Do green roofs enhance urban conservation?

Green roofs are now commonly included in the design of new public and private infrastructure, bolstered by energy savings, environmental recognition and certification, bylaw compliance, and in some cases tax or other direct monetary incentives (e.g., here).  While green roofs clearly provide local environmental benefits, such as reduced albedo (sunlight reflectance), storm water retention, CO₂ sequestration, etc., green roof proponents also frequently cite biodiversity and conservation enhancement as a benefit. This last claim has not been broadly tested, but existing data was assessed by Nicholas Williams and colleagues in a recent article published in the Journal of Applied Ecology.

Williams and colleagues compiled all available literature on biodiversity and conservation value of green roofs and they explicitly tested six hypotheses: 1) Green roofs support higher diversity and abundance compared to traditional roofs; 2) Green roofs support comparable diversity and composition to ground habitat; 3) Green roofs using native species support greater diversity than traditional green roofs; 4) Green roofs aid in rare species conservation; 5) Green roofs replicate natural communities; and 6) Green roofs facilitate organism movement through urban areas.

Photo by: Marc Cadotte

What is surprising is that given the abundance of papers on green roofs in ecology and environmental journals, very few quantitatively assessed some of these hypotheses. What is clear is that green roofs support greater diversity and abundance compared to non-green roofs, but we know very little about how green roofs compare to other remnant urban habitats in terms of species diversity, ecological processes, or rare species. Further, while some regions are starting to require that green roofs try to maximize native biodiversity, there are relatively few comparisons, but those that exist reveal substantial benefits for biodiverse green roofs.

How well green roofs replicate ground or natural communities is an important question, with insufficient evidence. It is important because, according to the authors, there is some movement to use green roofs to offset lost habitat elsewhere. This could represent an important policy shift, and one that may ultimately lead to lost habitats being replaced with lower quality ones. This is a policy direction that simply requires more science.

There is some evidence that green roofs, if designed correctly, could aid in rare species conservation. However, green roofs, which by definition are small patches in an inhospitable environment, may assist rare species management in only a few cases. The authors caution that enthusiasm for using green roofs to assist with rare species management needs to be tempered by designs that are biologically and ecologically meaningful to target species. They cite an example where green roofs in San Francisco were designed with a plant that is an important food source for an endangered butterfly, Bay Checkerspot, which currently persists in a few fragmented populations. The problem was that the maximum dispersal distance of the butterfly is about 5 km, and there are no populations within 15 km of the city. These green roofs have the potential to aid in rare species conservation, but it needs to be coupled with additional management activities, such as physically introducing the butterfly to the green roofs.

Overall, green do provide important environmental and ecological benefits in urban settings. Currently, very few studies document the ways in which green roofs provide ecological processes and services, enhance biodiversity, replicate other ground level habitats, or aid in biodiversity conservation. As the prevalence of green roofs increases, we will need scientifically valid ecological understanding of green roof benefits to better engage with municipal managers and affect policy.

Williams, N., Lundholm, J., & MacIvor, J. (2014). Do green roofs help urban biodiversity conservation? Journal of Applied Ecology DOI: 10.1111/1365-2664.12333

Data merging: are we moving forward or dealing with Frankenstein's monster

I’m sitting in the Sydney airport waiting for my delayed flight –which gives me some time to ruminate about the mini-conference I am leaving. The conference, hosted by the Centre for Biodiversity Analysis (CBA) and CSIRO in Australia, on "Understanding biodiversity dynamics using diverse data sources", brought together several fascinating thinkers working on disparate areas including ecology, macroecology, evolution, genomics, and computer science. The goal of the conference was to see if merging different forms of data could lead to greater insights into biodiversity patterns and processes. 

Happy integration

On the surface, it seems uncontroversial to say that bringing together different forms of data really does promote new insights into nature. However, this only really works if the data we combine meaningfully complement one another. When researchers bring together data, there are under-appreciated risks, and the resulting effort could result in trying to combine data that make weird bedfellows.

Weird bedfellows

The risks include data that mismatch in the scale of observation, resulting in meaningful variation being missed. Data are often generated according to certain models with specific assumptions, and these data-generation steps can be misunderstood by end-users, resulting in inappropriate uses of data. Further, different data may be combined in standard statistical models, but the linkages between data types is much more subtle and nuanced, requiring alternative models.

Why these are issues stems from the fact that researchers now have an unprecedented access to numerous large data sets. Whether these are large trait data sets, spatial locations, spatial environmental data, genomes, or historical data, they are all built with specific underlying uses, limitations and assumptions.  

Regardless of these issues of concern, the opportunity and power to address new questions is greatly enhanced by multiple types of data. One thing I gained from this meeting is that there is a new world of biodiversity analysis and understanding emerging by smart people doing smart things with multiple data. We will soon live in a world where the data and analytical tools allow research to truly combine multiple processes to predict species' distributions, or to move from evolutionary events in deep history to modern day ecological patterns.

Community structure - what are we missing?

Some of the most frequently used ecological concepts can be difficult to define. Sometimes this lack of clarity leads to a poor understanding and a weak base for further research. A great example is “community structure”, a concept frequently mentioned and rarely defined that probably changes a lot from use to use. The phrase “we’re interested in how communities are structured” is tossed around a lot, and I suppose an understood definition is that community structure encompasses the species that are present in a community and their abundances. Community structure may refer to  both a very simple concept (the abundances of species present in a community) and a very complicated one, connecting as it does mechanisms and models, observational data, and statistical measures. As a result, the precise way that ecologists delineate community structure and quantify it is both varied and vague.

The connection between models, community
structure and metrics.

In the literature, it seems that there are two ways of approaching “community structure”: bottom-up, in which community structure is a predicted outcome of theoretical models of different mechanisms, and top-down, in which community structure is measured in a relatively statistical or descriptive fashion. Both are valuable approaches: while statistical metrics often are interpreted as providing evidence for particular models or mechanisms, the reverse logic – that a model predicts particular results for a given metric – is rarely explicitly considered. Making connections between the model results and the descriptive metrics might actually be fairly difficult. Model predictions are often complex and multidimensional, predicting changes through time, growth rates, the combinations of species that can or cannot coexist (but only if assumptions hold), or particular relationships between measures like diversity, abundances, and range sizes. Metrics are necessarily confined to a few dimensions (or perhaps are ordination approaches), focus on straightforward observational measures like abundance and presence, and further include observational error (sampling, etc). Because community structure means something different to these two approaches, the connections between metrics and models are poorly explored. A theoretician might find it difficult to relate ordinations of communities with the typical predictions from a mathematical model (which might be something like growth rates in relation to changes in abundance), while someone collecting field data might feel that the data they can collect is difficult to relate to the predictions of models.

Part of the problem is that for a long time, the default focus was on what types of interactions structured communities (environment, competition, predation, mutualisms), and niches were assumed to be necessarily driving community structure. The type of measurements and metrics used reflected this search for niches (e.g. comparing environmental gradients with community structure). Many quantitative metrics may tell you something about how community structure relates to different variables (spatial, environment, biotic) and how much variation is still unexplained. The consideration that niches might not always be important eventually led ecologists to compare patterns in community structure to random, null, or neutral expectations. As a result, in the simplest cases the answers to questions about community structure and niches are binary – different from random (niches matter), or not. Looking for complex patterns predicted by models-for example, the relative contribution of niche based and neutral processes to community structure-is difficult using common metrics of community structure (although there are some papers that do a good job of this).

It is interesting that this problem of disconnection between theoretical models of community structure and community structure metrics received the most attention through criticisms of phylogenetic metrics of diversity. There, patterns of over- and under-dispersion were criticized for not being the necessary outcome from models of competition or environmental filtering (i.e. Mayfield and Levine 2010). While those criticisms were mostly fair, they are equally deserved in most studies of species diversity, where patterns in ordinations or beta-diversity are frequently used to infer mechanisms. In contrast, one of the best approaches thus far to integrating model predictions for community structure with metrics of community structure are null models. Though they differ greatly in ecological realism and complexity, null models suggest expected community structure or metric values if none of the expected processes are structuring a community.

One of the greatest failings of the top-down approach is that recognizing patterns outside of the expected, such as those that include stochasticity or a combination of different processes, or the effects of history, is nearly impossible. Models that can incorporate these complexities provide little suggestion of how the patterns we can easily record in communities might reflect complex structuring processes. Ecological research is limited by the poor connection between both top-down and bottom-up approaches and its vague definition of community structure. Patterns more complicated than those that the top-down approach searches for are likely being missed, while relations between models and metrics (or development of new metrics) aren’t considered often enough. One solution might be to more meaningfully define community structure, perhaps as the association (or lack thereof) between the combination of species present in a community and the combination of abiotic and/or biotic processes present. This association is generally compared to an association between species and processes that might arise from random effects alone. The difference is that structure shouldn’t be considered separately from the processes that produce it, and the connections should be explicitly rather than implicitly made.

Why greater diversity – even of parasites – might decrease infections

Pieter T. J. Johnson, Daniel L. Preston, Jason T. Hoverman, and Bryan E. LaFonte. 2013. Host and parasite diversity jointly control disease risk in complex communities. PNAS. Early view.

(Host competence - the tendency of host species to become infected and maintain infection.)

There is often a disconnect between the reality that communities and ecosystems are diverse assemblages with numerous, often complicated and variable interactions, and ecological research, which (perhaps necessarily) focuses on interactions between at most two or three species at a time. Disease ecology similarly has often considered interactions between particular host/parasite species pairs. Some researchers have considered the diversity of host species as an important factor in explaining disease transmission and mortality, but the reality is that parasites also interact, and most hosts harbour multiple parasites. Studying disease dynamics in the context of multi-parasite, multi-host interactions is increasingly recognized as key to understanding disease transmission and severity in communities.

With this in mind, a new paper from Pieter Johnson and colleagues attempts to combine research into the effects of both parasite and host diversity on disease. Two possible hypotheses predict the effect of diversity on disease transmission: the ‘dilution effect’ suggests that the presence of multiple hosts should decrease transmission risk, if the result of additional species is a decline in community competence. It is also hypothesized, somewhat contradictorily, that increased host diversity should support a greater variety of parasites, and parasite life cycles. Both these hypotheses take a host-centric view: understanding how changes in host diversity alter disease risk also requires that we understand how changes in parasite diversity affect disease transmission.

Mutations caused by Ribeiroia infection.
From:http://www.nature.com/scitable/knowledge/library/ecological-consequences-of-parasitism-13255694

The authors looked at the contribution of host and parasite diversity to parasite transmission success using field data and laboratory experiments. First, they looked at existing data on infections of the pathogenic trematode Ribeiroia ondatrae, in amphibian species. Observations showed a positive correlation between larval trematode diversity (parasites) and the richness of free-living species (hosts). Of course the two diversities might be correlated for many unrelated reasons, like site isolation, evolutionary history, or habitat productivity. But a closer analysis showed what appeared to be an interaction between Ribeiroia infection in Pseudacris regilla (Pacific tree frog, the most common amphibian in the survey) and the total number of amphibian species at a site (figure below). Infection by Ribeiroia was highest when there was low amphibian richness and low parasite richness. It dropped significantly lower when amphibian richness was high and/or parasite richness was high.

From Johnson et al. 2013 PNAS. Results of field observations.

In addition to these observations, the authors manipulated both parasite and host species richness, first in small laboratory microcosms and then in larger and more realistic outdoor mesocosms. Results from the laboratory microcosms showed that increases in both amphibian richness (one vs. three species) and parasite richness (one vs. five species) reduced the average number of Ribeiroia in Pseudacris regilla as well as the total infection rate in the amphibian community. The mesocosms had similar results, with both host and parasite diversity negatively influencing Ribeiroia infection. In support of the generality of these results, effect sizes were comparable between the two experiments. These effects were also quite large: for example, in the mesocosm high-host, high-parasite richness treatment there were 52.4% fewer Ribeiroia per P. regilla and 38.2% fewer Ribeiroia overall compared to the low-host, low-parasite richness. Clearly multi-species interactions are crucial for understanding infection by Ribeiroia.

From Johnson et al. 2013 PNAS. Results of the microcosm and mesocosm experiments,
 showing the effects of host and parasite diversity on transmission.

The results make it clear that if you want to understand disease transmission in communities, both host and parasite diversity should be considered. To some extent, both of the initial hypotheses were supported – host and parasite diversity were correlated in the wild, but (in agreement with the dilution effect) infection rates declined as host diversity increased. One factor missing from these hypotheses is the dynamics of the parasite community: in the paper, the authors found models of transmission that included both host and parasite richness were superior. Further, past and future studies that consider only host richness may be inadvertently accounting for the effects of parasite richness on transmission as well, if those two host and parasite diversities are correlated.

There are a number of possibilities for why both host and parasite communities alter parasite transmission success. If host diversity changes the susceptibility of the community to infection (i.e. as diversity increases, the number of low competence/susceptible species increases) then low-competence hosts could act as sinks for parasite infections. Increases in parasite diversity could result in inter-parasite competition and interactions via host immunity.

One future step will be to move beyond simple measurements of species richness to understanding how species identity or characteristics are tied to the putative mechanisms. For example, how do communities of host species vary from low to high diversity sites? Do sites in fact tend to assemble with increasing numbers of low competence host species? The implications are also of interest to other types of studies of community ecology – after all, host-parasite interactions are not very different from predator-prey interactions, and similarly, despite knowing that interactions are complex and involve multiple species, we tend to focus on two or three species examples.

The birds and the bees and the microbes

Vannette et al. 2013. “Nectar bacteria, but not yeast, weaken a plant-pollinator mutualism”. Proceedings of the Royal Society B-Biological Sciences.

"When we try to pick out anything by itself, we find it hitched to everything else in the Universe."- John Muir

You can’t help but marvel at the complexity of ecology, at the intricacy and multiplicity of species interactions. But this complexity is also problematic. For many ecologists, it becomes necessary to focus on a single type of interaction, or on interactions limited to only a few species. But real ecological systems are hardly ever limited to a single important process. They might include competition, mutualism, facilitation, predation, environmental constraints and fluctuations, additive and interactive effects, nonlinearities, thresholds and emergent properties. Can knowledge of  omplexity emerge from simplicity? Can simplicity emerge from complexity? These are important and longstanding questions in ecology, the focus of some of our smartest minds. We may not have the answer yet, but if nothing else, it is helpful when experimental work in community ecology attempts to explore multiple interactions.

For example, some of the work from Tadashi Fukami’s lab is focused on how communities of microorganisms (yeast and bacteria species) assemble in Mimulus aurantiacus nectar. In the past, this work has focused particularly on priority effects and resource competition, which plays an important role in structuring these communities. While past work has suggested the importance of pollinators as a dispersal vector for microorganisms, fascinating new work suggests that microbial communities have important effects on pollinators and their mutualistic interactions with the host plant as well.

Vannette et al. (2013) focused on the effects of the two most abundant species in Mimulus nectar, Gluconobacter sp., an acid-producing bacteria, and Metschnikowia reukaufii, a yeast. They then looked at three related questions – how do nectar microbes affect nectar chemistry, how do they affect nectar removal by hummingbird pollinators, and how to they affect pollination success and seed set. Basically, do nectar microbes disrupt important mutualistic interactions between the plant and their pollinators, or are their effects neutral?

This is where the story becomes interesting. Both types of microbes altered nectar chemistry, but in different ways. The bacteria acidified the nectar (to ~ pH 2.0) far more than the yeast species, and tended to also reduce the sugar content of the nectar far more than the yeast. Hypothesizing that these changes could ultimately affect pollinator preference, the authors then filled artificial flowers with nectar containing either the bacteria, yeast, or no microbes. Half of these flowers were bagged to prevent hummingbird access. Compared to the bagged controls, flowers with bacteria-inoculated nectar had less nectar removed than either yeast-inoculated or sterile nectar. It appeared that nectar removal was related to the changes in chemistry driven by bacterial growth in the nectar. Finally,  the authors looked pollination success in relation to microbial inoculation. Flowers inoculated with bacteria did indeed have less pollination success (measured as the number of stigmas closed) and had decreased seed numbers. Microbial communities were not isolated from the ecology of the plant.

Perhaps none of this is that surprising – hummingbirds are intelligent and will preferentially feed, and pollinator choice is important for plant fitness. However, these bacteria and yeast species are specialized for growth in the hypertonic nectar environment and their continued presence in the ecosystem depends on dispersal from one flower to the next before their host flower dies. The transient nature of this nectar habitat suggests that obtaining a dispersal vector should be important. The fact that Gluconobacter alters nectar chemistry in a way which negatively affects their likelihood of movement to other patches suggests an interesting paradox and a complicated relationship between plants, their nectar microbes, and pollinators. Gluconobacter species growing in Mimulus flowers produce acidifying H+ ions and reduce sugar concentrations in nectar – this increases their likelihood of winning competitive interactions with other microbes in the nectar, which should select for the maintenance of acidifying, sugar-reducing characteristics. But on the other hand, these characteristics reduce the likelihood of being transported to new flowers and persisting in the metacommunity. Further, these pollinator-decreasing characteristics may result in selection by the Mimulus plants for nectar compounds that reduce microbial contamination. So understanding competitive interactions in microbial communities, or understanding pollinator-plant interactions, or understanding pollinator-microbial interactions on their own might be inadequate to understand the important ecological and evolutionary processes structuring the entire system.

Given that the question of simplicity vs. complexity is still so difficult and at least for me, uncertain, I would hesitate to draw a general conclusion about whether this is the kind of work all community ecologists should strive for. But it seems that recognizing ecological and evolutionary context is key, whether you work with Arabidopsis, microcosms, or tropical forests.

The contrasting effects of habitat area and heterogeneity on diversity

“How extremely stupid not to have thought of that!” (Thomas H. Huxley, commenting on the obviousness of Darwin’s theory of natural selection)

Sometimes I read a paper and Huxley’s famous quote seems exceedingly appropriate. Why I say this is that a new idea or concept is presented which seems both so simple and at the same time a potentially powerful explanation of patterns in nature. This was my reaction to a recent paper from Omri Allouche and colleagues published in the Proceedings ofthe National Academy of Science. The paper presents a simple conceptual model, in the same vein as Connell’s classic intermediate disturbance hypothesis, which accounts for large-scale diversity patterns based on aspects of species niche requirements as well as classic stochastic theory. Merging these two aspects is a critical step forward, as in ecology, there has been a tension in explaining diversity patterns between niche-based processes requiring that species exhibit differences in their needs, and stochastic (or neutral) explanations that ignore these differences, but seem to do well at large scales.

The classic stochastic model in ecology, the theory of island biogeography, simply predicted that the number of species increases with the size of an island or habitat, and ultimately is the balance between species colonizing and going extinct. Allouche et al. also assume this stochastic colonization and extinction, such that in a uniform environment, the number of species increases with area. However, they then add the fact that species do not do equally well in different habitats, that is they have specific environmental niches associated with a particular environment. Thus as you increase the amount of heterogeneity in a landscape, you increase the total number of species, because you’ve captured more niches. However, there is a trade-off here. Namely, as you increase the heterogeneity in a landscape, the amount of area for the dominant habitat type decreases, thus reducing the number of species. So if you increase the heterogeneity too much, the individual habitat types will be too small to support large numbers of species and the numbers of species will be less than regions with less heterogeneity –paradoxically.

Their heuristic prediction is that diversity is maximized at intermediate levels of heterogeneity, as long as species have intermediate niche breadths (i.e., they could perhaps use a couple of different habitats). However, if their niche breadth is too narrow (i.e., they can only exist in a single habitat type), then diversity may only decline with increasing heterogeneity. Conversely, if species have very broad niche breadths (i.e., can survive in many different habitats) then the tradeoff vanishes and heterogeneity has little effect on diversity.

They tested this exceedingly simple prediction using European bird data and found that species richness was maximized at intermediate heterogeneity (measured by the variation in elevation). Further, when they classified species into different niche width classes, they found that the relationship between richness and heterogeneity changed was predicted (i.e., strongest for intermediate breadth).

This is a great paper and should have a large impact. It will be exciting to see what other systems fit this pattern and how specific studies later the interpretation or mechanisms in this model.

Allouche, O., Kalyuzhny, M., Moreno-Rueda, G., Pizarro, M., & Kadmon, R. (2012). Area-heterogeneity tradeoff and the diversity of ecological communities Proceedings of the National Academy of Sciences, 109 (43), 17495-17500 DOI: 10.1073/pnas.1208652109

Justifying assumptions: tests of seed size/mass tradeoffs

Ben-Hur, E. et al. 2012. Functional trade-offs increase species diversity in experimental plant communities. Ecology Letters. DOI: 10.1111/j.1461-0248.2012.01850.x

When ecologists develop theory and models, we generally need to make assumptions. The nicest definition of an assumption is that they are the framework we use to capture our beliefs about a system. All future analyses will treat these assumptions as true, and so ultimately the validity of a model is tied to the validity of its assumptions. As Joseph Connell said: “Ecological theory does not establish or show anything about nature. It simply lays out the consequences of certain assumptions. Only a study of nature itself can tell us whether these assumptions and consequences are true.” Often times the most interesting advances in ecology come when we questions popular assumptions, such as that species are ecologically different, that interspecific differences are more important than intraspecific differences, or that ecological interactions occur much more rapidly then evolutionary changes. 

Assumptions in models and theory can often serve as a sort of shorthand for ideas that there is some general evidence for, but for which comprehensive data may be lacking. Community ecology is full of assumptions about functional tradeoffs that mediate coexistence between species. Various assumptions about plant species coexistence include that species experience tradeoffs between competition and colonization, growth versus reproduction, or seed size versus seed number. A simplistic explanation for such tradeoffs is that you can’t do everything well: a strong competitor can’t be a good colonizer too, which creates opportunities for strong colonizers but poor competitors, etc.

Tests of these functional tradeoffs are lacking, or lag behind the theory that relies on them. For example, the idea that there should be a tradeoff between seed size and seed number has long been proposed to explain why plants have highly variable seed sizes. Plants with small seeds should produce more offspring, and these seeds should be more successful at reaching empty sites. Large seeded species should be more competitive in the seedling stage or more tolerant of difficult conditions, and so have higher survival. Theoretical models that rely on such a tradeoff suggest that many species could co-exist and that the resulting community would exhibit a wide variety of seed sizes. 

But though many studies and theories depend on this assumed tradeoff, a comprehensive experimental test was lacking. Ben-Hur et al. have finally provided such an experiment, testing the basic prediction that a negative correlation between seed size and seed number should increase species richness. They also tested whether small-seeded species were more likely to remain in the community when this tradeoff existed, increasing the amount of among-species variation in seed size. To do so, the authors created 3 ‘community treatments’ of 15 plant species. The abundance of each species in the starting seed mix was manipulated to create either (1) positive correlation between seed mass and seed number; (2) negative correlation between seed mass and seed number or (3) random allocation of the 15 species regardless of seed size.

From Ben-Hur et al. 2012. Ecology Letters. a) Final number of species in the community, when the correlation between seed size and seed number is negative, random, or positive. b) Seed mass distribution in community under positive correlation between seed size and seed number (left), and negative correlation (right). 

Ben-Hur et al.’s results strongly suggest that a seed size/seed mass functional tradeoff can increase species richness (figure, a). Further, when there is such a tradeoff, the variation in seed size represented in a community increases, again in agreement with predictions (figure, b). The results are particularly convincing because the authors used experimental manipulation of the strength of the correlation (i.e. from negative to positive) to test its importance. The authors suggest that the tradeoff they simulated did not involve competitive differences (i.e. was not a competition-colonisation tradeoff), and more likely reflects a trade-off in establishment probability and colonisation (Dalling and Hubbell 2002; Muller-Landau 2010).

Of course, these results represent relatively short-term coexistence, and community richness may have changed had the experiment been allowed to continue for longer. But as a starting point, this suggests that theories that rely on functional tradeoffs in seed characteristics to explain coexistence are capturing a mechanism that has some experimental support. 

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 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.

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.

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).

(click image for larger view)

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

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.

How can evolution inform conservation decisions?

First of all, let me apologize for the lack of blog posts over the past 2 weeks, I've been busy visiting the Olympics and reading a couple of hundred blogs, judging them for the Research Blogging awards.

The conservation of biological diversity is a major imperative for biologists. International agreements such as the Convention on Biological Diversity and intergovernmental exercises, such as the Millennium Ecosystem Assessment, call upon scientists to provide evidence on the current state of biological diversity and to evaluate solutions for reducing diversity and ecosystem function loss. Critical to these efforts have been the work of ecologists, conservation biologists and ecological economists. However, seemingly missing from the conversation about the state of biodiversity knowledge has been evolutionary biologists. Are they primarily concerned with describing historical processes and mechanisms of biological change, or do they have substantive knowledge and ideas that should be viewed as a critical component of any scheme to conserve biological diversity?

In a recent paper in Evolution, Hendry and a number of coauthors convincingly make the case that evolutionary biology is a necessary component for conservation. Evolution offer four key insights that should inform conservation and policy decisions. First, they point out that evolutionary biologists are in the business of discovering and documenting biodiversity. They are the primary drivers behind long-term, sustained biological collections, because they need to know what exists in order to better understand evolutionary history. With millions of species awaiting scientific discovery, their efforts are critical to measuring biodiversity. But not only are they discovering new species and enumerating them, they are uncovering their evolutionary relationships, which gives conservationists better information about which species to prioritize. What Vane-Wright famously called 'the agony of choice', with limited resources, we need to prioritize some species over others, and their evolutionary uniqueness ought to be a factor. More than this, evolutionary biologists have developed pragmatic tools for inventorying and sharing data on biodiversity at all levels, from genes to species, which is available for prioritization.

The second key insight is that by understanding the causes of diversification, we can better understand and predict diversity responses to environmental and climatic change. By understanding how key functional traits evolve, we can develop predictions about which species or groups of species can tolerate certain perturbations. Further, research into how and why certain evolutionary groups faced extinction can help us respond to the current extinction crisis. For example, the evolutionary correspondence between coevolved mutualists, such as plants and pollinators, can be used to assess the potential for cascading extinctions. These types of analyses can help identify those groups of related species, or those possessing some trait, which make species more susceptible to extinction.

Thirdly, evolution allows for an understanding of the potential responses to human disturbance. Evolutionary change is a critical part of ecological dynamics, and as environment change can result in reduced fitness, smaller population sizes and extinction, evolution offers an adaptive response to these negative impacts. Knowing when and how populations can evolve is crucial. Evolutionary change is a product of genetic variation, immigration, population size and stochasticity, and if the ability to evolve to environmental change is key for persistence, then these evolutionary processes are also key.

Finally, evolutionary patterns and processes have important implications for ecosystem services and economic and human well-being. Both genetic and evolutionary diversity of plant communities has been shown to affect arthropod diversity, primary productivity (including work by me) and nutrient dynamics. Thus understanding how changes in diversity affect ecosystem processes should consider evolutionary processes. Further, exotic species are often cited as one of the major threats to biodiversity, and evolutionary change in exotics has been shown to increase exotic impacts on native species.

All together, these key reasons why evolution matters for conservation, mean that developing sound management plans requires considering evolution patterns and processes. We can use evolution to our benefit only if we understand how evolution shapes current dynamics. The challenge to evolutionary biologists is the same as it was for ecologists perhaps 15 to 20 years ago, to present their understanding and conservation ideas to a broader audience and to engage policy makers. To this end, the authors highlight some recent advances in incorporating evolutionary views into existing biodiversity and conservation programmes –most notably into DIVERSITAS.

Just like ecological processes and dynamics cannot be fully understood without appreciating evolution ancestry or dynamics, developing an extensive, expansive conservation strategies must take into account evolution. I hope that this paper signals a new era of a synthesis between ecology and evolution, which produces precise, viable conservation strategies.

Hendry, A., Lohmann, L., Conti, E., Cracraft, J., Crandall, K., Faith, D., Häuser, C., Joly, C., Kogure, K., Larigauderie, A., Magallón, S., Moritz, C., Tillier, S., Zardoya, R., Prieur-Richard, A., Walther, B., Yahara, T., & Donoghue, M. (2010). EVOLUTIONARY BIOLOGY IN BIODIVERSITY SCIENCE, CONSERVATION, AND POLICY: A CALL TO ACTION Evolution DOI: 10.1111/j.1558-5646.2010.00947.x

Double or nothing

As I finished my undergrad career and started thinking about graduate school, I was totally infatuated with the chromosomal speciation of treefrogs in the genus Hyla. Hyla versicolor and H. chrysoscelis, the 'gray treefrogs', have similar geographic distributions and look almost identical - except that one is a tetraploid version of the other. The increase in genome size is associated with a slight increase in cell size, which has trickle-down effects into physiology, the sound of their call, and other ecological factors, and of course they are reproductively isolated. As it turns out, Margaret Ptacek and colleagues were unraveling this mystery at the genetic level just as I was learning of it, and while I was disappointed not to be able to explore this for my graduate work, Margaret made up for it by paying for all the drinks when I visited Clemson a few years back.

So it was with considerable interest that I stumbled across one of the first tables of contents of the new year, in BMC Evolutionary Biology. Two co-occurring populations of the diatom Ditylum brightwellii, it turns out, differ in genome size. In this case, the belief is that there is a single taxonomic species harboring a very recent genome duplication polymorphism (which are likely cryptic species). Of course, a species by any other name... well, that's the problem isn't it? In the world of diatoms, according to Koester and colleagues, the 'barcode' standard is to use the 18S rDNA gene sequences and silica cell wall morphology in diagnosing species. However, already armed with evidence that two substantially distinct populations could be identified with the more rapidly-evolving ITS gene region, these researchers explored how differences in reproductive rates and size distributions might be associated with genome size.

See, diatoms are the petri dishes of the natural world. In order to reproduce, each side of the interlocking silica case separates and generates a new nested case. One of the offspring of this fission will be the same size as the parental individual, the other will be slightly smaller - the smaller of the two original cell walls, with an even smaller one nested within. At least that is how I understand it. Over time, these clonal lineages reduce substantially in size, and cell size is eventually limited by genome size; sexual reproduction then allows them to regain a larger cell size and the process repeats. So, the life history of this species requires an interesting interaction among the genome (which places a lower bound on cell size, and a lower bound on reproductive rate) and the population.

In Ditylum, Koester et al. were able to show that there are not only two very distinct genetic lineages, but that the one that is regionally localized to Puget Sound appears to have been generated through genome duplication. That is, there is a cosmopolitan species, and an offshoot lineage that was formed through some form of genome duplication, with concomitant changes in cell size, rates of population growth, and reproductive isolation. Koester et al. conclude that these lineages are cryptic species, and that this form of isolation may be common in marine diatoms.

More generally, this shows another way in which our understanding of biodiversity is changing rapidly thanks to molecular diversity analysis. The latest term to be coined by John Avise, biodiversity genetics, reflects the fact that we must now consider all of the new ways in which this technology can accelerate the rate of discovery in our natural world. Taxonomists trained in the morphology and phenotypic diversity of life are few; certainly too few to keep up with growing scientific collections, and the bottleneck in describing species can be a difficult one for management and conservation. The '18S or bust' approach in diatoms may be one standard that will change as more studies like this one, out of Armbrust's lab at Washington, illuminate how dynamic biological diversity can be.

Eco-label Promotes Biodiversity on Farms

At first glance, potato farms might seem like an unlikely candidate for conservation efforts.

But Wisconsin researchers are demonstrating that biodiversity can be restored even in the midst of large-scale farming.

Paul Zedler, professor of Environmental Studies at the University of Wisconsin (UW)-Madison, and his colleagues are working with potato farmers to restore pre-settlement habitats on growers’ lands.

In central Wisconsin, 42,600 acres are devoted to potatoes. Since the landscape is dominated by agriculture, some proportion of farmland must be set aside for conservation to preserve biodiversity in this part of the state.

Restoration is a requirement of the Wisconsin Healthy Grown potato program, a partnership between UW–Madison, the Wisconsin Potato and Vegetable Growers’ Association, and NGOs such as the International Crane Foundation, Defenders of Wildlife, and the World Wildlife Fund.

The groundwork for the Healthy Grown program was laid out in the 1980s, when a group of potato growers voluntarily discontinued use of the high-risk pesticide aldicarb. The farmers turned to UW-Madison researchers for pest-management advice. This grassroots movement eventually drew attention from conservation agencies.

To be certified under the Healthy Grown eco-label, potatoes must be grown under a set of standards that restrict pesticide and fertilizer use. The program was able to draw from an extensive body of UW-Madison research to guide the formulation of these in-field standards. But farmers and environmentalists were interested in doing more.

Since the program's conception, growers had expressed interest in managing their farms as whole ecosystems rather than just focusing on crop production on a field by field basis. At the same time, the NGOs saw the program as an opportunity to bring farmland into regional-scale conservation plans.

Satisfying this interest in developing a conservation standard for the eco-label was challenging for researchers because fewer precedents existed. Even the largest and most well-known eco-label, USDA Organic, does not include a conservation requirement in its certification standards.

Zedler and his colleagues looked to the Nature Conservancy, which had established a system for making strategic conservation decisions and measuring conservation success at sites where the objective is to improve biodiversity on whatever land can be spared from intensive human use.

Potato farms in central Wisconsin are unusual in their tendency to contain significant patches of marginal land without crops because these patches cannot be irrigated – a necessary factor in growing potatoes. The result is a complex mosaic of land in which remnant patches of disturbed natural habitat are isolated within an agricultural matrix. Zedler and his colleagues focused their research efforts on these patches of non-crop land.

Their research suggests that prescribed burns and control of invasive plant species can help restore disturbed non-crop land to the habitats that characterized central Wisconsin before European settlement: prairie, oak-pine savannah, and sedge meadow.

Thus far, the Healthy Grown program has restored more than 400 acres of privately owned farmland. According to Zedler and his colleagues, farmers’ strong ties to their land motivate their commitment to the conservation standard of the Healthy Grown eco-label.

Zedler, P. H., T. Anchor, D. Knuteson, C. Gratton, and J. Barzen. 2009. Using an ecolabel to promote on-farm conservation: the Wisconsin Healthy Grown experience. International Journal of Agricultural Sustainability 7(1): 61-74. DOI:10.3763/ijas.2009.0394

(Image courtesy of FotoosVanRobin at flickr under a Creative Commons license)