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, a monotypic relict tree species endemic to China, has extremely sparse populations in the wild. The world's largest natural forest is distributed in the Zhuzhou Island Forest Nature Reserve, Zhuhai, Guangdong Province. However, artificial plantations of currently exhibit significant decline. To clarify the survival status and dynamic characteristics of populations, we constructed age structure diagrams, compiled static life tables, and applied survival function analysis and time series prediction to analyze population dynamics and driving mechanisms, aiming to provide a scientific basis for conservation and management. The results showed that the artificial population exhibited a "bell-shaped" structure, with fewer juvenile and elderly individuals, and the highest number observed in age class V (20 cm≤DBH<25 cm). Understory natural regeneration was severely limited. The static life table indicated that mortality and disa-ppearance rates initially increased and then decreased, peaking at age class Ⅵ (25 cm≤DBH<30 cm) and age class Ⅹ (DBH≥45 cm), respectively. Life expectancy declined with increasing age class, and the survival curve aligned with the Deevey-Ⅱ type. Spectral analysis demonstrated significant periodic fluctuations in population dynamics, dominated by the fundamental wave A1 and driven by the third harmonic, with age class V (20 cm≤DBH<25 cm) identified as the critical fluctuation phase. Time series prediction showed that population size increased during age classes Ⅱ-Ⅳ, reaching maximum size at class V, followed by a continuous decline from age classes Ⅵ-Ⅷ onward. Although the population temporarily maintained growth, long-term survival risks arose from insufficient juvenile recruitment, environmental stochasticity, and physiological senescence. To enhance population resilience, the following conservation strategies are recommended, inlcuding artificial propagation, habitat restoration, and invasive species control.
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http://dx.doi.org/10.13287/j.1001-9332.202508.001 | DOI Listing |
Ying Yong Sheng Tai Xue Bao
August 2025
Guangdong Eco-Engineering Polytechnic, Guangzhou 510520, China.
, a monotypic relict tree species endemic to China, has extremely sparse populations in the wild. The world's largest natural forest is distributed in the Zhuzhou Island Forest Nature Reserve, Zhuhai, Guangdong Province. However, artificial plantations of currently exhibit significant decline.
View Article and Find Full Text PDFSmall
August 2024
Key Laboratory of Advanced Packaging Materials and Technology of Hunan Province, Hunan University of Technology, Zhuzhou, 412007, China.
Eur Radiol
January 2022
Department of Diagnostic Imaging, Rhode Island Hospital, Providence, RI, 02903, USA.
Objectives: Early recognition of coronavirus disease 2019 (COVID-19) severity can guide patient management. However, it is challenging to predict when COVID-19 patients will progress to critical illness. This study aimed to develop an artificial intelligence system to predict future deterioration to critical illness in COVID-19 patients.
View Article and Find Full Text PDFClin Nutr
December 2022
Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA, USA.
Background: About 10-20% of patients with Coronavirus disease 2019 (COVID-19) infection progressed to severe illness within a week or so after initially diagnosed as mild infection. Identification of this subgroup of patients was crucial for early aggressive intervention to improve survival. The purpose of this study was to evaluate whether computer tomography (CT) - derived measurements of body composition such as myosteatosis indicating fat deposition inside the muscles could be used to predict the risk of transition to severe illness in patients with initial diagnosis of mild COVID-19 infection.
View Article and Find Full Text PDFRadiology
September 2020
From the Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, China (H.X.B., Z.X., D.C.W., W.H.L.); Department of Diagnostic Imaging, Rhode Island Hospital, Providence, RI (H.X.B., B.H., K.H., I.P., M.K.A.); Perelman School of Medicine at the University of Pennsylvan
Background Coronavirus disease 2019 (COVID-19) and pneumonia of other diseases share similar CT characteristics, which contributes to the challenges in differentiating them with high accuracy. Purpose To establish and evaluate an artificial intelligence (AI) system for differentiating COVID-19 and other pneumonia at chest CT and assessing radiologist performance without and with AI assistance. Materials and Methods A total of 521 patients with positive reverse transcription polymerase chain reaction results for COVID-19 and abnormal chest CT findings were retrospectively identified from 10 hospitals from January 2020 to April 2020.
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