Category Archives: Climate Emergency

How Can We Best Advance Ecological Research

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Everyone who supports scientific research wishes to see progress in understanding of the problems being studied. Ecologists face four critical difficulties in achieving these goals of progress.

  •  There are far too many ecological problems to be sorted out given the number of ecologists in the scientific world. There is a partial solution to this issue by dividing the ecological research into two broad categories: large scale critical problems and small-scale local problems. Large-scale problems are those that apply to many communities and ecosystems, from the local to the global. Large scale problems require first an agreement of what these problems are and second how they should be approached – both difficult to achieve in the current research environment. So there is too little agreement even on this simple issue. Large-scale problems require a coordinated team effort and to date in ecology large-scale problems have been poorly addressed. Small scale problems can be studied with less person power and are much more common. In an ideal world, governments would fund large-scale research programs that require effort that stretches over many years and require considerable reliable funding, and smaller grants could support the many specific postgraduate studies with a time limit of 3-4 years. It would be optimal for these two groups to meld together but this is difficult to achieve. The whole system we have currently fights against this cooperation, partly because in the world of science most of the recognition and rewards go to individual scientists and not to a research team.
  •  A second problem is that there are two paradigms of ecological science that are only partly overlapping. The first paradigm in its strong form states that ecological science will advance most rapidly by means of descriptive studies of changes in communities and ecosystems. Gaiser et al. (2020) provide good examples of this approach. Long-Term-Ecological-Research (LTER) approaches are typically large-scale and rely too much on the assumptions of correlation = causation science, but this paradigm suggests that long-term data will lead us to the long-term understanding of communities and ecosystems. The second approach can be described as the mechanistic paradigm because it attempts to explain long- and short-term population and community changes from whatever cause using experimental methods (Krebs 2002). Hone and Krebs (2023) detail the evidence levels needed for strong inference in both short-term and long-term issues. Lindenmayer (2018) provides an excellent synopsis of the difficulties of long-term research and a synopsis of how we might act to answer ecological questions about future issues (Lindenmayer et al. 2015, Lindenmayer 2018).
  • The third difficulty is that the individual scientist as the unit of research makes it unlikely in the present organization of science funding that these two paradigms can be easily brought together. Scientists by and large wish to be independent, a desirable trait, but we can and should work in a team effort, an interlocking independent research program that has specified objectives that all are organized into a partnership. If you want examples of this approach, you have only to look at the successes and failures of many long-term ecological research (LTER) programs around the world. One example of a successful LTER research program in Austria is reviewed in Gingrich et al. (2016). Additional evaluations of current LTER projects can be found in Vanderbilt and Gaiser (2017) and Rastetter et al. (2021). There has been a movement to integrate social and ecological frameworks to LTER research. A good example of this social-ecological approach is disturbance ecology described for the USA in Gaiser et al. (2020). But ecological approaches of the type described in Vanderbilt and Gaiser (2017) and Gaiser et al. (2020) appear to reduce ecological research to an endless study of descriptive changes in ecosystems with little theory. The hope is to advance ecological science by observations of changes in ecosystems as affected by human activity and climate change. The objective of these research programs is to provide solutions for future environmental problems from long term data sets. However, describing the past does not inherently predict the future, as evidenced by the issues surrounding climate change.
  • A fourth problem is that the long-term funding necessary to understand new and continuing ecological problems too often falls to a new Director or Chief who wishes to change the direction of the research or stop it altogether, so long term objectives are not supported. Another aspect of the funding problem for LTER research is the lack of substantial funding on a spatial and monetary scale that would permit comprehensive research with suitable replication. Cusser at al. (2021) have analysed LTER studies in the USA with respect to how long studies must be to achieve good results. They concluded that half of the LTER studies required 10 years or more to produce consistent results, and some required more than 20 years. Many of these LTER studies are focused on the descriptive paradigm and would not qualify as experimental ecology with specific hypotheses about community and ecosystem dynamics. LTER descriptive studies are useful for advancing knowledge of trends, but they may not be sufficient to identify and test the underlying drivers of community and ecosystem change.

Cusser, S., Helms IV, J., Bahlai, C.A., and Haddad, N.M. 2021. How long do population level field experiments need to be? Utilising data from the 40-year-old LTER network. Ecology Letters 24(5): 1103-1111. doi:10.1111/ele.13710.

Gaiser, E.E., Bell, D.M., Castorani, M.C.N., Childers, D.L., and Groffman, P.M. 2020. Long-term ecological research and evolving frameworks of disturbance ecology. Bioscience 70(2): 141-156. doi:10.1093/biosci/biz162.

Gingrich, S., Schmid, M., Dirnbock, T., Dullinger, I. et al. 2016. Long-Term Socio-Ecological Research in Practice: Lessons from Inter- and Transdisciplinary Research in the Austrian Eisenwurzen. Sustainability 8(8): 743. doi:10.3390/su8080743.

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

Krebs, C.J. 2002. Two complementary paradigms for analyzing population dynamics. Philosophical Transactions of the Royal Society of London, Series B 357: 1211-1219. doi:10.1098/rstb.2002.1122.

Lindenmayer, D.B., Burns, E.L., Tennant, P., Dickman, C.R., Green, P.T., Keith, D.A., et al. 2015. Contemplating the future: Acting now on long-term monitoring to answer 2050’s questions. Austral Ecology 40(3): 213-224. doi:10.1111/aec.12207.

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.

Rastetter, E.B., Ohman, M.D., Elliott, K.J., Rehage, J.S., and al., e. 2021. Time lags: insights from the U.S. Long Term Ecological Research Network. Ecosphere 12(5): e03431. doi:10.1002/ecs2.3431.

Vanderbilt, K., and Gaiser, E. 2017. The International Long Term Ecological Research Network: a platform for collaboration. Ecosphere 8(2): e01697. doi:10.1002/ecs2.1697.

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

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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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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 Time in Ecology

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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.

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.

The Meaningless of Random Sampling

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Statisticians tell us that random sampling is necessary for making general inferences from the particular to the general. If field ecologists accept this dictum, we can only conclude that it is very difficult to nearly impossible to reach generality. We can reach conclusions about specific local areas, and that is valuable, but much of our current ecological wisdom on populations and communities relies on the faulty model of non-random sampling. We rarely try to define the statistical ‘population’ which we are studying and attempting to make inferences about with our data. Some examples might be useful to illustrate this problem.

Marine ecologists ae mostly agreed that sea surface temperature rise is destroying coral reef ecosystems. This is certainly true, but it camouflages the fact that very few square kilometres of coral reefs like the Great Barrier Reef have been comprehensively studied with a proper sampling design (e.g. Green 1979, Lewis 2004). When we analyse the details of coral reef declines, we find that many species are affected by rising sea temperatures, but some are not, and it is possible that some species will adapt by natural selection to the higher temperatures. So we quite rightly raise the alarm about the future of coral reefs. But in doing so we neglect in many cases to specify the statistical ‘population’ to which our conclusions apply.

Most people would agree that such an approach to generalizing ecological findings is tantamount to saying the problem is “how many angels can dance on the head of a pin”, and in practice we can ignore the problem and generalize from the studied reefs to all reefs. And scientists would point out that physics and chemistry seek generality and ignore this problem because one can do chemistry in Zurich or in Toronto and use the same laws that do not change with time or place. But the ecosystems of today are not going to be the ecosystems of tomorrow, so generality in time cannot be guaranteed, as paleoecologists have long ago pointed out.

It is the spatial problem of field studies that collides most strongly with the statistical rule to random sample. Consider a hypothetical example of a large national park that has recently been burned by this year’s fires in the Northern Hemisphere. If we wish to measure the recovery process of the vegetation, we need to set out plots to resample. We have two choices: (1) lay out as many plots as possible, and sample these for several years to plot recovery. Or (2) lay out plots at random each year, never repeating the same exact areas to satisfy the specifications of statisticians to “random sample” the recovery in the park. We typically would do (1) for two reasons. Setting up new plots each year as per (2) would greatly increase the initial field work of defining the random plots and would probably mean that travel time between the plots would be greatly increased. Using approach (1) we would probably set out plots with relatively easy access from roads or trails to minimize costs of sampling. We ignore the advice of statisticians because of our real-world constraints of time and money. And we hope to answer the initial questions about recovery with this simpler design.

I could find few papers in the ecological literature that discuss this general problem of inference from the particular to the general (Ives 2018, Hauss 2018) and only one that deals with a real-world situation (Ducatez 2019). I would be glad to be sent more references on this problem by readers.

The bottom line is that if your supervisor or research coordinator criticizes your field work because your study areas are not randomly placed or your replicate sites were not chosen at random, tell him or her politely that virtually no ecological research in the field is done by truly random sampling. Does this make our research less useful for achieving ecological understanding – probably not. And we might note that medical science works in exactly the same way field ecologists work, do what you can with the money and time you have. The law that scientific knowledge requires random sampling is often a pseudo-problem in my opinion.  

Ducatez, S. (2019) Which sharks attract research? Analyses of the distribution of research effort in sharks reveal significant non-random knowledge biases. Reviews in Fish Biology and Fisheries, 29, 355-367. doi. 10.1007/s11160-019-09556-0

Green, R.H. (1979) Sampling Design and Statistical Methods for Environmental Biologists. Wiley, New York. 257 pp.

Hauss, K. (2018) Statistical Inference from Non-Random Samples. Problems in Application and Possible Solutions in Evaluation Research. Zeitschrift fur Evaluation, 17, 219-240. doi.

Ives, A.R. (2018) Informative Irreproducibility and the Use of Experiments in Ecology. BioScience, 68, 746-747. doi. 10.1093/biosci/biy090

Lewis, J. (2004) Has random sampling been neglected in coral reef faunal surveys? Coral Reefs, 23, 192-194. doi: 10.1007/s00338-004-0377-y.

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.

Alas Biodiversity

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One would have to be on another planet not to have heard of the current COP 15 meeting in Montreal, the Convention on Biological Diversity. Negotiators have recently finalised an agreement on what the signatory nations will do in the next 5 years or so. I do not wish to challenge the view that these large meetings achieve much discussion and suggestions for action on conservation of biodiversity. I do wish to address, from a scientific viewpoint, issues around the “loss of biodiversity” and in particular some of the claims that are being made about this problem.

The first elephant in the room which must not be ignored is human population growth. At a best guess there are perhaps three times as many people now on earth as the earth can support. So the background for all biodiversity action is human population size and the accompanying resource demands. Too few wish to discuss this elephant.

The second elephant is the vagueness of the concept of biodiversity. If we take its simple meaning to be ‘all life on Earth’, we must face the fact that we are not even close to having a complete catalogue of life on earth. To be sure we know most of the species of birds and mammals, a lot of the fish and the reptiles, so we have made a start. But look at the insects and you will find guesses of several million species that are undescribed. And we have hardly begun to look at the bacteria, fungi, and viruses.

The consequence of this is loose speech. When we say we wish to ‘protect biodiversity’ what exactly do we wish to protect? Only the birds but not all of them, only the ones we like? Or only the large mammals like the polar bears, the African lion, and the panda? Typically, conservation of biodiversity focuses on one charismatic species and hopes for spill over to others, applying the well-known principles of population ecology to the immediate threat. But ecologists talk about ecological communities and ecosystems, so this raises another issue of how to define these entities and how protecting biodiversity can be applied to them.

Now the third elephant comes into play, climate change. To appreciate this, we need to talk to paleoecologists. If you were fortunate to live in central Alaska or the Yukon 30,000 years ago and you formed a society for the conservation of biodiversity, you would face a vegetation community that was destined to disappear or change dramatically, not to mention species like the mammoths and saber-toothed tigers that no longer exist but we love to see in museums. So there is a time scale as well as a spatial scale to biodiversity that is easily forgotten. Small national parks and reserves may not be a solution to the issue.

So whither biodiversity science? If we are serious about biodiversity change, we must lay out more specific questions as a start. Exactly what species are we measuring and for how long and with what precision? We need to concentrate on areas that are protected from human exploitation, one of the main reasons for biodiversity losses, the loss of habitat due to agriculture, mining, forestry, human housing, roads, invasive pests, the list goes on. We need groups of ecologists to concentrate on the key areas we define, on the key threats affecting each area, how we might mitigate these effects, and once these questions are decided we need to direct funding to these groups. Biodiversity funding is all over the map and often wasted on trivial problems. Biodiversity issues are at their core problems in community and ecosystem ecology, and yet we typically treat them as single species problems. We need to study communities and ecosystems. To say that we as ecologists do not know how to study community and ecosystem ecology would be a start. Studying one fish species extensively will not protect the community and ecosystem it requires for survival. If you need a concrete example, consider Pacific salmon on the west coast of North America and the ecosystems they inhabit. This is not a single species problem. In some river systems stocks are doing well, while in other rivers salmon are disappearing. Why? If we know that at least part of the answer to this question lies in ecosystem management and yet no action is undertaken, is this because it costs too much or what? Why can we spend a billion dollars going to the moon and not spend this money on serious ecological problems subject to biodiversity increases or declines? Perhaps part of the problem is that to get to the moon we do not give money to 10 different agencies that do not talk or coordinate with one another. Part of the answer is that governments do not see biodiversity loss or gain as an important problem, and it is easier to talk vaguely about it and do little in the hope that Nature will rectify the problems.

So, we continue in the Era of Biodiversity without knowing what this means and too often without having any plan to see if biodiversity is increasing or declining in any particular habitat or region, and then devising a plan to ameliorate the situation as required. This is not a 5 year or a 10-year plan, so it requires a long-term commitment of public support, scientific expertise, and government agencies to address. For the moment we get an A+ grade for talking and an F- grade for action.

Dupont-Doaré, C. & Alagador, D. (2021) Overlooked effects of temporal resolution choice on climate-proof spatial conservation plans for biodiversity. Biological Conservation, 263, 109330.doi: 10.1016/j.biocon.2021.109330.

Fitzgerald, N., Binny, R.N., Innes, J., Pech, R., James, A., Price, R., Gillies, C. & Byrom, A.E. (2021) Long-Term Biodiversity Benefits from Invasive Mammalian Pest Control in Ecological Restorations. Bulletin of the Ecological Society of America, 102, e01843.doi: 10.1002/bes2.1843.

Moussy, C., Burfield, I.J., Stephenson, P.J., Newton, A.F.E., Butchart, S.H.M., Sutherland, W.J., Gregory, R.D., McRae, L., Bubb, P., Roesler, I., Ursino, C., Wu, Y., Retief, E.F., Udin, J.S., Urazaliyev, R., Sánchez-Clavijo, L.M., Lartey, E. & Donald, P.F. (2022) A quantitative global review of species population monitoring. Conservation Biology, 36, e13721.doi. 10.1111/cobi.13721.

Price, K., Holt, R.F. & Daust, D. (2021) Conflicting portrayals of remaining old growth: the British Columbia case. Canadian Journal of Forest Research, 51, 1-11.doi: 10.1139/cjfr-2020-04530.

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

In Honour of David Suzuki at his Retirement

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David Suzuki is retiring from his media work this year at age 86. If you wish to have a model for a lifetime of work, he should be high on your list – scientist, environmentalist, broadcaster, writer. He has been a colleague of mine at the Department of Zoology, UBC from the time when I first came there in 1970. He was a geneticist doing imaginative and innovative research with his students on the humble fruit fly Drosophila melanogaster. The Department at that time was a beehive of research and teaching, and David was a geneticist breathing fire at the undergraduates taking the genetics course. Many a doctor would probably tell you now that Suzuki’s genetics course was the most challenging in their undergraduate education.

The hierarchy in the Department of Zoology was very clear in the 1970s. First came the physiologists, top of the pack and excellent scientists who turned the spotlight on the Department nationally and internationally. Second came the geneticists, with the DNA revolution full on. At the bottom of the pile were the ecologists causing nothing but trouble about fisheries and wildlife management problems, pointing out a rising tide of environmental problems including climate change. Contrary to what you might conclude from the media, environmental problems and climate change issues were very alive even in the 1970s. But somehow these problems did not get through to governments, and David has been a key person turning this around. In 1979 he began a natural history and science program on the CBC entitled “The Nature of Things” which he then hosted for 43 years. In doing so he began to fill an empty niche in Canadian news affairs between the environmental scientists who had data on what was going on in the environment and what needed attention. Environmental scientists were severely ignored both by industry and the governments of the day who operated on two premises – first, that the most critical issues for Canada were economics and economic growth, and second that environmental issues could largely be ignored or could be solved by promises but no action. Alas we are still inundated with the news that “growth is good”, and “more growth is better”.   

I had relatively little involvement in David’s increasing interest in environmental issues by 1979, but I had written 3 ecology textbooks by then, pushing some of the environmental issues that are still with us, and I became a friend of David’s in the Department. We ecologists could only admire his ability to speak so clearly on the environmental issues of our day and connect these issues with the many travesties of how First Nations people had been sidelined. He pointed out very forcefully the astonishing failure of governments to address these issues. The public which was much less aware of environmental issues in the 1980s is now highly mobilized thanks in great part to all the work David and his colleagues have done in the last 50 years. He has many friends now but still strong enemies who continue to think of the environment as a large garbage can for economic growth. And he, still in his retirement, having achieved so much from his environmental work, bemoans the slow pace of government actions on environmental problems, as does every ecologist I know. His Foundation continues to press for action on many conservation fronts. So, thank you David for all your work and your wisdom over all these many years. You have engineered a strong environmental movement among old and young and I thank you for all that.

https://davidsuzuki.org/