A good understanding of the biological traits that have an effect on profit. Can we identify new, more efficient selection criteria?

A clear awareness of trade-offs between: traits, genetic evaluation options, deployment systems, etc. Trade-offs are everywhere in breeding programmes.

A database system that contains all the data.

A well-documented genetic evaluation system: we can rerun the evaluation and get exactly the same results. The system can be developed in-house or can use commercial software (like asreml, SAS, Bolt, etc) but the code must be available.

Reproductive biology: essential to sort out the best deployment.

Figured/figuring out what are the main environmental drivers affecting performance. It is easy for some species, very difficult for others.

Personnel continuity BUT the programme can survive the proverbial bus running over the breeder.

There was a time, roughly 30 years ago, when my whole career extended to an unknown, distant future. What should I do? Where should I be working? were the questions in my mind during a hot Chilean summer. At that time, New Zealand and Australia were not in the horizon and I had just applied to my first forestry job in Valdivia.

I got that job and three years later I started my PhD. I met people, travelled, gained citizenships, made friends, learned many things, forgot others. Today, thirty years after that summer, I look to the next 10 years in the future and ask myself: What should I do? Where should I be working? The same questions plus What would be the best use of my time?

Now that distant unknown is three decades closer. Should I do more administration and, strange misnomer, “service” to the profession? (as if all the other work was not of service). Should I go for a new push of research work, write up all the ideas thought but not completed and published? Maybe I should transfer all I know to other people.

All of the above, a mix of two, one only… What would be the best use of my time?

“Tree breeding has added 2 Billion dollars to the forest industry” said the presenter during a seminar.

Two billion? With a B? How come we struggle to get funding for projects then—I asked myself.

There are two testing cultures in forestry: the inventory/modeller crowd and the breeding crowd. The inventory crowd often relies on multiple-tree plots over a given area. Plots can be rectangular, circular, defined by prism, etc. The breeding crowd tends to use single-tree plots, because they (including myself) are testing many genotypes and it is more statistically efficient to use plots defined by a single individual.

Breeders use a selection index that gives a dollar value for each individual, while competing against a mix of genotypes (remember single-tree plots?). We would like to extend those results to inventory level and multiply the values by hundreds of thousands of hectares, there is a correlation with area-based performance, but not perfect.

Don’t get me wrong, I work in breeding. However, the selection values are Monopoly money until we get realised genetic gain validated by inventory plots in Real money. The two testing cultures have to match and forest valuation go up by $2 Billion before making a claim like that.