Biodiversity's impact on ecosystem functioning (BEF) is a central ecological question. Numerous studies across various ecosystems demonstrate a positive relationship between plant diversity (species or functional trait diversity) and productivity. Niche complementarity, where different species or genotypes utilize resources differently, is often invoked to explain this relationship. However, empirically demonstrating this is difficult because niches are hard to quantify. Functional ecology often uses trait differences as niche indicators, but correlation doesn't equal causation, particularly due to evolutionary trade-offs between traits. Furthermore, many small trait differences may contribute simultaneously, obscuring the specific mechanisms. This study proposes a gene-based approach to identify causal drivers of positive diversity-productivity relationships, complementing traditional trait-based methods. Positive BEF relationships exist at both interspecific and intraspecific levels; mixtures of genotypes often overyield compared to monocultures. This study focuses on intraspecific diversity effects in *Arabidopsis thaliana*, using a gene-centered approach to link genetic variation to overyielding in genotype mixtures. The approach involves creating genotype mixtures with varying genetic compositions, allowing for the establishment of causal links between genetic diversity and mixture performance. This builds upon recent research that integrates genetic analysis into the study of ecological communities, investigating how genetic effects can cascade across biological levels of organization.

Existing literature extensively documents the positive correlation between plant diversity and productivity, with studies conducted in grasslands, forests, and croplands. The prevailing theory attributes these positive diversity effects to niche complementarity, though empirical validation remains a significant challenge. Trait-based approaches have been used as proxies for niche differences, associating specific traits with environmental conditions and productivity. However, limitations exist. Covariation of traits due to evolutionary trade-offs complicate causal inference. Moreover, the association between a specific trait and environmental conditions does not automatically imply a causal role in the diversity effect; other, unmeasured, traits might be responsible. Finally, the need to consider many small phenotypic differences simultaneously poses another significant challenge in elucidating the mechanisms driving the biodiversity–ecosystem functioning (BEF) relationship. This study builds upon this body of work by shifting from trait-based to gene-based analysis to overcome the limitations described. It adopts a novel approach that allows for a causal link between genetic differences and overyielding.

The study employed a two-pronged approach combining quantitative trait locus (QTL) mapping and association mapping to identify the genetic basis of overyielding in *Arabidopsis thaliana* genotype mixtures. Initially, the researchers screened ten *A. thaliana* genotype pairs to identify those showing consistent overyielding, which was determined by comparing the biomass of the mixtures to the average biomass of their respective monocultures. The Umkirch-1 (Uk-1) and Slavice-O (Sav-0) pair exhibited consistent overyielding across various substrates and pot sizes. To pinpoint the genetic basis of this effect, a competition diallel panel was established. This involved growing 18 recombinant inbred lines (RILs) derived from a cross between Uk-1 and Sav-0, along with the parental lines, in all possible pairwise combinations and monocultures. This design allowed the estimation of general combining ability (GCA), capturing additive effects, and specific combining ability (SCA), representing non-additive interactions. SCAs were then used to perform QTL mapping, using high-resolution genotype maps generated from whole-genome resequencing of each RIL. To further verify the QTL finding and narrow down the candidate gene, an association mapping approach was applied using a previously published dataset consisting of a factorial competition design with 10 tester genotypes (including Uk-1 and Sav-0) and 98 natural *Arabidopsis* accessions. The SCAs derived from this independent dataset were tested for associations with single nucleotide polymorphisms (SNPs) within the QTL interval. Finally, to test whether the identified genetic variation leads to functional differences that affect overyielding, sucrose uptake assays and root growth experiments under different pH conditions were conducted using the *AtSUC8* gene. Specifically, the Uk-1 and Sav-0 variants of *AtSUC8* were expressed in *Xenopus laevis* oocytes and their sucrose uptake kinetics measured. Furthermore, the root growth of RILs carrying either the Uk-1 or Sav-0 allele at the *AtSUC8* locus were compared under different pH conditions on agarose plates. Statistical analyses involved linear models, t-tests, ANOVA, and meta-analysis.

The study yielded several key findings: First, consistent overyielding was observed in mixtures of the *A. thaliana* accessions Uk-1 and Sav-0 across multiple experimental settings. Second, QTL mapping of the competition diallel revealed a single major-effect QTL on chromosome 2 strongly associated with SCA variation. This QTL explained a significant portion of the overyielding observed in the genotype mixtures. Third, the high-resolution genetic map allowed for the precise location of the QTL to a small genomic region (approximately 178 kb). Mixtures with allelic diversity within this region exhibited significantly higher SCAs than those with only one allele. The overyielding was attributed primarily to complementarity effects rather than dominance effects of specific alleles. Fourth, association mapping of the independent competition experiment reinforced the QTL finding by identifying a significant association between an SNP within the *AtSUC8* gene (located within the QTL) and positive diversity effects. Functional analyses demonstrated that genetic variation at the *AtSUC8* locus affects the protein's activity, with the Uk-1 variant exhibiting reduced sucrose uptake compared to the Sav-0 variant. Moreover, the study revealed that genetic variation at the *AtSUC8* locus is associated with differential root growth responses to pH changes, with the Uk-1 allele showing less sensitivity to substrate acidification than the Sav-0 allele. Interestingly, the *BRX* gene, previously associated with adaptation to acidic soil in Uk-1, did not drive overyielding in this experiment. This suggests that diverse genetic mechanisms can underpin adaptation to different edaphic gradients.

The findings demonstrate that a surprisingly simple genetic basis can underlie complex community-level properties like overyielding in plant mixtures. The identification of *AtSUC8* as a major driver of the observed overyielding highlights the power of a gene-centered approach in dissecting biodiversity effects. It challenges the assumption that such effects are inherently complex and irreducibly emergent. The results suggest that investigating genetic differences first, and then deducing functional traits, may be a more efficient way to understand overyielding than directly searching for phenotypic trait differences. The identified *AtSUC8* variation is associated with differential root growth responses to soil acidity, suggesting a mechanism of niche partitioning that allows for more efficient resource utilization in mixtures. This could involve either pre-existing substrate heterogeneity or altered root foraging behaviors. Future research needs to address how the specific *AtSUC8*-mediated trait differences translate into overyielding. The study's findings underscore the potential of gene-based approaches to inform the development of sustainable cropping systems that leverage species or genotype diversity to enhance yield and stability. By integrating gene-centered approaches with the already existing trait-centered methods, we could design more effective crop mixtures.

This study successfully identified *AtSUC8*, a gene encoding a proton-sucrose symporter, as a major driver of diversity-driven overyielding in *Arabidopsis thaliana* genotype mixtures. The study's findings highlight the efficacy of a gene-centered approach in disentangling complex ecological phenomena and link evolutionary adaptation to ecological processes. Future research should investigate the detailed mechanisms by which *AtSUC8* variation contributes to overyielding, including exploring its role in root foraging and soil resource partitioning. Further studies could explore the generality of the findings to other plant species and environmental gradients.

The study focused on a specific *Arabidopsis thaliana* population and environmental conditions. The generalizability of the findings to other species and ecosystems requires further investigation. Although a strong association was found between SNPs in the *AtSUC8* gene and overyielding, the study doesn’t definitively prove causality; the identified SNP might be in tight linkage disequilibrium with the actual causal polymorphism. The study used pot experiments which may not fully capture the complexity of natural field conditions.