Models of individual tree mortality for trembling aspen, lodgepole pine, hybrid spruce and subalpine fir in northwestern British Columbia
Notice bibliographique
Résumé
Density dependent mortality is an important process in forest succession. The overall predictive abilities of forest simulation models are closely related to their ability to predict mortality. Finding appropriate methods for modelling mortality have often proved to be a difficult challenge. The objective of this study was to test a method on adult trees, which was previously used for modelling density dependent mortality for saplings with good results. In the basic model mortality is predicted as a function of recent diameter growth. It was also tested if incorporating tree size into the mortality model improved it. \n \nModels were developed for four species: trembling aspen (Populus tremuloides Michx.), lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia), hybrid spruce (a complex of white spruce (Picea glauca (Moench) Voss) and Engelmann spruce (Picea engelmanii Parry ex Engelm.)) and subalpine fir (Abies lasiocarpa (Hook.) Nutt.). The models were parameterized from field data using a maximum-likelihood method. Field data was gathered from 16 stands in the Sub-Boreal Spruce Zone in northwestern British Columbia and comprised of 337 live and 345 recently dead trees in total. The mortality models were tested by incorporating them into the individual tree, spatially explicit forest simulation model SORTIE-ND. SORTIE-ND simulations of single species even-aged stands were compared to simulations of a commonly used stand level simulation model. Furthermore, SORTIE-ND simulations of permanent sample plots in mixed species uneven-aged stands were compared to remeasurements of the plots. \n \nIt was determined that incorporating tree size into the mortality models gave better fits to the field data. Tolerance to low growth decreases to a minimum at intermediate trees size for all species except for subalpine fir, where it decreases and remains low as trees growth larger. This is probably an effect of the ontogenetic characteristics of the individual species. \n \nTesting the mortality models in SORTIE-ND showed that they contribute to realistic thinning patterns in simulations of both pure even-aged stands and complex stands. However, it was evident that the performance of the mortality models is highly dependent on the underlying growth models as well as mortality models accounting for random mortality. Discrepancies in modelling results were linked to over- and underestimation of growth or inappropriate random mortality rates. \n \nOverall the tested method provides a straight forwards approach to parameterizing growth based mortality models from field data which is relatively easy to obtain.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| 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 ».