Plus Tree

Will this be a good investment? This is a common question asked by buyers of ’superior’ genetic material. Why the quotation marks? Because the statement brings to mind the question ‘Superior for what?’ Before dealing with the initial question, we have to recognise a few things about tree improvement that have an effect on the answer.

The observed properties of a tree can be explained as the result of its genetic make up (the genotype), where it is growing (the environment) and the interaction between genotype and environment. That is, the expression of traits like stem volume, wood stiffness or pulp yield will depend on the genetic value of the trees (often expressed as a GF Plus rating in NZ), the site and silviculture that constitute the growing environment, and the interaction between genetic value and environment.

Genetic value is end-use dependent; the characteristics of a good tree for structural wood may differ, for example, from a good tree for the appearance or pulp markets. This is recognised in breeding programs where — in theory at least — the first step is to define a breeding objective: a list of traits that have an effect on profit and their relative economic importance.

With hindsight it was a really unfortunate idea to call ‘breeding objectives’, well, ‘breeding objectives’. The name implies that such objectives are useful only for breeding; however, their definition makes no reference to breeding at all. Maybe a more appropriate name would be ‘improvement objectives’, because they reflect the marginal benefit of changing a trait by any means. Thus, these objectives can be used to evaluate any silvicultural or technological tool that aims to change the intrinsic characteristics of trees.

The definition of improvement objectives is fraught with difficulties: processors are much more outspoken on what they dislike than on what they want, the relationships between wood characteristics and profit are somewhat opaque, there are asymmetric information problems, to name a few (see Apiolaza and Greaves 2001 for an extended list of issues). However, it is always possible to obtain a very long list of traits that people would like to see improved. The real problem comes when trying to estimate the relative economic importance of each trait.

There have been many attempts to side step the problem of estimating economic values, because it is difficult to obtain them. However, to avoid the estimation process is to tacitly accept unknown values. In other words, ‘if you choose not to decide, you still have made a choice’ (Peart 1980).

A typical economics-free alternative is to come up with ideotypes, an idea introduced in agricultural crops by Colin Donald in 1968. The original concept considered physiological indicators that would allow varieties to be good yield performers in a communal situation, that is, to compete with many individuals of the same variety. The concept was later extended to forestry, where the situation is akin to a Christmas shopping list of desirable traits (see, for example, Martin et al. 2001). It is tempting to base breeding only on such a list but:

• Industry profit depends on multiple traits,
• There are trade offs between traits, and
• The degree of genetic control and association between traits somewhat limits the space for changing traits.

Therefore, we require both a list of characteristics that we want to improve and their relative economic importance.

Those pesky interactions

Considering that environment encompasses both site and silviculture, we can split the interaction between genotype and environment into genotype by site and genotype by silviculture. Most studies in interaction have focused on the former, where results have been encouraging — in that they show little interaction — but they were based on a limited number of sites, families and traits. There is ongoing work to extend the coverage of such research.

But what is the effect of silviculture on the performance of superior material? There are few answers to this question; however, there are indications that silvicultural effects may have been poorly recognised. For example, higher initial stockings induce higher wood stiffness, both for pines (Lasserre et al. 2005) and eucalypts (Warren 2006). The heterogeneity of planted material is also relevant, as the best growing genotypes in a mixed stand are not necessarily the best ones in pure stands (as pointed out by Sharma 2007), which should affect our testing schemes. Similarly, this result should have a profound effect on deployment, particularly of clonal varieties.

From an operational point of view the value of a tree is the aggregated sum of each trait weighted by its relative economic value. I am not aware of any studies in New Zealand that track the interaction of this composite value trait rather than studying single variables, but this is exactly what we should care about from a practical point of view.

While we may be surprised by the changes to silviculture and targeted final product (another form of interaction) in the last twenty years, one thing is clear: more changes are coming. Some of these changes — particularly in processing technology — will fall in the ‘unknown unknows’ type popularised by Donald Rumsfeld . How will a breeding program cope with future unknown objectives, which may involve different economic weights and new traits?

It may well be that we need to maintain large diverse populations (including hybrids and under represented populations) in addition to the current breeding population. A large base population that we can always go back and screen for new traits, even if it implies sacrificing some gain for current objectives.

P.S. This is the first part of an opinion piece published in February 2008 in the New Zealand Journal of Forestry. Read the second part here.

This entry was posted Friday, February 1st, 2008 at 5:27 pm and is filed under objectives, short rotation. Responses are currently closed, but you can trackback from your own site.