Drivers of genotype by environment interaction in radiata pine as indicated by multivariate regression trees

Gapare, Washington J.; Ivković, Miloš; Liepe, Katharina; Hamann, Andreas; Low, C. B.

doi:10.1016/j.foreco.2015.05.027

Cited by 27 publications

(11 citation statements)

References 26 publications

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“…One way for doing this is the use of universal response functions (URFs) which predict provenance specific growth depending on the climate of the trial locations and the climatic conditions at the place of origin [32,33]. Multiple regression trees have served in a similar way as a tool to conclude about the performance of different provenances at given site conditions depending on the climate of origin [34,35]. The outcomes of these studies have been also proposed as a basis to adapt seed transfer guidelines to future climatic conditions [36,37].…”

Section: Provenance Researchmentioning

confidence: 99%

Growing Non-native Trees in European Forests Brings Benefits and Opportunities but Also Has Its Risks and Limits

et al. 2020

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Purpose of Review Non-native tree species (NNT) raise a range of different associations and emotions—to many citizens they are just an exotic curiosity in parks, to many conservationists they are an evil to native ecosystems that should be eradicated, to a rising group of foresters they are part of the solution to climate change and an increasing timber demand, and to others they are already daily forestry business. In this review, where we also summarise the findings of the recent COST Action FP1403 (NNEXT) ‘Non-native tree species for European forests: experiences, risks and opportunities’, we highlight opportunities and challenges in the light of climate change, ecological risks and legislative limits of growing non-native tree species in Europe. Recent Findings Few NNT in Europe show invasive behaviour and are listed as prohibited species or as species to be monitored. A larger number of NNT is utilised in productive forestry and forest restoration due to their superior growth, valuable timber properties and good performance under harsh growing conditions. Current species distribution, experiences with success and failures and environmental concerns differ profoundly across Europe, with Western Europe overall revealing higher shares in NNT and showing a stronger interest of forestry related stakeholder groups to continue planting NNT. Summary Many more NNT are already used in forestry than previously thought, but relatively few species have major importance in terms of area, mainly in western European countries. Diversification, mixing and avoidance of invasion in relation to NNT are necessities that are relatively new on the agenda. In contrast, provenance research of major NNT has been going on for many decades and now provides important information for climate change adaptation. Despite the limitations to the use of NNT either through legal restrictions or forest certification that differ considerably across Europe, the careful integration of a range of tested NNT also into future forest management planning shows a high potential for climate change adaptation and mitigation.

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Section: Provenance Researchmentioning

confidence: 99%

Growing Non-native Trees in European Forests Brings Benefits and Opportunities but Also Has Its Risks and Limits

et al. 2020

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“…Other studies, generally conducted in contexts of using fertilisers where needed, have pointed to some different site variables as drivers of such interaction. Wu and Matheson (2005) pointed to altitude (elevation), as did Raymond (2011), whereas Gapare et al (2015) pointed to temperature with a secondary role of humidity, Ivković et al (2015) and Dutkowski et al (2016) to rainfall and temperature, and Li et al (2015) to mean annual temperature along with soil levels of nitrogen and total P. However, given the different sets of sites, and the auto correlations between site variables within those studies, there were probably no real inconsistencies among the findings. Also of interest would be interactions involving the 300 index (Kimberley et al 2005) which is a measure of whole-crop productivity as distinct from individualtree growth rate.…”

Section: Genotype × Sitementioning

confidence: 97%

“…It is on the basis of r B and its departures from +1 that RC interaction has been studied for radiata pine in recent years, being the focus of several major studies (e.g. Wu and Matheson 2005;Raymond 2011;Cullis et al 2014;Gapare et al 2015;Ivković et al 2015;Li et al 2015). Of these studies, all gave strong indications as to what factors were driving the RC interactions, except that of Cullis et al despite the power of its factor analytic method for analysing a very large multi-site dataset with troublesome data properties.…”

Section: The Conceptual Frameworkmentioning

confidence: 99%

“…It applies whether the breeder chooses to select for 'stable' genotypes that perform well throughout or for different sets of genotypes that perform best in particular situations, a topic of perennial debate discussed by Li et al 2 Characterising the roles of particular environmental factors in generating G × E, though, is very challenging. While some consensus is emerging in respect of radiata pine (Raymond 2011;Gapare et al 2015;Ivković et al 2015;Dutkowski et al 2016) and in recent work by Li et al 2 , the task is much complicated by several factors, notably: poor genetic interconnections between different existing field trials, high degree of autocorrelation among various climatic factors and even between climatic and soil factors, the diversity of potentially relevant soil factors and imperfections in soil assays as proxies for relevant biological factors. Thus, we are far short of having any general understanding of the quantitative drivers of genotype × site interactions.…”

Section: Pointers For Further Researchmentioning

confidence: 99%

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Genotype × site × silviculture interactions in radiata pine: knowledge, working hypotheses and pointers for research§

Burdon

Suontama

et al. 2017

N.Z. j. of For. Sci.

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Background: Favourable interactions between genotype, site and silviculture are desired for growing radiata pine, site and silviculture being two components of environment. Our challenge is to characterise the interactions so as to exploit them to advantage. Four classes of interaction are involved: three first-order interactions between pairs of factors; and one second-order interaction involving all three factors. Also of interest is to partition the interactions into two types: involving rank change of genotypes (RC interaction) and differing level of expression of genotypic differences among environments (LoE interaction). Key issues: Tree breeders' immediate concern is with main effects of environment and interaction effects on genotypes' performance, yet prime interest for research and policy decisions lies in the role of environments and specific environmental factors in generating interactions. Of the two types of interaction, RC seems generally more important for breeding operations with LoE more so for deployment decisions.

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“…The provided guidance and several approaches to characterize patterns of GxE ensuing from MET analyses 82 with FA models, which include clustering sites based on the dissimilarity matrix of additive effects and 83 using a 'heatmap' to visualize patterns. Gapare et al (2015) attempted to further characterize patterns 84 of GxE from a MET analysis of radiata pine in New Zealand using hierarchical cluster analyses, multiple 85 regression tree models and climate data, and determined that minimum temperature was an important 86 driver of GxE in both progeny and provenance trials, and partitioned the target environment to optimize 87 deployment of selected material. 88…”

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confidence: 99%

Climatic drivers of genotype–environment interactions in lodgepole pine based on multi-environment trial data and a factor analytic model of additive covariance

2018

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The optimum deployment of select material from tree breeding programs is affected by the presence of genotype–environment interactions (G × E) and further complicated by future climate change. Here, we analyzed tree height data from 28 progeny test sites in a multi-environment trial (MET) dataset for two testing cycles of the lodgepole pine (Pinus contorta Douglas ex Loudon) breeding program in British Columbia to characterize one approach to investigating the climatic variables influencing G × E and the potential impacts of climate change. Linear mixed model analysis was conducted using an approximate reduced animal model with a factor analytic (FA) variance model to estimate the complex additive (co)variance structure. Test sites were grouped according to patterns of G × E, and climate modelling was employed to project historical and future deployment zones for each group. Based on these findings, it appears that breeding groups with historically wide deployment zones from northern environments will become less important as the climate warms, and therefore investment should be directed toward southern breeding groups, which will be useful across a very wide geographic range in the near to mid-term future.

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Drivers of genotype by environment interaction in radiata pine as indicated by multivariate regression trees

Cited by 27 publications

References 26 publications

Growing Non-native Trees in European Forests Brings Benefits and Opportunities but Also Has Its Risks and Limits

Growing Non-native Trees in European Forests Brings Benefits and Opportunities but Also Has Its Risks and Limits

Genotype × site × silviculture interactions in radiata pine: knowledge, working hypotheses and pointers for research§

Climatic drivers of genotype–environment interactions in lodgepole pine based on multi-environment trial data and a factor analytic model of additive covariance

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