Author Archives: Charles Krebs

How Do We Decide Controversial Issues in Conservation?

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While almost everyone favours conservation of plants and animals around the globe, it is far from clear how this broad goal can be disarticulated into smaller issues. Once we have done this the solution of the conservation problem should be simple. But it is not (Sutherland et al, 2021). Take an example of the koala in Australia, cute mid-size marsupials that live in trees and eat leaves. If koalas are to be protected, you must protect forests, but if you protect forests the companies that survive by logging on both private and crown land will be adversely affected. We have an immediate conflict, so how do we decide what to do. One response which we can label have-your-cake-and-eat-it-too suggests that we use some of our forests for logging and protect some forests for ecological reserves. Everyone is now happy, but things unravel. As the human population grows, we need more wood, so over time we would have to log more and more of the forested areas that could support koalas. Conflict now, jobs for loggers vs. conservation of koalas. The simplest solution is to decide all this in economic terms. Logging produces much money; conservation is largely a drain on the taxpayers. To propose that conservation should win, ecologists will pull out David Attenborough to show all the beauties of the forest and to point out that the forest contains many other animals and plants and not just trees for lumber. Stalemate, and social and economic goals begin to override the ecological issue until some compromise is suggested and accepted.

While this kind of oversimplified scenario is common, the whole issue of conservation decision making is fraught with problems and who is going to decide these issues (Christie et al. 2022)? In a democracy in the good old days, you took a vote or a poll and decided to win/lose at >50% of the vote. But this cannot work for critical problems. We have a good example of this problem now with Covid vaccination requirements, and a vocal minority opposed to vaccinations. This now spills over into the issue of whether to wear a face mask or not. In all these kinds of scenarios science delivers a simple decision about the consequences of decision A vs decision B, but the problem is that society can refuse to recognize the scientific results or just prefer decision B with little visible justification. Science is not always perfect, adding further complications. And in the case of the covid virus, the virus can mutate in unexpected ways, complicating prognoses. In the case of protected conservation areas, we can suffer fires, floods, insect outbreaks and any number of events that affect the balance of decision making.

There is a large literature on decision making in conservation (e.g., Bower et al. 2018) and even good advice from the field of psychology about this problem of making decisions (Papworth 2017). The best systematic decision tree I have found is that in Sutherland et al. 2021). Sutherland et al. (2021) compiled a framework that can be used profitably in deciding on the level of evidence assessment (see Table 1 and Figure 1 below from their paper).

Table 1 and Figure 1 from Sutherland et al. (2021)

The Strategic Evidence Assessment Framework. Seven levels of evidence assessment, how to apply them.

Assessment LevelApproach UsedGeneral Database ApplicationApproximate Time to reflect on the evidence
1 No consideration of evidenceContinue with existing practice or make decisions without considering scientific evidencenone
2 Assertion but no independent consideration of evidenceConsultation with others (including experts) that affect decision but are not verified e.g. “we normally do this”, “accepted best practice is to do this”minutes
3Papers reviewed, looking at: Read the title and/or summary points to determine whether action described in the paper is likely to be effective or not. Review effectiveness category e.g. “likely to be beneficial” on action page to decide whether action is likely to be effective or notminutes
4 Read abstract to assess the evidence described in the paper in relation to the local problemTens of minutes- hours
5  Read abstract, key results and conclusion assessing each paper in relation to the decision being madeHours
6 Read the full underlying paper/s. This is likely to affect decisions on study quality, relevance and modificationsHours to days
7Comprehensive assessmentA systematic review of all available literature. Assessed papers summarised as part of new reviewMonths to a year

Figure 1. A framework for considering the appropriate level of effort in decision making. Numbers refer to assessment level (Table 1). For a given decision about an action identify the column with the relevant level of consequence, start at the lowest level (1) and decide whether it would benefit from examining higher levels of evidence. Keep moving up until either the uncertainty in the effectiveness of the action is resolved from examining the evidence (from any platform) or the arrows end. This final number is the level at which the evidence assessment should occur. (From Sutherland et al. 2021 with permission).

Clearly conservation ecologists cannot use the highest assessment level for all issues that arise and must result to triage in many cases (Hayward and Castley 2018). But triage and assessment levels 1 and 2 should be rare in making judgement on what program to adopt. We need to get the science right for all conservation problems.

But this is not enough to get thoughtful political decisions. Some native species can be pests, yet nothing is done to reduce their damage (e.g. horses in North America and Australia, camels and goats in Australia, feral pigs in North America) and the list goes on. Nothing is done because of budget limitations or political concerns about “cute species”. The science of conservation is difficult enough, the social science of conservation is too often out of our control.

Bower, S.D., Brownscombe, J.W., Birnie-Gauvin, K. Ford, M.I. et al. (2018). Making Tough Choices: Picking the appropriate conservation decision-making tool. Conservation Letters 11, e12418. doi: 10.1111/conl.12418.

Christie, A.P., Downey, H., Bretagnolle, V., Brick, C., Bulman, C.R., et al. (2022). Principles for the production of evidence-based guidance for conservation actions. Conservation Science and Practice 4, e579. doi: 10.1111/csp2.12663.

Hayward, M.W. and Castley, J.G. (2018). Triage in Conservation. Frontiers in Ecology and Evolution 5, 168. doi: 10.3389/fevo.2017.00168.

Papworth, Sarah (2017). Decision-making psychology can bolster conservation. Nature Ecology & Evolution 1, 1217-1218. doi: 10.1038/s41559-017-0281-9.

Sutherland, W.J., Downey, H., Frick, W.F., Tinsley-Marshall, P., and McPherson, T. (2021). Planning practical evidence-based decision making in conservation within time constraints: the Strategic Evidence Assessment Framework. Journal for Nature Conservation 60, 125975. doi: 10.1016/j.jnc.2021.125975.

What Can You Do About the Climate Emergency?

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It is very easy to do little in the climate emergency because it is a long-term problem, and many of us will be gone by 2050 when Shell Oil and our government promise Net Zero emissions. Possibly the first thing you should do is find out what “net zero” really means. “Net zero emissions” refers to achieving an overall balance between greenhouse gas emissions produced by us and greenhouse gas emissions taken out of the atmosphere. So clearly it does not mean zero emissions so pollution will still be with us, and all it promises is equality between what goes in and what comes out. If you believe that net-zero will happen, you are living in la-la land, but consider it a scientific hypothesis and if you are young and live to 2050, check the numbers. It means that all the greenhouse gases that are here today will remain and all the problems on our doorstep today will continue – floods, fires, drought, sea level rise, agricultural changes, temperature increases – and if you think none of this will bother you, you can probably buy an inexpensive house in New Mexico and avoid shopping for groceries.

But do not throw your hands up since there are many small things all of us can do to minimize these problems. Here is a partial list:

  1. Drive less, fly less, walk more, get an electric car if you can. Try a bicycle.
  2. Avoid coal, gasoline, and natural gas implements. Sit in the sun, not under a propane heater on the deck.
  3. Put solar panels on your roof if you can. In addition to your windmill generating power.
  4. Put your retirement funds into renewable energy funds, not into oil companies.
  5. Educate yourself and ignore all the dangerous nonsense about climate change that is provided in advertisements, radio, TV, and social media.
  6. Protest against climate nonsense by writing letters, using social media, phoning the stations that allow nonsense to be perpetrated. Your one letter may have minimal effect, but if a million people do the same, someone might listen.
  7. Demand that politicians actually answer questions about climate change action plans. And as they say in Chicago, vote early and vote often.
  8. Nominate Greta Thunberg again for the Nobel Prize. If she does not receive it, request that the Nobel Committee be disbanded and replaced by young people.
  9. Relax and enjoy your life while keeping a lid on your carbon budget.

The climate emergency is not difficult to comprehend. Help the world survive it for your grandchildren.

Our World View and Conservation

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Recent events have large implications for conservation science. Behind these events – Covid, climate change, wars – lies a fundamental dichotomy of views about humanity’s place in the world today. At the most basic level there are those who view humans as the end-all-and-be-all of importance so that the remainder of the environment and all other species are far down the list of importance when it comes to decision making. The other view is that humans are the custodians of the Earth and all its ecosystems, so that humans are an important part of our policy decisions but not the only part or even the most important part. Between these extreme views there is not a normal distribution but a strongly bimodal one. We see this very clearly with respect to the climate emergency. If you explain the greenhouse dilemma to anyone, you can see the first reaction is that this does not apply to me, so I can do whatever I want versus the reaction of others that I should do something to reduce this problem now. It is the me-here-and-now view of our lives in contrast to the concern we should have about future generations.

Our hope lies in the expectation that things are improving, strongly in young people, more slowly in older people, and negligibly in our politicians. We must achieve sustainability professed by the Greta Thunberg’s of the world, and yet recognize that the action needed is promised by our policy makers only for 2050 or 2100. There is hope that the captains of industry will move toward sustainability goals, but this will be achieved only by rising public and economic pressure. We are beset by wars that make achieving any sustainability goals more difficult. In Western countries blessed with superabundant wealth we can be easily blinded by promises of the future like electricity from nuclear fusion at little cost, or carbon-capture to remove greenhouse gases from the atmosphere. If things get impossibly bad, we are told we can all go to Mars. Or at least the selected elite can.

Conservation gets lost in this current world, and pleas to set aside 30% or 40% of the Earth for biosphere conservation are rarely even heard about on the evening news. The requests for funds for conservation projects are continually cut when there are more important goals for economic growth. Even research funding through our first-class universities and government laboratories is falling, and I would wager without the data that less than 20% of funding for basic research goes to investigating environmental problems or conservation priorities. In my province in Canada a large section of this year’s budget labelled “Addressing Climate Change” is to be spent on repairing the highways from last year’s floods and trying to restore the large areas affected by fires in the previous dry summer.  

What is the solution to this rather depressing situation? Two things must happen soon. First, we the public must hold the government to account for sustainability. Funding oil companies, building pipelines, building highways through Class A farmland, and waging wars will not bring us closer to having a sustainable earth for our grandchildren. Second, we must encourage private industries and wealthy philanthropists to invest in sustainability research. Conservation cannot ever be achieved without setting aside large, protected areas. The list of species that are in decline around the Earth is growing, yet for the vast number of these we have no clear idea why they are declining or what can be done about it. We need funding for science and action, both in short supply in the world today. And some wisdom thrown in.   

On Rewilding and Conservation

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Rewilding is the latest rage in conservation biology, and it is useful to have a discussion of how it might work and what might go wrong. I am reminded of a comment made many years ago by Buzz Holling at UBC in which he said, “do not take any action that cannot be undone”. The examples are classic – do not introduce rabbits to Australia if you can not reverse the process, do not introduce weasels and stoats to New Zealand if you cannot remove them later if they become pests, do not introduce cheatgrass to western USA grasslands and allow it to become an extremely invasive species. There are too many examples that you can find for every country on Earth. But now we approach the converse problem of re-introducing animals and plants that have gone extinct back into their original geographic range, the original notion of rewilding (Schulte to Bühne et al. 2022).

The first question could be to determine what ‘rewilding’ means, since it is a concept used in so many ways. As a general concept it can be thought of as repairing the Earth from the ravages imposed by humans over the last thousands of years. It appeals to our general belief that things were better in the ‘good old days’ with respect to conservation, and that all we have seen are losses of iconic species and the introduction of pests to new locations. But we need to approach rewilding with the principle that “the devil is in the details”, and the problems are triply difficult because they must engage support from ecologists over the science and the public over policies that affect different social groups like farmers and hunters. Rewilding may range from initiatives that range from “full rewilding” to ‘minimal rewilding’ (Pedersen et al. 2020). Rewilding has been focused to a large extent on large-bodied animals and particularly those species of herbivores and predators that are high in the food chain, typified by the reintroduction of wood bison back into the Yukon after they went extinct about 800 years ago (Boonstra et al. 2018). So the first problem is that the term “rewilding” can mean many different things.

Two major issues must be considered by conservation ecologists before a rewilding project is initiated. First, there should be a comprehensive understanding of the food web of the ecosystem that is to be changed. This is a non-trivial matter in that our understanding of the food webs of what we describe as our best-known ecosystems are woefully incomplete. At best we can do a boxes and arrows diagram without understanding the strength of the connections and the essential nature of many of the known linkages. The second major issue is how rewilding will deal with climate change (Bakker and Svenning, 2018). There is now an extensive literature on paleoecology, particularly in Europe and North America. The changes in climate and species distributions that flowed from the retreat of the glaciers some 10,000 years ago are documented as a reminder to all ecologists that ecosystems and communities are not permanent in time. Rewilding at the present has a time frame with less than necessary thought to future changes in climate. We make the gigantic assumption that we can recreate an ecosystem that existed sometime in the past, and without being very specific about how we might measure success or failure in restoring ecological integrity. 

Pedersen et al. (2020) recognize 5 levels of rewilding of which the simplest is called “minimal rewilding” and the measure of success at this level is the “Potential of animal species to advance self-regulating biodiverse ecosystems” which I suggest to you is an impossible task to achieve in any feasible time frame less than 50-100 years, which is exactly the time scale the IPCC suggests for maximum climatic emergencies. We do not know what a ‘biodiverse ecosystem’ is since we do not know the boundaries of ecosystems under climate change, and we cannot measure what “natural population dynamics” is because we have so few long-term studies. Finally, at the best level for rewilding we cannot measure “natural species interaction networks” without much arm waving.

Where does this leave the empirical conservation ecologist (Hayward et al. 2019)? Rewilding appears to be more a public relations science than an empirical one. Conservation issues are immediate, and a full effort is needed to protect species and diagnose conservation problems of the day. Goshawks are declining in a large part of the boreal forest of North America, and no one knows exactly why. Caribou are a conservation issue of the first order in Canada, and they continue to decline despite good ecological understanding of the causes. The remedy of some conservation dilemmas like the caribou are clear, but the political and economic forces deny their implementation. As conservation biologists we are ever limited by public and governmental policies that favour exploitation of the land and jobs and money as the only things that matter. Simple rewilding on a small scale may be useful, but the losses we face are a whole Earth issue, and we need to address these more with traditional conservation actions and an increase in research to find out why many elements in our natural communities are declining with little or no understanding of the cause.

Bakker, E.S. and Svenning, J.-C. (2018). Trophic rewilding: impact on ecosystems under global change. Philosophical Transaction of the Royal Society B 373, 20170432. doi: 10.1098/rstb.2017.0432.

Boonstra, R., et al. (2018). Impact of rewilding, species introductions and climate change on the structure and function of the Yukon boreal forest ecosystem. Integrative Zoology 13, 123-138. doi: 10.1111/1749-4877.12288.

Hayward, M.W., et al. (2019). Reintroducing rewilding to restoration – Rejecting the search for novelty. Biological Conservation 233, 255-259. doi: 10.1016/j.biocon.2019.03.011.

Pedersen, P.B.M., Ejrnæs, R., Sandel, B., and Svenning, J.-C. (2020). Trophic rewilding advancement in Anthropogenically Impacted Landscapes (TRAAIL): A framework to link conventional conservation management and rewilding. Ambio 49, 231-244. doi: 10.1007/s13280-019-01192-z.

Schulte to Bühne, H., Pettorelli, N., and Hoffmann, M. (2022). The policy consequences of defining rewilding. Ambio 51, 93-102. doi: 10.1007/s13280-021-01560-8.

On Administration and Scientific Progress

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After talking and listening to my colleagues and friends who are still employed, I have the urge to try to quantify the utility of administrative meetings to scientific progress. I begin with a very simple model of what this relationship might look like.

The Neutral Model suggests that scientific progress is independent from the number of meetings that are focused on the scientific problem at hand. This is most likely the preferred model of administrators. The Optimistic Model suggests that scientific progress is positively related to the number of administrative meetings, possibly because the coordination among the members of the scientific team is enhanced. The Pessimistic Model suggests that the reverse is true, and if you as a scientific director wish to slow the progress of your scientific team, you should schedule many meetings all the time, presumably with a long agenda.

It is far from clear which model is appropriate for an ecological scientific team and more research is needed on this topic. Many scientists struggling with measurements and data collection are possibly attracted to the Pessimistic Model because time is the limiting element in their lives and both data and results are what limit progress. On the other hand, scientific administrators are possibly drawn to the Optimistic Model if they believe that meetings are the most important point of scientific progress and time is not the limiting factor, or perhaps they are drawn to the Neutral Model if they assume their scientists will work diligently and achieve the same goals no matter how many meetings are scheduled.

I hesitate to present this model given that the underlying mathematics are relatively simple, plus there are probably more business textbooks that make a detailed analysis of this issue than there are words in this blog. In a more realistic framework, we may have a peaked curve that indicate many meetings early in a project and fewer meetings once things are moving forward smoothly. There is going to be no magic numbers here, and the only purpose of this brief discussion is to think about how much you need to meet to define and deliver a set of objectives for a scientific question.

All my speculations above arose from an old paper (Moss 1978) illustrating these same general principles. Parkinson (1958) framed the law that “Work Expands To Fill The Time Available For Its Completion” and showed one consequence of this was that the fraction of administrators within a public organisation tends to increase irrespective of the amount of external scientific work done by that organisation. Moss (1978) produced these data to illustrate this law for British science data from 1976-77, illustrated in this graph:

Moss (1980) further elaborated on how Parkinson’s Law applied to scientific research organizations and noted that it may apply to many other research organizations. Although it is an old ‘law’ it may still be worth some discussion and consideration today.

Moss, R. (1978). An empirical test of Parkinson’s Law. Nature 273, 184. doi: 10.1038/273184a0.

Moss, R. (1980). Expanding on Parkinson’s Law. Nature 285, 9. doi: 10.1038/285009a0.

On How Genomics will not solve Ecological Problems

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I am responding to this statement in an article in the Conversation by Anne Murgai on April 19, 2022 (https://phys.org/news/2022-04-african-scientists-genes-species.html#google_vignette) : The opening sentence of her article on genomics encapsulates one of the problems of conservation biology today:

“DNA is the blueprint of life. All the information that an organism needs to survive, reproduce, adapt to environments or survive a disease is in its DNA. That is why genomics is so important.”

If this is literally correct, almost all of ecological science should disappear, and our efforts to analyse changes in geographic distributions, abundance, survival and reproductive rates, competition with other organisms, wildlife diseases, conservation of rare species and all things that we discuss in our ecology journals are epiphenomena, and thus our slow progress in sorting out these ecological issues is solely because we have not yet sequenced all our species to find the answers to everything in their DNA.

This is of course not correct, and the statement quoted above is a great exaggeration. But, if it is believed to be correct, it has some important consequences for scientific funding. I will confine my remarks to the fields of conservation and ecology. The first and most important is that belief in this view of genetic determinism is having large effects on where conservation funding is going. Genomics has been a rising star in biological science for the past 2 decades because of technological advances in sequencing DNA. As such, given a fixed budget, it is taking money away from the more traditional approaches to conservation such as setting up protected areas and understanding the demography of declining populations. Hausdorf (2021) explores these conflicting problems in an excellent review, and he concludes that often more cost-effective methods of conservation should be prioritized over genomic analyses. Examples abound of conservation problems that are immediate and typically underfunded (e.g., Turner et al. 2021, Silva et al, 2021).   

What is the resolution of these issues? I can recommend only that those in charge of dispensing funding for conservation science examine the hypotheses being tested and avoid endless funding for descriptive genomics that claim to have a potential and immediate outcome that will forward the main objectives of conservation. Certainly, some genomic projects will fit into this desirable science category, but many will not, and the money should be directed elsewhere.  

The Genomics Paradigm listed above is used in the literature on medicine and social science, and a good critique of this view from a human perspective is given in a review by Feldman and Riskin (2022). Scientists dealing with human breast cancer or schizophrenia show the partial but limited importance of DNA in determining the cause or onset of these complex conditions (e.g., Hilker et al 2018, Manobharathi et al. 2021). Conservation problems are equally complex, and in the climate emergency have a short time frame for action. I suspect that genomics for all its strengths will have only a minor part to play in the resolution of ecological problems and conservation crises in the coming years.

Feldman, Marcus W. and Riskin, Jessica (2022). Why Biology is not Destiny. The New York Review of Books 69 (April 21, 2022), 43-46.

Hausdorf, Bernhard (2021). A holistic perspective on species conservation. Biological Conservation 264, 109375. doi: 10.1016/j.biocon.2021.109375.

Hilker, R., Helenius, D., Fagerlund, B., Skytthe, A., Christensen, K., Werge, T.M., Nordentoft, M., and Glenthøj, B. (2018). Heritability of Schizophrenia and Schizophrenia Spectrum based on the Nationwide Danish Twin Register. Biological Psychiatry 83, 492-498. doi: 10.1016/j.biopsych.2017.08.017.

Manobharathi, V., Kalaiyarasi, D., and Mirunalini, S. (2021). A concise critique on breast cancer: A historical and scientific perspective. Research Journal of Biotechnology 16, 220-230.

Samuel, G. N. and Farsides, B. (2018). Public trust and ‘ethics review’ as a commodity: the case of Genomics England Limited and the UK’s 100,000 genomes project. Medicine, Health Care, and Philosophy 21, 159-168. doi: 10.1007/s11019-017-9810-1.

Silva, F., Kalapothakis, E., Silva, L., and Pelicice, F. (2021). The sum of multiple human stressors and weak management as a threat for migratory fish. Biological Conservation 264, 109392. doi: 10.1016/j.biocon.2021.109392.

Turner, A., Wassens, S., and Heard, G. (2021). Chytrid infection dynamics in frog populations from climatically disparate regions. Biological Conservation 264, 109391. doi: 10.1016/j.biocon.2021.109391.

More on Old Growth Forests and Conservation

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This is a short blog to alert you to a well written plea for saving old growth forests in British Columbia by Karen Price. Karen works with Dave Daust and Rachel Holt, three of our ecological heroes pushing the provincial government to recognize the value of old growth forests. This problem is world-wide but the scientific data alone will not capture the general public as much as this article might.

https://northernbeat.ca/opinion/old-growth-complexity-in-a-sound-bite/

These ecologists have reported their detailed analysis in a report that you can access through the Sierra Club of BC if you want more information on the struggle here in Canada (https://sierraclub.bc.ca/laststand/ ). At present there is nothing but denial from the government and from the industry that there is a problem – the forestry industry is not overharvesting or if it is, we need the jobs. As one person told me, it is not a problem “because we plant one tree seedling for every thousand-year-old tree that we log”.

So please keep up the pressure on governments around the world. Scientists have pushed a strong agenda on sustainable logging for many years with success now looking possible because ordinary citizens demand a change, understanding that forests are more than wood. We must continue the push for sustainable forestry and old growth forest protection.

Lindenmayer, D.B., Kooyman, R.M., Taylor, C., Ward, M., and Watson, J.E.M. (2020). Recent Australian wildfires made worse by logging and associated forest management. Nature Ecology & Evolution 4, 898-900. doi: 10.1038/s41559-020-1195-5.

Price, Karen, Holt, Rachel F., and Daust, Dave (2021). Conflicting portrayals of remaining old growth: the British Columbia case. Canadian Journal of Forest Research 51, 1-11. doi: 10.1139/cjfr-2020-0453.

On Assumptions in Ecology Papers

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What can we do as ecologists to improve the publishing standards of ecology papers? I suggest one simple but bold request. We should require at the end of every published paper a annotated list of the assumptions made in providing the analysis reported in the paper. A tabular format could be devised with columns for the assumption, the perceived support of and tests for the assumption, and references for this support or lack thereof. I can hear the screaming already, so this table could be put in the Supplementary Material which most people do not read. We could add to each paper in the final material where there are statements of who did the writing, who provided the money, and add a reference to this assumptions table in the Supplementary Material or a statement that no assumptions about anything were made to reach these conclusions.

The first response I can detect to this recommendation is that many ecologists will differ in what they state are assumptions to their analysis and conclusions. As an example, in wildlife studies, we commonly make the assumption that an individual animal having a radio collar will behave and survive just like another animal with no collar. In analyses of avian population dynamics, we might commonly assume that our visiting nests does not affect their survival probability. We make many such assumptions about random or non-random sampling. My question then is whether or not there is any value in listing these kinds of assumptions. My response is that this approach of listing what the authors think they are assuming should alert the reviewers to the elephants in the room that have not been listed.

My attention was called to this general issue by the recent paper of Ginzburg and Damuth (2022) in which they contrasted the assumptions of two general theories of functional responses of predators to prey – “prey dependence” versus “ratio dependence”. We have in ecology many such either-or discussions that never seem to end. Consider the long-standing discussion of whether populations can be regulated by factors that are “density dependent” or “density independent”, a much-debated issue that is still with us even though it was incisively analyzed many years ago.  

Experimental ecology is not exempt from assumptions, as outlined in Kimmel et al. (2021) who provide an incisive review of cause and effect in ecological experiments. Pringle and Hutchinson (2020) discuss the failure of assumptions in food web analysis and how these might be resolved with new techniques of analysis. Drake et al. (2021) consider the role of connectivity in arriving at conservation evaluations of patch dynamics, and the importance of demographic contributions to connectivity via dispersal. The key point is that, as ecology progresses, the role of assumptions must be continually questioned in relation to our conclusions about population and community dynamics in relation to conservation and landscape management.

Long ago Peters (1991) wrote an extended critique of how ecology should operate to avoid some of these issues, but his 1991 book is not easily available to students (currently available on Amazon for about $90). To encourage more discussion of these questions from the older to the more current literature, I have copied Peters Chapter 4 to the bottom of my web page at https://www.zoology.ubc.ca/~krebs/books.html for students to download if they wish to discuss these issues in more detail.

Perhaps a possible message in all this has been that ecology has always wished to be “physics-in-miniature” with grand generalizations like the laws we teach in the physical sciences. Over the last 60 years the battle in the ecology literature has been between this model of physics and the view that every population and community differ, and everything is continuing to change under the climate emergency so that we can have little general theory in ecology. There are certainly many current generalizations, but they are relatively useless for a transition from the general to the particular for the development of a predictive science. The consequence is that we now bounce from individual study to individual study, typically starting from different assumptions, with very limited predictability that is empirically testable. And the central issue for ecological science is how can we move from the present fragmentation in our knowledge to a more unified science. Perhaps starting to examine the assumptions of our current publications would be a start in this direction.  

Drake, J., Lambin, X., and Sutherland, C. (2021). The value of considering demographic contributions to connectivity: a review. Ecography 44, 1-18. doi: 10.1111/ecog.05552.

Ginzburg, L.R. and Damuth, J. (2022). The Issue Isn’t Which Model of Consumer Interference Is Right, but Which One Is Least Wrong. Frontiers in Ecology and Evolution 10, 860542. doi: 10.3389/fevo.2022.860542.

Kimmel, K., Dee, L.E., Avolio, M.L., and Ferraro, P.J. (2021). Causal assumptions and causal inference in ecological experiments. Trends in Ecology & Evolution 36, 1141-1152. doi: 10.1016/j.tree.2021.08.008.

Peters, R.H. (1991) ‘A Critique for Ecology.’ (Cambridge University Press: Cambridge, England.) ISBN:0521400171 (Chapter 4 pdf available at https://www.zoology.ubc.ca/~krebs/books.html)

Pringle, R.M. and Hutchinson, M.C. (2020). Resolving Food-Web Structure. Annual Review of Ecology, Evolution, and Systematics 51, 55-80. doi: 10.1146/annurev-ecolsys-110218-024908.

On Research Grant Funding

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All ecologists except for Charles Darwin have had to apply for funding to carry out their research. I am mainly familiar with how this is done in Canada and the United States, with a little experience in Australia. So, depending on where you live, these comments may or may not apply. I would expect the European Union, the United States, and Britain to have the best funding processes since they lead the developed world in research funding. But I stand to be corrected in all this discussion and in my evaluations which are largely focussed on ecological research.

Ecological research is funded largely from government funding and paid for by the taxpayer. There is relatively little private funding available for ecology and this could be because few think ecological science matters to the world, or because private funding goes mainly to medical research. Government funding is pulled in many diverse directions, as anyone who follows the news knows. Governments devoted to exponential growth are wary of ecological work because it does not usually contribute to GDP and ecologists are very wary of exponential growth. But changes in public expectations can influence how governments view environmental work. The continued concern about climate change and a growing interest in biodiversity in general is pushing governments ever so slowly in the direction of environmental science.

But despite this apparent positive trend we are going backwards. The fraction of money going into environmental work is going down once you correct for inflation. The funding of universities is also going down with more student debt so that as the population grows and more jobs in environmental work ought to occur, it is not happening. This situation is most apparent in funding universities for research and for training research students. The amount of money per capita is falling and this leads to two problems in research funding. The first is that governments in general have adopted what I call the “Oxford and Cambridge Paradigm” of research funding. This paradigm in its simple form argues that all the important and innovative research comes from Oxford and Cambridge, or the equivalent universities in your country, and so most of the government research funding must go to these places. But the minor research players in the smaller universities cannot be ignored so they are given a pittance to do some research to keep them quiet. The same strategy can be applied to the funding of graduate students and research assistants. A simple result is that this works well in part but produces clear cases of amazing researchers in a minor university being underfunded while a mediocre researcher at “Oxford” is rolling in money. One consequence of this general pattern is that the major universities reach out and hire the amazing researchers from the smaller universities at a high salary and substantial amounts of funding, so the pattern tends to stabilize rather than evolve into a better system.

The second problem is that competition increases if funding per capita is falling, so that excellent young scientists cannot be employed in their chosen field. The politicians will argue that young people should choose profitable areas in which to study, and perhaps university advisors should tell budding ecologists to go to business schools. Competition rarely leads to useful outcomes in human society, despite the economic gospels we are inundated with. Competition in research can lead to useful liaisons of many scientists working on the same problem, but this happens less frequently than seems desirable. The Holy Grail for competition is the Nobel Prize which goes to one or two scientists in a field despite the common knowledge that they achieved their goals with the help of dozens to hundreds of colleagues.

This problem has not gone unnoticed of course but few provide formal analysis of the details of funding and how funding is dispersed (Aagaard et al. 2020, Scholten et al. 2021). Murray et al. (2016) showed at least for Canada smaller universities were being research funded less well per capita than larger ones, and both Ferreira et al (2016) and De Peuter and Conix (2021) have discussed peer reviews as a major problem in the current funding situation. The problem of bias in review panels is well recognized. If the main objective is to fund excellence, the problem has become more difficult because of social considerations of sexism and racism added to the demand for excellence. This is a minefield I do not wish to enter here.

The existing situation cries out for answers as to how funding decisions are made at both lower and higher levels. In particular as a Canadian example, we might ask why fundamental science total funding in the Canadian Natural Science and Engineering Research Council (NSERC) has not changed since 2007 (https://can-acn.org/science-funding-in-canada-statistics/). The average research grant in Canada in the NSERC Ecology and Evolution Panel was $39K in 2016 and $37K in 2021. Lest we ecologists feel persecuted, in the Canadian Institutes of Health Research (CIHR) funding for basic biomedical research has not changed since 2006. The trends in these numbers are important because someone at the higher levels of making decisions on funding basic science at least in Canada has decided that basic science is not “important”, so that even though we are moving into catastrophic global predictions from climate change and biodiversity loss, basic science funding does not increase in real dollars. I am not sure whether other countries have a similar issue, but the same problem can be seen in many governments in decisions about funding for the basic sciences.

The bottom line is that there are continuing important issues in funding basic science, from biases at the committee level in evaluating individual research grants all the way to the much larger issue of who at the top of the decision pile allocates funds for national and local scientific priorities. If scientific research is about excellence, we have much left to do to achieve appropriate funding in Canada and elsewhere.

Aagaard, K., Kladakis, A., and Nielsen, M.W. (2020). Concentration or dispersal of research funding? Quantitative Science Studies 1, 117-149. doi: 10.1162/qss_a_00002.

De Peuter, S. and Conix, S. (2021). The modified lottery: Formalizing the intrinsic randomness of research funding. Accountability in Research 1-22. doi: 10.1080/08989621.2021.1927727

Ferreira, C. et al. (2016). The evolution of peer review as a basis for scientific publication: directional selection towards a robust discipline? Biological Reviews 91, 597-610. doi: 10.1111/brv.12185

Murray, D.L., Morris, D., Lavoie, C., Leavitt, P.R., and MacIsaac, H. (2016). Bias in research grant evaluation has dire consequences for small universities. PLoS ONE 11, e0155876. doi: 10.1371/journal.pone.0155876.

On Replication in Ecology

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All statistics books recommend replication in scientific studies. I suggest that this recommendation has been carried to extreme in current ecological studies. In approximately 50% of ecological papers I read in our best journals (a biased sample to be sure) the results of the study are not new and have been replicated many times in the past, often in papers not cited in ‘new’ papers. There is no harm in this happening, but it does not lead to progress in our understanding of populations, communities or ecosystems or lead to new ecological theory. We do need replication examining the major ideas in ecology, and this is good. On the other hand, we do not need more and more studies of what we might call ecological truths. An analogy would be to test in 2022 the Flat Earth Hypothesis to examine its predictions. It is time to move on.

There is an extensive literature on hypothesis testing which can be crudely summarized by “Observations of X” which can be explained by hypothesis A, B, or C each of which have unique predictions associated with them. A series of experiments are carried out to test these predictions and the most strongly supported hypothesis, call it B*, is accepted as current knowledge. Explanation B* is useful scientifically only if it leads to a new set of predictions D, E, and F which are then tested. This chain of explanation is never simple. There can be much disagreement which may mean sharpening the hypotheses following from Explanation B*. At the same time there will be some scientists who despite all the accumulated data still accept the Flat Earth Hypothesis. If you think this is nonsense, you have not been reading the news about the Covid epidemic.

Further complications arise from two streams of thought. The first is that the way forward is via simple mathematical models to represent the system. There is much literature on modelling in ecology which is most useful when it is based on good field data, but for too many ecological problems the model is believed more than the data, and the assumptions of the models are not stated or tested. If you think that models lead directly to progress, examine again the Covid modelling situation in the past 2 years. The second stream of thought that complicates ecological science is that of descriptive ecology. Many of the papers in the current literature describe a current set of data or events with no hypothesis in mind. The major offenders are the biodiversity scientists and the ‘measure everything’ scientists. The basis of this approach seems to be that all our data will be of major use in 50, 100 or whatever years, so we must collect major archives of ecological data. Biodiversity is the bandwagon of the present time, and it is a most useful endeavour to classify and categorise species. As such it leads to much natural history that is interesting and important for many non-scientists. And almost everyone would agree that we should protect biodiversity. But while biodiversity studies are a necessary background to ecological studies, they do not lead to progress in the scientific understanding of the ecosphere.

Conservation biology is closely associated with biodiversity science, but it suffers even more from the problems outlined above. Conservation is important for everyone, but the current cascade of papers in conservation biology are too often of little use. We do not need opinion pieces; we need clear thinking and concrete data to solve conservation issues. This is not easy since once a species is endangered there are typically too few of them to study properly. And like the rest of ecological science, funding is so poor that reliable data cannot be achieved, and we are left with more unvalidated indices or opinions on species changes. Climate change puts an enormous kink in any conservation recommendations, but on the other hand serves as a panchrestron, a universal explanation for every possible change that occurs in ecosystems and thus can be used to justify every research agenda, good or poor with spurious correlations.

We could advance our ecological understanding more rapidly by demanding a coherent theoretical framework for all proposed programs of research. Grace (2019) argues that plant ecology has made much progress during the last 80 years, in contrast to the less positive overview of Peters (1991) or my observations outlined above. Prosser (2020) provides a critique for microbial ecology that echoes what Peters argued in 1991. All these divergences of opinion would be worthy of a graduate seminar discussion.

If you think all my observations are nonsense, then you should read the perceptive book by Peters (1991) written 30 years ago on the state of ecological science as well as the insightful evaluation of this book by Grace (2019) and the excellent overview of these questions in Currie (2019).  I suggest that many of the issues Peters (1991) raised are with us in 2022, and his general conclusion that ecology is a weak science rather than a strong one still stands. We should celebrate the increases in ecological understanding that have been achieved, but we could advance the science more rapidly by demanding more rigor in what we publish.

Currie, D.J. (2019). Where Newton might have taken ecology. Global Ecology and Biogeography 28, 18-27. doi: 10.1111/geb.12842.

Grace, John (2019). Has ecology grown up? Plant Ecology & Diversity 12, 387-405. doi: 10.1080/17550874.2019.1638464.

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

Prosser, J.I. (2020). Putting science back into microbial ecology: a question of approach. Philosophical Transactions of the Royal Society. Biological sciences 375, 20190240. doi: 10.1098/rstb.2019.0240.