Monday, August 25, 2014

Researching ecological research

Benjamin Haller. 2014. "Theoretical and Empirical Perspectives in Ecology and Evolution: A Survey". BioScience; doi:10.1093/biosci/biu131.

Etienne Low-D├ęcarie, Corey Chivers, and Monica Granados. 2014. "Rising complexity and falling explanatory power in ecology". Front Ecol Environ 2014; doi:10.1890/130230.

A little navel gazing is good for ecology. Although maybe it seems like it, ecology spends far less time evaluating its approach, compared to simply doing research. Obviously we can't spend all of our time navel-gazing, but the field as a whole would benefit greatly from ongoing conversations about its strength and weaknesses. 

For example, the issue of theory vs. empirical research. Although this issue has received attention and arguments ad nauseum over the years (including here, 1, 2, 3), it never completely goes away. And even though there are arguments that it's not an issue anymore, that everyone recognizes the need for both, if you look closely, the tension continues to exist in subtle ways. If you have participated in a mixed reading group did the common complaint “do we have to read so many math-y papers?" ever arise; or equally “do we have to read so many system specific papers and just critique the methods?” Theory and empirical research don't see eye to eye as closely as we might want to believe.

The good news? Now there is some data. Ben Haller did a survey on this topic that just came out in BioScience. This paper does the probably necessary task of getting some real data beyond the philosophical and argumentative about the theory/data debate. Firstly, he defines empirical research as being involved in the gathering and analysis of real world data, while theoretical research does not gather or analyze real world data, instead involves mathematical models, numerical simulations, and other such work. The survey included 614 scientists from related ecology and evolutionary biology fields, representing a global (rather North American) perspective.

The conclusions are short, sweet and pretty interesting: "(1) Substantial mistrust and tension exists between theorists and empiricists, but despite this, (2) there is an almost universal desire among ecologists and evolutionary biologists for closer interactions between theoretical and empirical work; however, (3) institutions such as journals, funding agencies, and universities often hinder such increased interactions, which points to a need for institutional reforms."
For interpreting the plots – the empirical group represents respondents whose research is completely or primarily empirical; the theoretical group's research is mostly or completely related to theory, while the middle group does work that falls equally into both types. Maybe the results don't surprise anyone – scientists still read papers, collaborate, and coauthor papers mostly with others of the same group. What is surprising is that this trend is particularly strong for the empirical group. For example, nearly 80% of theorists have coauthored a paper with someone in the empirical group while only 42% of empiricists have coauthored at least one paper with a theorist. Before we start throwing things at empiricists, it should be noted that this could relate to a relative scarcity of theoretical ecologists, rather than insularity on the part of the empiricists. However, it is interesting that while the responses to the question “how should theory and empiricism coexist together?” across all groups agreed that “theoretical work and empirical work would coexist tightly, driving each other in a continuing feedback loop”, empirical scientists were significantly more likely to say “work would primarily be data-driven; theory would be developed in response to questions raised by empiri­cal findings.”

Most important, and maybe concerning, is that the survey found no real effect of age, stage or gender – i.e. existing attitudes are deeply ingrained and show no sign of changing.

Why is it so important that we reconcile the theoretical/empirical issue? The paper “Rising complexity and falling explanatory power in ecology” offers a pretty compelling reason in its title. Ecological research is getting harder, and we need to marshall all the resources available to us to continue to progress. 

The paper suggests that ecological research is experiencing falling mean Rvalues. Values in published papers have fallen from above 0.75 prior to 1950 to below 0.5 in today's papers.
The worrying thing is that as a discipline progresses and improves, you might predict that the result is an improving ability to explain ecological phenomenon. For comparison, criminology was found to show no decline in R2 values as that matured through time. Why don’t we have that? 

During the same period, however, it is notable that the average complexity of ecological studies also increased – the number of reported p-values is 10x larger on average today compared to the early years (where usually only a single p-value relating to a single question was reported). 

The fall in R2 values and the rise in reported p-values could mean a number of things, some worse for ecology than others. The authors suggest that R2 values may be declining as a result of exhaustion of “easy” questions (“low hanging fruit”), increased effort in experiments, or a change in publication bias, for example. The low hanging fruit hypothesis may have some merit – after all, studies from before the 1950s were mostly population biology with a focus on a single species in a single place over a single time period. Questions have grown increasingly more complex, involving assemblages of species over a greater range of spatial and temporal scales. For complex sciences, this fits a common pattern of diminishing returns: “For example, large planets, large mammals, and more stable elements were discovered first”.

In some ways, ecologists lack a clear definition of success. No one would argue that ecology is less effective now than it was in the 1920s, for example, and yet a simplistic measure (R2) of success might suggest that ecology is in decline. Any biases between theorists and empiricists is obviously misplaced, in that any definition of success for ecology will require both.  

Thursday, August 14, 2014

#ESA2014 Day 4: Battle Empiricism vs Theory

You are our only hope!(?)
First off, the Theory vs. Empiricism Ignite session was a goldmine for quotes:

In God we trust, all others bring data” (H. Edwards Deming)
Models are our only hope” (Greg Dwyer)
"Nature represents a special part of parameter space" (Jay Stachowicz)

The Theory vs. Empiricism Ignite session was designed in response to an impromptu survey at ESA last year that found that 2/3 s of an audience did not believe that there are general laws in ecology. Speakers were asked to choose whether an empirical paper or a theoretical paper would be most important for ecology, and to defend their choice, perhaps creating some entertaining antagonism along the way. 

There wasn't actually much antagonism to be had: participants were mostly conciliatory and hardly controversial. Despite this, the session was entertaining and also insightful, but perhaps not in the way I expected. First though, I should say that I think the conversation could have used some definitions of the terms (“theory”,  “empiricism”). We throw these terms around a lot but they mean different things to different people. What counts as theory to a field based scientist may be consider no more than a rule of thumb or statistical model to a pure theoretician. Data from a microcosm might not count as experimental evidence to a fieldwork-oriented ecologist.

The short talks included examples and arguments as to how theoretical or empirical science is a necessary and valuable contributor to ecological discoveries. That was fine, but the subtext from a number of talks turned out to be more interesting. The tension, it seemed, was not about whether theory is useful or empiricism is valuable, but about which one is more important. Should theory or empiricism be the driver of ecological research? (Kudos to Fred Adler for the joke that theory wants to be a demanding queen ant with empiricists as the brainless order-following workers!) And funding should follow the most worthy work. Thus empiricists bemoan the lack of funding for natural history, while theoreticians argue that pure theory is even harder to get grants for. The question of which one should lead research was sadly mostly unanswered (and 5 minutes per person didn't offer much space for a deeper discussion). 

Of course there was the inevitable call for reconciliation of the two areas, of some way to breach the arrogance and ignorance (to paraphrase Brad Cardinale) holding them apart. Or, perhaps all ecologists should be renaissance scientists, who have mastered theory and empiricism equally. Hard to say. For me, considering the example of ecological subfields that have found a balance and feedback between theory and data is wise. Areas such as disease ecology or population biology incorporate models and experiments successfully, for example. Why do some other fields like community ecology or conservation biology struggle so much more?

#ESA2014 - Day 3 bringing together theory and empiricism

I was tied up in a session all afternoon, so most of the interesting comments below are from Topher Weiss-Lehman, who caught what sounds like a pretty thought provoking session about theory and conservation biology, with thought provoking talks from Hugh Possingham and David Ackerly. This concept of bringing theory and empiricism together permeated through a number of talks, including the session I moderated on using microbes in theoretical ecology and applying theory to microbial ecology (although at the moment, the distance between those things still feels large).

The most thought-provoking talk I saw was Peter Chesson's, on "Diversity maintenance: new concepts and theory for communities as multiple-scale entities". Chesson discussed his discomfort with how his coexistence theory is sometimes applied (I suppose that is the definition of success, that you see your ideas misused). His concerns fall with those of many ecologists on the question of how to define and research an ecological community. Is the obsession with the looking at 'local' communities limiting and misguided, particularly when paired with the ridiculous assumption that such communities are closed systems? Much like Ricklef's well known paper on the defining a 'regional community', Chesson suggests we move to a multi-scale emphasis for community ecology.

Rather than calculating coexistence in a local community, Chesson argued that ecologists should be begin to think about how coexistence mechanisms varied in strength across multiple spatial scales. For example, is frequency dependence more importance at smaller or larger scales? He used a concept similar to the idea of Ricklef's regional community, in which a larger extent encompassed a number of increasingly smaller scale communities. The regional community likely includes environmental gradients, and species distributions that vary across them. Chesson presented some simulations based on a multi-scale model of species interactions to illustrate the potential of his multi-scale coexistence theory framework. The model appears to bring together Chesson's work on coexistence mechanisms-- including the importance of fitness differences (here with fitness calculated at each scale as the change in density over a time step) and stabilizing forces, and the invasion criteria (where coexistence has a signal of a positive growth rate from low density)--and his scale-transition theory work. This is a very obvious advance, and a sensible way of recognizing the scale-dependent nature of ecology in coexistence mechanisms. His approaches allows ecologists to drop their obsession with defining some spatial area as "the community" and a regional community decreases the importance of the closed system assumption. My one with is that there be some discussion of how this concept fits with existing ideas about scale and communities in ecology. For example, how compatible are existing larger scale approaches like macroecology/biogeography and other theoretical paradigms like metacommunity theory with this?  

#Notes from Topher Weiss-Lehman

Applied Theory I spent the morning of my third day at ESA in a symposium on Advancing Ecological Theory for Conservation Biology. Hugh Possingham started out with a call for more grand theories in a talk titled “Theory for conservation decisions: the death of bravery.” Possingham argued for the development of theory tailored to the needs of conservation managers, identifying the SLOSS debate as an example of the scientific community agonizing over the answer to a question no managers were asking. He described the type of theory he meant as simple and easily applicable rather than relying on intensive computer simulations that managers are unlikely to be able to use for their own systems. Possingham is right that conservation managers need theory to help guide them in decisions over where and what species to protect, however I can’t help but think about the scientific advances that arose specifically as a result of the SLOSS debate and computational models. The talk left me wondering if theoretical ecology, like other scientific fields, could be split into basic and applied theory.

The other talks in the session approached the topic of theory for conservation from a number of perspectives. Justin Kitzes discussed the ways in which macroecology can inform conservation concerns and Annette Ostling explored how niche and neutral community dynamics affect extinction debts. H. Resit Akakaya provided a wonderful example of the utility of computer simulations for conservation issues. He presented results predicting the extinction risk of species due to climate change via simulations based on niche modeling coupled with metapopulation dynamics. Jennifer Dunne then explored how the network structure of food webs changed as a result of human arrival and hunting in several systems. The session ended with a presentation by David Ackerly calling for a focus on disequilibrium dynamics in ecology. Ackerly made a compelling case for the importance of considering disequilibrium dynamics, particularly when making predictions of species reactions to climate change or habitat alteration. However the most memorable part of his talk for me was the last 5 minutes or so. He suggested that we reconsider what conservation success should mean. Since systems are changing and will continue to change, Ackerly argued that to set conservation goals based on keeping them the way they are is setting ourselves up for failure. Instead, we need to understand that systems are transitioning and that while we have a crucial role in deciding what they might transition into, we can’t and shouldn’t try to stop them from changing.

The talks today gave me lots of ideas and new papers to read, but they also left me pondering more questions on the philosophy of science (what we do, why we do it, and what our goals should be) than I expected.

Tuesday, August 12, 2014

#ESA2014: Day two, what are we measuring and how?

It's probably in part because I attended sessions that are along similar lines today, but I noticed a common theme played across a number of talks. Ecological data is in some ways becoming very complex - a single analysis may include traits, phylogenetic distances, and taxonomic information, and climate and soil variables, possibly at multiple spatial scales. How to combine disparate data appropriately and how to determine the comparable "scales" across which to measure each variable is more important than ever. But it is still difficult to determine what an appropriate comparison actually is.

Studies of intraspecific variation frequently have to determine how to measure and compare variables. (i.e. Do you measure intraspecific trait variation at the genotype level, the individual level, etc?) For example, in a nice talk by Jessica Abbott, the effects of intraspecific variation in genetic relatedness and trait similarity on intraspecific competition among eelgrass hit upon exactly this point. There was no relationship between trait similarity between genotypes and their degree of genetic relatedness. Traits, not relatedness, were the clearest predictor of competitive success. A number of the talks I saw today incorporated intraspecific variation, including a couple of excellent talks on Daphnia by Sarah Duple and Chris Holmes. Both of the Daphnia talks found evidence of great intraspecific trait variation in the Daphnia but weak relationships between that variation and competitive interactions or diversity. These talks were all nice examples of how empirical work can relate to larger ecological theory, and found fairly mixed evidence for the importance of intraspecific variation. There are many reasons why intraspecific variation is not always strongly tied to ecological processes - intraspecific variation may simply have low explanatory power, for example. But it is also interesting to consider the issues that arise as we ask questions at ever smaller and more precise scales. How do we distinguish a low importance of intraspecific variation, or trait variation, or phylogenetic variation from incorrect scale of measurement? Asking questions with multiple measures opens up new and important issues - how should we measure genetic relatedness to be truly comparable to trait variation at intraspecific or interspecific scales? How does combining mismatched variables (intraspecific trait values with interpolated large scale environmental values, for example) affect the explanatory power of those variables? Given the increasingly multi-faceted nature of ecological analyses it seems important that we consider these questions.

#Lauren Shoemaker
I started Day 2 of ESA attending talks focusing on quantifying coexistence mechanisms and the role of intraspecific competition in coexistence. Yue Li and Peter Chesson started the day presenting work quantifying the storage effect in three desert winter annuals in Arizona’s Goldwater Range. This work highlighted the methodology for quantifying the storage effect in empirical systems—which was refreshing for me since I spend so much time thinking about spatial storage mechanisms in simplified, theoretical systems.

In the same session, Peter Adler presented his work with Chengjin Chu examining the strength of stabilizing niche differences and fitness differences. When stabilizing niche differences are too low relative to fitness differences, competitive exclusion occurs, while high stabilizing niche forces create coexistence. Using long-term demographic data of perennial grasses from five communities, they found that all species exhibited high niche differences and low fitness differences, creating high coexistence strength. For all communities, stabilizing niche differences likely resulted from recruitment. The high niche differentiation highlights the need for a stronger focus on intraspecific density dependence and for more models of coexistence with explicit intraspecific competition.

In the afternoon, Louie Yang argued that ecologists as a whole need to more explicitly consider changes in species interaction through time, especially with increasing effects of climate change. Using an example of 17-year cicada cycles, he showed that questions of “bottom up or top-down” are often really bottom up and then top-down when viewed in a temporally explicit framework. He even ended his talk with an excellent analogy comparing historic artwork and ecology—a hard analogy to pull off!

As an added bonus, I finished the day with a long list of paper citations to look up and read after the conference.

Monday, August 11, 2014

#ESA2014: Day 1, just getting started

First off, apparently I wrote that I would be 'live blogging ESA'. Actually, all that means is that, I'm alive, I'm blogging, and I'm at ESA. :-)

Secondly, several other people will be giving snippets from their days this week, including Lauren Shoemaker, and Geoff Legault (below).

The first day is always more about the experience than the content: you are often lost, have no firm idea of where you need to be, and are constantly running into friends and acquaintances. It's great, but not conducive to settling into talks.

For that reason, I'll just mention the experiences that I found most exciting today. First, I saw a number of Ignite talks. These are a recent addition to ESA and are basically 5 minute talks using slides that advance every 15s. This requires a certain ability on the part of the speaker to be brief and yet informative, minimalist but not inaccurate, practiced, but not robotic. I thought that many of the speakers in the Ecosystems in the Third National Climate Assessment achieved this. One speaker, Linda Joyce said -  "if you want to feel like a graduate student again, sign up for an Ignite talk." Presumably because it makes you feel nerves like you haven't felt in years!

Joyce gave a great talk, as did others. Some of the conversation around the ecosystem assessment fell into the discourse that ecosystems provide services, and services imply people. Are ecosystem assessments only about people? Obviously this is too challenging a topic for a 5 minute talk, but it certainly sparks to further discussion on the topic, as it was meant to.

The second session of interest to me was an organized symposium in which early career scientists gave talks about their work. The central thread was simply that all of the speakers were pre-tenure academics. This really worked as a theme to tie the session together. At the end, the speakers answered questions briefly about their careers, advice, and research. Their best advice was really very good, if in line with what you here on attempting a job in academia. Find mentors. Set boundaries between your personal and private life. Say no sometimes, if it means maintaining some sort of sanity (e.g travel less, have more time with your family). A point that came up multiple times was simply, you have to have passion for science, have to love talking about your work. Having something you're passionate about is better than having ten things you are lukewarm on. And always find people to collaborate with, to talk with, to support.

Finally, there are many paths to success. And failure is universal, but not final.

(My favourite quote - someone who mentioned measuring effort in 'undergraduate work hours')

#Lauren Shoemaker

ESA had some excellent talks to start the 99th conference in Sacramento, California. I stayed in Community Assembly and Neutral Theory for several talks before running back and forth between the Hyatt, Sheraton, and conference center (missing the first few minutes of several talks).

In Community Assembly, Maria Stockenreiter gave a fantastic talk on community assembly in phytoplankton communities while building on the theory of Miller et al. (2009) examining the role of unsuccessful invaders in shaping communities. Even unsuccessful invaders within a community can alter environmental conditions or species distributions such that an unsuccessful invasion can exclude a current or future potentially successful invader. Maria tested this theory using two phytoplankton communities—a lab strain with no shared ecological history and a Gull lake community with shared history. While all invaders were unsuccessful in the experiments, they had large effects on community diversity. Unsuccessful invasion decreased diversity in the lab strains but increased diversity in the Gull Lake community, showing both the “ghost effect” of competition and the role of shared ecological histories.

In Paleoecology, Matthew Knope examined the functional diversity-taxonomic diversity relationships for marine animals during the past 500 million years. It was fun to think of a relationship I only consider in current-times over such a long timescale. Matthew categorized marine mammals according to their location in a discrete 3-dimensional niche space (tiering on sea floor, feeding mode, and motility). The data show that the amount of functional diversity was far lower than expected based on taxonomic diversity until only recently. Additionally, I was amazed to see a consistent trend (from 3 different mass extinctions in the dataset) that mass extinctions promote functional diversity 10-20 million years post extinction leading to even higher functional diversity than pre-extinction.

Back at the convention center in the Biodiversity I session, Pascal Niklaus examined if interspecific vertical canopy space partitioning promoted productivity in subtropical forests. While light is a directional resource, creating a large advantage for being tall, Pascal found that vertical niche partitioning still occurred when comparing monocultures to multiple species assemblages. Species in higher diversity communities also had narrower niches, and similar species shifted their vertical leaf biomass niche, but only in shaded treatments. Vertical niche partitioning did, indeed, promote higher ecosystem function.

#Geoff Legault
I arrived in Sacramento this afternoon so I did not get a chance to see many talks (though I did enjoy Meghan Duffy’s talk about possible hydra effects in Daphnia). I did, however, see a number of excellent posters, particularly one by Nick Rasmussen on the interactive effects of density and phenology on the recruitment of toads. I was impressed by his use of mesocosms to directly manipulate these factors and found that he made a compelling case for the idea that the degree of synchrony in hatching can determine which form of intraspecific competition dominates recruitment.

Monday, August 4, 2014

#ESA2014 : Getting ready for (and surviving) ESA

There is less than one week until ecology's largest meeting. ESA's annual meeting starts August 10th in Sacramento, California, and it can be both exciting and also be overwhelming in its size and scope. Here are a few suggestions for making it a success.

Getting ready for ESA.
Sure, things start in a week and you're scheduled for a talk/poster/meeting with a famous prof, but you haven't started preparing yet.

First off, no point beating yourself up for procrastinating: if you've been thinking about your presentation but doing other projects, you might be in the company of other successful people.

If you're giving a talk, and given it before or are an old hand at this sort of thing, go ahead and put it together the night before your talk. One benefit for the truly experienced or gifted speaker is that this talk will never sound over-rehearsed.

Regardless, all speakers should try for a talk that is focused, with a clear narrative and argument, and within the allotted time. (Nothing is more awkward for everyone involved than watching the moderate have to interrupt a speaker). The good news is that ESA audiences will probably be a) educated to at least a basic level on your topic, and b) are usually generous with their attention and polite with their questions. This blog has some really practical advice on putting together an academic talk.
If at all possible, practice in front of a friendly audience ahead of time.

The questions after your talk will vary, and if you're lucky they will relate to future directions, experimental design, quantitative double-checks, and the truly insightful thoughts. However, there other common questions that you should recognize: the courtesy question (good moderators have a few in hand), the "tell-me-how-it-relates-to-my-work" question, and the wandering unquestion.

Giving a poster is much different than giving a talk, and it has pros and cons. First, you have to have it finished in time to have it printed, so procrastination is less possible. Posters are great if you want one-on-one interactions with a wide range of people. You have to make your poster attractive and interesting: this always means don't put too much text on your poster. The start of this pdf gives some nice advice on getting the most out of your poster presentation.

For both posters and presentations, graphics and visual appeal make a big difference. Check out the blog, DeScience, which has some great suggestions for science communication.

Academic meetings. These run the gamut from collaborators that you're just catching up with, to strangers that you have contacted to meet to discuss common scientific interests. If scientists that you share common research activities and interests with are attending ESA, it never hurts to try to meet with them. Many academics are generous with their time, especially for young researchers. If they say yes, come prepared for the conversation. If necessary, review their work that relates to your own. Come prepared to describe your interests and the project/question/experiment you were looking for advice on. It can be very helpful to have some specific questions in mind, in order facilitate the conversation.

What to wear. Impossible to say. Depending on who you are and wear you work normally, you can wear anything from torn field gear and binos to a nice dress or suit (although not too many people will be in suits).

Surviving ESA.
ESA can be very large and fairly exhausting. The key is to pace yourself and take breaks: you don't need to see talks all day long to get your money's worth from ESA. Prioritize the talks that you want to see based on things like speaker or topic. Sitting in on topics totally different from those you study can be quite energizing as well. In this age of smartphones, the e-program is invaluable.

Social media can help you find popular or interesting sounding talks, or fill you in on highlights you missed. This year the official hashtag on twitter is #ESA2014.

One of the most important things you can do is be open to meeting new people, whether through dinner and lunch invites, mixers, or other organized activities. Introverts might cringe a little, but the longest lasting outcome from big conferences is the connections you make there.

Eat and try to get some sleep.

**The EEB & Flow will be live-blogging during ESA 2014 in Sacramento, as we have for the last few years. See everyone in Sacramento!**