Monday, February 24, 2014

Evolution at smaller and smaller scales: a role for microgeographic adaptation in ecology?

Jonathan L. Richardson, Mark C. Urban, Daniel I. Bolnick, David K. Skelly. 2014. Microgeographic adaptation and the spatial scale of evolution. Trends in Ecology & Evolution, 19 February 2014.

Among other trends in ecology, it seems that there is a strong trend towards re-integration of ecological and evolutionary dynamics, and also in partitioning ecological dynamics to finer and finer scales (e.g. intraspecific variation). So it was great to see a new TREE article on “Microgeographic adaptation and the spatial scale of evolution”, which seemed to promise to contribute to both topics.

In this paper, Richardson et al. attempt to define and quantify the importance of small-scale adaptive differences that can arise between even neighbouring populations. These are given the name “microgeographic adaptation”, and defined as arising via trait differences across fine spatial scales, which lead to fitness advantages in an individual’s home sites. The obvious question is what spatial scale does 'microgeographic' refer to, and the authors define it very precisely as “the dispersal neighborhood … of the individuals located within a radius extending two standard deviations from the mean of the dispersal kernel of a species”. (More generally they forward an argument for a unit--the ‘wright’--that would measure adaptive divergence through space relative to dispersal neighbourhoods.) The concept of microgeographic adaptation feels like it is putting a pretty fine point on already existing ideas about local adaptation, and the authors acknowledge that it is a special case of adaptation at scales where gene flow is usually assumed to be high. Though they also suggest that microgeographic adaptation has received almost no recognition, it is probably fairer to say that in practice the assumption is that on fine scales, gene flow is large enough to swamp out local selective differences, but many ecologists could name examples of trait differences between populations at close proximity.

From Richardson et al. (2014). One
example of microgeographic adaptations.
Indeed, despite the general disregard to fine-scale evolutionary differences, they note that there are some historical and more recent examples of microgeographic variation. For example, Robert Selander found that despite the lack of physical barriers to movement, mice in neighbouring barns show allelic differences, probably due to territorial behaviour. As you might expect, microgeographic adaptations result when migration is effectively lower than expected given geographic distance and/or selection is stronger (as when neighbouring locations are very dissimilar). A variety of mechanisms are proposed, including the usual suspects – strong natural selection, landscape barriers, habitat selection, etc.

A list of the possible mechanisms leading to microgeographic adaptation is rather less interesting than questions about how to quantify the importance and commonness of microgeographic adaptation, and especially about its implications for ecological processes. At the moment, there are just a few examples and fewer still studies of the implications, making it difficult to say much. Because of either the lack of existing data and studies or else the paper's attempt to be relevant to both evolutionary biologists and ecologists, the vague discussion of microgeographic differences as a source of genetic variation for restoration or response to climate change, and mention of the existing—but primarily theoretical—ecological literature feels limited and unsatisfying. The optimistic view is that this paper might stimulate a greater focus on (fine) spatial scale in evolutionary biology, bringing evolution and ecology closer in terms of shared focus on spatial scale. For me though, the most interesting questions about focusing on smaller and smaller scales (spatial, unit of diversity (intraspecific, etc)) are always about what they can contribute to our understanding. Does complexity at small scales simply disappear as we aggregate to larger and larger scales (a la macroecology) or does it support greater complexity as we scale up, and so merit our attention? 

Tuesday, February 18, 2014

P-values, the statistic that we love to hate

P-values are an integral part of most scientific analyses, papers, and journals, and yet they come with a hefty list of concerns and criticisms from frequentists and Bayesians alike. An editorial in Nature (by Regina Nuzzo) last week provides a good reminder of some of the more concerning issues with the p-value. In particular, she explores how the obsession with "significance" creates issues with reproducibility and significant but biologically meaningless results.

Ronald Fischer, inventor of the p-value, never intended it to be used as a definitive test of “importance” (however you interpret that word). Instead, it was an informal barometer of whether a test hypothesis was worthy of continued interest and testing. Today though, p-values are often used as the final word on whether a relationship is meaningful or important, on whether the the test or experimental hypothesis has any merit, even on whether the data is publishable. For example in ecology, significance values from a regression or species distribution model are often presented as the results. 

This small but troubling shift away from the original purpose for p-values is tied to concerns about false alarms and with replicability of results. One recent suggestion for increasing replicability is to make p-values more stringent - to require that they be less that 0.005. But the point the author makes is that although p-values are typically interpreted as “the probability of obtaining a test statistic at least as extreme as the one that was actually observed, assuming that the null hypothesis is true”, this doesn't actually mean that a p-value of 0.01 in one study is exactly consistent with a p-value of 0.01 found in another study. P-values are not consistent or comparable across studies because the likelihood that there was a real (experimental) effect to start with alters the likelihood that a low p-value is just a false alarm (figure). The more unlikely the test hypothesis, the more likely a p-value of 0.05 is a false alarm. Data mining in particular will be (unwittingly) sensitive to this kind of problem. Of course one is unlikely to know what the odds of the test hypothesis are, especially a priori, making it even more difficult to correctly think about and use p-values. 

The other oft-repeated criticism of p-values is that a highly significant p-value make still be associated with a tiny (and thus possibly meaningless) effect size. The obsession with p-values is particularly strange then, given that the question "how large is the effect?", should be more important than just answering “is it significant?". Ignoring effect sizes leads to a trend of studies showing highly significant results, with arguably meaningless effect sizes. This creates the odd situation that publishing well requires high profile, novel, and strong results – but one of the major tools for identifying these results is flawed. The editorial lists a few suggestions for moving away from the p-value – including to have journals require effect sizes and confidence intervals be included in published papers, to require statements to the effect of “We report how we determined our sample size, all data exclusions (if any), all manipulations and all measures in the study”, in order to limit data-mining, or of course to move to a Bayesian framework, where p-values are near heresy. The best advice though, is quoted from statistician Steven Goodman: “The numbers are where the scientific discussion should start, not end.”

Monday, February 10, 2014

Ecological progress, what are we doing right?

A post from Charles Krebs' blog called "Ten limitations on progress in ecology" popped up a number of times on social media last week. Krebs is a established population ecologist who has been working in the field for a long time, and he suggests some important problems leading to a lack of progress in ecology. These concerns range from lack of jobs and funding for ecologists, to the fracturing of ecology into poorly integrated subfields. Krebs' post is a continuation of the ongoing conversation about limitations and problems in ecology, which has been up for discussion for decades. And as such, I agree with many of the points being made. But it reminded me of something I have been thinking about for a while, which is that it seems much more rare to see ecology’s successes listed. For many ecologists, it is probably easier to come up with the problems and weaknesses, but I think that's more of a cognitive bias than a sign that ecology is inescapably flawed. And that’s unfortunate: recognizing our successes and advances also helps us improve ecology. So what is there to praise about ecology, and what successes we can build on?

Despite Krebs’ concerns about lack of jobs for ecologists, it is worth celebrating how much ecology has grown in numbers and recognition as a discipline. The first ESA annual meeting in 1914 had 307 attendees, recent years’ attendance is somewhere between 3000-4000 ecologists. Ecology is also increasingly diverse. Ecology and Evolutionary Biology departments are now common in big universities, and sometimes replacing Botany and/or Zoology programs. On a more general level, the idea of “ecology” has increasing recognition by the public. Popular press coverage of issues such as biological invasions, honeybee colony collapses, wolves in Yellowstone, and climate change, have at least made the work of ecologists slightly more apparent.

Long-term ecological research is probably more common and more feasible now than it has ever been. There are long-term fragmentation, biodiversity and ecosystem function studies, grants directed at LTER, and a dedicated institute (the National Ecological Observatory Network (NEON)) funded by the NSF for longterm ecological data collection. (Of course, not all long term research sites have had an easy go of things – see the Experimental Lakes Area in Canada).

Another really positive development is that academic publishing is becoming more inclusive – not only are there more reputable open access publishing options for ecologists, the culture is changing to one where data is available online for broad access, rather than privately controlled. Top journals are reinforcing this trend by requiring that data be published in conjunction with publications.

Multi-disciplinary collaboration is more common than ever, both because ecology naturally overlaps with geochemistry, mathematics, physics, physiology, and others, and also because funding agencies are rewarding promising collaborations. For example, I recently saw a talk where dispersal was considered in the context of wind patterns based on meteorological models. It felt like this sort of mechanistic approach provided a much fuller understanding of dispersal than the usual kernel-based model.

Further, though subdisciplines of ecology have at times lost connection with the core knowledge of ecology, some subfields have taken paths that are worth emulating, integrating multiple areas of knowledge, while still making novel contributions to ecology in general. For example, disease ecology is multidisciplinary, integrating ecology, fieldwork, epidemiological models and medicine with reasonable success.

Finally, more than ever, the complexity of ecology is being equalled by available methods. More than ever, the math, the models, the technology, and the computing resources available are sufficient. If you look at papers from ecology’s earliest years, statistics and models were restricted to simple regressions or ANOVAs and differential equations that could be solved by hand. Though there is uncertainty associated with even the most complex model, our ability to model ecological processes is higher than ever. Technology allows us to observe changes in alleles, to reconstruct phylogenetic trees, and to count species too small to even see. If used carefully and with understanding, we have the tools to make and continue making huge advances.

Maybe there are other (better) positive advances that I’ve overlooked, but it seems that – despite claims to the contrary – there are many reasons to think that ecology is a growing, thriving discipline. Not perfect, but successfully growing with the technological, political, and environmental realities.
Ecology may be successfully growing, but it's true that the timing is rough...

Tuesday, February 4, 2014

Competition and mutualism may be closely related: one example from myrmecochory

Robert J. Warren II, Itamar Giladi, Mark A. Bradford 2014. Competition as a mechanism structuring mutualisms. Journal of Ecology. DOI: 10.1111/1365-2745.12203.

As ecologists usually think about them, competition and mutualism are very different types of interactions. Competition has a negative effect on resource availability for a species, while mutualism should have a positive impact on resource availability. Mutualisms involve interactions between two or more species, and as such are biotic in nature. While the typical definition of the fundamental niche includes all (and only) abiotic conditions necessary for a population’s persistence, with the realized niche showing those areas that are suitable once biotic interactions are considered (Pulliam 2000), mutualisms are a reminder that the a niche is not as simple as we hope. Mutualisms may be necessary for a population’s persistence, as in the case of obligate pollinators, and so some biotic interactions might be “fundamental”. More complicated still, species may compete for mutualist partners – plant species for pollinators, for example. If the mutualist partner is considered a resource, mutualism and competition may not be so far apart after all. 

The relation between competition and mutualism is probably most acknowledged in terms of pollinators – patterns of staggered flowering in a plant community arise in part to decrease simultaneous demand for limited pollinator resources. Another possibly fundamental biotic resource is dispersers, which may be necessary for population persistence of some species. In Warren, Giladi, and Bradford (2014), the authors attempt to expand this idea of competition for mutualist partners to ant-mediated seed dispersal or myrmecochory. Myrmecochorous plant species are common in a number of regions of the world. They rely on ant dispersal to move their seeds, helping to increase the distance between parent and offspring (and thus decrease competition), lower seed predation, and introduce seeds to novel habitats. Ant species that disperse these seeds benefit from the high-energy seed attachment (elaiosome) provided by the plant. While myrmecochorous plants are dependent on ants for successful dispersal, most ants do not rely solely on elaiosomes for food; further, there are fewer seed-dispersing ant species than there are ant-requiring plant species. As a result, competition for ants between myrmecochorous species is a reasonable hypothesis. If there is competition for mutualist partners, the predictions are that species either increase their attractiveness as a competitor by making their seeds most attractive, or else decrease the intensity of competition by staggering seed release.

Warren et al. tested this predictions for eastern North American woodland perennials: at least 50 plant species rely on ant dispersal in this region, but a much smaller number of ants actually disperse seeds. This dearth of mutualist partners implies that competition for ant dispersers should be particularly strong. One way to successfully monopolize a mutualist is to ensure that the timing of seed release is coordinated with ant availability and attraction: in fact comparisons between myrmecochorous and non-myrmecochorous plant species suggests that those requiring ants set seed earlier, when ant attraction to seeds is higher (insect prey become more attractive later in the season). To look at competition within myrmecochorous species, the authors as whether seed size (and thereby attractiveness to ants) was staggered through time. Smaller mymecochore seeds should, for example, become available when larger and more attractive seeds are not in competition. This prediction held – small, less attractive seeds were available earlier in the season than the larger, more attractive later seeds. The authors then experimentally tested whether small and large seeds were in competition for ants and differed in their success in attracting them. Using weigh boats secured to the forest floor, the researchers provided either i) only small myrmecochore seeds, ii) only large seeds, or iii) a combination of both seed sizes. Not that surprisingly, the presence of large seeds inhibits the removal of smaller less attractive seeds by as much as 100% (i.e. no small seeds were removed).

The authors do a nice job of showing that species differ in their success in attracting ant dispersers, and species with differing seed attractiveness appear to partition the season in such a way as to maximize their success. Whether or not this likely competition for dispersers extends to impact the species’ spatial distribution or whether species are prevented from co-occurring by competition for mutualists is less clear, and an interesting future direction. The authors also hypothesize that dispersers, rather than pollinators, may drive flowering/seed production in a system, which is an alternative the usual assumption that pollinators, not dispersers are more important drivers of evolution. More generally, the paper is a reminder that, at least for some species, biotic interactions are fundamental to the niche. Or even more likely, that the separation between the determinants of a fundamental and realized niche aren’t so very distinct. And that’s a reminder that has value for many sections of ecology, from species distribution models to invasive species research.