arXiv subjects

Pablo A. Marquet

Publications and source records attributed to Pablo A. Marquet.

7 recordsLinked to original sources

arXiv2026

Exploring the conditions for sustainability with open-ended innovation

Can sustained open-ended technological progress preserve natural resources in a finite planet? We address this question on the basis of a stylized model with genuine open-ended technological innovation, where an innovation event corresponds to a random draw of a technology in the space of the parameters that define how it impacts the environment and how it interacts with the population. Technological innovation is endogenous because an innovation may invade if it satisfies constraints which depend on the state of the environment and of the population. We find that open-ended innovation leads either to a sustainable future where global population saturates and the environment is preserved, or to exploding population and a vanishing environment. What drives the transition between these two phases is not the level of environmental impact of technologies, but rather the demographic effects of technologies and labor productivity. Low demographic impact and high labor productivity (as in several western countries today) result in a Schumpeterian dynamics where new "greener" technologies displace older ones, thereby reducing the overall environmental impact. In this scenario, global population saturates to a finite value, imposing strong selective pressure on technological innovation. When technologies contribute significantly to demographic growth and/or labor productivity is low, technological innovation runs unrestrained, population grows unbounded, while the environment collapses. As such, our model captures subtle feedback effects between technological progress, demography and sustainability that rationalize and align with empirical observations of a demographic transition and the environmental Kuznets curve, without deriving it from profit maximization based on individual incentives.

physics.soc-ph↗

arXiv2026

Toward a general theory for the universality and scaling in critical thermal responses in biology

We developed a theory showing that under appropriate normalizations and rescalings, temperature response curves show a remarkably regular behavior and follow a general, universal law. The impressive universality of temperature response curves remained hidden due to various curve-fitting models not well-grounded in first principles. In addition, this framework has the potential to explain the origin of different scaling relationships in thermal performance in biology, from molecules to ecosystems. Here, we summarize the background, principles and assumptions, predictions, implications, and possible extensions of this theory.

q-bio.OT↗

arXiv2025

The Science of Urban Metabolism and Sustainability

Understanding the quantitative patterns behind scientific disciplines is fundamental for informed research policy. While many fields have been studied from this perspective, Urban Science (USc) and its subfields remain underexplored. As organisms, urban systems rely on materials and energy inputs and transformation (i.e. metabolism) to sustain essential dynamics. This concept has been adopted by various disciplines, including architecture and sociology, and by those focused on metabolic processes, such as ecology and industrial ecology. This study addresses the structure and evolution of Urban Metabolism (UM) and Sustainability research, analyzing articles by disciplines, study subjects (e.g., cities, regions), methodologies, and author diversity (nationality and gender). Our review suggests that UM is an emerging field that grew until 2019, primarily addressed by environmental science and ecology. Common methods include Ecological Network Analysis, and Life Cycle Assessment, and Material Flow Analysis, focusing flows over stocks, ecosystem dynamics and evolutionary perspectives of the urban system. Authors are predominantly from China and the USA, and there are less gender gaps compared to general science research. Our analysis identifies relevant challenges that have become evident in the statistical properties of this scientific field and which might be helpful for the design of improved research policies.

physics.soc-ph↗

arXiv2024

Persistence and neutrality in interacting replicator dynamics

We study the large-time behavior of an ensemble of entities obeying replicator-like stochastic dynamics with mean-field interactions as a model for a primordial ecology. We prove the propagation-of-chaos property and establish conditions for the strong persistence of the $N$-replicator system and the existence of invariant distributions for a class of associated McKean-Vlasov dynamics. In particular, our results show that, unlike typical models of neutral ecology, fitness equivalence does not need to be assumed but emerges as a condition for the persistence of the system. Further, neutrality is associated with a unique Dirichlet invariant probability measure. We illustrate our findings with some simple case studies, provide numerical results, and discuss our conclusions in the light of Neutral Theory in ecology.

math.PR↗

arXiv2023

Quantifying Hierarchical Selection

At what level does selective pressure effectively act? When considering the reproductive dynamics of interacting and mutating agents, it has long been debated whether selection is better understood by focusing on the individual or if hierarchical selection emerges as a consequence of joint adaptation. Despite longstanding efforts in theoretical ecology there is still no consensus on this fundamental issue, most likely due to the difficulty in obtaining adequate data spanning sufficient number of generations and the lack of adequate tools to quantify the effect of hierarchical selection. Here we capitalise on recent advances in information-theoretic data analysis to advance this state of affairs by investigating the emergence of high-order structures -- such as groups of species -- in the collective dynamics of the Tangled Nature model of evolutionary ecology. Our results show that evolutionary dynamics can lead to clusters of species that act as a selective group, that acquire information-theoretic agency. Overall, our findings provide quantitative evidence supporting the relevance of high-order structures in evolutionary ecology, which can emerge even from relatively simple processes of adaptation and selection.

q-bio.PE↗

arXiv2016

Humans: the hyper-dense species

Humans, like all organisms, are subject to fundamental biophysical laws. Van Valen predicted that, because of zero-sum dynamics, all populations of all species in a given environment flux the same amount of energy on average. Damuth's 'energetic equivalence rule' supported Van Valen's conjecture by showing a trade off between few big animals per area with high individual metabolic rates compared to abundant small species with low energy requirements. We use established metabolic scaling theory to compare variation in densities and individual energy use in human societies to other land mammals. We show that hunter-gatherers occurred at lower densities than a mammal of our size. Most modern humans, in contrast, concentrate in large cities at densities that are up to four orders of magnitude greater than hunter-gatherers yet cities consume up to two orders of magnitude greater energy per capita. Today, cities across the globe flux greater energy than net primary productivity on a per area basis. This is possible through enormous fluxes of energy and materials across urban boundaries to sustain hyper-dense, modern humans. The metabolic rift with nature created by hyper-dense cities supported by fossil fuel energy poses formidable challenges for establishing a sustainable relationship on a rapidly urbanizing, yet finite planet.

q-bio.PE↗

arXiv2004

Stationary States of a Random Copying Mechanism over a Complex Networks

An analytical approach to network dynamics is used to show that when agents copy their state randomly the network arrives to a stationary status in which the distribution of states is independent of the agents degree. The effects of network topology on the process are characterized introducing a quantity called influence and studying its behavior for scale-free and random networks. We show that for this model degree averaged means are constant in time regardless of the number of states involved.

cond-mat.dis-nn↗