Alternative plant designs: consequences for community assembly and ecosystem functioning

[Background] Alternative organism designs (i.e. the existence of distinct combinations of traits leading to the same function or performance) are a widespread phenomenon in nature and are considered an important mechanism driving the evolution and maintenance of species trait diversity. However, alternative designs are rarely considered when investigating assembly rules and species effects on ecosystem functioning, assuming that single trait trade-offs linearly affect species fitness and niche differentiation. [Scope] Here, we first review the concept of alternative designs, and the empirical evidence in plants indicating the importance of the complex effects of multiple traits on fitness. We then discuss how the potential decoupling of single traits from performance and function of species can compromise our ability to detect the mechanisms responsible for species coexistence and the effects of species on ecosystems. Placing traits in the continuum of organism integration level (i.e. traits hierarchically structured ranging from organ-level traits to whole-organism traits) can help in choosing traits more directly related to performance and function. [Conclusions] We conclude that alternative designs have important implications for the resulting trait patterning expected from different assembly processes. For instance, when only single trade-offs are considered, environmental filtering is expected to result in decreased functional diversity. Alternatively, it may result in increased functional diversity as an outcome of alternative strategies providing different solutions to local conditions and thus supporting coexistence. Additionally, alternative designs can result in higher stability of ecosystem functioning as species filtering due to environmental changes would not result in directional changes in (effect) trait values. Assessing the combined effects of multiple plant traits and their implications for plant functioning and functions will improve our mechanist