Wednesday, November 28, 2012

Why consistent terminology is important

Some time ago, I received this email from a grad student:
"Do you know the blog zombies ideas in ecology?? I think this is the kind of ideas that could interest you. After reading all these chase papers I just find myself completely lost in the meaning and use of words such as stochastic, random and neutral…. This text kind of help me (it’s a critic of the use of these terms in community ecology) but I’m still lost…do you have any tips on that?? It seems to me that a stochastic process is a process that you can  only predict in probabilistic term. But then it can of confuse me because it seems for me that neutrality is random and randomness is a stochastic process, right??..

And shortly after that a 2nd question from the same student:
"And what to do with that : . All Chase works on beta diversity assumption and works on limiting distance similarity is to throw in the garbage??..."
I took me a while indeed to figure out first the problem, and second a potential solution. I will try to break it down, and I will not use full prose, since I am still trying to work out the best way to present and think about this myself, thus the semi-concept map style of writing below.


  • spaghetti clump of terms in the literature:
    • neutral, drift, random, stochastic, unexplained, error term, probabilistic equivalence, dispersal limitation, noise, chance, spatial processes
    • deterministic, niche-based, selection
  • there is not a lot of confusion about niche-based processes = selection

  • neutral and stochastic pretty similar, while different definitions
    • stochastic - in Chase and Myers 2011: "chance colonization, random extinction and ecological drift", "indistinguishable from random chance alone"
  •  but
    • dispersal does not have to be neutral, while this is implied by the definition of Rosindell et al.
    • neutral and stochastic often used as synonyms in e.g. Chase and Myers
  • So lots of confusion around the first group of terms, hence the spaghetti clump 

  • Fox provides some thoughts on a solution, but I think that could use some more explanation (and he will probably correct me if I am wrong ;-)
  • looking at the four community processes from Vellend 2010, I suggest to identify five, fundamentally orthogonal, questions you need to ask to classify a process (and thus the associated terminology)
    • What is the time frame of the process: ecological versus evolutionary time frame (or is it necessary/useful to include speciation as an important process?)?
    • What is the spatial scale of the process, or the metacommunity context:  within- or between-site (dispersal) interactions? I would refrain from using "local vs. regional" here, because "regional" also has the connotation of "at a larger scale", while the action of these "regional" process are sometimes at the within-site scale. For instance, climatic features such as rain or temperature are regional in nature, but each organism experiences this within a site. So it is a regional process at a within-site scale, in that case (another quagmire of confusing terminology).
    • What is the nature of the species differences: are they niche-based (or under selection sensy Vellend 2010) versus neutral (or probabilistic equivalence of species sensu Rosindell et al.)?
    • What is the stochastic nature of these ecological processes: Do they result in a deterministic or stochastic outcome?
    • How do you detect the signature of these ecological processes? Through randomization procedures, or explained variation, or noise, or ...

Using this scheme, I think you could uniquely identify several terms and patterns in the literature, and solve some of the inconsistencies noted above:

  • drift is a specific type of end product of within-site, neutral, and stochastic, species interactions
  • dispersal can be 
    • neutral: all species similar in dispersal characteristics
    • or stochastic: see limiting dispersal sensu Winegardner et al. 2012 (see e.g. Matias et al. in press) , but with some deterministic patterns (see distance decay or isolation by distance in neutral metacommunities, Jeremy Fox's 2nd zombie idea mentioned above).
    • or deterministic: see efficient or high dispersal sensu Winegardner et al. 2012
  • neutral species interactions can
    • lead to dominance of one species over long time periods, and thus look deterministic
    • be deterministic (see Jeremy Fox's examples in his first zombie idea)
  • selection can be stochastic (see also Jeremy Fox's example in his first zombie idea)


  • It would be easy to fall in the trap outlined by Jeremy Fox, and treat these questions as "ends of a linear continuum". I do think they are ends of a continuum, but this does not have to linear (which is what I think the main danger is that Jeremy Fox wanted to point out).
  • I reserve the right to change my mind on this above classification, based on what I hope to be lots of discussion and exchange of ideas.

Monday, November 26, 2012

A new Dr. !

Thiago successfully defended his PhD in Brazil! Congratulations! You will be able to read all the innovative research he has done the last couple of years as they will become part of the vetted ecological literature, no doubt about that. But I think he learned more than "ecology" during these last years. Here is an excerpt from his acknowledgments:
"Tive muita sorte de conhecer o meu co-orientador Karl Cottenie. Para minha surpresa, um quadro branco e uma caneta preta - e não um programa de estatística - me mostraram como rabiscos podem gerar ideias e muito conhecimento. Foram seis meses que mudaram minha vida! Karl, I know that you'll google it ;-)"
 So after the magic of Google Translate:
"Ik was erg blij om mijn co-adviseur Karl Cottenie weten. Tot mijn verbazing, een wit bord en een zwarte pen - niet een statistisch programma - liet me zien hoe krabbels kan genereren ideeën en heel kennis. Het duurde zes maanden dat mijn leven veranderd!"
It is always satisfying to see another convert to the power of the whiteboard and concept maps. Keep Thiago on your radar, he will do fun things!

And thanks to the power of Facebook, here is a picture:

And here is a link to Thiago's amazing presentation: it not only looks nice, but presents a succinct and clear overview of what he did:

Friday, November 23, 2012

"We are creative people"

Some insights from a completely different source through amazing photography and words:

"I’ve started looking at some of my other work, to see if I can find a theme, a concept of some sort, and I think I’ve begun that process. It’s rather exciting to feel that one thing leads to another, and by simply being open and experiencing my existing work in a new way, I can see something lurking, waiting to be pulled out and developed. Maybe something new will come of it. I really don’t know, and I guess that’s what’s so great about the creative process, things often have a way of taking on a life of their own."

Thursday, November 8, 2012

The role of intuition in data analysis

Most of you readers probably followed the US elections with varying degrees of interest and passion, but as scientists are also aware of the "role" of Nate Silver and his blog Lots has been written about his success, which is "just" a nice example of the strengths of the scientific process, and thus not that surprising. What does surprise me, is the reluctance of journalists to come to terms with what he does. See this very insightful blog post by Mark Coddington.
"Silver’s process — his epistemology — is almost exactly the opposite of this: Where political journalists’ information is privileged, his is public, coming from poll results that all the rest of us see, too. Where political journalists’ information is evaluated through a subjective and nebulous professional/cultural sense of judgment, his evaluation is systematic and scientifically based. It involves judgment, too, but because it’s based in a scientific process, we can trace how he applied that judgment to reach his conclusions."
This reluctance reflects, amongst other aspects, a classic case of a an either/or role for intuition in science/data analysis. We already had a lengthy exchange about the scientific process on this blog (see for instance this and this), and Stefan's main critique against the scientific process as a method is maybe summarized in this statement:
"I am claiming here that in order to do good science, one must know which auxiliary assumptions are reasonable to question in the face of evidence that conflicts with one’s predictions."
One way to look at this is that intuition plays that role of knowing "which auxiliary assumptions are reasonable". So it is not an either/or relationship, but really a feedback between intuition and hypothesis testing.

Or my last commandment: "Thou Shalt Listen to thy Intuition, but Follow the Data."