Author Archives: Charles Krebs

On Progress in Ecology

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We are in ecology continually discussing what progress we are making in answering the central questions of our science. For this reason, it is sometimes interesting to compare our situation with that of economics, the queen of the social sciences, where the same argument also continues. A review by David Graeber (2019) in the New York Review of Books contains some comments about the ‘theoretical war’ in economics that might apply to some ecology subdisciplines. In it he discusses the arguments in social science between two divergent views of economics, that of the school of Keynesians and that of the now dominant Neoclassical School led by Frederich Hayek and later by Milton Friedman and many others of the Chicago School. John Maynard Keynes threw down a challenge illustrated in this quote from Graeber (2019):

“In other words, ‘(Keynes)’ assumed that the ground was always shifting under the analysts’ feet; the object of any social science was inherently unstable. Max Weber, for similar reasons, argued that it would never be possible for social scientists to come up with anything remotely like the laws of physics, because by the time they had come anywhere near to gathering enough information, society itself, and what analysts felt was important to know about it, would have changed so much that the information would be irrelevant. (p. 57)”

Precise quantitative predictions could be provided by simplified economic models, the Chicago School argued in rebutting Keynes. Graeber (2019) comments:

“Surely there’s nothing wrong with creating simplified models. Arguably, this is how any science of human affairs has to proceed. But an empirical science then goes on to test those models against what people actually do, and adjust them accordingly. This is precisely what economists did not do. Instead, they discovered that, if one encased those models in mathematical formulae completely impenetrable to the noninitiate, it would be possible to create a universe in which those premises could never be refuted. (“All actors are engaged in the maximization of utility. What is utility? Whatever it is that an actor appears to be maximizing.”) The mathematical equations allowed economists to plausibly claim theirs was the only branch of social theory that had advanced to anything like a predictive science.  (p. 57)”

In ecology the major divergence between schools of thought promoting progress have never been quite this distinct. Shades of complaint are evident in the writings of Peters (1991) and a burst of comment after that ranged from optimism (e.g. Bibby 2003) to more support for Peter’s critique (Underwood et al. 2000, Graham and Dayton 2002). Interest at this time seems to have waned in favour of very specific topics for review. If you check the Web of Science for the last 5 years for “progress” and “ecology” you will find reviews of root microbes, remote sensing of the carbon cycle, reintroduction of fishes in Canada and a host of very important reviews of small parts of the broad nature of ecology. As Kingsland (2004, 2005) recognized, ecology is an integrating science that brings together data from diverse fields of study. If this is correct, it is not surprising that ecologists differ in answering questions about progress in ecology. We should stick to small specific problems on which we can make detailed studies, measurements, and experiments to increase understanding of the causes of the original problem.

One of the most thoughtful papers on progress in ecology was that of Graham and Dayton (2002) who made an important point about progress in ecology:

“We believe that many consequences of ecological advancement will be obstacles to future progress. Here we briefly discuss just a few: (1) ecological specialization; (2) erasure of history; and (3) expansion of the literature. These problems are interconnected and have the potential to divert researchers and hinder ecological breakthroughs.” (p. 1486)

My question to all ecologists is whether or not we agree with this ‘prediction’ from 2002. There is no question in my judgement that ecology is much more specialized now, that history is erased in spite of search engines like the Web of Science and that the ecology literature is booming so rapidly that it feeds back to ecological specialization. There is no clear solution to these problems. The fact that ecology is integrative has developed into a belief that anyone with a little training in ecological science can call themselves an ecologist and pontificate about the problems of our day. This element of ‘fake news’ is not confined to ecology and we can counter it only by calling out errors propagated by politicians and others who continue to confuse truth in science with their uneducated beliefs.

Bibby, C.J. (2003). Fifty years of Bird Study. Bird Study 50, 194-210. Doi: 10.1080/00063650309461314.

Graham, M.H. and Dayton, P.K. (2002). On the evolution of ecological ideas: paradigms and scientific progress. Ecology 83, 1481-1489. Doi: 10.1890/0012-9658(2002)083[1481:OTEOEI]2.0.CO;2.

Graeber, D. (2019). Against Economics. New York Review of Books 66, 52-58. December 5, 2019.

Kingsland, S. (2004). Conveying the intellectual challenge of ecology: an historical perspective. Frontiers in Ecology and the Environment 2, 367-374. Doi: 10.1890/1540-9295(2004)002[0367:CTICOE]2.0.CO;2.

Kingsland, S.E. (2005) The Evolution of American Ecology, 1890-2000. Johns Hopkins University Press: Baltimore. 313 pp. ISBN 0801881714

Peters, R.H. (1991). A Critique for Ecology. Cambridge University Press: Cambridge, England. 366 pp. ISBN:0521400171

Underwood, A.J., Chapman, M.G., and Connell, S.D. (2000). Observations in ecology: you can’t make progress on processes without understanding the patterns. Journal of Experimental Marine Biology and Ecology 250, 97-115. Doi: 10.1016/S0022-0981(00)00181-7.

On Christmas Holiday Wishes

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We are all supposed to make some wishes over the Holiday Season, no matter what our age or occupation. So, this blog is in that holiday spirit with the constraint that I will write about ecology, rather than the whole world, to keep it short and specific. So, here are my 12 wishes for improving the science of ecology in 2020:

  1. When you start your thesis or study, write down in 50 words or less what is the problem, what are the possible solutions to this problem, and what can we do about it.
  2. Take this statement and convert it to a 7 second sound bite that points out clearly for the person on the street or the head of the Research Council why this is an important use of the foundation’s or taxpayers’ money.
  3. Read the literature that is available on your topic of study even if it was published in the last century.
  4. When writing your report, thesis, or paper on your research, prepare an abstract or summary that follows the old rules of stating clearly WHO, WHAT, WHEN, WHERE, WHY, and HOW. Spend much time on this step, since many of your readers will only be able to read this far. 
  5. Make tables and graphs that are clear and to the point. Define the points or histograms on a graph.
  6. Define all three- and four-letter acronyms. Not everyone will know what RSE or SECR means.
  7. Remember the cardinal rule of data presentation that if your data are an estimate of some value, you should provide the confidence limits or credible intervals of your data.
  8. Above all be truthful and modest in your conclusions. If your evidence points in one direction but is weak, say so. If the support of your evidence is strong, say so. But do not say that this is the first time anyone has ever suggested your conclusions.
  9. In the discussion of your results, give some space to suggesting what limits apply to your conclusions. Do your statements apply only to brown trout, or to all trout, or to all freshwater fish? Are your conclusions limited to one biogeographic zone, or one plant community, or to one small national park?  
  10. The key point at the end of your report should be what next? You or others will take up your challenges, and since you have worked hard and thought much about the ecological problems you have faced, you should be the best person to suggest some future directions for research.
  11. Once your have completed your report or paper, go back and read again all the literature that is available on your topic of study and review it critically.
  12. Finish your report or paper, keeping in mind the old adage, the perfect is the enemy of the good. It is quite impossible in science to be perfect. Better good than perfect.

And as you dive into any kind of biological research, it is useful to read about some of the controversies that you may run into as you write your papers or reports, particularly in the statistical treatment of biological data (Hardwicke and Ioannidis 2019, Ioannidis 2019). The statistical controversy over p-values has been a hot issue for several years and you will likely run into it sooner or later (Ioannidis 2019a, Siontis and Ioannidis 2018). The important point you should remember is that ecologists are scientists and our view of the value of our research work is the antithesis of Shakespeare’s Macbeth:

“Life’s but a walking shadow, a poor player that struts and frets his hour upon the stage, and then is heard no more. It is a tale told by an idiot, full of sound and fury,
signifying nothing.” (Act 5, Scene 5)

This is because our scientific work is valuable for conserving life on Earth, and so it must be carried out to a high and improving standard. It will be there as a contribution to knowledge and available for a long time. It may be useful now, or in one year, or perhaps in 10 or 100 years as an important contribution to solving ecological problems. So, we should strive for the best.

Hardwicke, T.E. and Ioannidis, J.P.A. (2019). Petitions in scientific argumentation: Dissecting the request to retire statistical significance. European Journal of Clinical Investigation 49, e13162.  doi: 10.1111/eci.13162.

Ioannidis, J.P.A. (2019). Options for publishing research without any P-values. European Heart Journal 40, 2555-2556. doi: 10.1093/eurheartj/ehz556.

Ioannidis, J.P.A. (2019a Ioannidis). What have we (not) learnt from millions of scientific papers with P values? American Statistician 73, 20-25. doi: 10.1080/00031305.2018.1447512.

Siontis, K.C. and Ioannidis, J.P.A. (2018). Replication, duplication, and waste in a quarter million systematic reviews and meta-analyses. Circulation: Cardiovascular Quality and Outcomes 11, e005212. doi: 10.1161/CIRCOUTCOMES.118.005212.

On Salmon Hatcheries as an Ecological Paradigm

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The West Coast of North America hosts 5 species of Pacific salmon that are an invaluable fishery resource and at least in theory a resource that is completely sustainable. The management of these fisheries provides a useful case study in how humans currently approach major resources, the mistakes they make, and how attempts to fix mistakes can lead to even further mistakes.

Salmon have been a major resource utilized by the First Nations of the Pacific Coast after the glaciers melted some 10-12,000 years ago. Salmon are anadromous fish, living in the ocean and spawning in fresh water. Their populations fluctuate from year to year but until the 1900s they were essentially considered an inexhaustible resource and thus became a target for exploitation. The buildup of salmon fisheries during the last 100 years coincided with an increase in environmental damage to freshwater spawning grounds. Dams on rivers cut migration routes to spawning grounds, pollution arising from mining, and erosion from forestry and agriculture all began to cut into spawning habitat and subsequently the available catch for the fishery. Salmon catches began to decline and in the late 1800s hatcheries began to be built both to restore fish stocks that were threatened and to increase the abundance of desirable fish like salmon (Naish et al 2007).

The simple model of salmon hatcheries was that the abundance of juvenile fish was the main factor limiting the adult population, so that adding more juveniles to wild juveniles moving out into the ocean would be profitable. This view of the world I call the “Farmer Paradigm” and if you are a dairy farmer with 4 cows that produce X milk, if you add 4 more cows to your farm, you now get 2X milk and thus more profit. But it became apparent with fish hatcheries that adding more juvenile fish did not necessarily increase the resulting fish catch. Some simple reasons might be that more juveniles were eaten by the predators waiting at the mouth of the river or stream, so that predation on juvenile fish was limiting. Alternatively, perhaps the ocean only had a given amount of food for juvenile growth, so that adding too many juveniles induced starvation deaths. Other explanations involving disease transmission could also be invoked.

Whatever the mechanism, it became clear that hatcheries for salmon sometimes worked and sometimes did not work to increase the productivity of the fishery. The Farmer Paradigm had to add a footnote to say “its complicated”. One complication noted early on was the possibility that natural selection in hatcheries was not equivalent to natural selection in wild populations. If hatchery fish were replacing wild fish in any population, the genetic changes involved could work in two directions by either making the entire population more fit or less fit, more productive or less. Much depends on what traits are selected for in hatcheries. In one example for sockeye salmon in Washington State, hatcheries appear to have selected for earlier spawning, so that wild sockeye in one river system return to spawn later than hatchery raised sockeye raised in the same river (Tillotson et al. 2019). Since in general juveniles from early spawners have poorer survival, climate change could favour earlier breeding and thereby reduce the overall productivity of the sockeye population in the river system. We are far from knowing the long-term selection that is occurring in hatcheries, and what it means for future populations of salmon (Cline et al. 2019, Stevenson et al. 2019).

Hatcheries are popular with the public because they indicate the government is doing something to assist fishers and hatcheries should increase and maintain fisheries production for species we love to eat. Consequently, there is a social signal that might be suppressed in data that might suggest a particular hatchery was in fact harming the fishery for a particular river or lake system. If someone wishes to do an economic analysis of the costs and benefits of a hatchery, one runs up against the standard simple belief that more juvenile fish equals higher fishery production. When Amoroso et al. (2017) tried to evaluate for pink salmon in Alaska whether hatcheries were an economic benefit or a loss, their best analysis suggested that recent increases in pink salmon productivity were higher in areas of Alaska with no hatcheries, compared with those with hatcheries. Since different river populations of pink salmon mix in their oceanic phase, it is difficult to obtain a clear experimental signal of hatchery success or failure. The immediate and the longer-term unintended consequences of hatcheries require further study. The assumption that every hatchery is an ecological and social good cannot be presumed.  

Salmon hatcheries are for me an ecological paradigm because they illustrate the management sequence: unlimited abundance → overharvesting → collapse of resource → find a technological fix → misdiagnosed problem → failure of technological fix → better diagnosis of the problem → competing socio-economic objectives → failure to act → collapse of the resource. This need not be the case, and we need to do better (Bendriem et al. 2019).

Amoroso, R.O. et al. (2017). Measuring the net biological impact of fisheries enhancement: Pink salmon hatcheries can increase yield, but with apparent costs to wild populations. Canadian Journal of Fisheries and Aquatic Sciences 74, 1233-1242. doi: 10.1139/cjfas-2016-0334.

Bendriem, N. et al. (2019). A review of the fate of southern British Columbia coho salmon over time. Fisheries Research 218, 10-21. doi: 10.1016/j.fishres.2019.04.002.

Cline, T.J. et al. (2019). Effects of warming climate and competition in the ocean for life-histories of Pacific salmon. Nature Ecology & Evolution 3, 935-942. doi: 10.1038/s41559-019-0901-7.

Naish, K.A. et al. (2007). An evaluation of the effects of conservation and fishery enhancement hatcheries on wild populations of salmon. Advances in Marine Biology 53, 61-194. doi: 10.1016/S0065-2881(07)53002-6.

Stevenson, C.F. et al. (2019). The influence of smolt age on freshwater and early marine behavior and survival of migrating juvenile sockeye salmon. Transactions of the American Fisheries Society 148, 636-651. doi: 10.1002/tafs.10156.

Tillotson, M.D. et al. (2019). Artificial selection on reproductive timing in hatchery salmon drives a phenological shift and potential maladaptation to climate change. Evolutionary Applications 12, 1344-1359. doi: 10.1111/eva.12730.

Do We Need Commissioners for the Environment?

Canada has just gone through an election, the USA will next year, and elections are a recurring news item everywhere. In our Canadian election we were spared any news on the state of the environment, and the dominant theme of the election was jobs, the economy, oil, gas, and a bit on climate change. The simplest theme was climate change, and yes, we are all in favour of stopping it so long as we do not need to do anything about it that would cost money or change our lifestyles. Meanwhile the fires of California and Australia and elsewhere carry on, generating another news cycle of crazy comments about the state of the environment.

Is there a better way? How can we get governments of the world to consider that the environment is worthy of some discussion? There is, and New Zealand has led the way in one direction. New Zealand has a Parliamentary Commissioner for the Environment, an independent Officer of Parliament, whose job it is to provide Members of Parliament with independent advice on matters that may have impacts on the environment. The Office is independent of the government of the day and the Prime Minister, and consequently can “tell it like it is”. A few quotations for the 2019 report give the flavour of this recent New Zealand report:

“If there is one thing that stands out from [our] reports, it is the extent of what we don’t know about what’s going on with our environment.  

“…the blind spots in our environmental reporting system don’t represent conscious choices to collect data or undertake research in some fields rather than others. Rather, they represent the unplanned consequences of a myriad choices over decades. Ours has been a passive system that has harvested whatever data is there and done the best it can to navigate what’s missing.

“In some ways, the most important recommendations in this report are those that relate to the prioritising and gathering of data in a consistent way. Despite attempts over more than two decades, no agreement has ever been reached on a set of core environmental indicators. This has to happen. Consistent and authoritative time series coupled with improved spatial coverage are essential if we are to detect trends. Only then will we be able to judge confidently whether we are making progress or going backwards – and get a handle on whether costly interventions are having an effect.

https://www.pce.parliament.nz/publications/focusing-aotearoa-new-zealand-s-environmental-reporting-system

This report is full of ecological wisdom and would be a useful starting point for many countries. Canada has (to my knowledge) no Environmental Commissioner and although various provinces and cities provide State of the Environment Reports, they are largely based on inadequate data. In some cases, like commercial fisheries, Parliaments or Congress have mandated annual reports, provided the secure funding, and retained independence of the relevant director and staff. In many cases there is far too much bickering between jurisdictions, use of inadequate methods of data collecting, long time periods between sampling, and no indication that the national interest has been taken into account.

Most Western countries have National Academies or Royal Societies which provide some scientific advice, sometimes requested, sometimes not. But these scientific publications are typically on very specific topics like smoking and lung cancer, vaccine protection, or automobile safety requirements. We can see this problem most clearly in the current climate emergency. The Intergovernmental Panel on Climate Change (IPCC) of the United Nations provides excellent reports on the climate emergency but no government is required to listen to their recommendations or to implement them. So, we have local problems, regional problems and global problems, and we need the political structures to address environmental problems at all these levels. New Zealand has provided a way forward, and here is another quote from the 2019 report that ecologists should echo:

Given that many of the environmental problems we face have been decades in the making and that for nearly 30 years we have [made] specific reference to cumulative effects that arise over time…it is astonishing that we have so little data on trends over time.

….it takes time to assemble time series. If we start collecting data today, it may be a decade or more before we can confidently judge whether the issue being monitored is getting better or worse. Every year that we delay the collection of data in an area identified as a significant gap, we commit New Zealand to flying blind in that area. …..A lack of time series in respect of some environmental pressure points could be costing us dearly in terms of poorly designed policies or irreversible damage.

One example may be enough. Caribou herds in southern Canada are threatened with extinction (Hebblewhite 2017, DeMars et al. 2019). Here is one example of counts on one caribou herd in southern Canada:

2009 = 2093 caribou
2012 = 1003
2019 = 185

It would be difficult to manage the conservation of any species of animal or plant that has such limited monitoring data. We can and must do better. We can start by dragging state of the environment reports out of the control of political parties by demanding to have in every country Commissioners of the Environment that are fully funded but independent of political influence. As long as the vision of elected governments is limited to 3 years, environmental decay will continue, out of sight, out of mind.

There is of course no reason that elected governments need follow the advice of any independent commission, so this recommendation is not a panacea for environmental issues. If citizens have independent information however, they can choose to use it and demand action.

DeMars, C.A.et al. (2019). Moose, caribou, and fire: have we got it right yet? Canadian Journal of Zoology 97, 866-879. doi: 10.1139/cjz-2018-0319.

Hebblewhite, M. (2017). Billion dollar boreal woodland caribou and the biodiversity impacts of the global oil and gas industry. Biological Conservation 206, 102-111. doi: 10.1016/j.biocon.2016.12.014.

The Central Predicament of Ecological Science

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Ecology like all the hard sciences aims to find generalizations that are eternally true. Just as physicists assume that the universal law of gravitation will still be valid 10,000 years from now, so do ecologists assume that we can find laws or generalizations for populations and ecosystems that will be valid into the future. But the reality for ecological science is quite different. If the laws of ecology depend on the climate being stable, soil development being ongoing, evolution being optimized, and extinction being slow in human-generation time, we are in serious trouble.

Paleoecology is an important subdiscipline of ecology because, like human history, we need to understand the past. But the generalizations of paleoecology may be of little use to understand the future changes the Earth faces for one major reason – human disturbance of both climate and landscapes. Climates are changing due to rising greenhouse gases that have a long half-life. Land and water are being appropriated by a rising human population that is very slow to stabilize, so natural habitats are continually lost. There is little hope in the absence of an Apocalypse that these forces will alleviate during the next 200 years. Given these changes in the Anthropocene where does ecology sit and what can we do about it?

If climate is a major driver of ecological systems, as Andrewartha and Birch (1954) argued (to the scorn of the Northern Hemisphere ecologists of the time), the rules of the past will not necessarily apply to a future in which climate is changing. Plant succession, that slow and orderly process we now use to predict future communities, will change in speed and direction under the influence of climatic shifts and the introduction of new plant species, plant pests, and diseases that we have little control over. Technological optimists in agriculture and forestry assume that by genetic manipulations and proper artificial selection we can outwit climate change and solve pest problems, and we can only hope that they are successful. Understanding all these changes in slow-moving ecosystems depends on climate models that are accurate in projecting future climate changes. Success to date has been limited because of both questionable biology and poor statistical procedures in climate models (Frank 2019; Kumarathunge et al. 2019; Yates et al. 2018).

If prediction is the key to ecological understanding, as Houlahan et al. (2017) have cogently argued, we are in a quandary if the models that provide predictions wander with time to become less predictive. Yates et al. (2018) have provided an excellent review of the challenges of making good models for ecological prediction. As such their review is either encouraging – ‘here are the challenges in bold type’ – or terribly depressing – ‘where are the long-term, precise data for predictive model evaluation?’ My colleagues and I have spent 47 years trying to provide reliable data on one small part of the boreal forest ecosystem, and the models we have developed to predict changes in this ecosystem are probably still too imprecise to use for management. Additional years of observations produce some ecosystem states that have been predictable but other changes that we have never seen before over this time frame of nearly 50 years.

In contrast to the optimism of Yates et al. (2018), Houlahan et al. (2017) state that:

“Ecology, with a few exceptions, has abandoned prediction and therefore the ability to demonstrate understanding. Here we address how this has inhibited progress in ecology and explore how a renewed focus on prediction would benefit ecologists. The lack of emphasis on prediction has resulted in a discipline that tests qualitative, imprecise hypotheses with little concern for whether the results are generalizable beyond where and when the data were collected.  (page 1)

I see this difference in views as a dilemma because despite much talk, there is little money or interest in the field work that would deliver reliable data for models in order to test their accuracy in predictions at small and large scales. An example this year is the failure of the expected large salmon runs to the British Columbia fishery, with model failure partly due to the lack of monitoring in the North Pacific (https://globalnews.ca/news/5802595/bc-salmon-stocks-plunge/; https://www.citynews1130.com/2019/09/09/worst-year-for-salmon/ , and in contrast with Alaska runs: https://www.adn.com/business-economy/2019/07/25/bristol-bay-sockeye-harvest-blowing-away-forecast-once-again/ ). Whatever the cause of the failure of B.C. salmon runs in 2019, the lack of precision in models of a large commercial fishery that has been studied for at least 65 yeas is not a vote of confidence in our current ecological modelling.

Andrewartha, H.G. and Birch, L.C. (1954) ‘The Distribution and Abundance of Animals.’ University of Chicago Press: Chicago. 782 pp.

Frank, P. (2019). Propagation of error and the reliability of global air temperature projections. Frontiers in Earth Science 7, 223. doi: 10.3389/feart.2019.00223.

Houlahan, J.E., McKinney, S.T., Anderson, T.M., and McGill, B.J. (2017). The priority of prediction in ecological understanding. Oikos 126, 1-7. doi: 10.1111/oik.03726.

Kumarathunge, D.P., Medlyn, B.E., Drake, J.E., Tjoelker, M.G., Aspinwall, M.J., et al. (2019). Acclimation and adaptation components of the temperature dependence of plant photosynthesis at the global scale. New Phytologist 222, 768-784. doi: 10.1111/nph.15668.

Yates, K.L., Bouchet, P.J., Caley, M.J., Mengersen, K., Randin, C.F., Parnell, S., Fielding, A.H., Bamford, A.J., et al. (2018). Outstanding challenges in the transferability of ecological models. Trends in Ecology & Evolution 33, 790-802. doi: 10.1016/j.tree.2018.08.001.

On Planting Trees to Solve the Climate Emergency

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Rising CO2 levels could possibly be stopped by planting lots of trees. In recent months the media have rejoiced in a proposal (The Bonn Challenge) to plant trees on 350 million ha of degraded forest land around the globe by 2030 and thereby stop or greatly slow the global increase in CO2. The Bonn Challenge was first proposed in 2011 at a meeting in Germany and to date 43 countries have made pledges to plant trees to cover about half of the proposed needs, perhaps a total of 1 billion trees. Lewis et al. (2019) recently reported on progress to date in meeting this challenge. The question that a flurry of letters to Nature and other journals have raised is whether this goal is ecologically feasible.

There has always been a cohort of scientists seeking a technological fix to the climate emergency by capturing greenhouse gases or changing the atmosphere. To date all these technological fixes fail the economic test. Can biologists ride to the rescue for the CO2 problem and save the world? Clearly many people as well as politicians are technological optimists who hope that we can continue our lifestyle with little change in the coming decades. No one likes nay-sayers but it is important to hear what problems might arise to achieve a forestry solution to the climate emergency.

Lewis et al. (2019) mapped the land areas potentially available for restoration by planting trees. To achieve the Bonn Challenge most plantings would need to be in tropical and subtropical areas where tree growth is rapid. Bond et al. (2019) concentrated their analysis on Africa where about 1 million km2 have been proposed for restoration with trees. But they point out that much of this proposed area is grassland and savannah which support high value biodiversity. Tanzania we might presume would not be happy if the Serengeti was converted to a closed forest ecosystem. If we proceed with the Bonn Challenge and grasslands and savannahs become closed forests, several unintended consequences would occur. Trees utilize more water to grow and given a fixed rainfall in an area, less water would go into rivers, streams and lakes. Trees also absorb more solar radiation so that the climate in the restored areas would warm, while a main objective of the Bonn Challenge is to reverse global warming.

The list of ecological problems is long. Plantations of monocultures typically capture less CO2 than natural forests on the same land area. Forest fires release large amounts of CO2 from both natural forests and plantations, and rising temperatures are increasing forest losses to fire. Carbon capture estimates depend critically on turnaround times which depend on tree growth rates and the uses to which wood is put after a tree is harvested. Smith et al. (2015) concluded in an earlier analysis that afforestation could not achieve the goal of limiting global warming below 2ºC.

All these problems should not stop the reforestation of closed forest areas that were degraded in historical time, as Bond et al. (2019) have pointed out. But unfortunately, this news that we cannot reverse climatic warming by planting large numbers of trees continues the negativity that bedevils the science of ecology – you cannot achieve this goal given the ecological constraints of the Earth. Politicians and the public at large do not want to hear these messages and prefer the belief that technology will come up with a simple inexpensive solution. To shout that “this will not work” is not a way to become popular.

We appear not to have progressed from what David Schindler said 22 years ago:

“Humans, including ecologists, have a peculiar fascination with attempting to correct one ecological mistake with another, rather than removing the source of the problem.”
                  (Schindler 1997, pg.4).

Bond, W.J., et al. (2019). The Trouble with Trees: Afforestation Plans for Africa. Trends in Ecology & Evolution (in press). doi: 10.1016/j.tree.2019.08.003.

Lewis, S.L., et al. (2019). Regenerate natural forests to store carbon. Nature 568, 25-28 (4 April 2019). doi: 10.1038/d41586-019-01026-8.

Schindler D.W. (1997). Liming to restore acidified lakes and streams: a typical approach to restoring damaged ecosystems? Restoration Ecology 5, 1-6. doi: 10.1046/j.1526-100X.1997.09701.x.

Smith, P. et al. (2016). Biophysical and economic limits to negative CO2 emissions. Nature Climate Change 6, 42-50 (January 2016). doi: 10.1038/nclimate2870.

On Random Sampling and Generalization in Ecology

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Virtually every introduction to statistics book makes the point that random sampling is a critical assumption that underlies all statistical inferences. It is assumption #1 of statistical inference and it carries with it an often-hidden assumption that in trying to make your inference, you have clearly defined what the statistical population is that you are sampling. Defining the ‘population’ under consideration should perhaps be rule # 1, but that is usually left as a vague understanding in many statistical studies. As an exercise consult a series of papers on ecological field studies and see if you can find a clear statement of what the ‘population’ under consideration is. An excellent example of this kind of analysis is given by Ioannidis (2003, 2005).

The problem of random sampling does not occur in theoretical statistics and all effort is concentrated on mathematical correctness. This is illustrated well in the polls we are subjected to on political or social issues, and in the medical studies that we hear about daily. The social sciences have considered sampling for polls in much more detail that have biologists. In a historical overview (Lusinchi 2017) provides an interesting and useful analysis of how pollsters have over the years bent the science of statistical inference to their methods of polling to provide an unending flow of conclusions about who will be elected, or which coffee is better tasting. By confounding sample size with an approach to Truth and ignoring the problem of random sampling, the public has been brainwashed to believe what should be properly labeled as ‘fake news’.

What has all of this got to do with the science of ecology? Much of the data we accumulate is uncertain when we ask what is the ‘population’ to which it applies. If you are concerned about the ecology of sharks, you face the problem that most species of shark have never been studied (Ducatez 2019). If you are interested in fish populations, for example, you may find that the fish you catch with hooks are not a random sample of the fish population (Lennox et al. 2017). If you are studying the trees in a large woodlot, that may be your universe for statistical purposes. Interest then shifts to the question of how much you will generalize to other woodlots over what geographical space, a question too rarely discussed in data papers. In an ideal world we would sample several woodlots randomly selected from a larger sample of similar woodlots, so that we could infer processes that were common to woodlots in general.

There are a couple of problems that confound ecologists at this point. No series of woodlots or study sites in general are identical, so we assume they are a collective of ‘very similar’ woodlots about which we could make an inference. Alternatively, we can simply state that we wish to make inferences about only this single woodlot, it is our total population. At this point your supervisor/boss will say that he or she is not interested only in this one woodlot but much more general conclusions, so you will be cut from research funding for having too narrow an interest.

The solution is in general to study one ‘woodlot’ and then generalize to all ‘woodlots’ with no further study on your part, so that it will be up to the next generation to find out if your generalization is right or wrong. While this way of proceeding will perhaps not matter to people interested in ‘woodlots’, it might well matter greatly if your ‘population of interest’ was composed of humans considering a drug for disease treatment. We are further confounded in this era of climate change in dealing with changing ecosystems, so that a study in 2000 about coral reef fish communities could be completely different if it were repeated in 2040 as oceans warm.

Back to random sampling. I would propose that random sampling in ecological systems is impossible and cannot be achieved in a global sense. Be concerned about local processes and sample accordingly. Descriptive ecology must come to the rescue here, so that we know as background information (for example) that trees grow slower as they age, that tree growth varies from year to year, that insect attacks vary with summer temperature, and so on, and sample accordingly following your favourite statistician. There are many very useful statistical techniques and sampling designs you can use as an ecologist to achieve random sampling on a local scale, and statisticians are most useful to consult to validate the design of your field studies.

But it is important to remember that your results and conclusions even though carried out with a perfect statistical design cannot ensure that your generalizations are correct in time or in space. The use of meta-analysis can assist in validating generalizations when enough replicated studies are available, but there are problems even with this approach (Siontis and Ioannidis 2018). Continued discussion of p-values in ecology could benefit much from similar discussions in medicine where funding is higher, and replication is more common (Ioannidis 2019b; Ioannidis 2019a).

All these statistical issues provide a strong argument as to why ecological field studies and experiments should never stop, and all our studies and conclusions are temporary signposts along a path that is never ending.

Ducatez, S. (2019). Which sharks attract research? Analyses of the distribution of research effort in sharks reveal significant non-random knowledge biases. Reviews in Fish Biology and Fisheries 29, 355-367. doi: 10.1007/s11160-019-09556-0.

Ioannidis, J.P.A. (2005). Contradicted and initially stronger effects in highly cited clinical research. Journal of the American Medical Association 294, 218-228. doi: 10.1001/jama.294.2.218.

Ioannidis, J.P.A. (2005). Why most published research findings are false. PLOS Medicine 2, e124. doi: 10.1371/journal.pmed.0020124.

Ioannidis, J.P.A. (2019a). What have we (not) learnt from millions of scientific papers with p values? American Statistician 73, 20-25. doi: 10.1080/00031305.2018.1447512.

Ioannidis, J.P.A. (2019b). The importance of predefined rules and prespecified statistical analyses: do not abandon significance. Journal of the American Medical Association 321, 2067-2068. doi: 10.1001/jama.2019.4582.

Lennox, R.J., et al. (2017). What makes fish vulnerable to capture by hooks? A conceptual framework and a review of key determinants. Fish and Fisheries 18, 986-1010. doi: 10.1111/faf.12219.

Lusinchi, D. (2017). The rhetorical use of random sampling: crafting and communicating the public image of polls as a science (1935-1948). Journal of the History of the Behavioral Sciences 53, 113-132. doi: 10.1002/jhbs.21836.

Siontis, K.C. and Ioannidis, J.P.A. (2018). Replication, duplication, and waste in a quarter million systematic reviews and meta-analyses. Circulation Cardiovascular Quality and Outcomes 11, e005212. doi: 10.1161/circoutcomes.118.005212.

Thoughts on Wildlife Management

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Stop for a moment and think about where we are now in the science of wildlife management and conservation. Look at the titles of paper in our scientific journals. The vast majority of the problems and questions being investigated are basically about how to reverse some human-caused folly. Many wildlife scientists, ecologists, and organismal biologists entered science with the goal of understanding natural systems from the ecosystem down to the molecular level but in the past 60 years the focus has had to shift. This shift has occurred almost unnoticed because it has been gradual in the time scale of human employment and turnover. The ecosystems of the world are in a frightful mess, and virtually all the mess is human caused. So while we engage in many discussions about how to define the ‘Anthropocene’ in the geological sciences (Correia et al. 2018; Zalasiewicz et al. 2017) ecological science is left in the dust because it never leads to ‘progress’.

This came home to me when I considered which of the many study sites in which classical ecological research has been carried out over the last century still exist. They have been replaced by suburbs, highways, shopping malls, farms, and industrial sites, and the associated waterways have been altered beyond recognition. A simple consequence is that if you wished to repeat a famous ecological study done 50-100 years ago, you could not do it because the site has been obliterated. One consequence is that if we wish to do field work today, we choose a new site that has so far been protected from development.

The elephant in the room now is climate change, so if you choose to investigate the trophic dynamics of an Amazonian forest area (for example), you face two problems – the site could be obliterated by ‘development’ before your work is completed, or the climate changes expected during the next 80 years will alter the trophic dynamics of your site so that your current results are no guide to the future state of these ecosystems. Whither predictive ecology? Many of us thought that by discovering and analyzing ecological principles, we could closely approach the precision of the physical sciences, the laws of physics and chemistry. But the more we search for generality in ecology the less we find. We retreat to general principles that are too vague to be of any predictive use for the wildlife managers of the future.

The thought has been prevalent that by investigating the changes in communities and ecosystems in the past we would have a guide to the future. This belief guides much of paleo-ecological research as well as the projections from evolutionary research of how species have recovered from the recent ice ages. But the past is perhaps not necessarily a good guide to the future when we add in the human footprint arising from the combination of population growth and climate change. Ecologists are left with the concern that our findings have much current value but perhaps little long-term insight. 

Many current papers on ecological changes assume a simple extrapolation predicting the future state of ecosystems (e.g. Martin et al. 2019; Yu et al. 2019). Testing these kinds of extrapolations is virtually possible within the lifetime of the typical ecologist, and my concern is that management actions that are recommended now may be completely off the mark in 30 years. Several papers have warned about this (e.g. Inkpen 2017; La Marca et al. 2019; Mouquet et al. 2015) but as far as I can determine to little effect.

I think the bottom line might be a recommendation for all predictive papers to state a strong prediction and a defined time frame so that there is hope of testing the predictive model in ecological time. Otherwise we ecologists begin to fall into the realm of science fiction.

Correia, R.A. et al. (2018). Pivotal 20th century contributions to the development of the Anthropocene concept: overview and implications. Current Science 115, 1871-1875. doi: 10.18520/cs/v115/i10/1871-1875.

Inkpen, S.A. (2017). Are humans disturbing conditions in ecology? Biology & Philosophy 32, 51-71. doi: 10.1007/s10539-016-9537-z.

La Marca, W. et al. (2019). The influence of data source and species distribution modelling method on spatial conservation priorities. Diversity & Distributions 25, 1060-1073. doi: 10.1111/ddi.12924.

Martin, D. et al. (2019). Long-distance influence of the Rhône River plume on the marine benthic ecosystem: Integrating descriptive ecology and predictive modelling. Science of The Total Environment 673, 790-809. doi: 10.1016/j.scitotenv.2019.04.010.

Mouquet, N. et al. (2015). Predictive ecology in a changing world. Journal of Applied Ecology 52, 1293-1310. doi: 10.1111/1365-2664.12482.

Yu, F., et al. (2019). Climate and land use changes will degrade the distribution of Rhododendrons in China. Science of The Total Environment 659, 515-528. doi: 10.1016/j.scitotenv.2018.12.223.

Zalasiewicz, J. et al. (2017). The Working Group on the Anthropocene: Summary of evidence and interim recommendations. Anthropocene 19, 55-60. doi: 10.1016/j.ancene.2017.09.001.

How Big an Area is Big Enough for Conservation?

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The larger the species, the more likely it is to be a species of conservation concern. Like many principles of conservation biology, this statement is a generalization with many exceptions. Often it has to be coupled with a statement of the geographic range size of the species of concern and the disturbances wrought by humans within this geographic range. And on top of these ecological issues, there are genetic concerns about population viability. The net result of all these issues is that conservation tends to focus on single species and to minimize the need to understand community and ecosystem dynamics. There is a limit on what we can achieve with limited funding and person-power. The public consensus at this time seems to be that we are losing the battle, that biodiversity is being lost on a global scale, even though we are winning the battle for some charismatic species (e.g. waterfowl, Anderson et al. 2018).

The scale issue is what has continued to defeat us. Take any group of species from your local area and try to determine what size of national park or protected area would be required for that group to survive for your great-grandchildren. No one knows the answer to this simple question, except for the negative finding that at present no protected area is large enough to prevent serious biodiversity loss of a 50-year time scale, no matter what its size.

One escape from this loss of biodiversity has been to call for establishing larger protected areas for conservation, and it leads directly into the critical question of how big a protected area is needed. This question can be analyzed at the level of the single species or an entire ecosystem, but the result is always the same – however big the protected area, it is not big enough. The only answer ecologists have to this challenge is to set up protected areas as large as is politically possible and then monitor them to see how they perform. The skeptic claims immediately that climate collapse will render the selected large protected areas unsuitable for many of the area’s fauna and flora as time progresses.

We cannot at present answer the simple question how big is big enough? The result of all this uncertainly is that we must set boundaries to our conservation goals, and that these will have to be on a local scale. We need to define a time limit for achieving our goals, perhaps 50 years is one we could cope with, and we need to monitor a defined subset of species so that we can track the resilience of the system under study over time and be able to use some feasible management tools if species are in long-term decline. Some national parks are now able to set these goals and keep track of how ecosystems are changing but in a majority of cases we do not have the monitoring data to define success or failure. This problem is not new (Newmark 1985, 1995).

Meanwhile we search for alternative approaches. In some cases, corridors between small protected areas are helpful, and in other cases fenced areas are sufficient for protecting threatened species, particularly when introduced predators are the major problem (Legge et al. 2018). More elaborate approaches must take account of climate change on protected areas (e.g. Rilov et al. 2019). Methods are being developed to deal with mosaic ecosystems in which conservation reserves are embedded in agricultural landscapes (Nowack et al. 2019). The conflict always remains whether to aim conservation at specific taxa or to try to maximize the number of species retained.

These issues of how big are most readily solvable in areas like northern Canada or Alaska, Russia, and in marine environments that are still relatively lightly used for human activities. Analyses of particular groups of taxa (e.g. trees, Médail et al. 2019) can also be usefully evaluated for conservation purposes for relatively large landscapes. The question of how big is big enough will continue to an important one for continuing efforts in conservation.

The assumption we should question is what size of area will protect the small species of insects and plants. It often seems to be assumed that our existing parks are too small for the larger species of the fauna and flora but are sufficiently large for small insects and plants. One should doubt that this simple principle is correct.

The related question of how long is long enough (for monitoring) is much simpler to deal with because in principle there should be no limit. In practice this limit is set by money and person-power, and in the end these decisions will rest on how much the world’s leaders are concerned about the loss of biodiversity. If the value of a species is directly related to its size, much could be lost with little public concern, and these questions of how big and how long will be “academic” in the worst sense of this word.

Anderson, M.G., et al. (2018) The migratory bird treaty and a century of waterfowl conservation. Journal of Wildlife Management, 82, 247-259. doi: 10.1002/jwmg.21326

Hewson, C.M., et al. (2018) Estimating national population sizes: Methodological challenges and applications illustrated in the common nightingale, a declining songbird in the UK. Journal of Applied Ecology, 55, 2008-2018. doi: 10.1111/1365-2664.13120

Legge, S., et al. (2018) Havens for threatened Australian mammals: the contributions of fenced areas and offshore islands to the protection of mammal species susceptible to introduced predators. Wildlife Research, 45, 627-644. doi: 10.1071/WR17172

Mason, C., et al. (2018) Telemetry reveals existing marine protected areas are worse than random for protecting the foraging habitat of threatened shy albatross (Thalassarche cauta). Diversity & Distributions, 24, 1744-1755. doi: 10.1111/ddi.12830

Médail, F., et al. (2019) What is a tree in the Mediterranean Basin hotspot? A critical analysis. Forest ecosystems, 6, 17. doi: 10.1186/s40663-019-0170-6

Newmark, W.D. (1985) Legal and biotic boundaries of Western North American National Parks: A problem of congruence. Biological Conservation, 33, 197-208. doi: 10.1016/0006-3207(85)90013-8

Newmark, W.D. (1995) Extinction of mammal populations in Western North American national parks. Conservation Biology, 9, 512-526. doi: 10.1046/j.1523-1739.1995.09030512.x

Nowack, S., Bauch, C.T. & Anand, M. (2019) A local optimization framework for addressing conservation conflicts in mosaic ecosystems. PLoS ONE, 14, e0217812. doi: 10.1371/journal.pone.0217812

Rilov, G., et al. (2019) Adaptive marine conservation planning in the face of climate change: What can we learn from physiological, ecological and genetic studies? Global Ecology and Conservation, 17, e00566. doi: 10.1016/j.gecco.2019.e00566

Big Science – Poor Data?

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The big global problems of our time are climate change, human population growth, and migration. From these emerge all the others that worry us from inequality leading to poverty, regional wars, emerging diseases, and biodiversity loss. As ecologists we typically worry about climate change and biodiversity loss. We can do little directly about climate change except to change our life style and replace our do-nothing-politicians. We can have some effect on biodiversity conservation, a subject of later discussions. But the elephant in the room is always climate change, and Bill McKibben (2019) has presented us with a synopsis of a positive evaluation from the viewpoint of fossil fuels and is currently bringing out a book on these issues (McKibben 2019a).

There is much discussion of these articles in reviews such as Diamond (2019) and in the social media. The negative concerns for the future have in recent years been getting more press than the positive possibilities and these negative views may cause the public to give up and say all efforts are hopeless. But these three references from McKibben and Diamond push the possibility of a positive outcome, premised partly on the growing concern of humans to the effects of climate change and the emerging technologies in energy capture that do not depend on oil and gas. I do not wish to question these statements but rather to raise the question of where ecological scientists should fit into this picture.

If natural capital is in decline and some to many species are at risk of extinction, what should be the reaction of a young ecologist just starting their ecological career? I can see two extreme responses to the current situation. One I will call the Carry-on-Regardless approach, and the other the Mad Panic approach. The Carry-on Regardless approach believes that we as one or a few scientists have little ability to change the global paradigm of environmental destruction. Certainly, we will use our own efforts to educate and give good environmental example to all we encounter. But as a scientist the most important achievement one can make is to do good ecological science, to understand in some small way how populations and communities of organisms interact and sustain themselves at the present time. In this way we can hopefully solve some immediate practical problems but more importantly collect some critical data for the next generations of ecologists to use in understanding the changes that will go on during the next several centuries. In a simple manner, future ecologists will be able to say, ‘so this is how system X was working in 2020”. We have no way to know now how much our hard-earned knowledge will be useful to our great-grandchildren, but we press on in the hope that it will be of some help in understanding the trace of the human footprint down the ages.

The Mad Panic approach at the other extreme argues that you should stop all the research that you are doing and become an advocate to try to convince the world to change course and prevent disaster. There is no time to do research, we ought to be out there shouting from the rooftops. If you wish to work at the research end of this school of thought you should perhaps be looking for an ecological disaster (e.g. plastics in the ocean) that you can investigate to beat politicians over the head about how we must change now to prevent further disaster. There is certainly a need for this sort of action.

The problem is how to advise ecologists starting their careers. There is no simple answer, and some are better at the first approach and others at the second. The key point is that we need both, and my concern (being a Carry-on phenotype) is that we need to have clear and precise data of how the planet is changing as a prerequisite for the second approach. We do not have this now except for a few species in a few locations. We have very little long-term data on biodiversity, and we only kid ourselves if we decide that a 3-year study can be classified as a long-term study, or that a list of species in a given area tells us something about ecosystem function. Consider how long it has taken to show clear trends in climate data, or in a more news-worthy area how little economic understanding has emerged from all the detailed minute-by-minute data on the stock market over the last 70 years.

So, we end up with big questions and poor data, and somehow hope that we can model the future changes in the world’s ecosystems to give the public guidance. To achieve this goal, we need more Carry-on Regardless ecologists doing good work and fewer, less strident Mad Panic environmentalists. Environmental warning bells are certainly going off, and we should listen to them and try to gather the data necessary to understand what is happening and how good management might counter negative environmental trends. It is good to be optimistic, but we must couple our optimism with strong ecological studies to understand how communities and ecosystems function. And we are a long way from having enough of these basic studies to be confident of future projections to guide the next generations.

Diamond, Jared. 2019. Striking a balance between fear and hope on climate change. New York Times, 15 April 2019.

McKibben, Bill. 2019. A Future Without Fossil Fuels? New York Review of Books, April 4, 2019, pp.

McKibben, Bill. 2019a. Falter: Has the Hunan Game Begun to Play Itself Out? Henry Holt and Company, 291 pp. ISBN:13: 9781250178268