141 research outputs found
Sustainability, collapse and oscillations in a simple World-Earth model
No full textThe Anthropocene is characterized by close interdependencies between the natural Earth system and the global human society, posing novel challenges to model development. Here we present a conceptual model describing the long-term co-evolution of natural and socio-economic subsystems of Earth. While the climate is represented via a global carbon cycle, we use economic concepts to model socio-metabolic flows of biomass and fossil fuels between nature and society. A well-being-dependent parametrization of fertility and mortality governs human population dynamics. Our analysis focuses on assessing possible asymptotic states of the Earth system for a qualitative understanding of its complex dynamics rather than quantitative predictions. Low dimension and simple equations enable a parameter-space analysis allowing us to identify preconditions of several asymptotic states and hence fates of humanity and planet. These include a sustainable co-evolution of nature and society, a global collapse and everlasting oscillations. We consider different scenarios corresponding to different socio-cultural stages of human history. The necessity of accounting for the ‘human factor’ in Earth system models is highlighted by the finding that carbon stocks during the past centuries evolved opposing to what would ‘naturally’ be expected on a planet without humans. The intensity of biomass use and the contribution of ecosystem services to human well-being are found to be crucial determinants of the asymptotic state in a (pre-industrial) biomass-only scenario without capital accumulation. The capitalistic, fossil-based scenario reveals that trajectories with fundamentally different asymptotic states might still be almost indistinguishable during even a centuries-long transient phase. Given current human population levels, our study also supports the claim that besides reducing the global demand for energy, only the extensive use of renewable energies may pave the way into a sustainable future.Open-Access-Publikationsfonds 201
Deep reinforcement learning in World-Earth system models to discover sustainable management strategies
No full textIncreasingly complex nonlinear World-Earth system models are used for describing the dynamics of the biophysical Earth system and the socioeconomic and sociocultural World of human societies and their interactions. Identifying pathways toward a sustainable future in these models for informing policymakers and the wider public, e.g., pathways leading to robust mitigation of dangerous anthropogenic climate change, is a challenging and widely investigated task in the field of climate research and broader Earth system science. This problem is particularly difficult when constraints on avoiding transgressions of planetary boundaries and social foundations need to be taken into account. In this work, we propose to combine recently developed machine learning techniques, namely, deep reinforcement learning (DRL), with classical analysis of trajectories in the World-Earth system. Based on the concept of the agent-environment interface, we develop an agent that is generally able to act and learn in variable manageable environment models of the Earth system. We demonstrate the potential of our framework by applying DRL algorithms to two stylized World-Earth system models. Conceptually, we explore thereby the feasibility of finding novel global governance policies leading into a safe and just operating space constrained by certain planetary and socioeconomic boundaries. The artificially intelligent agent learns that the timing of a specific mix of taxing carbon emissions and subsidies on renewables is of crucial relevance for finding World-Earth system trajectories that are sustainable in the long term
Every finite system of T1 uniformities comes from a single distance structure
Full text linkUsing the general notion of distance function introduced in an earlier paper, a construction of the finest distance structure which induces a given quasi-uniformity is given. Moreover, when the usual defining condition xy : d(y; x) of the basic entourages is generalized to nd(y; x) n (for a fixed positive integer n), it turns out that if the value-monoid of the distance function is commutative, one gets a countably infinite family of quasi-uniformities on the underlying set. It is then shown that at least every finite system and every descending sequence of T1 quasi-uniformities which fulfil a weak symmetry condition is included in such a family. This is only possible since, in contrast to real metric spaces, the distance function need not be symmetric
An integrative quantifier of multistability in complex systems based on ecological resilience
Full text linkAcknowledgements This work was supported by the German Federal Ministry of Education and Research (BMBF) via the Young Investigators Group CoSy-CC2 (grant no. 01LN1306A). C.M. acknowledges the support of Bedartha Goswami, Jobst Heitzig and Tim Kittel.Peer reviewe
From lakes and glades to viability algorithms: automatic classification of system states according to the topology of sustainable management
No full textThe framework Topology of Sustainable Management by Heitzig et al. (Earth Syst Dyn 7:21. https://doi.org/10.5194/esd-7-21-201
Bottom-up strategic linking of carbon markets: Which climate coalitions would farsighted players form?
No full textBottom-up strategic linking of carbon markets: Which climate coalitions would farsighted players form? / Jobst Heitzig. FEEM, 2013, 41 p. (Nota di lavoro ; 2013.048) http://www.feem.it/getpage.aspx?id=5558&sez=Publications&padre=73 Abstract : We present typical scenarios and general insights from a novel dynamic model of farsighted climate coalition formation involving market linkage and cap coordination, using a simple analytical model of the underlying cost-benefit structure. In our model,..
Bottom-Up Strategic Linking of Carbon Markets: Which Climate Coalitions Would Farsighted Players Form?
No full textWe present typical scenarios and general insights from a novel dynamic model of farsighted climate coalition formation involving market linkage and cap coordination, using a simple analytical model of the underlying cost-benefit structure. In our model, the six major emitters of CO2 can link domestic cap-and-trade systems to form one or several international carbon markets, and can either choose their emissions caps non-cooperatively or form a hierarchy of cap-coordinating coalitions inside each market. Based on individual and collective rationality and an assumed distribution of bargaining power, we derive scenarios of such a climate coalition formation process which show that a first-best state with a coordinated global carbon market might well emerge bottom-up, and underline the importance of coordinating caps immediately when linking carbon markets. Surprisingly, the process tends to involve less uncertainty when agreements can be terminated unanimously or unilaterally, depending on the level of farsightedness
Probability-Based Estimation
Full text linkWe develop a theory of estimation when in addition to a sample of
observed outcomes the underlying probabilities of the observed outcomes are
known, as is typically the case in the context of numerical simulation
modeling, e.g. in epidemiology. For this enriched information framework, we
design unbiased and consistent ``probability-based'' estimators whose variance
vanish exponentially fast as , as compared to the power-law decline
of classical estimators' variance.Comment: 5 page
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