The GenTree Dendroecological Collection, tree-ring and wood density data from seven tree species across Europe

Martinez-Sancho, E ; Slamova, L ; Morganti, S ; Grefen, C ; Carvalho, B ; Dauphin, B ; Rellstab, C ; Gugerli, F ; Opgenoorth, L ; Heer, K ; Knutzen, F ; von Arx, G ; Valladares, F ; Cavers, S ; Fady, B ; Alia, R ; Aravanopoulos, F ; Avanzi, C ; Bagnoli, F ; Barbas, E ; Bastien, C ; Benavides, R ; Bernier, F ; Bodineau, G ; Bastias, CC ; Charpentier, JP ; Climent, JM ; Correard, M ; Courdier, F ; Danusevicius, D ; Farsakoglou, AM ; del Barrio, JMG ; Gilg, O ; Gonzalez-Martinez, SC ; Gray, A ; Hartleitner, C ; Hurel, A ; Jouineau, A ; Karkkainen, K ; Kujala, ST ; Labriola, M ; Lascoux, M ; Lefebvre, M ; Lejeune, V ; Liesebach, M ; Malliarou, E ; Mariotte, N ; Matesanz, S ; Myking, T ; Notivol, E ; Pakull, B ; Piotti, A ; Pringarbe, M ; Pyhajarvi, T ; Raffin, A ; Ramirez-Valiente, JA ; Ramskogler, K ; Robledo-Arnuncio, JJ ; Savolainen, O ; Schueler, S ; Semerikov, V ; Spanu, I ; Thevenet, J ; Mette Tollefsrud, M ; Turion, N ; Veisse, D ; Vendramin, GG ; Villar, M ; Westin, J ; Fonti, P

Resumen: The dataset presented here was collected by the GenTree project (EU-Horizon 2020), which aims to improve the use of forest genetic resources across Europe by better understanding how trees adapt to their local environment. This dataset of individual tree-core characteristics including ring-width series and whole-core wood density was collected for seven ecologically and economically important European tree species: silver birch (Betula pendula), European beech (Fagus sylvatica), Norway spruce (Picea abies), European black poplar (Populus nigra), maritime pine (Pinus pinaster), Scots pine (Pinus sylvestris), and sessile oak (Quercus petraea). Tree-ring width measurements were obtained from 3600 trees in 142 populations and whole-core wood density was measured for 3098 trees in 125 populations. This dataset covers most of the geographical and climatic range occupied by the selected species. The potential use of it will be highly valuable for assessing ecological and evolutionary responses to environmental conditions as well as for model development and parameterization, to predict adaptability under climate change scenarios.

Idioma: Inglés

DOI: 10.1038/s41597-019-0340-y

Año: 2020

Publicado en: Scientific Data 7, 1 (2020), 1-7
ISSN: 2052-4463

Factor impacto JCR: 6.444 (2020)

Categ. JCR: MULTIDISCIPLINARY SCIENCES rank: 11 / 73 = 0.151 (2020) - Q1 - T1

Factor impacto SCIMAGO: 2.564 - Computer Science Applications (Q1) - Education (Q1) - Statistics, Probability and Uncertainty (Q1) - Library and Information Sciences (Q1) - Statistics and Probability (Q1) - Information Systems (Q1)

Financiación: info:eu-repo/grantAgreement/EC/H2020/676876 /EU/Optimising the management and sustainable use of forest genetic resources in Europe/GenTree

Tipo y forma: Artículo (Versión definitiva)