Understanding modern human society through the lens of evolution

Book review of Edmund Russell’s ‘Evolutionary History’

We often think about the ways in which evolution has shaped this world, from the amazing diversity of cichlid fishes in the African Great Lakes, to Australian marsupials that seem to replicate strategies that placental mammals have evolved elsewhere (e.g., Tasmanian tiger and the North American wolf). We even look at our own bodies or behaviors to find evolution’s imprint –why do I have a non-functional appendix attached to my intestine? However, we seldom look to important events in human history to examine the effects of evolution, yet, according to Edmund Russell, human history can be better understood through evolution –like my appendix.

Russell is advocating for a new field of inquiry within the study of human history –namely, evolutionary history. When I first read the book jacket, I must admit that I was skeptical. However, this book makes the compelling case that historians gain a much fuller understanding past events by including evolution. Russell’s main claim is that modern civilization is the product of an evolution revolution. Even Russell’s unremarkable dog “Riley, like all dogs, is a testament to the extraordinary power of human beings to shape the evolution of other species”. While citing dogs may seem like a trivial example, it was coevolution that shaped this relationship. Wolves that were less aggressive and less fearful, which tend to be more puppy-like, found benefits by associating with human groups. Human groups that tolerated the presence of these wolves were likely alerted to approaching threats. Even the fact that dogs bark is a product of this relationship. This evolution revolution can similarly explain the domestication of other animals and plants, and ultimately produces the necessary conditions for permanent large settlements.

An important and intriguing underlying theme of this book is that these evolutionary revolutions are not often the product of conscious effort. We are used to the narrative that highlights humans as selecting individuals and driving the evolution towards some goal. But this would require early peoples knowing what they wanted in the end, having a specific goal. In the dog example, do we really think that early humans thought ‘hey, I would like a poodle’? No, the reality is that canines and human changed with one another producing a mutually beneficial outcome. Even the domestication of many of the earliest crop species likely resulted from lazy and sloppy humans. Lazy because humans probably harvested the easiest, most accessible fruits and seeds –selecting for bigger, easily removed fruits that ripened at the same time. Sloppy because seeds were discarded around settlements. Then that laziness again means we looked to those nearby plants for harvesting. Thus evolution has continually informed the development of human civilization and produced the much of the cultural norms today.

While modern cultures may consciously drive evolution through selective breeding and genetic engineering, we are immersed in an evolving world. Diseases that are resistant to drugs, pest that are immune to pesticides, and commercial fish that are now smaller and reproduce earlier are examples of important evolutionary changes that affect human activities and economics. Russell provides evidence that evolution is in part responsible for the industrial revolution, due to some varieties of cotton evolving particular features.

Taken all together, Russell admirably succeeds in his goal of convincing the reader that evolution has influenced much of human civilization. Moreover, his intended audience of historians should be re-assessing previous explanations of important human events by asking the basic question: how has evolutionary change influenced major changes in human history.

Edmund Russell. 2011. Evolutionary History. Cambridge University Press.

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.

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.

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.

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.

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.

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.

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.

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.

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!

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...

Rumors of our death were greatly exaggerated

We're not dead yet!

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

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. 

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.

The contrasting effects of habitat area and heterogeneity on diversity

“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

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.

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

Little strokes fell great oaks: minor but chronic herbivory substantially reduces birch growth

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.

Scientific cul-de-sacs – fads in ecology

I’ve been thinking a lot about research topics I’m interested in pursuing once I finish (knock on wood) my PhD. During a conversation about possible post-PhD interests, a mentor warned me to be careful because they thought one topic might be a “fad”. I’m interpreting their definition of a “fad” as a subject that, while popular, is likely to be short-lived, misguided, and/or without a lasting impact. While we decided that the topic we were discussing is probably not a fad, it made me curious. How does one differentiates a faddish topic from a new but deserving idea or tool?

The scientific literature even includes a few papers about fads. And this is something they've been thinking about for a long time: in 1989 Warren G. Abrahamson, Thomas G. Whitham and Peter W. Price wrote a paper called “Fads in ecology” (in which they failed to identify any fads). Starbuck 2009 made excellent points about fads in the social sciences and behaviour that seem equally applicable to ecological research. Unfortunately, the first point these papers make is that identifying a fad is mostly about hindsight and even then, sometimes hindsight isn't enough. While Darwinism trumped Lamarckism in the 1800s, scientists now recognize that the idea of acquired characters is not (completely) wrong and ties into modern concepts like epigenetics. While most ecologists can think of some fads that have happened during their careers, picking a fad out in its early moments seems difficult. In the beginning, fads are simply attractive ideas, which slowly draw followers, until the number of people doing research on the topic reaches a critical mass. The way in which fads differ from a regular idea is that they rapidly establish, but this critical mass of research also rapidly makes the fad's limitations apparent. Once the promise of the fad is contradicted by evidence, people begin to jump ship.

It was also suggested to me that maybe fads shouldn't be judged too harshly, since they are just research bandwagon - topics which increase rapidly and disproportionately in attention, funding and publications. While some fads truly have negative effects on the science, most are simply overemphasized (hence their "faddish-ness") compared to other equally worthy topics, but still make contributions to science. 

Ultimately we’re susceptible to fads because in a publish-or-perish academic setting such ideas often promise a great degree of generality or explanatory power and emphasize novelty. “These … fads may have occurred in part because researchers value novelty and they have limited tolerance for imitation” (Starbuck 2009). It's true that novelty carries risk, but it also can be very rewarding. The advice I received on choosing a research project has been divergent and sometimes contradictory - ranging from "avoid trending topics and fads by understanding the classic, proven work" (always good advice) to "feel free to join a bandwagon, but only if you're on the leading edge of it" (a little harder to follow). And perhaps that's the most interesting thing - successful academics seem to have taken many paths to success, suggesting that there is room to explore the scientific landscape a little.

In praise of Peter Abrams, at Dynamic Ecology

A nice tribute to Peter Abrams, an eminent ecologist and evolutionary biologist who is retiring this year, from Jeremy Fox at Dynamic Ecology. By virtue of being in the same department I've been lucky enough to interact with Peter and the experience is a highlight of my time there. All I'll say is that Peter is both humble and brilliant, and his work is both wide-ranging and very thorough. Most books on ecology or evolutionary biology include a long list of references to his work, and he's an essential part of our field.

Also, I'm sure the comments will have lots of nice anecdotes, so head on over.

Justifying assumptions: tests of seed size/mass tradeoffs

Ben-Hur, E. et al. 2012. Functional trade-offs increase species diversity in experimental plant communities. Ecology Letters. DOI: 10.1111/j.1461-0248.2012.01850.x

When ecologists develop theory and models, we generally need to make assumptions. The nicest definition of an assumption is that they are the framework we use to capture our beliefs about a system. All future analyses will treat these assumptions as true, and so ultimately the validity of a model is tied to the validity of its assumptions. As Joseph Connell said: “Ecological theory does not establish or show anything about nature. It simply lays out the consequences of certain assumptions. Only a study of nature itself can tell us whether these assumptions and consequences are true.” Often times the most interesting advances in ecology come when we questions popular assumptions, such as that species are ecologically different, that interspecific differences are more important than intraspecific differences, or that ecological interactions occur much more rapidly then evolutionary changes. 

Assumptions in models and theory can often serve as a sort of shorthand for ideas that there is some general evidence for, but for which comprehensive data may be lacking. Community ecology is full of assumptions about functional tradeoffs that mediate coexistence between species. Various assumptions about plant species coexistence include that species experience tradeoffs between competition and colonization, growth versus reproduction, or seed size versus seed number. A simplistic explanation for such tradeoffs is that you can’t do everything well: a strong competitor can’t be a good colonizer too, which creates opportunities for strong colonizers but poor competitors, etc.

Tests of these functional tradeoffs are lacking, or lag behind the theory that relies on them. For example, the idea that there should be a tradeoff between seed size and seed number has long been proposed to explain why plants have highly variable seed sizes. Plants with small seeds should produce more offspring, and these seeds should be more successful at reaching empty sites. Large seeded species should be more competitive in the seedling stage or more tolerant of difficult conditions, and so have higher survival. Theoretical models that rely on such a tradeoff suggest that many species could co-exist and that the resulting community would exhibit a wide variety of seed sizes. 

But though many studies and theories depend on this assumed tradeoff, a comprehensive experimental test was lacking. Ben-Hur et al. have finally provided such an experiment, testing the basic prediction that a negative correlation between seed size and seed number should increase species richness. They also tested whether small-seeded species were more likely to remain in the community when this tradeoff existed, increasing the amount of among-species variation in seed size. To do so, the authors created 3 ‘community treatments’ of 15 plant species. The abundance of each species in the starting seed mix was manipulated to create either (1) positive correlation between seed mass and seed number; (2) negative correlation between seed mass and seed number or (3) random allocation of the 15 species regardless of seed size.

From Ben-Hur et al. 2012. Ecology Letters. a) Final number of species in the community, when the correlation between seed size and seed number is negative, random, or positive. b) Seed mass distribution in community under positive correlation between seed size and seed number (left), and negative correlation (right). 

Ben-Hur et al.’s results strongly suggest that a seed size/seed mass functional tradeoff can increase species richness (figure, a). Further, when there is such a tradeoff, the variation in seed size represented in a community increases, again in agreement with predictions (figure, b). The results are particularly convincing because the authors used experimental manipulation of the strength of the correlation (i.e. from negative to positive) to test its importance. The authors suggest that the tradeoff they simulated did not involve competitive differences (i.e. was not a competition-colonisation tradeoff), and more likely reflects a trade-off in establishment probability and colonisation (Dalling and Hubbell 2002; Muller-Landau 2010).

Of course, these results represent relatively short-term coexistence, and community richness may have changed had the experiment been allowed to continue for longer. But as a starting point, this suggests that theories that rely on functional tradeoffs in seed characteristics to explain coexistence are capturing a mechanism that has some experimental support. 

Things I've learned at ESA this year

1. It's more useful to talk to people than it is to be an audience member.
2. A successful talk is one that produces interactions with people.
3. The grass is not always greener- the talk you missed was probably not as great as everyone is saying anyways (actually it probably was, but it's too late now...)
4. Picking only specific talks and people to hear can be a good strategy for avoiding talk burnout. Symptoms of talk burnout include napping in conference centre hallways, feelings of annoyance when you hear the same concept re-explained for the 10th time (which is probably because you're in the 7th Community Patterns and Dynamics session), and a desire to yell 'but what is your hypothesis?!' during talks (this may just be me). The only cure for this is to go have a drink.
5. Conversely, sitting through entire sessions can lead to important discoveries.
6. There are more areas of research in ecology than you can list: by bringing these researchers together, ESA is helping to foster continued growth in our field. Integrating all these bodies of knowledge is important if ecology is to be a healthy, mature discipline.


08/10/6:50, edited for clarity. #7 could be 'it's better not to blog while tired'.

ESA day 3: a meeting of meetings

Wednesday was a crazy day, bouncing between talks and one-on-one meetings. This is what ESA is about: connecting with friends and colleagues, and seeing exciting new science. There were a bunch of fun talks that introduced new ideas and concepts, or made connections between different approaches. Some of these talks included Dylan Craven, who linked plant functional traits to performance in secondary successional forests in Panama. In Nicholas Gotelli’s talk, he tried to reconcile thousands of museum ant records with ecological surveys to estimate abundance, distribution and numbers of ant species in the north east USA. Sam Scheiner discussed a new approach to combine phylogeny and traits at the community level.

There were also some talks that seemed to really resonate with me, and the audiences attending them. Katherine Richgels gave a very interesting talk on trematode metacommunities, where the primary patches (snails) live in other patches (ponds). The primary patches have unique dynamics, including movement. The environment and host abundance seem to strongly determine trematode community patterns.

Bruce Menge astounded his audience with a new hypothesis: the ‘intermittent upwelling hypothesis’ which states that ecological process rates should be maximized at intermittent upwelling coastal zones. He ran experiments on coasts around the world and showed that recruitment, herbivory and predation rates were all maximized when upwelling was intermittent.

Cecil Albert showed how a model can predict the effects of global change and landscape alteration. She used a ‘sandwich’ modeling approach, where vegetation structure is sandwiched between climate change influences at large scale and landscape change at smaller scales. The resulting vegetation changes can be used to predict responses from specific indicator species or ecosystem function. She then showed how different scenarios of landuse change (random habitat removal, zoning and protecting corridors) can result in different responses in indicator species.

Finally, Caroline Tucker* gave a great talk on the effects of global warming on changes in flowering time in competitive communities.  Most people assume that plants will flower earlier in a warmer world, but these predictions ignore competitive effects. Using a set of linked growth and phenology models, she showed that indeed plants increase growth and flower earlier with warming in the absence of competition. However, once you allow the species to compete, the advance in flowering time is unequal. Early species, which are generally released from competition will flower earlier. So too will late species which tend to be good competitors. However, intermediate species do not advance their flowering due to competition.

*Yes this is our Caroline Tucker.

**Caroline has been on me to post my Wed. talk summary for two days.

ESA 2012: Day 4

 For some reason, Day 4 had many talks I wanted to see, just when the effects of late nights and over-caffeination were starting to peak. The reward to remaining awake through a day of talks was that I got to hear some excellent ecology.

At 8:20 (yes, 8:20) in the Biodiversity III session, Xubing Liu spoke about some of the work his research group is producing to expand our understanding of the Janzen-Connell effect. (For a good example of this work, see http://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2011.01715.x/abstract). The Janzen-Connell effect is a density-dependent mechanism in which proximity to individuals of the same species increases their chance of encountering species-specific predators or diseases, and therefore reduces their chance of survival. This is hypothesized to produce coexistence by maintaining lower abundances and higher diversity. In this talk, Liu explained how intraspecific variation could similarly be maintained via a Janzen-Connell effect. He showed experimentally that decreasing the degree of relationship between two individuals of the same species (increasing intraspecific diversity) increased their odds of surviving fungal infection. Such a mechanism could help explain how intraspecific variation is maintained, which is a hot topic these days.

A talk I found particularly interesting, perhaps because it was so different in content and style from my own work was that by Robert Beschta from Oregon State University. He convinced me, without statistics or plots, that the outcome of a natural experiment – the removal of apex predators from America’s park system – was highly detrimental to those ecosystems. Removal of wolves and cougars from National Parks such as Yellowstone and Olympia have produced many changes in community structure and function – the understory disappeared as deer and elk browsed all young greenery, river edges eroded without shrubbery, and forests aged. Yellowstone provided an additional validation to this conclusion; re-introducing wolves appears to be producing gradual reversion to more diverse and functional habitat.

Diane Srivastava further provided the type of perspective only gained from years of research. She also illustrated that the contribution of a body of work is often more than the sum of its parts. Diane has spent 15 years of studying a bromeliad system in which multiple invertebrates live in the water collected in the plants, forming a complex ecosystem with multiple trophic levels. The data collected over this time allowed her to perform a meta-analysis which shed more light on the dynamics of this system than any individual study allowed.

There were multiple talks from students of Peter Chesson, an eminent theoretician, and all shed light on mechanisms of coexistence. Although perhaps too complicated to explore in a short summary, they covered topics in keeping with other work from the lab, especially the role of temporal and spatial variability in driving fluctuations in recruitment and ultimately coexistence, and in understanding how mechanisms will scale with space. His students were well informed on the intricacies of Chessonian theory and the talks certainly created lots to think about.

Finally, two talks discussed the growing problem of reconciling trait- and phylogenetic-based community ecology. Rebecca Best presented the results of a amphipod competition experiment, in which she examined whether feeding traits or phylogenetic distances were a better explanation for the resulting diversity and abundances. She found, as is not uncommon, that traits were by far more useful in understanding the amphipod community. She didn’t stop there, however, and tested further how the phylogeny and trait values actually related – it turned out that traits and phylogeny were not correlated, and represented different mechanisms at play in the species' ecologies. Though she found that phylogenies could not predict the outcome of her community experiment, she concluded that this didn’t mean that phylogenies were not important, only that they were important at different scales or in different mechanisms then she had been focusing on.

Finally, a talk directly relevant to Best’s work came from the EEB & Flow’s Marc Cadotte. Since it was a well-received and interesting talk, I feel like giving his talk a plug here isn’t too biased. Cadotte presented a metric meant to incorporate both trait and phylogenetic information, and further to incorporate them in a meaningful way. Name FPDist (for functional phylogenetic distance), this metric incorporates an additional axis (functional diversity): this can be represented with a phylogenetic tree in which the x-axis represents trait distance and the y-axis phylogenetic distance. This allows you to visualize trait divergence and convergence in a way that traditional trees cannot. Further, the metric he presented is a function of both traits and phylogeny, combined in such a way that the relative importance of each can be captured and recognized. This allows us to more fully investigate both traits and phylogeny contribute to community diversity. No doubt an interesting paper will follow soon.

Off to survive one more night and one more morning.

ESA Portland day 2: march of the phylogeny

The day phylogenies took over. This is how I would describe the talks I attended on day two. There was a palpable collective enthusiasm for what phylogenies can bring to understanding ecological patterns. It seemed like every session I went to there were several talks that test for phylogenetic patterns and it will be interesting to see where this all goes in the future. For me, this phylogenetic onslaught was heralded by the very first talk I went to by Jeannine Cavender-Bares. She spoke about how phylogenetic relatedness and species traits can provide important insights into community patterns and ecosystem function. She ask some of the most pertinent questions such as: how do evolutionary processes affect ecological processes; and how deep in the phylogeny is the evolutionary signal in community assembly. This last question is interesting because it can potentially tell us about past environments when certain lineages evolved. Her talk was divided into three parts. In the first part, she discussed how certain plant traits, like specific leaf area (SLA), were correlated with fire frequency. At extremely low and high fire frequencies, there is a strong trait pattern associated with communtiy membership, and with a strong phylogenetic pattern as well. But this wasn't the case with intermediate fire frequencies. In the second part, she discussed plant community patterns across an urban to natural gradient. There were important trait differences, with species having smaller seeds and higher specific leaf area in urban areas. There were more species in urban areas, but they represented less phylogenetic diversity than in natural areas -meaning that there is an environmental filter selecting for similar species. In the third part, she investigated oak adaptive radiations in North America and the resulting biogeographical patterns. There we differences in diversity across latitude, with high diversity regions also have more close relatives.

The were a number of other very interesting talks, and I spent the day fluttering from room to room, like a confused butterfly in search of sweet rewards. And rewarded I was. There were handful of very memorable talks. By both young graduate students and established researchers. Christina Lamanna gave a nice talk about phylogenetic and functional diversity (PD and FD, respectively) across an elevation gradient, which in part she used to highlight a new measure of species functional overlap. Richness and FD peak at intermediate elevation. She also examined the turnover in FD and PD and that both of these show decreasing turnover at higher elevations. At high elevations, PD was found to be overdispersed as were some of the traits, but other traits appeared underdispersed, indicating the combination of traits under very different selective regimes.

In a session on ecosystem function Jane Cowles told us how diversity and warming interact to shape patterns of ecosystem function. The experiment was great, and they overlaid warming arrays on some of the plots at the classic biodiversity experiment at Cedar Creek, Minnesota. The arrays warmed 1.5 and 3 degrees on 1, 4 and 16 spp plots and they measured aboveground and belowground biomass. More aboveground biomass was observed with warming, but not for belowground, except for deeper roots. Dominant species increased the most in aboveground biomass, seeming to respond to large pools of nitrogen available in early spring. 

One of the two best talks I saw today was given by Amelia Wolf. She constructed a biodiversity-ecosystem function experiment based on realistic scenarios of species loss. Whereas most experiments randomly assemble species together, realistic species loss selects species with certain traits, and once they are lost, those species are not part of the system at lower diversity. She used 20 years of observational data to select those species most susceptible to extinction and then created a series of plots where diversity was based on removing susceptible species. These plots were nested in that when a species was excluded from say the highest to next highest treatment, it could not be included in a lower diversity treatment. She compared this to random diversity treatments and found that the realistic species loss had a stronger effect on ecosystem function. But she suggested that this could be due to the nested structure and not the realistic scenario. So, to cover all her bases, she created 32 different nested loss regimes that were not the realistic one, and found that they were no different than random. Thus species identity and susceptibility really matter for ecosystem function decline with species extinction, as most susceptible species are often from the same functional group.

The other superb talk was from Jay Stachowicz on the influence of eelgrass genotypic richness, relatedness and trait diversity on productivity. Genotypes interact though a number of mechanisms including competition, cooperation, interbreeding, and so there are complex possibilities for the influence of genotype on productivity. From experimental combinations, he found that, counter to his expectations, plots with closer relatives had higher productivity. Further these plots with close relatives also had greater trait diversity, highlighting the complex nature of species interactions and differentiation.

Andrew Siefert gave a talk on disentangling multiple drivers on species turnover in space. Betadiversity is driven by both niche based decay of environmental similarity and stochastic due to dispersal limitation. Both generate similar patterns. But if one uses functional traits, then you can see higher or lower functional turnover than expected from chance, which indicates niche based turnover. He reported the results from 1500 forest plots across eastern USA,  with climate data and data on four functional traits. He found high turnover in soils and species, lower for climate and functional diversity. Both taxonomic and functional betadiversity best explained by climate. Close sites have high taxonomic turnover, but low functional turnover, thus climate filtering.

Finally, Elizabeth Boyle exmined arthropod phylogenetic community patterns in near arctic aquatic systems (ponds, streams, rivers, etc.). These habitats harbor an amazing diversity of insects and Elizabeth collected data from dozens of habitats over a large area, for hundreds of species and constructed a molecular phylogeny based on her own genetic work. An amazing effort for a masters project! She resampled the habitats through the summer and found that many of the habitats started off as phylogenetically clustered but became overdispersed through time. But not all habitats showed the same response, and she found that some environmental variables seemed to be strongly correlated with relatedness patterns. She also questioned whether the emergence of adults caused some of these patterns as the timing of emergence is phylogenetically nonrandom, which to me is a new explanation of potential phylogenetic patterns.

- Posted using BlogPress from my iPad

ESA Portland: Day 1

Today proved a typical first day of ESA, with delayed flights, hotel difficulties and luggage to carry around. Then you head to the convention centre and are reminded all over again just how big ESA actually is. The benefit of the crowds is that the sessions take on a specificity and quantity that you can't find anywhere else. The bad news is that you will have to make choices.

Today's choices weren’t too difficult - I moved between the Community Assembly and Neutral I and Community Pattern and Dynamics I sessions to start. Some common themes emerged, especially that people are quite interested in the relationship between diversity and phylogeny, and then phylogeny and traits, and also in patterns of beta and alpha-diversity along environmental gradients. 

A few talks stood out: Emma Moran spoke about identifying the processes of deterministic assembly and stochasticity that drive community diversity. In agreement with previous work from Jonathan Chase, her co-author, she spoke about how using null models allows scientists to differentiate between these two processes by observing temporal and spatial patterns of species diversity and comparing them to those patterns expected by chance alone. By looking at both temporal and spatial patterns of diversity, it is possible to differentiate between stochastic arrival of species at a site, followed by deterministic interactions (spatial stochasticity + temporal determinism) and purely stochastic assembly (both temporal and spatial patterns of diversity random), for example. Using both simulations and empirical data, she demonstrated the patterns of diversity that might be expected and tested for under these scenarios. When she used a null model that controlled for random expectations, her conclusions about which processes were important were dramatically different from those arrived at without a null model.

In the Population Dynamics session, Emanuel Fronhofer asked 'Why are metapopulations so rare' and came to the possibly controversial conclusion that they are rare because there aren't many conditions that should result in metapopulations. Metapopulations are a common concept in ecology, based on the idea that population dynamics in different patches are linked via dispersal between those patches. However, it's unclear how common metapopulations really are in nature. Fronhofer used individual based models (IBMs) to explore the range of dispersal values, environmental stochasticity, or reproductive system type, for example, that would result in a metapopulation. In particular, he looked at the most strict definition of a metapopulation: occupancy of patches less than 1 and more than 0, turnover through time, and FST values such that populations are genetically differentiated. What he found agreed with the nay-sayers: only quite narrow values of parameters like dispersal resulted in true metapopulations. Does this mean metapopulation ecology is a highly specialized field? Difficult to say, although it maybe that a particularly stringent definition of a metapopulation (with occupancy between 0 and 1, for example) is not necessary to describe the movement of individuals and alleles between patches in a way that is consistent with metapopulation dynamics. 

Finally, Geoff Legault discussed spatial synchrony among populations, in which population cycles in different spatial patches become synchronized. In particular, using a protist predator-prey microcosm, he showed that in agreement with some theory, there is a dispersal threshold after which synchrony is achieved between the two populations. This leads to interesting questions about what determines the level of dispersal required to produce synchrony, and how factors such as population growth rates alter this threshold, something which a microcosm is particularly useful to address. 

EEB & Flow Portland bound

Just a heads up that Marc Cadotte and I will be live blogging the Ecological Society of America's Annual Meeting in Portland, from Aug. 6-10th. As always, this is a great chance for ecologists to hear about great science and run into old and new friends. If you see Marc Cadotte there, be sure to harass him to post on time, as he claims to be 'busy' ;)

Why non-theoreticians don’t cite your paper

T.W. Fawcett and A. D. Higginson. 2012. Heavy use of equations impedes communication among biologists. PNAS.

The more equations a paper has, the less it will be cited by other biologists. This should come as a surprise to few people, but if it does, Fig.1 from Fawcett and Higginson (2012) makes this pretty clear. Papers with many equations per page are cited less often by non-theoretical papers (A). In fact, citations by non-theoretical papers decrease by 35% for each additional equation per page. This is not true of theoretical papers, which happily cite other equation-filled theoretical works (B). It’s an interesting conundrum: theory unifies empirical observations and generates predictions, but theory uses equations. And papers with equations have less impact.

The authors make suggestions for both sides of this divide. All biologists should have adequate mathematical training so that equations are not necessarily considered daunting or confusing. Theoreticians should strive to communicate their works in accessible ways (something Steve Ellner covered nicely in the aptly named “How to write a theoretical ecology paper that people will cite”). The authors also suggest increased placement of equations in appendices, where they do not decrease citation rates. (However, if equations don’t decrease citation rates when in the appendix, you wonder if this is because equations are easier to ignore there). The surprising thing about this  bias is that I don’t think it exists as much in the other direction. Theoretical papers generally do cite empirical works. Reviewers frequently require that model assumptions be justified based on empirical knowledge. A balance between theory and empiricism seems important for ecology, and while this paper doesn't tell us anything surprising, it makes it quite clear that there is a problem.

From Fawcett and Higginson 2012.

Insight and advocacy: transitioning from scientist to advocate (Guest Post)

In Malcolm Gladwell’s “The Tipping Point” he describes how information is disseminated. It takes three types of people: a collector, a connector and a persuader. As a research scientist, I am familiar with being a collector. I have spent years reading papers, testing hypotheses and validating assumptions to develop a personal understanding of fisheries and ecology. Until recently, I was content to let my perspectives circulate among a small group of colleagues. Until recently, I did not see a need to address the connector or persuader in my academic life. But I do now. I am not an advocate. I have on occasion written a letter to my MP, signed a petition or joined a protest but always as a follower of those who, I felt, were much better suited for it. And this is because on most political issues I am as informed as the news/internet media will allow me to be. So when somebody with some good insight steps forward, I’m more likely to egg them on then run with their thunder.

But recently I have found myself to be one with insight. It was a startling moment. Natural Resource Minister Joe Oliver was on the news plugging the dismantling of Canada’s environmental legislation. He’d said that our environmental safeguards held up badly needed economic development and as an example he used Enbridge’s Gateway Pipeline. I had worked on the environmental permitting for that pipeline, and I didn’t agree with him. Working as an environmental consultant in Alberta was a wonderful life spent on deserted oil roads assessing fish habitat and negotiating permits for industrial development. Over that time I observed first hand that Canada’s environmental laws did not hold up pipelines, mines or bridge crossings any longer than the lengthy processes of engineering, surveying, contracting or First Nation consultation. Environmental permits typically cost a small fraction of the total development, were often acquired concurrently with the general planning process, and were unquestionably necessary to protect the health of the natural resources that belong to all Albertans and Canadians. Beyond my first hand experiences, I found no independent studies that could back up Minister Oliver’s statement. In fact, in a series of papers examining Canadian and American environmental legislation, their overall effect on the economy was determined to be either “overstated” or even “a net benefit”.

Politicians embellish, and perhaps I would have left it there, but over the next few weeks news emerged that the federal government were scrapping the National Round Table on the Environment and the Economy, the Experimental Lakes Area, the Marine Pollution Program, the Kluane Arctic Research Station, Ozone Monitoring Stations, the Species at Risk scientists at Fisheries and Oceans Canada, fish habitat protection under the Fisheries Act. This after years of muzzling government scientists, laying off climate change researchers, and cutting funding to non-business partnered science in Canada. And last, and cruellest, most of these recent changes were being done wrapped up in a budget, Bill C-38, thus circumventing a proper discussion in Parliament. I was shaken by this policy direction.

It is difficult not to be emotionally invested when ideals and institutes you believe in get torn down. I found that many Canadians including environmentalists, economists, politicians and advocates were appearing on the news, writing op-eds and tweeting their concerns. Their seat in this public debate was one earned from decades of being public figures, which connected them to a wide network and taught them how to engage those around them. I realized my opportunity was to share my insights with them, and provide more substance to their thunder. I researched further the economic role of environmental legislation in Canada and canvased old colleagues from consulting firms on permit wait times. Next, I began to share. I put out these insights to my own social and professional network. I was amazed by how quickly people responded. With one LinkedIn post and an email to 75 contacts I received responses from most of my immediate contacts, but also from people across the country that I had never met. I heard from collectors who shared their insights with me, connectors who forwarded mine on, and persuaders who were still appearing in the news. I was amazed and heartened by how quickly an insight could spread.

Insight is a powerful and rare commodity, because it can comment on current issues yet is not necessarily advocacy. For example, eminent researcher David Schindler’s paper on oil sands contamination was not advocacy; it was insight into contaminant levels in the Athabasca River. Yet the paper sent shockwaves through a political system that had been repeating for over a decade that the oil sands had a clean record and was picked up by advocates who further publicized it. It can gain such traction because there is a vacuum of objective facts and concrete statements in today’s political theater. Over the last few decades our political leaders have increasingly changed their dialogue to reflect emotional, persuasive and ideology driven statements. For example, in Canada Ministers Kent, Ashfield and Oliver discuss “protecting” our “valuable” species, and “modernizing” our legislation. Other ministers present economic or foreign affairs in similar vague terms. This type of dialogue puts a new onus on economists and scientists to share their perspectives beyond the academic walls. It seems like an insurmountable hurdle as many of us are not connectors or persuaders, but the traction for a pure nugget of insight may surprise you. So I encourage you all to keep collecting but to also start sharing beyond our academic circles, where your contribution may be more meaningful that you realize.

   

By Derrick de Kerckhove