Wednesday, December 12, 2012

holiday caRd from the EEB & Flow 2012

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

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

Monday, November 19, 2012

Coexistence theory: community assembly's next great hope?

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

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

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

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

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

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

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

Tuesday, October 30, 2012

The contrasting effects of habitat area and heterogeneity on diversity“How extremely stupid not to have thought of that!” (Thomas H. Huxley, commenting on the obviousness of Darwin’s theory of natural selection)

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

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

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

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

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

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

Friday, October 26, 2012

Open access: where to from here?

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

Thursday, October 18, 2012

Amusing titles for papers - the crowning touch?

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

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

Some amusing titles in the last month or two:

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

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

Dragonflies: climate canaries for river management

Bayesian transmogrification of clade divergence dates: a critique 

A slightly older but still excellent title:

The well-temperatured biologist

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

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

Friday, September 28, 2012

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.

Friday, September 14, 2012

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.

Wednesday, August 22, 2012

Justifying assumptions: tests of seed size/mass tradeoffs

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. 

Friday, August 10, 2012

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.

Thursday, August 9, 2012

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 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.

Wednesday, August 8, 2012

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

Tuesday, August 7, 2012

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. 

Wednesday, August 1, 2012

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' ;)

Tuesday, June 26, 2012

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.

Thursday, June 14, 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.

Thursday, May 31, 2012

Putting ecological niche models to good use

I won’t be the first or the last person to state that I find ecological niche models (ENMs) a bit problematic. In their simplest form, ENMs are statistical models correlating species presences or presences and absences with climatic factors. These models can then be used to predict the location of suitable habitat either elsewhere in space or later in time. They can be used to examine how species’ ranges may shift with climate change, to predict where invasive species’ ranges will expand, or to suggest appropriate locations for new reserves. Over the last while, they’ve faced a fair amount of criticism. For example, most fail to incorporate biotic interactions and so they capture a species’ realized niche: this means that it might not be accurate to extrapolate the model to areas where the biotic environment is different. There are also questions of what is the appropriate spatial scale for environmental data; the problem that many populations’ dynamics (especially invasive species) are not at equilibrium with the environment, so their observed relationship with climatic factors may not represent their niche; statistical and data-quality issues; and the difficulties of validating predictions that may be made for changes in habitat 50+ years in the future. Like many new techniques, ENMs became popular quickly, before they developed an appropriate foundation, and so they were subject to misuse and inappropriate conclusions. But this is a typical pattern – the development of ecophylogenetic tools has followed a similar path.

While this period of early growth has tarnished some people’s view of ENMs, it would be a shame to disregard them altogether when there are people still using them in interesting and inventive ways. A great example is Banta et al. (2012), which combines a model organism, intraspecific phenotypic variation, and spatial structure of genetic variation with ecological niche modelling. Banta et al. focus on the problematic assumption of such models that intraspecific variation in climatic tolerances is minimal or unimportant. One approach to exploring this issue more is to develop intraspecific ENMs using genotypes, rather than species, as the unit of analysis.

Banta et al. take advantage of the fact that the model organism Arabidopsis thaliana is genetically well understood, allowing them to identify ecologically different genotypes, and is widely distributed across highly varied habitats. The authors looked at genotypes of Arabidopsis that varied in flowering time and asked whether these ecologically differentiated genotypes had different niche breadths and potential range sizes. They also looked at the classic macroecological question of whether niche breadth and range size are correlated (in this case, intraspecifically). To answer these questions, they identified 15 single locus genotypes for flowering time (henceforth “genotypes”), and developed ENMs for each, looking at the climatic conditions associated with each genotype. Using the output from these models, Banta et al. calculated the niche breadth (measured based on how much suitability varies among habitat types) and the size of potential habitat (the sum of units of suitable habitat) for each genotype.

The authors could then look at how intraspecific variation in flowering time related to differences in niche breadth and range size among the different Arabidopsis genotypes. They found that genotypes tended to differ from each other in both niche breadth and range size. This is important because ENMs assume that small amounts of genetic variation among populations shouldn’t affect the accuracy of their results. In fact, even differences in a single gene between genotypes could be associated with differences in niche breadth and potential range. In general, late flowering genotypes tended to have smaller potential ranges. The authors suggest a few explanations for this, including that late flowering genotypes may be adapted to harsher conditions, where flowering late is beneficial, but unable to compete in less stressful habitat. Regardless of the particular explanation, it shows that single locus differences can drive phenotypic differences among individuals, which in turn have notable macroecological effects.
From Banta et al. 2012. Relationship between potential range size and flowering time/niche breadth

Similar to the pattern found in a number of interspecific studies, the authors found a strong correlation between potential range size and niche breadth. This matches the oft-quoted statement by Brown (1984) that generalist species should have large potential ranges compared to specialist species, which should have small potential ranges since they only tolerate a narrow range of environments. It should be noted that this explanation is based on the assumption that habitat types are equally common: should a specialist species be adapted (only) to a widespread habitat type, the correlation between niche breadth and potential habitat size would be weakened. Because this study didn’t incorporate competition or other biotic interactions, it is not possible to conclude that there are differences in climatic tolerances among genotypes rather than differences in competitive abilities, for example. Inferior competitors may be exclude from ideal habitats and so appear to be specialized to harsh conditions (and the authors note this). This is always the difficulty with interpreting observational patterns, and further, the ongoing difficulty with defining a species’ niche based on observational data. In any case, this study does a nice job of exploring the underpinnings of macroecological variation and uses EMNs in an informative way, and suggests many interesting extensions.

Monday, May 14, 2012

Writing about writing about research.

I suppose it was inevitable that someone would publish a scientific paper about blogs that write about scientific publications. That’s either very meta, or a little myopic, or both. Appropriately then, the paper “Research Blogs and the Discussion of Scholarly Information” is published in PLoS ONE, the most prominent open access journal. The internet has expanded scientific discourse beyond the traditional forms of published media, and blogs tend to provide a less formal, more accessible form of communication. The authors were particularly interested in how discussion of published works on research blogs related to the citation of published works in the traditional published literature. When we discuss and cite papers in blogs, those citations are meaningless in the traditional sense, in that they aren’t incorporated into citation analyses.

The authors used the blog aggregator to identify well-established science blogs. They surveyed 126 blogs, recording the names and fields of journals of the 10 most recently reviewed articles on each blog. They also recorded general information about the blog author(s). Life sciences were by far the most common area blogged about (39% of blogs), although life sciences account for only 21% of all publications. Given the fact that women now receive similar numbers of life science degrees, it is perhaps surprising that the vast majority of blogs have male authors (~67% have a single male author, and ~9% have multiple authors, at least one of which is male).

Regardless of who authors the blogs, the papers that are cited in blogs are predominantly from the highest profile journals – Science, Nature, and PNAS. These journals all have expensive paywalls for non-subscribers. The fourth most cited journal, by contrast, is PLoS ONE. It’s hard to say what this means. It may just be that Science, Nature, and PNAS are well represented in their sample because they are interdisciplinary, and so many blogs will cite them. Or, it may be that bloggers are attracted to the same types of papers that Science and Nature are – high profile, “important”, maybe controversial. Further, bloggers may write about high profile papers, but they do so with greater depth and knowledge than most mainstream media.

There’s only so much that you can draw from a relatively small, simple survey, but some of the trends seem contrary to the supposed openness and accessibility of web-based science communication. Research blogs are written primarily by men, and focus on high-profile, non-open access papers. Does the open-access nature of a blog overcome the non-open access nature of the papers they write about? Does writing about a Science paper make the information within it accessible to more people, or does it decrease the number of people who can fully appreciate your post? Ultimately research blogging is complex, like any form of online media; it can improve on traditional communication while still showing some of the same limitations. It does bode well though that, given the number of blogs commenting on this paper, research bloggers tend to be informed and pretty self-aware.

Thursday, May 3, 2012

Robert Sokal: Statistical giant in ecologists' boots

Robert Sokal (1960):
from Wikipedia

No student of my generation, trained in ecology and evolutionary biology, will not have heard of Sokal and Rholf’s Biometry textbook. Most would have used it in a class or to inform their analyses. Sadly, Robert Sokal passed away last month at the age of 86. He had a tremendous career, mostly at Stony Brook University in New York, and contributing to statistics and science for over half a century. As a testament to his impact, the third edition of Biometry has been cited over 14000 times! It is the canon for experimental design and analysis in the biological sciences.

He had extraordinary and tumultuous experiences as a youth -fleeing Nazi Germany and being raised in China. Whether, such experiences give rise to greatness, or whether his innate intellectual abilities sealed his destiny is an interesting question. Regardless, his impact and legacy will be deservedly long lasting.

47th Carnival of Evolution: catch the news.

The latest edition of the Carnival of Evolution is up at Evolving Thoughts. Read it, enjoy it, pass it along.

Tuesday, April 17, 2012

Community ecology is complicated: revisiting Robert May’s weak interactions

When it comes to explaining species diversity, Stefano Allesina differs from the traditional approach. Community ecology has long focused on the role of two species interactions in determining coexistence (Lotka-Volterra models, etc), particularly in theory. The question then is whether two species interactions are representative of the interactions that are maintaining the millions of species in the world, and Allesina strongly feels that they are not.

In the paper “Stability criteria for complex ecosystems”, Stephano Allesina and Si Tang revisit and expand on an idea proposed by Robert May in 1972. In his paper “Will a large complex system be stable?” Robert May showed analytically that the probability a large system of interacting species is stable – i.e. will return to equilibrium following perturbation – is a function of the number of species and their average interactions strength. Systems with many species are more likely to be stable when the interactions among species are weak.

May’s paper was necessarily limited by the available mathematics of the time. His approach examined a large community matrix, with a large number of interacting species. The sign and strength of the interactions among species were chosen at random. Stability then could be assessed based on the sign of the eigenvalues of the matrix – if the eigenvalues of the matrix are all negative the system is likely to be stable. Solving for the distribution of the eigenvalues of such a large system relied on the semi-circle law for random matrices, and looking at more realistic matrices, such as those representing predator-prey, mutualistic, or competitive interactions, was not possible in 1972. However, more modern theorems for the distribution of eigenvalues from large matrices allowed Allesina and Tang to reevaluate May’s conclusions and expand them to examine how specific types of interactions affect the stability of complex systems.

Allesina and Tang examined matrices where the interactions among species (sign and strength) were randomly selected, similar to those May analyzed. They also looked at more realistic community matrices, for example matrices in which pairs of species have opposite-signed interactions (+ & -) representing predator prey systems (since the effect of a prey species is positive on its predator, but that predator has a negative effect on its prey). A matrix could also contain pairs of species with interactions of the same sign, creating a system with both competition (- & -) and mutualism (+ & +). When these different types of matrices were analyzed for stability, Allesina and Tang found that there was a hierarchy in which mixed competition/mutualism matrices were the least likely to be stable, random matrices (similar to those May used) are intermediate, and predator–prey matrices were the most likely to be stable (figure below).

When the authors looked at more realistic situations where the mean interaction strength for the matrix wasn’t zero (e.g. so a system could have all competitive or all mutualistic interactions), they found such systems were much less likely to be stable. Similarly, realistic structures based on accepted food web models (cascade or niche type) also resulted in less stable systems.

The authors reexamined May’s results that showed that weak interactions made large systems more likely to be stable. In particular they examined how the distribution of interactions strengths, rather than the mean value alone, affected system stability. In contrast to accepted ideas, they found that when there were many weak interactions, predator-prey systems tended to become less stable, suggesting that weak interactions destabilize predator-prey systems. In contrast, weak interactions tended to stabilize competitive and mutualistic systems. The authors concluded, “Our analysis shows that, all other things being equal, weak interactions can be either stabilizing or destabilizing depending on the type of interactions between species.” 

Approaching diversity and coexistence from the idea of large systems and many weak interactions  flies in the face of how much community ecology is practiced today. For that reason, it wouldn't be surprising if this paper has little influence. Allesina suggests that focusing on two species interactions is ultimately misleading, since if species experience a wide range of interactions that vary in strength and direction, sampling only a single interaction will likely misrepresent the overall distribution of interactions. Even when researchers do carry out experiments with multiple species, finding a result of very weak interactions between species is often interpreted as a failure to elucidate the processes maintaining diversity in the system. That said, Allesina’s work (which is worth reading, few people explain complex ideas so clearly) doesn’t necessarily make itself amenable to being tested or applied to concrete questions. Still, there’s unexplored space between traditional, two-species interactions and systems of weak interactions among many species, and exploring this space could be very fruitful. 

Monday, April 9, 2012

Disagreeing about ecology: how debate advances science

A good scientific debate makes for excellent spectator sport (although it’s probably less fun for the participants). Many of the best ecological debates are now classics of the literature—Diamond vs. Simerberloff, Lawton vs. Simberloff, Hubbell vs. many—and these historical debates influence present day ecology. Interestingly, debates in ecology seem to revolve around two particular issues: whether the data is appropriate and whether the methods are adequate to draw conclusions about a particular process.

As an example, there’s a typical ecological debate occurring in Science over Kraft et al.’s “Disentangling the drivers of β-diversity along latitudinal and elevational gradients”. In this paper, the authors reevaluate the mechanisms that drive changes in species identity along latitudinal and elevation gradients using a null model. Although β-diversity may vary along biogeographical gradients as a result of processes such as dispersal limitation, range size, and habitat filtering, total (γ) diversity also varies along these gradients (we know that richness is generally higher in the tropics and the lowlands). Since this suggests that γ- and β-diversity aren’t independent, it may be that changes in γ-diversity need to be accounted for as an explanation for changes in β-diversity (Chase 2011). When Kraft et al. controlled for γ-diversity using a null model, they found that the magnitude of β-diversity did not vary along latitudinal or elevational gradients. They stated that this means: “there may be no need to invoke differences in the mechanisms of community assembly in temperate versus tropical systems to explain these global-scale patterns of β-diversity.”

This conclusion is in contrast to multiple papers that have suggested that tropical communities are somehow structured differently from temperate communities. Such work has been far from conclusive, however, finding evidence for everything from stochastic assembly to microhabitat-driven assembly in tropical regions. However, given the strong conclusion from the Kraft et al. paper, it’s not surprising that there were several responses from other researchers of β-diversity (Tuomisto and Ruokolainen and Qian et al.). It’s also not surprising that the points raised in these responses are fairly typical for debates in community ecology, calling into question the suitability of the data, the appropriateness of the spatial scale for capturing the processes of interest, and the question of whether the methods are correct. The debate is as much about the fundamental questions of how we define and measure β-diversity as it is about the particulars of the Kraft et al. article.

For example, both Tuomisto and Ruokolainen and Qian et al. questioned the sampling design of the data, as to whether there was too much within-plot variation (Tuomisto and Ruokolainen) or, alternately, too little between-plot variation (Qian et al.) to correctly capture the amount of β-diversity. Tuomisto and Ruokolainen further suggested that the plots used in the original study undersample local (α) diversity and therefore overestimate the differences between plots. Both sets of authors suggest that inappropriate sampling would make it difficult to generalize Kraft et al.’s results to other studies of β-diversity. Kraft et al.’s response was that although plots are placed to minimize among-plot environmental variation, this does not make them inappropriate to test for finer scale evidence of environmental processes, and that β-diversity still varies markedly between plots. However, given that this debate - about whether there is a “best” spatial scale at which to examine the ecological causes of β-diversity and a “best” way to sample to capture variation among communities – is occurring among experienced β-diversity researchers suggests that these are still fuzzy areas.

Another aspect of this debate relates to the ongoing discussion about the appropriate definition and calculation of β-diversity (Tuomisto 2010). The most traditional methods define β-diversity as a multiplicative or additive function of α- and γ-diversity, and Kraft et al. argue that as a result β-diversity is not independent of those variables. To account for this fact, Kraft et al. use a null model that incorporates γ-diversity, to predict β-diversity under random or stochastic assembly. However, Tuomisto and Ruokolainen argue that the measure of β-diversity used (βP = 1 – α/γ) is such that γ-diversity can vary without affecting β-diversity, provided alpha-diversity is also free to vary. However, Kraft et al. dispute this, suggesting that perfectly scaled changes in both γ- and α-diversity, such that β-diversity remains unchanged, represent a special case that does not appear in their data set.

Of course, other points were discussed among the authors. Qian et al. disagreed with the use of latitudinal gradients, noting that the ecological “meaning” of a given latitude is rather vague. However, given that the authors admit their site data is likely to capture small-scale variation in β-diversity, it seems that trying to relate their results to large-scale latitudinal or elevational gradients is a greater issue.

Kraft et al. suggested in their response that many of the criticisms were misunderstandings of the methods and findings of the original paper. You might more correctly say that disagreements like this capture important weaknesses or ambiguities in current understanding and theory. It’s true that at their worst, debates create conflict and that since responses are rarely peer-reviewed to the same extent the original publication is, too much weight may be given to meritless counter-arguments. However, good debate should drive progress, force researchers to reevaluate their assumptions, and ultimately hold science accountable. And for that reason it should be encouraged.

**I should note that this post is specifically meant in relation to debate among researchers, not to situations where scientists are in agreement and the debate is occurring in the public sphere.