The Role of Evolution in Shaping Ecological Networks
Notice bibliographique
Résumé
Networks of ecological interactions define the way that ecosystems function. Network assembly and temporal persistence can be thought of as contemporary ecological functions but shaped by historical evolutionary processes. Increasingly, researchers study networks within a phylogenetic comparative context, acknowledging that networks are sensitive to evolutionary constraints operating at regional or local scales. Methodological progress in population genomics and molecular detection, combined with theoretical developments in modelling, now permit investigation of ecoevolutionary feedback loops within networks. Although understanding of isolated parts of network assembly and persistence is developing, a unifying framework for making connections and predictions across evolutionary scales is lacking. Approaches are being developed on multiple fronts from which such a framework may well emerge. The structure of ecological networks reflects the evolutionary history of their biotic components, and their dynamics are strongly driven by ecoevolutionary processes. Here, we present an appraisal of recent relevant research, in which the pervasive role of evolution within ecological networks is manifest. Although evolutionary processes are most evident at macroevolutionary scales, they are also important drivers of local network structure and dynamics. We propose components of a blueprint for further research, emphasising process-based models, experimental evolution, and phenotypic variation, across a range of distinct spatial and temporal scales. Evolutionary dimensions are required to advance our understanding of foundational properties of community assembly and to enhance our capability of predicting how networks will respond to impending changes. The structure of ecological networks reflects the evolutionary history of their biotic components, and their dynamics are strongly driven by ecoevolutionary processes. Here, we present an appraisal of recent relevant research, in which the pervasive role of evolution within ecological networks is manifest. Although evolutionary processes are most evident at macroevolutionary scales, they are also important drivers of local network structure and dynamics. We propose components of a blueprint for further research, emphasising process-based models, experimental evolution, and phenotypic variation, across a range of distinct spatial and temporal scales. Evolutionary dimensions are required to advance our understanding of foundational properties of community assembly and to enhance our capability of predicting how networks will respond to impending changes. ‘A network whose links change adaptively with respect to its states, resulting in a dynamical interplay between the state and the topology of the network’ [46.Gross T. Sayama H. Adaptive networks.in: Adaptive Networks. Springer, 2009: 1-8Crossref Scopus (42) Google Scholar]. networks in which the links represent interactions with negative impacts on the fitness of one level of interacting species. evolution of a continuous trait across a phylogeny, modelled as a random walk for comparison with other processes [20.Revell L. J. et al.Phylogenetic signal, evolutionary process, and rate.Syst. Biol. 2008; 57: 591-601Crossref PubMed Scopus (571) Google Scholar]. simultaneous diversification (speciation) of two interacting lineages. mutual and concurrent evolutionary adaptation of traits in a population of one species to individuals from another [34.Janzen D. H. When is it coevolution?.Evolution. 1980; 34: 611-612Crossref PubMed Google Scholar]. phylogenies pruned to include only cooccurring species rather than all species within a taxon or clade. ‘cyclical interaction between ecology and evolution such that changes in ecological interactions drive evolutionary change in organismal traits that, in turn, alter the form of ecological interactions, and so forth’ [87.Post D. M. Palkovacs E. P. Eco-evolutionary feedbacks in community and ecosystem ecology: interactions between the ecological theatre and the evolutionary play.Philos. Trans. R. Soc. B. 2009; 364: 1629-1640Crossref PubMed Scopus (397) Google Scholar]. ‘process whereby organisms colonise and persist in novel environments, use novel resources or form novel associations with other species as a result of the suites of traits that they carry at the time they encounter the novel condition’ [88.Agosta S. J. On ecological fitting, plant–insect associations, herbivore host shifts, and host plant selection.Oikos. 2006; 114: 556-565Crossref Scopus (218) Google Scholar]. any depiction of a set of interindividual or interspecies interactions in nature, usually comprising nodes (the species themselves) and edges (the functional links among species). field of study focused on exploring patterns and process in ecology through the combination of ecological data with phylogenetic and biogeographic data. frequency and/ or fidelity of a connection between two nodes in a network when sampled at multiple points (across time and/or space). evolution on a scale at or above the level of species. relates specifically to the turnover of allele frequencies within a population through inheritance, selection and drift. networks in which the links represent interactions with positive impacts on the fitness of both sets of interacting species. statistical nonindependence, and phylogenetic clustering, among interactions in a network due to the phylogenetic relatedness of nodes (modified from [20.Revell L. J. et al.Phylogenetic signal, evolutionary process, and rate.Syst. Biol. 2008; 57: 591-601Crossref PubMed Scopus (571) Google Scholar]). multidimensional component (metrics include persistence, robustness, resistance, resilience and variability) that quantifies the ability of a network to resist restructuring or collapse following perturbation. tendency of species to retain ancestral traits. extent to which a trait in one species exceeds or overcomes a corresponding trait in another ( e. g., animal gape must exceed fruit diameter in seed dispersal mutualisms) [35.Nuismer S. L. et al.Coevolution and the architecture of mutualistic networks: coevolving networks.Evolution. 2013; 67: 338-354Crossref PubMed Scopus (94) Google Scholar]. phenotypic resource traits that match those of consumers, ( e. g., phenological cooccurrence of plants and pollinators). ‘ability of individual genotypes to produce different phenotypes when exposed to different environmental conditions’ [89.Pigliucci M. Phenotypic plasticity and evolution by genetic assimilation.J. Exp. Biol. 2006; 209: 2362-2367Crossref PubMed Scopus (693) Google Scholar]. ‘phylogenetic tracking occurs if there is strong asymmetry in the interaction between two species, implying one species is much more dependent on the other. This leads to parallel phylogenetic trees’ [31.Russo L. et al.Quantitative evolutionary patterns in bipartite networks: Vicariance, phylogenetic tracking or diffuse co-evolution ?.Methods Ecol. Evol. 2018; 9: 761-772Crossref Scopus (13) Google Scholar]. morphological, behavioural, ecological, or chemical features of a species reflecting both its evolutionary history and its local phenotypic adaptation.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».