Reconstructing community dynamics from limited observations
| hal.structure.identifier | University of Turku | |
| dc.contributor.author | ROSS, Chandler | |
| hal.structure.identifier | University of Turku | |
| dc.contributor.author | LAITINEN, Ville | |
| hal.structure.identifier | University of Turku | |
| dc.contributor.author | KHALIGHI, Moein | |
| hal.structure.identifier | Faculty of Medecine [Helsinki] | |
| dc.contributor.author | SALOJÄRVI, Jarkko | |
| hal.structure.identifier | Nanyang Technological University [Singapour] [NTU] | |
| hal.structure.identifier | Organismal and Evolutionary Biology [Helsinki] | |
| dc.contributor.author | DE VOS, Willem | |
| hal.structure.identifier | University of Turku | |
| hal.structure.identifier | Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE] | |
| dc.contributor.author | SOMMERIA-KLEIN, Guilhem | |
| hal.structure.identifier | University of Turku | |
| dc.contributor.author | LAHTI, Leo | |
| dc.date.issued | 2025 | |
| dc.description.abstractEn | Ecosystems tend to fluctuate around stable equilibria in response to internal dynamics and environmental factors. Occasionally, they enter an unstable tipping region and collapse into an alternative stable state. Our understanding of how ecological communities vary over time and respond to perturbations depends on our ability to quantify and predict these dynamics. However, the scarcity of long, dense time series data poses a severe bottleneck for characterising community dynamics using existing methods. We overcome this limitation by combining information across multiple short time series using Bayesian inference. By decomposing dynamics into deterministic and stochastic components using Gaussian process priors, we predict stable and tipping regions along the community landscape and quantify resilience while addressing uncertainty. After validation with simulated and real ecological time series, we use the model to question common assumptions underlying classical potential analysis and re-evaluate the stability of previously proposed "tipping elements" in the human gut microbiota. | |
| dc.language.iso | en | |
| dc.subject.en | Bistability | |
| dc.subject.en | exit time | |
| dc.subject.en | Gaussian processes | |
| dc.subject.en | human gut microbiota | |
| dc.subject.en | microbial ecology | |
| dc.subject.en | stability landscape | |
| dc.subject.en | stochastic differential equation | |
| dc.subject.en | tipping points | |
| dc.title.en | Reconstructing community dynamics from limited observations | |
| dc.type | Document de travail - Pré-publication | |
| dc.identifier.doi | 10.48550/arXiv.2501.03820 | |
| dc.subject.hal | Sciences de l'environnement | |
| dc.subject.hal | Mathématiques [math]/Statistiques [math.ST] | |
| hal.identifier | hal-04908644 | |
| hal.version | 1 | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-04908644v1 | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2025&rft.au=ROSS,%20Chandler&LAITINEN,%20Ville&KHALIGHI,%20Moein&SALOJ%C3%84RVI,%20Jarkko&DE%20VOS,%20Willem&rft.genre=preprint |
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