Complexity Science and Evolution Unit (Ulf Dieckmann)

FY2021 Annual Report

Complexity Science and Evolution Unit
Professor Ulf Dieckmann

How the unit combines complexity science, socio-economics, game theory, physics, mathematics, computer science, ecology, evolution, nonlinear feedbacks, nonequilibrium dynamics, multiple scales, emergent phenomena, tipping points, systemic risks

Abstract

Systems governing human wellbeing and ecosystem services are complex, involving nonlinear feedbacks, nonequilibrium dynamics, multiple scales, emergent phenomena, tipping points, and systemic risks. The structure and function of such complex systems are driven by self-organization and adaptation, with complexity science describing how self-organization shapes the interaction structure among system agents and evolutionary theory describing how adaptation shapes the adaptable characteristics of system agents. While social and biological forms of adaptation operate through fundamentally different mechanisms – social learning of memes and biological inheritance of genes –, their mathematical descriptions have in common essential features rooted in replicator dynamics. Taken together, complexity science and evolution provide the most powerful toolbox we have available for understanding and managing the challenges posed by complexity in social and biological systems.

The Complexity Science and Evolution Unit analyzes the dynamics of complex adaptive systems. Since this necessitates a pluralistic spectrum of approaches, methods are selected, combined, and developed as problems require, drawing on complexity science, evolution, socio-economics, ecology, game theory, theoretical physics, applied mathematics, and computer science. Key questions addressed include how to promote prosocial behavior, how to understand and manage biodiversity formation and loss, and how to utilize living resources sustainably. The unit’s specific research areas are outlined below.

Social dilemmas and governance of common goods. Social dilemmas are posing pervasive challenges to the functioning of societies, occurring whenever goods important for collective wellbeing are under the threat of selfish actors. Overcoming such dilemmas requires promoting cooperative action through governance solutions based on diverse mechanisms such as positive and negative incentives, appropriate rules and regulations, conditional cooperation and participation, as well as competition and movement among social groups. Building on and combining these mechanisms, we explore how to design governance solutions that are effective and efficient.

Biodiversity dynamics and speciation. Even though biodiversity has become recognized as a key determinant of ecosystem services, biodiversity dynamics are only partially understood. In the ongoing quest to comprehend how species form, mounting attention is being devoted to parapatric speciation (advancing despite incipient species not being geographically isolated), ecological speciation (driven by selection pressures originating from biotic interactions), and adaptive speciation (occurring when evolving populations escape from being trapped at a fitness minimum). We investigate how ecological and evolutionary forces drive biodiversity formation and loss.

Sustainable fisheries management and fishing-induced evolution. Once believed to be virtually inexhaustible, living aquatic resources have become overexploited. Promoting sustainable fisheries from an ecological perspective requires understanding the complex adaptive systems involving biotic resources and their environments, ecosystem services, management interventions and their political determinants, and the socio-economic interplay of fishers, consumers, and market forces. Promoting sustainable fisheries from an evolutionary perspective requires recognizing how fishing imposes changes not only on the numbers of fish but also on their functional traits. We analyze fishing from both angles.

Systemic risk and network dynamics. Systemic risk describes the likelihood of cascading failures in networks and occurs in a wide range of domains including disease dynamics, ecosystems, financial networks, supply chains, power grids, and transportation networks. A typical example is the spread of contagious diseases percolating across social contact networks: even when health systems are well geared to treating individual infections, they can be overwhelmed by infection cascades spiraling out of control. Across domains, we study how to assess, model, predict, and mitigate such dynamics.

Evolutionary community ecology and eco-evolutionary vegetation dynamics. The structure and function of all ecosystems have been shaped by evolution. Evolutionary community models based on functional traits explain how ecological settings determine, in turn, biotic environments, selection pressures, coevolutionary dynamics, and thus, changes to the ecological settings. We apply this approach to diverse ecosystems including food webs and to vegetation dynamics in particular, where it enables us to predict from first principles how the compositions of plant biomes around the globe follow from regional environmental conditions.

Adaptive dynamics theory and models. Adaptive dynamics theory describes the evolutionary and coevolutionary dynamics of phenotypic traits driven by natural selection in realistic social and ecological settings. Moving beyond classical evolutionary frameworks postulating fitness functions, adaptive dynamics theory stands out by deriving them from the underlying population dynamics. Having contributed to the foundations and applications of adaptive dynamics theory since its inception, we develop innovative theory and models on topics including species packing, function-valued evolution, evolutionary bifurcations, environmental-feedback dimension, and evolution of pattern formation.

Simplifying spatial complexity. Spatial structures are ubiquitous in nature, and neither ecological nor evolutionary dynamics can be accurately understood without accounting for them. Nowadays, this is often accomplished by brute-force numerical simulations, while corresponding analytical methods have fallen behind needs. New avenues for overcoming this shortcoming and simplifying spatial complexity are opened up by realizing that classical models of well-mixed populations are special cases in a broader theoretical framework that uses as state variables the spatial densities of singlets, pairs, triplets, etc. of individuals. We research how truncating such moment hierarchies at the triplet level yields powerful approximations.

Disease ecology and evolution. Humans, animals, and plants live under the constant threat of contracting contagious diseases. Pathogens frequently jump between species and incessantly adapt their functional traits, facilitating the transmission of variant pathogens. This is creating moving targets for individual and collective efforts at disease protection, as evidenced by the ongoing Covid-19 pandemic. The success of public health interventions thus crucially depends on accurately forecasting not only pathogen spread but also pathogen evolution. Strengthening the young field of evolutionary epidemiology, we devise new methods for predicting changes in the virulence of pathogens and the resistance of their hosts.

1. Staff

Prof. Ulf Dieckmann, Professor
Dr. Chulwook Park, Visiting Researcher
Mayu Suzuki, Research Unit Administrator

2. Collaborations

The CSE unit is conducting joint research together with a large range of national and international experts on the following topics and involving the following collaborators in FY2021.

2.1 Alternative pathways of fishery collapse

Professor Cang Hui, University of Stellenbosch, South Africa
Professor Pietro Landi, University of Stellenbosch, South Africa

2.2 Analyses of moment-based spatial dynamics

Mr. Yegor Galkin, Lomonosov Moscow State University, Russia
Professor Alexey Nikitin, Lomonosov Moscow State University, Russia
Mr. Mikhail Nikolaev, Lomonosov Moscow State University, Russia

2.3 Climate vulnerability of Arctic whitefish

Professor Raul Primicerio, The Arctic University of Norway, Norway
Dr. Aslak Smalås, The Arctic University of Norway, Norway

2.4 Community assembly under mutualism and competition

Professor Cang Hui, University of Stellenbosch, South Africa
Dr. Ony Minoarivelo, University of Cape Town, South Africa

2.5 Ecological and evolutionary food-web responses to size-selective harvesting

Professor Åke Brännström, Umeå University, Sweden
Professor Nicolas Loeuille, Sorbonne University, France

2.6 Emergence of Cope’s rule through eco-evolutionary community dynamics

Professor Åke Brännström, Umeå University, Sweden
Professor Shovonlal Roy, University of Reading, United Kingdom

2.7 Empirical assessment of fisheries-induced selection pressures

Dr. Asbjørn Christensen, Technical University of Denmark, Denmark
Dr. Bruno Ernande, National Institute for Ocean Science (Ifremer), France
Professor Mikko Heino, University of Bergen, Norway
Professor Ane Laugen, University of Agder, Norway
Professor Shuichi Matsumura, Gifu University, Japan
Professor Raul Primicerio, The Arctic University of Norway, Norway
Dr. Aslak Smalås, The Arctic University of Norway, Norway

2.8 Evolution of flowering schedules

Professor Mikko Heino, University of Bergen, Norway
Professor Kalle Parvinen, University of Turku, Finland

2.9 Evolution of sexual dimorphism in North Sea plaice

Professor David Boukal, Institute of Entomology – Biology Centre CAS, Czech Republic
Professor Katja Enberg, University of Bergen, Norway
Dr. Fabian Mollet, Blueyou Consulting Ltd., Switzerland
Professor Adriaan Rijnsdorp, Wageningen University & Research, The Netherlands

2.10 Evolutionary cycling of cooperation and participation

Professor Åke Brännström, Umeå University, Sweden
Dr. Rupert Mazzucco, University of Veterinary Medicine, Austria
Dr. Henrik Sjödin, Umeå University, Sweden

2.11 Evolutionary rescue along environmental gradients

Professor Åke Brännström, Umeå University, Sweden
Professor David Vasseur, Yale University, United States
Dr. Anna Vinton, University of Oxford, United Kingdom

2.12 Evolutionary trapping under frequency-dependent selection

Professor Cang Hui, University of Stellenbosch, South Africa
Professor Hans (J.A.J.) Metz, Leiden University, The Netherlands
Professor Feng Zhang, Anhui University, China

2.13 Fisheries-induced evolution (book project)

Dr. Olav Rune Godø, University of Bergen, Norway
Professor Mikko Heino, University of Bergen, Norway

2.14 Fishing-induced and climate-induced life-history evolution in walleye

Professor Mikko Heino, University of Bergen, Norway
Ms. Lyndsie Wszola, University of Nebraska–Lincoln, United States

2.15 Frugivory and fruit harvesting in spatially structured plant populations

Professor Åke Brännström, Umeå University, Sweden
Professor Pietro Landi, University of Stellenbosch, South Africa
Mr. Mozzamil Mohammed, Carl von Ossietzky University of Oldenburg, Germany

2.16 Determinants of invasion success in complex ecological communities

Professor Åke Brännström, Umeå University, Sweden
Dr. Rupert Mazzucco, University of Veterinary Medicine, Austria
Dr. Daisuke Takahashi, AI System Research Inc., Kyoto, Japan

2.17 Determinants of species packing

Professor Akira Sasaki, The Graduate University for Advanced Studies (SOKENDAI), Japan

2.18 Harvest-induced maturation adaptations under competition

Professor Åke Brännström, Umeå University, Sweden
Professor Mats Bodin, Umeå University, Sweden
Professor Anna Gårdmark , Swedish University of Agricultural Sciences, Sweden

2.19 Incorporating fairness perspectives into integrated assessment models

Professor Åke Brännström, Umeå University, Sweden
Dr. Oskar Franklin, International Institute for Applied Systems Analysis (IIASA), Austria
Dr. Elena Rovenskaya, International Institute for Applied Systems Analysis (IIASA), Austria
Dr. Piotr Żebrowski, International Institute for Applied Systems Analysis (IIASA), Austria

2.20 Informing transformative change by analyses of systemic risk

Dr. Stefan Hochrainer-Stigler, International Institute for Applied Systems Analysis (IIASA), Austria
Dr. Reinhard Mechler, International Institute for Applied Systems Analysis (IIASA), Austria

2.21 Life-history dynamics of cutlassfish

Professor Mikko Heino, University of Bergen, Norway
Professor Hideyasu Shimadzu, Loughborough University, United Kingdom
Professor Hui-Yu Wang, National Taiwan University, Taiwan

2.22 Management of Japanese seabass under climate change

Professor Åke Brännström, Umeå University, Sweden
Dr. Taiki Fuji, Tohoku National Fisheries Research Institute – Japan Fisheries Research and Education Agency, Japan
Professor Mikko Heino, University of Bergen, Norway
Professor Aki Kasai, Hokkaido University, Japan

2.23 Multi-objective, multi-stakeholder, integrative fisheries management

Professor Dorothy Dankel, University of Bergen, Norway
Professor Mikko Heino, University of Bergen, Norway

2.24 Nonparametric estimation of probabilistic maturation reaction norms

Dr. Asbjørn Christensen, Technical University of Denmark, Denmark
Dr. Bruno Ernande, National Institute for Ocean Science (Ifremer), France
Professor Ane Laugen, University of Agder, Norway
Professor Mikko Heino, University of Bergen, Norway
Professor Shuichi Matsumura, Gifu University, Japan
Professor Raul Primicerio, The Arctic University of Norway, Norway
Dr. Aslak Smalås, The Arctic University of Norway, Norway

2.25 Perspectives on speciation (book project)

Professor Daniel Bolnick, University of Connecticut, United States
Professor Åke Brännström, Umeå University, Sweden
Professor Catherine Peichel, University of Bern, Switzerland
Professor Rebecca Safran, University of Colorado Boulder, United States

2.26 Predicting plant photosynthesis and hydraulics by eco-evolutionary optimization

Dr. Jaideep Joshi, International Institute for Applied Systems Analysis (IIASA), Austria
Professor Colin Prentice, Imperial College London, United Kingdom

2.27 Quantifying the dimension of environmental feedback

Professor Hans (J.A.J.) Metz, Leiden University, The Netherlands
Professor Kalle Parvinen, University of Turku, Finland

2.28 Recurrent outbreaks of cooperation in public good games

Professor Åke Brännström, Umeå University, Sweden
Dr. Sedigheh Yagoobi, Max Planck Institute for Evolutionary Biology, Germany

2.29 Resilience of plant-pollinator networks to multiple anthropogenic threats

Professor Åke Brännström, Umeå University, Sweden
Dr. Rupert Mazzucco, University of Veterinary Medicine, Austria
Dr. Vera Pfeiffer, University of Wisconsin–Madison, United States

2.30 Responses of seasonal reproduction to climate-change

Professor Kalle Parvinen, University of Turku, Finland
Professor Easton White, University of New Hampshire, United States

2.31 Safe operating spaces in fisheries management under climate change

Professor Mikko Heino, University of Bergen, Norway
Dr. Jaideep Joshi, International Institute for Applied Systems Analysis (IIASA), Austria
Dr. Anna Shchiptsova, International Institute for Applied Systems Analysis (IIASA), Austria

2.32 Sequential collapses in metapopulations of living resources

Professor Shuichi Matsumura, Gifu University, Japan

2.33 Social evolution of protection heuristics against systemic risk

Dr. Chulwook Park, Seoul National University, Republic of Korea

2.34 Socio-economic development of China’s fishery population

Professor Mikko Heino, University of Bergen, Norway
Dr. Yi Huang, Xiamen University, China

2.35 Spatial and evolutionary responses of vegetation patterns to desertification

Dr. Jamie Bennett, Ben-Gurion University of the Negev, Israel
Dr. Bidesh Kumar Bera, Ben-Gurion University of the Negev, Israel
Professor Ehud Meron, Ben-Gurion University of the Negev, Israel
Dr. Omer Tsuk, Tel Aviv University, Israel

2.36 Tipping points and safe operating spaces in ocean management under climate change (grant)

Professor Thorsten Blenckner, Stockholm University, Sweden
Dr. Marion Gehlen, Laboratory for Sciences of Climate and Environment, France
Professor Christoph Heinze, University of Bergen, Norway
Dr. Tsuyoshi Wakamatsu, Nansen Environmental and Remote Sensing Center, Norway

2.37 Tipping points in fisheries management under climate change

Dr. Jaideep Joshi, International Institute for Applied Systems Analysis (IIASA), Austria
Professor Mikko Heino, University of Bergen, Norway
Dr. Anna Shchiptsova, International Institute for Applied Systems Analysis (IIASA), Austria

2.38 Virulence evolution in metapopulations

Professor Akira Sasaki, The Graduate University for Advanced Studies (SOKENDAI), Japan
Dr. Masato Sato, University of Tokyo, Japan

2.39 Vulnerability of food webs to anthropogenic disturbances

Professor Åke Brännström, Umeå University, Sweden
Professor Mateusz Iskrzyński, Systems Research Institute of the Polish Academy of Sciences, Poland
Professor Karol Opara, Systems Research Institute of the Polish Academy of Sciences, Poland
Dr. Elena Rovenskaya, International Institute for Applied Systems Analysis (IIASA), Austria
Professor Ursula Scharler, University of KwaZulu-Natal, South Africa

3. Activities and Findings

The following OIST publications have been published by CSE staff in FY2021.

3.1 An evolutionary explanation of female-biased sexual size dimorphism in North Sea plaice, Pleuronectes platessa L.

Sexual size dimorphism (SSD) is caused by differences in selection pressures and life-history tradeoffs faced by males and females. Proximate causes of SSD may involve sex-specific mortality, energy acqui-sition, and energy expenditure for maintenance, reproductive tissues, and reproductive behavior. Using a quantitative, individual-based, eco-genetic model parameterized for North Sea plaice, we explore the importance of these mechanisms for female-biased SSD, under which males are smaller and reach sexual maturity earlier than females (common among fish, but also arising in arthropods and mammals). We consider two mechanisms potentially serving as ultimate causes: (1) male investments into male repro-ductive behavior might detract energy resources that would otherwise be available for somatic growth, and (2) diminishing returns on male reproductive investments might lead to reduced energy acquisition. In general, both of these can bring about smaller male body sizes. We report the following findings. First, higher investments into male reproductive behavior alone cannot explain the North Sea plaice SSD. This is because such higher reproductive investments require increased energy acquisition, which would cause a delay in maturation, leading to male-biased SSD contrary to observations. When account-ing for the observed differential (lower) male mortality, maturation is postponed even further, leading to even larger males. Second, diminishing returns on male reproductive investments alone can qualitative-ly account for the North Sea plaice SSD, even though the quantitative match is imperfect. Third, both mechanisms can be reconciled with, and thus provide a mechanistic basis for, the previously advanced Ghiselin-Reiss hypothesis, according to which smaller males will evolve if their reproductive success is dominated by scramble competition for fertilizing females, as males would consequently invest more into reproduction than growth, potentially implying lower survival rates relaxing male-male competition. Fourth, a good quantitative fit is achieved by combining both mechanisms while accounting for costs males incur during spawning

3.2 Application of special function spaces to the study of nonlinear integral equations arising in equilibrium spatial logistic dynamics

In this paper, we study a nonlinear integral equation that arises in a model of spatial logistic dynamics. The solvability of this equation is investigated by introducing special spaces of functions that are integrable up to a constant. Sufficient conditions for the biological characteristics and the parameters of the third spatial moment closure are established that guarantee the existence of the solution of the equation described above in some ball centered at zero. In addition, it is shown that this solution is unique in the considered ball and not zero. This means that, under appropriate conditions, the equilibrium state of the population of a certain species exists and does not coincide with the state of extinction.

3.3 Sharing the burdens of climate mitigation and adaptation: Incorporating fairness perspectives into policy optimization models

Mitigation of, and adaptation to, climate change can be addressed only through the collective action of multiple agents. The engagement of involved agents critically depends on their perception that the burdens and benefits of collective action are distributed fairly. Integrated Assessment Models (IAMs), which inform climate policies, focus on the minimization of costs and the maximization of overall utility, but they rarely pay sufficient attention to how costs and benefits are distributed among agents. Consequently, some agents may perceive the resultant model-based policy recommendations as unfair. In this paper, we propose how to adjust the objectives optimized within IAMs so as to derive policy recommendations that can plausibly be presented to agents as fair. We review approaches to aggregating the utilities of multiple agents into fairness-relevant social rankings of outcomes, analyze features of these rankings, and associate with them collections of properties that a model’s objective function must have to operationalize each of these rankings within the model. Moreover, for each considered ranking, we propose a selection of specific objective functions that can conveniently be used for generating this ranking in a model. Maximizing these objective functions within existing IAMs allows exploring and identifying climate polices to which multiple agents may be willing to commit.

4. Publications

4.1 Journals

Mollet F., Enberg K., Boukal D., Rijnsdorp A., and Dieckmann U. "An evolutionary explanation of female-biased sexual size dimorphism in North Sea plaice, Pleuronectes platessa L.". Ecology and Evolution, in press (2022).
Nikolaev M. V., Dieckmann U., and Nikitin A. A. "Application of special function spaces to the study of nonlinear integral equations arising in equilibrium spatial logistic dynamics". Doklady Mathematics, 104: 188–192, https://doi.org/10.1134/S1064562421040128 (2021).
Żebrowski P., Dieckmann U., Brännström Å., Franklin O., and Rovenskaya E. "Sharing the burdens of climate mitigation and adaptation: Incorporating fairness perspectives into policy optimization models". Sustainability, 14(7): 3737, https://doi.org/10.3390/su14073737 (2011).