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".


(click to make larger)

Metacommunity data and theory: the tortoise and the hare

Empirical approaches to metacommunities: a review and comparison with theory
Logue et al. 2011

The recognition that community composition is a function of both local and regional-scale processes, meaning that a community cannot be understood in isolation from the network of communities with which it interacts, is the fundamental idea behind metacommunity ecology. In a relatively short period of time, metacommunity ecology has integrated concepts from spatial ecology, metapopulation ecology, and community ecology with novel ideas, and developed a strong body of theory. However, metacommunity theory has advanced much more rapidly than empirical tests of that theory. In an interesting review in TREE, Logue et al. examine whether empirical data needs to catch up with the pace of theory development, or whether theory is moving too fast to incorporate the information available from empirical data.

The types of systems used in the 34 experimental and 74 observational studies that Logue et al. found were very limited – the most common experimental approach involved setting up aquatic microcosms of unicellular organisms.* Observational studies similarly tested microorganisms, usually in aquatic systems. The organisms so beloved in the rest of community ecology (plants? vertebrates?) barely feature. Most studies focus on aquatic systems composed of multiple patches (such as microcosms, ponds, pitcher plant communities) because systems with discrete boundaries are more amenable to testing current theory. However, natural systems are rarely configured into a clear “patch” versus “matrix” dichotomy. Instead they are complex and heterogeneous, and may lack clear boundaries.

Dynamics in metacommunities are generally described using four dominant paradigms: mass-effects, species sorting, neutral perspective, or patch-dynamics. These paradigms reflect the most important processes structuring communities, that is, either dispersal between communities, environmental differences between communities, dynamics driven by the tenets of neutral theory, or extinction and colonization, respectively. Strikingly, experimental studies mostly tested for mass-effects or patch dynamics, and observational studies mostly tested for species-sorting and mass effects paradigms. The neutral paradigm was rarely tested in any type of study. Logue et al. found that many studies had difficulty designing experiments that tested for evidence of specific paradigms, because natural communities are much more complex than the simple paradigms suggest. Most studies that did test for evidence of particular paradigms found evidence for multiple paradigms or had difficulty disentangling different mechanisms.

The metacommunity theory that has developed in the last five years is among the most exciting and interesting work in ecology. However, the slower pace of experimental work means that theory has developed with little feedback. For example, Logue et al. make a strong argument that the results from these studies suggest that it is time to integrate the four-paradigm system into a single, comprehensive framework (see figure). Theory is only valuable if it’s useful - this paper is an important reminder that there is an important feedback loop between theory and data, and successful science requires input from both.

*Important disclaimer: at this very moment I'm running aquatic microcosms of microscopic protists in the lab. We all have room for improvment. :)

Navjot Sodhi, conservation for all

I opened my e-mail to see the shocking and saddening news that Navjot Sodhi passed away yesterday (see here for more details). He was an absolute leader in tropical conservation biology from his base in Singapore. But more than this he made conservation biology accessible to the public and especially to those working on the front lines trying to protect biodiversity. His free edited book: 'Conservation Biology for All' set a new milestone in conservation biology and in the efforts of academics to step out of the ivory tower and reach out to broader communities.

Nature’s little blue pill

Something often happens to mature community ecology studies as they get older that we don’t like to talk about much. Occasionally, when biodiversity and ecosystem functioning experiments are performed in a controlled, homogeneous setting, they can suffer from flaccid response curves. It’s perfectly normal, happens to lots of healthy microcosm communities, but it can be troubling and embarrassing nonetheless. After all, who doesn’t want a nice stiff linear response curve?

Bear with me here for a minute.

A few weeks ago, Bradley Cardinale published a study in which he tested the effects of algal biodiversity on water quality in streams. It’s a pretty classic diversity-function experiment; lots of artificial streams with different numbers of species of algae in them, and he measured productivity and nitrogen uptake. As is usually the case, the more species he put in each stream, the more these ecosystem functions increased.

But Cardinale did something else in this experiment that has never been done before, at least not on this scale. He added extra niche opportunities to some of the streams, so that they offered multiple different habitats for algae. He did this by introducing heterogeneity through flow and disturbance manipulations.

Figures from Cardinale 2011, Nature. a and b are the heterogeneous streams, d and e are the homogeneous ones.

You might be familiar with that saturating response curve that is typical of so many diversity-function experiments. It starts off with large increases in ecosystem functioning as species are added to communities, and then it levels off so that as additional species are added, they only increase ecosystem functioning by small amounts (figures d and e). The theory behind this is that there are only so many niches in an environment, and as more and more species are added some of them become redundant.

Well when Cardinale threw those extra habitats into his artificial streams, that floppy old saturating curve sprang up like a regressional jack-in-the-box (figures a and b).

What happened was the homogeneous streams became dominated by just a single species that was well adapted to that environment. The heterogeneous streams allowed different species to coexist and this let them make more efficient use of the resources in those streams.

This is a major finding for a few reasons. First, it confirms that one of the main mechanisms behind diversity-function relationships is niche partitioning. I’ve said in the past that knowledge of these mechanisms is sorely needed. Second, it links coexistence theory to ecosystem functioning, two fields that are closely related but often disconnected.

Finally, it means that biodiversity is even more valuable than we had previously thought. The natural world doesn’t contain very many homogeneous streams; it’s a complicated place. The real world is probably better represented by figures a and b than by figures d and e. So while controlled experiments have shown that some species are redundant for ecosystem functioning, there is no evidence here for any redundancy in more natural settings.

This paper also underlines the fact that these studies need to be done in nature as opposed to labs. Cardinale was able to simulate nature fairly realistically because he was using algae. That’s harder to do with more complex organisms. It’s difficult to recreate environmental heterogeneity in artificial ecosystems, and if ecosystem functioning depends on both biodiversity and heterogeneity, then it’s time to take this research outside. Manipulative field studies are a good start, but completely natural settings will probably reveal more of the true story.

So although it’s very common for artificial communities to suffer from Ecological Dysfunction, there is no reason that they can’t enjoy a healthy relationship with biodiversity like any other community. All they need is a little heterogeneity to spice things up and put that spring back in their step.

Andy Hector has written an excellent perspective on the study. I recommend reading it, particularly if you don’t want to read the entire original article.

The ecology blogosphere just got a little more crowded, and better (welcome Oikos blog)

A diversity of voices is why the internet is such a powerful intellectually democratizing form of communication. Ecology blogs, long the minority in scientific blogging just received an immense boost from the new Oikos blog, obviously associated with the journal, Oikos. While some of their content is dedicated to journal business, there have been great posts on ecological research and broader intellectual topics from Jeremy Fox, aka oikosjeremy.

Welcome.

Happy 10th birthday, neutral theory!

Rosindell, Hubbell, and Etienne. (2011). The unified neutral theory of biodiversity and biogeography at age ten.

I would argue that neutral theory is not only the most controversial idea, but also the most successful idea to permeate community ecology in the last ten years. A quick keyword search suggests that ~30 ecological papers related to the topic were published in the last year, including some with titles still reflecting the controversy; “Different but equal: the implausible assumption at the heart of neutral theory”. Neutral theory makes a seemingly unreasonable assumption—that species identity doesn’t matter—and yet seems to predict species-area relationships and species abundance distributions as well or better than niche theory does. This made it an infuriating challenge for many ecologists. The number and quality of papers that it inspired—both in support and opposition—are a reminder that disagreement is good for science.

It’s been a decade since the publication of “The Unified Neutral Theory of Biodiversity and Biogeography”, in which Steve Hubbell proposed a controversial model in which coexistence results from drift, dispersal and speciation, rather than ecological differences between species. To mark this anniversary, a review in TREE by James Rosindell, Stephen Hubbell, and Rampal Etienne reflects on neutral theory’s first ten years, and examine the influence neutral theory has had in many areas of community ecology. The authors also note that some of the limitations of neutral theory can be dealt with by extending the classic formulation of the model, so that unrealistic assumptions related to spatial structure, speciation rates, or the zero-sum assumption can be relaxed. The excessive interest in neutral theory’s species-abundance predictions left its other predictions unexamined, and there is still room for tests of how neutral theory informs species-time relationships, modes of speciation, and even conservation decisions.

Despite these accomplishments, the review is remarkably subdued, underlined by statements such as neutral theory is a “good starting point”, a “valuable null model”, and a “useful baseline”. However, it seems unnecessary to state, as some have, that "neutral theory is dead". Its legacy, captured in the final paragraphs, is still incredibly important: “…niches have dominated our attention and left less obvious, but still important processes forgotten… Perhaps the most important contribution of neutral theory has been to highlight the key roles of dispersal limitation, speciation and ecological drift, by showing how much can be explained by these processes alone...”

George Box said it best: “All models are wrong, but some are useful”.