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Models of natural processes necessarily sacrifice some realism for the sake of tractability. Detailed, parameter‐rich models often provide accurate estimates of system behaviour but can be data‐hungry and difficult to operationalize. Moreover, complexity increases the danger of 'over‐fitting', which leads to poor performance when models are applied to novel conditions. This challenge is typically described in terms of a trade‐off between bias and variance (i.e. low accuracy vs. low precision).In studies of ecological communities, this trade‐off often leads to an argument about the level of detail needed to describe interactions among species. Here, we used data from a grassland biodiversity experiment containing nine locally abundant plant species (the Jena 'dominance experiment') to parameterize models representing six increasingly complex hypotheses about interactions. For each model, we calculated goodness‐of‐fit across different subsets of the data based on sown species richness levels, and tested how performance changed depending on whether or not the same data were used to parameterize and test the model (i.e. within vs. out‐of‐sample), and whether the range of diversity treatments being predicted fell inside or outside of the range used for parameterization.As expected, goodness‐of‐fit improved as a function of model complexity for all within‐sample tests. In contrast, the best out‐of‐sample performance generally resulted from models of intermediate complexity (i.e. with only two interaction coefficients per species—an intraspecific effect and a single pooled interspecific effect), especially for predictions that fell outside the range of diversity treatments used for parameterization. In accordance with other studies, our results also demonstrate that commonly used selection methods based on AIC of models fitted to the full dataset correspond more closely to within‐sample than out‐of‐sample performance.Synthesis. Our results demonstrate that models which include only general intra and interspecific interaction coefficients can be sufficient for estimating species‐level abundances across a wide range of contexts and may provide better out‐of‐sample performance than do more complex models. These findings serve as a reminder that simpler models may often provide a better trade‐off between bias and variance in ecological systems, particularly when applying models beyond the conditions used to parameterize them. [ABSTRACT FROM AUTHOR]

Darwin's naturalisation hypothesis posing that phylogenetic distance of alien species to native residents predicts invasion success, and Elton's diversity–invasibility hypothesis posing that diversity of native communities confers resistance to invasion, are both rooted in ideas of species coexistence. Because the two hypotheses are inherently linked, the mechanisms underlying them may interact in driving the invasion success. Even so, these links and interactions have not been explicitly disentangled in one experimental study before.To disentangle the links between the two hypotheses, we used 36 native grassland herbs to create greenhouse mesocosms with 90 grassland communities of different diversities, and introduced each of five herbaceous alien species as seeds and seedlings. We used phylogeny and four functional traits (plant height, specific leaf area, leaf size, and seed mass) to calculate different measures of phylogenetic and functional distance and diversity. Specifically, we tested how the alien–native distance (phylogenetic or functional) and the native diversity (phylogenetic or functional) affected each other in their effects on germination, seedling survival, growth, and reproduction of the aliens.Overall, our results supported both hypotheses. Multivariate functional distance based on four traits jointly had stronger positive effects than phylogenetic distance and the univariate ones based on each trait separately. Moreover, the aliens were more successful if they were more competitive by being taller and having larger leaves with a lower SLA than the native residents. Univariate functional diversity based on each trait separately had stronger negative effects than phylogenetic and multivariate functional diversity. Most importantly, we found that the effects of alien–native phylogenetic and multivariate functional distance became stronger as diversity increased. Our analyses with single traits also showed that the strength of the effects of both alien–native hierarchical functional distances (indicative of competitive inequalities) and absolute functional distances (indicative of niche differences) increased at higher diversities, where competition is more severe.Synthesis. Our study explicitly demonstrates for the first time how the mechanisms underlying the two classical invasion hypotheses interact in driving invasion success in grassland communities. This may help to explain some of the puzzling results of studies testing either of the two hypotheses. This study explicitly demonstrates how the mechanisms underlying the two classical invasion hypotheses, Darwin's naturalisation hypothesis and Elton's diversity–invasibility hypothesis, interact in driving the success of alien species in experimental grassland communities. Our findings could help explain some of the puzzling results of studies testing either of the two hypotheses. [ABSTRACT FROM AUTHOR]