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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