27Results from a decade of association studies in different organisms suggest that most complex 28 traits are polygenic, that is, their genetic architectures are determined by numerous causal loci 29 distributed across the genome each with small effect-size. Thus, determining the degree of 30 polygenicity is a central goal to understand the genetic basis of phenotypic variation. 31Recently, multi-loci methods able to detect variants associated with a phenotype of interest 32 despite the subtle allele frequency changes between populations usually observed have been 33 developed. In this study, we applied two multi-loci methods to estimate the degree of 34 polygenicity of fitness-related traits in a long-lived plant species (maritime pine) and to 35 analyze how polygenicity changes across years and environments. For this purpose, we 36 evaluated five categories of fitness related traits, such as, height, survival, phenology-related, 37 biotic-stress resistance and functional traits in a clonal common garden network planted in 38 contrasted environments. Most of the analyzed traits showed evidences of local adaptation. 39We observed a remarkably stable degree of polygenicity (average 6%) across traits, 40 environments and years. Additionally, some of the measured traits showed evidences of 41 negative selection that could explain the observed degree of polygenicity, as previously 42 suggested in humans. The observed genetic architecture of fitness-related traits in maritime 43 pine is in accordance with the polygenic adaptation model. Because polygenic adaptation can 44 take place rapidly, our results can contribute to improve the predictions about the capacity of 45