Tag Archives: wildlife management

How Much Can Ecologists Lie?

An ethical dilemma arises in ecology for scientists who have strong beliefs about climate change and the protection of biodiversity. Should you tell lies in your scientific papers or to the media regarding ecological issues? In essence the simple answer is never. Science is the search for the truth and the truth should be obtained from empirical evidence. This does not mean that a scientist cannot have any opinions about which you can shout very loudly, if for example you think that poached eggs are better than scrambled eggs. But there should be a general taboo about lying and we should keep a sharp distinction that opinions ≠ evidence.

But in the real world these distinctions are not always clear. How much should you as a scientist bend or gloss over the evidence? If you find that a particular pollutant will have a 75% chance of killing fish in a river system, should you stand aside as an industry argues that there is a 25% chance that nothing will happen, and profits must come before caution. In these kinds of discussions environmentalists always lose because of the precautionary principle and information is never 100% precise. The temptation is to avoid losing by lying, stretching the evidence, or shouting.

In this era of the climate disaster, it is difficult to restrain from talking about what will happen in the future. While opinions fly back and forth on what is happening, whether it will all reverse, and how soon changes will occur, ecologists must remain trustworthy by countering misinterpretations of ecological trends without rancour. When our research is incomplete, we should say so and indicate what needs to be done next to fill in the gaps in knowledge. If we are wrong in our predictions, we should admit it and discuss why. We need to point out the problems and the potential consequences from what we know today. This is not as difficult as it sounds, and it requires only to draw a line between the existing evidence and likely extrapolations from current knowledge.

A major part of current misinformation on social media about scientific issues is that existing evidence is blown out of proportion in an attempt to get some kind of specific action by governments or corporations. Lies or disinformation are more interesting to the media than the details of what is actually reliable knowledge. Uncertain predictions about future changes by scientists are often translated in social media as certain predictions. Perhaps the most important but most difficult aspect of predictions is the need to go back one or more years and list the predictions that were made and evaluate how accurate they were. Model systems for the sciences are perhaps earthquake predictions and weather predictions. While we know a great deal about the geological causes of earthquakes and have mapped major faults along which they occur, so all would agree that we “understand earthquakes scientifically”, we are not able to predict exactly where and when the next major quake will occur. Similarly we are all familiar with weather predictions which are limited to short time intervals even though we have detailed knowledge of the physical laws that govern air mass movements.

Some samples of the very large literature on forecasting earthquakes (Fallou et al. 2022, Wikelski et al. 2020), and on biotic extinctions (Cowie et al. 2022, Kehoe et al. 2021, Lambdon and Cronk 2020, Nikolaou and Katsanevakis 2023, Williams et al. 2021) provide an introduction to finding out how scientists deal with the uncertainties of prediction in these two example areas of science. Knowledge is power but it is not infinite power, and all scientists should qualify their predictions or projections as possibly in error. Lying about complex questions is not part of science.  

Cowie, R.H., Bouchet, P. & Fontaine, B. (2022) The Sixth Mass Extinction: fact, fiction or speculation? Biological Reviews, 97, 640-663.doi: 10.1111/brv.128161.

Fallou, L., Corradini, M. & Cheny, J.M. (2022) Preventing and debunking earthquake misinformation: Insights into EMSC’s practices. Frontiers in Communication, 7, 993510.doi. 10.3389/fcomm.2022.993510

Kehoe, R., Frago, E. & Sanders, D. (2021) Cascading extinctions as a hidden driver of insect decline. Ecological Entomology, 46, 743-756.doi: 10.1111/een.129851.

Lambdon, P. & Cronk, Q. (2020) Extinction dynamics under extreme conservation threat: The Flora of St Helena. Frontiers in Ecology and Evolution, 8, 41.doi: 10.3389/fevo.2020.00041.

Nikolaou, A. & Katsanevakis, S. (2023) Marine extinctions and their drivers. Regional Environmental Change, 23, 88.doi: 10.1007/s10113-023-02081-8.

Wikelski, M., Mueller, U., Scocco, P., Catorci, A., Desinov, L.V., Belyaev, M.Y., Keim, D., Pohlmeier, W., Fechteler, G. & Martin Mai, P. (2020) Potential short-term earthquake forecasting by farm animal monitoring. Ethology, 126, 931-941.doi: 10.1111/eth.13078.

Williams, N.F., McRae, L. & Clements, C.F. (2021) Scaling the extinction vortex: Body size as a predictor of population dynamics close to extinction events. Ecology and Evolution, 11, 7069-7079.doi: 10.1002/ece3.7555.

On Discourse and Evidence

A major problem that bedevils society as well as science today is the distinction between opinion and evidence. The world is awash in opinions and short of evidence for many questions that fill the news media as well as the scientific literature. In trying to evaluate this statement we should recognize that there are many important issues for which we have no evidence but only beliefs. A current discussion in the news media is whether or not any particular country should spend 2% of its GDP on military expenses. Much hot air follows from these discussions because as an individual person you have no evidence one way or the other for different points of view, spend more, spend less. You will have an opinion that everyone should respect but for this and many issues any evidence that can be cited is vague. Discussion on many issues like this example are important and should be civilized but often are not.

But there are a range of issues for which scientific evidence is available. The first rule of discourse on these issues ought to be that you as a person are allowed to have any opinion you wish but you must be able to present evidence to support your opinions. You should be allowed as a person to proclaim that the Earth is not round but flat and provide the evidence one way or the other. More serious issues with different opinions involve issues like vaccination for a particular disease. On these issues scientists can only advise and provide evidence. But if a vaccine X for example has a complex side effect rate of 1 person in 1000, you could always argue that you are that one person and you are opposed to vaccination X.

How does all this relate to ecological science? First, we should recognize that many of the arguments in the ecological literature are about opinions rather than evidence. In many cases this should lead to more studies of particular problems to gather more evidence. But as we see with climate change research the evidence is accumulating but varies greatly in quality and time span from area to area and from taxonomic group to taxonomic group. We cannot agree whether our research should be focused on the oceans or on land, or on birds rather than mammals or insects. We cannot do everything, and the consequence is that ecological research funding is driven in many directions depending on who is on the committee dispersing funding and what their opinions are. The result is that for large scale problems like climate change we have convinced most people that it is a reality, but we cannot agree on the details of future change. So, we build models with past data and try to project them into the future with uncertain confidence.

The consequence is that the ecological world is awash in opinions in the same way as other parts of society, and in support of opinions the evidence often gets lost. The main problem here is that opinions are generated rapidly while evidence accumulates slowly. We see this more readily in medical science in which the media trumpets treatment X rather than Y with opinions and little evidence. We cannot demand answers to important questions tomorrow when the problem spans years or decades for evidence to accumulate. 

Ecology like every science becomes more complicated with age, and a fisheries biologist trained 40 years ago lives in a different world from one trained today. The accumulated evidence from research changes our list of important questions illustrated well by the reviews of progress in conservation science by Sutherland et al. (2022, 2023) and Christie et al. (2023), in predator- prey dynamics by Sheriff et al. (2020), wildlife management by Hone et al. (2023), and in insect conservation by Saunders et al. (2020). Understanding and solving ecology problems must rely more on evidence and less on opinions.

Christie, A.P., Christie, A.P., Morgan, W.H. & Sutherland, W.J. (2023) Assessing diverse evidence to improve conservation decision‐making. Conservation Science and Practice, 5, e13024.doi. 10.1111/csp2.13024

Hone, J., Drake, A. & Krebs, C.J. (2023) Evaluation Options for Wildlife Management and Strengthening of Causal Inference. BioScience, 73, 48-58.doi: 10.1093/biosci/biac105.

Saunders, M.E., Janes, J.K. & O’Hanlon, J.C. (2020) Moving On from the Insect Apocalypse Narrative: Engaging with Evidence-Based Insect Conservation. BioScience, 70, 80-89.doi: 10.1093/biosci/biz143.

Sheriff, M.J., Peacor, S.D., Hawlena, D. & Thaker, M. (2020) Non-consumptive predator effects on prey population size: A dearth of evidence. Journal of Animal Ecology, 89, 1302-1316.doi: 10.1111/1365-2656.13213.

Sutherland, W.J. & Jake M. Robinson, D.C.A., Tim Alamenciak, Matthew Armes, Nina Baranduin, Andrew J. Bladon, Martin F. Breed, Nicki Dyas, Chris S. Elphick, Richard A. Griffiths, Jonny Hughes, Beccy Middleton, Nick A. Littlewood, Roger Mitchell, William H. Morgan, Roy Mosley, Silviu O. Petrovan, Kit Prendergast, Euan G. Ritchie,Hugh Raven, Rebecca K. Smith, Sarah H. Watts, Ann Thornton (2022) Creating testable questions in practical conservation: a process and 100 questions. Conservation Evidence Journal, 19, 1-7.doi. 10.52201/CEJ19XIFF2753

Sutherland, W.J., Sutherland, W.J., Bennett, C. & Thornton, A. (2023) A global biological conservation horizon scan of issues for 2023. Trends in Ecology & Evolution, 38, 96-107.doi. 10.1016/j.tree.2022.10.005

Should Ecology Abandon Popper?

The first question I must ask is whether you the reader have ever heard of Karl Popper. If the answer is no, then you could profit from reading Popper (1963) before you read this. An abbreviated version of the Popperian approach to science is presented in a short paper by Platt (1963) The simplest version of Popper and Platt is that we should have a hypothesis with specific predictions and one or more alternative hypotheses with other predictions, and science advances by finding out which hypotheses could be rejected with empirical evidence. The focus of this blog is on a recent paper by Raerinne (2024) claiming that Popperian ecology is a delusion. This is a claim well worth discussing particularly since most of the sciences progress using a Popperian approach to testing hypotheses.

To begin perhaps we should recognize two kinds of papers that appear in ecological journals. A very large set of ecological papers appear to be largely or entirely descriptive natural history typically of past or present events with no hypotheses in mind. Many of these papers end with a conclusion that could be designated as a hypothesis but with little discussion of alternatives. These papers can be very valuable in giving us the state of populations, communities, or ecosystems with recommendations for changes that should be made to alleviate developing problems. A good example are papers describing forest and grassland fires of recent years which can end with some management recommendations, and perhaps with alternative recommendations. These recommendations usually arise from experience and judgements, and they may or not be valid. The Popperian approach would be to set up hypotheses and test them empirically, but if we are people of action, we press onward with a preferred management action. The non-Popperian approach would be very efficient if we were correct in our diagnosis, and in many cases this approach works well. The basis of the issue here is what is evidence in ecology and how should it be sharpened into recommendations for conservation and management.  

The Popperian approach to ecological science is to recognize problems that require a solution to increase our knowledge base, and to suggest a series of alternative set of mechanisms that could solve or alleviate the problem. Ecological papers supporting this approach can often be recognized by searching for the word “hypothesis” in the text. A simple example of this Popperian approach could be finding the causes of the continuing decline of a commercial fishery. The decline might be due to predation on the target fish or invertebrate, a disease, added pollution to the water body, climate change increasing the water temperature and thus metabolic functions, introduced species of competitors for food or space. One or more of these causal factors could be involved and the job of the ecologist is to find out which one or several are diagnostic. Given the complexity of ecological problems, it is typically not possible to test these alternative hypotheses in one grand experiment, and the typical approach will involve adaptive management or evidence-based conservation (Gillson et al. 2019, Serrouya et al., Westgate et al. 2013). Complexity however should not be used as an excuse to do poor science.

What is the alternative if we abandon Popper? We could adopt the inductive approach and gather data that we put together with our judgement to declare that we have a correct answer to our questions, “seat of the pants” ecology. But this approach is heavily dependent on the idea that “the future will be like the past”. This approach to ecological problems will be most useful for the very short term. The simplest example comes from weather forecasting in which the prognosis for today’s weather is what it was like yesterday with minor adjustments. We could observe trends with this approach but then we must have a statistical model that predicts, for example, that the trend is linear or exponential. But the history of science is that we can do much better by understanding the mechanisms underlying the changes we see. A good overview of the dilemmas of this inductive approach for conservation biology is provided by Caughley (1994). The operative question here is whether the inductive approach achieves problem resolutions more efficiently than the Popperian approach through conjecture and refutation.

Raerinne (2023, 2024) does biology in general and ecology in particular a disservice in criticizing Popper’s approach to ecology by arguing that ecology should not be criticized nor evaluated from the Popperian perspective. I think this judgement is wrong, and Raerinne’s conclusion arises from a philosophical viewpoint which could well have little applicability to how ecologists solve empirical problems in the real world. But you can judge.  

Carducci, A., Federigi, I. & Verani, M. (2020) Airborne transmission and its prevention: Waiting for evidence or applying the Precautionary Principle? Atmosphere, 11 (7), 710.doi: 10.3390/atmos11070710.

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

Gillson, L., Biggs, H. & Rogers, K. (2019) Finding common ground between adaptive management and evidence-based approaches to biodiversity conservation. Trends in Ecology & Evolution, 34, 31-44.doi: 10.1016/j.tree.2018.10.003.

Platt, J.R. (1964) Strong inference. Science, 146, 347-353.doi: 10.1126/science.146.3642.347.

Popper, K.R. (1963) Conjectures and Refutations: The Growth of Scientific Knowledge. Routledge and Kegan Paul, London.

Raerinne, J. (2023) Myths of past biases and progress in biology. Theory in Biosciences, 142, 383-399.doi: 10.1007/s12064-023-00403-2.

Raerinne, J. (2024) Popperian ecology is a delusion. Ecology and Evolution, 14, e11106.doi: 10.1002/ece3.11106.

Serrouya, R., Seip, D.R., Hervieux, D., McLellan, B.N., McNay, R.S., Steenweg, R., Heard, D.C., Hebblewhite, M., Gillingham, M. & Boutin, S. (2019) Saving endangered species using adaptive management. Proceedings of the National Academy of Sciences, 116, 6181-6186.doi: 10.1073/pnas.1816923116 .

Westgate, M.J., Likens, G.E. & Lindenmayer, D.B. (2013) Adaptive management of biological systems: A review. Biological Conservation, 158, 128-139.doi: 10.1016/j.biocon.2012.08.016 .

On Critical Evaluation in Ecology

Science proceeds by “conjecture-and-refutation” if we agree with Karl Popper (1963). There is a rich literature on science in general and ecological science in particular that is well worth a series of graduate discussions even if it is pre-2000 ancient history (Peters 1991, Weiner 1995, Woodward and Goodstein 1996). But I wish to focus on a current problem that I think is hindering ecological progress. I propose that ecological journals at this time are focusing their publications on papers that present apparent progress and are shedding papers that are critical of apparent progress. Or in Popper’s words, they focus on publishing ‘conjecture’ and avoid ‘refutation’. The most important aspect of this issue involves wildlife management and conservation issues. The human side of this issue may involve personal criticism and on occasion the loss of a job or promotion. The issue arises in part because of a confusion between the critique of ideas or data and the interpretation that all critiques are personal. So, the first principle of this discussion is that I discuss here only critiques of ideas or data.

There are many simple reasons for critiques of experimental design and data gathering. Are the treatments replicated, are the estimates of data variables reliable and sufficient, are proxy variables good or poor? Have the studies been carried out long enough? All these critiques can be summarized under the umbrella of measurement reliability. There are many examples we can use to illustrate these ideas. Are bird populations declining across the globe or locally? Are fisheries overharvesting particular species? Can we use climate change as a universal explanation of all changes in wildlife populations? Are survey methods for population changes across very large areas reliable? The problem is tied into the need for good or bad news that must be filtered to the news media or social media with high impact but little reliability. 

The problem at the level of science is the temptation to extrapolate beyond the limits of the available data. Now we come to the critical issue – how do our scientific journals respond to critical reviews of papers already published? My concern is that in the present time journals do not wish to receive or accept manuscripts that are critical of previously published papers. These decisions are no doubt confidential for journal publishers. There is perhaps some justification for this rejection policy, given that in the few cases where critiques are published on existing papers, the citation score of the original paper may greatly exceed that of the critique. So, conjecture pays, refutation does not.

Journals are flooded with papers and for the better journals I would expect at least a 60-80% rejection rate. For Science the rejection rate is 94%, for Nature 92%, and for the Journal of Animal Ecology 85% of submitted manuscripts are rejected. Consequently, the suggestion that they reserve space for ‘refutation’ is too negative to their publication model. There is little I can suggest if one in caught in this dilemma except to try another less premium journal, and remember that web searches find papers easily no matter where published. If you need inspiration, you can follow Peters (1991) and write a book critique and suffer the brickbats from the establishment (e.g. Nature 354: 444, 12 December 1991).

But if you are upset about a particular paper or series of papers, remember critiques are valuable but follow these rules for a critique:

  1. Keep it short, 5 typed pages should be near maximal length.
  2. Raise a set of major points. Do not try to cover everything.
  3. Summarize briefly the key points you are in agreement with, so they are not confounded in the discussion.
  4. Discuss what studies might distinguish hypothesis A vs B, or A+B vs C.
  5. Discuss what better methods of measurement might be used if funding is available.
  6. Never attack individuals or research groups. The discussion is about ideas, results, and inferences.

Decisions to accept some management actions may have to be taken immediately and journal editors must take that into consideration. Prognostication over accepting critiques may be damaging. But all actions must be continually evaluated and changed once the understanding of the problem changes.

There are too many examples to recommend reading about past and present controversies in ecology, so here are only two examples. Dowding et al. (2009) report a comment on suggested methods of controlling introduced pests on Macquarie Island in the Southern Ocean. I was involved in that discussion. A much bigger controversy in Canada involves Southern Mountain caribou populations which are in rapid decline. The proximate explanation for the decline is postulated to be predation by wolves and thus the suggested management action is shooting the wolves. Johnson et al. (2022), Lamb et al. (2022) and Superbie et al. (2022) provide an entre into this literature and the decisions of what to do now and in the future to prevent extinction of these ungulates. The caribou problem is complicated by the interaction of human alteration of landscapes and the natural processes of predation and food availability. Alas nothing is simple.

All these ecological dilemmas are controversial and the important role of criticism involving evaluations of alternative hypotheses are the only way forward for ecologists involved in controversies. In my opinion most ecological journals are not doing their part is publishing critiques of the conventional wisdom.

Dowding, J.E., Murphy, E.C., Springer, K., Peacock, A.J. & Krebs, C.J. (2009) Cats, rabbits, Myxoma virus, and vegetation on Macquarie Island: a comment on Bergstrom et al. (2009). Journal of Applied Ecology, 46, 1129-1132. doi: 10.1111/j.1365-2664.2009.01690.x.

Johnson, C.J., Ray, J.C. & St-Laurent, M.-H. (2022) Efficacy and ethics of intensive predator management to save endangered caribou. Conservation Science and Practice, 4: e12729. doi: 10.1111/csp2.12729.

Lamb, C.T., Willson, R., Richter, C., Owens-Beek, N., Napoleon, J., Muir, B., McNay, R.S., Lavis, E., Hebblewhite, M., Giguere, L., Dokkie, T., Boutin, S. & Ford, A.T. (2022) Indigenous-led conservation: Pathways to recovery for the nearly extirpated Klinse-Za mountain caribou. Ecological Applications 32 (5): e2581. doi: 10.1002/eap.2581.

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

Popper, K.R. (1963) Conjectures and Refutations: The Growth of Scientific Knowledge. Routledge and Kegan Paul, London. 412 pp. ISBN-13: 978-0415285940.

Superbie, C., Stewart, K.M., Regan, C.E., Johnstone, J.F. & McLoughlin, P.D. (2022) Northern boreal caribou conservation should focus on anthropogenic disturbance, not disturbance-mediated apparent competition. Biological Conservation, 265, 109426. doi: 10.1016/j.biocon.2021.109426.

Weiner, J. (1995) On the practice of ecology. Journal of Ecology, 83, 153-158.

Woodward, J. & Goodstein, D. (1996) Conduct, misconduct and the structure of science. American Scientist, 84, 479-490.

On Conservation Complexities

It is too often the case that biodiversity problems are managed by single species solutions. If you have too many deer in your parks or conservation areas, start a culling program. If your salmon fishing stocks are declining, cull seals and sea lions. The overall issue confounding these kinds of ‘solutions’ are now being recognized as a failure to appreciate the food web of the community and ecosystem in which the problem is embedded. Much of conservation action is directed at heading back to the “good old days” without very much data about what the ecosystem was like in the “good old days”.

Problems with introduced species top the list of conservation dilemmas, and nowhere are these problems more clearly illustrated than by the conservation dilemmas of New Zealand and Australia. If we concentrate our management efforts on introduced predators or herbivores, we face a large set of conservation issues, well-illustrated by the current New Zealand situation (Leathwick and Byrom 2023, Parkes and Murphy 2003).

New Zealand is a particularly strong case history because we have a good knowledge of its indigenous biodiversity from the time that people colonized these islands, as well as reasonable information about how things have changed since Europeans colonized the country (Thomson 1922). It is in some respects the classic case of biodiversity impacts from introduced species. The introduced species list is large and I can talk only about part of these species introduced mostly in the late 1800s. Seven species of deer were released in New Zealand, along with chamois, hares, rabbits, cats, hedgehogs, three mustelid species, brushtail possums, rats, house mice, along with all the usual farm animals like cattle, horses, and dogs (King & Forsyth 2021). The first concerns began about 100 years ago over ungulate browsing in forests and grasslands. Deer control began about 1930, and over 3 million deer were shot between 1932 and 1954. Caughley (1983) showed that this amount of control did not reduce the impact of browsing and grazing by ungulates in native ecosystems. Control and harvesting efforts decreased in recent years partly from a lack of government funding with the result that deer numbers have rebounded. The recognition of the impact of other pests like rabbits, weasels, and rats led to a focus on poison campaigns. Brushtail possum control with poisons was started to reduce tree browsing damage by the 1970s and gradually increased to reduce TB transmission to domestic livestock by the 1990s. Large scale predator control began in the late 1990s with a focus on rats, stoats (weasels, Mustela erminea), and possums with good success in preventing declines in threatened bird species. All this history is covered in detail in Leathwick and Byrom (2023).

These efforts led to a declaration in 2016 of “Predator Free New Zealand 2050” (PF2050) a compelling promise that would alleviate biodiversity problems by making New Zealand free of possums, mustelids, and rats by 2050, and predator control has thus became the focus of recent conservation action. The 2050 part of the promise was always a worry, since governments in general promise much in advances by that year, but the optimistic view is that predator control will achieve this objective if careful planning is made, adequate funding is available (c.f. Department of Conservation 2021), and well-articulated guidelines for eradication of invasive species are followed (Bomford & O’Brien 1995). The message is that biodiversity goals can be achieved if we move from single species management to a stable system of ecosystem management in the broad sense, including strong research, good public participation and support toward these goals, and that biodiversity conservation will be greatly boosted by thorough consultation with (if not leadership by) the indigenous groups involved.

The New Zealand specific situation cannot be applied directly to all biodiversity concerns, but the New Zealand conservation story and the 12 recommendations given in Leathwick and Byrom (2023) show the necessity of goal definition and coordination between the public, government, and private foundations if we are to maximize the effectiveness of our approach to the biodiversity crisis. Not every conservation issue involves introduced species, but the principle must be: What do we want to achieve, and how are we going to get there?

Bomford, M, & O’Brien, P 1995. Eradication or control for vertebrate pests? Wildlife Society Bulletin 23, 249–255.

Caughley, G. (1983) The Deer Wars: The Story of Deer in New Zealand. Heinemann, Auckland. ISBN: 0868633895.

Department of Conservation (2020). Annual Report. Available at: https://www.doc.govt. nz/nature/pests-and-threats/predator-free-2050/goal-tactics-and-new-technology/tools-to-market/.    See also: PF2050-Limited-Annual-Report-2022.pdf

King, C.M. & Forsyth, D.M. (2021). eds. The Handbook of New Zealand Mammals. 3rd edition. CSIRO Publishing, Canberra. ISBN 978-1988592589.

Leathwick, J.R. & Byrom, A.E. (2023) The rise and rise of predator control: a panacea, or a distraction from conservation goals? New Zealand Journal of Ecology, 47, 3515. doi: 10.20417/nzjecol.47.3515.

Parkes, J. & Murphy, E. (2003) Management of introduced mammals in New Zealand. New Zealand Journal of Zoology, 30, 335-359. doi:10.1080/03014223.2003.9518346.

Thomson, G.M. (1922) The Naturalisation of Animals and Plants in New Zealand. The University Press, Cambridge, England. doi: 10.5962/bhl.title.28093.

Management by Killing

While reading a recent wildlife management magazine I became focused on the idea that the main topic of interest was killing in the same way that the news every day is now about who killed who yesterday. The management paradigm behind my concerns is this simple one:

  1. Decide who are the “good guys” and who are the “bad guys”.
  2. Kill all (or many) of the “bad guys”.

I know this sounds too simple but bear with me. In the papers this week are two current management issues. In Sweden they have decided they need only 400 wolves in the entire country, and they have several hundred too many, so they armed many hunters with very large guns to go out and kill every wolf they can find, using dogs and other tricks, until they reach the magic number of 400 left. In British Columbia there is concern that predators like sea lions and seals eat Pacific salmon so there are fewer salmon for the fishers to catch and sell. The answer again leaps to mind – kill the sea lions and seals and anything else that eats salmon, Fisheries Science 101.

If this approximates ‘management’, our main discussions must be to decide who are the “good guys”. This leads to conflicts with conservation at times, so we must develop a “killing for conservation” subroutine (Shutt and Lees 2021) which raises the cumbersome question of whether our conservation efforts are causing harm to other species.

One way to challenge the Management by Killing paradigm is to start with a food web of the species involved – what might be the consequences of taking one species out of a food web on any or all the other species in the web? Now the management problem expands because we must do good community ecology to answer these questions. Some of the simple food web consequences have already been well described. Study the coyotes in the grasslands and you will find out how complex its diet is (Lingle et al. 2022), so that killing coyotes will affect other species and you may get many more prairie dogs or ground squirrels, some of which may carry the plague bacterium and many of which predate on ground nesting birds. Or if you are a fan of penguins in Antarctica you will find that killer whales eat penguins (Pitman and Durban 2010) so do we kill killer whales to save penguins? King penguins are declining on Macquarie Island for reasons that are not clear, and predation by a suite of avian birds of prey is one possible component (Pascoe et al. 2022). Yet we are reluctant to kill bird predators. Barred owls kill the endangered spotted owl in western North America, so should we be killing barred owls in areas of overlap (Bodine and Capaldi 2017, Wiens et al. 2021)? So even if you have available detailed natural history information on a predator, you cannot easily estimate the effect of removing it without field experimentation.  

My main points are two. First, if you are able, educate your favourite newscaster about the complexities of the Management by Killing approach to conservation. Second, support more detailed research on food web dynamics to show that ecosystems cannot be managed by the two simple rules listed above.

It does not escape me that all this discussion could be applied to the human species, but I venture far out of my field of competence to address this political and social issue (Ein et al. 2022).

Bodine, E.N. & Capaldi, A. (2017) Can culling Barred Owls save a declining Northern Spotted Owl population? Natural Resource Modeling, 30, e12131.doi. 10.1111/nrm.12131.

Ein, N., Liu, J.J.W. Houle, S. Easterbrook, B. et al. (2022) The effects of child encounters during military deployments on the well-being of military personnel: a systematic review. European Journal of Psychotraumatology, 13(2): 2132598. doi. 10.1080/20008066.2022.2132598.

Lingle, S., Breiter, C.J., Schowalter, D.B. & Wilmshurst, J.F. (2022) Prairie dogs, cattle subsidies and alternative prey: seasonal and spatial variation in coyote diet in a temperate grassland. Wildlife Biology, 2022: 5.1doi. 10.1002/wlb3.01048.

Pascoe, P., Raymond, B. & McInnes, J. (2022) The current trajectory of king penguin (Aptenodytes patagonicus ) chick numbers on Macquarie Island in relation to environmental conditions. ICES Journal of Marine Science, 79, 2084-2092.doi.

Pitman, R.L. & Durban, J.W. (2010) Killer whale predation on penguins in Antarctica. Polar Biology, 33, 1589-1594.doi. 10.1007/s00300-010-0853-5.

Shutt, J.D. & Lees, A.C. (2021) Killing with kindness: Does widespread generalised provisioning of wildlife help or hinder biodiversity conservation efforts? Biological Conservation, 261, 109295.doi: 10.1016/j.biocon.2021.109295.

Wiens, J.D., Dugger, K.M., Higley, J.M., Lesmeister, D.B., Franklin, A.B., et al. (2021) Invader removal triggers competitive release in a threatened avian predator. Proceedings of the National Academy of Sciences, 118 (31), e2102859118.doi. 10.1073/pnas.2102859118.

Is Ecology Becoming a Correlation Science?

One of the first lessons in Logic 101 is classically called “Post hoc, ergo propter hoc” or in plain English, “After that, therefore because of that”. The simplest example of many you can see in the newspapers might be: “The ocean is warming up, salmon populations are going down, it must be another effect of climate change. There is a great deal of literature on the problems associated with these kinds of simple inferences, going back to classics like Romesburg (1981), Cox and Wermuth (2004), Sugihara et al. (2012), and Nichols et al. (2019). My purpose here is only to remind you to examine cause and effect when you make ecological conclusions.

My concern is partly related to news articles on ecological problems. A recent example is the collapse of the snow crab fishery in the Gulf of Alaska which in the last 5 years has gone from a very large and profitable fishery interacting with a very large crab population to, at present, a closed fishery with very few snow crabs. What has happened? Where did the snow crabs go? No one really knows but there are perhaps half a dozen ideas put forward to explain what has happened. Meanwhile the fishery and the local economy are in chaos. Without very many critical data on this oceanic ecosystem we can list several factors that might be involved – climate change warming of the Bering Sea, predators, overfishing, diseases, habitat disturbances because of bottom trawl fishing, natural cycles, and then recognizing that we have no simple way for deciding cause and effect and therefore making management choices.

The simplest solution is to say that many interacting factors are involved and many papers indicate the complexity of populations, communities and ecosystems (e,g, Lidicker 1991, Holmes 1995, Howarth et al. 2014). Everyone would agree with this general idea, “the world is complex”, but the arguments have always been “how do we proceed to investigate ecological processes and solve ecological problems given this complexity?” The search for generality has led mostly into replications in which ‘identical’ populations or communities behave very differently. How can we resolve this problem? A simple answer to all this is to go back to the correlation coefficient and avoid complexity.

Having some idea of what is driving changes in ecological systems is certainly better than having no idea, but it is a problem when only one explanation is pushed without a careful consideration of alternative possibilities. The media and particularly the social media are encumbered with oversimplified views of the causes of ecological problems which receive wide approbation with little detailed consideration of alternative views. Perhaps we will always be exposed to these oversimplified views of complex problems but as scientists we should not follow in these footsteps without hard data.

What kind of data do we need in science? We must embrace the rules of causal inference, and a good start might be the books of Popper (1963) and Pearl and Mackenzie (2018) and for ecologists in particular the review of the use of surrogate variables in ecology by Barton et al. (2015). Ecologists are not going to win public respect for their science until they can avoid weak inference, minimize hand waving, and follow the accepted rules of causal inference. We cannot build a science on the simple hypothesis that the world is complicated or by listing multiple possible causes for changes. Correlation coefficients can be a start to unravelling complexity but only a weak one. We need better methods for resolving complex issues in ecology.

Barton, P.S., Pierson, J.C., Westgate, M.J., Lane, P.W. & Lindenmayer, D.B. (2015) Learning from clinical medicine to improve the use of surrogates in ecology. Oikos, 124, 391-398.doi: 10.1111/oik.02007.

Cox, D.R. and Wermuth, N. (2004). Causality: a statistical view. International Statistical Reviews 72: 285-305.

Holmes, J.C. (1995) Population regulation: a dynamic complex of interactions. Wildlife Research, 22, 11-19.

Howarth, L.M., Roberts, C.M., Thurstan, R.H. & Stewart, B.D. (2014) The unintended consequences of simplifying the sea: making the case for complexity. Fish and Fisheries, 15, 690-711.doi: 10.1111/faf.12041

Lidicker, W.Z., Jr. (1991) In defense of a multifactor perspective in population ecology. Journal of Mammalogy, 72, 631-635.

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

Pearl, J., and Mackenzie, D. 2018. The Book of Why. The New Science of Cause and Effect. Penguin, London, U.K. 432 pp. ISBN: 978-1541698963

Popper, K.R. 1963. Conjectures and Refutations: The Growth of Scientific Knowledge. Routledge and Kegan Paul, London. 608 pp. ISBN: 978-1541698963

Romesburg, H.C. (1981) Wildlife science: gaining reliable knowledge. Journal of Wildlife Management, 45, 293-313.

Sugihara, G., et al. (2012) Detecting causality in complex ecosystems. Science, 338, 496-500.doi: 10.1126/science.1227079.

On the Meaning of ‘Food Limitation’ in Population Ecology

There are many different ecological constraints that are collected in the literature under the umbrella of ‘food limitation’ when ecologists try to explain the causes of population changes or conservation problems. ‘Sockeye salmon in British Columbia are declining in abundance because of food limitation in the ocean’. ’Jackrabbits in some states in the western US are increasing because climate change has increased plant growth and thus removed the limitation of their plant food supplies.’ ‘Moose numbers in western Canada are declining because their food plants have shifted their chemistry to cope with the changing climate and now suffer food limitation”. My suggestion here is that ecologists should be careful in defining the meaning of ‘limitation’ in discussing these kinds of population changes in both rare and abundant species.

Perhaps the first principle is that it is the definition of life that food is always limiting. One does not need to do an experiment to demonstrate this truism. So to start we must agree that modern agriculture is built on the foundation that food can be improved and that this form of ‘food limitation’ is not what ecologists who are interested in population changes in the real world are trying to test. The key to explain population differences must come from resource differences in the broad sense, not food alone but a host of other ecological causal factors that may produce changes in birth and death rates in populations.

‘Limitation’ can be used in a spatial or a temporal context. Population density of deer mice can differ in average density in 2 different forest types, and this spatial problem would have to be investigated as a search for the several possible mechanisms that could be behind this observation. Often this is passed off too easily by saying that “resources” are limiting in the poorer habitat, but this statement takes us no closer to understanding what the exact food resources are. If food resources carefully defined are limiting density in the ‘poorer’ habitat, this would be a good example of food limitation in a spatial sense. By contrast if a single population is increasing in one year and declining in the next year, this could be an example of food limitation in a temporal sense.

The more difficult issue now becomes what evidence you have that food is limiting in either time or space. Growth in body size in vertebrates is one clear indirect indicator but we need to know exactly what food resources are limiting. The temptation is to use feeding experiments to test for food limitation (reviewed in Boutin 1990). Feeding experiments in the lab are simple, in the field not simple. Feeding an open population can lead to immigration and if your response variable is population density, you have an indirect effect of feeding. If animals in the experimentally fed area grow faster or have a higher reproductive output, you have evidence of the positive effect of the feeding treatment. You can then claim ‘food limitation’ for these specific variables. If population density increases on your feeding area relative to unfed controls, you can also claim ‘food limitation of density’. The problems then come when you consider the temporal dimension due to seasonal or annual effects. If the population density falls and you are still feeding in season 2 or year 2, then food limitation of density is absent, and the change must have been produced by higher mortality in season 2 or higher emigration.

Food resources could be limiting because of predator avoidance (Brown and Kotler 2007). The ecology of fear from predation has blossomed into a very large literature that explores the non-consumptive effects of predators on prey foraging that can lead to food limitation without food resources being in short supply (e.g., Peers et al. 2018, Allen et al. 2022).

All of this seems to be terribly obvious but the key point is that if you examine the literature about “food limitation” look at the evidence and the experimental design. Ecologists like medical doctors at times have a long list of explanations designed to sooth the soul without providing good evidence of what exact mechanism is operating. Economists are near the top with this distinguished approach, exceeded only by politicians, who have an even greater art in explaining changes after the fact with limited evidence.

As a footnote to defining this problem of food limitation, you should read Boutin (1990). I have also raved on about this topic in Chapter 8 of my 2013 book on rodent populations if you wish more details.

Allen, M.C., Clinchy, M. & Zanette, L.Y. (2022) Fear of predators in free-living wildlife reduces population growth over generations. Proceedings of the National Academy of Sciences (PNAS), 119, e2112404119. doi: 10.1073/pnas.2112404119.

Boutin, S. (1990). Food supplementation experiments with terrestrial vertebrates: patterns, problems, and the future. Canadian Journal of Zoology 68(2): 203-220. doi: 10.1139/z90-031.

Brown, J.S. & Kotler, B.P. (2007) Foraging and the ecology of fear. Foraging: Behaviour and Ecology (eds. D.W. Stephens, J.S. Brown & R.C. Ydenberg), pp. 437-448.University of Chicago Press, Chicago. ISBN: 9780226772646

Krebs, C.J. (2013) Chapter 8, The Food Hypothesis. In Population Fluctuations in Rodents. University of Chicago Press, Chicago. ISBN: 978-0-226-01035-9

On Cats and Birds and Policy Gaps

Many people in western societies like to keep cats as pets, and with that simple observation we run into two problems that require resolution. First, cats are killers of wildlife, particularly birds but also an array of other small prey. Most people do not believe this, because cats are adored and make good, if somewhat disinterested pets. So, my first point might be that if you think cats are not killers, I invite you to keep another cat like a mountain lion for a pet. But we need some data on the kill rate of cats. Before we begin this search, we should note that cats can be kept inside dwellings or in cat runs with no access to birds or other prey. If this is the case, no problem exists for wildlife, and you can skip to the bottom of this blog for one other issue to recognize.

How much mortality can be traced to cats roaming out of doors? This will include normal house cats let out to roam at night, as well as wild cats that have been discarded by their owners into the wild. There is extensive literature on cats killing birds. If you want a brief introduction Greenwall et al. (2019) discuss a nesting colony of Fairy Terns, a threatened species of Australian seabird, along a beach in southwestern Australia. With detailed observations and photographic data, they recorded the complete failure of all 111 nests in this colony with the loss of all tern chicks in the early summer of 2018. The predator was a single desexed feral cat. Many local governments allow the capture of feral cats with the protocol that they are desexed and then released back into the environment. Clearly desexing and release does not remove the problem.

The domestic cat has been spread world-wide, so that the cat problem is not a local one. Li et al. (2021) completed a survey of feral cat kill rates in the eastern part of China and found that the minimum annual loss of wildlife to feral cats was in the range of 2.7-5.5 billion birds, and 3.6-9.8 billion mammals, as well as large numbers of amphibians, reptiles, and fish. In gardens in Western Europe cat predation on ringed birds studied with precise data showed that up to 25% of dead birds were killed by cats, but these data varied greatly among species (Pavisse et al. 2019). For the European Robin which often feeds on the ground 40% of all ringed birds were killed by cats, for the European Greenfinch the figure was 56% of ringed birds killed. These are just two examples of an extensive literature on cat kills going back many years (Calvert et al. 2013).

What can we do about this predation? As with too many conservation issues the answer is simple but difficult to implement: Ban all cats from free-ranging unless they are on a leash and under control. Keep cats in the house or in special cat runs that are confined outdoors. Ban completely stupid programs of catching feral cats, sterilizing them, and releasing them back to the wild to continue their killing. Cats may make marvellous pets but need to be kept indoors. Many people would support these measures but many cat owners would disagree about such measures. Some progress is being made in urban environments in which some suburbs do not permit cats to roam freely.

Feral cats are a serious issue in Australia because they attack many threatened birds and reptiles (Doherty et al. 2019). In this case a federal environmental policy to kill 2 million cats is popular but from a conservation viewpoint still a poor policy. We do not know if killing 2 million cats is too much or too few, and without specific goals for conservation and careful monitoring of bird populations widespread killing my not achieve the goal of protection for threatened species. Eradications of cats on islands is often feasible, but no mainland eradication is currently possible.

As conservation biologists know too well, when humans are the problem, wise policies may not be implemented. So, the second issue and the bottom line might be to consider the human costs of cat ownership. Adhikari et al. (2020) report a highly significant association between the risk of dying from colon cancer and cat ownership. These results are not confounded by sedentary lifestyle, cigarette smoking or socio-economic status. In a similar study Adhikari et al. (2019) found that living with a cat significantly increased the death rate from lung cancer among women. The cause of these associations cannot yet be deciphered but are postulated to result from mycotoxins, toxic secondary metabolites produced by fungi (moulds) in cereal crops used in cat food. Aflatoxin is a mycotoxin that produces well-known chemicals that are seriously toxic to animals and humans.

These kinds of studies of associations arising from surveys can be tossed off by the typical comments ‘these-things-do-not-concern-my cats’ or ‘that there is no proof of the exact cause’ so if you are concerned you might investigate the literature on both mycotoxins and the diseases that cats carry.

It is up to humans to solve human problems, but up to conservation biologists to point out the detrimental effects of household pets and their feral cousins on wildlife. The present situation is a complete policy failure by governments at all levels. Good science is relatively easy, good policy is very difficult.

Adhikari, Atin, Adhikari, A., Jacob, N. K., and Zhang, J. (2019). Pet ownership and the risk of dying from lung cancer, findings from an 18 year follow-up of a US national cohort. Environmental Research 173, 379-386. doi: 10.1016/j.envres.2019.01.037.

Adhikari, Atin, Adhikari, A., Wei, Y. D., and Zhang, J. (2020). Association between pet ownership and the risk of dying from colorectal cancer: an 18-year follow-up of a national cohort. Journal of Public Health 28, 555-562. doi: 10.1007/s10389-019-01069-1.

Calvert, A.M., Bishop, C.A., Elliot, R.D., Krebs, E.A., Kydd, T.M., Machtans, C.S., Robertson, G.J., 2013. A synthesis of human-related avian mortality in Canada. Avian Conservation and Ecology 8: 11. doi 10.5751/ACE-00581-080211.

Doherty, T.S., Driscoll, D.A., Nimmo, D.G., Ritchie, E.G., and Spencer, R. (2019). Conservation or politics? Australia’s target to kill 2 million cats. Conservation Letters 12, e12633. doi: 10.1111/conl.12633.

Li, Yuhang, Wan, Yue, Shen, Hua, Loss, S.R., Marra, P.P., and Li, Zhongqiu (2021). Estimates of wildlife killed by free-ranging cats in China. Biological Conservation 253, 108929. doi: 10.1016/j.biocon.2020.108929.

Greenwell, C.N., Calver, M.C., and Loneragan, N.R. (2019). Cat Gets Its Tern: A Case Study of Predation on a Threatened Coastal Seabird. Animals 9, 445. doi: 10.3390/ani9070445.

Pavisse, R., Vangeluwe, D., and Clergeau, P. (2019). Domestic Cat Predation on Garden Birds: An Analysis from European Ringing Programmes. Ardea 107, 103-109. doi: 10.5253/arde.v107i1.a6.

Blaming Climate Change for Ecological Changes

The buzz word for all ecological applications for funding and for many submitted papers is climate change. Since the rate of climate change is not something ecologists can control, there are only two reasons to cite climate change as a reason to fund current ecological research. First, since change is continuous in communities and ecosystems, it would be desirable to determine how many of the observed changes might be caused by climate change. Second, it might be desirable to measure the rate of change in ecosystems, correlate these changes to some climate variable, and then use these data as a political and social tool to stimulate politicians to do something about greenhouse gas emissions. The second approach is that taken by climatologists who blame hurricanes and tornadoes on global warming. There is no experimental way to trace any particular hurricane to particular amounts of global warming, so it is easy for critics to say these are just examples of weather variation of which we have measured much over the last 150 years and paleo-ecologists have traced over tens of thousands of years using proxies from tree rings and sediment cores. If we are to use the statistical approach we need a large enough sample to argue that extreme events are becoming more frequent, and that might take 50 years by which time the argument would be made too late to request proper action.

The second approach to prediction in ecology is fraught with problems, as outlined in Berteaux et al. (2006) and Dietze (2017). The first approach has many statistical problems as well in selecting a biologically coherent model that can be tested by in a standard scientific manner. Since there are a very large number of climate variables, the possibility of spurious correlations is excessive, and the only way to avoid these kinds of results is to be predictive and to have a biological causal chain that is testable. Myers (1998) reviewed all the fishery data for predictive models of juvenile recruitment that used environmental variables as predictors and data was subsequently collected and tested with the published model. The vast majority of these aquatic models failed when retested but a few were very successful. The general problem is that model failures or successes might not be published so even this approach can be biased if only a literature survey is undertaken. The take home message from Myers (1998) was that almost none of the recruitment-environment correlations were being used in actual fishery management.

How much would this conclusion about the failure of environmental models in fishery management apply to other areas in ecology? Mouquet et al. (2014) pointed out that predictions could be classified as ‘explanatory’ or ‘anticipatory’ and that “While explanatory predictions are necessarily testable, anticipatory predictions need not be…….In summary, anticipatory predictions differ from explanatory predictions in that they do not aim at testing models and theory. They rely on the assumption that underlying hypotheses are valid while explanatory predictions are based on hypotheses to be tested. Anticipatory predictions are also not necessarily supposed to be true.” (page 1296). If we accept these distinctions, we have (I think) a major problem in that many of the predictive models put forward in the ecological literature are anticipatory, so they would be of little use to a natural resource manager who requires an explanatory model.

If we ignore this problem with anticipatory predictions, we can concentrate on explanatory predictions that are useful to managers. One major set of explanatory predictions in ecology are those associated with range changes in relation to climate change. Cahill et al. (2014) examined the conventional hypothesis that warm-edge range limits are set by biotic interactions rather than abiotic interactions. Contrary to expectations, they found in 125 studies that abiotic factors were more frequently supported as setting warm-edge range limits. Clearly a major paradigm about warm-edge range limits is of limited utility.

Explanatory predictions are not always explicit. Mauck et al. (2018) for example developed a climate model to predict reproductive success in Leach’s storm petrel on an island off New Brunswick in eastern Canada. From 56 years of hatching success they concluded that annual global mean temperature during the spring breeding season was the single most important predictor of breeding success. They considered only a few measures of temperature as predictor variables and found that a quadratic form of annual global mean temperature was the best variable to describe the changes in breeding success. The paper speculates about how global or regional mean temperature could possibly be an ecological predictor of breeding success, and no mechanisms are specified. The actual data on breeding success are not provided in the paper, even as a temporal plot. Since global temperatures were rising steadily from 1955 to 2010, any temporal trend in any population parameter that is rising would correlate with temperature records. The critical quadratic relationship in their analysis suggests that a tipping point was reached in 1988 when hatching success began to decline. Whether or not this is a biologically correct explanatory model can be determined by additional data gathered in future years. But it would be more useful to find out what the exact ecological mechanisms are.

If the ecological world is going to hell in a handbasket, and temperatures however measured are going up, we can certainly construct a plethora of models to describe the collapse of many species and the rise of others. But this is hardly progress and would appear to be anticipatory predictions of little use to advancing ecological science, as Guthery et al. (2005) pointed out long ago. Someone ought to review and evaluate the utility of AIC methods as they are currently being used in ecological and conservation science for predictions.

Berteaux, D., Humphries, M.M., Krebs, C.J., Lima, M., McAdam, A.G., Pettorelli, N., Reale, D., Saitoh, T., Tkadlec, E., Weladji, R.B., and Stenseth, N.C. (2006). Constraints to projecting the effects of climate change on mammals. Climate Research 32, 151-158. doi: 10.3354/cr032151.

Cahill, A.E., Aiello-Lammens, M.E., Fisher-Reid, M.C., Hua, X., and Karanewsky, C.J. (2014). Causes of warm-edge range limits: systematic review, proximate factors and implications for climate change. Journal of Biogeography 41, 429-442. doi: 10.1111/jbi.12231.

Dietze, M.C. (2017). Prediction in ecology: a first-principles framework. Ecological Applications 27, 2048-2060. doi: 10.1002/eap.1589.

Guthery, F.S., Brennan, L.A., Peterson, M.J., and Lusk, J.J. (2005). Information theory in wildlife science: Critique and viewpoint. Journal of Wildlife Management 69, 457-465. doi: 10.1890/04-0645.

Mauck, R.A., Dearborn, D.C., and Huntington, C.E. (2018). Annual global mean temperature explains reproductive success in a marine vertebrate from 1955 to 2010. Global Change Biology 24, 1599-1613. doi: 10.1111/gcb.13982.

Mouquet, N., Lagadeuc, Y., Devictor, V., Doyen, L., and Duputie, A. (2015). Predictive ecology in a changing world. Journal of Applied Ecology 52, 1293-1310. doi: 10.1111/1365-2664.12482.

Myers, R.A. (1998). When do environment-recruitment correlations work? Reviews in Fish Biology and Fisheries 8, 285-305. doi: 10.1023/A:1008828730759.