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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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”.

Carnival three-five.

The 35th installment of the Carnival of Evolution is available from Lab Rat. Want to know who said what about evolution? Go to the Carnival.

Ecological interactions and evolutionary relatedness: contrary effects of conserved niches

Over the past several years a multitude of papers linking patterns of evolutionary relatedness to community structure and species coexistence. Much of this work has looked at co-occurrence patterns and looked for non-random patterns of relatedness. The key explanations of patterns has been that communities comprised of more distantly-related species is thought to be structured by competitive interactions, excluding close relatives. Alternatively, communities comprised of species that are closely related, are thought to share some key feature that allows them to persist in a particular set of environmental conditions or stress. This whole area of research is completely predicated on close relatives having more similar niche requirements then two distant relatives. This predication is seldom tested.In a recent paper in the Proceedings of the National Academy of Science, Jean Burns and Sharon Strauss examine the ecological similarity among 32 plant species and tested if evolutionary relationships offered insight into these similarities. The ecological aspects they examined were germination and early survival rates as well as interaction strengths among species. To assess how these were influenced by evolutionary relatedness, they planted each species in the presence of one of four other species varying in time since divergence from a common ancestor, creating a gradient of relatedness for each species. They found that germination and early survival decreased with increasing evolutionary distance. This surprising result means that species germinating near close relatives do better early on then if they are near distant relatives. The explanation could be that they share many of their biotic and abiotic requirements, and these conserved traits influence early success.

Conversely, when they examined interaction strengths over a longer period (measured as relative individual biomass with and without a competitor), they found that negative interactions were stronger among close relatives.

These two results reveal how evolutionary history can offer insight into ecological interactions, and that the mutually exclusive models of competitive exclusion versus environmental filtering do not capture the full and subtle influence of conserved ecologies. Evolutionarily conserved traits can explain both correlated environmental responses and competitive interactions.

Burns, J., & Strauss, S. (2011). More closely related species are more ecologically similar in an experimental test Proceedings of the National Academy of Sciences, 108 (13), 5302-5307 DOI: 10.1073/pnas.1013003108

The bellybutton, biodiversity reserve of the body

Although less recognized--and less glamourous--than most biodiversity hotspots, the human bellybutton harbours it own diverse collection of species, and these species tell us something about ourselves. That's the premise behind the Belly Button Biodiversity Project, which is getting some press for its large-scale sampling of bellybutton bacteria. For interesting discussion about where the data could lead, see Rob Dunn's (one of the researchers) website. His post, including the comments, hints at how much there is to learn about the ecology of human bacteria.

Update: Rob Dunn has now published a book "The Wild Life of Our Bodies", telling more stories of our changing relationships with other species.

Carnival time.

The 34th edition of the Carnival of Evolution is hosted at Quintessence of Dust. Everything from the evolution of perfection to the evolution of small importance will be found there.

White-nose syndrome and wind turbines: why biodiversity matters

Linking ecosystem services to economic benefits is a vital step in connecting ecological research to policy and political action. The UN Environmental Programme’s The Economics of Ecosystems and Biodiversity (TEEB) initiative represents a concerted effort to draw attention to the economic benefits of biodiversity and cost of ecosystem degradation, and to bring together scientists, economists and policy-makers.

Accordingly, Boyles et al. (Nature, 2011) paint a troubling picture about the value of economic benefits that insectivorous bats provide to the North American economy, and the degree of extinction risk they currently face. The authors point out that bats are “among the most overlooked, yet economically important, non-domesticated animals in North America”, and their loss would cost North Americans more than 3.7 billion dollars/year. Given rapid declines in populations due to white-nose syndrome (over 1 million bats killed) and wind turbine fatalities (projected to reach up to 30,000-100,000 fatalities/year as wind turbine installations increase), the authors suggest action can't wait.



Hopefully using the universal language of money helps translate scientific knowledge into political action. After all, bats are only one group of species: imagine the true cost of current rates of biodiversity loss and ecosystem destruction, from the smallest microorganism to the largest megafauna. The total must be staggering. And so, it seems, is the scale of action required to halt this decline.

The regional community, maximum entropy, and other ideas in ecology

Looking through my feed of community ecology papers this month, I couldn’t help but notice that while most tested well-established concepts–density-dependence, niche partitioning, metacommunities, competition, dispersal limitation–there was also–as I suppose is usually true–a subset of papers championing newer, less established ideas.

For example, the article “Applying a regional community concept to forest birds of eastern North America” by Robert Ricklefs, furthers the regional community concept he introduced in 2008. Ricklefs is uncomfortable with how ecologists typically define local communities – i.e as spatially and ecologically discreet entities – and the predominant focus in community ecology on local coexistence. He argues that communities make sense as entities only at a larger scale, taking into account that local communities are not isolated, but instead interact as a function of overlapping ranges and species dispersal. In this paper he applies this concept to Breeding Bird Survey data to examine the distribution and abundance of birds in eastern NA.

Partel, Szava-Kovats, and Zobel are also critical of the predominant focus on local diversity. In their paper “Dark diversity: shedding light on absent species”, they pitch the idea of “dark diversity” as a valid diversity metric. Dark diversity accounts for the number of species which belong to the species pool for a particular habitat in a region but are not actually present in a local community of that habitat type. The resulting value can be used to calculate a dimensionless ratio of local to dark diversity, suitable for comparison of diversity components in dissimilar regions.

Lastly, in “A strong test of a maximum entropy model of trait-based community assembly”, Shipley et al. further test Shipley’s model of Entropy Maximization, using it to predict the composition of communities in the South African fynbos. The model predicts community composition (species identity and relative abundances) through an assumption of random assembly (or entropy maximization) within environmental constraints on species traits.

New ideas are a constant in ecology, but they face stiff competition in an already crowded field. The possible mechanisms of local coexistence, for example, are already a long list. What determines which of these–or any–ideas become entrenched in ecology? The likelihood of a concept becoming established must be a complex function relying on a cost-benefit analysis–what does applying this idea cost compared to the gain in understanding it produces?–further adjusted by intangible variables like timing and the skill and prestige of an idea’s advocate. After all, some ideas require decades to establish properly, requiring changes in the theoretical climate or technical capabilities, for example, neutral theory or spatial ecology. Others seem to catch on immediately. Philosophers have written more cogently on how scientific ideas change and paradigms shift, but as participants in the process, we have a rather unique perspective. After all, as scientists we play an active role in driving these shifts in thought and action. You might argue that the merit of the ecological ideas that become established are as much a reflection on those who accept and institute them, as on those who propose them.

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awesome infographic by Caroline Tucker

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There exists a problem in science so complicated that decades of work have yet to solve it. Its causes and consequences make some of the toughest questions in complex analysis or astrophysics look like child’s play. And yet when we consider this problem, the conclusion is immediately obvious and simple: it should not exist.

I am talking about the fact that today, in 2011, female scientists are punished solely because they are female scientists.

In theory, this problem doesn’t exist anymore. Multiple waves of feminism should have chipped away whatever glass ceilings once capped our ivory towers. Women are receiving more PhDs than men in many fields and they are earning such a high proportion of bachelor’s degrees that we may have to rethink that name.

But in the last several weeks, some disturbing realities have resurfaced in the science media. At the end of January, Nature reported that women earn fewer scholarly awards than they should, based on the proportion of their respective fields that they represent. That same week, Science published a graph showing the number of European Research Council grants awarded to women in its last funding round – 9.4%.

Stats like these are nothing new; they pop up all the time. What is new, however, is the article that followed in Proceedings of the National Academy of Sciences a few days later. It turns out that there is no longer much evidence for overt discrimination against women applying for jobs or grants in quantitative fields. Instead, disparities in available resources are causing many of the differences between women and men’s scientific careers.

Yes, there are discrepancies in publication acceptance rates and grants, but the authors attribute these to factors like women occupying more positions at teaching-intensive schools rather than research institutions. When they compared men and women with similar resources, the biases disappeared, or in some cases, favoured women. (If you don’t want to read the whole article, there’s a nice summary of it here.)

Ok great, the science community isn’t explicitly discriminating against women. But this leads us to a much more troubling conclusion; the culprits are actually deeply engrained societal expectations and constraints that likely extend well beyond the sciences, and certainly beyond the scope of this blog post, though a few of them are highlighted in this thoughtful opinion piece.

Here’s what I will say: it’s not written in our DNA. How many times have you heard lines like, “Men and women are just different, they always will be, our brains aren’t wired the same”? This kind of just so statement is rarely backed up with evidence. For a good debunking of these misconceptions, check out two new books, reviewed here.

Now it’s possible that I, as a young male grad student, do not hold the most valuable two cents on these issues. I could keep rambling about things that I don’t fully understand, but my perspective is limited, and I think maybe the most constructive thing to do at this point would be to hear about other people’s ideas and experiences in the comments section below. So I’m cutting this short and leaving it incomplete in favour of a more open forum. In particular, it occurred to me that we in the ecology and evolution community have a unique opportunity to shed light on many gender issues. The PNAS article focuses on the underrepresentation of women in math-intensive fields, but comparing mathy fields to less-mathy fields entails a lot of confounding factors. In ecology and evolution, however, we cover the whole spectrum, from the completely mathless and descriptive, to the suspender-wearing, calculator-toting quants. We generally all come from relatively similar biology backgrounds, eliminating many of those confounding factors, and it would be great to hear how you all think these issues play out in E & E. So go for it blogosphere, do your thing.

Documenting the sacrifice

Whether working in remote regions or with poisonous animals, biologists often put themselves in peril in the name of discovery. The first organized expeditions of naturalists sailed to exotic lands, their bravery supplemented by their curiosity, were threatened by storms while at sea, new and deadly diseases, unfamiliar animals, and new cultures. Add plane crashes and paramilitary groups to this list and not much has changed.

In a great New York Times piece titled 'Dying for Discovery', Richard Conniff recounts several stories of naturalists, ecologists and conservation biologists killed while pursuing their passion for discovery. But just how many field biologists have died while working to understand life's secrets? This is an interesting question, and begs the further question, are they adequately memorialized?

Gary Polis (1946-2000) desert ecologist, drown with four other biologists during a storm in the Sea of Cortez.

In an attempt to tell the stories of the fallen naturalists, Conniff hosts an interactive list, called the Wall of the Dead, which lists all biologists killed in the field and that he has a record of. People are able to add names, and I've visited this list several times over the past month and it has grown substantially. I've known a few field biologists that have died -and added one to the list, and know several that survived near-death experiences, and this list is a great and important monument to their memories.

Further studies of the decline effect find decline of the decline effect

“The Truth Wears Off: Is something wrong with the scientific method?”

The Decline Effect explored in an article by Jonah Lehrer in the New Yorker refers to a temporal decline in the size of an observed effect: for example, the therapeutic value of antidepressants appears to have declined threefold since the original trials. Based on the cases presented, this effect is not limited to medical and psychological studies. One example in evolutionary biology is the relationship between physical symmetry and female choice: initial studies consistently found strong selection for symmetry in mates by females, but as time passed, the evidence grew increasingly smaller.

This may be a result of selective reporting – scientists focus on results that are novel and interesting, even if they are in fact simply statistical outliers, or worse, the result of unconscious human bias. This sentiment is troubling; humans – scientists or not– are proficient pattern finders, but our subconscious (or conscious) beliefs influence what we search for. Lehrer argues that replication – the process of carrying out additional, comparable but independent studies – isn’t an effective part of the scientific method. After all, if study results are biased, and replications don’t agree, how can we know what to trust?

I don’t disagree with most of the article’s points: that scientists can produce biased results, PhD not withstanding, that more effort and time should be invested in data collection and experimental methodology, that the focus on 5% statistical significance is problematic. For one, it’s not clear from the article how prevalent the decline effect is. However, I wonder whether Lehrer, similar to the scientists he’s reporting on, has selected specific, interesting data points, while ignoring the general trend of the research. In 2001, Jennions and Moller published evidence of a small negative trend in effect size over time for 200+ studies, however, they suggest this is due to a bias toward high statistical significance, which requires either large effect sizes (the early studies published), or small effect sizes in combination with large sample sizes (a scenario which takes more time).

Even if the decline effect is rampant, does it represent a failure of replicability? Lehrer states that replication is flawed because “it appears that nature often gives us different answers”. As ecologists though, we know that nature doesn’t give different answers, we ask it different questions (or the same question in different contexts). Ecology is complex and context-dependent, and replication is about investigating the general role of a mechanism that may have been studied only in a specific system, organism, or process. Additional studies will likely produce slightly or greatly different results, and optimally a comprehensive understanding of the effect results. The real danger is that scientists, the media, and journals over-emphasize the significance of initial, novel results, which haven’t (and may never be) replicated.

Is there something wrong with the scientific method (which is curiously never defined in the article)? The decline effect hardly seems like evidence that we’re all wasting our time as scientists – for one, the fact that “unfashionable” results are still publishable suggests that replicability is doing what it’s supposed to, that is, correct for unusual outcomes and produce something close to the average effect size. True, scientists are not infallible, but the strength of the scientific process today is that it doesn’t operate on the individual level: it relies on a scientific community made of peers, reviewers, editors, and co-authors, and hopefully this encourages greater accuracy in our conclusions.

Carinval #32 and still going strong

Want to know what people are talking about? The 32nd Carnival of Evolution is online, hosted by Denim and Tweed. Check it out, pass it along.

Trend in ecology, 2010

Sciences are always in a state of ebb and flow (sorry), and topics of study fall in or out of fashion in response to paradigms shifts, methodological advances, and to support necessary ecological applications.
For the sake of curiosity, I've compiled the top keywords from ecology publications in 2010. Obviously there are many covariates, but it should come as no surprise that the top words were "biodiversity" (667 times), "climate change" (293), and "conservation" (274); other popular keywords were "evolution" (277), "population (ecology)" (273), and the rather vague "patterns" (196).

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The evolutionary story of ecosystem function

Twenty years of research has repeatedly shown that communities with greater diversity result higher functioning -namely greater production of biomass. One of the major mechanisms producing this relationship is that different species use differing resources, such that their complementary use of resources uses the total resource pool more thoroughly, thus converting more resources into biomass. Resource preference is the product of evolution and how organisms have adapted to using various resources can influence the strength of the diversity-function.

In a recent paper in Nature, Dominique Gravel and colleagues test how the evolution of specialization versus general resource use affect the strength of the diversity-function relationship. They use bacteria strains that have undergone evolution on diverse resources (generalist) versus on a singular resource (specialist). The resources in their case are different carbon substrates.

Assemblages of generalists were able to use many available resources and generally had greater productivity than specialist assemblages. Generalists also show an increasing relationship between diversity and productivity, because no generalist used all resources and they still showed some preferences. Combining multiple such generalists meant that more of the total resource pool was consumed. Specialists also resulted in the positive relationship, but a much steeper one. Because specialist use many fewer carbon substrates, additional specialists meant that new resources were tapped into. Thus increasing specialist diversity resulted in more new resources being consumed than with the generalist species.

While these results are logical, they are important for two reasons. First is that the strength of the relationship between diversity and function is mechanistically determined by the resource use efficiency of individual strains, and how many of the total substrates they can use. The mechanisms producing different relationships in previous experiments were hypothesized after the results analyzed, as opposed to being predicted. Second, recent work has shown that evolutionary history seems to be a better explanation of community function than the number of species. These results show how the history of evolution can have important consequences for function.

Gravel, D., Bell, T., Barbera, C., Bouvier, T., Pommier, T., Venail, P., & Mouquet, N. (2010). Experimental niche evolution alters the strength of the diversity–productivity relationship Nature, 469 (7328), 89-92 DOI: 10.1038/nature09592

Who is a scientist, I am a scientist: the bees of Blackawton

In discussions of the larger societal implications of scientific findings, the question of who is a scientist is frequently asked. I've talked with with creationists who invoke the authority of someone who has a PhD in a scientific discipline and happens to share their belief of supernatural origins, as a scientific authority. Does the fact that I have a PhD in ecology and evolutionary biology make me scientist or is being scientist something more?

This is an important question. It goes to the core of whose authority we believe for public discussion of such issues as climate change, evolution, risks of vaccines, and so on. Regardless of how we define 'scientist', a scientist participates in science by publishing peer-reviewed research articles in scientific publications. This notion of who is a scientist has been enjoyably stretched by the publication of a paper in Biology Letters by a group of elementary school children from Blackawton, UK. In consultation with a academic scientist and under the supervision of teachers, 25 8-10 year olds devised and carried out an experiment on bee visual perception and behavior, and wrote up their results into a publishable manuscript.

The students trained bees by offering them nectar rewards in different color containers. They then allowed these trained bees to forage in multicolored arenas and they conclusively show that the bees unambiguously select the colored containers they were trained on. Bess learn and adapt their behavior based on previous experience.

Publishing a paper by a group of children may sound like a gimmick, but the study is very interesting. The commentary from the journal says it best: "The children's findings show that bees are able to alter their foraging behaviour based on previously learned colours and pattern cues in a complex scene consisting of a (local) pattern within a larger (global) pattern . As there has been little testing of bees learning colour patterns at small and large scales, the results can add considerably to our understanding of insect behaviour."

The paper is extremely enjoyable to read and will have you chuckling to yourself. Sincerity pours from the words and I was left wondering if I could have reasoned so well at that age. The children develop hypotheses using information available to them, such as watching Dave Letterman's 'Stupid Dog Tricks'. Reading this article made me realize why I love being scientist. The students note that "This experiment is important, because, as far as we know, no one in history (including adults) has done this experiment before" and because they were given the opportunity to carryout this study they "also discovered that science is cool and fun because you get to do stuff that no one has ever done before". Too true. I could not have said it better myself.

Being scientist can mean a lot of things, it can mean knowledge (which the Latin origin, Scientia means), it can mean training and acquired skills, but at its core, being a scientist means conducting research, testing hypotheses and writing publications that are deemed acceptable by other scientists. Therefore the children of Blackawton are scientists, I am a scientist.

Blackawton, P., Airzee, S., Allen, A., Baker, S., Berrow, A., Blair, C., Churchill, M., Coles, J., Cumming, R., Fraquelli, L., Hackford, C., Hinton Mellor, A., Hutchcroft, M., Ireland, B., Jewsbury, D., Littlejohns, A., Littlejohns, G., Lotto, M., McKeown, J., O'Toole, A., Richards, H., Robbins-Davey, L., Roblyn, S., Rodwell-Lynn, H., Schenck, D., Springer, J., Wishy, A., Rodwell-Lynn, T., Strudwick, D., & Lotto, R. (2010). Blackawton bees Biology Letters DOI: 10.1098/rsbl.2010.1056

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The carnival is on!

Check out the 31st edition of the Carnival of Evolution, hosted by The Dispersal of Darwin. Check it out, a fun read for sure!

Science 2.0 - science comes of age on the Internet

by Marc Cadotte, Nicholas Mirotchnick and Caroline Tucker

The Internet is not just for lolcats and porn anymore, scientists have begun using it in constructive ways. The past few weeks’ controversy about the ability (or lack thereof) of bacteria to incorporate arsenic exemplifies how the relationship between science and the Internet is changing. If you’ve missed the debate over the recent Science paper, researchers funded by NASA’s exobiology/evolutionary biology program published experimental results suggesting that a Halomonas species could incorporate arsenic into its DNA in the absence of available phosphorus. This paper received extensive attention in the mainstream media, but also vocal criticism, which was expressed primarily through postings and comments on scientific blogs. Until recently, for scientific communication the Internet has functioned primarily as an electronic source of published journal articles. Earlier attempts to take advantage of the Internet’s potential (immediacy, accessibility, and ability to connect individuals, organizations, and ideas) in scientific discourse have been mixed (e.g. Nature Precedings versus PLoS ONE). The use of blogs as a forum for scientific debate suggests that this is changing: posters tended to be active scientists and the comments were similarly knowledgeable. In contrast to this online approach, the authors of the Science paper stated that they would only respond to peer-reviewed critiques and would not engage in discussions on the blogosphere.

The story of the arsenic-utilizing bacteria highlights an emergent tension in the transition to internet-based scientific discourse. Traditional communication in science has been primarily unidirectional, from the authors of a study to the readership of a journal. Any discourse transpired on the pages of a journal, regulated by editorial and peer review. This gatekeeping meant that this discourse was technically sound and kept personal grudges and tangential discussions to a minimum. This also meant, however, that only a few voices were heard, the discussion was slow (occurring over months) and only happened for one back and forth (journals will not devote precious page space to on-going discussions and debates).

This method of discourse is changing. Journals have experimented with online discussion or commenting features on their websites. Methods in Ecology and Evolution, for example, has a correspondence page with discussion threads for each paper they publish, and PloS ONE allows for comments to be posted to every paper they publish. While, in concept, these are positive developments for scientific communication, commenting features are seldom, if ever, used. The main obstacle to their success is that they are only available on the publishers’ websites, but scientists access articles in many different ways, from database searches to library links. Few scientists actually go to individual journal websites to access papers. This is not to say that there are not discussions about scientific papers occurring online. As highlighted by the arsenic bacterial episode, blogs are an important avenue for discussing and disseminating new ideas in science. Blogs may not, however, actually foster conversations very well. One person or a few people usually run them and there is little discussion among blogs (a comment on a blog post at blog X will not be part of the discussion of the same story at blog Y). Rather, the greatest potential to foster discourse is through virtual networks where people are linked together either through friendships or professional self-identification (e.g., as fisheries biologists), with Google Reader being a particularly powerful communication tool.

It’s exciting to think about what the future of science will look like, given the changes that we’ve already started to see. The major upside of new channels of communication is that they give us the potential to quickly reach thousands of readers, instead of the handful that usually read any given journal article. They also let us communicate in both directions, and in real time. The pitfall, of course, is that they’re free-for-alls; anyone can blog about science.

But here’s what’s unexpected: these free-for-alls have been amazingly reliable at filtering out the bad and promoting the good. Inaccuracies are pulled from Wikipedia faster than anyone had predicted, the social news site Reddit is “astonishingly” altruistic, with users eliminating offensive or erroneous comments from the site and promoting other users’ questions and problems, and the reputations of blogs are shattered if their content becomes unreliable. Social networking has revolutionized the way we consume news, with sites like Facebook and Twitter launching the best articles into viral webspace. The open-access world has evolved self-regulating mechanisms that work surprisingly well so far and if these media are to continue to grow, we will have to ensure that these mechanisms remain built-in.

Seems like an easy task, right? Apparently not. For some reason, academics are slow and conservative when it comes to adopting new media. A letter to Nature two weeks ago scolded scientists for not contributing their share to Wikipedia pages. Various facebooks for academics, like Mendeley and ResearchGATE have emerged, but last week, another Nature article complained that researchers aren’t jumping on the bandwagon. These sites are potential collaborative goldmines, but we seem to be incapable mastering what tweens can do with two thumbs.

It’s not so hard to imagine a world where anyone with a broadband connection can contribute creative ideas to science, the good ideas get automatically filtered to the top and the information is all free to anyone. In this world, children count ants (or bees!) in their backyards and upload their data to global networks. Revolutionary discoveries are published instantly on blogs and thousands of scientists get to decide if they’re valid. Every gene ever sequenced and every tree height ever measured can be readily downloaded in an Excel (or OpenOffice) spreadsheet. In this world, the report on our little arsenophilic friends might never have been published in Science, because instead of being reviewed by two referees, the thousands of readers on the blogosphere would have filtered it out, if was in fact porous.

Academics should be the first, not the last, to adopt new communication tools. We are no longer limited by the postal service, email or PDFs; the web has gone 2.0 and we should follow suit. So go forth, young researchers, and blog, edit and share. And then go tweet about it all so your eight year-old kid knows how hip you are.

Biodiversity and ecosystem functioning – without fungi?

Different subfields of ecology have a propensity to remain remarkably isolated – researchers in aquatic systems independently develop hypotheses that already exist in some form in other systems, and vice versa. Population ecology and community ecology, despite their obvious relevance to each other, are rarely integrated. There is a tendency – resulting from limits on our time, experience, and possibly imagination – to stay within whatever box we’ve defined for ourselves.

Historically, it seems that biodiversity and ecosystem functioning has lost sight of the progress made in classical ecology in understanding the mechanisms behind species coexistence (and all the functional implications that follow). Studies of ecosystem functioning often vaguely reference concepts such as “niche partitioning”, which would hardly be explicit enough for most papers on coexistence. Fortunately, there are periodically attempts to unifying ecological knowledge.

One of the most important contributions to understanding coexistence is Chesson’s (2000) framework of equalizing and stabilizing effects. Unlike previous approaches to species interactions, which tended to reference these vaguely-defined “niche differences”, Chesson proposed that species interactions depended on both fitness differences (differences in absolute growth rates after niche differences are controlled for) and niche differences (ecological differences between species which cause intraspecific competition to exceed interspecific competition). He also suggested rigorous methods to quantify these concepts. This framework has been applied both to the obvious questions of species coexistence and diversity maintenance, as well as predator-prey relationships (2008) and the phylogenetic structure of communities (2010).

In a recent paper, Ian Carroll et al. apply this framework to the search for the mechanisms behind biodiversity and ecosystem functioning. They point out that the questions in studies of ecosystem functioning are directly analogous to Chesson’s concepts – selection effects result from fitness or competitive differences between species, while complementarity relates to the partitioning of resources, or niche differences between species. The added benefit is that Chesson has provided clear definitions for these concepts.

While this may not be world-altering, it’s encouraging. Anytime different areas of ecology intersect, both benefit. Of course there are difficulties – no doubt the question of how to measure niche differences and fitness differences will be contentious (as attempts to translate ecological theory into ecological methodology often are) - but the possibility that a few general ecological concepts explain diverse observations is worth pursuing.

Biodiversity and ecosystem functioning - only with fungi

Once again scientists have come to an age-old conclusion: fungus is behind all of life’s great mysteries. It's responsible for curing strep throat, delicious veggie burgers, that unique musk emanating from your gym bag, the colour-morphing walls at last night’s party and now, biodiversity and ecosystem functioning.

The world of biodiversity and ecosystem functioning (BEF), like many other high-profile disciplines of science, has often been bogged down by controversy. In such situations, we often spend a disproportionate amount of time focusing on the controversy instead of actually advancing the science itself (sound familiar?)

There have been several posts about BEF on this blog in the last few months, but briefly and oversimplified, here's how it works. Ecosystem functions are things like productivity, nutrient cycling and decomposition. Ecosystems that contain many species produce higher levels of these functions than monocultures do. The controversy here surrounds the cause of this phenomenon. In the 1990s, researchers originally disagreed over whether the relationship they observed was due to complementarity (different species partitioning resources) or selection effects (the higher chance of a really productive species being included in a community with many species). The question was largely settled a few years ago; selection effects do exist, but most of the relationship is driven by complementarity. Nonetheless, many biologists who are only tangentially familiar with this area of research are unaware of the consensus and continue to believe that the issue remains unresolved. Some still dismiss the whole field of BEF because of selection effects. I guess people just love a controversy.

The result of all this is that the ecologists studying these relationships have had to spend an undue amount of time parsing their results into selection and complementarity and discussing the two phenomena. They have even come to refer to these as the “mechanisms” behind BEF. And this is where we start to have a problem. Selection and complementarity are not mechanisms - they are symptoms of mechanisms. They do not tell us what is actually causing the positive effect that biodiversity has on ecosystem functioning, only what the shape of the relationship is. In fact, very few studies have actually looked for true mechanisms that explain the effects that we have repeatedly observed.

But this week I read a new paper in Ecology Letters that actually did find a mechanism, and it wasn’t one that we expected. John Maron and his coauthors at the universities of Montana and British Columbia found that belowground fungi were causing plant productivity to increase with diversity.

In an impressively complete experiment, Maron et al. put together a classic BEF setup of many plots containing varying levels of plant diversity and then measured plant biomass. But this time they added a twist; they applied fungicide to the soil in some of these plots. The result was that in the absence of fungi, the common BEF relationship disappeared. The low diversity plots became much more productive, while productivity at high diversity only increased slightly. The authors explained their results by the fact that fungi can be both species-specific and density-dependent, so as plant diversity increases, the fungi’s negative impact on plant productivity diminishes. And for good measure, they of course also ruled out a significant selection effect in their results.

So what does this all mean? Well for one thing, it means that we now have at least one good mechanistic explanation for that black box that we’ve been calling “complementarity” for years. But perhaps more importantly, it means that the link between biodiversity and ecosystem functioning is now more real than ever. If plant species go extinct, the remaining ones will be more susceptible to fungal pathogens and productivity will decline. So let’s try to not let that happen, k?

Maron, J. L., Marler, M., Klironomos, J. N. and Cleveland, C. C. , Soil fungal pathogens and the relationship between plant diversity and productivity. Ecology Letters, DOI: 10.1111/j.1461-0248.2010.01547.x

The effects of forest fragmentation after 30 years

Large-scale alteration of nature landscapes has had profound implications for biological diversity. The single biggest contributor to the current extinction crisis is the wholesale destruction of habitats. As habitats are destroyed, formerly contiguous landscapes become fragmented into smaller patches. But what exactly the effects of fragmentation are, independent of habitat destruction, is not always so clear (e.g., Simberloff 2000. What do we really know about fragmentation? Texas Journal of Science 52: S5-S22).

The biological dynamics of forest fragments project (BDFFP) in the Amazon, was started in 1979 and created 11 tropical forest patches ranging from 1 to 100 ha in size. The dynamics of these fragments have been consistently monitored and compared to plots in intact forest. This experiment represents the world's largest, longest-running fragmentation experiment and has told us more about fragmentation then any other study system. In a recent publication by William Laurance and many colleagues involved in this project, they summarize 30 years of data and show how fragmentation affects ecological patterns and processes.
Fragments turn out to be very dynamic and defined by change, compared to interior plots. They have higher tree mortality and are much more susceptible to weather events such as storms or droughts. The effects are especially pronounced at the edges of these fragments. The edge community face high mortality but also have higher tree density. Faunal communities in fragments and especially near edges are depauperate.

One interesting aspect highlighted by this 30 years of research is that the edge effects are strongly influenced by what is happening around the fragments. The fragment edge effects are sensitive to the composition of the inter-patch matrix, giving managers the opportunity to influence fragment diversity and health by managing the matrix in ways that support fragments. Because of over 30 years of perseverance of the researchers involved, this experiment give scientists, managers and policy-makers information to help manage an increasingly fragmented world and to find ways to reduce to negative impacts of habitat destruction.

Laurance, W., Camargo, J., Luizão, R., Laurance, S., Pimm, S., Bruna, E., Stouffer, P., Bruce Williamson, G., Benítez-Malvido, J., & Vasconcelos, H. (2010). The fate of Amazonian forest fragments: A 32-year investigation Biological Conservation DOI: 10.1016/j.biocon.2010.09.021

Carnival of Evolution!

The 29th installment of Carnival of Evolution is here, hosted by Byte Size Biology. Check out recent evolutionary musings and rants from around the blogoshpere.

Grassland diversity increases stability across multiple functions

As ecological systems are altered with cascading changes in diversity, the oft-asked question is: does diversity matter for ecosystem function? This question has been tested a multitude of times, with the results often supporting the idea that more diverse assemblages provide greater functioning (such as productivity, nutrient cycling, supporting greater pollinator abundance, etc.). Besides greater functioning, scientists have hypothesized that more diverse systems are inherently more stable. That is, the functions communities provide remain more constant over time compared with less diverse systems, which may be less reliable.

While the relationship between diversity and stability has been tested for some functions, Proulx and colleagues examined the stability of 42 variables over 7 years across 82 experimental plots planted with either 1, 2, 4, 8, 16 or 60 plant species in Jena, Germany. They examined patterns of variation (and covariation) in the functions and found that many show lower variation over time in plots with more plant species. Greater stability was found at many different trophic levels including plant biomass production, the abundance and diversity of invertebrates and the abundance of parasitic wasps -which indicate more complex food webs. They also found greater stability in gas flux, such as carbon dioxide. Despite the greater stability in these measures of above-ground functions, below ground processes, such as earthworm abundance and soil nutrients, were not less variable in high diversity plots.

How ecosystems function is of great concern; these results show that more diverse plant communities function more stably and reliably than less diverse ones. The next step for this type of research should be to address what kind of diversity matters. A greater number of species means more different kinds of species, with differing traits and functions. What aspect of such functional differences determine stability of ecosystem function?

This is an exciting paper that continues to highlight the need to understand how community diversity drives ecosystem function.

Proulx, R., Wirth, C., Voigt, W., Weigelt, A., Roscher, C., Attinger, S., Baade, J., Barnard, R., Buchmann, N., Buscot, F., Eisenhauer, N., Fischer, M., Gleixner, G., Halle, S., Hildebrandt, A., Kowalski, E., Kuu, A., Lange, M., Milcu, A., Niklaus, P., Oelmann, Y., Rosenkranz, S., Sabais, A., Scherber, C., Scherer-Lorenzen, M., Scheu, S., Schulze, E., Schumacher, J., Schwichtenberg, G., Soussana, J., Temperton, V., Weisser, W., Wilcke, W., & Schmid, B. (2010). Diversity Promotes Temporal Stability across Levels of Ecosystem Organization in Experimental Grasslands PLoS ONE, 5 (10) DOI: 10.1371/journal.pone.0013382

Protecting biodiversity one task at a time: have your say

The fact that the Earth is in the midst of a biodiversity crisis has been repeatedly acknowledged by world governments. The greatest pronouncement was is 2002 with the '2010 Biodiversity Target' where many of the largest economies signed a pledge to halt biodiversity loss by 2010. Yet it is now 2010 and species are continuing to go extinct and habitats are continuing to be destroyed or degraded. But it shouldn't be a surprise that non-binding governmental proclamations fail to produce substantial results. Yet the reality is that we need to do something, inaction only worsens the legacy of biological deficit for future generations.

Maybe the best way forward is not more international governmental summits, but rather focusing on small scale, achievable short term goal. Guillaume Chapron started the Biodiversity 100 campaign, hosted by the Guardian (see story here), which seeks out public and professional input into the 100 immediate and achievable projects or ideas that will help protect biodiversity. The idea is to be able to go to governments and international agencies with this list and get them to make specific pledges to carry out these tasks.

There is till time to participate! If you have an idea of an action to protect biodiversity, fill out the web form. There are already a plethora of great suggestions, from protecting specific habitats to stemming population growth. This list is important because it includes the voices of the international public citizenry and that of scientists. More than that though, there will be a concrete list of tasks (ranging from very local to very global) that citizen groups can use to sustain pressure on governments.

Enhanced biodiversity-ecosystem function relationships in polluted systems

*note: this text was adapted from an Editor's Choice I wrote for the Journal of Applied Ecology.

In this era of species loss and habitat degradation, understanding the link between biodiversity and functioning of species assemblages is a critically important area of research. Two decades of research has shown that communities with more species or functional types results in higher levels of ecosystem functioning, such as nutrient processing rates, carbon sequestration and productivity, among others. This research has typically used controlled experiments that standardize environmental influences and manipulate species diversity. However, a number of people have hypothesized that biodiversity may be even more important for the maintenance of ecosystem functioning during times of environmental stress or change rather than under stable, controlled conditions. It is during these times of environmental change that preserving ecological function is most important, as changes in function can have cascading effects on other trophic levels, compounding environmental stress. Therefore, explicitly testing how biodiversity affects function under environmental stress can help to inform management decisions.

Image from Wikimedia commons

In a recent paper in the Journal of Applied Ecology, Li and colleagues examine how algal biodiversity influences productivity in microcosms with differing cadmium concentrations. Cadmium (Cd) is a heavy metal used in a number of products and industrial processes, but it is toxic and Cd pollution is a concern for human populations and biological systems, especially aquatic communities. This is especially true in nations currently undergoing massive industrial expansion. In response to concerns about Cd pollution effects on aquatic productivity, Li et al. used algal assemblages from single species monocultures to eight species polycultures grown under a Cd-free control and two concentrations of Cd, and measured algal biomass.

Their results revealed that there was only a weak biodiversity-biomass relationship in the Cd-free teatment, which the authors ascribed to negative interactions offsetting positive niche partitioning. In particular, those species that were most productive in their monocultures were the most suppressed in polycultures. However, in microcosms with Cd present there were positive relationships between diversity and biomass. They attribute this to a reduction in the strength of competitive interactions and the opportunity for highly productive species to persist in the communities.

While a plethora of experiments generally find increased ecosystem function with greater diversity, Li et al.’s research indicates that the effect of biodiversity on function may be even more important in polluted systems. If this result can be duplicated in other systems, then this gives added pressure for management strategies to maintain maximal diversity as insurance against an uncertain future.

Li, J., Duan, H., Li, S., Kuang, J., Zeng, Y., & Shu, W. (2010). Cadmium pollution triggers a positive biodiversity-productivity relationship: evidence from a laboratory microcosm experiment Journal of Applied Ecology, 47 (4), 890-898 DOI: 10.1111/j.1365-2664.2010.01818.x