Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze 11/A, 43124 Parma, Italy.
Department of Geography, University of Cambridge, Downing Place, CB2 3EN Cambridge, United Kingdom.
Sci Total Environ. 2019 Feb 10;650(Pt 1):493-504. doi: 10.1016/j.scitotenv.2018.08.348. Epub 2018 Aug 28.
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 R values 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.
形成层生长是一种表型特征，受到多种生理过程、众多生物和非生物驱动因素以及遗传背景的影响。树木年轮作为一种特殊的资源，记录了这种复杂相互作用的结果，可用于解决个体对环境变化和气候的长期生长响应问题。然而，由于缺乏多学科数据，因此要解开树木生长的不同驱动因素的影响仍然具有挑战性。在这里，我们结合个体树木年代学、遗传和空间数据，评估遗传相似性和空间邻近性对挪威云杉（Picea abies (L.) Karst.）生长表现的相对重要性。我们从南欧和中欧的两个种群中密集采样了五个样地，共对 482 棵树进行了特征描述。我们采用两步分析框架。首先，使用随机斜率线性混合效应模型，对每个个体的气候和树龄对树木年轮宽度（TRW）的影响进行估计。然后，通过 Mantel 检验、偏冗余分析和方差分解，将个体参数与遗传和空间变量进行测试。我们的建模方法成功地捕捉到了 TRW 中很大一部分方差（条件 R 值高达 0.94），其中很大一部分嵌入了个体差异中。所有的统计方法都一致表明，遗传相似性与描述生长响应的个体参数的变化无关。相比之下，个体参数的方差中有高达 29%可以由空间变量来解释，这表明微环境特征比遗传相似性更能决定相似的生长模式。我们的研究强调了在个体水平上对树木年代学数据进行建模的优势，以及微环境变化对个体生长模式的重要性。在未来关于自然种群生长动态的多学科研究中，这两个方面都应仔细考虑。
