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Background Meta-analysis is often used to make generalisations across all available evidence at the global scale. But how can these global generalisations be used for evidence-based decision making at the local scale, if the global evidence is not perceived to be relevant to local decisions? We show how an interactive method of meta-analysis—dynamic meta-analysis—can be used to assess the local relevance of global evidence. Results We developed Metadataset ( www.metadataset.com ) as a proof-of-concept for dynamic meta-analysis. Using Metadataset, we show how evidence can be filtered and weighted, and results can be recalculated, using dynamic methods of subgroup analysis, meta-regression, and recalibration. With an example from agroecology, we show how dynamic meta-analysis could lead to different conclusions for different subsets of the global evidence. Dynamic meta-analysis could also lead to a rebalancing of power and responsibility in evidence synthesis, since evidence users would be able to make decisions that are typically made by systematic reviewers—decisions about which studies to include (e.g. critical appraisal) and how to handle missing or poorly reported data (e.g. sensitivity analysis). Conclusions In this study, we show how dynamic meta-analysis can meet an important challenge in evidence-based decision making—the challenge of using global evidence for local decisions. We suggest that dynamic meta-analysis can be used for subject-wide evidence synthesis in several scientific disciplines, including agroecology and conservation biology. Future studies should develop standardised classification systems for the metadata that are used to filter and weight the evidence. Future studies should also develop standardised software packages, so that researchers can efficiently publish dynamic versions of their meta-analyses and keep them up-to-date as living systematic reviews. Metadataset is a proof-of-concept for this type of software, and it is open source. Future studies should improve the user experience, scale the software architecture, agree on standards for data and metadata storage and processing, and develop protocols for responsible evidence use.

Data on the development of two white clover cultivars (AberHerald and Huia) in mixed clover/ryegrass swards were available at 12 sites in Europe from experiments conducted for several years under a common protocol. Swards were measured up to seven times over winter and up to seven times over the growing season. In the overwintering period, detailed morphological measurements were taken for clover at each sampling time and, during the growing season, the clover contribution to total available biomass was recorded. Detailed meteorological data were available at all sites. The development of these clover/ryegrass communities over time and sites was modelled. The modelling strategy had three main elements: ( a) division of the annual growth cycle of the clover/ryegrass community into a number of functional periods; ( b) development of relationships within each functional period using models incorporating plot-level biotic variables characterizing each community at the start of the period and site-level climatic and management variables measured during the period; and ( c) introduction of a dynamic element by linking the models across functional periods. The response variable(s) for a functional period was the biotic independent variable(s) of the succeeding period. The object was to produce a dynamic series of models in which community development within and across sites was described as a resultant of the initial state of the community and climatic and other forces acting on it. The analysis used a mixed models technique in recognition of the complex error structure of the data. Various statistical aspects of the modelling are discussed including the models and fitting strategy used, the complexity of the error structure in an experiment that includes sites and years, and the desirability of transforming certain variables before modelling. The issues in presenting the results of a series of complex models are discussed and a graphical/tabular approach is outlined.

Sales research has long established that salesperson individual and team drivers are key for executing effective selling strategies. Yet radical changes in the sales context in the past decade also require today’s salespeople to adapt their selling strategies. Moreover, considering the current international selling environment, many firms pursue a wide range of attractive country markets too, which increases the complexity and challenges of managing country-specific selling strategies. The authors undertake an elasticity meta-analysis of 48 studies, conducted in seven countries and one region (Study 1), to determine the effectiveness of individual and team drivers from a dynamic and global perspective. They also perform a correlation-based meta-analysis of 328 studies conducted in 32 countries (Study 2) to assess the correlations between specific salesperson drivers and performance, and how such correlations might be conditioned by country development and cultural characteristics. The results reveal a positive elasticity of individual and team drivers on performance that decreases over time, providing managers with key empirical insights on sales management; selling skill and aptitude show greater correlation with performance than intrafirm relationship and coordination activity. The country and cultural contingency analysis further indicates a stronger correlation between salesperson drivers and performance outcomes in country markets with high unbranded competition, low resource availability, and high long-term orientation.

The risk of predation strongly affects mammalian population dynamics and community interactions. Bright moonlight is widely believed to increase predation risk for nocturnal mammals by increasing the ability of predators to detect prey, but the potential for moonlight to increase detection of predators and the foraging efficiency of prey has largely been ignored. Studies have reported highly variable responses to moonlight among species, calling into question the assumption that moonlight increases risk. Here, we conducted a quantitative meta‐analysis examining the effects of moonlight on the activity of 59 nocturnal mammal species to test the assumption that moonlight increases predation risk. We examined patterns of lunarphilia and lunarphobia across species in relation to factors such as trophic level, habitat cover preference and visual acuity. Across all species included in the meta‐analysis, moonlight suppressed activity. The magnitude of suppression was similar to the presence of a predator in experimental studies of foraging rodents (13·6% and 18·7% suppression, respectively). Contrary to the expectation that moonlight increases predation risk for all prey species, however, moonlight effects were not clearly related to trophic level and were better explained by phylogenetic relatedness, visual acuity and habitat cover. Moonlight increased the activity of prey species that use vision as their primary sensory system and suppressed the activity of species that primarily use other senses (e.g. olfaction, echolocation), and suppression was strongest in open habitat types. Strong taxonomic patterns underlay these relationships: moonlight tended to increase primate activity, whereas it tended to suppress the activity of rodents, lagomorphs, bats and carnivores. These results indicate that visual acuity and habitat cover jointly moderate the effect of moonlight on predation risk, whereas trophic position has little effect. While the net effect of moonlight appears to increase predation risk for most nocturnal mammals, our results highlight the importance of sensory systems and phylogenetic history in determining the level of risk.

Afforestation has been proposed as an effective method of carbon (C) sequestration; however, the magnitude and direction of soil carbon accumulation following afforestation and its regulation by soil nitrogen (N) dynamics are still not well understood. We synthesized the results from 292 sites and carried out a meta-analysis to evaluate the dynamics of soil C and N stocks following afforestation. Changes in soil C and N stocks were significantly correlated and had a similar temporal pattern. Significant C and N stock increases were found 30 and 50 yr after afforestation, respectively. Before these time points, C and N stocks were either depleted or unchanged. Carbon stock increased following afforestation on cropland and pasture, and in tropical, subtropical and boreal zones. The soil N stock increased in the subtropical zone. The soil C stock increased after afforestation with hardwoods such as Eucalyptus, but did not change after afforestation with softwoods such as pine. Soil N stocks increased and decreased, respectively, after afforestation with hardwoods (excluding Eucalyptus) and pine. These results indicate that soil C and N stocks both increase with time after afforestation, and that C sequestration through afforestation depends on prior land use, climate and the tree species planted.

Within the capabilities-based view of the firm, there is debate about the relative importance of ordinary and dynamic capabilities for firm performance and about the extent to which their performance effects are contingent on environmental conditions. We meta-analyze 115 studies to investigate the relationship between both ordinary and dynamic capabilities and the financial performance of firms in relatively stable versus changing environments. The results suggest that the performance effects of both types of capabilities are positive and similar in magnitude. Environmental dynamism reinforces the effects of both ordinary and dynamic capabilities. Furthermore, the two types of capabilities are closely associated. Our findings provide support for a moderate capabilities-based view of the firm, rather than one that considers dynamic capabilities as superior to ordinary ones.

The distributions of many terrestrial organisms are currently shifting in latitude or elevation in response to changing climate. Using a meta-analysis, we estimated that the distributions of species have recently shifted to higher elevations at a median rate of 11.0 meters per decade, and to higher latitudes at a median rate of 16.9 kilometers per decade. These rates are approximately two and three times faster than previously reported. The distances moved by species are greatest in studies showing the highest levels of warming, with average latitudinal shifts being generally sufficient to track temperature changes. However, individual species vary greatly in their rates of change, suggesting that the range shift of each species depends on multiple internal species traits and external drivers of change. Rapid average shifts derive from a wide diversity of responses by individual species.

Studies comparing the instructional effectiveness of dynamic versus static visualizations have produced mixed results. In this work, we investigated whether gender imbalance in the participant samples of these studies may have contributed to the mixed results. We conducted a meta-analysis of randomized experiments in which groups of students learning through dynamic visualizations were compared to groups receiving static visualizations. Our sample focused on tasks that could be categorized as either biologically secondary tasks (science, technology, engineering, and mathematics: STEM) or biologically primary tasks (manipulative-procedural). The meta-analysis of 46 studies (82 effect sizes and 5474 participants) revealed an overall small-sized effect (g⁺ =0.23) showing that dynamic visualizations were more effective than static visualizations. Regarding potential moderators, we observed that gender was influential: the dynamic visualizations were more effective on samples with less females and more males (g⁺ =0.36). We also observed that educational level, learning domain, media compared, and reporting reliability measures moderated the results. We concluded that because many visualization studies have used samples with a gender imbalance, this may be a significant factor in explaining why instructional dynamic and static visualizations seem to vary in their effectiveness. Our findings also support considering the gender variable in research about cognitive load theory and instructional visualizations.

Plant–herbivore interactions have evolved in response to coevolutionary dynamics, along with selection driven by abiotic conditions. We examine how abiotic factors influence trait expression in both plants and herbivores to evaluate how climate change will alter this long-standing interaction. The paleontological record documents increased herbivory during periods of global warming in the deep past. In phylogenetically corrected meta-analyses, we find that elevated temperatures, CO₂ concentrations, drought stress and nutrient conditions directly and indirectly induce greater food consumption by herbivores. Additionally, elevated CO₂ delays herbivore development, but increased temperatures accelerate development. For annual plants, higher temperatures, CO₂ and drought stress increase foliar herbivory. Our meta-analysis also suggests that greater temperatures and drought may heighten florivory in perennials. Human actions are causing concurrent shifts in CO₂, temperature, precipitation regimes and nitrogen deposition, yet few studies evaluate interactions among these changing conditions. We call for additional multifactorial studies that simultaneously manipulate multiple climatic factors, which will enable us to generate more robust predictions of how climate change could disrupt plant–herbivore interactions. Finally, we consider how shifts in insect and plant phenology and distribution patterns could lead to ecological mismatches, and how these changes may drive future adaptation and coevolution between interacting species.

Drawing from Marks, Mathieu, and Zaccaro (2001), we proposed that narrowly focused teamwork processes load onto 3 higher‐order teamwork process dimensions, which in turn load onto a general teamwork process factor. Results of model testing using meta‐analyses of relationships among narrow teamwork processes provided support for the structure of this multidimensional theory of teamwork process. Meta‐analytic results also indicated that teamwork processes have positive relationships with team performance and member satisfaction, and that the relationships are similar across the teamwork dimensions and levels of process specificity. Supplemental analyses revealed that the 3 intermediate‐level teamwork processes are positively and strongly related to cohesion and potency. Results of moderator analyses suggested that relationships among teamwork processes and team performance are somewhat dependent on task interdependence and team size.