Navigating the complexities of authorship: Part 2 -author order

Authorship can be tricky business. It is easy to establish agreed upon rules within, say, your lab or among frequent collaborators, but with large collaborations, multiple authorship traditions can cause tension. Different groups may not even agree on who should be included as an author (see Part 1), much less what order they should appear. The number of authors per paper has steadily increased over time reflecting broad cultural shifts in science. Research is now more collaborative, relying on different skill sets and expertise.

 Average number of authors per publication in computer science, compiled by Sven Bittner

Within large collaborations are researchers who have contributed to differing degrees and author order needs to reflect these contribution levels. But this is where things get complicated. In different fields of study, or even among sub-disciplines, there are substantial differences in cultural norms for authorship. According to Tscharntke andcolleagues (2007), there are four main author order strategies:

1.        Sequence determines credit (SDC), where authors are ordered according to contribution.
2.        Equal contribution (ED), where authors are ordered alphabetically to give equal credit.
3.        First-last-author emphasis (FLAE), where last author is viewed as being very important to the work (e.g., lab head).
4.        Percent contribution indicated (PCI), where contributions are explicitly stated.

The main approaches in ecology and evolutionary biology are SDC and FLAE, though journals are increasingly requiring PCI, regardless of order scheme. This seems like a good compromise allowing the two main approaches (SDC & FLAE) to persist without confusing things. However, PCI only works if people read these statements. Grant applications and CVs seldom contain this information, and the perspective from these two cultures can bias career-defining decisions.

I work in a general biology department with cellular and molecular biologists who wholeheartedly follow FLAE. They may say things like “I need X papers with me as last author to get tenure”. As much as I probe them about how they determine author order in multi-lab collaborations, it is not clear to me how exactly they do this. I know that all the graduate students appear towards the front in order of contribution, but the supervisor professors appear in reverse order starting from the back. Obviously an outsider cannot disentangle the meaning of such ordering schemes without knowing who the supervisors were.

The problem is especially acute when we need to consider how much people have contributed in order to assign credit (see Part 3 on assigning credit). With SDC, you know that author #2 contributed more than the last author. With FLAE, you have no way of knowing this. Did the supervisor fully participate in carrying out the research and writing the paper? Or did they offer a few suggestions and funding? The are cases where the head of ridiculously large labs appears as last author on dozens of publications a year, and grumbling from those labs insinuate that the professor hasn’t even read half the papers.

Under SDC, this person should appear as the last author, reflecting this minimal contribution, but this shouldn’t give the person some sort of additional credit.

In my lab, I try to enforce a strict SDC policy, which is why I appear as second author on a number of multi-authored papers coming out of my lab. I do need to be clear about this when my record is being reviewed in my department, or else they will think some undergrad has a lab somewhere. Even with this policy, there are complexities, such as collaborations with other labs we follow FLAE, such as with many European colleagues. I have two views on this, which may be mutually exclusive. 1) There is a pragmatic win-win, where I get to be second author and some other lab head gets the last position and there is no debate about who deserves this last position. But 2) this enters morally ambiguous territory where we each may receive elevated credit depending on whether people look at the order through SDC or FLAE.

I guess the win-win isn’t so bad, but it would nice if there was an unambiguous criterion directing author order. And the only one that is truly unambiguous is SDC –with ED (alphabetical) for all the authors after the first couple in large collaborations. The recent paper by Adler and colleagues(2011) is a perfect example of how this should work.

References:

Adler, P. B., E. W. Seabloom, E. T. Borer, H. Hillebrand, Y. Hautier, A. Hector, W. S. Harpole, L. R. O’Halloran, J. B. Grace, T. M. Anderson, J. D. Bakker, L. A. Biederman, C. S. Brown, Y. M. Buckley, L. B. Calabrese, C.-J. Chu, E. E. Cleland, S. L. Collins, K. L. Cottingham, M. J. Crawley, E. I. Damschen, K. F. Davies, N. M. DeCrappeo, P. A. Fay, J. Firn, P. Frater, E. I. Gasarch, D. S. Gruner, N. Hagenah, J. Hille Ris Lambers, H. Humphries, V. L. Jin, A. D. Kay, K. P. Kirkman, J. A. Klein, J. M. H. Knops, K. J. La Pierre, J. G. Lambrinos, W. Li, A. S. MacDougall, R. L. McCulley, B. A. Melbourne, C. E. Mitchell, J. L. Moore, J. W. Morgan, B. Mortensen, J. L. Orrock, S. M. Prober, D. A. Pyke, A. C. Risch, M. Schuetz, M. D. Smith, C. J. Stevens, L. L. Sullivan, G. Wang, P. D. Wragg, J. P. Wright, and L. H. Yang. 2011. Productivity Is a Poor Predictor of Plant Species Richness. Science 333:1750-1753.

Tscharntke T, Hochberg ME, Rand TA, Resh VH, Krauss J (2007) Author Sequence and Credit for Contributions in Multiauthored Publications. PLoS Biol 5(1): e18. doi:10.1371/journal.pbio.0050018

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.