Precipitation is the most crucial factor determining the distribution of moso bamboo in Mainland China
Notice bibliographique
Résumé
Moso bamboo is widespread in natural forests and is cultivated over large areas in China. This study investigated how climate controls its distribution, about which little is known. We collected moso bamboo presence-absence data from 674 sites with long-term climate data in Mainland China. Generalized additive models that included location and climate variables were used to test the effects of these predictors on the species’ occurrence. We identified the best model as the one with the lowest Akaike’s Information Criterion value that contained only statistically significant predictors. We found precipitation, especially the mean (APRE) and interannual standard deviation (SDPRE) of the annual precipitation at each site, rather than temperature, to be the main factors determining the distribution of moso bamboo in Mainland China. In addition, we found that there was a significant power law relationship between the mean and interannual variance of precipitation, which made it possible to make long-term predictions. The SDPRE in climate scenarios of changes in the APRE could then be calculated using the fitted power law relationship. We simulated six climate scenarios, in which the APRE increased/decreased by 25, 50, and 75%. We used the 0.5 and 0.9 probability contour lines of model predictions to represent the suitable and core distributions, respectively, of moso bamboo under each scenario. The current core distribution of moso bamboo in Mainland China predicted by our model agreed with actual observations. Our model suggested that the middle and lower reaches of the Huaihe River Plain in eastern China should be climatically suitable for the growth of moso bamboo; it seems likely that its current absence there has resulted from intensive land use. Our model predicted that changes in APRE can strongly alter the distribution of moso bamboo. Increased APRE would expand the core distribution of moso bamboo into southern Shandong Province and over all of Chongqing and most of Guizhou Provinces, which are areas not currently in the species’ core distribution. Conversely, decreased APRE would shrink the core distribution of moso bamboo to the junction of Anhui, Fujian, Jiangxi, and Zhejiang Provinces. We showed that the current distribution of moso bamboo is mainly determined by annual precipitation rather than temperature. The deviations between the moso distributions predicted by the climate model and the current distribution in some plain areas might have resulted from human activities. Future changes in annual precipitation will probably change the distribution of moso bamboo considerably.
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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 ».