The vanishing pangolin: How do you change the value of an endangered species?

Extinction is forever. Extinction reduces the biological heritage of the Earth and is something that we cannot undo.

While living in China, and traveling around Asia, I have said something to my children I have never said before: “I want you to take a really good look, these animals will go extinct in your lifetime”.  I said this as we were watching 8 of the 60 remaining Hong Kong pink dolphins.

Hong Kong pink dolphin (photo by Shirley Lo-Cadotte)

Species become rare and endangered for many reasons, like habitat destruction, pollution, human facilitated spread of problematic species (rats for example), and direct harvesting. While all of these factors are subject to laws and regulations that attempt to control them, it is the last one, harvesting, that relies most on altering peoples' wants and desires. I don’t know why, but to me it is also the saddest cause, the idea that a species dies out because we desire it and kill it or chop it down, just doesn’t seem right.  

Walking through the market alley near my apartment in Guangzhou, China, I saw something that both intrigued and horrified me: a dead and quartered pangolin. You may not be familiar with pangolins –also called scaly anteaters; they are mammals about the size of a large cat or medium-small dog (like a cocker spaniel), with a very long and thick prehensile tail that they use in trees. Their most unique feature is that they are covered in large flat scales that are made of keratin –the same as your fingernails. 

A Chinese pangolin, Manis pentadactyla (https://commons.wikimedia.org/wiki/File:Pangolin%27s_tail.jpgsted to Flickr by verdammelt cc-by-sa-2.0) 

Pangolins are critically endangered. They also have the distinction of being one of the most trafficked animals in the world. In China and Vietnam there is high demand for pangolins because they are considered a delicacy and more importantly their scales are used in traditional medicine. These scales are believed to provide a cure for a number of diseases, including cancer. The incidence of cancers in China is skyrocketing, which is not surprising given the level of pollution, and couple this with increasing affluence, the desire and ability to pay for pangolin parts has never been greater.

Obviously pangolin scales do not cure cancer. You might as well save your money and suck on your fingernails instead, but evidence and logic are not likely to sway mortal fear. There are groups in Asia dedicated to protecting endangered animals and educate citizens about wildlife. Such organizations have an opportunity to capitalize on recent attitude shifts in China and elsewhere, where animal wellbeing is increasingly seen as important. In China, pet ownership has increased dramatically over the past decade and pets are now seen as companions –which I suspect was partially a result of the one-child policy. But the demand for pangolins still exists. When we visited the Angkor Conservation Centre in Cambodia, which works tirelessly to rehabilitate animals and educate people, they were recovering from the theft of one of their pangolins from an enclosure, which they knew was transported to China.

The Chinese authorities are coming down hard on the illegal pangolin trade. They now routinely arrest individuals selling pangolins and seize large shipments. While such seizures and arrests show that the Chinese government is taking pangolin protection seriously, there is only so much they can do while demand is high.

Police confiscating a large illegal pangolin shipment bound for China (photo originally from news.163.com) 

My Mother-in-law, who is from southern China, said it best when I told her about the dead pangolin in the alley: “people just need to be educated”. That is really where the answer lies. Laws can only change peoples’ behaviour so much; education campaigns are desperately needed. Currently, there is an internationally funded billboard campaign in China to stop people from buying elephant ivory. Ivory demand is high in China. Despite the importance of reducing ivory purchases, I would argue that this type of education campaign needs to focus a little closer to home, and Pangolin conservation efforts are in desperate need of help. 

When we were visiting the conservation centre in Cambodia, I told my children that the Pangolin would go extinct in their lifetime. I really hope that I am wrong.

New ways to address an old idea: rethinking the regional species pool

Like many concepts in ecology (metacommunity, community), the idea of a regional species pool is useful, makes conceptual sense, and is incredibly difficult to apply to real data. Originally, the idea of a species pool came from the theory of island biogeography (MacArthur and Wilson, 1967), where it referred to all the species that could disperse to an island. Today, the regional species pool appears frequently, across null models, studies of community assembly both empirical and theoretical, and metacommunity theory. 

Understanding how particular processes shape community membership—whether the environmental, competition, or dispersal limitation—depends on knowing the identity of all the species that could have potentially assembled there. The species pool as defined by the research provides the frame of reference against which to consider a community's composition. Most null models of community assembly rely on correctly identifying this set of species, and worse, tend to be very sensitive to bias in how the regional pool is defined. If you include all species physically present in a region, in your species pool, environmental filtering may appear to be particularly important simply because many of those species can’t actually survive in your community (the narcissus effect). Given the importance of null models to community ecology, defining the species pool appropriately is an ongoing concern.

There are many decisions that can be made when asking 'which species could potentially be members of a community'? You could include all species that can physically arrive at a site (so only dispersal or geographic distance limits membership), or only include those species that can both arrive and establish (both dispersal and environmental conditions limit membership). Further, the availability of data is key: if you use observational data used to determine the environmental limitations, you may also incorporate the outcome of biotic interactions indirectly. If some species are rare and have low observation likelihoods, they will be under-represented. Abundances may be useful but inaccurate depending on how they are measured. Finally, it is common to define species as either present or not present for a species pool; this binary approach may conceal ecologically important information.

The 'filtering' heuristic for understanding community membership. Species groups 1-3 could each be defined as a regional species pool, depending on the definition applied.

A number of recent papers provide alternative approaches to constructing species pools, meant to avoid these pitfalls. Researchers can define multiple contrasting species pools, each pool representing an ecological process (or perhaps multiple processes) of interest. Each species pool can be modified further to reflect the strength of a particular process in constraining membership. The regional pool is not seen as a single entity but as a number of possible configurations whose utility is in comparison.

Lessard et al. (2016) illustrates how to produce this kind of process-based species pool with various constraints (figure below). Their three-step approach is to:

1. Define absolutely all possible members of regional pool. This is determined by identifying all assemblages in the region containing at least one species also found in the focal community (creating a 'dispersion field') (figure below, section A). This delineates a large region and identifies all species within it.
2. Calculate the probability of resampling a species from the focal community elsewhere in the dispersion field. This is done in the context of the process of interest. For example, the probability of observing a species in the focal community and another community might be determined based on the geographical or environmental distance between those sites. Every site in the dispersion field would now have a probability (or distance really) associated with it, representing some similarity with the focal site.
3. Finally, apply constraints to the calculated probabilities. You might choose to consider only the species within communities that are at least 50% similar to the focal community, for example. Such constraints would reflect the strength or importance of filtering by the process of interest.

Another recent paper (Karger et al., 2016) takes an approach with a number of commonalities to the Lessard et al. method. However, rather than resampling to produce potential pools of species (with species being defined as present or absent), they advocate a probabilistic approach to species pools. They suggest that species pools should be thought of as a set of probabilities of membership, which may be more reflective of ecological reality. In some ways, this is a simply a formalization of probabilistic sampling from Lessard, but instead of applying constraints, the researcher acknowledges that probabilities vary for different species. “Hence, a species pool can simply be defined as a function of probabilities of a species’ occurrence in the focal unit given the unit’s environmental and biotic conditions, geographical location and the time frame of interest”.

Both comparative and probabilistic approaches to defining species are logical advances, and one way of dealing with the untidy concept of the species pool. If this topic is of interest, a few other papers, albeit slightly less recent, are definitely worth reading: Pigot and Etienne 2015; Lessard et al. 2012, Carsten et al., 2013.

From Lessard et al., 2016. The three steps to build a species pool.

Reining in traffic –looking to China for solutions?

Human impacts on landscapes are immense. Urban areas represent complete transformations of the geological, hydrological and ecological norms in landscapes. But while urban effects are concentrated to relatively small areas, the roads and rail lines feeding cities create a pervasive and diffuse network of negative impacts. Roads funnel rain runoff and can cause local flooding and this runoff also concentrates pollutants. Further, roads alter wildlife movement. For example, the fragmentation of formerly continuous forest in Florida is worsened by large busy roads, and black bears there are unable to move long distances to find mates. The result of this is that the Florida Black bear populations are getting smaller and more genetically inbreed.

Roads are created to meet traffic demands. The more people drive and the further they drive, the more roads we build. Cities around the world are growing, meaning that more cars are concentrated in small areas. The increase in automobile use also has direct environmental consequences. Cars, thanks to their internal combustion engines, add pollution to our local environments –carbon monoxide, particulate matter, and other toxins create smog, exacerbate respiratory ailments, and contribute to global warming.

More cars also means more traffic congestion and greater difficulty in getting from A to B, meaning that we spend more time travelling to, instead of being, somewhere. Heavy reliance on automobiles directly affects our quality life in both positive and negative ways.

1950s traffic jam in Los Angeles (from Wikipedia)

Given the undesirable consequences of cars, many cities try to reduce car use. In North America, cities employ a number of strategies, including: minor improvements to public transit (while often passing on the costs to riders), creating car free zones (which have been very modest in North America, whereas European cities have been much more successful –Montpellier, France is a great example), introducing tolls, and limiting parking in the city core. It is safe to say that the North American approach to dealing with traffic has been less than spectacular –just drive through Toronto or Los Angeles during rush hour.

Living in China for the past several months, I have been intrigued by how Chinese jurisdictions have dealt with traffic. And traffic was something that needed dealing with here. In the late 1990s and early 2000s, thousands of new cars were added to roads every single day.  The air quality in China is abysmal and having hundreds of millions of cars driving at the same time only make things worse. So governments in China decided to experiment with ways to reduce automobile use.

In China, much of the power to control automobiles resides with municipalities –they are the ones who set local traffic laws and issue license plates. From conversations with scientists from different regions of China, I have compiled ways different municipalities deal with traffic and reduce automobile use. Here are some of the ways that municipalities try to reduce automobile traffic:

1) Massive investments in public transit

There can be no real traffic solutions without building fast, efficient and affordable public transit. China has been a world leader in public infrastructure development over the past ten years. For example, Shanghai has one of the largest metro systems in the world, and has opened a new line every other year since 1999! They are currently building two new lines, which will give Shanghai 18 metro lines and about 400 stations. In Guangzhou, where I currently live, they also have a very modern and rapidly expanding metro system. Guangzhou currently has 8 lines with 4 more under construction! In all the Chinese cities I’ve been in, the metro systems are modern, efficient, heavily used, and very affordable. In Guangzhou, a bus ride works out to be about 35 cents US and a metro trip to the airport (the longest trip you can take in Guangzhou I believe) is about $1.15 US.

In Toronto, where I normally live, and like most other large North American cities, subway construction has not been sufficient to keep up with population growth. Local politicians seem to be unable to make the tough decisions to get public transit infrastructure built. But this infrastructure is the linchpin for any successful reduction in automobile usage.

2) Driving days

During the 2008 summer Olympics, Beijing created a system where cars were allowed on the roads only on certain days. Which days people could drive their cars depended on the last number of their license plates. This scheme was successful in reducing traffic congestion and air pollution. Since then, they have periodically reinstated this policy, especially during extremely bad air pollution days. I was there in early December, and road sharing was in effect then.

3) Making license plates really, really expensive (or difficult to get).

In Guangzhou, Beijing, and Shanghai, getting a car is easy, but getting a license plate, now there is the real hurdle. Since 2012, Guangzhou and other cities have severely limited the number of license plates issued, and now people can get a plate in one of two ways in these cities: by joining a lottery or going to an auction. In the lottery, a person submits an application and waits for the results. One person told me it took them three years to get their plate in the lottery. In the auction, the plates go to the highest bidder and the price for a license plate at auction has sky rocketed. A person told me that plates at auction now go for more than 60,000 RMB (about  $10,000 USD), which costs more than an economy car here! This person also quipped that the plates have become more of a status symbol than the actual car.

4) Your license plate will die

In Guangzhou and other cities, license plates expire. No, not like they expire in North America where you pay an annual license fee. They expire after 10 years and are no longer valid, and the driver must re-enter the lottery. 

5) Pay the toll

Many of the intercity highways have tolls here. While this is not a policy that affects travel behaviour within cities, it does influence driver choices traveling outside the city. Tolls only work when there are decent alternatives, and the rail system in China is excellent. There are frequent trains and many high speed lines in operation (where the trains go faster than 250 km/h). We don't have many toll roads in Ontario, but the one we have near Toronto, hwy 407, doesn't go into the city (so doesn't influence commuter decisions), and does not have viable options for alternative travel. This highway is an example of poor government policy and it was one of the worst policy decisions by a government who thought private companies should run public infrastructure. Its nothing more than a cash grab that doesn't serve the broader good. But I digress.

I have been struck by the variety of approaches and the experimental nature of policy making. What I mean by experimental, is that some policies seem to be ‘test run’ to see how people respond and if the policies result in the desired effects. China is able to institute creative and extreme measures because of the government’s unique ability to change policy without public debate. Often these policies are instituted overnight with little warning. In China, people seem to take government edicts with a “well, what can you do?” attitude. But if there is a country that can change the automobile culture, China is a good candidate. They did change what a family was with the one-child policy.

While most North Americans would certainly have a problem with the lack of transparency and seemingly impulsive nature of government decisions, China is providing the world with working examples of how to reduce the number of automobiles. It is clear to most, that without strong governmental leadership, a robust set of policies, and massive infrastructure investment, heavy automobile traffic will be unavoidable.

Commenting Issues, solved(?)

A few people mentioned that they have had problems commenting on the EEB & Flow for a while. I think the problem a blogger issue with the embedded comment format (if your computer doesn't accept 3rd party cookies, it looks like your comments may not post). I've changed the comment format to hopefully fix this issue.

My apologies, and if you still run into problems, please let me know!

Things to keep in mind when finding a PhD

A wonderful student who worked with me when I was a graduate student is in the midst of applying for graduate school, and has been going through the process of finding a suitable program and advisor. It's been nearly 7 years (!?) since I was first in graduate school and, in my case, I mostly lucked my way from undergraduate to a great lab without nearly enough due diligence (and no one I knew or in my family had been to grad school to provide advice).

If asked during grad school, I had a list of advice I would have liked to have received (admin questions, funding issues, how to get to campus on public transport). But the advice I think is important has actually changed a lot, from just “make sure you love research” (although you should, at least most of the time), to more strategic and practical considerations.

I now think the most important thing is to ask yourself while you consider graduate school is, "Why do I want to get a PhD?" Note that there is absolutely no right answer to this question, but there are some wrongs ones, e.g. "I don’t know what else to do next" or "I have good grades". The problem is that these answers aren’t enough to motivate you through a PhD program. And some people find themselves 5 years later, still not knowing what they’re going to do next or why they got a PhD. It’s okay to answer "I like the research I did as an undergrad" or "I want to develop strong quantitative skills", or "I love working with ideas", because these kind of answers mean you want something from your experience and you've thought about what that is.

Educate yourself about the opportunities that a PhD will bring, both academic and non-academic. Continue this education while you are in graduate school. [Departments, offer more opportunities for students to learn about non-academic jobs.] The reality is that getting the oft-desired research professorship is very difficult (e.g. 200+ applicants for a general ecology position is not unusual). But PhDs produce desirable skill sets and there are other opportunities, so long as you are aware of them. There are many LACs (liberal arts schools) in the US, and thus more teaching oriented professorships advertised every year than there are R1 professorships. There are NGO and government research jobs. And as many of my grad school friends leave academia, it’s a relief to see that their skills – strong quantitative abilities, good data management, a clarity of vision on how to ask questions and answer them with appropriate data – make them employable across a range of professions.

Ask questions ask questions ask questions. Don’t go into a program without knowing what it will entail. Ask the same questions of both faculty and students and see how their answers compare. 

To understand a department, you want to know what the teaching load is on average, how funding works (and for how long!). You should find out the average time to completion of a PhD program, what classwork looks like, whether there are student-lead reading or discussion groups? Is there funding for student travel to conferences or meetings?

If you have a lab in mind, you need to similarly learn about that lab. Find out, from both the PI and their students, how the lab works. What is the supervisory style? Does the PI tend to be hands on, or expect more independent research? How does your personal approach to working mesh with their style? Don't assume that if you like to have structure and feedback and the PI only is around once a month, it will just work out. How often are they physically on campus? How often would you meet? What are other students in the lab working on? Is the lab collaborative? Do students publish together? What skills are emphasized in the group? Has the PI published recently (last 2-3 years, depending on context) and, perhaps most importantly, have they graduated any students? If not, try to figure out why.

Once you’ve found a place, remember that how you feel about your PhD will rise and fall all the time. That’s normal. Avoid the worst of these dips by taking care of your mental health. The sort of unstructured, isolating, often un-rewarded work that goes into a PhD can be draining. But it is also 100% okay to change your mind, to decide a Master’s is sufficient, to hate everything you are doing and quit. Seriously. The sunk-cost fallacy will make you (and people around you) miserable.

Of course, grad school—like life—is stochastic and full of uncertainty. But its possible, with care to increase the probability that you find a supportive, nurturing lab and have a wonderful time as a graduate student. 

Have humans altered community interactions?

A recent Nature paper argues that there is evidence for human impacts on communities starting at least six thousand years ago, which altered the interactions that structure communities. “Holocene shifts in the assembly of plant and animal communities implicate human impacts” from Lyons et al. (2016, Nature) analyses data spanning modern communities through to 300 million year old fossils, to measure how the co-occurrence structure of communities has changed. The analyses look at the co-occurrence of pairs of species, and identifies those that are are significantly more likely ('aggregation') or less likely ('segregation') than a null expectation. Once the authors identified the species pairs with non-random co-occurrences, they calculated the proportion of these that were aggregated (i.e. y-axis on Figure 1). Compared to the ancient past, the authors suggest that modern species had fewer aggregated species pairs than in the past, perhaps reflecting an increase in negative interactions or distinct habitat preferences. 

Main figure from Lyons et al. 2016.

The interpretation offered by the paper is “[o]ur results suggest that assemblage co-occurrence patterns remained relatively consistent for 300 Myr but have changed over the Holocene as the impact of humans has dramatically increased.” and "...that the rules governing the assembly of communities have recently been changed by human activity". 

There are many important and timely issues related to this – changing processes in natural systems, lasting human effects, the need to use all available data from across scales, the value of cross-disciplinary collaboration. But, in my view, the paper ignores a number of the assumptions and considerations that are essential to community ecology. There are a number of statistical issues that others have pointed out (e.g. temporal autocorrelation, use of loess regression, null model questions), but a few in particular are things I was warned about in graduate courses. Such as the peril of proportions as response data (Jackson 1997), and the collapsing of huge amounts of data into an analysis of a summary of the data ("the proportion of significant pairwise associations that are aggregated"). Beyond the potential issues with calculating correct error terms, interpretation is made much more difficult for the reader. 

Most importantly, in my view, the Nature paper commits the sin of ignoring the essential role of scale in community ecology. A good amount of time and writing has been spent reconciling issues of spatial and temporal scale in ecology. These concepts are essential even to the definition of a 'community'. And yet, scale is barely an afterthought for these analyses.  (Sorry, perhaps that's a bit over-dramatic....) Fossils—undeniably an incomplete and biased sample of the an assemblage—can't be described to more than a very broad spatial and temporal scale. E.g. a 2 million year old fossil and a 2.1 million year old fossil may or may not have interacted, habitats may have varied between those times, and populations of S1 and S2 may well have differed greatly over a few thousand years. Compare this to modern data, which represents species occurring at the exact same time and in relatively small areas. The differences in scale is huge, and so these data are not directly comparable.

Furthermore, because we know that scale matters, we might predict that co-occurrences should increase at larger spatial grains (you include more habitat, so more species with the same broad requirements will be routinely found in a large area). But the authors reported that they found no significant relationship between dataset scale and the degree of aggregation observed (their Figure 2, not replicated here): this might suggest the methodology or analyses needs further consideration. Co-occurrence data is also, unfortunately, a fairly weak source of inference for questions about community assembly, without other data. So while the questions remain fascinating to me - is community assembly changing fundamentally over time? is that a frequent occurrence or driven by humans? what did paleo-communities look like? - I think that the appropriate data and analyses to answer these questions are not so easy to find and apply.


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Response from Brian McGill:

My comment I was trying to post was:

Interesting perspective Caroline! As a coauthor, I of course am bound to disagree. I'll keep it short, but 3 thoughts:

1) The authors definitely agonized over potential confounding effects. Indeed spent over a year on it. In my experience paleoecologists default to assuming everything is an artefact in their data until they can convince themselves otherwise, much more than neo-ecologists do.

2) They did analyze the effects of scale (both space and time) and found it didn't seem to have much effect at all on the variable of interest (% aggregations). You interpret this as "this might suggest the methodology or analyses needs further consideration". But to me, I hardly think we know enough about scaling of species interactions to reject empirical data when it contradicts our very limited theoretical knowledge (speculation might be a better word) of how species interactions scale.

3) To me (and I think most of the coauthors) by far the most convincing point is that the pattern (a transition around 8000 years ago plus or minus after 300,000,000 years of constancy) occurs WITHIN the two datasets that span it (pollen of North America and mammal bones of North America both span about 20,000 years ago to modern times) and they have consistent taphonomies, sampling methods, etc and yet both show the transition.

I agree that better data without these issues is difficult (impossible?) to find. The question is what you do with that. Do you not anwwer certain questions. Or do you do the best you can and put it it out for public assessment. Obviously I side with the latter.

Thanks for the provoking commentary.

Cheers

Brian

Resolutions for 2016

Having now been a postdoc for a couple of years, I think I’ve slowly developed more perspective about the day-to-day aspects of working as a researcher and the costs and benefits of various approaches. So this year, I am resolving to be proactive about the various challenges of academic life, and try some things meant to make my work life more productive and better: 

1) Carve out more time to read the literature. The busier I get, the more difficult it is to keep up with new papers that aren’t directly connected to my current projects. One of the best parts of being a grad student (without a heavy teaching load) was how much time I had to keep up with the literature. As my time is more scheduled and there are more concrete deadlines, it is harder to make time for activities like reading that don’t have an immediate pay off. I have a feed reader, but I find that I only check it monthly; I also come across interesting papers while doing lit reviews/etc and leave those open in my browser, planning to get to them eventually...

I know that braver souls than I are tackling this problem #365papers style, but I don’t think that’s what I want. Instead, I am scheduling three 1-hour slots per week, and I think that’s a manageable goal.

2) Continue to work on good project management practices (such as those described here). I use the suggestions for predictable directory structures, separation of code into different types of scripts and of course, version control, and find them very helpful. I wish that I had learnt best practices for coding and project management as a grad student, but it’s never too late.

3) Take vacations (and mean it!). Every academic I know who has good work-life balance takes vacations. That means not working—at all, including no responding to emails. This is one of the things I admire most about my European colleagues, and I look forward to enjoying the French holidays when I start a fellowship in Montpellier this spring :-)

4) Maintain relationships across distances. It can be difficult to connect with people during short postings here and there, and even harder to maintain those relationships after you move on to the next place. The tools are there (Skype, Facebook, Twitter, email, etc), so I shouldn’t forget to take advantage of them.

5) Learn a new skill. Still deciding what, given the many things I want to learn!

6) Emphasize the positive more often. In general, I think people (or at least me) can be overwhelmed by the negatives in academia – e.g. the rejections of manuscripts and applications, the difficulties in securing the next job, etc. Unlike in undergrad, we don’t get grades or quantitative measures of our success too often (and I haven’t gotten a sticker on my work in years). And when we do get praise, it is often informal (e.g. “good talk”, “I liked your paper”), or balanced with criticism (e.g. “accept but with major revisions”). This is all in pursuit of improvement, but it can be difficult to keep even constructive criticism in perspective because the brain is biased towards remembering the negative. So I’m considering keeping an explicit list of successes to help highlight the positive.