Cooperación pre-reproductiva en plantas. El efecto de compartir polinizadores con familiares sobre la eficacia biológica

Plants interact very intensely with other nearby plants, and there is a growing body of evidence demonstrating recognition and cooperation among related plants, e.g., warning against herbivore attacks and reducing competition for resources. However, little is known about how plants adjust their reproductive traits to the local neighborhood context, especially when it is composed of related plants. Neighboring plants facilitate pollination through a “magnet effect.” The resources invested in attractive floral structures by one individual can therefore have a positive impact on its individual fitness, but also on the fitness of its neighbors, increasing both individual and collective benefits. Thus, the inclusive fitness of any plant collectively displaying flowers within a patch will ultimately depend on its relationship with other individuals in its local neighborhood. Consistent with this, we have recently shown that individuals of the self-incompatible annual species Moricandia moricandioides produce larger floral displays when their neighbors are related than when they are not.

Our general hypothesis is that this process of sharing pollination services will influence plant reproduction, driving pre-reproductive cooperative reproductive strategies through adjustments in the resources invested to attract pollinators. However, to definitively determine whether this increased floral display is cooperative or competitive, we must evaluate its consequences for biological fitness at both the individual and neighborhood levels. Therefore, we will test this hypothesis by studying how the genetic relationship with neighboring plants affects both direct and indirect fitness gains due to pollinator sharing in M. moricandioides.

This project will combine theoretical modeling and empirical studies through the following four specific objectives: (1) We will explore the fine-scale genetic structure of natural populations using SNPs generated by genotyping through sequencing. (2) We will manipulate neighborhood size and floral display to assess the effects of the efficiency of individual attractive traits on pollinator visitation behavior. (3) We will manipulate the genetic relationships of neighboring plants to assess the consequences of pollinator sharing in different genetic neighborhoods on direct and indirect biological fitness components, exploring the possible mechanisms involved (pollinator behavior, pollen limitation, and mating patterns). (4) We will construct an individual-based model, incorporating the information obtained in the previous tasks, to determine the role of ecological factors in the evolution of pre-reproductive cooperative strategies in plants.

SocialPlants will thus allow us to predict under what circumstances pre-reproductive cooperative behavior should evolve in animal-pollinated plants. The results will be disseminated to the scientific community and the general public, with a particular focus on the agricultural sector, which can benefit from future applications.