Characterization of spring thaw for different forest types in the southern boreal forest under current and future climate
Notice bibliographique
Résumé
Spring thaw timing is of great significance for ecological, biogeochemical, and hydrological processes in seasonally-frozen boreal forests. Site characteristics such as canopy architecture, ground cover type, thickness of organic soils, and mineral soil texture can influence thaw dynamics causing spring thaw variability for different forest types. The objective of this research was to characterize the existing and future variability of spring thaw between the two coniferous (black spruce and jack pine) and one deciduous (aspen) forests located in the southern boreal forest of Western Canada. Long-term observations (1997-98 to 2015-16) were used to explore existing inter-site variability of spring thaw. During the observation period, seasonal snowfall was similar at all three sites, but snow accumulation on the ground was 15% to 20% higher for the deciduous than the coniferous forests. The timing for the onset of snowmelt and soil thaw were similar between the sites, but varied considerably for soil thaw completion. The soil thawed at the aspen site about 2.5 and 4.5 weeks earlier than the jack pine and black spruce sites, respectively. This was likely driven by the higher sub-canopy net radiation of the leafless deciduous canopy. The differences between the two coniferous forest sites were driven by the thicker forest floor at the black spruce site causing higher ice content and providing better insulation effects. Carbon uptake was strongly correlated with snowmelt and soil thaw at both the coniferous forest sites but the correlations were not statistically significant for the aspen site. The Simultaneous Heat and Water (SHAW) model was used to predict the future spring thaw variability for the study sites. The model was selected after its performance evaluation against the observations and simulations of the Canadian Land Atmosphere Surface Scheme (CLASS) and Cold Regions Hydrological Model (CRHM) for winter-spring transition at the jack pine site. All three models simulated similar snow ablation date, with a difference of 1 to 5 days, despite large differences in snowmelt rates. The SHAW model performed better for simulating soil thaw timing (the maximum difference between observations and simulations was about 1 week for SHAW, 3 weeks for CLASS, and 6 weeks for CRHM) but spring evapotranspiration was overestimated (by 40 to 95 mm) by all three models. After a rigorous parameter sensitivity analysis and calibration of SHAW, it was determined that the ground cover layer in the model is important for improved simulations of soil temperature/soil thaw and an additional term in Jarvis-Stewart resistance scheme to consider the influence of low soil temperatures on stomatal conductance is needed for improving simulations of spring evapotranspiration. An approach based on the growing degree days (GDD) was proposed to indirectly consider the soil thermal environment in modelling the functioning of stomatal conductance. The consideration of ground cover layer reduced model bias up to 2.5 weeks and the proposed GDD factor reduced root mean square error for evapotranspiration by 35 to 40 mm. Future (2085-2097) weather data over Western Canada was generated by the Weather Research and Forecasting (WRF) model using the Pseudo Global Warming approach. The future climate at the study sites is projected to be wetter (18%) and warmer (5.8°C). In response, SHAW predicted significant changes in spring thaw processes. For example, future snow ablation and soil thaw timing are predicted to advance relative to historical conditions (2000-2012) by about 2.5 weeks and 6 to 7 weeks, respectively. The frozen ground depth is predicted to reduce by 45% to 58% with the highest reduction at the black spruce site which has the highest average soil water content. The mean annual soil temperature is projected to rise by 3.3°C to 3.9°C at all three sites. The evapotranspiration is predicted to increase by 26% to 28%. This study advances our understanding about the existing variability of spring thaw for different forest types in the southern boreal forest and predicts future changes in spring thaw dynamics at these sites.
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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 | 0,000 |
| 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 | 0,001 | 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 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 ».