Thursday, March 22, 2012

NCEAS is dead; long live NCEAS. A view towards NCEAS 2.0.

"is this a wake or revival?" Jim Brown

March 21-22, 2012, Santa Barbara, CA. National Center for Ecological Analysis and Synthesis (NCEAS) symposium.

A special invitation- only symposium marking the end of NCEAS as we know it, saw a number of interesting talks and retrospectives about where NCEAS has been and where it is going. 170 people attended, including some former postdocs, working group participants and leaders in ecology. The reason for this introspective meeting is that NCEAS's core NSF funding is about to end, without renewel. Jim Brown's quote from his talk, whether we were here for a wake or a revival really captured the spirit of the meeting.

The goals were twofold. First was to look back and celebrate the accomplishments of NCEAS. University of California at Santa Barbara is globally one the top influential research institutions in the world, and this success has been driven in large part by the success of NCEAS. More than 5000 people have come to NCEAS and their efforts have resulted in thousands of publications, and many citation classics. The early visions of NCEAS were broad and fuzzy and by all accounts NCEAS has exceeded all expectations.

The second motivation for ts meeting was to think about the future. What can NCEAS be under different funding regimes, and how should it move forward? The is no doubt that it will be fundamentally different, but can there be a successful continuation of the NCEAS model, will it die, or will it give birth to a new enerprise, NCEAS 2.0?

The symposium saw great talks, from people like Jim Brown and Jane Lubchenco, and interesting panel discussions on numerous topics (see #treas2012 in twitter for synopsis of the meeting). There were a lot of past tense statements.

However, it was clear that there was much to celebrate. NCEAS clearly impacted ecology. Did its success simply coincide with cultural changes in the field or did it drive changes? The consensus was that it drove changes. It fostered large collaborations. Dave Tilman said that before NCEAS, ecology was largely local and lab-driven, but NCEAS offered a way to get people together to ask bigger questions. The postdoctoral fellows have been extremely successful, with the vast majority ending up in faculty positions in top institutions. It was acknowledged that many sub fields were created or coalesced at NCEAS, including disease ecology and metacommunity dynamics.

Why has it been so successful? NCEAS is a special inclusive place where people want to come, away from their responsibilities. The technical help here and expertise that made anything possible, any data challenges were overcome and analytical difficulties solved. Postdocs were given complete independence and were allowed to pursue collaboration and networking. Jim Brown remarked that NCEAS is the single greatest event in the history of ecology. Subfields now talk, lab projects are now geared towards collaboration and linkages with other work in ways that did not exist before.

So then, what will the future hold for NCEAS? The answer to this was left vague and uncertain. People argued for what NCEAS 2.0 should look like. For example, it was argued that NCEAS 2.0 should resurface something like science 2.0, making the focus data and data sharing, changing methods and philosophy of how science is done. Massive anonymous collaboration requires assumed standards and altruism. Other arguments focused on the need for NCEAS to reach out to new partners and to go global.

Peter Karieva said it well. NCEAS 2.0 should be interacting with major corporations, since they represent the drastic impacts on ecological systems around the world. 1.0 was about data accessability, 2.0 should about applicability and tools to affect change.

Whatever NCEAS 2.0 looks like, it will be different. There seems to be two ways forward. One is that it struggles to maintain its past activities or one that like the Phoenix rises from the ashes and boldly goes forward to again push the ecology in new directions.

Sunday, March 11, 2012

On rejection: or, life in academia


I guess it’s not surprising, given that I’ve written about failure in science, that I would write a post about rejection as well. Actually, I’m not so interested in writing about rejection as I am in hearing how people have learned to deal with it.  

Academia is a strange workplace. It’s stocked with bright people who’ve been successful throughout their previous academic endeavours (with some exceptions*). For the most part, they haven’t faced too much criticism of their intellectual abilities. But in academia you will spend your career being questioned and criticized, in large part by your peers. You will constantly be judged (with every submitted manuscript, grant application, or tenure review). And this is the universal truth about academia: you will be rejected. And for some (many?) people, that's a difficult thing to accept.

Rejection may be so painful in part because it can be hard to interpret. After all, it’s an old trope that rejection is a normal part of academia. But how much rejection is normal, when is it just a numbers game and when is it a sign of professional failing? Let alone the fact that rejection depends on a shifting academic landscape where available funding, journal quotas, and research caliber are always changing. So I’m curious: does the ability to deal with rejection factor into academic success? Are some people, based on personality, more likely to weather rejections successfully, and does this translate into academic success? Or is the development of a thick skin just the inevitable outcome of an academic life?

*A couple of the people I know who are generally unfazed by rejections would say that they deal well with rejection because they weren’t particularly great students and so academic failure isn’t new or frightening to them. 

Friday, March 2, 2012

The niche as a changeable entity: phenotypic plasticity in community ecology



Nearly all explanations for coexistence in communities focus on differences between species. The scale of these differences may occur over large temporal (e.g. evolutionary history, phylogenetic relationships) or spatial scales (e.g. environmental tolerances), or at the scale of the individual. In plants, interactions at the local scale are given particular attention, including interactions mediated by trait differences between species. At finer scales still, there has been recent focus on differences between individuals of the same species, whether they are driven by genotypic differences (link) or plastic changes in individual phenotypes.

From Ashton et al. 2010
Phenotypic plasticity can be defined as phenotypic differences among individuals of the same genotype that occur in response to an environmental cue. The ability of plant species to alter their usage of resources, for example, has clear relevance to resource partitioning among species, since a given individual could adaptively take advantage of alternate resources in response to their particular competitive environment. In such a case, an individual’s realized niche is a function of phenotypic changes in response to the biotic and abiotic environment and thus physiologically-determined. This is in contrast to the usual approach to species’ niches, where physiological constraints are considered to determine a species’ fundamental niche. Although the plant literature shows clear examples of phenotypic plasticity among plants, including in response to competition (for example, perception of light quality leading to changes in growth form), the topic usually receives only passing mention in the community ecology literature.
The number of papers addressing questions of coexistence and competition through the lens of phenotypic plasticity is slowly rising.
From Schiffer et al. 2011, Lithium uptake is
significantly higher on the non-competitor side


A couple of papers from the last few years provide tantalizing glimpses into the possible contribution of plasticity to coexistence. In Schiffers et al. (2011), the authors use experimental and modeling approaches to test whether root uptake can change in response to the proximity of competitors. In the experimental study, the authors looked at the uptake of lithium (a stable nutrient that will be taken up in the place of potassium) by Bromus hordeaceus. They planted pairs of B. hordeaceus  at varying distances apart and then injected lithium into the soil at different differences from the focal plant. They found that lithium uptake was significantly higher on the non-competitor side of the focal plant than on the competitor side, suggesting that plastic changes in resource uptake occurred in response to competitor proximity. Modelling results from the same study suggest that plasticity may allow individuals minimize competitive pressure by making changes in belowground architecture, thereby using available space more efficiently.

Ashton et al. (2010) take a similar approach, looking at how the uptake of nutrients (in this case three forms of nitrogen (N)) varies among species depending on their competitive environment. They explored the ways in which plasticity could lead to changes in the realized niche. In particular, they explored two hypotheses: that plants would exhibit niche preemption, where the inferior competitor switched to a different form of nitrogen in the presence of the superior competitor; or dominant plasticity, where plasticity actually enhances competitive ability.  The authors looked at 4 species, 3 common and 1 rare(r), in an alpine tundra community, isolating naturally occurring pairs of each combination of species. These ‘competitive arenas’ were isolated, and other species within the arena were removed. After a year, the authors added N15 tracers to each arena, in three forms (NH4+, NO3-, and glycine): these tracers would allow them to track the N once it was incorporated into the plant tissue. The plants were then harvested and the amount of each type of nitrogen in each was measured. Plant biomass was also recorded, and used to estimate the ‘competitive response’ (basically the ratio of biomass when grown with a competitor compared biomass to when grown solo). Their findings were rather neat: the 3 common plants experienced no negative effect on biomass from growing in competition with the rare plant, but the rare plant had much lower biomass when grown in the presence of any of the common plants. Further, while the common plants showed changes in the form of N they used when growing with the rare plant, the rare plant did not switch its N preference. The rare plant’s lack of plasticity in response to competition may relate to its lower biomass when grown with superior competitors, and ultimately its lower abundance.

Although limited, these studies hint at the role that phenotypic plasticity could play in interspecific interactions. Unfortunately plasticity may be difficult to measure in many contexts, particularly since variation within a species can be attributed to genetic differences or phenotypic plasticity, and these factors must be teased apart. Further, there is an issue of differentiating the effects of resource limitations from ‘adaptive’ plastic changes in growth. While plants are relatively tractable for these types of studies (they’re sessile, they use limited abiotic resources), other organisms are less explored for a reason.

What these studies can’t address is the question of ‘how important is phenotypic plasticity, really’? Reviews of coexistence mechanisms list numerous possible ways by which coexistence is facilitated among species. For plants especially, the limited number of resources required for survival has lead to great consideration of the possible niche axes over which species can differentiate themselves. Phenotypic plasticity's contribution to coexistence may be that it provides another way by which plants can partition resources at very fine scales. And if nothing else, such results provide further evidence that variation within species may be an important component of coexistence.

Thanks to Kelly Carscadden for discussions on the topic.

Tuesday, February 14, 2012

A good null model is hard to find



Ecologists have always found the question of how communities assemble to be of great interest. However, studies of community assembly are often thwarted by the large temporal and spatial scales over which processes occur, making experimental tests of assembly theory difficult. As a result, researchers are often forced to rely on observational data and make inferences about the mechanisms at play from patterns alone. While historical assembly research focused on inferring evidence of competition or environmental filtering from patterns of species co-occurrence, more recent research often looks at patterns of phylogenetic or trait similarity in a community to answer these questions. 

Not surprisingly, when methods rely heavily on observational data they are open to criticism: one of the most important outcomes of early community assembly literature was the recognition that patterns that appeared to support a hypothesis about competition or environmental filtering could in fact result by random chance. This ultimately lead to the widespread incorporation of null models, which are meant to simulate patterns that might be observed by random chance (or other processes not under study), against which the observed data can be compared. Patterns of functional and phylogenetic information in communities can also be compared against null expectations to ensure that patterns of phylogenetic or functional over- or under-dispersion can't arise due to chance alone. However, while null models are an important tool in assembly research, they are sometimes as the foolproof solution to all of its problems.

In a new paper by Francesco de Bello, the author states frankly “whilst reading null-model methods applied in the literature (indeed including my work), one may have the impression of reading a book of magic spells”. While null models are increasingly sophisticated, allowing researchers to determine which processes to control for and which to leave out, de Bello suggests that the decision to include or omit particular factors from a null model can be unclear, making it difficult to interpret results or compare results across studies. Further, results from null models may not mean what researchers expect them to mean.

Using the example of functional diversity (FD; variation in trait values among species in a community), de Bellow illustrates how null models may have different meanings than expected. Ideally, a null model for FD should produce random values of FD, against which the observed values of FD can be compared. Interpreting the difference between the observed and random results can be done using the standardized effect size (SES, the standardized difference between the observed and randomly generated FD values); SES values >0 show that traits are more divergent than expected by chance, suggesting competition structures communities. If SES<0, traits are more convergent than expected by chance, suggesting environmental conditions structure communities. Finally, if SES ~0, then trait values aren’t different from random. However, de Bello shows that the SES is driven by the observed FD values, because the ‘random’ FD values are dependent on the pool of observations sampled. This means that the values the null model produces are ultimately dependent on those observed values, despite the fact you plan to make inferences by comparing the null and observed values as though they are independent. For example, consider the situation where you are building a null model of community structure for plant communities found along two vegetation belts. If the null model is constructed using all the plant communities, regardless of the habitat they are found in, the resulting null FD value will be higher, since species that are dissimilar and found in different vegetation belts are being randomly selected as occurring in a community. If null models are constructed separately for both vegetation belts, the null FD value is lower, since species are more similar. The magnitude of the difference between the null model and the observed values, and further, the biological conclusions one would take from this study, would therefore depend on which null model was constructed.

from de Bello 2012, illustrating how combining species pools (right) can lead to entirely different decisions about whether communities are convergent or divergent in terms of traits than when they are considered separately (left, centre).
De Bello’s findings make important points about the limitations of null models, particularly for functional diversity, but likely for other types of response variable. The type of null model he explores is relatively simplistic (reshuffling of species among sites), and the suggestion that the species pool affects the null model is not unique (Shipley & Weiher, 1995). However, even sophisticated and complex null models need to be biologically relevant and interpretable, and null models are still frequently used incorrectly. Although only mentioned briefly, De Bello also notes another problem with studies of community assembly, which is that popular indices like FD, PD, and others may not always be able to distinguish correctly between different assembly mechanisms (Mouchet et al. 2010Mayfield & Levine, 2010), something that null model do not control for. 

Monday, January 30, 2012

Should we still be testing neutral theory? If so, how?



For many ecologists, neutral theory was a (good/bad, you choose) idea that dominated ecology for the last decade but failed to provide the burden of empirical proof necessary for its acceptance. Even its creator Stephen Hubbell  recently suggested that the controversial hypothesis is no longer a plausible description of community structure, going as far to say that it is “good starting point”, a “valuable null model”, and a “useful baseline” (in Etienne et al 2011)

But ideas, when they’re shared, are no longer the sole property of their creators. Other researchers continue to study neutral theory, and despite the apparent consensus that neutral theory is not an important explanation of community structure and dynamics, papers testing neutral theory continue to be published. This leads to an important question: do we still want to test for neutral dynamics? And if we do, how should we approach it, given what we have learned from the past decade of strawman arguments and using pattern-based evidence for processes (e.g. looking at species-area relationships and species abundance distributions)? What empirical evidence would provide strong support for the predictions of neutral theory?

Damselfly larvae
(http://www.uta.edu/biology/robinson/odonate_research.htm)
In “Experimental evidence for neutral community dynamics governing an insect assemblage”, Siepielski et al. (2010) attempt to provide a more rigorous test of neutral theory using two Enallagma (damselfly) larvae. Siepielski et al. focus on changes in demographic rates (growth, mortality) in response to changes in species relative and total abundances. In particular, they predicted that if niche differences drive coexistence, increasing a species’ relative abundance should drive lower growth rates and higher mortality, since that species is above its equilibrium; lowered relative abundances should result in higher growth rates and lowered mortality since the species is below its equilibrium density. As a result, species should return to their equilibrial abundances. Raising the total abundances but leaving the relative abundances untouched should have similar demographic responses across species and have no effect on the relative abundances. In contrast, neutral theory predicts that if all species are equal, their demographic rates depend on the density of the entire group (total abundance) and not on each individual species’ relative abundance. Therefore the response of demographic rates to changes in species relative abundances, while the total abundance is held constant, should provide support to either neutral or niche theory.

For two Enallagma sp. larvae Siepielski et al. used cages in the littoral zone of lakes, with cages receiving different treatments of relative abundance and/or total abundance manipulation. The result of these manipulations were that replicates with increased total abundances and constant relative abundances had lowered per-capita growth rates, while replicates with manipulated relative abundances and constant total abundances showed no change in demographic rates. Both species had similar mortality rates across the experimental treatments, although their growth rates differed slightly. From these results, Siepielski et al. concluded that these species are ecologically equivalent.

One of the reasons work (such as this) from Mark McPeek’s lab is interesting is because he is an outlier: someone whose work is deeply rooted in a natural system, and yet who also argues that ecological equivalency seems plausible, and attempts to support that argument. Regardless of whether the Enallagma species are in fact ecologically equivalent, this paper provides an example of how coexistence theory can be more rigorously tested than simply observing species co-ocurrences and concluding species coexistence. Further, it provides some interesting discussion about whether ecological equivalency is possible within functional groups, with niche differences occurring between functional groups (see Leibold and McPeek 2006, and from MacNaughton and Wolf 1970 for similar suggestions). Future work might focus on questions such as how to capture the effects of small niche differences, which, if balanced against very similar fitnesses could explain stable coexistence. In addition, it might be valuable to look at how resources fluctuate and how much overlap there is in resource requirements among species, when looking at how growth and mortality change with species densities.

With Adam Siepielski, Mark McPeek also published the paper “On the evidence for species coexistence: a critique of the coexistence program about the apparently lowered standards for tests of niche-based species coexistence compared to those of neutral theory. What is certainly true is that experimental tests of coexistence theory are often less rigorous than necessary to support any coexistence theory, and should strive to take a more rigorous approach. If nothing else, this will allow criticism of particular theories to focus on the ideas themselves, rather than on how those ideas were tested.

Tuesday, January 10, 2012

Trends in ecology, 2011

What were the topics of research that dominated ecology in 2011, and where is ecology likely to head in 2012?

A brief answer can be found by looking at the most common keywords found in ecology papers published during 2011*. "Abundance" proved the most common keyword. Interestingly, "climate change" and "global warming" appeared less common as keywords compared to last year. In contrast, words tying research to places ("Great Barrier Reef") and systems ("rainforest") seemed more common. Although it's hard to draw any specific conclusions from this kind of thing, it's notable that many of the most common words are related to community ecology, lending credence to Marc Cadotte's assertion that community ecology is flourishing as a discipline.



*Although hardly rigorous, I analyzed the keywords from 4000 randomly selected ecology papers published in 2011 found using a Web of Science search. The most common 150 terms are represented in the word cloud, where text size represents the frequency with which a word appears on the list.

Tuesday, January 3, 2012

Carnival of Evolution 43!

The history of human thought is an epic adventure of exploration and discovery. Since the beginning of time, humans have been curious about order and chaos in nature and our place in the world. By understanding the natural world around us, we understand ourselves better. But how we attempt to answer these fundamental questions has evolved over time. This evolving history, looks something like this:

146,000 BCE
Targ: "Hey Lerb, why big cat have long teeth?"
Lerb: "I dunno Targ, but cousin Seb went for look. He gone"
Targ: " Cat lucky, seem good for people eating. I go for closer look."

523 BCE
Anaximander: "Thales, my teacher, how is it that animals take their form?"
Thales: "Anaximander, all matter is an aggregation formed from a single substance, water, and qualities are obtained through need"
Anaximander: "Ah yes, water, I will now think about how air can be the primordial substance."

1849 CE
Thomas Thomson: "I do say, the flora of northern India is peculiar in the sheer number of forms of life that populate this region. I do wonder though, what the cause is for such brilliant numbers of species?"
Joseph Hooker: "My dear Thomas, the flora of northern India is brilliant indeed! These forms find their origins in those very places where they live. Of course Lamarck believes that the crises endured by the tissues of organisms, themselves pass on the incentive to produce offspring better equipped to endure such crises. However, in my correspondence with Charles Darwin, he confirms that variation is an inherent aspect of life and gives rise to the diversity we see."

2012 CE
You: "Man, I wish I new more about evolution. Hey, what is this Carnival of Evolution? OMG, this is totally sick."
You no longer need to ponder the mysteries of life, travel the globe making observations, or running complex experiments to test hypotheses; everything you want to know about evolution today can be found by reading the monthly installments of the Carnival of Evolution!

The first installment of 2012 (or is this the last of 2011?) offers a great smattering of many different aspects of current evolutionary understanding. These 26 posts cover many of the major areas of research that define current evolutionary biology.

Most evolutionary research aims to understand how the amazing diversity of life came to be. Core to this is studying both paleontological record and patterns among modern organisms. Early explosions of diversity have always captured scientists imaginations, and Larry Moran at Sandwalk (and fellow Torontonian) explains that recent evidence is casting doubt that the Cambrian explosion was actually an explosion, at least according to genetic evidence. Much later on, ray-finned fish became extremely successful and are now the dominate form of fish on Earth. Their success and resulting diversification is likely better explained by rapid morphological changes to head shape and not fin evolution, according to Lucas Brouwers at Thoughtomics. Nothing in the paleontological record excites the imagination more than dinosaurs. Recent work has developed a detailed understanding of the ecology and evolution of these amazing creatures. Marc Vincent at Love in the Time of Chasmosaurs describes research that indicates that head crests and feathers on many dinosaurs were likely to product of sexual selection. While, according to David Orr, also at Love in the Time of Chasmosaurs, the big toe claw on both hind feet of Deinonychus evolved to pin down small prey, and not to slice open large prey (thank you Jurassic Park). In one of the best, 'huh, I didn't know that' posts, Fins to Feet shows that Mosasaurs -giant predatory marine reptiles found during the time of the dinosaurs, are likely closely related to monitor lizards and not part of the ancestral lineage that includes dinosaurs.

Studying and explaining patterns among modern day critters is the evolutionary biologists' bread and butter, and studies of organisms seem to constantly shed light on new ways in which evolution has shaped life. The interesting story of the oil beetle and how it has evolved to hitch rides on other insects is presented by Anne Buchanan The Mermaid's Tale. As relayed by Jeremy Yoder at Denim and Tweed, birds that lay eggs in the nests of other species (nest parasites) have been associated with the same hosts for millions of years. Flower colors are commonly thought to be shaped by pollinator preference, but Zen Faulkes at NeuroDojo shows evidence that white variants of bluebells (are they still bluebells?) do not see different pollinator visitation rates. Species differences can be difficult to identify using our human senses, but Lucas Brouwers at Thoughtomics explains how echolocation has diverged between indistinguishable bat species. Lungfish are oft-cited exemplars of evolution, mainly because they are so fascinating -not only do they have lings, but they walk too. Which is why they are the subject of two posts this month (one by Matthew Cobb at Why Evolution is True and one by Carl Zimmer at the Loom), both about how they move and how they may have transitioned to walking.

Evolutionary change for many animals is often not a linear move from genes to fitness, but rather behavior has the potential to affect evolution in complex ways. In one example, Jeremy Yoder at Denim and Tweed, tells the tale of how fear of being eaten can lower fitness. In another example, Simon's Science explains research that shows female stickleback fish, which are raised by their fathers, will prefer mates from their father's species, even when experimentalists switch the species providing parental care.

To unveil the wizard, a number of posts show how evolutionary research is done and how our understanding evolves. In two posts at BEACON, researchers Tasneem Pierce and Michael DeNieu give fascinating firsthand accounts of doing research. You can sense the wonder and excitement of doing scientific research from their posts. Stan Rice at Honest Ab has a wonderful sequence of five posts relaying his dinosaur adventure -at least playing with paleontology and avoiding creationists. John Wilkins at Evolving Thoughts examines the definition of evolutionary novelty in an ongoing series (maybe his next book?), and looks at comparative versus functional definitions.

For most people, evolution is central to the ultimate questions about who we are and where we come from. True to this anthropocentric* view of evolution, there are a large number of excellent posts about human evolution and why we are the way we are. For those people who feel that the Carnival of Evolution does not provide all the answers to their questions about human evolution, Greg Laden reviews two new books on understanding human evolution. Suzanne Elvidge at Genome Engineering reports that scientists have sequenced the genome of a descendent of Genghis Khan. Why is this interesting? Well it turns out that millions of people -half a percent of the current global population, are related to Genghis Khan! The obvious question to me was how is this possible? It turns out that, according to Wikipedia, Genghis Khan had a harem of between 2000-3000 women and many of his many, many sons also had obscenely** large harems. Thus, by the time Genghis was a dirty old man, he could have had 10,000 descendents.

Often the need for evolutionary explanations comes from the question: "Why the heck do we do that?". True to this question, there are four posts that look at human behavior. In a controversial but intriguing post, Khudadad Azara at Khudadad's Knols suggests that terrorism is a macho impulse for glory and honor shaped by sexual selection. The most convincing parts are that males often do stupid things for sexual advantage, and terrorism is a stupid thing. Why the hell are yawns contagious? Well, according to Suzanne Elvidge at Genome Engineering, yawns may be evolutionary as they are most contagious among close relatives. Holly Dunsworth at The Mermaid's Tale makes the case that the uniquely human ability to throw (chimps actually aren't very good at it) is not so much an anatomical thing, but a brain thing, interesting. PZ Myers at Pharyngula asks why women menstruate and suggests that it is the evolutionary result of mother-fetus conflict.

A big part of human history, culture and belief, is our conflict with disease. This month there are several very interesting posts on evolution and human disease. Swenson at Nothing in Biology Makes Sense! discusses how reconstructing the evolutionary relationships among HIV samples dating as far back as 1959 reveals that there are deep divergences indicating that HIV has likely been in humans since the late 1800's! Carl Zimmer at the Loom relays the latest research showing that Syphilis evolved in the New World and was likely brought to Europe (Italy) from early European explorers. Ford Denison writes at This Week in Evolution that a genetic mutation increasing the risk of breast cancer in women is also associated with increased fertility. This invites the conclusion that there may be a tradeoff between longevity and fertility.

That is all for this month from the Carnival of Evolution. Everything you ever wanted to know about evolution but were afraid to ask. When you start to have new questions, luckily there will be a new edition of the Carnival in a months time.


*I realized after I wrote this sentence that it sounds negative. I do not mean the increasing pejorative 'unnatural', but rather legitimately human-focused.

**Having a harem of any size is obscene, but what adjective can you use for harems with thousands of women?

Monday, December 26, 2011

Rumors of community ecology’s death were greatly exaggerated: reflections on Lawton 1999

In 1999, John Lawton, eminent British ecologist, published a lament for the state of community ecology entitled “Are there general laws in ecology?” Cited more than 600 times, Lawton’s paper forced a re-evaluation of community ecology’s value, success, and even future existence. Other scientists at the time seemed to agree, with papers starting with phrases like “Although community ecology is a struggling science…” and “Given the lack of general laws in ecology…”. Lawton appeared to be suggesting that community ecology be abandoned for the generality of macroecology or the structure of population ecology.

An important point to be made is that Lawton was simply making a particularly public expression of ecology’s growing pains. In 1999, ecology was at a crossroads between the traditional approach of in-depth system-based study, and a fairly single-minded focus on competition as an explanation for patterns (e.g., Cooper 1993 ‘The Competition Controversy in Community Ecology’ Biology and Philosophy 8: 359-384), while at the same time there were emergent approaches and explanations like neutrality, macroecology, spatial ecology, ecophylogenetics, and improved computer and molecular methods. There was also growing dissent about ecology’s philosophical approach to ecology (e.g., Peters 1991 ‘A Critique for Ecology’; Haila and Heininen 1995 ‘Ecology: A New Discipline for Disciplining’ Social Text 42: 153-171): ecologists tended to ignore the Popperian approach, which required falsification of existing hypothesis, instead tending to look for support for an existing hypothesis, or at least advocated looking for patterns without considering alternative mechanisms. Not only this, but the applications for ecology were more clear than ever – the Intergovernmental Panel for Climate Change was meeting , and the ecological consequences of human actions were perhaps more obvious they had ever been. But ecologists were failing at providing solutions –Lawton argued-correctly-that in 1999 ecologists could provide little insight into how a community might change in structure and function in response to changing climate.

Although everyone should read Lawton’s paper, a simple synthesis of his concerns would be this – that community ecology is too contingent, communities are too complex, and therefore community ecology cannot formulate any laws, cannot make predictions, cannot be generalized from one system to another. This makes community ecology suspect as a science (physics being the most common example of an “ideal” science), and certainly not very useful. Lawton suggests that population ecology, where only a few models of growth could explain the majority of species’ dynamics, or macroecology, which focuses on the most general, large-scale patterns, were a better example of how ecology should be practiced.

Community ecology, rather than dying, has experienced an incredible surge in popularity, with a large contingent represented at meetings and in journal publications. Ecology itself is also thriving, as one of the fastest growing departments in universities. So what, if anything, has changed? Has ecology addressed Lawton’s criticisms?

Two major things happened in the late 1990’s and early 2000’s, which helped ecologists see beyond this general malaise. The first was that a number of well-thought out alternative ecological mechanisms explaining community membership were published. Before the late 90’s community ecologists looked for evidence of competition in patterns of community composition, either among locales or through time following disturbance. When local competition was insufficient to explain patterns, researchers likely cited, but did not test other mechanisms. Or if they did test other mechanisms, say predation, it was as an alternative, mutually exclusive mechanism. The new publications, drawing on previous ideas and concepts formalized assembly mechanisms like neutral processes or metacommunity dynamics where uneven fitnesses in a heterogeneous landscape can affect local coexistence. More than these as solely alternative mechanisms, these allowed for a synthesis where multiple mechanisms operate simultaneously to affect coexistence. Probably the most emblematic paper of this renewed excitement is Peter Chesson’s 2000 ‘Mechanisms of maintenance of species diversity’ published in Annual Reviews of Ecology and Systematics. This paper, cited over a thousand times, offers a way forward with a framework that includes competitive and niche differences but can also account for neutral dynamics.

A second major development that rejuvenated ecology was the formation of technological and statistical tools engendering broad-scale synthetic research. Suddenly the search for general explanations – Lawton’s most piercing criticism - became more common and more successful. With the advent of on-line databases, meta-analytic procedures and centers (e.g., the National Center for Ecological Analysis and Synthesis) that foster synthetic research, ecologists routinely test hypotheses that transcend local idiosyncrasies. Often, the capstone publication on a particular hypothesis is no longer a seminal experiment, but rather a meta-analysis that is combines all the available information to assess how strongly and how often a particular mechanism affects patterns.

While these theoretical and technological developments have been essential ingredients in this ecological rejuvenation, there has also been a subtle shift the philosophical approach to what it is ecological theory can and should do. Criticism in the 1990’s (e.g., Peters 1991 ‘A Critique for Ecology’) centered on the inability of ecological theory to make accurate predictions. The concept of science common in ecology in the 1990’s was that a rigorous, precise science (i.e., with laws) results in the ability to accurately predict species composition and species abundances given a set of mechanisms. This view of ecological science has been criticized as simplistic ‘physics-envy’ (e.g., see Massimo Pigliucci’s PhD dissertation ‘Dangerous habits: examining the philosophical baggage of biological research’published by the University of Tennessee in 2003). The subtle philosophical change has been a move from law=prediction to law=understanding. This is as true for physics as it is for ecology. We don’t expect a physicist to predict precisely where a falling feather will land, but we do expect to totally understand why it landed where it did based on fundamental processes. (for more on the contrast of prediction and understanding, see Wilhelm Windelband’s nomothetic and idiographic knowledge)


While the feather example above is simplistic, it is telling. In reality a physicist can produce probability contours of where the feather is likely to land, which could be very focused on a calm day or broad on a windy one. This is exactly what ecologists do. Once they understand how differing mechanisms come together to shape diversity, they make probabilistic predictions about the outcome of a set of known mechanisms.

Ecology today is as vibrant as ever. This is not a result of finding new laws that proved Lawton incorrect. Rather, ecologists now have a more sophisticated understanding of how various mechanisms operate in concert to shape diversity. Moreover, conceptual, technological and philosophical revolutions have fundamentally changed what ecologists do and what they are trying to explain. It is a great time to be an ecologist.

Lawton, J. H. (1999). Are there general laws in ecology? Oikos, 84(2), 177-192.


By Marc Cadotte and Caroline Tucker

Sunday, December 18, 2011

holiday caRd

I wasn't planning on making any more "caRds", but since I received a number of requests, find below a holiday card from the EEB & flow. For optimal viewing, perhaps throw some Jingle Bells on in the background.

This code relies heavily on the rgl package in R. Be sure to run the first line of code to install this package if you don't already have it. 

###holiday caRd

#install "rgl" package if necessary:
install.packages("rgl")

#load library
library(rgl)

##Data
r=1.0
h=5.0
m=h/r
x=seq(0:99)
y=x
X=x*cos(y)
Y=x*sin(y)
Z=-1*(m*x)
Z1=Z+rnorm(length(Z),Z,5)
sub<-matrix(subset(c(X,Y,Z),Z==max(Z)),ncol=3)
trunk<-matrix(c(0.54,0.84,-200,0.54,0.84,-650),byrow=TRUE,ncol=3)
sno<-c(0,rep(15,9))

##Plot card
open3d(FOV=1)
par3d(windowRect=c(100,100,600,600))
bg3d("aquamarine2")
plot3d(X,Y,Z,col="darkgreen",type="l",box=FALSE,axes=FALSE,lwd=10,zlim=c(min(Z),0),xlab="",ylab="",zlab="",top=TRUE,border=TRUE)
plot3d(X,Y,Z,col=c("yellow","red"),add=TRUE,type="s",radius=3)
points3d(sub,col="orange",size=10)
lines3d(trunk,col="brown",lwd=20)
text3d(matrix(c(0.54,-100,300),ncol=3),text="Happy Holidays",font=5,cex=1.9,color="darkred",adj=c(0.5,1))
text3d(matrix(c(0.54,0.84,-650),ncol=3),text="and",font=5,cex=1.5,color="darkred",adj=c(0.5,1))
text3d(matrix(c(0.54,75,-780),ncol=3),text="a Happy New Year",font=5,cex=1.9,color="darkred",adj=c(0.5,1))
mat<-par3d("scale")

##Play card
for(i in 1:10){
par3d(scale=mat,ignoreExtent=TRUE)
points3d(matrix(c(sample(-160:160,sno[i]),sample(-160:160,sno[i]),sample(-500:150,sno[i])),ncol=3),col="white",size=3)
play3d(spin3d(axis=c(0,0,1)),duration=1)
if(i==10){points3d(sub,col="darkorange",size=17)
plot3d(X,Y,Z,col=c("yellow","red"),type="s",radius=4,add=TRUE) } }
text3d(matrix(c(0,140,-900),ncol=3),text="From the EEB & Flow",font=1,cex=1.0,color="darkgreen",adj=c(0.5,1))


##The rgl device window allows you to use your mouse to manipulate the plot in 3-dimensions, so feel free to do so before closing it.

You can also access the script here.