Ecological Thoughts

But it's gonna take money, A whole lot of spending money. It's gonna take plenty of money, To do it right, child. It's gonna take time, A whole lot of precious time. It's gonna take patience and time, To do it, to do it, to do it, to do it, to do it, To do it right!   George Harrison (1943-2001)     Much has been written on the fact that doing (good) science requires money. Essays have looked at how much countries invest in science as function of the GDP , how much of this investment comes from the private sector and even some indication of productivity stems from socio-economic analysis, often carried out by the academic community . Papers produced by dollar invested, papers by scientist or the number of scientists per inhabitant are examples of this. Also, monetary return ratios per units of investment are showcased to highlight the contribution of science to the economy.   Productivity indicators are called for because the scientific community uses-to a very var...

  A student of ecology knocks on a supervisor’s office door, -” Excuse me…are you busy right now? …wanted to show you something”  The supervisor (always -and never- busy) replies: -“Sure thing…do come in’   The student walks in, takes a seat and pulls-open a laptop. The screen shows R code and different consoles. For the next many minutes, the excited student shows code and graphs and explains in careful detail how all was achieved, what packages were downloaded and how this changes the last analysis done so far, of the data collected last summer.  The supervisor nods in agreement while entertains a shy smile. This exact situation occurred a week ago, and last month and… who knows how many times.   This scenario has probably been experienced in recent times by students and supervisors throughout academia. The adoption of R-coding to analyze ecological data has been a game changer. Accessibility, almost unlimited capabilities and power are attractive assets,...

Been silent for a while. Every day stuff, meetings, meditation(?)…you all know what I mean.   However, what got me thinking lately, is the advent of LLM and its impacts on academia. I’ve heard a lot and read some more, about its grey aspects: students writing essays with it, fellowship candidates preparing applications with Chat gpt, or even full papers being drafted by AI. The challenges are clear for teachers, journal editors and PIs who have (too strongly?) relied on the writing skills of students and researchers as a means to show their capacity to do good science. But is AI bad for science?   Less often we hear the positive aspects that, such an amazing technological development, can offer to academia. For starters, its speeds access to code which may be needed for statistical analysis, model building, larger coding or drawing neat figures. Nevertheless, it is for the writing that I think there is much to gain. One aspect that is without question, is how it improves speed...

“I don’t know, I’m making this up as I go.” — Indiana Jones and the Raiders of the Lost Ark (1981) (yet another of my Indy Jones’s quotes)   In recent times (and in some countries more than in others), there is an increasing debate about what scientists do. The various challenges humankind faces, from global change, to sustainable food production or antimicrobial resistance, heed urgent solutions for which, a vast part of modern society agrees on, should be based on science.   The urgency for scientist to get down to work and solve our ‘big’ issues, resonates with (some) research agencies and employers. It is not new to many of us, that via oriented research grant windows, we are drawn towards studying new issues or systems which match our interests with those of the funders. Needless to say, here, research needs funding (I say this because it seems to me that not all employers in the Global South are fully aware of this connection). However nowadays, we see a stronger pressur...

The way science is communicated is changing fast, super-fast.    Only a few years ago, scientists would access research within their field of interest, by reading published papers, accessed through subscriptions to journals. Recall that then, all was printed in paper (and black and white) and bounded in issues and volumes which were mailed (snail-mailed) to paying subscribers. In the larger universities and wealthier countries, libraries hosted most major journals and had agreements in place with other libraries to access works they did not harbor themselves. To access a paper, you just needed to walk into the library or ask the librarian for help.    In the Global South (gee… I hate this term!) there were already in place, some basic loopholes. We knew some colleague or research groups (abroad for instance, but not exclusively) to whom we would write and would kindly ask to photocopy (and fax?) that critical paper they had and that we had found by spending hours goi...

  For us ecologists, publication of our findings is a key aspect of doing science. We conceptualize questions, plan and execute experiments and then we need to report them to our peers. However, nowadays, the landscape of publication is seeing rapid change. Open science is out there; an important transformation to democratize science. Pre-print servers based on a ‘crowdsourcing’ model are an interesting and growing development that, however, also brings up much debate 1 . And then, we have recently a number of papers shouting out the problems with inequities in access to scholarly publication by researchers working in less developed world economies, or more often termed, the Global South  2,3  (I admit I’m not a big fan of this term, as I disagree with the geographical implication as well the grouping of wealthy vs poor nations, especially so in the sciences). This brings-up a much called for problem. Are we scientists from the Global South hindered to publish and have an...