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Multiple mutualism effects generate synergistic selection and strengthen fitness alignment in the interaction between legumes, rhizobia, and mycorrhizal fungi

Citation

Afkhami, Michelle; Friesen, Maren; Stinchcombe, John (2021), Multiple mutualism effects generate synergistic selection and strengthen fitness alignment in the interaction between legumes, rhizobia, and mycorrhizal fungi, Dryad, Dataset, https://doi.org/10.5061/dryad.vq83bk3sb

Abstract

Nearly all organisms participate in multiple mutualisms, and complementarity within these complex interactions can result in synergistic fitness effects. However, it remains largely untested how multiple mutualisms impact eco-evolutionary dynamics in interacting species. We tested how multiple microbial mutualists-- N-fixing bacteria and mycorrrhizal fungi-- affected selection and heritability of traits in their shared host plant (Medicago truncatula), as well as fitness alignment between partners. Our results demonstrate for the first time that multiple mutualisms synergistically affect selection and heritability of host traits and enhance fitness alignment between mutualists. Specifically, we found interaction with multiple microbial symbionts doubled the strength of natural selection on a plant architectural trait, resulted in 2-3-fold higher heritability of plant reproductive success, and more than doubled fitness alignment between N-fixing bacteria and plants. These findings show synergism generated by multiple mutualisms extends to key components of microevolutionary change, emphasizing the importance of multiple mutualism effects on evolutionary trajectories.

Methods

The details on data collection are available in the associated paper in Ecology Letters. In brief, 213 M. truncatula genotypes were grown in a factorial experiment with four microbial environments environments: no microbes (NM,NR), rhizobia alone (NM, R), mycorrhizal fungi alone (M, NR), and both microbes (R,M). We measured a plant fitness proxy (pod production), a rhizobia fitness proxy (nodule number), and several plant traits related to plant architecture (branch number) and investment (allocation to roots vs shoot biomass). 

Usage Notes

The data are from 213 M. truncatula genotypes grown in four microbial environments environments: no microbes (NM,NR), rhizobia alone (NM, R), mycorrhizal fungi alone (M, NR), and both microbes (R,M).  For each M. truncatula genotype in each of the four microbial environments, we provide in this dataset the average number of pods produced, number of branches grown, and root investment vs shoot investment (root to shoot ratio) as well as number of nodules produced by rhizobia associating with that plant genotype (associated columns are mean_pod, mean_branch, mean_root2shoot, and mean_nodule respectively). We also provide the relativized versions of these metric that were used and described in the paper analyses (associated columns of plant_rel_fitness, rel_mean_ branch, rel_mean_root2shoot, and rhizo_rel_fitness , respectively). The remaining columns describe the treatments and are myco (= mycorrhizal treatment), rhizo (= rhizobia treatment), and line (= plant genotype). The line genotype codes match the Medicago hapmap project (http://www.medicagohapmap.org/). Note that NA indicates no data is available for that genotype-by-microbial environment combination; it happens most frequently in the nodulation related columns because in the treatments with no rhizobia (MNR and NMNR) nodulation is not possible.

Funding

National Science Foundation, Award: IOS-1401840

National Science Foundation, Award: DEB-1922521

National Science Foundation, Award: DEB-2030060

National Science Foundation, Award: DEB-1823419

Natural Sciences and Engineering Research Council of Canada, Award: Discovery Grant

National Science Foundation, Award: DEB-1943628

U.S. Department of Agriculture, Award: 1014527