Tag Archives: progress in ecology

The Time Frame of Ecological Science

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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 Two Questions: So what? What next?

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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

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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 Ecological Imperialism

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

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

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

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

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

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

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

Belief vs. Evidence

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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.

Have we moved on from Hypotheses into the New Age of Ecology?

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For the last 60 years a group of Stone Age scientists like myself have preached to ecology students that one needs hypotheses to do proper science. Now it has always been clear that not all ecologists followed this precept, and a recent review hammers this point home (Betts et al. 2021). I have always asked my students to read the papers from the Stone Age about scientific progress – Popper (1959), Platt (1964), Peters (1991) and even back to the Pre-Stone Age, Chamberlin (1897). There has been much said about this issue, and the recent Betts et al. (2021) paper pulls much of it together by reviewing papers from 1991 to 2015. Their conclusion is dismal if you think ecological science should make progress in gathering evidence. No change from 1990 to 2015. Multiple alternative hypotheses = 6% of papers, Mechanistic hypotheses = 25% of papers, Descriptive hypotheses = 12%, No hypotheses = 75% of papers. Why should this be after years of recommending the gold standard of multiple alternative hypotheses? Can we call ecology a science with these kinds of scores? 

The simplest reason is that in the era of Big Data we do not need any hypotheses to understand populations, communities, and ecosystems. We have computers, that is enough. I think this is a rather silly view, but one would have to interview believers to find out what they view as progress from big data in the absence of hypotheses. The second excuse might be that we cannot be bothered with hypotheses until we have a complete description of life on earth, food webs, interaction webs, diets, competitors, etc. Once we achieve that we will be able to put together mechanistic hypotheses rapidly. An alternative statement of this view is that we need very much natural history to make any progress in ecology, and this is the era of descriptive natural history and that is why 75% of papers do not list the word hypothesis.

But this is all nonsense of course, and try this view on a medical scientist, a physicist, an aeronautical engineer, or a farmer. The fundamental principle of science is cause-and-effect or the simple view that we would like to see how things work and why often they do not work. Have your students read Romesburg (1981) for an easy introduction and then the much more analytical book by Pearl and Mackenzie (2018) to gain an understanding of the complexity of the simple view that there is a cause and it produces an effect. Hone et al. (2023) discuss these specific problems with respect to improving our approach to wildlife management

What can be done about the dismal situation described by Betts et al. (2021)? One useful recommendation for editors and reviewers would be to request for every submitted paper for a clear statement of the hypothesis they are testing, and hopefully for alternative hypotheses. There should be ecology journals specifically for natural history where the opposite gateway is set: no use of ‘hypothesis’ in this journal. This would not solve all the Betts et al. problems because some ecology papers are based on the experimental design of ‘do something’ and then later ‘try to invent some way to support a hypotheses’, after the fact science. One problem with this type of literature survey is, as Betts et al. recognized, is that papers could be testing hypotheses without using this exact word. So words like ‘proposition’, ‘thesis’, ‘conjectures’ could camouflage thinking about alternative explanations without the actual word ‘hypothesis’.

One other suggestion to deal with this situation might be for journal editors to disallow all papers with hypotheses that are completely untestable. This type of rejection could be instructive to authors to assist rewriting your paper to be more specific about alternative hypotheses. If you can make a clear causal set of predictions that a particular species will go extinct in 100 years, this could be described as a ‘possible future scenario’ that could be guided by some mechanisms that are specified. Or if you have a hypothesis that ‘climate change will affect species geographical ranges, you are providing  a very vague inference that is difficult to test without being more specific about mechanisms, particularly if the species involved is rare.

There is a general problem with null hypotheses which state there is “no effect”. In some few cases these null hypotheses are useful but for the most part they are very weak and should indicate that you have not thought enough about alternative hypotheses.

So read Platt (1964) or at least the first page of it, the first chapter of Popper (1959), and Betts et al. (2021) paper and in your research try to avoid the dilemmas they discuss, and thus help to move our science forward lest it become a repository of ‘stamp collecting’.

Betts, M.G., Hadley, A.S., Frey, D.W., Frey, S.J.K., Gannon, D., Harris, S.H., et al. (2021) When are hypotheses useful in ecology and evolution? Ecology and Evolution, 11, 5762-5776. doi: 10.1002/ece3.7365.

Chamberlin, T.C. (1897) The method of multiple working hypotheses. Journal of Geology, 5, 837-848 (reprinted in Science 148: 754-759 in 1965). doi. 10.1126/science.148.3671.754.

Hone, J., Drake, A. & Krebs, C.J. (2023) Evaluation options for wildlife management and strengthening of causal inference BioScience, 73, 48-58.doi: 10.1093/biosci/biac105.

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

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

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

Popper, K.R. (1959) The Logic of Scientific Discovery. Hutchinson & Co., London. ISBN: 978-041-5278-447.

Romesburg, H.C. (1981) Wildlife science: gaining reliable knowledge. Journal of Wildlife Management, 45, 293-313. doi:10.2307/3807913.

Is Ecology Becoming a Correlation Science?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Five Stages of Ecological Research

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Ecological research falls into five broad classes or stages. Each stage has its strengths and its limitations, and it is important to recognize these since no one stage is more or less important than any other. I suggest a classification of these five stages as follows:

  1. Natural History
  2. Behavioural Ecology
  3. Applied Ecology
  4. Conservation Ecology
  5. Ecosystem Ecology

The Natural History stage is the most popular with the public and in some sense the simplest type of ecological research while at the same time the critical foundation of all subsequent research. Both Bartholomew (1986) and Dayton (2003) made impassioned pleas for the study of natural history as a basis of understanding all the biological sciences. In some sense this stage of biological science has now come into its own in popularity, partly because of influential TV shows like those of David Attenborough but also because of the ability of talented wildlife photographers to capture amazing moments of animals in the natural world. Many scientists still look upon natural history as “stamp-collecting” unworthy of a serious ecologist, but this stage is the foundational element of all ecological research.

Behavioural ecology became popular as one of the early outcomes of natural history observations within the broad framework of asking questions about how individuals in a population behave, and what the ecological and evolutionary consequences of these behaviours are to adaptation and possible future evolution. One great advantage of studying behavioural ecology has been that it is quick, perfectly suited to asking simple questions, devising experimental tests, and then being able to write a report, or a thesis on these results (Davies et al. 2012). Behavioural ecology is one of the strongest research areas of ecological science and provides entertainment for students of natural history and excellent science to understand individual behaviour and how it fits into population studies. It is perhaps the strongest of the ecological approaches for drawing the public into an interest in biodiversity.

Applied ecology is one of the oldest fields of ecology since it arose more than 100 years ago from local problems of how organisms affected human livelihoods. It has subdivided into three important sub-fields – pest management, wildlife management, and fisheries management. Applied ecology relies heavily on the principles of population ecology, one level above the individual studies of behavioural and natural history research. These fields are concerned with population changes, whether to reduce populations to stop damage to crops, or to understand why some species populations become pests. All applied ecology heavily interreacts with human usage of the environment and the economics of farming, fisheries, and wildlife harvesting. In a general sense applied ecology is a step more difficult than behavioural ecology because answering the applied problems or management has a longer time frame than the typical three-year thesis project. Applied ecology has a broad interface with evolutionary ecology because human actions can disrupt natural selection and pest evolution can complicate every management problem.

Conservation ecology is the new kid on the block. It was part of wildlife and fisheries management until about 1985 when it was clear to all that some populations were endangered by human changes to the ecosystems of fisheries, forestry, and agriculture. The essential problems of conservation ecology were described elegantly by Caughley (1994). Conservation issues are the most visible of all issues in population and community ecology, and they are often the most difficult to resolve when science dictates one conservation solution that interferes with the dominant economic view of human society. If species of interest are rare the problem is further confounded by the difficulty of studying rare species in the field. What will become of the earth’s ecosystems in the future depends in large part as to how these conservation conflicts can be resolved.

Ecosystem ecology and community ecology are the important focus at present but are hampered by a lack of a clear vision of what needs to be done and what can be done. The problem is partly that there is much poor theory, coupled with much poor data. The critical questions in ecosystem ecology are currently too vague to be studied in a realistic time period of less than 50 years. Climate change is impacting all our current ideas about community stability and resilience, and what predictions we can make for whole ecosystems in the light of a poor database. Ironically experimental manipulations are being done by companies with an economic focus such as forestry but there are few funds to make use of these large-scale landscape changes. In the long term, ecosystem ecology is the most significant aspect of ecology for humans, but it is the weakest in terms of understanding ecosystem processes. We can all see the negative effects of human changes on landscapes, but we have little in the way of scientific guidance to predict the long-term consequences of these changes and how they can be successfully ameliorated.

All of this is distressing to practical ecologists who wish to make a difference and be able to counteract undesirable changes in populations and ecosystems. It is important for all of us not to give up on reversing negative trends in conservation and land management and we need to do all we can to influence the public in general and politicians in particular to change negative trends to positive ones in our world. An array of good books points this out very forcefully (e.g., Monbiot 2018, Klein 2021). It is the job of every ecologist to gather the data and present ecological science to the community at large so we can contribute to decision making about the future of the Earth.

Bartholomew, G. A. (1986). The role of natural history in contemporary biology. BioScience 36, 324-329. doi: 10.2307/1310237

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

Davies, N.B., Krebs, J.R., and West, S.A. (2012) ‘An Introduction to Behavioural Ecology.‘ 4th edn. (Wiley-Blackwell: Oxford.). 520 pp.

Dayton, P.K. (2003). The importance of the natural sciences to conservation. American Naturalist 162, 1-13. doi: 10.1086/376572

Klein, Naomi (2021) ‘How to Change Everything: The Young Human’s Guide to Protecting the Planet and Each Other ‘ (Simon and Schuster: New York.) 336 pp. ISBN: 978-1534474529

Monbiot, George. (2018) ‘Out of the Wreckage: A New Politics for an Age of Crisis.’ (Verso.). 224 pp. ISBN: 1786632896

What is the Ratio of Thought to Action in Biodiversity Conservation?

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Many ecologists who peruse the conservation literature will come away with a general concern about the amount of effort that goes into thoughts about how conservation should be done and how much action is currently being carried out to achieve these goals in the field. My premise here is that currently the person-power given to thought greatly exceeds the person-power devoted to actually achieving the broad conservation goal of protecting biodiversity. Let me illustrate this with one dilemma in conservation: should we be concerned predominately with the loss of threatened and endangered species, or should we concentrate on the major dominant species in our ecosystems? Of course, this is not a black-or-white dichotomy, and the first answer is that we should do both. But the economist would suggest that resources are limited, and you cannot do both, so the question should be reworded as to what fraction of resources should go to one or the other of these two activities.

Consider the example of threatened and endangered species. Many of these species are rare numerically at present. In the past they may have been abundant but that is not always the case. The ecologist will know as a universal constant that most species in ecosystems are rare, and because they are rare, they are most difficult to study to answer the simple question why are they rare? Pick your favourite rare species and try to answer this question. For some species under persecution by humans the answer is simple; for most it is not, and ecologists fall back on explanations like the resources they require are not abundant, or their niche is specialized, meaningless statements that can be called panchrestons unless we have infinite time and funds to find out exactly what the limiting resources are, or why their niche is specialized. Now let us make a simple thought experiment that asks: what would happen if all these rare and endangered species disappeared from the world’s ecosystems? The first response would be total outrage that anyone would ask such a terrible question, so it is best not to talk about it. The second would be that we would be outraged if our favorite bird or frog disappeared like the passenger pigeon. The third might be that we should consider this question seriously.

Some community and ecosystem ecologists might wager that nothing would happen to ecosystem dynamics if all the rare and endangered species disappeared. No one of course would admit to such a point of view since it would end their career. At the moment we are in the unenviable state of doing the opposite experiment on the world’s coral reefs which are suffering in an ocean that is acidifying and heating up, pollution that is increasing, and overfishing that is common (Fraser et al. 2019, Lebrec et al. 2019, Romero-Torres et al. 2020). Coral reefs are an extreme example of human impacts on areas of high conservation and economic value such that the entire ecosystem will have to reconstruct itself with corals of greater tolerance to current and future conditions, a future with no clear guess of what positive effects will transpire.

Perhaps the message of both coral reef conservation and terrestrial ecosystem conservation is that you cannot destroy the major species without major consequences. Australia provides a good example of the consequences of altering predator abundance in an ecosystem. The dingo (Canis familaris) has been persecuted because of predation on sheep, and at the same time domestic cats (Felis catus) and red foxes (Vulpes vulpes) have been introduced to the continent. The ecological question is whether the reintroduction of the dingo to places where it has been exterminated will reduce the abundance of cats and foxes, and thus save naïve prey species from local extinction (Newsome et al. 2015). The answer to this question is far from clear (Morgan et al. 2017, Hunter and Letnic 2022) and may differ in different ecosystems within Australia.  

The bottom line is that our original question about rare species cannot be answered. There is much literature on introduced predators affecting food webs, following from Estes et al. (2011) important paper. and now there is much research effort on the roles of apex predators and consumers on ecosystem dynamics (Serrouya et al. 2021). Much of this effort concentrates on the common animals rather than the rare ones with which we began this discussion. Much more action in the field is needed on all conservation fronts since in my opinion the amount of thought we have available now will last field workers for the rest of the century.

Estes, J.A., Terborgh, J., Brashares, J.S., Power, M.E., Berger, J., et al. (2011). Trophic downgrading of Planet Earth. Science 333, 301-306. doi: 10.1126/science.1205106.

Fraser, K.A., Adams, V.M., Pressey, R.L., and Pandolfi, J.M. (2019). Impact evaluation and conservation outcomes in marine protected areas: A case study of the Great Barrier Reef Marine Park. Biological Conservation 238, 108185. doi: 10.1016/j.biocon.2019.07.030

Hunter, D.O. and Letnic, M. (2022). Dingoes have greater suppressive effect on fox populations than poisoning campaigns. Australian Mammalogy 44. doi: 10.1071/AM21036.

Lebrec, M., Stefanski, S., Gates, R., Acar, S., Golbuu, Y., Claudel-Rusin, A., Kurihara, H., Rehdanz, K., Paugam-Baudoin, D., Tsunoda, T., and Swarzenski, P.W. (2019). Ocean acidification impacts in select Pacific Basin coral reef ecosystems. Regional Studies in Marine Science 28, 100584. doi: 10.1016/j.rsma.2019.100584.

Morgan, H.R., Hunter, J.T., Ballard, G., Reid, N.C.H., and Fleming, P.J.S. (2017). Trophic cascades and dingoes in Australia: Does the Yellowstone wolf–elk–willow model apply? Food Webs 12, 76-87. doi: 10.1016/j.fooweb.2016.09.003.

Newsome, TM., Ballard, G.-A., Crowther, M.S., Dellinger, J.A., Fleming, P.J.S., et al. (2015). Resolving the value of the dingo in ecological restoration. Restoration Ecology 23, 201-208.  doi: 10.1111/rec.12186.

Romero-Torres, M., Acosta, A., Palacio-Castro, A.M., Treml, E.A., Zapata, F.A., Paz-García, D.A., and Porter, J.W. (2020). Coral reef resilience to thermal stress in the Eastern Tropical Pacific. Global Change Biology 26, 3880-3890. doi: 10.1111/gcb.15126

Serrouya, R., Dickie, M., Lamb, C., Oort, H. van, Kelly, A.P., DeMars, C., et al. (2021). Trophic consequences of terrestrial eutrophication for a threatened ungulate. Proceedings of the Royal Society B: Biological Sciences 288, 20202811. doi: 10.1098/rspb.2020.2811.

How Do We Decide Controversial Issues in Conservation?

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While almost everyone favours conservation of plants and animals around the globe, it is far from clear how this broad goal can be disarticulated into smaller issues. Once we have done this the solution of the conservation problem should be simple. But it is not (Sutherland et al, 2021). Take an example of the koala in Australia, cute mid-size marsupials that live in trees and eat leaves. If koalas are to be protected, you must protect forests, but if you protect forests the companies that survive by logging on both private and crown land will be adversely affected. We have an immediate conflict, so how do we decide what to do. One response which we can label have-your-cake-and-eat-it-too suggests that we use some of our forests for logging and protect some forests for ecological reserves. Everyone is now happy, but things unravel. As the human population grows, we need more wood, so over time we would have to log more and more of the forested areas that could support koalas. Conflict now, jobs for loggers vs. conservation of koalas. The simplest solution is to decide all this in economic terms. Logging produces much money; conservation is largely a drain on the taxpayers. To propose that conservation should win, ecologists will pull out David Attenborough to show all the beauties of the forest and to point out that the forest contains many other animals and plants and not just trees for lumber. Stalemate, and social and economic goals begin to override the ecological issue until some compromise is suggested and accepted.

While this kind of oversimplified scenario is common, the whole issue of conservation decision making is fraught with problems and who is going to decide these issues (Christie et al. 2022)? In a democracy in the good old days, you took a vote or a poll and decided to win/lose at >50% of the vote. But this cannot work for critical problems. We have a good example of this problem now with Covid vaccination requirements, and a vocal minority opposed to vaccinations. This now spills over into the issue of whether to wear a face mask or not. In all these kinds of scenarios science delivers a simple decision about the consequences of decision A vs decision B, but the problem is that society can refuse to recognize the scientific results or just prefer decision B with little visible justification. Science is not always perfect, adding further complications. And in the case of the covid virus, the virus can mutate in unexpected ways, complicating prognoses. In the case of protected conservation areas, we can suffer fires, floods, insect outbreaks and any number of events that affect the balance of decision making.

There is a large literature on decision making in conservation (e.g., Bower et al. 2018) and even good advice from the field of psychology about this problem of making decisions (Papworth 2017). The best systematic decision tree I have found is that in Sutherland et al. 2021). Sutherland et al. (2021) compiled a framework that can be used profitably in deciding on the level of evidence assessment (see Table 1 and Figure 1 below from their paper).

Table 1 and Figure 1 from Sutherland et al. (2021)

The Strategic Evidence Assessment Framework. Seven levels of evidence assessment, how to apply them.

Assessment LevelApproach UsedGeneral Database ApplicationApproximate Time to reflect on the evidence
1 No consideration of evidenceContinue with existing practice or make decisions without considering scientific evidencenone
2 Assertion but no independent consideration of evidenceConsultation with others (including experts) that affect decision but are not verified e.g. “we normally do this”, “accepted best practice is to do this”minutes
3Papers reviewed, looking at: Read the title and/or summary points to determine whether action described in the paper is likely to be effective or not. Review effectiveness category e.g. “likely to be beneficial” on action page to decide whether action is likely to be effective or notminutes
4 Read abstract to assess the evidence described in the paper in relation to the local problemTens of minutes- hours
5  Read abstract, key results and conclusion assessing each paper in relation to the decision being madeHours
6 Read the full underlying paper/s. This is likely to affect decisions on study quality, relevance and modificationsHours to days
7Comprehensive assessmentA systematic review of all available literature. Assessed papers summarised as part of new reviewMonths to a year

Figure 1. A framework for considering the appropriate level of effort in decision making. Numbers refer to assessment level (Table 1). For a given decision about an action identify the column with the relevant level of consequence, start at the lowest level (1) and decide whether it would benefit from examining higher levels of evidence. Keep moving up until either the uncertainty in the effectiveness of the action is resolved from examining the evidence (from any platform) or the arrows end. This final number is the level at which the evidence assessment should occur. (From Sutherland et al. 2021 with permission).

Clearly conservation ecologists cannot use the highest assessment level for all issues that arise and must result to triage in many cases (Hayward and Castley 2018). But triage and assessment levels 1 and 2 should be rare in making judgement on what program to adopt. We need to get the science right for all conservation problems.

But this is not enough to get thoughtful political decisions. Some native species can be pests, yet nothing is done to reduce their damage (e.g. horses in North America and Australia, camels and goats in Australia, feral pigs in North America) and the list goes on. Nothing is done because of budget limitations or political concerns about “cute species”. The science of conservation is difficult enough, the social science of conservation is too often out of our control.

Bower, S.D., Brownscombe, J.W., Birnie-Gauvin, K. Ford, M.I. et al. (2018). Making Tough Choices: Picking the appropriate conservation decision-making tool. Conservation Letters 11, e12418. doi: 10.1111/conl.12418.

Christie, A.P., Downey, H., Bretagnolle, V., Brick, C., Bulman, C.R., et al. (2022). Principles for the production of evidence-based guidance for conservation actions. Conservation Science and Practice 4, e579. doi: 10.1111/csp2.12663.

Hayward, M.W. and Castley, J.G. (2018). Triage in Conservation. Frontiers in Ecology and Evolution 5, 168. doi: 10.3389/fevo.2017.00168.

Papworth, Sarah (2017). Decision-making psychology can bolster conservation. Nature Ecology & Evolution 1, 1217-1218. doi: 10.1038/s41559-017-0281-9.

Sutherland, W.J., Downey, H., Frick, W.F., Tinsley-Marshall, P., and McPherson, T. (2021). Planning practical evidence-based decision making in conservation within time constraints: the Strategic Evidence Assessment Framework. Journal for Nature Conservation 60, 125975. doi: 10.1016/j.jnc.2021.125975.