The Effect of Anthropogenic Land Cover Change on Pollen-Vegetation Relationships in the American Midwest
Notice bibliographique
Résumé
Fossil pollen assemblages are widely used to reconstruct past vegetation community composition at time scales ranging from centuries to millennia. These reconstructions often are based on the observed relationships between the proportions of plant taxa in the source vegetation and the proportions of the corresponding pollen types in pollen assemblages collected from surface sediments. Pollen-vegetation models rely upon parameters whose values typically are assumed to be stable through time, but this assumption is largely unevaluated, due in part to the rarity of comprehensive forest data, particularly for earlier time periods. Here we present a new dataset of early settlement-era pollen records for the upper Midwest of North America and combine it with three other pollen and forest composition datasets to assess the stability of the relationship between relative pollen composition and relative abundances of tree genera for two time periods: immediately prior to Euro-American settlement, and the late 20th Century. Over this time interval, Euro-American settlement resulted in widespread forest clearance for agriculture and logging, producing major changes to forest composition and structure and the pollen assemblages produced by these forests. These major changes provide an opportunity to test the constancy of the relationship between pollen and forest vegetation during a period of large vegetation change. Pollen-vegetation relationships are modeled, using a Generalized Linear Model, for thirteen upper Midwestern tree genera. We find that estimates of pollen source radius for the gridded mesoscale data are 25-85 kilometers, consistent with prior studies. Pollen-vegetation relationships are significantly altered for several genera: Fagus, Betula, Tsuga, Quercus, Pinus, and Picea (p < 0.05). The use of contemporary pollen-vegetation relationships to model settlement era community composition significantly under-predicts the presence of Fagus, Betula, Tsuga, Quercus and Picea at all tree densities. Pinus is over-predicted at low relative proportions (<25%), but under-predicted at greater abundances. The divergence of pollen-vegetation relationships appears to be greatest for late-successional taxa characterized by high shade tolerance and low fire tolerance, although the statistical power is low for this analysis. Hence, the ongoing rapid changes in land use and ecological communities associated with the Anthropocene affect not just our ability to make confident ecological forecasts for the future, but can also modify our inferences about the past. In the Anthropocene era, which is characterized by its rapidly changing vegetation and climates, paleoecology must move from its traditional reliance on spatial calibration datasets assumed to represent a single "present". Instead, when possible, paleoecologists should develop calibration datasets of pollen and forest composition that are distributed across major vegetation changes in time and space. Multitemporal calibration datasets are increasingly possible given the growing length and availability of vegetation observational data and will enable paleoecologists to better understand the complex processes governing pollen-vegetation relationships and make better-informed reconstructions of past vegetation dynamics.
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».