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.

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

Day 5 in Austin

The ecological community in Austin assembled for the final morning of talks today, and despite the advanced stage of the conference, the 8 o’clock talk I was at was surprisingly well-attended. There was only a morning worth of talks, but frankly, the Community Pattern and Dynamics session I attended had some of the most interesting talks I’d seen all week.

I started out in the Aquatic Terrestrial Linkages section, where Tiffany Schriever introduced me to the concept of spatial subsidies (the transfer of energy from one system to another), and described her system-temporary ponds in Ontario, Canada-in which the dual aquatic and terrestrial nature of the pond amphibian and insect life cycles couple aquatic and terrestrial systems.

Although I arrived late for Rafael D’Andrea’s talk in this session, it seemed that he did an excellent job of presenting ecological models, making his question and results both clear and interesting. He examined how tradeoff models, such as Muller Landau’s seed tolerance vs. seed fecundity model, predict far less diversity can be supported when the tradeoff changes smoothly rather than abruptly.

Nathan Sanders then explained his shift from primarily place-based research to global, macroecological studies. However, Sanders acknowledged the common criticisms of the macroecological approach, in that patterns are not necessarily evidence of mechanism, and has attempted to reach a compromise between the benefits of the two approaches. To balance place-based with global approaches, Sanders and his collaborators form a global network of researchers who are carrying out the same manipulative experiments (looking at resource limitation in ants) across different systems worldwide, and the results promise to be exciting.

In the final talk in the session, Steve Walker from the Legendre lab presented his approach to dealing with the “fourth corner problem”, that is relating species traits to environmental conditions. Rather than developing new approaches for analysis, Walker has focused on approaching this problem via data management. In particular, he has developed an R package (beta available here) called multitable in which data with different dimensions (such as a site-by-species matrix and a trait-by-species matrix) can be subscripted simultaneously, and coerced into a single data frame for use in standard R functions.



All in all it was a great week, and I’m excited to get back to work and feed off the energy of the conference. ESA gave me a chance to meet some of my favourite ecology bloggers, including Ethan White and Morgan Ernest from Jabberwocky Ecology and Jeremy Fox from the Oikos blog. It made me wonder whether there might be room next year for a more formal meeting of these online colleagues, whether in a loosely organized sense, or even as a workshop or symposium focused on the how ecologists can use (and are using) new technology—especially the internet—to communicate their science. If anyone has any comments or thoughts about whether there would be a role for something like this at ESA, I'd be happy to hear them.

See you in Portland, one year from now!

Day 4

As the fourth day of ESA sessions began, it was clear that many attendees’ (including my own) energy was flagging, and 8:00 am talks were more sparsely attended. However, this didn’t mean that the presentations were of any less quality or interest. In the face of so many competing talks, I took the path of least resistance, in that I chose an interesting-sounding session, and stayed put. Today, that meant that I saw much of the Community Pattern and Dynamics IV session, and some talks in the Invasion: Invasibility, Stability, and Diversity session.

Thursday poster session

The early morning portion of Community Patterns and Dynamics provided some interesting talks focused on diversity in aquatic ecosystems, in particular ponds. Schalk et al. examined how the community structure of tadpoles related to environmental gradients in Bolivia, in particular how tradeoffs in pond permanency, predation, and canopy cover determine the tadpole species present. This talk proved that frog ovipositing behaviour can be fascinating, and provided the first example I've seen of a mule-aided sampling strategy (the mule transported supplies).

Jamie Kneitel reminded us that aquatic ecosystems, and the functions and services they provide, are under threat. One issue is human-driven increases in turbidity. To examine the impacts of turbidity, and how these impacts may differ depending on the underlying cause – turbidity may be cause by input of resource, leading to eutrophication, or directly, such as via cattle trampling in pools—Kneitel used experimental mesocosms meant to simulate vernal pools. He showed that different causes of turbidity conferred different types of changes in water chemistry, and that turbidity had different effects on vegetation and invertebrate communities.

Moving to the Invasion: Invasibility, Stability, and Diversity session, Jiaqui Tan from Lin Jiang’s lab gave a very interesting talk about the oft-observed negative relationship between invasibility and diversity. In particular he connected the suggested explanation for this pattern (the sampling effect and the niche complementarity effect) to phylogenetic patterns of relationship between species. He predicted that increasing phylogenetic relatedness would increase the sampling effect, while increasing phylogenetic diversity would increase niche complementarity. Using microcosms of aquatic bacteria, in which Serratia marcesens acted as the invader, he looked at how a factorial design of low, medium, and high phylogenetic relatedness and phylogenetic diversity effected invasibility of the bacterial communities. Perhaps surprisingly, phylogenetic diversity had only a little effect on the degree of invasibility, but phylogenetic relatedness strongly decreased invasibility. However, an explanation for these results was made more difficult by the fact that the 57 traits he measured for the bacteria showed little evidence of niche conservation.

At the same session, Karen Alofs shared some preliminary analysis of a fantastic dataset showing changes in the presence of introduced smallmouth bass over 30 years in Ontario, Canada. Ontario is a place where southern and northern range limits of many fish species occur, and ranges are limited by temperature. Smallmouth bass is an invasive species originally introduced for sport, and Karen examined how changes through time in the bass’ range related to species composition, environmental characteristics and predator presence. She found that abiotic and biotic variables were correlated with invasion probability, but made the important conclusion that community composition affects invasibility, but the reverse—invasion alters community composition—is also true.

Finally, Galen Holt from Peter Chesson’s lab gave a great talk about fitness-density covariance as a possible mechanism of coexistence, and the interaction of dispersal with it. He examined water invertebrate species in a stream, in which both symmetrical dispersal and asymmetric dispersal (i.e. stream flow) could affect the strength of this mechanism. In fact, he found that dispersal weakens fitness-density covariance since species are less likely to stay where environment is best, as is required by this mechanism.

An unidentified University of Toronto student,

letting loose after a long day of talks

ESA Austin: Day 3

Another great day of talks, and surprisingly so. I went to several talks that were more or less randomly chosen, and was impressed by some of the science that graduate students and younger scientists are doing. While others see a potential decline in ecology, I see a very bright future.

M. Duffy examined how virulence susceptibility and the cost of disease resistance in daphnia and its pathogen (yeast). This talk had one of the best setups I seen, and is based on a trade off between r and resistance. Epidemics result in increased resistance, as one would expect with evolution, but equal number of lakes showed evolution for increased susceptibility because of these tradeoffs. Small epidemics should result in increased susceptibility because of a greater fitness cost from reducing r than from mortality. Large outbreaks should result in greater susceptibility as mortality is high. She also showed that environmental context could alter expectation (e.g., productivity or predation).

In the next talk N. Loeuille examined the heterogeneity of resource dispersal. Classic models assume homogeneity in resources availability for competition. But with different diffusion rates, niche competition may be decoupled from tradeoffs needed for coexistence. He used a model with differential dispersal of resources. Depending on tradeoffs, the model will produce the evolution of diverse strategies of disperal. There will be specialization on single resource if dispersal is symmetric. If dispersal rate is too high or too low, but equal, then the resources support lower diversity. If two resources disperse differentially, creates heterogeneity at different scales and will support higher consumer diversity.

I ran over to Tad Fukami’s talk. He examined phylogenetic patterns in priority effects in the assemblages of yeast that colonize flower nectar. He hypothesized that there should be a strong priority effect with close relatives, since they tend to occupy similar niches. He tested this by Introducing species in different orders and assessed relatedness effects using genetic sequences. The experiment was directed by natural history of the system, like time length of flowers, microbial population dynamics in flowers. If one species colonizes first, he showed that it can reach carrying capacity regardless of the presence of other species. If it arrives second, there are major effects on abundance, but differs between which is first species. Closely related species result in strong priority effect, but weak with distant relatives. Result robust even if you control for differential ability to deal with abiotic conditions. The potential mechanisms include differentially reducing amino acids, and different growth rates on sugars.

Kevin smith gave a great talk on extinctions. He used several large, recently assembled datasets to examine how range size correlates with extinction risk under different scenarios of habitat destruction. Randomly, you would expect that broad species have a low probability of extinction overall and endemics have a high probability. Across the datasets, widespread species are going extinct at higher probabilities then a random model. Land snails conform to random model based on species range. However, for bird and amphibian datasets, the rare species bahave as expected with high extinction risk, but the middle ranged species have higher than expected extinction risk

L. Prevost examined how the theory of Island Biogeography (IBG) explained diversity patterns in fragmented habitats in mid to high elevation habitats in Costa Rica. The short answer is not very well, there were not distance or area effects on plant diversity. Communities have low similarity, no relationship with distance, but are similar according to elevation. It seems as though species responses to heterogeneity drives the system, so she recommends that many small reserves could be valuable.

In a very interesting and stimulating talk, A. Rominger examined fluctuations in evolutionary history. He showed that there are more fluctuations than predicted by various models including random walks (which conforms to a Gaussian distribution). Gaussian is observed in small time slices, but variances change over time. Fluctuations within orders fit Gaussian very well, but different from one another. Volatility itself evolves by gamma distribution. He shows that volatility is inherited within orders, and fascinating and controversial conclusion.

John Parker testing the often assumed, but understudied assumption that exotics differ in advented populations versus native. Basically, is there an away-field advantage? Examined home and away for 1000 worst invaders, across many taxa. Looked at size, reproduction, population growth. None of these were particularly enlightening. For example they are not bigger in away sites, size at home predicts invader size 1:1. There is some variation, but no consistent trend. Fecundity, also no consistent trend, with noninvasive just as likely to increased fecundity. Abundance not consistent but slight trend to be bigger away. Survival, growth, same thing. Overall slightly better away, but not greatly. We need to reexamine our hypotheses.

Day 2 in Austin

The second day of ESA got off to a good start in Austin, with a day full of more community ecology talks than one person could attend. I split my day between Community Assembly and Neutral Theory II& III (it's interesting to note that ten years in neutral theory is now included in so many eponymous sessions) and Biodiversity I, and regretted missing talks in many other sessions.



The Community Assembly and Neutral Theory II covered a diverse range of systems (from microcosms to primates), scales, and methods of study. Lin Jiang presented an experiment examining the relationship between diversity and invasibility, in particular testing whether priority effects reduce the oft-seen negative relationship between diversity and invisibility. Most manipulative experiments "assemble" communities instantaneously rather than continuously and stochastically as in natural systems, and so more realistic assembly may weaken the sampling effect and niche complementarity, which are suggested to drive the negative relationship. Using protist-based microcosms of 5 resident species and one invading species, Jiang examined how more realistic assembly of communities affected the diversity-invasibility relationship. Under these conditions, there was still evidence of a negative invasion diversity effect. His most interesting result however were that in fact the presence of a close relative had the strongest influence on the success of the invasive species, in line with other theoretical and empirical results (although not conclusive given the small number of species).

In the Community Assembly and Neutral Theory II session common topics in this session included the widely-used framework of hierarchical filters (i.e. abiotic, biotic, dispersal limitation) determining local species composition and tests of the predictions of the neutral theory (with a focus on non-SAD predictions). For example Wang et al. looked at the patterns of clade age versus abundance that were predicted by neutral theory, in comparison with empirical data from the BCI dataset. There was a clear divergence between the observed data, which included old clades with high or medium abundances compared to the neutral theory prediction that old species should have low abundances. Wang examined how relaxing the assumption of equal rates of speciation among species affected the age-abundance patterns, but concluded that different rates of speciation among species wouldn't produce the observed pattern without then failing the SAD predictions. However, one astute commenter noted that it might also be important to model the possibility of changing rates of speciation through time.

There were many other interesting talks. For example, in Biodiversity I, Matthew Leibold provided a master class on resilience to human disturbance, focusing on concept of communities and ecosystems as complex sets of coupled oscillators. Finally, Angela Brandt presented the results of a 7-year experiment in California grasslands (which no doubt represents many hours of hard work), in which she examined the relationship between invasion success, resource availability, and disturbance. In particular, she framed the question from a phylogenetic context, and discovered evidence that disturbed communities tended to be both more species-rich and phylogenetically diverse, and also less phylogenetically clustered, compared to non-disturbed communities. However, if communities received nutrient enrichment and disturbance, invasion was greater, and diversity lower, than in communities that received disturbance treatments only.

Looking forward to day 3!

***Addendum by Marc:
There were two additional talks that were particularly interesting. First was Andy Gonzalez’s talk on Evolutionary rescue, which is when a population is in demographic decline, heading towards extinction and adaptation saves it from extinction. This is particularly important in changing environments. He has previously shown this using yeast growing under salt stress. His question now was whether migration in a metapopulation with heterogeneous affects this evolutionary rescue. This is an interesting question because too little dispersal means that genetic variation or beneficial mutations do not get to other patches, and too high means that suboptimal genes are maintained in patches where they are maladapted. Not surprisingly he showed that in a constant environment, dispersal is not very important. In heterogeneous metapopulations, patches at the edge of salt tolerance thresholds increase in yield with dispersal.

The other very interesting talk was from K. Anderson on niche-based sorting in highly diverse palm assemblages. She looked at soil type and resource availability, as well as herbivore damage. She experimentally planted 13 species across a soil gradient with and without herbivore exclosures. In low nutrient soils, the palms invested more in roots while in high resources soils, there was a greater investment in above ground biomass and an increase in photosynthetic rate. Leaf toughness also increased in poor sites, meaning that they were more resistant to herbivory and plants growing in the high resource sites experience more herbivore damage. She mentioned that there were differential responses from the different species, and I am very interested to see more about this neat system.

ESA Austin: Day 1

We are now through a great first day at the ESA Austin meeting, and have been having a great time both at talks and out on the town in Austin (see photos). Looking over the program, it was obvious that the day had too many good talks, and that it was impossible to see them all. Considering that I was giving a talk, I decided to spend my entire time in my session on biodiversity and ecosystem function. It may seem lazy, but there were a bunch of talks that sounded great. Here are short summaries of all the talks in the session (excluding mine of course).

The Decemberists playing at Stubbs. Fantastic show (maybe the highlight of day 1, if not for the many interesting talks)

Darwin's pub, great name, OK pub.

The first talk by Nicolas Mouquet was probably the best. It was on the relationship between species diversity and ecosystem function, asking how we can move from the question of how many species to which species. The ultimate answer, according Mouquet, comes from evolution. By understanding the evolution of specialization, one can discern the importance of niche complementarity in the additive contributions to ecosystem function. Using simulations, he showed that the relationship between richness and function is dependent on whether species are specialist or generalist and the strength of tradeoffs in resource use. He then told us about fantastic experiments that evolve bacteria on differing resources, creating specialists and generalists. Positive diversity-function relationships were higher but not stronger in assemblages of generalists, because they deal with heterogeneity better. He manipulated the amount of evolutionary history in assemblages and found that the relationship between evolutionary diversity and function was stronger with groups of specialists. This research goes beyond most others in that it explicitly links coexistence to ecosystem function.

Next was a talk by J. Passari, looking at ecosystem multifunctionality in a long term plant experiment. He examined eight different functions and examined how local, large scale and among site diversity influenced ecosystem function. He found that multifunctionality increased with increasing local diversity but less so with diversity at larger scales.

Greg Crutsinger, showed how genotypic and phenotypic differences in coyote shrub morphs resulted in differences in arthropod abundance and richness, and changes in litter communities.

M. Striebel examined how phytoplankton diversity affect function. She showed that total pigment diversity (representing photosynthesis) increased with phytoplankton diversity. Also she examine how this diversity affected zooplankton diversity and found positive relationships in oligotrophic and mesotrophic systems, but not eutrophic ones.

J. Mclaren manipulated the functional group richness in desert and arctic plant communities and examine the community and functional responses. There was some compensation by other functional groups, but only a weak overall affect on function.

J. Petermann manipulated basal resource diversity and predator richness in bromeliad aquatic communities. She measured four functions and found only weak effects, it seems as though bromeliad leaf complexity may drive some of these relationships.

E. Harvey showed how multiple extinctions in complex food webs can have important cascading effects on ecosystem function. He measured multiple functions in freshwater and marine communities, and that different extinctions had differential effects and some where non-linear.

JJ Weis gave a very interesting talk where he used a model to assess how intra- and interspecific diversity affect function. He found that high complementarity resulted when species had high genotypic variation but low genotypic breadth.

Finally, T. Hanley, who is also a student in the same lab as JJ Weis, examined how intraspecific variation affected population dynamics of daphnia and their algal prey. There wasn’t any effect of daphnia genotypes on algal or daphnia dynamics, but daphnia genotypic diversity increased through time.

What is interesting about this group of talks is the diversity of organisms, systems, scales and functions being considered. These talks are a great signal that biodiversity-ecosystem function research transcend locales and is now a broad, mature field of study.

Blogging our way through Texas

We are on our way to the ESA meeting in Texas! During the meeting next week, we will provide daily updates on the EEB and Flow, recounting some of the interesting talks and happenings there. See y'all in Texas.

The empirical divide

Has there been a shift in how ecology is done? In an interesting editorial in the most recent ESA Bulletin, titled “Losing the Culture of Ecology”, David Lindenmayer and Gene Likens wrote that “empirical and place-based research”, such as field studies and taxonomy, appear to be falling out of favor. They suggest that ecological modeling, meta-analysis, and data-mining (the three M’s) are more lucrative (and popular) approaches today, because these methods are faster, cheaper, and “easier” to perform, allowing more rapid publication. While they recognize the important advancements resulting from these methods, the result—they suggest—is that field-based empirical research is becoming less prevalent, to the detriment of ecology.

This is a polarizing issue, and the response of those ecologists we spoke to depended on where they position themselves on the field/theoretical divide. Those who define themselves as field ecologists tended to feel embattled in the face of long, expensive months of fieldwork, with slow returns in terms of data and publications. Some felt there is a subtle insinuation that fieldwork is less generalizable and so less valuable than techniques such as meta-analysis and ecological modeling, which by their nature tend to be theory-based and general.

On the other side, some theoretical ecologists we spoke to felt the need to defend the validity of doing “indoor” ecology, noting that theory and modeling can link pattern and process, without the confounding variation common in field experiments/observations. Although field ecologists felt that they have a more difficult time obtaining funding, theoretical ecologists noted that they often receive far less money because the assumption is that theory is “free”. Further, with the exception of very specialized funding opportunities (e.g., NCEAS), meta-analyses do not typically get funded as stand-alone projects.

It’s important to note that in its short history, ecology has frequently struggled with the balance between the field and lab. The primary criticism of field-based research at the turn of the 20th century was that it was “unscientific”, inseparable from natural history, producing lists of species names rather than furthering understanding, while labwork was considered to be too divorced from natural systems to be informative (producing so-called “armchair ecologists”). These conflicts split some of the first organismal departments in the United States (*) and tensions exist to this day. No doubt these criticisms are not unfamiliar to many modern ecologists.

There needs to be a balance between the production and consumption of data. Obviously abandoning fieldwork and using only meta-analysis, modeling, and data-mining is not sustainable, but these are important methods for modern ecology. In addition, the perceptions of bias against fieldwork may be due to a general decline in funding and greater overall competitiveness for the rewards of academic labour (jobs, grants, publishing in top journals, etc.), rather than a true decline in field ecology. As we discussed this article, it became clear that our own perceptions, and perhaps those of the broader community, have formed in the absence of empirical data. We examined the last few issues of some highly-ranked ecological journals that publish primary research (Ecology Letters, Molecular Ecology, American Naturalist), and recorded the number of papers that used empirical data, and further the number of those that collected their own data (versus using data from databases, literature, etc). Surprisingly, the vast majority of studies were based on empirical data, mostly data collected by the authors. In Molecular Ecology, 27 out of 28 papers were empirical, and 26 of these used data collected by the author(s); in Ecology Letters, 17 out of 20 papers were empirical, and 12 of these used data collected by the author(s). Even in American Naturalist, which is known for its theoretical bent, 44 out of 70 papers were empirical, and 32 used the author(s)’ own data. Overall, these journals, where competition for space is most severe, primarily publish empirical research.

It appears then, that neither grants nor publications systemically bias towards the three M’s. But is there still a cost to researchers on either side of the data producer-consumer divide? The answer is likely yes. The three M’s result in quicker publications, which means these researchers look more productive on paper, resulting in greater visibility. With more publications, they are likely to make it to the top of hiring committee lists. Conversely, unless a specific job has been advertised as a modeling position, candidates giving job talks focusing on the three M’s do not come across as knowledgeably as a very skilled field person. One of us (MWC) has seen job searches at four different institutions, and the unadvertised stipulation for many departmental faculty or committee members is that the candidate will come and establish a field program. Another common criticism of 3-M candidates is that they will not be able to secure large amounts of research funding.

Given this double-edged sword, what is the optimal strategy? The glib, easy answer is that ecologists need to become less specialized, to do both theory and empirical work, if they want a successful career. And maybe this is the solution, at least for some ecologists. But is having everyone become a generalist really the answer? Most field ecologists will tell you that they do fieldwork in part because they love being in the field and they’re good at it; most theoretical ecologists are adept at manipulating ideas and theory. Perhaps there is still a role for the specialist: after all quantitative ecology—which produces data—and theoretical ecology—which consumes it—are inseparable. They have a complementary relationship, in which field observations and data fuel new models and ideas, which in turn provides new hypotheses to be tested in the field. It’s obvious that people should be able to specialize, and that the focus should be on increasing collaboration between the two groups.

Despite the hand-wrenching, perhaps this collaboration is already happening. Many of the very best 3-M papers unite theoretically-minded with empirically-grounded ecologists. The working-group style funding by NCEAS (and its emulates) explicitly links together data producers and data consumers. These papers may be deserving of greater visibility. If collaboration is the future of ecology, why does the tension still exist between lab and field? The historical tension was not really about the laboratory vs. the field, but rather about scientific philosophy, and we think this holds true today. Ecology has tangibly moved towards hypothesis-driven research, at the expense of inductive science, which was more common in the past. The tensions between “indoor ecology” and field ecology have been conflated with changes in the philosophy of modern ecology, in the difficulties of obtaining funding and publishing as a modern ecologist, and some degree of thinking the “grass is always greener” in the other field. In fact, the empirical divide may not be as wide as is often suggested.

By Caroline Tucker and Marc Cadotte


* Robert E. Kohler. Landscapes and labscapes: Exploring the lab-field border in biology. 2002. University of Chicago Press. (This is a fascinating book about the early years of ecology, and definitely worth a read).

The reality of publishing papers

This is in response to my undergrads, who ask me "Have you published any of the stuff we're working on yet?" practically every week. To which my response invariably is "not yet".


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