Quantifying coniferous subalpine tree transpiration and source water under seasonal and hydrological stress in the Canadian Rocky Mountains, Kananaskis, Alberta
Notice bibliographique
Résumé
Fresh water supplies in mountainous regions are at risk as snow and ice stores continue to decline \nunder rising global temperatures, earlier winter snowmelt and changing climate regimes. Alpine \nforests are of particular importance due to their hydrological connectivity within watersheds \ncontrolling groundwater base flow, influencing evapotranspiration (ET) and snow storage dynamics. \nA change in the water availability to subalpine vegetation via changes in winter snowpack \naccumulation and quantities or differing summer precipitation (P) regimes could have a drastic effect \non the long-term health of these forests. This makes it imperative to understand and quantify their \nhydrological connectivity within these watersheds. Study sites located at Fortress Mountain in \nKananaskis, Alberta are composed of co-occurring coniferous tree stands of Abies lasiocarpa and \nPicea engelmannii. Little is known about water use dynamics of these species at high elevations, \nspecifically the quantity and timing of transpiration (T) in addition to the water sources most \nimportant for T during the entire length of the growing season. \nThis study used a combination of hydrological and meteorological tools to address coniferous \nsubalpine tree water use behaviours before, during and after the growing season (June-September). \nMethodologies focussed on determining seasonal T patterns using the non-invasive stem-heat balance \nmethod to determine sap flow and eddy covariance to capture stand ET. The source water of the \nstudied trees was determined using δ18O and δ2H stable water isotopes and further partitioned using \nthe MixSIAR Bayesian Mixing Model (BMM). Groundwater monitoring wells, soil tensiometers, P \ngauges, and meteorological stations were used to determine baseline environmental conditions. Stable \nwater isotopes δ18O and δ2H were collected from all source waters (P, snow cover, soil water, \ngroundwater) in addition to xylem water samples from the coniferous trees within the study area. \nUnderstanding tree response to P and drying events was the main objective addressed, \nyielding stark differences between the growing seasons of 2016 and 2017. Stand T was higher in 2017 \n(165 mm) than 2016 (118 mm) despite a much drier and warmer season (155 mm of rain in 2017 \ncompared to 283 mm in 2016). A deeper, sustained snowpack in 2017 coupled with higher net \nradiation allowed for higher T rates. Paired with δ18O and δ2H stable isotope source partitioning, this \nstudy was able to identify soil water as the most important source to season-long tree productivity, \nwith groundwater the most important for early growing season. Well-drained soils and shallow depth \nto bedrock inhibited groundwater access for the studied trees after the snowmelt period concluded. \nThus soil moisture supplied a majority of water to the tree population during mid growing season, \ndetermined both hydrometrically and isotopically. Dry conditions in 2017 showed a clear trend \nbetween soil moisture levels and tree water use, with 2016 having almost double the soil moisture and \ntree productivity in the tail end of the growing season. By closely examining the patterns of subalpine \ntree water use, we can begin to clarify how these important ecosystems services will be impacted \nunder a changing climate in addition to helping us better manage our forest and freshwater resources.
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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 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| 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 ».