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'.