Biology subjects

Marquet, P. A.

Publications and source records attributed to Marquet, P. A..

5 recordsLinked to original sources

bioRxiv2025

A general allometric rule predicts sustainable growth across societies

Balancing population growth against finite resources remains a foundational challenge in sustainability science. Although qualitative sustainability principles have matured over decades, translating these principles into universal quantitative rules has been challenging due to the diverse environmental and cultural contexts under which human societies develop. Here, we demonstrate that a general sustainability rule emerges naturally when population-resource feedbacks follow empirically observed allometric scaling laws, condensing ecological, technological, and social complexities into four fundamental parameters. This rule predicts "sustainability corridors" within which societies must remain to ensure long-term persistence. Testing our theoretically derived rule against ethnographic data from 299 hunter-gatherer societies across varied ecological and social environments, we find consistent alignment: these societies tend to occupy the predicted corridors despite substantial contextual differences. By grounding sustainability in biophysical scaling rather than context-specific variables, our approach bridges ecology and sustainability science, suggesting that despite cultural and technological differences, all societies face fundamental constraints for sustainable growth.

ecology↗

bioRxiv2020

Alteration of coastal productivity and artisanal fisheries interact to affect a marine food-web

Top-down and bottom-up forces determine ecosystem function and dynamics. Fisheries as a top-down force can shorten and destabilize food-webs, while climate-change driven effects can alter the bottom-up forces of primary productivity. We assessed the response of a highly-resolved intertidal food-web to these two global-change drivers, using network analysis and bioenergetic modelling. We quantified the relative importance of artisanal fisheries as another predator species, and evaluated the independent and combined effects of fisheries and plankton-productivity changes on food-web dynamics. The food-web was robust to the loss of all harvested species but sensible to plankton-productivity decline. Interestingly, fisheries dampened the negative impacts of decreasing plankton productivity on non-harvested species, while plankton-productivity decline increased the sensitivity of harvested species to fishing. Our results show that strategies for new scenarios caused by climate change are needed to protect marine ecosystems and the wellbeing of local communities dependent on their resources.

ecology↗

bioRxiv2020

NetworkExtinction: an R package to explore the propagation of extinctions through complex ecological networks

O_LIEarths biosphere is currently undergoing drastic reorganisation as a consequence of the sixth mass extinction brought on by the Anthropocene. Impacts of local and regional extirpation of species have been demonstrated to propagate through the complex interaction networks they are part of, subsequently leading to secondary extinctions, exacerbating biodiversity loss. Contemporary ecological theory has developed several measures to analyse the structure and robustness of ecological networks under biodiversity loss. However, a toolbox for direct simulation and quantification of extinction cascades and the creation of novel interactions (i.e. rewiring) remains absent. C_LIO_LIHere, we present NetworkExtinction - a novel R package which we have developed to explore the propagation of species extinctions sequences through ecological networks as well as quantify the effects of rewiring potential in response to primary species extinctions. With NetworkExtinction we have integrated ecological theory and computational simulations to develop functionality with which users may analyze and visualize the structure and robustness of ecological networks. The core functions introduced with NetworkExtinction focus on simulations of sequential primary extinctions and associated secondary extinctions while allowing for user-specified secondary extinction thresholds and realisation of rewiring potential. C_LIO_LIWith the package NetworkExtinction, users can estimate the robustness of ecological networks after performing species extinction routines based on several algorithms. Moreover, users can compare the number of simulated secondary extinctions against a null model of random extinctions. In-built visualizations enable graphing topological indices calculated by the deletion sequence functions after each simulation step. Finally, the user can define the degree distribution of the network by fitting different common distributions. Here, we illustrate the use of the package and its outputs by analyzing a Chilean coastal marine food web. C_LIO_LINetworkExtinction is a compact and easy-to-use R package with which users can quantify changes in ecological network structure in response to different patterns of species loss, thresholds, and rewiring potential. Therefore, this package is particularly useful to evaluate ecosystem responses to anthropogenic and environmental perturbations that produce non-random species extinctions. C_LI

ecology↗

bioRxiv2017

The network structure of cancer ecosystems

Ever since Pagets seed-and-soil and Ewings connectivity hypotheses to explain tumor metastasis (1,2), it has become clear that cancer progression can be envisaged as an ecological phenomenon. This connection has flourished during the past two decades (3-7), giving rise to important insights into the ecology and evolution of cancer progression, with therapeutic implications (8-10). Here, we take a metapopulation view of metastasis (i.e. the migration to and colonization of, habitat patches) and represent it as a bipartite network, distinguishing source patches, or organs that host a primary tumor, and acceptor patches, or organs colonized ultimately from the source through metastasis. Using 20,326, biomedical records obtained from literature, we show that: (i) the network structure of cancer ecosystems is non-random, exhibiting a nested subset pattern as has been found both in the distribution of species across islands and island-like habitats (11-13), and in the distribution of among species interactions across different ecological networks (14-16); (ii) similar to ecological networks, there is a heterogeneous distribution of degree (i.e., number of connections associated with a source or acceptor organ); (iii) there is a significant correlation between metastatic incidence (or the frequency with which tumor cells from a source organ colonize an acceptor one) and arterial blood supply, suggesting that more irrigated organs have a higher probability of developing metastasis or being invaded; (iv) there is a positive correlation between metastatic incidence and acceptor organ degree (or number of different tumor-bearing source organs that generate metastasis in a given acceptor organ), and a negative one between acceptor organ degree and number of stem cell divisions, implying that there are preferred sink organs for metastasis and that this could be related to average acceptor organ cell longevity; (v) there is a negative association between organ cell turnover and source organ degree, implying that organs with rapid cell turnovers tend to generate more metastasis, a process akin to the phenomenon of propagule pressure in ecology (17); and (vi) the cancer ecosystem network exhibits a modular structure in both source and acceptor patches, suggesting that some of them share more connections among themselves than with the rest of the network. We show that both niche-related processes occurring at the organ level as well as spatial connectivity and propagule pressure contribute to metastaticspread and result in a non-random cancer network, which exhibits a truncated power law degree distribution, clustering and a nested subset structure. The similarity between the cancer network and ecological networks highlights the importance of ecological approaches in increasing our understanding of patterns in cancer incidence and dynamics, which may lead to new strategies to control tumor spread within the human ecosystem.

ecology↗

bioRxiv2017

On the proportional abundance of species: Integrating population genetics and community ecology

The frequency of genes in interconnected populations and of species in interconnected communities are affected by similar processes, such as birth, death and immigration. The equilibrium distribution of gene frequencies in structured populations is known since the 1930s, under Wrights metapopulation model known as the island model. The equivalent distribution for the species frequency (i.e. the species proportional abundance distribution (SPAD), at the metacommunity level, however, is unknown. In this contribution, we develop a stochastic model to analytically account for this distribution (SPAD). We show that the same as for genes SPAD follows a beta distribution, which provides a good description of empirical data and applies across a continuum of scales. This stochastic model, based upon a diffusion approximation, provides an alternative to neutral models for the species abundance distribution (SAD), which focus on number of individuals instead of proportions, and demonstrate that the relative frequency of genes in local populations and of species within communities follow the same probability law. We hope our contribution will help stimulate the mathematical and conceptual integration of theories in genetics and ecology.

ecology↗