Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small “many analyst” study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future.

Herders’ living strategy is a function of the capitals at their disposal which also serve as a buffering mechanism when shocks arise. An insight into the connection between livelihood strategies and capitals owned by herders provides guidance to recognize their living situation. This study evaluated the different livelihood capitals of herders across the five ecological types (meadow, typical, desert, sandy, and desert steppe) in Inner Mongolia region of China, using the sustainable livelihood framework approach. An evaluation index was developed and used to investigate how the livelihood capitals of herders affects preferential selection of livelihood strategies using multinomial logit model. Results indicate that: (1) The stocks of human and social capitals were higher while those for natural, physical, and financial capitals were lower. (2) There were significant regional differences in the livelihood capital stock of herders’ families with zonal horizontal decrease from east to west. (3) Natural capitals affects the preferential selection of livelihood strategies by herders positively implying that possession of more natural capitals by herders leads to selection of livelihood strategies that are devoid of pastoral production; the preferred livelihood strategy of herders was significantly negatively affected by physical and financial capitals, an indication that, when herders possess more physical and financial capitals, they tend to choose livelihood strategies that involve pastoral production. The living strategy of herders was not affected by human and social capitals. (4) Production of rented pasture capital index affected the preferential selection of livelihood strategies by herders positively while cash income capital index had negative influence on how pastoralists select their livelihood strategies. In conclusion, the total livelihood capital of herders in Inner Mongolia is low, and there is perceived benefit in the differentiation of herders families into petty-herders and non-grazing families from the perception of natural resource management and sustainability. This requires income diversification programs such as capacity building and business education that will aid the smooth transition of households to these less resource exploiting livelihood strategies.

Livestock grazing is one of the significant causes of land degradation. However, the effect of contrasting grazing intensities on soil properties and vegetation in the southeastern Qinghai-Tibetan Plateau (QTP) is poorly understood. We studied the impact of light grazing (LG), moderate grazing (MG), heavy grazing (HG) and no grazing (NG) on vegetation characteristics and the chemical properties of soil samples taken at 0–10 cm, 10–20 cm and 20–30 cm layers from the designated grazing treatments. A total of 42 species representing 32 genera and 16 families were identified. Our result shows that HG significantly reduced total aboveground biomass, vegetation cover, canopy average height, but increased unpalatable aboveground biomass. Soil organic matter declined with increasing grazing intensity and respectively decreased to 64.51%, 65.38% and 82.40% for LG, MG and HG compared to the NG treatment and soil carbon storage exhibited a similar pattern. Soil total nitrogen and phosphorus contents decreased with increasing soil depth, while soil total potassium was not affected by grazing across soil depths. We conclude that 1 yak would have a more severe impact than 3 sheep units on the vegetation community and soil characteristics of alpine meadows in the southeastern QTP.

Fine root traits span two independent axes of variation, the conservation and collaboration axes, which define the root economic space (RES). However, whether early‐stage fine root decomposition rates (quantified as proportion mass loss, i.e. pml) are more strongly related to collaboration or conservation traits remains unclear. We studied 63 tree species in New Zealand's temperate rain forest. We determined the phylogenetic signal in pml and fine root traits, conducted phylogenetic principal component analysis and used phylogenetic generalized least squares to determine which traits are most strongly related to pml. Root decomposition exhibited a high phylogenetic signal and was more strongly related to the conservation than the collaboration axis. Root tissue density (RTD) was negatively correlated and root nitrogen (RN) was positively correlated with pml. Root diameter was positively yet weakly correlated with pml, but specific root length was uncorrelated with pml. The lignin‐to‐N ratio and root cellulose were the strongest predictors of pml. Synthesis: Early‐stage fine root decomposition is most strongly driven by tissue quality traits, such as root nitrogen, tissue density and lignin‐to‐N ratio, which all align with the conservation axis of the root economics space. However, root diameter plays a weak yet undeniable role in early‐stage fine root decomposition. Some thick‐rooted species decomposed faster, possibly due to the higher quality cortical tissue. Thin‐rooted species decomposed slower, possibly because of their higher cellulose concentration that maintains the structural integrity of small diameter roots. Relationships between decomposition and other traits that align with the collaboration gradient deserve further study across the phylogeny of vascular plants.