Plant roots determine carbon uptake, survivorship, and agricultural yield and represent a large proportion of the world’s vegetation carbon pool. Study of belowground competition, unlike aboveground shoot competition, is hampered by our inability to observe roots. We developed a consumer-resource model based in game theory that predicts the root density spatial distribution of individual plants and tested the model predictions in a greenhouse experiment. Plants in the experiment reacted to neighbors as predicted by the model’s evolutionary stable equilibrium, by both overinvesting in nearby roots and reducing their root foraging range. We thereby provide a theoretical foundation for belowground allocation of carbon by vegetation that reconciles seemingly contradictory experimental results such as root segregation and the tragedy of the commons in plant roots.

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Aim To improve our knowledge of the process of selection of important plant areas (IPAs), a recent requirement of the Global Strategy for Plant Conservation. The study was conducted at a hotspot of plant conservation in the European continent, using a comprehensive database of plant species distribution in the area.Location Spain.Methods We used range distribution data for 3218 vascular plants found in Spain, in the form of 10 km UTM squares, totalling 169,124 species occurrences across 5508 UTM cells. We identified IPAs by scoring threat status, endemism, rarity, phylogeny and species richness. We then performed two different analyses, with and without incorporating the species richness score of every square. Finally, a null model was used to obtain a general pattern of species occurrences, we computed an index of occurrence richness (SI), and then we selected a number of specific territories of different sizes to reveal differences in sampling effort within the study area.Results We identified IPAs in Spain according to the proposed scoring method. We detected a positive relationship among richness and total score calculated with the rest of the criteria. However, endemism and threat status produced certain specific effects for species-poor squares. Regarding sample bias, we detected over-and under-recorded areas. This bias seems to be due to the accumulation of field prospecting in species-rich areas in detriment to poor areas.Main conclusions We envisage two different approaches to address IPA selection in hotspots. First, we advocate a complementary scoring-mapping method for areas where a relatively large amount of range distribution data and plant knowledge is available. Secondly, as richness per se encompasses a great amount of biogeographical information, we suggest using species richness or any other environmental surrogate to delineate preliminary IPAs in poorly known but species-rich territories.

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Community ecologists value the phenomenological observation of plant biotic interactions because they provide assumptions to make predictions of other ecosystem features, such as species diversity, community structure, or plant atmospheric carbon uptake. However, a rising number of scientists claim for the need of a mechanistic understanding of plant interactions, due to the limitations that a phenomenological approach raises both in empirical and modeling studies. Scattered studies take a mechanistic approach to plant interactions, but we still lack an integrated theoretical framework to start approaching holistically. In this Review and Synthesis, we present a comprehensive foundation for the study of the mechanisms underpinning the net interaction between two plants. First, we recapitulate the elementary units of plant interactions, i.e. all the known biophysical processes affected by the presence of an influencing plant and the possible phenotypic responses of influenced plants to these processes. Following, we discuss how a net interaction between two plants may emerge from the simultaneous effect of these elementary units. We then touch upon the spatial and temporal variability of this net interaction, and scrutinize how that variability may be linked to the underlying biophysical processes. We conclude by arguing how these processes can be integrated in a mechanistic framework for plant interactions, and why it must necessarily focus on the individual scale, incorporate the spatial structure of the community, and explicitly account for environmental factors.

Ecologists use the net biotic interactions among plants to predict fundamental ecosystem features. Following this approach, ecologists have built a giant body of theory founded on observational evidence. However, due to the limitations that a phenomenological approach raises both in empirical and theoretical studies, an increasing number of scientists claim the need for a mechanistic understanding of plant interaction outcomes, and a few studies have taken such a mechanistic approach. In this synthesis, we propose a modeling framework to study the plant interaction mechanistically. We first establish a conceptual ground to frame plant-plant interactions, and then, we propose to formalize this research line theoretically developing a family of individual-based, spatially-explicit models in which biotic interactions are an emergent property mediated by the interaction between plants’ functional traits and the environment. These models allow researchers to evaluate the strength and sign of biotic interactions under different environmental scenarios and thus constitute a powerful tool to investigate the mechanisms underlying facilitation, species coexistence, or the formation of vegetation spatial patterns.

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