A tangled web of vicious circles, driven by cultural issues, has prevented ecology from growing strong theoretical roots. Now this hinders development of effective conservation policies. To overcome these barriers in view of urgent societal needs, we propose a global network of postgraduate theoretical training programs

Barabas, G

Evans, MR

Hui, C

Marquet, PA

Meszena, G

Pascual, M

Possingham, HP

Rossberg, AG

Trends in Ecology & Evolution

English

A tangled web of vicious circles, driven by cultural issues, has prevented ecology from growing strong theoretical roots. Now this hinders development of effective conservation policies. To overcome these barriers in view of urgent societal needs, we propose a global network of postgraduate theoretical training programs.Funding Agencies|Swedish Research Council [VR 2017-05245]; Hungarian National Research, Development and Innovation Office [K123796]</p

Rossberg, Axel G.

Barabas, György

Possingham, Hugh P.

Pascual, Mercedes

Marquet, Pablo A.

Hui, Cang

Evans, Matthew R.

Meszena, Geza

Digitala Vetenskapliga Arkivet - Academic Archive On-line

Lets Train More Theoretical Ecologists - Here Is Why

Academic Archive On-line (Linköping University, Sweden)

Rossberg, A.G.

Barabas, G.

Possingham, H.P.

Pascual, M.

Marquet, P.A.

Hui, C.

Evans, M.R.

Meszena, G.

Stellenbosch University SUNScholar Repository

Let's train more theoretical ecologists - here is why

Queen Mary Research Online

Let’s train more theoretical ecologists - here is whyAxel G. Rossberg1†*, György Barabás2,3†, Hugh P. Possingham4,5, Mercedes Pascual6,7,Pablo A. Marquet8, Cang Hui9,10, Matthew R. Evans11, and Géza Meszéna12,3†1School of Biological and Chemical Sciences, Queen Mary University of London,London, UK2Division of Theoretical Biology, Dept. IFM, Linköping University, Linköping, Sweden3ELTE-MTA Theoretical Biology and Evolutionary Ecology Research Group, Budapest,Hungary4The Nature Conservancy, Arlington, VA, 22203, USA5The University of Queensland, Brisbane, 4072, Australia6Department of Ecology and Evolution, University of Chicago, 1101 E 57th Street,Chicago, IL, 60637, USA7Santa Fe Institute, Santa Fe, NM, 87501, USA8Departamento de Ecoloǵıa, Facultad de Ciencias Biológicas, Pontificia UniversidadCatólica de Chile, Santiago, Chile9Centre for Invasion Biology, Department of Mathematical Sciences, StellenboschUniversity, Matieland, South Africa10African Institute for Mathematical Sciences, Muizenberg, South Africa11School of Biological Sciences, Kadoorie Biological Sciences Building, The University ofHong Kong, Pok Fu Lam Road, Hong Kong, SAR, China12Department of Biological Physics, Eötvös Loránd University, Budapest, Hungary†International Initiative for Theoretical Ecology, http://iite.info*Corresponding author: contact@iite.infoAccepted for publication in Trends in Ecology and Evolution, June 5, 2019AbstractA tangled web of vicious circles, driven by cultural issues, has prevented ecology from growingstrong theoretical roots. Now this hinders development of effective conservation policies. To overcomethese barriers in view of urgent societal needs, we propose a global network of postgraduate theoreticaltraining programs.Keywords: Theoretical ecology, ecological modelling, mathematical biology, biodiversity crisis, capacitybuilding11970 1980 1990 2000 2010 20200102030405060Publication YearMentioning model or theory (%)Figure 1: Interest in theory and models is increasing in ecological research. Points represent the propor-tion, amongst those scientific articles that mention ‘ecology’ (or grammatical variants) in title, abstractor keywords, that also mention ‘theory’ or ‘model’ (or variants), in articles listed in March 2019 in thedatabase Science Citation Index Expanded (Clarivate Analytics). The discontinuity around 1990 is anartefact due to subsequent inclusion of abstracts in records. However, the degree to which the trendrepresents changes in methodology rather than a linguistic shift [7] is difficult to assess. Of the 50 mostrecent ecological publication in the database referencing ‘theory’ or ‘model’ (on 5 March 2019), onlyeight actually invoke process-based models or mathematical theory.Why theoretical ecologyAs for all natural sciences, identification of regularities in observations is the foundation of ecologicalresearch. Ecology has been highly successful in this respect, despite the challenges our complex researchsubject poses. However, any understanding that certain regularities occur [1, 2] also raises questions ofwhy and how they arise in terms of basic principles and driving mechanisms (https://iite.info/2018/12/10/understanding-that-why-or-how-in-ecology/)—the principal concern of theory. While ecol-ogists are becoming increasingly interested in theory and models (Fig. 1), answers to most fundamentalquestions have remained open or controversial. This limits our ability to extrapolate with confidence fromknown situations to the unknown [1], thus restricting the utility of the science of ecology to dynamicallychanging societies.These limitations matter. An assessment of scientific tools available for policy support by the Inter-governmental science-policy Platform on Biodiversity and Ecosystem Services (IPBES, an organisationunder the auspices of the United Nations) drily concludes that “The scientific community may want togive priority to addressing gaps in methods for modelling impacts of drivers and policy interventionson biodiversity and ecosystem services.” [3] The knowledge gaps identified by IPBES reach deeply intoareas studied in theoretical ecology [3, Ch. 8]: species interactions and community dynamics, ecologyon large spatio-temporal scales, responsiveness of ecosystems to external drivers, projection models forindicators and ecosystem services, inclusion of social decision making, methods for combining models,etc. Insufficiency of theoretical ecology has thus become a major hindrance to the effective managementof biodiversity on a global scale.Causes and remedies for this insufficiency have often been debated over the years [1, 2, 4–11]. Theissues are so diverse that we provide an overview over the symptoms first before proposing a diagnosisand a possible cure.2SymptomsAt the purely technical level, we often see examples of problematic mathematical notation [12] andtechnical errors in the literature [13]—certainly more so than in disciplines with more mature theoreticaltraditions. In verbal arguments, theoretical concepts are often invoked inconsistently [4, 10].A deeper running issue is that, despite building on a core canon of established understanding [14],Theoretical Ecology does not give the impression of an intellectually coherent field of study. Onlookerssee a frighteningly diverse conglomerate of various particular models and ideas [1], which are at bestunrelated and at worst contradictory. The problem of competitive exclusion and limiting similarity,reverberating in the literature to the present day, is a good example. Original models [15] asserted theexistence of a definite lower limit to the similarity of coexisting species. But later it was found that thisconclusion depended on particular assumptions, which, when relaxed, revealed that there is no hard-setlimit to species similarity. It is even possible to construct models where a continuum of species coexist.This diversity of results must give the impression that all cases are different and no general conclusionscan be drawn [16]. In fact, careful analysis connects these different findings, yielding a unified picture—the idea is to shift focus from whether the coexistence of a number of phenotypes is stable to whetherit is robust ; i.e., whether coexistence is maintained for a sufficiently large range of parameters [17]. Itthen turns out that instances where very similar species are able to stably coexist require aggressivefine-tuning of model parameters. In this altered sense, the limiting similarity principle still holds: verysimilar species can only coexist only in a very narrow parameter range. However, such analyses tend todig deep into the mathematical toolbox and rarely percolate down to the canon of ecology textbooks.From our experience in teaching, young ecologists can be left with the impression that the theoreticalliterature forms a fractured, confused, and heterogeneous landscape. There is little guidance for what tolearn and what to ignore, and which ideas and methods are most reliable and useful.A wealth of theoretical concepts, ideas, and methods are regularly invoked in ecosystem manage-ment (e.g., stage-structured population models for fisheries or invasive species, epidemiological models,species distribution models, metapopulation models) [9, 11]. Practitioners find however their reliabilityuncertain [18]. This is partly why, rather than vindicating theoretical approaches and encouraging theirdevelopment, these applications can be seen as justifying scepticism about theory. While theorists havefound avenues to understand and deal with the inherent limits to predictability of ecosystems (e.g. Work-shop on Uncertainty, Sensitivity and Predictability in Ecology on 26-30 October at the MathematicalBiosciences Institute in Columbus, Ohio), these remain underutilised [9, 18].Remarkably many theoretical ecologists enter the community from the “outside”: field ecology, chem-istry, mathematics, physics, statistics, etc [2, 5]. Each of these disciplines has its own way of thinking,terminology, and notation. This can obscure strong connections between similar ideas which appearunrelated at first glance, so that important, well-established insights are easily missed. For example, thetheory of population dynamical processes is treated in apparently different ways in ecology, populationgenetics, and the replicator dynamics used in evolutionary game theory. Rarely, if ever, is it emphasisedthat the different formulations of these sub-disciplines are really about one and the same thing—thevarious, seemingly different perspectives turn out to differ mostly in notation [19].Scepticism about mathematical methods [2, 5–7, 16] (also https://dynamicecology.wordpress.com/2014/11/03/a-hypothesis-about-why-some-ecologists-dont-like-pure-theory) coupled withthe mixed backgrounds of theorists also means that peer review of theoretical research does not neces-sarily operate as efficiently as it could. Journal editors tell us that they often have difficulty findingreliable reviewers for advanced theoretical manuscripts. There is a strong incentive to either drop de-tailed theoretical arguments entirely or else to hide them in supplements [8], which may not get asthoroughly reviewed as the main article. Consequences of this de-emphasis of formal reasoning are thaterrors creep in more easily, relationships between new and established results are harder to pinpoint, andthe generality of new results is easily over- or underestimated [8].DiagnosisNone of the symptoms we considered above suggests that the reasons for the insufficient development oftheoretical ecology are inherent to the nature of the field itself. Rather, we believe that the main limitingfactors are of a cultural nature.In the tradition of natural history, many people enter ecology because they love being in nature(https://teamshrub.com/2017/03/24/theory-meta-analyses-and-stylised-facts-in-ecology/) [5,8]. And when ecologists harbour uneasy feelings towards theory, they have a point: theoretical ecology,3tradition ofnatural historyfew ecologistsstudy theorydifferentskill setsfor theory andobservationmany theorists enterfrom outsidethere are fewtheoristsineffective peer reviewtechnical issuesin literaturemathematical models considereduncertainlearning theorynot attractivelow coherenceof theorylearning theory is difficultde-emphasis of formal reasoningin literaturebreak here with trainingdriveFigure 2: The tangle of vicious circles impeding development of theoretical ecology. Black arrows indicatecausation. Boxes with round corners represent extrinsic drivers, the other boxes form part of the viciouscircles. We proposed to train more theoretical ecologists as a way to break these circles. This will benefitthe field as a whole by reversing observed symptoms along the indicated causal chains.as they see it, does not motivate them to learn it, for the reasons discussed above. Theoretical method-ology asking which limited sets of model elements (”assumptions”) lead to which high-level phenomena[6] might strike ecologists as incessant rediscovery of empirically known phenomena using unrealisticmodels [2]. All this creates an undesirable positive feedback [5], whereby preexisting attitudes towardstheory entice fewer ecologists to do theoretical research, which in turn erodes the amount and quality oftheoretical research—reinforcing the impression that learning theory is not worthwhile.Finally, ecology is a science where the required skill sets of empiricists and theorists can be verydifferent [13]. As in other biological sciences, good empirical work requires mastery of a wide rangeof techniques and a detailed knowledge of the study system. However, contrary to genes, cells, andorganisms, ecosystems and ecological communities do not replicate, are therefore not subjected to evo-lution by mutation and selection, and have not become living ‘clockworks’ that are best understood bystudying the role and working of their individual parts. Instead, strong nonlinearity and a fair dose ofrandomness give rise to emergent phenomena (ecological patterns [1]) which theorists aim to explain us-ing mathematical models, formulated in sufficient generality to accommodate the idiosyncrasies of livingsystems. The skills and techniques required for this are very different from those required for empiricalwork. Communication barriers easily arise, even when all participants acknowledge that good scienceultimately means integration of theory and observation.Theoretical ecology is thus held back by a tangle of vicious circles, reinforced by cultural biases thatwork against the organic development of the field (Fig. 2).4TreatmentTo cut through these vicious circles, appeals for changes in attitude towards theory [1, 5, 11] and fund-ing [11] are important, but insufficient. As a powerful remedy, we propose an intensive drive to traintheoretical ecologists in a global network of postgraduate training centres (Fig. 2). This would scaleup and build on experiences such as courses on modelling and theory in applied areas including infec-tious diseases and resource management that were initiated at the International Centre for TheoreticalPhysics (Trieste) by T. Hallam, S. Levin and L. Gross, aiming at participants from developing countries.We advocate for a mature state of ecology with regards to theory training, while also recognising thedifferences in skill sets underlying empirical and theoretical work. This is why we propose to targetecology graduates with theoretical interest [13], while also welcoming students from other backgroundsor disciplines. The training network will not only support efficient transmission of coherent theoreticalknowledge to the next generation of researchers. It will also facilitate: a better coverage of the fieldby putting it in on a broader base; networking within the community at the level of both students andteachers; joint efforts to organise and consolidate advanced ecological theory in textbooks; applicationsof the science, by bringing the training closer to the places where societal change and planning needs arehighest; and establishment of the profession of the Theoretical Ecologist as a recognised brand.PrognosisOur vision for ecology is to eventually become a science that explains the major observed patterns bya coherent set of theories; where these theories tell us not only what the dominant mechanisms arecontrolling predictable patterns but also what limits predictability and controllability elsewhere; wherethis understanding informs identification of management objectives and construction of problem-specificmanagement models; where these models are calibrated—wherever they are needed—using cutting-edgemethods of data collection and statistical inference; where society has confidence in what ecology pre-dicts; and where curiosity-driven empirical and theoretical research discovers ever new possibilities forunderstanding and managing ecological systems.Ecological research will always form a spectrum from purely empirical work through data-drivenmodelling to theoretical analysis of fundamental principles [1, 2, 5, 9]. It is essential however that allparticipants have a basic understanding and a joint sense of ownership of the entire spectrum [5, 20].Only then can knowledge and understanding flow effectively in both directions, bringing to full fruitionthe unity and utility of our science.AcknowledgementsG.B. acknowledges funding by the Swedish Research Council (grant VR 2017-05245), G.M. by the Hun-garian National Research, Development and Innovation Office (grant K123796).References[1] Marquet, P.A. et al. (2014) On Theory in Ecology. BioScience 64, 701–710[2] Keddy, P. (2005) Putting the Plants Back into Plant Ecology: Six Pragmatic Models for Under-standing and Conserving Plant Diversity. Ann Bot 96, 177–189[3] Ferrier, S. et al. (2016) The Methodological Assessment Report on Scenarios and Models of Biodi-versity and Ecosystem Services. Secretariat of the Intergovernmental Science-Policy Platform onBiodiversity and Ecosystem Services, Bonn, Germany[4] Levin, S.A. (1975) On the Care and Use of Mathematical Models. Am. Nat. 109, 785–786[5]  Lomnicki, A. (1988) The Place of Modelling in Ecology. Oikos 52, 139–142[6] Caswell, H. (1988) Theory and models in ecology: A different perspective. Ecological Modelling 43,33–44[7] Scheiner, S.M. and Willig, M.R. (2008) A general theory of ecology. Theor Ecol 1, 21–285[8] Fawcett, T.W. and Higginson, A.D. (2012) Heavy use of equations impedes communication amongbiologists. Proc. Natl. Acad. Sci. U. S. A. 109, 11735–11739[9] Evans, M.R. et al. (2013) Predictive systems ecology. Proc Biol Sci 280, 20131452–20131452[10] Kendall, B.E. (2015) Some directions in ecological theory. Ecology 96, 3117–3125[11] Courchamp, F. et al. (2015) Fundamental ecology is fundamental. Trends in Ecology & Evolution30, 9–16[12] Edwards, A.M. and Auger-Méthé, M. (2019) Some guidance on using mathematical notation inecology. Methods Ecol. Evol. 10, 92–99[13] Chiel, H.J. et al. (2010) From Biology to Mathematical Models and Back: Teaching Modeling toBiology Students, and Biology to Math and Engineering Students. LSE 9, 248–265[14] Hastings, A. and Gross, L., eds. (2012) Encyclopedia of Theoretical Ecology. University of CaliforniaPress, Berkeley[15] MacArthur, R. and Levins, R. (1967) The limiting similarity, convergence, and divergence of coex-isting species. Am. Nat. 101, 377–385[16] Simberloff, D. (1982) The status of competition theory in ecology. Ann. Zool. Fenn. 19, 241–253[17] Barabás, G. et al. (2012) Continuous coexistence or discrete species? A new review of an oldquestion. Evol Ecol Res 14, 523–554[18] Milner-Gulland, E.J. and Shea, K. (2017) Embracing uncertainty in applied ecology. J Appl Ecol54, 2063–2068[19] Page, K.M. and Nowak, M.A. (2002) Unifying Evolutionary Dynamics. Journal of TheoreticalBiology 219, 93–98[20] Pásztor, L. et al. (2016) Theory-Based Ecology: A Darwinian Approach. Oxford University Press,Oxford, New York6

Let's Train More Theoretical Ecologists - Here Is Why

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Let's Train More Theoretical Ecologists - Here Is Why

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