This week the University of Connecticut expressed its appreciation for employees. I am nearing the end of my 31st year with the University, and I’ve heard through the grapevine that I’ll be receiving a “surprise” gift recognizing 30 years of service at a meeting I’m attending next week. On Tuesday, I presented a gift to an employee of The Graduate School recognizing 35 years of service as a state employee. I was surprised and gratified to receive the unofficial “Certificate of Awesomeness” pictured above from members of The Graduate School staff. I feel very appreciated – and fortunate to have been a part of UConn for more than 30 years.
I recently discovered the Future of Conservation Project. It’s a project designed “to explore the views of conservationists on a range of issues, as a way of informing debates on the future of conservation.” As the About page says,
Recent debates about the future of conservation have been dominated by a few high-profile individuals, whose views seem to fit fairly neatly into polarised positions. In this survey, we are exploring the range of views that exist within the conservation movement globally, and how this varies by key demographic characteristics such as age, gender, geography and educational background.
The blue dots in the figure above are results from the 99 people who responded to the survey before me. Here’s how to interpret my results:
How to interpret your results
Your position is weakly negative along the people & nature axis and weakly positive along the conservation & capitalism axis.
Your position on the two axes above reflects your survey answers. A move from left to right along the horizontal axis (people/nature) implies a shift from seeing conservation as a means of improving human welfare to conservation for nature’s own sake.
The vertical axis (conservation & capitalism) indicates a spectrum of willingness to embrace markets and capitalism as conservation tools: the higher up the graph your score is, the more pro-markets it is. This places you in the top left quadrant of the graph – a position suggesting your views on these particular dimensions of the debate are most closely related to those of ‘new conservationists’ as set out in the literature.
Your thinking most closely aligns with: New Conservation
Central to the ‘new conservation’ position is a shift towards framing conservation as being about protecting nature in order to improve human wellbeing (especially that of the poor), rather than for biodiversity’s own sake. ‘New conservationists’ believe that win-win situations in which people benefit from conservation can often be achieved by promoting economic growth and partnering with corporations.
Although new conservation advocates have been criticised for doing away with nature’s intrinsic value, key authors within the movement have responded by clarifying that their motive is not so much an ethical as a strategic or pragmatic one. In other words, they claim that conservation needs to emphasise nature’s instrumental value to people because this better promotes support for conservation compared to arguments based solely on species’ rights to exist.
If you’re interested in taking the survey, here’s the link: http://www.futureconservation.org/.
I visited Dublin a couple of weeks ago for meetings of the Deans and Directors of Graduate Studies (DDoGS) from Universitas 21 (http://www.universitas21.com/article/research/details/55/deans-and-directors-of-graduate-studies-ddogs). The meeting began on 20 March with a workshop on “The Future of the Doctorate.” It continued on 21 and 22 March with discussions of graduate research project grants, the possibility of a 3-MT competition for master’s students, plans for a supervisor development project,1, and a discussion of wellness and mental health. This was the fifth DDoGS meeting I’ve attended, and I’ve always found them useful.
There is a direct flight from Hartford to Dublin. I left in the evening on 18 March and arrived in Dublin a little after 5:00am on 19 March. Since there weren’t any activities until 6:00pm that night, I spent most of the day on the 19th wandering around Dublin taking photographs. I also spent the day on 23 March taking photographs, since I didn’t return home until the 24th. The photograph above is of Temple Bar, one of the most famous pubs in Dublin. If you’d like to see more of the photographs I took while I was there, here’s a link: https://www.flickr.com/photos/billandkent/albums/72157679862838432.
In case you’ve ever wondered why I have spent so much time working in, thinking about, and writing about Protea this video from CapeNature will give you a bit of a clue. The fynbos is a very interesting place. It has an enormous diversity of plants, many of which are found nowhere else in the world, and much of that diversity is concentrated in a relatively small number of big evolutionary radiations, one of which is Protea.1 One of my students,
Kristen Nolting (@KristenNolting on Twitter) pointed me to this video. Thanks, Kristen.
The genus Protea is one of the iconic evolutionary radiations in the Greater Cape Floristic Region of southwestern South Africa. Its range extends north through Mozambique into parts of central Africa, but the vast majority of species are found in South Africa. From 2011-2014 we collected samples from most of the South African species (59 in total), and for most of the species we collected samples from several individuals from different populations. Over the last couple of years, we extracted DNA, built libraries for next generation sequencing using targeted phylogenomics, and constructed a highly-resolved estimate of phylogenetic relationships in the genus. The paper describing our results is now out in “early view” in American Journal of Botany. Most species from which we have multiple samples are supported as monophyletic units, and most relationships we identify are strongly supported (> 90% support in ASTRAL-II and SVDquartets analyses). We use the species tree from our data as a backbone to provide reliable estimates of relationship for additional species included in a paper by Schnitzler and colleagues for which we did not have samples.
Mitchell, N., P.O. Lewis, E.M. Lemmon, A.R. Lemmon, and K.E. Holsinger. 2017. Anchored phylogenomics improves the resolution of evolutionary relationships in the rapid radiation of Protea L. American Journal of Botany doi: 10.3732/ajb.1600227
Increased equity and pro-poor actions are not only moral issues to be kept in mind by conservationists. They are, rather, central to the larger goal of protecting the planet. – Bill Murdoch
In the past 15-20 years, conservation biologists have become increasingly aware that successful conservation efforts require the support and involvement of local communities, but only more recently have we become fully aware that getting that support and involvement requires that we pay attention to what communities need, not only to what we want. Reducing economic inequality, and in particular improving the lives of those in poverty, is not only the right thing to do on its own terms. It’s the only way we can protect the natural systems we can care about in the long term.
In Fall 2015, I discussed some of these issues in my graduate course in conservation biology. The problem is that it’s easy to say the “right” words and to congratulate ourselves for our wisdom and generosity. It’s harder to see how the attitudes those of us who live in relatively prosperous communities are influenced by the economic privileges we have. Those privileges are part of the reason it’s hard for us to understand farmers, ranchers, and oilmen who seem to have little regard for the land. I grew up among farmers and ranchers in southern Idaho, and the people I knew care as deeply about the land as I do. The difference? They draw their livelihood directly from the land, and their livelihood is less secure. Not unreasonably, they focus on immediate needs,1 not far-off benefits.
Fortunately, I had a very talented teaching assistant for the course, Holly Brown. She had the idea of using a “privilege walk” to illustrate the ways in which we – graduate students and faculty at UConn – are privileged when compared to many of those living in areas where conservation action is needed. Holly, Ambika Kamath, and Margaret Rubega describe the exercise in a recent article in Conservation Biology. This anonymous comment from one of our students was particularly striking:
The main thing I took away was that, when it comes to issues that are controversial (including climate change or biodiversity preservation), approaching those who might oppose ecologists with an understanding of my own privilege and how it differs from the background of others can help me to open myself up to innovative solutions, instead of imposing my beliefs on others.
If you teach a course in conservation biology, I encourage you to read Holly’s article and use some of the ideas in it the next time you teach your course.
Last week I pointed out a new paper by Denes Szucs and John Ioannidis, When null hypothesis significance testing is unsuitable for research: a reassessment.1 I mentioned that P-values from small, noisy studies are likely to be misleading. Last April, Raghu Parthasarathy at The Eighteenth Elephant had a long post on a more fundamental problem with P-values: they encourage binary thinking. Why is this a problem?
- “Binary statements can’t be sensibly combined” when measurements have noise.
- “It is almost never necessary to combine boolean statements.”
- “Everything always has an effect.”
Those brief statements probably won’t make any sense,2 so head over to The Eighteenth Elephant to get the full explanation. The post is a bit long, but it’s easy to read, and well worth your time.
Andrew Gelman recently linked to Parthasarathy’s post and adds one more observation on how P-values are problematic: they are “interpretable only under the null hypothesis, yet the usual purpose of the p-value in practice is to reject the null.” In other words, P-values are derived assuming the null hypothesis is true. They tell us what the chances of getting the data we got are if the null hypothesis were true. Since we typically don’t believe the null hypothesis is true, the P-value doesn’t correspond to anything meaningful.
To take Gelman’s example, suppose we had an experiment with a control, treatment A, and treatment B. Our data suggest that treatment A is not different from control (P=0.13) but that treatment B is different from the control (P=0.003). That’s pretty clear evidence that treatment A and treatment B are different, right? Wrong.
P=0.13 corresponds to a treatment-control difference of 1.5 standard deviations; P=0.003, to a treatment-control difference of 3.0 standard deviations, a difference of 1.5 standard deviations, which corresponds to a P-value of 0.13. Why the apparent contradiction? Because if we want to say that treatment A and treatment B, we need to compare them directly to each other. When we do so, we realize that we don’t have any evidence that the treatments are different from one another.
As Parthasarthy points out in a similar example, a better interpretation is that we have evidence for the ordering (control < treatment A < treatment B). Null hypothesis significance testing could easily mislead us into thinking that what we have instead is (control = treatment A < treatment B). The problem arises, at least in part, because no matter how often we remind ourselves that it’s wrong to do so, we act as if a failure to reject the null hypothesis is evidence for the null hypothesis. Parthasarthy describes nicely how we should be approaching these problems:
It’s absurd to think that anything exists in isolation, or that any treatment really has “zero” effect, certainly not in the messy world of living things. Our task, always, is to quantify the size of an effect, or the value of a parameter, whether this is the resistivity of a metal or the toxicity of a drug.
We should be focusing on estimating the magnitude of effects and the uncertainty associated with those estimates, not testing null hypotheses.
Ecologists and paleoecologists have used the width of tree rings for years as a way of inferring past climates. In fact, tree ring data were an important component of the proxy data Mann et al. (1998) used when they constructed their famous1 hockey stick representing global surface temperatures over the last millennium. I don’t have anything as earth shattering as a hockey stick to share with you, but I am pleased to report that a paper on which I am a co-author demonstrates how to combine tree ring and growth increment data (with other data) to predict growth of forest trees. Here’s tha abstract and a link to the paper on bioRxiv.
Fusing tree-ring and forest inventory data to infer influences on tree growth
Better understanding and prediction of tree growth is important because of the many ecosystem services provided by forests and the uncertainty surrounding how forests will respond to anthropogenic climate change. With the ultimate goal of improving models of forest dynamics, here we construct a statistical model that combines complementary data sources: tree-ring and forest inventory data. A Bayesian hierarchical model is used to gain inference on the effects of many factors on tree growth (individual tree size, climate, biophysical conditions, stand-level competitive environment, tree-level canopy status, and forest management treatments) using both diameter at breast height (DBH) and tree-ring data. The model consists of two multiple regression models, one each for the two data sources, linked via a constant of proportionality between coefficients that are found in parallel in the two regressions. The model was applied to a dataset developed at a single, well-studied site in the Jemez Mountains of north-central New Mexico, U. S. A. Inferences from the model included positive effects of seasonal precipitation, wetness index, and height ratio, and negative effects of seasonal temperature, southerly aspect and radiation, and plot basal area. Climatic effects inferred by the model compared well to results from a dendroclimatic analysis. Combining the two data sources did not lead to higher predictive accuracy (using the leave-one-out information criterion, LOOIC), either when there was a large number of increment cores (129) or under a reduced data scenario of 15 increment cores. However, there was a clear advantage, in terms of parameter estimates, to the use of both data sources under the reduced data scenario: DBH remeasurement data for ~500 trees substantially reduced uncertainty about non-climate fixed effects on radial increments. We discuss the kinds of research questions that might be addressed when the high-resolution information on climate effects contained in tree rings are combined with the rich metadata on tree- and stand-level conditions found in forest inventories, including carbon accounting and projection of tree growth and forest dynamics under future climate scenarios.
Several months ago I pointed out that P-values from small, noisy experiments are likely to be misleading. Given our training, we think that if a result is significant with a small sample, it must be a really big effect. But unless we have good reason to believe that there is very little noise in the results (a reason other than the small amount of variation observed in our sample), we could easily be misled. Not only will we overestimate how big the effect is, but we are almost as likely to say that the effect is positive when it’s really negative as we are to get the sign right. Look back at this post from August to see for yourself (and download the R code if you want to explore further). As Gelman and Carlin point out,
There is a common misconception that if you happen to obtain statistical significance with low power, then you have achieved a particularly impressive feat, obtaining scientific success under difficult conditions.
I bring this all up again because I recently learned of a new paper by Denes Szucs and John Ioannidis, When null hypothesis significance testing is unsuitable for research: a reassessment. They summarize their advice on null hypothesis significance testing (NHST) in the abstract:
Whenever researchers use NHST they should justify its use, and publish pre-study power calculations and effect sizes, including negative findings. Studies should optimally be pre-registered and raw data published.
They go on to point out that part of the problem is the way that scientists are trained:
[M]ost scientists…are still near exclusively educated in NHST, they tend to misunderstand and abuse NHST and the method is near fully dominant in scientific papers.
The whole paper is worth reading, and reading carefully. If you use statistics in your research, please read it and remember its lessons the next time you’re analyzing your data.
Last July, the United States banned nearly all commercial trade in ivory. Last Friday, China announced that it will “end the processing and selling of ivory and ivory products by the end of March as it phases out the legal trade” (The New York Times).
There are some professionals who believe that legal trade in ivory promotes conservation. (See this article from The Guardian for some of the give and take.) The arguments are two-fold (from The Guardian):
- The ivory ban has made prices high and poaching lucrative. Enrico Di Minin and Douglas MacMillan
- Lifting Africans from poverty is the only way to save elephants. Rowan Martin
I haven’t studied the issue carefully, but I am not persuaded by their arguments. For one thing, Nitin Sekar and Solomon Hsiang point out in The Guardian that the limited legal trade in ivory established in 2008 seems to have increased the amount of poaching.
To be fair, with only 5 points from before the 2008 announcement of legal ivory sales and 6 points after, you’d be hard-pressed to demonstrate that a statistical model favoring a switch in poaching rates in 2008 is better than one where rates are simply increasing over time, but either way, the limited trade in ivory introduced in 2008 did not decrease the rate of poaching.
Point 2 is undeniably true. Lifting Africans from poverty is the only way to make lasting progress on any conservation problem in Africa. But that observation argues for promoting policies that directly reduce poverty, like increasing sanitation, enhancing access to health care, and strengthening education. Elephant poaching has increased since 2008, and prices of ivory are high. Is there any evidence that incomes of Africans have improved as a result? If there is, Martin Rowan doesn’t provide it.
That’s why I regard it as good news that China is shutting down its domestic ivory trade. A ban on the legal trade of ivory won’t shut down the black market, any more than a ban on cocaine in the US shut down the cocaine market here. But a ban on the legal trade of ivory will make it more difficult for black marketeers to hide. With strong enforcement, a ban will reduce the incentives to trade in ivory and the incentives for poachers.