Evolving notes, images and sounds by Luis Apiolaza

Category: teaching (Page 1 of 14)

¿A quién citamos en el sector forestal?

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.

Sometimes we want more, sometimes we want less

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

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.

Genetic correlations for DBH and wood density under three genetic models.

A few things that I expect to find in a well-functioning breeding programme

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.

Tuesday evening mid-life crisis

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?

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