Liana optical traits increase tropical forest albedo and reduce ecosystem productivity

Lianas are a key growth form in tropical forests. Their lack of self-supporting tissues and their vertical position on top of the canopy make them strong competitors of resources. A few pioneer studies have shown that liana optical traits differ on average from those of colocated tree. Those trait discrepancies were hypothesized to be responsible for the competitive advantage of lianas over trees. Yet, in the absence of reliable modelling tools, it is impossible to unravel their impact on the forest energy balance, light competition and on the liana success in Neotropical forests. To bridge this gap, we performed a meta-analysis of the literature to gather all published liana leaf optical spectra, as well as all canopy spectra measured over different levels of liana infestation. We then used a Bayesian data assimilation framework applied to two radiative transfer models (RTMs) covering the leaf and canopy scales to derive tropical tree and liana trait distributions, which finally informed a full dynamic vegetation model. According to the RTMs inversion, lianas grew thinner, more horizontal leaves with lower pigment concentrations. Those traits made the lianas particularly efficient at light interception and completely modified the forest energy balance and its carbon cycle. While forest albedo increased by 14% in the shortwave, light availability was dramatically reduced in the understory (-30% of the PAR radiation) and soil temperature decreased by 0.5 degree Celsius. Those liana-specific traits were also responsible for a significant reduction of tree (-19%) and ecosystem (-7%) gross primary productivity (GPP) while lianas benefited from them (their GPP increased by +27%). This study provides a novel mechanistic explanation to the increase in liana abundance, new evidence of the impact of structural parasitism on forest functioning, and paves the way for the evaluation of the large-scale impacts of woody vines on forest biogeochemical cycles.

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Lianas reduce carbon accumulation and storage in tropical forests

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1504869112 ◽

2015 ◽

Vol 112 (43) ◽

pp. 13267-13271 ◽

Cited By ~ 88

Author(s):

Geertje M. F. van der Heijden ◽

Jennifer S. Powers ◽

Stefan A. Schnitzer

Keyword(s):

Tropical Forests ◽

Large Scale ◽

Net Primary Production ◽

Carbon Dynamics ◽

Carbon Accumulation ◽

Carbon Uptake ◽

Woody Vines ◽

Significant Difference ◽

Agent Of Change ◽

The Impact

Tropical forests store vast quantities of carbon, account for one-third of the carbon fixed by photosynthesis, and are a major sink in the global carbon cycle. Recent evidence suggests that competition between lianas (woody vines) and trees may reduce forest-wide carbon uptake; however, estimates of the impact of lianas on carbon dynamics of tropical forests are crucially lacking. Here we used a large-scale liana removal experiment and found that, at 3 y after liana removal, lianas reduced net above-ground carbon uptake (growth and recruitment minus mortality) by ∼76% per year, mostly by reducing tree growth. The loss of carbon uptake due to liana-induced mortality was four times greater in the control plots in which lianas were present, but high variation among plots prevented a significant difference among the treatments. Lianas altered how aboveground carbon was stored. In forests where lianas were present, the partitioning of forest aboveground net primary production was dominated by leaves (53.2%, compared with 39.2% in liana-free forests) at the expense of woody stems (from 28.9%, compared with 43.9%), resulting in a more rapid return of fixed carbon to the atmosphere. After 3 y of experimental liana removal, our results clearly demonstrate large differences in carbon cycling between forests with and without lianas. Combined with the recently reported increases in liana abundance, these results indicate that lianas are an important and increasing agent of change in the carbon dynamics of tropical forests.

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The Association between COMT Val158Met Polymorphism and the Post-Traumatic Stress Disorder Risk: A Meta-Analysis

Neuropsychobiology ◽

10.1159/000514076 ◽

2021 ◽

pp. 1-14

Author(s):

Mi Su ◽

Yongyan Song

Keyword(s):

Post Traumatic Stress Disorder ◽

Traumatic Stress ◽

Large Scale ◽

Stress Disorder ◽

Meta Analysis ◽

Cochrane Library ◽

Post Traumatic Stress ◽

Val158met Polymorphism ◽

Post Traumatic ◽

The Impact

Background: Genetic factors were suggested to have influence on the development of post-traumatic stress disorder (PTSD). The possible association between catechol-O-methyltransferase (COMT) Val158Met polymorphism and PTSD has been evaluated in several studies. But the results were still controversial. Therefore, we conduct this meta-analysis to address these issues. Methods: The PubMed, EMBASE, Cochrane Library, and Web of Science databases were searched for eligible studies. The pooled odds ratio (OR) with 95% confidence interval (CI) was calculated to estimate the association between COMT Val158Met polymorphism and PTSD. Results: Five articles including 6 studies with 893 cases and 968 controls were finally included in the present meta-analysis. The pooled analyses did not demonstrate a significant association between the COMT Val158Met polymorphism and PTSD in any of the selected genetic models: allele model (OR = 1.13, 95% CI: 0.97–1.31), dominant model (OR = 1.17, 95% CI: 0.93–1.46), recessive model (OR = 1.44, 95% CI: 0.78–2.66), and additive model (OR = 1.54, 95% CI: 0.85–2.80). Subgroup analyses suggested that the Hardy-Weinberg equilibrium status of genotype distributions could influence the relationship of COMT Val158Met polymorphism and PTSD. Conclusions: The present meta-analysis suggested that the COMT Val158Met polymorphism may not be associated with the PTSD risk. Further large-scale and population-representative studies are warranted to evaluate the impact of the COMT Val158Met polymorphism on the risk of PTSD.

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Informal nature experience on the school playground

International Journal for Transformative Research ◽

10.1515/ijtr-2015-0004 ◽

2015 ◽

Vol 2 (1) ◽

pp. 18-25 ◽

Cited By ~ 3

Author(s):

Andreas Raith

Keyword(s):

Primary Schools ◽

Large Scale ◽

School Teacher ◽

Meta Analysis ◽

Educational Institutions ◽

Primary School Teacher ◽

School Playgrounds ◽

First Results ◽

The Impact ◽

Nature Experience

Abstract In Germany, all-day care and all-day schooling are currently increasing on a large-scale. The extended time children spend in educational institutions could potentially result in limited access to nature experience for children. On the other hand, it could equally create opportunities for informal nature experience if school playgrounds have a specific nature-oriented design. This article is written from the perspective of a primary school teacher and presents the findings of a meta-analysis which looks at the impact nature experience has on the development of children. Furthermore, the first results of a research study on green playgrounds in primary schools is discussed. The results so far seem to indicate that green school playgrounds have the potential of providing nature experience particularly for primary students

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A systematic review and meta-analysis of the impact of sleep duration on adiposity and components of energy balance

10.37766/inplasy2020.7.0073 ◽

2020 ◽

Author(s):

Li Tong ◽

Shi Xiaoshuang ◽

Teng Rufeng ◽

Liang Fengxia ◽

Chen Rui ◽

...

Keyword(s):

Systematic Review ◽

Energy Balance ◽

Sleep Duration ◽

Meta Analysis ◽

The Impact

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Association Analysis and Meta-Analysis of Multi-allelic Variants for Large Scale Sequence Data

10.1101/197913 ◽

2017 ◽

Author(s):

Xiaowei Zhan ◽

Sai Chen ◽

Yu Jiang ◽

Mengzhen Liu ◽

William G. Iacono ◽

...

Keyword(s):

Large Scale ◽

Rare Variants ◽

Sequence Data ◽

Meta Analysis ◽

Joint Modeling ◽

Allelic Variants ◽

Association Analyses ◽

Link Type ◽

Gene Level ◽

The Impact

AbstractMotivation:There is great interest to understand the impact of rare variants in human diseases using large sequence datasets. In deep sequences datasets of >10,000 samples, ∼10% of the variant sites are observed to be multi-allelic. Many of the multi-allelic variants have been shown to be functional and disease relevant. Proper analysis of multi-allelic variants is critical to the success of a sequencing study, but existing methods do not properly handle multi-allelic variants and can produce highly misleading association results.Results:We propose novel methods to encode multi-allelic sites, conduct single variant and gene-level association analyses, and perform meta-analysis for multi-allelic variants. We evaluated these methods through extensive simulations and the study of a large meta-analysis of ∼18,000 samples on the cigarettes-per-day phenotype. We showed that our joint modeling approach provided an unbiased estimate of genetic effects, greatly improved the power of single variant association tests, and enhanced gene-level tests over existing approaches.Availability:Software packages implementing these methods are available at (https://github.com/zhanxw/rvtestshttp://genome.sph.umich.edu/wiki/RareMETAL).Contact:[email protected]; [email protected]

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TDD Dynamics: Understanding the Impact of Test-Driven Development on Software Quality and Productivity

10.32920/ryerson.14661051.v1 ◽

2021 ◽

Author(s):

Yahha Rafique

Keyword(s):

Empirical Research ◽

Large Scale ◽

Meta Analysis ◽

Empirical Studies ◽

Extreme Programming ◽

Second Phase ◽

Moderator Variables ◽

Empirical Measures ◽

Test Driven Development ◽

The Impact

Test-Driven Development (TDD) is one of the cornerstone practices of the Extreme Programming agile methodology. Today, despite the large scale adoption of TDD in industry, including large software firms such as Microsoft and IBM, its usefulness with regard to the quality and productivity constructs it still under question. Empirical Research has failed to produce conclusive results; all possible results have been reported for both constructs. This research adopts non-empirical measures to gain a deeper understanding of TDD. A two-phased approach has been undertaken towards the goal. The first phase involves conducting a meta-analysis of past empirical research. The meta-analysis quantitatively combines the results of individual empirical studies and identifies moderator variables that could potentially govern the performance of TDD. The second phase of the approach involves the construction of a simulation model of a TDD-based development process. The presented model further analyzes the impact of changes in moderator variables.

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Efficacy and safety profile of doxofylline compared to theophylline in asthma: a meta-analysis

Multidisciplinary Respiratory Medicine ◽

10.4081/mrm.2019.26 ◽

2019 ◽

Vol 14 ◽

Author(s):

Paola Rogliani ◽

Luigino Calzetta ◽

Josuel Ora ◽

Mario Cazzola ◽

Maria Gabriella Matera

Keyword(s):

Safety Profile ◽

Large Scale ◽

Meta Analysis ◽

Forced Expiratory Volume ◽

Chronic Obstructive ◽

Efficacy And Safety ◽

Major Drawback ◽

Asthmatic Patients ◽

Quantitative Synthesis ◽

The Impact

Background: Oral methylxanthines are effective drugs for the treatment of chronic obstructive respiratory disorders. The novel methylxanthine doxofylline, that has bronchodilator and anti-inflammatory activities, is not affected by the major drawback of theophylline. Nowadays large-scale quantitative synthesis comparing the efficacy and safety profile of doxofylline vs. theophylline in the treatment of asthma is still lacking. Therefore, we performed a quantitative synthesis to compare the efficacy/safety profile of doxofylline and theophylline in asthma. Methods: A pairwise and network meta-analyses were performed to assess the impact of doxofylline vs. theophylline and placebo on the change in asthma events, risk of adverse events (AEs), forced expiratory volume in 1 s (FEV1), and salbutamol use. Results: Data obtained from 696 asthmatic patients were extracted from 4 randomized controlled trials published between 2015 and 2018. Doxofylline was significantly (P < 0.05) more effective than theophylline in reducing the daily asthma events (mean difference − 0.14, 95%CI -0.27 – 0.00) and risk of AEs (relative risk 0.76, 95%CI 0.59–0.99). Doxofylline was as effective as theophylline in improving FEV1, and a trend of superiority (P = 0.058) was detected for doxofylline over theophylline with respect to the reduction in the use of salbutamol as rescue medication. The rank of effectiveness was doxofylline>theophylline> > placebo, and the rank of safety was placebo>doxofylline> > theophylline. Conclusions: Doxofylline is an effective and safe methylxanthine for the treatment of asthma, with an efficacy/ safety profile greater than that of theophylline. Trial registration: Meta-analysis registration: CRD42019119849.

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Meta-Analysis of the Relationship Between the Big Five and Academic Success at University

Zeitschrift für Psychologie / Journal of Psychology ◽

10.1027/0044-3409.215.2.132 ◽

2007 ◽

Vol 215 (2) ◽

pp. 132-151 ◽

Cited By ~ 110

Author(s):

Sabrina Trapmann ◽

Benedikt Hell ◽

Jan-Oliver W. Hirn ◽

Heinz Schuler

Keyword(s):

Academic Success ◽

Big Five ◽

Large Scale ◽

Meta Analysis ◽

Correlation Coefficients ◽

The United States ◽

Personality Factors ◽

Big Five Personality ◽

Meta Analyses ◽

The Impact

Abstract. Interest in the prediction of academic success in higher education has grown considerably in recent years in German-speaking countries. While the validity of school grades and admission tests has been investigated by meta-analyses and large-scale studies at least in the United States, less is known about noncognitive predictors of academic success. The present meta-analysis investigates the impact of the Big Five personality factors on academic success at university. A total of 258 correlation coefficients from 58 studies published since 1980 were included. Grades, retention, and satisfaction served as success criteria. Correlations were corrected for attenuation caused by measurement error. Results show that the influence of personality traits on academic achievement depends on the success criterion. While Neuroticism is related to academic satisfaction (? = -.369, k = 8), Conscientiousness correlates with grades (? = .269, k = 41). Extraversion, Openness to Experience, and Agreeableness have no significant impact on academic success. Moderator analyses suggest effects of culture for the validity of Extraversion. Parallels to validity for job performance are identified and implications for admission and counseling of students are discussed.

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Graphing Ecotoxicology: The MAGIC Graph for Linking Environmental Data on Chemicals

Data ◽

10.3390/data4010034 ◽

2019 ◽

Vol 4 (1) ◽

pp. 34 ◽

Cited By ~ 3

Author(s):

Sascha Bub ◽

Jakob Wolfram ◽

Sebastian Stehle ◽

Lara Petschick ◽

Ralf Schulz

Keyword(s):

Large Scale ◽

Meta Analysis ◽

Environmental Data ◽

Relational Data ◽

Chemical Information ◽

Graph Database ◽

Data Systems ◽

Large Scale Analysis ◽

Multiple Data ◽

The Impact

Assessing the impact of chemicals on the environment and addressing subsequent issues are two central challenges to their safe use. Environmental data are continuously expanding, requiring flexible, scalable, and extendable data management solutions that can harmonize multiple data sources with potentially differing nomenclatures or levels of specificity. Here, we present the methodological steps taken to construct a rule-based labeled property graph database, the “Meta-analysis of the Global Impact of Chemicals” (MAGIC) graph, for potential environmental impact chemicals (PEIC) and its subsequent application harmonizing multiple large-scale databases. The resulting data encompass 16,739 unique PEICs attributed to their corresponding chemical class, stereo-chemical information, valid synonyms, use types, unique identifiers (e.g., Chemical Abstract Service registry number CAS RN), and others. These data provide researchers with additional chemical information for a large amount of PEICs and can also be publicly accessed using a web interface. Our analysis has shown that data harmonization can increase up to 98% when using the MAGIC graph approach compared to relational data systems for datasets with different nomenclatures. The graph database system and its data appear more suitable for large-scale analysis where traditional (i.e., relational) data systems are reaching conceptional limitations.

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Association Analysis and Meta-Analysis of Multi-Allelic Variants for Large-Scale Sequence Data

Genes ◽

10.3390/genes11050586 ◽

2020 ◽

Vol 11 (5) ◽

pp. 586

Author(s):

Yu Jiang ◽

Sai Chen ◽

Xingyan Wang ◽

Mengzhen Liu ◽

William G. Iacono ◽

...

Keyword(s):

Large Scale ◽

Rare Variants ◽

Sequence Data ◽

Meta Analysis ◽

Joint Modeling ◽

Allelic Variants ◽

Association Analyses ◽

Software Packages ◽

Gene Level ◽

The Impact

There is great interest in understanding the impact of rare variants in human diseases using large sequence datasets. In deep sequence datasets of >10,000 samples, ~10% of the variant sites are observed to be multi-allelic. Many of the multi-allelic variants have been shown to be functional and disease-relevant. Proper analysis of multi-allelic variants is critical to the success of a sequencing study, but existing methods do not properly handle multi-allelic variants and can produce highly misleading association results. We discuss practical issues and methods to encode multi-allelic sites, conduct single-variant and gene-level association analyses, and perform meta-analysis for multi-allelic variants. We evaluated these methods through extensive simulations and the study of a large meta-analysis of ~18,000 samples on the cigarettes-per-day phenotype. We showed that our joint modeling approach provided an unbiased estimate of genetic effects, greatly improved the power of single-variant association tests among methods that can properly estimate allele effects, and enhanced gene-level tests over existing approaches. Software packages implementing these methods are available online.

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