2024
DOI: 10.3390/f15010162
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Suitable Habitat Prediction and Analysis of Dendrolimus houi and Its Host Cupressus funebris in the Chinese Region

Guangting Miao,
Youjie Zhao,
Yijie Wang
et al.

Abstract: The Dendrolimus houi, a phytophagous pest, displays a broad range of adaptations and often inflicts localized damage to its hosts. Cupressus funebris, an indigenous timber species in China, is significantly impacted by D. houi. Investigating the suitable habitat distribution and changes in D. houi and its host plant, C. funebris, within the context of climate warming, is essential for understanding D. houi’s development and providing novel insights for managing D. houi and conserving C. funebris resources. In … Show more

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Cited by 4 publications
(2 citation statements)
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“…Furthermore, expansion has also been found in studies of picea.purpurea and picea.smithiana in the context of future global warming [44,58]. Comparing with the suitable area for the four endangered spruce species under the current climate scenario, the four endangered spruce species show different degrees of expansion towards the northwest of the Tibetan Plateau under the three different future climate pathways, which follows the expansion trend [44,58,68]. It has been shown that the northward migration of plants may be created by global warming [69].…”
Section: Discussionmentioning
confidence: 82%
“…Furthermore, expansion has also been found in studies of picea.purpurea and picea.smithiana in the context of future global warming [44,58]. Comparing with the suitable area for the four endangered spruce species under the current climate scenario, the four endangered spruce species show different degrees of expansion towards the northwest of the Tibetan Plateau under the three different future climate pathways, which follows the expansion trend [44,58,68]. It has been shown that the northward migration of plants may be created by global warming [69].…”
Section: Discussionmentioning
confidence: 82%
“…In this study, the parameters of the A. trifida prediction model were optimized by using the Kuenm package in R, setting the RM parameter interval [0.1-4], each interval 0.1, and 29 FC feature function combinations. When the AIC value was the minimum, the AIC value was the lowest (delta AICc = 0), the model parameters were the best, and the distribution prediction model of A. trifida was established using the optimal parameters [30].…”
Section: Maxent Model Optimization and Results Evaluationmentioning
confidence: 99%