Tag Archives: taxonomist shortage

Two Visions of Ecological Research

Let us assume for the moment that the goal of scientific ecology is to understand the reasons for changes in the distribution and abundance of animals, plants, and microbes. If you do not think this is our main agenda, perhaps you should not read further.

The conventional, old paradigm to achieve this goal is to obtain a good description of the natural history of the organisms of interest in a population or community, define the food web they operate within, and then determine by observations or manipulations the parameters that limit its distribution and abundance. This can be difficult to achieve in rich food webs with many species, and in systems in which the species are not yet taxonomically described, and particularly in microbe communities. Consequently a prerequisite of this paradigm is to have good taxonomy and to be able to recognize species X versus species Y. A whole variety of techniques can be used for this taxonomy, including morphology (the traditional approach) and genetics. Using this approach ecologists over the past 90 years have made much progress in deriving some tentative explanations for the changes that occur in populations and communities. If there has been a problem with this approach, it is largely because of disagreements about what data are sufficient to test hypothesis X, and whether the results of manipulation Y are convincing. A great deal of the accumulated data obtained with this approach has been useful to fisheries management, wildlife management, pest control, and agricultural production.

The new metagenomics paradigm, to use one label, suggests that this old approach is not getting us anywhere fast enough for microbial communities, and we need to forget most of this nonsense and get into sequencing, particularly for microbial communities. New improvements in the speed of doing this work makes it feasible. The question I wish to address here is not the validity or the great improvements in genetic analysis, but rather whether or not this approach can replace the conventional old paradigm. I appreciate that if we grab a sample of mud, water, or the bugs in an insect trap and grind it all up, and run it through these amazing sequencing machines, we get a very great amount of data. We then might try to associate some of these kinds of data with particular ‘species’ and this may well work in groups for which the morphological species are well described. But what do we do about the undescribed sequences? We know that microbial diversity is much higher than what we can currently culture in the laboratory. We can make rules about what to call unknown unit A, unknown unit B, and so on. That is fine, but now what? We are in some sense back where Linnaeus was in 1753 in giving names to plants.

Now comes the difficult bit. Do we just take the metagenomics approach and tack it on to the conventional approach, using unknown A, unknown B, etc. instead of Pseudomonas flavescens or Bacillus licheniformis? We cannot get very far this way because the first thing we need to decide is does unknown A a primary producer or unknown B a decomposer of complex organic molecules? So perhaps this leads us to invent a whole new taxonomy to replace the old one. But perhaps we will go another way to say we will answer questions with the new system like is this pond ecosystem changing in response to global warming or nutrient additions? We can describe many system shifts in DNA-terminology but will we have any knowledge of what they mean or how management might change these trends? We could work all this out in the long term I presume. So I guess my confusion is largely exactly which set of hypotheses are you going to test with the new metagenomics paradigm? I can see a great deal of alpha-descriptive information being captured but I am not sure where to go from there. My challenge to the developers of the new paradigm is to list a set of problems in the Earth’s ecosystems for which this new paradigm could provide better answers more quickly than the old approach.

Microbial ecology is certainly much more difficult to carry out than traditional ecology on macroscopic animals and plants. As such it should be able to use new technology that can improve understanding of the structure and function of microbe communities. All new advances in technology are helpful for solving some ecological problems and should be so used. The suggestion that the conventional approach is out of date should certainly be entertained but in the last 70 years the development of air photos, of radio telemetry, of satellite imagery, of electrophoresis, of simplified chemical analyses, of automated weather stations, and the new possibilities of genetic analysis have been most valuable to solving ecological questions for many of our larger species. But in every case, at every step we should be more careful to ask exactly what questions the new technology can answer. Piling up terabytes of data is not science and could in fact hinder science. We do not wish to validate the Rutherford prediction that our ecological science is “stamp collecting”.

10 Limitations on Progress in Ecology

Ecological science moves along slowly in its mission to understand how the Earth’s populations, communities, and ecosystems operate within the constraints of human impacts on the Biosphere. The question of the day is can we identify the factors currently limiting the rate of progress so that at least in principle we could speed up progress in our science. Here is my list.

1. A shortage of ecologists or more properly jobs for ecologists. In particular a scarcity of government agencies employing ecologists in secure jobs to work on stable, long-term environmental projects that are beyond the scope of university scientists. Many young ecologists of high quality are stalled in positions that are beneath their talents. We are in a situation similar to having highly trained medical doctors being used as hospital janitors. This is a massive failure on many fronts, regional and national, political and scientific. Many governments around the world think economists and lawyers are key while environmental scientists are superfluous.

2. The lack of proper funding from both government, private companies and private individuals. This is typified by the continual downsizing of government scientists working on natural resource problems – fisheries, wildlife, park management – and continuing political interference with scientific objectives. Private companies too often rely on taxpayers to fund their environmental investigations and do not view them as a part of their business model. Private citizens give money to medical research rather than to environmental programs largely based on the belief that of all the life on Earth, only the human component is important.

3. The deficiency of taxonomic expertise to define clearly the species that inhabit the Earth. The estimates vary but perhaps only 10% of the total biota can be given a Latin name and morphological description, leaving out for the moment all the bacteria and viruses. Equate this with having a batch of various shaped coins in your pocket with only a few of them giving the denomination. This problem has been identified for years with little action.

4. Given adequate taxonomy, the lack of adequate natural history data on most of the biota. This activity, so critical for all ecological science, was called “stamp collecting” and thus condemned to the lowest point on the scientific totem pole. The consequence of this is that we try to understand the Earth with data only on butterflies, some birds, and some large mammals.

5. A failure of ecologists to map out the critical questions facing natural populations, communities, and ecosystems on Earth. The roadmap of ecology is littered with wrecks of ideas once pushed to explain nearly everything, and we need a more nuanced map of what is a critical issue. There are a considerable number of fractures within the ecological discipline about what needs to be done, if people and money were available. This fosters the culture of I win = you lose in competition for money and jobs.

6. The confusion of mathematical models with reality. There is a strong disconnect between models and data that persists. Models rapidly proliferate, data are slow to accumulate, so we try to paper over the fragility of our understanding with mathematical wizardry, trying to be like physicists. Connecting model predictions with empirical data studies would go a long way to righting this problem but it is a tall order in a world that confuses the number of publications and h scores with important contributions.

7 The fact that too many ecologists do not adopt the scientific method of investigation, to carry out experiments with multiple alternative hypotheses with clear predictions. Arguments continue endlessly based on words (‘concepts’) that are so vaguely defined as to be meaningless operationally. If you need an example, think ‘stability’ or ‘diversity’. These vague words are then herded into pseudo-hypotheses to doubly confound the confusion over what the critical questions in ecology really are.

8. The need for ecologists to work in stable groups. Serious ecological problems demand expertise in many scientific specialities, and we need better mechanisms to foster and maintain such groups. The assessment of scientists on the basis of individual work is long out of date, the Nobel Prize is an anachronism, and we need strong groups concentrating on important issues for long term studies. At the moment many groups exist to do meta-analyses and fewer to do science.

9. Placing the technological horse in front of the ecological cart. Ecology like many sciences is often led by technology rather than by questions. The current DNA bandwagon is one example, but we should not get so confused to think that that most important questions in ecology are those that use the most technology. Jumping from one technological bandwagon to the next is a good recipe for minimizing progress.

10. The fractionation of ecology into subdisciplines and the assumption that the only important research work has been done since 2000. Aquatic ecologists do not talk to terrestrial ecologists, microbial ecologists live in their own special world, and avian ecologists do not talk to insect ecologists. The result is that the existing literature is too often wasted by investigators who have no idea that question XX has already been answered either in another subdiscipline or in existing literature from 50 years ago.

Not all of these limitations apply to every ecologist, and at best I would view them as a set of guideposts that need to be considered as we move further into the 21st century.

Krebs, C. J. 2006. Ecology after 100 years: progress and pseudo-progress. New Zealand Journal of Ecology 30:3-11.

Majer, J. D. 2012. Critical times: How has ecological research responded over the past 35 years? Austral Ecology 37:149-152.

Sutherland, W. J. et al. 2010. A horizon scan of global conservation issues for 2010. Trends in Ecology & Evolution 25:1-7.