Tag Archives: conservation ecology

Whither Demography in an Era of Biodiversity Science?

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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?

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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.

Should Ecology Abandon Popper?

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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

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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

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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.

The Problem of Evidence in Ecology

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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 Ecological Outlook

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There is an extensive literature on ecological traps going back two decades (e.g. Schlaepfer et al. 2002, Kristan 2003, Battin 2004) discussing the consequences of particular species selecting a habitat for breeding that is now unsuitable. A good example is discussed in Lamb et al. (2017) for grizzly bears in southeastern British Columbia in areas of high human contact. The ecological trap hypothesis has for the most part been discussed in relation to species threatened by human developments with some examples of whole ecosystems and human disturbances (e.g. Lindenmayer and Taylor 2020). The concept of an ecological trap can be applied to the Whole Earth Ecosystem, as has been detailed in the IPCC 2022 reports and it is this global ecological trap that I wish to discuss.

The key question for ecologists concerned about global biodiversity is how much biodiversity will be left after the next century of human disturbances. The ecological outlook is grim as you can hear every day on the media. The global community of ecologists can ameliorate biodiversity loss but cannot stop it except on a very local scale. The ecological problem operates on a century time scale, just the same as the political and social change required to escape the global ecological trap. E.O. Wilson (2016) wrote passionately about our need to set aside half of the Earth for biodiversity. Alas, this was not to be. Dinerstein et al. (2019) reduced the target to 30% in the “30 by 30” initiative, subsequently endorsed by 100 countries by 2022. Although a noble political target, there is no scientific evidence that 30 by 30 will protect the world’s biodiversity. Saunders et al. (2023) determined that for North America only a small percentage of refugia (5– 14% in Mexico, 4–10% in Canada, and 2–6% in the USA) are currently protected under four possible warming scenarios ranging from +1.5⁰C to +4⁰C. And beyond +2⁰C refugia will be valuable only if they are at high latitudes and high elevations.

The problem as many people have stated is that we are marching into an ecological trap of the greatest dimension. A combination of global climate change and continually increasing human populations and impacts are the main driving factors, neither of which are under the control of the ecological community. What ecologists and conservationists can do is work on the social-political front to protect more areas and keep analysing the dynamics of declining species in local areas. We confront major political and social obstacles in conservation ecology, but we can increase our efforts to describe how organisms interact in natural ecosystems and how we can reduce undesirable declines in populations. All this requires much more monitoring of how ecosystems are changing on a local level and depends on how successful we can be as scientists to diagnose and solve the ecological components of ecosystem collapse.

As with all serious problems we advance by looking clearly into what we can do in the future based on what we have learned in the past. And we must recognize that these problems are multi-generational and will not be solved in any one person’s lifetime. So, as we continue to march into the ultimate ecological trap, we must rally to recognize the trap and use strong policies to reverse its adverse effects on biodiversity and ultimately to humans themselves. None of us can opt out of this challenge.

There is much need in this dilemma for good science, for good ecology, and for good education on what will reverse the continuing degradation of our planet Earth. Every bit counts. Every Greta Thunberg counts.

Battin, J. (2004) When good animals love bad habitats: ecological traps and the conservation of animal populations. Conservation Biology, 18, 1482-1491.

Dinerstein, E., Vynne, C., Sala, E., et al. (2019) A Global Deal For Nature: Guiding principles, milestones, and targets. Science Advances, 5, eaaw2869.doi: 10.1126/sciadv.aaw2869..

IPCC, 2022b. In: Skea, J., Shukla, P.R., et al. (Eds.), Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of theIntergovernmental Panel on Climate Change. Cambridge University Press. doi: www.ipcc.ch/report/ar6/wg3/.

Kristan III, W.B. (2003) The role of habitat selection behavior in population dynamics: source–sink systems and ecological traps. Oikos, 103, 457-468.

Lamb, C.T., Mowat, G., McLellan, B.N., Nielsen, S.E. & Boutin, S. (2017) Forbidden fruit: human settlement and abundant fruit create an ecological trap for an apex omnivore. Journal of Animal Ecology, 86, 55-65. doi. 10.1111/1365-2656.12589.

Lindenmayer, D.B. and Taylor, C. (2020) New spatial analyses of Australian wildfires highlight the need for new fire, resource, and conservation policies. Proceedings of the National Academy of Sciences 117, 12481-124485. doi. 10.1073/pnas.2002269117.

Saunders, S.P., Grand, J., Bateman, B.L., Meek, M., Wilsey, C.B., Forstenhaeusler, N., Graham, E., Warren, R. & Price, J. (2023) Integrating climate-change refugia into 30 by 30 conservation planning in North America. Frontiers in Ecology and the Environment, 21, 77-84. doi. 10.1002/fee.2592.

Schlaepfer, M.A., Runge, M.C. & Sherman, P.W. (2002) Ecological and evolutionary traps. Trends in Ecology & Evolution, 17, 474-480.

Wilson, E.O. (2016) Half-Earth: Our Planet’s Fight for Life. Liveright, New York. ISBN: 978-1-63149-252-5.

On Ignoring Evidence

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If you listen to the media in any form, you will find that you are bombarded with facts provided with no evidence. Unfortunately, this tendency has been moving into science in a way that is potentially dangerous. At worst such a move could call scientific information into disrepute. The current worst case is all the information we have been given on Covid vaccines, and the dispute whether we need any vaccines now for anything. Most scientists would classify these disputes as lunacy, but we are too polite to say this openly. Climate change is another current problem that has subdivided the public into four camps – (1) the climate has always changed back and forth in the past so we should not worry about it. (2) Human caused climate change is happening but there is nothing we as a small city or nation can do anything about, so carry on. (3) It is an emergency but fear not, science will find a technical solution like carbon capture that will take care of the problem. So again, we do not have to do anything. (4) It is a critical threat and demands immediate action to reduce greenhouse gas emissions.

Compounding the failure to recognize evidence, we mix the climate emergency issue with economics and GDP growth so that we can take no serious actions on the problem because economic growth will be affected. There is a hint of evidence coming in economics now that some economists recognize that the ‘evidence’ put out by economic models for future change and policies are largely from failed models of how the economic system works (Chatziantoniou et al. 2019).

These kinds of observations should alert us to the models we use to understand population changes and to predict the success of a particular manipulation that will solve conservation and management problems. Hone and Krebs (2023) have just published a paper on cause and effect, what does it mean, and if we posit that a particular cause or set of causes is producing an effect, what is the strength of evidence for this particular hypothesis? I suspect that if we took a poll of conservation, wildlife, and fisheries ecologists, our recent paper would be low on the reading list. Yet the question of cause and effect is central to all of science and deserves scrutiny. There are a series of criteria that can help ecologists determine a measure of strength of evidence so that we can avoid the twin problems of current management – “I have a model that predicts XYZ so that is the way to go”, or alternatively “I know what is going on in the ecosystem so we must do ABC” (Dennis et al. 2019). Opinion vs evidence. No one likes to be told that a particular statement they announce is just an opinion. If you think this is not a central issue of today, read the news and the controversies that continue about how to avoid getting Covid, or how to slow climate change, or how much land and water do we need to protect in parks and reserves. If we have no evidence about what changes to make to solve a particular problem in conservation ecology or management, we must act but we should do so in a way that provides data via adaptive management (Taper et al. 2021, Johnson et al 2015, Westgate et al. 2013).  

Perhaps one of the critical communication problems of our time involves evidence of the rapid loss of global biodiversity which is based on incomplete studies. Anyone who is involved in a serious local study of biodiversity change will attest to the problems explored by Cardinale et al. (2018) on the need for high quality datasets that are long-term and provide the evidence for conservation programs that inform global change (Watson et al. 2022). Evidence and more evidence is badly needed.

Cardinale, B.J., Gonzalez, A., Allington, G.R.H. & Loreau, M. (2018) Is local biodiversity declining or not? A summary of the debate over analysis of species richness time trends. Biological Conservation, 219, 175-183.doi: 10.1016/j.biocon.2017.12.021.

Chatziantoniou, I., Degiannakis, S., Filis, G. & Lloyd, T. (2021) Oil price volatility is effective in predicting food price volatility. Or is it? The Energy Journal 42, 25-48. doi: 10.5547/01956574.42.6.icha

Dennis, B., Ponciano, J.M., Taper, M.L. & Lele, S.R. (2019) Errors in statistical inference under model misspecification: Evidence, hypothesis testing, and AIC. Frontiers in Ecology and Evolution, 7, 372. doi: 10.3389/fevo.2019.00372.

Hone, J. & Krebs, C.J. (2023) Causality and wildlife management. Journal of Wildlife Management, 2023, e22412. doi: 10.1002/jwmg.22412.

Johnson, F.A., Boomer, G.S., Williams, B.K., Nichols, J.D. & Case, D.J. (2015) Multilevel Learning in the Adaptive Management of Waterfowl Harvests: 20 Years and Counting. Wildlife Society Bulletin, 39, 9-19.doi: 10.1002/wsb.518.

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.

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.

Watson, R., Kundzewicz, Z.W. & Borrell-Damián, L. (2022) Covid-19, and the climate change and biodiversity emergencies. Science of The Total Environment, 844, 157188.doi: 10.1016/j.scitotenv.2022.157188.

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 Ecological Imperialism

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It is well known among ecologists that there are more species of almost everything in the tropical regions, and it is also well known that there is rather much more research in the ecosystems of the temperate zone. A recent note in Science 379 (6632) – 8 Feb. 2023 highlights the problems faced by ornithologists in Latin America and the Caribbean trying to carry out research on their local birds. The details are in two papers now published (Soares et al. 2023, Ruelas Inzunza et al. 2023). Both of these papers are a response to a review paper published in 2020 (Lees et al. 2020) which discussed how much was not known about birds in Latin America, but which ignored most of the contributions of Latin American scientists. The red flag arose in part because all the authors of the 2020 paper were based at universities either in the United States or in the United Kingdom. The central criticisms were that the 2020 paper perpetuated an elitist, exclusionary, “northern” approach that has overlooked the knowledge produced by Latin American experts and Indigenous people, partly because these papers were not in English.

    Their case is certainly important and should be a call-to-arms but it should be read with a few minor qualifications. It is certainly not valid to ignore local knowledge both of scientists and indigenous peoples. But this has been going on now for more than 200 years in all areas of biological science, not that history justifies these barriers. Alas Charles Darwin would fall under the knife of this criticism. The funding for ecological research is higher in most European countries as well as North America compared with tropical countries. So we are dealing with economic issues that underlie the scientific funding that is less in Latin America in addition to the global problem that too many governments prefer guns to butter. We recognize these problems, but we can do nothing immediately about them.

    The language issue is much more difficult because it is so clear. There is a long history of this conflict in scientific papers as well as in literature in general. French scientists years ago refused to publish in English, that has changed. Chinese scientists were all educated in Russian but when the tide turned they learned English and started to write scientific papers in English. The problem revolves back to the education system of North American schools that seem to operate on the assumption that to learn a foreign language is very close to being a traitor. Alas students hardly learn to speak and write English but that is another social issue. I think many northern scientists have helped Latin America scientists to assist them in English usage, so it is to me quite obscene to think that someone has a business charging people $600 for a translation. So much of the complaint in the predominance of English scientific papers arises from social issues that are difficult to overcome.

    In the end I am very sympathetic with the inequities raised in these papers and the desire to move forward on all these issues. Ironically the skeleton of the Lees et al. (2020) paper is an excellent roadmap for the analysis of any taxonomic group anywhere is the world, and these papers should be a reminder that similar reviews should be more inclusive of all published literature. Remember always that European or American knowledge is not the only or the best knowledge.

Lees, A.C., Rosenberg, K.V., Ruiz-Gutierrez, V., Marsden, S., Schulenberg, T.S. & Rodewald, A.D. (2020) A roadmap to identifying and filling shortfalls in Neotropical ornithology. Auk, 137, 1-17. doi: 10.1093/auk/ukaa048.

Ruelas Inzunza, E., Cockle, K.L., Núñez Montellano, M.G., Fontana, C.S., Cuatianquiz Lima, C., Echeverry-Galvis, M.A., Fernández-Gómez, R.A., Montaño-Centellas, F.A., Bonaccorso, E., Lambertucci, S.A., Cornelius, C., Bosque, C., Bugoni, L., Salinas-Melgoza, A., Renton, K., Freile, J.F., Angulo, F., Mugica Valdés, L., Velarde, E., Cuadros, S. & Miño, C.I. (2023) How to include and recognize the work of ornithologists based in the Neotropics: Fourteen actions for Ornithological Applications, Ornithology, and other global-scope journals. Ornithological Applications, 125, duac047. doi: 10.1093/ornithapp/duac047.

Soares, L., Cockle, K.L., Ruelas Inzunza, E., Ibarra, J.T., Miño, C.I., Zuluaga, S., Bonaccorso, E., Ríos-Orjuela, J.C., Montaño-Centellas, F.A., Freile, J.F., Echeverry-Galvis, M.A., Bonaparte, E.B., Diele-Viegas, L.M., Speziale, K., Cabrera-Cruz, S.A., Acevedo-Charry, O., Velarde, E., Cuatianquiz Lima, C., Ojeda, V.S., Fontana, C.S., Echeverri, A., Lambertucci, S.A., Macedo, R.H., Esquivel, A., Latta, S.C., Ruvalcaba-Ortega, I., Alves, M.A.S., Santiago-Alarcon, D., Bodrati, A., González-García, F., Fariña, N., Martínez-Gómez, J.E., Ortega-Álvarez, R., Núñez Montellano, M.G., Ribas, C.C., Bosque, C., Di Giacomo, A.S., Areta, J.I., Emer, C., Mugica Valdés, L., González, C., Rebollo, M.E., Mangini, G., Lara, C., Pizarro, J.C., Cueto, V.R., Bolaños-Sittler, P.R., Ornelas, J.F., Acosta, M., Cenizo, M., Marini, M.Â., Vázquez-Reyes, L.D., González-Oreja, J.A., Bugoni, L., Quiroga, M., Ferretti, V., Manica, L.T., Grande, J.M., Rodríguez-Gómez, F., Diaz, S., Büttner, N., Mentesana, L., Campos-Cerqueira, M., López, F.G., Guaraldo, A.C., MacGregor-Fors, I., Aguiar-Silva, F.H., Miyaki, C.Y., Ippi, S., Mérida, E., Kopuchian, C., Cornelius, C., Enríquez, P.L., Ocampo-Peñuela, N., Renton, K., Salazar, J.C., Sandoval, L., Correa Sandoval, J., Astudillo, P.X., Davis, A.O., Cantero, N., Ocampo, D., Marin Gomez, O.H., Borges, S.H., Cordoba-Cordoba, S., Pietrek, A.G., de Araújo, C.B., Fernández, G., de la Cueva, H., Guimarães Capurucho, J.M., Gutiérrez-Ramos, N.A., Ferreira, A., Costa, L.M., Soldatini, C., Madden, H.M., Santillán, M.A., Jiménez-Uzcátegui, G., Jordan, E.A., Freitas, G.H.S., Pulgarin-R, P.C., Almazán-Núñez, R.C., Altamirano, T., Gomez, M.R., Velazquez, M.C., Irala, R., Gandoy, F.A., Trigueros, A.C., Ferreyra, C.A., Albores-Barajas, Y.V., Tellkamp, M., Oliveira, C.D., Weiler, A., Arizmendi, M.d.C., Tossas, A.G., Zarza, R., Serra, G., Villegas-Patraca, R., Di Sallo, F.G., Valentim, C., Noriega, J.I., Alayon García, G., de la Peña, M.R., Fraga, R.M. & Martins, P.V.R. (2023) Neotropical ornithology: Reckoning with historical assumptions, removing systemic barriers, and reimagining the future. Ornithological Applications, 125, duac046. doi: 10.1093/ornithapp/duac046.

Should Empirical Ecology be all Long-term?

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The majority of empirical ecology research published in our journals is short-term with the time span dictated by the need for 1–2-year Master’s degree studies and 3-4-year PhD research. This has been an excellent model when there was little of a framework for researching the critical questions ecologists ought to answer. Much of ecology in the good old days was based on equilibrium models of populations, communities, and ecosystems, an assumption we know to be irrelevant to a world with a changing climate. Perhaps we should have listened to the paleoecologists who kept reminding us that there was monumental change going on in the eras of glaciation and much earlier in the time of continental drift (Birks 2019). All of this argues that we need to change direction from short-term studies to long-term studies and long-term thinking.

There are many short-term ecological studies that are useful and should be done. It is necessary for management agencies to know if the spraying of forest insect pests this year reduces damage next year, and many similar problems exist that can be used for student projects. But the big issues of our day are long term problems, defined in the first place by longer than the research lifespan of the average ecologist, about 40 years. These big issues are insufficiently studied for two reasons. First, there is little funding for long term research. We can find a few exemptions to this statement, but they are few and many of them are flawed. Second, we as research scientists want to do something new that no one has done before. This approach leads to individual fame and sometimes fortune and is the social model behind many of the research prizes that we hear about in the media, the Nobel Prize, the MacArthur Awards, the National Medal of Science, the Kyoto Prize and many more. The point here is not that we should stop giving these awards (because they are socially useful), but that we should take a broader perspective on how research really works. Many have recognized that scientific advances are made by groups of scientists standing on the shoulders of an earlier generation. Perhaps some of the awards in medicine recognize this more frequently than other areas of science. My point is that large problems in ecology require a group effort by scientists that is too often unrecognized in favour of the individual fame model of science prizes.

A few examples may exemplify the need in ecology to support group studies of long-term problems. The simplest cases are in the media every day. The overharvesting of trees continues with little research into the long-term recovery of the harvested area and exactly how the forest community changes as it recovers. We mine areas for minerals and drill and mine tar sands for oil and gas with little long-term view of the recovery path which may stretch to hundreds or thousands of years while our current research program is long-term if it goes for 10 years. Canada has enough of these disturbance problems to fill the leger. The Giant Gold Mine in the Northwest Territories of Canada mined 220,000 kg of gold from 1948 to 2004 when it closed. It left 237 tonnes of arsenic trioxide dust, a by-product for extracting gold. The long-term ecosystem problems from this toxic compound will last for centuries but you might expect it will be much sooner forgotten than subjected to long-term study.

So where are we ecologists with respect to these large problems? We bewail biodiversity loss and when you look at the available data and the long-term studies you would expect to measure biodiversity and, if possible, manage this biodiversity loss. But you will find only piecemeal short-term studies of populations, communities, and ecosystems that are affected. We tolerate this unsatisfactory scientific situation even for ecosystems as iconic as the Great Barrier Reef of eastern Australia where we have a small number of scientists monitoring the collapse of the reef from climate change. The only justification we can give is that “Mother Nature will heal itself” or in the scientific lingo, “the organisms involved will adapt to environmental change”. All the earth’s ecosystems have been filtered through a million years of geological change, so we should not worry, and all will be well for the future, or so the story goes.

I think few ecologists would agree with such nonsense as the statements above, but what can we do about it? My main emphasis here is long-term monitoring. No matter what you do, this should be part of your research program. If possible, do not count birds on a plot for 3 years and then stop. Do not live trap mice for one season and think you are done. If you have any control over funding recommendations, think continuity of monitoring. Long-term monitoring is a necessary but not a sufficient condition for managing biodiversity change.

There are many obstacles interfering with achieving this goal. Money is clearly one. If your research council requests innovation in all research proposals, they are probably driven by Apple iPhone producers who want a new model every year. For the past 50 years we have been able to fund monitoring in our Yukon studies without ever using the forbidden word monitor because it was not considered science by the government granting agencies. In one sense it is not whether you consider science = innovation or not, but part of the discussion about long term studies might be shifted to consider the model of weather stations, and to discuss why we continue to report temperatures and CO2 levels daily when we have so much past data. No one would dream of shutting down weather monitoring now after the near fiasco around whether or not to measure CO2 in the atmosphere (Harris, 2010, Marx et al. 2017).

Another obstacle has been the destruction of research sites by human developments. Anyone with a long history of doing field research can tell you of past study areas that have been destroyed by fire or are now parking lots, or roads, or suburbia. This problem could be partly alleviated by the current proposals to maintain 30% of the landscape in protected areas. We should however avoid designating areas like the toxic waste site of the Giant Gold Mine as a “protected area” for ecological research.

Where does this all lead? Consider long-term monitoring if you can do the research as part of your overall program. Read the recent contributions of Hjeljord, and Loe (2022) and Wegge et al. (2022) as indicators of the direction in which we need to move, and if you need more inspiration about monitoring read Lindenmayer (2018).

Birks, H.J.B. (2019) Contributions of Quaternary botany to modern ecology and biogeography. Plant Ecology & Diversity, 12, 189-385.doi: 10.1080/17550874.2019.1646831.

Harris, D.C. (2010) Charles David Keeling and the story of atmospheric CO2 measurements. Analytical Chemistry, 82, 7865-7870.doi: 10.1021/ac1001492.

Hjeljord, O. & Loe, L.E. (2022) The roles of climate and alternative prey in explaining 142 years of declining willow ptarmigan hunting yield. Wildlife Biology, 2022, e01058.doi: 10.1002/wlb3.01058.

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

Marx, W., Haunschild, R., French, B. & Bornmann, L. (2017) Slow reception and under-citedness in climate change research: A case study of Charles David Keeling, discoverer of the risk of global warming. Scientometrics, 112, 1079-1092.doi: 10.1007/s11192-017-2405-z.

Wegge, P., Moss, R. & Rolstad, J. (2022) Annual variation in breeding success in boreal forest grouse: Four decades of monitoring reveals bottom-up drivers to be more important than predation. Ecology and Evolution.12, e9327. doi: 10.1002/ece3.9327.