Analyses from stand to tree level allow disentangling the effects of age, size, origin and competition on tree growth sensitivity to climate in natural and afforested Scots pine forests

© 2024 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

The sensitivity of tree growth to climate is conditioned by several variables, often intermingled, such as the origin of the forest (natural vs. artificial), tree age, tree size and tree-to-tree competition. The effect of these variables is usually inferred from average growth series obtained at the stand level, thus ignoring the differences at the individual tree level and their drivers. Our objective is to disentangle the effects of stand origin, age, size, competition and social status on the sensitivity of tree growth to climate, including the effects of extreme climatic events, such as droughts, on resistance and resilience, and also to show the advantages of using a tree-level approach. To this end, we compared four stands of Pinus sylvestris with contrasting characteristics: young afforested, young of natural origin, old afforested and old of natural origin. We analyzed differences in growth sensitivity to climate at both stand and tree levels to compare both approaches. Our results show the great complexity of the relationships of the variables considered with the sensitivity of growth to climate. All these variables are important and with strong interactions between them, which makes their effects not unidirectional and strongly dependent on the site conditions. While the stand approach hides these interactions, the tree-level approach makes it possible to analyze them in detail. In general, the sensitivity of growth to climate increases with age, diameter, afforested origin, decreasing competition and higher social status; growth resistance increases with age, decreasing diameter, afforested origin, decreasing competition and higher social status; and growth resilience increases with age, diameter, natural origin, decreasing competition and higher social status. We show the usefulness of the analysis of data at individual tree level, which, combined with the joint analysis at stand level, allows us to obtain more accurate and detailed information.

ARC acknowledges support by Margarita Salas postdoctoral fellowship (reference RCMS-22-G1T6IW-17-NLHJ80) of the Universidad Politécnica de Madrid. IA and IC acknowledges support by projects SUPERB H2020 (Systemic solutions for upscaling of urgent ecosystem restoration for forest related biodiversity and ecosystem services; grant agreement number 101036849 of the Horizon 2020 research and innovation programme) and IFN-2021 (Monitorización de la red de parcelas permanentes de Gestión Forestal y Tratamientos Selvícolas del CIFOR-INIA). JJC acknowledges support by project TED2021-129770B-C21 (Spanish Ministry of Science and Innovation). JAMV acknowledges support by Becas Fundación Ramón Areces para Estudios Posdoctorales postdoctoral fellowship. CPC acknowledges support by Ramón y Cajal postdoctoral fellowship (reference RYC2018-024939-I) and by project PID2020-119204RB-C22. AH was supported by PinCaR project (UHU-1266324, FEDER Funds, Andalusia Regional Government, Consejería de Economía, Conocimiento, Empresas y Universidad), "Action 7: Grants for the temporary incorporation of postdoctoral research staff, from the Operational Plan for Research Support of the University of Jaén (POAI-UJA)", project LITHOFOR (RTI2018-095345-B-C21, Spanish Ministry of Science, Innovation and Universities) and the fellowship II.4 from VII-PPITUS 2022 (Univ. Sevilla). The authors gratefully acknowledge the Universidad Politécnica de Madrid (www.upm.es) for providing computing resources on Magerit Supercomputer (www.cesvima.upm.es).

Peer reviewed