Monthly Archives: November 2020

How should biodiversity research be directed?

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There are many scientific papers and news reports currently that state that biodiversity is in rapid decline on Earth. No evidence is usually cited for this statement – it is considered to be self evident. What follows from that is typically a panic request for more work on declining populations, more money for conservation NGOs and national parks. Political ecology statements that request more money for ecological research are certainly on the right track if we are to understand how to achieve conservation of our biota. But the question I want to raise here is how to proceed on this broad issue in a logical manner. To do this I will not discuss political ecology or how to gain more donors for conservation agencies, valuable services to be sure. But behind all this advertising is a scientific agenda which needs careful consideration.    

Problem #1 is to determine if there is a problem. In some areas of conservation ecology there is much agreement on principles – we all agree that we are losing natural areas for urban and agricultural development, that we need more protected areas, that most protected areas are not large enough, that there are serious problems with poaching of wildlife and lumber in some protected areas, and that global pollution is affecting much of our biodiversity. In other areas of conservation ecology there is much controversy about details. Is global biodiversity in rapid decline (Vellend et al. 2017, Cardinale et al. 2018)? How can we best identify species at risk, and once we identify them, what can we do to prevent population collapse?

The answer to Problem #1 is that there are problems in some areas but not in others, in some taxonomic groups, but not in others, but overall the data are completely inadequate for a clear statement that overall biodiversity is in global decline (Dornelas et al. 2019). The problems of biodiversity conservation are local and group specific, which leads us to Problem #2.

Problem # 2 is to go back to the ecological details, concentrating on local and specific problems, exactly what should we do, and what can we do? The problems here relate almost entirely to ecological methods – how do we estimate species abundances particularly for rare species? How do we deal with year to year changes in communities? How long should a monitoring program continue until it has reliable conclusions about biodiversity change? None of these questions are simple to answer and require much discussion which is currently under way. How long is a long-term study? It might be something like 30 generations for vertebrate species or even longer, but what is it for earthworms or bark beetles? How can we best sample the variety of insects in an ecosystem in which they might be in decline (Habel et al. 2019)?

We need to scale our conservation studies for particular species, and this has led us into the Species-At-Risk dilemma. We can gather data for a specific geographical area like Canada on the species that we deem at risk. Typically, these are vertebrates, and we ignore the insects, microbes, and the rest of the community. We try to identify threatening processes for each species and write a detailed report (Bird and Hodges 2017). The action plan specified can rarely be carried out because it is multi-year and expensive, so the matter rests. For many of these species at risk and for almost all that are ignored the central problem is action – what could you do about a declining species-at-risk, given funds and person-power? We do what we can on a local scale on the principle that it is better to do something than nothing (Westwood et al. 2019). But too often even if we have a good ecological understanding of declines, for example in mountain caribou in Canada, little or nothing is done (Palm et al. 2020). Conservation collides with economics.

I will try to draw a few possible conclusions out of this general discussion.

  1. It is far from clear that global biodiversity is declining rapidly.
  2. On a local level we can do careful evaluations for some species at risk and take possible action if funding is available.
  3. Setting aside large areas of habitat is currently the best immediate conservation strategy. Managing land use is critical.
  4. Designing strong monitoring programs is essential to discover population and community trends so that, if action can be taken, it is not too late.
  5. Climate change will have profound biodiversity effects in the long run, and conservation scientists must work short-term but plan long-term.

As we take actions for conservation, we ought to keep in mind the central question: What will this ecosystem look like in 100 or 200 years? Perhaps that could be a t-shirt slogan.

Bird, S.C., and Hodges, K.E. (2017). Critical habitat designation for Canadian listed species: Slow, biased, and incomplete. Environmental Science & Policy 71, 1-8. doi: 10.1016/j.envsci.2017.01.007.

Cardinale, B.J., Gonzalez, A., Allington, G.R.H., and 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.

Dornelas, M., Gotelli, N.J., Shimadzu, H., Moyes, F., Magurran, A.E., and McGill, B.J. (2019). A balance of winners and losers in the Anthropocene. Ecology Letters 22, 847-854. doi: 10.1111/ele.13242.

Habel, J.C., Samways, M.J., and Schmitt, T. (2019). Mitigating the precipitous decline of terrestrial European insects: Requirements for a new strategy. Biodiversity and Conservation 28, 1343-1360. doi: 10.1007/s10531-019-01741-8.

Palm, E.C., Fluker, S., Nesbitt, H.K., Jacob, A.L., and Hebblewhite, M. (2020). The long road to protecting critical habitat for species at risk: The case of southern mountain woodland caribou. Conservation Science and Practice 2 (7). doi: 10.1111/csp2.219.

Vellend, M., Dornelas, M., Baeten, L., Beauséjour, R., Brown, C.D., De Frenne, P., Elmendorf, S.C., et. al. (2017). Estimates of local biodiversity change over time stand up to scrutiny. Ecology 98, 583-590. doi: 10.1002/ecy.1660.

Westwood, A.R., Otto, S.P., Mooers, A., Darimont, C., Hodges, K.E., Johnson, C., Starzomski, B. et al. (2019). Protecting biodiversity in British Columbia: Recommendations for developing species at risk legislation. FACETS 4, 136-160. doi: 10.1139/facets-2018-0042.

How Should We Test Global Models in Ecology?

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There is an understandable desire to view ecological ideas on an exceptionally large or even global scale. Just as physicists, chemists, and engineers apply their scientific results as correct everywhere, biologists would like to have global hypotheses and global models of ecological principles. There is only one problem – that ecological principles or ‘laws’ are climate contingent. This simple fact has produced a minor mode of panic in the ecological literature. How reliable are our ecological principles? Must we change them as the climate changes? In principle not, since many chemical and physical laws are temperature dependent or moisture dependent, and we just recognize that these laws have a temperature or moisture parameter as part and parcel of how things like chemical reactions can change.

This kind of argument would suggest that if we build the physical-chemical universe into our ecological models we could approach the hard sciences in predictive precision. Alas as we know this is not to be. Why not? The first argument is that ecological systems are composed of many variables – all individuals in a population are not identical, communities and ecosystems contain many interacting species with different physical and chemical requirements. But this does not necessarily let ecologists off the hook because it can be interpreted to mean that we simply have a much harder job to do and it will take much longer but it is in principle achievable. The second argument is that evolution continues to occur and is in principle unpredictable, so that while we know where we are at present, we do not know the future (Ivory et al. 2019).

Let us take a global example of the decline in coral reefs as temperature in the ocean rises. We will ignore for the moment CO2 acidity changes to keep the discussion simple. We can define closely the thermal limits of different coral species, so that should give us good predictability. But we do not know if natural selection will change these thermal limits, or whether or not it can do so rapidly enough. For the most part we project that increasing ocean temperatures will destroy most of our coral reefs and turn them into algal communities. This prediction is partly based on observations of the last 40 years in different parts of the tropics and partly based on measurements in physiological ecology in the lab. But the elephant in the prediction room is evolution and what genetic variation now exists but has not been measured, as well as how far temperature and CO2 will increase (Frank 2019).  

So ecologists are caught in a dilemma – we can in principle define the current state of ecosystems and make short term predictions that we can test with further monitoring, but we cannot make the long term predictions everyone wants to have. As conservation biologists we can make warnings but few of them would stand up in court when push comes to shove. So the consequence is that we live in a world of make believe where, for example in British Columbia the government in its wisdom says yes we must protect old growth forests, and we will do all possible to achieve this goal, as long as new policies do not reduce the annual allowable cut to the forest industry.

We can look to paleoecology to get an overview of how life on Earth has changed in the past on any time scale you wish. If there is a general law coming out of all this research it is that when climate changes, ecological communities and ecosystems change. The simple message that is hard to get across is that, if you like current environmental conditions and desire only small changes in our present ecological communities, it is desirable to reduce the pollution that is causing rapid climate change. No clever and detailed global ecological model will help us overcome the tragedies unfolding with the business as usual models we currently use unless we control rapid climate change (van der Zande et al. 2020). A current popular example is the suggestion that if we plant trees around the world, we can reverse rising CO2 level. That sounds like a good achievable plan but in fact it is impossible (Friedlingstein et al. 2019).

So, my advice is two-fold. First, design and test global ecological models for short term understanding and predictions. Do not pretend they will provide accurate long-term predictions for ecological systems. In some cases, there is little predictability (Geary et al. 2020). Second, do much more long-term monitoring of communities and ecosystems to trace local and global changes quantitatively (Wagner 2020). Then at least we will know how big the ‘wolf’ is before we ‘cry wolf’. 

Frank, P. (2019). Propagation of error and the reliability of global air temperature projections. Frontiers in Earth Science 7, 223. doi: 10.3389/feart.2019.00223.

Friedlingstein, P., Allen, M., Canadell, J.G., Peters, G.P., and Seneviratne, S.I. (2019). Comment on “The global tree restoration potential”. Science 366, eaay8060. doi: 10.1126/science.aay8060.

Geary, W.L., Doherty, T.S., Nimmo, D.G., Tulloch, A.I.T., and Ritchie, E.G. (2020). Predator responses to fire: A global systematic review and meta-analysis. Journal of Animal Ecology 89, 955-971. doi: 10.1111/1365-2656.13153.

Ivory, S. J., Russell, J., Early, R., and Sax, D.F. (2019). Broader niches revealed by fossil data do not reduce estimates of range loss and fragmentation of African montane trees. Global Ecology and Biogeography 28, 992-1003. doi: 10.1111/geb.12909.

van der Zande, R.M., Achlatis, M., Bender-Champ, D., Kubicek, A., and Dove, S. (2020). Paradise lost: End-of-century warming and acidification under business-as-usual emissions have severe consequences for symbiotic corals. Global Change Biology 26, 2203-2219. doi: 10.1111/gcb.14998.

Wagner, D.L. (2020). Insect declines in the Anthropocene. Annual Review of Entomology 65, 457-480. doi: 10.1146/annurev-ento-011019-025151.

On the Use of Statistics in Ecological Research

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There is an ever-deepening cascade of statistical methods and if you are going to be up to date you will have to use and cite some of them in your research reports or thesis. But before you jump into these methods, you might consider a few tidbits of advice. I suggest three rules and a few simple guidelines:

Rule 1. For descriptive papers keep to descriptive statistics. Every good basic statistics book has advice on when to use means to describe “average values”, when to use medians, or percentiles. Follow their advice and do not in your report generate any hypotheses except in the discussion. And follow the simple advice of statisticians not to generate and then test a hypothesis with the same set of data. Descriptive papers are most valuable. They can lead us to speculations and suggest hypotheses and explanations, but they do not lead us to strong inference.

Rule 2. For explanatory papers, the statistical rules become more complicated. For scientific explanation you need 2 or more alternative hypotheses that make different, non-overlapping predictions. The predictions must involve biological or physical mechanisms. Correlations alone are not mechanisms. They may help to lead you to a mechanism, but the key is that the mechanism must involve a cause and an effect. A correlation of a decline in whale numbers with a decline in sunspot numbers may be interesting but only if you can tie this correlation into an actual mechanism that affects birth or death rates of the whales.

Rule 3. For experimental papers you have access to a large variety of books and papers on experimental design. You must have a control or unmanipulated group, or for a comparative experiment a group A with treatment X, and a group B with treatment Y. There are many rules in the writings of experimental design that give good guidance (e.g. Anderson 2008; Eberhardt 2003; Johnson 2002; Shadish et al. 2002; Underwood 1990).

For all these ecology papers, consider the best of the recent statistical admonitions. Use statistics to enlighten not to obfuscate the reader. Use graphics to illustrate major results. Avoid p-values (Anderson et al. 2000; Ioannidis 2019a, 2019b). Measure effect sizes for different treatments (Nakagawa and Cuthill 2007). Add to these general admonitions the conventional rules of paper or report submission – do not argue with the editor, argue a small amount with the reviewers (none are perfect), and put your main messages in the abstract. And remember that it is possible there was some interesting research done before the year 2000.

Anderson, D.R. (2008) ‘Model Based Inference in the Life Sciences: A Primer on Evidence.’ (Springer: New York.). 184 pp.

Anderson, D.R., Burnham, K.P., and Thompson, W.L. (2000). Null hypothesis testing: problems, prevalence, and an alternative. Journal of Wildlife Management 64, 912-923.

Eberhardt, L.L. (2003). What should we do about hypothesis testing? Journal of Wildlife Management 67, 241-247.

Ioannidis, J.P.A. (2019a). Options for publishing research without any P-values. European Heart Journal 40, 2555-2556. doi: 10.1093/eurheartj/ehz556.

Ioannidis, J. P. A. (2019b). What have we (not) learnt from millions of scientific papers with P values? American Statistician 73, 20-25. doi: 10.1080/00031305.2018.1447512.

Johnson, D.H. (2002). The importance of replication in wildlife research. Journal of Wildlife Management 66, 919-932.

Nakagawa, S. and Cuthill, I.C. (2007). Effect size, confidence interval and statistical significance: a practical guide for biologists. Biological Reviews 82, 591-605. doi: 10.1111/j.1469-185X.2007.00027.x.

Shadish, W.R, Cook, T.D., and Campbell, D.T. (2002) ‘Experimental and Quasi-Experimental Designs for Generalized Causal Inference.’ (Houghton Mifflin Company: New York.)

Underwood, A. J. (1990). Experiments in ecology and management: Their logics, functions and interpretations. Australian Journal of Ecology 15, 365-389.

On Three Kinds of Ecology Papers

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There are many possible types of papers that discuss ecology, and in particular I want to deal only with empirical studies that deal with terrestrial and aquatic populations, communities, or ecosystems. I will not discuss here theoretical studies or modelling studies. I suggest it is possible to classify papers in ecological science journals that deal with field studies into three categories which I will call Descriptive Ecology, Explanatory Ecology, and Experimental Ecology. Papers in all these categories deal with a description of some aspects of the ecological world and how it works but they differ in their scientific impact.

Descriptive Ecology publications are essential to ecological science because they present some details of the natural history of an ecological population or community that is vital to our growing understanding of the biota of the Earth. There is much literature in this group, and ecologists all have piles of books on the local natural history of birds, moths, turtles, and large mammals, to mention only a few. Fauna and flora compilations pull much of this information together to guide beginning students and the interested public in increased knowledge of local fauna and flora. These publications are extremely valuable because they form the natural history basis of our science, and greatly outnumber the other two categories of papers. The importance of this information has been a continuous message of ecologists over many years (e.g. Bartholomew 1986; Dayton 2003; Travis 2020).

The scientific journals that professional ecologists read are mostly concerned with papers that can be classified as Explanatory Ecology and Experimental Ecology. In a broad sense these two categories can be described as providing a good story to tie together and thus explain the known facts of natural history or alternatively to define a set of hypotheses that provide alternative explanations for these facts and then to test these hypotheses experimentally. Rigorous ecology like all good science proceeds from the explanatory phase to the experimental phase. Good natural history provides several possible explanations for ecological events but does not stop there. If a particular bird population is declining, we need first to make a guess from natural history if this decline might be from disease, habitat loss, or predation. But to proceed to successful management of this conservation problem, we need studies that distinguish the cause(s) of our ecological problems, as recognized by Caughley (1994) and emphasized by Hone et al. (2018). Consequently the flow in all the sciences is from descriptive studies to explanatory ideas to experimental validation. Without experimental validation ‘ecological ideas’ can transform into ‘ecological opinions’ to the detriment of our science. This is not a new view of scientific method (Popper 1963) but it does need to be repeated (Betini et al. 2017). 

If I repeat this too much, I suggest you do a survey of how often ecological papers in your favorite journal are published without ever using the word ‘hypothesis’ or ‘experiment’. A historical survey of these or similar words would be a worthwhile endeavour for an honours or M.Sc. student in any one of the ecological subdisciplines. The favourite explanation offered in many current papers is climate change, a particularly difficult hypothesis to test because, if it is specified vaguely enough, it is impossible to test experimentally. Telling interesting stories should not be confused with rigorous experimental ecology.

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

Betini, G.S., Avgar, T., and Fryxell, John M. (2017). Why are we not evaluating multiple competing hypotheses in ecology and evolution? Royal Society Open Science 4, 160756. doi: 10.1098/rsos.160756.

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

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

Hone, J., Drake, Alistair, and Krebs, C.J. (2018). Evaluating wildlife management by using principles of applied ecology: case studies and implications. Wildlife Research 45, 436-445. doi: 10.1071/WR18006.

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

Travis, Joseph (2020). Where is natural history in ecological, evolutionary, and behavioral science? American Naturalist 196, 1-8. doi: 10.1086/708765.