A Hierarchical Bayesian Model to Predict Self-Thinning Line for Chinese Fir in Southern China.
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ABSTRACT:
SUBMITTER: Zhang X
PROVIDER: S-EPMC4594911 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background:High-density conditions are global issues that threaten the sustainable management of plantations throughout the world. Monocultures and untimely management practices have identically resulted in the simplex of community structures, decreases in biodiversity, and long-term productivity losses in plantations China. The most popular measure which is commonly used to address these issues is thinning, which potentially results in increases in the development of understory plants in plantations. However, there is limited information currently available regarding the community composition of understory vegetation and the associated environmental factors, which has limited the sustainable management of China's fir plantation ecosystems. Method:In the present study, a thinning experiment was implemented which included a control check (CK: no thinning), as well as low intensity thinning (LIT: 20%), moderate intensity thinning (MIT: 33%), and high intensity thinning (HIT: 50%) in Chinese fir plantations located in the Southeastern China. During the investigation process, the understory vegetation examined three years after thinning measures were completed, in order to analyze the impacts of different thinning intensities on the growth and community composition of the understory plants. At the same time, the associated environmental factors in the fir plantations were also investigated. Results:The species richness, total coverage, and biomass of the understory vegetation were observed to be apparently increased with increasing thinning intensity. In addition, it was found that the thinning measures had prominently influenced the soil nutrients. The community compositions of the understory vegetation were significantly different among the four thinning intensity levels, especially between the CK and the HIT. Furthermore, the development of the understory vegetation was found to be significantly correlated with the soil nutrient contents, and the community compositions of the understory vegetation were prominently driven by the tree densities, slope positions, and soil nutrient contents.
| S-EPMC7020821 | biostudies-literature
Project description:Large ex situ germplasm collections of plants generally contain significant diversity. A set of 700 well-conserved Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) clones from six provinces in southern China in the ex situ gene bank of Longshan State Forest, was analyzed using 21 simple sequence repeat markers, with the aim of assessing the genetic diversity of these germplasm resources. Genetic analysis revealed extensive genetic variation among the accessions, with an average of 8.31 alleles per locus and a mean Shannon index of 1.331. Excluding loci with null alleles, we obtained a low level of genetic differentiation among provinces, consistent with the interpopulation genetic variation (1%). Three clusters were identified by STRUCTURE, which did not match the individuals' geographical provenances. Ten traits related to growth and wood properties were quantified in these individuals, and there was substantial variation in all traits across individuals, these provide a potential source of variation for genetic improvement of the Chinese fir. Screening large collections for multiple-trait selective breeding programs is laborious and expensive; a core collection of 300 accessions, representative of the germplasm, was established, based on genotypic and phenotypic data. The identified small, but diverse, collections will be useful for further genome-wide association studies.
| S-EPMC5653812 | biostudies-literature
Project description:Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is the most important conifer species for timber production with huge distribution area in southern China. Accurate estimation of biomass is required for accounting and monitoring Chinese forest carbon stocking. In the study, allometric equation W = a(D2H)b was used to analyze tree biomass of Chinese fir. The common methods for estimating allometric model have taken the classical approach based on the frequency interpretation of probability. However, many different biotic and abiotic factors introduce variability in Chinese fir biomass model, suggesting that parameters of biomass model are better represented by probability distributions rather than fixed values as classical method. To deal with the problem, Bayesian method was used for estimating Chinese fir biomass model. In the Bayesian framework, two priors were introduced: non-informative priors and informative priors. For informative priors, 32 biomass equations of Chinese fir were collected from published literature in the paper. The parameter distributions from published literature were regarded as prior distributions in Bayesian model for estimating Chinese fir biomass. Therefore, the Bayesian method with informative priors was better than non-informative priors and classical method, which provides a reasonable method for estimating Chinese fir biomass.
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Project description:Chinese fir (Cunninghamia lanceolata) is the most important commercial tree species in southern China. The objective of this study was to develop a variable taper equation for Chinese fir, and to quantify the effects of stand planting density on stem taper in Chinese fir. Five equations were fitted or evaluated using the diameter-height data from 293 Chinese fir trees sampled from stands with four different densities in Fenyi County, Jiangxi Province, in southern China. A total of 183 trees were randomly selected for the model development, with the remaining 110 trees used for model evaluation. The results show that the Kozak's, Sharma/Oderwald, Sharma/Zhang and modified Brink's equations are superior to the Pain/Boyer equation in terms of the fitting and validation statistics, and the modified Brink's and Sharma/Zhang equations should be recommended for use as taper equations for Chinese fir because of their high accuracy and variable exponent. The relationships between some parameters of the three selected equations and stand planting densities can be built by adopting some simple mathematical functions to examine the effects of stand planting density on tree taper. The modelling and prediction precision of the three taper equations were compared with or without incorporation of the stand density variable. The predictive accuracy of the model was improved by including the stand density variable and the mean absolute bias of the modified Brink's and Sharma/Zhang equations with a stand density variable were all below 1.0 cm in the study area. The modelling results showed that the trees have larger butt diameters and more taper when stand density was lower than at higher stand density.
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Project description:Thinning is a widely used practice in forest management, but the acclimation mechanisms of fine roots to forest thinning are still unclear. We examined the variations in fine root traits of different branching orders and functional groups along a thinning intensity gradient in a 26-year-old Chinese fir (Cunninghamia lanceolata) plantation. With increasing thinning intensity, the root C concentration (RCC), root N concentration (RNC), specific root area (SRA), and specific root length (SRL) of the absorptive roots (the first two orders) significantly decreased, while root abundance (root biomass and root length density) and root tissue density (RTD) significantly increased. Fifty-four percent of the variation in the absorptive root traits could be explained by the soil N concentration and the biomass and diversity of the understorey vegetation. Conversely, transport root (third- and higher-order) traits did not vary significantly among different thinning intensities. The covariation of absorptive root traits across thinning intensities regarding two dimensions was as follows: the first dimension (46% of the total variation) represented changes in root abundance and chemical traits (related to RCC, RNC), belonging to an extensive foraging strategy; the second dimension (41% of the total variation) represented variations in root morphological traits (related to RTD, SRL and SRA), which is an intensive foraging strategy (i.e., root economic spectrum). These results suggested that the absorptive roots of Chinese fir adopt two-dimensional strategies to acclimate to the altered surroundings after thinning.
| S-EPMC8608833 | biostudies-literature
Project description:BackgroundThinning practices are useful measures in forest management and play an essential role in maintaining ecological stability. However, the effects of thinning on the soil properties and microbial community in large Chinese fir timber plantations remain unknown. The purpose of this study was to investigate the changes in soil physicochemical properties and microbial community composition in topsoil (0-20 cm) under six different intensities (i.e., 300 (R300), 450 (R450), 600 (R600), 750 (R750) and 900 (R900) trees per hectare and 1650 (R1650) as a control) in a large Chinese fir timber plantation.ResultsCompared with the CK treatment, thinning significantly altered the contents of soil organic carbon (SOC) and its fractions but not in a linear fashion; these indicators were highest in R900. In addition, thinning did not significantly affect the soil microbial community diversity indices but significantly affected the relative abundance of the core microbial community. Proteobacteria, Acidobacteria, and Actinobacteria were the dominant bacterial phyla; the relative abundances of Proteobacteria and Acidobacteria were highest in R900, and that of Actinobacteria was lowest in R900. The dominant fungal phyla were Ascomycota, Basidiomycota and Mucoromycota; the relative abundance of Ascomycota was lowest in R900, and that of Mucoromycota was highest in R900. The fungal microbial community composition was more sensitive than the bacterial community composition. The activity of the carbon-cycling genes was not linearly correlated with thinning, and the abundance of C-cycle genes was highest in R900.ConclusionsThese findings are important because they show that SOC and its fractions and the abundance of the soil microorganism community in large Chinese fir timber plantations can be significantly altered by thinning, thus affecting the capacity for carbon storage. These results may advance our understanding of how the density of large timber plantations could be modified to promote soil carbon storage.
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Project description:Chromosomal microarray analysis (CMA) in prenatal diagnosis detects copy number variations (CNVs) in many fetuses; however, the low penetrance and phenotypic diversity of CNVs complicate genetic counseling, resulting in limited understanding of intrauterine ultrasound phenotypes linked to CNVs. In a retrospective analysis of 25,000 cases at Fujian Maternal and Child Health Hospital, 18,000 pregnant women underwent SNP array testing (December 2015 to June 2023).
2024-08-14 | GSE274505 | GEO
Project description:BACKGROUND:Bipolar disorder is a prevalent mental health condition that is imposing significant burden on society. Accurate forecasting of symptom scores can be used to improve disease monitoring, enable early intervention, and eventually help prevent costly hospitalizations. Although several studies have examined the use of smartphone data to detect mood, only few studies deal with forecasting mood for one or more days. OBJECTIVE:This study aimed to examine the feasibility of forecasting daily subjective mood scores based on daily self-assessments collected from patients with bipolar disorder via a smartphone-based system in a randomized clinical trial. METHODS:We applied hierarchical Bayesian regression models, a multi-task learning method, to account for individual differences and forecast mood for up to seven days based on 15,975 smartphone self-assessments from 84 patients with bipolar disorder participating in a randomized clinical trial. We reported the results of two time-series cross-validation 1-day forecast experiments corresponding to two different real-world scenarios and compared the outcomes with commonly used baseline methods. We then applied the best model to evaluate a 7-day forecast. RESULTS:The best performing model used a history of 4 days of self-assessment to predict future mood scores with historical mood being the most important predictor variable. The proposed hierarchical Bayesian regression model outperformed pooled and separate models in a 1-day forecast time-series cross-validation experiment and achieved the predicted metrics, R2=0.51 and root mean squared error of 0.32, for mood scores on a scale of -3 to 3. When increasing the forecast horizon, forecast errors also increased and the forecast regressed toward the mean of data distribution. CONCLUSIONS:Our proposed method can forecast mood for several days with low error compared with common baseline methods. The applicability of a mood forecast in the clinical treatment of bipolar disorder has also been discussed.
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Project description:In this work we use a hierarchical Bayesian paradigm to introduce a theoretical framework to determine an individual's Apolipoprotein ε4 (APOE4) genotype, which heavily influences both the age of onset and probability of acquiring Alzheimer's disease (AD). This calculation is based solely on an individual's family history. This APOE4 genotype estimation is then combined with a number of known factors that influence AD onset to produce a function that estimates the onset of AD as a function of age. We disseminated our Alzheimer's predictive tool online at http://www.alzheimerspredictor.com.
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Project description:Motivated by the self-thinning meta-data, a random-effects meta-analysis model with unknown precision parameters is proposed with a truncated Poisson regression model for missing sample sizes. The random effects are assumed to follow a heavy-tailed distribution to accommodate outlying aggregate values in the response variable. The logarithm of the pseudo-marginal likelihood (LPML) is used for model comparison. In addition, in order to determine which self-thinning law is more supported by the meta-data, a measure called "Plausibility Index (PI)" is developed. A simulation study is conducted to examine empirical performance of the proposed methodology. Finally, the proposed model and the PI measure are applied to analyze a self-thinning meta-data set in details.
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