Simulating the Potential Effects of a Changing Climate on Black Spruce and Jack Pine Plantation Productivity by Site Quality and Locale through Model Adaptation
Notice bibliographique
Résumé
Modifying the stand dynamic functional determinates of structural stand density management models (SSDMMs) through the incorporation of site-specific biophysical height-age equations enabled the simulation of the effects of increasing mean temperature and precipitation during the growing season on black spruce (Picea mariana (Mill.) BSP) and jack pine (Pinus banksiana Lamb.) plantation productivity. The analytical approach consisted of calculating future values of growing season mean temperature and precipitation rates under three emissions scenarios (no change (NC); B1; and A2), spanning three continuous commitment periods (2011–2040; 2041–2070; and 2071–2100), for three geographically separated sites throughout the central portion of the Canadian Boreal Forest Region (north-eastern (Kirkland Lake); north-central (Thunder Bay); and north-western (Dryden) Ontario, Canada), using the Canadian Coupled Global Climate Model (CGCM3) in conjunction with a geographic-referencing climatic surface model. These estimates were entered into the embedded biophysical equations in the SSDMMs in order to forecast emission-scenario-specific developmental patterns of plantations managed under a conventional density management regime by species and site quality (poor-to-medium and good-to-excellent) at each locale; from which stand development rates and associated productivity metrics over 75 year-long rotations were estimated and compared (e.g., mean sizes, volumetric, biomass and carbon yields, end-products, economic worth, stand stability, wood quality indices, and operability status). Simulation results indicated that black spruce plantations situated on both site qualities at the north-western location and on the lower site quality at the north-eastern location were negatively affected from the predicted increased warming and rainfall as evidenced from consequential declines in stand development rates and resultant decreases in rotational mean sizes, biomass yields, recoverable end-product volumes, and economic worth (A2 > B1). Conversely, black spruce plantations situated on both site qualities at the north-central location and on the higher site quality at the north-eastern location were minimally and positively affected under the A2 and B1 scenarios, respectively. Jack pine plantations situated on both site qualities at all three locations were negatively affected as evident by the reductions in stand development rates and rotational mean sizes, biomass yields, recoverable end-product volumes, and economic worth (A2 > B1). Collectively, these response patterns suggest that stand-level productivity under a changing climate will vary by species, site quality, geographic locale, and emission scenario, potentially resulting in a landscape-level mosaic of both negative and positive productivity impacts in the case of black spruce, and mostly negative impacts in the case of jack pine. As demonstrated, modelling stand-level responses to projected increases in thermal and moisture regimes through the modification of existing stand-level forecasting models, and accounting for divergent effects due to species, site quality, and geographic locale differences, is a viable and efficient alternative approach for projecting productivity outcomes arising from anthropogenic-induced changes in growing conditions.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| 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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 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 tête enseignante, 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 ».