arXiv subjects

Paolo D'Odorico

Publications and source records attributed to Paolo D'Odorico.

8 recordsLinked to original sources

arXiv2024

Quantifying Global Food Trade: A Net Caloric Content Approach to Food Trade Network Analysis

As the global population and the per capita demand for resource intensive diets continues to grow, the corresponding increase in food demand challenges the global food system, enhancing its reliance on trade. Most previous research typically constructed either unweighted networks or weighted solely by tonnage to represent food trade, and focused on bilateral trade relationships between pairs of countries. This study investigates the properties of global food trade constructed in terms of total food calories associated with all the main food products exchanged along each trade link (edge of the food trade network). Utilizing data from the Food and Agriculture Organization between 1986 and 2022, we construct a directed, weighted network of net caloric flows between countries. This approach highlights the importance of considering nutritional value in discussions of food security and trade policies, offering a more holistic view of global food trade dynamics. Our analysis reveals significant heterogeneity in trade patterns, with certain countries emerging as major exporters or importers of food calories. Moreover, we employ network measures, including network connectivity, network heterogeneity, network modularity, and node correlation similarity, to elucidate the structural dynamics of global net food calorie trade networks that are relevant to the stability and resilience of the global food system. Our work provides a more nuanced understanding of global food trade dynamics, emphasizing the need for comprehensive strategies to enhance the resilience and sustainability of food trade networks.

econ.GN↗

arXiv2024

The role of the Allee effect in common-pool resource and its sustainability

The management of common-pool resources is a complex challenge due to the risk of overexploitation and the tragedy of the commons. A novel framework has been introduced to address this issue, focusing on the coevolutionary relationship between human behavior and common-pool resources within a human-environment system. However, the impact of the Allee effect on the coevolution and its resource sustainability is still unexplored. The Allee effect, a biological phenomenon characterized by a correlation between resource availability and growth rate, is a fundamental attribute of numerous natural resources. In this paper, we introduce two coevolutionary models of resource and strategy under replicator dynamics and knowledge feedback by applying the Allee effect to the common-pool resources within human-environment system. These models encapsulate various facets of resource dynamics and the players' behavior, such as resource growth function, the extraction rates, and the strategy update rules. We find that the Allee effect can induce bi-stability and critical transition, leading to either sustainable or unsustainable outcomes depending on the initial condition and parameter configuration. We demonstrate that knowledge feedback enhances the resilience and sustainability of the coevolving system, and these results advances the understanding of human-environment system and management of common-pool resources.

econ.TH↗

arXiv2024

Modelling co-evolution of resource feedback and social network dynamics in human-environmental systems

Games with environmental feedback have become a crucial area of study across various scientific domains, modelling the dynamic interplay between human decisions and environmental changes, and highlighting the consequences of our choices on natural resources and biodiversity. In this work, we propose a co-evolutionary model for human-environment systems that incorporates the effects of knowledge feedback and social interaction on the sustainability of common pool resources. The model represents consumers as agents who adjust their resource extraction based on the resource's state. These agents are connected through social networks, where links symbolize either affinity or aversion among them. The interplay between social dynamics and resource dynamics is explored, with the system's evolution analyzed across various network topologies and initial conditions. We find that knowledge feedback can independently sustain common pool resources. However, the impact of social interactions on sustainability is dual-faceted: it can either support or impede sustainability, influenced by the network's connectivity and heterogeneity. A notable finding is the identification of a critical network mean degree, beyond which a depletion/repletion transition parallels an absorbing/active state transition in social dynamics, i.e., individual agents and their connections are/are not prone to being frozen in their social states. Furthermore, the study examines the evolution of the social network, revealing the emergence of two polarized groups where agents within each community have the same affinity. Comparative analyses using Monte-Carlo simulations and rate equations are employed, along with analytical arguments, to reinforce the study's findings. The model successfully captures how information spread and social dynamics may impact the sustanebility of common pool resource.

physics.soc-ph↗

arXiv2022

Snowpack Estimation in Key Mountainous Water Basins from Openly-Available, Multimodal Data Sources

Accurately estimating the snowpack in key mountainous basins is critical for water resource managers to make decisions that impact local and global economies, wildlife, and public policy. Currently, this estimation requires multiple LiDAR-equipped plane flights or in situ measurements, both of which are expensive, sparse, and biased towards accessible regions. In this paper, we demonstrate that fusing spatial and temporal information from multiple, openly-available satellite and weather data sources enables estimation of snowpack in key mountainous regions. Our multisource model outperforms single-source estimation by 5.0 inches RMSE, as well as outperforms sparse in situ measurements by 1.2 inches RMSE.

cs.CV↗

arXiv2014

Early warning signs in social-ecological networks

Social ecological systems are often difficult to investigate and manage because of their inherent complexity1. Small variations in external drivers can lead to abrupt changes associated with instabilities and bifurcations in the underlying dynamics2-4. Anticipating critical transitions and divergence from the present state of the system is particularly crucial to the prevention or mitigation of the effects of unwanted and irreversible changes5-10. Recent research in ecology has focused on leading indicators of regime shift in ecosystems characterized by one state variable5,7,11,12. The case of systems with several mutually interacting components, however, has remained poorly investigated13, while the connection between network stability and research on indicators for loss of resilience has been elusive14. Here we develop a theoretical framework to analyze early warning signs of instability and regime shift in social ecological networks. We provide analytical expressions for a set of precursors of instability in social ecological systems with additive noise for a variety of network structures. In particular, we show that the covariance matrix of the dynamics can effectively anticipate the emergence of instability. We also compare signals of early warning based on the dynamics of suitably selected nodes, to indicators based on the integrated behavior of the whole network. We find that the performances of these indicators are affected by the network structure and the type of interaction among nodes. These results provide new advances in multidimensional early warning analysis and offer a framework to evaluate the resilience of social ecological networks.

q-bio.PE↗

arXiv2013

Virtual water controlled demographic growth of nations

Population growth is in general constrained by food production, which in turn depends on the access to water resources. At a country level, some populations use more water than they control because of their ability to import food and the virtual water required for its production. Here, we investigate the dependence of demographic growth on available water resources for exporting and importing nations. By quantifying the carrying capacity of nations based on calculations of the virtual water available through the food trade network, we point to the existence of a global water unbalance. We suggest that current export rates will not be maintained and consequently we question the long-run sustainability of the food trade system as a whole. Water rich regions are likely to soon reduce the amount of virtual water they export, thus leaving import-dependent regions without enough water to sustain their populations. We also investigate the potential impact of possible scenarios that might mitigate these effects through (1) cooperative interactions among nations whereby water rich countries maintain a tiny fraction of their food production available for export; (2) changes in consumption patterns; and (3) a positive feedback between demographic growth and technological innovations. We find that these strategies may indeed reduce the vulnerability of water-controlled societies.

physics.soc-ph↗

arXiv2012

Spatio-temporal stochastic resonance induces patterns in wetland vegetation dynamics

Water availability is a major environmental driver affecting riparian and wetland vegetation. The interaction between water table fluctuations and vegetation in a stochastic environment contributes to the complexity of the dynamics of these ecosystems. We investigate the possible emergence of spatial patterns induced by spatio-temporal stochastic resonance in a simple model of groundwater-dependent ecosystems. These spatio-temporal dynamics are driven by the combined effect of three components: (i) an additive white Gaussian noise, accounting for external random disturbances such as fires or fluctuations in rain water availability, (ii) a weak periodic modulation in time, describing hydrological drivers such as seasonal fluctuations of water table depth, and (iii) a spatial coupling term, which takes into account the ability of vegetation to spread and colonize other parts of the landscape. A suitable cooperation between these three terms is able to give rise to ordered structures which show spatial and temporal coherence, and are statistically steady in time.

q-bio.PE↗

arXiv2012

Spatial pattern formation induced by Gaussian white noise

The ability of Gaussian noise to induce ordered states in dynamical systems is here presented in an overview of the main stochastic mechanisms able to generate spatial patterns. These mechanisms involve: (i) a deterministic local dynamics term, accounting for the local rate of variation of the field variable, (ii) a noise component (additive or multiplicative) accounting for the unavoidable environmental disturbances, and (iii) a linear spatial coupling component, which provides spatial coherence and takes into account diffusion mechanisms. We investigate these dynamics using analytical tools, such as mean-field theory, linear stability analysis and structure function analysis, and use numerical simulations to confirm these analytical results.

cond-mat.stat-mech↗