Drivers of population differentiation in phenotypic plasticity in a temperate conifer: a 27-year study [Dataset]

[EN] These project improve our understanding of the microevolutionary drivers of phenotypic plasticity, a critical process for resilience of long-lived species under climate change, and support decision making in tree genetic improvement programs and seed transfer strategies. The dataset compiles th...

Descripción completa

Detalles Bibliográficos
Autor: Mata Pombo, Raúl de la
Tipo de recurso: conjunto de datos
Fecha de publicación:2022
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/280295
Acceso en línea:http://hdl.handle.net/10261/280295
https://doi.org/10.20350/digitalCSIC/14756
Access Level:acceso abierto
Palabra clave:Pinus ponderosa
Phenotypic plasticity
Genotype by environment interaction
Genotypic stability
Environmental heterogeneity
Patch size
Descripción
Sumario:[EN] These project improve our understanding of the microevolutionary drivers of phenotypic plasticity, a critical process for resilience of long-lived species under climate change, and support decision making in tree genetic improvement programs and seed transfer strategies. The dataset compiles the three common garden tests (Condon, Lubrecht and Little Wolf) established in western Montana (USA) followed a Population × Family structure. Seeds were collected from 115 open-pollinated, unrelated wild mother trees in the 23 populations. Every population was represented by 5 open-pollinated families and every family was planted in all three trials. One-year-old bare-root seedlings were planted in 1974 on a 3 × 3 m spacing using a randomized complete block design at the family level with 4-tree-row plots and 5 blocks in each site. Tree growth was measured as tree height at ages 2, 4, 5, 11, 16, 21 and 27, and diameter at breast height (DBH; 1.4 m above ground) at ages 5, 11, 16, 21 and 27. DBH at age 27 was chosen as the best predictor of genetic growth potential in these trials. Means and standard errors of DBH27 were compueted at the family level within each site.