Tuesday, March 29, 2016

What are important directions for ecology?

I was recently asked “what is the most important problem in ecology?”. I was dissatisfied with whatever I ended up answering, so it has been on my mind. I think there is an analogy with medicine here – it’s a little like asking a medical scientist “what is the most important disease to cure?” Similarly, there are multiple possible answers, and the one you give will depend on your area of interest/what type of doctor you are. (I also assume this is a question about basic research, and the answer is not as simple as saying, stop extinctions or prevent habitat loss).

Levels of biological organisation.
The medical analogy breaks down a little because ecology is *far* more complicated than medical science. Medicine has a foundation in anatomy and physiology, which in turn rely on basic sciences like cell biology and genetics. This creates a reasonably constrained framework within which further learning/investigation can be organized. Medicine typically stops at the level of the individual, but ecology inherently involves many additional levels of organization (from individuals, to populations, to species and communities, to ecosystems, and beyond). Within any one of these higher levels of organization (population, community, ecosystem), there can be such an immense amount of variation in outcomes and dynamics that ecologists can lose sight of connections with lower and higher levels. For example, community ecology encompasses so much complexity on its own, that also considering the impacts of population level processes and on ecosystem level processes is a tall order. But, we should also appreciate, given these barriers to understanding, just how far ecology has actually advanced in the last 100 years. The combination of reductionist experiments and descriptive work at all scales has been immensely successful (e.g. see this blog post for a partial list). Many general tools have been developed that we can then use to answer specific ecological questions (the integration with statistics with ecology has been highly successful; the use of specific mathematical models). Still, the ability to reconcile multiple levels of organization and scales still limits ecology.

This is a problem that cell biology has also experienced, and is now approaching via systems biology: "The reductionist approach has successfully identified most of the components and many of the interactions but, unfortunately, offers no convincing concepts or methods to understand how system properties emerge...the pluralism of causes and effects in biological networks is better addressed by observing, through quantitative measures, multiple components simultaneously and by rigorous data integration with mathematical models"(1): to me, this quote rings so true for ecology as well. Systems biology uses mechanistic, mathematical and computational models to attempt to represent multi-scale complexity.

Of course, the optimism about systems biology might be premature in that it hasn’t produced many useful models yet, such that it may be “more of an agenda than a body of results.”. Some of the best “systems ecology” (e.g. meta-ecosystem models) are very system specific and data-heavy (e.g. 2). Can they inform us about generality in ecology?

All of which is to say, I think the most important problems in ecology relate to this need to make the connections between studies and systems and levels of organization. But, doing so may be difficult.

More specific problems

1. The scaling of ecological processes. Many ecologists include a line about being ‘interested in questions of scale’ on their website blurbs. Despite this, our understanding of the aggregate outcome of multiple processes that are occurring at different spatial or temporal scales remains limited, and poorly predictive. There have been a few useful starts (particularly in Peter Chesson’s scale transition papers (3, 4)), but recent theoretical interest seems to be low. We have data at the community scale, and data at the macro-scale. How do we connect these (and can we)? Models describing how processes occurring at smaller scales produce larger scale dynamics can be complex: they may include non-linearities, autocorrelation between regions, the combination of discrete and continuous events, and multiple attractors.

2. Mechanisms maintaining multi-species coexistence in the real world. Hutchinson’s paradox of the plankton remains unsolved*. Community ecologists have invested a lot of time and energy into understanding species interactions as seen in natural communities. To explore the mechanisms behind coexistence, usually (but not always) ecologists have focused on two-species interactions (or maybe 3): understanding coexistence in larger groups tends to be mostly restricted to theory. But fitting the individual pieces into the larger puzzle is exponentially more difficult: in observed large groups of interacting species, what is the relative contribution of the many coexistence mechanisms identified? Which mechanisms are most important, and how do they change through space and time?
*Perhaps not surprisingly, given it is a paradox...

3. Moving farther away from species. In so many ways, focusing on ‘species’ as the unit of measurement is limiting, because ‘species’ is a discrete term and ecology is interested in quantitative measures. Important advances have been made by redefining ecology as the outcome of species traits and species interactions (5). But I think our ability to connect these ideas more closely to species’ multidimensional niches can still improve. In particular, understanding that traits and interactions can change in context-dependent ways (plasticity, ontogeny, environment) will be important (6, 7).

4. Reproducibility of ecological research. This is more of a philosophical question - how do we achieve reproducibility in a science where context-dependence, alternative stable states, chaos and stochasticity all affect results? How do we differentiate between reproducibility (same results under identical conditions) and generality (same results under similar conditions) in results?

References:
1) Sauer, Uwe; Heinemann, Matthias; Zamboni, Nicola. Genetics: Getting Closer to the Whole Picture. Science 316 (5824): 550–551. doi:10.1126/science.1142502. PMID 17463274.

2) Dominique Gravel, Frédéric Guichard, Michel Loreau and Nicolas Mouquet. Source and sink dynamics in meta-ecosystems. Ecology 91(7): 2172-2184.

3) Chesson, Peter. Scale transition theory with special reference to species coexistence in a variable environment. Journal of biological dynamics 3.2-3 (2009): 149-163.

4) Melbourne, Brett A., and Peter Chesson. The scale transition: scaling up population dynamics with field data. Ecology 87.6 (2006): 1478-1488.

5) McGill, Brian J., et al. Rebuilding community ecology from functional traits. Trends in ecology & evolution 21.4 (2006): 178-185.

6) Poisot, T., Canard, E., Mouillot, D., Mouquet, N., Gravel, D. & Jordan, F. (2012) The dissimilarity of species interaction networks. Ecology letters, 15, 1353–61.

7) Siefert, A., Violle, C., Chalmandrier, L., Albert, C.H., Taudiere, A., Fajardo, A., Aarssen, L.W., Baraloto, C., Carlucci, M.B., Cianciaruso, M.V. and L Dantas, V. A global meta‐analysis of the relative extent of intraspecific trait variation in plant communities. Ecology letters 18.12 (2015): 1406-1419.

Wednesday, March 23, 2016

The evolutionary canary in the coal mine*

*note -this post originally appeared on the Applied Ecologist's blog

Like canaries in coal mines, species can provide important information about deteriorating environmental conditions. A whole sub-discipline of environmental biomonitoring has emerged to provide the necessary tools to evaluate biological responses to changes in environmental conditions. While historically biomonitoring focused on contaminant concentrations in sentinel species –such as heavy metals in clams; modern biomonitoring uses information across multiple biological levels of organisation, from tissues, to organism behaviour, to the abundances and distributions of species. Since it is impossible to assess every aspect of an ecosystem’s response to pollution, scientists and practitioners still need to make decisions about which elements of an ecosystem should be monitored.
A coal miner with a canary –the classic sentinel species (url for photo: http://www.academia.dk/Blog/wp-content/uploads/CanaryInACoalMine_2.jpg)

In freshwater systems, diatoms are often the preferred organisms for monitoring since they have high diversity and diatom communities are structured strongly by local environmental conditions. Because of their long use in biomonitoring, freshwater biologists have sensitivity and indicator values for thousands of diatom species. Thus, in principle, you should be able to sample diatom communities in lakes and rivers of interest, and then assess the water quality based on the presence and abundance of different diatom species. While such proxies should always be validated and interpreted carefully (Stephens et al. 2015), there is a long and successful history of using diatoms for environmental monitoring.
Image of diatoms from a scanning electron microscope. (By Kostas Tsobanoglou - Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=45315566)
The difficulty in practice is to identify diatom species, which requires expert training and can be time consuming. A number of researchers have pursued proxies and surrogates, for example using life form (e.g., diatom shape) or higher taxonomic groupings, instead of identifying species (Wunsam, Cattaneo & Bourassa 2002). In a recent article in the Journal of Applied Ecology, Francois Keck and colleagues (Keck et al. 2016) take this one step further, by using diatom evolutionary relationships as the biomonitoring tool.

Keck et al. employ novel statistical methods to create clusters of species based on their evolutionary relatedness from a phylogenetic tree and species’ sensitivity to pollution and show that these clusters, when delineated by short to moderate phylogenetic distances, do a good job of replicating species-level community pollution sensitivity indices.

This may seem like a onerous task, to assign diatoms to a correct position on a phylogenetic tree, but with the availability and now widespread use of DNA barcoding techniques, it is becoming easier to get genetic data for microscopic assemblages than to identify cells to species. This means that samples can be fit to the phylogenetic clusters without needing to shift through samples. Further, if species are observed, which have not been properly assessed for their sensitivity, they can be assigned an expected sensitivity value based on their relatedness to assessed species.
The phylogenetic tree and species’ sensitivities (Fig. 2 in Keck et al.).
While diatom evolutionary history may not have been strongly influenced by environmental pollutants in the past –because they are relatively recent stressors; it is clear from Keck et al.’s results that closely related species are similarly sensitive to pollution. Other fields of applied management have also begun to incorporate evolutionary history in the design and assessment of applied actions –for example, restoration (Hipp et al. 2015). Evolutionary history can provide important insights and management tools for dealing with the consequences of environmental change.


References

Hipp, A.L., Larkin, D.J., Barak, R.S., Bowles, M.L., Cadotte, M.W., Jacobi, S.K., Lonsdorf, E., Scharenbroch, B.C., Williams, E. & Weiher, E. (2015) Phylogeny in the Service of Ecological Restoration. American Journal of Botany, 102, 647-648.
Keck, F., Bouchez, A., Franc, A. & Rimet, F. (2016) Linking phylogenetic similarity and pollution sensitivity to develop ecological assessment methods: a test with river diatoms (microalgae). Journal of Applied Ecology.
Stephens, P.A., Pettorelli, N., Barlow, J., Whittingham, M.J. & Cadotte, M.W. (2015) Management by proxy? The use of indices in applied ecology. Journal of Applied Ecology, 52, 1-6.
Wunsam, S., Cattaneo, A. & Bourassa, N. (2002) Comparing diatom species, genera and size in biomonitoring: a case study from streams in the Laurentians (Quebec, Canada). Freshwater Biology, 47, 325-340.


Wednesday, March 9, 2016

Debating limits on diversity in class

I wrote a while ago about the debate on whether global diversity has ecological limits, based on two papers from Harmon and Harrison, and Rabosky and Hurlbert. This was in turn based on a debate from the ASN meeting (aside: there should be more formal debates at conferences). I decided to try replicating this debate in the Advanced Ecology class I'm teaching with Kendi Davies, and I was pleasantly impressed with the outcome. The class is mostly upper year students and small (~25 people), and the focus is on reading the primary literature and exploring key topics in ecology using active learning techniques (e.g. 1, 2). Since we're reading about patterns and processes of diversity through space and time, the debate topic was fitting.

The debate was split over two classes - in the first, students were split into two groups and they prepared their opening and closing statements and their supporting arguments. I've tried having students use Google documents and slides for these kind of group collaborative activities, and it seems to work well. (This is in part because there are 'lender laptops' available from the department's IT, which means that all students can participate, even without owning a personal laptop). What is great about Google docs is that when anyone adds or removes or edits text, the other members of the group can see it in real time, which seems to encourage more students to be actively involved than if, say, a single student is taking notes. Each group decided who would present the opening statement, each supporting argument, the rebuttal statement, and the closing statement, and who would take notes and prep the rebuttal.

To raise the stakes a bit, the winning team would get a pass on one homework assignment (the other motivator presumably being fear of letting their group down). What impressed me was how engaged students were during prep and during the actual debate. (For example, during prep, students were watching videos on how to debate, and expressed some concerns about espionage by the other teams ;-) ) More seriously, they took the time to understand the arguments presented in the source literature, and went beyond that to integrate support from other primary literature. I think at times students (okay, most of us) can get away with skimming papers for the key points: this rewarded them for reading carefully and thoughtfully.
Current US political debates provided instruction
on what not to do (from cnn.com).

The judges were a few generous postdocs (motivated by the promise of free food), who not only scored the debates, but gave some feedback to the teams. Ironically, the winning team had argued that “Species Diversity Is Dynamic and Unbounded at Local and Continental Scales” (after Harmon and Susan Harrison), but the class was nearly unanimous that they personally felt that there likely were ecological limits on diversity.

What I would do differently next time:

  • Plan some redundancy - a couple of people were sick, etc, who had roles in the debate. This left team members scrambling a bit. 
  • Group sizes: 12 people is a bit big for a group and makes coordination difficult. It might be possible to have smaller groups and do 2 sets of debates. Or, alternatively, to assign half the class as judges (or press - another prof here uses students as press who have to prepare questions for the debaters).
  • Consider not randomly assigning people to groups - it might be better to try to balance teams.
  • Public speaking and argument logic - interestingly, most of the students have little experience in constructing convincing and well supported arguments. We talk a lot about hypothesis construction with STEM students, but persuasive speech and writing receive less attention. Things like 'signposting' important points could use more practice.

Friday, March 4, 2016

Pulling a fast one: getting unscientific nonsense into scientific journals. (or, how PLOS ONE f*#ked up)

The basis of all of science is that we can explain the natural world through observation and experiments. Unanswered questions and unsolved riddles are what drive scientists, and with every observation and hypothesis test, we are that much closer to understanding the universe. However, looking to supernatural causes for Earthly patterns is not science and has no place in scientific inquiry. If we relegate knowledge to divine intervention, then we fundamentally lose the ability to explain phenomena and provide solutions to real world problems.

Publishing in science is about leaping over numerous hurdles. You must satisfy the demands of reviewers and Editors, who usually require that methodologies and inferences satisfy strict and ever evolving criteria -science should be advancing. But sometimes people are able to 'game the system' and get junk science into scientific journals. Usually, this happens by improper use of the peer review systems or inventing data, but papers do not normally get into journals while concluding that simple patterns conform to divine intervention.

Such is the case in a recent paper published in the journal PLOS ONE. This is a fairly pedestrian paper about human hand anatomy and they conclude that anatomical structures provide evidence of a Creator. They conclude that since other primates show a slight difference in tendon connections, a Creator must be responsible for the human hand (well at least the slight, minor modification from earlier shared ancestors). Obviously this lazy science and an embarrassment to anyone that works as an honest scientist. But more importantly, it calls into question the Editor who handled this paper (Renzhi Han, Ohio State University Medical Center), but also PLOS ONE's publishing model. PLOS ONE handles thousands of papers and requires authors to pay for the costs of publishing. This may just be an aberration, a freak one-off, but the implications of this seismic f$@k up, should cause the Editors of PLOS to re-evaluate their publishing model.  

Wednesday, March 2, 2016

What explains persistent species' rarity in communities?

Someone asked me what is the most important or lingering issue in community ecology recently. (There’s probably a whole post to answer that question (to come...)). One answer is the mystery of species coexistence: for more than 50 years (from Hutchinson’s paradox of the plankton through today) we have tried to explain the immense and variable diversity on earth by understanding what allows two or more species to coexist. There are many ways to explain coexistence, and yet the details and the specifics for any given system are also still usually incompletely understood.

A good and fascinating example is that of persistent rarity. Why are so many species in communities rare? What allows species to remain rare for long periods of time, given that small populations should be at greater risk for stochastic extinction? A new preprint from Yenni et al. (1) considers the empirical evidence for one potential explanation for persistent rarity: asymmetric negative frequency dependence (see also Yenni et al. 2012 (2)).

Coexistence theory (Chesson 2000) considers stabilizing mechanisms to be those that allow intraspecific competition to be greater than interspecific competition (often defined as ‘niche’ mechanisms). The strength of such stabilizing mechanisms can be estimated by looking at how a species’ population growth rate is limited by the frequency of conspecifics compared to the frequency of heterospecifics in the community. Negative frequency dependence is expected when stabilizing mechanisms are strong. This allows species to increase when rare, since limitation by conspecifics is low, followed by a decline in growth rates as conspecific frequency increases.

Asymmetric negative frequency dependence may explain persistent rarity, since it suggests especially strong conspecific limitation. As a species’ frequency increases, their growth rate greatly declines and intraspecific interactions, rather than interspecific competition, determine abundances. Species are rare, but also less likely to experience extinctions through competition with other species. The authors suggest that as a result of this, we should expect rare species to have stronger negative frequency dependence, in comparison to more common species. They look for evidence for asymmetric frequency dependence using data from 148 communities collected across multiple taxonomic groups (birds, fish, herpetofauna, invertebrates, mammals, and plants), 5 continents, and 3 trophic levels. The data represented time series of species abundances, which the authors used to estimate negative frequency dependence as the relationship between a species’ frequency in the community and their annual per capita population growth rate.

Several aspects of the results are particularly interesting. First, the authors had to omit rare species that are not persistent, since other processes likely explain the presence of such ephemeral members of communities. The frequency of ephemeral species (not stably coexisting at a local scale), for example, was quite high, particularly in plant communities (average of 82 species per community, of which only 22.6 species were on average identified as ‘persistent’). This may suggest the importance of spatial mechanisms for coexistence or co-occurrence. Their overall prediction of stronger negative frequency dependence in rare species appeared to holds in 46% of the communities they examined, consistently for all of the taxonomic groups but one (herps!). Additionally, the opposite pattern (common species having stronger negative frequency dependence) was never observed.

Rarity in nature is common :-) but not well predicted using most coexistence theory. Many interesting and important questions arise from it, and from results like those shown in Yanni et al. For example, do rare species have rare traits or rare niches? Is the frequency dependent growth rate context dependent (i.e. can a species be strongly limited by conspecifics in one environment but not another)?

*Note I haven’t reproduced any figures here, since this is a preprint. However, it is openly available, so do have a look (link 1 below). I’m not certain if there is a rule of thumb on blogging about preprints, but I imagine it is much like blogging about conference talks. The work may not have been peer reviewed/published yet, but the broad results and ideas remain interesting to discuss.

References:

1. Glenda Yenni, Peter Adler, Morgan Ernest. Do persistent rare species experience stronger negative frequency dependence than common species? doi: http://dx.doi.org/10.1101/040360. Preprint.

2. Yenni, Glenda, Peter B. Adler, and S. K. Ernest. "Strong self‐limitation promotes the persistence of rare species." Ecology 93.3 (2012): 456-461.