Tag Archives: progress in ecology

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.

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.

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 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.

On the Canadian Biodiversity Observation Network (CAN BON)

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I have been reading the report of an exploratory workshop from July 2021 on designing a biodiversity monitoring network across Canada to address priority monitoring gaps and engage Indigenous people across Canada. The 34 pages of their workshop report can be accessed here, and I recommend you might read it before reading my comments on the report:

https://www.nserc-crsng.gc.ca/Media-Media/NewsDetail-DetailNouvelles_eng.asp?ID=1310

I have a few comments on this report that are my opinion only. I think the Report on this workshop outlines a plan so grand and misguided that it could not be achieved in this century, even with a military budget. The report is a statement of wisdom put together with platitudes. Why is this and what are the details that I believe to be unachievable?

The major goal of the proposed network is to bring together everyone to improve biodiversity monitoring and address the highest priority gaps to support biodiversity conservation. I think most of the people of Canada would support these objectives, but what does it mean? Let us do a thought experiment. Suppose at this instant in time we knew the distribution and the exact abundance of every species in Canada. What would we know, what could we manage, what good would all these data be except as a list taking up terabytes of data? If we had these data for several years and the numbers or biomass were changing, what could we do? Is all well in our ecosystems or not? What are we trying to maximize when we have no idea of the mechanisms of change? Contrast these concerns about biodiversity with the energy and resources applied in medicine to the mortality of humans infected with Covid viruses in the last 3 years. A monumental effort to examine the mechanisms of infection and ways of preventing illness, with a clear goal and clear measures of progress toward that goal.

There is no difficulty in putting out “dream” reports, and biologists as well as physicists and astronomers, and social scientists have been doing this for years. But in my opinion this report is a dream too far and I give you a few reasons why.

First, we have no clear definition of biodiversity except that it includes everything living, so if we are going to monitor biodiversity what exactly should we do? For some of us monitoring caribou and wolves would be a sufficient program, or whales in the arctic, or plant species in peat bogs. So, to begin with we have to say what operationally we would define as the biodiversity we wish to monitor. We could put all our energy into a single group of species like birds and claim that these are the signal species to monitor for ecosystem integrity. Or should we consider only the COSEWIC list of Threatened or Endangered Species in Canada as our major monitoring concern? So, the first job of CAN BON must be to make a list of what the observation network is supposed to observe (Lindenmayer 2018). There is absolutely no agreement on that simple question within Canada now, and without it we cannot move forward to make an effective network.

The second issue that I take with the existing report is that the emphasis is on observations, and then the question is what problems will be solved by observation alone. The advance of ecological science has been based on observation and experiment directed to specific questions either of ecological interest or of economic interest. In the Pacific salmon fishery for example the objective of observation is to predict escapement and thus allowable harvest quotas. Despite years of high-quality observations and experiments, we are still a long way from understanding the ecosystem dynamics that drive Pacific salmon reproduction and survival.

Contrast the salmon problem with the caribou problem. We have a reasonably good understanding of why caribou populations are declining or not, based on many studies of predator-prey dynamics, harvesting, and habitat management. At present the southern populations of caribou are disappearing because of a loss of habitat because of land use for forestry and mining, and the interacting nexus of factors is well understood. What we do not do as a society is put these ideas into practice for conservation; for example, forestry must have priority over land use for economic reasons and the caribou populations at risk suffer. Once ecological knowledge is well defined, it does not lead automatically to action that biodiversity scientists would like. Climate change is the elephant in the room for many of our ecological problems but it is simultaneously easy to blame and yet uneven in its effects.

The third problem is funding, and this overwhelms the objectives of the Network. Ecological funding in general in Canada is a disgrace, yet we achieve much with little money. If this ever changes it will require major public input and changed governmental objectives, neither is under our immediate control. One way to press this objective forward is to produce a list of the most serious biodiversity problems facing Canada now along with suggestions for their resolution. There is no simple way to develop this list. A by-product of the current funding system in Canada is the shelling out of peanuts in funding to a wide range of investigators whose main job becomes how to jockey for the limited funds by overpromising results. Coordination is rare partly because funding is low. So (for example) I can work only on the tree ecology of the boreal forest because I am not able to expand my studies to include the shrubs, the ground vegetation, the herbivores, and the insect pests, not to mention the moose and the caribou.  

For these reasons and many more that could be addressed from the CAN BON report, I would suggest that to proceed further here is a plan:

  1. Make a list of the 10 or 15 most important questions for biodiversity science in Canada. This alone would be a major achievement.
  2. Establish subgroups organized around each of these questions who can then self-organize to discuss plans for observations and experiments designed to answer the question. Vague objectives are not sufficient. An established measure of progress is essential.
  3. Request a realistic budget and a time frame for achieving these goals from each group.  Find out what the physicists, astronomers, and medical programs deem to be suitable budgets for achieving their goals.
  4. Organize a second CAN BON conference of a small number of scientists to discuss these specific proposals. Any subgroup can participate at this level, but some decisions must be made for the overall objectives of biodiversity conservation in Canada.

These general ideas are not particularly new (Likens 1989, Lindenmayer et al. 2018). They have evolved from the setting up of the LTER Program in the USA (Hobbie 2003), and they are standard operating procedures for astronomers who need to come together with big ideas asking for big money. None of this will be easy to achieve for biodiversity conservation because it requires the wisdom of Solomon and the determination of Vladimir Putin.

Hobbie, J.E., Carpenter, S.R., Grimm, N.B., Gosz, J.R., and Seastedt, T.R. (2003). The US Long Term Ecological Research Program. BioScience 53, 21-32. doi: 10.1016/j.oneear.2021.12.008

Likens, G. E. (Ed.) (1989). ‘Long-term Studies in Ecology: Approaches and Alternatives.’ (Springer Verlag: New York.) ISBN: 0387967435

Lindenmayer, D. (2018). Why is long-term ecological research and monitoring so hard to do? (And what can be done about it). Australian Zoologist 39, 576-580. doi: 10.7882/az.2017.018.

Lindenmayer, D.B., Likens, G.E., and Franklin, J.F. (2018). Earth Observation Networks (EONs): Finding the Right Balance. Trends in Ecology & Evolution 33, 1-3. doi: 10.1016/j.tree.2017.10.008.

On Global Science and Local Science

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I suggest that the field of ecology is fragmenting into two large visions of the science which for the sake of simplicity I will call Global Science and Local Science. This fragmentation is not entirely new, and some history might be in order.

Local Science deals with local problems, and while it aspires to develop conclusions that apply to a broader area than the small study area, it has always been tied to useful answers for practical questions. Are predators the major control of caribou declines in northern Canada? Can rats on islands reduce ground-nesting birds to extinction? Does phosphate limit primary production in temperate lakes? Historically Local Science has arisen from the practical problems of pest control and wildlife and fisheries management with a strong focus on understanding how populations and communities work and how humans might solve the ecological problems they have largely produced (Kingsland 2005). The focus of Local Science was always on a set of few species that were key to the problem being studied. As more and more wisdom accumulated on local problems, ecologists turned to broadening the scope of enquiry, asking for example if solutions discovered in Minnesota might also be useful in England or vice versa. Consequently, Local Science began to be amalgamated into a broader program of Global Science.

Global Science can be defined in several ways. One is purely financial and big dollars; this not what I will discuss here. I want to discuss Global Science in terms of ecological syntheses, and Global Science papers can often be recognized by having dozens to hundreds of authors, all with data to share, and with meta-analysis as the major tool of analysis. Global Science is now in my opinion moving away from the experimental approach that was a triumph of Local Science. The prelude to Global Science was the International Biological Program (IBP) of the 1970s that attempted to produce large-scale systems analyses of communities and ecosystems but had little effect in convincing many ecologists that this was the way to the future. At the time the problem was largely the development of a theory of stability, a property barely visible in most ecological systems.

Global Science depends on describing patterns that occur across large spatial scales. These patterns can be discovered only by having an extensive, reliable set of local studies and this leads to two problems. The first is that there may be too few reliable local studies. This may occur because different ecologists use different methods of measurement, do not use a statistically reliable sampling design, or may be constrained by a lack of funding or time. The second problem is that different areas may show different patterns of the variables under measurement or have confounding causes that are not recognized. The approach through meta-analysis is fraught with the decisions that must be made to include or exclude specific studies. For example, a recent meta-analysis of the global insect decline surveyed 5100 papers and used 166 of them for analysis (van Klink et al. 2020). It is not that the strengths and limitations of meta-analysis have been missed (Gurevitch et al. 2018) but rather the question of whether they are increasing our understanding of the Earth’s ecology. Meta-analyses can be useful in suggesting patterns that require more detailed analyses. In effect they violate many of the rules of conventional science in not having an experimental design, so that they suggest patterns but can be validated only by a repeat of the observations. So, in the best situations meta-analyses lead us back to Local Science. In some situations, meta-analyses lead to no clear understanding at all, as illustrated in the conclusions of Geary et al. (2020) who investigated the response of terrestrial vertebrate predators to fire:

“There were no clear, general responses of predators to fire, nor relationships with geographic area, biome or life-history traits (e.g. body mass, hunting strategy and diet). Responses varied considerably between species.” (page 955)

Note that this study is informative in that it indicates that ecologists have not yet identified the variables that determine the response of predators to fire. In other cases, meta-analysis has been useful in redirecting ecological questions because the current global model does not fit the facts very well (Szuwalski et al. 2015).

The result of this movement within both ecological and conservation science toward Global Science has been a shift in the amount of field work being done. Rios-Saldana et al. (2018) surveyed the conservation literature over the last 35 years and found that fieldwork-based publications decreased by 20% in comparison to a rise of 600% and 800% in modelling and data analysis studies. This conclusion could be interpreted that ecologists now realize that less fieldwork is needed at this time, or perhaps the opposite. 

In an overview of ecological science David Currie (2019) described an approach to understanding how progress in ecology has differed from that in the physical sciences. He suggests that the physical sciences focused on a set of properties of nature whose variation they analyzed. They developed ‘laws’ Like Newton’s laws or motion that could be tested in simple or complex systems. By contrast ecology has developed largely by asking how processes like competition or predation work, and not by asking questions about the properties of natural systems, which is what interests the general public trying to solve problems in conservation or pest or fisheries management. Currie (2019) summarized his approach as follows:

“Successful disciplines identify specific goals and measure progress toward those goals. Predictive accuracy of properties of nature is a measure of that progress in ecology. Predictive accuracy is the objective evidence of understanding. It is the most useful tool that science can offer society.” (page 18)

Many of these same questions underlay the critical appraisal of ecology by Peters (1991).

There is no one approach to ecological science, but we need to continue to ask what progress is being made with every approach. These are key questions for the future of ecological research, and they are worthy of much more discussion because they determine what students will be taught and what kinds of research will be favoured for funding in the future.

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

Geary, W.L., Doherty, T.S., Nimmo, D.G., Tulloch, A.I.T., and Ritchie, E.G. (2020). Predator responses to fire: A global systematic review and meta-analysis. Journal of Animal Ecology 89, 955-971. doi: 10.1111/1365-2656.13153.

Gurevitch, J., Koricheva, J., Nakagawa, S., and Stewart, G. (2018). Meta-analysis and the science of research synthesis. Nature 555, 175-182. doi: 10.1038/nature25753.

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

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

Ríos-Saldaña, C. Antonio, Delibes-Mateos, Miguel, and Ferreira, Catarina C. (2018). Are fieldwork studies being relegated to second place in conservation science? Global Ecology and Conservation 14: e00389. doi: 10.1016/j.gecco.2018.e00389.

Szuwalski, C.S., Vert-Pre, K.A., Punt, A.E., Branch, T.A., and Hilborn, R. (2015). Examining common assumptions about recruitment: a meta-analysis of recruitment dynamics for worldwide marine fisheries. Fish and Fisheries 16, 633-648. doi: 10.1111/faf.12083.

van Klink, R., Bowler, D.E., Gongalsky, K.B., Swengel, A.B., Gentile, A. and Chase, J.M. (2020). Meta-analysis reveals declines in terrestrial but increases in freshwater insect abundances. Science 368, 417-420. doi: 10.1126/science.aax9931.

On Biodiversity Science

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With David Attenborough and all the amazing picture books on biodiversity there can be few people in the world who have not been alerted to the array of beautiful and interesting species on Earth. Until recently the subject of biodiversity, known to First Nations since long, long ago, had not entered the western world of automobiles, industry, farming, fishing, music, theatres, and movies. Biodiversity is now greatly appreciated by most people, but perhaps more as entertainment for western societies and more for subsistence food in less wealthy parts of our world.

There are many different measures of ‘biodiversity’ and when discussing how we should protect biodiversity we should be careful about exactly how this word is being used. The number of different species in an area is one simple measure of biodiversity. But often the types of organisms being considered are less well defined. Forest ecologists attempt to protect forest biodiversity, but logging companies are more concerned only with trees and tree size for commercial use. Bird watchers are concerned with birds and have developed much citizen science in counting birds. Mushroom connoisseurs may worry about what edible mushrooms will be available this summer. But in many cases biodiversity scientists recognize that the community of organisms and the ecosystem that contains them would be a more appropriate unit of analysis. But as the number of species in an ecosystem increases, the complexity of the ecosystem becomes unmanageable. A single ecosystem may have hundreds to thousands of species, and we are in the infant stage of trying to determine how to study these biological systems.

One result is that, given that there are perhaps 10 million species on Earth and only perhaps 10,000 biologists who study biodiversity, where do we begin? The first and most popular way to answer this question is to pick a single species and concentrate on understanding its ecology. This makes are researcher’s life fairly simple. If elephants in Africa are under threat, find out all about the ecology of elephants. If a particular butterfly in England is very rare, try to find out why and how to protect them. This kind of research is very valuable for conservation because it provides a detailed background for understanding the requirements of each species. But the single species approaches lead into at least two quagmires. First, all species exist in a web of other species and understanding this web greatly expands the problem. It is possible in many cases to decipher the effects other species have on our elephants or butterflies, but this requires many more scientists to assist in analysing the species’ food chain, its diseases, its predators and parasites, and that is only a start. The second quagmire is that one of the general rules of ecology is that most species on Earth are rare, and few are common. So that we must concentrate our person-power on the common species because they are easier to find and study. But it is often the rare species that are of conservation concern, and so we should focus on them rather than the common species. In particular, given that only about 10% of the species on Earth have been described scientifically, we may often be assigned a species that does not have any information on its food habits or habitat requirements, its distribution, and how its abundance might be changing over time, a lifetime research program.

The result of this general overview is that the mantra of our day – Protect Biodiversity – begins as a compelling slogan and ends in enormous scientific complexity. As such it falls into the category of slogans like ‘Reduce Poverty’ and ‘Peace on Earth’, something we can all agree on, but the devil is in the details of how to achieve that particular goal.

One way to avoid all these pitfalls has been to jump over the problems of individual species and analyse communities of species or entire ecosystems. The result of this approach is to boil down all the species in the community to a number that estimates “biodiversity” and then use that number in relating ‘biodiversity’ to community attributes like ‘productivity’ or ‘stability’. This approach leads to testing hypotheses like ‘Higher biodiversity leads to greater stability’. There are serious problems with this approach if it is used to test any such hypothesis. First, biodiversity in this example must be rigorously defined as well as stability. The fact that higher biodiversity of butterflies in a particular region is associated with a more stable abundance of these butterflies over time is worthy of note but not of generalization to global communities or ecosystems. And as in all ecological studies we do not know if this is a generalization applicable to all butterfly populations everywhere until many more studies have been done.

A second problem is that this community or ecosystem approach to address ecological questions about biodiversity is not very useful in promoting conservation which boils down to particular species in particular environments. It should force us back to looking at the population ecology of species that are of conservation concern. It is population ecologists who must push forward the main goals of the conservation of the Earth’s biota, as Caughley (1994) recognized long ago.

The practical goals of conservation have always been local, and this constraint is mostly ignored in papers that demand some global research priorities and global ecological rules. The broad problem is that the conservation of biodiversity is a gigantic scientific and political problem that is currently underfunded and in its scientific infancy. At the present too much biodiversity research is short-term and not structured in a comprehensive framework that identifies critical problems and concentrates research efforts on these problems (Nichols et al. 2019, Sutherland et al. 2018). One more important issue for a seminar discussion group. 

Caughley, G. (1994). Directions in conservation biology. Journal of Animal Ecology 63, 215-244. doi: 10.2307/5542

Nichols, J.D., Kendall, W.L., and Boomer, G.S. (2019). Accumulating evidence in ecology: Once is not enough. Ecology and Evolution 9, 13991-14004. doi: 10.1002/ece3.5836.

Sutherland, W.J., Butchart, Stuart H.M., Connor, B., Culshaw, C., Dicks, L.V., et al. (2018). A 2018 Horizon Scan of Emerging Issues for Global Conservation and Biological Diversity. Trends in Ecology & Evolution 33, 47-58. doi: 10.1016/j.tree.2017.11.006.

A Poem on the State of Agriculture in 1935

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After listening to me rant about the state of modern agriculture in the Anthropocene, a colleague in Australia sent me this poem by C.J. Dennis (1876 – 1938) written long before most of us were born. I reprint it here as a reminder that many of our ecological problems are not new, that we have perhaps made progress on some but that in many areas Dennis’s poem about agriculture could have been published today. A powerful poem that in a classroom discussion might lead us to second thoughts that we now live in the best of all possible worlds. Vale C.J. Dennis.

C.J. Dennis in the Herald in 1935 in Australia
THE SPOILERS

“Because overstocking and continuous grazing have denuded the land of vegetation and removed all resistance to wind and flood, it has now been suddenly realised that erosion in the Western districts of N.S.W. has reduced thousands of acres to little better than desert. A descendant of the original black inhabitants of this country might regard this as just retribution.

Ye are the Great White People, masters and lords of the earth,
Spreading your stern dominion over the world’s wide girth.
Here, where my fathers hunted since Time’s primordial morn,
To our land’s sweet, fecund places, you came with your kine and corn.
Mouthing your creed of Culture to cover a baser creed,
Your talk was of White Man’s magic, but your secret god was Greed.
And now that your generations to the second, the third have run,
White Man, what of my country?  Answer, what have you done?

Now the God of my Simple People was a simple, kindly God,
Meting his treasure wisely that sprang from this generous sod,
With never a beast too many and never a beast too few,
Thro’ the lean years and the fruitful, he held the balance true.
Then the White Lords came in their glory; and their cry was: “More!  Yet more!”
And to make them rich for a season they filched Earth’s age-old store,
And they hunted my Simple People — hunters of yester-year —
And they drove us into the desert — while they wrought fresh deserts here.

They ravaged the verdant uplands and spoiled wealth ages old,
Laid waste with their pumps and sluices for a gunny-bag of gold;
They raided the primal forests and the kind, rain-bringing trees
That poured wealth over the lowlands thro’ countless centuries;
They fed their kine on the grasslands, crowding them over the land,
Till blade and root in the lean years gave place to hungry sand.
Then, warned too late of their folly, the White Lords grew afraid,
And they cried to their great god Science; but Science could not aid.

This have you done to our country, lords of the air and the seas,
This to the hoarded riches of countless centuries —
Life-yielding loam, uncovered, unsheltered in the drought,
In the floods your hand unbridled, to the age-old sea drifts out.
You have sold man’s one true birthright for a White Man’s holiday,
And the smothering sands drift over where once green fields turn grey —
Filched by the White Man’s folly to pamper the White Lords’ vice;
And leave to your sons a desert where you found a paradise.”

Herald, 6 December 1935, page 6

http://www.middlemiss.org/lit/authors/denniscj/newspapers/herald/1935/works/spoilers.html