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Percolation and scaling in ecology

5 minute read


Scaling is a central theme in ecology, well this is my opinion, but there are others that think like me, for example Brian Enquist, that organized a symposium for the 100th anniversary of the Ecological Society of America Scaling in Ecology. He mentioned that two of the most influential papers from ESA were about scaling: Simon Levin The Problem of Pattern and Scale in Ecology and J.H. Brown The Metabolic Theory of Ecology. But why some processes permeate through scales and others do not; scaling is important because it implies something that crosses scales, did you ever heard the phrase: think globally act locally. Our new preprint analyzes what happens when one species percolates through the landscape Read more

Metacommunities or self organization principles

3 minute read


I am thinking of writing in Spanish, because Spanish is my mother language, but there seem to be not much people writing about ecological science in Spanish. At the end I started to think in English and then write in English, so the next one should be in Spanish, who knows. Read more

A protocol towards a general theory of community ecology

3 minute read


Definitive answers are scarce in biology 1 2 but if we want the advance of ecological knowledge we should reach a point where we have a theory we can trust, and can be used for prediction.

  1. Hubbell SP (2005) Neutral theory in community ecology and the hypothesis of functional equivalence. Funct Ecol 19: 166–172. doi:10.1111/j.0269-8463.2005.00965.x. 
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How to make slides without powerpoint (or LibreOffice Impress)

1 minute read


I started to use R Markdown with RStudio, but what is Markdown? :

"Markdown is a simple markup language designed to make authoring web content easy for everyone"

So it's easy to do a report of the millions of figures and analysis  while experimenting with a dataset or developing a manuscript.

A good stating point is the post of Jeromy Anglim's Blog about that.

Then I found that you could produce slides for presentations with only an additional step pandoc. The Markdown generated by RStudio can be converted to html slides and there are different "kinds" of slides you can convert to, and they look nice.
I have to prepare two talks for the RAE2012, so why not?

I was happy because I thought I would end with the curse of Powerpoint/Impress

But it was not so easy, things were not always as they should be. I was pressed to finish and tables don't get formated, figures don't get in the places I wanted, and the videos don't work at all. 

After endless try and error cycles  I finished, I have to learn a little of html and the posts of Markus Gesmann and Christopher Gandrud  were invaluable. I decided to use slidy and as there was no internet connection at the conference room everything must be included in the html file so I used the following pandoc command:

pandoc --self-contained -s -S -i -t slidy -V slidy-url=slidy -o RAE2012_Charla_slidy.html

for use this you have to download the Slidy code in a local folder called "slidy" 

 The source of one of talks is here and the slides are

One drawback is that if I upload talk to figshare the html code is displayed and not like when uploading a pdf, it shows the formated talk ...

I think it's a matter of experience, things get easier after some work,  but I'm not sure if I get rid of powerpoint/impress... next time we'll see.

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Los 10 puntos para revisar antes de enviar un manuscrito

5 minute read


Well this is extracted from the highly recommended blog of Mike Kaspari </span>so we can call it a steal, but it will be a useful theft anyway.
  1. Get rid of every adjective modifying a relationship. Was x larger than y? Just say so. Saying it was much larger, or especially tiny, or amazingly huge adds no information.
  2. Replace long words with short words. Good writing maximizes the content of the message per number of letters used. Replace long words with short words of equal meaning. Replace utilization with use.
  3. Replace every “differed” or “was different” with the actual, quantitative relationship. Compare the content per letters used for the following two sentences:
    Plants fertilized with nitrogen differed in height from controls.
    Plants fertilized with nitrogen were 2.5 x taller than controls.
    Not only have you conveyed that nitrogen increased growth, you’ve given a vivid word picture as to how much. In fewer words!

  4. Make sure your Discussion has a caveat paragraph. Every study is flawed or makes simplifying assumptions; every study has a method or result that may be misinterpreted. Grad students often attempt to hide these flaws. But, like an untreated cut, such problems can fester in the mind of a reviewer. Consider inserting a caveat paragraph somewhere in the middle of the Discussion that thoughtfully addresses at least two topics.
    The first is a plausible mistake a harried reader might make and why it is incorrect (look for patterns in your friendly reviews to identify likely candidates). Good writing is good teaching, and good teachers anticipate the problems of their students.

    The second should confront the biggest weakness of the study, how you tried to ameliorate it, and perhaps how future work could better tackle it (in other words, ending on a positive note). Do you want to be the first person to raise this issue, or would you rather your reviewers do so?
    A caveat paragraph depicts a thoughtful author who is after the truth, not someone who is trying to sell something.

  5. If your Discussion is more than 2x longer than your results, cut it down. Discussions are not brain dumps, nor are they opportunities to lay claim in print to every idea you have on the subject. Careful topical reviewers, by the time they reach the Discussion, want to know how your results relate to your hypotheses, the strengths and weaknesses of your results, and perhaps one or two implications of your results. Focus on these three tasks, and leave your reviewer wanting more, not flipping ahead to see when the bibliography begins.
  6. Market test your title and abstract. More and more editors are rejecting papers before they send them out for review. Reviewers typically accept or decline to review papers on the basis of the title and abstract. The title and abstract are the front door to your study. They are the most important parts of the paper. Craft them carefully and show them to your friendly reviewers.
  7. Spell check everything. Natch.
  8. Even your bibliography. Your scientific career is built on a bedrock of trust. Reviewers want to believe that you have carefully collected and analyzed your data. However, to a large degree, your reviewer’s ability to see just how meticulous you are is limited. This is why typos in the manuscript loom far larger than many beginning scientists think. And, similarly, why care in constructing your bibliography–that Latinate names are italicized, that the journal’s formatting is followed to the letter, that authors names are spelled correctly–also reflects your ability to conscientiously manage detail. Will reviewers give you the benefit of the doubt? Often it’s the little things that decide.
  9. Read it aloud. There is no better way to gauge the flow and logic of a manuscript than to read it aloud, effectively using your whole brain in the enterprise. Beginning scientists should do this in three steps:
    Read the first sentence of every paragraph, in sequence, from the Introduction through the Discussion. If the paper is well written, it should sound like you are explaining the study to a colleague, albeit in a rather stilted way. If the paper doesn’t make much sense, it needs work on its paragraph structure.

    Next do it again, but this time read the first and last sentence of every paragraph. This should result in greater logical flow–the final sentence of one paragraph leading into, and often introducing, the first sentence of the next paragraph. If you find little difference between this reading and the previous, spend a day or two fixing the ends of your paragraphs.

    Now, after a cup of coffee, a long walk, or a nice bout of screaming into a pillow, read the whole paper aloud. Listen for any awkward phrasing, which will sound like your car engine misfiring. For some reason, reading the whole manuscript aloud allows you to see it in a new light, or, more aptly, with fresh ears.
  10. The following is from  the comentaries of the original post:
    Arrange the tables and figures on your desk in the order they appear in your manuscript, but don’t look at the text. Do they tell your story, even with the text removed? Does the progression of figures have a natural feel to it, or do they need to be rearranged to flow better? Are there any figures that don’t seem to belong and potentially could be removed to streamline the paper? Is there consistency in style? If the figures are shrunk by 50%, can you still read the text? (Ben)
  11. Here there are more: "Fourteen steps to a clearly written paper"
  12. UPDATE: a great post with more writing advice: some well known tricks for clear writing
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The neutral bomb

2 minute read


This is not a sex bomb, but who knows. A couple of weeks ago I was giving a talk at the Escuela Argentina de Matemática y Biología about neutral and non-neutral models in ecology. I was pointed to the paper of  Clark 2012 The coherence problem with the Unified Neutral Theory of Biodiversity with the commentary: the neutral theory is uninformative. And the paper  basically says that neutral models or neutral theory is based on ignorance and that they are incoherent.
I think this is very interesting, but I disagree, here I review the last four points of the article:

(i) Incoherence: Neutral models assume all individuals are equal then go on and predict things like SADs and SARs, what is this telling us about the niche? The individuals are all equal, the species can have different effective probabilities to reach a place, different densities, but there is no niche. In this sense it can be thought as a null model for niches, other kinds of null models for niche can be constructed and maybe they are better, but I don't see incoherence.  Competition and niche are not the only things relevant to coexistence of species.

(ii) Ignorance: I am sure we are ignorant about nature, but assuming that all individuals are equal is not equal probability and equal probability is not a null model for sameness. Anyway the equivalence of individuals is certainly not ignorance is an assumption.

(iii)Victory: There are no victories here, but models or theories to explain nature patterns and we need to confront them with data in several ways, and much better in several ways at the same time.

(iv)Applying neutral models in conservation: you have to be careful to apply a model to conservation practices, neutral or not neutral does not matter at all. Models are not reality, always have simplifications, aproximations, or assumptions and we can select which is better for our problem (see Model selection in ecology and evolution).

The real issue I think is a matter of scale: which are the microscale processes that determine macroscale patterns. If niche models predicts the same patterns that neutral models and both are consistent with real data (see Niche and neutral models predict asymptotically equivalent...) a parsimonious interpretation is that we don't need niche. But if real data does not match the model we do need to add more complexities.

I think that neutral models are usefull both intellectually and practically, more about this in Neutrality without incoherence: a response to Clark
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Come together

1 minute read


Aggregation of objects is widespread phenomena in several sciences and of course in biology and ecology. Two cases I found and seem interesting to me are: the aggregation  in niche space: The clumping transition in niche competition, and the aggregation in neutral models: Clustering in neutral ecology.

This seems to depend only on the discreteness and finiteness of the objects and space. And in both cases the clumps have sizes distributed as power laws.
Furthermore when you have aggregation is possible that you will find multifractals, so is very possible that multifractals are widespread on ecological and biological phenomena.

All this introduction is because my article in Oikos is available as early view:

Multifractal growth in periphyton communities
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Why don’t you take a bath?

less than 1 minute read


I had a hard day, lots of data, many papers, many ideas crossing my mind, all ended in confusion, nothing was clear

I went home and my wife said why do not you take a bath?

Under the shower, soaping me, suddenly, everything was fixed in my head.

But this always happens to me, the best ideas come while I am taking a shower.

It looks like someone did the experiment and found the same:

Why greater ideas come when you are not trying?

(Went to bath)
(came back from bath)

The problem is that sometimes an hour passes and I am still under the shower, and I realize that because my fingers get wrinkled.

PS: next post will be about ecology: stochastic aggregation. 
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A poster like a flower

1 minute read


These are my ideas about self-publishing a poster. There are tons of places on the Internet about how to write the best poster, but I think that most of them don’t apply their guidelines for it’s own publication, I mean the web page where the guidelines are published.\ Read more

Disentangling the Drivers of beta Diversity Along Latitudinal and Elevational Gradients (updated)

1 minute read


Roughly, this science paper suggest that gamma diversity can explain the latitudinal/altitudinal variations in beta diversity so there is no need to invoke different local assembly mechanisms, they use two extensive data sets (One of them is here ). It seems to me that almost the same thing is formulated in the Hubbell’s neutral theory, local alfa diversity is determined by metacommunity (regional or gamma) diversity so beta diversity will also be determined by gamma diversity. In fact an expression for beta diversity under the neutral model was derived and it was found inconsistent with data. But different measures of beta diversity were used… Read more

First post

1 minute read


I don’t know exactly why I chose this name for this blog, it was the first thing that came to my mind when I thought about my own science blog. I had blogs about poetry and short stories (in Spanish) but this is a new challenge it was slowly forged inside me from some time ago, this last step was inspired by a note about open science by Carly Strasser and by the Oikos blog, that was the first blog about ecology I met. So I am a ecologist interested in biodiversity usually working with models and data, I will try post the things that go through my head in the process of making and learning open science. Posting will be in English but sometimes I will post in Spanish so in any case we have big brother’s help of google translation. One more thing, I googled the name of the blog and this note about blue water thinking appeared, I will reproduce the first phrase. Here we go: Read more



On the phytoplankton bloom in coastal waters of southern King George Island (Antarctica) in January 2010: An exceptional feature

Published in Limnology and Oceanography, 2014

Schloss, I. R., Wasilowska, A., Dumont, D., Almandoz, G. O., Hernando, M. P., Michaud-Tremblay, C.-A., … Ferreyra, G. A. (2014). On the phytoplankton bloom in coastal waters of southern King George Island (Antarctica) in January 2010: An exceptional feature? Limnology and Oceanography, 59(1), 195–210. Read more

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Life between tides: Spatial and temporal variations of an intertidal macroalgal community at Potter Peninsula, South Shetland Islands, Antarctica

Published in Estuarine, Coastal and Shelf Science, 2016

Marcías, M. L., Deregibus, D., Saravia, L., Campana, G. L., & Quartino, M. L. (2016). Life between tides: Spatial and temporal variations of an intertidal macroalgal community at Potter Peninsula, South Shetland Islands, Antarctica. Estuarine, Coastal and Shelf Science, 187, 193–203. Read more

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Modelos de metapoblaciones en R

Posgraduate course, Universidad Nacional de General Sarmiento, 2013

Este es un curso de posgrado sobre metapoblaciones utilizando lenguaje R, basicamente es una introducción a la modelación de metapoblaciones utilizando el modelo cĺásico de Levins y agregando estocacidad como error de proceso, error de observación, usando tiempo continuo con procesos de Markov y sistemas de particulas interactivas para hacerlo espacialmente explícito. Read more