Why pattern-based hypotheses fail ecology: the rise and fall of ecological character displacement

Yoel E. Stuart, Jonathan B. Losos, Ecological character displacement: glass half full or half empty?, Trends in Ecology & Evolution, Available online 26 March 2013

Just as ecology is beginning to refocus on integrating evolutionary dynamics and community ecology, a paper from Yoel Stuart and Jonathan Losos (2013) suggests that perhaps the best-known eco-evolutionary hypothesis - Ecological Character Displacement (ECD) – needs to be demoted in popularity. They review the existing evidence for ECD and in the process illustrate the rather typical path that research into pattern-based hypotheses seems to be taking.

ECD developed during that period of ecology when competition was at the forefront of ecological thought. During the 1950s-1960s, Connell, Hutchinson and McArthur produced their influential ideas about competitive coexistence. At the same time, Brown and Wilson (1956) first described ecological character displacement. ECD is defined as involving first, competition for limited resources; second, in response, selection for resource partitioning which drives populations to diverge in resource use. Ecological competition drives adaptive evolution in resource usage – either resulting in exaggerated divergence in sympatry or trait overdispersion. ECD fell in line with a competition-biased worldview, integrated ecology and evolution, and so quickly became entrenched: the ubiquity of trait differences between sympatric species seemed to support its predictions. Pfennig and Pfennig (2012) go so far as to say ‘Character displacement...plays a key, and often decisive, role in generating and maintaining biodiversity.’

One problem was that tests of ECD tended to make it a self-fulfilling prophecy. Differences in resource usage are expected when coexisting species compete; therefore if differences in resource usage are observed, competition is assumed to be the cause. In the ideal test, divergent sympatric species would be found experimentally to compete, and ECD could be used to explain the proximal cause of divergence. But the argument was also made that when divergent sympatric species were not found to compete, this was also evidence of ECD, since “ghosts of competition past” could have lead to complete divergence such that competition no longer occurred. This made it rather difficult to disprove ECD.

There was pushback in the 1970s against these problems, but interestingly, ECD didn’t fall out of favour. A familiar pattern took form: initial ecstatic support, followed by critical papers, which were in turn rebutted by new experimental studies. Theoretical models both supported or rebutted the hypothesis depending on the assumptions involved. In response the large literature, several influential reviews were written (Schluter (2000), Dayan and Simberloff (2005)) that appeared to suggest at least partial support for the ECD from existing data. Rather than dimming interest in ECD, debate kept it relevant for 40+ years. And continued relevance translated to the image of ECD as a longstanding (hence important) idea. Stuart and Losos carry out a new evaluation of the existing evidence for ECD using Schluter and McPhail’s (1992) ‘6 criteria’, using both the papers from the two previous reviews and more recent studies. Their results suggest that strong evidence for ECD is nearly non-existent, with only 5% of all 144 studies meeting all 6 criteria. (Note: this isn't equivalent to suggesting that ECD is nearly non-existent, just that currently support is limited. There's a good discussion as to some of the possible reasons that ECD has been rarely observed, in the paper).

From Stuart and Losos (2013). Fraction of cases from Schluter 2000, Dayan and Simberloff 2005, and this study that meet either 4 or all 6 of the criteria for ECD.

The authors note that there are many explanations for this finding of weak support: the study of evolution in nature is difficult, particularly given the dearth of long term studies. The 6 criteria are very difficult to fulfill. But they also make an important, much more general point: character displacement patterns can result from multiple processes that are not competition, so patterns on their own are not indicative. Patterns that result from legitimate ecological character displacement may not show the predicted trait overdispersion. The story of the rise and fall of ECD is a story with applications to many pattern-driven ecological hypotheses. There are many axiomatic relationships you learn about in introductory courses: productivity-diversity hump shaped relationships, the intermediate disturbance hypothesis, ECD, etc, etc. These have guided hypothesis formation and testing for 40 years and have become entrenched in the literature despite criticism. And similarly, there are recent papers suggesting that long-standing pattern-based hypotheses are actually wrong or at least misguided (e.g. 1, 2, 3, etc). Why? Because pattern-driven hypotheses lack mechanism, usually relying on some sort of common-sense description of a relationship. The truth is that the same pattern may result from multiple processes. Further, a single process can produce multiple patterns. So a pattern means very little without the appropriate context.

So have we wasted 40 years of time, energy and resources jousting at windmills? Probably not, data and knowledge are arrived at in many ways. And observing patterns is important - it is the source of information from natural systems we use to develop hypotheses. But it is hopeful that this is a period where ecology is recognizing that pattern-based hypotheses (and particularly the focus on patterns as proof for these hypotheses) ask the right questions but focus on the wrong answers.

Long-term studies of Darwin's finches have provided strong evidence for ECD.

Wine-ing about climate change

Lee Hannah, Patrick R. Roehrdanz, Makihiko Ikegami, Anderson V. Shepard, M. Rebecca Shaw,Gary Tabor, Lu Zhi, Pablo A. Marquet, and Robert J. Hijmans. 2013. Climate change, wine, and conservation. PNAS. 110 (17) 6907-6912.

If you like wine, particularly Old World wines, a recent paper by Lee Hannah et al (PNAS 2013), suggests that climate change is going to put a dent in your drinking habits. One way of communicating the ecosystem and economic effects of global warming has been to relate them to products or factors that affect the general population directly (an approach which has had mixed success). Wine (from Vitis vinifera grapes) is a great focal product - the success and quality of winemaking depends on terroir, which results from local temperatures and soil moisture. Changes in climate suitability for grapes reflects changes in suitability for many other agricultural and native species. Also, the motivations behind examining the effects of climate change on vineyards is more than economic – viticulture particularly thrives in Mediterranean-type ecosystems (France, Spain, Italy, California, Chile, South Africa, and Australia), which are areas with particularly high biodiversity and endemism. Vineyards use large amounts of fresh water and house low numbers of native species – so changes in their location and size may have contrasting effects on native biodiversity, local economies, and water supplies.

Given these relationships, the authors suggest that modeling regional changes in viticulture suitability provides insight into changes in ecosystem services and diversity. They examined 17 possible climate  models (GCMs) to look at how appropriate conditions for viticulture might shift by 2050. More than 50% of the models predicted that traditional wine producing regions (Bordeaux and Rhône valley regions in France and Tuscany in Italy) will decline greatly. However, regions farther north in Europe may become increasingly suitable. 

From Hannah et al. 2013. PNAS. The percentage of GCMs supporting a prediction reflects the degree of certainty behind it. Click for larger image.

New World vineyards receive a less dire forecast – some areas in Australia, Chile, California, and South Africa will remain suitable for viticulture in the future and new areas to the north are likely to become available. According to model predictions, New Zealand may one day produce many times more wine than it does currently. Such predicted increases in wine production in novel regions may be accompanied by viticulture’s increased ecological footprint. Some shifts take advantage of high elevations with cooler temperatures, leading to the development of areas that are currently relatively preserved. Water usage demands are likely to be problematic in the future: for example, vineyards in Chile’s Maipo Valley rely on runoff mountain basins that are vulnerable to warming conditions.

From Hannah et al. 2013. PNAS. (CA, California floristic province; CFR, Cape floristic region (South Africa); CHL, Chile; MedAus, Mediterranean-climate Australia; MedEur, Mediterranean-climate Europe; NEur, Northern Europe; NMAus, non–Mediterranean-climate Australia; NZL, New Zealand; WNAm, western North America).

Wine is a useful focal point for another reason - it exemplifies the complicated nature of most predictions related to climate change: positive outcomes (increased wine production in NZ) may be linked to negative changes (threatened water supply and native diversity in these new areas). Wine producers in a number of regions have recognized the possible impacts of vineyards, and groups such as the Biodiversity and Wine Initiative in the Cape Floristic Region of South Africa, and the Wine, Climate Change and Biodiversity Program in Chile exist to reconcile conflicting interests. There may be ways to mediate the effects of changing climate on viticulture, including developing tolerant varieties, changing methodologies, or the separation of varieties from their traditional regions. 

Making predictions about how ecosystems will change in the future is still difficult. However, the climate envelope model approach is actually well suited for situations like human agriculture, where dispersal limitation, competition, and non-equilibrium conditions are unlikely to be an issue. Cultivated crops are limited mostly by human/economic motivation. The results across most models strongly support the idea that Mediterranean climate growing regions will experience decreased viticultural suitability. It is likely more difficult on a fine scale to determine which regions will become more suitable in the future (i.e. probably don’t invest in land in New Zealand, assuming you can start a vineyard there in 50 years) but the strong agreement between models suggests that you should enjoy some French or Italian wine sooner rather than later.

Be vigilant against predatory journals

I'm sure most of the academic readers of this blog are frequently inundated by numerous requests to serve on the editorial boards of journals you've never heard of. Many of these claim to be 'open access' even though they do not adhere to the open access code of conduct. Rather, they are following a business model where the researcher pays to publish, while the predatory journal fails to provide even base services or indexing for your paper. The problem is that we often receive e-mails from legitimate start-up open access journals, and people need to separate the two. Jeffrey Beall has developed a set of guidelines to help you determine the legitimacy of the journal, as well as providing a list of known predatory publishers. These are great resources to ensure that you do not get duped.

Progress on the problem of pattern, process and scale

Jérôme Chave. 2013. The problem of pattern and scale in ecology: what have we learned in 20 years? Ecology Letters. DOI: 10.1111/ele.12048.

Why do patterns get so much attention from ecologists? MacArthur (1972) suggested it was because patterns imply repetition, and repetition implies predictability. And prediction is the Holy Grail of ecology. Of course, patterns are meaningless without consideration of spatial or temporal scale. As Levin put it in his MacArthur lecture (1992) "the description of pattern is the description of variation, and the quantification of variation requires the determination of scales". Observing, modelling, and predicting ecological patterns at differing spatial scales has dominated much of ecological thought since Levin’s paper – today, entire subfields heavily focus on patterns through space or time (species-area relationships, macroecology, biogeography, etc).

When ecological research focuses on pattern, but lacks attention to process and scale, it has received much (deserved) criticism. Even when patterns are considered at the appropriate scale and with regard to process, the ability to understand how these processes and patterns translate from one scale to the next (i.e. how do we explain the differing relationship between invasion success and community diversity at local compared to regional scales?) is still limited. And yet clearly connecting processes across scales is a central goal. In the upcoming issue of Ecology Letters, a review article by Jérôme Chave looks at how ecology has progressed in dealing with patterns and scale in the last 20 years.

Chave does a great job of placing current ecological thought into historical context. Sometimes we forget that one of the benefits of ecology’s youth is that ecology has developed concurrently with necessary technological advancements and demand for ecological knowledge. As a result, the need for ecological knowledge and the ability to provide it are tightly linked in time. As a result, Chave suggests that ecology is making noticeable progress, particularly in four focal areas: 1) coupling ecology and evolution, 2) global change, 3) modularity in interaction networks, and 4) spatial patterns of diversity.

The first two topics reflect ongoing issues in ecology. The incorporation of evolutionary dynamics into ecology is an increasingly popular topic (for example), and it is not uncommon for ecological and evolutionary dynamics to have similar temporal scales. Explaining temporal patterns then may require coupling models of ecology and evolution: for example a study of Darwin’s finches found that for one period evolutionary dynamics were occurring on a more rapid temporal scales than ecological dynamics. Global change has dominated ecological research and the problem of scaling processes up from local to global or from global to local effects (of temperature on productivity, etc) is another clear area of growth. This may be the most successful attempts to scale, since models of global carbon cycles have progressed from empirical data and models to predictive models. An apparent example of what can be achieved when demand and appropriate technology are both present.

The remaining two foci relate to networks, and spatial patterns of diversity. The first, modularity in interaction networks, allows groups of interactions to be incorporated into larger scale networks; for individual variation could be incorporated into interactions between species. More generally, Chave suggests that the “abstracted multidimensional space of an interaction network” might be one way to simplify temporal and spatial scales. He suggests that this is where ecology could learn from other studies of complex biological systems such as cellular networks and networks of human governance and management. Finally, spatial patterns of diversity – a striking and oft-considered issue in ecology – are suggested as an area in ecology that has seen advances. Biological diversity is patchy through space, and the amount of patchiness is dependent on the scale of observation. Planktonic blooms might be patchy on a global scale while tropical trees might be patchy over meters. Scaling from local patterns to global has been difficult – for example, models of local dispersal don’t necessarily predict regional dispersal patterns. Chave suggests that one problem in the past was the ignorance of processes at larger scales (i.e. systematics, biogeography) and a predominant focus is on local processes. He provides a few examples that have bridged this issue, for example neutral theory includes both regional and local processes, while ecophylogenetics incorporates evolutionary history.

The review focuses attention on several relevant or insightful approaches to the problem of pattern and scale, and suggests possible connections between ecology and other areas of work (for example, interaction networks and metabolic networks). Although it provides interesting examples, it offers little synthesis or ideas for reconciling issues of pattern and scale, and while the four foci are valid and appropriate, they feel like a rather patchy way of covering a larger and more general issue. This may simply be too complicated and large a topic to cover in a single short review. Chave seems a little generous is giving props to approaches which at their best do incorporate multiple scales (e.g. neutral theory and ecophylogenetics), but which arguably have relied heavily on pattern analyses without a strong focus on process, something that seems to go against the spirit of the review. In addition, some of the explicitly general attempts to reconcile scale and pattern in community ecology are missing. For example, a series of papers from Brett Melbourne and Peter Chesson used 'scale transition theory' to model dynamics across multiple scales. This framework has been applied at least to a few fisheries-related papers. In addition, research on predator-prey dynamics has long considered the question of how functional responses scale up (one review). That said, it's clear that ecology has made progress in some areas and that there are options for moving forward.

Ultimately, Chave seems to suggest that the question of how well ecology can deal with patterns and scale depends on whether complexity is reducible or intrinsic to understanding natural systems. He goes so far as to state “This suggests that in approaching novel frontiers of the study of complex ecological systems we need to pause about the challenge ahead of us...Once we enter the realm of complex systems, neither physics nor biology are well equipped to progress.” This is obviously a pessimistic take on the future for ecology. Is it true?

Ecology goes east: research in China

with Shaopeng Li

It is increasingly common to see papers from Chinese institutes in top ecological journals, and Chinese ecological research is growing exponentially. I've been chatting informally about the topic of Chinese ecology with Shaopeng Li, who is a graduate student visiting the Cadotte lab from Sun Yat-sen University in China. His thoughts about where Chinese ecology is going and about being a graduate student in ecology there were so interesting that I talked him into letting me post some of his answers. As you might expect, some things are the common everywhere - grad students have low wage and work long hours, supervisors can be intimidating - and some things are distinctly different - for example, hiring armies of farmers to help with fieldwork. Of course this reflects Shaopeng's experience and thoughts,  and others who have had similar or different experiences there are encouraged to comment.

To start with, what is the general perception of ecology in China? Is it popular as a science? How likely are undergrads to choose it as a major or postgraduate degree?
Shaopeng Li: The common people in China often treat ecology as “ecological civilization”, “environmental protection” or “sustainable development”. Few people recognize it as a science. Some people even don’t know the difference between ecologists and environmentalists. But I think most people agree that ecology and what the ecologists do are very important to the development of China and their own life, despite that they often do not know what the ecologists exactly do.

It is sad to say that ecology is one of the most unpopular areas of life sciences in China. Most of undergrads in life sciences want to get a Master or PhD degree in molecular biology, pharmacy or environmental technology, which is easier to find a suitable job. Undergraduate students who major in ecology find it hard to get jobs in China. Most of them now think about career change. But we believe the situation will change in next five years.

How well are ecology grad students paid? What are the hours like? What are your regular duties? (i.e. do you teach, do field work, write papers? etc).
SL: The pay of the students in all the universities of China is very low. For example, in our school, the PhD students could get 1,500 RMB/month [~$250 USD], and the master students could only get 600-800 RMB/month. But the students of Chinese Academy of Sciences could get much more.

In China, most of the graduate students work very hard, from 9:00 am to 5:30 pm in every workday. Sometimes we must work extra hours at night or weekend. I know some of my friends often sleep in their work office. But it depends on the culture of different labs. In my lab, if you could finish your duties on time, you could set your own hours.

Students in my lab do not need to teach, although other students may have to. As a TA, we only need to send messages to the undergrads. Most of a PhD’s time is spend on fieldwork, experiments and paper-writing. Master students do not need to publish papers, so they spend most of their time on doing experiments in the first two years. For the third year, they will spend their time on thesis and finding jobs.

How are research labs structured?
SL: In the labs of our department (School of Life Sciences), we often have one professor (the PI), two or three associate professors, three or four postdoctorates, ten PhD students and 20 master students. We often do not have assistant professors in universities, and it is much easier to become an associate professor in China than in Western countries. Our lab is a little smaller than average; we only have 20 people. Some labs of the famous molecular biologists often have more than 40 students. The biggest lab in our school has about 100 master and PhD students total.

What is your perception of differences between the lab here and the lab you came from?
SL: In China, one big lab often focuses on many different projects. Take our lab for example, we have three different research areas: phytoremediation, environmental microbiology and biodiversity and ecosystem function. The biggest problem is that nobody could understand your research fully except yourself, even your supervisor. If you have any technological or statistical question, you must search for the books or papers by yourself, and it often takes us a lot of time to find the suitable methods and learn how to use them. But in lab here, many of us focus on phylogenetic ecology. If I have any problem, I could discuss it with Marc, you and Lanna [another graduate student] directly. It saved me a lot of time and I can pay more attention to the scientific question, not the technology.

Another difference is the relationship between the students and the professors. In China, the supervisor plays a role as a father, sometimes he is very kindly and sometimes he is very critical. Most of students are afraid of their supervisors. But here, we are all friends and the lab is like a big family. [CT-This may vary among western labs...] One noticeable phenomenon is that there are more excellent female ecologists in western countries. In China, it is very stressful for a girl to become a PhD student because of the traditional culture, especially in ecology.

Are English-language journals available to students? When you publish, is it in Chinese journals, English journals, or a mixture? Is it considered better to publish in international journals?
SL: Most of the English journals are available in Sun Yat-sen University. I think it is not a problem for the top 50 universities in China. However, for small universities and colleges, it may be very difficult for them to download English papers.

Most of the professors do not encourage students to publish papers in Chinese journals. If you only publish papers on Chinese journals, you will not get a good position after you graduate. Instead, publishing papers in international journals is very important for our academic career. If anyone could publish one research paper in Science or Nature, he may be able to get an associate professor position in any universities in China, even full professor position in some universities. However, some of the famous Chinese ecologists publish review papers in Chinese journals to introduce recent international advances, which is a good thing for our young students.

What are the requirements for finishing your PhD? How long will it usually take?
SL: Every student needs to publish at least one paper in any international journals listed on the Web of Knowledge to get their PhD degree. In some departments of our university, you must publish a paper in top journals with an impact factor higher than 3 or 5. We also need to write a thesis and pass the defence. But the thesis is not as important as the paper. I have never seen anyone who published a SCI paper cannot pass the defence. It takes us about 5 years totally to get a PhD degree. If you already have a master’s degree, it only takes you three years. But if you cannot publish a SCI paper on time, you can only get the degree after your paper is accepted. Half of PhD students in our department could not get their degree on time. Most of them would spend one or two years more to wait for the final acceptance for the paper (This is why Chinese scientists often want to urge the editors to deal with their papers as soon as possible). If you cannot publish any paper in your seventh year, you cannot get your degree anymore.

How important is mathematics in ecology in China? Are students expected to have a strong background in it?
SL: All Chinese students have a strong background in mathematics, except for statistics. I think the weak background in statistics is the second biggest problem for ecology students in China (The first one is English). Most of us have not learned statistics comprehensively. If we want to learn some methods of advanced biometrics, we need to read the obscure statistics books. Then we still cannot understand quite well. Most of our students want to learn more about statistics. Last year, Prof. Fangliang He, then at University of Alberta, ran a course named Advanced Biometrics in our university. More than 50 PhD students from 10 different universities came to our university to take this class. Few professors and students focus on theoretical ecology. Instead, most students want to know some advanced skills to deal with their experimental data.

What is doing fieldwork in China like?
In my opinion, we do much more fieldwork than the students of North American universities. I have spent most of my time on grassland experiments and fixed plots experiments in natural reserves. Sometime we even live in a tent on the top of the mountain for several days to collect specimens. The fieldwork in China is often very heavy. I also know that one PhD student who built up 100 fixed plots all over the China by herself.

For most of the time, if it is available, we often hire a lot of laborers to help us do the fieldwork. Chinese farmers are very kind and professional. They do the fieldwork much better than our students. Hiring laborers is very cheap in China, and this is why we could do a lot of big projects that the western ecologists may not be able do.

A large-scale biodiversity and ecosystem function experiment. The people in the picture are hired labourers who do the fieldwork.
http://www.bef-china.de/index.php/en/

What do you think is behind the recent growth in Chinese science in general, and ecology in particular?
SL: Recently, the development of science in China is very fast, with more and more Chinese scientists publishing high impact papers in international journals. I think there are many reasons. First, Chinese government is paying more and more attentions and money to scientific research, especially the hot topics such as climatic change, biological invasion and environmental pollution. The total investment of research funds was approximately one trillion in 2012 in China. Second, we have the largest number of researchers and PhD students all over the world. The number is still increased very quickly. Third, more and more ethnic Chinese (even non-ethnic Chinese) scientists would like to come back to work in China, which greatly narrowed the gap of research capabilities between China and western countries. In the area of ecology, the international communication and the ethnic Chinese ecologists in western countries contribute a lot to the development of ecology in China. More and more Chinese scientists want to interact with western ecologists. And 80% of the papers published by Chinese have foreign co-authors, who often help them to improve the language and statistical analysis.

However, there are still many problems in our science research. In my opinion, the lack of creative and critical thinking is the biggest problem in recent Chinese science. Most of the time, we are just following the hot topics. For ecology, there are few new theories or hypothesis created by Chinese ecologists. Instead, we like to do a lot of work on long-term and large scales experiments to test the recent hot topics. We spend more money and labor force on research projects, but often publish papers of lower qualities. There are many big project at large scales in China. For example, we have about 15 plots in the Center for Tropical Forest Science (CTFS) system, each 5-30ha. The Chinese Ecosystem Research Network (CERN) also consists of 36 field research stations all over the nation. Few Chinese ecologists focus on theoretical ecology and ecological modeling. Personally, I want to see more work with a basis in well-defined hypothesis and clever experiment design.

Are the ecological topics that are popular in China similar to those that are popular in North America? Is there more or less of a focus on ecological applications, or is basic research also very common there?
SL: I think the three most popular ecological topics in China are: climatic change, biological invasion and the causes and consequences of biodiversity. Most of us focus on the hot topics that are popular in North America (also easy to publish papers in good journals). Our discipline is not comprehensive as North America. Many of the traditional sciences such as taxonomy are dying out.

A lot of ecologists focus on ecological applications in China. Environmental Engineering, restoration ecology and phytoremediation are always hot topics in China because of the serious environmental problems. The ecologists focusing on applications are more popular in newspapers and TV. But doing basic research often has more academic influence.

What is the government doing to encourage scientists to stay in China or come back to China from overseas?
SL: The Chinese government has done a lot of things to encourage oversea scientists come back to China. For example, in December, 2008, the General Office of the Central Committee of the Chinese Communist Party made a decision to have high-level talents (full professor) from overseas come to work in China. Every one could get a lump-sum subsidy of 1 million RMB [~$160,000 USD] and a research subsidy ranging from 3 to 5 million RMB [~$0.5 million USD]. They proposed the “1000-talent Plan”. There are a total of 2,263 registered by July 2012. They also have sub-programs for the young researchers (postdoctorate and assistant professor) and non-ethnic Chinese experts. These subsidies are much higher than the income of native professors. There are many policies that favor scientists from overseas. Advertised positions of Chinese universities often ask for overseas research experiences and papers on top journals.

In contrast, the life of young scientists who stay in China seems very miserable. The subsidies for PhD students, post-doctorates and associate professors are much much less, although they can vary.  More importantly, you could not find a good position because you do not have “overseas research experiences” and high-quality papers. This is why more and more young people in China want to study abroad. The government does also encourages young scientists to study abroad. Every year, China Scholarship Council (CSC) supports more than 10,000 students to study abroad as full or visiting PhD students. For example, I am a visiting PhD supported by CSC, and my scholarship covers all the international airfare and my living stipend in Canada for one year. 

Students from Shaopeng's lab in the field. Shaopeng is second from the right.

Edited 4:00 pm EST, April 15 2013.

Navigating the complexities of authorship: Part 1 –inclusion

One of the highlights of grad school is publishing your very first papers in peer-reviewed journals. I can still remember the feeling of seeing my first paper appear in print (yes on paper and not a pdf). But what this novice scientist should not be fretting over is which colleagues should be included as authors and whether they are breaking any norms. The two things that should be avoided are including as authors, those that did not substantially contribute to the work, and excluding those that deserve authorship. There have been controversial instances where breaking these authorship rules caused uncomfortable situations. None of us would want someone writing a letter to a journal arguing that they deserved authorship. Nor is it comfortable to see someone squirming out of authorship, arguing they had minimal involvement when an accusation of fraud has been levelled against a paper. How to determine who should be an author can be difficult.

From PHD Comics (http://www.phdcomics.com/comics/archive.php?comicid=562)

Even though I spell out my own rules below, it is important to be flexible and to understand that different types of papers and differing situations can have an impact on this decision. That said, you do not want to be arbitrary in this decision. For example, if two people contribute similar amounts to a paper, you do not want to include only one because you personally dislike the other. You should have a benchmark for inclusion that can be defended. The cartoon above highlights the complexity and arbitrariness of authorship –and the perception that there are many instances of less than meritorious inclusion.

Journals do have their own guidelines, and many now require statements about contributions, but even these can be vague, still making it difficult to assess how much individuals actually contributed. When I discuss issues of authorship with my own students, I usually reiterate the criteria from Weltzin et al. (2006). I use four criteria to evaluate contribution:

1)   Origination of the idea for the study. This would include the motivation for the study, developing the hypotheses and coming up with a plan to test hypotheses.

2)   Running the experiment or data collection. This is where the blood, sweat and tears come in.

3)   Analyzing the data. Basically moving from a database to results, including deciding on the best analyses, programming (or using software) and dealing with inevitable complexities, issues and problems.

4)   Writing the paper. Putting everything together can sometimes be the most difficult and external motivation can be important.

My basic requirements for authorship are that one of these steps was not possible without a key person, or else there was a person who significantly contributed to more than one of these. Such requirements mean that undergraduates assisting with data collection do not meet the threshold for authorship. Obviously these are idealized and different types of studies (e.g., theory or methodological papers) do not necessarily have all these activities. Regardless, authors must have contributed in a meaningful way to the production of this research and should be able to defend it. All authors need to sign off on the final product.

While this system is idealized, there are still complexities making authorship decisions difficult or uncomfortable. Here are three obvious ones –but there are others.

Data sharing

Large, synthetic analyses require multiple datasets and some authors are loath to share their hard work without credit. This is understandable, as a particular dataset could be the product of years of work. But when is inclusion for authorship appropriate? It is certainly appropriate to offer authorship if the questions being asked in the synthesis overlap strongly with planned analyses for the dataset. Both the data owner and the synthesis architect have a mutual interest in fostering collaboration. In this case every effort should be made to include the data owner in the analyses and writing of the manuscript.

When is it not appropriate to include data owners as authors? First and foremost, if the data is publically available, then it is there for further independent investigation. No one would offer authorship to each originator of a gene sequence in Genbank. Secondly, if it is a dataset that has already been used in many publications and has fulfilled its intended goals, then it should be made available without authorship strings. I’ve personally seen scientists reserve the right of authorship for the use of datasets that are both publically available and have satisfied the intended purpose long ago.

The basic rule of thumb should be that if the dataset is recent and still being analyzed, and if the owner has an interest in examining similar questions, then authorship should be offered –with the caveat that additional work is required, beyond simply supplying the data.

Idea ontogeny

I thought about labeling this section ‘idea stealing’ but thought that wasn’t quite right. An idea is a complex entity. It lives, dies and morphs. It is fully conceivable to listen to a news story about agricultural subsidies, which somehow spurs an idea about ecosystem dynamics. We all have conversations with colleagues and go to talks, and these interactions can morph into new scientific ideas, even subconsciously. We need to be careful and acknowledge how much an idea came from a direct conservation with another scientist. Obviously if a scientist says “you should do this experiment…”,  then you need to acknowledge them and perhaps turn your idea into a collaboration.

Funding

Now here is the tricky one. Often people are authors because they control the purse strings. Yes, a PI has done an excellent job of securing funding, and should be acknowledged for this. If the study is a part of a funded project, where the PI developed the original idea, then the PI fully deserves to be included. However, if the specific study is independent from the funded project in terms of ideas and work plan, but uses funding from this project, then this contribution belongs in the acknowledgements and does not deserve authorship. There are cases where the PI of an extremely large lab gets dozens of papers a year, always appearing last in the list of authors (see part 2 on author order -forthcoming), and it is legitimate to view their contributions skeptically. Their relationship to many of the papers is likely financial and they probably couldn’t defend the science. I had a non-ecologist colleague ask me if it was still the case that graduate students in ecology produce papers without their advisors, to which I said yes (Caroline has several papers without me as an author).

Clearly there are cultural differences among sub disciplines. However, I do feel that authorship norms need to be robust and enforced. Cheaters (those gratuitously appearing on numerous papers –see part 3 on assigning credit; also forthcoming) reap the rewards and benefits of authorship, with little cost. It is disingenuous to list authors that have not have a substantial input into the publication, and the lead author is responsible for the accuracy of authorship. The easiest way to ensure that authors are really authors is to make an effort to include them in various aspects of the paper. For example, give them every opportunity to provide feedback –send them the first results and early drafts, have Skype for phone meetings with them to get their input and incorporate that input. Ultimately, we all should walk away from a collaboration feeling like we have contributed and made the paper better, and we should be proud to talk about it to other colleagues.

Many of these ideas were directly informed by this great paper by Weltzin and colleagues (2006):

Weltzin, J. F., Belote, R. T., Williams, L. T., Keller, J. K. & Engel, E. C. (2006) Authorship in ecology: attribution, accountability, and responsibility. Frontiers in Ecology and the Environment, 4, 435-441.

http://www.esajournals.org/doi/abs/10.1890/1540-9295(2006)4%5B435:AIEAAA%5D2.0.CO%3B2 

Measuring the Pacific extinction spasm

It is a fact that humans have caused numerous extinctions around the globe. Almost all of the large bodied mammals of North America disappeared after the arrival of humans sometime around 20,000 years ago –likely due to compounding effects of hunting and climate change.  This North American example has been controversial, largely because it constitutes a single observation. However, humans colonized the Pacific islands over a span of a couple of thousand years, between 3,500 to 700 years ago. Species extinctions followed these colonizations on each island, confirming the link between humans and extinctions. Yet how many species went extinct? This question may be relatively easily answered for large organisms since evidence of their existence is well recorded, but for small-bodied organisms like birds, this is a difficult question to answer.

In a recent paper in the Proceedings of the National Academy of Sciences, Richard Duncan, Alison Boyer and Tim Blackburn use sophisticated methods to estimate the true magnitude of bird (specifically nonpasserines –i.e., not perching or songbirds) extinctions on 41 Pacific islands (including islands from Hawaii, Melanesia, Micronesia and Polynesia). Estimating the number of extinctions prior to recorded history is an extremely difficult exercise, but Duncan and colleagues use a set of statistical methods (Bayesian mark-recapture) to produce reliable estimates. The data available include a spotty fossil record, and so the researchers needed an appropriate estimate of the number of species present on islands in the past. To do this they examined the fossil record and compared it to species that are found there today. Only a subset was found in the fossil record. From this, they determined how the number of fossils found, body size of the organisms and island size affected detection probability. With these informative detection probabilities, they were able to estimate past richness and compare that to today’s richness – and the difference is the number of extinctions.

Across these 41 islands, Duncan et al. estimate that human colonization resulted in at least 983 extinctions. Nine-hundred and eighty-three species are no longer with us because of the presence of humans. Coupled with human activities elsewhere, from over-hunting, habitat destruction and the introduction of non-native species, we responsible for thousands of extinctions. For the first time in Earth’s history, a single species (us) is the direct cause for thousands of other species going extinct. A paper such as this is an important analysis, but it certainly doesn’t make us feel good about ourselves.

Duncan, R., Boyer, A., & Blackburn, T. (2013). Magnitude and variation of prehistoric bird extinctions in the Pacific Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1216511110

Gendered assumptions and science: still a problem

Sometimes I feel like covering sexism and science has the potential to trigger a weary response, a feeling that this is well-travelled territory. And generally, academia is fairly self-aware about the causes and consequences of its current gender gap (see the special issue in Nature). But then I hear or read something that disappointingly reminds me that society as a whole still has a ways to go.

The first was a minor story. The curator of “I f--king love science”, a widely-followed Facebook page on things scientific and otherwise, happened to reveal that they were Elise Andrew--a female. While this seemed to be a non-event, apparently young men everywhere (i.e. on the internet) were shocked that their mental picture of a male scientist was untrue. Many comments fell along the lines of “you’re a girl?!” and “all that time picturing a man!”. Even more frustrating was that commenters also mentioned Elise’s appearance – attractive and female and a scientist--apparently this was so surprising as to be worthy of comment. And while I wanted to dismiss this as being limited to problems with Internet culture and hardly indicative of larger societal trends, something else happened – Yvonne Brill, a brilliant American rocket scientist passed away. Her work on propulsion systems now helps keep communications satellites in orbit, and she was a successful engineer with an interesting career. She clearly deserved a national obituary, and she got one in the New York Times. It started:

“She made a mean beef stroganoff, followed her husband from job to job and took eight years off from work to raise three children. “The world’s best mom,” her son Matthew said.

But Yvonne Brill, who died on Wednesday at 88 in Princeton, N.J., was also a brilliant rocket scientist, who in the early 1970s invented a propulsion system to help keep communications satellites from slipping out of their orbits.”

By way of comparison, not one of Steve Jobs’ obituaries started with a mention of his hobbies or personal accomplishments, or his status as a father. The only other recently (2012) deceased female scientist I could think of, astronaut Sally Ride, similarly received an obituary in the NYT that emphasized her gender - "American Woman Who Shattered Space Ceiling".

The need of society, reporters, and popular culture to reconcile a female scientist’s gender with their occupation appears to still be common. So much so that the one science writer came up with the Finkbeiner Test (Columbia Journalism Review) to point out articles which rely on the “she’s a woman AND a scientist” trope. Such articles tend to mention:

• The fact that she’s a woman 
• Her husband’s job 
• Her child-care arrangements 
• How she nurtures her underlings 
• How she was taken aback by the competitiveness in her field 
• How she’s such a role model for other women 
• How she’s the “first woman to…” 

The point is not that it is always unacceptable to include such things in articles, but that unless the article is about sexism or balancing work-life balance, these facts are irrelevant when reporting on a scientist's professional accomplishments. Gender shouldn't be the default position when we consider scientists who happen to be women. And apparently this message still needs to be repeated. Some people have suggested that one equalizer is to simply to also ask male scientists about their personal lives more often. However writer Finkbeiner notes that these questions rarely improve science journalism: "They’re [scientists] all normal human beings and the thing that makes them so interesting is the science. So, if you want to humanize them, talk about their motivations. Talk about how they got interested in their field. Talk about the part of their life that led them to become such an interesting scientist—because childcare is not interesting."

Note: while problems with gendered assumptions is a very general societal issue, academia isn't totally blameless. Having served on a number of lecture organizing committees, I've noticed that if the email for speaker nominations doesn't explicitly say that we wish to nominate male and female scientists at the top of their careers, female scientists are rarely nominated. Students' mental image of a top scientist tends to skew male. If that simple note is included though, nominations begin to approach gender ratios for professors at that career stage.

Carbon sequestration in boreal forests: below-ground interactions matter

K. E. Clemmensen, A. Bahr, O. Ovaskainen, A. Dahlberg, A. Ekblad, H. Wallander, J. Stenlid, R. D. Finlay, D. A. Wardle, B. D. Lindahl. Roots and Associated Fungi Drive Long-Term Carbon Sequestration in Boreal Forest. 2013. Science. Vol. 339 no. 6127 pp. 1615-1618. DOI:10.1126/science.1231923 

One of the most important developments in plant ecology over the last 20 or so years is the inclusion of belowground interactions with fungi into traditional studies of plant diversity, productivity, and ecosystem functions. Results like those from van der Heijden (1998)--which showed experimentally that the assumed link between ecosystem function and plant diversity was actually driven by arbuscular mycorrhizal fungal diversity (through their effects on plant communities)—must alter how we see plant community dynamics. Not only does this reinforce the importance of complexity in ecology, but more specifically it suggests that if fungi are a necessary component of plant community identity and function, they must be explicitly considered in management and conservation plans.

For example, an important current issue is the question of which ecosystems will be carbon sinks as part of a focus on atmospheric CO2 levels. Understanding the mechanisms by which carbon is stored is therefore an important topic. Boreal forests sequester net amounts of carbon in soil and it is generally assumed that this is as a result of plant litter and organic matter accumulating in soil. Clemmensen et al. (2013) examined soil chronosequences for forested islands in Sweden to test whether this hypothesis held. These islands differed in the frequency of fire occurrences, between large and frequently burnt islands and smaller, infrequently burnt islands.

The authors identified the age since fixation of C found in the chronosequences and used models of C source to look at the relative contribution of the two possible processes: either fixation of C through aboveground plant litter or below-ground inputs through root-associated fungi. Carbon input tended to be higher on the small islands that were burnt less often, and this was associated entirely with root-derived input. Further, DNA barcoding showed that on these small islands, there were mycorrhizal fungi associated with the soil depths where the root-derived inputs were occurring. On islands which burned more frequently, and had lower carbon input, fungi were absent at these depths (figure below). This difference in fungal profile was related to the fact that infrequently burnt islands had older mycelium with low turnover, hence greater carbon sequestration.

From Clemmensen et al (2013). A) Fungal functional groups associated with soil depths on large, frequently burnt islands (panel 1) and small, infrequently burnt islands (panel 2).

The authors convincingly show that, at least in some ecosystems, the view that decomposition of litter primarily drives humus accumulation (and the accompanying carbon sequestration) must be tempered with the knowledge that organic layers also accumulate from below by roots and root-associated fungi. This suggests that there is a need to consider fungal communities as well as plant communities for when managing forests and making inventories of global carbon stores. And probably a need to consider fungi much more often in general.

A map for defending your PhD

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