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Enregistrement W7043103491

RESOLVING THE ROLE OF SUBARCTIC VEGETATION ON MOUNTAIN WATER CYCLING IN A RAPIDLY CHANGING CLIMATE

2023· dissertation· en· W7043103491 sur OpenAlexfundaboutno aff

Notice bibliographique

RevueMacSphere (McMaster University) · 2023
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiquePlant Water Relations and Carbon Dynamics
Établissements canadiensnon disponible
Organismes subventionnairesGlobal Water Futures
Mots-clésSubarctic climateVegetation (pathology)TaigaClimate changeEvapotranspirationMireWater cyclePrecipitationEcosystemEcotone
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

High latitude and altitude ecosystems are currently undergoing rapid and unprecedented warming in response to anthropogenically induced climate change. Subarctic, alpine regions are particularly vulnerable to increases in air temperature and changing precipitation regimes, which have caused cascading hydrological and ecological impacts. In addition to changing flow regimes, thawing permafrost, and declining glaciers, widespread changes in vegetation composition, density and distribution have been observed across northern regions. Specifically, treeline is advancing with increasing latitude and altitude and shrubs are increasing in height, extent, and density. Despite widespread documentation of this northern greening, few field-based studies have evaluated the hydrological implications of these changes. Quantification of total evapotranspiration (ET) across a range of vegetation gradients is essential for predicting water yield, yet challenging in cold alpine catchments due to heterogeneous land cover. Direct field-level measurements of transpiration (T) and evaporative partitioning across subarctic, alpine ecosystems and species are rare, yet essential to assess sensitivities and hydrological response to changing climate drivers. This thesis presents six years of surface energy balance components and ET dynamics and two years of sap flux measurements and critical zone stable water isotope sampling at three sites along an elevational gradient in a subarctic, alpine catchment near Whitehorse, Yukon Territory, Canada. These sites span a gradient of thermal and vegetation regimes, providing a space-for-time comparison for future ecosystem shifts: 1) a low-elevation boreal white spruce forest (~12-20 m), 2) a mid-elevation subalpine taiga comprised of tall, dense willow (Salix) and birch (Betula) shrubs (~1-3 m) and 3) a high-elevation subalpine taiga with short, sparse shrub cover (< 0.75 m) and moss, lichen, and bare rock. We utilize both mass flux measurements and stable water isotopes to evaluate the timing, magnitude, sensitivities, and sources of plant water uptake across these vegetation covers. Total ET decreased and interannual variability increased with elevation, with mean May to September ET totals of 349 (±3) mm at the forest, 249 (±10) mm at the tall, dense shrub site, and 240 (± 26) mm at the short, sparse shrub site. The shrub sites exhibited similar ET losses over 6 years despite differences in shrub height and abundance, although daily rates were higher at the tall shrub site in the peak growing season. From May to September, ET:R ratios were the highest and most variable at the forest (2.19 ± 0.37) and similar at the tall, dense shrub (1.22 ± 0.09) and short, sparse shrub (1.14 ± 0.05) sites. In the mid-growing season, mean T rates were greater at the dense shrub site (2.0 ± 0.75 mm d-1) than the forest (1.47 ± 0.52 mm d-1). During this time, T:ET was lower at the forest (0.48) than at the tall, dense shrub site (0.80). During the growing season between the two years, 2020 was considerably wetter and cooler than 2019. At the tall shrub site, during the mid-growing season (July 1-Aug 15), T dropped considerably in 2020 (-26%), as T was suppressed during the short, wet growing season. In contrast, T at the forest was only moderately suppressed (-3%) between years in this same period. Evapotranspiration was more strongly controlled by air temperature during the early and late season at the forest, while ET at the shrub site was more sensitive to warmer temperatures in the mid-growing season. At the shrub sites, ET was energy limited with no observed soil moisture limitation on T. While 2H and 18O of volume weighted precipitation became more depleted with elevation, the opposite was true in xylem water, where 2H and 18O became more enriched with elevation. Plant water uptake was more reflective of snow water at the forest site than both shrub sites, particularly early in the year and during dry periods. Near-surface bulk soil water had more negative lc-excess at the forest throughout the season and with depth, highlighting increased contributions from soil evaporation. This study combined direct measurements of sap flux, ET, and critical zone isotopes to provide new details on multi-year plant-soil-water dynamics, critical zone water cycling, and species-specific plant water uptake patterns in seasonally frozen soils, which have not previously been reported in cold regions. Our results suggest that advances in treeline will increase overall ET and lower interannual variability; however, the large growing season water deficit and stable water isotope signature at the forest indicates strong reliance on soil moisture from late fall and snowmelt recharge and the potential for plant water stress. Differences between the shrub species were apparent in the sap flux and stable isotope measurements, highlighting the need to further evaluate species specific responses and feedbacks when predicting hydrological fluxes across subarctic ecosystems. Overall, our results suggest that predicted changes in vegetation type and structure in northern regions will have a considerable impact on water partitioning and will vary in a complex way in response to changing precipitation timing, phase and magnitude.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,373
Score d'incertitude au seuil0,741

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,006
Tête enseignante GPT0,183
Écart entre enseignants0,177 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission2
Résumé présentoui

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