Category Archives: Conservation Biology

On the Forest Industry and why we might worry about our forests

This blog differs from my usual in being a plea to read one book on the forest industry in Australia and why we might worry in every country about our forestry practices. The book is by David Lindenmayer and in it is a capsular summary of the evidence presented about the state of the forest industry in Australia and the myths that are continually presented about sustainability of forests wherever they are. If you teach students or adults about environmental problems, you could discuss whether these myths apply to your part of the world. For more details on the evidence behind these statements read the book. Much action is needed to eliminate these myths.

Lindenmayer, David. (2024) “The Forest Wars” Allen and Unwin, Sydney, Australia. ISBN: 978 76147 075 2.  Available as a paperback or a kindle book from Allen and Unwin.
Allen and Unwin: The Forest Wars

I copy here the opening 2 pages of this book:

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The Myths

  1. The forest will grow back.
  2. Animals just move on.
  3. Only a small proportion of the forestry estate is logged.
  4. Only small patches of the forest are logged each year, so the forest remains intact.
  5. Forestry departments do proper pre-logging surveys for animals.
  6. Detecting more animals means a species is OK.
  7. Retaining a few big trees on logged sites will save the animals.
  8. We can solve the animal housing crisis with nest boxes.
  9. Selective logging is better than clearfelling.
  10. It is good to ‘clean up’ storm and fire-damaged forest.
  11. Forest gardening heals country.
  12. We need to log forests to keep them safe.
  13. Forests will be less flammable if we thin them.
  14. Logging has the same effects as wildfires.
  15. We can burn our way out of the wildfire problem.
  16. Tall, wet forests [in Australia] were open and park-like at the time of the British invasion.
  17. Cultural burning was practiced all over Australia.
  18. Most wood cut in a logging coupe gets milled for sawn lumber.
  19. We need native forest logging to build and furnish our houses.
  20. Without native forest logging we will bring in imports that kill Orangutans.
  21. Native forest logging is value added.
  22. Logging is good business.
  23. Logging is more lucrative than other forest uses.
  24. Native forest logging employs tens of thousands of people.
  25. Australia has the best regulated native forest logging industry in the world.
  26. Government regulators will keep the bastards honest.
  27. Regulations protect old-growth forest.
  28. Regional forest agreements solved the forest wars.
  29. Melbourne is not Moscow – the spy who came in from the forest.
  30. Native forest logging is sustainable.
  31. Forest industries are enduring industries.
  32. There is nothing to worry about – carbon dioxide is natural.
  33. The best way to tackle climate change is to cut down forests and regrow them.
  34. Burning biomass from forests is better than burning fossil fuels.
  35. We already have enough reserves.
  36. Intact forests are selected for reserves.
  37. Politicians keep their promises about preserving forests.

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With thanks to David Lindemayer and his research group in Canberra.

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Whither Demography in an Era of Biodiversity Science?

Biodiversity science has overtaken traditional ecological science in an important way that bears some discussion. Biodiversity science seeks as its main goal to protect species from declining to extinction. It overlaps traditional population and community ecology partly by concentrating on iconic species that are declining in abundance and thus trying to prevent species loss, but the major focus of biodiversity science is on the species composition of communities and ecosystems and trying to understand what factors are driving deleterious changes. This task is difficult to complete currently because of a shortage of research time, person-power and money, so we are driven to select relatively few ecosystems to concentrate our conservation efforts upon. If we cannot do everything for all species, we must choose what to do at the present time, and this releases a cascade of discussions and arguments about what species are ‘flagship’, “umbrella”, or “keystone” in any particular community or ecosystem (Barua 2011).

Now we can go in two directions. We can take the simplest route and say that all species are of equal importance, so the objective of biodiversity science becomes ‘occupancy” – is species X still existing in ecosystem Y? Occupancy can be established in a variety of ways from simple visual sightings, traps, cameras, e-DNA, to electronic sound recording devices. Occupancy for species in a particular ecosystem is a useful parameter for biodiversity studies but it is alpha-level ecology for understanding community or ecosystem dynamics. Determining occupancy every month, year, or decade will provide a start in community and ecosystem understanding but in order to achieve its goal as a science it needs population and community ecology to measure and understand the dynamics underlying occupancy, and this is the more complicated route that we can take. The defining science for this second level of understanding comes from dynamics, both population and community dynamics.

Population dynamics is necessary for determining if a particular species is declining in numbers or biomass, and what the causes are of the observed trends. We are led into demography, the measurement of births, deaths, and movements in animals and the equivalent parameters in plants. But now we run into the most serious problem of determining what parameters are the causal agents of declines in abundance and what procedures will alleviate species declines. If we have many species in our community or ecosystem, the requirements for research are extravagant, given the current workers and dollars currently available for environmental science. All ecologists want to protect biodiversity but how might we best achieve that goal?

We fall back at this point into simple general procedures for biodiversity conservation like designation of national parks or protected areas with the hope that the biodiversity of the designated area will not decline. We do not have the person-power to have frequent occupancy surveys for any national park, much less to have the investigations of why an iconic species is declining in an area. At present we must fall back on ‘umbrella species’ or ‘flagship species’ (Simberloff 1998). There is an extensive literature on this approach to biodiversity conservation and recent reviews, some critical (Tälle et al. 2023), others somewhat more positive (Sumbh and Hof 2022, Clark-Wolf et al. 2024), combining this approach with food web structure (Wang and Zhou 2023).   

Complicating the whole issue of protecting biodiversity is the issue of cryptic species, undescribed species, and rare species that are capable of taxonomic and ecological resolution but only at a large cost and a long timeframe to achieve results (Cheng et al. 2024). Once we are successful in protecting our communities and ecosystems, we immediately face the demographic issue of what affects the abundance of all the species of interest, and then the social and political issue of the funds available for conservation of these species. We need to bring the approaches of biodiversity science and classical demographic ecology together to achieve conservation goals. We can do this only by recognizing that knowing occupancy is not enough to achieve conservation success, and we need to follow up with population and community ecology within the context of food webs so that we can understand trends in abundance and finally propose possible actions for conservation management. We have much to do.

Barua, M. (2011) Mobilizing metaphors: the popular use of keystone, flagship and umbrella species concepts. Biodiversity and Conservation, 20, 1427-1440.doi:10.1007/s10531-011-0035-y.

Cheng, R., Luo, A., Orr, M., Ge, D., Houu, Z.e., Qu, Y., Guo, B., Zhang, F., Sha, Z., Zhao, Z., Wang, M., Shi, X., Han, H., Zhou, Q., Li, Y., Liu, X., Shao, C., Zhang, A., Zhou, X. & Zhu, C. (2024) Cryptic diversity begets challenges and opportunities in biodiversity research. Integrative Zoology, (in press). doi: 10.1111/1749-4877.12809.

Clark-Wolf, T.J., Holt, K.A., Johansson, E., Nisi, A.C., Rafiq, K., West, L., Boersma, P.D., Hazen, E.L., Moore, S.E. & Abrahms, B. (2024) The capacity of sentinel species to detect changes in environmental conditions and ecosystem structure. Journal of Applied Ecology, (in press). doi: 10.1111/1365-2664.14669.

Simberloff, D. (1998) Flagships, umbrellas, and keystones: is single-species management passe in the landscape era? Biological Conservation, 83, 247-257.doi: 10.1016/S0006-3207(97)00081-5.

Sumbh, O. & Hof, A.R. (2022) Can pikas hold the umbrella? Understanding the current and future umbrella potential of keystone species Pika (Ochotona spp.). Global Ecology and Conservation, 38, e02247.doi: 10.1016/j.gecco.2022.e02247.

Tälle, M., Ranius, T. & Öckinger, E. (2023) The usefulness of surrogates in biodiversity conservation: A synthesis. Biological Conservation, 288; e110384. doi: 10.1016/j.biocon.2023.110384.

Wang, Q., Li, X.C. & Zhou, X.H. (2023) New shortcut for conservation: The combination management strategy of “keystone species” plus “umbrella species” based on food web structure. Biological Conservation, 286, 110265.doi: 10.1016/j.biocon.2023.110265.

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 .

Biodiversity Science

Protecting biodiversity is a goal of most people who value the environment. My question is what are the goals of biodiversity science and how do we achieve them? Some history is in order here. The term ‘biodiversity’ was coined in the 1980s as the complete biosphere including all species and ecosystems on Earth. The idea of cataloguing all the species on Earth was present many decades before this time, since the origin of the biological sciences. By the 1990s ‘biodiversity conservation’ became a popular subject and has grown greatly since then as a companion to CO2 emissions and the climate change problem. The twin broad goals of biodiversity science and biodiversity conservation are (1) to name and describe all the species on Earth, and (2), to protect all species from extinction, preventing a loss of biodiversity. How can we achieve these two goals?

The first goal of describing species faces challenges from disagreements over what a species is or is not. The old description of a species was to describe what group it was part of, and then how different this particular species was from other members of the group. In the good old days this was primarily based on reproductive incompatibility between species, if no successful reproduction, must be a new species. This simple common-sense view was subject to many attacks since some organisms that we see as different can in fact interbreed. Lions and tigers breed together and are an example, but if their interbred offspring are sterile, clearly, they are two different species. But many arguments arose because there was no data available for 99% of species to know if they could interbreed or not. The fallback position has been to describe the anatomy of a potential species and its relatives and judge from anatomy how different they were. Endless arguments followed, egged on by naturalists who pointed out that if the elephants in India were separated by a continent from elephants in Africa, clearly, they must be different species defined by geography. Many academic wars were fought over these issues.

Then in 1953 the structure of DNA was unravelled, and a new era dawned because with advances in technology of decoding genes we could describe species in a completely new way by determining how much DNA they had in common. But what is the magic percentage of common DNA? Humans and chimpanzees have 98.6% of their DNA in common, but despite this high similarity no one argues that they are the same species.

Despite this uncertainty the answer now seems much simpler: sequence the DNA of everything and you will have the true tree of life for defining separate species. While this was a dream 20 years ago, it is now a technical reality with rapid sequencing methods to help us get criminals and define species. Problem (1) solved?

Enter the lonely ecologist into this fray. Ecologists do not just want names, they wish to understand the function of each of the ‘species’ within communities and ecosystems, how does all this biodiversity interact to produce what we see in the landscape? For the moment we have approximately 10 million species on Earth, but somewhere around 80% of these ‘species’ are still undescribed. So now we have a clash of biodiversity visions, we cannot describe all the species on Earth even on the time scale of centuries, so we cannot achieve goal (1) of biodiversity science in any reasonable time. We have measured the DNA sequence of thousands of organisms that we can capture but we cannot describe them formally as species in the older sense. Perhaps it is akin to having all the phone numbers in the New York City phone book but not knowing to whom the numbers belong.

But the more immediate problem comes with objective (2) to prevent extinctions. Enter the conservation ecologist. The first problem is discussed above, we ecologists have no way of knowing how many species are in danger of extinction. We must look for rare or declining species, but we have complete inventory for few places on Earth. We must concentrate on large mammals and birds, and hope that they act as umbrella species and represent all of biodiversity. When we do have information on threatened species, for the most part there is no money to do the ecological studies needed to reverse declines in abundance. If there is money to list species and give a recovery plan on paper, then we find there is no money to implement the recovery plan. The Species-At-Risk act in Canada was passed in 2002 and has generated many recovery plans mostly for vertebrate species that have come to their attention. Almost none of these recovery plans have been completed, so in general we are all in favour of preventing extinctions but only it if costs us nothing. By and large the politics of preventing extinctions is very strongly supported, but the economic value of extinctions is nearly zero.

None of this is very cheery to conservation biologists. Two approaches have been suggested. The first is Big Science, use satellites and drones to scan the Earth every year to describe changes in landscapes and from these images infer biodiversity ‘health’. Simple and very expensive with AI to the rescue. But while we can see largescale landscape changes, the crux is to do something about them, and it is here that we fail because of the wall of climate change that we have no control over at present. Big Science may well assist us in seeing patterns of change, but it produces no path to understanding food webs or mediating changes in threatened populations. The second is small-scale biodiversity studies that focus on what species are present, how their numbers are changing, and what are the causes of change. Difficult, possible, but very expensive because you must put biologists in the field, on the ground to do the relevant measurements over a long-time frame. The techniques are there to use, thanks to much work on ecological methods in the past. What is missing again is the money. There are a few good examples of this small-scale approach but without good organization and good funding many of these attempts stop after too few years of data.

We are left with a dilemma of a particular science, Biodiversity Science, that has no way of achieving either of its two main objectives to name and to protect species on a global level. On a local level we can adopt partial methods of success by designating and protecting national parks and marine protected areas, and by studying only a few important species, the keystone species of food webs. But then we need extensive research to determine how to protect these areas and species from the inexorable march of climate change, which has singlehandedly complicated achieving biodiversity science’s two goals. Alas at the present time we may have another science to join the description of economics as a “dismal science” And we have not even started to discuss bacteria, viruses, and fungi.

Coffey, B. & Wescott, G. (2010) New directions in biodiversity policy and governance? A critique of Victoria’s Land and Biodiversity White Paper. Australasian Journal of Environmental Management 17: 204-214. doi: 10.1080/14486563.2010.9725268.

Donfrancesco, V., Allen, B.L., Appleby, R., et al. (2023) Understanding conflict among experts working on controversial species: A case study on the Australian dingo. Conservation Science and Practice 5: e12900. doi: 10.1111/csp2.12900.

Ritchie, J., Skerrett, M. & Glasgow, A. (2023) Young people’s climate leadership in Aotearoa. Journal of Peace Education, 12-2023: 1-23. doi: 10.1080/17400201.2023.2289649.

Sengupta, A., Bhan, M., Bhatia, S., Joshi, A., Kuriakose, S. & Seshadri, K.S. (2024) Realizing “30 × 30” in India: The potential, the challenges, and the way forward. Conservation Letters 2024, e13004. doi: 10.1111/conl.13004.

Wang, Q., Li, X.C. & Zhou, X.H. (2023) New shortcut for conservation: The combination management strategy of “keystone species” plus “umbrella species” based on food web structure. Biological Conservation 286: 110265.doi. 10.1016/j.biocon.2023.110265.

On Ecology and Medicine

As I grow older and interact more with doctors, it occurred to me that the two sciences of medicine and ecology have very much in common. That is probably not a very new idea, but it may be worth spending time on looking at the similarities and differences of these two areas of science that impinge on our lives. The key question for both is how do we sort out problems? Ecologists worry about population, community and ecosystem problems that have two distinguishing features. First, the problems are complex and the major finding of this generation of ecologists is to begin to understand and appreciate how complex they are. Second, the major problems that need solving to improve conservation and wildlife management are difficult to study with the classical tools of experimental, manipulative scientific methods. We do what we can to achieve scientific paradigms but there are many loose ends we can only wave our hands about. As an example, take any community or ecosystem under threat of global warming. If we heat up the oceans, many corals will die along with the many animals that depend on them. But not all corals will die, nor will all the fish and invertebrate species, and the ecologists is asked to predict what will happen to this ecosystem under global warming. We may well understand from rigorous laboratory research about temperature tolerances of corals, but to apply this to the real world of corals in oceans undergoing many chemical and physical changes we can only make some approximate guesses. We can argue adaptation, but we do not know the limits or the many possible directions of what we predict will happen.

Now consider the poor physician who must deal with only one species, Homo sapiens, and the many interacting organs in the body, the large number of possible diseases that can affect our well-being, the stresses and strains that we ourselves cause, and the physician must make a judgement of what to do to solve your particular problem. If you have a broken arm, it is simple thankfully. If you have severe headaches or dizziness, many different causes come into play. There is no need to go into details that we all appreciate, but the key point is that physicians must solve problems of health with judgements but typically with no ability to do the kinds of experimental work we can do with mice or rabbits in the laboratory. And the result is that the physician’s judgements may be wrong in some cases, leading possibly to lawyers arguing for damages, and one appreciates that once we leave the world of medical science and enter the world of lawyers, all hope for solutions is near impossible.

There is now some hope that artificial intelligence will solve many of these problems both in ecological science and in medicine, but this belief is based on the premise that we know everything, and the only problem is to find the solutions in some forgotten textbook or scientific paper that has escaped our memory as humans. To ask that artificial intelligence will solve these basic problems is problematic because AI depends on past knowledge and science solves problems by future research.

Everyone is in favour of personal good health, but alas not everyone favours good environmental science because money is involved. We live in a world where major problems with climate change have had solutions presented for more than 50 years, but little more than words are presented as the solutions rather than action. This highlights one of the main differences between medicine and ecology. Medical issues are immediate since we have active lives and a limited time span of life. Ecological issues are long-term and rarely present an immediate short-term solution. Setting aside protected areas is in the best cases a long-term solution to conservation issues, but money for field research is never long term and ecologists do not live forever. Success stories for endangered species often require 10-20 years or more before success can be achieved; research grants are typically presented as 3- or 5-year proposals. The time scale we face as ecologists is like that of climate scientists. In a world of immediate daily concerns in medicine as in ecology, long-term problems are easily lost to view.

There has been an explosion of papers in the last few years on artificial intelligence as a potentially key process to use for answering both ecological and medical questions (e.g. Buchelt et al. 2024, Christin, Hervet, and Lecomte, 2019, Desjardins-Proulx, Poisot, & Gravel, 2019). It remains to be seen exactly how AI will help us to answer complex questions in ecology and medicine. AI is very good in looking back, but will it be useful to solve our current and future problems? Perhaps we still need to continue training good experimental scientists in ecology and in medicine.  

Buchelt, A., Buchelt, A., Adrowitzer, A. & Holzinger, A. (2024) Exploring artificial intelligence for applications of drones in forest ecology and management. Forest Ecology and Management, 551, 121530. doi: 10.1016/j.foreco.2023.121530.

Christin, S., Hervet, É. & Lecomte, N. (2019) Applications for deep learning in ecology. Methods in Ecology and Evolution, 10, 1632-1644. doi: 10.1111/2041-210X.13256.

Desjardins-Proulx, P., Poisot, T. & Gravel, D. (2019) Artificial Intelligence for ecological and evolutionary synthesis. Frontiers in Ecology and Evolution, 7. doi: 10.3389/fevo.2019.00402.

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.

The Problem of Evidence in Ecology

The good news is that the general public are becoming more concerned about the problems of wildlife management and conservation in general. The bad news arising from this interest is the lack of understanding exhibited by many of the comments in the media about ecological problems. This leads to a suggestion that we need an ecological “fact checking” team that looks at what is said about broad scale environmental issues and points out how much evidence there is for what is stated in the media. My interest in this issue is driven by so many news stories that are stated as fact with very little scientific understanding. Too many well-meaning reports fly around the media that border on complete error or complete nonsense. One consequence of this problem is a failure of evidence-based decision making for ecological problems (Christie et al. 2022).

This is not of course a problem confined to ecological science as you can see by reading nonsense claims about medical issues like Covid. It will not go away and with the climate crisis the number of ‘experts’ has multiplied. The problem comes down to the issue of evidence and how we evaluate evidence. A partial solution to this is better education about what is evidence in ecology as well as all of science. We need to teach workshops or courses on concrete examples of what is suggested to be evidence in ecological papers. The first step might be to analyse one or a few papers with the following procedure:

  1. What is the major conclusion of the paper?
  2. What data are presented to reach this conclusion?
  3. What background assumptions are being made to move from data to conclusions?

These questions lead us back to basic questions illustrated well by statistical inference. What is the ‘population’ to which the major conclusions apply? There is very little discussion of this in most ecological papers and the consequence can be overgeneralizations. Suppose for example we are examining the hypothesis that the geographic range of a species set is moving toward the poles because of a warming climate. We must for practical purposes restrict our study to a small set of species, so this is a major assumption that the species selected are a random sample of the biota under discussion. Another limitation is that it may be difficult to isolate climate change without considering for example human disturbances to the landscape from forestry and agriculture. A consequence of these complications is that our major conclusion for all this research rests on minimal data. So, a conclusion might be that we need to design further extensive studies. But perhaps of the 6 species under study, 4 are moving as the climate hypothesis predicts, but one is not moving at all, and one is moving in the opposite direction to what is predicted. Do we now turn our attention to these anomalous species that do not follow our major hypothesis? Or should we be happy that most of our candidate species follow the rule specified in our major conclusion?

       By doing manipulative experiments ecologists attempt to insert more rigor into their conclusions, but many of the generic questions mentioned above apply equally to these experimental designs. If we do a set of experiments in Iowa and in Germany, should we get the same results? We are back to the question of generality in all our studies. We hope for global rules, but experiments are all limited in time and space.

Can we escape all these bottlenecks with models that capture the generality and behave according to our assumptions? But models suffer from the same problems that make empirical studies difficult – what are the hidden assumptions? Taper et al. (2021) discuss the problem of errors arising from model misspecification in evaluating empirical data. Perhaps every ecological publication should end with an additional short section listing the assumptions made in reaching the major conclusions of the research.

These points come to the fore when we attempt to predict future environmental changes. A simple example is the hypothesis that, by humans increasing CO2 in the atmosphere, plants will increase photosynthesis and thus negate part or all the effects of climate change on our current ecosystems. This has caused much discussion ranging from planting more trees to alleviate climate change to relying on engineering solutions to climate change.

The bottom line that we should all recognize is that our predictions in ecology and our understanding of ecosystem changes are more limited than we admit. We know that we cannot rely on the old adage of the equilibrium hypothesis that “Mother Nature will take care of the earth” so all will be well. Wisdom always relies on critical evaluations which are too often lost in the media of our current world.

An important alternative approach is illustrated by the Conservation Evidence Journal and the approaches recommended by Sutherland et al. (2022) to specify local actions that can improve the conservation status of particular species or groups of species, for example by reintroducing birds to islands or areas from which they have been extirpated. The dichotomy here is a divide between the particular and the general, from short-term local questions to long-term general questions (Saunders et al. 2020). The hope is that progress on local questions will gradually inform the dominant global theories of ecology to bring them together and support the “devil in the details’ approach that can define ecological progress in our time (Sutherland et al. 2021).

Christie, A.P., 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 .

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.

Sutherland, W.J., Downey, H., Frick, W.F., Tinsley-Marshall, P. & 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.

Sutherland, W.J. et al. (2022) Creating testable questions in practical conservation: a process and 100 questions. Conservation Evidence Journal, 19, 1-7.doi: 10.52201/CEJ19XIFF2753.

Taper, M., Lele, S., Ponciano, J., Dennis, B. & Jerde, C. (2021) Assessing the global and local uncertainty of scientific evidence in the presence of model misspecification Frontiers in Ecology and Evolution, 9, 679155.doi: 10.3389/fevo.2021.679155.

The Problem of Time in Ecology

There is a problem in doing ecological studies that is too little discussed – what is the time frame of a good study? The normal response would be that the time frame varies with each study so that no guidelines can be provided. There is increasing recognition that more long-term studies are needed in ecology (e.g. Hughes et al. 2017) but the guidelines remain unclear.

The first issue is usually to specify a time frame, e.g. 5 years, 10 years. But this puts the cart before the horse, as the first step ought to be to define the hypothesis being investigated. In practice hypotheses in many ecological papers are poorly presented and there should not be one hypothesis but a series of alternative hypotheses. Given that, the question of time can be given with more insight. How many replicated time periods do you need to measure the ecological variables in the study? If your time scale unit is one year, 2 or 3 years is not enough to come to any except very tentative conclusions. We have instantly fallen into a central dilemma of ecology – studies are typically planned and financed on a 3–5-year time scale, the scale of university degrees.

Now we come up against the fact of climate change and the dilemma of trying to understand a changing system when almost all field work assumes an unchanging environment. Taken to some extreme we might argue that what happens in this decade tells us little about what will happen in the next decade. The way around this problem is to design experiments to test the variables that are changing ahead of time, e.g., what a 5⁰C temperature increase will do to the survival of your corals. To follow this approach, which is the classic experimental approach of science, we must assume we know the major variables affecting our population or community changes. At present we do not know the answer to this question, and we rely on correlations of a few variables as predictors of how large a change to expect.

There is no way out of this empirical box, which defines clearly how physics and chemistry differ from ecology and medicine. There are already many large-scale illustrations of this problem. Forest companies cut down old-growth timber on the assumption that they can get the forest back by replanting seedlings in the harvested area. But what species of tree seedlings should we replant if we are concerned that reforestation often operates on a 100–500-year time scale? And in most cases, there is no consideration of the total disruption of the ecosystem, and we ignore all the non-harvestable biodiversity. Much research is now available on reforestation and the ecological problems it produces. Hole-nesting birds can be threatened if old trees with holes are removed for forestry or agricultural clearing (Saunders et al. 2023). Replanting trees after fire in British Columbia did not increase carbon storage over 55 years of recovery when compared with unplanted sites (Clason et al. 2022). Consequently, in some forest ecosystems tree planting may not be useful if carbon storage is the desired goal.

At the least we should have more long-term monitoring of the survival of replanted forest tree seedlings so that the economics of planting could be evaluated. Short-term Australian studies in replanted agricultural fields showed over 4 years differences in survival of different plant species (Jellinek et al. 2020). For an on-the-ground point of view story about tree planting in British Columbia see:
https://thetyee.ca/Opinion/2023/11/02/Dont-Thank-Me-Being-Tree-Planter/. But we need longer-term studies on control and replanted sites to be more certain of effective restoration management. Gibson et al. (2022) highlighted the fact that citizen science over a 20-year study could make a major contribution to measuring the effectiveness of replanting. Money is always in short supply in field ecology and citizen science is one way of achieving goals without too much cost. 

Forest restoration is only one example of applied ecology in which long-term studies are too infrequent. The scale of restoration of temperate and boreal ecosystems is around 100 years, and this points to one of the main failures of long-term studies, that they are difficult to carry on after the retirement of the principal investigators who designed the studies.

The Park Grass Experiment begun in 1856 on 2.8 ha of grassland in England is the oldest ecological experiment in existence (Silvertown et al. 2006). As such it is worth a careful evaluation for the questions it asked and did not ask, for the scale of the experiment, and for the experimental design. It raises the question of generality for all long-term studies and cautions us about the utility and viability of many of the large-scale, long-term studies now in progress or planned for the future.

The message of this discussion is that we should plan for long-term studies for most of our critical ecological problems with clear hypotheses of how to conserve biodiversity and manage our agricultural landscapes and forests. We should move away from 2–3-year thesis projects on isolated issues and concentrate on team efforts that address critical long-term issues with specific hypotheses. Which says in a nutshell that we must develop a vision that goes beyond our past practices in scatter-shot, short-term ecology and at the same time avoid poorly designed long-term studies of the future.

Clason, A.J., Farnell, I. & Lilles, E.B. (2022) Carbon 5–60 Years After Fire: Planting Trees Does Not Compensate for Losses in Dead Wood Stores. Frontiers in Forests and Global Change, 5, 868024. doi: 10.3389/ffgc.2022.868024.

Gibson, M., Maron, M., Taws, N., Simmonds, J.S. & Walsh, J.C. (2022) Use of citizen science datasets to test effects of grazing exclusion and replanting on Australian woodland birds. Restoration Ecology, 30, e13610. doi: 10.1111/rec.13610.

Hughes, B.B.,et al. (2017) Long-term studies contribute disproportionately to ecology and policy. BioScience, 67, 271-281. doi.: 10.1093/biosci/biw185.

Jellinek, S., Harrison, P.A., Tuck, J. & Te, T. (2020) Replanting agricultural landscapes: how well do plants survive after habitat restoration? Restoration Ecology, 28, 1454-1463. doi: 10.1111/rec.13242.

Saunders, D.A., Dawson, R. & Mawson, P.R. (2023) Artificial nesting hollows for the conservation of Carnaby’s cockatoo Calyptorhynchus latirostris: definitely not a case of erect and forget. Pacific Conservation Biology, 29, 119-129. doi: 10.1071/PC21061.

Silvertown, J., Silvertown, J., Poulton, P. & Biss, P.M. (2006) The Park Grass Experiment 1856–2006: its contribution to ecology. Journal of Ecology, 94, 801-814. doi: 10.1111/j.1365-2745.2006.01145.x.