Dataset Information

Mobility constraints in segregation models.

ABSTRACT: Since the development of the original Schelling model of urban segregation, several enhancements have been proposed, but none have considered the impact of mobility constraints on model dynamics. Recent studies have shown that human mobility follows specific patterns, such as a preference for short distances and dense locations. This paper proposes a segregation model incorporating mobility constraints to make agents select their location based on distance and location relevance. Our findings indicate that the mobility-constrained model produces lower segregation levels but takes longer to converge than the original Schelling model. We identified a few persistently unhappy agents from the minority group who cause this prolonged convergence time and lower segregation level as they move around the grid centre. Our study presents a more realistic representation of how agents move in urban areas and provides a novel and insightful approach to analyzing the impact of mobility constraints on segregation models. We highlight the significance of incorporating mobility constraints when policymakers design interventions to address urban segregation.

SUBMITTER: Gambetta D

PROVIDER: S-EPMC10372033 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Mobility constraints in segregation models.

Gambetta Daniele D Mauro Giovanni G Pappalardo Luca L

Scientific reports 20230726 1

Since the development of the original Schelling model of urban segregation, several enhancements have been proposed, but none have considered the impact of mobility constraints on model dynamics. Recent studies have shown that human mobility follows specific patterns, such as a preference for short distances and dense locations. This paper proposes a segregation model incorporating mobility constraints to make agents select their location based on distance and location relevance. Our findings in ...[more]

PMID: 37495661

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Project description:BACKGROUND:The spatiotemporal distribution of animals is dependent on a suite of factors, including the distribution of resources, interactions within and between species, physiological limitations, and requirements for reproduction, dispersal, or migration. During breeding, reproductive constraints play a major role in the distribution and behavior of central place foragers, such as pelagic seabirds. We examined the foraging behavior and marine habitat selection of Laysan (Phoebastria immutabilis) and black-footed (P. nigripes) albatrosses throughout their eight month breeding cycle at Tern Island, Northwest Hawaiian Islands to evaluate how variable constraints of breeding influenced habitat availability and foraging decisions. We used satellite tracking and light-based geolocation to determine foraging locations of individuals, and applied a biologically realistic null usage model to generate control locations and model habitat preference under a case-control design. Remotely sensed oceanographic data were used to characterize albatross habitats in the North Pacific. RESULTS:Individuals of both species ranged significantly farther and for longer durations during incubation and chick-rearing compared to the brooding period. Interspecific segregation of core foraging areas was observed during incubation and chick-rearing, but not during brooding. At-sea activity patterns were most similar between species during brooding; neither species altered foraging effort to compensate for presumed low prey availability and high energy demands during this stage. Habitat selection during long-ranging movements was most strongly associated with sea surface temperature for both species, with a preference for cooler ocean temperatures compared to overall availability. During brooding, lower explanatory power of habitat models was likely related to the narrow range of ocean temperatures available for selection. CONCLUSIONS:Laysan and black-footed albatrosses differ from other albatross species in that they breed in an oligotrophic marine environment. During incubation and chick-rearing, they travel to cooler, more productive waters, but are restricted to the low-productivity environment near the colony during brooding, when energy requirements are greatest. Compared to other albatross species, Laysan and black-footed albatrosses spend a greater proportion of time in flight when foraging, especially during the brooding period; this strategy may be adaptive for locating dispersed prey in an oligotrophic environment.

Project description:BACKGROUND:In order to improve the accuracy of constraint-based metabolic models, several approaches have been developed which intend to integrate additional biological information. Two of these methods, MOMENT and GECKO, incorporate enzymatic (kcat) parameters and enzyme mass constraints to further constrain the space of feasible metabolic flux distributions. While both methods have been proven to deliver useful extensions of metabolic models, they may considerably increase size and complexity of the models and there is currently no tool available to fully automate generation and calibration of such enzyme-constrained models from given stoichiometric models. RESULTS:In this work we present three major developments. We first conceived short MOMENT (sMOMENT), a simplified version of the MOMENT approach, which yields the same predictions as MOMENT but requires significantly fewer variables and enables direct inclusion of the relevant enzyme constraints in the standard representation of a constraint-based model. When measurements of enzyme concentrations are available, these can be included as well leading in the extreme case, where all enzyme concentrations are known, to a model representation that is analogous to the GECKO approach. Second, we developed the AutoPACMEN toolbox which allows an almost fully automated creation of sMOMENT-enhanced stoichiometric metabolic models. In particular, this includes the automatic read-out and processing of relevant enzymatic data from different databases and the reconfiguration of the stoichiometric model with embedded enzymatic constraints. Additionally, tools have been developed to adjust (kcat and enzyme pool) parameters of sMOMENT models based on given flux data. We finally applied the new sMOMENT approach and the AutoPACMEN toolbox to generate an enzyme-constrained version of the E. coli genome-scale model iJO1366 and analyze its key properties and differences with the standard model. In particular, we show that the enzyme constraints improve flux predictions (e.g., explaining overflow metabolism and other metabolic switches) and demonstrate, for the first time, that these constraints can markedly change the spectrum of metabolic engineering strategies for different target products. CONCLUSIONS:The methodological and tool developments presented herein pave the way for a simplified and routine construction and analysis of enzyme-constrained metabolic models.

Dataset Information

Mobility constraints in segregation models.

Publications

Mobility constraints in segregation models.

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