What scares ecologists?

In the spirit of Halloween, a non-comprehensive list of a few of the things that have frightened ecologists. The things we are scared of vary, with career trajectory and stage (graduate student, post-docs, faculty, non-academic), educational background, and goals. And even if the business of ecology doesn't scare you, some of the things we study should...


A few scary things

-That ghostly thesis - will it ever solidify?

-The undead paper

-Co-authors and supervisors

-Vampire reviewers: they've been around forever, they've seen everything, and they're looking for blood. (uncommon)

The whole process is pretty frightening.

-The Bayesian conspiracy:

• "Q. What is the Bayesian Conspiracy? A. The Bayesian Conspiracy is a multinational, interdisciplinary, and shadowy group of scientists that controls publication, grants, tenure, and the illicit traffic in grad students. The best way to be accepted into the Bayesian Conspiracy is to join the Campus Crusade for Bayes in high school or college, and gradually work your way up to the inner circles. It is rumored that at the upper levels of the Bayesian Conspiracy exist nine silent figures known only as the Bayes Council."

-The job market (or lack thereof?)

-The two-body monster

Fun but troublesome

-That our work is invisible

(0?)

-That our ideas come to life and go terribly wrong

-The science news makeover

And a few (of many) ecological topics that are truly scary

Kudzu

Zombie ants

Toxoplasmosis and human mind control

And the incredibly deadly mosquitoes?

(and all the pathogens it carries)

Waste not, want not? How human food waste changes ecosystems

Daniel Oro, Meritxell Genovart, Giacomo Tavecchia, Mike S. Fowler and Alejandro Martínez-Abraín. 2013. Ecological and evolutionary implications of food subsidies from humans. Ecology Letters. Volume 16, Issue 12, pp 1501–1514. DOI: 10.1111/ele.12187

Humans have always been connected to their environment, directly and indirectly. Ecologists in particular, and people in general, have been thinking about the causes and consequences of these connections for hundreds of years. One form of interaction results when human food resources become available to other animals – for example, through waste dumps, crop waste, fishery by-catches, bird feeders, or road kill. Starting with middens and waste piles in early human settlements, our food waste has always passed t

Garbage dump in India.

o other species. And while rarely considered compared to human impacts like habitat destruction and climate change, a new review by Daniel Oro and colleagues argues that these subsidies have shaped ecosystems around the globe.

Human food waste (aka subsidies) may come from a variety of human activities, with the three most prominent being crop residuals (remnants of harvest remaining on fields), waste dumps, and fishery discards (by-catch thrown overboard). Each of these forms of subsidy occurs globally and large numbers of species rely partially or completely on them for food. For example, dumps are global in distribution, and contain enough edible waste to attract 20-30% of all mammal and bird in a region (particularly omnivorous and carnivorous species). Crop residues usually attract herbivorous or granivorous species (particularly birds), while fisheries’ waste alter marine ecosystems. Eight percent of all catch (~7 million tonnes!) is simply released back into the ocean, and this supplements species across the food web, including half of all seabirds.

Food waste from human activities may not seem so terrible – after all, they are predictably available, easy to access, fast to forage, and can lead to increased condition and fertility among species that take advantage of them. For example, seabirds foraging among fishing boats for by-catch take advantage of the predictability of boat (and food) appearances and as a result have decreased foraging time and areas, higher individual fitness and reproductive success, and ultimately increased population growth. But the authors suggest that these benefits must be considered in a more complicated web of interactions. After all, human food subsidies tend to be much more predictable than natural sources of food and quickly have large effects spanning from individuals, communities, ecosystems, and evolutionary pressures.

Individuals often, though not always, experience positive effects from subsidies – increased biomass, fertility, and survival, accompanied by changes in dispersal and ranges. If food waste draws in high densities of individuals, it may be associated with greater disease occurrence, or draw in predators attracted to easy pickings. Populations also often respond positively to food subsidies, and become larger and more stable as food waste availability increases. But this boon for one species can cascade through the food web, and have large negative effects in communities and ecosystems. For example, yellow-legged gulls are found around dumps and fishing trawlers, taking advantage of the quantities of food available there, and as a result have increased greatly in population. The downside is that in turn these larger populations increase predation pressure on other vulnerable seabird species. Seabirds in particular can create complicated interactions between human food waste and far-flung ecosystems, connecting as they do both terrestrial and marine systems, moving nutrients, pollution, and calories between systems and through trophic levels.

Snow goose exclosure in northern Canada.
Only the small green rectangle has avoided goose grazing.

A famous example of the unexpected consequences of waste subsidies is the snow goose (Chen chen caerulescens). Snow geese have moved from feeding predominantly on marsh plants to landing en masse in farmers’ fields to feed on grain residues. This new and widespread source of food lead to a population boom, and the high numbers of geese stripped away the vegetation in the arctic habitats where they summer and breed. Agriculture food subsidies in southern habitats were felt far away in the arctic, as migratory snow geese tied these systems and food webs together. Though snow geese are unlikely to lose their new source of food, other animals may face plummeting populations or extinctions if food sources disappear. Until the 1970s, in Yellowstone, grizzly bears fed nearly exclusively at a local dump that then closed: the result was both increased mortality and rapid increases in foraging distances and behaviours.

Finally, and of most concern, food waste subsidies can alter the selective pressures a population faces. Species that become reliant on dumps or fields for food may experience changes in selective pressures, leading to selection for traits necessary to exploit these subsidies, and a loss of genotypic/phenotypic variation from the population. Changes in selective pressure change with the situation, of course. In the case of Yellowstone, the dump closure and loss of food source seemed to have large effects on traits important for sexual attractiveness in males, suggesting potential effects on reproductive success. In the best known (and my favourite) example of the selective effect of human food waste, dogs eventually were domesticated from wolf ancestors. Of course dumps can also relax selective pressures, if they allow individuals in poor condition (juveniles, the elderly) to successfully feed and reproduce.

Though food waste subsidies are clearly important and can have wide ranging effects, it is worth noting that the effect and importance of food subsidies is context-dependent. Studies seem to indicate that effects are greatest when food is low naturally or habitat quality is poor; in high quality systems, food waste may only be used by juveniles or individuals in poor condition. Unfortunately, as humans degrade natural habitats, subsidies are only likely to increase in importance as a food source for species. The extent and effects of human food waste are yet another legacy of the global alterations the human species has made. Unfortunately, like so many of the changes we have made, the issues are complex and transcend political and regional boundaries. Practices in one system or nation are tied to effects in another nation, and this complexity can make it difficult to monitor and measure the effects of subsidies as thoroughly as is necessary. This review from Oro et al. certainly makes a case for why our garbage needs to receive more attention.

One example of the ecosystem wide effects of subsidies: here, fisheries inputs.

Biodiversity and ecosystem functioning: now with more spatial scales, more functions, and more measures of diversity.

Jae R. Pasari, Taal Levi, Erika S. Zavaleta, and David Tilman. 2013. Several scales of biodiversity affect ecosystem multifunctionality. PNAS. 110:25

Responses:
1) Karel Mokany, Hugh M. Burley, and Dean R. Paini. β 2013. Diversity contributes to ecosystem processes more than by simply summing the parts. PNAS. 110:43.
2) Jae R. Pasari, Taal Levi, Erika S. Zavaleta. 2013. Reply to Mokany et al: Comprehensive measures of biodiversity are critical to investigations of ecosystem multifunctionality. PNAS. 110:43.

One of the big topics in ecology in recent years is ecosystem services and functioning. In particular, the question has been how diversity (in its many forms, including species, intraspecific, phylogenetic, or functional) relates to ecosystem function (often, but not always, measured in terms of productivity). Most often, this is framed as a question about how (alpha) diversity at the local scale affects one or two functional responses. Because diversity can be measured at multiple scales (local, regional or landscape, etc), because how we measure diversity is scale-dependent (i.e. alpha, beta, and gamma diversity), and because a functional ecosystem relies on many different services, the obvious next step is to think of biodiversity and ecosystem functioning in a framework that incorporates multiple spatial scales, multiple functions, and multiple measures of diversity.

A new paper in PNAS takes advantage of David Tilman’s long running Cedar Creek biodiversity experiment to explore how multiple functions in a landscape relates to local and regional diversity, and beta-diversity. In Pasari et al. (2013), the authors use five years of data collected for 168 9x9 m plots in the Cedar Creek experiment. These plots contained 1, 2, 4, 8, or 16 perennial plant species, and had measurements for 8 ecosystem functions (invasion resistance, aboveground NPP, belowground biomass, nitrogen retention, insect richness and abundance, and change in soil C and plant N). The authors simulated combinations of these plots to create 50,000 landscapes composed of 24 local plots. Multi-functionality in this case was the (scaled) mean of each of the 8 functions minus their standard deviation, for the landscape. The authors then asked whether the average alpha-diversity of the local plots, the beta-diversity between plots, and the gamma-diversity of the landscape were important predictors of this multi-functionality.

Not surprisingly, when considering the different functional responses individually, the average alpha-diversity of plots in a landscape was the most important determinant. Past research has shown that as local diversity increases, niches may be filled, or functional redundancy may increase, and so ecosystem functioning tends to increase. When considering all 8 ecosystem functions using a single measure though, beta- and gamma-diversity also appeared to be important, although alpha diversity remains the dominant predictor (figure below). It should be noted though that the total explained variance in functionality was always low. Increasing either alpha- or gamma-diversity increased multi-functionality, while the effect of beta-diversity on ecosystem functioning was not linear. “[O]nly experimental landscapes with low β diversity were capable of achieving very high multi-functionality, whereas high β-diverse experimental landscapes more consistently achieved moderate multi-functionality”. One important conclusion suggested by these results, then, is that even at larger scales the most important determinant of ecosystem function is how local communities are assembling, since this determines local diversity.

These results are an important update to the current state of biodiversity ecosystem function research, and add to the large body of research that says that all types of diversity are important insurance for functioning natural systems. It is difficult from this study to get a clear picture of how important each type of diversity is, and when alpha, beta, and gamma diversity might be more or less important. This is in part because despite the upsides of having multiple years of tightly controlled data from the Cedar Creek data, experimental communities artificially combined into landscapes lack realism. For example, beta-diversity captures turnover between communities that may result from spatial dynamics (environmental heterogeneity, dispersal, biotic interactions). All of these characteristics may be very important for functioning at the landscape scale. The response from Mokany et al. expresses some of these concerns, noting that artificially creating landscapes like this may omit important spatial and temporal connections found in real systems.

In addition, and this is a more technical concern about how alpha, beta, and gamma diversity are defined, I’m not clear on what the implications of using all three measures as explanatory variables in the same model may be. Mostly because under the strictest definitions of diversity, these three terms should be dependent on each other – changes in alpha and beta diversity necessarily alter gamma diversity. The authors didn’t use this definition in their study, but to understand the mechanisms that relate diversity and functionality, it may be more informative to take this inter-relationship into account.

Despite any caveats, I think that a role for beta-diversity in ecosystem functioning will be shown in further work, and perhaps its role will prove to be much greater than these initial results show. As we expand our understanding of the scales at which diversity matters, unfortunately this will no doubt highlight the limitations in our conservation focuses even more.

Is ecology really failing at theory?

Sam Scheiner. 2013. The ecological literature, an idea free distribution. Ecology Letters. Early View. DOI: 10.1111/ele.12196 

“Ecology is awash with theory, but everywhere the literature is bereft”. That is Sam Scheiner's provocative start to his editorial about what he sees as a major threat to modern ecology. The crux of his argument is simple – theory is incredibly important, it allows us to understand, to predict, to apply, to generalize. Ecology began as a study rooted in system-specific knowledge or natural history in the early 1900s, and developed into a theory-dominated field in the 1960s, when many great theoreticians came to the forefront of ecology. But today, he fears that theory is dwindling in importance in ecology. To test this, he provides a small survey of ecological and evolutionary journals for comparison (Ecology Letters, Oikos, Ecology, AmNat, Evolution, Journal of Evolutionary Biology), recording papers from each journal as either containing no theory, being ‘theory motivated’, or containing theory (either tests of, development of, or reviews of theory). The results showed that papers in ecological journals on average include theory only 60% of the time, compared to 80% for evolutionary papers. Worse, ecological papers seem to be more likely to develop theory than to test it. Scheiner’s editorial (as the title makes clear) is an indictment of this shortcoming of modern ecology.

Plots made based on data table in Scheiner 2013. Results combined for all evolution and all ecology papers.
The proportion of papers in each category - all categories starting with
 "Theory" refer to theory-containing papers.

Plots made based on data table in Scheiner 2013. Results for papers from individual journals.
The proportion of papers of each type - all categories starting with
 "Theory" refer to theory-containing papers.

This is not the kind of conclusion that I find myself arguing against too often. And I mostly agree with Scheiner: theory is the basis of good science, and ecology has suffered from a lack of theoretical motivation for work, or pseudo-theoretical motivation (e.g. productivity-diversity, intermediate diversity patterns that may lack an explanatory mechanism). But I think the methods and interpretation, and perhaps some lack of recognition of differences between ecological and evolutionary research make the conclusions a little difficult to embrace fully. There are three reasons for this – first, is this brief literature review a good measure of how and why we use theory as ecologists? Second, do counts of papers with or without theory really scale into impact or harm? And third, is it fair to directly compare ecological and evolutionary literature, or are there differences in the scope, motivations, and approaches of these fields?

If we are being truly scientific, this might be a good time to point out that The 95% confidence intervals for the percentage of ecology papers with theory overlap with the confidence intervals for the percentage of evolutionary papers with theory suggesting the difference that is the crux of the paper is not significant. [Thanks to a commenter for pointing out this difference is likely significant]. While significant at the 5% level, the amount of overlap is enough that whether this difference is meaningful is less clear. (I would accept an argument that this is due to small sample sizes though). The results also show that choice of journal makes a big difference in terms of the kinds of paper found within – Ecology Letters and AmNat had more theoretical papers or theory motivated papers, while Oikos had more tests of theory and Ecology had more case studies. This sort of unspoken division of labour between journals means that the amount of theory varies greatly. And most ecologists recognize this - if I write a theory paper, it will be undoubtedly targeted to a journal that commonly publishes theory papers. So to more fully represent ecology, a wider variety of journals and more papers would be helpful. Still, Scheiner's counterargument would likely be that even non-theory papers (case studies, etc) should include more theory.

It may be that the proportion of papers that include theory is not a good measure of theory’s importance or inclusion in ecology in general. For example, Scheiner states, “All observations presuppose a theoretical context...the simple act of counting individuals and assessing species diversity relies on the concepts of ‘individual’ and ‘species,’ both of which are complex ideas”. While absolutely true, does this suggest that any paper with a survey of species’ distributions needs to reference theory related to species’ concepts? What is the difference between acknowledging theory used via a citation and more involved discussion of theory? In neither of these cases is the paper “bereft” of theory, but it is not clear from the methods how this difference was dealt with. As well, I think that ecological literature contains far more papers about applied topics, natural history, and system-specific reports than evolutionary biology. Applied literature is an important output of ecology, and as Scheiner states, builds undeniably on years of theoretical background. But on the other hand, a paper about the efficacy of existing reserves in protecting diversity using gap analysis is both important and may not have a clear role for a theoretical section (but will no doubt cite some theoretical and methodological studies). Does this make it somehow of less value to ecology than a paper explicitly testing theory? In addition, case reports and data *are* a necessary part of the theoretical process, since they provide the raw observations on which to build or refine theory. In many ways, Scheiner's editorial is a continuation of the ongoing tension between theory and empiricism that ecology has always faced.

The point I did agree strongly with is that ecology is prone to missing the step between theory development and data collection, i.e. theory testing. Far too few papers test existing theories before the theoreticians have moved on to some new theory. The balance between data collection, theory development, and theory testing is probably more important than the absolute number of papers devoted to one or the other.

Scheiner’s conclusion, though, is eloquent and easy to support, no matter how you feel about his other conclusions: “My challenge to you is to examine the ecological literature with a critical eye towards theory engagement, especially if you are a grant or manuscript reviewer. Be sure to be explicit about the theoretical underpinnings of your study in your next paper…Strengthening the ecological literature by engaging with theory depends on you.”

Science shutdown

As the United States enters the 10th day of its government shutdown, the impacts on science and scientific researchers are becoming very apparent. Ignoring the political mess, the fact is that the shutdown is having devastating effects for science, ranging from small to very large scales.

Some of the largest obvious effects relate to the cessation of highly necessary services. For example, the majority of employees the Centers for Disease Control and Prevention were furloughed. Days later experts on foodborne illness were called back to work, because, surprise, they are essential in cases of E. coli outbreaks. Similarly, nearly all of the Environmental Protection Agency’s employees were furloughed, which means that air and water quality monitoring is furloughed too. According to one employee: "No one is going to be out inspecting water discharges, or wet lands. Nobody is going to be out inspecting waste water treatment plants, drinking water treatment plants, or landfills – nothing". Most of the employees whose work relates to climate science research and related environmental controls at the EPA, NASA, and the National Oceanic and Atmospheric Administration (NOAA) are also no longer at work.

Non-government scientists of every form are also being affected in multiple ways. The overwhelming issue is that the National Science Foundation (NSF) and National Institute of Health (NIH), have been all but closed. (For a great illustration, flip through the messages currently on US gov't science webpages, here). Technically, these furloughed employees are prohibited from replying to phone calls or answering emails from their work email. From one furlough letter: “Due to legal requirements, working in any way during a period of furlough is grounds for disciplinary action, up to and including termination of employment”. If your supervisor or collaborator is a federal scientist, this is a very direct impact of the furlough. But more generally and most importantly, these agencies (particularly the NSF for EEB academics) is the primary funding source for many scientists and institutes, and that means that until the shutdown is over, there will be no new payments or grants awarded.

(From nsf.gov/outage.html, regarding new awards)

"Proposal Preparation & Submission
No new funding opportunities (program descriptions, announcements or solicitations) will be issued.
FastLane proposal preparation and submission will be unavailable."
(existing awards)

"Performance of Work
Awardees may continue performance under their NSF awards during the shutdown, to the extent funds are available, and the term of the grant or cooperative agreement has not expired. Any expenses must be allowable and in accordance with the Office of Management and Budget (OMB) cost circulars. During the shutdown, NSF cannot authorize costs exceeding available award amounts or obligate additional funds to cover such costs.
Payments
No payments will be made during the shutdown."

If your grant is up for review or you are applying for a new grant (it was DDIGs season), then you are out of luck for the moment (FastLane, necessary for submitting grants, is not available), and there undoubtedly will be delays in processing once the shutdown does end.


Even if you have money to spend, limitations may arise from the fact that permits for research activities can’t be filled, and National Parks, National Wildlife Reserves, National Forests are all closed, so planned field activities may be limited. For example, Long-term Ecological Reseach projects (LTERs), which by definition require continuity in sampling, some projects are now inaccessible. Researchers in charge of long-term studies of rodent populations in Sevilleta National Wildlife Refuge, New Mexico, found the gates locked and the combinations changed, making monitoring stations impossible to reach. If you were planning a field season in Antarctica, you are especially out of luck, since the field season has been cancelled altogether. If you planned to use the collections at a national museum (e.g. the Smithsonian), or use government websites and federally funded data repositories, you can’t. I’ve received several mass emails from researchers attempting to locate other sources of necessary data, since their government source is gone. Even if you aren’t a researcher in the US, you might notice the effect of the shutdown because the high profile open-access journal from the Public Library of Science, PLOS ONE, is also at a standstill. And if the keynote speaker at your conference is a US government employee, you’ll notice their absence, since they are not allowed to attend conferences. 

Given the global nature of science, these effects are not isolated to only just a single country in the world – scientists everywhere share US websites and institutions, museum collections, collaborate with US-located researchers, government or otherwise, do fieldwork in US national parks, or rely on the continuity of data from long-term research projects. The impacts of this shutdown are broad and deep, and the most important question is how long will it take for science and scientists to recover?


*If anyone has examples of how this shutdown is affecting their research, please leave a comment!

Why greater diversity – even of parasites – might decrease infections

Pieter T. J. Johnson, Daniel L. Preston, Jason T. Hoverman, and Bryan E. LaFonte. 2013. Host and parasite diversity jointly control disease risk in complex communities. PNAS. Early view.

(Host competence - the tendency of host species to become infected and maintain infection.)

There is often a disconnect between the reality that communities and ecosystems are diverse assemblages with numerous, often complicated and variable interactions, and ecological research, which (perhaps necessarily) focuses on interactions between at most two or three species at a time. Disease ecology similarly has often considered interactions between particular host/parasite species pairs. Some researchers have considered the diversity of host species as an important factor in explaining disease transmission and mortality, but the reality is that parasites also interact, and most hosts harbour multiple parasites. Studying disease dynamics in the context of multi-parasite, multi-host interactions is increasingly recognized as key to understanding disease transmission and severity in communities.

With this in mind, a new paper from Pieter Johnson and colleagues attempts to combine research into the effects of both parasite and host diversity on disease. Two possible hypotheses predict the effect of diversity on disease transmission: the ‘dilution effect’ suggests that the presence of multiple hosts should decrease transmission risk, if the result of additional species is a decline in community competence. It is also hypothesized, somewhat contradictorily, that increased host diversity should support a greater variety of parasites, and parasite life cycles. Both these hypotheses take a host-centric view: understanding how changes in host diversity alter disease risk also requires that we understand how changes in parasite diversity affect disease transmission.

Mutations caused by Ribeiroia infection.
From:http://www.nature.com/scitable/knowledge/library/ecological-consequences-of-parasitism-13255694

The authors looked at the contribution of host and parasite diversity to parasite transmission success using field data and laboratory experiments. First, they looked at existing data on infections of the pathogenic trematode Ribeiroia ondatrae, in amphibian species. Observations showed a positive correlation between larval trematode diversity (parasites) and the richness of free-living species (hosts). Of course the two diversities might be correlated for many unrelated reasons, like site isolation, evolutionary history, or habitat productivity. But a closer analysis showed what appeared to be an interaction between Ribeiroia infection in Pseudacris regilla (Pacific tree frog, the most common amphibian in the survey) and the total number of amphibian species at a site (figure below). Infection by Ribeiroia was highest when there was low amphibian richness and low parasite richness. It dropped significantly lower when amphibian richness was high and/or parasite richness was high.

From Johnson et al. 2013 PNAS. Results of field observations.

In addition to these observations, the authors manipulated both parasite and host species richness, first in small laboratory microcosms and then in larger and more realistic outdoor mesocosms. Results from the laboratory microcosms showed that increases in both amphibian richness (one vs. three species) and parasite richness (one vs. five species) reduced the average number of Ribeiroia in Pseudacris regilla as well as the total infection rate in the amphibian community. The mesocosms had similar results, with both host and parasite diversity negatively influencing Ribeiroia infection. In support of the generality of these results, effect sizes were comparable between the two experiments. These effects were also quite large: for example, in the mesocosm high-host, high-parasite richness treatment there were 52.4% fewer Ribeiroia per P. regilla and 38.2% fewer Ribeiroia overall compared to the low-host, low-parasite richness. Clearly multi-species interactions are crucial for understanding infection by Ribeiroia.

From Johnson et al. 2013 PNAS. Results of the microcosm and mesocosm experiments,
 showing the effects of host and parasite diversity on transmission.

The results make it clear that if you want to understand disease transmission in communities, both host and parasite diversity should be considered. To some extent, both of the initial hypotheses were supported – host and parasite diversity were correlated in the wild, but (in agreement with the dilution effect) infection rates declined as host diversity increased. One factor missing from these hypotheses is the dynamics of the parasite community: in the paper, the authors found models of transmission that included both host and parasite richness were superior. Further, past and future studies that consider only host richness may be inadvertently accounting for the effects of parasite richness on transmission as well, if those two host and parasite diversities are correlated.

There are a number of possibilities for why both host and parasite communities alter parasite transmission success. If host diversity changes the susceptibility of the community to infection (i.e. as diversity increases, the number of low competence/susceptible species increases) then low-competence hosts could act as sinks for parasite infections. Increases in parasite diversity could result in inter-parasite competition and interactions via host immunity.

One future step will be to move beyond simple measurements of species richness to understanding how species identity or characteristics are tied to the putative mechanisms. For example, how do communities of host species vary from low to high diversity sites? Do sites in fact tend to assemble with increasing numbers of low competence host species? The implications are also of interest to other types of studies of community ecology – after all, host-parasite interactions are not very different from predator-prey interactions, and similarly, despite knowing that interactions are complex and involve multiple species, we tend to focus on two or three species examples.

The demise of peer review?

Scientists are often inundated with numerous requests to submit their papers to 'open access' journals with no track record, no editor-in-chief, and dubious sounding promises. Why this explosion in dubious journals? -simple, there is money to be made. Many of these journals are scams meant to maximize profits. As it turns out, they don't even bother with peer review. In a recent, fascinating story in Science, John Bohannon sent fatally flawed bogus articles to hundreds of open access journals, with more than half being accepted with little or no peer review. This article is a must read for anyone concerned about science publishing.

Struggling (and sometimes cheating) to catch up

Scientific research is maturing in a number of developing nations, which are trying to join North American and European nations as recognized centres of research. As recent stories show, the pressure to fulfill this vision--and to publish in English-language, international journals--has led to some large-scale schemes to commit academic fraud, in addition to cases of run-of-the-mill academic dishonesty.

In China, a widely-discussed incident involved criminals with a sideline in the production of fake journal articles, and even fake versions of existing medical journals in which authors could buy slots for their articles. China has been criticized for widespread academic problems for some time, for example, 2010 the New York Times published a report suggesting academic fraud (plagiarism, falsification or fabrication) was rampant in China and would hold the country back in its goal to become an important scientific contributor. In the other recent incident, four Brazilian medical journals were caught “citation stacking”, where each journal cited the other three excessively, thus avoiding notice for obvious journal self-citation, while still increasing their journal’s impact factor. These four journals were among 14 having their impact factors suspended for a year, with other possible incidences that were flagged but could not be proven involved Italian, a Chinese, and a Swiss journal.

There are some important facts that might provide context to these outbreaks of cheating. Both Brazil and China are nations where to be a successful scientist in the national system, you need to prove that you are capable of success on the world stage. This is probably a tall order in countries where scientific research has not traditionally had an international profile and most researchers do not speak English as their first language. In particular it leads to focus on values which are comparable across the globe, such as journal impact factors, as measures of success. In China, there is great pressure to publish in journals included on the Science Citation Index (SCI), a list of leading international journals. When researcher, department, and university success is quantified with impact factors and SCI publications, it becomes a numbers game, a GDP of research. Further, bonuses for publications in high caliber journals can double a poorly-paid researcher’s salary: a 2004 survey found that for nearly half of Chinese researchers, performance based pay was 50+ percent of their income. In Brazil, the government similarly emphasizes publications in Western journals as evidence of researcher quality.

It’s easy to dismiss these problems as specific to China or Brazil, and there are some aspects of the issue that are naturally country-specific. On the other hand, if you peruse Ivan Oransky’s Retraction Watch website, you’ll notice that academic dishonesty leading to article retraction is hardly restricted to researchers from developing countries. At the moment, the leading four countries in retractions due to fraud are the US, Germany, Japan, and then China, suggesting that Western science isn’t free from guilt. But in developing nations the conditions are ripe to produce fraud. Nationalistic ambition is funnelled into pressure on national scientists to succeed on the international stage; disproportionate focus on metrics of international success; high monetary rewards to otherwise poorly paid individuals for achieving these measures of success; combined with the reality that it is particularly difficult for researchers who were educated in a less competitive scientific system and who may lack English language skills, to publish in top journals. The benefits of success for these researchers are large, but the obstacles preventing their success are also huge. Combine that with a measure of success (impact factor, h-index) that is open to being gamed, and essentially relies on honesty and shared scientific principles, and it is not surprising that system fails.

Medical research was at the heart of both of these scandals, probably because the stakes (money, prestige) are high. Fortunately (or not) for ecology and evolutionary biology, the financial incentives for fraud are rather smaller, and thus organized academic fraud is probably less common. But the ingredients that seem to lead to these issues – national pressures to succeed on the world stage and difficulty in obtaining such success; combined with reliance on susceptible metrics  – would threaten any field of science. And issues of language and culture are so rarely considered by English-language science (eg.), that it can be difficult for scientists from smaller countries to integrate into global academia. There are really two ways for the scientific community to respond to these issues of fraud and dishonesty – either treat these nations as second-class scientific citizens and assume their research may be unreliable, or else be available and willing to play an active role in their development. There are a number of ways the latter could happen. For example, some reputable national journals invite submissions from established international researchers to improve the visibility of their journals. In some nations (Portugal, Iceland, Czech Republic, etc), international scientists review funding proposals, so that an unbiased and external voice on the quality of work is provided. Indeed, the most hopeful fact is that top students from many developing nations attend graduate school in Europe and North America, and then return home with the knowledge and connections they gained. Obviously this is not a total solution, but we need to recognize fraud as problem affecting and interacting with all of academia, rather than solely an issue of a few problem nations.

Can common tradeoffs predict your supervisor’s functional type?

With Lanna Jin

If you’re a graduate student, the most important question (even more important than who you’re writing your paper with) is who is running your lab. New graduate students everywhere are settling in and getting to know their supervisors are little better. Supervisors come in all types, and hypothesizing a priori what their style is can be difficult. Fortunately, a couple of common tradeoffs underlie most functional styles...

---

1)

The invisible man/woman: The ultimate laissez-faire approach. You have the freedom to choose the ideas and projects that interest you, and the responsibility to make them work. Freedom can be replaced by frustrations when you need a signature, some support, or a manuscript commented on.

El generalissimo: "Here's my idea, now go do it." These labs are usually run in a top-down manner. Day to day operations are fairly hands off though, giving you room to work through those problems on your own. El generalissimo will reward their supporters well for good work.

The coach: The coach provides you the best of both worlds: enough rope to explore your ideas, but not so much to hang yourself. They are available for troubleshooting and brainstorming, but you ultimately have responsibility for your project. But if you rely on them to much, it's going to be hard to function without them.

The micromanager: These supervisors expect regular presence, frequent meetings, records of progress, and milestones to be met promptly. If you like working from home, leaving early or starting late, or need lots of freedom to be most productive it could be a poor fit. For students who thrive on structure and prefer set goals though, this might be an ideal environment.

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2)

The skeleton: This supervisor has established themselves in their career and been active for some time, but now other interests consume them. The scientific meat that made their name seems to be gone, and all that's left is the skeleton of their earlier career. They are happy to chat with you about the many things they are interested in, but supervising your science doesn't seem to be a priority. They often see you as a person who has with non-academic interests and responsibilities, which can be a nice feeling.

The superwoman/superman: This career superstar has made their name, possibly quite early, and they are passionate about their science. This can make for an exciting and successful lab experience, as new ideas and opportunities are always on the horizon. But since they have so many demands on their time, sometimes their capes (and they) are feeling a bit ragged.

The silverback: Labs of influential individuals can be an amazing opportunity for a graduate student. Silverback experiences might be quite variable, depending on how involved they are in day to day lab activities, their travel schedules, and the size of the lab. When they are available, they have a lot to teach a student about making a successful academic career.

Bad idea: This corner of the tradeoff (low interest in science, poor establishment in the career) probably doesn't exist in tenure-track faculty. If you do manage to find such a person, run away.

The unknown: A motivated but still unestablished supervisor is a blank slate. Their early career state means that they might have time and energy to devote to you and be especially motivated to see you and the lab succeed. On the other hand, they may not yet know how to manage people and their supervisor style could morph into anything - the coach, the micromanager, el generalissimo. A bit of a gamble.

Can intraspecific differences lead to ecosystem differences?

Sara Lindsay Jackrel and J. Timothy Wootton. 2013. Local adaptation of stream communities to intraspecific variation in a terrestrial ecosystem subsidy. Ecology. Online early.

It’s funny how complex outcomes can arise from simple realizations. For example, it is plausible that when there are differences among individuals of a species (like when local populations are adapted to the local environment), these could implications for function on the ecosystem scale. But while there is increasing evidence for the importance of intraspecific variation for ecological interactions within communities, the question of how intraspecific diversity scales up to ecosystem functioning is still ambiguous.

Sara Jackrel and Timothy Wootton explore this question in “Local adaptation of stream communities to intraspecific variation in a terrestrial ecosystem subsidy”. The basis for their study was simple: local adaptation is common, and populations/genotypes/ecotypes tend to be best adapted to the particular conditions of their locale. For example, “spatial variation in prey and predators can lead to a geographic mosaic of co-evolutionary interactions”. Further, these localized interactions can affect the greater ecosystem, if individuals or materials move between ecosystem boundaries.

In particular, the authors note that there is evidence that tree species composition riverside can alter the composition of the local aquatic community. This occurs via leaf litter fluxes into the river: the type and amount of leaf litter that falls into streams varies, and so the type of macroinvertebrates in the recipient stream also varies in response. These macroinvertebrates break down the leaf litter via shredding, collecting, and filtering, playing an important role in nutrient cycles. Leaf litter is carried from a given tree by wind or water and may decompose near or far away, creating a connection between ecosystems. The question then is whether macroinvertebrate compositional shifts will occur in response to intraspecific differences in leaf (i.e. trees), and what the implications might be for ecosystem functions such as leaf decomposition. To explore this question, Jackrel and Wootton performed reciprocal transplants of leaf litter material between eight sites along rivers in the Olympic Peninsula of Washington.

All eight of these sites were early successional forests dominated by red alder. The authors collected fresh leaves from alder trees, bagging leaves from each tree separately. These bags of leaves were either placed in the river adjacent to the trees they were taken from, or in a more distant site. Non-adjacent sites were either in the same river as the home site, or in different river all together. Leaf packs were weighed before and after spending 17-18 days in the river. This would allow comparison of how decomposition rates vary between home and away sites, and between home and away rivers.

Their results suggested a few interesting things. First, the identity of a tree affects the rate of decomposition of its leaves: individual alder trees’ leaves were highly variable in the rate of decomposition. Second, the combined identities of trees at a site seem to have affected the composition of the decomposer community at the home river site: put leaves from that site in another river with a new community of decomposers, and the decomposition rate drops significantly. In general, leaves decomposed significantly more rapidly when in their home river, regardless of whether at the home site or elsewhere along the river. But if they put leaves upstream from the home site, but in the same river, the rate of decomposition also dropped. Upstream decomposer communities were apparently much worse at breaking down leaves from novel communities of alders. However, if you put the leaves in sites downstream from home, the decomposition rates are not significantly different than in the home site. This is likely because of the directional movement of a river, such that downstream locations receive leaf litter from all upstream sites, and so downstream decomposer communities experience a greater variety of leaf litter than upstream sites. This might lead to upstream sites being more closely adapted to the individual trees in their neighbourhood than downstream sites, which receive inputs from a wide variety of trees. These results suggest that individual differences in trees at different spatial locations can matter, both locally, across trophic levels, and even across ecosystems.

Admittedly there is not a lot you can infer about the mechanisms at play from this preliminary experiment. One interesting follow up would be to measure compositional differences in aquatic macroinvertebrates at very fine scales in correspondence with differences in trees. Another important question is whether these communities differ via phenotypic plasticity, adaptation to local sites, or species sorting. But this paper does hint at one way in differences among individuals can shape local ecosystems and even structure distant ecosystems (e.g. downstream decomposer communities) through fluxes across boundaries. And that is a rather complicated implication from a logical and simple starting point.