What can we do as ecologists to improve the publishing standards of ecology papers? I suggest one simple but bold request. We should require at the end of every published paper a annotated list of the assumptions made in providing the analysis reported in the paper. A tabular format could be devised with columns for the assumption, the perceived support of and tests for the assumption, and references for this support or lack thereof. I can hear the screaming already, so this table could be put in the Supplementary Material which most people do not read. We could add to each paper in the final material where there are statements of who did the writing, who provided the money, and add a reference to this assumptions table in the Supplementary Material or a statement that no assumptions about anything were made to reach these conclusions.
The first response I can detect to this recommendation is that many ecologists will differ in what they state are assumptions to their analysis and conclusions. As an example, in wildlife studies, we commonly make the assumption that an individual animal having a radio collar will behave and survive just like another animal with no collar. In analyses of avian population dynamics, we might commonly assume that our visiting nests does not affect their survival probability. We make many such assumptions about random or non-random sampling. My question then is whether or not there is any value in listing these kinds of assumptions. My response is that this approach of listing what the authors think they are assuming should alert the reviewers to the elephants in the room that have not been listed.
My attention was called to this general issue by the recent paper of Ginzburg and Damuth (2022) in which they contrasted the assumptions of two general theories of functional responses of predators to prey – “prey dependence” versus “ratio dependence”. We have in ecology many such either-or discussions that never seem to end. Consider the long-standing discussion of whether populations can be regulated by factors that are “density dependent” or “density independent”, a much-debated issue that is still with us even though it was incisively analyzed many years ago.
Experimental ecology is not exempt from assumptions, as outlined in Kimmel et al. (2021) who provide an incisive review of cause and effect in ecological experiments. Pringle and Hutchinson (2020) discuss the failure of assumptions in food web analysis and how these might be resolved with new techniques of analysis. Drake et al. (2021) consider the role of connectivity in arriving at conservation evaluations of patch dynamics, and the importance of demographic contributions to connectivity via dispersal. The key point is that, as ecology progresses, the role of assumptions must be continually questioned in relation to our conclusions about population and community dynamics in relation to conservation and landscape management.
Long ago Peters (1991) wrote an extended critique of how ecology should operate to avoid some of these issues, but his 1991 book is not easily available to students (currently available on Amazon for about $90). To encourage more discussion of these questions from the older to the more current literature, I have copied Peters Chapter 4 to the bottom of my web page at https://www.zoology.ubc.ca/~krebs/books.html for students to download if they wish to discuss these issues in more detail.
Perhaps a possible message in all this has been that ecology has always wished to be “physics-in-miniature” with grand generalizations like the laws we teach in the physical sciences. Over the last 60 years the battle in the ecology literature has been between this model of physics and the view that every population and community differ, and everything is continuing to change under the climate emergency so that we can have little general theory in ecology. There are certainly many current generalizations, but they are relatively useless for a transition from the general to the particular for the development of a predictive science. The consequence is that we now bounce from individual study to individual study, typically starting from different assumptions, with very limited predictability that is empirically testable. And the central issue for ecological science is how can we move from the present fragmentation in our knowledge to a more unified science. Perhaps starting to examine the assumptions of our current publications would be a start in this direction.
Drake, J., Lambin, X., and Sutherland, C. (2021). The value of considering demographic contributions to connectivity: a review. Ecography 44, 1-18. doi: 10.1111/ecog.05552.
Ginzburg, L.R. and Damuth, J. (2022). The Issue Isn’t Which Model of Consumer Interference Is Right, but Which One Is Least Wrong. Frontiers in Ecology and Evolution 10, 860542. doi: 10.3389/fevo.2022.860542.
Kimmel, K., Dee, L.E., Avolio, M.L., and Ferraro, P.J. (2021). Causal assumptions and causal inference in ecological experiments. Trends in Ecology & Evolution 36, 1141-1152. doi: 10.1016/j.tree.2021.08.008.
Peters, R.H. (1991) ‘A Critique for Ecology.’ (Cambridge University Press: Cambridge, England.) ISBN:0521400171 (Chapter 4 pdf available at https://www.zoology.ubc.ca/~krebs/books.html)
Pringle, R.M. and Hutchinson, M.C. (2020). Resolving Food-Web Structure. Annual Review of Ecology, Evolution, and Systematics 51, 55-80. doi: 10.1146/annurev-ecolsys-110218-024908.
Hi Charley, totally in favour of your suggestion re assumptions, especially for management papers. It was something that Prof Andrewartha would stress, but seems to have fallen out the window these days. Articulating the assumptions that successful management is based on and critically assessing the likelihood that they are valid is a crucial initial step, at least for planning effective ecological management.