A population‐averaged approach to diagnostic test meta‐analysis

The meta‐analysis of diagnostic accuracy studies is often of interest in screening programs for many diseases. The typical summary statistics for studies chosen for a diagnostic accuracy meta‐analysis are often two dimensional: sensitivities and specificities. The common statistical analysis approach for the meta‐analysis of diagnostic studies is based on the bivariate generalized linear‐mixed model (BGLMM), which has study‐specific interpretations. In this article, we present a population‐averaged (PA) model using generalized estimating equations (GEE) for making inference on mean specificity and sensitivity of a diagnostic test in the population represented by the meta‐analytic studies. We also derive the marginalized counterparts of the regression parameters from the BGLMM. We illustrate the proposed PA approach through two dataset examples and compare performance of estimators of the marginal regression parameters from the PA model with those of the marginalized regression parameters from the BGLMM through Monte Carlo simulation studies. Overall, both marginalized BGLMM and GEE with sandwich standard errors maintained nominal 95% confidence interval coverage levels for mean specificity and mean sensitivity in meta‐analysis of 25 of more studies even under misspecification of the covariance structure of the bivariate positive test counts for diseased and nondiseased subjects.     

Psychotherapies for depression in low‐ and middle‐income countries: a meta‐analysis

Most psychotherapies for depression have been developed in high‐income Western countries of North America, Europe and Australia. A growing number of randomized trials have examined the effects of these treatments in non‐Western countries. We conducted a meta‐analysis of these studies to examine whether these psychotherapies are effective and to compare their effects between studies from Western and non‐Western countries. We conducted systematic searches in bibliographical databases and included 253 randomized controlled trials, of which 32 were conducted in non‐Western countries. The effects of psychotherapies in non‐Western countries were large (g=1.10; 95% CI: 0.91‐1.30), with high heterogeneity (I²=90; 95% CI: 87‐92). After adjustment for publication bias, the effect size dropped to g=0.73 (95% CI: 0.51‐0.96). Subgroup analyses did not indicate that adaptation to the local situation was associated with the effect size. Comparisons with the studies in Western countries showed that the effects of the therapies were significantly larger in non‐Western countries, also after adjusting for characteristics of the participants, the treatments and the studies. These larger effect sizes in non‐Western countries may reflect true differences indicating that therapies are indeed more effective; or may be explained by the care‐as‐usual control conditions in non‐Western countries, often indicating that no care was available; or may be the result of the relative low quality of many trials in the field. This study suggests that psychotherapies that were developed in Western countries may or may not be more effective in non‐Western countries, but they are probably no less effective and can therefore also be used in these latter countries.     

The Use of Two‐Way Linear Mixed Models in Multitreatment Meta‐Analysis

Summary Meta‐analysis summarizes the results of a series of trials. When more than two treatments are included in the trials and when the set of treatments tested differs between trials, the combination of results across trials requires some care. Several methods have been proposed for this purpose, which feature under different labels, such as network meta‐analysis or mixed treatment comparisons. Two types of linear mixed model can be used for meta‐analysis. The one expresses the expected outcome of treatments as a contrast to a baseline treatment. The other uses a classical two‐way linear predictor with main effects for treatment and trial. In this article, we compare both types of model and explore under which conditions they give equivalent results. We illustrate practical advantages of the two‐way model using two published datasets. In particular, it is shown that between‐trial heterogeneity as well as inconsistency between different types of trial is straightforward to account for.     

The influence of male age on within‐pair and extra‐pair paternity in passerines

Although male age has often been found to predict success in gaining extra‐pair paternity, it is unclear whether this gain is associated with an individual’s success in avoiding cuckoldry. We examined the relationship between male age and both within‐ and extra‐pair paternity in passerines using a meta‐analytical approach. There was a positive correlation between male age and success in extra‐pair paternity but little evidence for an association between male age and within‐pair paternity. In addition, effect sizes for male within‐pair paternity and male extra‐pair paternity were not significantly correlated. Thus, factors that predict success in obtaining extra‐pair paternity, such as male age, may not necessarily predict success in avoiding cuckoldry.     

Interleukin‐8 ‐251A/T gene polymorphism and lung cancer susceptibility: a meta‐analysis

Many studies have examined the association between the interleukin‐8 ‐251T/A ( rs4073 ) gene polymorphism and lung cancer risk in various populations, but the results have been inconsistent. In this meta‐analysis, PubMed was searched for case–control studies published through 01 December 2013. The data were extracted, and pooled odds ratios (OR) with 95% confidence intervals (CI) were calculated. We assessed six published studies on the association between the interleukin‐8 ‐251T/A polymorphism and lung cancer risk. The included studies yielded a total of 3265 lung cancer cases and 3607 controls. For the homozygous A/A and A allele carriers (T/A + A/A), the pooled ORs for all studies combining 3265 cases and 3607 controls were 1.03 (95% CI = 0.92–1.14; P = 0.235 for heterogeneity) and 1.07 (95% CI = 0.96–1.19; P = 0.245 for heterogeneity) when compared with the homozygous wild‐type genotype (T/T). When the analysis was stratified by ethnicity, significant risks were found among Asians for both the A allele carriers and the homozygous A/A individuals. However, no significant associations were found in non‐Asian populations using any of the genetic models. This meta‐analysis suggests that the interleukin‐8 ‐251A allele confer an increased risk for the development of lung cancer among Asians.     

Bottom‐up vs. top‐down effects on terrestrial insect herbivores: a meta‐analysis

Primary consumers are under strong selection from resource (‘bottom‐up’) and consumer (‘top‐down’) controls, but the relative importance of these selective forces is unknown. We performed a meta‐analysis to compare the strength of top‐down and bottom‐up forces on consumer fitness, considering multiple predictors that can modulate these effects: diet breadth, feeding guild, habitat/environment, type of bottom‐up effects, type of top‐down effects and how consumer fitness effects are measured. We focused our analyses on the most diverse group of primary consumers, herbivorous insects, and found that in general top‐down forces were stronger than bottom‐up forces. Notably, chewing, sucking and gall‐making herbivores were more affected by top‐down than bottom‐up forces, top‐down forces were stronger than bottom‐up in both natural and controlled (cultivated) environments, and parasitoids and predators had equally strong top‐down effects on insect herbivores. Future studies should broaden the scope of focal consumers, particularly in understudied terrestrial systems, guilds, taxonomic groups and top‐down controls (e.g. pathogens), and test for more complex indirect community interactions. Our results demonstrate the surprising strength of forces exerted by natural enemies on herbivorous insects, and thus the necessity of using a tri‐trophic approach when studying insect‐plant interactions.     

Nonindependence and sensitivity analyses in ecological and evolutionary meta‐analyses

Meta‐analysis is an important tool for synthesizing research on a variety of topics in ecology and evolution, including molecular ecology, but can be susceptible to nonindependence. Nonindependence can affect two major interrelated components of a meta‐analysis: (i) the calculation of effect size statistics and (ii) the estimation of overall meta‐analytic estimates and their uncertainty. While some solutions to nonindependence exist at the statistical analysis stages, there is little advice on what to do when complex analyses are not possible, or when studies with nonindependent experimental designs exist in the data. Here we argue that exploring the effects of procedural decisions in a meta‐analysis (e.g. inclusion of different quality data, choice of effect size) and statistical assumptions (e.g. assuming no phylogenetic covariance) using sensitivity analyses are extremely important in assessing the impact of nonindependence. Sensitivity analyses can provide greater confidence in results and highlight important limitations of empirical work (e.g. impact of study design on overall effects). Despite their importance, sensitivity analyses are seldom applied to problems of nonindependence. To encourage better practice for dealing with nonindependence in meta‐analytic studies, we present accessible examples demonstrating the impact that ignoring nonindependence can have on meta‐analytic estimates. We also provide pragmatic solutions for dealing with nonindependent study designs, and for analysing dependent effect sizes. Additionally, we offer reporting guidelines that will facilitate disclosure of the sources of nonindependence in meta‐analyses, leading to greater transparency and more robust conclusions.     

A matrix‐based method of moments for fitting the multivariate random effects model for meta‐analysis and meta‐regression

Multivariate meta‐analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between‐study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta‐regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example.     

Multivariate meta‐analysis with an increasing number of parameters

Meta‐analysis can average estimates of multiple parameters, such as a treatment's effect on multiple outcomes, across studies. Univariate meta‐analysis (UVMA) considers each parameter individually, while multivariate meta‐analysis (MVMA) considers the parameters jointly and accounts for the correlation between their estimates. The performance of MVMA and UVMA has been extensively compared in scenarios with two parameters. Our objective is to compare the performance of MVMA and UVMA as the number of parameters, p, increases. Specifically, we show that (i) for fixed‐effect (FE) meta‐analysis, the benefit from using MVMA can substantially increase as p increases; (ii) for random effects (RE) meta‐analysis, the benefit from MVMA can increase as p increases, but the potential improvement is modest in the presence of high between‐study variability and the actual improvement is further reduced by the need to estimate an increasingly large between study covariance matrix; and (iii) when there is little to no between‐study variability, the loss of efficiency due to choosing RE MVMA over FE MVMA increases as p increases. We demonstrate these three features through theory, simulation, and a meta‐analysis of risk factors for non‐Hodgkin lymphoma.     

Circulating trimethylamine N‐oxide and the risk of cardiovascular diseases: a systematic review and meta‐analysis of 11 prospective cohort studies

Circulating trimethylamine N‐oxide (TMAO), a canonical metabolite from gut flora, has been related to the risk of cardiovascular disorders. However, the association between circulating TMAO and the risk of cardiovascular events has not been quantitatively evaluated. We performed a systematic review and meta‐analysis of all available cohort studies regarding the association between baseline circulating TMAO and subsequent cardiovascular events. Embase and PubMed databases were searched for relevant cohort studies. The overall hazard ratios for the developing of cardiovascular events (CVEs) and mortality were extracted. Heterogeneity among the included studies was evaluated with Cochran's Q Test and I² statistics. A random‐effect model or a fixed‐effect model was applied depending on the heterogeneity. Subgroup analysis and meta‐regression were used to evaluate the source of heterogeneity. Among the 11 eligible studies, three reported both CVE and mortality outcome, one reported only CVEs and the other seven provided mortality data only. Higher circulating TMAO was associated with a 23% higher risk of CVEs (HR = 1.23, 95% CI: 1.07–1.42, I² = 31.4%) and a 55% higher risk of all‐cause mortality (HR = 1.55, 95% CI: 1.19–2.02, I² = 80.8%). Notably, the latter association may be blunted by potential publication bias, although sensitivity analysis by omitting one study at a time did not significantly change the results. Further subgroup analysis and meta‐regression did not support that the location of the study, follow‐up duration, publication year, population characteristics or the samples of TMAO affect the results significantly. Higher circulating TMAO may independently predict the risk of subsequent cardiovascular events and mortality.     

LMO1 polymorphisms and the risk of neuroblastoma: Assessment of meta‐analysis of case‐control studies

Neuroblastoma (NB), a neuroendocrine tumour, is one of the most prevalent cancers in children. The link between LMO1 polymorphisms and NB has been investigated by several groups, rendering inconclusive results. Here, with this comprehensive systematic review and up‐to‐date meta‐analysis, we aim to distinctively elucidate the possible correlation between LMO1 polymorphisms and NB susceptibility. Eligible studies were systematically researched and identified using PubMed, Web of Science and Scopus databases up to 10 February 2019. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the strength of the associations. Our findings revealed that rs110419 and rs2168101 polymorphisms were significantly associated with a decreased risk of NB in all genetic models. In addition, the rs4758051 variant appeared protective against NB in homozygous, dominant and allele genetic models, whereas the rs10840002 variant markedly decreased the risk of NB in the allele model. In contrast, the rs204938 polymorphism showed a positive association with NB susceptibility in allele genetic models. In summary, our meta‐analysis is the first to provide clear evidence of an association between specific polymorphisms of LMO1 and susceptibility to NB. Of note, additional larger well‐designed studies would be helpful to further evaluate and confirm this association.     

Evaluation of association of maternal IL‐10 polymorphisms with risk of preeclampsia by A meta‐analysis

Emerging evidence shows that interleukin (IL)‐10 gene polymorphisms can regulate its expression level and thus influence person's susceptibility to preeclampsia. However, various published results were inconsistent. To explore the association between maternal IL‐10 gene polymorphisms and preeclampsia, we performed a meta‐analysis based upon 11 individual studies here. Our meta‐analysis results indicated that IL‐10 ‐819C/T (C versus T, OR = 1.28, 95% CI = 1.08–1.50, P = 0.003) and ‐592C/A (C versus A, OR = 1.28, 95% CI = 1.03–1.59, P = 0.03) polymorphisms were associated with preeclampsia. Although there was no overall association between ‐1082A/G polymorphism and preeclampsia (G versus A, OR = 0.93, 95% CI = 0.77–1.13, P = 0.49), such association existed among Asian (G versus A, OR = 1.29, 95% CI = 1.04–1.60, P = 0.02) and South American (G versus A, OR = 0.72, 95% CI = 0.54–0.94, P = 0.02) populations in the subgroup analysis stratified by continents.     

Hemispheric‐scale patterns of climate‐related shifts in planktonic diatoms from North American and European lakes

A synthesis of over 200 diatom‐based paleolimnological records from nonacidified/nonenriched lakes reveals remarkably similar taxon‐specific shifts across the Northern Hemisphere since the 19th century. Our data indicate that these diatom shifts occurred in conjunction with changes in freshwater habitat structure and quality, which, in turn, we link to hemispheric warming trends. Significant increases in the relative abundances of planktonic Cyclotella taxa (P<0.01) were concurrent with sharp declines in both heavily silicified Aulacoseira taxa (P<0.01) and benthic Fragilaria taxa (P<0.01). We demonstrate that this trend is not limited to Arctic and alpine environments, but that lakes at temperate latitudes are now showing similar ecological changes. As expected, the onset of biological responses to warming occurred significantly earlier (P<0.05) in climatically sensitive Arctic regions (median age=ad 1870) compared with temperate regions (median age=ad 1970). In a detailed paleolimnological case study, we report strong relationships (P<0.005) between sedimentary diatom data from Whitefish Bay, Lake of the Woods (Ontario, Canada), and long‐term changes in air temperature and ice‐out records. Other potential environmental factors, such as atmospheric nitrogen deposition, could not explain our observations. These data provide clear evidence that unparalleled warming over the last few decades resulted in substantial increases in the length of the ice‐free period that, similar to 19th century changes in high‐latitude lakes, likely triggered a reorganization of diatom community composition. We show that many nonacidified, nutrient‐poor, freshwater ecosystems throughout the Northern Hemisphere have crossed important climatically induced ecological thresholds. These findings are worrisome, as the ecological changes that we report at both mid‐ and high‐latitude sites have occurred with increases in mean annual air temperature that are less than half of what is projected for these regions over the next half century.     

Tardive dyskinesia risk with first‐ and second‐generation antipsychotics in comparative randomized controlled trials: a meta‐analysis

Tardive dyskinesia (TD) risk with D2/serotonin receptor antagonists or D2 receptor partial agonists (second‐generation antipsychotics, SGAs) is considered significantly lower than with D2 antagonists (first‐generation antipsychotics, FGAs). As some reports questioned this notion, we meta‐analyzed randomized controlled studies (RCTs) to estimate the risk ratio (RR) and annualized rate ratio (RaR) of TD comparing SGAs vs. FGAs and SGAs vs. SGAs. Additionally, we calculated raw and annualized pooled TD rates for each antipsychotic. Data from 57 head‐to‐head RCTs, including 32 FGA and 86 SGA arms, were meta‐analyzed, yielding 32 FGA‐SGA pairs and 35 SGA‐SGA pairs. The annualized TD incidence across FGA arms was 6.5% (95% CI: 5.3‐7.8%) vs. 2.6% (95% CI: 2.0‐3.1%) across SGA arms. TD risk and annualized rates were lower with SGAs vs. FGAs (RR=0.47, 95% CI: 0.39‐0.57, p<0.0001, k=28; RaR=0.35, 95% CI: 0.28‐0.45, p<0.0001, number‐needed‐to‐treat, NNT=20). Meta‐regression showed no FGA dose effect on FGA‐SGA comparisons (Z=?1.03, p=0.30). FGA‐SGA TD RaRs differed by SGA comparator (Q=21.8, df=7, p=0.003), with a significant advantage of olanzapine and aripiprazole over other non‐clozapine SGAs in exploratory pairwise comparisons. SGA‐SGA comparisons confirmed the olanzapine advantage vs. non‐clozapine SGAs (RaR=0.66, 95% CI: 0.49‐0.88, p=0.006, k=17, NNT=100). This meta‐analysis confirms a clinically meaningfully lower TD risk with SGAs vs. FGAs, which is not driven by high dose FGA comparators, and documents significant differences with respect to this risk between individual SGAs.     

Soil carbon stock change following afforestation in Northern Europe: a meta‐analysis

Northern Europe supports large soil organic carbon (SOC) pools and has been subjected to high frequency of land‐use changes during the past decades. However, this region has not been well represented in previous large‐scale syntheses of land‐use change effects on SOC, especially regarding effects of afforestation. Therefore, we conducted a meta‐analysis of SOC stock change following afforestation in Northern Europe. Response ratios were calculated for forest floors and mineral soils (0–10 cm and 0–20/30 cm layers) based on paired control (former land use) and afforested plots. We analyzed the influence of forest age, former land‐use, forest type, and soil textural class. Three major improvements were incorporated in the meta‐analysis: analysis of major interaction groups, evaluation of the influence of nonindependence between samples according to study design, and mass correction. Former land use was a major factor contributing to changes in SOC after afforestation. In former croplands, SOC change differed between soil layers and was significantly positive (20%) in the 0–10 cm layer. Afforestation of former grasslands had a small negative (nonsignificant) effect indicating limited SOC change following this land‐use change within the region. Forest floors enhanced the positive effects of afforestation on SOC, especially with conifers. Meta‐estimates calculated for the periods <30 years and >30 years since afforestation revealed a shift from initial loss to later gain of SOC. The interaction group analysis indicated that meta‐estimates in former land‐use, forest type, and soil textural class alone were either offset or enhanced when confounding effects among variable classes were considered. Furthermore, effect sizes were slightly overestimated if sample dependence was not accounted for and if no mass correction was performed. We conclude that significant SOC sequestration in Northern Europe occurs after afforestation of croplands and not grasslands, and changes are small within a 30‐year perspective.     

Explaining global variation in the latitudinal diversity gradient: Meta‐analysis confirms known patterns and uncovers new ones

Aim

The pattern of increasing biological diversity from high latitudes to the equator [latitudinal diversity gradient (LDG)] has been recognized for > 200 years. Empirical studies have documented this pattern across many different organisms and locations. Our goal was to quantify the evidence for the global LDG and the associated spatial, taxonomic and environmental factors. We performed a meta‐analysis on a large number of individual LDGs that have been published in the 14 years since Hillebrand's ground‐breaking meta‐analysis of the LDG, using meta‐analysis and meta‐regression approaches largely new to the fields of ecology and biogeography.

Location

Global.

Time period

January 2003–September 2015.

Major taxa studied

Bacteria, protists, plants, fungi and animals.

Methods

We synthesized the outcomes of 389 individual cases of LDGs from 199 papers published since 2003, using hierarchical mixed‐effects meta‐analysis and multiple meta‐regression. Additionally, we re‐analysed Hillebrand's original dataset using modern methods.

Results

We confirmed the generality of the LDG, but found the pattern to be weaker than was found in Hillebrand's study. We identified previously unreported variation in LDG strength and slope across longitude, with evidence that the LDG is strongest in the Western Hemisphere. Locational characteristics, such as habitat and latitude range, contributed significantly to LDG strength, whereas organismal characteristics, including taxonomic group and trophic level, did not. Modern meta‐analytical models that incorporate hierarchical structure led to more conservative and sometimes contrasting effect size estimates relative to Hillebrand's initial analysis, whereas meta‐regression revealed underlying patterns in Hillebrand's dataset that were not apparent with a traditional analysis.

Main conclusions

We present evidence of global latitudinal, longitudinal and habitat‐based patterns in the LDG, which are apparent across both marine and terrestrial realms and over a broad taxonomic range of organisms, from bacteria to plants and vertebrates.     

Meta‐analyzing the likely cross‐species responses to climate change

Ecological Niche Models (ENMs) have different performances in predicting potential geographic distributions. Here we meta‐analyzed the likely effects of climate change on the potential geographic distribution of 1,205 bird species from the Neotropical region, modeled using eight ENMs and three Atmosphere‐Ocean General Circulation Models (AOGCM). We considered the variability in ENMs performance to estimate a weighted mean difference between potential geographic distributions for baseline and future climates. On average, potential future ranges were projected to be from 25.7% to 44.5% smaller than current potential ranges across species. However, we found that 0.2% to 18.3% of the total variance in range shifts occurred “within species” (i.e., owing to the use of different modeling techniques and climate models) and 81.7% to 99.8% remained between species (i.e., it could be explained by ecological correlates). Using meta‐analytical techniques akin to regression, we also showed that potential range shifts are barely predicted by bird biological traits. We demonstrated that one can combine and reduce species‐specific effects with high uncertainty in ENMs and also explore potential causes of climate change effect on species using meta‐analytical tools. We also highlight that the search for powerful correlates of climate change‐induced range shifts can be a promising line of investigation.     

Predictive value of plasma copeptin level for the risk and mortality of heart failure: a meta‐analysis

Epidemiologic studies are inconsistent regarding the association between plasma copeptin level and heart failure (HF). The aim of this study was to perform a meta‐analysis to determine whether high level of copeptin is correlated with incidence of HF and mortality in patients with HF. We searched PUBMED and EMBASE databases for studies conducted from 1966 through May 2016 to identify studies reporting hazard ratio (HR) estimates with 95% confidence intervals (CIs) for the association between plasma copeptin level and HF. A random‐effects model was used to combine study‐specific risk estimates. A total of 13 studies were included in the meta‐analysis, with five studies on the incidence of HF and eight studies on the mortality of patients with HF. For incidence of HF, the summary HR indicated a borderline positive association of high plasma copeptin level with HF risk (HR, 1.60; 95% CI, 0.90–2.85). Furthermore, an increase of 1 standard deviation in log copeptin level was associated with a 17% increase in the risk of incident HF (HR, 1.17; 95% CI, 1.02–1.33). For all‐cause mortality of patients with HF, we also found a significant association between elevated plasma copeptin level and increased mortality of HF (HR, 1.76; 95% CI, 1.33–2.33). Our dose–response analysis indicated that an increment in copeptin level of 1 pmol/l was associated with a 3% increase in all‐cause mortality (HR, 1.03; 95% CI, 1.01–1.05). In conclusion, our results suggest that elevated plasma copeptin level is associated with an increased risk of HF and all‐cause mortality in patients with HF.     

Effects of climate warming on carbon fluxes in grasslands— A global meta‐analysis

Climate warming will affect terrestrial ecosystems in many ways, and warming‐induced changes in terrestrial carbon (C) cycling could accelerate or slow future warming. So far, warming experiments have shown a wide range of C flux responses, across and within biome types. However, past meta‐analyses of C flux responses have lacked sufficient sample size to discern relative responses for a given biome type. For instance grasslands contribute greatly to global terrestrial C fluxes, and to date grassland warming experiments provide the opportunity to evaluate concurrent responses of both plant and soil C fluxes. Here, we compiled data from 70 sites (in total 622 observations) to evaluate the response of C fluxes to experimental warming across three grassland types (cold, temperate, and semi‐arid), warming methods, and short (≤3 years) and longer‐term (>3 years) experiment lengths. Overall, our meta‐analysis revealed that experimental warming stimulated C fluxes in grassland ecosystems with regard to both plant production (e.g., net primary productivity (NPP) 15.4%; aboveground NPP (ANPP) by 7.6%, belowground NPP (BNPP) by 11.6%) and soil respiration (Rs) (9.5%). However, the magnitude of C flux stimulation varied significantly across cold, temperate and semi‐arid grasslands, in that responses for most C fluxes were larger in cold than temperate or semi‐arid ecosystems. In semi‐arid and temperate grasslands, ecosystem respiration (Reco) was more sensitive to warming than gross primary productivity (GPP), while the opposite was observed for cold grasslands, where warming produced a net increase in whole‐ecosystem C storage. However, the stimulatory effect of warming on ANPP and Rs observed in short‐term studies (≤3 years) in both cold and temperate grasslands disappeared in longer‐term experiments (>3 years). These results highlight the importance of conducting long‐term warming experiments, and in examining responses across a wide range of climate.     

Methane and nitrous oxide emissions under no‐till farming in China: a meta‐analysis

No‐till (NT) practices are among promising options toward adaptation and mitigation of climate change. However, the mitigation effectiveness of NT depends not only on its carbon sequestration potential but also on soil‐derived CH₄ and N₂O emissions. A meta‐analysis was conducted, using a dataset involving 136 comparisons from 39 studies in China, to identify site‐specific factors which influence CH₄ emission, CH₄ uptake, and N₂O emission under NT. Comparative treatments involved NT without residue retention (NT0), NT with residue retention (NTR), compared to plow tillage (PT) with residue removed (PT0). Overall, NT0 significantly decreased CH₄ emission by ~30% (P < 0.05) compared to PT0 with an average emission 218.8 kg ha⁻¹ for rice paddies. However, the increase in N₂O emission could partly offset the benefits of the decrease in CH₄ emission under NT compared to PT0. NTR significantly enhanced N₂O emission by 82.1%, 25.5%, and 20.8% (P < 0.05) compared to PT0 for rice paddies, acid soils, and the first 5 years of the experiments, respectively. The results from categorical meta‐analysis indicated that the higher N₂O emission could be mitigated by adopting NT within alkaline soils, for long‐term duration, and with less N fertilization input when compared to PT0. In addition, the natural log (lnR) of response ratio of CH₄ and N₂O emissions under NT correlated positively (enhancing emission) with climate factors (temperature and precipitation) and negatively (reducing emission) with experimental duration, suggesting that avoiding excess soil wetness and using NT for a long term could enhance the benefits of NT. Therefore, a thorough understanding of the conditions favoring greenhouse gas(es) reductions is essential to achieving climate change mitigation and advancing food security in China.