Problems in funding biological conservation research

REPLY TO: 20 Jul 2024: https://www.zoology.ubc.ca/~krebs/ecological_rants/problems-in-funding-biological-conservation-research/

I am neither a good ecologist nor a good environmentalist. But this is about research funding and conservation, so bear with me.

My wife and I enjoy walks around Deer Lake. If somebody were to ask me "Why are there so many mallards but so few wood ducks?", all I could do is some handwaving. It's survival and reproduction, it's the niche, it's all very complicated. I know, I know. Coexistence is one result of the Lotka-Volterra competition model (1), but to ask Platt's famous question (2): "But [Madam or] Sir, what experiment would disprove your hypothesis?" Causality is hard to establish in the historical sciences (3).

I am also not sure about conservation. As I have asked before (4): Why is biodiversity worth protecting? More than that. When I see the family-tent-sized rubber sheets rolled out around Deer Lake to combat the invasion of the yellow flag iris, I wonder how well these rubber sheets work. Looking at the sizeable populations next to the rubber sheets, my response is: Not well. 

Of course, you may say I am an idiot, and indeed I know very little. But if we cannot come up with good explanations for the abundance and the distribution of organisms, if the only reasons for protecting biodiversity we can name are vague notions of ecosystem stability and aesthetics, if the outcomes of our conservation efforts are uncertain at best and pathetic at worst, and if the timescales governing our objects of interest is decades to centuries, it is half a miracle that we do get funding at all.  

The question is this: How can we convince the average citizen that ecological research is important? (5)

I am not sure if education is the answer. I teach ecology and evolution at a fourth-rate university. I do have students who think that humans are the cause for the extinction of dinosaurs, a belief that would have gotten me thrown out of middle school. And a couple of months ago, I visited the Beaty Biodiversity Museum at U.B.C. with four questions in mind (4): How much biodiversity is out there? Why are there so many species, or why are there so few? Why is biodiversity worth protecting? How should we manage biodiversity? The only question that was somewhat answered is the first.

But maybe I am expecting too much from us humans. 

(An afterthought: When I was a postdoc at U.B.C. in the late 1990s, I dreamt of an independent research institute for ecology (6), where researchers could focus on hypotheses and evidence. I even imagined the funding. Not from the public, because it requires the writing of grant proposals that may not get funded and the publishing of papers that nobody reads. Not from "philanthropists", because it may require sycophancy, compromise, and possibly hypocrisy (7). The funding I envisioned was achieved through -- hold on to your seats -- sports betting. If we are as good at data analysis as we think we are, this should be a piece of cake. I even trained an artificial neural network on about a thousand baseball games. The trouble was that it never converged.)

NOTES AND REFERENCES

(1) C. J. Krebs (2009), Ecology (Sixth Edition).

(2) J. R. Platt (1964), Strong Inference. Science 146: 347 - 353.

(3) My comment on https://www.zoology.ubc.ca/~krebs/ecological_rants/the-two-ecologies/.

(4) My comment on https://www.zoology.ubc.ca/~krebs/ecological_rants/biodiversity-science/.

(5) If the average citizen is not convinced, the average politician will not act. That said, it is still a mystery to me how the physicists get their particle accelerators or the astronomers their space telescopes. 

(6) What the Institute for Advanced Study used to be to mathematics, the Santa Fe Institute to complex adaptive systems, the Oregon Research Institute to psychology.

(7) Who would you NOT accept money from? 

The calculator and artificial intelligence

A group of university administrators has made the following foolish argument (1).

OBSERVATIONS

O1: The introduction of the calculator in the classroom was opposed by many who predicted a decline in academic standards. 

O2: The introduction of the calculator in the classroom DID NOT result in a decline in academic standards. 

O3: The introduction of A.I. in the classroom is opposed by many who predict a decline in academic standards.

ASSUMPTION

A1: The introduction of A.I. in the classroom IS equivalent to the introduction of the calculator in the classroom.

CONCLUSION

C1: The introduction of A.I. in the classroom WILL NOT result in a decline in academic standards.

Here are my objections.

ON O2

The introduction of the calculator DID result in a decline in academic standards.

Perform the following long division by hand: 123456 ÷ 789. 

Did you find it easy? No? Why then should students be exposed to this avoidable tedium?

Because long division does train the mind NOT ONLY in long division. It also teaches students to break a big unsolvable problem into smaller solvable ones. And it exercises the mind in the consistent application of a simple set of rules, a procedure, an algorithm. And it teaches students perseverance and resilience. 

Not exactly irrelevant transferable skills and traits in life and in the workplace. 

ON A1

The introduction of A.I. in the classroom IS NOT equivalent to the introduction of the calculator.

Calculators are primitive tools. They are about arithmetic, the processing of numbers. Calculators are not smarter than humans, they are just faster. 

Of course, mathematics also deals in algebra and calculus, the processing of variables and equations, respectively. We have invented tools to make us faster and more accurate in those areas as well (2). But using these tools requires knowledge about what you are doing. 

Even using the calculator: What exactly is it that you want to calculate? 

Conversely, much of today's "A.I." is based on Large Language Models, artificial neural networks that process complex symbols. These provide easy access to products of analysis and synthesis. Using them doesn't require the discipline of acquiring knowledge. An idiot can use ChatGPT and look smart (3). 

ON C1

Prompted with the observations (O1, O2, O3), the assumption (A1), and the conclusion (C1), the ChatGTP artificial neural network responded (4): 

"The key to this conclusion lies in the assumption that the introduction of A.I. is fundamentally similar to the introduction of calculators in terms of the context and scope of use. If this premise holds true, then the positive outcome from calculators can be reasonably extended to A.I., supporting the conclusion that the impact on academic standards will not be adverse."

Not bad. A machine displaying more intellectual rigour than the authors of the article. (And yes, I see the irony here: Had the authors used ChatGTP, they could have made a stronger argument.) Still, I am somewhat disappointed. I expected the machine to have more of an agenda. 

NOTES AND REFERENCES

(1) M. M. Crow, N. K. Mayberry, T. Mitchell, and D. Anderson (2024), AI Can Transform the Classroom Just Like the Calculator. https://www.scientificamerican.com/article/ai-can-transform-the-classroom-just-like-the-calculator/ (Accessed: 24 Apr 2024).

(2) E.g. Mathematica, Maple. 

(3) You want to give a presentation on say 17th century French literature? Just sign up to ChatGPT and enter the following prompt: "Can you provide me with the text for ten PowerPoint slides on 17th century French literature?" Hey presto! 

(4) ChatGTP 3.5 (Prompted: 25 Apr 2024). ChatGTP gave a variety of responses to the same prompt. All consistent with each other. 

Biodiversity science

REPLY TO: 28 Feb 2024: https://www.zoology.ubc.ca/~krebs/ecological_rants/biodiversity-science/

(I know, I know, too long again. I always seem to drag myself into a swamp of thoughts.)

How much biodiversity is out there?

Why are there so many species (1), or why are there so few (2)?

Why is biodiversity worth protecting?

How should we manage biodiversity?

These are the questions of biodiversity science, of course, but I am afraid that we will fail at the first one. Answering how much biodiversity is out there does require taxonomists.

It is not a secret that around the time of the Watson and Crick paper in 1953 (3), a chasm opened in biology, a chasm between molecular biology and organismic biology. Molecular biology received faculty positions, research funding, research castles, and journals (4). Organismic biology received a kick in the groin. 

In their classic paper from 1979 -- 1979!! -- Gould and Lewontin quote Rupert Riedl (5): 

"[T]he whole of the huge and profound thought collected in the field of morphology, from Goethe to Remane, has virtually been cut off from modern biology. It is not taught in most American universities. Even the teachers who could teach it have disappeared."

(I received my undergraduate training under Rupert Riedl at the University of Vienna. A lot of courses in morphology and comparative anatomy, a lot of Linnean tables and classification keys, nothing on cladistics, very little biochemistry. But even as zoologists we had to be able to identify at least 125 plant species (6).)

The situation wasn't helped when in 1988 Nobel laureate Luis Alvarez disparaged the scientists who try to understand species (7): 

"I don't like to say bad things about paleontologists, but they're really not very good scientists. They're more like stamp collectors.'' 

Except, of course, Alvarez did say a lot of "bad things" about other scientists. 

Taxonomists used to be respected as collectors of historical evidence to test hypotheses on the origins of species, disparity in body plans, biodiversity, variation within species, and, more recently, invasive species (8). There is no comfort in the irony that the profession that can tell us whether a species is going extinct is going extinct itself.

Maybe I don't know enough, or maybe my judgement is too harsh. I am wondering, Charley, how do you see recruitment and training in biodiversity science?

NOTES AND REFERENCES

(1) G. E. Hutchinson (1959), Homage to Santa Rosalia or Why Are There So Many Kinds of Animals. The American Naturalist 93(870): 145 - 159

(2) J. Felsenstein (1981), Skepticism Towards Santa Rosalia, or Why Are There So Few Kinds of Animals. Evolution 35:124 - 138

(3) J. D. Watson and F. H. C. Crick (1953), Molecular Structure of Nucleic Acids. Nature 171: 737 - 738

(4) Have a look: https://www.nature.com/siteindex#journals-N (Accessed: 7 Mar 2024). How many Nature journals cover molecular biology, how many organismic biology?

(5) S. J. Gould and R. C. Lewontin (1979), The spandrels of San Marco and the Panglossian paradigm: a critique of the adaptationist programme. Proceedings of the Royal Society B 205: 581 - 597

(6) Of course, there are some good identification apps out there (e.g. Pl@ntNet for plants, Merlin for birds), but they are for hobbyists. Besides, who is going to produce the data required to train the artificial neural networks? 

(7) M. W. Browne (1988), The Debate Over Dinosaur Extinctions Takes an Unusually Rancorous Turn. The New York Times (19 Jan 1988): C1 + C4, 

(8) Currently there are 110 known invasive species in British Columbia alone. See: https://bcinvasives.ca/ (Accessed: 7 Mar 2024).

Higher education: The things we do and fail to do

The original title of my article was "Higher education: The things we do and fail to do". The editors changed it to "Preparing good citizens and workers means treating students as adults", which is lame.

https://www.timeshighereducation.com/blog/preparing-good-citizens-and-workers-means-treating-students-adults 

What to read in the ecological literature

REPLY TO: 23 Jan 2024: https://www.zoology.ubc.ca/~krebs/ecological_rants/on-what-to-read-in-the-ecological-literature/

Three thoughts, but a caveat first. 

"In our times, we would only publish when we felt we had something to say. Today, if you don’t have anything to say, you do that in at least two or three papers." Dennis Chitty said that (1). That was in 1996, when Chitty was 84 years old, and I was 31. I have lived by his standards ever since. 

I never had much to say, and even fewer things that hadn't been said before.  (I remember one time I discovered something interesting about probabilities, and it turned out to be Bayes's theorem (2). About 250 years too late.) Consequently, I never believed that reckless publishing would move society forward. 

And yes, as was pointed out to me frequently: "Publication is the currency of our success." (3)

1: During my grammar school years and undergraduate studies, I wish my teachers had taken the time to expose me to the original books rather than some child's play version of them. Euklid, Newton, Darwin, and Einstein, come to mind.

2: During my Ph.D. years, I rated every book and paper I read. It turned out that about 90% of the books I read were worth my time and 90% of the papers were not. So, I focused on books and classic papers (4). But even here I wish I had had better guidance (5).

3: There is normal science and there are scientific revolutions (6). During periods of normal science, scientists work within a framework of beliefs and accumulate facts that strengthen the framework. Who is challenging the frameworks today?

And of course, there is the story of the newly hired professor at U.B.C. who only reads the abstracts, because reading doesn't get you tenure or grants, writing does.

NOTES AND REFERENCES

(1) D. Chitty (1996), pers. comm.

(2) T. Bayes (1763), An Essay towards solving a Problem in the Doctrine of Chances.

(3) L. M. Ward (2003, 2004, 2005, 2006), pers. comm.

(4) F. Courchamp and C. J. A. Bradshaw (2018), 100 articles every ecologist should read. Nature Ecology and Evolution 2: 395 - 401. This publication lists only six papers that were published after 2000.  

(5) It was years after I completed my Ph.D. in 1998 that I discovered: E.g. T. C. Chamberlin (1890), The Method of Multiple Working Hypotheses; A. Szent-Györgyi (1960), Introduction to a Submolecular Biology; J. R. Platt (1964), Strong Inference. 

(6) T.S. Kuhn (1970), The Structure of Scientific Revolutions. Second edition.