Although spatial variation in climate can directly affect the survival and reproduction of forest insects and the tree species compositions of forests, little is known about the indirect effects of climate on outbreaks of forest insects through its effects on forest composition. In this study, we use structural equation modeling to examine the direct and indirect effects of climate, water capacity of the soil, host tree density, and non-host density on the spatial extent of Lymantria dispar outbreaks in the Eastern USA over a period of 44 years (1975-2018). Host species were subdivided into four taxonomic and ecologically distinct groups: red oaks (Lobatae), white oaks (Lepidobalanus), other preferred hosts, and intermediate (less preferred) hosts. We found that mean annual temperature had stronger effects than mean annual precipitation on the spatial extent of outbreaks, and that indirect effects of temperature (via its effects on oak density) on defoliation were stronger than direct effects. The density of non-host trees increased with increasing precipitation and, consistent with the 'associational resistance hypothesis', defoliation decreased with increasing density of non-host trees. This study offers quantitative evidence that geographic variation in climate can indirectly affect outbreaks of a forest insect through its effects on tree species composition.
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http://dx.doi.org/10.1007/s00442-022-05123-w | DOI Listing |
PLoS One
January 2025
Department of Social Sciences and Health Policy, Wake Forest University School of Medicine, Winston-Salem, NC, United States of America.
Globally, those who live in rural areas experience significant barriers to accessing health care due to a maldistribution of health care providers. Those who live in rural areas in the Appalachian region of the United States face one of the worst shortages of health care providers despite experiencing more complex health needs compared to Americans in more affluent, urban areas. Prior research has failed to identify effective solutions to narrow the provider maldistribution, despite it being a policy focus for decades.
View Article and Find Full Text PDFJ Womens Health (Larchmt)
January 2025
Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
We investigated associations of menopausal age category with body mass index (BMI), waist circumference, waist-hip ratio, and waist-height ratio. We also explored the moderating effect of anthropometric measures on associations of menopausal age category with prespecified sex hormones: estradiol, dehydroepiandrosterone (DHEA), sex hormone-binding globulin, bioavailable testosterone, and total testosterone-estradiol (T/E) ratio. In this cross-sectional study, we included 2,436 postmenopausal women from the Multi-Ethnic Study of Atherosclerosis who had menopausal age, anthropometric, and sex hormone data at baseline.
View Article and Find Full Text PDFJCO Oncol Pract
January 2025
Lineberger Comprehensive Cancer Center (LCCC), UNC-CH, Chapel Hill, NC.
Purpose: Lung cancer mortality rates for American Indians (AIs) are the highest among US race groups. End-of-life (EOL) care presents opportunities to limit aggressive and potentially unnecessary treatment. We evaluated differences in EOL quality of care between AI and White (WH) decedents with lung cancer.
View Article and Find Full Text PDFAnn Med
December 2025
Institute of Clinical Virology, Department of Infectious Diseases, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Objective: We aimed at identifying acute phase biomarkers in Severe Fever with Thrombocytopenia Syndrome (SFTS), and to establish a model to predict mortality outcomes.
Methods: A retrospective analysis was conducted on multicenter clinical data. Group-based trajectory modeling (GBTM) was utilized to demonstrate the overall trend of laboratory indicators and their correlation with mortality.
Sci Rep
January 2025
Department of Otolaryngology, Hospital of Chengdu University of Traditional Chinese Medicine, No.39, Shierqiao Road, Jinniu District, Chengdu, Sichuan, China.
The present study analyzed the impact of age on the causes of death (CODs) in patients with nasopharyngeal carcinoma (NPC) undergoing chemoradiotherapy (CRT) using machine learning approaches. A total of 2841 patients (1037 classified as older, ≥ 60 years and 1804 as younger, < 60 years) were enrolled. Variations in the CODs between the two age groups were analyzed before and after applying inverse probability of treatment weighting (IPTW).
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