MS07 - ECOP-06

Coupled human and natural systems

Thursday, July 17 at 3:50pm

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Frank M. Hilker (Osnabrück University), Rebecca C. Tyson (University of British Columbia Okanagan)

Description:

Coupled human and natural systems (CHANS) model human and environmental systems as coupled, rather than independent. The feedback between the two is crucial, as humans are a key factor impacting ecological and environmental systems, e.g., through exploitation of natural resources, pollution, habitat deterioration, or greenhouse gas emissions. It is therefore imperative to gain a better understanding how human behavior affects the natural systems – and vice versa. Traditionally, many environmental models tend to oversimplify human systems, often in the form of parameters. Similarly, social science research tends to ignore the complexity of ecosystem dynamics. Considering in this interaction the key characteristics of both human and environmental systems is fundamental to maintaining ecosystems in a desirable state. A failure to do so can result in environmental mismanagement. This minisymposium features selected presentations that analyze the complex interactions in CHANS with novel mathematical models that highlight the significance of understanding the coupling and that address challenges arising from reciprocal effects, heterogeneities, uncertainties, and nonlinearities. The minisymposium begins with an overview of a mathematical framework. It then covers socio-climate systems and evolutionary harvesting dynamics motivated from fisheries. Last but not least, a “perspectives talk” on the mathematics of rewilding will illustrate the opportunities in this research area.

Brian Beckage

University of Vermont

"Why We Do What We Do: A Mathematical Framework for Modeling Human Behavior in Coupled Human-Environmental Systems"

Many 'wicked' problems superficially appear to be problems in management of environmental systems but are actually problems in the interactions of human social and behavioral systems (HSBs) with biophysical systems. Prominent examples include climate change, loss of biodiversity, emerging diseases, or any number of the planetary boundaries that the Earth system is being pushed beyond. The models used to address these wicked problems have traditionally paid minimal attention to the social and behavioral system using static scenarios or low dimensional representations of the human system while expending great effort to represent the biophysical system in great detail. The focus on the biophysical system stems in part from the fundamental limitation in how to represent the human behavioral and social system in mathematical and computational models. There are a large number of diverse theories proposed to understand various aspects of human behavior but few of these have been translated into mathematical or algorithmic representations. We present a framework that represents a minimal set of processes for constructing computational models of human behavioral systems. This framework, based on key processes of contagion and cognition within a cultural context, enables more realistic modeling of human-environment interactions and could improve our ability to address critical environmental challenges.

Jonas Wahl

Osnabrück University, Germany

"Evolutionary dynamics of constant and proportional harvest strategies in a coupled human-environment system with dynamic resources"

Two of the classical harvesting strategies considered in ecological modelling are constant and proportional harvesting. They show different characteristics in their impact on a harvested resource or population. While these strategies and their consequences are well-documented on their own and fully analyzed in isolation, this talk will put the strategies in a competition within one joint model: each of the two strategies is represented by the fraction of harvesters applying it to an underlying logistically growing resource, and the fractions dynamically change according to the replicator equation from evolutionary game theory, which is set up based on the economic payoff of the strategies. This is done for a model with a fixed number of harvesters and a model with a dynamic number of harvesters. The talk will present an analysis of the models' equilibria and their stability leading to a bifurcation analysis, which is then used to derive the economical and ecological implications of the models as well as to interpret the results of the competition of the harvesting strategies with an additional focus on the management of such a system, especially regarding the regulation of access to the resource.

Amrita Punnavajhala

University of Waterloo

"Region-level mitigation in a coupled social-climate model"

Mathematical models of climate change have traditionally described anthropogenic carbon emissions as functions of evolving socio-economic scenarios. A drawback of this approach is that the underlying dynamics of human behaviour that are, ultimately, responsible for the carbon emissions causing contemporary climate change, are ignored. So far, there exist a handful of `social-climate’ models that address this shortcoming, results from which make a compelling case for the inclusion of social and behavioural processes in models of climate change. We have constructed and analyzed a coupled social-climate model with region-level structure, parameterized by data on costs of renewables, vulnerability to climate change and the strength of social norms, combined with socio-economic data. Our results show that social learning rates have an outsized effect on mitigation across all regions, mitigation progresses spreads faster in regions more vulnerable to climate change impacts and that interventions to increase mitigation are more effective when introduced early and universally. While increasing the social learning rate always reduces the magnitude of the peak temperature, the time at which this peak occurs can be move forward or backward, depending on which region the increase is implemented in.

Christina A. Cobbold

University of Glasgow

"Mathematics for Rewilding: opportunities and challenges"

Achieving a sustainable coexistence of humans with well-functioning ecological systems providing key essential ecosystem services is now vitally important under global change. Rewilding is an increasingly popular approach which provides a paradigm shift to return degraded ecosystems to a state regulated by natural processes, by using and recovering ecological processes, interactions and conditions. Crucially, rewilding occurs in complex systems over large spatio-temporal scales, under high uncertainty. Predicting such ecological changes also requires integration with socio-economic dimensions and thinking. We evaluate the current state of the quantitative treatment of rewilding, highlighting significant deficiencies and opportunities for harnessing mathematics for rewilding. We present an emerging quantitative framework, encompassing four key areas across the entire cycle of rewilding projects - design and planning, metrics for assessment, ecological modelling, and coupled human-ecological systems, informed by recent progress in multiple areas of mathematics and ecological modelling.

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Annual Meeting for the Society for Mathematical Biology, 2025.