Modelling population dynamics and persistence in fragmented landscapes
Notice bibliographique
Résumé
Of the many factors that affect population dynamics and persistence, landscape heterogeneity is increasingly recognized as one important factor that is particularly relevant to biodiversity conservation and management. However, understanding interactions between mobile species and landscape heterogeneity remains an outstanding challenge in ecology. Studies considering the influence of landscape heterogeneity on population dynamics are less common, and detailed knowledge of the relationship between landscape heterogeneity and population dynamics in patchy habitats is very poor. This study tested how landscape heterogeneity affects population behaviour and persistence in patchy environments, including (1) relative influences of patch geometry and within-patch heterogeneity, (2) effects of spatial patterns of within-patch heterogeneity on patchy populations, (3) landscape spatial structure and species’ life-history traits, and (4) differential roles of structural and functional landscape heterogeneity. The results presented in this thesis demonstrate that spatial heterogeneity within habitat patches, together with patch area, controls population abundance of the habitat specialists, but had little influence on generalist species. Populations of specialised species become less variable in size, and experience lower probability of extinction in landscapes with positively autocorrelated within-patch habitat quality. Increasing scale of spatial autocorrelation in habitat quality would greatly increase the size and mean resource share of virtual populations, and low-tolerant species were appreciably greater in size than high-tolerant species. Species’ movement capacity plays a critical role in shaping the increase in population size in response to increased spatial autocorrelation in habitat quality, where low-mobility species had a logarithmic-like increase in response to increased scale of spatial autocorrelation, contrasting with the exponential-like increase for high-mobility species. Such contrasting patterns of population increase in relation to movement capacity indicate that the effect of distance-based movement capacity may function in highly scale-dependent ways, and its relative strength is determined by the interaction of movement distance and the scale of spatial autocorrelation. Structural and functional properties of landscape heterogeneity can have different consequences on animal species. As we shown in the thesis, functional landscape heterogeneity influenced space use of black bears at intermediate scales (i.e., 1~2 km), whereas the impact of structural heterogeneity was most significant at the finest scale analysed (i.e., 200 m). The scale-dependent responses of animals to different forms of landscape heterogeneity indicate that an explicit separation of the effects of different landscape heterogeneity across scales is critical to our understanding of the spatial nature of animal-environment relationships. Summarizing, this study highlights the importance of the landscape heterogeneity in determining the dynamics and persistence of populations inhabiting patchy environments. Both the spatial pattern and extent of landscape heterogeneity can interact with fragmentation to greatly influence populations with different life-history traits. Ecologists need to be mindful of the simplifying assumptions of theories and resulting models and predictions in assessing the suitability of their application for specific species and landscapes.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».