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.

Thursday, December 1, 2011

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.

Thursday, November 17, 2011

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...

Thursday, October 27, 2011

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)

Wednesday, October 12, 2011

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

Tuesday, October 4, 2011

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?

Sunday, October 2, 2011

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.

Tuesday, September 27, 2011

The European Ecology Federation Congress, day 2

Day two of the conference, and still many great talks. I mainly stayed in the session on synthesizing community ecology, phylogenetics and macroecology. This has turned out to be a great conference and Avila is a great venue.


Carsten Rahbek. His talk is on merging the fields of macroecology to better understand patterns of diversity. Different models explain variation differentially at different scales. For example, climate models do well for wide-ranging species but not for scarce species. A model of evolution may do much better for scarce species, but not for wide-ranged species. Statistical tests confirm a correlation, but not necessarily a mechanism. One could get different conclusions if one were to compare to a null model. He advocates a spatially explicit species assembly model that integrates macroecological models with community assembly. It is scale invariant and can explain spatial and temporal variation in assemblages. In an example, he shows that, based on small scale sampling, species distribution models will over-predict richness. Need to combine macroecological models with distribution models, because acroecological models do well to predict richness but not composition while distribution models predict composition but not diversity.


Jens-Christian Svenning. He talked about paleoclimatic influences on ecological patterns and function across scales. Past climates have shown masive changes and different groups of species have evolved during these events, while other species have gone extinct. The velocity of climate change was highest in northern Europe and North temperate North America, and higher velocity results in lower endemism since it is quicker for species to migrate than diversify. Higher velocity results in lower specialization in hummingbirds. He finishes with a note about current regions undergoing fast climate change; these are not necessarily those same regions that had the most change in the past.


Adreas Prinzing. His talk was about how niche conservatism can inform our potential solutions for changing environments. Specialists are declining in changing environments and how does this apply to specialist clades of closely related species? Specialist species tend to occur in specialist genera. However, niche conservatism does not tell us everytng about species differences/similarities because closely related species clearly coexist and exhibit substantial trait differences. Species coexist within niches by key divergences.


Kenneth Kozak. He presented a way that phylogeny illuminates the origin of climate-richness relationships. Only speciation, extinction or dispersal can change richness, and many models do not ask how these processes change. He examined salamader diversity and evolutionary history using 16000 occurrence records in North America, and examined climate variables for occurrences. Diversity was highly associated with cool, moist places. Richness is strongly correlated with evolutionary time of colonization of climatic conditions. For example, evolution of warm species is recent, hence fewer species. Diversity does seem to be saturating, and so time is limiting factor, and more species can probably still emerge.


David Vietes. He gave an interesting talk on the amphibians of Madagascar, which is a diversity hotspot for amphibians. There were 132 described species n 1999 and now 263 with about 200 still needing to be described. Many are endemic to small regions of Madagascar (the whole family is endemic to Madagascar). He discussed many aspects of the distribution of these species, and looked at phylogenetic patterns. Some interesting observations include: older species pairs are further separated in space and smaller species have smaller ranges. Also, there appears to be a predictable pattern of richness hotspots, but endemism hotspots are more idiosyncratic.


Joaquin Hortal. He discussed the effect of glaciation on richness, functional diversity and phylogenetic diversity for European mammals. The hypothesis he explored was that current distributional patterns driven more by past changes since glaciation than current climate. He compare several different types of measures and it turns out that current climate is more important for explaining patterns of co-occurrence and relatedness, with more closely related species occurring together at northern locales.


Catherine Graham. She also explored patterns of richness, functional and phylogenetic diversity, but was looking at hummingbirds diversity patterns across elevation gradients in South America. She compiled an impressive dataset with several morphological traits and co-occurrence patterns. Broadly, close relatives co-occur at high elevations and more distantly at lower where competition is stronger. In local communities a mix of environmental filtering and competitive dispersion seem to be operating. At high elevations, both functional and phylogenetic diversity are high.


Rob Dunn. He gave a fantastic talk on the species on the human body and in our lives and homes. He told us about projects that involve citizen scientists from across the USA and had them sample their homes and bellybuttons. Amazingly, Dunn’s group has so far identified 1400 species in belly buttons, and many of them are unknown species –which could not be classified into known species groups. He looked at many factors like ethnicity, geography, cleanliness, but none of these explained this diversity well. A subset of these species are bellybutton specialists and dominate bellybutton floras within and among people, and are phylogenetically clustered, evidence that the bellybutton habitat is a conserved trait.


Cecil Albert. I ran to another session to see this talk on intraspecific variation in species traits. She eloquently showed that for plant assemblages, there was substantial intraspecific variation in traits. Some species showed high variation and some showed almost no variation. Importantly, she showed that this variation could substantially change our ability to explain how functional traits link to abundance and coexistence. She simulated different levels of variation and looked at the strength of the correlation between expectations from mean trait versus the actual trait that varies. The strength quickly declines for some traits as variation increases, meaning that with variable traits, the explanatory ability of using a mean trait is weak.


Sally Keith (Flash talk*). She examined the Mid-domain effect (where, because of range sizes, maximal diversity is found in the centre of a geographic landmass by random chance), and process based models to test mechanism for middomain prediction. She showed that these models seem to have limited success. Perhaps environmental gradients and species interactions could be important. But when she added interactions to the model, it then predicts humped shaped pattern predicted by the mid-domain effect.


Tamara Munkemuller (Flash talk). She examined phylogenetic relationships as a way to examine niche patterns and coexistence. She hypothesized that there should be strong filtering under stressful conditions. She examined thousands of plots across elevational gradients, and plots that were in stressful locations tended to be phylogenetically clustered, meaning certain groups of species exist there.


Susanne Fritz (Flash talk). She was looking at diversification patterns in birds. Using lineage through time plots one should expect that the rate of diversification should decline trough time, which perhaps equates to niche filling. For species in tropical Asia, she found that there is not much leveling off of diversification rate. Though interestingly, groups that have not dispersed (for example, birds of paradise) do show a plateau in diversification. Globally, diversification slows down more in more speciose regions.


Jake Alexander (Flash talk). He had a very interesting talk on elevation gradients in richness in non-native plants invading mountain habitats. Most species have narrow elevational ranges in lower and mid elevations and high ranges for those species found at high elevations. The explanation is that these non-natives are generalist and that they originate form lower elevations –where human activity dominates, and must spread up the mountain to get to the high elevations.


*Flash talks are 3 minutes long, and a great way for people to communicate new and exciting results.

Monday, September 26, 2011

The European Ecology Federation Congress, day 1

I’m in the beautiful walled city of Avila, Spain for the European Ecology Congress. It is at a lovely venue and with about 800-1000 attendees, seems like just the right size. It is a young meeting, with relatively few old-timers like me, but there is an excitement, and the talks have been excellent. Each session starts with a keynote, where the person gets 25 minutes, followed by a bunch of 15 minute talks. The most interesting aspects of the sessions I went to was that they usually include several 3-minute ‘flash’ talks, which surprisingly works. I spent the day going to talks in two sessions, plus a plenary talk by Jordi Bascompte, and here are the talks I saw*:


*sorry about the abrupt, choppy nature of some of the entries, there were a lot of talks, and they go until after 7pm.


I spent the morning in a session on biodiversity and ecosystem function under environmental change. Most of these talks we by people associated with the BACCARA project on forest biodiversity.


1) Xavier Morin, Montpellier, talked about climate change and tree diversity and productivity. Looked at SR (see glossary at end for acronyms) and FD on biomass produced. Do grassland BEF studies predict frost ones, with no opportunity for random assembly? Use forest dynamics model where species are defined by rigorous parameterization –one can examine long-term dynamics and many species combinations. Simulated 30 species monocultures and many combinations from 2-30. Strong relationship between realized richness and productivity, but a lot of variation. 93% of 30 species plots show transgressive over-yielding after 2000 years. FD predicts increase in productivity. Assess future climates from three climate change scenarios, always steeper slope with future climate, meaning diversity is more important in the future. This was a great talk.


Sibylle Stoeckli. Affects of diversity on individual tree performance. She wanted to assess the influences of tree traits (e.g., size) on the performance of neighbours. Plots planted with four species combinations, with a pool of 16 species, and treatment is different FD levels (based on 9 traits). No effect of plot diversity on tree performance. Tree height has effects on neighbours depending on whether focal tree is shade tolerant or intolerant. Diversity not important as traits of species such as growth rate. Interspecific competition lower than intraspecific.


Aitor Ameztegui. Montane-apine ecotone is diverse and are traits important for coexistence. Are interspecific differences key for coexistence, and can these tell us about biome changes. One species has advantage at low light but quickly saturated with increasing light. Silver fir had constant survivorship, while other species increased survivorship with increasing light. Fir has low plasticity, whereas Scots pine is more plasticity and should adapt to climate change.


Alfredo saldena. FD on decomposition in South American rainforest (Chile). He looked at two forest types within the Andes. In both forests strong positive relationship between FD and litter decomposition. FD is based on leaf traits.


Julia Koricheva. Forest diversity and insect communities. Boreal species (5) in southern Finland in monocultures and 2, 3 and 5 species mixtures. Looked at different types of leaf damage. For birch, increasing skelontonizing damage with diversity. During aphid outbreak, decline in density with increasing SR. They prefer birch. Leaf miner richness on birch increased with SR. In another, german, experiment (the experiment in Stoeckli's talk) where FD was manipulated. Again several types of herbivores had positive relationships with FD, again counter to expectations of more specialized herbivores declining with tree diversity.


Laura Concostrina-Zubiri. Biological soil crusts (BSC) are important for soil fertility and stability in dry ecosystems. creates soil heterogeneity. Examined the role of BSC across a grazing gradient. Measured 17 soil variables for a bunch of species. Species differ in their different soil fertilities. Less heterogeneity with higher grazing. Grazing also reduces individual species contributions to soil fertility.


Plenary talk: Jordi Bascompte. Plant-animal mutualistic networks. He talked about Global datasets to answer three questions: 1) are there regularities in network architecture; 2) Do these provide robustness to extinction; and 3) what are the contribution of species to network architecture and robustness? Networks seem to be nested such that specialist animals use most utilized plants. This means there should be a link between structure and robustness (losing an aminal should not result in plant extinction). Half of communities have interactions dictated by evolutionary history. Thus when there is extinction, it tends to be related species, nonrandom. Therefore clades are more likely to be lost. How much of the interactions that are shared can be used as a competition term in coexistence model. The higher the nestedness the lower the competition and the higher maximum diversity. Some species contribute to nestedness much more than others and therefore are much more responsible for stability and have greater probability to go extinct.


I spoke in a session on evolutionary history, ecosystem function and conservation, and (probably ignoring my talk) these were excellent.


Marten Winter. He asked whether phylogenetic studies purporting to do conservation actually did conservation and whether using PD was feasible. Assumptions, some not proven. Unsderstandability of terms like evolutionary potential, what that means for species and communities can cause confusion. Different measures can produce different patterns and he asked Don't we already conserve what we want? Or is there an added advantage to accounting for PD. There were a surprising number of papers that do make conservation recommendations.


Nicolas Mouquet. Phylogenetic constraints on BEF. Biodiversity crisis is a change for synthesis for diffect fields to come together. Positive relationships went from how much to what kind diversity. Evolution is necessary for understanding how biodiversity shapes ecosystem function. He tested these relationships with bacteria from Mediterranean and evolved in lab. There are ancestral and derived groups. Strong positive BEF relationships for both ancestral and derived taxa. For ancestors, a strong PD influence was observed. But not for derived taxa, a reshuffling of traits in the lab. Need to understand the history.


Ana Rodrigues. Species are not all the same such as mouse versus echidna. Need to be cognizant of tree structure and species distributions. Does it matter if we use PD for complimentary reserve design and compare maximizing PD vs SR vs random. SR conserved then look at PD. Little difference for mammals at global level, meaning that current reserve selection routines seem sufficient. Important for species level, but perhaps species level activities may have done a good job at conserving PD.


Sandrine Pavoine. Rockfish declines and phylogeny. Phylogenetic diversity based on period between speciation events. Sum abundances for lineages for each period. Sum period lengths times relative abundance. Calculate lineage contribution to total diversity. Which period is reponsible for abundance change. One period explained declines in rockfish and is actually quite an old period (6 million years).


Wilfried Thuiller. Preserving the tree of life and climate change. Are there winners and losers? Estimate phylogenetic consequences of climate change, if there are sensitive clusters, would one expect more loss than expected by chance. There is a phylogenetic signal in climate, kind of weak, but extremely close relatives respond similarly. Loss of PD is not much different than random. Sensitive species tend to be young. But there is a predicted loss of phylobetadiversity for all birds, mammals and plants with climate change.


Vincent Devictor. Comparing several components of biodiversity. Can SR, FD, PD serve as surrogates. Compared metrics using birds surveys in France with 22 traits. Abundance weighted measures. FD declining while SR increasing. Differential responses important for making conservation decisions.


Laure Turcoti (Flash talk 1). Comparison of SR FD PD on plant communities. SR increases with urbanization and FD and PD decrease with urbanization.


Laure Zupan (Flash talk 2). Current distribution of phylogenetic diversity. Covariation across different clades. Birds, amphibians and mammals. Mismatch between tax am amphibians high PD relative to SR, while mammals low.


Jonathan Davies. Plant extinction risk in the Cape using IUCN rankings. Genera level phylogeny for the over 700 genera in the Cape. Clustering of extinction risk on phylogeny, but plant extinction is correlated with clade size, meaning that large clades have more risk –opposite of what has been observed for mammals. The reason is that many small peripheral species with small range.


Sebastian lavergne. Dechronization of niches, i.e., travel back in time. Is there signal of niche conservatism, and for different niches for the birds for Europe. Climatic, habitat and trophic niches. Trophic niche evolves at slower rate but niches evolve in punctual way, not gradual. High clade disparity in niches since niches evolving faster.


Glossary

BEF: Biodiversity and ecosystem function

FD: Functional diversity

PD: Phylogenetic diversity

SR: Species richness

Friday, September 23, 2011

NSF funds Project Baseline

NSF approved 1.2 million dollars for a unique and visionary idea: collect 12 million seeds and store them in seed banks for years to come. And while storing seeds for the future doesn't sounds so different from what other groups have already done, where Project Baseline differs is that this seed bank is not only a conservation measure--preserving natural genetic variation from plant populations for the future--but also an opportunity to track the effects of changing climate on the direction and rate of evolution in these species.

This idea was first explored in "The Resurrection Initiative: Storing Ancestral Genotypes to Capture Evolution in Action" (Franks et al 2007). By collecting and storing seeds from both within and across populations throughout the range of a species, ancestral and descendent populations can be compared in the not too distant future. The role of adaptive evolution and range shifts can be explored through this lens. Project Baseline is a great example of how much we can learn from long-term, collaborative experiments and projects (other examples include NutNet , NCEAS), and how valuable funding such projects should be considered.

Friday, September 16, 2011

Ecology needs more evolution (and vice versa)

One historical weakness in community ecology is its singular focus on ecology in the absence of any consideration of the role of evolution. Ecological theory may attempt to explain and expand on mechanisms of coexistence, but this is done in ignorance of whether such a mechanism could have reasonably evolved in the first place. Evolutionary biology has equally ignored the role of ecology (for example, just-so stories invented in the absence of ecological support). Fortunately, it is becoming more common to see papers that incorporate, empirically or theoretically, evolution and community ecology.

A recent paper by Robin Snyder and Peter Adler attempts to incorporate both ecology and evolution in reference to the storage effect, a mechanism in which species coexist as a result of environmental variability and corresponding differential variation in species fecundity in response to the environment. As a simplistic example, consider a system of two annual plants for which each species has their highest recruitment at different temperatures, and temperature varies randomly between years. Each species is expected to have high recruitment in different years/environmental conditions, and this high recruitment in good years can then buffer that species’ fitnesses in years of poor conditions, provided the species have some way of “storing” fitness (such as long-lived seedbanks). The storage effect therefore predicts that environmental variability can mediate the coexistence of otherwise unequal competitors. Because the requirements of the storage effect appear so ubiquitous (environmental variation, differential species responses to the environment, some sort of buffer), it seems that the storage effect could be very common. However, there is also theory suggesting that variation in demographic rates should come at a fitness cost, since the long term mean growth rate will be lower if demographic rates vary than if they are fixed (as the result of geometric averaging). This predicts that there should be selection against flexible—rather than fixed—demographic rates, including rates that vary in response to environmental or other cues. Is it possible then for variable demographic rates, which are necessary for the storage effect, to evolve?

Snyder and Adler discuss this disconnect between community ecology and evolution, questioning whether the storage effect can be supported by both evolutionary and ecological theory. To this end, the authors explore whether, and under what conditions, the storage effect could evolve. Snyder and Adler use a simple model of competition between two annual plants, in which fecundity fluctuates due to environmental variation, and germination rate can be temporally fixed, or variable. Germination rates should be constant, despite environmental variation, due to the cost of variability. Germination rates would be expected to vary year to year only if this conferred a fitness benefit to the species. Hypothesized benefits of variable germination rates include if germination rates are positively correlated with fecundity (that is, in good years germination is higher as well), or if it allows a species to avoid competition (by having high germination when their competitor has low germination). To test this hypothesis, the authors varied the correlation between fecundity and germination, and the correlation between the two species’ germination rates. They then examined the conditions under which variable germination rates were an evolutionarily stable strategy (ESS).

Snyder and Adler’s results suggest that the storage effect is expected to evolve only under anarrow set of conditions. A variable germination rate was most likely to evolve if there was a strong correlation between fecundity and germination rate. They note that such a correlation might occur if seed production and germination depended on similar environmental cues or similar resource requirements. A variable germination rate was also a stable strategy if one species was limited in its ability to evolve, in which case the other species evolved variable germination rates. If these specific conditions didn’t hold, the storage effect was not evolutionarily stable.

These results are meaningful because they highlight how different the conclusions of community ecology, which has proposed that the storage effect could be a widespread contributor to coexistence, and evolutionary theory, which suggests that the storage effect may only occur under particular conditions, can be. This kind of reconciliation of community ecology and evolution tells us more about natural systems than either approach can on its own. It also hints that theory and conclusions we’ve drawn in community ecology in the absence of evolution may be limited and incomplete.

Wednesday, September 14, 2011

BES day 2: Plants, plants and way more plants

From Sept 13


I attended the Journal of Ecology Centenary symposium all morning, where the talks were broad overviews of select areas in plant ecology. They were quite good; I really do feel that I was informed about recent research advances.


In the first talk of the morning, Sandra Lavorel gave a tour de force about how plant functional traits scale up to ecosystem services. She recognizes that there are trade offs in services, where one service (say agricultural value) is in direct conflict with a noter service (say species richness). She very cleverly asks whether these services are constrained by ecological trade offs or traits. It is known that functional traits affect ecosystem functions and services, and it is also known that there are strong tradeoffs in plant traits such as explained by the world wide leaf economic spectrum. Where plants have these tradeoffs they affect productivity and litter decomposition. Height for example affects productivity and other trophic levels supported. Abiotic gradients affect traits like height or leaf N, and these traits affect ecosystem function such as biomass or litter. Multiple service such as agronomic value, pollination, cultural value, richness, etc. To understand how traits relate to tradeoffs in services.


Next was Angela Moles who talked about how the study of invasions has progressed and whether there were important future directions. The have been 10,000 studies on invasions over the last 30 years and she recognizes that the fact that species evolve in their new ranges to be a critical future research need. Specifically, she asked: do exotics evolve to be more similar or different tha natives? And, can differences be predicted by environmental differences between home and away range. Most interestingly she brought up the point that if on-going change produce new species, should they then be conserved as natives? She went on to say that broad generalizations about trait differences between natives and exotics have produced largely idiosyncratic results, and so other priorities such take the forefront. She went on to say that impact on natives is actually an understudied problem, which needs to be rectified. Finally, she showed us that there is a generally positive relationship between disturbance and invasion. But invasions are favored when there is a change in disturbance rate, since natives are likely adapted to historical disturbance regime. She showed some relatively weak evidence that change in disturbance better predictor of invader richness and abundance then the amount of disturbance, but more work is needed.


Yadvinder Malhi talked about how productivity and metabolism were related to biomass in tropical forests. He sowed us that a small proportion of primary production is turned into biomass. Thus small changes in various pathways could have large consequences. In exhaustive studies in the tropics, he showed that increases in GPP (gross primary production) occurred with soils nutrient quality, and decreases with elevation, likely because of temperature effects on photosynthesis. He also showed that carbon use efficiency is lower than thought, about 30% of carbon turned to biomass. Further, higher productivity is associated with lower residence times, and he hypothesized that rapid growth leads to earlier senescence or less defences if trade offs exist. Biomass appears to be increasing with climate change, but potentially greater mortality and turnover.


Then James Bullock talked about where we are at with understanding seed dispersal. There has been a long history of not understanding long distance dispersal, LDD. The main empirical approaches have grown rapidly lately: tracking seeds, molecular methods and marking seeds or to track dispersers. But at the same time spread models have appeared and advanced. However, Bullock really supports mechanistic models for wind-dispersed species, and these models seem to really provide insights. He then compared a handful of models for invasive and scarce natives, and did mechanistic modeling with climate change. Changes in future wind speeds may result in even larger changes in spread rates. Only Ailanthus appears to have dispersal rates at or faster than the rate of climate change, most species do not appear to be able to move fast enough (except animal dispersed species). Movement on shoes major dispersal vector.


Hans Jacquemyn was the final speaker, and talked about evolution and habitat fragmentation. He studies calcareous grasslands, forests and heathlands in Belgium that have increasingly become isolated and fragmented. Observed declines in genetic diversity in populations, as they get smaller in size. More recent fragmentations have less loss of genetic diversity compared to older fragments. Reduced seed output in small populations for self-incompatible species, results in reduced population growth rates. To counteract plants can increase floral displays or increase selfing rates, which they observed. Also, he has observed changes in timing of flowering and investing more in nectar.


*Some thoughts about the BES. It is a great Society, and a great meeting. It is relatively small and it is nice to see how many members know each other. For those of us in North America, I think it is a great experience to go to one of these meetings.

**I also participated in the BESdigital workshop on communicating science in a digital era. I will have a post about this tomorrow –I've been without internet connection at both the Sheffield dorm and various airports.

Monday, September 12, 2011

British Ecological Society meeting: day 1, the Tansley Lecture by Diane Wall

I am at the BES meeting in Sheffield. I will be spending most of the day in journal meetings, but I was able to attend the opening lecture. I will be able to attend more talks tomorrow.

Diana Wall gave the Tansley Lecture to open the meeting. The focus of her talk was about integrating soil biodiversity into ecosystem science. She started with a quote from Arthur Tansley about how all the aspects of an ecosystem can not be ignored, and Professor Wall argues that type soils, specifically the organisms living below ground have been largely ignored, and we do now live in an era where we can study all aspects of ecosystems. Her talk showed the ways in which soil orgasims matter and how global change may have consequences for the link between soil organisms and the ecosystem functions they provide.

This is especially important because soils are deteriorating globally, and while soils are home to an impressive diversity of organisms, so little understood about these organisms. Often we do not even know how many species are found in soils (though in many cases we are talking about hundreds or thousands of species per square meter, which means we can cannot predict how global change could affect these biota and the functions they provide.

She went through three examples to highlight the importance of soil organisms and research needs to predict the impacts of global change (here global change seems broadly defined including: temperature, precipitation, land use, and water flow). In the first example, she reviews the role of soil organisms in extreme ecosystems (Antarctic and hot desert) and how climate change may alter dynamics. Experiments show how important soil organism are for flow of nutrients and energy, and global change experiments show drastic changes in their abundance, thus we should expect large consequences as environments change, especially as moisture regimes change. In different systems, the relative importance of biotic vs abiotic drivers (e.g., the presence of plants versus moisture gradients) differs and differentially important for the ecosystem effects, and so more understanding is required for predictions.

In the second part, soil animals affect soil decomposition in moist places, thus changes in moisture affect ecosystem pathways. In the third part, she outlines the ways in which soil organisms provide ecosystem services, nutrient cycling, diseases, food, food webs, biocontrol, carbon storage, waster breakdown, etc. These services have been understudied and under appreciated.

Overall this talk was a lucid and poignant call for more work to be done on soil biota -not to know what is there necessarily, but rather to be able to link together the effects of changing environments on ecosystem function.

Thursday, August 25, 2011

How is a species like a baseball player?

Biomass is to runs as species is to player, and as ecologist is to Brad Pitt.

Community ecology and major league baseball have a lot to learn from each other.

Let's back up. As a community ecologist, I think about how species assemble into communities, and the consequences for ecosystems when species disappear. I'm especially interested using traits of species to address these issues. For the grassland plants that I often work with, the traits are morphological (for example, plant height and leaf thickness), physiological (leaf nitrogen concentration, photosynthetic rate), and life history (timing and mode of reproduction).

As a baseball fan, I spend a lot of time watching baseball. Actually, I'm watching my Red Sox now (multitasking as usual; I freely admit there's a lot of down time in between pitches). I care about how the team does, mostly in terms of beating the Yankees. I'm especially interested in how individual players are doing at any time; for fielders I care about their batting average and defensive skills, and for the pitchers I care about how few runs they allow and how many strikeouts they get.

So my vocation and avocation have some similarities. Both ecology and baseball have changed in the last decade or so to become more focused on 'granular' data at the individual level. In ecology this has been touted as a revolutionary shift in perspective, but is really a return to the important aspects of what roles organisms play in ecosystems, and how ecosystems are shaped by the organisms in them. This trait-based approach has shifted the collection and sharing of data on organism morphology, physiology, and life history into warp speed, to the great benefit of quantitatively-minded ecologists everywhere.

In baseball, the ability to collate and analyze data on every pitch and every play has lead to an explosion of new metrics to evaluate players. One of the simplest of these new metrics, which even the traditionalists in baseball now value, is "on base plus slugging" (OPS, see all the details here). This data-intensive approach to analyzing player performance was most famously championed by the manager of the Oakland Athletics in the late 1990's, now being played by Brad Pitt in the upcoming movie Moneyball.

There is no one ecologist in particular who can claim credit for popularizing trait-based approaches in community ecology, but for the sake of laughs let's make Owen Petchey the Brad Pitt analogue.

What can we do with this analogy? For pure nerd fun, we can think about what these two worlds can learn from each other.

What can baseball learn from community ecology?

One of the most notable trait-centric innovations in community ecology has been the use of functional diversity (FD), which represents how varied the species in a community are in terms of their functional traits. Many flavors of FD exist (one of which was authored by Owen Petchey, above), but the goal is to use one value to summarize the variation in functional traits of species in a community. A high value for a set of communities indicates greater distinctiveness among the community members, and is taken to represent greater niche complementarity.

For fun, I've taken stats from a fantastic baseball database[i] and calculated the FD of all baseball teams from 1871 to 2010. I used a select set of batting, fielding, and pitching statistics[ii], and you can see the data here. For the two teams that I pay the most attention to, I plotted their FD against wins, with World Series victories highlighted:

Given that these FD values represent how different the members of a team are, it's surprising that there is much of a pattern at all. But the negative relationship between wins and FD is strong and significant by several measures[iii]. So: the more similar a team is in terms of player statistics, the better the team does!

This pattern of less dissimilarity among players correlating with better performance at the team level has apparently been noticed before, by Stephen Jay Gould, who extrapolated this pattern also across teams to explain the gradual shrinking of differences among players over time:

"if general play has improved, with less variation among a group of consistently better payers, then disparity among teams should also decrease"

and so:

"As play improves and bell curves march towards right walls, variation must shrink at the right tail." (from "Full House", thanks to Marc for this quote!).

Interesting, but is it useful? One obvious drawback in this approach of examining variation in individual performance is that it ignores the fact that in baseball, we know that a high number of earned runs allowed is bad for a pitcher, and a low number for hits is bad for a hitter. In contrast, a high value for specific leaf area is neither good nor bad for a plant, just an indication of its nutrient acquisition strategy.

There are many exponentially more nerdy avenues to go with applying community ecology tools to baseball data, but I'll spare you from that for now!

What can community ecology learn from baseball?

One new baseball stat that gets a lot of attention during trades is 'wins above replacement'. This is such a complicated statistic to calculate that the "simple" definition is that for fielders, you add together wRAA and UZR, while for pitchers it is based off of FIP. I hope that cleared things up.

The point in the end is to say how many wins a player is worth, when compared to the average player. In ecology, the concept of 'wins above replacement' has at least two analogies.

First, community ecologists have been doing competition experiments since the dawn of time. The goal is to figure out what the effect of a species is at the community level, although fully factorial competition experiments at the community level are challenging to carry out. For example, Weigelt and colleagues showed that there can be non-additive effects of competitor plant species on a target species, but could rank the effect of competitors. This result allowed them to predict the effect of adding or removing a competitor species from a mixture, in a roughly similar way to how a general manager would want to know how a trade would change his or her team's performance.

Second, ecologists have shown that both niche complementarity and a 'sampling effect' are responsible for driving the positive relationship between biodiversity and ecosystem functioning. The sampling effect refers to the increasing chance of including a particularly influential species when the number of species increases. Large-scale experiments in grasslands have been carried out where plants are grown in monoculture and then many combinations, up to 60 species. The use of the monocultures allows an analysis similar in spirit to 'wins above replacement', by testing how much the presence of a particular species, versus the number of species, alters the community performance.

We could take this analogy further, and think of communities more like teams. A restoration ecologist might calculate 'wins above replacement' for all the species in a set of communities, and then create All Star communities from the top performers.

Lessons learned

A. Shockingly, there are baseball nerds, and there are ecology nerds, and there are even double-whammy basebology nerds.

B. There are quantitative approaches to analyzing individual performance in these crazily disparate realms which might be useful to each other.

C. I might need to spend more time writing papers and less time geeking out about baseball!

More analogies to consider:

Reciprocal transplants: trades?

Trophic levels: minor league system?

Nitrogen fertilization: steroids?


[i] One of the most astonishing databases around: complete downloadable stats for every player since 1871. This database is what NEON should aspire to be, except that this one was compiled completely privately by some single-minded and visionary baseball geeks!

[ii] Batting: Hits, at bats, runs batted in, stolen bases, walks, home runs

Fielding: Put outs, assists, errors, zone rating

Pitching: Earned run average, home runs allowed, walks, strike outs.

[iii] E.g. even after taking into account other more typical measures of success in offense (runs, R) and defense (runs allowed, RA), within years, there is still a negative slope for FD on wins:

lme(win ~ R + RA + FD, random = ~1|yearID, data = team)

Value Std.Err DF t-value p-value

(Intercept) 80.289 0.7411 2159 108.3 <0.001

R 0.107 0.0009 2159 116.8 <0.001

RA -0.105 0.0009 2159 -115.6 <0.001

FD -1.729 0.8083 2159 -2.1 0.0325