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Palabras clave – provistas por la editorial

early selection; stomatal characteristics; water stress; water relations; specific leaf area; Eucalyptus clones; LTR-retrotransposon; Ty3-gypsy; Ty1-copia; IRAP; molecular markers; bamboo; Phyllostachys; genetic diversity; populations structure; AMOVA; central-marginal hypothesis; cline; Pinaceae; trailing edge population; Sakhalin fir; sub-boreal forest; gibberellin; male strobilus induction; transcriptome; conifer; Cryptomeria japonica; linkage map; male sterility; marker-assisted selection; C. fortunei; differentially expressed genes; phenylpropanoid metabolism; candidate genes; Camellia oleifera; leaf senescence; transcriptome analysis; senescence-associated genes; physiological characterization; cpDNA; next generation sequencing; northern limit; nucleotide diversity; phylogeny; In/Del; SNP; SSR; Chinese fir; heartwood; secondary metabolites; widely targeted metabolomics; flavonoids; amplicon sequencing; AmpliSeq; genomic selection; Japanese cedar (Cryptomeria japonica); multiplexed SNP genotyping; spatial autocorrelation error; pine wood disease; resistance to pine wood nematode; inoculation test; multisite; cumulative temperature; Pinus thunbergii; Thujopsis dolabrata; EST-SSR markers; varieties; population structure; pine wilt disease; Bursaphelenchus xylophilus; genotype by environment interaction; Japanese black pine; variance component; local adaptation; silviculture; seed zone; tree improvement program; breeding; genotype × environment interaction; mast seeding; seed production; thinning; forest tree breeding; high-throughput phenotyping; epigenetics; genotyping; genomic prediction models; quantitative trait locus; breeding cycle; Cryptomeria japonica var. sinensis; demographic history; RAD-seq; ancient tree; conservation; infrared thermography; chlorophyll fluorescence; cumulative drought stress; genetic conservation; genetic management; pine wood nematode; pine wood nematode-Pinus thunbergii resistant trees; n/a