Category Archives: Charley Krebs’ blogs

Back to Nature vs. Nurture

The ancient argument of ‘nature’ versus ‘nurture’ continues to arise in biology. The question has arisen very forcefully in a new book by James Tabery (Tabery 2023). The broad question he examines in this book is the conflict between ‘nature’ and ‘nurture’ in western medicine. In a broad sense ‘nature’ is discussed as the modern push in medicine to find the genetic basis of some of the common human degenerative diseases – Parkinson’s, dementia, asthma, diabetes, cancer, hypertension – to mention only a few medical problems of our day. The ‘nature’ approach to medicine in this book is represented by molecular genetics and the Human Genome Project. The ‘nurture’ approach to treating these medical conditions is via studying health outcomes in people subject to environmental contamination, atmospheric pollution, water quality, chemicals in food preparations, asbestos in buildings, and other environmental issues including how children are raised and educated. The competition over these two approaches was won very early by the Human Genome Project, and many of the resources for medicine over the last 30 years were put into molecular biology which made spectacular progress in diving into the genome of affected people and then making great promises of personalized medicine. The environmental approach to these medical conditions received much less money and was not viewed as sufficiently scientific. The irony of all this in retrospect is that the ‘nature’ or DNA school had no hypotheses about the problems being investigated but relied on the assumption that if we got enough molecular genetic data on thousands of people that something would jump out at us, and we would locate for example the gene(s) causing Parkinson’s, and then we could alter these genes with gene therapy or specific pharmaceuticals. By contrast the ‘nurture’ school had many specific hypotheses to test about air pollution and children’s health, about lead in municipal water supply and brain damage, and a host of very specific insights about how some of these health problems could be alleviated by legislation and changes in diet for example.

So, the question then becomes where are we today? The answer Tabery (2023) gives is that the ‘nature’ or molecular genetic “personalized medicine” approach has largely failed in achieving its goals despite the large amount of money invested because there is no single or small set of genes that cause specific diseases, but many genes that have complex interactions. In contrast, the ‘nurture’ school has made progress in identifying conditions that help decrease the occurrence of some of our common diseases, realizing that the problems are often difficult because they require changes in human behaviour like stopping smoking or improving diets.

All this discussion would possibly produce the simple conclusion that both “nature” and “nurture” are both involved in these complex human conditions. So, what could this medical discussion tell us about the condition of modern ecological science? I think two things perhaps. First, it is a general error to use science without hypotheses. Yet this is too often what ecologists do – gather a large amount of data that can be measured without too much prolonged effort and then try to make sense of it by applying hypotheses after the fact. And second, technology in ecology can be a benefit or a curse. Take, for example, the advances in vertebrate ecology that have come from the ability to describe the movements of individual animals in space. To have a map of hundreds of locations of an individual animal provides good natural history but does not address any specific hypothesis. Contrast this approach with that of Studd et al. (2021) and Shiratsuru et al. (2023) who use movement data to test important questions about kill rates of predators on different species of prey.

Many large-scale ecological approaches suffer from the same problem as the ‘nature’ paradigm – use ‘big science’ to measure many variables and then try to answer some important question for example about how climate change is affecting communities of plants and animals. Nagy et al. (2021) and Li et al. (2022) provide excellent examples of this approach. Schimel and Keller (2015) discuss what is needed to bring hypothesis testing to ‘big science’. Lindenmayer et al. (2018) discuss how conventional, question-driven long-term monitoring and hypothesis testing need to be combined with ‘big science’ to better ecological understanding. Pau et al. (2022) give a warning of how ‘big science’ data from airborne imaging can fail to agree with ground-based field studies in one core NEON grassland site in central USA.

The conclusion to date is that there is little integration in ecology of the equivalent of “nature” and “nurture” in medicine if in ecology we match ‘big science’ with ‘nature’ and field studies on the ground with ‘nurture’. Without that integration we risk in future another negative review in ecology like that provided now by Tabery (2023) for medical approaches to human diseases.

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

Li, D., et al. (2022) Standardized NEON organismal data for biodiversity research. Ecosphere, 13, e4141.doi:10.1002/ecs2.4141.

Nagy, R.C., et al. (2021) Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community. Ecosphere, 12, e03833.doi: 10.1002/ecs2.3833.

Pau, S., et al. (2022) Poor relationships between NEON Airborne Observation Platform data and field-based vegetation traits at a mesic grassland. Ecology, 103, e03590.doi: 10.1002/ecy.3590.

Schimel, D. & Keller, M. (2015) Big questions, big science: Meeting the challenges of global ecology. Oecologia, 177, 925-934.doi: 10.1007/s00442-015-3236-3.

Shiratsuru, S., Studd, E.K., Majchrzak, Y.N., Peers, M.J.L., Menzies, A.K., Derbyshire, R., Jung, T.S., Krebs, C.J., Murray, D.L., Boonstra, R. & Boutin, S. (2023) When death comes: Prey activity is not always predictive of diel mortality patterns and the risk of predation. Proceedings of the Royal Society B, 290, 20230661.doi.

Studd, E.K., Derbyshire, R.E., Menzies, A.K., Simms, J.F., Humphries, M.M., Murray, D.L. & Boutin, S. (2021) The Purr-fect Catch: Using accelerometers and audio recorders to document kill rates and hunting behaviour of a small prey specialist. Methods in Ecology and Evolution, 12, 1277-1287.doi. 10.1111/2041-210X.13605

Tabery, J. (2023) Tyranny of the Gene: Personalized Medicine and the Threat to Public Health. Knopf Doubleday Publishing Group, New York. 336 pp. ISBN: 9780525658207.

The Meaningless of Random Sampling

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.

The Time Frame of Ecological Science

Ecological research differs from many branches of science in having a more convoluted time frame. Most of the sciences proceed along paths that are more often than not linear – results A → results B → results C and so on. Of course, these are never straight linear sequences and were described eloquently by Platt (1964) as strong inference:

“Strong inference consists of applying the following steps to every problem in science, formally and explicitly and regularly: 1) Devising alternative hypotheses; 2) Devising a crucial experiment (or several of them), with alternative possible outcomes, each of which will, as nearly as possible, exclude one or more of the hypotheses; 3) Carrying out the experiment so as to get a clean result; “Recycling the procedure, making sequential hypotheses to refine the possibilities that remain; and so on. It is like climbing a tree.” (page 347 in Platt).

If there is one paper that I would recommend all ecologists read it is this paper which is old but really is timeless and critical in our scientific research. It should be a required discussion topic for every graduate student in ecology.

Some ecological science progresses as Platt (1964) suggests and makes good progress, but much of ecology is lost in a failure to specify alternative hypotheses, in changing questions, in abandoning topics because they are too difficult, and in a shortage of time. It is the time component of ecological research that I wish to discuss in this blog.

The idea of long-term studies has always been present in ecology but was perhaps brought to our focus by the compilation by Gene Likens in 1989 in a book of 14 chapters that are as vital now as they were 34 years ago. Many discussions of long-term studies are now available to examine this issue. Buma et al. (2019) for example discuss plant primary succession at Glacier Bay, Alaska which has 100 years of data, and which illustrates in a very slow ecosystem a test of conventional rules of community development. Cusser et al. (2021) follow this by asking a critical question of how long field experiments need to be. They restrict long-term to be > 10 years of study and used data from the USA LTER sites. This question depends very much on the community or ecosystem of study. Studies in areas with a stable climate produced results more quickly than those in highly seasonal environments, and plant studies needed to be longer term than animal studies to reach stable conclusions. Ten years may not be enough.

Reinke et al. (2019) reviewed 3 long term field studies and suggest that long-term studies can be useful to allow us to predict how ecosystems will change with time. All these studies lead to three unanswered questions that are critical for progress in ecology. The first question is how we decide as a community exactly which ecological system we should be studying long-term. No one knows how to answer this question, and a useful graduate seminar could debate the utility of what are now considered model long-term studies, such as the three highlighted in Reinke et al. (2019) or the Park Grass Experiment (Addy et al. 2022). At the moment these decisions are opportunistic, and we should debate how best to proceed. Clearly, we cannot do everything for every population and community of interest, so how do we choose? We need model systems that can be applied to a wide variety of environments across the globe and that ask questions of global significance. Many groups of ecologists are trying to do this, but a host of decisions about who to fund and support in what institution are vital to avoid long-term studies driven more by convenience than by ecological importance.

A second question involves the implied disagreement whether many important questions in ecology today could be answered by short-term studies, so we reach a position where there is competition between short- and long-term funding. These decisions about where to do what for how long are largely uncontrolled. One would prefer to see an articulated set of hypotheses and predictions to proceed with decision making, whether for short-term studies suitable for graduate students or particularly for long-term studies that exceed the life of individual researchers.

A third question is the most difficult one of the objectives of long-term research. Given climate change as it is moving today, the hope that long-term studies will give us reliable predictions of changes in communities and ecosystems is at risk, the same problem of extrapolating a regression line beyond the range of the data. Depending on the answer to this climate dilemma, we could drop back to the suggestion that because we have only a poor ability to predict ecological change, we should concentrate more on widespread monitoring programs and less on highly localized studies of a few sites that are of unknown generality. Testing models with long-term data is enriching the ecological literature (e.g. Addy et al 2022). But the challenge is whether our current understanding is sufficient to make predictions for future populations or communities. Should ecology adopt the paradigm of global weather stations?

Addy, J.W.G., Ellis, R.H., MacLaren, C., Macdonald, A.J., Semenov, M.A. & Mead, A. (2022) A heteroskedastic model of Park Grass spring hay yields in response to weather suggests continuing yield decline with climate change in future decades. Journal of the Royal Society Interface, 19, 20220361. doi: 10.1098/rsif.2022.0361.

Buma, B., Bisbing, S.M., Wiles, G. & Bidlack, A.L. (2019) 100 yr of primary succession highlights stochasticity and competition driving community establishment and stability. Ecology, 100, e02885. doi: 10.1002/ecy.2885.

Cusser, S., Helms IV, J., Bahlai, C.A. & 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, 1103-1111. doi: 10.1111/ele.13710.

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

Likens, G.E. (Editor, 1989) Long-term Studies in Ecology: Approaches and Alternatives. Springer Verlag, New York. 214 pp. ISBN: 0387967435.

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

Reinke, B.A., Miller, D.A.W. & Janzen, F.J. (2019) What have long-term field studies taught as about population dynamics? Annual Review of Ecology, Evolution, and Systematics, 50, 261-278. doi: 10.1146/annurev-ecolsys-110218-024717.

The Five Stages of Conservation

While listening to the reports on the COP 15 meeting in Montreal I began thinking that one way to look at conservation science and action is to think of it in 5 stages. So I decided to put out this discussion of how we might view all the conservation news.

Stage 1: Recognize the Issue

The most important issue is to make both scientists and the general public aware that there is a large problem with the conservation of the Earth’s biota. We start with having to convince all that biodiversity does not mean dangerous animals and plants. This stage would be simple for anyone who has taken a good biology course in school, but we still find that some people fear the “environment” because it is synonymous with spiders and alligators and bears and wolves. One might think that children’s books involving cute or anthropomorphised animals would make them less susceptible to this worry, but this does not work for all who have read “The Big Bad Wolf” and Little Red Riding Hood. So education about animals and plants should begin to point everyone toward conservation.

Stage 2: Become Concerned

People see that animals die from a great array of problems, and this connects to the human world where people get ill and pass away or become injured in a car accident. Depending on what their interest is, concern about this leads to interventions such as the feeding of birds and other wildlife on the assumption that they cannot take care of themselves. These worries generate a concern in many to protect wildlife on the unfounded assumption that without human interference, all would disappear.

Stage 3: Demand Action

By this stage wildlife and fishery scientists have begun doing many excellent studies on how some populations of wildlife are in serious trouble. The crux at this point is that often the origin of these problems are human actions in cutting down forests, clearing land for agriculture and housing, and polluting the general environment. The problem is people do things related to “progress” and then find it is killing wildlife. If you need an example, think DDT or seismic lines. The public grows more aware and demands conservation action. These demands are translated into small amounts of government action with large amounts of publicity.

Stage 4: Achieve Action

The consequences of the human exploitation of the earth’s resources begins to bite, largely driven by climate emergencies. Much pressure from NGOs and even business people starts to result in action. Wildlife and fisheries agencies make progress but almost always on the scale of single species management often constrained by state or provincial boundaries. Who is in charge of this mess? Biodiversity becomes the cry of the age, and even the New York Times begins to realize that the Earth consists of more than human beings. But while there is more talk, there is less understanding because of the shouting of people who know very little about these conservation issues and how tangled they are. It is important to appear to be on the side of the angels, so progress is slower than one would like.

Stage 5: Understand the Problem

We have barely entered this stage. To be sure ecologists have been at this Stage for many years with reasonable understanding of how to ameliorate conservation problems, but still too few powers that be are convinced, so that we continue to provide subsidies to oil and gas companies that are busy destroying the earth. Subsidies can go in good or bad directions, but few of us can comprehend the volumes of money being committed to subsidies in all directions. We hear promises to achieve X by 2030, and Y by 2050, and still we believe these when we can just look up and see that few of the promises of the last 30 years have been achieved. Few beyond ecologists understand that it is communities and ecosystems that must be protected but almost all our conservation efforts now operate on single species of ecological beauty. Think rhinos.

One hopes for Stage 6 to come to be, but only a small sign of that progress is so far in sight. If only we could convince everyone that conservation issues ought to be treated with the urgency and the funding that COVID has obtained, we could press ahead with more serious conservation objectives. But it is more than declaring that we should protect 30% of our wild areas. Even if we can achieve the 30% goal in the next 8 years, it is but a start toward understanding the stewardship of the Earth if we do not know how the machinery of nature works. Alas, it is a long road ahead being driven by humans who are short-sighted. Can we avoid Plus ça change?

The Two Questions: So what? What next?

Assuming that these two questions are not copyright, I wanted to explore them as a convenient part of writing a scientific or popular paper in ecology, conservation, and wildlife and fisheries management. To protect the innocent, I will not identify which of many ecological colleagues has stimulated this blog.

The first question should be addressed in every scientific paper but clearly is not if you read a random sample of the articles in many ecological journals. So what? is the critical question of exactly what current problem this paper or book will contribute to. It is the microscopic and macroscopic focus of why we do science, and it does not matter at all if it addresses a minor problem or a major catastrophe like species loss in conservation. In writing one should assume that time is the critical limiting factor in our lives, and while it is fine to be entertained by watching a movie, scientists do not read scientific papers to be entertained. Some journals demand that the abstract of every paper ends with a statement of the importance of the research findings, captured by So what? Too often these statements are weak and editors as well as granting agencies should demand more incisive statements. Asking yourself So what? can be a useful guide as you progress in your research and evaluate others.

While most scientists should agree on the findings presented in a paper or lecture, not all of them will agree about the importance of the answer to So what? What is a major and important scientific finding for some may be of minor significance to others, but the key is to remember here that science is a broad church that should be progressing on a broad front, so that differences of opinion are to be expected, and we rely on evidence to evaluate these differences of opinion. Tests of ideas that turn out to be incorrect or only partly correct must not be considered as failures. If you doubt that, interview any senior scientist in your area and ask about progress and regress during their scientific career. If you find a scientist who insists that they were correct in all their ideas, you should probably request them to go into politics to improve decision making in the real world.

The second question is probably the most critical for all scientific research. Once research is completed, there are two paths. If the original question or problem is solved or answered, the question becomes what does this work suggest needs to be done to advance the general area of research. Most typically however a research project will end up with more questions than it solves. The growing end of science is the critical one, and by asking What next? we delve deeper into the area of research to fill in details that were not evident when it was started. Read Sutherland et al. (2013, 2022) for an excellent example of this approach in conservation science. A simple example of this approach comes from many conservation problems. A particular species of bird may be thought to be declining in numbers, so the first issue is whether this is correct, and so an investigation into the changes in abundance of the species becomes the first step. This could lead to an analysis of the demography of the species population, birth, death and movement rates could be determined to isolate more precisely why abundance is changing. Given these data, the next step might be (for example) why the death rate is increasing if indeed this is the case. The next step is what management methods can be applied to reduce the death rate, and does this situation apply to other closely related species. It is important that asking What next? does not imply a linear sequence in time, and a study could be designed to address more than one question at the same time. We finish the What next? approach with a web of information and conclusions that address a broader question than the original simple question. And What next? should not be answered with a broad set of statements like “climate change is the cause” but by suggestions of very specific experiments and studies to carry investigations forward.

The result in ecology is an increasing precision of thought into ecological interactions and the processes that link species, communities, and ecosystems to very large questions such as the environmental response to climate change. Not all questions need to be large-scale because there are important local questions about the adequacy of designated parks and protected areas to protect species, communities, and ecosystems. The key message is that ecological understanding is not static but grows incrementally by well-designed research programs that by themselves seem to address only small-scale issues.

Seemingly failed research programs are not to be scorned but rather to indicate what avenues of research have not led to good insights. In a sense ecological science is like an evolutionary tree in which some branches fade away with time and others blossom into a variety of forms that surprise us all. So, my advice is to carry on asking these two simple questions in science to help sharpen your research program.

Sutherland, W.J., Freckleton, R.P., Godfray, H.C.J., Beissinger, S.R., Benton, T., Cameron, D.D., Carmel, Y., Coomes, D.A., Coulson, T., Emmerson, M.C., Hails, R.S., Hays, G.C., Hodgson, D.J., Hutchings, M.J., Johnson, D., Jones, J.P.G., Keeling, M.J., Kokko, H., Kunin, W.E. & Lambin, X. (2013) Identification of 100 fundamental ecological questions. Journal of Ecology, 101, 58-67.doi: 10.1111/1365-2745.12025.

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

The Two Ecologies

Trying to keep up with the ecological literature is a daunting task, and my aging efforts shout to me that there are now two ecologies that it might be worth partially separating. First, many published “ecological” papers are natural history. This is certainly an important component of the environmental literature but for the most part good observations alone are not science in the formal sense of science addressing problems and trying to solve them with the experimental approach. The information provided in the natural history literature regarding both plants and animals include their identification, where they live, what nutrients or food resources they utilize and in some cases information on their conservation status. A good foundation of natural history is needed to do good ecological research to be sure so my statements must not be misinterpreted to suggest that I do not appreciate natural history. Good natural history leads into the two parts of ecology that I would like to discuss. I call these social ecology and scientific ecology.

Social ecology flows most easily out of natural history and deals with the interaction between humans and the biota. Thus, for example, many people love birds which are ever present in both cities and countryside, are often highly colourful and vocal in our environment. Similarly, many tourists from North America visit Australia, Africa and Central America to see birds that are unique to those regions. Similar adventures are available to see elephants, bison, bears, and whales in their natural habitats. Social ecology flows into conservation biology in cases where preferred species are threatened by human changes to the landscape. The key here is that there is a mix in social ecology between human entertainment and a concern for species losses that are driven by human actions. Social ecology is mostly about people and their views of what parts of the environment are important to them. People love elephants but are little concerned about earthworms unless they bother them.

Scientific ecology should operate with a broader perspective of testing hypotheses to understand how populations and communities of animals and plants interact to produce the world as we see it. It asks about how species interactions change over time and whether they lead to environmental stability or instability. Scientific ecology has a time dimension that is much longer than that of social ecology. The focus of scientific ecology is hypothesis testing to answer problems or questions about how the biological world works. This perspective interacts strongly with climate change and human disturbances as well as natural disturbances like flooding or forest fires. While social ecology asks what is happening, scientific ecology asks why this is happening in our ecosystems. Scientific ecology allows us to determine the causal factors behind problems of change and the management approaches that might be required. While social ecology observes that migratory birds appear to be declining in abundance, scientific ecology asks exactly which bird species are at risk and what factors like food supplies, predation, or disease are the cause of the decline. And most importantly can humans change the environment to prevent species losses?

Conservation ecology has become the link between social and scientific ecology and shares elements of both approaches. Too much of social conservation biology consists of moaning and groaning about changes with little data and unverifiable speculations. As such it provides little help to solve conservation problems. When there is clear public support for issues like old growth logging, politicians often do not act ethically to follow public support because of economics or inertia. Scientific ecology has been strongly influenced by Karl Popper’s (1963) book, with much discussion today among philosophers about Popper’s approach to hypotheses within the context of our social values and objectives (Dias 2019). Lundblad and Conway (2021) provide a classic example of hypothesis testing for clutch size in birds which illustrates well the path of scientific ecology over many years from initial conjectures to more refined understanding of the original scientific question.

In a sense this ecological dichotomy is found in many of the sciences. Medicine is a good example. We can observe and describe symptoms of people dying of lung cancer, but medical scientists really wish to know what environmental causes like air pollution or cigarette smoking are producing this mortality, and whether genetic backgrounds are involved. Science is far from perfect and there are many false leads in proposals of drugs in medicine that turn out to be counterproductive to solving a particular problem. Kim and Kendeou (2021) discuss the critical question of knowledge transfer as science progresses in our society today through knowledge transfer from generation to generation.

My concern is that social ecology is replacing scientific ecology in the ecological literature so that as we are so enamoured with the beauty of nature, we forget the need to find out quantitatively what is happening and how it might be mitigated. As with medicine, talking about problems does not solve them without serious empirical scientific study.

Dias, E.A. (2019) Science as a game in Popper. Griot : Revista de Filosofia,, 19, 327-337.doi: 10.31977/grirfi.v19i3.1239. (in Portuguese; use Google Translate)

Kim, J. & Kendeou, P. (2021) Knowledge transfer in the context of refutation texts. Contemporary Educational Psychology, 67, 102002.doi: 10.1016/j.cedpsych.2021.102002.

Lundblad, C.G. & Conway, C.J. (2021) Ashmole’s hypothesis and the latitudinal gradient in clutch size. Biological Reviews, 96, 1349-1366.doi: 10.1111/brv.12705.

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

On Ignoring Evidence

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 Conservation Complexities

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

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

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

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

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

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

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

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

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

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

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

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

On Ecological Imperialism

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.

Belief vs. Evidence

There is an interesting game you could enter into if you classified the statements you hear or read in the media or in ecological papers. The initial dichotomy is whether or not a statement is a BELIEF or EVIDENCE BASED. There is a continuum between these polar opposites so there can easily be disagreements based on a person’s background. If I say “I believe that the earth is round” you will recognize that this is not a simple belief but a physical fact that is evidence-based. Consequently we use the word ‘belief’ in many different ways. If I say that “Aliens from outer space are firing ray guns to cause flooding in California and Australia”, it is unlikely that you will be convinced because there is no evidence of how this process could work.

If we listen to the media or read the news, you will hear many statements that I or we ‘believe’ that speed limits on streets should be reduced, or that certain types of firearms should be prohibited. The natural response of a scientist to such statements is to ask for what evidence is available that such actions will solve problems, and if there is no evidence, we deal only with opinions or beliefs. If  you lived several hundred years ago, you would be told that “malaria” was a disease caused by “bad air” coming from swamps and rivers, since there was no evidence at the time about microorganisms causing disease. So in a broad sense historical progress was made by people looking for ‘evidence’ to temper and test ‘beliefs’.

How does all this relate to ecological science? I would add the requirement to papers that state some conclusions in ecology journals to also state the beliefs the paper rely on to reach its conclusions, in addition to stating clear hypotheses and alternative hypotheses. Consider the simple case of random sampling, a basic requirement in all statistical methods. But almost no paper states what statistical population is being sampled, and if it does often the study plots are not placed randomly. The standard excuse to this is that our results apply to a large biome, and it is not physically possible to sample randomly, or that we get the same results whether we sample randomly or not. Whatever the excuse, we need to recognize this as a belief or an assumption, a less damning scientific term. And if this assumption is not accepted it is possible to sample other areas or with other methods to test if the evidence validates the assumption. Evidence can always be improved with enough funding, and this replication is exactly what many scientists are doing daily.

Until recently most scientists believed that CO2 was good for plants, and so the more CO2 the better. But the evidence provided was based on simple theory and short term lab experiments. Reich et al. (2018) and Zhu et al. (2018) pointed out that this was not correct when long-term studies were done on C3 plants like rice. So this is a good illustration of the progress of science from belief to evidence. And over the past 50 years it has become very clear that increased CO2 increases atmospheric temperature with drastic climatic and biodiversity consequences (Ripple et al. 2021). The result of these scientific advances is that now there is an extensive amount of scientific research giving the empirical evidence of climate change and CO2 effects on plants and animals. Most people agree with these broad conclusions, but there are people in large corporations and governments around the world who deny these scientific conclusions because they believe that climate change is not happening and is of little consequence to biodiversity or to daily life.

It is quite possible to ignore all the scientific literature about the consequences of climate change, CO2 increase, and biodiversity loss but the end result of passing over these problems now will fall heavily onto your children and grandchildren. The biosphere is screaming the message that ignorance will not necessarily lead to bliss.

Reich, P.B., Hobbie, S.E., Lee, T.D. & Pastore, M.A. (2018) Unexpected reversal of C3 versus C4 grass response to elevated CO2 during a 20-year field experiment. Science, 360, 317-320.doi: 10.1126/science.aas9313.

Ripple, W.J., Wolf, C., Newsome, T.M., Gregg, J.W., Lenton, T.M., Palomo, I., Eikelboom, J.A.J., Law, B.E., Huq, S., Duffy, P.B. & Rockström, J. (2021) World Scientists’ Warning of a Climate Emergency 2021. BioScience, 71, 894-898.doi: 10.1093/biosci/biab079.

Shivanna, K.R. (2022) Climate change and its impact on biodiversity and human welfare. Proceedings of the Indian National Science Academy, 88, 160-171.doi: 10.1007/s43538-022-00073-6.

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.

Williams, S.E., Williams, S.E. & de la Fuente, A. (2021) Long-term changes in populations of rainforest birds in the Australia Wet Tropics bioregion: A climate-driven biodiversity emergency. PLoS ONE, 16.doi: 10.1371/journal.pone.0254307.

Zhu, C., Kobayashi, K., Loladze, I., Zhu, J. & Jiang, Q. (2018) Carbon dioxide (CO2) levels this century will alter the protein, micronutrients, and vitamin content of rice grains with potential health consequences for the poorest rice-dependent countries. Science Advances, 4, eaaq1012 doi: 10.1126/sciadv.aaq1012.