Author Archives: Charles Krebs

On Gravity Waves and the 1%

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The news this week has been all about the discovery of gravity waves and the great triumphs of modern physics to understand the origin of the universe. There is rather less news on the critical ecological problems of the Earth – of agricultural sustainability, biodiversity collapse, pollution, climate change – not to mention the long recognized economic problems of poverty and inequality, globally and within our own countries. All of these issues converge to the questions of resource allocations by our governments that have failed to assess priorities on many fronts. Many see this but have little power to change the system that is continually moving to save and improve the fortunes of the 1% to the detriment of most people.

In scientific funding there has always been a large bias in favor of the physical sciences, as I have commented on previously, and the question is how this might be publicized to produce  a better world. I suggest a few rules for scientific funding decisions both by governments and by private investors.

Rule 1: For maximizing scientific utility for the biosphere including humans, we require a mix of basic and applied science in every field. Whether this mix should be 50:50, 30:70, or 70:30 should be an item for extended discussion with the implicit assumption that it could differ in different areas of science.

Rule 2: Each major area of science should articulate its most important issues that must be addressed in the short term and the long term (>50 years). For biodiversity, as an example, the most important short term problem is to minimize extinctions while the most important long term problem might be to maintain genetic variability in populations.

Rule 3: The next step is most critical and perhaps most controversial: What are the consequences for the Earth and its human population if the most important issue in any particular science is not solved or achieved? If the required experiments or observations can be delayed for 30 (or 50) years, what will it matter?

If we could begin to lay out this agenda for science, we could start a process of ranking the importance of each of the sciences for funding in the present and in the long term. At the present time this ranking process is partly historical and partly based on extreme promises of future scenarios or products that are of dubious validity. There is no need to assume that all will agree, and I am sure that several steps would have to be designated to involve not only young and older scientists but also members of the business community and the public at large.

If this agenda works, I doubt that we would spend quite so much money on nuclear physics and astronomy and we might spend more money on ocean science, carbon budgets, and sustainable agricultural research. This agenda would mean that powerful people could not push their point of view in science funding quite so freely without being asked for justification. And perhaps when budgets are tight for governments and businesses, the first people on the firing line for redundancy will not be environmental scientists trying their best to maintain the health of the Earth for future generations.

So I end with 2 simple questions: Could gravity waves have waited another 100 years for discovery? What is there that cannot wait?

(Finally, an apology. I failed to notice that on a number of recent blogs the LEAVE A REPLY option was not available to the reader. This was inadvertent and somehow got deleted with a new version of the software. I should have noticed it and it is now corrected on all blogs.)

On Conservation Dilemmas

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Conservation is a strange mix of science and politics. What exactly the fraction of the mix is I would not hazard a guess, but probably the science of conservation biology is a small part of the total. That is not an excuse for anyone not to go into conservation as a career but you need to realize what you are walking into.

Many people have written about this but the latest radio announcements about wolf killing in western Canada got me thinking again about the problem of killing one native species to possibly protect another native species. Wolves eat caribou, mountain caribou are endangered, wolves are not (at the moment) endangered, therefore a simple solution: shoot A to save B. But think about this a bit and first of all realize that this is certainly not a scientific decision. Science tests hypotheses but it does not decree policies of action. The scientific issue buried in this controversy is whether or not shooting wolves will save the mountain caribou. How far, as a conservation scientist, do you trace the causality of a problem like this? Wolves eat a lot of moose as well as caribou. Oil and gas companies make roads to their wells and gas fields, paving the way for easy wolf dispersal to catch more moose or caribou. Moose love successional landscapes, and forestry companies love to make moonscapes by logging, generating successional landscapes. Deer also love farmland and successional landscapes, and mountain lions increase when deer increase. Mountain lions also take the occasional jogger. Where do we stop the causal chain?

If causality stops at the farm gate, wolves eat caribou therefore shoot them, life is simple. But to an ecologist this is missing the elephant in the room, our human use of landscapes. We make landscapes better for some species and worse for others, but we typically refuse to bear any responsibility for these landscape changes. How many logging companies or oil companies have been prosecuted for making wolves more abundant? So we go back to the farm gate and argue that killing wolves will have no effect on dwindling caribou because there are other predators out there – bears for example – that also eat caribou. And an honoured law of conservation biology is that once you get to a low population for the most part you are doomed no matter what happens. You cannot in a limiting case save a caribou herd of n = 1. But let us be optimistic as ecologists and argue that killing wolves will save the caribou. We have to add “this year” to that statement because, as Bob Hayes (2010) so elegantly argued in his book, once you start killing wolves you can never stop if that is your management solution. Caribou are caught in a nexus of wolves, bears, moose, deer, and elk in parts of western North America, and there is as yet no clear way of analyzing this nexus in a predictive manner. Killing wolves is the answer, but what is the question?

Money for management is yet another matter that enters the picture. Dollars spent on helicopter gunships cannot be spent on habitat improvements for other less charismatic species. So one needs value judgements here also, and this is not a scientific question but a policy one.

I think these conservation dilemmas are a general problem, and no doubt much is written about them. Do we kill an introduced species to save a native one? Do we forget about an introduced pest because a threatened bird species feeds on the pest? Do we get rid of an introduced weed that is poisonous to cattle but provides nectar for bees? Or in the present case do we kill one native species to potentially save another native species? Few of these questions are scientific questions and few can ever be sorted out by getting more data. So this is the problem I am not sure how to face. We go into conservation ecology to do science, but in the end we become a policy advisor that can be easily dismissed for political, social, or budget reasons. There is no way around this as far as I can see. If you think wolves are a valuable part of biodiversity, agitate not to kill them. If you think caribou will be preserved by killing wolves, go for the guns. All the arguments about the role of top predators in ecosystems (Ordiz et al. 2013, Ripple et al. 2014) can fall on deaf ears if society has a different value system than conservation biologists have.

Hayes, B. (2010) Wolves of the Yukon. Wolves of the Yukon Publishing, Smithers, B.C.

Ordiz, A., Bischof, R. & Swenson, J.E. (2013) Saving large carnivores, but losing the apex predator? Biological Conservation, 168, 128-133. doi: 10.1016/j.biocon.2013.09.024

Ripple, W.J., Estes, J.A., Beschta, R.L., Wilmers, C.C., Ritchie, E.G., Hebblewhite, M., Berger, J., Elmhagen, B., Letnic, M., Nelson, M.P., Schmitz, O.J., Smith, D.W., Wallach, A.D. & Wirsing, A.J. (2014) Status and ecological effects of the world’s largest carnivores. Science, 343, 1241484. doi: 10.1126/science.1241484

 

On Philanthropic Investment in Conservation – Part 2

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Here is an optimistic thought for the day. After writing my previous blog on philanthropy and conservation, it occurred to me that a single scenario might focus the mind of ecologists and conservation biologists as we think about relevant research:

Suppose you are sitting in your office and someone comes in and tells you that they wish to donate one billion dollars to your research in ecology. What would you tell them you would like to do?

This is of course ridiculous but let us be optimistic and think it may happen. There are a lot of very rich people around the world and they will have to do something with all their money. Some of it will be wasted but some could do much good for the development of strong science. So let us pretend for the moment that this will happen sometime in the future.

We need to think clearly what this money entails. First, if we want to live off the interest and we expect 5% return on investment, we end up with $ 50 million to spend per year. What are we going to do with all this money? The two options would seem to be to buy land and maintain it for conservation, or to set up a foundation for conservation that would support graduate student and postdoctoral fellows. Let us check these options out with a broad brush.

The first option is based on the belief that habitat loss is the key process driving biodiversity decline so we should use part of the money for land purchase or marine rights to areas. But we note that land purchases are not very useful if the land is not managed and protected so that some group of people need to be in charge. So suppose we spend half immediately on land acquisition, and land costs are $100 per ha, we could purchase about 50,000 km2, an area approximately the size of Denmark, slightly smaller than Scotland, and about the size of West Virginia. Then we can employ about 250 people full time to do research or manage the protected landscape at an overall cost of $100 K per scientist including salary and operating research costs. This is an attractive option and the decision that would need to be made is what areas are most important to purchase for conservation in what part of the world.

The second option is to establish a permanent foundation for conservation that would be devoted to supporting graduates and postdoctoral fellows worldwide. I am not clear on the costs for a foundation to operate but let us assume $ 2 million a year for staff and operating costs. This would leave $ 48 million for operating costs, supporting 480 students or postdocs at $100,000 each per year or 320 students if you wished to give each an average $150,000 per year for research and salary. If these were spread out over the 196 countries on Earth, clearly there would be about 2 scientists per country. If we spread them out evenly over the 148 million km2 of land area over the whole Earth, we would require each student or scientist to be in charge of about 300,000 km2, an area about the size of Norway, or Poland or the Philippines. Clearly one would not operate in such a fashion, and would concentrate person-power in the areas of greatest need.

There is considerable literature discussing the issue of how philanthropy can augment conservation in the most effective manner, and a few papers are given here that further the discussion.

Where does this theoretical exercise leave us? Clearly there would be many other ways to utilize these hypothetical funds for conservation, but the point that shows clearly is that the funds needed to achieve conservation on a global scale are very large, and even a billion dollars disappears very quickly if we are attempting to achieve solid conservation outcomes. The costs of conservation are large and there is the need to recognize that government funding is critical, so that an additional billion dollars from a philanthropist will only add icing on the cake and not the whole cake.

Not that anyone I know would turn down a billion-dollar donation as too little.

Adams, W., and J. Hutton. 2007. People, parks and poverty: Political ecology and biodiversity conservation. Conservation and Society 5:147-183.

Diallo, R. 2015. Conservation philanthropy and the shadow of state power in Gorongosa National Park, Mozambique. Conservation and Society 13:119-128. doi: 10.4103/0972-4923.164188

Ferraro, P. J., and S. K. Pattanayak. 2006. Money for Nothing? A call for empirical evaluation of biodiversity conservation investments. PLoS Biology 4:e105.
doi: 10.1371/journal.pbio.0040105

Jones, C. 2012. Ecophilanthropy, neoliberal conservation, and the transformation of Chilean Patagonia’s Chacabuco Valley. Oceania 82:250-263.
doi: 10.1002/j.1834-4461.2012.tb00132.x

 

On Log-Log Regressions

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Log-log regressions are commonly used in ecological papers, and my attention to their limitations was twigged by a recent paper by Hatton et al. (2015) in Science. I want to look at just one example of a log-log regression from this paper as an illustration of what I think might be some pitfalls of this approach. The regression under discussion is Figure 1 in the Hatton paper, a plot of predator biomass (Y) on prey biomass (X) for a variety of African large mammal ecosystems. I emphasize that this is a critique of log-log regression problems, not a detailed critique of this paper.

Figure 1 shows the raw data reported in the Hatton et al. (2015) paper but plotted in arithmetic space. It is clear that the variance increases with the mean and the data are highly variable, as well as slightly curvilinear, so a transformation is clearly desirable for statistical analysis. Unfortunately we are given no error bars on each of the point estimates, so it is not possible to plot confidence limits for each estimate.

Figure 1A

We log both the axes and get Figure 2 which is identical to that plotted as Figure 1 in Hatton et al. (2015). Clearly the regression fit is better that that of Figure 1 and yet there is still considerable variation around the line of best fit.

Figure 2A

The variation around this log-log line is the main issue I wish to discuss here. Much depends on the reason for the regression line. Mac Nally (2000) made the point that regressions are often used for predictive purposes but sometimes used only as explanations. I assume here one wishes this to be a predictive regression.

So the next question is if the Figure 2 regression is predictive, how wide are the confidence limits? In this case we will adopt the usual 95% confidence predictions for a single data point. The result is shown in Figure 3, which did not appear in the Science article. The red lines define the 95% confidence belt.

Figure 3A

Now comes the main point of my concerns with log-log regressions. What do these error limits really mean when they are translated back to the original measurements that define the graph?

The table given below gives the prediction intervals for a hypothetical set of 8 prey abundances scattered along the span of prey densities reported.

Prey abundance (kg/km2)

Estimated predator abundance (kg/km2)

Predicted lower 95% confidence limit

Predicted upper 95% confidence limit

Width of lower confidence interval (%)

Width of upper confidence interval (%)

200

4.4

2.46

7.74

-44%

+76%

1000

14.1

8.16

24.6

-42%

+74%

1500

19.0

11.0

33.2

-42%

+70%

2000

23.4

13.2

41.0

-44%

+75%

4000

38.7

22.4

69.0

-42%

+78%

8000

64.0

35.4

113.6

-45%

+78%

10000

75.2

43.6

134.4

-42%

+79%

12000

85.8

49.0

147.6

-43%

+72%

The overall average confidence limits for this log-log regression are -43% to +75%, given that the SE of the predictions varies little across the range of values used in the regression. These are very broad confidence limits for any prediction from a regression line.

The bottom line is that log-log regressions can camouflage a great deal of variation, which may or may not be acceptable depending on the use of the regression. These plots always visually look much better than they are. You probably already knew this but I worry that it is a point that can be easily overlooked.

Lastly, a minor quibble with this regression. Some authors (e.g. Ricker 1983, Smith 2009) have discussed the issue of using the reduced major axis (or geometric mean regression) when the X variable is measured with error instead of the standard regression method. One could argue for this particular data set that the X variable is measured with error, so that I have used a reduced major axis regression in this discussion. The overall conclusions are not changed if standard regression methods are used.

Hatton, I.A., McCann, K.S., Fryxell, J.M., Davies, T.J., Smerlak, M., Sinclair, A.R.E. & Loreau, M. (2015) The predator-prey power law: Biomass scaling across terrestrial and aquatic biomes. Science 349 (6252). doi: 10.1126/science.aac6284

Mac Nally, R. (2000) Regression and model-building in conservation biology, biogeography and ecology: The distinction between – and reconciliation of – ‘predictive’ and ‘explanatory’ models. Biodiversity & Conservation, 9, 655-671. doi: 10.1023/A:1008985925162

Ricker, W.E. (1984) Computation and uses of central trend lines. Canadian Journal of Zoology 62 (10), 1897-1905.doi: 10.1139/z84-279

Smith, R.J. (2009) Use and misuse of the reduced major axis for line-fitting. American Journal of Physical Anthropology, 140, 476-486. doi: 10.1002/ajpa.21090

On Philanthropic Investment in Biodiversity Conservation

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In the holiday season there is much talk and recommendations about donations to worthy causes, and this raises an interesting conundrum in biodiversity conservation. The question is relatively simple to answer if you have little money, but any reading of the business pages of our newspapers or a walk around the shopping centers of our large cities makes you realize that there are a great many people with more than a little money. What should you do with your excess cash?

Some people (but not all) will want to ‘make a difference’ with their accumulated wealth, at least until medical science can overcome the universal belief that “you can’t take it with you”. Peter Singer (2015) has addressed this question of how to spend your money most effectively when you donate. It comes down in the first instance of your time frame. If you wish to make a difference in the short term of a few years, your choices may differ fundamentally from those taken to make a difference in the long term of 100-500 years. The bulk of philanthropic donations now are in the short-term camp. We have poor people living on the street in most of our cities, people with curable diseases in less developed countries but no medical aid, and victims of wars, earthquakes and tsunamis who must rebuild their lives. So we must start with what I think is the biggest decision regarding philanthropy – do we worry only about people, or do we worry about the biological world as well? Most donations are directly related to improving the human condition, locally or globally.

But there is hope because more and more people are realizing that we cannot separate people from biodiversity because of ecosystem services. Without well-functioning ecosystems on Earth, all the medical advances of our time are for naught. This is an important message to convey to potential donors.

Conservation philanthropy is a curious mix of short term and long term goals. Many endangered species need action now to survive. But ecologists typically look at both the shorter and the longer term goals of conservation. The simplest goal is to set aside land for protection. Without habitat all is lost. But this goal must be paired with long term funding to hire rangers to protect the area from poachers and to monitor the status of the species within the protected zone. Relying on the government to do this by itself is not adequate and never has been. But beyond this primary goal of land protection, the conservation movement fractionates. There are arguments that without effective human population stabilization biodiversity loss must continue. So does this mean that effective donations should be earmarked for agencies that empower women and offer reproductive services? But this points out that we must not fall into the trap of thinking we can do only one thing at a time. Pandas or population – why not “both and”? Climate change is a similar ‘elephant in the room’ problem.

What are the long-term goals of conservation biology that would benefit from philanthropic investment? Start with pest control. Biological control of pests is a long-term issue par excellence (Goldson et al. 2015, Myers et al. 2009, Wyckhuys et al. 2013). But biological control programs are underfunded by governments and obtain little private philanthropy. Weed control, insect pest control, vertebrate pest control all fit in the same problem basket – long term problem supported only by short term funding. Invasive pest eradication on islands is one area of pest control in which both governments and private funding have been joining forces (http://www.islandconservation.org/ ) with good results.

Two other areas of conservation biology that are classically underfunded are taxonomy and monitoring. In many taxonomic groups the majority of the species on Earth are not yet identified and described with a scientific name. The nearest analogy would be having a bank with tons of coins of different sizes and shapes, but only a few of which had any engraving on them. Taxonomy which is so vital to biology suffers because physical scientists consider it “stamp collecting” and unworthy of scientific funding. Monitoring of ecological communities faces the same problem. Monitoring ecological communities is similar to monitoring weather, yet we support meteorological stations around the world but provide little support for ecological monitoring. At present ecological monitoring is done ad hoc by dedicated people but with little systematic organization. Monitoring of changes in the arctic is being coordinated globally (http://www.amap.no/ ) and specific programs have been outlined for example for northern Canada (https://www.ec.gc.ca/faunescience-wildlifescience/, but the funding levels are low considering the size of the areas under consideration. Tropical ecosystem monitoring is even less well funded, yet that is where much of global biodiversity is located (c.f. for example, Cardoso et al. 2011, Burton 2012).

So what can you do about this? Talk up the necessity and the advantages of conservation biodiversity. Imagine what would happen to any of these biodiversity problems if a foundation the size of the Bill & Melinda Gates Foundation devoted a large amount of its donations to conservation. Environmental stewardship is the key to the Earth’s survival, and a combination of problem solving of current biodiversity problems combined with a strong research component on how species interact and ecosystems operate to sustain themselves would be a legacy for future generations and a flagship for the next 100 years.

Burton, A.C. (2012) Critical evaluation of a long-term, locally-based wildlife monitoring program in West Africa. Biodiversity and Conservation, 21, 3079-3094. doi: 10.1007/s10531-012-0355-6

Cardoso, P., Erwin, T.L., Borges, P.A.V. & New, T.R. (2011) The seven impediments in invertebrate conservation and how to overcome them. Biological Conservation, 144, 2647-2655. doi: 10.1016/j.biocon.2011.07.024

Glen, A.S., Atkinson, R., Campbell, K.J., Hagen, E., Holmes, N.D., Keitt, B.S., Parkes, J.P., Saunders, A., Sawyer, J. & Torres, H. (2013) Eradicating multiple invasive species on inhabited islands: the next big step in island restoration? Biological Invasions, 15, 2589-2603. doi: 10.1007/s10530-013-0495-y

Goldson, S.L., Bourdôt, G.W., Brockerhoff, E.G., Byrom, A.E., Clout, M.N., McGlone, M.S., Nelson, W.A., Popay, A.J., Suckling, D.M. & Templeton, M.D. (2015) New Zealand pest management: current and future challenges. Journal of the Royal Society of New Zealand, 45, 31-58. doi: 10.1080/03036758.2014.1000343

Myers, J.H., Jackson, C., Quinn, H., White, S.R. & Cory, J.S. (2009) Successful biological control of diffuse knapweed, Centaurea diffusa, in British Columbia, Canada. Biological Control, 50, 66-72. doi: 10.1016/j.biocontrol.2009.02.008

Singer, P. (2015) The Most Good You Can Do. Yale University Press, New Haven. ISBN: 978-0-300-18027-5

Wyckhuys, K.A.G., Lu, Y., Morales, H., Vazquez, L.L., Legaspi, J.C., Eliopoulos, P.A. & Hernandez, L.M. (2013) Current status and potential of conservation biological control for agriculture in the developing world. Biological Control, 65, 152-167. doi: 10.1016/j.biocontrol.2012.11.010 http://www.islandconservation.org/where-we-work/

 

On Improving Canada’s Scientific Footprint – Breakthroughs versus insights

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In Maclean’s Magazine on November 25, 2015 Professor Lee Smolin of the Perimeter Institute for Theoretical Physics, an adjunct professor of physics at the University of Waterloo, and a member of the Royal Society of Canada, wrote an article “Ten Steps to Make Canada a Leader in Science” (http://www.macleans.ca/politics/ottawa/ten-steps-to-make-canada-a-leader-in-science/ ). Some of the general points in this article are very good but some seem to support the view of science as big business and that leaves ecology and environmental science in the dust. We comment here on a few points of disagreement with Professor Smolin. The quotations are from the Maclean’s article.

  1. Choose carefully.

“Mainly invest in areas of pure science where there is a path to world leadership. This year’s Nobel prize shows that when we do this, we succeed big.” We suggest that the Nobel Prizes are possibly the worst example of scientific achievement that is currently available because of their disregard for the environment. This recommendation is at complete variance to how environmental sciences advance.

  1. Aim for breakthroughs.

“No “me-too” or catch-up science. Don’t hire the student of famous Prof. X at an elite American university just because of the proximity to greatness. Find our own path to great science by recruiting scientists who are forging their own paths to breakthroughs.” But the essence of science has always been replication. Long-term monitoring is a critical part of good ecology, as Henson (2014) points out for oceanographic research. But indeed we agree to the need to recruit excellent young scientists in all areas.

  1. Embrace risk.

“Learn from business that it takes high risk to get high payoff. Don’t waste money doing low-risk, low-payoff science. Treat science like venture capital.” That advice would remove most of the ecologists who obtain NSERC funding. It is one more economic view of science. Besides, most successful businesses are based on hard work, sound financial practices, and insights into the needs of their customers.

  1. Recruit and invest in young leaders-to-be.

“Be savvy and proactive about choosing them…. Resist supporting legacies and entitlements. Don’t waste money on people whose best work is behind them.” We agree. Spending money to fund a limited number of middle aged, white males in the Canadian Excellence in Research Chairs was the antithesis of this recommendation. See the “Folly of Big Science” by Vinay Prasad (2015). Predicting in advance who will be leaders will surely depend on diverse insights and is best evaluated by giving opportunities for success to many from which leaders will arise.

  1. Recruit internationally.

“Use graduate fellowships and postdoctoral positions as recruitment tools to bring the most ambitious and best-educated young scientists to Canada to begin their research here, and then target the most promising of these by creating mechanisms to ensure that their best opportunities to build their careers going forward are here.” This seems attractive but means Canadian scientists have little hope of obtaining jobs here, since we are < 0.1% of the world’s scientists. A better idea – how about Canada producing the “best-educated” young scientists?

  1. Resist incrementalism.

“If you spread new money around widely, little new science gets done. Instead, double-down on strategic fields of research where the progress is clear and Canada can have an impact.“ Fortin and Currie (2013) show that spreading the money around is exactly the way to go since less gets wasted and no one can predict where the “breakthroughs” will happen.  This point also rests on one’s view of the world of the future and what “breakthroughs” will contribute to the sustainability of the earth.

  1. Empower ambitious, risk-taking young scientists.

“Give them independence and the resources they need to develop their own ideas and directions. Postdocs are young leaders with their own ideas and research programs”. This is an excellent recommendation, but it does conflict with the recommendation of many universities around the world of bringing in old scientists to establish institutes and giving incentives for established senior scientists.

  1. Embrace diversity.

“Target women and visible minorities. Let us build a Canadian scientific community that looks like Canada.” All agreed on this one.

  1. Speak the truth.

“Allow no proxies for success, no partial credit for “progress” that leaves unsolved problems unsolved. Don’t count publications or citations, count discoveries that have increased our knowledge about nature. We do research because we don’t know the answer; don’t force us to write grant proposals in which we have to pretend we do.” This confounds the scientists’ code of ethics with the requirements of bureaucracies like NSERC for accounting for the taxpayers’ dollars. Surely publications record the increased knowledge about nature recommended by Professor Smolin.

  1. Consider the way funding agencies do business.

“We scientists know that panels can discourage risk-taking, encourage me-too and catch-up science, and reinforce longstanding entitlements and legacies. Such a system may incentivize low-risk, incremental work and limit the kind of out-of-the-box ideas that….leads to real breakthroughs. So create ambitious programs, empower the program officers to pick out and incubate the brightest and most ambitious risk-takers, and reward them when the scientists they invest in make real discoveries.” What is the evidence that program officers in NSERC or NSF have the vision to pick winners? This is difficult advice for ecologists who are asked for opinions on support for research projects in fields that require long-term studies to produce increases in ecological understanding or better management of biodiversity. It does seem like a recipe for scientific charlatans.

The bottom line: We think that the good ideas in this article are overwhelmed by poor suggestions with regards to ecological research. We come from an ecological world faced with three critical problems that will determine the fate of the Earth – food security, biodiversity loss, and overpopulation. While we all like ‘breakthroughs’ that give us an IPhone 6S or an electric car, few of the discoveries that have increased our knowledge about nature would be considered a breakthrough. So do we say goodbye to taxonomic research, biodiversity monitoring, investigating climate change impacts on Canadian ecosystems, or investing in biological control of pests? Perhaps we can add the provocative word “breakthrough” to our ecological papers and media reports more frequently but our real goal is to acquire greater insights into achieving a sustainable world.

As a footnote to this discussion, Dev (2015) raises the issue of the unsolved major problems in biology. None of them involve environmental or ecological issues.

Dev, S.B. (2015) Unsolved problems in biology—The state of current thinking. Progress in Biophysics and Molecular Biology, 117, 232-239.

Fortin, J.-M. & Currie, D.J. (2013) Big science vs. little science: How scientific impact scales with funding. PLoS ONE, 8, e65263.

Prasad, V. (2015) The folly of big science. New York Times. October 2, 2015 (http://www.nytimes.com/2015/10/03/opinion/the-folly-of-big-science-awards.html?_r=0 )

Henson, S.A. (2014) Slow science: the value of long ocean biogeochemistry records. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 372 (2025). doi: 10.1098/rsta.2013.0334.

 

On Funding for Agricultural Research

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One of the most important problems of our day is the interaction between human population growth and the maintenance of sustainable agriculture in the face of climate change. I am currently sitting at the International Rice Research Institute (IRRI) near Manila where I am told they are responding to a 15-20% reduction in funding for their work. I have found this funding situation to be so ridiculous that I have decided to write this blog. Please stop reading if you think agricultural research already has too much funding, or that climate change and sustainable agriculture are not very important issues in comparison to our need for economic growth and increased wealth.

The critical issues here in Southeast Asia are the increasing human population and the productivity of rice agriculture. IRRI has done and is doing outstanding research to raise production of rice with new varieties and to control pests of rice with clever techniques that minimize the spreading of poisons, which everyone agrees must be minimized to protect agricultural and natural ecosystems. Present research concentrates on the ‘yield gap’, the difference between the actual production from farmer’s fields and the maximum possible yield that can be achieved with the best farm practices. The yield gap can be closed with more research by both social and natural scientists, but that is what is under stress now. IRRI operates with funding from a variety of governments and from private donors. Research funds are now being reduced from many of these sources, and the usual explanation is the faltering global economy combined with the severe refugee problems in the Middle East.

Consequently we now do not have enough money to support the most important research on a crop – rice – that is the essential food of half of the Earth’s human population. And it is not just research on rice that is being reduced, but that on corn, wheat, and any other crop you wish to name. Governments of developed countries like Canada, Australia and the USA are reducing their funding of agricultural research. Anyone who likes to eat might think this is the most ridiculous decision of all because agricultural research is an essential part of poverty reduction in the world and overall human welfare. So I ask a simple question – Why? How is it that you can visit any city in a developed country and see obscene excesses of wealth defined in any way you wish? Yet our governments continue to tell us that we are taxed too much, and we cannot afford more foreign aid, and that if we raised the taxation rate to help the poor of the Earth, our countries would all collapse economically. Yet historically taxes have often been raised during World Wars with general agreement that we needed to do so to achieve society’s goals. The goal now must be poverty reduction and sustainability in agriculture as well as in population. Important efforts are being done on these fronts by many people, but we can and must do more if we wish to leave a suitable Earth for future generations.

At the same time this shortage of funding should not all be laid at the feet of governments. Private wealth continues to increase in the world, and private gifts to research agencies like IRRI and to universities are substantial. But if we believe Piketty (2014), the rich will only get richer in the present economic climate and perhaps the message needs to be sent that donations are long overdue from the wealthy to establish foundations devoted to the problems of sustainability in agriculture, population, and society, as well as the protection of biodiversity. The inactions of people and governments in the past are well documented in books like Diamond (2005). Many scientific papers are mapping and have mapped the way forward to achieve a sustainable society (e.g. Cunningham et al. 2013). To make effective progress we must begin reinvestment in agriculture while not neglecting the human tragedies of our time. It can be both-and rather than either-or.

Cunningham, S.A., et al. (2013) To close the yield-gap while saving biodiversity will require multiple locally relevant strategies. Agriculture, Ecosystems & Environment, 173, 20-27. doi 10.1016/j.agee.2013.04.007

Diamond, J. (2005) Collapse: How Societies Choose to Fail or Succeed. Viking, New York. 575 pp. ISBN: 0670033375

Piketty, T. (2014) Capital in the Twenty-First Century. Belknap Press, Harvard University, Boston. 696 pp. ISBN 9780674430006

The Volkswagen Syndrome and Ecological Science

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We have all been hearing the reports that Volkswagen fixed diesel cars by some engineering trick to show low levels of pollution, while the actual pollution produced on the road is 10-100 times higher than the laboratory predicted pollution levels. I wonder if this is an analogous situation to what we have in ecology when we compare laboratory studies and conclusions to real-world situations.

The push in ecology has always been to simplify the system first by creating models full of assumptions, and then by laboratory experiments that are greatly oversimplified compared with the real world. There are very good reasons to try to do this, since the real world is rather complicated, but I wonder if we should call a partial moratorium on such research by conducting a review of how far we have been led astray by both simple models and simple laboratory population, community and ecosystem studies in microcosms and mesocosms. I can almost hear the screams coming up that of course this is not possible since graduate students must complete a degree in 2 or 3 years, and postdocs must do something in 2 years. If this is our main justification for models and microcosms, that is fair enough but we ought to be explicit about stating that and then evaluate how much we have been misled by such oversimplification.

Let me try to be clear about this problem. It is an empirical question of whether or not studies in laboratory or field microcosms can give us reliable generalizations for much more extensive communities and ecosystems that are not in some sense space limited or time limited. I have a personal view on this question, heavily influenced by studies of small mammal populations in microcosms. But my experience may be atypical of the rest of natural systems, and this is an empirical question, not one on which we can simply state our opinions.

If the world is much more complex than our current understanding of it, we must conclude that an extensive list of climate change papers should be moved to the fiction section of our libraries. If we assume equilibrial dynamics in our communities and ecosystems, we fly in violation of almost all long term studies of populations, communities, and ecosystems. The problem lies in the space and time vision of our science. Our studies are too short to show even a good representation of dynamics over a 100 year time scale, and the problems of landscape ecology highlight that what we see in patch A may be greatly influenced by whether patches B and C are close by or not. We see this darkly in a few small studies but are compelled to believe that such landscape effects are unusual or atypical. This may in fact be the case, but we need much more work to see if it is rare or common. And the broader issue is what use do we as ecologists have for ecological predictions that cannot be tested without data for the next 100 years?

Are all our grand generalizations of ecology falling by the wayside without us noticing it? Prins and Gordon (2014) in their overview seem to feel that the real world is poorly reflected in many of our beloved theories. I think this is a reflection of the Volkswagen Syndrome, of the failure to appreciate that the laboratory in its simplicity is so far removed from real world community and ecosystem dynamics that we ought to start over to build an ecological edifice of generalizations or rules with a strong appreciation of the limited validity of most generalizations until much more research has been done. The complications of the real world can be ignored in the search for simplicity, but one has to do this with the realization that predictions that flow from faulty generalizations can harm our science. We ecologists have very much research yet to do to establish secure generalizations that lead to reliable predictions.

Prins, H.H.T. & Gordon, I.J. (2014) Invasion Biology and Ecological Theory: Insights from a Continent in Transformation. Cambridge University Press, Cambridge. 540 pp. ISBN 9781107035812.

In Praise of Long Term Studies

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I have been fortunate this week to have had a tour of the Konza Prairie Long Term Ecological Research (LTER) site in central Kansas. Kansas State University has run this LTER site for about the last 30 years with support from the National Science Foundation (NSF) of the USA. Whoever set up this program in NSF so many years ago deserves the praise of all ecologists for their foresight, and the staff of KSU who have managed the Konza site should be given our highest congratulations for their research plan and their hard work.

The tall grass prairie used to occupy much of the central part of the temperate zone of North America from Canada to Texas. There is almost none of it left, in Kansas about 1% of the original area with the rest given over to agriculture and grazing. The practical person sees this as progress through the lens of dollar bills, the ecologist sees it as a biodiversity catastrophe. The big questions for the tall-grass prairie are clear and apply to many ecosystems: What keeps this community going? Is it fire or grazing or both in some combination? If fire is too frequent, what are the consequences for the plant community of tall-grass prairie, not to mention the aquatic community of fishes in the streams and rivers? How can shrub and tree encroachment be prevented? All of these questions are under investigation, and the answers are clear in general but uncertain in many details about effects on particular species of birds or forbs.

It strikes me that ecology very much needs more LTER programs. To my knowledge Canada and Australia have nothing like this LTER program that NSF funds. We need to ask why this is, and whether this money could be used much better for other kinds of ecological research. To my mind ecology is unique among the hard sciences in requiring long term studies, and this is because the ecological world is not an equilibrial system in the way we thought 50 years ago. Environments change, species geographical ranges change, climate varies, and all of this on top of the major human impacts on the Earth. So we need to ask questions like why is the tall grass prairie so susceptible to shrub and tree encroachment now when it apparently was not this way 200 years ago? Or why are polar bears now threatened in Hudson’s Bay when they thrived there for the last 1000 or more years? The simple answer is that the ecosystem has changed, but the ecologist wants to know how and why, so that we have some idea if these changes can be managed.

By contrast with ecological systems, physics and chemistry deal with equilibrial systems. So nobody now would investigate whether the laws of gravitation have changed in the last 30 years, and you would be laughed out of the room by physical scientists for even asking such a question and trying to get a research grant to answer this question. Continuous system change is what makes ecology among the most difficult of the hard sciences. Understanding the ecosystem dynamics of the tall-grass prairie might have been simpler 200 years ago, but is now complicated by landscape alteration by agriculture, nitrogen deposition from air pollution, the introduction of weeds from overseas, and the loss of large herbivores like bison.

Long-term studies always lead us back to the question of when we can quit such studies. There are two aspects of this issue. One is scientific, and that question is relatively easy to answer – stop when you find there are no important questions left to pursue. But this means we must have some mental image of what ‘important’ questions are (itself another issue needing continuous discussion). Scientists typically answer this question with their intuition, but not everyone’s intuition is identical. The other aspect leads us into the monitoring question – should we monitor ecosystems? The irony of this question is that we monitor the weather, and we do so because we do not know the future. So the same justification can be made for ecosystem monitoring which should be as much a part of our science as weather monitoring, human health monitoring, or stock market monitoring are to our daily lives. The next level of discussion, once we agree that monitoring is necessary, is how much money should go into ecological monitoring? The current answer in general seems to be only a little, so we stumble on with too few LTER sites and inadequate knowledge of where we are headed, like cars driving at night with weak headlights. We should do better.

A few of the 186 papers listed in the Web of Science since 2010 that include reference to Konza Prairie data:

Raynor, E.J., Joern, A. & Briggs, J.M. (2014) Bison foraging responds to fire frequency in nutritionally heterogeneous grassland. Ecology, 96, 1586-1597. doi: 10.1890/14-2027.1

Sandercock, B.K., Alfaro-Barrios, M., Casey, A.E., Johnson, T.N. & Mong, T.W. (2015) Effects of grazing and prescribed fire on resource selection and nest survival of upland sandpipers in an experimental landscape. Landscape Ecology, 30, 325-337. doi: 10.1007/s10980-014-0133-9

Ungerer, M.C., Weitekamp, C.A., Joern, A., Towne, G. & Briggs, J.M. (2013) Genetic variation and mating success in managed American plains bison. Journal of Heredity, 104, 182-191. doi: 10.1093/jhered/ess095

Veach, A.M., Dodds, W.K. & Skibbe, A. (2014) Fire and grazing influences on rates of riparian woody plant expansion along grassland streams. PLoS ONE, 9, e106922. doi: 10.1371/journal.pone.0106922

On Sequencing the Entire Biosphere

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There is an eternal war going on in science which rests on the simple question of “What should we fund?” If you are at a cocktail party and want to set up a storm of argument you should ask this question. There may be general agreement among many scientists that we should reduce funding on guns and wars and increase funding on alleviating poverty. But then the going gets tough. It is easier to restrict our discussion to science. There is a clear hierarchy in science funding favouring the physical sciences that can make money and the medical sciences that keep us alive until 150 years of age. But now let’s go down to biology.

The major rift in biology is between funding blue sky research and practical research. In the discussions about funding, protagonists often confound these two categories by saying that blue sky research will lead us to practical research and nirvana. We can accept salesmanship to a degree. The current bandwagon in Canada is to barcode all of life on earth, at a cost of perhaps $2 billion but probably much more. Or we can sequence everything we can get our hands on with the implicit promise that it will help us understand these organisms better or solve practical problems in conservation and management. But all of this is driven by what we can do technically, so it is machine driven, not necessarily thought driven. So if you want another heated discussion among ecologists, ask them how they would spend $2 billion for research in ecology.

We sequence because we can. Fifty years ago I heard a lecture by Richard Lewontin in which he asked what we would know if we had a telephone book with all the genetic sequences of all the organisms on earth. He concluded, as I remember, that we would know nothing unless we had a purely ‘genetic-determinism’ view of life. There is more to life than amino acid sequences perhaps.

No one I know thinks that current ecological changes are driven by genetics, but perhaps I do not know the right people. So for example, if we sequence the genomes of all the top predators on earth (Estes et al. 2011, Ripple et al. 2014), would we know anything about their importance in community and ecosystem dynamics? Probably not. But still we are told that if in New Zealand we sequence the common wasp genome we will find new ways to control this insect pest. Perhaps an equally important area would be funding to understand their biology in New Zealand, and the threats and threatening processes in an ecosystem context.

We are back to the starting question about the allocation of resources within biology. Perhaps we cycle endlessly in science funding in search of the Promised Land. In a recent paper Richards (2015) makes the argument that genome sequencing is the key to biology and thus the Promised Land:

“The unifying theme of biology is evolutionary conservation of the gene set and the resultant proteins that make up the biochemical and structural networks of cells and organisms throughout the tree of life.”

“The absence of these genome references is not just slowing research into specific questions; it is precluding a complete description of the molecular underpinnings of biology necessary for a true understanding of life on our planet.” (p. 414)

There seems little room in all this for ecological thought or ecological viewpoints. It is implicit to me that these arguments for genome sequencing have as a background assumption that ecological research is rather useless for achieving biological understanding or for solving any of the problems we currently face in conservation or management. Richards (2015) makes the point himself in saying:

“While the author is fond of ‘stamp collecting’, there are many good reasons to expand the reference sequences that underlie biological research (Table 2).”

The table he refers to in his paper has not a single item on ecological research, except that this approach will achieve “Acceleration of total biological research output”. It remains to be seen whether this view will achieve much more than stamp collecting and a massive confusion of correlation with causation. It requires a great leap of faith that this approach through genome sequencing can help to solve practical ecological problems.

Richards, S. (2015) It’s more than stamp collecting: how genome sequencing can unify biological research. Trends in Genetics, 31, 411-421.

Estes, J.A., et al. (2011) Trophic downgrading of Planet Earth. Science, 333, 301-306.

Ripple, W.J., et al. (2014) Status and ecological effects of the world’s largest carnivores. Science, 343, 1241484.