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What have we learned from global change manipulative experiments in China? A meta-analysis.

ABSTRACT: Although China has the largest population in the world, a faster rate of warming than the global average, and an active global change research program, results from many of the global change experiments in Chinese terrestrial ecosystems have not been included in global syntheses. Here, we specifically analyze the observed responses of carbon (C) and nitrogen (N) cycling in global change manipulative experiments in China, and compare these responses to those from other regions of the world. Most global change factors, vegetation types, and treatment methods that have been studied or used elsewhere in the world have also been studied and applied in China. The responses of terrestrial ecosystem C and N cycles to N addition and climate warming in China are similar in both direction and intensity to those reported in global syntheses. In Chinese ecosystems as elsewhere, N addition significantly increased aboveground (AGB) and belowground biomass (BGB), litter mass, dissolved organic C, net ecosystem productivity (NEP), and gross ecosystem productivity (GEP). Warming stimulated AGB, BGB and the root-shoot ratio. Increasing precipitation accelerated GEP, NEP, microbial respiration, soil respiration, and ecosystem respiration. Our findings complement and support previous global syntheses and provide insight into regional responses to global change.

SUBMITTER: Fu Z

PROVIDER: S-EPMC4513293 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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What have we learned from global change manipulative experiments in China? A meta-analysis.

Fu Zheng Z Niu Shuli S Dukes Jeffrey S JS

Scientific reports 20150724

Although China has the largest population in the world, a faster rate of warming than the global average, and an active global change research program, results from many of the global change experiments in Chinese terrestrial ecosystems have not been included in global syntheses. Here, we specifically analyze the observed responses of carbon (C) and nitrogen (N) cycling in global change manipulative experiments in China, and compare these responses to those from other regions of the world. Most ...[more]

PMID: 26205333

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Project description:BACKGROUND:In silico functional genomics have become a driving force in the way we interpret and use gene expression data, enabling researchers to understand which biological pathways are likely to be affected by the treatments or conditions being studied. There are many approaches to functional genomics, but a number of popular methods determine if a set of modified genes has a higher than expected overlap with genes known to function as part of a pathway (functional enrichment testing). Recently, researchers have started to apply such analyses in a new way: to ask if the data they are collecting show similar disruptions to biological functions compared to reference data. Examples include studying whether similar pathways are perturbed in smokers vs. users of e-cigarettes, or whether a new mouse model of schizophrenia is justified, based on its similarity in cytokine expression to a previously published model. However, there is a dearth of robust statistical methods for testing hypotheses related to these questions and most researchers resort to ad hoc approaches. The goal of this work is to develop a statistical approach to identifying gene pathways that are equivalently (or inversely) changed across two experimental conditions. RESULTS:We developed Equivalent Change Enrichment Analysis (ECEA). This is a new type of gene enrichment analysis based on a statistic that we call the equivalent change index (ECI). An ECI of 1 represents a gene that was over or under-expressed (compared to control) to the same degree across two experiments. Using this statistic, we present an approach to identifying pathways that are changed in similar or opposing ways across experiments. We compare our approach to current methods on simulated data and show that ECEA is able to recover pathways exhibiting such changes even when they exhibit complex patterns of regulation, which other approaches are unable to do. On biological data, our approach recovered pathways that appear directly connected to the condition being studied. CONCLUSIONS:ECEA provides a new way to perform gene enrichment analysis that allows researchers to compare their data to existing datasets and determine if a treatment will cause similar or opposing genomic perturbations.

Project description:Osteopathic manipulative treatment (OMT) is a distinctive modality commonly used by osteopathic physicians to complement their conventional treatment of musculoskeletal disorders. Previous reviews and meta-analyses of spinal manipulation for low back pain have not specifically addressed OMT and generally have focused on spinal manipulation as an alternative to conventional treatment. The purpose of this study was to assess the efficacy of OMT as a complementary treatment for low back pain.Computerized bibliographic searches of MEDLINE, EMBASE, MANTIS, OSTMED, and the Cochrane Central Register of Controlled Trials were supplemented with additional database and manual searches of the literature. Six trials, involving eight OMT vs control treatment comparisons, were included because they were randomized controlled trials of OMT that involved blinded assessment of low back pain in ambulatory settings. Data on trial methodology, OMT and control treatments, and low back pain outcomes were abstracted by two independent reviewers. Effect sizes were computed using Cohen's d statistic and meta-analysis results were weighted by the inverse variance of individual comparisons. In addition to the overall meta-analysis, stratified meta-analyses were performed according to control treatment, country where the trial was conducted, and duration of follow-up. Sensitivity analyses were performed for both the overall and stratified meta-analyses.Overall, OMT significantly reduced low back pain (effect size, -0.30; 95% confidence interval, -0.47 - -0.13; P = .001). Stratified analyses demonstrated significant pain reductions in trials of OMT vs active treatment or placebo control and OMT vs no treatment control. There were significant pain reductions with OMT regardless of whether trials were performed in the United Kingdom or the United States. Significant pain reductions were also observed during short-, intermediate-, and long-term follow-up.OMT significantly reduces low back pain. The level of pain reduction is greater than expected from placebo effects alone and persists for at least three months. Additional research is warranted to elucidate mechanistically how OMT exerts its effects, to determine if OMT benefits are long lasting, and to assess the cost-effectiveness of OMT as a complementary treatment for low back pain.

Dataset Information

What have we learned from global change manipulative experiments in China? A meta-analysis.

Publications

What have we learned from global change manipulative experiments in China? A meta-analysis.

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