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.

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?

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

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.

What should be the basic unit of community ecology, 2011.

“Why intraspecific variation matters in community ecology” Bolnick et al. 2011, Trends in Ecology and Evolution.

Intraspecific variation in gastropod
shell morphology (Goodrich 1934).

 There has been a long debate in community ecology on the fundamental unit, a debate on what Tansley described as the “necessity of first determining empirically our natural units”. In early years, it involved tension between Clements' and Gleason’s view of the plant community, either as a “superorganism” or simply as a conglomeration of co-occurring species. This latter, Gleasonian view won out, signaling a move towards the species-oriented approach that dominates community ecology today. In later years, there was a push to view the individual—not the species—as the fundamental unit, championed by people like Dan Simberloff. However, though this view has had some influence, it has never been mainstream.

 The basis of these debates about the basic unit is simple: do similarities matter more than differences? Recently, the argument that intraspecific differences are important and that community ecology should consider individuals has become much stronger. In “Why intraspecific variation matters in community ecology”, Bolnick et al. suggest that a species-level view of community ecology is an incomplete one, and that we should be aware of making simplifying assumptions about intraspecific variation (e.g. that it is minimal and species-level means are appropriate). Bolnick et al. state their hypothesis clearly:

  “… many models of species’ interactions implicitly assume that all conspecific individuals are effectively interchangeable. In this paper we argue that this assumption is misleading and that intraspecific trait variation can substantially alter ecological dynamics.” 

 To that end, the paper does an excellent job of identifying the key mechanisms by which intraspecific variation might be expected to alter ecological dynamics (especially as summarized in the paper's Table 1). Some of these mechanisms might be fairly ubiquitous. For example, when there are nonlinear relationships between trait values and interaction strengths, Jansen’s Inequality means that the amount of intraspecific variation around the species mean will alter the strength of that interaction. The mechanisms discussed make a convincing argument that intraspecific variation can alter ecological interactions and evolutionary dynamics.

However, a move to individual level ecology has many practical implications*: for example, it would require that we move beyond using average species-level demographic rates, dispersal abilities, and interaction strengths, since these miss important intraspecific variation; that phylogenetic trees be built to the level of the individual, requiring additional genetic information; and that perhaps fundamental changes be made to current coexistence theory. Possibly this would mean many more hours of fieldwork, more complex theory, and much more explanatory power is required. On the other hand, it could mean breakthroughs in how we understand longstanding ecological problems like ecosystem functioning, species diversity and coexistence, or trophic web structure.

For that reason, the fact that Bolnick et al. doesn’t demonstrate very clearly the gains or breakthroughs that could result from including intraspecific differences is a bit of a disappointment. Will we find that increasingly smaller amounts of variation are explained as we divide our units increasingly smaller? Or is the key to explaining community-level interactions found at the individual scale? Most of the examples in this paper are too simplistic to be useful, and for understandable reasons of space, there is little review of the literature (though they cite a number of important papers). That’s really too bad, since there are some subfields that have focused on intraspecific differences (for example, the ecosystem functioning literature), and their findings would contribute to the question of what makes intraspecific differences so promising for community ecologists. Despite that, when the mechanisms presented in Bolnick et al. are considered in combination with papers such as Crutsinger et al. 2006, Clark et al 2010, Albert et al. 2011, and Schindler et al. 2010 (just as a few examples), there is some tantalizing evidence suggesting that intraspecific variation can and does matter.

 *Although no doubt similar concerns about workload have accompanied any shift in approach throughout ecology's history. And certainly most shifts in ecological approach (spatial, phylogenetic, etc) only occur once the necessary methodological infrastructure was in place.

Google Scholar will track your citations

In case you haven't noticed, Google Scholar is now offering "My citations", which tracks citations and calculates indices for your papers. Setting it up looks straightforward and fast, making it another alternative to ISI Web of Science and other services. Let the h-index one-upmanship begin...

halloween caRd

To view the card, run the code below using R

###########################################################################

###required libraries
##if you do not have the "fields" and "MBA" libraries, you need this step to install them
install.packages("fields")
install.packages("MBA")
## load libraries
library(fields)
library(MBA)

###data
data<-matrix(c(44.9186,81.0824,46.9512,80.1061,49.187,80.7055,57.9268,80.1493,60.3659,81.34,69.3089,80.1941,78.4553,79.2459,91.8699,70.834,99.7967,55.9047,101.2195,30.9102,96.1381,17.3075,85.5691,7.4235,74.3902,4.2299,61.7886,1.8181,55.4878,1.0059,49.187,0.9811,45.3252,1.7532,37.1951,1.9181,20.3252,7.1666,8.9431,17.1612,4.2683,29.1507,4.2683,50.8042,9.5528,66.3761,18.4959,76.2539,29.065,80.6261,38.6179,80.8607,44.9186,81.0824),ncol=2,byrow=TRUE)
stem<-matrix(c(60.3659,81.34,57.9268,80.1493,49.187,80.7055,46.9512,80.1061,44.9186,81.0824,45.5285,83.6438,47.561,88.1794,44.1057,97.2209,48.7805,99.9952,54.878,87.6176,60.3659,81.34),ncol=2,byrow=TRUE)
eye<-matrix(c(45.935,46.4407,34.1463,44.8195,36.7886,46.9952,36.382,50.9306,32.3171,53.08,29.065,53.0672,26.0163,49.7086,28.0488,45.1892,20.3252,48.7021,20.1219,55.3942,23.5772,61.1164,30.8942,65.476,32.3171,59.7729,45.935,46.4407),ncol=2,byrow=TRUE)
eye2<-matrix(c(58.9431,46.6888,65.4472,51.2419,71.748,56.9754,74.3902,65.4504,82.7236,59.7745,84.9593,56.4368,84.7561,48.562,77.439,45.7772,78.8618,50.5072,74.3902,53.6393,69.9186,51.6532,68.6992,47.9083,70.5285,44.9627,58.9431,46.6888),ncol=2,byrow=TRUE)
mouth<-matrix(c(8.9431,44.7202,23.374,41.2338,30.0813,22.7562,38.2114,38.5363,65.0407,38.445,73.374,22.533,80.2846,40.8673,96.9512,44.673,93.4959,31.8641,84.1463,18.8352,66.2602,9.7097,61.9919,16.1889,59.3496,8.3045,45.5285,8.447,42.8862,16.1137,38.2114,9.4024,22.7642,17.4125,11.9919,31.7401,8.9431,44.7202),ncol=2,byrow=TRUE)
stars<-matrix(c(sample(seq(0,100),80),sample(seq(20,100),80,replace=TRUE)),ncol=2)

###plot
par(bg = "black")
par(mar=c(5,2,4,2))+0.1
plot(data,type="n",xlim=c(0,100),ylim=c(0,100),xaxt="n",yaxt="n",xlab="",ylab="",axes=FALSE)
symbols(x=stars[,1],y=stars[,2],circles=rep(0.001,nrow(stars)),inches=0.015,bg="white",xlim=c(0,100),ylim=c(0,100))
col<-runif(nrow(data),min=4,max=7)
datmb<-mba.surf(matrix(cbind(data,col),ncol=3),no.X=200,no.Y=200,extend=FALSE)
image(datmb$xyz,zlim=c(0,10),col=heat.colors(40),add=TRUE)
polygon(stem,col="darkgreen")
polygon(eye,col="yellow")
polygon(eye2,col="yellow")
polygon(mouth,col="yellow")
points(data,type="l")
mtext("Happy Halloween",side=3,col="green3",cex=3.5,font=4)
mtext("from the EEB and Flow",side=1,col="green3",cex=2.5,font=4)

Seed dispersal: plant height seems to be more important than seed size!

I really like papers that teach me something that I didn’t know. But, I love papers that show me that what I learned is wrong. This is the case of a new paper by Fiona Thomson, Angela Moles, Tony Auld, and Richard Kingsford on seed dispersal that appears in the last issue of the Journal of Ecology. This group from Australia analyzed the effects of seed size and plant height on their dispersal abilities. They reviewed intensively the literature gathering data on 200 species from 148 studies around the world. Surprisingly to me, they found plant height was much better at predicting seed dispersal than seed size. This might not sound so surprising for many people (and after seeing the paper, kind of intuitive), but there was a lot of evidence that seed size was the best predictor of dispersal, with species with smaller seeds dispersing further than species with bigger seeds. For wind dispersed species, their results are more intuitive, but they found this pattern in a number dispersal syndromes analyzed (i.e. unassisted, wind, ballistic, ingestion, and ant dispersal). So, in your next study on seed dispersal consider adding plant height as an explanatory variable.

Thomson, F. J., A. T. Moles, T. D. Auld, and R. T. Kingsford. 2011. Seed dispersal distance is more strongly correlated with plant height than with seed mass. Journal of Ecology 99:1299-1307. DOI 10.1111/j.1365-2745.2011.01867.x

The four types of failure, or how to fail in science

As scientists, we’re all wrong, at least sometimes. The question is, how are we wrong?

The arsenic bacteria saga, which we’ve discussed on this blog before, is turning out to be a very public example of failure in science. First announced by NASA press conference in December 2010, authors lead by Felisa Wolfe-Simon shared their discovery of a bacterium capable of replacing phosphorus in its DNA with arsenic, suggesting the possibility of life in phosphorus-limited conditions. This apparently momentous discovery was published in Science, and met with disbelief and severe criticism. Critics throughout the blogosphere and academic departments began to compile a comprehensive list of failings on the part of the paper—8 technical criticisms were published in Science—and as the result of the intense focus on the paper’s lead author is no longer associated with the lab group where this research was carried out. This is failure at its worst—the science was flawed and it drew immediate and intense censure. This is the kind of failure that most young scientists fear: judgment, intense criticism, career-long repercussions. But it’s also probably the least common type of failure in science.

However, it’s arguable that the saddest form of failure is the opposite of this: when a paper is right—innovative, ahead of its time—but somehow never receives the attention it deserves. There are lots of famous examples of scientific obscurity, with Gregor Mendel being the poster child for scientists who toil for years in anonymity. In ecology, for example, papers that considered species as equivalent (a la neutral theory) to explain coexistence were around in the 1950’s-1960s, but received little attention. Other papers suggesting variation in environment as a possible mechanism for plant coexistence were published prior to Chesson and Huntly's influential paper, yet essentially uncited. Most researchers can name at least one paper that foreshadows the direction the field will take many years later, yet is unacknowledged and poorly cited. There are many reasons that papers could be under recognized—they are written by scientists outside of the dominant geographical areas or social networks, or who lack the ability to champion their ideas, either in writing or in person. In some instances the intellectual climate may not be conducive to an idea that, at a later time, will take off.

If that is the saddest type of failure, then the best type of failure is when being wrong inspires an explosion of new research and new ideas. Rather than causing an implosion, as the arsenic-bacteria paper did, these wrong ideas reinvigorate their field. Great examples in ecology include Steve Hubbell’s Unified Neutral Theory of Biodiversity, which although criticized rightly for its flaws, produced a high-quality body of literature debating its merits and flaws. When Jared Diamond (1975) proposed drawing conclusions about community assembly processes based on patterns of species co-occurrence, the disagreement, led by Dan Simberloff ultimately led to the current focus on null models. Cam Webb’s hypothesis that there should be a relationship between phylogenetic patterns in communities and the importance of different processes in structuring those communities sparked a decade-long investigation into the link between phylogenetic information and community assembly. Although Webb’s hypothesis proved too simplistic, it still informs current research. This is the kind of failure on which you can build a career, particularly if you are willing to continually revisit and develop your theory as the body of evidence against it grows.

However, the most common form of failure occurs when a paper is published that is wrong, yet no one notices or worse, cares. For every paper that blows up to the proportion of the arsenic bacteria paper, or inspires years of new research, there are hundreds of papers that just fade away, poorly cited and poorly read. Is it better to fail quietly, or to take the chance at public failure, with all its risks and rewards?

The European Ecology Federation Congress, day 3

*sorry for the delay in getting the last day up, I've been catching up. The first talk of the morning was by Georgina Mace -great talk, and I will have an extended post on it later. Here are the other talks. This meeting was great!

Elisa Thebault. This was a great talk. She talked about the structure and stability of mutualistc and antagonistic networks. Nested interactions means that several generalists and specialists, but specialists use the same resource as generalists and do list overlap with other specialists. She addressed two main questions. First are there differences between mutualistic and antagonistic networks? Second, do these differences have consequences for coexistence and stability? First question, herbivores seem to have less nestedness and interact with closely related plants, while pollinators are more nested but less phylogenetically structured. For the second question, with is examined using modeling, using coupled predator prey equations (with a positive effect in the mutualism model) and simulated communities. She looked at two types of stability, persistence of species and resilience. She showed some very interesting results, for mutualistic networks, connectence and diversity increase stability, while for antagonistic, the opposite. Because of diversity change in the simulation, the mutualistic networks become more nested and more connected, again the opposite for antagonistic network, which becaome less connected and nested. What happens when you put these interactions together with both mutualistc and antagonist models? The same patterns emerge with muralists being more nested and connected.

Pedro Jordano. He talked about the functional role of complex networks including different types of seed dispersers and pollinators. Can phylogenetic relationships explain patterns of interactions between the seed dispersers and plants. In degraded habitats, through hunting, only a restribected subset of species are interacting with plants. What is the minimum complexity required to maintain ecosystem function.

Jason Tylianakis. He talked about global change and ecosystem function. In an example dataset, soil resource availability and grazing intensity affected trait compositiona dn diverisyt and changed plant productivity. When resources are heterogeneous then diversity affects function, but not when resources were homogeneous. Across a gradient of land use intensitfication, networks become simpler with functional links being dominated by few species. He looked at 133 host-parasitoid interaction webs. These webs deviate from null expectation and some habitats were significantly less complex than predicted.

Daniel Stouffer. He talk about understanding species roles and importance in food webs. Different types of interactions (sub webs) have differential probabilities of being present. Certain motifs appear to differentially contribute to stability. This approach can inform species conservation if a particular species appears in different motifs that contribute to network function or stability. Certain species may be common in motifs that reduce stability. Using New Zealand river food webs, he asked three questions: is the benefit of species phylogenetically conserved -yes, certain clades add benefit. Are these benefits community specific? No, beneficial species are so in all communities (bit similar communities). How general are these results? He compared the results to webs elsewhere in the world. Similar species are similarly beneficial elsewhere.

-Here I lost my notes from Jane Memmott’s plenary talk (sorry Jane!). It was a great overview of her research in restoration. At the heart of her talk was about making restoration scientifically rigorous.

Henrique Pereira. His talk was on modeling the response of biodiversity to global change. Biodiversity indicators for global change are biassed towards North America and Europe and certain taxa. Major uncertainty in extinction rates and what are the sources of uncertainty? A big source is the differences in scenarios for land change and human population growth. Also lack of ecological knowledge. Finally there are differences between models. He proposes a countryside species area relationship (cSAR) instead of regular SAR, which assumes an uninhabited matrix. Multiplies area by the affinity of species to live in that area, and so as long as a species has an affinity greater than zero for marginal habitat, it can persist in those areas –changing our predictions about habitat loss on species persistence. The cSAR predicts much lower extinction rates compared to classical SARs. Need data to classify affinities, such as uses surveys to cluster species by where they are found. The cSAR fits real data better than SAR.

Christophe Randin. His presentation was on whether elevational limits of deciduous trees match their thermal latitudinal limits. Species often not at equilibrium with their predicted fundamental niche, may reflect dispersal limitation. Species should reach their equilibrium since climate change so much quicker. Based olots of data, he presented where the distributional limitation should be and examined the distance from that edge. Surprisingly, the latitudinal limit was less likely to be reached by. Species, thus they are lagging on mountains.

Rita Bastos. She used a Dynamic model for understanding the recovery of the Azorean bullfinch in a changing environment, a lot a land use change and invasive species. Specifically, the model is a stochastic, spatially explicit model that incorates environmental variables and projected habitat change. She was able to test different management scenarios. Certain management actions on habitats can significantly increase population sizes but not spread.

Diogo Alagador. He spoke on adjusting protected areas to account for climate range adjustments. Species will move with climate change, but reserves do not move. Planning must involve multiple potential reserves and likely assisted migration. It is difficult to extrapolate for multiple species. Persistence then is the product of suitablility and dispersal ability for a species for each time period in future projections. This can be summed across species. This was tested for seveal species across all major taxa. There is variability in persistence across species and are very sensitive to disperal pathways.