Tuesday, January 22, 2013

Bob Paine's footprint

A great post by Ed Yong on Bob Paine's influence on ecology -both conceptually and numerically, with a large number of academic children and grandchildren.

Thursday, January 17, 2013

Who are you writing your paper with?


Choosing who you work with plays an important role in who you become as a scientist. Every grad student knows this is true about choosing a supervisor, and we’ve all heard the good, the bad, and the ugly when it comes to student-advisor stories. But writing a paper with collaborators is like dealing with the supervisor-supervisee relationship writ small. Working with coauthors can be the most rewarding or the most frustrating process, or both. Ultimately, the combination of personalities involved merge in such a way as to produce a document that is usually more (but sometimes less) than the sum of its parts. The writing process and collaborative interactions are fascinating to consider all on their own.

Field Guide to Coauthors
The Little General
The Little General is willing to battle till the death for the paper to follow his particular pet idea. Regardless of the aim or outcome of an experiment, a Little General will want to connect it to his particular take on things. Two Little Generals on a paper can spell disaster.
Little General
The Silent Partner
These are the middle authors, the suppliers of data and computer code, people who were involved in the foundations of the work, but not actively a part of the writing process.
Silent Partner
The Nay-sayer
These are the coauthors who disagree, seemingly on principle, with any attempt to generalize the paper. Given free rein, such authors can prevent a work from having any generality beyond the particular system and question in the paper. These authors do help a paper become reviewer-proof, since every statement left in the paper is well-supported.
Nay-sayer

The Grammar Nazi
The Grammar Nazi returns your draft of the paper covered in edits, but he has mostly corrected for grammar and style rather than content. This is not the worst coauthor type, although it can be annoying, especially if these edits are mostly about personal taste.
Grammar Nazi
The Snail
This is the coauthor that you just don’t hear from. You can send them reminder emails, give them a phone call, pray to the gods, but they will take their own sweet time getting anything back to you. (And yes, they are probably really busy).

 The Cheerleader
The Cheerleader can encourage you through a difficult writing process or fuel an easy one. These are the coauthors who believe in the value of the work and will help motivate you through multiple edits, rejections, or revisions, as needed.
Cheerleader
The Good Samaritan
The Good Samaritan is a special type of person. They aren’t authors of your manuscript, but they read it for you out of pure generosity  They might provide better feedback and more useful advice than any of your actual coauthors. They always end up in the acknowledgements, but you often feel like you owe them more.
Good Samaritan
The Sage
The Sage is probably your supervisor or some scientific silverback. They read your manuscript and immediately know what’s wrong with it, what it needs, and distill this to you in a short comment that will change everything. The Sage will improve your work infinitely, and make you realize how far you still have to go.
Sage

There are probably lots of other types that I haven't thought of, so feel free to describe them in the comments. And, it goes without saying that if you coauthored a paper with me, you were an excellent coauthor with whom I have no complaints. Especially Marc Cadotte, who is often both Cheerleader and Sage :)

Thanks to Lanna Jin for the amazing illustrations!














Wednesday, January 9, 2013

Replicable methods

This has been making the internet rounds: If you were being truly honest in your methods, what would you say?
Overly honest methods in science

Mine would probably something like: "We had a sample size of 260 individuals. It may sound like we planned to have 260 plants, but actually 40 seedlings died, luckily leaving us with a nice round number."

A friend joked that hers would be: "All this work was done with a totally different experiment in mind, but this is all I could salvage."

I'm sure everyone has a few of these...

Monday, January 7, 2013

Reinventing the ecological wheel – why do we do it?


Are those who do not learn from (ecological) history are doomed to repeat it?

A pervasive view within ecology is that discovery tends to be inefficient and that ideas reappear as vogue pursuits again and again. For example, the ecological implications of niche partitioning re-emerges as an important topic in ecology every decade or so. Niche partitioning was well represented in ecological literature of the 1960s and 1970s, which focused theoretical and experimental attention on how communities were structured through resource partitioning. It would be fair to say that the evolutionary causes and the ecological consequences of communities structured by niche differences were one of the most important concepts in community ecology during that time. Fast-forward 30 years, and biodiversity and ecosystem functioning (BEF) research slowly  has come to the conclusion that niche partitioning to explains the apparent relationship between species diversity and ecosystem functioning. Some of the findings in the BEF literature could be criticized as simply being rediscoveries of classical theory and experimental evidence already in existence. How does one interpret these cycles? Are they a failure of ecological progress or evidence of the constancy of ecological mechanisms?

Ecology is such a young science that this process of rediscovery seems particularly surprising. Most of the fundamental theory in ecology arose during this early period: from the 1920s (Lotka, Volterra), 1930s (Gause) to 1960s (Wilson, MacArthur, May, Lawton, etc). There are several reasons why this was the foundational period for ecological theory – the science was undeveloped, so there was a void that needed filling. Ecologists in those years were often been trained in other disciplines that emphasized mathematical and scientific rigor, so the theory that developed was in the best scientific tradition, with analytically resolved equations meant to describe the behaviour of populations and communities. Most of the paradigms we operate in today owe much to this period, including an inordinate focus on predator-prey, competitive interactions, and plant communities, and the use of Lotka-Volterra and consumer-resource models. So when ecologists reinvent the wheel, is this foundation of knowledge to blame, is it flawed or incomplete? Or does ecology fail in education and practice in maintaining contact with the knowledge base that already exists? (Spoiler alert – the answer is going to be both).

Modern ecologists face the unenviable task of prioritizing and decoding an exponentially growing body of literature. Ecologists in the 1960s could realistically read all the literature pertaining to community ecology during their PhD studies –something that is impossible today with an exponentially growing literature. Classic papers can be harder to access than new ones: old papers are less likely to be accessible online, and when they are, the quality of the documents is often poor. The style and accessibility of some of these papers is also difficult for readers used to the succinct and direct writing more common today. The cumulative effect of all of this is that we read very little older literature and instead find papers that are cited by our peers.

True, some fields may have grown or started apart from a base of theory that would have been useful during their development. But it would also be unfair to ignore the fact that ecology’s foundation is full of cracks. Certain interactions are much better explored than others. Models of two species interactions fill in for complex ecosystems. Lotka-Volterra and related consumer-resource models make a number of potentially unrealistic assumptions, and parameter space has often been incompletely explored. We seem to lack a hierarchical framework or synthesis of what we do know (although a few people have tried (Vellend 2010)). When models are explored in-depth, as Peter Abrams has done in many papers, we discover the complexity and possible futility of ecological research: anything can result from complex dynamics. The cynic then, would argue that models can predict anything (or worse, nothing). This is unfair, since most modelling papers test hypotheses by manipulating a single parameter associated with a likely mechanism, but it hints at the limits that current theory exhibits.

So the bleakest view of would be this: the body of knowledge that makes up ecology is inadequate and poorly structured. There is little in the way of synthesis, and though we know many, many mechanisms that can occur, we have less understanding of those that are likely to occur. Developing areas of ecology often have a tenuous connection to the existing body of knowledge, and if they eventually connect with and contribute to the central body, it is through an inefficient, repetitive process. For example a number of papers have remarked that invasion biology has dissociated itself from mainstream ecology, reinventing basic mechanisms. The most optimistic view, is that when we discover similar mechanisms multiple times, we gain increasing evidence for their importance. Further, each cycle of rediscovery reinforces that there are a finite number of mechanisms that structure ecological communities (maybe just a handful). When we use the same sets of mechanisms to explain new patterns or processes, in some ways it is a relief to realize that new findings fit logically with existing knowledge. For example niche partitioning has long been used to explain co-occurrence, but with a new focus on ecosystem functioning, it has leant itself as an efficacious explanation. But the question remains, how much of what we do is inefficient and repetitive, and how much is advancing our basic understanding of the world?

By Caroline Tucker & Marc Cadotte


Wednesday, December 12, 2012

holiday caRd from the EEB & Flow 2012


To celebrate the start of the holiday season for many of us, the end of exams and marking for others, and for fellow Canadians, snow, enjoy this caRd from the EEB & flow! We will see you around the New Year with our traditional year-end post about the current state of ecology.

You should be able to download the R code directly, here
Or, copy and paste the code here into your R console. 

Monday, November 19, 2012

Coexistence theory: community assembly's next great hope?


Rethinking Community Assembly through the Lens of Coexistence Theory
J. HilleRisLambers, P.B. Adler, W.S. Harpole, J.M. Levine, and M.M. Mayfield

The big (literally, at 24 pages) paper to read this year is a review by a number of well-known community ecologists that aims to package years of often contradictory and confusing results from community assembly research (Weiher & Keddy 2001) into a manageable package using coexistence theory. Coexistence theory arose particularly out of Peter Chesson’s work (particularly his own annual review paper (Chesson 2000)), and rests in the idea that coexistence between species is the result of a balance of stabilizing forces (i.e. niche differences) and equalizing forces (i.e. fitness similarity) between those species. Coexistence is stable when stabilizing forces dominate, so a species competes more strongly with itself than with other, more dissimilar, species. The most successful adaptations of this framework to “real world” experiments have come from Jonathan Levine’s lab (in collaboration with many of the coauthors on this work). Indeed, there are probably few people more qualified to attempt to re-explain the often complicated findings in community assembly research using coexistence theory.

The classic heuristic model for community assembly involves a regional species pool that is consecutively filtered through environmental and then biotic filters, selecting only for those species adapted to the local environment. While logically appealing, this model may have constrained thinking about assembly: after all, our definition of a niche recognizes that species are impacted by and impact their environments (Chase & Leibold 2003), and unlike a expectations for a biotic "filter", arrival order can alter the outcome of biotic interactions. But does coexistence theory do a better job of capturing these dynamics? 

The important message to take from coexistence theory, the authors suggest, is that stabilizing niche differences facilitate coexistence, whereas relative fitness differences drive competitive exclusion. And although this yields predictions about how similar or different coexisting species should be, coexistence theory diverges in a number of ways from trait-based or phylogenetic approaches to community assembly. “First, competitive exclusion can either preferentially eliminate taxa that are too functionally similar when trait differences function as stabilizing niche differences or preferentially eliminate all taxa that do not possess the near optimal trait when such trait differences translate into fitness differences. Second, both stabilizing niche differences and relative fitness differences are influenced by abiotic and biotic factors. For both reasons, patterns of trait dissimilarity or similarity cannot easily be used to infer the relative importance of environmental versus biotic (competitive) filters, which is an important goal of community assembly studies.”

There are a number of ways in which pre-existing research might provide evidence for the predictions of coexistence theory. You can look at studies which modify fitness differences between species (for example, through nutrient addition experiments), those which modify niche differences (for example, manipulating colonization differences between species), and those which manipulate the types of species competing to establish. You can take advantage of trait or phylogenetic information about communities (and traits are valuable because they provide a mechanistic linkage), although Mayfield and Levine (2010) have already shown there are clear limitations to such approaches. A particularly useful approach may be to look at demographic rates, particularly looking for frequency-dependent growth rates, an indicator of niche differences between species – when niche differences are large, species should have higher growth rates at low density (lower intraspecific competition) than at high density. And indeed, there is some evidence for the effect of fitness differences or niche differences on community composition.

Ultimately reanalyzing old research has its limitations: is it possible that nutrient additions leading to changes in community structure are evidence of fitness differences? Yes. Are there other possible explanations? Yes. Convincing evidence will take new studies, and the authors make some excellent  suggestions to this end: that we need to combine demographic and trait-based approaches so that assembly studies results suggest at mechanisms, not patterns. The focus would be on correlating niche and fitness differences with traits, rather than correlating traits with species’ presence or absence in the community. 

Given the muddle that is community assembly research, a review that offers a new approach is always timely, and this one is very comprehensive and sure to be well cited. Strangely, for me this paper perhaps lacked the moment of insight I felt when I read about coexistence theory being applied to invasive species (MacDougall et al 2009) or phylogenetic analyses of communities (Mayfield and Levine, 2010). There are a few reasons why that might be: one is that there are difficulties that are not well explored, particularly that traits may not realistically be able to be categorized in an either-niche-or-fitness fashion, and that abiotic and biotic factors can interact with traits. The predictions this framework makes for community assembly are less clear: even the tidiness of coexistence theory can't escape the complications of community assembly. But perhaps that is a pessimistic take on community assembly. Regardless, the paper has a lot to offer researchers and will hopefully encourage new work exploring the role of niche and fitness differences in community assembly.

Tuesday, October 30, 2012

The contrasting effects of habitat area and heterogeneity on diversity


ResearchBlogging.org“How extremely stupid not to have thought of that!” (Thomas H. Huxley, commenting on the obviousness of Darwin’s theory of natural selection)

Sometimes I read a paper and Huxley’s famous quote seems exceedingly appropriate. Why I say this is that a new idea or concept is presented which seems both so simple and at the same time a potentially powerful explanation of patterns in nature. This was my reaction to a recent paper from Omri Allouche and colleagues published in the Proceedings ofthe National Academy of Science. The paper presents a simple conceptual model, in the same vein as Connell’s classic intermediate disturbance hypothesis, which accounts for large-scale diversity patterns based on aspects of species niche requirements as well as classic stochastic theory. Merging these two aspects is a critical step forward, as in ecology, there has been a tension in explaining diversity patterns between niche-based processes requiring that species exhibit differences in their needs, and stochastic (or neutral) explanations that ignore these differences, but seem to do well at large scales.

The classic stochastic model in ecology, the theory of island biogeography, simply predicted that the number of species increases with the size of an island or habitat, and ultimately is the balance between species colonizing and going extinct. Allouche et al. also assume this stochastic colonization and extinction, such that in a uniform environment, the number of species increases with area. However, they then add the fact that species do not do equally well in different habitats, that is they have specific environmental niches associated with a particular environment. Thus as you increase the amount of heterogeneity in a landscape, you increase the total number of species, because you’ve captured more niches. However, there is a trade-off here. Namely, as you increase the heterogeneity in a landscape, the amount of area for the dominant habitat type decreases, thus reducing the number of species. So if you increase the heterogeneity too much, the individual habitat types will be too small to support large numbers of species and the numbers of species will be less than regions with less heterogeneity –paradoxically.

Their heuristic prediction is that diversity is maximized at intermediate levels of heterogeneity, as long as species have intermediate niche breadths (i.e., they could perhaps use a couple of different habitats). However, if their niche breadth is too narrow (i.e., they can only exist in a single habitat type), then diversity may only decline with increasing heterogeneity. Conversely, if species have very broad niche breadths (i.e., can survive in many different habitats) then the tradeoff vanishes and heterogeneity has little effect on diversity.

They tested this exceedingly simple prediction using European bird data and found that species richness was maximized at intermediate heterogeneity (measured by the variation in elevation). Further, when they classified species into different niche width classes, they found that the relationship between richness and heterogeneity changed was predicted (i.e., strongest for intermediate breadth).

This is a great paper and should have a large impact. It will be exciting to see what other systems fit this pattern and how specific studies later the interpretation or mechanisms in this model.

Allouche, O., Kalyuzhny, M., Moreno-Rueda, G., Pizarro, M., & Kadmon, R. (2012). Area-heterogeneity tradeoff and the diversity of ecological communities Proceedings of the National Academy of Sciences, 109 (43), 17495-17500 DOI: 10.1073/pnas.1208652109

Friday, October 26, 2012

Open access: where to from here?

Undoubtedly, readers of this blog have: a) published in an open access (OA) journal; b) debated the merits of an OA journal; and/or c) received spam from shady, predatory OA journals (I know when my grad students have 'made it' when they tell me they got an e-mail invite to submit to the Open Journal of the Latest Research Keyword). Now that we have had OA journals operating for several years, it is a good time to ask about their meaningfulness for research and researchers. Bob O'Hara has recently published an excellent reflection on OA in the Guardian newspaper, and it deserves to be read and discussed. Find it here.

Thursday, October 18, 2012

Amusing titles for papers - the crowning touch?

I'll try for a more content-full blog post in the near future, but I couldn't help noticing that there are a number of papers in my reader this month with amusing titles. Titles are always one of the most difficult parts of writing a paper - how do you capture the important aspects of your paper in a minimum of words, while avoiding the usual traps of colons, question marks, and cliches (not to mention the urge to throw in buzzwords)? For that reason, I always appreciate authors willing to be a little intriguing, whether with metaphors, puns, or clever references.

(As an anecdote, I was in a reading group a week ago where we were discussing a paper about turtle movements. People couldn't stop making Ninja Turtle jokes throughout the meeting (academics are cool like that), and I'll admit I had a moment of jealousy over people who work with charismatic creatures which lend themselves to amusing references in papers and talks. There aren't too many jokes about computer models.)

Some amusing titles in the last month or two:

Taxonomy versus phylogeny: evolutionary history of marsh rabbits without hopping to conclusions

Declining woodland birds in North America: should we blame Bambi?

Dragonflies: climate canaries for river management


Bayesian transmogrification of clade divergence dates: a critique 













A slightly older but still excellent title:

The well-temperatured biologist

Although this study suggests that a clever titles will get cited less, I am at least more likely to read the abstract...

There are lots of classic titles I've overlooked, feel free to add them to the comments.