On Making Biodiversity Research (UPDATED!)

This post was originally published on BioDiverse Perspectives – a research blog aimed at fostering communication about biodiversity.

One of the most exciting aspects of being a field ecologist is the ability to walk into a hardware store, pick up an object, and ask yourself, ‘How can I use this to answer my question?’ – Mary Power, Population and Community Ecology, Spring 2007

To some people, the beginning of field season is signified by the emergence of a particular wildflower, the sound of that one birdcall, or the sudden quiet around campus after finals. To me, it’s that look from the cashier at the hardware store.  “You want how many rolls of weed barrier?” they ask with disbelief.

This year, I got that look when I asked for help to load 10ft lengths of conduit pipe into a little Hyundai, and it got me thinking about the choice words above that Mary Power offered when discussing experimental design in my introductory ecology class. In the study of biodiversity, researchers often try to tackle very complicated systems, and adequately testing their hypotheses can require some serious creativity. As a result, many ecologists share a unique bond of having to create the tool that lets them answer their question.

And just like there are frontier and foundational papers in biodiversity research, I think that there are foundational and frontier tools created to accomplish biodiversity research. For example, where would plant ecology be without the invention of the PVC quadrat?

To me, a great example of the maker culture of ecology shows up in Paul K. Dayton’s 1971 Ecological Monograph exploring the factors that structure sessile organisms in the rocky intertidal. One hypothesis that he tested was that disturbance by logs in exposed sites served as a key environmental factor influencing community structure. He noticed that in exposed sites, drift logs would smash into the shore, obliterating anything that was previously occupying that site, and he hypothesized that this disturbance could have huge impacts on community structure. He had a solid hypothesis and a great set of research sites that varied in exposure, but Dayton had one major problem. How do you quantify log disturbance in the intertidal?

His solution:

The probability of log disturbance at each study site was measured by embedding cohorts of nails haphazardly into the substratum at three different intertidal levels. The nails were embedded with a construction stud gun using .32 caliber blanks; each nail stood approximately 2 cm high. Survival curves of these nail cohorts show that within most of the study areas there is a 5-30% probability of any given spot being struck by a log within 3 years. –Dayton. 1971 Ecological Monographs Pg 357

Being able to create the tools that we need empowers ecologists to generate ever more creative hypotheses, and I think that this culture sets us apart from other scientists. In some instances, our ingenuity has even led to new industry ventures and advances in technology, such as with the development of radio-telemetry, and camera traps. And subsequent market advances once the technology reaches industry leads to better equipment, which allows us to better test our hypotheses!

But this all has me thinking about another important parallel with biodiversity research. We take such care not to reinvent the wheel when it comes to testing the same ideas. Is there a way that we could prevent reinventing the wheel in how we test those ideas? What creative ways have you used to test your hypotheses?

Update: Somehow I missed being a part of this trending hashtag, Meg Duffy has a post about unusual equipment, and over at Parasite Ecology, they’re using snail polish for mark-recapture.

Tradeoffs, correlated traits, and functional diversity

This post was originally published on BioDiverse Perspectives – a research blog aimed at fostering communication about biodiversity.

Tradeoffs are everywhere, and never has this been more apparent to me, than in graduate school. With only so many hours in a day, and an ever-growing to-do list, how I choose to allocate my time becomes an increasingly important decision. Do I work in the greenhouse, resample my field experiment, analyze data, catch up on reading…? Every day, when I wake up, I’m faced with these decisions.  And every day, these decisions are constrained by the same two major factors: What can I do? e.g., how much time do I have in the day; and what have I already done?

Well, I’m glad to say that I know I’m not alone. In fact, most organisms face nearly the exact same constraints. And these two constraints don’t just occur within a single organism’s lifetime. They can often be reflected over evolutionary time, too. In this case, “what can I do?” becomes a question of physiological constraints on phenotypes (some combinations of traits are physiologically impossible), and “what have I done?” becomes a question of evolutionary history, or natural selection (some combinations of traits would confer fitness disadvantages).

As studies of diversity move from descriptions of species numbers (e.g., taxonomic diversity) to descriptions of species physiology (e.g., functional diversity) or evolutionary history (e.g., phylogenetic diversity), it’s becoming more important that we pay attention to the tradeoffs that underlie those patterns. Although not the first to suggest this, Wright et. al’s description of the worldwide leaf economics spectrum demonstrated the universality of tradeoffs between natural selection and physiological constraints, and argued that plants tend to fall on a continuum between two fundamental strategies for dealing with these tradeoffs, termed the slow- to quick-return continuum.

This spectrum runs from species with potential for quick returns on investments of nutrients and dry mass in leaves to species with a slower potential rate of return. At the quick-return end are species with high leaf nutrient concentrations, high rates of photosynthesis and respiration, short leaf lifetimes and low dry-mass investment per leaf area. At the slow-return end are species with long leaf lifetimes, expensive high-LMA leaf construction, low nutrient concentrations, and low rates of photosynthesis and respiration.

For example, imagine you are a small grass seedling, your goal in life is reproduction, and you only have a finite number of resources to allocate in order to reach that goal. Do you allocate them to growth and additional resource acquisition, or do you conserve the resources that you have so that you can allocate them all to reproduction? What Wright et al. suggest is that you are fundamentally asking, “Should I be a quick-return plant or a slow return plant?” Physiologically, it is not possible to exhibit both high rates of photosynthesis (future resource acquisition) as well as low leaf nitrogen concentrations and long lived leaves (resource conservation). In addition, if you choose to allocate few resources to photosynthesis, jack up your leaf nitrogen concentrations, and rapidly shed leaves, you are unlikely to successfully reproduce. As a result, your phenotype is constrained physiologically and evolutionarily, and Wright et al. argue that this tradeoff is fundamental across all plants and results in a predictable spectrum of phenotypes.

I was introduced to this paper very early in my graduate career, long before I had a flicker of an inkling of a speck of a thought about the multiple dimensions of biodiversity. But when I start to think about patterns of functional diversity through the lens of the leaf economics spectrum, I start to wonder. If groups of physiological traits covary and are constrained by physiological processes and evolutionary history, how might this influence the inferences that we draw from patterns of functional diversity? When measuring functional diversity, how important are the specific traits that we consider? And if groups of physiological traits are strongly correlated along a phylogeny, how useful are measures of phylogenetic diversity at inferring patterns of functional diversity?

On biodiversity and disease risk

This post was originally published on BioDiverse Perspectives – a research blog aimed at fostering communication about biodiversity.

Few studies have had as large of an impact on me as Charles Mitchell’s study of the impacts of plant species diversity on fungal diseases at the Cedar Creek grassland in Minnesota, USA.

Ok; quick caveat, Charles Mitchell is my advisor. But I’m not saying this to put my advisor on a pedestal.  This study is in large part the reason that I study what I do, and that I am a graduate student where I am.  By evaluating disease impact in an experiment that directly manipulated host species diversity, Mitchell was able to provide empirical evidence that decreased host diversity should increase the abundance of many diseases. Not only did it key in on the link between biodiversity loss and health risk, but the study showed me that such a complicated question could be approached in a way that was experimentally tractable.

But I don’t want to focus on Mitchell’s research here.  See, although his study provided evidence to support the diversity-disease hypothesis, I am highlighting it here because it led to the search for general mechanisms behind that phenomenon.  Instead I want to focus on a paper that I consider a true frontier in biodiversity science. This is a paper that took an often disjointed and complicated field, grounded it in a very simple theoretical model, and then generated some clear, testable hypotheses to move the field forward.

In their 2006 paper, Effects of species diversity on disease risk, Keesing, Holt, and Ostfeld provided a synthesis that would address the key question that underlies the diversity-disease hypothesis: What is the mechanism by which biodiversity influences disease risk?  By generating 5 discrete mechanisms from a litany of previous research, they provided what would hopefully become a roadmap for future research aiming to understand and possibly mitigate for the relationship between biodiversity loss and increased disease risk.

I’m not going to get into the nitty-gritty details of this paper. Rather, I want to highlight one really cool aspect of it that I think was truly innovative and inspirational: that they take something almost immeasurably complicated (the ecology of plant and animal hosts, and the epidemiology of specialist, generalist, and vector born pathogens) and reduce it to the simplest system possible (a simple epidemiological susceptible-infected model) to identify the specific mechanisms by which diversity can influence disease risk. From this simplified model, they are then able to scale up in complexity to explain patterns observed in far more complicated systems.

So obviously, this paper is important to disease ecologists and conservationists aiming to prevent the spread and emergence of infectious diseases (not a trivial thing in and of itself). But I think this paper has value to all biodiversity researchers.  It’s so easy to get bogged down in our own subfields and forget that we can often look to other disciplines or simple theory to synthesize our own research. Keesing, Holt, and Ostfeld used a simple epidemiological model to decompose nearly 100 years of research into 5 testable hypotheses. Biodiversity, with it’s multiple dimensions, drivers, results, and feedbacks, can often seem immeasurably complicated. Is there a simple, ecological theory that can unify this field as well?

Update: The PEGE Journal Club just posted a review of a recent empirical study of biodiversity and disease risk in a trematode parasite of amphibians that was published in Nature. Pieter Johnson’s lab at CU Boulder is doing a lot of really cool research in disease ecology, and this recent paper is a great example! Here, they argue that there’s an emergent property of host diversity that can decrease disease risk that acts independent of host density.

Why Students Should Read Blogs

This post was originally published on BioDiverse Perspectives – a research blog aimed at fostering communication about biodiversity.

Last week, I subtly pointed out that perhaps more academics should be writing blogs. I struggled a bit with this statement, since the majority of scientists that I know don’t even read science blogs, let alone contribute to them.  Luckily for me, Jeremy Fox has a great post on why an academic should read blogs, and it looks like it’s already changing some opinions around me.

Well, this morning, Jon Lefcheck, a regular contributor here at BioDiverse Perspectives wrote a response to Jeremy’s post in which he suggested why students in particular should read blogs.

Now, presumably, if you’re a student reading this post, then you are already aware of some good reasons to read science blogs. Even so, I think Jon’s argument that reading and commenting on blogs is a novel way to make meaningful connections is worth thinking about, and I encourage you to check out his post and comment on it with your thoughts.

I also thought that I’d put in my two cents as to why students should read blogs. For me, there are two key reasons that I read blogs: (1) Exposure and (2) Engagement.

  1. Exposure.  I try to read a wide range of literature in my field. I really do. But realistically, I tend to only read a very small subset of articles that directly relate to my research interests. By subscribing to blogs that are written by other researchers in my field, I am exposed on a daily basis to new research that I might otherwise miss.  Furthermore, that research comes with commentary. And that commentary often comes from researchers that I hold in high regard. Reading blogs, then, is a way for me to gain exposure to the opinions of researchers that might otherwise only be available at a major conference.
  2. Engagement. I am afforded amazing opportunities to interact with brilliant graduate students and faculty at my university. Additionally, we have a weekly seminar series that allows me to interact with faculty members from other universities. However, this opportunity isn’t universal. In addition to providing exposure, blogs provide an opportunity for graduate students to engage with one another and with faculty members. Yes, as Jon points out, this can often lead to long-term and meaningful connections. But even in the absence of meaningful connections, it provides students with an opportunity to engage with researchers beyond their own sphere, and could lead to exposure to even more new ideas.

Ecology simplified

This post was originally published on BioDiverse Perspectives – a research blog aimed at fostering communication about biodiversity.

I want to preface this post by saying that I am not a theoretician.  In fact, I often find long presentations full of complex equations and zero-growth isoclines dizzying. But lacking an inclination (or even possessing a slight aversion) towards theoretical models should not ever keep someone away from reading Peter Chesson’s 2000 Mechanisms of Maintenance of Species Diversity. Continue reading “Ecology simplified”