Category: teaching (Page 2 of 16)

Why is this trait I like getting worse in the breeding programme?

2024-06-05 / Luis

The short answer: because the trait you like is not part of the breeding objective and, therefore, has not an economic weight assigned to it. And if it doesn’t have an economic weight it has 0 (zero) economic importance.

A longer answer: in breeding there is a distinction between objective traits (which have an impact on profit), and the selection criteria (variables that are easy and cheap to assess, and that are correlated with the objective traits). They may even happen at different ages. For example, in forestry stem volume and wood stiffness at rotation age (say 25 years) can be objective traits for the production of structural timber. Stem diameter, wood density and standing tree velocity at age 8 can be selection criteria.

Some of the confusion may come from when people like a selection criterion (like wood density) and think the breeding programme is trying to improve that. In this example, we weren’t (at least at that time). We cared about volume and stiffness. Sacrificing levels of some selection criterion while pursuing the objective traits is perfectly fine if I am maximising value. And in a modern breeding programme you are pretty much always looking at value, not at a single trait.

If you find this interesting, you may also like Why did my breeding values go down?

Back of the envelope calculations: pulp mill

2024-05-12 / Luis

Imagine that someone stops you on the street and asks “How many hectares of plantations do we need for a pulp mill that produces 1 million tonnes per year of Eucalyptus pulp in Chile?” They don’t need a highly accurate result but a ballpark figure, the right order of magnitude. A Fermi estimate.

How many assumptions do we need?

We need 4 cubic metres of wood for a metric tonne of pulp (wood density 0.5 ton/m³ and 0.5 pulp yield)
Harvest age 12 years
Productivity 25 m³/year/ha

Using 1. we need 4 m³/ton x 1,000,000 ton = 4,000,000 m³ of wood per year. Using 2. and 3. we see that 1 ha produces 25 m³/year/ha x 12 year = 300 m³/ha.

Therefore we need 4,000,000 m³/year / (300 m³/ha) = 13,333.33 ha/year and because we need the same amount in year 1, 2, …, 12 (Harvest age) and we keep on planting forever, the total is 13,333.33 ha/year x 12 year = 160,000 ha.

If you have been paying attention, you’ll notice that we divide and multiply by the rotation (12 years) so we can simplify the calculation back to:

product conversion (4 m³/ton) x capacity (1,000,000 ton/year) / productivity (25 m³/year/ha) = 160,000 ha.

We know that none of those numbers is perfectly correct, but put together they give us an idea of the magnitude of the problem. We can play with them: change site productivity, conversion rate, add safety margins, etc.

Now let’s say that we read of people complaining because a Chilean company announces a 2.5 million tonnes short fibre mill in Brasil. That would need 160,000 ha x 2.5 = 400,000 ha. Massive. As a comparison, INFOR tells us that the whole Eucalyptus estate in Chile is about 900,000 ha and that’s already used by the existing pulp mills, bioenergy producers, etc.

Just from the resource access point of view, having a pulp mill that size would need increasing the country’s Eucalyptus forest estate by roughly 50%. That gives some context to the speculation about the reasons for the investment in Brasil.

Stall owner talking with customer, surrounded by colourful produce. — Sunday market stall, Concepción, Chile.

¿A quién citamos en el sector forestal?

2024-04-22 / Luis

En mi post anterior preguntaba ¿A quién subsidiamos en el sector forestal?, lo que despertó una buena y civilizada discusión. Aprecio mucho la posibilidad de conversar así.

Hoy ví que Horacio Gilabert puso un link a una columna en El Mostrador que nos recordaba las palabras de Jacques Chonchol a la Asociación de Ingenieros Forestales en 1970. Un llamado a plantar árboles en tierras erosionadas por la eliminación de bosque nativo y sobreexplotación agrícola. Muy interesante, pero me preguntaba del contexto: rara vez uno escucha palabras de un fundador del Movimiento de Acción Popular Unitario (MAPU) en la discusión forestal actual.

Es fascinante recordar lo que dijo Chonchol, Vicepresidente del INDAP durante el gobierno de Frei y Ministro de Agricultura de Allende (implementando la reforma agraria) con respecto a la necesidad de plantar árboles en Chile. Ahí ya hay más contexto: era plantar pero hacer otros cambios radicales.

Viene a colación recordar que el mismo Chonchol publicó el libro “Por una nueva reforma agraria para Chile” en 2018, en que el capítulo 14 llama a “evitar la extensión del monocultivo forestal” y el capítulo 12 a “evitar la nueva concentración y extranjerización de la tierra” y el capítulo 17 a “devolver a las comunidades mapuches las tierras usurpadas y desarrollar una política de mejoramiento económico y social de los pueblos indígenas”. Uff, ¿Mucho contexto? Quizás. El libro es asequible y conviene darle una mirada antes de invocar a Jacques Chonchol como un partidario de más plantaciones de pino y eucalipto.

Yo también estoy de acuerdo con que necesitamos más árboles en Chile pero—como decía en un comentario en el post original—no podemos repetir los subsidios del DL701 y esperar un resultado diferente. Necesitamos paquetes tecnológicos que conduzcan a un manejo forestal que produzca madera que califique de grado estructural si queremos madera para construcción en altura. En caso contrario, vamos a seguir alimentando el mercado de metro ruma, con poco valor agregado, pasando parte del subsidio a las empresas de pulpa y las PYMEs continuarán quebrando por falta de materia prima apropiada.

Podemos pensar en plantar algunas especies nativas; he escuchado cosas muy interesantes acerca de roble, raulí y su híbrido, viniendo de la Universidad Austral. Podemos usar otras especies exóticas también, que amplíen la cadena productiva con más alto valor. Ahí estamos hablando de subsidios interesantes y de un sector forestal más diverso. Buscando algo así entré a estudiar Ingeniería Forestal un día de marzo de los años ochenta en Antumapu.

Staircase, Rehua Building, University of Canterbury.

Sometimes we want more, sometimes we want less

2024-04-11 / Luis

I am running analyses for a new article with my colleague Clemens Altaner (a smart cookie), reprocessing old samples to get resin data. This got me thinking on types of traits, as in there are “we always want more” traits, like stem volume in trees, or yield per ha for many agricultural crops. Assuming there were no trade-offs (like reducing quality) we always want more stem volume.

There are also traits with technical thresholds, like wood stiffness grades, or fruit quality grades, where there is a stepwise value function. There is an extra payoff when reaching a new grade, followed by a plateau, when extra expression of the trait is worth nothing until… we get to the next step/grade.

And there are traits which are highly dependent on the end-product, like resin content or heartwood content. If you want to grow a crop for resin production (like some pines in China) you want as much resin as possible. However, if you are interested in solid wood, resin and resin canals are an annoyance, as they reduce the wood grade. A similar situation occurs with heartwood. It’s great to have heartwood if I want more durability, but it may affect processing (including preservative injection) if we want the wood for other uses.

For the current analysis and end-use we want lower values of the traits, but things can change if we move countries or industries.

I would like to know if you can give me examples of this three types of traits (or if there are more types) for your species/end-product. It’s always handy to have non-forestry examples for class.

All that glitters (still) is not GxE interaction

2024-04-10 / Luis

Five months ago I was saying all that glitters is not GxE interaction, putting forward the idea that, at least in forestry, some of the reported GxE interaction was not interaction at all but poor connectedness.

Today Forest Ecology and Management published the work by Duncan McLean (our PhD student, congratulations!), Jaroslav Klápště, Mark Paget and myself (Open Access article). We have eight well-replicated and connected trials, SNP-based pedigree, covering a range of environmental conditions with little signs of interaction.

For wood basic density, a typically highly heritable & low interacting trait, out of the 28 cross-site genetic correlations (Type B in forestry parlance) the lowest value was 0.86. For stem diameter at breast height, a typically low heritability & high interacting trait, 20/28 cross-site correlations were greater or equal to 0.7, often used to define interacting sites. The lowest correlations came from a single South Island site (lowest value was 0.59).

Trees live for a long time and tree breeding programmes are long-lived endeavours. Our genetic evaluations often include trees from many selection series, with many trials connected by tenuous relationships. There are publications that show we only need small connections to compare genotypes across trials: the predicted error variance of the comparison is OK. We need to remember though, that those comparisons are assuming we know the true genetic correlations across sites (as in animal breeding); instead, we are estimating them from data. Data coming from poorly connected trials, subject to biases.

Now imagine we start explaining the estimated GxE interaction, Are we explaining real interaction or just estimation noise? We still have to continue revisiting this topic, which I hope it leads to updating the genetic evaluation system.