Impacts of litter microbial community on litter decomposition in the absence of soil microorganisms.

What is the effect of phyllosphere microorganisms on litter decomposition in the absence of colonization by soil microorganisms? Here, we simulated the litter standing decomposition stage in the field to study the differences in the composition and structure of the phyllosphere microbial community after the mixed decomposition of Populus × canadensis and Pinus sylvestris var. mongolica litter. After 15 months of mixed decomposition, we discovered that litters that were not in contact with soil had an antagonistic effect (the actual decomposition rate was 18.18%, which is lower than the expected decomposition rate) and the difference between the litters themselves resulted in a negative response to litter decomposition. In addition, there was no significant difference in bacterial and fungal community diversity after litter decomposition. The litter bacterial community was negatively responsive to litter properties and positively responsive to the fungal community. Importantly, we found that bacterial communities had a greater impact on litter decomposition than fungi. This study has enriched our understanding of the decomposition of litter itself and provided a theoretical basis for further exploring the "additive and non-additive effects" of litter decomposition and the mechanism of microbial drive. IMPORTANCE: The study of litter decomposition mechanism plays an important role in the material circulation of the global ecosystem. However, previous studies have often looked at contact with soil as the starting point for decomposition. But actually, standing litter is very common in forest ecosystems. Therefore, we used field simulation experiments to simulate the decomposition of litters without contact with soil for 15 months, to explore the combined and non-added benefits of the decomposition of mixed litters, and to study the influence of microbial community composition on the decomposition rate while comparing the differences of microbial communities.

Network connectivity underlying episodic memory in children: Application of a pediatric brain tumor survivor injury model.

Episodic memory involves personal experiences paired with their context. The Medial Temporal, Posterior Medial, Anterior Temporal, and Medial Prefrontal networks have been found to support the hippocampus in episodic memory in adults. However, there lacks a model that captures how the structural and functional connections of these networks interact to support episodic memory processing in children. Using diffusion-weighted imaging, magnetoencephalography, and memory tests, we quantified differences in white matter microstructure, neural communication, and episodic memory performance, respectively, of healthy children (n = 23) and children with reduced memory performance. Pediatric brain tumor survivors (PBTS; n = 24) were used as a model, as they exhibit reduced episodic memory and perturbations in white matter and neural communication. We observed that PBTS, compared to healthy controls, showed significantly (p < 0.05) (1) disrupted white matter microstructure between these episodic memory networks through lower fractional anisotropy and higher mean and axial diffusivity, (2) perturbed theta band (4-7 Hz) oscillatory synchronization in these same networks through higher weighted phase lag indices (wPLI), and (3) lower episodic memory performance in the Transverse Patterning and Children's Memory Scale (CMS) tasks. Using partial-least squares path modeling, we found that brain tumor treatment predicted network white matter damage, which predicted inter-network theta hypersynchrony and lower verbal learning (directly) and lower verbal recall (indirectly via theta hypersynchrony). Novel to the literature, our findings suggest that white matter modulates episodic memory through effect on oscillatory synchronization within relevant brain networks. RESEARCH HIGHLIGHTS: Investigates the relationship between structural and functional connectivity of episodic memory networks in healthy children and pediatric brain tumor survivors Pediatric brain tumor survivors demonstrate disrupted episodic memory, white matter microstructure and theta oscillatory synchronization compared to healthy children Findings suggest white matter microstructure modulates episodic memory through effects on oscillatory synchronization within relevant episodic memory networks.

A Feedback Active Control Approach to Road Noise Based on a Single Microphone Sensor to Improve Automotive Cabin Sound Comfort.

Tire-road noise deteriorates the sound quality of a vehicle's interior and affects the driving safety and comfort. Obtaining low interior noise is a challenge for passenger car manufacturers. Traditional passive noise control (PNC) is efficient for canceling high frequency noise but not useful for low frequency noise, while active noise control (ANC), according to the residual error signal, can generate an anti-noise signal to reduce the original noise. Most research has focused on improving the control effect for a feedforward ANC system. However, this paper emphasizes a feedback ANC system based on a signal microphone sensor. There are two main contributions in this study to improve automotive cabin sound comfort. One is that the algorithm of the feedback ANC system using a single microphone sensor without a reference noise signal is proposed based on the Filtered-x Least Mean Square method. The other is that the algorithm applies additive random noise online to estimate the secondary path model. A simulation was implemented based on measured real road noise data, and the simulation results indicate that the proposed feedback ANC system with the single microphone sensor can effectively attenuate road noise. This study shows the feasibility of applying a feedback ANC system in automobiles to increase the cabin sound quality.

The Role of Parental Involvement in the Development of Prosocial Behavior in Young Children: An Evolutionary Model Among Colombian Families.

Prosocial behavior is a relevant indicator of children's socio-emotional development linked to decreased conduct and emotional problems. The present study aimed to identify cross-sectional direct effects of parental involvement on prosocial behavior in three-time assessments at ages 3, 5, and 7 years, to identify carryover effects of the study constructs, and to identify the evolution of these effects over time. A sample of 235 Colombian families participated at t0, 220 at t1, and 145 at t2 by completing self-reported questionnaires for prosocial behavior using the Strengths and Difficulties Questionnaire and the Alabama Parenting Questionnaire for parental involvement. Using PLS-SEM path modeling, we found that the contribution of parental involvement to prosocial behavior was significant in the three assessments. Carryover analyses indicated that initial levels of parental involvement and initial levels of prosocial behavior predict later levels. Using multigroup analysis, we tested significant changes in the path coefficients of direct effects, finding nonsignificant results. For carryover effects, we found changes in parental involvement between t0/t1 and t1/t2. Finally, t-test analyses were used to identify changes in the construct's means over time, finding significant changes between parental involvement at t1 and t2. No mean differences were found for prosocial behavior. Results from this study highlight the relevance of parental involvement during childhood for maintaining children's levels of prosocial behavior and reducing the risk of socio-emotional problems. Preventive approaches for these problems should include parents' training on parental involvement from age 3.5 years or earlier.

The relationship between bullying, learning disorders and psychiatric comorbidity.

BACKGROUND: Both learning disorders and bullying are major sources of public concern. Children with learning disorders often suffer from social rejection, potentially rendering them more susceptible to bullying involvement. Bullying involvement leads to a higher risk towards developing various problems including self-harm and suicidality. Past research on whether learning disorders are childhood bullying risk factors yielded inconsistent results. METHODS: The current study used path analyses on a representative sample of 2,925 German 3rd and 4th grades to examine whether learning disorders are a direct bullying risk factor, or whether their impact depends on psychiatric comorbidity. More so, the current study sought to examine whether associations differ between children with and without learning disorders, compare different bullying roles (i.e., only victim, only bully, or bully-victim), compare gender, and control for IQ and socioeconomic status. RESULTS: Results indicated that learning disorders are not a direct but rather an indirect childhood risk factor for bully-victim involvement, depending on psychiatric comorbidity with internalizing or externalizing disorders. Regarding the comparison between the samples of children with and without learning disorders, an overall difference and a difference in the path between spelling and externalizing disorders emerged. No difference for different bullying roles (i.e., only victim, only bully) emerged. Negligible differences emerged when IQ and socioeconomic status were controlled. An overall gender difference emerged, compatible with past research, indicating higher bullying involvement among boys compared to girls. CONCLUSION: Children with learning disorders are at a higher risk of having psychiatric comorbidity, which in turn renders them at a higher risk of bullying involvement. Implications for bullying interventions and school professionals are deduced.

Effects of iron additives on the removal of antibiotics and antibiotic resistance genes in anaerobic fermentation of food waste.

The presence of antibiotics and antibiotic resistance genes (ARGs) in food waste (FW) during anaerobic fermentation poses significant environmental and health risks. This study elucidated the potential of iron additives, specifically 500-nm and 50-nm zero-valent iron (ZVI) and magnetite, in mitigating these contaminants. These findings revealed that 500-nm magnetite significantly reduced tetracyclines by 81.04%, while 500-nm ZVI effectively reduced cefotaxime by 89.90%. Furthermore, both 500-nm and 50-nm ZVI were observed to decrease different types and abundance of heavy metal resistance and virulence genes. Interestingly, while 500-nm ZVI reduced the overall abundance of ARGs by 50%, 500-nm magnetite primarily reduced the diversity of ARGs without significantly impacting their abundance. These results elucidate the efficacy of iron additives in addressing antibiotic contamination and resistance during the anaerobic fermentation process of FW. The findings acquired from this study mitigate the development of innovative and environmentally sustainable technologies for FW treatment, emphasizing the reduction of environmental risks and enhancement of treatment efficiency.

More powerful parameter tests? No, rather biased parameter estimates. Some reflections on path analysis with weighted composites.

Recently, a study compared the effect size and statistical power of covariance-based structural equation modeling (CB-SEM) and path analysis using various types of composite scores (Deng, L., & Yuan, K.-H., Behavior Research Methods, 55, 1460-1479, 2023). This comparison uses nine empirical datasets to estimate eleven models. Based on the meta-comparison, that study concludes that path analysis via weighted composites yields "path coefficients with less relative errors, as reflected by greater effect size and statistical power" (ibidem, p. 1475). In our paper, we object to this central conclusion. We demonstrate that the justification these authors provided for comparing CB-SEM and path analysis via weighted composites is not well grounded. Similarly, we explain that their employed study design, i.e., a meta-comparison, is very limited in its ability to compare the effect size and power delivered across these methods. Finally, we replicated Deng and Yuan's (ibidem) meta-comparison and show that CB-SEM using the normal-distribution-based maximum likelihood estimator does not necessarily deliver smaller effect sizes than path analysis via composites if a different scaling method is employed for CB-SEM.

Arbuscular Mycorrhizal Fungi Compete Asymmetrically for Amino Acids with Native and Invasive Solidago.

Arbuscular mycorrhizal fungi (AMF) and soil amino acids both affect plant performance. However, little is known about how AMF compete for amino acids with native and invasive congeners. We conducted a factorial experiment (inoculation, native and invasive species, and amino acids) to examine the competition for amino acids between soil microbes and both native and invasive congeners. The competition for amino acids between AMF and invasive Solidago canadensis was weaker than that observed between AMF and native S. decurrens. This asymmetric competition increased the growth advantage of S. canadensis over S. decurrens. The efficacy (biomass production per unit of nitrogen supply) of amino acids compared to ammonium was smaller in S. canadensis than in S. decurrens when both species were grown without inoculation, but the opposite was the case when both species were grown with AMF. AMF and all microbes differentially altered four phenotypic traits (plant height, leaf chlorophyll content, leaf number, and root biomass allocation) and the pathways determining the effects of amino acids on growth advantages. These findings suggest that AMF could enhance plant invasiveness through asymmetric competition for amino acids and that amino acid-driven invasiveness might be differentially regulated by different microbial guilds.

Emotional outcomes of e-learning adoption during compulsory online education.

Information on the emotional outcomes of e-learning system use and emotional aspects of user experience in higher education is quite limited. Accordingly, the aim of the study is to identify the factors that influence university students' intention to continue using e-learning systems and to examine the emotional outcomes of the continuance intention. The core constructs of the Technology Acceptance Model formed the basis of the proposed model, and the model was extended with a framework of emotions (challenge, achievement, deterrence, loss) and external variables. Data were collected online from 19,530 university students of a state university. For the analysis, Partial Least Squares-Structural Equation Modeling was employed. The proposed model explained 73.5% of continuance intention, 50.3% of achievement, and 52.2% of challenge emotions. In addition, 23 of the 25 tested hypotheses were supported. The findings indicate that perceived usefulness is a decisive factor in creating user experiences that generate emotions such as enjoyment, playfulness and satisfaction. In addition, the results showed that personal innovativeness strongly influenced the core constructs of technology acceptance model and the positive aspects of emotions (achievement and challenge). Accordingly, it can be stated that these findings lead us to the fact that students' value perceptions regarding e-learning systems have a critical role in terms of emotional outcomes. In addition, the findings suggest that both intrinsic-extrinsic motivators, innovativeness characteristics and emotional outcomes should be taken into account in design and development process in order to improve the quality of the user experience. In this direction, implications for research and practice are discussed.

Cardiovascular risk factors and APOE-ε4 status affect memory functioning in aging via changes to temporal stem diffusion.

Prior research investigating associations between hypertension, obesity, and apolipoprotein (APOE) genotype status with memory performance among older adults has yielded inconsistent results. This may reflect, in part, a lack of first accounting for the effects these variables have on structural brain changes, that in turn contribute to age-related memory impairment. The current study sought to clarify the relationships between these factors via path modeling. We hypothesized that higher body mass index (BMI), hypertension, and being an APOE-ε4 allele carrier would predict poorer memory scores, with much of these effects accounted for by indirect effects operating via differences in the integrity of temporal stem white matter. Participants included 125 healthy older adults who underwent neuropsychological assessment and diffusion-weighted MRI scanning. Direct effects were found for hypertension and demographic variables including age, sex, and education. Importantly, indirect effects were found for BMI, hypertension, APOE-ε4 status, age, and sex, where these factors predicted memory scores via their impact on temporal stem diffusion measures. There was also a dual effect of sex, with a direct effect indicating that females had better memory performance overall, and an indirect effect indicating that females with greater temporal stem diffusion had poorer memory performance. Results suggest that changes to the integrity of temporal white matter in aging may underpin reduced memory performance. These results highlight that accounting for variables that not only directly impact cognition, but also for those that indirectly impact cognition via structural brain changes, is crucial for understanding the impact of risk factors on cognition.

Need frustration and depressive symptoms in French older people: using a self-determination approach.

OBJECTIVES: To provide evidence of the relationship between basic psychological need frustration (BPNF) for autonomy, competence and relatedness, and depressive symptoms in French older people, and to explore the potential moderator effects of place of residence (home vs nursing home) on this relationship. METHODS: Partial least squares path modeling (PLS-PM) was used. A total of 410 French older people (212 women, 198 men, Mage = 77.13 years, SD = 9.19, age range: 60-98 years) voluntarily participated in the study and completed the measures of BPNF and depressive symptoms. Sociodemographic data were collected. RESULTS: Findings showed that for all the participants, competence and relatedness need frustration positively predicted depressive symptoms. More particularly, BPNF for relatedness significantly predicted depressive symptoms for older people living at home (ß = .18, p < .05), whereas BPNF for competence significantly predicted depressive symptoms for both participants living at home (ß = .25, p < .05) and in nursing homes (ß = .34, p < .05). Among participants living at home, results showed that BPNF for competence significantly predicted depressive symptoms (ß = .28, p < .05) across married participants, while BPNF for relatedness significantly predicted depressive symptoms (ß = .27, p < .05) across participants living alone. CONCLUSION: By focusing on BPNF and its relationship to depressive symptoms, this study suggests the importance of investigating further this concept, and alerts to the long-term consequences of frustration of competence and relatedness needs in older people.

Energy Efficient UAV Flight Path Model for Cluster Head Selection in Next-Generation Wireless Sensor Networks.

Wireless sensor networks (WSNs) are one of the fundamental infrastructures for Internet of Things (IoTs) technology. Efficient energy consumption is one of the greatest challenges in WSNs because of its resource-constrained sensor nodes (SNs). Clustering techniques can significantly help resolve this issue and extend the network's lifespan. In clustering, WSN is divided into various clusters, and a cluster head (CH) is selected in each cluster. The selection of appropriate CHs highly influences the clustering technique, and poor cluster structures lead toward the early death of WSNs. In this paper, we propose an energy-efficient clustering and cluster head selection technique for next-generation wireless sensor networks (NG-WSNs). The proposed clustering approach is based on the midpoint technique, considering residual energy and distance among nodes. It distributes the sensors uniformly creating balanced clusters, and uses multihop communication for distant CHs to the base station (BS). We consider a four-layer hierarchical network composed of SNs, CHs, unmanned aerial vehicle (UAV), and BS. The UAV brings the advantage of flexibility and mobility; it shortens the communication range of sensors, which leads to an extended lifetime. Finally, a simulated annealing algorithm is applied for the optimal trajectory of the UAV according to the ground sensor network. The experimental results show that the proposed approach outperforms with respect to energy efficiency and network lifetime when compared with state-of-the-art techniques from recent literature.

Leaf shape is a predictor of fruit quality and cultivar performance in tomato.

Commercial tomato (Solanum lycopersicum) is one of the most widely grown vegetable crops worldwide. Heirloom tomatoes retain extensive genetic diversity and a considerable range of fruit quality and leaf morphological traits. Here the role of leaf morphology was investigated for its impact on fruit quality. Heirloom cultivars were grown in field conditions, and BRIX by yield (BY) and other traits were measured over a 14-wk period. The complex relationships among these morphological and physiological traits were evaluated using partial least-squares path modeling, and a consensus model was developed. Photosynthesis contributed strongly to vegetative biomass and sugar content of fruits but had a negative impact on yield. Conversely leaf shape, specifically rounder leaves, had a strong positive impact on both fruit sugar content and yield. Cultivars such as Stupice and Glacier, with very round leaves, had the highest performance in both fruit sugar and yield. Our model accurately predicted BY for two commercial cultivars using leaf shape data as input. This study revealed the importance of leaf shape to fruit quality in tomato, with rounder leaves having significantly improved fruit quality. This correlation was maintained across a range of diverse genetic backgrounds and shows the importance of leaf morphology in tomato crop improvement.

The cognitive, affective motivational and clinical longitudinal determinants of apathy in schizophrenia.

Apathy is a frequent and debilitating condition with few treatment options available in schizophrenia patients. Despite evidence of its multidimensional structure, most of past studies have explored apathy through a categorical approach. The main objective of this study was to identify the cognitive, emotional, motivational, and clinical factors at baseline that best predicted the three subtypes of apathy dimensions at follow-up. In a longitudinal study, 137 participants diagnosed with schizophrenia underwent different assessments including clinical, motivational, affective and cognitive measurements, at 1-month (referred to as baseline) and 12-month follow-ups. Data were analyzed using partial least squares variance-based structural equation modeling. Three latent variables representing the three previously described domains of apathy reaching consensus in the literature were extracted from the Lille Apathy Rating Scale. Results showed that in addition to baseline apathy, positive symptoms, anticipatory pleasure and sensibility to punishment at baseline predicted cognitive apathy at follow-up. Likewise, both baseline apathy and sensibility to punishment predicted emotional apathy at follow-up. Finally, baseline anhedonia and episodic memory were the main variables the predicted behavioral apathy at follow-up. This is the first study to show specific associations between apathy subtypes and clinical and cognitive motivational dysfunction in individual with schizophrenia, indicating possible distinct underlying mechanisms to these demotivational symptoms. Treatment for apathy should address both types of processes. Importantly, our results demonstrate the interest of multidimensional approaches in the understanding of apathy in schizophrenia.

Factors Influencing Rust (Melampsora apocyni) Intensity on Cultivated and Wild Apocynum venetum in Altay Prefecture, China.

Rust (Melampsora apocyni) on Apocynum venetum is the major constraint to the commercial development of this medicinal herb. To determine the factors influencing rust intensity (maximum disease index [DImax]), rust was investigated from 2011 to 2015 in both cultivated and wild A. venetum plants. Partial least squares path modeling (PLS-PM) was used to analyze the paths and extent of the factors related to pathogen, environment, and host that affect rust intensity. DImax exhibited considerable variations across years and study sites, with variations linked to various factors fostering disease development. PLS-PM explained 80.0 and 70.1% of variations in DImax in cultivated and wild plants, respectively. Precipitation was the key factor determining DImax in both cultivated and wild plants (path coefficient [PC] = 0.313 and 0.544, respectively). In addition, the topsoil water content in cultivated plants and the total vegetation coverage in wild plants were also critical determinants of DImax via their effects on the microclimatic factor (contribution coefficients [CC] = 0.681 and 0.989, respectively; PC = 0.831 and 0.231, respectively). In both cultivated and wild plants, host factors were mainly dominated by A. venetum density (CC = 0.989 and 0.894, respectively), and their effect on DImax via the microclimatic factor (PC = 0.841 and 0.862, respectively) exceeded that via the inoculum factor (PC = 0.705 and 0.130, respectively). However, the indirect effects led to DImax variation, while the dilution effect on host (CC = 0.154) from weed in wild plants led to the indirect effect size in wild plants of 0.200, which was lower than -0.699 in cultivated plants.

Path modeling of knowledge, attitude and practice toward palliative care consultation service among Taiwanese nursing staff: a cross-sectional study.

BACKGROUND: The Taiwanese government has promoted palliative care consultation services (PCCS) to support terminally ill patients in acute ward settings to receive palliative care since 2005. Such an intervention can enhance the quality of life and dignity of terminally ill patients. However, research focusing on the relationship between the knowledge, attitude and practice of a PCCS using path modelling in nursing staff is limited. Therefore, the aim of this study was to elucidate the effect of path modeling on the knowledge, attitude and practice toward PCCS in Taiwanese nursing staff. METHODS: This was a cross-sectional, descriptive study design using convenience sampling. Data collected included demographics, knowledge, attitude and practice as measured by the PCCS inventory (KAP-PCCSI). Two hundred and eighty-four nursing staff from a medical center in northern Taiwan participated in the study in 2013. We performed descriptive statistics, regression analysis, and path modeling using SPSS 19.0 and set p < 0.05 as the statistical significance threshold. RESULTS: The results showed that the identical factor significantly associated with knowledge, attitude, and practice toward PCCS among nurses was the frequency of contact with PCCS. In addition, higher level of knowledge toward PCCS was associated with working in haematology and oncology wards, and participation in education related to palliative care. A more positive attitude toward PCCS was associated with working in a haematology and oncology ward, and experience of friends or relatives dying. Higher level of practice toward PCCS was associated with nurses who participated in education related to palliative care. In the path modeling, we found that holders of a master's degree indirectly positive affected practice toward PCCS. Possession of a bachelor degree or above, being single, working within a haematology and oncology ward, and frequency of contact with PCCS positively affected practice toward PCCS. CONCLUSIONS: Based on this study, it is proposed that consultation with PCCS has a positive impact on the care of terminally ill patients. Encouragement of staff to undertake further education can improve the practice of ward staff providing palliative care.

A singular, broadly-applicable model for estimating on- and off-path walking travel rates using airborne lidar data.

Accurate prediction of walking travel rates is central to wide-ranging applications, including modeling historical travel networks, simulating evacuation from hazards, evaluating military ground troop movements, and assessing risk to wildland firefighters. Most of the existing functions for estimating travel rates have focused on slope as the sole landscape impediment, while some have gone a step further in applying a limited set of multiplicative factors to account for broadly defined surface types (e.g., "on-path" vs. "off-path"). In this study, we introduce the Simulating Travel Rates In Diverse Environments (STRIDE) model, which accurately predicts travel rates using a suite of airborne lidar-derived metrics (slope, vegetation density, and surface roughness) that encompass a continuous spectrum of landscape structure. STRIDE enables the accurate prediction of both on- and off-path travel rates using a single function that can be applied across wide-ranging environmental settings. The model explained more than 80% of the variance in the mean travel rates from three separate field experiments, with an average predictive error less than 16%. We demonstrate the use of STRIDE to map least-cost paths, highlighting its propensity for selecting logically consistent routes and producing more accurate yet considerably greater total travel time estimates than a slope-only model.

A comprehensive study of psychological well-being and traditional Chinese medicine constitutions among model workers in Beijing.

Background: Body constitution is the foundation of Traditional Chinese Medicine (TCM), and model workers consist of a special group of workers within China. This study aims to research the relationship between the physical body constitutions based on TCM and the mental health of model workers. Methods: We recruited 314 model workers from Beijing Rehabilitation Hospital to conduct the questionnaires such as SCL-90 and CCMQ to investigate if there is an association between mental health status and TCM body constitutions. We performed a Partial Least Squares Path Modeling (PLS path modeling). Results: Our path model results revealed associations between different TCM constitution types and SCL scores, which serve as indicators of psychological well-being. Our research findings demonstrate a strong correlation between the Balanced constitution and elevated levels of psychological well-being, with a path coefficient of -0.503. In contrast, the other eight constitutional types exhibit path coefficients exceeding 0.3, indicating a tendency toward lower levels of psychological well-being. We also investigated the intricate connections between various TCM constitutional types and both mild and severe psychological well-being. Conclusion: In conclusion, the Balanced constitution continues to be closely associated with higher levels of psychological well-being, while the remaining eight body constitution types are consistently linked to lower levels of psychological well-being.

Effect of plant-soil system on the restoration of community stability after wildfire in the northeast margin of Qinghai-Tibet plateau.

Wildfires, as an environmental filter, are pivotal ecological disturbances that reshape plant communities and soil dynamics, playing a crucial role in regulating biogeographic patterns and ecosystem services. In this study, we aim to explore the effects of wildfires on forest ecosystems, specifically focusing on the plant-soil feedback mechanisms within the northeastern margin of the Qinghai-Tibet Plateau (QTP). Utilizing Partial Least Squares Path Modeling (PLS-PM), we investigated the interrelationships among soil physicochemical properties, enzyme activities, species diversity, and community stability at varying post-fire recovery stages (5, 15, and 23 years). Results indicated that in the early recovery stages, rapid changes in soil properties such as decreased pH (p < 0.001) and increased nutrient availability facilitate the emergence of early successional species with high resource utilization traits. As the ecosystem evolved toward a climax community, the soil and vegetation exhibit increased stability. Furthermore, soil enzyme activities displayed dynamic patterns that corresponded with changes in soil nutrient content, directly influencing the regeneration and diversity of plant communities. Importantly, our study documented a transition in the influence of soil properties on community stability from direct positive effects in initial recovery phases to negative impacts in later stages, while indirect benefits accrue through increased species diversity and enzyme activity. Vegetation composition and structure changed dynamically with recovery time during community succession. Plant nutrient absorption and accumulation affected nutrient dynamics in the soil, influencing plant regeneration, distribution, and diversity. Our results underscore the complex interactions between soil and vegetation that drive the recovery dynamics post-wildfire, highlighting the resilience of forest ecosystems to fire disturbances. This study contributes to the understanding of post-fire recovery processes and offers valuable insights for the management and restoration of fire-affected forest ecosystems.

Dynamic restoration mechanism of plant community in the burned area of northeastern margin of Qinghai-Tibet Plateau.

Forest fires play a pivotal role in influencing ecosystem evolution, exerting a profound impact on plant diversity and community stability. Understanding post-fire recovery strategies holds significant scientific importance for the ecological succession and restoration of forest ecosystems. This study utilized Partial Least Squares Path Modeling (PLS-PM) to investigate dynamic relationships among plant species diversity, phylogenetic diversity, soil properties, and community stability during various recovery stages (5-year, 15-year, and 23-year) following wildfires on the northeastern margin of the Qinghai-Tibet Plateau. The findings revealed: (1) Over time, species richness significantly decreased (p< 0.05 or p< 0.01), while species diversity and dominance increased, resulting in uniform species distribution. Community stability progressively improved, with increased species compositional similarity. (2) Throughout succession, phylogenetic diversity (PD) significantly decreased (p< 0.01), accompanied by rising Mean Pairwise Distance (MPD) and Mean Nearest Taxon Distance (MNTD). Net Relatedness Index (NRI) shifted from positive to negative, indicating an increasing aggregation and dominance of plants with similar evolutionary traits in burned areas. Early succession witnessed simultaneous environmental filtering and competitive exclusion, shifting predominantly to competitive exclusion in later stages. (3) PLS-PM revealed that in the early recovery stage, soil properties mainly affected community stability, while species diversity metamorphosed into the primary factor in the mid-to-late stages. In summary, this study showed that plant diversity and phylogenetic variation were successful in revealing changes in community structure during the succession process. Soil characteristics functioned as selective barriers for plant communities during succession, and community stability underwent a multi-faceted and dynamic process. The soil-plant dynamic feedback continuously enhanced soil conditions and community vegetation structure thereby augmenting stability. Post-fire vegetation gradually transitioned towards the original native state, demonstrating inherent ecological self-recovery capabilities in the absence of secondary disturbances.