Palimpsest

Evolving notes, images and sounds by Luis Apiolaza

Page 2 of 67

¿A quién subsidiamos en el sector forestal?

Las últimas semanas ha habido una ofensiva comunicacional grande del sector forestal chileno, con participación de las empresas grandes, CORMA, el Colegio de Ingenieros Forestales, etc. Editoriales, entrevistas a página completa, cartas al editor… acceso completo a los medios. Instalando la idea de una crisis del sector forestal, de la necesidad de “apoyo” del gobierno, de incrementar la seguridad en la macrozona sur y de políticas que impulsen la expansión del área plantada.

Un componente importante de esa ofensiva comunicacional es establecer como punto de prensa la necesidad de subsidios, en ocasiones indirectamente (“el área forestal creció mientras hubo subsidios, ahora no”), a veces directamente (“necesitamos subsidios”). Otro componente es destacar que el apoyo es para la pequeña y mediana empresa, no las grandes, porque se ve feo que empresas con capitalizaciones de miles de millones de dólares anden pidiendo apoyo del Estado.

Estaba en la ducha, lugar de origen de muchas ideas de investigación y artículos, pensando en esta historia cuando me surgió la siguiente duda: ¿Cuánto de los subsidios a la pequeña y mediana empresa es, al mismo tiempo, subsidio a las grandes empresas?

Línea de pensamiento: el mercado de trozas de pulpa es un monopsonio o un oligopsonio para los pequeños y medianos propietarios forestales (uno o dos compradores, depende de dónde uno esté). Las empresas de pulpa tienen sus propias plantaciones, pero también compran de terceros y fijan el precio de metros ruma (unidad de volumen 1 m x 1 m x 2,44 m), afectando en buena medida la rentabilidad de pequeños y medianos propietarios. Subsidios a las plantaciones se transfieren, al menos parcialmente, como subsidios a las empresas grandes que logran mantener su rentabilidad por medio del precio de metros ruma.

Me gustaría saber si hay estudios que han mirado a este ángulo del problema. Esto es lo que pensaba mirando desde la distancia al sector forestal chileno, necesita ser pulido, digerido, dado vuelta, procesado y escrito con más claridad. 🙂

Do you remember your first time?

You were nervous. Would they like it as much as you did? Would you make the cut? Your first manuscript as a senior author tends to be a memorable experience. On one side, you have been working a long time, coming to terms with the problem, learning, building models, polishing the words [insert a few iterations here] until you submit the manuscript. It is a hopeful act.

Do you remember the feeling of the first acceptance? Your work was judged good enough to be published in that special journal, the one you like. The one were so and so, the authors you admire, published their work. Later you’ll understand that there are diminishing returns, so your tenth article will not provoke the same reaction, and your fiftieth article… you get the idea.

Do you remember your first rejection? Was it just a “desk-rejection”, wrong journal, no big deal? Or was it a “we hate the manuscript, what a turd”? This one can hurt, but there are diminishing returns too: your tenth rejection is more like “meh, what do they know?”.

Both the acceptances and rejections are of that particular piece of work. They are not about you, although some referees (typically referee No2) sometimes manage to make it feel personal. You are not a better or worse person because of the comments of a random set of referees. It is good to remember that a different sample of referees could have told you something very different about the manuscript.

I do remember the first acceptance; I barely remember the first rejection. I do look at those experiences with older eyes, thinking that in both cases I would write the manuscript very differently today.

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.

Taylor & Francis made me do it

Today I received an email from Taylor & Francis letting me know that the final volume and pagination for one of our papers was available, and telling me that I should share this paper with the world. I should, as the open access (OA) costs are USD 3,000+. The article is here, by the way.

Today Elsevier sent me an email as well, confirming that OA fees of USD 3,400+ for our new accepted article were covered by our university’s Read and Publish Agreement.

Also today (it was a busy day!), MDPI sent me an email, stating that the authors of a new review were sharing their new OA article with me. It cost them 2,600 Swiss Francs or roughly USD 2,900 to do so. I consider MDPI Forests borderline predatory, so I wouldn’t pay to go there, but “cada loco con su tema”, as we say in Spanish.

I am part of a priviledged group, who works at one of the members of CAUL, an organisation for university libraries in Australia and New Zealand. We have access to big bucket agreements with publishers (the usual suspects like Elsevier, Springer Nature, Taylor & Francis, etc). We have a quota of articles, first-in, first-served, that are published open access “for free”. Not quite, the universities pay for that quota, but researchers are not charged individually.

This situation creates funny incentives: OA publishing in journals run by big publishers has no direct cost to me. OA publishing in journals that I like—Annals of Forest Science, for example—but that are not part of my university agreement is unaffordable. I literally have no funding for it. As Annals of Forest Science only publishes OA articles, that’s bye, bye for me. A good alternative, in forestry at least, is to publish for free in an OA journal like the New Zealand Journal of Forestry Science. Give them a  try.

Today I was left with the horrible feeling that we are burning money for no clear purpose in the current publication environment. We could easily pay for better PhD scholarships or postdoc salaries with that money, although is not available for those purposes. We can only use it to keep on feeding publishers with insanely high profit rates. Crazy.

Anyway, if you are interested in essential oils from eucalypts, read the article. I mentioned this work before but now comes with fresh, shiny, cineole-smelling page numbers. Either that or the article smells like burning money.

« Older posts Newer posts »

© 2024 Palimpsest

Theme by Anders NorenUp ↑