Tuesday, December 15, 2015

2015 caRd - A diveRsity of Santas

A keen observer will note that there are a number of similar taxa that are active this time of year.

Although well described in the literature, surprisingly little attention has been given to the ecology of these creatures. Observational data allows some traits to be compiled, however, and some simple exploratory analyses may allow us to better understand the 'Santa' assemblage.

                       heft transport first.appearance
Coca.cola.Santa         fat  reindeer             1900
Department.Store.Santa  fat  reindeer             1900
Salvation.Army.Santa    fat  reindeer             1890
Kriss.Kringle           fat  reindeer             1800
Santa.Claus             fat  reindeer             1700
Pere.Noel              thin    donkey             1400
Father.Christmas        fat      foot             1400
Sinterklaas            thin     horse              400
Saint.Nicholas         thin      foot              300
Ded.Moroz              thin      foot             1937

We are fortunate to also have sequence data (from DNA on milk glasses and lost beard hairs), so we can add additional information about relatedness amongst these species.

plot(xmas.tree, type = "c", FALSE, edge.color="darkgreen",  edge.lty=1, edge.width=18, label.offset = 1, direction="downward", font=3, tip.color="darkred")

The phylogeny shows that there seems to be an early divergence between European and North American santas. Indeed, there is a group of North American santas (Mall Santa, Coca-cola Santa, Salvation Army Santa) which are closely related (and also appear to share very similar traits, based on the table above). (Note that branch lengths in this phylogeny show nucleotide substitutions, and it is not time-calibrated, due to the absence of santa fossils).

One approach is to identify a few traits and plot them on the phylogeny to compare how traits vary among santas. Let's start with anatomical characteristics:

#Plot traits (fatness) against Santa
co1 = c("blue", "purple")
tiplabels(pch = 12, col = co1[as.factor(heft)], cex = 3.5, adj=c(0.5, 0), lwd=2)

#Let's see the transportation mode trait too:
co2 <- c("yellow", "gold", "darkorange", "red")
tiplabels(pch = 8, col = co2[as.factor(transport)], cex = 2, adj=c(0.5, 0), lwd=2)

legend("topleft", legend=c("reindeer", "donkey", "foot", "horse"), fill=rev(c("yellow", "gold", "darkorange", "red")))
legend("topright", legend=c("fat", "thin"), fill=c("blue", "purple"))
For a future study, we could ask whether the apparent correlation between fatness and reindeer usage is significant, once the underlying phylogenetic relationships were controlled for. 

We can also reconstruct santa traits (here, we look at the form of transportation) to explore what form of transportation ancestral santas likely used:

#reconstruct ancestral state
cc = ace(transport, xmas.tree, type="discrete")
co2 = c("yellow", "gold", "darkorange", "red")
nodelabels(pie = cc$lik.anc, piecol = co2, cex = c(1.5, rep(1, 8)))

The markers at each node show the probability that this ancestral taxa used each of the four possible types of transportation. It seems that the North American santas and their ancestors have long relied on a trusty reindeer mutualism.

Finally, we can look at the geography of all the various santas:

phylo.to.map(xmas.tree, locales)

To run this caRd yourself, follow the link to the R code: https://gist.github.com/cmtucker/8e5677bdd5c409d70738

Monday, December 14, 2015

A bird in the hand… Worth a bunch in the bush?

Guest post by University of Toronto-Scarborough Masters of Environmental Science Student Amica Ferras
     In less than a week, Christopher Filardi achieved a level of cyber-fame worthy of this digital age— but for all the wrong reasons. If you haven’t heard of him yet, that’s okay. Not all of us peruse biodiversity articles over our morning cereal. Here’s what you’ll need to know to hold your own around the water cooler.
Photo: University of Kansas

Christopher Filardi is the director of Pacific Programs at the American Museum of Natural History’s Center for Biodiversity and Conservation. This past September he and his team were part of an international expedition to the mountains of Guadalcanal, one of the islands in the Solomon Archipelago. Lead by native islanders, the team was on a mission to assess the biodiversity and habitat constraints of this unique region in order to develop a tailored conservation strategy. It was there on those mysterious island mountains that Filardi happened upon a true legend by any biology geek’s standards — the Guadalcanal Moustached Kingfisher. Even if you have zero interest in species biology, the stats on this bird are impressive. Only three sightings of the Kingfisher have been documented in all of history: a single female captured in the 1920’s, and another two in the 1950’s. No male specimen had ever been recorded and no live animal had ever been photographed. This bird can play a mean game of Hide-and-Go-Seek.
Upon discovery of the Kingfisher colony, Filardi and his team set to work. Calls were recorded, habitat was meticulously documented, behavior and motion patterns were scrutinized and population dynamics were assessed. And then, they killed one. (Cue the angry villagers with pitchforks and hippies with signs).
The collection was purely scientific. Filardi and his team stuck to a field biology motto of collect, dissect, but ultimately respect. Filardi hoped that the Kingfisher specimen would open the door to discovering more about the elusive species and their ultra-specific habitat. But the road to media-hell is paved with good intentions, and as the story spread like wildfire Filardi’s actions fell under attack. His ‘collection’ was deemed “perverse, cruel” by a representative from PETA to the Daily News, and the UK online Daily Mail described it as “slaughter”. The story exploded, appearing in the Huffington Post, Washington Post, Nature World News and Audubon, just to name a few. For those links and more I suggest checking the wonderful world of Google, but I will personally recommend that you read Fildari’s self-defense in Audubon https://www.audubon.org/news/why-i-collected-moustached-kingfisher, and the Toronto Star’s coverage of the controversy http://www.thestar.com/news/insight/2015/10/17/why-a-scientist-killed-a-bird-that-hadnt-been-seen-in-50-years.html. The Star does a fabulous job of presenting both sides of the story, and also goes into detail about the rather dubious past of field biology.
In the 1700’s and 1800’s specimen collection was more sport than science. It was a my-stuffed-animal-carcass-is-bigger-than-your-stuffed-carcass race, and rare species paid the ultimate price. Great Auks, for example, upon classification as endangered in 1775, were hunted at an alarming rate by naturalists attracted to its rareness. In 1884 a final pair of Auks was caught by fishermen, and no Auk has ever been sighted since. Specimen collection has come a long way since then though, and field biology has contributed to some groundbreaking scientific discoveries. Consider eggs— comparisons of eggshell thickness from samples collected across decades was used to identify the detrimental effects of DDT and other pesticides to natural ecosystems.
So, those are the facts. And my opinion about it? I’m siding with Filardi. Science has come a long way from naturalist trophy hunting in the 1800’s. Nowadays, before even setting foot outside of the lab scientists must undergo a rigorous evaluation process to determine if collection permits will be granted. Cost-benefit analyses, potential outcomes, and fragility of a species and ecosystem are all heavily weighted in before a decision is reached. Filardi’s expedition was no exception to this rule. (And for anyone questioning the usefulness of collections at all, I suggest you read the following article http://biology.unm.edu/Witt/pub_files/Science-2014-Rocha-814-5.pdf. I’d be happy to argue with you on that front another day).
It wasn’t as if Filardi saw the Kingfisher, pulled a net out of his pack and started swinging. After discovering the Kingfisher colony, the bird was carefully observed over several days. Input from the native islanders, assessments of habitat resilience and population robustness were all carefully analyzed before deciding to humanely collect the single male specimen. The unwilling sacrifice of the Kingfisher was honorably recognized, and the collection will be worthwhile if Filardi has anything to do with it. Scientists now have access to a complete set of genetic information for the Kingfisher. It will now be possible to undertake full molecular, toxicological and evolutionary diagnostics. Scientists may discover disease and pollutant susceptibilities that will guide Kingfisher protection efforts, or identify a direct evolutionary pressure to explain the appearance or behavior of the birds. At a more macro level, the specimen could reveal a shared trait between all high-elevation avian species or allow for an assessment of the particular environmental pressures the island ecosystem exerts over its inhabitants.  
Remember though, the point of the Guadalcanal expedition was not a Kingfisher hunt, but an internationally commissioned excursion to study the biodiversity and ecosystem threats in the Solomon Archipelago. Working with native islanders and Solomon government officials, Filardi’s team was working to establish a conservation strategy to protect the unique island system. The Pacific Island tribes have tended to their mountainous lands for decades, but recent international development has threatened the natural state of the ecosystem. Intensive mining and logging ventures have already begun transforming the lowlands of the islands, and climate change at large is effecting the delicate balance of ocean and forest features that unique species like the Kingfisher rely on. For species limited to a single isolated habitat, even minor changes in soil pH, precipitation or fluid motility can have astronomical effects on species survival. These are not the resilient squirrels and raccoons we in North America watch thrive everywhere from lush forests to derelict urban alleyways. Filardi’s collection will go a long way in identifying what needs to be done to protect these habitat-specific island species.
In fact, it already has. Discovery of the Kingfisher led Filardi to talks with local tribes and the Solomon government which culminated in formal agreements to protect the island mountain region under the recently passed Protected Areas Act. Filardi has already booked a return flight to Guadalcanal to help negotiate the next steps in this exciting conservation effort.

So, what do you think? 

Sunday, December 6, 2015

The hurdles and hardships of science in China

In my last post on China I discussed why China is becoming a scientific juggernaut. I focussed on all the things that seem to be working in its favour (funding, high expectations on scientists, etc.). While I do think that science in China is good and getting better, it is also important to point out some of the hurdles and limitations that hold back some aspects of scientific advance here.

In my previous post I noted that the expectations placed on students and researchers (i.e., to produce a minimum number of papers in journals with high impact factors, IFs) provided motivation to do good science. This is undoubtedly true, however, these strict expectations also reinforce a strategy of ‘paper-chasing’ where students are encourage to figure out how to get a paper. This is because the reward structure is so quantitative. While this type of evaluation systems has pros and cons, it does create a different sense of urgency than I’ve experienced elsewhere.

Pragmatic factors
The Great Fire Wall of China from "Cracks appear in the Great Fire Wall of China" posted by the China Daily Mail, Sep. 25th 2013.
I have never yelled at my computer or cursed the internet as much as I have in China. In the west we often hear about the ‘Great Firewall of China’ and probably do not think much about what this actually means. It sucks. The internet barely functions for significant proportions of the working day. I thought that this might have to do with the number of people and lack of infrastructure, but I no longer believe this to be true. Other countries in the region have great internet, and China has very advanced infrastructure. I’m pretty sure that when there is high traffic, the national security protocols and activity monitoring servers are the bottleneck.

Because the government policy is to block certain websites, most of the scientific internet websites and data sharing portals are not accessible here, but this may change at any given time. For example: Google Drive, Dropbox, Facebook, Blog sites, Twitter, Google Maps, and Google Scholar are all services routinely used by scientists and which are blocked in China. The reason for these to be blocked, as far as I understand it, is that they do not share users’ activities and the government cannot monitor what individuals share and download (which reinforces the value of these services to me). I also suspect that they are blocked to give local companies a chance to succeed without competition from global corporations, or perhaps simply because of disagreements with the companies.

I have had immense trouble trying to share files with my lab back in Canada (and to post this blog entry –which is why I’m doing it from Cambodia!). I am not currently engaging in social media –something that I saw as a legitimate activity for communicating science. I am having a very hard time searching for articles without Google Scholar. I also have trouble with other websites that should not be blocked, but that use third party encryption. For example, I can’t log in to my University library in Toronto, and I couldn’t connect my Canadian grant application to the Canadian Common CV (which we are required to do in Canada) because the CCV web interface was blocked (I had to get my post doc in Canada to do it for me). I have tried to go to researchers’ websites to find that they are blocked because they use a blogging site (e.g., Wordpress). The amount of time I spend doing basic online professional activities has increased 3 to 4-fold.

This is important because Chinese scientists are at a disadvantage when it comes to international collaboration and participating in online initiatives. I would encourage scientists outside of China to consider these imposed limitations to ensure that information and collaboration is barrier-free. Here are some tips:

  1. Don’t link to your Google scholar publications on the publications page of your website
  2. Don’t use a blog site to host your website (e.g., Wordpress)
  3. Don’t use Dropbox or Google drive to collaborate on papers
  4. Don’t use gmail as your work e-mail, Air China, for example, won’t send e-mails to gmail.
  5. Social media has emerged as a great way to communicate with broader communities, it is important to recognize that these dialogues exclude Chinese scientists.
  6. Ironically, as I write in this blog, blogs are blocked and while blogs provide a great platform to discuss ideas and issues, they are not available to Chinese scientists. 

These last two are interesting as journals increasingly require or request tweets or blog posts to help maximize exposure, but these forms of communication are not on scientists’ radar here.

Chinese science has been increasing by leaps and bounds despite these limitations. This is a testament to the hard work and dedication by Chinese scientists. I have no doubts that basic scientific research in China will continue to increase its stature and impact.

One thing that is interesting to me is that many of the graduate students here use VPNs (Virtual Private Networks) to mask their IP addresses. They are able to access blogs, Google Scholar, etc. In conversations with people, VPN use is extremely widespread and successful at circumventing government filters, most of the time (there seems to be an arms race between the government and VPNs). It really makes me wonder how much longer these governmental controls can be realistically maintained.

Wednesday, December 2, 2015

Paper of the lustrum*

(*lustrum = five years)

I’m co-teaching (with Kendi Davies and Julian Resasco) a graduate seminar focused on current trends and advances in community ecology. It’s been great, and having a small group with varied backgrounds (disease ecology, microbial ecology, restoration, community ecology theory, etc) allows for flexible and interesting discussions. Somehow the topic last week drifted to favourite papers, and we ended up with a plan to choose and defend the paper that was—in our opinion—the best one published in ecology in the last 5 years.

Today we described and defended our choices and tried to decide what the ‘best’ actually means, anyways. I don’t think anyone quite realised just how difficult this exercise would be. First, 5 years isn’t actually a very long time when measured in academic publishing years. That’s only the time of the average PhD, or less than the entire tenure-track period. I immediately thought of several papers I love, only to realize that sadly, they were from before 2010 (e.g. papers like these). 

Nearly everyone started their search the same way: with a Google Scholar search, looking at the most cited papers between 2010-2015. Some people looked at the most popular papers from high impact journals (Ecology Letters, Science, Nature, PNAS, etc); others looked at the output of eminent ecologists during that time period. At least one used his committee members for advice, and for the new grad students this was a nice crash course in the recent literature. Citations, quality journals, or eminent names might have been starting points for finding these papers, but it was interesting how little these actually seemed to matter. When defending their choice of paper, absolutely no one mentioned citations or journal as deciding factors. 

The papers we chose, and why: 
Conceptual synthesis in community ecology. (The Quarterly Review of Biology) Vellend 2010  
This was my choice, although I went back and forth between a short list of papers. For me, the ‘best’ paper had to either change how we do ecology, or how we think about ecology. I think Vellend 2010 has a lot of value as a pedagogical tool, and a device for organizing ecological knowledge. It has the potential to aggregate the varied, context dependent data that ecologists have been collecting for generations. Further, rather than the disjointed approach my undergraduate texts took for community ecology (productivity here, lynx-hare plot there), a single framework should help students understand community ecology as a cohesive set of ideas. And I admire papers that have big ideas.

 This was a cool choice, because it turns out to be a massively important development that many of the less molecularly-inclined knew little about. This paper introduced the use of CRISPR/Cas for gene editing. The CRISPR system is been found in archaea and bacteria, and provides a form of adaptive immunity against viruses. Importantly, it has been developed for use in incredibly precise genome editing that is heritable. It has massive implications for the study of evolution, microbial ecology, disease, population genetics, and everything in between. It is also the source of ethical concerns because it can (and has) be used to modify human embryos. 

Biodiversity loss and its impact on humanity. (Nature) Cardinale et al. 2012 
This was the choice of two students, so it may have been the de facto winner. It is a massively cited paper (>1000), and both students chose it in part because it makes a clear contribution to human welfare and society. It represents a massive undertaking (they analysed more than 1000 papers) reviewing research on how biodiversity relates to a large number of relevant ecosystem services. In particular, Table 1 (below) can be used for applied and basic research, and shows where research and data agree, disagree, or are lacking. This is certainly a must read for ecologists.

This paper helped to concentrate and inspire research on intraspecific variation and to highlight the areas of research that are still poorly studied (and it actually made my short list too). There is obvious variation within species (long acknowledged as important to evolution, starting with Darwin) but this is often ignored in community ecology. Bolnick et al. point out the many possible and important implications that arise from such variation. The writing is clear and highlights extremely well the general mechanisms that might interact with intraspecific variation. For the student who chose it, it was inspiring enough when it first came out, that they changed their research direction. 
Table 1: Bolnick et al. 
This paper was chosen in an opposite fashion: it is brand new, and rather than having inspired current research, the student thought it would inspire future approaches. The paper integrates community ecology and disease ecology in a novel and sophisticated way, advancing an area of research currently receiving a lot of attention. In this paper, mice are ‘mesocosms’ in which the importance of bottom-up versus top-down control of infection (by malaria and a nematode) could be tested. (Quote: "It's a real page-turner"). 

This was another paper chosen because it inspired the student's current studies. Ladau et al. brought together a massive data set for marine bacterial biodiversity, allowing them to map it on a global scale and develop predictive distribution models. Interestingly, they found that diversity patterns were lower at the equator, contrary to typical findings in other organisms. The student cited the careful methodology, extensive data, and comparison of results to those in macro-scale systems as the paper’s strengths. 
From Ladau et al. "Maps of predicted global marine bacterial diversity. Color scale shows relative richness of marine surface waters as predicted by SDM. Samples were rarefied to 4266 rDNA sequences to enable accurate estimation of relative richness patterns on a global scale from data sets with different sequencing depths. True richness is expected to exceed estimated values. (a) In December, OTU richness peaks in temperate and higher latitudes in the Northern Hemisphere. (b) In June, OTU richness peaks in temperate latitudes in the Southern Hemisphere..."

The final paper was Kendi’s choice. Community ecology has struggled with weak connections between pattern and process. The experimental and quantitative work coming from this research group has provided multiple examples for how to connect theory, statistics, and experimental results in a very rigourous fashion. In this paper, the focus is particularly on functional/trait approaches to community assembly and coexistence, and the authors manage to connect careful experimental data with Chessonian coexistence theory, using trait data to estimate species’ fitness and niche differences, and then using these to predict species coexistence.

After the fact, of course, lots of other great papers came to mind. It isn't really possible to choose one best paper, either. But the characteristics people looked for in a great paper were pretty similar - inspiring, providing novel approaches to particular questions, focused on big questions or ideas, and making contributions that go beyond academic ecology.

Monday, November 23, 2015

Challenges for microbial ecology

It is common in ecology for promising new areas of research to grow rapidly in terms of funding, students, and papers. Sometimes, such growth outpaces supporting development. This can lead to criticisms, which, when properly dealt with, can help such burgeoning subfields to mature. These are challenges currently facing microbial ecology as well. [Note I use the term microbial ecology here to refer to the ecology of microbes, not simply ecology that happens to use microbes as a study organism (e.g. Graham Bell or Lin Jiang’s experimental work).]

Microbes are fascinating. They are a very large and important group that has been under appreciated in ecological research until recently. Now, thanks to ever-improving molecular methods, the ecology of microbes is increasingly accessible. It has formed the basis of some great citizen science and public outreach (microbes in space, your home, your cat). And scientifically, work from this emerging subfield is often excellent, with broad implications to other areas of ecology (just as a couple of cool examples). Microbes are different from other taxa for all sorts of cool reasons - horizontal transfer of genes, tiny genomes, and immense functional plasticity – and this makes for fascinating discoveries.

However, the newness of this subfield is apparent as it attempts to mesh microbiology with the existing body of ecological knowledge and approaches. The result, at times, is that existing ecological theory and methods are applied unquestioningly to microbial datasets, but may not be appropriate. Unfortunately, the assumptions behind such analyses and their limitations with respect to microbial datasets aren’t always recognized, leading to questionable interpretations. There is sometimes also an over-reliance on “pipeline” approaches to microbial research; for example: collect samples, extract DNA, sequence, run through the QIIME pipeline, and present descriptive analyses, particularly beta-diversity metrics (Unifrac), PCoA or NMDS plots, and permutation-based statistical tests (e.g. ANOSIM) to determine whether assemblages of interest differ in composition. These pipelines originally arose because of the difficulties in handling such data sets and the need for specific software for analyses.

Of course, it is important to keep in mind that microbial ecology is in an early phase, where accumulating data and cataloging diversity is a priority. Mostly, issues arise when major questions in ecology are posed but perhaps without quite having appropriate methods or data to answer them. To provide an example, I sometimes see microbial ecology papers attempting to differentiate between niche and neutral processes as the drivers of microbial community assembly. Microbes are often thought of as lacking meaningful dispersal limitation (‘everything is everywhere; the environment decides’ is a common heuristic). As a result, it may be that communities assemble in a highly stochastic fashion (random arrival) or perhaps environmental filters and interactions do matter. But the issue of “niche” versus “neutrality” is a difficult question to answer using observational data in any system. It requires considering the many assumptions that underlie “niche” and “neutral”, making predictions about the patterns that would arise from these mechanisms, and then being able to differentiate these patterns from others that you might observe. This is a tall order for any observational data set, and I think that is especially true for microbial data sets.

Below I have listed in more detail the challenges arising when attempting to integrate ecology and microbiology. These relate to all sorts of ecological questions and analyses, including but not limited to “niche versus neutral”.

a) True measures of abundance are not typically available, and 16S copy number is incorrectly used as a measure of abundance. 16S ribosomal RNA is the typical target of studies of bacterial ecology. However, counts of 16S copies per taxa are not equivalent to abundances (as say, counts of individuals in macro-systems are): instead, different taxa can have different copy numbers. Where one taxa might have 2 copies, another might have 10. 

Despite this, it is common to see it used as a proxy for abundances; for example, to calculate beta-diversity measures such as Bray-Curtis. Since neutrality predicts patterns related to species' abundance distributions, and changes in diversity through time, when conclusions rely on 16S-based ‘abundance’ metrics, they are suspect. Some attempts are being made to address this – for example, this paper from Steve Kembel et al. (2012) recognizes that copy number is a conserved trait and so could be controlled for in a phylogenetically-informed way. qPCR can also be used to measure true abundances in samples. (See comments).

b) What spatial scale is relevant to microbes? Bacteria are very small (of course). However, sampling methods often involve fairly large samples in relation to bacterial body size. 1 g of soil, although tiny compared to many ecological samples, is a massive amount of material in the context of bacteria. There can be 10^8 cells/g of soil, and by one estimate the interaction distance between individuals is ~20um, and so it is not likely that a 1g sample is equivalent in scale to a “community”.

If a typical observational sample is not representative of a community, community ecology theory, which is dependent on assumptions about local interactions and environmental filters at particular spatial scales may not be relevant. Scale issues are an ongoing problem in ecology, and defining the ‘community’ is a thorn in our sides. It is understandable that this is a problem for a new field. Thinking about the kind of data collected as relating to macroecology may be a fruitful approach (see this paper for similar ideas on the topic). 

c) Temporal scale has similar issues. Unlike in macro-scale systems, microbial time scales are very rapid, with approximately 100-300 generations per year (with some variation between taxa). The scale of environmental variation that affects these communities should be finer as well. This is a benefit and a difficulty of the system. For examples, one can potentially observe a community assemble to equilibrium in a bacterial system. But describing changes in bacterial composition observed over 1 year as succession and placing them in the context of ecological literature on plant succession seems imprecise. The scale of observation is of particular importance.

d) There can be issues in differentiating between active and inactive taxa, since microbes may be present in a sample but dormant. Methods exist to differentiate between these taxa, but when not applied, an apparently rare taxa in an assemblage may actually be an inactive taxa.

e) Sampling artifacts and other biases can arise between labs and runs, including biases related to PCR, primers, DNA extraction, storage, rarefaction, and more. This is an issue equivalent to limitations in methodological approaches in every field, and one that is actively being worked on (for example, developing standardized approaches). Further, the existing technology is pretty amazing.

f) Limitations of the current null models and statistical methods being applied. Null models are still a work in progress for ecology, and need to continue to be developed and perfected. But I think that there are specific issues that need to be considered in applying some of these methods to microbial data in particular, and there is a need for concerted research on developing statistical methods for such massive datasets.

In particular, I suspect there is an issue regarding heightened Type 1 error rates and issues with inadequately randomizing very large data sets. Ulrich and Gotelli (2012) hint at some of these possible issues:
“null model analysis may not be well-suited to such large data sets. The general statistical problem is that with very large data sets, the null hypothesis will always be rejected unless the data were actually generated by the null model process itself. So, large data sets may often deviate significantly from null models in which row and column sums are fixed, regardless of whether species occurrences are random or not (Fayle and Manica 2010). This was not a problem in the early history of null model analysis, when ecologists worried that apparent patterns in relatively small data sets might reflect random processes”
There is not enough time here to delve into most of these issues in detail, but permutation tests/Mantel test type analyses have a number of important limitations and assumptions must be tested for appropriate usage (from Pierre Legendre). From the ANOSIM website
“Recent work…has shown distance-based methods (e.g., ANOSIM, Mantel Test, BIOENV, BEST) are inappropriate for analyzing Beta diversity because they do not correctly partition the variation in the data and do not provide the correct Type-I error rates.” 
If Type I error rates are frequently high in past analyses, or inappropriate statistical models were used, data can be re-analysed as better procedures arise. But we should also recognize that there is uncertainty in past results (particularly weak or barely significant patterns). It should also suggest that we have yet to gain a true understanding of what patterns and relationships in microbial ecology are truly significant.

Microbial research produces some of the most complex and large datasets that ecology has ever had to deal with. As a result, developing specific theory and appropriate methods for this data should be a priority alongside discovery-focused research. Fortunately, this creates opportunities for ecologists to develop methods for complex systems, which should be beneficial for the entire ecological discipline. And many people are already attempting to fill these knowledge gaps, so this is not to underplay their accomplishments. Hopefully there will continue to be developments in microbe-specific theory, with appropriate assumptions regarding temporal and spatial scale. Microbial ecologists can do better than co-opt standard ecological approaches, they can improve on them (e.g. Coyte et al. (2015)).

Conservation’s toughest decision

Guest post by Shelby Hofstetter, currently enrolled in the Professional Masters of Environmental Science program at the University of Toronto-Scarborough

“We should have thrown in the towel years ago!”- the dinner-table conversation takes a drastic turn from gushing over new panda bear cubs at the Toronto Zoo to a more pessimistic view of the state of global panda conservation efforts. The speaker of these words is recalling a program that aired on the CBC when the pandas were first arriving at the Toronto Zoo. In it, host Amanda Lang acknowledged herself as a “panda hater” and expressed her disapproval of the money wasted on continued panda conservation efforts that are based solely on their appearance (link to video below). As someone who queued in line for the chance to take far too many pictures of the adorable bears, I blanch at some of Lang’s comments that pandas are “big and stupid“ and “want to be extinct”. But as a student of conservation, I recognise the underlying truth that we as a society have a bias for spending our conservation dollars on big, fluffy animals, regardless of their likelihood of survival.

(Photo taken by Shelby Hofstetter at the Toronto Zoo)

But what are the alternatives? With the realisation that funds for biodiversity conservation are finite, there has been a long history of debate over the best methods for choosing worthy species. The umbrella species concept seems to be the logical response to this conundrum – the classic 2 for 1 sale where conservation efforts for one species have the added bonus of protecting various other species that share the same ecosystem. This is the reason why some claim that the “big, fluffy” species are often highlighted in conservation projects, because the large, continuous tracts of land that are a necessity for their protection become a safe haven for many more.

The reality of the umbrella species concept may not be as simple however- there is some debate over how well it actually works. In some cases the large habitats required for the umbrella species do not overlap with biodiversity hotspots for other types of organisms like invertebrates, plants, amphibians or reptiles[1]. And unfortunately, even in cases where these pieces of habitat would provide protection for additional species, safeguarding the large amount of land necessary is often unrealistic[2].

Figure 1. Based on phylogenetic diversity, species A would be a higher conservation priority than species B or C as it has fewer close relatives that would be similar genetically[4]

Another response to this conservation riddle is aptly named the “Noah’s Ark Problem”, and is a framework for choosing species for conservation based on cost and likelihood of survival, but also on phylogenetic diversity[3]. This objective focus on phylogenetic diversity, or the amount of genetic history that a species contains, has gained momentum in recent years and is aimed at saving species that encapsulate high amounts of Earth’s evolutionary life history. The hope is that phylogenetic diversity is correlated with genetic diversity in general, which could also give these species a better chance of adapting to a changing planet[4].

Another notion that is becoming more prevalent is the consideration of ecosystem services, or the benefits that humans derive from a species or ecosystem, when planning for conservation projects. This concept is not necessarily centered around a specific species, but is more focused on the ecosystem as a whole. The emphasis on ecosystem services may help increase the perceived relevance of conservation projects, as the benefit to society is being highlighted. The uptake of this idea within global conservation efforts has been slow however, with less than 10% of conservation assessments including ecosystem services as part of their rationale for conservation[5]. There also seems to be a push for determining the corresponding economic and monetary value of the services that ecosystems provide to society. This is a science that, in a world focused on dollars and cents, may become very important to determining which species or areas are worthy of conservation efforts.

The jury is still out on how to best make conservation’s toughest decision-   determining which struggling species on this planet should be the lucky winners of our conservation resources. In the meantime the importance of this issue is becoming very clear, as many suggest that Earth is currently experiencing a sixth mass extinction. Smart and timely decision-making is vital for which species limited conservation efforts should be focused on. I wouldn’t go so far as to call myself a “panda hater”, or suggest that we “throw in the towel” on conservation efforts for big fluffy species that may not be likely to recover, but I do agree that these decisions should go beyond visual appearances.
Additional Links:
link to Amanda Lang video: https://www.youtube.com/watch?v=0bm-kEnK3yk

1. Marris, E. (2013, December 24). Charismatic mammals can help guide conservation. Nature | News.
2. Fleishman, E., Blair, R., & Murphy, D. (2001). Empirical Validation Of A Method For Umbrella Species Selection. Ecological Applications, 11(5), 1489-1501.
3. Weitzman, M. (1998). The Noah's Ark Problem. Econometrica, 66(6), 1279-1298.
4. Owen, N. (2014). Life on the edge. Significance, 26-29.
5. Egoh, B., Rouget, M., Reyers, B., Knight, A., Cowling, R., Jaarsveld, A., & Welz, A. (2007). Integrating ecosystem services into conservation assessments: A review. Ecological Economics, 63(4), 714-721.

Monday, November 16, 2015

Where is south? Uncovering bird migration routes

Guest post by John Viengkone, currently enrolled in the Professional Masters of Environmental Science program at the University of Toronto-Scarborough
Wilson’s Warbler http://www.utahbirds.org/birdsofutah/BirdsS-Z/WilsonsWarbler.htm
There are approximately 450 native migrating bird species that for at least part of the year reside in Canada, but where do they go when they aren’t in the True North Strong and Free? If you ask just about anyone, they’ll tell you that birds fly south for the winter, but where exactly is south? South could be as close as the next city, the USA or as far as Tierra Del Fuego. Also do they make stops on their way to this “south” and do they mix with other populations? The truth is there isn’t much information on where many migrating species go or the route they take to get there.

But why should we care where they go when they leave Canada, they seem to always come back in the spring. The truth is not all birds are coming back, there has been a marked decline in the population size of many migrating neotropical bird species. As the leading cause of species loss, humans need to figure out whether these bird populations are facing stressors in their breeding, wintering, stopover range or some combination of the three so we can help manage them. The first step in doing this is learning the birds’ migration route. 

The effort to understand the movement patterns of birds began in North America during the 1800s when the famous ornithologist John James Audubon started tying silver string to the legs of eastern phoebes, Sayornis phoebe, to see if individuals that left in the fall returned in the spring. Of all the birds Audubon marked, 2 returned in the spring. This little experiment transformed into the bird banding/ringing program we know today with different coloured metal bands replacing the pieces of silver string.

Though the bird banding program has been essential to the understanding of bird ecology, life history and migration it is has one major flaw. This flaw is that banded birds must be spotted again and it’s estimated that only 1 in 10,000 banded birds are recaptured, leaving a large data gap. So why use bands, why not use GPS tracking devices? Well, they do for larger birds but for many bird species the size and weight of a tracker is too much of stress so a better solution is needed. This solution is up and coming from Dr. Kristen Ruegg’s lab at UCLA and it has been dubbed The Bird Genoscape Project.

Ruegg and company have taken on the task of creating a protocol that will allow them to identify where a migrating bird has come from by using just a feather. To get a full comprehensive understanding of this protocol please refer to Ruegg et al. 2014 but I’ll briefly explain their methods here: Variation in DNA is what makes individuals unique but a huge portion of an organism is actually shared with the individuals of the same species. As groups or populations of a species become more isolated and breed with other individuals in their populations more, the populations start to diverge, this is population differentiation. Individuals in a breeding population will be more similar to each other than to other populations.

The UCLA team used the concept of population differentiation to find the small bits of DNA, called single nucleotide polymorphisms (SNPs), that are unique to each breeding population, a genetic fingerprint some might say. For their study they looked at the Wilson’s warbler, Cardellina pusilla, taking small blood samples from individuals in each breeding population and each population’s genetic fingerprint was made.

With a genetic fingerprint for each breeding population Dr. Ruegg and her collaborators were able to collect feathers from Wilson’s warblers across North America and identify where it came from with an 80-100% success rate. So a feather collected in Colorado in the late fall could be traced back to the British Columbia breeding population, meaning Colorado is a stop off point. This solves the major problem that banding had; you don’t need to come in contact with the same bird to get information, any bird in the species will work. 

From Ruegg et al. 2014. Each colour depicts a breeding population, arrows are stopovers and circles are wintering grounds
An interesting finding from UCLA’s study was that there are 6 breeding populations of Wilson’s warblers opposed to the 2-3 that biologist previously thought and that 3 of the breeding populations actually share a wintering ground and flight path. Two of these three breeding populations are stable but one population is declining, suggesting the cause of decline stems from the declining population’s breeding ground. If the issue stemmed from the wintering ground of the flight path, the other populations should be affected too.

So what’s next? Ecological managers now know where the issue is likely originating from for the Wilson’s warbler but still need to identify the root cause. As for The Bird Genoscape Project, Dr. Ruegg has moved on to repeating this study with the American Kestrel. There is also work being done with museum samples to see if ranges and flight paths have shifted with time. It’s looking like The Bird Genoscape Project can only get bigger, spreading to more migrating bird species and become an essential tool for bird conservation just as bird banding did in the past.

For more information see:
Ruegg K.C., Anderson E.C., Paxton K.L., Apkenas V., Lao S., Siegel R.B., Desante D.F., Moore F., and Smith T.B. 2014. Mapping migration in a songbird using high-resolution genetic markers. Molecular Ecology 23:5726-5739.
Kristen’s interview with Podcast Eye’s on Conservation is available on iTunes