Category Archives: General Ecology

Some Reflections on Evo-Eco

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Some ecologists study evolutionary processes and we call them evolutionary ecologists. They have their own journals and are a thriving field of science. Other ecologists study populations, communities, and ecosystems in ecological time and do not in general concern themselves with evolutionary changes.The question is should they? Evo-Eco is a search for evolutionary changes that have a decisive impact on observable ecological changes like that of a collapsing bird population.

There are two schools of thought. The first is that evo-eco is very important and the changes that ecologists are trying to understand are partly caused by ecological mechanisms like predation and competition but are also associated with genetic changes that affect survival and reproduction. Consequently an ecologist studying the declining bird population should study both genetics and ecology. The second school of thought is that evo-eco is rarely of any importance in causing ecological changes, so that we can more or less ignore genetics if we wish to understand why this bird population is disappearing.

A practical problem immediately rears its head. To be safe we should all follow evo-eco in case genetics is involved in dynamics. But given the number of problems that ecologists face, the number of scientists available to analyse them, and the research dollars available it is rare to have the time, energy or money to take the comprehensive route. Conservation ecologists are perhaps the most tightly squeezed of all ecologists because they have no time to spare. Environmental managers request answers about what to do, and the immediate causes of conservation problems are (as everyone knows) habitat loss, introduced pests and diseases, and pollution.

The consequence of all this is that the two schools of thought drift apart. I cannot foresee any easy way to solve this issue. Progress in evolutionary ecology is often very slow and knowing the past rarely gives us much insight into predicting the human-affected future. Progress in conventional ecology is faster but our understanding is based on short-term studies of unknown generality for future events. Both schools of thought race along with mathematical models that may or may not tell us anything about the real world, but are conceptually elegant and in a pinch might be called progress if we had time to test them adequately.

The most useful evo-eco approach has been to look at human-caused selection via fishing for large sized fish or hunting for Dall sheep with the largest horns. The overuse of antibiotics for human sickness and as prophylactics for our farm animals is another classic case in which to understand the ecological dynamics we need to know the evolutionary changes that we humans have caused. These are clear cases in which genetic insights can teach us very much.

I end with a story from my past. In the 1950s, nearly 70 years ago now, Dennis Chitty working at Oxford on population fluctuations in small grassland rodents considered that he could reject most of the conventional explanations for animal population changes, and he suggested that individuals might change in quality with population density. This change he thought might involve genetic selection for traits that were favourable only in high density populations that reappeared every 3-4 years. So in some strange sense he was one of the earliest evo-eco ecologists. The result was that he was nearly laughed out of Oxford by the geneticists in control. The great evolutionary geneticist E.B. Ford told Chitty he was completely mad to think that short term selection was possible on a scale to impact population dynamics. Genetic changes took dozens to hundreds of years at the best of time. There were of course in the 1950s only the most primitive of genetic methods available for mammals that all look the same in their coat colour, and the idea that changes in animal behaviour involving territoriality might cause genetic shifts on a short-term period gradually lost favour. Few now think that Chitty was right in being evo-eco, but in some sense he was ahead of his time in thinking that natural selection might operate quickly in field populations. Given the many physiological and behavioural changes that can occur phenotypically in mammals, most subsequent work on grassland rodents has become buried in mechanisms that do not change because of genetic selection.

When we try to sort out whether to be concerned about evo-eco, we must strike a compromise between what the exact question is that we are trying to investigate, and how we can best construct a decision tree that can operate in real time with results that are useful for the research question. Not every ecological problem can be solved by sequencing the study organism.

Chitty, D. 1960. Population processes in the vole and their relevance to general theory. Canadian Journal of Zoology 38:99-113.

Models need testable predictions to be useful

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It has happened again.  I have just been to a seminar on genetic models – something about adaptation of species on the edges of their ranges.  Yes this is an interesting topic of relevance to interpreting species’ responses to changing environments.  It ended by the speaker saying something like, “It would be a lot of work to test this in the field”. How much more useful my hour would have been spent if the talk had ended with “Although it would be difficult to do, this model makes the following predictions that could be tested in the field,” or “The following results would reject the hypothesis upon which this model is based.”

Now it is likely that some found these theoretical machinations interesting and satisfying in some mathematical way, but I feel that it is irresponsible to not even consider how a model could be tested and the possibility (a likely possibility at that) that it doesn’t apply to nature and tells us nothing helpful about understanding what is going to happen to willow or birch shrubs at the edge of their ranges in the warming arctic (for example).

Recommendation – no paper on models should be published or talked about unless it makes specific, testable predictions of how the model can be tested.

On Important Questions in Ecology

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There is a most interesting paper that you should read about the important questions in ecology:

Sutherland, W.J. et al. (2013) Identification of 100 fundamental ecological questions. Journal of Ecology, 101, 58-67.

This paper represents the views of 388 ecologists who culled through all of the 754 questions submitted and vetted in a two day workshop in London in April 2012. There are many thesis topics highlighted in this list and it gives a good overview of what many ecologists think is important. But there are some problems with this approach that you might wish to consider after you read this paper.

We can begin with a relatively trivial point. The title indicates that it will discuss ‘fundamental’ questions in ecology but the Summary changes this to ‘important’ questions. To be sure the authors recognize that what we now think is ‘important’ may be judged in the future to be less than important, so in a sense they recognize this problem. ‘Important’ is not an operational word in science, and consequently it is always a focus for endless argument. But let us not get involved with semantics and look at the actual 100 questions.

As I read the paper I was reminded of the discussion in Peters (1991, p. 13) who had the audacity to point out that academic ecologists thrived on unanswerable questions. In particular Peters (1991) focused on ‘why’ questions as being high on the list of unanswerable ones, and it is good to see that there are only 2 questions out of 100 that have a ‘why’ in them. Most of the questions posed are ‘how’ questions (about 65 instances) and ‘what’ questions (about 52 instances).

In framing questions in any science there is a fine line in the continuum of very broad questions that define an agenda and at the other extreme to very specific questions about one species or community. With very broad questions there will never be a clear point at which we can say that we have answered that question so we can move on. With very specific questions we can answer them experimentally and move on. So where do we cut the cake of questions? Most of these 100 questions are very broad and so they both illuminate and frustrate me because they cannot be answered without making them more specific.

Let me go over just one example. Question 11 What are the evolutionary and ecological mechanisms that govern species’ range margins? First, we might note that this question goes back at least 138 years to Alfred Wallace (1876, The Geographical Distribution of Animals), and has been repeated in many ecology textbooks ever since. There are few organisms for which it has been answered and very much speculation about it. At the moment the ecological mechanism in favour is ‘climate’. This is a question that can be answered ecologically only for particular species, and cannot be answered in real (human) time for the evolutionary mechanisms. Consequently it is an area rife for correlational ecology whose conclusions could possibly be tested in a hundred years if not longer. All of these problems should not stand in the way of doing studies on range margins, and there are many hundreds of papers that attest to this conclusion. My question is when will we know that we have answered this question, and my answer is never. We can in some cases use paleoecology to get at these issues, and then extrapolate that the future will be like the past, a most dubious assumption. My concern is that if we have not answered this question in 138 years, what is the hope that we will answer it now?

It is good to be optimistic about the future development of ecological science. Perhaps I have picked a poor example from the list of 100 questions, and my concern is that in this case at least this is not a question that I would suggest to a new PhD student. Still I am glad to have this list set out so clearly and perhaps the next step would be to write a synthesis paper on each of the 100 topics and discuss how much progress has been made on that particular issue, and what exactly we might do to answer the question more rapidly. How can we avoid in ecology what Cox (2007) called a “yawning abyss of vacuous generalities”?

Cox, D. R. (2007) Applied statistics: A review. Annals of Applied Statistics, 1, 1-16.

Peters, R. H. (1991) A Critique for Ecology, Cambridge University Press, Cambridge, England.

Sutherland, W. J., Freckleton, R. P., Godfray, H. C. J., Beissinger, S. R., Benton, T., Cameron, D. D., Carmel, Y., Coomes, D. A., Coulson, T., Emmerson, M. C., Hails, R. S., Hays, G. C., Hodgson, D. J., Hutchings, M. J., Johnson, D., Jones, J. P. G., Keeling, M. J., Kokko, H., Kunin, W. E. & Lambin, X. (2013) Identification of 100 fundamental ecological questions. Journal of Ecology, 101, 58-67.

Open Letter from a Scientist to a Bureaucrat

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Let us assume for the moment that I am a scientist who has worked in a government research organization for 25 years under a series of bureaucrats. I have just retired and the object of this letter is to tell a bureaucrat what is good and what is bad about the bureaucratic government system. If you work in a perfect government system, perhaps you do not need to read further.

Dear Sir/Madam:

I would like to offer you some free advice that comes from a scientist who has worked in government for many years. This is presumptuous to be sure in light of our relative positions, but I feel you might benefit from some notes from the trenches.

First, science should never be organized in a top-down manner. We ecologists know about trophic cascades and the consequences it has for the lower trophic levels. You should not tell us what to do because you know nothing about the subject matter of the science, in this case ecology. I note especially that an MBA does not confer infinite wisdom on science matters. So I suggest you consider organizing things bottom-up. Your job is to provide scientists with the technical support, the funding, and the facilities to do their work. I note that this does not preclude you providing us with general areas of science in which we are expected to do our research. If our general position is to study the effectiveness of pollination in California crops, you should not tolerate us going to Africa to study elephant ecology. We appreciate that the government has at least some general ideas of what is critical to study. If they do not, it would be advisable to gather a group of scientists to discuss what the critical problems are in a particular area of science. Scientists do not work in closed rooms and do have a general understanding of what is happening in their field.

Second, do not muzzle us about anything scientific. We do not work for you or for the current government but we do work for the people of Canada or Australia or whatever country, and our mandate is to speak out on scientific questions, to provide evidence based policy guidance and to educate the public when errors are promulgated by people who know nothing about what they speak. This could well include government ministers who are known at least on occasion to utter complete nonsense. Our job is not to support the government’s policies of the day but to provide evidence about scientific questions. In general we scientists do not see government ministers crying out that they know more about brain surgery than trained doctors, so we think the same attitude ought to be taken toward ecologists.

Third, ask your scientists about the time frame of their scientific studies. Most bureaucrats seem to think that, since the world was created in 7 days, scientific work ought to take no more than a year or two or perhaps three. We would like to tell you that many, perhaps most, important ecological questions involve a time frame of 10 years or more, and some require continuous funding and support for periods in excess of 50 years. You apparently did not ask medical scientists to stop working on cancer or malaria after 3 years or even 50 years, so we are uncertain why ecologists should be kept to short time frames for their research. Ecological research is perhaps the most difficult of all the sciences, so if we do not find answers in a few years it is not because we are not working hard enough.

Finally, ask your scientists to publish in national and international journals because that is the corner stone for judging scientific progress. We do not mind having rules about rates of publication. And as a spur please fund your scientists to go to scientific meetings to present their results to the scientific world. And have them communicate to the public what they are doing and what they have found. After all the public pays, so why should they not hear about what has come of their tax dollars.

Your job, in a nutshell, is to support your scientists not to hinder them, to encourage their work, and to speak to the higher levels of government about why funding science is important. And to (at least on occasion) protest about government policies that are not based on scientific evidence. If you are successful in all of this, the people of your country will be the better for it. On the other hand, you may be headed for early retirement if you follow my advice.

I wish you success.

Sincerely yours,

A.B.C. Jones PhD, DSc, FRS, FAA
Retired

Two Visions of Ecological Research

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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”.

On House Mouse Outbreaks in Australia

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It occurred to me after some recent discussions that the problem of house mouse outbreaks in Australia is almost a paradigm for modern ecological science. A brief synopsis. At irregular intervals house mice (an introduced pest) reach high densities in the wheat growing areas of eastern and southern Australia, and cause serious damage to wheat, barley, oats, and sunflower crops. There are two approaches to this applied problem.

The ecological approach is to understand why these outbreaks occur and why for many years (2-9 years) between outbreaks, hardly a mouse can be found. This approach has been highly successful led by a series of excellent Australian ecologists over the last 40 years. The key limitation is food, combined with social interactions, and the food supply is driven by rain at critical times of the year to provide seeds for the mice. There are no competitors for house mice, and there are a few insignificant predators, overwhelmed by the mouse’s high reproductive rate. These ecological facts are clearly known, and the job now is to build the best predictive models to help the farmers anticipate when the outbreak is coming. There are still important ecological questions to be studied, to be sure, but the broad outline of the ecological play is well described.

The management approach is much simpler because farmers can control house mice with poison, primarily zinc phosphide, and for them the question is when to poison, and secondarily (over time and with more research) can we develop better poisons so there are few non-target problems. Poisoning costs time and money so good farmers wish to minimize these costs.

The long-term issues get lost in this situation, a model of the way the world operates now with ecological and environmental problems. Questions about sustainability multiply in any system dependent on poisons for a solution. Will the target organisms become resistant so the poison does not work? Many examples exist of this already. Are there any long-term problems with soil organisms, or non-target species? No research yet on these issues, and perhaps they are more serious with herbicide applications in agriculture. And while predators do not control house mice during outbreaks, they do eat many of them and this food pulse may have implications for the wider ecosystem. We focus on farming and forget the wider ecosystem which has no dollars attached to it.

Ecologists recognize that these issues are not the farmers’ fault, but we raise the question of who worries about the long-term future of this system, and the answers to these long-term questions. The government is rushing to get out of long-term ecological and agricultural research and we leave problems that do not have immediacy.

Consequently we become short-sighted as a society. Long-term research becomes 1-3 years and not the 50-100 years that ecologists would support. And consequently applied ecologists bounce from one problem to the next under the paradigm that, no matter what we do, science will come up with a technological fix. There should be a better way. To go back to our house mice, we might ask (for example) if we implement no-till agriculture, what will be the consequences for house mouse survival and future outbreaks? The practical minister of agriculture will respond that we have no time or money for such research, so we lurch along, managing the world in an ad-hoc manner. There should be a better way. But meanwhile we must follow the money.