraffin-embedded (FFPE) tissues, including benign prostatic hyperplasia (BPH, n = 7), low-grade tumors (Gleason 6–7 [3 + 4]; LG; n = 7), and high-grade tumors (Gleason 7 [4 + 3]–10; HG; n = 7). Differential expressions, pathway-level enrichment analyses and the estimation of immune cell composition were carried out, followed by comparison with publicly available datasets (TCGA-PRAD, n = 496), including LG tumors (n = 292) and HG tumors (n = 204), using the GEPIA2 and UALCAN platforms. Selected genes were further assessed using qRT-PCR in an independent set of samples (n = 21). Representative immunohistochemical images from the Human Protein Atlas were reviewed to provide descriptive protein-level context across tumor grades. Results: Transcriptomic comparisons of tumor samples with benign controls identified a set of shared transcriptional changes present in both low- and high-grade disease. Among these, SLC29A2 and IL2RA showed consistent upregulation across tumor grades and similar expression trends in external datasets. Direct comparison between HG and LG tumors revealed distinct transcriptional profiles with patterns indicative of increased proliferative activity and altered immune-related signaling in higher-grade disease. Pathway-level analyses showed the enrichment of cell-cycle and metabolic gene signatures in HG tumors, whereas inflammatory and NF-κB-associated transcriptional signatures showed a comparatively reduced expression. Additional genes, including AAMDC, ASAH2, TNFRSF1B, NFKBIL1, and NFKBIZ, were associated with these grade-dependent differences. qRT-PCR findings were generally consistent with the RNA-seq results for selected targets. Conclusions: This study describes transcriptional patterns associated with the PC grade in a MENA cohort using a pathology-guided framework. The findings highlight candidate genes associated with tumor presence and grade progression and provide a foundation for further investigation in larger, well-annotated cohorts, particularly in populations that remain underrepresented in transcriptomic studies. Full article

Preservation of mitochondrial integrity has emerged as a central hub in the anti-inflammatory effect of exercise. This narrative review advances a framework in which mitochondrial damage-associated molecular patterns (mtDAMPs) serve as the mechanistic bridge between exercise and inflammation. Mitochondrial dysfunction releases mtDAMPs, including mitochondrial DNA (mtDNA), reactive oxygen species, cardiolipin, N-formyl peptides, and ATP, which activate cGAS–STING, the NLRP3 inflammasome, TLR9, AIM2, ZBP1, and NF-κB signaling. Crosstalk among these pathways allows mild mitochondrial damage to escalate into chronic inflammation. Exercise opposes this cascade through the AMPK–PGC-1α axis, which coordinately activates four mitochondrial quality control (MQC) modules: biogenesis, antioxidant defense, dynamics, and mitophagy. The cardiovascular system illustrates this framework, as myocardial inflammation runs mainly through mtDNA–cGAS–STING signaling and vascular inflammation through oxidized mtDNA–NLRP3 signaling, while cardiovascular aging engages both axes at once. Throughout, exercise refers to repeated training rather than to a single bout, and the framework targets middle-aged and older adults with, or at risk of, cardiovascular disease. The upstream half of the sequence, in which training raises mitochondrial content and antioxidant capacity, rests on human muscle biopsy data; the downstream half remains largely preclinical. MQC is therefore proposed as a testable target rather than an established one. Full article

River turbidity is a key indicator of water quality that influences both human activities and riverine ecosystem functioning. However, strong seasonal variability, high sensitivity to disturbances, and pronounced spatial heterogeneity make turbidity patterns difficult to characterize and generalize across river systems. In ecological modeling, incorporating environmental variables can improve model accuracy by providing process-relevant context that is not fully captured by spectral signals alone. However, this strategy has not been systematically evaluated in water-quality remote sensing, especially for cross-river turbidity retrieval. Here, we applied this strategy to build cross-river turbidity models and compared it with a spectral-only scenario. A total of 43 monitoring sites across the conterminous United States were analyzed. Four models, random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM), and artificial neural network (ANN), were implemented under two scenarios using spectral features alone and in combination with environmental variables. Incorporating environmental variables substantially improved overall model performance, with median R² increasing from 0.60–0.69 to 0.67–0.78 and median Kling–Gupta efficiency (KGE) increasing from 0.59–0.67 to 0.71–0.77. Among them, RF and XGBoost maintained or improved cross-site generalization under Scenario 2, with median KGE values of 0.65 and 0.67 in leave-one-site-out tests, respectively, compared with 0.56 for SVM and 0.58 for ANN. Performance gains tended to be larger at sites with stronger discharge seasonality. Site-level and range-specific analyses further suggested that the improvement was mainly associated with low-flow and low-turbidity conditions and tended to occur in smaller catchments at lower elevations. These results demonstrate that integrating spectral and environmental information improves both the accuracy and generalizability of turbidity retrieval and helps clarify when and why environmental context benefits water-quality remote sensing across diverse river systems. Full article

The Future of Jobs Report 2025 identifies technological change, geoeconomic fragmentation, demographic shifts, and the green transition as compounding forces restructuring global labour markets. Rather than merely adding new risks, these pressures erode the foundational assumptions upon which labour rights rest, widening the gap between workers’ lived conditions and the reach of existing legal frameworks across international, regional, national, and platform levels. Algorithmic management serves as the focal case through which these pressures converge. In platform and conventional workplaces alike, technical systems now allocate tasks, price labour, rank workers, enforce sanctions, and determine classification, cutting across traditional boundaries separating labour law, private law, data protection, and AI regulation. Two analytical concepts organise the argument. Mediated autonomy denotes a condition in which workers retain nominal choice, yet that choice is structured in advance by systems governing incentives, visibility, risk, and legal categorisation. Algorithmic subordination captures the resulting form of control: indirect, informationally asymmetric, and legally dispersed dependence on data flows, automated rankings, and code-driven decisions. Drawing on the philosophy of technology and classificatory looping theory, the article demonstrates that legal and technical categories do not merely describe workers; they actively constitute the field within which workers bear risk and assert entitlements. Biometric monitoring and affective computing intensify this dynamic by extending managerial authority to bodily signals and inferred emotional states. China’s regulatory approach to non-standard employment is examined as a case study and compared with the EU’s status-and-algorithm model, situating both within broader patterns of global regulatory divergence. The article concludes that effective labour protection must move beyond employment-status classification toward control-sensitive and technology-sensitive frameworks, encompassing transparency obligations, contestation rights, human review mechanisms, fair remuneration, data minimisation for biometric and affective information, and meaningful worker participation in platform governance. Full article

Nighttime light (NTL) data is widely used to monitor urban development, economic activity and population distribution, supporting socio-economic analysis and sustainable development planning. SDGSAT-1 NTL data, with its multiple bands and high resolution, has become an important source for studying human activity patterns. However, directly summing radiance values on geographic grids assumes equal contributions from all grid cells, regardless of the differences in the ground area represented by each cell. As a result, regional nighttime light totals may be systematically distorted, particularly in cross-latitude analyses where pixel areas differ substantially. To address this aggregation issue, this study proposes a physically explicit area-weighting framework that converts SDGSAT-1 radiance to radiant flux by incorporating the actual surface area represented by each grid cell. The framework is validated using 25 cities spanning different latitudes and development levels in the Northern Hemisphere. Results show that the radiant flux model, which captures total emitted power, demonstrates improved performance over radiance-based aggregation (a density-based measure) in population estimation (R² = 0.85 vs. 0.82). By shifting from light intensity to integrated total energy, this approach improves cross-latitude comparability and enhances the methodological robustness of NTL-based analyses. Full article

Ehrlichia and Anaplasma are important tick-borne obligate intracellular bacteria that cause clinically and economically significant infections in humans and animals. Despite their importance, vaccine development for these pathogens remains limited, and the overall progression of vaccine-related research in this field has not been quantitatively characterized. In this study, we conducted a comprehensive bibliometric analysis to characterize the trajectory and the research landscape of vaccine-related research for these pathogens. The literature was retrieved from the Web of Science Core Collection using the search terms (Ehrlichia OR ehrlichiosis OR Anaplasma OR anaplasmosis) AND (vaccine OR vaccines). A total of 483 publications published between 1965 and 2025 were included in the analysis. Bibliometric analyses were conducted using Biblioshiny (Version 4.3.3) and VOSviewer (Version 1.6.20) to assess publication trends, citation patterns, leading countries, institutions, and major research themes. The literature showed gradual growth over time, with more consistent publication output from the late 1990s onward. Scientific output was concentrated in a relatively small number of countries and institutions, led by the United States, South Africa, Brazil, Spain, and France. Keyword frequency and co-occurrence analyses showed that the field has been shaped mainly by bovine anaplasmosis, heartwater, and tick-associated vaccine research, with Anaplasma marginale and Ehrlichia ruminantium emerging as dominant pathogen-focused themes. Major surface proteins, msp1a, subolesin, and Bm86, appeared frequently, indicating continued interest in both pathogen-derived and tick-associated vaccine targets. In contrast, human and canine pathogens such as Ehrlichia chaffeensis, Anaplasma phagocytophilum, and Ehrlichia canis were less represented. Our analysis maps the research landscape of Ehrlichia and Anaplasma vaccine development, quantifying how research activity has been distributed across pathogens, geographic regions, institutions, collaborations, and vaccine-related themes. It also identifies areas that remain comparatively less represented in the published literature and provides a quantitative baseline for future comparisons with independent measures of disease burden and research funding data. Full article

Background: Periodontitis is a chronic inflammatory disease characterized by dysregulated host immune responses that drive connective tissue destruction and alveolar bone loss. Human gingival fibroblasts (HGFs) are central regulators of periodontal inflammation through their production of cytokines, chemokines, matrix-remodeling enzymes, and other inflammatory mediators. Although cannabinoid receptor 2 (CB2) activation has demonstrated anti-inflammatory properties, its coordinated effects on multiple inflammatory pathways in gingival fibroblasts remain poorly understood. This study investigated the transcriptomic effects of the selective CB2 agonist HU-308 on IL-1β-induced inflammatory responses in HGFs. Methods: Primary HGFs were divided into untreated controls, IL-1β-stimulated cells (10 ng/mL), and IL-1β-stimulated cells treated with HU-308 (10 μM). Twenty-four hours after stimulation, transcriptome-wide expression profiling was performed using Affymetrix Human Clariom S microarrays, followed by targeted analysis of selected inflammation-related transcriptional domains. Selected transcripts were evaluated within predefined biological domains including cytokines, chemokines, extracellular matrix-associated genes, NO/cGMP-related genes, transporter-associated genes, and GPCR-related transcripts. Gene expression was analyzed using one-way ANOVA with Tukey’s post hoc test. Results: IL-1β induced a coordinated inflammatory transcriptional program characterized by increased expression of pro-inflammatory cytokines, chemokines, matrix metalloproteinases, glucose transporter genes, and multiple GPCR-related transcripts, while suppressing collagen-associated genes, NOS3, GPR4, and GPR78. HU-308 broadly attenuated these inflammatory responses by reducing the expression of cytokines, chemokines, matrix metalloproteinases, and several GPCR-related genes while restoring collagen-associated transcripts, nitric oxide signaling components, anti-inflammatory mediators, and selected glucose transporters toward basal levels. Schematic multidimensional visualizations were used to illustrate relative expression patterns among selected transcripts within each functional domain; these visualizations do not represent statistically derived gene networks or molecular interactions. Conclusions: Pharmacological modulation of CB2 by HU-308 exerts broad immunomodulatory effects in IL-1β-stimulated human gingival fibroblasts by coordinately regulating multiple transcriptional networks involved in periodontal inflammation. These findings demonstrate that HU-308 treatment is associated with coordinated modulation of inflammatory, extracellular matrix, nitric oxide, metabolic, and GPCR-associated transcriptional pathways in IL-1β-stimulated HGFs. The results support the hypothesis that CB2 signaling may participate in the broader regulation of these interconnected responses; however, receptor-specific studies using CB2 antagonism or CNR2 knockdown are required to establish causality. Full article

Changing disturbance regimes and uncertain recovery trajectories under global change have created a need for conceptual models to guide forest management within a sustainability framework. This conceptual article develops on operational framework for ecosystem memory in forest ecosystems. Conventional views of resilience may foster the misleading assumption that ecosystem development follows a fixed trajectory within the boundaries of the natural range of variation. However, climate change may transform resilience mechanisms, causing forest ecosystems to shift beyond their historical range of variation. Under such conditions, the concept of ecosystem memory offers a framework for analyzing and quantifying temporal system properties. The constraints inherited through memory patterns are themselves likely to be modified under changing environmental conditions. A valid interpretation of ecosystem memory requires a clear ontological understanding of memory components as material entities organized under temporal and spatial constraints. The human memory metaphor is an appealing entry point for understanding ecosystem memory but risks erroneously attributing semantic encoding and representational processes to ecological systems, where no such mechanisms exist. Based on a narrative synthesis of 39 publications, supplemented by an updated Web of Science search that identified 396 records, we develop an operational ecosystem-memory framework that distinguishes persistent ecological legacies from functionally active memory by linking ecological imprints, ecosystem engrams, and measurable ecosystem responses. The framework provides a basis for identifying and monitoring measurable legacy variables, including deadwood, retained trees, regeneration, soil properties, and refugial structures, in post-disturbance forest management. Full article