Cambial growth is a phenotypic trait influenced by various physiological processes, numerous biotic and abiotic drivers, as well as by the genetic background. By archiving the outcome of such complex interplay, tree-rings are an exceptional resource for addressing individual long-term growth responses to changing environments and climate. Disentangling the effects of the different drivers of tree growth, however, remains challenging because of the lack of multidisciplinary data. Here, we combine individual dendrochronological, genetic and spatial data to assess the relative importance of genetic similarity and spatial proximity on Norway spruce (Picea abies (L.) Karst.) growth performances. We intensively sampled five plots from two populations in southern and central Europe, characterizing a total of 482 trees. A two-step analytical framework was developed. First, the effects of climate and tree age on tree-ring width (TRW) were estimated for each individual using a random slope linear mixed-effects model. Individual parameters were then tested against genetic and spatial variables by Mantel tests, partial redundancy analyses and variance partitioning. Our modelling approach successfully captured a large fraction of variance in TRW (conditional R2values up to 0.94) which was largely embedded in inter-individual differences. All statistical approaches consistently showed that genetic similarity was not related to variation in the individual parameters describing growth responses. In contrast, up to 29% of the variance of individual parameters was accounted by spatial variables, revealing that microenvironmental features are more relevant than genetic similarity in determining similar growth patterns. Our study highlights both the advantages of modelling dendrochronological data at the individual level and the relevance of microenvironmental variation on individual growth patterns. These two aspects should be carefully considered in future multidisciplinary studies on growth dynamics in natural populations.

Disentangling the effects of spatial proximity and genetic similarity on individual growth performances in Norway spruce natural populations / Avanzi, Camilla; Piermattei, Alma; Piotti, Andrea; Büntgen, Ulf; Heer, Katrin; Opgenoorth, Lars; Spanu, Ilaria; Urbinati, Carlo; Vendramin, Giovanni Giuseppe; Leonardi, Stefano. - In: SCIENCE OF THE TOTAL ENVIRONMENT. - ISSN 0048-9697. - 650:Pt 1(2018), pp. 493-504. [10.1016/j.scitotenv.2018.08.348]

Disentangling the effects of spatial proximity and genetic similarity on individual growth performances in Norway spruce natural populations

Avanzi, Camilla
Membro del Collaboration Group
;
Piotti, Andrea
Membro del Collaboration Group
;
Leonardi, Stefano
Membro del Collaboration Group
2018

Abstract

Cambial growth is a phenotypic trait influenced by various physiological processes, numerous biotic and abiotic drivers, as well as by the genetic background. By archiving the outcome of such complex interplay, tree-rings are an exceptional resource for addressing individual long-term growth responses to changing environments and climate. Disentangling the effects of the different drivers of tree growth, however, remains challenging because of the lack of multidisciplinary data. Here, we combine individual dendrochronological, genetic and spatial data to assess the relative importance of genetic similarity and spatial proximity on Norway spruce (Picea abies (L.) Karst.) growth performances. We intensively sampled five plots from two populations in southern and central Europe, characterizing a total of 482 trees. A two-step analytical framework was developed. First, the effects of climate and tree age on tree-ring width (TRW) were estimated for each individual using a random slope linear mixed-effects model. Individual parameters were then tested against genetic and spatial variables by Mantel tests, partial redundancy analyses and variance partitioning. Our modelling approach successfully captured a large fraction of variance in TRW (conditional R2values up to 0.94) which was largely embedded in inter-individual differences. All statistical approaches consistently showed that genetic similarity was not related to variation in the individual parameters describing growth responses. In contrast, up to 29% of the variance of individual parameters was accounted by spatial variables, revealing that microenvironmental features are more relevant than genetic similarity in determining similar growth patterns. Our study highlights both the advantages of modelling dendrochronological data at the individual level and the relevance of microenvironmental variation on individual growth patterns. These two aspects should be carefully considered in future multidisciplinary studies on growth dynamics in natural populations.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11381/2849839
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